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Irreconciliable Dissonance in Physical Space and Cellular Metabolic Conception
Curator: Larry H. Bernstein, MD, FCAP
Pasteur Effect – Warburg Effect – What its history can teach us today.
José Eduardo de Salles Roselino
The Warburg effect, in reality the “Pasteur-effect” was the first example of metabolic regulation described. A decrease in the carbon flux originated at the sugar molecule towards the end of the catabolic pathway, with ethanol and carbon dioxide observed when yeast cells were transferred from an anaerobic environmental condition to an aerobic one. In Pasteur´s studies, sugar metabolism was measured mainly by the decrease of sugar concentration in the yeast growth media observed after a measured period of time. The decrease of the sugar concentration in the media occurs at great speed in yeast grown in anaerobiosis (oxygen deficient) and its speed was greatly reduced by the transfer of the yeast culture to an aerobic condition. This finding was very important for the wine industry of France in Pasteur’s time, since most of the undesirable outcomes in the industrial use of yeast were perceived when yeasts cells took a very long time to create, a rather selective anaerobic condition. This selective culture media was characterized by the higher carbon dioxide levels produced by fast growing yeast cells and by a higher alcohol content in the yeast culture media.
However, in biochemical terms, this finding was required to understand Lavoisier’s results indicating that chemical and biological oxidation of sugars produced the same calorimetric (heat generation) results. This observation requires a control mechanism (metabolic regulation) to avoid burning living cells by fast heat released by the sugar biological oxidative processes (metabolism). In addition, Lavoisier´s results were the first indications that both processes happened inside similar thermodynamics limits. In much resumed form, these observations indicate the major reasons that led Warburg to test failure in control mechanisms in cancer cells in comparison with the ones observed in normal cells.
[It might be added that the availability of O2 and CO2 and climatic conditions over 750 million years that included volcanic activity, tectonic movements of the earth crust, and glaciation, and more recently the use of carbon fuels and the extensive deforestation of our land masses have had a large role in determining the biological speciation over time, in sea and on land. O2 is generated by plants utilizing energy from the sun and conversion of CO2. Remove the plants and we tip the balance. A large source of CO2 is from beneath the earth’s surface.]
Biology inside classical thermodynamics places some challenges to scientists. For instance, all classical thermodynamics must be measured in reversible thermodynamic conditions. In an isolated system, increase in P (pressure) leads to increase in V (volume), all this occurring in a condition in which infinitesimal changes in one affects in the same way the other, a continuum response. Not even a quantic amount of energy will stand beyond those parameters.
In a reversible system, a decrease in V, under same condition, will led to an increase in P. In biochemistry, reversible usually indicates a reaction that easily goes either from A to B or B to A. For instance, when it was required to search for an anti-ischemic effect of Chlorpromazine in an extra hepatic obstructed liver, it was necessary to use an adequate system of increased biliary system pressure in a reversible manner to exclude a direct effect of this drug over the biological system pressure inducer (bile secretion) in Braz. J. Med. Biol. Res 1989; 22: 889-893. Frequently, these details are jumped over by those who read biology in ATGC letters.
Very important observations can be made in this regard, when neutral mutations are taken into consideration since, after several mutations (not affecting previous activity and function), a last mutant may provide a new transcript RNA for a protein and elicit a new function. For an example, consider a Prion C from lamb getting similar to bovine Prion C while preserving its normal role in the lamb when its ability to change Human Prion C is considered (Stanley Prusiner).
This observation is good enough, to confirm one of the most important contributions of Erwin Schrodinger in his What is Life:
“This little book arose from a course of public lectures, delivered by a theoretical physicist to an audience of about four hundred which did not substantially dwindle, though warned at the outset that the subject matter was a difficult one and that the lectures could not be termed popular, even though the physicist’s most dreaded weapon, mathematical deduction, would hardly be utilized. The reason for this was not that the subject was simple enough to be explained without mathematics, but rather that it was much too involved to be fully accessible to mathematics.”
After Hans Krebs, description of the cyclic nature of the citrate metabolism and after its followers described its requirement for aerobic catabolism two major lines of research started the search for the understanding of the mechanism of energy transfer that explains how ADP is converted into ATP. One followed the organic chemistry line of reasoning and therefore, searched for a mechanism that could explain how the breakdown of carbon-carbon link could have its energy transferred to ATP synthesis. One of the major leaders of this research line was Britton Chance. He took into account that relatively earlier in the series of Krebs cycle reactions, two carbon atoms of acetyl were released as carbon dioxide ( In fact, not the real acetyl carbons but those on the opposite side of citrate molecule). In stoichiometric terms, it was not important whether the released carbons were or were not exactly those originated from glucose carbons. His research aimed at to find out an intermediate proteinaceous intermediary that could act as an energy reservoir. The intermediary could store in a phosphorylated amino acid the energy of carbon-carbon bond breakdown. This activated amino acid could transfer its phosphate group to ADP producing ATP. A key intermediate involved in the transfer was identified by Kaplan and Lipmann at John Hopkins as acetyl coenzyme A, for which Fritz Lipmann received a Nobel Prize.
Alternatively, under possible influence of the excellent results of Hodgkin and Huxley a second line of research appears. The work of Hodgkin & Huxley indicated that the storage of electrical potential energy in transmembrane ionic asymmetries and presented the explanation for the change from resting to action potential in excitable cells. This second line of research, under the leadership of Peter Mitchell postulated a mechanism for the transfer of oxide/reductive power of organic molecules oxidation through electron transfer as the key for the energetic transfer mechanism required for ATP synthesis.
This diverted the attention from high energy (~P) phosphate bond to the transfer of electrons. During most of the time the harsh period of the two confronting points of view, Paul Boyer and followers attempted to act as a conciliatory third party, without getting good results, according to personal accounts (in L. A. or Latin America) heard from those few of our scientists who were able to follow the major scientific events held in USA, and who could present to us later. Paul Boyer could present how the energy was transduced by a molecular machine that changes in conformation in a series of 3 steps while rotating in one direction in order to produce ATP and in opposite direction in order to produce ADP plus Pi from ATP (reversibility).
However, earlier, a victorious Peter Mitchell obtained the result in the conceptual dispute, over the Britton Chance point of view, after he used E. Coli mutants to show H+ gradients in the cell membrane and its use as energy source, for which he received a Nobel Prize. Somehow, this outcome represents such a blow to Chance’s previous work that somehow it seems to have cast a shadow over very important findings obtained during his earlier career that should not be affected by one or another form of energy transfer mechanism. For instance, Britton Chance got the simple and rapid polarographic assay method of oxidative phosphorylation and the idea of control of energy metabolism that brings us back to Pasteur.
This metabolic alternative result seems to have been neglected in the recent years of obesity epidemics, which led to a search for a single molecular mechanism required for the understanding of the accumulation of chemical (adipose tissue) reserve in our body. It does not mean that here the role of central nervous system is neglected. In short, in respiring mitochondria the rate of electron transport linked to the rate of ATP production is determined primarily by the relative concentrations of ADP, ATP and phosphate in the external media (cytosol) and not by the concentration of respiratory substrate as pyruvate. Therefore, when the yield of ATP is high as it is in aerobiosis and the cellular use of ATP is not changed, the oxidation of pyruvate and therefore of glycolysis is quickly (without change in gene expression), throttled down to the resting state. The dependence of respiratory rate on ADP concentration is also seen in intact cells. A muscle at rest and using no ATP has a very low respiratory rate. [When skeletal muscle is stressed by high exertion, lactic acid produced is released into the circulation and is metabolized aerobically by the heart at the end of the activity].
This respiratory control of metabolism will lead to preservation of body carbon reserves and in case of high caloric intake in a diet, also shows increase in fat reserves essential for our biological ancestors survival (Today for our obesity epidemics). No matter how important this observation is, it is only one focal point of metabolic control. We cannot reduce the problem of obesity to the existence of metabolic control. There are numerous other factors but on the other hand, we cannot neglect or remove this vital process in order to correct obesity. However, we cannot explain obesity ignoring this metabolic control. This topic is so neglected in modern times that we cannot follow major research lines of the past that were interrupted by the emerging molecular biology techniques and the vain belief that a dogmatic vision of biology could replace all previous knowledge by a new one based upon ATGC readings. For instance, in order to display bad consequences derived from the ignorance of these old scientific facts, we can take into account, for instance, how ion movements across membranes affects membrane protein conformation and therefore contradicts the wrong central dogma of molecular biology. This change in protein conformation (with unchanged amino acid sequence) and/or the lack of change in protein conformation is linked to the factors that affect vital processes as the heart beats. This modern ignorance could also explain some major pitfalls seen in new drugs clinical trials and in a small scale on bad medical practices.
The work of Britton Chance and of Peter Mitchell have deep and sound scientific roots that were made with excellent scientific techniques, supported by excellent scientific reasoning and that were produced in a large series of very important intermediary scientific results. Their sole difference was to aim at very different scientific explanations as their goals (They have different Teleology in their minds made by their previous experiences). When, with the use of mutants obtained in microorganisms P Mitchell´s goal was found to survive and B Chance to succumb to the experimental evidence, all those excellent findings of B Chance and followers were directed to the dustbin of scientific history as an example of lack of scientific consideration. [On the one hand, the Mitchell model used a unicellular organism; on the other, Chance’s work was with eukaryotic cells, quite relevant to the discussion.]
We can resume the challenge faced by these two great scientists in the following form: The first conceptual unification in bioenergetics, achieved in the 1940s, is inextricably bound up with the name of Fritz Lipmann. Its central feature was the recognition that adenosine triphosphate, ATP, serves as a universal energy “currency” much as money serves as economic currency. In a nutshell, the purpose of metabolism is to support the synthesis of ATP. In microorganisms, this is perfect! In humans or mammals, or vertebrates, by the same reason that we cannot consider that gene expression is equivalent to protein function (an acceptable error in the case of microorganisms) this oversimplifies the metabolic requirement with a huge error. However, in case our concern is ATP chemistry only, the metabolism produces ATP and the hydrolysis of ATP pays for the performance of almost, all kinds of works. It is possible to presume that to find out how the flow of metabolism (carbon flow) led to ATP production must be considered a major focal point of research of the two contenders. Consequently, what could be a minor fall of one of the contenders, in case we take into account all that was found during their entire life of research, the real failure in B Chance’s final goal was amplified far beyond what may be considered by reason!
Another aspect that must be taken into account: Both contenders have in the scientific past a very sound root. Metabolism may produce two forms of energy currency (I personally don´t like this expression*) and I use it here because it was used by both groups in order to express their findings. Together with simplistic thermodynamics, this expression conveys wrong ideas): The second kind of energy currency is the current of ions passing from one side of a membrane to the other. The P. Mitchell scientific root undoubtedly have the work of Hodgkin & Huxley, Huxley & Huxley, Huxley & Simmons
*ATP is produced under the guidance of cell needs and not by its yield. When glucose yields only 2 ATPs per molecule it is oxidized at very high speed (anaerobiosis) as is required to match cellular needs. On the other hand, when it may yield (thermodynamic terms) 38 ATP the same molecule is oxidized at low speed. It would be similar to an investor choice its least money yield form for its investment (1940s to 1972) as a solid support. B. Chance had the enzymologists involved in clarifying how ATP could be produced directly from NADH + H+ oxidative reductive metabolic reactions or from the hydrolysis of an enolpyruvate intermediary. Both competitors had their work supported by different but, sound scientific roots and have produced very important scientific results while trying to present their hypothetical point of view.
Before the winning results of P. Mitchell were displayed, one line of defense used by B. Chance followers was to create a conflict between what would be expected by a restrictive role of proteins through its specificity ionic interactions and the general ability of ionic asymmetries that could be associated with mitochondrial ATP production. Chemical catalyzed protein activities do not have perfect specificity but an outstanding degree of selective interaction was presented by the lock and key model of enzyme interaction. A large group of outstanding “mitochondriologists” were able to show ATP synthesis associated with Na+, K+, Ca2+… asymmetries on mitochondrial membranes and any time they did this, P. Mitchell have to display the existence of antiporters that exchange X for hydrogen as the final common source of chemiosmotic energy used by mitochondria for ATP synthesis.
This conceptual battle has generated an enormous knowledge that was laid to rest, somehow discontinued in the form of scientific research, when the final E. Coli mutant studies presented the convincing final evidence in favor of P. Mitchell point of view.
Not surprisingly, a “wise anonymous” later, pointed out: “No matter what you are doing, you will always be better off in case you have a mutant”
(Principles of Medical Genetics T D Gelehrter & F.S. Collins chapter 7, 1990).
However, let’s take the example of a mechanical wristwatch. It clearly indicates when the watch is working in an acceptable way, that its normal functioning condition is not the result of one of its isolated components – or something that can be shown by a reductionist molecular view. Usually it will be considered that it is working in an acceptable way, in case it is found that its accuracy falls inside a normal functional range, for instance, one or two standard deviations bellow or above the mean value for normal function, what depends upon the rigor wisely adopted. While, only when it has a faulty component (a genetic inborn error) we can indicate a single isolated piece as the cause of its failure (a reductionist molecular view).
We need to teach in medicine, first the major reasons why the watch works fine (not saying it is “automatic”). The functions may cross the reversible to irreversible regulatory limit change, faster than what we can imagine. Latter, when these ideas about normal are held very clear in the mind set of medical doctors (not medical technicians) we may address the inborn errors and what we may have learn from it. A modern medical technician may cause admiration when he uses an “innocent” virus to correct for a faulty gene (a rather impressive technological advance). However, in case the virus, later shows signals that indicate that it was not so innocent, a real medical doctor will be called upon to put things in correct place again.
Among the missing parts of normal evolution in biochemistry a lot about ion fluxes can be found. Even those oscillatory changes in Ca2+ that were shown to affect gene expression (C. De Duve) were laid to rest since, they clearly indicate a source of biological information that despite the fact that it does not change nucleotides order in the DNA, it shows an opposing flux of biological information against the dogma (DNA to RNA to proteins). Another, line has shown a hierarchy, on the use of mitochondrial membrane potential: First the potential is used for Ca2+ uptake and only afterwards, the potential is used for ADP conversion into ATP (A. L. Lehninger). In fact, the real idea of A. L. Lehninger was by far, more complex since according to him, mitochondria works like a buffer for intracellular calcium releasing it to outside in case of a deep decrease in cytosol levels or capturing it from cytosol when facing transient increase in Ca2+ load. As some of Krebs cycle dehydrogenases were activated by Ca2+, this finding was used to propose a new control factor in addition to the one of ADP (B. Chance). All this was discontinued with the wrong use of calculus (today we could indicate bioinformatics in a similar role) in biochemistry that has established less importance to a mitochondrial role after comparative kinetics that today are seen as faulty.
It is important to combat dogmatic reasoning and restore sound scientific foundations in basic medical courses that must urgently reverse the faulty trend that tries to impose a view that goes from the detail towards generalization instead of the correct form that goes from the general finding well understood towards its molecular details. The view that led to curious subjects as bioinformatics in medical courses as training in sequence finding activities can only be explained by its commercial value. The usual form of scientific thinking respects the limits of our ability to grasp new knowledge and relies on reproducibility of scientific results as a form to surpass lack of mathematical equation that defines relationship of variables and the determination of its functional domains. It also uses old scientific roots, as its sound support never replaces existing knowledge by dogmatic and/or wishful thinking. When the sequence of DNA was found as a technical advance to find amino acid sequence in proteins it was just a technical advance. This technical advance by no means could be considered a scientific result presented as an indication that DNA sequences alone have replaced the need to study protein chemistry, its responses to microenvironmental changes in order to understand its multiple conformations, changes in activities and function. As E. Schrodinger correctly describes the chemical structure responsible for the coded form stored of genetic information must have minimal interaction with its microenvironment in order to endure hundreds and hundreds years as seen in Hapsburg’s lips. Only magical reasoning assumes that it is possible to find out in non-reactive chemical structures the properties of the reactive ones.
For instance, knowledge of the reactions of the Krebs cycle clearly indicate a role for solvent that no longer could be considered to be an inert bath for catalytic activity of the enzymes when the transfer of energy include a role for hydrogen transport. The great increase in understanding this change on chemical reaction arrived from conformational energy.
Again, even a rather simplistic view of this atomic property (Conformational energy) is enough to confirm once more, one of the most important contribution of E. Schrodinger in his What is Life:
“This little book arose from a course of public lectures, delivered by a theoretical physicist to an audience of about four hundred which did not substantially dwindle, though warned at the outset that the subject matter was a difficult one and that the lectures could not be termed popular, even though the physicist’s most dreaded weapon, mathematical deduction, would hardly be utilized. The reason for this was not that the subject was simple enough to be explained without mathematics, but rather that it was much too involved to be fully accessible to mathematics.”
In a very simplistic view, while energy manifests itself by the ability to perform work conformational energy as a property derived from our atomic structure can be neutral, positive or negative (no effect, increased or decreased reactivity upon any chemistry reactivity measured as work)
Also:
“I mean the fact that we, whose total being is entirely based on a marvelous interplay of this very kind, yet if all possess the power of acquiring considerable knowledge about it. I think it possible that this knowledge may advance to little just a short of a complete understanding -of the first marvel. The second may well be beyond human understanding.”
In fact, scientific knowledge allows us to understand how biological evolution may have occurred or have not occurred and yet does not present a proof about how it would have being occurred. It will be always be an indication of possible against highly unlike and never a scientific proven fact about the real form of its occurrence.
As was the case of B. Chance in its bioenergetics findings, we may get very important findings that indicates wrong directions in the future as was his case, or directed toward our past.
The Skeleton of Physical Time – Quantum Energies in Relative Space of S-labs
By Radoslav S. Bozov Independent Researcher
WSEAS, Biology and BioSystems of Biomedicine
Space does not equate to distance, displacement of an object by classically defined forces – electromagnetic, gravity or inertia. In perceiving quantum open systems, a quanta, a package of energy, displaces properties of wave interference and statistical outcomes of sums of paths of particles detected by a design of S-labs.
The notion of S-labs, space labs, deals with inherent problems of operational module, R(i+1), where an imagination number ‘struggles’ to work under roots of a negative sign, a reflection of an observable set of sums reaching out of the limits of the human being organ, an eye or other foundational signal processing system.
While heavenly bodies, planets, star systems, and other exotic forms of light reflecting and/or emitting objects, observable via naked eye have been deduced to operate under numerical systems that calculate a periodic displacement of one relative to another, atomic clocks of nanospace open our eyes to ever expanding energy spaces, where matrices of interactive variables point to the problem of infinity of variations in scalar spaces, however, defining properties of minute universes as a mirror image of an astronomical system. The first and furthermost problem is essentially the same as those mathematical methodologies deduced by Isaac Newton and Albert Einstein for processing a surface. I will introduce you to a surface interference method by describing undetermined objective space in terms of determined subjective time.
Therefore, the moment will be an outcome of statistical sums of a numerical system extending from near zero to near one. Three strings hold down a dual system entangled via interference of two waves, where a single wave is a product of three particles (today named accordingly to either weak or strong interactions) momentum.
The above described system emerges from duality into trinity the objective space value of physical realities. The triangle of physical observables – charge, gravity and electromagnetism, is an outcome of interference of particles, strings and waves, where particles are not particles, or are strings strings, or are waves waves of an infinite character in an open system which we attempt to define to predict outcomes of tomorrow’s parameters, either dependent or independent as well as both subjective to time simulations.
We now know that aging of a biological organism cannot be defined within singularity. Thereafter, clocks are subjective to apparatuses measuring oscillation of defined parameters which enable us to calculate both amplitude and a period, which we know to be dependent on phase transitions.
The problem of phase was solved by the applicability of carbon relative systems. A piece of diamond does not get wet, yet it holds water’s light entangled property. Water is the dark force of light. To formulate such statement, we have been searching truth by examining cooling objects where the Maxwell demon is translated into information, a data complex system.
Modern perspectives in computing quantum based matrices, 0+1 =1 and/or 0+0=1, and/or 1+1 =0, will be reduced by applying a conceptual frame of Aladdin’s flying anti-gravity carpet, unwrapping both past and future by sending a photon to both, placing present always near zero. Thus, each parallel quantum computation of a natural system approaching the limit of a vibration of a string defining 0 does not equal 0, and 1 does not equal 1. In any case, if our method 1+1 = 1, yet, 1 is not 1 at time i+1. This will set the fundamentals of an operational module, called labris operator or in simplicity S-labs. Note, that 1 as a result is an event predictable to future, while interacting parameters of addition 1+1 may be both, 1 as an observable past, and 1 as an imaginary system, or 1+1 displaced interactive parameters of past observable events. This is the foundation of Future Quantum Relative Systems Interference (QRSI), taking analytical technologies of future as a result of data matrices compressing principle relative to carbon as a reference matter rational to water based properties.
Goedel’s concept of loops exist therefore only upon discrete relative space uniting to parallel absolute continuity of time ‘lags’. ( Goedel, Escher and Bach: An Eternal Golden Braid. A Metaphorical Fugue on Minds and Machines in the Spirit of Lewis Carroll. D Hofstadter. Chapter XX: Strange Loops, Or Tangled Hierarchies. A grand windup of many of the ideas about hierarchical systems and self-reference. It is concerned with the snarls which arise when systems turn back on themselves-for example, science probing science, government investigating governmental wrongdoing, art violating the rules of art, and finally, humans thinking about their own brains and minds. Does Gödel’s Theorem have anything to say about this last “snarl”? Are free will and the sensation of consciousness connected to Gödel’s Theorem? The Chapter ends by tying Gödel, Escher, and Bach together once again.) The fight struggle in-between time creates dark spaces within which strings manage to obey light properties – entangled bozons of information carrying future outcomes of a systems processing consciousness. Therefore, Albert Einstein was correct in his quantum time realities by rejecting a resolving cube of sugar within a cup of tea (Henri Bergson 19th century philosopher. Bergson’s concept of multiplicity attempts to unify in a consistent way two contradictory features: heterogeneity and continuity. Many philosophers today think that this concept of multiplicity, despite its difficulty, is revolutionary.) However, the unity of time and space could not be achieved by deducing time to charge, gravity and electromagnetic properties of energy and mass.
Charge is further deduced to interference of particles/strings/waves, contrary to the Hawking idea of irreducibility of chemical energy carrying ‘units’, and gravity is accounted for by intrinsic properties of anti-gravity carbon systems processing light, an electromagnetic force, that I have deduced towards ever expanding discrete energy space-energies rational to compressing mass/time. The role of loops seems to operate to control formalities where boundaries of space fluctuate as a result of what we called above – dark time-spaces.
Indeed, the concept of horizon is a constant due to ever expanding observables. Thus, it fails to acquire a rational approach towards space-time issues.
Richard Feynman has touched on issues of touching of space, sums of paths of particle traveling through time. In a way he has resolved an important paradigm, storing information and possibly studying it by opening a black box. Schroedinger’s cat is alive again, but incapable of climbing a tree when chased by a dog. Every time a cat climbs a garden tree, a fruit falls on hedgehogs carried away parallel to living wormholes whose purpose of generating information lies upon carbon units resolving light.
In order to deal with such a paradigm, we will introduce i+1 under square root in relativity, therefore taking negative one ( -1 = sqrt (i+1), an operational module R dealing with Wheelers foam squeezed by light, releasing water – dark spaces. Thousand words down!
What is a number? Is that a name or some kind of language or both? Is the issue of number theory possibly accountable to the value of the concept of entropic timing? Light penetrating a pyramid holding bean seeds on a piece of paper and a piece of slice of bread, a triple set, where a church mouse has taken a drop of tear, but a blood drop. What an amazing physics! The magic of biology lies above egoism, above pride, and below Saints.
We will set up the twelve parameters seen through 3+1 in classic realities:
– discrete absolute energies/forces – no contradiction for now between Newtonian and Albert Einstein mechanics
– mass absolute continuity – conservational law of physics in accordance to weak and strong forces
– quantum relative spaces – issuing a paradox of Albert Einstein’s space-time resolved by the uncertainty principle
– parallel continuity of multiple time/universes – resolving uncertainty of united space and energy through evolving statistical concepts of scalar relative space expansion and vector quantum energies by compressing relative continuity of matter in it, ever compressing flat surfaces – finding the inverse link between deterministic mechanics of displacement and imaginary space, where spheres fit within surface of triangles as time unwraps past by pulling strings from future.
To us, common human beings, with an extra curiosity overloaded by real dreams, value happens to play in the intricate foundation of life – the garden of love, its carbon management in mind, collecting pieces of squeezed cooling time.
The infinite interference of each operational module to another composing ever emerging time constrains unified by the Solar system, objective to humanity, perhaps answers that a drop of blood and a drop of tear is united by a droplet of a substance separating negative entropy to time courses of a physical realities as defined by an open algorithm where chasing power subdue to space becomes an issue of time.
Jose Eduardo de Salles Roselino
Some small errors: For intance an increase i P leads to a decrease in V ( not an increase in V)..
Radoslav S. Bozov Independent Researcher
If we were to use a preventative measures of medical science, instruments of medical science must predict future outcomes based on observable parameters of history….. There are several key issues arising: 1. Despite pinning a difference on genomic scale , say pieces of information, we do not know how to have changed that – that is shift methylome occupying genome surfaces , in a precise manner.. 2. Living systems operational quo DO NOT work as by vector gravity physics of ‘building blocks. That is projecting a delusional concept of a masonry trick, who has not worked by corner stones and ever shifting momenta … Assuming genomic assembling worked, that is dealing with inferences through data mining and annotation, we are not in a position to read future in real time, and we will never be, because of the rtPCR technology self restriction into data -time processing .. We know of existing post translational modalities… 3. We don’t know what we don’t know, and that foundational to future medicine – that is dealing with biological clocks, behavior, and various daily life inputs ranging from radiation to water systems, food quality, drugs…
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Table of Contents forMetabolic Genomics & Pharmaceutics, Vol. I
Chapter 1: Metabolic Pathways
Chapter 2: Lipid Metabolism
Chapter 3: Cell Signaling
Chapter 4: Protein Synthesis and Degradation
Chapter 5: Sub-cellular Structure
Chapter 6: Proteomics
Chapter 7: Metabolomics
Chapter 8: Impairments in Pathological States: Endocrine Disorders; Stress
Hypermetabolism and Cancer
Chapter 9: Genomic Expression in Health and Disease
Emeritus Prof. Department of Pathology, Yale University, USA
Triplex Consulting Pharmaceuticals, MA, USA
larry.bernstein@gmail.com
*To whom correspondence should be addressed
Abstract
Background: It was 80 years after the Otto Warburg discovery of aerobic glycolysis, a major hallmark in the understanding of cancer. The Warburg effect is the preference of cancer cell for glycolysis that produce lactate even when sufficient oxygen is provided. “Reverse Warburg effect” refers to the interstitial tissue communications with adjacent epithelium, that in the process of carcinogenesis, is needed to be explored. Among these cell-cell communications, the contact between epithelial cells, between epithelial cells and matrix, and between fibroblasts and inflammatory cells in the underlying matrix. Cancer involves dysregulation of Warburg and Reverse Warburg cellular metabolic pathways. Aim: How these gene and protein-based regulatory mechanisms have functioned has been the basis for this review. Method: the importance of the Warburg in oxidative phosphorylation suppression, with increased glycolysis in cancer growth and proliferation are emphasized. Studies that are directed at pathways that would be expected to shift cell metabolism to an increased oxidation and to a decrease in glycolysis are emphasized. Key enzymes required for oxidative phosphorylation, and affect the inhibition of fatty acid metabolism and glutamine dependence are conferred. Discussion: The findings are of special interest to cancer pharmacotherapy. Studies described in this review are concerned with the effects of therapeutic modalities that are intimately related to the Warburg effect. These interactions described may be helpful as adjuvant therapy in controlling the process of proliferation and metastasis.
Cancer therapeutic modalities based on Warburg effect
New Insights on the Warburg Effect [2.2]
Defective Mitochondria Transform Normal Cells into Tumors
GEN News Jul 9, 2015
Ninety-one years ago Otto Warburg demonstrated that cancer cells have impaired respiration, which became known as the Warburg Effect. The interest in this and related work was superceded in the last quarter of the twentieth century by work on the genetic code. Now there is renewed interest.
An international research team reports that a specific defect in mitochondria plays a key role in the transition from normal cells to cancerous ones. The scientists disrupted a key component of mitochondria of otherwise normal cells and the cells took on characteristics of malignant cells.
Their study (“Disruption of cytochrome c oxidase function induces the Warburg effect and metabolic reprogramming”) is published Oncogene and was led by members of the lab of Narayan G. Avadhani, Ph.D., the Harriet Ellison Woodward Professor of Biochemistry in the department of biomedical sciences in the school of veterinary medicine at the University of Pennsylvania. Satish Srinivasan, Ph.D., a research investigator in Dr. Avadhani’s lab, was the lead author.
This is consistent with the 1924 observation by Warburg that cancerous cells consumed glucose at a higher rate than normal cells (Meyerhof ratio) and had defects in their grana, the organelles that are now known as mitochondria. He postulated that these defects led to problems in the process by which the cell produces energy. But the process called oxidative phosphorylation was not yet known. Further work in his laboratory was carried out by Hans Krebs and by Albert Szent Gyorgyi elucidating the tricarboxylic acid cycle. The discovery of the importance of cytochrome c and adenosine triphosphate in oxidative phosphorylation was made in the post World War II period by Fritz Lippman, with an important contribution by Nathan Kaplan. All of the name scientists, except Kaplan, received Nobel Prizes. The last piece of the puzzle became the demonstation of a sequence of hydrogen transfers on the electron transport chain. The researchers above have now shown that mitochondrial defects indeed contributed to the cells becoming cancerous.
“The first part of the Warburg hypothesis has held up solidly in that most proliferating tumors show high dependence on glucose as an energy source and they release large amounts of lactic acid,” said Dr. Avadhani. “But the second part, about the defective mitochondrial function causing cells to be tumorigenic, has been highly contentious.”
To see whether the second part of Warburg’s postulation was correct, the researchers took cell lines from the skeleton, kidney, breast, and esophagus and used RNA molecules to silence the expression of select components of mitochondrial cytochrome oxidase C, or CcO, a critical enzyme involved in oxidative phosphorylation. CcO uses oxygen to make water and set up a transmembrane potential that is used to synthesize ATP, the molecule used for energy by the body’s cells.
The biologists observed that disrupting only a single protein subunit of cytochrome oxidase C led to major changes in the mitochondria and in the cells themselves. “These cells showed all the characteristics of cancer cells,” noted Dr. Avadhani.
The normal cells that converted to cancerous cells displayed changes in their metabolism, becoming more reliant on glucose by utilization of the glycolytic pathway. They reduced their synthesis of ATP. Oxidative phosphorylation was reduced in concert with the ATP reduction. The large switch to glycolysis as primary energy source is a less efficient means of making ATP that is common in cancer cells.
The cells lost contact inhibition and gained an increased ability to invade distant tissues, both hallmarks of cancer cells. When they were grown in a 3D medium, which closely mimics the natural environment in which tumors grow in the body, the cells with disrupted mitochondria formed large, long-lived colonies, akin to tumors.
The researchers also silenced cytochrome oxidase C subunits in breast and esophageal cancer cell lines. They found that the cells became even more invasive, according to Dr. Srinivasan. The team then looked at actual tumors from human patients and found that the most oxygen-starved regions, which are common in tumors, contained defective versions of CcO.
“That result alone couldn’t tell us whether that was the cause or effect of tumors, but our cell system clearly says that mitochondrial dysfunction is a driving force in tumorigenesis,” explained Dr. Avadhani.
The researchers observed that disrupting CcO triggered the mitochondria to activate a stress signal to the nucleus, akin to an SOS alerting the cell that something was wrong. Dr. Avadhani and his colleagues had previously seen a similar pathway activated in cells with depleted mitochondrial DNA, which is also linked to cancer.
Building on these findings, Dr. Avadhani and members of his lab will examine whether inhibiting components of this mitochondrial stress signaling pathway might be a strategy for preventing cancer progression.
“We are targeting the signaling pathway, developing a lot of small molecules and antibodies,” said Dr. Avadhani. “Hopefully if you block the signaling the cells will not go into the so called oncogenic mode and instead would simply die.”
In addition, they noted that looking for defects in CcO could be a biomarker for cancer screening.
Who controls the ATP supply in cancer cells? Biochemistry lessons to understand cancer energy metabolism
Rafael Moreno-Sánchez, Alvaro Marín-Hernández, Emma Saavedra, Juan P. Pardo, Stephen J. Ralph, Sara Rodríguez-Enríquez
Intl J Biochem Cell Biol 7 Feb 2014; 50:10-23 http://dx.doi.org/10.1016/j.biocel.2014.01.025
The supply of ATP in mammalian and human cells is provided by glycolysis and oxidative phosphorylation (OxPhos). There are no other pathways or processes able to synthesize ATP at sufficient rates to meet the energy demands of cells. Acetate thiokinase or acetyl-CoA synthetase, a ubiquitous enzyme catalyzing the synthesis of ATP and acetate from acetyl-CoA, PPi and AMP, might represent an exception under hypoxia in cancer cells, although the flux through this branch is negligible (≤10%) when compared to the glycolytic flux (Yoshii et al., 2009).
Glycolysis in human cells can be defined as the metabolic process that transforms 1 mol of glucose (or other hexoses) into 2 moles of lactate plus 2 moles of ATP. These stoichiometric values represent a maximum and due to the several reactions branching off glycolysis, they will be usually lower under physiological conditions, closer to 1.3–1.9 for the lactate/glucose ratio (Travis et al., 1971; Jablonska and Bishop, 1975; Suter and Weidemann, 1975; Hanson and Parsons, 1976; Wu and Davis, 1981; Pick-Kober and Schneider, 1984; Sun et al., 2012). OxPhos is the metabolic process that oxidizes several substrates through the Krebs cycle to produce reducing equivalents (NADH, FADH2), which feed the respiratory chain to generate an H+.
Applying basic biochemical principles, this review analyzes data that contrasts with the Warburg hypothesis that glycolysis is the exclusive ATP provider in cancer cells. Although disregarded for many years, there is increasing experimental evidence demonstrating that oxidative phosphorylation (OxPhos) makes a significant contribution to ATP supply in many cancer cell types and under a variety of conditions.
Substrates oxidized by normal mitochondria such as amino acids and fatty acids are also avidly consumed by cancer cells. In this regard, the proposal that cancer cells metabolize glutamine for anabolic purposes without the need for a functional respiratory chain and OxPhos is analyzed considering thermodynamic and kinetic aspects for the reductive carboxylation of 2-oxoglutarate catalyzed by isocitrate dehydrogenase.
In addition, metabolic control analysis (MCA) studies applied to energy metabolism of cancer cells are reevaluated. Regardless of the experimental/environmental conditions and the rate of lactate production, the flux-control of cancer glycolysis is robust in the sense that it involves the same steps:
glucose transport,
hexokinase,
hexosephosphate isomerase, and
glycogen degradation,
all at the beginning of the pathway; these steps together with phosphofructokinase 1 also control glycolysis in normal cells.
The respiratory chain complexes exert significantly higher flux-control on OxPhos in cancer cells than in normal cells. Thus, determination of the contribution of each pathway to ATP supply and/or the flux-control distribution of both pathways in cancer cells is necessary in order to identify differences from normal cells which may lead to the design of rational alternative therapies that selectively target cancer energy metabolism.
Fig. 1. Labeling patterns of 13C-glutamate or 13C-glutamine mitochondrial metabolism in cancer cells.
Fig. 2. Survey in PubMed of papers published in the field of tumor mitochondrial metabolism from 1951 to September 2013.
Emerging concepts in bioenergetics and cancer research: Metabolic flexibility, coupling, symbiosis, switch, oxidative tumors, metabolic remodeling, signaling and bioenergetic therapy
The field of energy metabolism dramatically progressed in the last decade, owing to a large number of cancer studies, as well as fundamental investigations on related transcriptional networks and cellular interactions with the microenvironment. The concept of metabolic flexibility was clarified in studies showing the ability of cancer cells to remodel the biochemical pathways of energy transduction and linked anabolism in response to glucose, glutamine or oxygen deprivation.
A clearer understanding of the large scale bioenergetic impact of C-MYC, MYCN, KRAS and P53 was obtained, along with its modification during the course of tumor development. The metabolic dialog between different types of cancer cells, but also with the stroma, also complexified the understanding of bioenergetics and raised the concepts of metabolic symbiosis and reverse Warburg effect.
Signaling studies revealed the role of respiratory chain derived reactive oxygen species for metabolic remodeling and metastasis development. The discovery of oxidative tumors in human and mice models related to chemoresistance also changed the prevalent view of dysfunctional mitochondria in cancer cells. Likewise, the influence of energy metabolism-derived oncometabolites emerged as a new means of tumor genetic regulation. The knowledge obtained on the multi-site regulation of energy metabolism in tumors was translated to cancer preclinical studies, supported by genetic proof of concept studies targeting LDHA, HK2, PGAM1, or ACLY.
Here, we review those different facets of metabolic remodeling in cancer, from its diversity in physiology and pathology, to the search of the genetic determinants, the microenvironmental regulators and pharmacological modulators.
Pyruvate kinase M2: A key enzyme of the tumor metabolome and its medical relevance
Mazurek, S.
Biomedical Research 2012; 23(SPEC. ISSUE): Pages 133-142
Tumor cells are characterized by an over expression of the glycolytic pyruvate kinase isoenzyme
type M2 (abbreviations: M2-PK or PKM2). In tumor metabolism the quaternary structure of M2-PK (tetramer/dimer ratio) determines whether glucose is used for glycolytic energy regeneration (highly active tetrameric form, Warburg effect) or synthesis of cell building blocks (nearly inactive dimeric form) which are both prerequisites for cells with a high proliferation rate. In tumor cells the nearly inactive dimeric form of M2- PK is predominant due to direct interactions with different oncoproteins. Besides its key functions in tumor metabolism recent studies revealed that M2-PK may also react as protein kinase as well as co activator of transcription factors. Of medical relevance is the quantification of the dimeric form of M2-PK with either an ELISA or point of care rapid test in plasma and stool that is used for follow-up studies during therapy (plasma M2-PK) and colorectal cancer (CRC) screening (fecal M2-PK; mean sensitivity for CRC in 12 independent studies with altogether 704 samples: 80% ± 7%). An intervention in the regulation mechanisms of the expression, activity and tetramer: dimer ratio of M2-PK has significant consequences for the proliferation rate and tumorigenic capacity of the tumor cells, making this enzyme an intensively
Normal mitochondrial function is a critical factor in maintaining cellular homeostasis in various organs of the body. Due to the involvement of mitochondrial dysfunction in many pathological states, the real-time in vivo monitoring of the mitochondrial metabolic state is crucially important. This type of monitoring in animal models as well as in patients provides real-time data that can help interpret experimental results or optimize patient treatment. The goals of the present review are the following: 1) to provide an historical overview of NADH fluorescence monitoring and its physiological significance; 2) to present the solid scientific ground underlying NADH fluorescence measurements based on published materials; 3) to provide the reader with basic information on the methodologies used in the past and the current state of the art fluorometers; and 4) to clarify the various factors affecting monitored signals, including artifacts. The large numbers of publications by different groups testify to the valuable information gathered in various experimental conditions. The monitoring of NADH levels in the tissue provides the most important information on the metabolic state of the mitochondria in terms of energy production and intracellular oxygen levels. Although NADH signals are not calibrated in absolute units, their trend monitoring is important for the interpretation of physiological or pathological situations. To understand tissue function better, the multiparametric approach has been developed where NADH serves as the key parameter. The development of new light sources in UV and visible spectra has led to the development of small compact units applicable in clinical conditions for better diagnosis of patients.
UNDERSTANDING THE MITOCHONDRIAL function has been a challenge for many investigators, including cytologists, biochemists, and physiologists, since its discovery more than 120 years ago. In addition to many books regarding the mitochondria, Ernster and Schatz (79) reviewed the history of mitochondrial structure and function studies. In the past two decades, several studies have reported mitochondrial involvement in pathological processes such as stroke (225) or cytoprotection (77). Most of the information on the mitochondrial function has been accumulated from in vitro studies. A relatively small portion of published papers dealt with the monitoring of mitochondrial function in vivo and in real time. Presently, examination of the involvement of the mitochondrial function in many pathological states, such as sepsis, requires monitoring of patients treated in intensive care units. Unfortunately, real-time monitoring of the mitochondrial function in patients has rarely been performed. The current study presents a review of this issue. To evaluate the activity of the respiratory chain in vivo, it is possible to monitor the mitochondrial NADH, FAD, or the cytochrome oxidase oxidation-reduction state. The interference of blood with the monitoring of FAD and cytochrome oxidase is much higher than with NADH (48); therefore, we invest our effort into the monitoring of the mitochondrial NADH redox state. We do not know of any publication showing clearly that Fp fluorescence could be monitored in vivo in blood-perfused organs. In our preliminary report, we showed that in specific brain areas, one can see the fluorescence of Fp but we were not sure how to validate the results. During the past 33 years, we have published >140 papers in this very significant area, including the largest number of studies using NADH redox state monitoring in patients.
Since the discovery of pyridine nucleotides by Harden and Young (94), >1,000 papers have been published on the use of NADH (Fig. 1A) as a marker for mitochondrial function. In 2000, Schleffler et al. (217) reviewed mitochondrial research methods over the past century. A major aspect of mitochondrial function, namely monitoring the energy state of tissues in vivo, was not discussed in that review. Therefore, the present review will summarize 50 years of research, started in 1955 by Chance and Williams (56, 57), by defining the mitochondrial metabolic state in vitro. To understand mitochondrial function in vivo and under various pathophysiological conditions, it is important to monitor the redox state of the respiratory chain in real time. The present review will discuss the monitoring principles for one of the electron carriers, namely, nicotinamide adenine dinucleotide (NADH). It is well known that mitochondrial dysfunction is involved in many diseases, such as ischemia, hypoxemia, Parkinson’s disease, Alzheimer’s disease, and in the apoptotic process. Therefore, the possibility of monitoring the mitochondrial NADH redox state in experimental animals and patients is of great importance.
inter-conversion of NAD+ and NADH & difference in the absorption spectra of NAD+ and NADH
Fig. 1. A: molecular structure of NAD+ and the inter-conversion of NAD+ and NADH. B: difference in the absorption spectra of NAD+ and NADH. C: emission spectra of brain NADH excited by 366 nm light (A1, A2, B1, B2, C1) or 324 nm laser light (C2). C1 and C2 show measurements from a dead brain, for comparison of NADH spectra using two different light sources.
To assess the energy demand, it is necessary to measure different organ-specific parameters. In the brain, the energy demand can be evaluated by measuring the extracellular levels of K+ that reflect the activity of the major ATP consumer: Na+-K+-ATPase (152, 161). In the heart, most of the energy is consumed by the muscle contraction activity. On the other hand, the energy supply mechanism is the same in all tissues: oxygenated blood reaching the capillary bed releases O2that diffuses into the cells. Therefore, it is possible to evaluate tissue energy supply by monitoring the same four different parameters in all tissues.
The main function of the mitochondria is to convert the potential energy stored in various substrates (e.g., glucose) into ATP. The inner membrane of the mitochondria contains 5 complexes of integral membrane proteins, including NADH dehydrogenase (complex 1). Three of those proteins are involved in the respiratory chain activity. The main function of the respiratory chain is to gradually transfer electrons from NADH and FADH2 (originating from the TCA cycle) to O2. With the addition of protons (H+), H2O is generated in complex 4. NADH (Fig. 1A, right side) is a substrate or a coenzyme for the enzymatic activity of dehydrogenases that form part of the respiratory chain and reside in the inner membrane of the mitochondria.
Spectroscopic Monitoring of NADH: An Historical Overview
The discovery of the optical properties of reduced nicotinamide adenine dinucleotide (NADH; previously known as diphosphopyridine nucleotide or pyridine nucleotide) has led to a very intensive research since the early 1950s. The reduced form of this molecule, NADH, absorbs light at 320–380 nm (Fig. 1B) and emits fluorescent light at the 420–480 nm range (Fig. 1C).
Because the oxidized form NAD+ does not absorb light in this range, it was possible to evaluate the redox state of the mitochondria by monitoring the UV absorbance (see Monitoring UV absorbance by NADH) or blue fluorescence of NADH (see Monitoring NADH fluorescence).
Undoubtedly, the pioneering work of Britton Chance of the Johnson Research Foundation at the University of Pennsylvania in Philadelphia led to the establishment and development of the unique measurement technology and theoretical conceptualization of the mitochondrial function based on NADH redox state monitoring in vitro as well as in vivo.
The foundations for future NADH monitoring in vitro and in vivo were established mainly in the 1950s; thus this period will be discussed in this section.
Monitoring of NADH UV absorbance
In 1951, Theorell and Bonnichsen found a shift in the absorption spectrum of DPNH upon addition of alcohol dehydrogenase (238). In the same year, Theorell and Chance described a new spectrophotometric technique for measuring the formation and disappearance of the compound of alcohol dehydrogenase and NADH (239). In 1952, Chance showed the applicability of this new technique to the measurements of pyridine nucleotide enzymes of muscle homogenate or intact cells (25). In 1954, Chance and Williams briefly described new sensitive differential spectrophotometric methods applied to the study of reduced NADH in isolated rat liver mitochondria and the same approach was used by Connelly and Chance (61) in monitoring NADH in stimulated frog nerve and muscle preparations. The oxidation of NADH in the muscle was similar to its oxidation in isolated mitochondria upon addition of ADP. In a comprehensive paper, “Enzyme mechanisms in living cells,” Chance described in detail the measurements of the respiratory enzymes, including NADH (26).
A major milestone in NADH monitoring was the technique presented in 1954 by Chance (27) using a double beam spectrophotometer to determine the appropriate wavelengths in measurements of respiratory enzymes.
The detailed descriptions of the respiratory chain and oxidative phosphorylation in the mitochondria (published in 1955 by Chance and Williams) established our basic knowledge of the mitochondrial function (57). Chance and Williams defined, for the first time, the metabolic states of isolated mitochondria in vitro, depending on the substrate, oxygen, and ADP levels. In addition, they correlated those metabolic states to the oxidation-reduction levels of the respiratory enzymes. The physiological significance of those metabolic states was discussed in 1956 by Chance and Williams (58).
Monitoring NADH fluorescence
The fact that NADH was monitored by the difference in the absorption spectrum of its reduced form, limited the use of that technique to the study of mitochondria in vitro, and in very thin tissue samples (e.g., muscle) or in cell suspension. To provide a method more specific than absorption spectroscopy, fluorescence spectrophotometry in the near-ultraviolet range was applied for NADH measurement. The initial model of fluorescence recorder was described by Theorell and Nygaard in 1954 (240). The first detailed study using fluorescence spectrophotometry of NADH in intact Baker’s yeast cells and algae cells was published in 1957 by Duysens and Amesz (75).
In the next 5 years (1958–1962), the monitoring of NADH fluorescence was significantly expanded, led by Chance and collaborators. In a first preliminary study, Chance et al. (37) performed simultaneous fluorometric and spectrophotometric measurements of the reaction kinetics of bound pyridine nucleotides (PN) in the mitochondria. In the same year (1958), Chance and Baltscheffsky presented preliminary results of measuring the fluorescence of intramitochondrial PN (34). In this study, they proved the connection between the mitochondrial metabolic state and the redox state of NADH as measured by spectral fluorometry in mitochondria isolated from rat liver (57). The correlation between the enzymatic assay of PN and sensitive spectrophotometry was investigated by Klingeberger et al. (120) by using the rat liver, heart, kidney, and brain.
In 1959, Chance and collaborators were able to expand the use of NADH fluorometry to various experimental models, from isolated mitochondria to intact tissue. To monitor NADH localization in intact cells, Chance and Legallais (42) developed a unique differential microfluorimeter with a very high spatial resolution. This approach was used in various cells to identify the intracellular localization of NADH fluorescence signals (54, 201). The next step was to apply the fluorometric technique to the higher organization level of animal tissues. Together with Jobsis, Chance measured in vitro changes in muscle NADH fluorescence following stimulation (41). In another paper published by Chance and Theorell (55) the authors came to the very significant conclusion that “The oxidation and reduction state of mitochondrial pyridine nucleotide without a measurable change of cytoplasmic fluorescence suggest that compartmentalization of mitochondrial and cytoplasmic pyridine nucleotide occurs in vivo, at least in the grasshopper spermatid.”
An intensive use of the in vivo NADH monitoring approach started in 1962. The “classic” paper on in vivo monitoring of NADH was published in 1962 by Chance et al. (36). They were able to simultaneously monitor the brain and kidney of anesthetized rats using two microfluorometers. In 1962, Chance and collaborators elaborated on this kind of in vivo monitoring and used it in other rat organs (43, 50).
Scientific Background And Technological Aspects
The absorption and fluorescence spectra of NADH (the reduced form) have been well characterized at different levels of organization, i.e., in solution, mitochondria and cell suspensions, tissue slices, and organs in vitro and in vivo. NADH has an optical absorption band at about 300 to 380 nm and a fluorescence emission band at 420 to 480 nm (Fig. 1, B and C). The spectra are considered the same, although there are small differences in the shape and maxima of the spectra for different environments and measurement conditions. However, there is a universal agreement that the intensity of the fluorescence band, independent of the organization level of the environment, is proportional to the concentration of mitochondrial NADH (the reduced form), particularly when measured in vivo from a tissue.
The biochemical and physiological significance of these spectral qualities is also universally accepted, that is, an increase in the fluorescence intensity indicates a more reduced state of NADH and of the rest of the mitochondrial electron transfer chain. Under various circumstances, changes in the redox state of the electron transport chain can be associated with various conditions.
To monitor NADH fluorescence, it is possible to use one of the two principles available. At the early stage, it was necessary to measure and identify the fluorescence spectrum of NADH. Fluorescence spectra were compared in different in vitro and in vivo preparations. In parallel, the second approach was adopted, namely, measuring the total fluorescence signal accumulated and integrated into a single intensity using appropriate filters. This approach was necessary to measure NADH fluorescence continuously. The following parts of this section describe the fluorescence spectra of NADH measured in various in vitro and in vivo models by different investigators. We present this review of the reported spectra to describe the foundations for the second monitoring approach, namely, the continuous monitoring of integrated spectra.
Fluorescence Emission Spectra of NADH
NADH in solution.
Several investigators have measured NADH fluorescence in solution. Very recently, Alfano’s group (62) performed a calibration test of pure β-NADH in solution, compared it to porcine myocutaneous flap, and found a very significant correlation. The NADH solution spectrum and mitochondrial spectrum were also compared by Chance and Baltscheffsky (34).
Similar spectra of NADH in solution were recorded by Schomacker et al. (219) using 337-nm excitation light for colonic tissue diagnosis.
NADH spectra in isolated mitochondria.
The excitation and emission spectra of NADH (PN) and flavoprotein were measured in frozen samples of pigeon heart mitochondria (52). Using rat liver mitochondria, Chance and Baltscheffsky (34) measured the fluorescence spectra in the three metabolic states defined by Chance and Williams (58). The 330-nm light excitation resulted in a fluorescence peak at 440–450 nm. The same kind of spectra was obtained by other investigators using different fluorometers or mitochondria isolated from various organs. Galeotti et al. (87) measured similar spectra from rat liver mitochondria. Using Rhodamine B as an internal standard for system calibration, Koretsky and Balaban (125) found the same spectra emitted from isolated rat liver mitochondria. Koretsky et al. (126) compared the emitted spectrum from heart homogenates (similar to isolated mitochondria) with that of dissolved heart homogenates (126).
Intact cells.
The use of microfluorimetry to study intact cell metabolism was described in several publications by Kohen and collaborators (see, for example, Ref. 123).
The typical NADH fluorescence spectrum was measured in suspension of ascite tumor cells (87). This study demonstrated that the spectrum of intact cells was similar to that of NADH solution.
Using isolated myocytes, Eng et al. (78) compared the spectra measured under various conditions of the mitochondria. They found that cyanide induced an increase in the spectrum difference, whereas FCCP, used as a typical uncoupler of oxidative phosphorylation, produced a marked decrease in the spectrum.
….
Principles of NADH monitoring.
As described in the introductory section, NADH can be measured by utilizing its absorption spectrum in the UV range, as well as by the blue fluorescence spectrum under UV illumination. In the early stages, NADH monitoring was based on the difference in the absorption of NADH and NAD+. At the range of 320 to 380 nm, only the reduced form; NADH absorbs light, while NAD+does not (Fig. 1B). Therefore, when a mixture of NADH and NAD+ is illuminated in a cuvette by 320–380 nm, only NADH will affect the absorption spectrum peak at 340 nm. This property of NADH was used in the early 1950s by several investigators, as reviewed in Spectroscopic Monitoring of NADH–Historical Overview. Chance and collaborators utilized this technique to measure NADH in muscle homogenates or intact cells (25) and published many papers concerning the unique absorption spectrum of NADH.
The absorption approach is not practical for measuring NADH in a thick tissue; hence, another property of NADH was used. Since the early 1950s, fluorescence spectrophotometry of NADH has been employed in various in vitro and in vivo models. The emission of NADH fluorescence, under illumination at 320–380 nm, has a very wide spectrum (420–480) with a peak at 450–460 nm (Fig. 1C). NADH fluorescence has been identified by Chance and his collaborators as a good indicator of the intramitochondrial oxidation-reduction state (48).
…
The review article on in vivo NADH fluorescence monitoring, published in 1992 by Ince et al. (102) included many other technical aspects of the methodology. Nevertheless, here we will elaborate on the historical development of the various models of NADH fluorometers. We recently (155) reported on a new type of NADH fluorometer based on a very small and stable UV light source: a 375-nm light-emitting diode.
….
In 1959, Chance and Legallais (42) described a differential fluorometer that heralded a new era in monitoring NADH fluorescence in vivo as an indicator of mitochondrial function. They used a microscope, serving as the fluorometer basis, with two light sources: tungsten and mercury lamps with appropriate filters. In 1959, Chance and Jobsis (41) proved that mechanical muscle activity is associated with NADH oxidation measured in excised muscle. This study was the bridge from the subcellular (mitochondria) and cellular (intact cell) monitoring approaches toward actual in vivo applications.
The first in vivo NADH monitoring device was presented in the early 1960s. At that stage, the effects of scattered light and tissue absorption due to blood were not taken into consideration when monitoring NADH fluorescence. The first detailed results of in vivo NADH fluorescence measurements were published in 1962 (36).
These classic papers described two microfluorometers that were modifications of previous designs (42, 54). This microfluorimeter type employed Leitz “Ultrapack” illumination, which had been used for many years by various groups until the appearance of UV transmitting optical fibers. To avoid movement artifacts, rats were anesthetized deeply and their heads were fixated in a special holder attached to the operation table. Numerous studies utilized the principles of the “Ultrapack” illumination system. The same instrumentation was used in other in vivo studies, including those of Chance’s group (38, 43, 44, 59), Dora and Kovach’s group (71, 92), Rievich’s group (93), Jobsis and collaborators (108, 110, 111, 213), Gosalvez et al. (89), and Anderson and Sundt (5, 232). This is only a partial list.
Monitoring NADH fluorescence and reflectance.
The effect of blood on NADH fluorescence was discussed early by Chance et al. (36). To monitor NADH in vivo, Chance’s group had to avoid areas containing large blood vessels, which interfere with the emission and excitation light. The monitoring of a second channel in tissue fluorometry in vivo was reported by Chance and Legallais in 1963 (44). They showed that “changes due to the deoxygenation of oxyhemaglobin do not interfere with measurement of the time course of fluorescence changes in the tissue studies.”
The addition of a second monitoring signal, namely, tissue reflectance at the excitation wavelength was reported in 1968 by Jobsis and Stansby (112). It was based on a previous model described by Jobsis et al. in 1966 (107). In two more papers by Jobsis and collaborators (110,111), the measurement of 366-nm reflectance was used for the correction of the NADH fluorescence signal from the brain. The reflectance signal was subtracted from the fluorescence signal. The same type of instrumentation was used by various groups for the measurement of NADH in single cells (124) or in vitro preparations (13, 19).
Fiber optic fluorometer/reflectometer.
To enable the monitoring of NADH fluorescence in unanesthetized animals or other in vivo preparations, a flexible means was needed to connect the fluorometer with the tested organ, for example the brain. This was achieved in 1972, when UV transmitting quartz fibers became available (Schott Jena Glass). We have used the light guide-based fluorometer for in vivo monitoring of the brain (48, 157) subjected to anoxia or cortical spreading depression. The historical development of light guide-based fluorometery-reflectometry is shown in Fig. 2. The original device functioned on the time-sharing principle (Fig. 2A), where four filters were placed in front of a two-arms light guide. Filters 1 and 3 enabled the measurement of NADH fluorescence, while filters 2 and 4 were used to measure tissue reflectance at the excitation wavelength. The reflectance trace was used to correct the NADH signal for hemodynamic artifacts, and to indicate changes in the blood volume of the sampled tissue.
Fig. 2. The three stages in the development of the fiber optic fluorometer/reflectometer (started in the early 1970s).
development of the fiber optic fluorometer_reflectometer
Factors Affecting NADH Fluorescence and Reflectance Signals
The excitation and emission spectra of NADH are affected by the redox state of this fluorochrome and by other factors, leading to artifacts in the fluorescence measurements. This section will discuss various NADH-unrelated factors, affecting the measured signal. Since most fluorometers involve the measurement of the total backscattered light at the excitation wavelength (i.e., 366 nm), the discussion will concern changes in NADH fluorescence as well as in tissue reflectance.
The following factors may affect the two measured signals, 366-nm reflectance and 450-nm fluorescence: 1) tissue movement due to mechanical or intracranial pressure changes; 2) extracellular space events, such as volume changes or ion shifts between intra- and extracellular space; 3) vascular and intravascular events, for example, oxy-deoxy Hb changes, and blood volume changes due to autoregulatory vasoconstriction under pathological conditions; and 4) intracellular space factors, such as O2 level, ATP turnover rate, substrate availability, and mitochondrial redox state.
Fig. 3. Comparison between the mitochondrial metabolic state, defined by Chance and Williams (56, 57) and responses of the in vivo brain to changes in O2 supply and brain activation.
mitochondrial metabolic state, defined by Chance and Williams (56, 57) and responses of the in vivo brain to changes in O2 supply
Changes in mitochondrial NADH and tissue metabolic state
The pioneering work of Chance and Williams in the 1950s, led to the definition of the metabolic state of isolated mitochondria in vitro. The foundations for the use of NADH fluorescence as a marker of mitochondrial activity have been posited in detail by Chance and Williams (56, 57). The left portion of ⇓Fig. 6 is a modification of a published table, while the right hand segment demonstrates the responses of NADH fluorescence measured in the brain in vivo under various perturbations. The “resting state” of the mitochondria in vitro was defined as state 4, where NADH was 99% in the reduced form, and ADP was the rate limiting substance. If ADP is added to a suspension of mitochondria, ATP synthesis will be stimulated, O2 consumption will increase, and the rate limit will be determined by the activity of the respiratory chain. During this state 3, or the “active state,” the NADH redox state will decrease or become more oxidized (∼50%). When the resting mitochondria are deprived of O2, the activity of the mitochondria will stop and NADH will reach its maximum redox state (state 5).
A definitive description of the mitochondrial metabolic state has never been given for in vivo conditions. Therefore, we described the in vivo mitochondria conditions as recorded by NADH fluorescence in a representative tissue or organ; e.g., the brain. While the range between minimal NADH (∼0) and its maximal level was determined in vitro, it is almost impossible to determine in the intact brain or other organs in vivo. For example, state 2, with a substrate free medium, could not be achieved in vivo since the tissue would die. On the other hand, the maximal level of NADH (state 5) could be monitored in vivo under complete deprivation of O2 by anoxia or complete ischemia.
We used changes in NADH levels monitored in vivo to create a new scale ranging from a maximal definite point to the minimal level recorded in vivo. Details of this approach have been published (152). As shown in Fig. 3, the maximal NADH level is achieved under complete O2 deprivation that can be induced both under in vitro and in vivo conditions. This signifies that this definitive point can be used to determine state 5 in vivo as well. The problem is to determine the metabolic state of a tissue in an in vivo situation. If we adopt the in vitro value of a resting state (state 4), this would signify that the increase in NADH during state 5, induced by anoxia (0% O2), would be only 1%. According to all in vivo studies, this is not the case, and during anoxia the increase in NADH is lager than the decrease under state 4 to 3 transition. Figure 3, right, illustrates that the observed level of NADH increase is indeed larger than the decrease. Therefore, we concluded that, under in vivo conditions, the “resting” metabolic state of the brain is found between states 4 and 3 rather than in state 4 as defined in vitro (152). To determine the maximal and minimal levels of NADH in vivo it is almost impossible to use cyanide or uncoupler (FCCP). Nevertheless, we were able to determine the maximal level by anoxia and the “minimal” level by nonfluorescing uncoupler. We injected the uncoupler pentachlorophenol into the ventricles of the rat’s brain while monitoring the NADH responses to anoxia and spreading depression (146). To perform a reliable study with cyanide, the animal would have to die and the results will not be helpful; therefore, we used the anoxia response to measure the maximal level of NADH. Using fiber optic fluorometry, we were able to monitor both anesthetized and awake rats. This figure will be discussed later on in this review. It is important to note that most of the published data on NADH monitoring, have been accumulated in brain studies. Therefore, we will present our data mainly relating to the brain, though results on other organs will be presented as well. Table 1⇓ lists studies published by various investigators as well as our publications. The papers are classified according to the organ monitored and the type of perturbation used. This table does not include rarely studied types of organs or perturbations. Such studies are cited individually in the text.
Table 1. Effect of O2 delivery and consumption on NADH redox state measured in various intact organs by various investigators
Table 2. Historical milestones in monitoring NADH fluorescence in vivo
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Anoxia and Hypoxia.
The responses to hypoxia and anoxia are very similar; therefore, they will be discussed together. According to the definition of Chance and Williams (56, 57), a shift toward state 5 involves an increase in NADH proportional to a decrease in O2 supply.
It is assumed that the response of NADH fluorescence to hypoxia or anoxia, induced in vivo, should be very similar to the response of isolated mitochondria. As shown in Fig. 4B, when the blood-free brain was exposed to N2, the fluorescence showed a clear increase-decrease cycle depending on the availability of O2. The reflectance trace was not affected at all. In autoregulated blood-perfused organs, it is expected that the lack of O2 will trigger compensation mechanisms that may lead to an increase in the blood flow and volume, or a decrease in thereflectancesignal. We tested, in the same rats, the response to anoxia of the normoxic blood-perfused brain. The results are shown in Fig. 4A. Indeed, reflectance exhibited a large decrease due to the increase in blood volume (vasodilatation of brain vessels). Figure 4, C and D, presents the responses to anoxia measured via 2 mm and 1 mm light guides. A small variation can be seen in the reflectance response between the two light guides.
Ischemia, Or Decreased Blood Flow.
Under partial or complete ischemia, blood flow to the monitored organ is decreased and, as a result, O2 delivery is limited or even abolished. The use of ischemia in animal models provides information relevant to critical clinical situations such as brain stroke or heart attack. The primary factor starting the pathological state is the decrease in O2 supply, making the tissue energy balance negative, and preventing the tissue from performing its function. Figure 7 illustrates the effects of ischemia and anoxia on the NADH level in the brain of an anesthetized gerbil. The measurements of NADH in the cerebral hemispheres were correlated to the brain electrical activity (ECoG; electrocorticogram). To test and compare the measurements done in the two hemispheres, we exposed the gerbil to short-term anoxia. As shown, the two responses are very similar and correlate to the depression of the ECoG signal measured in the two hemispheres.
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After the introduction of the light guide-based fluorometry, we were able to expose the awake brain to hyperbaric conditions. A clear decrease in NADH (oxidation) was recorded during the shift from 21% to 100% O2, as well as during compression of up to 10 atmospheres 100% O2 (150,152, 153, 167, 177). A similar oxidation was found upon CO2 addition to the gas mixture (94–99% O2) (149). We also found a correlation between the elevated brain PO2 and the oxidation of NADH in awake rats (151). The oxidation of NADH was also recorded under normobaric hyperoxia (113). Furthermore, we tested the effects of hyperbaric oxygenation on carbon monoxide intoxication (212) or cyanide exposure (235).
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Responses to energy consumption changes
As shown by Chance and Williams (57, 58), the activation of the mitochondria by increased ADP is coupled with oxidation of NADH (decreased NADH levels) and is known as the state 4 to state 3 transition in isolated mitochondria. Most of the investigations in this field of tissue activation were made on neuronal tissue in vivo. However, studies of other organs, such as the heart or skeletal muscle, were conducted as well. The demand for energy (ATP) by various tissues is dependent on the specific tasks of each organ or tissue. Nevertheless, the stimulation of mitochondrial function is common in all tissues in the body. We will describe the effects of tissue activation on NADH fluorescence under normoxic conditions as well as during limitation of O2 supply in the tissue (hypoxia, ischemia).
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Responses to energy consumption changes
As shown by Chance and Williams (57, 58), the activation of the mitochondria by increased ADP is coupled with oxidation of NADH (decreased NADH levels) and is known as the state 4 to state 3 transition in isolated mitochondria. Most of the investigations in this field of tissue activation were made on neuronal tissue in vivo. However, studies of other organs, such as the heart or skeletal muscle, were conducted as well. The demand for energy (ATP) by various tissues is dependent on the specific tasks of each organ or tissue. Nevertheless, the stimulation of mitochondrial function is common in all tissues in the body. We will describe the effects of tissue activation on NADH fluorescence under normoxic conditions as well as during limitation of O2 supply in the tissue (hypoxia, ischemia).
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The effects of pharmacological agents on NADH redox state in various organs were published as well. Kedem et al. researched the influence of various inotropic agents (1) as well as nitroprusside (2), nitroglycerin (76), and propranolol (86).
Osbakken and collaborators (194, 195) also monitored NADH under various drug exposures. Baron et al. (17) described the effects of lidocaine on NADH, during ischemia in the dog heart. The effects of blood substitute emulsion on NADH in the kidney were reported (260). The influence of radioprotective chemicals on NADH in rat tissue was described in the 1960s (103). The action of various drugs (e.g., the uncoupler Amytal) was studied in the liver exposed to hyperbaric oxygenation (31, 40).
Monitoring Human Body Organs
The first attempt to apply NADH fluorometry to human tissues in vivo was made in 1971 by Jobsis et al. (111). Using NADH fluorescence microfluorometry, they monitored the exposed brain of neurosurgical patients undergoing treatments for focal cerebral seizures. They correlated the electrocorticographic data to the NADH redox state under direct cortical stimulation of the monitored area. The clear decrease in the NADH signal was interpreted as a change in oxidation. The recorded changes were very similar to those obtained in analogous procedures in the cat brain (213). A few years later, the collaboration between Austin and Chance (8) led to the recording of NADH in the brain of patients subjected to microanastomosis of the superficial temporal artery to the middle cerebral artery. The same group found an improvement of cerebral oxidative metabolism after the anastomosis, which was correlated to the elevated blood flow and increased tissue PO2 (9).
The next step was taken by Barlow et al. (16), who expanded this technique to monitor the heart and the brain. Using a different type of fluorometer, Van Buren et al. showed a decrease in NADH (oxidation) due to cortical stimulation in epileptic patients (251). In 1979, Fein and Jobsis (81) studied the changes in brain energetics in patients undergoing superficial temporal arterial-middle cerebral artery microanastomosis. Fein and Olinger (82, 83) monitored patients after transient ischemic attacks. The brain of these patients, who had undergone an extracranial-intracranial bypass, was stimulated, and changes in NADH were recorded.
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The laser-based fluorimeter developed by Renault (207) was used to monitor NADH redox state in the heart muscle during pharmacological treatments (207), as well as in skeletal muscle (91). Attempts to apply NADH fluorometry in clinical practice (reported in a dozen short publications) did not lead to the development of a proper medical device applicable on a daily basis.
In 1990, our team started developing a unique multiparametric monitoring system that included the measurement of NADH fluorescence, using a light guide-based device. This system was initially applied to monitor neurosurgical patients undergoing brain surgery or those treated in the intensive care unit. In the first paper on the subject (published in 1991), we showed the feasibility of our approach. After a transient short occlusion of one common carotid artery, the increase in NADH was correlated to a decrease in cerebral blood flow (164). It took another 5 years to restart organized clinical testing of our monitoring system.
Monitoring Nadh And The Multiparametric Approach
The need for multiparametric monitoring of other parameters, additional to NADH, results from the basic understanding that NADH is affected by two major factors. The redox state of NADH reflects not only the availability of O2 inside the mitochondria but also the turnover rate of the ATP-ADP cycling activity (state 4 to state 3 transition). The interaction between these two factors affects the nature of NADH response to various conditions. For example, an increase in energy consumption (e.g., cortical spreading depression) under O2 restriction will be manifested as an increase in NADH rather than a decrease (oxidation) measured in normal well-oxygenated tissue. According to Chance and Williams, an increase in ATP production is always recorded as a decrease in NADH (57, 58). Therefore, the “reduction cycle” measured by the NADH signal in response to CSD can be interpreted as an artifact of some kind. This phenomenon and the fact that the mitochondrial NADH signal cannot yet be calibrated in absolute values prompted us to develop a multiparametric monitoring approach and a probe that could be used in various tissues exposed to different pathophysiological conditions. By this approach, two major advantages were gained. First, it provided the possibility of a better interpretation of the recorded results; second, nonphysiological responses could also be more easily detected. To elaborate on these points, we will consider the following typical example. In the early stage of NADH monitoring using a time sharing fluorometer, we found that a few minutes after complete ischemia was induced by decapitation in a rat model, a large increase in the reflectance signal was recorded in parallel to a clear NADH decrease in the dead monitored brain, apparently indicative of NADH oxidation. We termed this event “the Secondary Reflectance Increase-SRI” (147). It was clear to us that this late “oxidation” of NADH in the dead animal was an artifact of the monitoring system. The same response was recorded also when partial ischemia was induced in a gerbil’s brain. The “oxidation” of NADH in a dead or partially ischemic brain did not have any physiological or biochemical interpretation, so we suspected that this “oxidation” is due to the large increase in the reflectance signal, and to a failure of the fluorescence signal’s correction method. We speculated that the large increase in the reflectance trace (SRI) after ischemia or brain death, resulted from a spasm of blood vessels. Such spasms are known to occur in this type of conditions, namely during cortex depolarization. Only when monitoring other parameters, in addition to NADH, such as extracellular K+ and DC steady potential, were we able to give a substantial explanation for the SRI event (85). On the basis of these experiments, we concluded that the SRI phenomenon is always associated with a negative shift in the DC potential and a large increase in extracellular potassium when energy is not available.
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NADH and electrical activity
The first attempt to combine NADH and electrical measurements was made by Chance and Schoener in 1962 (50). They showed the time relationship between the increase in NADH due to anoxia or hypoxia, and the disappearance of electrical activity (ECoG) in rat cerebral cortex. The same type of correlation was reported later by Jobsis et al. (110) for epileptic activity, and by Rosenthal and Somjen (163) and Mayevsky and Chance (157) for CSD. The accumulated results have made it clear that under limited energy or O2 supply, NADH becomes elevated in the brain, while the spontaneous ECoG activity is depressed. The ECoG begins to decelerate when NADH reaches 70%-80% of its maximal increase upon death (157, 159) or decapitation (160, 259). The recovery of ECoG after anoxia is completed much later than NADH oxidation, suggesting that energy availability is a prerequisite condition but not the only condition needed for a complete ECoG recovery. Depression of the ECoG is also recorded when the brain is exposed to depolarization due to CSD; however, it is not caused by a lack of O2. Similar correlations between NADH and ECoG were described in cat cerebral cortex exposed to seizures and hemorrhagic hypotension (100).
NADH and respiratory chain components
Since the activities of various respiratory chain components are strongly coupled, the tissue respiratory rate can be better evaluated by monitoring several such components. Very few attempts have been made to correlate NADH responses in vivo, with other components of the respiratory chain. The main reason for this was the stronger interference of blood with Fp or cytochrome oxidase measurements, compared with NADH. The effects of hypotension and anoxia on NADH and cytochrome aa3, were measured in the brain in vivo (99). LaManna et al. showed the effects of Ethanol on brain NADH and cytochrome aa3 in rats and cats (137). Therefore, almost all correlations between Fp and NADH were studied in blood-free organs (49). In 1976, we presented preliminary results indicating that in certain morphological areas of the brain, containing less blood vessels, a good correlation is recorded between NADH and Fp responses to anoxia in vivo (146). The only practical way to measure these two signals together was to freeze the tissue and then analyze the two parameters in the frozen state (168, 183). Another approach to correlating NADH and Fp redox state was suggested by Paddle et al. (198). They used a NADH/Fp scanning fluorometer to monitor the muscle (198) or rat diaphragm (197). A few papers have been published on the use of flying spot fluorometer to monitor the two fluorescent signals in the brain and other organs (35). Most of the data published in this field have been acquired in vitro (33, 49) or in blood-free organs such as the liver (218).
In this review, we tried to summarize the scientific background and technological aspects of in vivo NADH fluometry approach for the monitoring of mitochondrial functions. This technology still has some limitations including the need for better correction technique for hemodynamic artefacts as well as a new approach for quantitative calibration of the signals. During the past decade, the preliminary application of the NADH fluorometry to clinical environment was very promising. This stimulates us to improve the technology to provide a practical medical device that will be used by many clinicians after approval by the regulatory agencies around the world.
2.1.5.2 A microscale mathematical model for metabolic symbiosis: Investigating the effects of metabolic inhibition on ATP turnover in tumors
Cancer cells are notorious for their metabolic adaptations to hypoxic and acidic conditions, and especially for highly elevated glycolytic rates in tumor tissues. An end product of glycolysis is lactate, a molecule that cells can utilize instead of glucose to fuel respiration in the presence of oxygen. This could be beneficial to those cells that do not have sufficient oxygen as it conserves glucose for glycolysis. To better quantify this phenomenon we develop a diffusion-reaction mathematical model for nutrient concentrations in cancerous tissue surrounding a single cylindrical microvessel. We use our model to analyze the interdependence between cell populations’ metabolic behaviors on a microscopic scale, specifically the emerging paradigm of metabolic symbiosis that exists between aerobic and glycolytic cells. The ATP turnover rates are calculated as a function of distance from the blood vessel, which exhibit a lactate-consuming population at intermediate distances from the vessel. We also consider the ramifications of the Warburg effect where cells utilize aerobic glycolysis along with this lactate consuming respiration. We also investigate the effect of inhibiting metabolic pathways on cancer cells since insufficient ATP can trigger cell apoptosis. Effects that could be induced by metabolic inhibitors are analyzed by calculating the total ATP turnover in a unit tissue annulus in various parameter regimes that correspond to treatment conditions where specific metabolic pathways are knocked out. We conclude that therapies that target glycolysis, e.g. lactate dehydrogenase inhibitors or glycolytic enzyme inhibition, are the keys to successful metabolic repression.
The extensive metabolic requirements for cancer cell proliferation coupled with the harsh microenvironment in solid tumors culminate in a highly adaptive and complex network for cellular energy production. The genetically altered metabolic behavior of cancer cells has led to a number of emerging metabolic paradigms, in addition to those that are universally exhibited in both cancerous and normal cells. We will investigate this complex metabolic behavior by formulating a minimal mathematical model that includes the essential metabolites of glucose, lactate and oxygen in the tissue surrounding a microvessel. The cylindrical geometry used here has been used in a similar context to consider interactions between metabolites and tumor cells with treatment effects in a simplified setting (e.g. Bertuzzi et al., 2000, 2007a). The model presented here will enable the quantification of various behaviors, such as the symbiotic relationship that exists between lactate producing glycolytic cells and lactate-consuming respiratory cells, and the analysis of metabolic dependence on various physiological conditions such as hypoxia and induced metabolic inhibition. Metabolic inhibition including glycolytic inhibitors among many others targets could be very important for cancer treatment since an ATP deficit can induce apoptosis (Izyumov et al., 2004). The key consideration for addressing this problem with mathematics is the formulation of nutrient consumption rates that encompass the various primary facets of cancer cell metabolism and their corresponding ATP yields. In normal well-oxygenated tissues the primary source of ATP is the process of cellular respiration. The complete conversion of glucose to carbon dioxide and water has an ideal yield of about 29 ATP, although realistically the yield is substantially lower (Brand, 2005). The preliminary stage of cellular respiration is glycolysis, the conversion of glucose to pyruvate; this process directly produces 2 ATP. In hypoxic conditions this pyruvate is preferentially converted into lactate via the enzyme lactate dehydrogenase (LDH) to regenerate the essential cofactor NAD+. In oxygenated conditions this pyruvate is transported across the inner mitochondrial matrix where it is decarboxylated and enters the citric acid cycle; the citric acid cycle directly generates 2 more ATP per glucose. The primary energy payoff is a result of cofactor oxidization that enables the electron transport chain to establish a proton gradient across the inner mitochondrial matrix. ATP synthase utilizes this electrochemical gradient to drive the phosphorylation of approximately 25 additional ATP per glucose molecule.
The aforementioned universal traits that cancer cells and normal cells share include cellular responses to various levels of oxygen, lactate or glucose. Examples include a Crabtree-like effect and a Pasteur-like effect (Casciari et al., 1992a). The Crabtree-like effect is when oxygen consumption decreases as glucose concentration increases. This can be explained by an increasing reliance on glycolysis for ATP when hyperglycemic conditions are encountered. The Pasteur-like effect is decreased glucose consumption as oxygen increases. This is due primarily to the inhibition of various metabolic steps by the presence of elevated ATP and other intermediaries. However, cancer cells are unique in that they preferentially utilize glycolysis, even in the presence of oxygen, coined aerobic glycolysis. This phenomenon is generally referred to as the Warburg effect whereby cells rely primarily on glycolysis even in the presence of sufficient oxygen to perform respiration (Warburg, 1956). There is a perceived inefficiency of this metabolic strategy, namely the dramatically reduced ATP yield, just 2 per glucose instead of 29, however, it has the benefits of faster ATP production and it is likely that much of this glucose is being consumed for proliferative (Vander Heiden et al., 2009) (e.g. by the pentose phosphate pathway) purposes. In addition to the typical glycolytic phenotype exhibited in many cancers, there is also a developing story of a co-operative relationship existing between aerobic and anaerobic cancer cells. The lactate necessarily produced by glycolytic cells is being pushed back into the respiratory cycle by being converted into pyruvate (summarized in Feron, 2009; Nakajima and Van Houten, 2012); this spatial relationship is shown in Fig. 1. Lactate consumption has been observed in vitro in various models (Bouzier et al.,1998; Katz et al., 1974) as well as in vivo as early as the early 1980s (Sauer et al., 1982). However, a renewed interest in the topic was piqued when Sonveaux et al. (2008) showed that reducing lactate uptake by cancer cells led to hypoxic cell death, a particularly difficult subpopulation to target using traditional methods.
Metabolic phenomena have been studied in great detail by mathematical models, but models of tumor metabolism rarely include the interaction of the transport mechanisms of microvessels with the localized metabolic behavior of cells (with one recent exception McGillen et al., 2013). In the section to follow, we will develop a mathematical model that describes the concentrations of molecules that are important to cellular metabolism in the tissue around a single three-dimensional vessel that exhibits diffusion dominated interstitial transport. We will then use this model to demonstrate how the properties of the tumor cell population, such as glucose, lactate and oxygen consumption rates, affect tumor hypoxia and ATP production around a single vessel. The effects of metabolic inhibitors will be investigated by parameter changes that could be elicited by the application of glycolysis inhibitors, lactate dehydrogenase (LDH) inhibitors or respiratory inhibitors. We are interested in those metabolic inhibitors that could cripple the cells’ ability to produce ATP.
Fig.1. The spatial relationship between the cell populations in the model indicating dominant metabolism as we move away from the vessel. When the glucose and oxygen concentrations are highest near the vessel wall, the cells preferentially utilize glucose-fuelled respiration. When the oxygen supply is depleted far from the vessel, the cells rely on glycolysis. The glycolytic cells produce large quantities of lactate which are consumed by cells at intermediary distances and hypoxic oxygen concentrations. These cells are participating in a behavior that we will refer to as metabolic symbiosis.
A model to describe the concentrations of the major players in the metabolic pathways of respiration and glycolysis, will be outlined here. Its origins lie in a metabolic model developed by Casciari et al. (1992b) that was subsequently applied on the microscale by Molavian et al. (2009). The functional forms for the production rates are similar to those proposed by MendozaJuez et al. (2012) and subsequently extended to a spatial model by McGillen et al. (2013). In hypoxic and anoxic conditions, cells must partially or exclusively rely on metabolic pathways, such as glycolysis, that do not require oxygen for ATP production. In glycolysis, the preliminary stage of respiration, a single glucose molecule (C6H12O6) yields 2 ATP, which we will denote under the reaction arrow with a boxed ATP yield number, with the byproducts of lactate and a proton. Denoting glucose by G and lactate by L– C3H5O3–, the net reaction is G kG> 2L– + 2H+; [2]
where kG (mM/s) is the rate of glucose consumption by glycolysis that results in lactate formation. The accumulation of these hydrogen ions in a solid tumor is a primary contributor to tumor acidosis. In the presence of oxygen (O2), glycolysis is typically followed by the rest of the respiratory process with an ideal energy yield of approximately 29 ATP molecules with carbon dioxide (CO2) and water (H2O) as the only byproducts. The simplified summary reaction is given by G kO à 6O2 6CO2 + 6H2O; [29]
where kO is the rate of glucose consumption that results in cellular respiration. To represent the metabolic symbiosis between cells primarily producing energy via glycolysis and those consuming lactate in well-oxygenated areas, we will link the above two reactions with the lactate-consuming net reaction: L– + H+ + 3O2kLà 3CO2 + 3H2O; [13.5]
where kL is the rate of lactate consumption. This summarizes the re-entry of lactate, via conversion to pyruvate, into aerobic respiration that yields 13.5 ATP per lactate molecule. The relationships between the summary reactions included in the model are given in Fig. 2.
Fig. 2. The summary reactions included in the metabolism model. Glycolysis proceeds at rate kG and produces 2 ATP from the conversion of glucose to pyruvate. Glucose-fuelled respiration occurs at rate kO in the presence of oxygen, while lactate-fuelled respiration occurs at rate kL (2 kL is present in the diagram to remain consistent with the glycolytic yield of 2 lactate molecules).
Fig. 3. Solution to base case boundary value problem. Nondimensional oxygen o and glucose g concentrations decrease due to metabolic consumption. Lactate ℓ increases to almost double its vessel concentration since it is produced by glycolysis at a higher rate than it is consumed by respiration due to a limiting oxygen concentration. This image has been spatially truncated to 300 μm since the concentrations are approximately constant after this point.
Fig. 4. Consumption rates of oxygen, lactate and glucose (QO, QL and QG for the concentrations given in Fig. 3). The glucose and oxygen consumption rates are strictly positive while the consumption rate of lactate is predominantly negative. This indicates that even in regions where lactate is being consumed, it is being produced at a higher rate by glycolysis.
Fig. 5. The base case for ATP turnover (consumption/production) rates corresponding to consumption rates given in Fig. 4. The contributions of the pathways are bounded by the total ATP turnover rate PATP . Glycolysis dominates in hypoxic/ anoxic regions while glucose-fuelled respiration occurs sparingly near the blood vessel. Lactate-fuelled cells are consuming the byproduct of the glycolytic cells where there is oxygen present.
Warburg effect
In the base case considered above glycolysis is inhibited until the oxygen consumption drops to values that prevent the production of sufficient ATP to maintain cell survival. However, cancer cells will commonly utilize glycolysis as a primary energy source even when there is enough oxygen to ensure cell survival. In the model we characterize the cell’s ability to hold off on utilizing glycolysis in oxygenated areas by the parameter ΛO. Reducing it 400-fold from the base case above (from 4000 to 100) results in spatial ATP turnover rate as given in Fig. 6. Cells near the vessel greedily consume the available resources leaving cells further from the vessel to die from insufficient ATP supply. The ATP production breakdown corresponds to the second bar in Fig. 8 and is slightly higher than the whole tissue considered in the base case above.
Fig. 6. ATP turnover (consumption/production) rates for cells exhibiting the Warburg effect (differs from base case because ΛO = 100 instead of 4000). The contributions of the pathways are bounded by the total ATP turnover rate PATP. Glycolysis is dominant in all regions of the tumor, however, glucose and lactate fueled respiration occur sparingly near the blood vessel where there is oxygen present.
Fig. 7. The optimal metabolic behavior on the microscale given an ATP turnover maximum of X mM=s. This shows glucose-fuelled respiration near the vessel, glycolysis far from the vessel and a lactate-consuming population in between these two
Instead of fixing all of the parameters to the values given in Table 1, we could leave some of the parameters free and optimize the amount of ATP generated from the given metabolites by imposing a maximum constraint on ATP production. For instance, setting all of the parameters initially to those given in Table 1, and then minimizing some function of Z¼PATP θ where θ is the maximum allowed ATP turnover rate would theoretically ensure that the available resources were not being selfishly consumed by oxidative cells near the vessel. Allowing cells to alter their glycolytic parameters: βg, δ and κg along with their lactate–glucose switch parameter λ yields the results shown in Fig. 7. While there was still enough constraint that the system still exhibited a non-constant ATP turnover where it could, this reinforces the suggested optimal strategy of glucose-fuelled respiration near the vessel, glycolysis far from the vessel and a lactate-consuming population in between these two. This optimization procedure most notably resulted in a reduced δ enabling the switch to glycolysis to happen closer to the vessel and a lower κg enabling a later and more drastic shut off of glycolysis; the parameter results of this simulation are presented in Table C1.
The mathematical model presented here can give insight into the effects of blocking various metabolic pathways. The three metabolic pathways that we have considered, namely (i) glucosefuelled respiration, (ii) lactate-fuelled respiration and (iii) glycolysis, could be inhibited by various agents, and the effects on local ATP production will be outlined below. For illustrative purposes we will consider complete inhibition of these pathways, but this will be followed by consideration of the more realistic scenario where these pathways are only partially inhibited. Entirely knocking out lactate metabolism could be achieved by inhibiting lactate dehydrogenase (LDH) which is responsible for the reentry of lactate into respiratory pathways by converting lactate into pyruvate. Successful inhibition would concurrently prevent the conversion of pyruvate to lactate as well, a crucial step for regenerating NAD+ in glycolytic cells. This has been shown to reduce ATP levels and consequently induce cell death in tumors (Le et al., 2010). The complete inhibition of lactate dehydrogenase would eliminate two of the three pathways considered here: lactate-fuelled respiration and glycolysis. Complete inhibition can be reflected in the model by setting BL¼0 and BG¼0, leaving only glucose-fuelled respiration to produce ATP, a physiologically normal condition. However, the hypoxic and hypoglycaemic conditions considered here do not leave enough fuel for cell survival. This scenario corresponds to the third bar in Fig. 8. We could also target glucose transport into the cell, an intermediary of glycolysis or one of the critical enzymes responsible for converting glucose to pyruvate. This is distinct from the strategy noted above of inhibiting LDH which prevents the conversion of lactate to pyruvate and vice versa. This has also been noted as a prime target for cancer therapy (Pelicano et al., 2006; Gatenby and Gillies, 2007) and there are currently many potential targets (Granchi and Minutolo, 2012). Here we will consider the shutdown of glycolysis as preventing both glucose-fuelled respiration and glycolysis since both of these require glucose to be converted into pyruvate. However, it leaves the lactate-fuelled respiratory pathway intact. This could be considered in the model by taking BO¼0 and BG¼0.Similar tothe caseof LDH inhibition this leads to a significant decrease in ATP production as shown in the fourth bar of Fig. 8. The final scenario that we consider corresponds to full inhibition of respiration somewhere along the chain between pyruvate transport into the mitochondria and the electron transport chain. There are numerous potential targets in the mitochondria (Costantini et al., 2000) and we will consider the complete shutdown of respiration by setting BL¼0 and BO¼0. This would result in negligible oxygen consumption and with our base case of ΛO 100-4000 this would lead to repressed glycolysis in the tissue.
Fig. 9. The effects of metabolic repression on total ATP production in a unit annulus of tumor tissue ðΦÞ. Cell metabolism is fully functioning when the relative rate is 1, while the cell metabolism is fully inhibited when the relative rateis 0. Intermediary values correspond to partial inhibition of both affected metabolic rates, e.g. for LDH half-inhibition: BG and BL are half the base case value, and BO remains at its base case value. The legend abbreviations are the same as those used in bars 3–6 in Fig. 8: LDH inhibition (LDH), glycolytic inhibition (Glyc), respiratory inhibition (Resp), and respiratory inhibition with Warburg effect (R-W). The total ATP production begins to significantly decrease for LDH and glycolytic inhibition only once more than half inhibition is reached. For respiratory inhibition, significant decreases are not detected until metabolic rates drop to one-tenth of the base case value.
The functional form for glycolysis given in (8) is similar to that used in McGillen et al. (2013), except where our form uses oxygen as the inhibitory molecule, they use lactate. McGillen et al. (2013) do not include glucose-fuelled respiration at all (as it was deemed to occur at negligible rates), and they use a similar lactate-fuelled respiratory term as used here, that was originally formulated by Mendoza-Juez et al. (2012). Instead of including a Michaelis– Menten oxygen dependence, they introduce a switch parameter that turns oxygen-fuelled metabolism on and off at a threshold oxygen concentration. However, they did enable the cells to use combinations of respiration and glycolysis as opposed to the strict switching between these two pathways modelled by Mendoza Juez et al. (2012). The novel aspects of our model include the introduction of a glycolytic inhibition parameter that can prevent or enable the Warburg effect, an explicit and smoothly defined oxygen dependence for the respiratory pathways, and the inclusion of an accurate ATP yield formula. While our results focus on the energetic consequences of metabolic inhibition, McGillen et al. (2013) focus on the interaction between metabolite consumption and tumor growth.
Conclusions
The mathematical model formulated and analyzed above can give insight into the metabolic behaviors of cancer cells on the microscale. The tumor microenvironment characterized by hypoxia and nutrient deprivation leads to the utilization of highly unregulated glycolytic pathways and the consumption by respiring cells of the lactate produced by these cells. These metabolic scenarios are encompassed by the functional forms proposed for glucose, lactate and oxygen consumption. To consider the effect of altering parameters in the model to the efficiency of energy production we must also consider the rate of ATP turnover in the tissue. To this end a detailed biochemical summary was performed in order to calculate estimates for ATP yields. These energetic landscapes were considered in tissues that utilize anaerobic glycolysis, thus keeping more cells alive, and those that experience the Warburg effect, performing glycolysis in oxygenated areas. The analysis shows that the latter does confer a proliferative advantage by producing more ATP. The effects of metabolic inhibition were taken into account by knocking out the pathways considered in our model. Glycolytic inhibition blocked glycolysis and glucose-fuelled respiration, LDH inhibition blocked glycolysis and lactate-fuelled respiration while respiration inhibition blocked both forms of respiration. Both strategies that block glycolysis lead to appreciable decreases in total ATP production, while those that block respiration are only effective in the base case where the cells are unable to elevate glycolytic rates due to the repressive effect of oxygen in the model. However, when considering a more realistic scenario where cells can adapt to blocked respiratory pathways by upregulating glycolysis via the Warburg effect, we observe that this treatment strategy allows sufficient ATP for cell survival. The work presented here should lead to a reconsideration of the importance of the spatial relationships between cells performing under specific metabolic regimes and provides a minimally parameterized and straightforward basis for future phenomenological metabolite consumption models.
2.1.5.3 Localization and Kinetics of Reduced Pyridine Nucleotide in Living Cells by Microfluorometry J. Biol. Chem.-1959-Chance-3044-50
Britton Chance and Bo Thorell
J Biological Chemistry Nov 1959; 234(11)
On the basis of early studies of the blue fluorescence of living cells and tissues before chemical treatment, l Sjiistrand (1) suggested its association with the mitochondrial bodies. Microspectroscopic observations of prepared tissue sections revealed emission bands of the fluorescent material of axons (1) and acid treated groups of kidney cells; (2) critical evaluations of available spectrograms of purified materials lead to the identification of thiamin and riboflavin, respectively. Although some of the of the kidney sections, before acid treatment, showed fluorescence bands in the spectrograms that are now regarded as suggestive of reduced pyridine nucleotide, the fluorescence of which was first observed by Warburg (2), insufficient data were available at that time to consider reduced pyridine nucleotide as a possible cause of the tissue fluorescence. Recent studies by Boyer and Theorell (3) and Duysens and Kronenberg (4) on alcohol dehydrogenase show clearly the great enhancement of DPNH fluorescence that is caused by a binding of the coenzyme to the enzyme surface. Furthermore, Duysens and Amesz (5) demonstrate that the intact yeast cell shows a fluorescence characteristic of bound reduced pyridine nucleotide. In more recent experiments, it has been found that intramitochondrial reduced pyridine nucleotide also exhibits the same characteristic fluorescence, calling attention to the possibility of a close relationship between this effect and the blue fluorescence of living cells and tissues (6). The fluorometric result agrees with the spectrophotometrically determined large RPN3 content of mitochondria (7). Furthermore, its binding to a mitochondrial component has been suggested by kinetic studies (7). More recent data show that the fluorescence of intact muscle diminishes upon electrically induced contraction, in agreement with the spectrophotometrically observed oxidation of RPN (8). Thus, there is good evidence that a considerable amount of tissue fluorescence is due to this component. To study the fluorescence of mitochondrial RPN independently of that of the cytoplasm, it has been desirable to develop a microfluorometric method, which, in conjunction with suitable biological materials showing isolation of the mitochondrial bodies, could be used to investigate cytoplasmic-mitochondrial interactions and also to permit the assay of RPN localized in different
1 The term “autofluorescence” is used by Sjostrand and other workers to indicate the fluorescence of a tissue before its treatment with stains, acids, and so forth.
2 F. S. Sjiistrand, unpublished experiments.
* The abbreviation used is: RPN, reduced pyridine nucleotide.
This paper describes such an instrument and its application to the observation of mitochondrial RPN, particularly in highly localized mitochondrial bodies such as the nebenkern4 of the grasshopper spermatid (11). It is now possible to investigate in viva the independent changes of mitochondrial and cytoplasmic pyridine nucleotide in the aerobic-anaerobic transition. In other cells, where mitochondrial localization is not sufficient for independent characterization of cytoplasmic and mitochondrial components of the fluorescence, assays of the oxidation-reduction state of the total pyridine nucleotide in individual cells in different states of metabolism and growth are possible. The combination of this differential fluorometer with the spectrophotometer described elsewhere (12, 13) for the localization of activities of respiratory and glycolytic enzymes in cells affords a new approach to the dynamic aspects of metabolic reactions.
The closure of the switch contacts and the wave form of the photocurrent and light intensity for an AC-operated light source (see below) are indicated in Fig. 1. The fluctuations of the light intensity (~100 per cent modulation) indicated on the top line cause synchronous variations which result in an asymmetrical wave form for the photocurrent, provided the fluorescent object coincides with the extremes of the excursions of the vibrating diaphragm. To measure the fluorescence intensity of the object (M) and that of a nearby “free space” (R), the switch circuit is adjusted so that it closes for a brief interval at the peaks of the photocurrent wave form (Fig. 1). The portions of the photocurrent selected by this switch are used to charge a condenser so that its potential represents the difference of the photocurrents at the two times. This potential is amplified by a “Millivac,” type 17C, and by an Esterline-Angus l-ma. recorder.
FIQ. 1. Wave forms of light intensity and photocurrent relative to the times of switch closure (alternating current operated by lamp). The vibrating diaphragm operates synchronously with the fluctuations in light intensity so that the extremes of its vibration correspond to maxima of light intensity
Fig. 2. Relative fluorescence maxima for suspensions of diploid bakers’ yeast, pentaploid yeast, and ascites tumor cells. These fluorescence emission spectra are obtained with excitation of the cell suspensions by the 366-rnr mercury line passed through the same filter used in the microfluorometer. The energy obtained through the Wratten 2A filter is analyzed by means of a grating monochromator and is plotted as a function of wave length. Significant features of the record are that no measurable energy at 366, 436, or 546 mp is received by the photocell. The cell suspensions are relatively concentrated (60 mg. per cc. for the yeast cell suspensions). The close correspondence of the amplitudes of the peaks is a consequence of adjusting the photocell dynode voltage appropriately (928).
Studies of mitochondria treated with ADP to cause the disappearance of RPN fluorescence show that a relatively small contribution of the flavoprotein of the respiratory chain remains and that flavoprotein fluorescence does not measurably change with its oxidation-reduction state. Thus, it is felt justified in these preliminary studies to attribute the major portion of the fluorescence observed to RPN. Evidence in favor of this view is indicated below, where chemical transitions affecting the oxidation-reduction state and hence the fluorescence of reduced pyridine nucleotide show that most of the fluorescence localized in the mitochondria is affected by this transition and hence is not a “fixed” background fluorescence.
Relative Intensities of Signals-A survey of various biological materials has been made to determine the relative intensities of the signals obtained and to demonstrate the feasibility of studies of their fluorescence. This study is largely incomplete, but the preliminary results summarized in Table I are rather encouraging. These fluorescence intensities range from a small value for the aerobic nebenkern of the grasshopper spermatid to a large value for the anaerobic pentaploid yeast cell. The larger currents give a signal-to-noise ratio of such magnitude that delicate indications are given, not only of the magnitude of the fluorescence, but also of changes that may occur in different metabolic states or in different parts of the cells. At higher currents, accuracies > 100 : 1 are possible. Localization of Fluorescence-The inadequate resolution of the optical microscope and the uniform distribution of the mitochondria throughout the cytoplasm of such cells as bakers’ or pentaploid yeast or ascites tumor cells offer little possibility for localizing the mitochondrial fluorescence as opposed to the cytoplasmic fluorescence.
Table I Summary of fluorescence intensities for various cell types and metabolic states
FIG. 7. Time course of the fluorescence changes of the nebenkern and of the cytoplasm in the aerobic-anaerobic transition. A, the ratio of nebenkern to cytoplasmic fluorescence, plotted as determined by records similar to those of Fig. 6. The numbers in the diagram refer to the cell studied. The abrupt upward discontinuity of the record at approximately 45 minutes occurs when anaerobiosis is expected. B, the individual measurements of the cytoplasmic (0-O) and nebenkern (0-C) fluorescence. The number of the cell used for measurement is also indicated along the scale of the abscissa (922a, b).
A fluorescence with spectral characteristics that are similar to those of reduced pyridine nucleotide of isolated mitochondria has been demonstrated to be localized in three cell configurations which cytologically show mitochondrial aggregation. The oxidation and reduction of mitochondrial pyridine nucleotide without a measurable change of cytoplasmic fluorescence suggest that compartmentalization of mitochondrial and cytoplasmic pyridine nucleotide occurs in viva, at least in the grasshopper spermatid. Studies of other material, particularly pentaploid yeast cells and ascites tumor cells, indicate that similar changes of fluorescence of the single cell are observed in the aerobic-anaerobic transition. In such cells, optical resolution does not permit localization of mitochondrial bodies. Nevertheless, the state of pyridine nucleotide in the individual cell can be investigated.
Discussion:
Radoslav S. Bozov (@Radobozov)
Your interpretations approximates wrong conclusions: 1. Oxygen is processed via mitochondrial Cu2+/3+ metalloproteins , H2O2 (King’s water) electro-negativity processing). 2. Lactate formation is an effect of cancerogenesis, a Lewis base., you lack fundamental understanding pKa issues in science and more accurately in moderns science. Such thing as protons have never been observed directly, that is a concept for explaining pH. All organic acids in bio systems are deprotonated carboxyl functional groups entering resonance state , which allows interpretation of spectra: There i s no way in real chemical science to have measured pH of a compartment and especially nano space! The physiological charge is -1: http://www.hmdb.ca/metabolites/HMDB00190
Biophysical concepts might be applied in a wrong direction! which is the case of perceiving NADH/Pyruavte/Lactate triangle , you lack conceptual frames of systems applicability in expanded biological space/energies – proteins, nucleotides, and meta states! Pyridines have nothing to do with energy states, pyridines are nitrogen capacitors , they have nothing to do with origin and implications of mutation/evolution, regulation! You lack fundamental understanding of physical implications today!
Lactate is a compensatory mechanism of the genome for copying with disregulated supply of pyruvate for synthesizing negative methyl groups, energy processed in biospaces via compression/decompressing bio systems! Remember, quantum chemistry and implications of quantum physics is not one and the same! General Relativity is applied only towards statistical cloud delocalization, that implicates induction vs deductive reasoning! Classic mechanics of optics is a neat way to do math, nothing more than that of accepting reality of none observable parameters! Lactic acid was considered an end product of metabolism and physiological fatigue for a long time! Now, we know that is not true! To contrary lactic acid is used to have healthy pluripotecy differentiation of bone marrow derived cell lines. LDH proteins demonstrate high similarity motif selection with a range of transcriprion factors via blast studies. In general DATA IS MESSED UP and likely WRONGLY INTERPRETED!
Larry H Bernstein,
I am quite sure that what I presented is the best that science has produced. Whether there is a theoretical issue in physical interpretation is another matter. Two key papers are by Mayekovsky and by Britton Chance. Britton Chance only died recently at nearly 100, but he was a giant in biochemistry, and my final exam question in freshman biochemistry was – should B Chance get the Nobel Prize. His conception was then controversial, and the ETC won out. Nevertheless, his contributions went far beyond the explanation for the H+ transfer role in ETC. When I was a resident in pathology, my mentor (who identified the difference between myokinase and liver AK) commented that the only reason that Chance had not been awarded was because his work was so technologically focused. I had studied the malate dehydrogenase reaction in Nate Kaplan’s lab, and I carried out stop-flow studies of the inhibition of the mitochondrial isoenzyme by oxaloacetate. When I went to Washington, DC at the end of the Vietnam War and the time of Watergate, I had the good fortune to be introduced to Chance in a visit to Philadelphia. I think that I do understand acidemia, cationic and anionic balance, which is not a simple matter – after some 35 years in pathology, with a main focus on clinical pathology. If you could step back and give a point by point elucidation of where the experimental interpretation is in error, and a point by point highlight of your explanation, it would be very helpful. I know that I am quite knowledgable about the mechanism of reactions of the pyridine nucleotide linked dehydrogenases, and the isoenzymes, and the abortive ternary complexes. I also published in the Brit J Cancer in the 1970’s on an abnormality in the cytoplasmic MDH in fast growing murine hepatomas, and in human cancer. I spent many months purifying the heart mitochondrial MDH to purity, and established that there was no histidine residue at the active site.
Oxidation of fatty acids and amino acids is increased upon MPC inhibition
•Respiration, proliferation, and biosynthesis are maintained when MPC is inhibited
•Glutaminolytic flux supports lipogenesis in the absence of MPC
•MPC inhibition is distinct from hypoxia or complex I inhibition
Summary
Pyruvate lies at a central biochemical node connecting carbohydrate, amino acid, and fatty acid metabolism, and the regulation of pyruvate flux into mitochondria represents a critical step in intermediary metabolism impacting numerous diseases. To characterize changes in mitochondrial substrate utilization in the context of compromised mitochondrial pyruvate transport, we applied 13C metabolic flux analysis (MFA) to cells after transcriptional or pharmacological inhibition of the mitochondrial pyruvate carrier (MPC). Despite profound suppression of both glucose and pyruvate oxidation, cell growth, oxygen consumption, and tricarboxylic acid (TCA) metabolism were surprisingly maintained. Oxidative TCA flux was achieved through enhanced reliance on glutaminolysis through malic enzyme and pyruvate dehydrogenase (PDH) as well as fatty acid and branched-chain amino acid oxidation. Thus, in contrast to inhibition of complex I or PDH, suppression of pyruvate transport induces a form of metabolic flexibility associated with the use of lipids and amino acids as catabolic and anabolic fuels.
oxidation-of-fatty-acids-and-amino-acids
Graphical Abstract – Oxidation of fatty acids and amino acids is increased upon MPC inhibition
Figure 2. MPC Regulates Mitochondrial Substrate Utilization (A) Citrate mass isotopomer distribution (MID) resulting from culture with [U-13C6]glucose (UGlc). (B) Percentage of 13C-labeled metabolites from UGlc. (C) Percentage of fully labeled lactate, pyruvate, and alanine from UGlc. (D) Serine MID resulting from culture with UGlc. (E) Percentage of fully labeled metabolites derived from [U-13C5]glutamine (UGln). (F) Schematic of UGln labeling of carbon atoms in TCA cycle intermediates arising via glutaminoloysis and reductive carboxylation. Mitochondrion schematic inspired by Lewis et al. (2014). (G and H) Citrate (G) and alanine (H) MIDs resulting from culture with UGln. (I) Maximal oxygen consumption rates with or without 3 mM BPTES in medium supplemented with 1 mM pyruvate. (J) Percentage of newly synthesized palmitate as determined by ISA. (K) Contribution of UGln and UGlc to lipogenic AcCoA as determined by ISA. (L) Contribution of glutamine to lipogenic AcCoA via glutaminolysis (ISA using a [3-13C] glutamine [3Gln]) and reductive carboxylation (ISA using a [5-13C]glutamine [5Gln]) under normoxia and hypoxia. (M) Citrate MID resulting from culture with 3Gln. (N) Contribution of UGln and exogenous [3-13C] pyruvate (3Pyr) to lipogenic AcCoA. 2KD+Pyr refers to Mpc2KD cells cultured with 10 mM extracellular pyruvate. Error bars represent SD (A–E, G, H, and M), SEM(I), or 95% confidence intervals(J–L, and N).*p<0.05,**p<0.01,and ***p<0.001 by ANOVA with Dunnett’s post hoc test (A–E and G–I) or * indicates significance by non-overlapping 95% confidence intervals (J–L and N).
Figure 3. Mpc Knockdown Increases Fatty Acid Oxidation. (A) Schematic of changes in flux through metabolic pathways in Mpc2KD relative to control cells. (B) Citrate MID resulting from culture with [U-13C16] palmitate conjugated to BSA (UPalm). (C) Percentage of 13C enrichment resulting from culture with UPalm. (D) ATP-linked and maximal oxygen consumption rate, with or without 20m Metomoxir, with or without 3 mM BPTES. Culture medium supplemented with 0.5 mM carnitine. Error bars represent SD (B and C) or SEM (D). *p < 0.05, **p < 0.01, and ***p < 0.001 by two-tailed, equal variance, Student’s t test(B–D), or by ANOVA with Dunnett’s post hoc test (D).
Figure 4. Metabolic Reprogramming Resulting from Pharmacological Mpc Inhibition Is Distinct from Hypoxia or Complex I Inhibition
2.1.3.2 Oxidation of Alpha-Ketoglutarate Is Required for Reductive Carboxylation in Cancer Cells with Mitochondrial Defects
Cells with mitochondrial defects use bidirectional metabolism of the TCA cycle
•Glutamine supplies the succinate pool through oxidative and reductive metabolism
•Oxidative TCA cycle metabolism is required for reductive citrate formation
•Oxidative metabolism produces reducing equivalents for reductive carboxylation
Summary
Mammalian cells generate citrate by decarboxylating pyruvate in the mitochondria to supply the tricarboxylic acid (TCA) cycle. In contrast, hypoxia and other impairments of mitochondrial function induce an alternative pathway that produces citrate by reductively carboxylating α-ketoglutarate (AKG) via NADPH-dependent isocitrate dehydrogenase (IDH). It is unknown how cells generate reducing equivalents necessary to supply reductive carboxylation in the setting of mitochondrial impairment. Here, we identified shared metabolic features in cells using reductive carboxylation. Paradoxically, reductive carboxylation was accompanied by concomitant AKG oxidation in the TCA cycle. Inhibiting AKG oxidation decreased reducing equivalent availability and suppressed reductive carboxylation. Interrupting transfer of reducing equivalents from NADH to NADPH by nicotinamide nucleotide transhydrogenase increased NADH abundance and decreased NADPH abundance while suppressing reductive carboxylation. The data demonstrate that reductive carboxylation requires bidirectional AKG metabolism along oxidative and reductive pathways, with the oxidative pathway producing reducing equivalents used to operate IDH in reverse.
Proliferating cells support their growth by converting abundant extracellular nutrients like glucose and glutamine into precursors for macromolecular biosynthesis. A continuous supply of metabolic intermediates from the tricarboxylic acid (TCA) cycle is essential for cell growth, because many of these intermediates feed biosynthetic pathways to produce lipids, proteins and nucleic acids (Deberardinis et al., 2008). This underscores the dual roles of the TCA cycle for cell growth: it generates reducing equivalents for oxidative phosphorylation by the electron transport chain (ETC), while also serving as a hub for precursor production. During rapid growth, the TCA cycle is characterized by large influxes of carbon at positions other than acetyl-CoA, enabling the cycle to remain full even as intermediates are withdrawn for biosynthesis. Cultured cancer cells usually display persistence of TCA cycle activity despite robust aerobic glycolysis, and often require mitochondrial catabolism of glutamine to the TCA cycle intermediate AKG to maintain rapid rates of proliferation (Icard et al., 2012, Hiller and Metallo, 2013).
Some cancer cells contain severe, fixed defects in oxidative metabolism caused by mutations in the TCA cycle or the ETC. These include mutations in fumarate hydratase (FH) in renal cell carcinoma and components of the succinate dehydrogenase (SDH) complex in pheochromocytoma, paraganglioma, and gastrointestinal stromal tumors (Tomlinson et al., 2002, Astuti et al., 2001, Baysal et al., 2000, Killian et al., 2013, Niemann and Muller, 2000). All of these mutations alter oxidative metabolism of glutamine in the TCA cycle. Recently, analysis of cells containing mutations in FH, ETC Complexes I or III, or exposed to the ETC inhibitors metformin and rotenone or the ATP synthase inhibitor oligomycin revealed that turnover of TCA cycle intermediates was maintained in all cases (Mullen et al., 2012). However, the cycle operated in an unusual fashion characterized by conversion of glutamine-derived AKG to isocitrate through a reductive carboxylation reaction catalyzed by NADP+/NADPH-dependent isoforms of isocitrate dehydrogenase (IDH). As a result, a large fraction of the citrate pool carried five glutamine-derived carbons. Citrate could be cleaved to produce acetyl-CoA to supply fatty acid biosynthesis, and oxaloacetate (OAA) to supply pools of other TCA cycle intermediates. Thus, reductive carboxylation enables biosynthesis by enabling cells with impaired mitochondrial metabolism to maintain pools of biosynthetic precursors that would normally be supplied by oxidative metabolism. Reductive carboxylation is also induced by hypoxia and by pseudo-hypoxic states caused by mutations in the von Hippel-Lindau (VHL) tumor suppressor gene (Metallo et al., 2012, Wise et al., 2011).
Interest in reductive carboxylation stems in part from the possibility that inhibiting the pathway might induce selective growth suppression in tumor cells subjected to hypoxia or containing mutations that prevent them from engaging in maximal oxidative metabolism. Hence, several recent studies have sought to understand the mechanisms by which this pathway operates. In vitro studies of IDH1 indicate that a high ratio of NADPH/NADP+ and low citrate concentration activate the reductive carboxylation reaction (Leonardi et al., 2012). This is supported by data demonstrating that reductive carboxylation in VHL-deficient renal carcinoma cells is associated with a low concentration of citrate and a reduced ratio of citrate:AKG, suggesting that mass action can be a driving force to determine IDH directionality (Gameiro et al., 2013b). Moreover, interrupting the supply of mitochondrial NADPH by silencing the nicotinamide nucleotide transhydrogenase (NNT) suppresses reductive carboxylation (Gameiro et al., 2013a). This mitochondrial transmembrane protein catalyzes the transfer of a hydride ion from NADH to NADP+ to generate NAD+ and NADPH. Together, these observations suggest that reductive carboxylation is modulated in part through the mitochondrial redox state and the balance of substrate/products.
Here we used metabolomics and stable isotope tracing to better understand overall metabolic states associated with reductive carboxylation in cells with defective mitochondrial metabolism, and to identify sources of mitochondrial reducing equivalents necessary to induce the reaction. We identified high levels of succinate in some cells using reductive carboxylation, and determined that most of this succinate was formed through persistent oxidative metabolism of AKG. Silencing this oxidative flux by depleting the mitochondrial enzyme AKG dehydrogenase substantially altered the cellular redox state and suppressed reductive carboxylation. The data demonstrate that bidirectional/branched AKG metabolism occurs during reductive carboxylation in cells with mitochondrial defects, with oxidative metabolism producing reducing equivalents to supply reductive metabolism.
Shared metabolomic features among cell lines with cytb or FH mutations
To identify conserved metabolic features associated with reductive carboxylation in cells harboring defective mitochondrial metabolism, we analyzed metabolite abundance in isogenic pairs of cell lines in which one member displayed substantial reductive carboxylation and the other did not. We used a pair of previously described cybrids derived from 143B osteosarcoma cells, in which one cell line contained wild-type mitochondrial DNA (143Bwt) and the other contained a mutation in the cytb gene (143Bcytb), severely reducing complex III function (Rana et al., 2000, Weinberg et al., 2010). The 143Bwt cells primarily use oxidative metabolism to supply the citrate pool while the 143Bcytb cells use reductive carboxylation (Mullen et al., 2012). The other pair, derived from FH-deficient UOK262 renal carcinoma cells, contained either an empty vector control (UOK262EV) or a stably re-expressed wild-type FH allele (UOK262FH). Metabolites were extracted from all four cell lines and analyzed by triple-quadrupole mass spectrometry. We first performed a quantitative analysis to determine the abundance of AKG and citrate in the four cell lines. Both 143Bcytb and UOK262EV cells had less citrate, more AKG, and lower citrate:AKG ratios than their oxidative partners (Fig. S1A-C), consistent with findings from VHL-deficient renal carcinoma cells (Gameiro et al., 2013b).
Next, to identify other perturbations, we profiled the relative abundance of more than 90 metabolites from glycolysis, the pentose phosphate pathway, one-carbon/nucleotide metabolism, the TCA cycle, amino acid degradation, and other pathways (Tables S1 and S2). Each metabolite was normalized to protein content, and relative abundance was determined between cell lines from each pair. Hierarchical clustering (Fig 1A) and principal component analysis (Fig 1B) revealed far greater metabolomic similarities between the members of each pair than between the two cell lines using reductive carboxylation. Only three metabolites displayed highly significant (p<0.005) differences in abundance between the two members of both pairs, and in all three cases the direction of the difference (i.e. higher or lower) was shared in the two cell lines using reductive carboxylation. Proline, a nonessential amino acid derived from glutamine in an NADPH-dependent biosynthetic pathway, was depleted in 143Bcytb and UOK262EV cells (Fig. 1C). 2-hydroxyglutarate (2HG), the reduced form of AKG, was elevated in 143Bcytb and UOK262EV cells (Fig. 1D), and further analysis revealed that while both the L- and D-enantiomers of this metabolite were increased, L-2HG was quantitatively the predominant enantiomer (Fig. S1D). It is likely that 2HG accumulation was related to the reduced redox ratio associated with cytb and FH mutations. Although the sources of 2HG are still under investigation, promiscuous activity of the TCA cycle enzyme malate dehydrogenase produces L-2HG in an NADH-dependent manner (Rzem et al., 2007). Both enantiomers are oxidized to AKG by dehydrogenases (L-2HG dehydrogenase and D-2HG dehydrogenase). It is therefore likely that elevated 2-HG is a consequence of a reduced NAD+/NADH ratio. Consistent with this model, inborn errors of the ETC result in 2-HG accumulation (Reinecke et al., 2011). Exposure to hypoxia (<1% O2) has also been demonstrated to reduce the cellular NAD+/NADH ratio (Santidrian et al., 2013) and to favor modest 2HG accumulation in cultured cells (Wise et al., 2011), although these levels were below those noted in gliomas expressing 2HG-producing mutant alleles of isocitrate dehydrogenase-1 or -2 (Dang et al., 2009).
Figure 1Metabolomic features of cells using reductive carboxylation
Finally, the TCA cycle intermediate succinate was markedly elevated in both cell lines (Fig. 1E). We tested additional factors previously reported to stimulate reductive AKG metabolism, including a genetic defect in ETC Complex I, exposure to hypoxia, and chemical inhibitors of the ETC (Mullen et al., 2012, Wise et al., 2011, Metallo et al., 2012). These factors had a variable effect on succinate, with impairments of Complex III or IV strongly inducing succinate accumulation, while impairments of Complex I either had little effect or suppressed succinate (Fig. 1F).
Oxidative glutamine metabolism is the primary route of succinate formation
UOK262EV cells lack FH activity and accumulate large amounts of fumarate (Frezza et al., 2011); elevated succinate was therefore not surprising in these cells, because succinate precedes fumarate by one reaction in the TCA cycle. On the other hand, TCA cycle perturbation in 143Bcytb cells results from primary ETC dysfunction, and reductive carboxylation is postulated to be a consequence of accumulated AKG (Anastasiou and Cantley, 2012, Fendt et al., 2013). Accumulation of AKG is not predicted to result in elevated succinate. We previously reported that 143Bcytb cells produce succinate through simultaneous oxidative and reductive glutamine metabolism (Mullen et al., 2012). To determine the relative contributions of these two pathways, we cultured 143Bwt and 143Bcytb with [U-13C]glutamine and monitored time-dependent 13C incorporation in succinate and other TCA cycle intermediates. Oxidative metabolism of glutamine generates succinate, fumarate and malate containing four glutamine-derived 13C nuclei on the first turn of the cycle (m+4), while reductive metabolism results in the incorporation of three 13C nuclei in these intermediates (Fig. S2). As expected, oxidative glutamine metabolism was the predominant source of succinate, fumarate and malate in 143Bwt cells (Fig. 2A-C). In 143Bcytb, fumarate and malate were produced primarily through reductive metabolism (Fig. 2E-F). Conversely, succinate was formed primarily through oxidative glutamine metabolism, with a minor contribution from the reductive carboxylation pathway (Fig. 2D). Notably, this oxidatively-derived succinate was detected prior to that formed through reductive carboxylation. This indicated that 143Bcytb cells retain the ability to oxidize AKG despite the observation that most of the citrate pool bears the labeling pattern of reductive carboxylation. Together, the labeling data in 143Bcytb cells revealed bidirectional metabolism of carbon from glutamine to produce various TCA cycle intermediates.
Figure 2Oxidative glutamine metabolism is the primary route of succinate formation in cells using reductive carboxylation to generate citrate
Pyruvate carboxylation contributes to the TCA cycle in cells using reductive carboxylation
Because of the persistence of oxidative metabolism, we determined the extent to which other routes of metabolism besides reductive carboxylation contributed to the TCA cycle. We previously reported that silencing the glutamine-catabolizing enzyme glutaminase (GLS) depletes pools of fumarate, malate and OAA, eliciting a compensatory increase in pyruvate carboxylase (PC) to supply the TCA cycle (Cheng et al., 2011). In cells with defective oxidative phophorylation, production of OAA by PC may be preferable to glutamine oxidation because it diminishes the need to recycle reduced electron carriers generated by the TCA cycle. Citrate synthase (CS) can then condense PC-derived OAA with acetyl-CoA to form citrate. To examine the contribution of PC to the TCA cycle, cells were cultured with [3,4-13C]glucose. In this labeling scheme, glucose-derived pyruvate is labeled in carbon 1 (Fig. S3). This label is retained in OAA if pyruvate is carboxylated, but removed as CO2 during conversion of pyruvate to acetyl-CoA by pyruvate dehydrogenase (PDH).
Figure 3Pyruvate carboxylase contributes to citrate formation in cells using reductive carboxylation
Oxidative metabolism of AKG is required for reductive carboxylation
Oxidative synthesis of succinate from AKG requires two reactions: the oxidative decarboxylation of AKG to succinyl-CoA by AKG dehydrogenase, and the conversion of succinyl-CoA to succinate by succinyl-CoA synthetase. In tumors with mutations in the succinate dehydrogenase (SDH) complex, large accumulations of succinate are associated with epigenetic modifications of DNA and histones to promote malignancy (Kaelin and McKnight, 2013, Killian et al., 2013). We therefore tested whether succinate accumulation per se was required to induce reductive carboxylation in 143Bcytb cells. We used RNA interference directed against the gene encoding the alpha subunit (SUCLG1) of succinyl-CoA synthetase, the last step in the pathway of oxidative succinate formation from glutamine (Fig. 4A). Silencing this enzyme greatly reduced succinate levels (Fig. 4B), but had no effect on the labeling pattern of citrate from [U-13C]glutamine (Fig. 4C). Thus, succinate accumulation is not required for reductive carboxylation.
Figure 5AKG dehydrogenase is required for reductive carboxylation
Figure 6AKG dehydrogenase and NNT contribute to NAD+/NADH ratio
Finally, we tested whether these enzymes also controlled the NADP+/NADPH ratio in 143Bcytb cells. Silencing either OGDH or NNT increased the NADP+/NADPH ratio (Fig. 6F,G), whereas silencing IDH2reduced it (Fig. 6H). Together, these data are consistent with a model in which persistent metabolism of AKG by AKG dehydrogenase produces NADH that supports reductive carboxylation by serving as substrate for NNT-dependent NADPH formation, and that IDH2 is a major consumer of NADPH during reductive carboxylation (Fig. 6I).
Reductive carboxylation of AKG initiates a non-conventional form of metabolism that produces TCA cycle intermediates when oxidative metabolism is impaired by mutations, drugs or hypoxia. Because NADPH-dependent isoforms of IDH are reversible, supplying supra-physiological pools of substrates on either side of the reaction drives function of the enzyme as a reductive carboxylase or an oxidative decarboxylase. Thus, in some circumstances reductive carboxylation may operate in response to a mass effect imposed by drastic changes in the abundance of AKG and isocitrate/citrate. However, reductive carboxylation cannot occur without a source of reducing equivalents to produce NADPH. The current work demonstrates that AKG dehydrogenase, an NADH-generating enzyme complex, is required to maintain a low NAD+/NADH ratio for reductive carboxylation of AKG. Thus, reductive carboxylation not only coexists with oxidative metabolism of AKG, but depends on it. Furthermore, silencing NNT, a consumer of NADH, also perturbs the redox ratio and suppresses reductive formation of citrate. These observations suggest that the segment of the oxidative TCA cycle culminating in succinate is necessary to transmit reducing equivalents to NNT for the reductive pathway (Fig 6I).
Succinate accumulation was observed in cells with cytb or FH mutations. However, this accumulation was dispensable for reductive carboxylation, because silencing SUCLG1 expression had no bearing on the pathway as long as AKG dehydrogenase was active. Furthermore, succinate accumulation was not a universal finding of cells using reductive carboxylation. Rather, high succinate levels were observed in cells with distal defects in the ETC (complex III: antimycin, cytb mutation; complex IV: hypoxia) but not defects in complex I (rotenone, metformin, NDUFA1 mutation). These differences reflect the known suppression of SDH activity when downstream components of the ETC are impaired, and the various mechanisms by which succinate may be formed through either oxidative or reductive metabolism. Succinate has long been known as an evolutionarily conserved anaerobic end product of amino acid metabolism during prolonged hypoxia, including in diving mammals (Hochachka and Storey, 1975, Hochachka et al., 1975). The terminal step in this pathway is the conversion of fumarate to succinate using the NADH-dependent “fumarate reductase” system, essentially a reversal of succinate dehydrogenase/ETC complex II (Weinberg et al., 2000, Tomitsuka et al., 2010). However, this process requires reducing equivalents to be passed from NADH to complex I, then to Coenzyme Q, and eventually to complex II to drive the reduction of fumarate to succinate. Hence, producing succinate through reductive glutamine metabolism would require functional complex I. Interestingly, the fumarate reductase system has generally been considered as a mechanism to maintain a proton gradient under conditions of defective ETC activity. Our data suggest that the system is part of a more extensive reorganization of the TCA cycle that also enables reductive citrate formation.
In summary, we demonstrated that branched AKG metabolism is required to sustain levels of reductive carboxylation observed in cells with mitochondrial defects. The organization of this branched pathway suggests that it serves as a relay system to maintain the redox requirements for reductive carboxylation, with the oxidative arm producing reducing equivalents at the level of AKG dehydrogenase and NNT linking this activity to the production of NADPH to be used in the reductive carboxylation reaction. Hence, impairment of the oxidative arm prevents maximal engagement of reductive carboxylation. As both NNT and AKG dehydrogenase are mitochondrial enzymes, the work emphasizes the flexibility of metabolic systems in the mitochondria to fulfill requirements for redox balance and precursor production even when the canonical oxidative function of the mitochondria is impaired.
2.1.3.3 Rewiring Mitochondrial Pyruvate Metabolism. Switching Off the Light in Cancer Cells
Figure 1. MPC Expression and Metabolic Targeting of Mitochondrial Pyruvate High MPC expression (green) is associated with more favorable tumor prognosis, increased pyruvate oxidation, and reduced lactate and ROS, whereas low expression or mutated MPC is linked to poor tumor prognosis and increased anaplerotic generation of OAA. Dual targeting of MPC and GDH with small molecule inhibitors may ameliorate tumorigenesis in certain cancer types.
The study by Yang et al., (2014) provides evidence for the metabolic flexibility to maintain TCA cycle function. Using isotopic labeling, the authors demonstrated that inhibition of MPCs by a specific compound (UK5099) induced glutamine-dependent acetyl-CoA formation via glutamate dehydrogenase (GDH). Consequently, and in contrast to single agent treatment, simultaneous administration of MPC and GDH inhibitors drastically abrogated the growth of cancer cells (Figure 1). These studies have also enabled a fresh perspective on metabolism in the clinic and emphasized a need for high-quality translational studies to assess the role of mitochondrial pyruvate transport in vivo. Thus, integrating the biomarker of low MPC expression with dual inhibition of
MPC and GDH as a synthetic lethal strategy (Yang et al., 2014) is testable and may offer a novel therapeutic window for patients (DeBerardinis and Thompson, 2012). Indeed, combinatorial targeting of cancer metabolism may prevent early drug resistance and lead to enhanced tumor control, as shown recently for antifolate agents combined with arginine deprivation with modulation of intracellular glutamine (Szlosarek, 2014). Moreover, it will be important to assess both intertumoral and intratumoral metabolic heterogeneity going forward, as tumor cells are highly adaptable with respect to the precursors used to fuel the TCA cycle in the presence of reduced pyruvate transport. The observation by Vacanti et al. (2014) that the flux of BCAAs increased following inhibition of MPC activity may also underlie the increase in BCAAs detected in the plasma of patients several years before a clinical diagnosis of pancreatic cancer (Mayers et al., 2014). Since measuring pyruvate transport via the MPC is technically challenging, the use of 18-FDG positron emission tomography and more recently magnetic spectroscopy with hyperpolarized 13C-labeled pyruvate will need to be incorporated into these future studies (Brindle et al., 2011).
References
Bricker, D.K., Taylor, E.B., Schell, J.C., Orsak, T., Boutron, A., Chen, Y.C., Cox, J.E., Cardon, C.M., Van Vranken, J.G., Dephoure, N., et al. (2012). Science 337, 96–100.
Betaine enhances cytochrome c oxidase activity and mitochondrial respiration.
• Betaine increases mitochondrial membrane potential and cellular energy levels.
• Betaine’s anti-tumorigenic effect might be due to a reversal of the Warburg effect.
Betaine protects cells from environmental stress and serves as a methyl donor in several biochemical pathways. It reduces cardiovascular disease risk and protects liver cells from alcoholic liver damage and nonalcoholic steatohepatitis. Its pretreatment can rescue cells exposed to toxins such as rotenone, chloroform, and LiCl. Furthermore, it has been suggested that betaine can suppress cancer cell growth in vivo and in vitro. Mitochondrial electron transport chain (ETC) complexes generate the mitochondrial membrane potential, which is essential to produce cellular energy, ATP. Reduced mitochondrial respiration and energy status have been found in many human pathological conditions including aging, cancer, and neurodegenerative disease. In this study we investigated whether betaine directly targets mitochondria. We show that betaine treatment leads to an upregulation of mitochondrial respiration and cytochrome c oxidase activity in H2.35 cells, the proposed rate limiting enzyme of ETC in vivo. Following treatment, the mitochondrial membrane potential was increased and cellular energy levels were elevated. We propose that the anti-proliferative effects of betaine on cancer cells might be due to enhanced mitochondrial function contributing to a reversal of the Warburg effect.
2.1.3.5 Mitochondrial dysfunction in human non-small-cell lung cancer cells to TRAIL-induced apoptosis by reactive oxygen species and Bcl-XL/p53-mediated amplification mechanisms
Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a promising agent for anticancer therapy; however, non-small-cell lung carcinoma (NSCLC) cells are relatively TRAIL resistant. Identification of small molecules that can restore NSCLC susceptibility to TRAIL-induced apoptosis is meaningful. We found here that rotenone, as a mitochondrial respiration inhibitor, preferentially increased NSCLC cells sensitivity to TRAIL-mediated apoptosis at subtoxic concentrations, the mechanisms by which were accounted by the upregulation of death receptors and the downregulation of c-FLIP (cellular FLICE-like inhibitory protein). Further analysis revealed that death receptors expression by rotenone was regulated by p53, whereas c-FLIP downregulation was blocked by Bcl-XL overexpression. Rotenone triggered the mitochondria-derived reactive oxygen species (ROS) generation, which subsequently led to Bcl-XL downregulation and PUMA upregulation. As PUMA expression was regulated by p53, the PUMA, Bcl-XL and p53 in rotenone-treated cells form a positive feedback amplification loop to increase the apoptosis sensitivity. Mitochondria-derived ROS, however, promote the formation of this amplification loop. Collectively, we concluded that ROS generation, Bcl-XL and p53-mediated amplification mechanisms had an important role in the sensitization of NSCLC cells to TRAIL-mediated apoptosis by rotenone. The combined TRAIL and rotenone treatment may be appreciated as a useful approach for the therapy of NSCLC that warrants further investigation.
Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) has emerged as a promising cancer therapeutic because it can selectively induce apoptosis in tumor cells in vitro, and most importantly, in vivo with little adverse effect on normal cells.1 However, a number of cancer cells are resistant to TRAIL, especially highly malignant tumors such as lung cancer.2, 3 Lung cancer, especially the non-small-cell lung carcinoma (NSCLC) constitutes a heavy threat to human life. Presently, the morbidity and mortality of NSCLC has markedly increased in the past decade,4 which highlights the need for more effective treatment strategies.
TRAIL has been shown to interact with five receptors, including the death receptors 4 and 5 (DR4 and DR5), the decoy receptors DcR1 and DcR2, and osteoprotegerin.5 Ligation of TRAIL to DR4 or DR5 allows for the recruitment of Fas-associated protein with death domain (FADD), which leads to the formation of death-inducing signaling complex (DISC) and the subsequent activation of caspase-8/10.6 The effector caspase-3 is activated by caspase-8, which cleaves numerous regulatory and structural proteins resulting in cell apoptosis. Caspase-8 can also cleave the Bcl-2 inhibitory BH3-domain protein (Bid), which engages the intrinsic apoptotic pathway by binding to Bcl-2-associated X protein (Bax) and Bcl-2 homologous antagonist killer (BAK). The oligomerization between Bcl-2 and Bax promotes the release of cytochrome c from mitochondria to cytosol, and facilitates the formation of apoptosome and caspase-9 activation.7 Like caspase-8, caspase-9 can also activate caspase-3 and initiate cell apoptosis. Besides apoptosis-inducing molecules, several apoptosis-inhibitory proteins also exist and have function even when apoptosis program is initiated. For example, cellular FLICE-like inhibitory protein (c-FLIP) is able to suppress DISC formation and apoptosis induction by sequestering FADD.8, 9, 10, 11
Until now, the recognized causes of TRAIL resistance include differential expression of death receptors, constitutively active AKT and NF-κB,12, 13overexpression of c-FLIP and IAPs, mutations in Bax and BAK gene.2 Hence, resistance can be overcome by the use of sensitizing agents that modify the deregulated death receptor expression and/or apoptosis signaling pathways in cancer cells.5 Many sensitizing agents have been developed in a variety of tumor cell models.2 Although the clinical effectiveness of these agents needs further investigation, treatment of TRAIL-resistant tumor cells with sensitizing agents, especially the compounds with low molecular weight, as well as prolonged plasma half-life represents a promising trend for cancer therapy.
Mitochondria emerge as intriguing targets for cancer therapy. Metabolic changes affecting mitochondria function inside cancer cells endow these cells with distinctive properties and survival advantage worthy of drug targeting, mitochondria-targeting drugs offer substantial promise as clinical treatment with minimal side effects.14, 15, 16 Rotenone is a potent inhibitor of NADH oxidoreductase in complex I, which demonstrates anti-neoplastic activity on a variety of cancer cells.17, 18, 19, 20, 21 However, the neurotoxicity of rotenone limits its potential application in cancer therapy. To avoid it, rotenone was effectively used in combination with other chemotherapeutic drugs to kill cancerous cells.22
In our previous investigation, we found that rotenone was able to suppress membrane Na+,K+-ATPase activity and enhance ouabain-induced cancer cell death.23 Given these facts, we wonder whether rotenone may also be used as a sensitizing agent that can restore the susceptibility of NSCLC cells toward TRAIL-induced apoptosis, and increase the antitumor efficacy of TRAIL on NSCLC. To test this hypothesis, we initiated this study.
Rotenone sensitizes NSCLC cell lines to TRAIL-induced apoptosis
Four NSCLC cell lines including A549, H522, H157 and Calu-1 were used in this study. As shown in Figure 1a, the apoptosis induced by TRAIL alone at 50 or 100 ng/ml on A549, H522, H157 and Calu-1 cells was non-prevalent, indicating that these NSCLC cell lines are relatively TRAIL resistant. Interestingly, when these cells were treated with TRAIL combined with rotenone, significant increase in cell apoptosis was observed. To examine whether rotenone was also able to sensitize normal cells to TRAIL-mediated apoptosis, peripheral blood mononuclear cell (PBMC) isolated from human blood were used. As a result, rotenone failed to sensitize human PBMC to TRAIL-induced apoptosis, indicating that the sensitizing effect of rotenone is tumor cell specific. Of note, the apoptosis-enhancing effect of rotenone occurred independent of its cytotoxicity, because the minimal dosage required for rotenone to cause toxic effect on NSCLC cell lines was 10 μM, however, rotenone augmented TRAIL-mediated apoptosis when it was used as little as 10 nM.
http://www.nature.com/cddis/journal/v5/n12/fig_tab/cddis2014547f1.html#figure-title
To further confirm the effect of rotenone, cells were stained with Hoechst and observed under fluorescent microscope (Figure 1b). Consistently, the combined treatment of rotenone with TRAIL caused significant nuclear fragmentation in A549, H522, H157 and Calu-1 cells. Rotenone or TRAIL treatment alone, however, had no significant effect.
Caspases activation is a hallmark of cell apoptosis. In this study, the enzymatic activities of caspases including caspase-3, -8 and -9 were measured by flow cytometry by using FITC-conjugated caspases substrate (Figure 1c). As a result, rotenone used at 1 μM or TRAIL used at 100 ng/ml alone did not cause caspase-3, -8 and -9 activation. The combined treatment, however, significantly increased the enzymatic activities of them. Moreover, A549 or H522 cell apoptosis by TRAIL combined with rotenone was almost completely suppressed in the presence of z-VAD.fmk, a pan-caspase inhibitor (Figure 1d). All of these data indicate that both intrinsic and extrinsic pathways are involved in the sensitizing effect of rotenone on TRAIL-mediated apoptosis in NSCLC.
Upregulation of death receptors expression is required for rotenone-mediated sensitization to TRAIL-induced apoptosis
Sensitization to TRAIL-induced apoptosis has been explained in some studies by upregulation of death receptors,24 whereas other results show that sensitization can occur without increased TRAIL receptor expression.25 As such, we examined TRAIL receptors expression on NSCLC cells after treatment with rotenone. Rotenone increased DR4 and DR5 mRNA levels in A549 cells in a time or concentration-dependent manner (Figures 2a and b), also increased DR4 and DR5 protein expression levels (Supplementary Figure S1). Notably, rotenone failed to increase DR5 mRNA levels in H157 and Calu-1 cells (Supplementary Figure S2). To observe whether the increased DR4 and DR5 mRNA levels finally correlated with the functional molecules, we examined the surface expression levels of DR4 and DR5 by flow cytometry. The results, as shown in Figure 2c demonstrated that the cell surface expression levels of DR4 and DR5 were greatly upregulated by rotenone in either A549 cells or H522 cells.
To analyze whether the upregulation of DR4 and DR5 is a ‘side-effect’, or contrarily, necessary for rotenone-mediated sensitization to TRAIL-induced apoptosis, we blocked upregulation of the death receptors by small interfering RNAs (siRNAs) against DR4 and DR5 (Supplementary Figure S3). The results showed that blocking DR4 and DR5 expression alone significantly reduced the rate of cell apoptosis in A549 cells (Figure 2d). However, the highest inhibition of apoptosis was observed when upregulation of both receptors was blocked in parallel, thus showing an additive effect of blocking DR4 and DR5 at the same time. Similar results were also obtained in H522 cells
To analyze whether the upregulation of DR4 and DR5 is a ‘side-effect’, or contrarily, necessary for rotenone-mediated sensitization to TRAIL-induced apoptosis, we blocked upregulation of the death receptors by small interfering RNAs (siRNAs) against DR4 and DR5 (Supplementary Figure S3). The results showed that blocking DR4 and DR5 expression alone significantly reduced the rate of cell apoptosis in A549 cells (Figure 2d). However, the highest inhibition of apoptosis was observed when upregulation of both receptors was blocked in parallel, thus showing an additive effect of blocking DR4 and DR5 at the same time. Similar results were also obtained in H522 cells.
Rotenone-induced p53 activation regulates death receptors upregulation
TRAIL receptors DR4 and DR5 are regulated at multiple levels. At transcriptional level, studies suggest that several transcriptional factors including NF-κB, p53 and AP-1 are involved in DR4 or DR5 gene transcription.2 The NF-κB or AP-1 transcriptional activity was further modulated by ERK1/2, JNK and p38 MAP kinase activity. Unexpectedly, we found here that none of these MAP kinases inhibitors were able to suppress the apoptosis mediated by TRAIL plus rotenone (Figure 3a). To find out other possible mechanisms, we observed that rotenone was able to stimulate p53 phosphorylation as well as p53 protein expression in A549 and H522 cells (Figure 3b). As a p53-inducible gene, p21 mRNA expression was also upregulated by rotenone treatment in a time-dependent manner (Figure 3c). To characterize the effect of p53, A549 cells were transfected with p53 siRNA. The results, as shown in Figure 3d-1 demonstrated that rotenone-mediated surface expression levels of DR4 and DR5 in A549 cells were largely attenuated by siRNA-mediated p53 expression silencing. Control siRNA, however, failed to reveal such effect. Similar results were also obtained in H522 cells (Figure 3d-2). Silencing of p53 expression in A549 cells also partially suppressed the apoptosis induced by TRAIL plus rotenone (Figure 3e).
Rotenone suppresses c-FLIP expression and increases the sensitivity of A549 cells to TRAIL-induced apoptosis
The c-FLIP protein has been commonly appreciated as an anti-apoptotic molecule in death receptor-mediated cell apoptosis. In this study, rotenone treatment led to dose-dependent downregulation of c-FLIP expression, including c-FLIPL and c-FLIPs in A549 cells (Figure 4a-1), H522 cells (Figure 4a-2), H441 and Calu-1 cells (Supplementary Figure S4). To test whether c-FLIP is essential for the apoptosis enhancement, A549 cells were transfected with c-FLIPL-overexpressing plasmids. As shown in Figure 4b-1, the apoptosis of A549 cells after the combined treatment was significantly reduced when c-FLIPL was overexpressed. Similar results were also obtained in H522 cells (Figure 4b-2).
Bcl-XL is involved in the apoptosis enhancement by rotenone
Notably, c-FLIP downregulation by rotenone in NSCLC cells was irrelevant to p53 signaling (data not shown). To identify other mechanism involved, we found that anti-apoptotic molecule Bcl-XL was also found to be downregulated by rotenone in a dose-dependent manner (Figure 5a). Notably, both Bcl-XL and c-FLIPL mRNA levels remained unchanged in cells after rotenone treatment (Supplementary Figure S5). Bcl-2 is homolog to Bcl-XL. But surprisingly, Bcl-2 expression was almost undetectable in A549 cells. To examine whether Bcl-XL is involved, A549 cells were transfected with Bcl-XL-overexpressing plasmid. As compared with mock transfectant, cell apoptosis induced by TRAIL plus rotenone was markedly suppressed under the condition of Bcl-XL overexpression (Figure 5b). To characterize the mechanisms, surface expression levels of DR4 and DR5 were examined. As shown in Figure 5c, the increased surface expression of DR4 and DR5 in A549 cells, or in H522 cells were greatly reduced after Bcl-XLoverexpression (Figure 5c). In addition, Bcl-XL overexpression also significantly prevented the downregulation of c-FLIPL and c-FLIPs expression in A549 cells by rotenone treatment (Figure 5d).
Rotenone suppresses the interaction between BCL-XL/p53 and increases PUMA transcription
Lines of evidence suggest that Bcl-XL has a strong binding affinity with p53, and can suppress p53-mediated tumor cell apoptosis.26 In this study, FLAG-tagged Bcl-XL and HA-tagged p53 were co-transfected into cells; immunoprecipitation experiment was performed by using FLAG antibody to immunoprecipitate HA-tagged p53. As a result, we found that at the same amount of p53 protein input, rotenone treatment caused a concentration-dependent suppression of the protein interaction between Bcl-XL and p53 (Figure 6a). Rotenone also significantly suppressed the interaction between endogenous Bcl-XL and p53 when polyclonal antibody against p53 was used to immunoprecipitate cellular Bcl-XL (Figure 6b). Recent study highlighted the importance of PUMA in BCL-XL/p53 interaction and cell apoptosis.27 We found here that rotenone significantly increased PUMA gene transcription (Figure 6c) and protein expression (Figure 6d) in NSCLC cells, but not in transformed 293T cell. Meanwhile, this effect was attenuated by silencing of p53 expression (Figure 6e).
Mitochondria-derived ROS are responsible for the apoptosis-enhancing effect of rotenone
As an inhibitor of mitochondrial respiration, rotenone was found to induce reactive oxygen species (ROS) generation in a variety of transformed or non-transformed cells.20, 22 Consistently, by using 2′,7′-dichlorofluorescin diacetate (DCFH) for the measurement of intracellular H2O2 and dihydroethidium (DHE) for O2.−, we found that rotenone significantly triggered the .generation of H2O2(Figure 7a) and O2.− (Figure 7b) in A549 and H522 cells. To identify the origin of ROS production, we first incubated cells with diphenylene iodonium (DPI), a potent inhibitor of plasma membrane NADP/NADPH oxidase. The results showed that DPI failed to suppress rotenone-induced ROS generation (Figure 7c). Then, we generated A549 cells deficient in mitochondria DNA by culturing cells in medium supplemented with ethidium bromide (EB). These mtDNA-deficient cells were subject to rotenone treatment, and the result showed that rotenone-induced ROS production were largely attenuated in A549 ρ° cells, but not wild-type A549 cells, suggesting ROS are mainly produced from mitochondria (Figure 7d). Notably, the sensitizing effect of rotenone on TRAIL-induced apoptosis in A549 cells was largely dependent on ROS, because the antioxidant N-acetylcysteine (NAC) treatment greatly suppressed the cell apoptosis, as shown in annexin V/PI double staining experiment (Figure 7e), cell cycle analysis (Figure 7f) and caspase-3 cleavage activity assay (Figure 7g). Finally, in A549 cells stably transfected with manganese superoxide (MnSOD) and catalase, apoptosis induced by TRAIL and rotenone was partially reversed (Figure 7h). All of these data suggest that mitochondria-derived ROS, including H2O2 and O2.−, are responsible for the apoptosis-enhancing effect of rotenone.
Rotenone promotes BCl-XL degradation and PUMA transcription in ROS-dependent manner
To understand why ROS are responsible for the apoptosis-enhancing effect of rotenone, we found that rotenone-induced suppression of BCL-XL expression can be largely reversed by NAC treatment (Figure 8a). To examine whether this effect of rotenone occurs at posttranslational level, we used cycloheximide (CHX) to halt protein synthesis, and found that the rapid degradation of Bcl-XL by rotenone was largely attenuated in A549 ρ0 cells (Figure 8b). Similarly, rotenone-induced PUMA upregulation was also significantly abrogated in A549 ρ0 cells (Figure 8c). Finally, A549 cells were inoculated into nude mice to produce xenografts tumor model. In this model, the therapeutic effect of TRAIL combined with rotenone was evaluated. Notably, in order to circumvent the potential neurotoxic adverse effect of rotenone, mice were challenged with rotenone at a low concentration of 0.5 mg/kg. The results, as shown in Figure 8d revealed that while TRAIL or rotenone alone remained unaffected on A549 tumor growth, the combined therapy significantly slowed down the tumor growth. Interestingly, the tumor-suppressive effect of TRAIL plus rotenone was significantly attenuated by NAC (P<0.01). After experiment, tumors were removed and the caspase-3 activity in tumor cells was analyzed by flow cytometry. Consistently, the caspase-3 cleavage activities were significantly activated in A549 cells from animals challenged with TRAIL plus rotenone, meanwhile, this effect was attenuated by NAC (Figure 8e). The similar effect of rotenone also occurred in NCI-H441 xenografts tumor model (Supplementary Figure S6).
Restoration of cancer cells susceptibility to TRAIL-induced apoptosis is becoming a very useful strategy for cancer therapy. In this study, we provided evidence that rotenone increased the apoptosis sensitivity of NSCLC cells toward TRAIL by mechanisms involving ROS generation, p53 upregulation, Bcl-XL and c-FLIP downregulation, and death receptors upregulation. Among them, mitochondria-derived ROS had a predominant role. Although rotenone is toxic to neuron, increasing evidence also demonstrated that it was beneficial for improving inflammation, reducing reperfusion injury, decreasing virus infection or triggering cancer cell death. We identified here another important characteristic of rotenone as a tumor sensitizer in TRAIL-based cancer therapy, which widens the application potential of rotenone in disease therapy.
As Warburg proposed the cancer ‘respiration injury’ theory, increasing evidence suggest that cancer cells may have mitochondrial dysfunction, which causes cancer cells, compared with the normal cells, are under increased generation of ROS.33 The increased ROS in cancer cells have a variety of biological effects. We found here that rotenone preferentially increased the apoptosis sensitivity of cancer cells toward TRAIL, further confirming the concept that although tumor cells have a high level of intracellular ROS, they are more sensitive than normal cells to agents that can cause further accumulation of ROS.
Cancer cells stay in a stressful tumor microenvironment including hypoxia, low nutrient availability and immune infiltrates. These conditions, however, activate a range of stress response pathways to promote tumor survival and aggressiveness. In order to circumvent TRAIL-mediated apoptotic clearance, the expression levels of DR4 and DR5 in many types of cancer cells are nullified, but interestingly, they can be reactivated when cancer cells are challenged with small chemical molecules. Furthermore, those small molecules often take advantage of the stress signaling required for cancer cells survival to increase cancer cells sensitivity toward TRAIL. For example, the unfolded protein response (UPR) has an important role in cancer cells survival, SHetA2, as a small molecule, can induce UPR in NSCLC cell lines and augment TRAIL-induced apoptosis by upregulating DR5 expression in CHOP-dependent manner. Here, we found rotenone manipulated the oxidative stress signaling of NSCLC cells to increase their susceptibility to TRAIL. These facts suggest that cellular stress signaling not only offers opportunity for cancer cells to survive, but also renders cancer cells eligible for attack by small molecules. A possible explanation is that depending on the intensity of stress, cellular stress signaling can switch its role from prosurvival to death enhancement. As described in this study, although ROS generation in cancer cells is beneficial for survival, rotenone treatment further increased ROS production to a high level that surpasses the cell ability to eliminate them; as a result, ROS convert its role from survival to death.
2.1.3.6 PPARs and ERRs. molecular mediators of mitochondrial metabolism
Since the revitalization of ‘the Warburg effect’, there has been great interest in mitochondrial oxidative metabolism, not only from the cancer perspective but also from the general biomedical science field. As the center of oxidative metabolism, mitochondria and their metabolic activity are tightly controlled to meet cellular energy requirements under different physiological conditions. One such mechanism is through the inducible transcriptional co-regulators PGC1α and NCOR1, which respond to various internal or external stimuli to modulate mitochondrial function. However, the activity of such co-regulators depends on their interaction with transcriptional factors that directly bind to and control downstream target genes. The nuclear receptors PPARs and ERRs have been shown to be key transcriptional factors in regulating mitochondrial oxidative metabolism and executing the inducible effects of PGC1α and NCOR1. In this review, we summarize recent gain-of-function and loss-of-function studies of PPARs and ERRs in metabolic tissues and discuss their unique roles in regulating different aspects of mitochondrial oxidative metabolism.
Energy is vital to all living organisms. In humans and other mammals, the vast majority of energy is produced by oxidative metabolism in mitochondria [1]. As a cellular organelle, mitochondria are under tight control of the nucleus. Although the majority of mitochondrial proteins are encoded by nuclear DNA (nDNA) and their expression regulated by the nucleus, mitochondria retain their own genome, mitochondrial DNA (mtDNA), encoding 13 polypeptides of the electron transport chain (ETC) in mammals. However, all proteins required for mtDNA replication, transcription, and translation, as well as factors regulating such activities, are encoded by the nucleus [2].
The cellular demand for energy varies in different cells under different physiological conditions. Accordingly, the quantity and activity of mitochondria are differentially controlled by a transcriptional regulatory network in both the basal and induced states. A number of components of this network have been identified, including members of the nuclear receptor superfamily, the peroxisome proliferator-activated receptors (PPARs) and the estrogen-related receptors (ERRs) [3, 4 and 5].
The Yin-Yang co-regulators
A well-known inducer of mitochondrial oxidative metabolism is the peroxisome proliferator-activated receptor γ coactivator 1α (PGC1α) [6], a nuclear cofactor which is abundantly expressed in high energy demand tissues such as heart, skeletal muscle, and brown adipose tissue (BAT) [7]. Induction by cold-exposure, fasting, and exercise allows PGC1α to regulate mitochondrial oxidative metabolism by activating genes involved in the tricarboxylic acid cycle (TCA cycle), beta-oxidation, oxidative phosphorylation (OXPHOS), as well as mitochondrial biogenesis [6 and 8] (Figure 1).
Figure 1. PPARs and ERRs are major executors of PGC1α-induced regulation of oxidative metabolism. Physiological stress such as exercise induces both the expression and activity of PGC1α, which stimulates energy production by activating downstream genes involved in fatty acid and glucose metabolism, TCA cycle, β-oxidation, OXPHOS, and mitochondrial biogenesis. The transcriptional activity of PGC1α relies on its interactions with transcriptional factors such as PPARs (for controlling fatty acid metabolism) and ERRs (for regulating mitochondrial OXPHOS).
The effect of PGC1α on mitochondrial regulation is antagonized by transcriptional corepressors such as the nuclear receptor corepressor 1 (NCOR1) [9 and 10]. In contrast to PGC1α, the expression of NCOR1 is suppressed in conditions where PGC1α is induced such as during fasting, high-fat-diet challenge, and exercise [9 and 11]. Moreover, the knockout of NCOR1 phenotypically mimics PGC1α overexpression in regulating mitochondrial oxidative metabolism [9]. Therefore, coactivators and corepressors collectively regulate mitochondrial metabolism in a Yin-Yang fashion.
However, both PGC1α and NCOR1 lack DNA binding activity and rather act via their interaction with transcription factors that direct the regulatory program. Therefore the transcriptional factors that partner with PGC1α and NCOR1 mediate the molecular signaling cascades and execute their inducible effects on mitochondrial regulation.
Both PGC1α and NCOR1 are co-factors for the peroxisome proliferator-activated receptors (PPARα, γ, and δ) [7, 11, 12 and 13]. It is now clear that all three PPARs play essential roles in lipid and fatty acid metabolism by directly binding to and modulating genes involved in fat metabolism [13, 14, 15, 16, 17,18 and 19]. While PPARγ is known as a master regulator for adipocyte differentiation and does not seem to be involved with oxidative metabolism [14 and 20], both PPARα and PPARδ are essential regulators of fatty acid oxidation (FAO) [3, 13, 15, 19 and 21] (Figure 1).
PPARα was first cloned as the molecular target of fibrates, a class of cholesterol-lowering compounds that increase hepatic FAO [22]. The importance of PPARα in regulating FAO is indicated in its expression pattern which is restricted to tissues with high capacity of FAO such as heart, liver, BAT, and oxidative muscle [23]. On the other hand, PPARδ is ubiquitously expressed with higher levels in the digestive tract, heart, and BAT [24]. In the past 15 years, extensive studies using gain-of-function and loss-of-function models have clearly demonstrated PPARα and PPARδ as the major drivers of FAO in a wide variety of tissues.
ERRs are essential regulators of mitochondrial energy metabolism [4]. ERRα is ubiquitously expressed but particularly abundant in tissues with high energy demands such as brain, heart, muscle, and BAT. ERRβ and ERRγ have similar expression patterns, both are selectively expressed in highly oxidative tissues including brain, heart, and oxidative muscle [45]. Instead of endogenous ligands, the transcriptional activity of ERRs is primarily regulated by co-factors such as PGC1α and NCOR1 [4 and 46] (Figure 1).
Of the three ERRs, ERRβ is the least studied and its role in regulating mitochondrial function is unclear [4 and 47]. In contrast, when PGC1α is induced, ERRα is the master regulator of the mitochondrial biogenic gene network. As ERRα binds to its own promoter, PGC1α can also induce an autoregulatory loop to enhance overall ERRα activity [48]. Without ERRα, the ability of PGC1α to induce the expression of mitochondrial genes is severely impaired. However, the basal-state levels of mitochondrial target genes are not affected by ERRα deletion, suggesting induced mitochondrial biogenesis is a transient process and that other transcriptional factors such as ERRγ may be important maintaining baseline mitochondrial OXPHOS [41•, 42 and 43]. Consistent with this idea, ERRγ (which is active even when PGC1α is not induced) shares many target genes with ERRα [49 and 50].
Conclusion and perspectives
Taken together, recent studies have clearly demonstrated the essential roles of PPARs and ERRs in regulating mitochondrial oxidative metabolism and executing the inducible effects of PGC1α (Figure 1). Both PPARα and PPARδ are key regulators for FA oxidation. While the function of PPARα seems more restricted in FA uptake, beta-oxidation, and ketogenesis, PPARδ plays a broader role in controlling oxidative metabolism and fuel preference, with its target genes involved in FA oxidation, mitochondrial OXPHOS, and glucose utilization. However, it is still not clear how much redundancy exists between PPARα and PPARδ, a question which may require the generation of a double knockout model. In addition, more effort is needed to fully understand how PPARα and PPARδ control their target genes in response to environmental changes.
Likewise, ERRα and ERRγ have been shown to be key regulators of mitochondrial OXPHOS. Knockout studies of ERRα suggest it to be the principal executor of PGC1α induced up-regulation of mitochondrial genes, though its role in exercise-dependent changes in skeletal muscle needs further investigation. Transgenic models have demonstrated ERRγ’s powerful induction of mitochondrial biogenesis and its ability to act in a PGC1α-independent manner. However, it remains to be elucidated whether ERRγ is sufficient for basal-state mitochondrial function in general, and whether ERRα can compensate for its function.
2.1.3.7 Metabolic control via the mitochondrial protein import machinery
Mitochondria have to import most of their proteins in order to fulfill a multitude of metabolic functions. Sophisticated import machineries mediate targeting and translocation of preproteins from the cytosol and subsequent sorting into their suborganellar destination. The mode of action of these machineries has been considered for long time as a static and constitutively active process. However, recent studies revealed that the mitochondrial protein import machinery is subject to intense regulatory mechanisms that include direct control of protein flux by metabolites and metabolic signaling cascades.
2.1.3.8 The Protein Import Machinery of Mitochondria—A Regulatory Hub
AB Harbauer, RP Zahedi, A Sickmann, N Pfanner, C Meisinger
Cell Metab 4 Mar 2014; 19(3):357–372
Mitochondria are essential cell. They are best known for their role as cellular powerhouses, which convert the energy derived from food into an electrochemical proton gradient across the inner membrane. The proton gradient drives the mitochondrial ATP synthase, thus providing large amounts of ATP for the cell. In addition, mitochondria fulfill central functions in the metabolism of amino acids and lipids and the biosynthesis of iron-sulfur clusters and heme. Mitochondria form a dynamic network that is continuously remodeled by fusion and fission. They are involved in the maintenance of cellular ion homeostasis, play a crucial role in apoptosis, and have been implicated in the pathogenesis of numerous diseases, in particular neurodegenerative disorders.
Mitochondria consist of two membranes, outer membrane and inner membrane, and two aqueous compartments, intermembrane space and matrix (Figure 1). Proteomic studies revealed that mitochondria contain more than 1,000 different proteins (Prokisch et al., 2004, Reinders et al., 2006, Pagliarini et al., 2008 and Schmidt et al., 2010). Based on the endosymbiotic origin from a prokaryotic ancestor, mitochondria contain a complete genetic system and protein synthesis apparatus in the matrix; however, only ∼1% of mitochondrial proteins are encoded by the mitochondrial genome (13 proteins in humans and 8 proteins in yeast). Nuclear genes code for ∼99% of mitochondrial proteins. The proteins are synthesized as precursors on cytosolic ribosomes and are translocated into mitochondria by a multicomponent import machinery. The protein import machinery is essential for the viability of eukaryotic cells. Numerous studies on the targeting signals and import components have been reported (reviewed in Dolezal et al., 2006,Neupert and Herrmann, 2007, Endo and Yamano, 2010 and Schmidt et al., 2010), yet for many years little has been known on the regulation of the import machinery. This led to the general assumption that the protein import machinery is constitutively active and not subject to detailed regulation.
Figure 1. Protein Import Pathways of Mitochondria. Most mitochondrial proteins are synthesized as precursors in the cytosol and are imported by the translocase of the outer mitochondrial membrane (TOM complex). (A) Presequence-carrying (cleavable) preproteins are transferred from TOM to the presequence translocase of the inner membrane (TIM23 complex), which is driven by the membrane potential (Δψ). The proteins either are inserted into the inner membrane (IM) or are translocated into the matrix with the help of the presequence translocase-associated motor (PAM). The presequences are typically cleaved off by the mitochondrial processing peptidase (MPP). (B) The noncleavable precursors of hydrophobic metabolite carriers are bound to molecular chaperones in the cytosol and transferred to the receptor Tom70. After translocation through the TOM channel, the precursors bind to small TIM chaperones in the intermembrane space and are membrane inserted by the Δψ-dependent carrier translocase of the inner membrane (TIM22 complex).
(C) Cysteine-rich proteins destined for the intermembrane space (IMS) are translocated through the TOM channel in a reduced conformation and imported by the mitochondrial IMS import and assembly (MIA) machinery. Mia40 functions as precursor receptor and oxidoreductase in the IMS, promoting the insertion of disulfide bonds into the imported proteins. The sulfhydryl oxidase Erv1 reoxidizes Mia40 for further rounds of oxidative protein import and folding. (D) The precursors of outer membrane β-barrel proteins are imported by the TOM complex and small TIM chaperones and are inserted into the outer membrane by the sorting and assembly machinery (SAM complex). (E) Outer membrane (OM) proteins with α-helical transmembrane segments are inserted into the membrane by import pathways that have only been partially characterized. Shown is an import pathway via the mitochondrial import (MIM) complex
Studies in recent years, however, indicated that different steps of mitochondrial protein import are regulated, suggesting a remarkable diversity of potential mechanisms. After an overview on the mitochondrial protein import machinery, we will discuss the regulatory processes at different stages of protein translocation into mitochondria. We propose that the mitochondrial protein import machinery plays a crucial role as regulatory hub under physiological and pathophysiological conditions. Whereas the basic mechanisms of mitochondrial protein import have been conserved from lower to higher eukaryotes (yeast to humans), regulatory processes may differ between different organisms and cell types. So far, many studies on the regulation of mitochondrial protein import have only been performed in a limited set of organisms. Here we discuss regulatory principles, yet it is important to emphasize that future studies will have to address which regulatory processes have been conserved in evolution and which processes are organism specific.
Protein Import Pathways into Mitochondria
The classical route of protein import into mitochondria is the presequence pathway (Neupert and Herrmann, 2007 and Chacinska et al., 2009). This pathway is used by more than half of all mitochondrial proteins (Vögtle et al., 2009). The proteins are synthesized as precursors with cleavable amino-terminal extensions, termed presequences. The presequences form positively charged amphipathic α helices and are recognized by receptors of the translocase of the outer mitochondrial membrane (TOM complex) (Figure 1A) (Mayer et al., 1995, Brix et al., 1997, van Wilpe et al., 1999, Abe et al., 2000, Meisinger et al., 2001 and Saitoh et al., 2007). Upon translocation through the TOM channel, the cleavable preproteins are transferred to the presequence translocase of the inner membrane (TIM23 complex). The membrane potential across the inner membrane (Δψ, negative on the matrix side) exerts an electrophoretic effect on the positively charged presequences (Martin et al., 1991). The presequence translocase-associated motor (PAM) with the ATP-dependent heat-shock protein 70 (mtHsp70) drives preprotein translocation into the matrix (Chacinska et al., 2005 and Mapa et al., 2010). Here the presequences are typically cleaved off by the mitochondrial processing peptidase (MPP). Some cleavable preproteins contain a hydrophobic segment behind the presequence, leading to arrest of translocation in the TIM23 complex and lateral release of the protein into the inner membrane (Glick et al., 1992, Chacinska et al., 2005 and Meier et al., 2005). In an alternative sorting route, some cleavable preproteins destined for the inner membrane are fully or partially translocated into the matrix, followed by insertion into the inner membrane by the OXA export machinery, which has been conserved from bacteria to mitochondria (“conservative sorting”) (He and Fox, 1997, Hell et al., 1998, Meier et al., 2005 and Bohnert et al., 2010). …
Regulatory Processes Acting at Cytosolic Precursors of Mitochondrial Proteins
Two properties of cytosolic precursor proteins are crucial for import into mitochondria. (1) The targeting signals of the precursors have to be accessible to organellar receptors. Modification of a targeting signal by posttranslational modification or masking of a signal by binding partners can promote or inhibit import into an organelle. (2) The protein import channels of mitochondria are so narrow that folded preproteins cannot be imported. Thus preproteins should be in a loosely folded state or have to be unfolded during the import process. Stable folding of preprotein domains in the cytosol impairs protein import. …
Import Regulation by Binding of Metabolites or Partner Proteins to Preproteins
Binding of a metabolite to a precursor protein can represent a direct means of import regulation (Figure 2A, condition 1). A characteristic example is the import of 5-aminolevulinate synthase, a mitochondrial matrix protein that catalyzes the first step of heme biosynthesis (Hamza and Dailey, 2012). The precursor contains heme binding motifs in its amino-terminal region, including the presequence (Dailey et al., 2005). Binding of heme to the precursor inhibits its import into mitochondria, likely by impairing recognition of the precursor protein by TOM receptors (Lathrop and Timko, 1993, González-Domínguez et al., 2001,Munakata et al., 2004 and Dailey et al., 2005). Thus the biosynthetic pathway is regulated by a feedback inhibition of mitochondrial import of a crucial enzyme, providing an efficient and precursor-specific means of import regulation dependent on the metabolic situation.
Figure 2. Regulation of Cytosolic Precursors of Mitochondrial Proteins
(A) The import of a subset of mitochondrial precursor proteins can be positively or negatively regulated by precursor-specific reactions in the cytosol. (1) Binding of ligands/metabolites can inhibit mitochondrial import. (2) Binding of precursors to partner proteins can stimulate or inhibit import into mitochondria. (3) Phosphorylation of precursors in the vicinity of targeting signals can modulate dual targeting to the endoplasmic reticulum (ER) and mitochondria. (4) Precursor folding can mask the targeting signal. (B) Cytosolic and mitochondrial fumarases are derived from the same presequence-carrying preprotein. The precursor is partially imported by the TOM and TIM23 complexes of the mitochondrial membranes and the presequence is removed by the mitochondrial processing peptidase (MPP). Folding of the preprotein promotes retrograde translocation of more than half of the molecules into the cytosol, whereas the other molecules are completely imported into mitochondria.
Regulation of Mitochondrial Protein Entry Gate by Cytosolic Kinases
Figure 3. Regulation of TOM Complex by Cytosolic Kinases
(A) All subunits of the translocase of the outer mitochondrial membrane (TOM complex) are phosphorylated by cytosolic kinases (phosphorylated amino acid residues are indicated by stars with P). Casein kinase 1 (CK1) stimulates the assembly of Tom22 into the TOM complex. Casein kinase 2 (CK2) stimulates the biogenesis of Tom22 as well as the mitochondrial import protein 1 (Mim1). Protein kinase A (PKA) inhibits the biogenesis of Tom22 and Tom40, and inhibits the activity of Tom70 (see B). Cyclin-dependent kinases (CDK) are possibly involved in regulation of TOM. (B) Metabolic shift-induced regulation of the receptor Tom70 by PKA. Carrier precursors bind to cytosolic chaperones (Hsp70 and/or Hsp90). Tom70 has two binding pockets, one for the precursor and one for the accompanying chaperone (shown on the left). When glucose is added to yeast cells (fermentable conditions), the levels of intracellular cAMP are increased and PKA is activated (shown on the right). PKA phosphorylates a serine of Tom70 in vicinity of the chaperone binding pocket, thus impairing chaperone binding to Tom70 and carrier import into mitochondria.
Casein Kinase 2 Stimulates TOM Biogenesis and Protein Import
Metabolic Switch from Respiratory to Fermentable Conditions Involves Protein Kinase A-Mediated Inhibition of TOM
Network of Stimulatory and Inhibitory Kinases Acts on TOM Receptors, Channel, and Assembly Factors
Protein Import Activity as Sensor of Mitochondrial Stress and Dysfunction
Figure 4. Mitochondrial Quality Control and Stress Response
(A) Import and quality control of cleavable preproteins. The TIM23 complex cooperates with several machineries: the TOM complex, a supercomplex consisting of the respiratory chain complexes III and IV, and the presequence translocase-associated motor (PAM) with the central chaperone mtHsp70. Several proteases/peptidases involved in processing, quality control, and/or degradation of imported proteins are shown, including mitochondrial processing peptidase (MPP), intermediate cleaving peptidase (XPNPEP3/Icp55), mitochondrial intermediate peptidase (MIP/Oct1), mitochondrial rhomboid protease (PARL/Pcp1), and LON/Pim1 protease. (B) The transcription factor ATFS-1 contains dual targeting information, a mitochondrial targeting signal at the amino terminus, and a nuclear localization signal (NLS). In normal cells, ATFS-1 is efficiently imported into mitochondria and degraded by the Lon protease in the matrix. When under stress conditions the protein import activity of mitochondria is reduced (due to lower Δψ, impaired mtHsp70 activity, or peptides exported by the peptide transporter HAF-1), some ATFS-1 molecules accumulate in the cytosol and can be imported into the nucleus, leading to induction of an unfolded protein response (UPRmt).
Regulation of PINK1/Parkin-Induced Mitophagy by the Activity of the Mitochondrial Protein Import Machinery
Figure 5. Mitochondrial Dynamics and Disease
(A) In healthy cells, the kinase PINK1 is partially imported into mitochondria in a membrane potential (Δψ)-dependent manner and processed by the inner membrane rhomboid protease PARL, which cleaves within the transmembrane segment and generates a destabilizing N terminus, followed by retro-translocation of cleaved PINK1 into the cytosol and degradation by the ubiquitin-proteasome system (different views have been reported if PINK1 is first processed by MPP or not; Greene et al., 2012, Kato et al., 2013 and Yamano and Youle, 2013). Dissipation of Δψ in damaged mitochondria leads to an accumulation of unprocessed PINK1 at the TOM complex and the recruitment of the ubiquitin ligase Parkin to mitochondria. Mitofusin 2 is phosphorylated by PINK1 and likely functions as receptor for Parkin. Parkin mediates ubiquitination of mitochondrial outer membrane proteins (including mitofusins), leading to a degradation of damaged mitochondria by mitophagy. Mutations of PINK1 or Parkin have been observed in monogenic cases of Parkinson’s disease. (B) The inner membrane fusion protein OPA1/Mgm1 is present in long and short isoforms. A balanced formation of the isoforms is a prerequisite for the proper function of OPA1/Mgm1. The precursor of OPA1/Mgm1 is imported by the TOM and TIM23 complexes. A hydrophobic segment of the precursor arrests translocation in the inner membrane, and the amino-terminal targeting signal is cleaved by MPP, generating the long isoforms. In yeast mitochondria, the import motor PAM drives the Mgm1 precursor further toward the matrix such that a second hydrophobic segment is cleaved by the inner membrane rhomboid protease Pcp1, generating the short isoform (s-Mgm1). In mammals, the m-AAA protease is likely responsible for the balanced formation of long (L) and short (S) isoforms of OPA1. A further protease, OMA1, can convert long isoforms into short isoforms in particular under stress conditions, leading to an impairment of mitochondrial fusion and thus to fragmentation of mitochondria.
….
Mitochondrial research is of increasing importance for the molecular understanding of numerous diseases, in particular of neurodegenerative disorders. The well-established connection between the pathogenesis of Parkinson’s disease and mitochondrial protein import has been discussed above. Several observations point to a possible connection of mitochondrial protein import with the pathogenesis of Alzheimer’s disease, though a direct role of mitochondria has not been demonstrated so far. The amyloid-β peptide (Aβ), which is generated from the amyloid precursor protein (APP), was found to be imported into mitochondria by the TOM complex, to impair respiratory activity, and to enhance ROS generation and fragmentation of mitochondria (Hansson Petersen et al., 2008, Ittner and Götz, 2011 and Itoh et al., 2013). An accumulation of APP in the TOM and TIM23 import channels has also been reported (Devi et al., 2006). The molecular mechanisms of how mitochondrial activity and dynamics may be altered by Aβ (and possibly APP) and how mitochondrial alterations may impact on the pathogenesis of Alzheimer’s disease await further analysis.
It is tempting to speculate that regulatory changes in mitochondrial protein import may be involved in tumor development. Cancer cells can shift their metabolism from respiration toward glycolysis (Warburg effect) (Warburg, 1956, Frezza and Gottlieb, 2009, Diaz-Ruiz et al., 2011 and Nunnari and Suomalainen, 2012). A glucose-induced downregulation of import of metabolite carriers into mitochondria may represent one of the possible mechanisms during metabolic shift to glycolysis. Such a mechanism has been shown for the carrier receptor Tom70 in yeast mitochondria (Schmidt et al., 2011). A detailed analysis of regulation of mitochondrial preprotein translocases in healthy mammalian cells as well as in cancer cells will represent an important task for the future.
Conclusion
In summary, the concept of the “mitochondrial protein import machinery as regulatory hub” will promote a rapidly developing field of interdisciplinary research, ranging from studies on molecular mechanisms to the analysis of mitochondrial diseases. In addition to identifying distinct regulatory mechanisms, a major challenge will be to define the interactions between different machineries and regulatory processes, including signaling networks, preprotein translocases, bioenergetic complexes, and machineries regulating mitochondrial membrane dynamics and contact sites, in order to understand the integrative system controlling mitochondrial biogenesis and fitness.
2.1.3.9 Exosome Transfer from Stromal to Breast Cancer Cells Regulates Therapy Resistance Pathways
Exosome transfer from stromal to breast cancer cells instigates antiviral signaling
• RNA in exosomes activates antiviral STAT1 pathway through RIG-I
• STAT1 cooperates with NOTCH3 to expand therapy-resistant cells
• Antiviral/NOTCH3 pathways predict NOTCH activity and resistance in primary tumors
Summary
Stromal communication with cancer cells can influence treatment response. We show that stromal and breast cancer (BrCa) cells utilize paracrine and juxtacrine signaling to drive chemotherapy and radiation resistance. Upon heterotypic interaction, exosomes are transferred from stromal to BrCa cells. RNA within exosomes, which are largely noncoding transcripts and transposable elements, stimulates the pattern recognition receptor RIG-I to activate STAT1-dependent antiviral signaling. In parallel, stromal cells also activate NOTCH3 on BrCa cells. The paracrine antiviral and juxtacrine NOTCH3 pathways converge as STAT1 facilitates transcriptional responses to NOTCH3 and expands therapy-resistant tumor-initiating cells. Primary human and/or mouse BrCa analysis support the role of antiviral/NOTCH3 pathways in NOTCH signaling and stroma-mediated resistance, which is abrogated by combination therapy with gamma secretase inhibitors. Thus, stromal cells orchestrate an intricate crosstalk with BrCa cells by utilizing exosomes to instigate antiviral signaling. This expands BrCa subpopulations adept at resisting therapy and reinitiating tumor growth.
stromal-communication-with-cancer-cells
Graphical Abstract
2.1.3.10 Emerging concepts in bioenergetics and cancer research
The field of energy metabolism dramatically progressed in the last decade, owing to a large number of cancer studies, as well as fundamental investigations on related transcriptional networks and cellular interactions with the microenvironment. The concept of metabolic flexibility was clarified in studies showing the ability of cancer cells to remodel the biochemical pathways of energy transduction and linked anabolism in response to glucose, glutamine or oxygen deprivation. A clearer understanding of the large-scale bioenergetic impact of C-MYC, MYCN, KRAS and P53 was obtained, along with its modification during the course of tumor development. The metabolic dialog between different types of cancer cells, but also with the stroma, also complexified the understanding of bioenergetics and raised the concepts of metabolic symbiosis and reverse Warburg effect. Signaling studies revealed the role of respiratory chain-derived reactive oxygen species for metabolic remodeling and metastasis development. The discovery of oxidative tumors in human and mice models related to chemoresistance also changed the prevalent view of dysfunctional mitochondria in cancer cells. Likewise, the influence of energy metabolism-derived oncometabolites emerged as a new means of tumor genetic regulation. The knowledge obtained on the multi-site regulation of energy metabolism in tumors was translated to cancer preclinical studies, supported by genetic proof of concept studies targeting LDHA, HK2, PGAM1, or ACLY. Here, we review those different facets of metabolic remodeling in cancer, from its diversity in physiology and pathology, to the search of the genetic determinants, the microenvironmental regulators and pharmacological modulators.
2.1.3.11 Protecting the mitochondrial powerhouse
M Scheibye-Knudsen, EF Fang, DL Croteau, DM Wilson III, VA Bohr
Trends in Cell Biol, Mar 2015; 25(3):158–170
Highlights
Mitochondrial maintenance is essential for cellular and organismal function.
• Maintenance includes reactive oxygen species (ROS) regulation, DNA repair, fusion–fission, and mitophagy.
• Loss of function of these pathways leads to disease.
Mitochondria are the oxygen-consuming power plants of cells. They provide a critical milieu for the synthesis of many essential molecules and allow for highly efficient energy production through oxidative phosphorylation. The use of oxygen is, however, a double-edged sword that on the one hand supplies ATP for cellular survival, and on the other leads to the formation of damaging reactive oxygen species (ROS). Different quality control pathways maintain mitochondria function including mitochondrial DNA (mtDNA) replication and repair, fusion–fission dynamics, free radical scavenging, and mitophagy. Further, failure of these pathways may lead to human disease. We review these pathways and propose a strategy towards a treatment for these often untreatable disorders.
Discussion
Radoslav Bozov –
Larry, pyruvate is a direct substrate for synthesizing pyrimidine rings, as well as C-13 NMR study proven source of methyl groups on SAM! Think about what cancer cells care for – dis-regulated growth through ‘escaped’ mutability of proteins, ‘twisting’ pathways of ordered metabolism space-time wise! mtDNA is a back up, evolutionary primitive, however, primary system for pulling strings onto cell cycle events. Oxygen (never observed single molecule) pulls up electron negative light from emerging super rich energy carbon systems. Therefore, ATP is more acting like a neutralizer – resonator of space-energy systems interoperability! You cannot look at a compartment / space independently , as dimension always add 1 towards 3+1.
The Warburg discoveries from 1922 on, and the influence on metabolic studies for the next 50 years was immense, and then the revelations of the genetic code took precedence. Throughout this period, however, the brilliant work of Briton Chance, a giant of biochemistry at the University of Pennsylvania, opened new avenues of exploration that led to a recent resurgence in this vital need for answers in cancer research. The next two series of presentations will open up this resurgence of fundamental metabolic research in cancer and even neurodegenerative diseases.
2.1.2.1 Cancer Cell Metabolism. Warburg and Beyond
Described decades ago, the Warburg effect of aerobic glycolysis is a key metabolic hallmark of cancer, yet its significance remains unclear. In this Essay, we re-examine the Warburg effect and establish a framework for understanding its contribution to the altered metabolism of cancer cells.
It is hard to begin a discussion of cancer cell metabolism without first mentioning Otto Warburg. A pioneer in the study of respiration, Warburg made a striking discovery in the 1920s. He found that, even in the presence of ample oxygen, cancer cells prefer to metabolize glucose by glycolysis, a seeming paradox as glycolysis, when compared to oxidative phosphorylation, is a less efficient pathway for producing ATP (Warburg, 1956). The Warburg effect has since been demonstrated in different types of tumors and the concomitant increase in glucose uptake has been exploited clinically for the detection of tumors by fluorodeoxyglucose positron emission tomography (FDG-PET). Although aerobic glycolysis has now been generally accepted as a metabolic hallmark of cancer, its causal relationship with cancer progression is still unclear. In this Essay, we discuss the possible drivers, advantages, and potential liabilities of the altered metabolism of cancer cells (Figure 1). Although our emphasis on the Warburg effect reflects the focus of the field, we would also like to encourage a broader approach to the study of cancer metabolism that takes into account the contributions of all interconnected small molecule pathways of the cell.
Figure 1. The Altered Metabolism of Cancer Cells
Drivers (A and B). The metabolic derangements in cancer cells may arise either from the selection of cells that have adapted to the tumor microenvironment or from aberrant signaling due to oncogene activation. The tumor microenvironment is spatially and temporally heterogeneous, containing regions of low oxygen and low pH (purple). Moreover, many canonical cancer-associated signaling pathways induce metabolic reprogramming. Target genes activated by hypoxia inducible factor (HIF) decrease the dependence of the cell on oxygen, whereas Ras, Myc, and Akt can also upregulate glucose consumption and glycolysis. Loss of p53 may also recapitulate the features of the Warburg effect, that is, the uncoupling of glycolysis from oxygen levels. Advantages (C–E). The altered metabolism of cancer cells is likely to imbue them with several proliferative and survival advantages, such as enabling cancer cells to execute the biosynthesis of macromolecules (C), to avoid apoptosis (D), and to engage in local metabolite-based paracrine and autocrine signaling (E). Potential Liabilities (F and G). This altered metabolism, however, may also confer several vulnerabilities on cancer cells. For example, an upregulated metabolism may result in the build up of toxic metabolites, including lactate and noncanonical nucleotides, which must be disposed of (F). Moreover, cancer cells may also exhibit a high energetic demand, for which they must either increase flux through normal ATP-generating processes, or else rely on an increased diversity of fuel sources (G).
The Tumor Microenvironment Selects for Altered Metabolism
One compelling idea to explain the Warburg effect is that the altered metabolism of cancer cells confers a selective advantage for survival and proliferation in the unique tumor microenvironment. As the early tumor expands, it outgrows the diffusion limits of its local blood supply, leading to hypoxia and stabilization of the hypoxia-inducible transcription factor, HIF. HIF initiates a transcriptional program that provides multiple solutions to hypoxic stress (reviewed in Kaelin and Ratcliffe, 2008). Because a decreased dependence on aerobic respiration becomes advantageous, cell metabolism is shifted toward glycolysis by the increased expression of glycolytic enzymes, glucose transporters, and inhibitors of mitochondrial metabolism. In addition, HIF stimulates angiogenesis (the formation of new blood vessels) by upregulating several factors, including most prominently vascular endothelial growth factor (VEGF).
The oxygen levels within a tumor vary both spatially and temporally, and the resulting rounds of fluctuating oxygen levels potentially select for tumors that constitutively upregulate glycolysis. Interestingly, with the possible exception of tumors that have lost the von Hippel-Lindau protein (VHL), which normally mediates degradation of HIF, HIF is still coupled to oxygen levels, as evident from the heterogeneity of HIF expression within the tumor microenvironment (Wiesener et al., 2001; Zhong et al., 1999). Therefore, the Warburg effect—that is, an uncoupling of glycolysis from oxygen levels—cannot be explained solely by upregulation of HIF.
Recent work has demonstrated that the key components of the Warburg effect—increased glucose consumption, decreased oxidative phosphorylation, and accompanying lactate production—are also distinguishing features of oncogene activation. The signaling molecule Ras, a powerful oncogene when mutated, promotes glycolysis (reviewed in Dang and Semenza, 1999; Samanathan et al., 2005). Akt kinase, a well-characterized downstream effector of insulin signaling, reprises its role in glucose uptake and utilization in the cancer setting (reviewed in Manning and Cantley, 2007), whereas the Myc transcription factor upregulates the expression of various metabolic genes (reviewed in Gordan et al., 2007). The most parsimonious route to tumorigenesis may be activation of key oncogenic nodes that execute a proliferative program, of which metabolism may be one important arm. Moreover, regulation of metabolism is not exclusive to oncogenes. Loss of the tumor suppressor protein p53 prevents expression of the gene encoding SCO2 (the synthesis of cytochrome c oxidase protein), which interferes with the function of the mitochondrial respiratory chain (Matoba et al., 2006). A second p53 effector, TIGAR (TP53-induced glycolysis and apoptosis regulator), inhibits glycolysis by decreasing levels of fructose-2,6-bisphosphate, a potent stimulator of glycolysis and inhibitor of gluconeogenesis (Bensaad et al., 2006). Other work also suggests that p53-mediated regulation of glucose metabolism may be dependent on the transcription factor NF-κB (Kawauchi et al., 2008).
It has been shown that inhibition of lactate dehydrogenase A (LDH-A) prevents the Warburg effect and forces cancer cells to revert to oxidative phosphorylation in order to reoxidize NADH and produce ATP (Fantin et al., 2006; Shim et al., 1997). While the cells are respiratory competent, they exhibit attenuated tumor growth, suggesting that aerobic glycolysis might be essential for cancer progression. In a primary fibroblast cell culture model of stepwise malignant transformation through overexpression of telomerase, large and small T antigen, and the H-Ras oncogene, increasing tumorigenicity correlates with sensitivity to glycolytic inhibition. This finding suggests that the Warburg effect might be inherent to the molecular events of transformation (Ramanathan et al., 2005). However, the introduction of similar defined factors into human mesenchymal stem cells (MSCs) revealed that transformation can be associated with increased dependence on oxidative phosphorylation (Funes et al., 2007). Interestingly, when introduced in vivo these transformed MSCs do upregulate glycolytic genes, an effect that is reversed when the cells are explanted and cultured under normoxic conditions. These contrasting models suggest that the Warburg effect may be context dependent, in some cases driven by genetic changes and in others by the demands of the microenvironment. Regardless of whether the tumor microenvironment or oncogene activation plays a more important role in driving the development of a distinct cancer metabolism, it is likely that the resulting alterations confer adaptive, proliferative, and survival advantages on the cancer cell.
Altered Metabolism Provides Substrates for Biosynthetic Pathways
Although studies in cancer metabolism have largely been energy-centric, rapidly dividing cells have diverse requirements. Proliferating cells require not only ATP but also nucleotides, fatty acids, membrane lipids, and proteins, and a reprogrammed metabolism may serve to support synthesis of macromolecules. Recent studies have shown that several steps in lipid synthesis are required for and may even actively promote tumorigenesis. Inhibition of ATP citrate lyase, the distal enzyme that converts mitochondrial-derived citrate into cytosolic acetyl coenzyme A, the precursor for many lipid species, prevents cancer cell proliferation and tumor growth (Hatzivassiliou et al., 2005). Fatty acid synthase, expressed at low levels in normal tissues, is upregulated in cancer and may also be required for tumorigenesis (reviewed in Menendez and Lupu, 2007). Furthermore, cancer cells may also enhance their biosynthetic capabilities by expressing a tumor-specific form of pyruvate kinase (PK), M2-PK. Pyruvate kinase catalyzes the third irreversible reaction of glycolysis, the conversion of phosphoenolpyruvate (PEP) to pyruvate. Surprisingly, the M2-PK of cancer cells is thought to be less active in the conversion of PEP to pyruvate and thus less efficient at ATP production (reviewed in Mazurek et al., 2005). A major advantage to the cancer cell, however, is that the glycolytic intermediates upstream of PEP might be shunted into synthetic processes.
Biosynthesis, in addition to causing an inherent increase in ATP demand in order to execute synthetic reactions, should also cause a decrease in ATP supply as various glycolytic and Krebs cycle intermediates are diverted. Lipid synthesis, for example, requires the cooperation of glycolysis, the Krebs cycle, and the pentose phosphate shunt. As pyruvate must enter the mitochondria in this case, it avoids conversion to lactate and therefore cannot contribute to glycolysis-derived ATP. Moreover, whereas increased biosynthesis may explain the glucose hunger of cancer cells, it cannot explain the increase in lactic acid production originally described by Warburg, suggesting that lactate must also result from the metabolism of non-glucose substrates. Recently, it has been demonstrated that glutamine may be metabolized by the citric acid cycle in cancer cells and converted into lactate, producing NADPH for lipid biosynthesis and oxaloacetate for replenishment of Krebs cycle intermediates (DeBerardinis et al., 2007).
Metabolic Pathways Regulate Apoptosis
In addition to involvement in proliferation, altered metabolism may promote another cancer-essential function: the avoidance of apoptosis. Loss of the p53 target TIGAR sensitizes cancer cells to apoptosis, most likely by causing an increase in reactive oxygen species (Bensaad et al., 2006). On the other hand, overexpression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) prevents caspase-independent cell death, presumably by stimulating glycolysis, increasing cellular ATP levels, and promoting autophagy (Colell et al., 2007). Whether or not GAPDH plays a physiological role in the regulation of cell death remains to be determined. Intriguingly, Bonnet et al. (2007) have reported that treating cancer cells with dichloroacetate (DCA), a small molecule inhibitor of pyruvate dehydrogenase kinase, has striking effects on their survival and on xenograft tumor growth.
DCA, a currently approved treatment for congenital lactic acidosis, activates oxidative phosphorylation and promotes apoptosis by two mechanisms. First, increased flux through the electron transport chain causes depolarization of the mitochondrial membrane potential (which the authors found to be hyperpolarized specifically in cancer cells) and release of the apoptotic effector cytochrome c. Second, an increase in reactive oxygen species generated by oxidative phosphorylation upregulates the voltage-gated K+ channel, leading to potassium ion efflux and caspase activation. Their work suggests that cancer cells may shift their metabolism to glycolysis in order to prevent cell death and that forcing cancer cells to respire aerobically can counteract this adaptation.
Cancer Cells May Signal Locally in the Tumor Microenvironment
Cancer cells may rewire metabolic pathways to exploit the tumor microenvironment and to support cancer-specific signaling. Without access to the central circulation, it is possible that metabolites can be concentrated locally and reach suprasystemic levels, allowing cancer cells to engage in metabolite-mediated autocrine and paracrine signaling that does not occur in normal tissues. So called androgen-independent prostate cancers may only be independent from exogenous, adrenal-synthesized androgens. Androgen-independent prostate cancer cells still express the androgen receptor and may be capable of autonomously synthesizing their own androgens (Stanbrough et al., 2006).
Metabolism as an Upstream Modulator of Signaling Pathways
Not only is metabolism downstream of oncogenic pathways, but an altered upstream metabolism may affect the activity of signaling pathways that normally sense the state of the cell. Individuals with inherited mutations in succinate dehydrogenase and fumarate hydratase develop highly angiogenic tumors, not unlike those exhibiting loss of the VHL tumor suppressor protein that acts upstream of HIF (reviewed in Kaelin and Ratcliffe, 2008). The mechanism of tumorigenesis in these cancer syndromes is still contentious. However, it has been proposed that loss of succinate dehydrogenase and fumarate hydratase causes an accumulation of succinate or fumarate, respectively, leading to inhibition of the prolyl hydroxylases that mark HIF for VHL-mediated degradation (Isaacs et al., 2005; Pollard et al., 2005; Selak et al., 2005). In this rare case, succinate dehydrogenase and fumarate hydratase are acting as bona fide tumor suppressors.
There are many complex questions to be answered: Is it possible that cancer cells exhibit “metabolite addiction”? Are there unique cancer-specific metabolic pathways, or combinations of pathways, utilized by the cancer cell but not by normal cells? Are different stages of metabolic adaptations required for the cancer cell to progress from the primary tumor stage to invasion to metastasis? How malleable is cancer metabolism?
2.1.2.2 Cancer metabolism. The Warburg effect today
One of the first studies on the energy metabolism of a tumor was carried out, in 1922, in the laboratory of Otto Warburg. He established that cancer cells exhibited a specific metabolic pattern, characterized by a shift from respiration to fermentation, which has been later named the Warburg effect. Considerable work has been done since then, deepening our understanding of the process, with consequences for diagnosis and therapy. This review presents facts and perspectives on the Warburg effect for the 21st century.
Research highlights
► Warburg first established a tumor metabolic pattern in the 1920s. ► Tumors’ increased glucose uptake has been studied since then. ► Cancer bioenergetics’ study provides insights in all its hallmarks. ► New cancer diagnostic and therapeutic techniques focus on cancer metabolism.
Introduction
Contestation to Warburg’s ideas
Glucose’s uptake and intracellular fates
Lactate production and induced acidosis
Hypoxia
Impairment of mitochondrial function
Tumour microenvironment
Proliferating versus cancer cells
More on cancer bioenergetics – integration of metabolism
Perspectives
2.1.2.3 New aspects of the Warburg effect in cancer cell biology
Altered cellular metabolism is a defining feature of cancer [1]. The best studied metabolic phenotype of cancer is aerobic glycolysis–also known as the Warburg effect–characterized by increased metabolism of glucose to lactate in the presence of sufficient oxygen. Interest in the Warburg effect has escalated in recent years due to the proven utility of FDG-PET for imaging tumors in cancer patients and growing evidence that mutations in oncogenes and tumor suppressor genes directly impact metabolism. The goals of this review are to provide an organized snapshot of the current understanding of regulatory mechanisms important for Warburg effect and its role in tumor biology. Since several reviews have covered aspects of this topic in recent years, we focus on newest contributions to the field and reference other reviews where appropriate.
Highlights
► This review discusses regulatory mechanisms that contribute to the Warburg effect in cancer. ► We list cancers for which FDG-PET has established applications as well as those cancers for which FDG-PET has not been established. ► PKM2 is highlighted as an important integrator of diverse cellular stimuli to modulate metabolic flux and cancer cell proliferation. ► We discuss how cancer metabolism can directly influence gene expression programs. ► Contribution of aerobic glycolysis to the cancer microenvironment and chemotherapeutic resistance/susceptibility is also discussed.
Regulation of the Warburg effect
PKM2 integrates diverse signals to modulate metabolic flux and cell proliferation
Fig. 1. PKM2 integrates diverse signals to modulate metabolic flux and cell proliferation
Metabolism can directly influence gene expression programs
Fig. 2. Metabolism can directly influence gene expression programs. A schematic representation of how metabolism can intrinsically influence epigenetics resulting in durable and heritable gene expression programs in progeny.
2.1.2.4 Choosing between glycolysis and oxidative phosphorylation. A tumor’s dilemma
A considerable amount of knowledge has been produced during the last five years on the bioenergetics of cancer cells, leading to a better understanding of the regulation of energy metabolism during oncogenesis, or in adverse conditions of energy substrate intermittent deprivation. The general enhancement of the glycolytic machinery in various cancer cell lines is well described and recent analyses give a better view of the changes in mitochondrial oxidative phosphorylation during oncogenesis. While some studies demonstrate a reduction of oxidative phosphorylation (OXPHOS) capacity in different types of cancer cells, other investigations revealed contradictory modifications with the upregulation of OXPHOS components and a larger dependency of cancer cells on oxidative energy substrates for anabolism and energy production. This apparent conflictual picture is explained by differences in tumor size, hypoxia, and the sequence of oncogenes activated. The role of p53, C-MYC, Oct and RAS on the control of mitochondrial respiration and glutamine utilization has been explained recently on artificial models of tumorigenesis. Likewise, the generation of induced pluripotent stem cells from oncogene activation also showed the role of C-MYC and Oct in the regulation of mitochondrial biogenesis and ROS generation. In this review article we put emphasis on the description of various bioenergetic types of tumors, from exclusively glycolytic to mainly OXPHOS, and the modulation of both the metabolic apparatus and the modalities of energy substrate utilization according to tumor stage, serial oncogene activation and associated or not fluctuating microenvironmental substrate conditions. We conclude on the importance of a dynamic view of tumor bioenergetics.
Research Highlights
►The bioenergetics of cancer cells differs from normals. ►Warburg hypothesis is not verified in tumors using mitochondria to synthesize ATP. ►Different oncogenes can either switch on or switch off OXPHOS. ►Bioenergetic profiling is a prerequisite to metabolic therapy. ►Aerobic glycolysis and OXPHOS cooperate during cancer progression.
Cancer cell variable bioenergetics
Cancer cells exhibit profound genetic, bioenergetic and histological differences as compared to their non-transformed counterpart. All these modifications are associated with unlimited cell growth, inhibition of apoptosis and intense anabolism. Transformation from a normal cell to a malignant cancer cell is a multi-step pathogenic process which includes a permanent interaction between cancer gene activation (oncogenes and/or tumor-suppressor genes), metabolic reprogramming and tumor-induced changes in microenvironment. As for the individual genetic mapping of human tumors, their metabolic characterization (metabolic–bioenergetic profiling) has evidenced a cancer cell-type bioenergetic signature which depends on the history of the tumor, as composed by the sequence of oncogenes activated and the confrontation to intermittent changes in oxygen, glucose and amino-acid delivery.
In the last decade, bioenergetic studies have highlighted the variability among cancer types and even inside a cancer type as regards to the mechanisms and the substrates preferentially used for deriving the vital energy. The more popular metabolic remodeling described in tumor cells is an increase in glucose uptake, the enhancement of glycolytic capacity and a high lactate production, along with the absence of respiration despite the presence of high oxygen concentration (Warburg effect) [1]. To explain this abnormal bioenergetic phenotype pioneering hypotheses proposed the impairment of mitochondrial function in rapidly growing cancer cells [2].
Although the increased consumption of glucose by tumor cells was confirmed in vivo by positron emission tomography (PET) using the glucose analog 2-(18F)-fluoro-2-deoxy-d-glucose (FDG), the actual utilization of glycolysis and oxidative phosphorylation (OXPHOS) cannot be evaluated with this technique. Nowadays, Warburg’s “aerobic-glycolysis” hypothesis has been challenged by a growing number of studies showing that mitochondria in tumor cells are not inactive per se but operate at low capacity [3] or, in striking contrast, supply most of the ATP to the cancer cells [4]. Intense glycolysis is effectively not observed in all tumor types. Indeed not all cancer cells grow fast and intense anabolism is not mandatory for all cancer cells. Rapidly growing tumor cells rely more on glycolysis than slowly growing tumor cells. This is why a treatment with bromopyruvate, for example is very efficient only on rapidly growing cells and barely useful to decrease the growth rate of tumor cells when their normal proliferation is slow. Already in 1979, Reitzer and colleagues published an article entitled “Evidence that glutamine, not sugar, is the major energy source for cultured Hela cells”, which demonstrated that oxidative phosphorylation was used preferentially to produce ATP in cervical carcinoma cells [5]. Griguer et al. also identified several glioma cell lines that were highly dependent on mitochondrial OXPHOS pathway to produce ATP [6]. Furthermore, a subclass of glioma cells which utilize glycolysis preferentially (i.e., glycolytic gliomas) can also switch from aerobic glycolysis to OXPHOS under limiting glucose conditions [7] and [8], as observed in cervical cancer cells, breast carcinoma cells, hepatoma cells and pancreatic cancer cells [9], [10] and [11]. This flexibility shows the interplay between glycolysis and OXPHOS to adapt the mechanisms of energy production to microenvironmental changes as well as differences in tumor energy needs or biosynthetic activity. Herst and Berridge also demonstrated that a variety of human and mouse leukemic and tumor cell lines (HL60, HeLa, 143B, and U937) utilize mitochondrial respiration to support their growth [12]. Recently, the measurement of OXPHOS contribution to the cellular ATP supply revealed that mitochondria generate 79% of the cellular ATP in HeLa cells, and that upon hypoxia this contribution is reduced to 30% [4]. Again, metabolic flexibility is used to survive under hypoxia. All these studies demonstrate that mitochondria are efficient to synthesize ATP in a large variety of cancer cells, as reviewed by Moreno-Sanchez [13]. Despite the observed reduction of the mitochondrial content in tumors [3], [14], [15], [16], [17], [18] and [19], cancer cells maintain a significant level of OXPHOS capacity to rapidly switch from glycolysis to OXPHOS during carcinogenesis. This switch is also observed at the level of glutamine oxidation which can occur through two modes, “OXPHOS-linked” or “anoxic”, allowing to derive energy from glutamine or serine regardless of hypoxia or respiratory chain reduced activity [20].
While glutamine, glycine, alanine, glutamate, and proline are typically oxidized in normal and tumor mitochondria, alternative substrate oxidations may also contribute to ATP supply by OXPHOS. Those include for instance the oxidation of fatty-acids, ketone bodies, short-chain carboxylic acids, propionate, acetate and butyrate (as recently reviewed in [21]).
Varying degree of mitochondrial utilization during tumorigenesis
In vivo metabolomic analyses suggest the existence of a continuum of bioenergetic remodeling in rat tumors according to tumor size and its rate of growth [22]. Peter Vaupel’s group showed that small tumors were characterized by a low conversion of glucose to lactate whereas the conversion of glutamine to lactate was high. In medium sized tumors the flow of glucose to lactate as well as oxygen utilization was increased whereas glutamine and serine consumption were reduced. At this stage tumor cells started with glutamate and alanine production. Large tumors were characterized by a low oxygen and glucose supply but a high glucose and oxygen utilization rate. The conversion of glucose to glycine, alanine, glutamate, glutamine, and proline reached high values and the amino acids were released [22]. Certainly, in the inner layers constituting solid tumors, substrate and oxygen limitation is frequently observed. Experimental studies tried to reproduce these conditions in vitro and revealed that nutrients and oxygen limitation does not affect OXPHOS and cellular ATP levels in human cervix tumor [23]. Furthermore, the growth of HeLa cells, HepG2 cells and HTB126 (breast cancer) in aglycemia and/or hypoxia even triggered a compensatory increase in OXPHOS capacity, as discussed above. Yet, the impact of hypoxia might be variable depending on cell type and both the extent and the duration of oxygen limitation.
In two models of sequential oncogenesis, the successive activation of specific oncogenes in non-cancer cells evidenced the need for active OXPHOS to pursue tumorigenesis. Funes et al. showed that the transformation of human mesenchymal stem cells increases their dependency on OXPHOS for energy production [24], while Ferbeyre et al. showed that cells expressing oncogenic RAS display an increase in mitochondrial mass, mitochondrial DNA, and mitochondrial production of reactive oxygen species (ROS) prior to the senescent cell cycle arrest [25]. Such observations suggest that waves of gene regulation could suppress and then restore OXPHOS in cancer cells during tumorigenesis [20]. Therefore, the definition of cancer by Hanahan and Weinberg [26] restricted to six hallmarks (1—self-sufficiency in growth signals, 2—insensitivity to growth-inhibitory (antigrowth) signals, 3—evasion of programmed cell death (apoptosis), 4—limitless replicative potential, 5—sustained angiogenesis, and 6—tissue invasion and metastases) should also include metabolic reprogramming, as the seventh hallmark of cancer. This amendment was already proposed by Tennant et al. in 2009 [27]. In 2006, the review Science published a debate on the controversial views of Warburg theory [28], in support of a more realistic description of cancer cell’s variable bioenergetic profile. The pros think that high glycolysis is an obligatory feature of human tumors, while the cons propose that high glycolysis is not exclusive and that tumors can use OXPHOS to derive energy. A unifying theory closer to reality might consider that OXPHOS and glycolysis cooperate to sustain energy needs along tumorigenesis [20]. The concept of oxidative tumors, against Warburg’s proposal, was introduced by Guppy and colleagues, based on the observation that breast cancer cells can generate 80% of their ATP by the mitochondrion [29]. The comparison of different cancer cell lines and excised tumors revealed a variety of cancer cell’s bioenergetic signatures which raised the question of the mechanisms underlying tumor cell metabolic reprogramming, and the relative contribution of oncogenesis and microenvironment in this process. It is now widely accepted that rapidly growing cancer cells within solid tumors suffer from a lack of oxygen and nutrients as tumor grows. In such situation of compromised energy substrate delivery, cancer cell’s metabolic reprogramming is further used to sustain anabolism (Fig. 1), through the deviation of glycolysis, Krebs cycle truncation and OXPHOS redirection toward lipid and protein synthesis, as needed to support uncontrolled tumor growth and survival [30] and [31]. Again, these features are not exclusive to all tumors, as Krebs cycle truncation was only observed in some cancer cells, while other studies indicated that tumor cells can maintain a complete Krebs cycle [13] in parallel with an active citrate efflux. Likewise, generalizations should be avoided to prevent over-interpretations.
Fig. 1. Energy metabolism at the crossroad between catabolism and anabolism.
Energy metabolism at the crossroad between catabolism and anabolism.
The oncogene C-MYC participate to these changes via the stimulation of glutamine utilization through the coordinate expression of genes necessary for cells to engage in glutamine catabolism [30]. According to Newsholme EA and Board M [32] both glycolysis and glutaminolysis not only serve for ATP production, but also provide precious metabolic intermediates such as glucose-6-phosphate, ammonia and aspartate required for the synthesis of purine and pyrimidine nucleotides (Fig. 1). In this manner, the observed apparent excess in the rates of glycolysis and glutaminolysis as compared to the requirement for energy production could be explained by the need for biosynthetic processes. Yet, one should not reduce the shift from glycolysis to OXPHOS utilization to the sole activation of glutaminolysis, as several other energy substrates can be used by tumor mitochondria to generate ATP [21]. The contribution of these different fuels to ATP synthesis remains poorly investigated in human tumors.
The metabolism of pre-cancer cells and its ongoing modulation by carcinogenesis
At the beginning of cancer, there might have been a cancer stem cell hit by an oncogenic event, such as alterations in mitogen signaling to extracellular growth factor receptors (EGFR), oncogenic activation of these receptors, or oncogenic alterations of downstream targets in the pathways that leads to cell proliferation (RAS–Raf–ERK and PI3K–AKT, both leading to m-TOR activation stimulating cell growth). Alterations of checkpoint genes controlling the cell cycle progression like Rb also participate in cell proliferation (Fig. 2) and this re-entry in the cell cycle implies three major needs to fill in: 1) supplying enough energy to grow and 2) synthesize building blocks de novo and 3) keep vital oxygen and nutrients available. However, the bioenergetic status of the pre-cancer cell could determine in part the evolution of carcinogenesis, as shown on mouse embryonic stem cells. In this study, Schieke et al. showed that mitochondrial energy metabolism modulates both the differentiation and tumor formation capacity of mouse embryonic stem cells [37]. The idea that cancer derives from a single cell, known as the cancer stem cell hypothesis, was introduced by observations performed on leukemia which appeared to be organized as origination from a primitive hematopoietic cell [38]. Nowadays cancer stem cells were discovered for all types of tumors [39], [40], [41] and [42], but little is known of their bioenergetic properties and their metabolic adaptation to the microenvironment. This question is crucial as regards the understanding of what determines the wide variety of cancer cell’s metabolic profile.
Impact of different oncogenes on tumor progression and energy metabolism remodeling.
Fig. 2. Impact of different oncogenes on tumor progression and energy metabolism remodeling.
The analysis of the metabolic changes that occur during the transformation of adult mesenchymal stem cells revealed that these cells did not switch to aerobic glycolysis, but their dependency on OXPHOS was even increased [24]. Hence, mitochondrial energy metabolism could be critical for tumorigenesis, in contrast with Warburg’s hypothesis. As discussed above, the oncogene C-MYC also stimulates OXPHOS [30]. Furthermore, it was recently demonstrated that cells chronically treated with oligomycin repress OXPHOS and produce larger tumors with higher malignancy [19]. Likewise, alteration of OXPHOS by mutations in mtDNA increases tumorigenicity in different types of cancer cells [43], [44] and [45].
Recently, it was proposed that mitochondrial energy metabolism is required to generate reactive oxygen species used for the carcinogenetic process induced by the K-RAS mutation [46]. This could explain the large number of mitochondrial DNA mutations found in several tumors. The analysis of mitochondria in human embryonic cells which derive energy exclusively from anaerobic glycolysis have demonstrated an immature mitochondrial network characterized by few organelles with poorly developed cristae and peri-nuclear distribution [47] and [48]. The generation of human induced pluripotent stem cell by the introduction of different oncogenes as C-MYC and Oct4 reproduced this reduction of mitochondrial OXPHOS capacity[49] and [50]. This indicates again the impact of oncogenes on the control of OXPHOS and might explain the existence of pre-cancer stem cells with different bioenergetic backgrounds, as modeled by variable sequences of oncogene activation. Accordingly, the inhibition of mitochondrial respiratory chain has been recently found associated with enhancement of hESC pluripotency [51].
Based on the experimental evidence discussed above, one can argue that 1) glycolysis is indeed a feature of several tumors and associates with faster growth in high glucose environment, but 2) active OXPHOS is also an important feature of (other) tumors taken at a particular stage of carcinogenesis which might be more advantageous than a “glycolysis-only” type of metabolism in conditions of intermittent shortage in glucose delivery. The metabolic apparatus of cancer cells is not fixed during carcinogenesis and might depend both on the nature of the oncogenes activated and the microenvironment. It was indeed shown that cancer cells with predominant glycolytic metabolism present a higher malignancy when submitted to carcinogenetic induction and analysed under fixed experimental conditions of high glucose [19]. Yet, if one grows these cells in a glucose-deprived medium they shift their metabolism toward predominant OXPHOS, as shown in HeLa cells and other cell types [9]. Therefore, one might conclude that glycolytic cells have a higher propensity to generate aggressive tumors when glucose availability is high. However, these cells can become OXPHOS during tumor progression [24] and [52]. All these observations indicate again the importance of maintaining an active OXPHOS metabolism to permit evolution of both embryogenesis and carcinogenesis, which emphasizes the importance of targeting mitochondria to alter this malignant process.
Oncogenes and the modulation of energy metabolism
Several oncogenes and associated proteins such as HIF-1α, RAS, C-MYC, SRC, and p53 can influence energy substrate utilization by affecting cellular targets, leading to metabolic changes that favor cancer cell survival, independently of the control of cell proliferation. These oncogenes stimulate the enhancement of aerobic glycolysis, and an increasing number of studies demonstrate that at least some of them can also target directly the OXPHOS machinery, as discussed in this article (Fig. 2). For instance, C-MYC can concurrently drive aerobic glycolysis and/or OXPHOS according to the tumor cell microenvironment, via the expression of glycolytic genes or the activation of mitochondrial oxidation of glutamine [53]. The oncogene RAS has been shown to increase OXPHOS activity in early transformed cells [24], [52] and [54] and p53 modulates OXPHOS capacity via the regulation of cytochrome c oxidase assembly [55]. Hence, carcinogenic p53 deficiency results in a decreased level of COX2 and triggers a shift toward anaerobic metabolism. In this case, lactate synthesis is increased, but cellular ATP levels remain stable [56]. The p53-inducible isoform of phosphofructokinase, termed TP53-induced glycolysis and apoptotic regulator, TIGAR, a predominant phosphatase activity isoform of PFK-2, has also been identified as an important regulator of energy metabolism in tumors [57].
Tumor specific isoforms (or mutated forms) of energy genes
Tumors are generally characterized by a modification of the glycolytic system where the level of some glycolytic enzymes is increased, some fetal-like isozymes with different kinetic and regulatory properties are produced, and the reverse and back-reactions of the glycolysis are strongly reduced [60]. The GAPDH marker of the glycolytic pathway is also increased in breast, gastric, lung, kidney and colon tumors [18], and the expression of glucose transporter GLUT1 is elevated in most cancer cells. The group of Cuezva J.M. developed the concept of cancer bioenergetic signature and of bioenergetic index to describe the metabolic profile of cancer cells and tumors [18], [61], [64], [65]. This signature describes the changes in the expression level of proteins involved in glycolysis and OXPHOS, while the BEC index gives a ratio of OXPHOS protein content to glycolytic protein content, in good correlation with cancer prognostic[61]. Recently, this group showed that the beta-subunit of the mitochondrial F1F0-ATP synthase is downregulated in a large number of tumors, thus contributing to the Warburg effect [64] and [65]. It was also shown that IF1 expression levels were increased in hepatocellular carcinomas, possibly to prevent the hydrolysis of glytolytic ATP [66]. Numerous changes occur at the level of OXPHOS and mitochondrial biogenesis in human tumors, as we reviewed previously [67]. Yet the actual impact of these changes in OXPHOS protein expression level or catalytic activities remains to be evaluated on the overall fluxes of respiration and ATP synthesis. Indeed, the metabolic control analysis and its extension indicate that it is often required to inhibit activity beyond a threshold of 70–85% to affect the metabolic fluxes [68] and [69]. Another important feature of cancer cells is the higher level of hexokinase II bound to mitochondrial membrane (50% in tumor cells). A study performed on human gliomas (brain) estimated the mitochondrial bound HK fraction (mHK) at 69% of total, as compared to 9% for normal brain [70]. This is consistent with the 5-fold amplification of the type II HK gene observed by Rempel et al. in the rapidly growing rat AS-30D hepatoma cell line, relative to normal hepatocytes [71]. HKII subcellular fractionation in cancer cells was described in several studies [72], [73] and [74]. The group led by Pete Pedersen explained that mHK contributes to (i) the high glycolytic capacity by utilizing mitochondrially regenerated ATP rather than cytosolic ATP (nucleotide channelling) and (ii) the lowering of OXPHOS capacity by limiting Pi and ADP delivery to the organelle [75] and [76].
All these observations are consistent with the increased rate of FDG uptake observed by PET in living tumors which could result from both an increase in glucose transport, and/or an increase in hexokinase activity. However, FDG is not a complete substrate for glycolysis (it is only transformed into FDG-6P by hexokinase before to be eliminated) and cannot be used to evidence a general increase in the glycolytic flux. Moreover, FDG-PET scan also gives false positive and false negative results, indicating that some tumors do not depend on, or do not have, an increased glycolytic capacity. The fast glycolytic system described above is further accommodated in cancer cells by an increase in the lactate dehydrogenase isoform A (LDH-A) expression level. This isoform presents a higher Vmax useful to prevent the inhibition of high glycolysis by its end product (pyruvate) accumulation. Recently, Fantin et al. showed that inhibition of LDH-A in tumors diminishes tumorigenicity and was associated with the stimulation of mitochondrial respiration [79]. The preferential expression of the glycolytic pyruvate kinase isoenzyme M2 (PKM2) in tumor cells, determines whether glucose is converted to lactate for regeneration of energy (active tetrameric form, Warburg effect) or used for the synthesis of cell building blocks (nearly inactive dimeric form) [80]. In the last five years, mutations in proteins of the respiratory system (SDH, FH) and of the TCA cycle (IDH1,2) leading to the accumulation of metabolite and the subsequent activation of HIF-1α were reported in a variety of human tumors [81], [82] and [83].
Tumor microenvironment modulates cancer cell’s bioenergetics
It was extensively described how hypoxia activates HIF-1α which stimulates in turn the expression of several glycolytic enzymes such as HK2, PFK, PGM, enolase, PK, LDH-A, MCT4 and glucose transporters Glut 1 and Glut 3. It was also shown that HIF-1α can reduce OXPHOS capacity by inhibiting mitochondrial biogenesis [14] and [15], PDH activity [87] and respiratory chain activity [88]. The low efficiency and uneven distribution of the vascular system surrounding solid tumors can lead to abrupt changes in oxygen (intermittent hypoxia) but also energy substrate delivery. .. The removal of glucose, or the inhibition of glycolysis by iodoacetate led to a switch toward glutamine utilization without delay followed by a rapid decrease in acid release. This illustrates once again how tumors and human cancer cell lines can utilize alternative energy pathway such as glutaminolysis to deal with glucose limitation, provided the presence of oxygen. It was also observed that in situations of glucose limitation, tumor derived-cells can adapt to survive by using exclusively an oxidative energy substrate [9] and [10]. This is typically associated with an enhancement of the OXPHOS system. … In summary, cancer cells can survive by using exclusively OXPHOS for ATP production, by altering significantly mitochondrial composition and form to facilitate optimal use of the available substrate (Fig. 3). Yet, glucose is needed to feed the pentose phosphate pathway and generate ribose essential for nucleotide biosynthesis. This raises the question of how cancer cells can survive in the growth medium which do not contain glucose (so-called “galactose medium” with dialysed serum [9]). In the OXPHOS mode, pyruvate, glutamate and aspartate can be derived from glutamine, as glutaminolysis can replenish Krebs cycle metabolic pool and support the synthesis of alanine and NADPH [31]. Glutamine is a major source for oxaloacetate (OAA) essential for citrate synthesis. Moreover, the conversion of glutamine to pyruvate is associated with the reduction of NADP+ to NADPH by malic enzyme. Such NADPH is a required electron donor for reductive steps in lipid synthesis, nucleotide metabolism and GSH reduction. In glioblastoma cells the malic enzyme flux was estimated to be high enough to supply all of the reductive power needed for lipid synthesis [31].
Fig. 3. Interplay between energy metabolism, oncogenes and tumor microenvironment during tumorigenesis (the “metabolic wave model”).
Interplay between energy metabolism, oncogenes and tumor microenvironment
While the mechanisms leading to the enhancement of glycolytic capacity in tumors are well documented, less is known about the parallel OXPHOS changes. Both phenomena could result from a selection of pre-malignant cells forced to survive under hypoxia and limited glucose delivery, followed by an adaptation to intermittent hypoxia, pseudo-hypoxia, substrate limitation and acidic environment. This hypothesis was first proposed by Gatenby and Gillies to explain the high glycolytic phenotype of tumors [91], [92] and [93], but several lines of evidence suggest that it could also be used to explain the mitochondrial modifications observed in cancer cells.
Aerobic glycolysis and mitochondria cooperate during cancer progression
Metabolic flexibility considers the possibility for a given cell to alternate between glycolysis and OXPHOS in response to physiological needs. Louis Pasteur found that in most mammalian cells the rate of glycolysis decreases significantly in the presence of oxygen (Pasteur effect). Moreover, energy metabolism of normal cell can vary widely according to the tissue of origin, as we showed with the comparison of five rat tissues[94]. During stem cell differentiation, cell proliferation induces a switch from OXPHOS to aerobic glycolysis which might generate ATP more rapidly, as demonstrated in HepG2 cells [95] or in non-cancer cells[96] and [97]. Thus, normal cellular energy metabolism can adapt widely according to the activity of the cell and its surrounding microenvironment (energy substrate availability and diversity). Support for this view came from numerous studies showing that in vitro growth conditions can alter energy metabolism contributing to a dependency on glycolysis for ATP production [98].
Yet, Zu and Guppy analysed numerous studies and showed that aerobic glycolysis is not inherent to cancer but more a consequence of hypoxia[99].
Table 1. Impact of different oncogenes on energy metabolism
Impact of different oncogenes on energy metabolism.
For many years, mitochondria were viewed as semiautonomous organelles, required only for cellular energetics. This view has been largely supplanted by the concept that mitochondria are fully integrated into the cell and that mitochondrial stresses rapidly activate cytosolic signaling pathways that ultimately alter nuclear gene expression. Remarkably, this coordinated response to mild mitochondrial stress appears to leave the cell less susceptible to subsequent perturbations. This response, termed mitohormesis, is being rapidly dissected in many model organisms. A fuller understanding of mitohormesis promises to provide insight into our susceptibility for disease and potentially provide a unifying hypothesis for why we age.
Figure 1. The Basis of Mitohormesis. Any of a number of endogenous or exogenous stresses can perturb mitochondrial function. These perturbations are relayed to the cytosol through, at present, poorly understood mechanisms that may involve mitochondrial ROS as well as other mediators. These cytoplasmic signaling pathways and subsequent nuclear transcriptional changes induce various long-lasting cytoprotective pathways. This augmented stress resistance allows for protection from a wide array of subsequent stresses.
Figure 2. Potential Parallels between the Mitochondrial Unfolded Protein Response and Quorum Sensing in Gram-Positive Bacteria. In the C. elegans UPRmt response, mitochondrial proteins (indicated by blue swirls) are degraded by matrix proteases, and the oligopeptides that are generated are then exported through the ABC transporter family member HAF-1. Once in the cytosol, these peptides can influence the subcellular localization of the transcription factor ATFS-1. Nuclear ATFS-1 is capable of orchestrating a broad transcriptional response to mitochondrial stress. As such, this pathway establishes a method for mitochondrial and nuclear genomes to communicate. In some gram-positive bacteria, intracellularly generated peptides can be similarly exported through an ABC transporter protein. These peptides can be detected in the environment by a membrane-bound histidine kinases (HK) sensor. The activation of the HK sensor leads to phosphorylation of a response regulator (RR) protein that, in turn, can alter gene expression. This program allows communication between dispersed gram-positive bacteria and thus coordinated behavior of widely dispersed bacterial genomes.
Figure 3. The Complexity of Mitochondrial Stresses and Responses. A wide array of extrinsic and intrinsic mitochondrial perturbations can elicit cellular responses. As detailed in the text, genetic or pharmacological disruption of electron transport, incorrect folding of mitochondrial proteins, stalled mitochondrial ribosomes, alterations in signaling pathways, or exposure to toxins all appear to elicit specific cytoprotective programs within the cell. These adaptive responses include increased mitochondrial number (biogenesis), alterations in metabolism, increased antioxidant defenses, and augmented protein chaperone expression. The cumulative effect of these adaptive mechanisms might be an extension of lifespan and a decreased incidence of age-related pathologies.
2.1.2.6 Mitochondrial function and energy metabolism in cancer cells. Past overview and future perspectives
The involvements of energy metabolism aspects of mitochondrial dysfunction in cancer development, proliferation and possible therapy, have been investigated since Otto Warburg published his hypothesis. The main published material on cancer cell energy metabolism is overviewed and a new unique in vivo experimental approach that may have significant impact in this important field is suggested. The monitoring system provides real time data, reflecting mitochondrial NADH redox state and microcirculation function. This approach of in vivo monitoring of tissue viability could be used to test the efficacy and side effects of new anticancer drugs in animal models. Also, the same technology may enable differentiation between normal and tumor tissues in experimental animals and maybe also in patients.
Energy metabolism in mammalian cells
Fig. 1. Schematic representation of cellular energy metabolism and its relationship to microcirculatory blood flow and hemoglobin oxygenation.
Fig. 2. Schematic representation of the central role of the mitochondrion in the various processes involved in the pathology of cancer cells and tumors. Six issues marked as 1–6 are discussed in details in the text.
In vivo monitoring of tissue energy metabolism in mammalian cells
Fig. 3. Schematic presentation of the six parameters that could be monitored for the evaluation of tissue energy metabolism (see text for details).
Optical spectroscopy of tissue energy metabolism in vivo
Multiparametric monitoring system
Fig. 4. (A) Schematic representation of the Time Sharing Fluorometer Reflectometer (TSFR) combined with the laser Doppler flowmeter (D) for blood flow monitoring. The time sharing system includes a wheel that rotates at a speed of3000 rpm wit height filters: four for the measurements of mitochondrial NADH(366 nm and 450 nm)and four for oxy-hemoglobin measurements (585 nm and 577 nm) as seen in (C). The source of light is a mercury lamp. The probe includes optical fibers for NADH excitation (Ex) and emission (Em), laser Doppler excitation (LD in), laser Doppler emission (LD out) as seen in part E The absorption spectrum of Oxy- and Deoxy- Hemoglobin indicating the two wave length used (C).
Fig. 7. Comparison between mitochondrial metabolic states in vitro and the typical tissue metabolic states in vivo evaluated by NADH redox state, tissue blood flow and hemoglobin oxygenation as could be measured by the suggested monitoring system.
(very important)
2.1.2.7 Metabolic Reprogramming. Cancer Hallmark Even Warburg Did Not Anticipate
Cancer metabolism has long been equated with aerobic glycolysis, seen by early biochemists as primitive and inefficient. Despite these early beliefs, the metabolic signatures of cancer cells are not passive responses to damaged mitochondria but result from oncogene-directed metabolic reprogramming required to support anabolic growth. Recent evidence suggests that metabolites themselves can be oncogenic by altering cell signaling and blocking cellular differentiation. No longer can cancer-associated alterations in metabolism be viewed as an indirect response to cell proliferation and survival signals. We contend that altered metabolism has attained the status of a core hallmark of cancer.
The propensity for proliferating cells to secrete a significant fraction of glucose carbon through fermentation was first elucidated in yeast. Otto Warburg extended these observations to mammalian cells, finding that proliferating ascites tumor cells converted the majority of their glucose carbon to lactate, even in oxygen-rich conditions. Warburg hypothesized that this altered metabolism was specific to cancer cells, and that it arose from mitochondrial defects that inhibited their ability to effectively oxidize glucose carbon to CO2. An extension of this hypothesis was that dysfunctional mitochondria caused cancer (Koppenol et al., 2011). Warburg’s seminal finding has been observed in a wide variety of cancers. These observations have been exploited clinically using 18F-deoxyglucose positron emission tomography (FDG-PET). However, in contrast to Warburg’s original hypothesis, damaged mitochondria are not at the root of the aerobic glycolysis exhibited by most tumor cells. Most tumor mitochondria are not defective in their ability to carry out oxidative phosphorylation. Instead, in proliferating cells mitochondrial metabolism is reprogrammed to meet the challenges of macromolecular synthesis. This possibility was never considered by Warburg and his contemporaries.
Advances in cancer metabolism research over the last decade have enhanced our understanding of how aerobic glycolysis and other metabolic alterations observed in cancer cells support the anabolic requirements associated with cell growth and proliferation. It has become clear that anabolic metabolism is under complex regulatory control directed by growth factor signal transduction in non-transformed cells. Yet despite these advances, the repeated refrain from traditional biochemists is that altered metabolism is merely an indirect phenomenon in cancer, a secondary effect that pales in importance to the activation of primary proliferation and survival signals (Hanahan and Weinberg, 2011). Most proto-oncogenes and tumor suppressor genes encode components of signal transduction pathways. Their roles in carcinogenesis have traditionally been attributed to their ability to regulate the cell cycle and sustain proliferative signaling while also helping cells evade growth suppression and/or cell death (Hanahan and Weinberg, 2011). But evidence for an alternative concept, that the primary functions of activated oncogenes and inactivated tumor suppressors are to reprogram cellular metabolism, has continued to build over the past several years. Evidence is also developing for the proposal that proto-oncogenes and tumor suppressors primarily evolved to regulate metabolism.
We begin this review by discussing how proliferative cell metabolism differs from quiescent cell metabolism on the basis of active metabolic reprogramming by oncogenes and tumor suppressors. Much of this reprogramming depends on utilizing mitochondria as functional biosynthetic organelles. We then further develop the idea that altered metabolism is a primary feature selected for during tumorigenesis. Recent advances have demonstrated that altered metabolism in cancer extends beyond adaptations to meet the increased anabolic requirements of a growing and dividing cell. Changes in cancer cell metabolism can also influence cellular differentiation status, and in some cases these changes arise from oncogenic alterations in metabolic enzymes themselves.
Metabolism in quiescent vs. proliferating cells: both use mitochondria.
(A) In the absence of instructional growth factor signaling, cells in multicellular organisms lack the ability to take up sufficient nutrients to maintain themselves. Neglected cells will undergo autophagy and catabolize amino acids and lipids through the TCA cycle, assuming sufficient oxygen is available. This oxidative metabolism maximizes ATP production. (B) Cells that receive instructional growth factor signaling are directed to increase their uptake of nutrients, most notably glucose and glutamine. The increased nutrient uptake can then support the anabolic requirements of cell growth: mainly lipid, protein, and nucleotide synthesis (biomass). Excess carbon is secreted as lactate. Proliferating cells may also use strategies to decrease their ATP production while increasing their ATP consumption. These strategies maintain the ADP:ATP ratio necessary to maintain glycolytic flux. Green arrows represent metabolic pathways, while black arrows represent signaling.
Metabolism is a direct, not indirect, response to growth factor signaling nihms-360138-f0002
Metabolism is a direct, not indirect, response to growth factor signaling.
(A) The traditional demand-based model of how metabolism is altered in proliferating cells. In response to growth factor signaling, increased transcription and translation consume free energy and decrease the ADP:ATP ratio. This leads to enhanced flux of glucose carbon through glycolysis and the TCA cycle for the purpose of producing more ATP. (B) Supply-based model of how metabolism changes in proliferating cells. Growth factor signaling directly reprograms nutrient uptake and metabolism. Increased nutrient flux through glycolysis and the mitochondria in response to growth factor signaling is used for biomass production. Metabolism also impacts transcription and translation through mechanisms independent of ATP availability.
Alterations in classic oncogenes directly reprogram cell metabolism to increase nutrient uptake and biosynthesis. PI3K/Akt signaling downstream of receptor tyrosine kinase (RTK) activation increases glucose uptake through the transporter GLUT1, and increases flux through glycolysis. Branches of glycolytic metabolism contribute to nucleotide and amino acid synthesis. Akt also activates ATP-citrate lyase (ACL), promoting the conversion of mitochondria-derived citrate to acetyl-CoA for lipid synthesis. Mitochondrial citrate can be synthesized when glucose-derived acetyl-CoA, generated by pyruvate dehydrogenase (PDH), condenses with glutamine-derived oxaloacetate (OAA) via the activity of citrate synthase (CS). mTORC1 promotes protein synthesis and mitochondrial metabolism. Myc increases glutamine uptake and the conversion of glutamine into a mitochondrial carbon source by promoting the expression of the enzyme glutaminase (GLS). Myc also promotes mitochondrial biogenesis. In addition, Myc promotes nucleotide and amino acid synthesis, both through direct transcriptional regulation and through increasing the synthesis of mitochondrial metabolite precursors.
Pyruvate kinase M2 (PKM2) expression in proliferating cells is regulated by signaling and mitochondrial metabolism to facilitate macromolecular synthesis. PKM2 is a less active isoform of the terminal glycolytic enzyme pyruvate kinase. It is also uniquely inhibited downstream of tyrosine kinase signaling. The decreased enzymatic activity of PKM2 in the cytoplasm promotes the accumulation of upstream glycolytic intermediates and their shunting into anabolic pathways. These pathways include the serine synthetic pathway that contributes to nucleotide and amino acid production. When mitochondrial metabolism is excessive, reactive oxygen species (ROS) from the mitochondria can feedback to inhibit PKM2 activity. Acetylation of PKM2, dependent on acetyl-CoA availability, may also promote PKM2 degradation and further contribute to increased flux through anabolic synthesis pathways branching off glycolysis.
IDH1 and IDH2 mutants convert glutamine carbon to the oncometabolite 2-hydroxyglutarate to dysregulate epigenetics and cell differentiation. (A) α-ketoglutarate, produced in part by wild-type isocitrate dehydrogenase (IDH), can enter the nucleus and be used as a substrate for dioxygenase enzymes that modify epigenetic marks. These enzymes include the TET2 DNA hydroxylase enzyme which converts 5-methylcytosine to 5-hydroxymethylcytosine, typically at CpG dinucleotides. 5-hydroxymethylcytosine may be an intermediate in either active or passive DNA demethylation. α-ketoglutarate is also a substrate for JmjC domain histone demethylase enzymes that demethylate lysine residues on histone tails. (B) The common feature of cancer-associated mutations in cytosolic IDH1 and mitochondrial IDH2 is the acquisition of a neomorphic enzymatic activity. This activity converts glutamine-derived α-ketoglutarate to the oncometabolite 2HG. 2HG can competitively inhibit α-ketoglutarate-dependent enzymes like TET2 and the JmjC histone demethylases, thereby impairing normal epigenetic regulation. This results in altered histone methylation marks, in some cases DNA hypermethylation at CpG islands, and dysregulated cellular differentiation.
Hypoxia and HIF-1 activation promote an alternative pathway for citrate synthesis through reductive metabolism of glutamine. (A) In proliferating cells under normoxic conditions, citrate is synthesized from both glucose and glutamine. Glucose carbon provides acetyl-CoA through the activity of PDH. Glutamine carbon provides oxaloacetate through oxidative mitochondrial metabolism dependent on NAD+. Glucose-derived acetyl-CoA and glutamine-derived oxaloacetate condense to form citrate via the activity of citrate synthase (CS). Citrate can be exported to the cytosol for lipid synthesis. (B) In cells proliferating in hypoxia and/or with HIF-1 activation, glucose is diverted away from mitochondrial acetyl-CoA and citrate production. Citrate can be maintained through an alternative pathway of reductive carboxylation, which we propose to rely on reverse flux of glutamine-derived α-ketoglutarate through IDH2. This reverse flux in the mitochondria would promote electron export from the mitochondria when the activity of the electron transport chain is inhibited because of the lack of oxygen as an electron acceptor. Mitochondrial reverse flux can be accomplished by NADH conversion to NADPH by mitochondrial transhydrogenase and the resulting NADPH use in α-ketoglutarate carboxylation. When citrate/isocitrate is exported to the cytosol, some may be metabolized in the oxidative direction by IDH1 and contribute to a shuttle that produces cytosolic NADPH.
A major paradox remaining with PKM2 is that cells expressing PKM2 produce more glucose-derived pyruvate than PKM1-expressing cells, despite having a form of the pyruvate kinase enzyme that is less active and more sensitive to inhibition. One way to get around the PKM2 bottleneck and maintain/enhance pyruvate production may be through an proposed alternative glycolytic pathway, involving an enzymatic activity not yet purified, that dephosphorylates PEP to pyruvate without the generation of ATP (Vander Heiden et al., 2010). Another answer to this paradox may emanate from the serine synthetic pathway. The decreased enzymatic activity of PKM2 can promote the accumulation of the 3-phosphoglycerate glycolytic intermediate that serves as the entry point for the serine synthetic pathway branch off glycolysis. The little studied enzyme serine dehydratase can then directly convert serine to pyruvate. A third explanation may lie in the oscillatory activity of PKM2 from the inactive dimer to active tetramer form. Regulatory inputs into PKM2 like tyrosine phosphorylation and ROS destabilize the tetrameric form of PKM2 (Anastasiou et al., 2011; Christofk et al., 2008b; Hitosugi et al., 2009), but other inputs present in glycolytic cancer cells like fructose-1,6-bisphosphate and serine can continually allosterically activate and/or promote reformation of the PKM2 tetramer (Ashizawa et al., 1991; Eigenbrodt et al., 1983). Thus, PKM2 may be continually switching from inactive to active forms in cells, resulting in an apparent upregulation of flux through anabolic glycolytic branching pathways while also maintaining reasonable net flux of glucose carbon through PEP to pyruvate. With such an oscillatory system, small changes in the levels of any of the above-mentioned PKM2 regulatory inputs can cause exquisite, rapid, adjustments to glycolytic flux. This would be predicted to be advantageous for proliferating cells in the setting of variable extracellular nutrient availability. The capability for oscillatory regulation of PKM2 could also provide an explanation for why tumor cells do not select for altered glycolytic metabolism upstream of PKM2 through deletions and/or loss of function mutations of other glycolytic enzymes.
IDH1 mutations at R132 are not simply loss-of-function for isocitrate and α-ketoglutarate interconversion, but also acquire a novel reductive activity to convert α-ketoglutarate to 2-hydroxyglutarate (2HG), a rare metabolite found at only trace amounts in mammalian cells under normal conditions (Dang et al., 2009). However, it still remained unclear if 2HG was truly a pathogenic “oncometabolite” resulting from IDH1 mutation, or if it was just the byproduct of a loss of function mutation. Whether 2HG production or the loss of IDH1 normal function played a more important role in tumorigenesis remained uncertain.
A potential answer to whether 2HG production was relevant to tumorigenesis arrived with the study of mutations in IDH2, the mitochondrial homolog of IDH1. Up to this point a small fraction of gliomas lacking IDH1 mutations were known to harbor mutations at IDH2 R172, the analogous residue to IDH1 R132 (Yan et al., 2009). However, given the rarity of these IDH2 mutations, they had not been characterized for 2HG production. The discovery of IDH2 R172 mutations in AML as well as glioma samples prompted the study of whether these mutations also conferred the reductive enzymatic activity to produce 2HG. Enzymatic assays and measurement of 2HG levels in primary AML samples confirmed that these IDH2 R172 mutations result in 2HG elevation (Gross et al., 2010; Ward et al., 2010).
It was then investigated if the measurement of 2HG levels in primary tumor samples with unknown IDH mutation status could serve as a metabolite screening test for both cytosolic IDH1 and mitochondrial IDH2 mutations. AML samples with low to undetectable 2HG were subsequently sequenced and determined to be IDH1 and IDH2 wild-type, and several samples with elevated 2HG were found to have neomorphic mutations at either IDH1 R132 or IDH2 R172 (Gross et al., 2010). However, some 2HG-elevated AML samples lacked IDH1 R132 or IDH2 R172 mutations. When more comprehensive sequencing of IDH1 and IDH2 was performed, it was found that the common feature of this remaining subset of 2HG-elevated AMLs was another mutation in IDH2, occurring at R140 (Ward et al., 2010). This discovery provided additional evidence that 2HG production was the primary feature being selected for in tumors.
In addition to intensifying efforts to find the cellular targets of 2HG, the discovery of the 2HG-producing IDH1 and IDH2 mutations suggested that 2HG measurement might have clinical utility in diagnosis and disease monitoring. While much work is still needed in this area, serum 2HG levels have successfully correlated with IDH1 R132 mutations in AML, and recent data have suggested that 1H magnetic resonance spectroscopy can be applied for 2HG detection in vivo for glioma (Andronesi et al., 2012; Choi et al., 2012; Gross et al., 2010; Pope et al., 2012). These methods may have advantages over relying on invasive solid tumor biopsies or isolating leukemic blast cells to obtain material for sequencing of IDH1 and IDH2. Screening tumors and body fluids by 2HG status also has potentially increased applicability given the recent report that additional IDH mutations can produce 2HG (Ward et al., 2011). These additional alleles may account for the recently described subset of 2HG-elevated chondrosarcoma samples that lacked the most common IDH1 or IDH2 mutations but were not examined for other IDH alterations (Amary et al., 2011). Metabolite screening approaches can also distinguish neomorphic IDH mutations from SNPs and sequencing artifacts with no effect on IDH enzyme activity, as well as from an apparently rare subset of loss-of-function, non 2HG-producing IDH mutations that may play a secondary tumorigenic role in altering cellular redox (Ward et al., 2011).
Will we find other novel oncometabolites like 2HG? We should consider basing the search for new oncometabolites on those metabolites already known to cause disease in pediatric inborn errors of metabolism (IEMs). 2HG exemplifies how advances in research on IEMs can inform research on cancer metabolism, and vice versa. Methods developed by those studying 2HG aciduria were used to demonstrate that R(-)-2HG (also known as D-2HG) is the exclusive 2HG stereoisomer produced by IDH1 and IDH2 mutants (Dang et al., 2009; Ward et al., 2010). Likewise, following the discovery of 2HG-producing IDH2 R140 mutations in leukemia, researchers looked for and successfully found germline IDH2 R140 mutations in D-2HG aciduria. IDH2 R140 mutations now account for nearly half of all cases of this devastating disease (Kranendijk et al., 2010). While interest has surrounded 2HG due to its apparent novelty as a metabolite not found in normal non-diseased cells, there are situations where 2HG appears in the absence of metabolic enzyme mutations. For example, in human cells proliferating in hypoxia, α-ketoglutarate can accumulate and be metabolized through an enhanced reductive activity of wild-type IDH2 in the mitochondria, leading to 2HG accumulation in the absence of IDH mutation (Wise et al., 2011). The ability of 2HG to alter epigenetics may reflect its evolutionary ancient status as a signal for elevated glutamine/glutamate metabolism and/or oxygen deficiency.
With this broadened view of what constitutes an oncometabolite, one could argue that the discoveries of two other oncometabolites, succinate and fumarate, preceded that of 2HG. Loss of function mutations in the TCA cycle enzymes succinate dehydrogenase (SDH) and fumarate hydratase (FH) have been known for several years to occur in pheochromocytoma, paraganglioma, leiomoyoma, and renal carcinoma. It was initially hypothesized that these mutations contribute to cancer through mitochondrial damage producing elevated ROS (Eng et al., 2003). However, potential tumorigenic effects were soon linked to the elevated levels of succinate and fumarate arising from loss of SDH and FH function, respectively. Succinate was initially found to impair PHD2, the α-ketoglutarate-dependent enzyme regulating HIF stability, through product inhibition (Selak et al., 2005). Subsequent work confirmed that fumarate could inhibit PHD2 (Isaacs et al., 2005), and that succinate could also inhibit the related enzyme PHD3 (Lee et al., 2005). These observations linked the elevated HIF levels observed in SDH and FH deficient tumors to the activity of the succinate and fumarate metabolites. Recent work has suggested that fumarate may have other important roles that predominate in FH deficiency. For example, fumarate can modify cysteine residues to inhibit a negative regulator of the Nrf2 transcription factor. This post-translational modification leads to the upregulation of antioxidant response genes (Adam et al., 2011; Ooi et al., 2011).
There are still many unanswered questions regarding the biology of SDH and FH deficient tumors. In light of the emerging epigenetic effects of 2HG, it is intriguing that succinate has been shown to alter histone demethylase activity in yeast (Smith et al., 2007). Perhaps elevated succinate and fumarate resulting from SDH and FH mutations can promote tumorigenesis in part through epigenetic modulation.
Despite rapid technological advances in studying cell metabolism, we remain unable to reliably distinguish cytosolic metabolites from those in the mitochondria and other compartments. Current fractionation methods often lead to metabolite leakage. Even within one subcellular compartment, there may be distinct pools of metabolites resulting from channeling between metabolic enzymes. A related challenge lies in the quantitative measurement of metabolic flux; i.e., measuring the movement of carbon, nitrogen, and other atoms through metabolic pathways rather than simply measuring the steady-state levels of individual metabolites. While critical fluxes have been quantified in cultured cancer cells and methods for these analyses continue to improve (DeBerardinis et al., 2007; Mancuso et al., 2004; Yuan et al., 2008), many obstacles remain such as cellular compartmentalization and the reliance of most cell culture on complex, incompletely defined media.
Over the past decade, the study of metabolism has returned to its rightful place at the forefront of cancer research. Although Warburg was wrong about mitochondria, he was prescient in his focus on metabolism. Data now support the concepts that altered metabolism results from active reprogramming by altered oncogenes and tumor suppressors, and that metabolic adaptations can be clonally selected during tumorigenesis. Altered metabolism should now be considered a core hallmark of cancer. There is much work to be done.
2.1.2.8 A Role for the Mitochondrial Pyruvate Carrier as a Repressor of the Warburg Effect and Colon Cancer Cell Growth
Cancer cells are typically subject to profound metabolic alterations, including the Warburg effect wherein cancer cells oxidize a decreased fraction of the pyruvate generated from glycolysis. We show herein that the mitochondrial pyruvate carrier (MPC), composed of the products of the MPC1 and MPC2 genes, modulates fractional pyruvate oxidation. MPC1 is deleted or underexpressed in multiple cancers and correlates with poor prognosis. Cancer cells re-expressing MPC1 and MPC2 display increased mitochondrial pyruvate oxidation, with no changes in cell growth in adherent culture. MPC re-expression exerted profound effects in anchorage-independent growth conditions, however, including impaired colony formation in soft agar, spheroid formation, and xenograft growth. We also observed a decrease in markers of stemness and traced the growth effects of MPC expression to the stem cell compartment. We propose that reduced MPC activity is an important aspect of cancer metabolism, perhaps through altering the maintenance and fate of stem cells.
Figure 2. Re-Expressed MPC1 and MPC2 Form a Mitochondrial Complex (A and B) (A) Western blot and (B) qRT-PCR analysis of the indicated colon cancer cell lines with retroviral expression of MPC1 (or MPC1-R97W) and/or MPC2. (C) Western blots of human heart tissue, hematologic cancer cells, and colon cancer cell lines with and without MPC1 and MPC2 re-expression. (D) Fluorescence microscopy of MPC1-GFP and MPC2-GFP overlaid with Mitotracker Red in HCT15 cells. Scale bar: 10 mm. (E) Blue-native PAGE analysis of mitochondria from control and MPC1/2-expressing cells. (F) Western blots of metabolic and mitochondrial proteins across four colon cancer cell lines with or without MPC1/2 expression
Figure 3. MPC Re-Expression Alters Mitochondrial Pyruvate Metabolism (A) OCR at baseline and maximal respiration in HCT15 (n = 7) and HT29 (n = 13) with pyruvate as the sole carbon source (mean ± SEM). (B and C) Schematic and citrate mass isotopomer quantification in cells cultured with D-[U-13C]glucose and unlabeled glutamine for 6 hr (mean ± SD, n = 2). (D) Glucose uptake and lactate secretion normalized to protein concentration (mean ± SD, n = 3). (E–G) (E) Western blots of PDH, phospho-PDH, and PDK1; (F) PDH activity assay and (G) CS activity assay with or without MPC1 and MPC2 expression (mean ± SD, n = 4). (H and I) Effects of MPC1/2 re-expression on mitochondrial membrane potential and ROS production (mean ± SD, n = 3). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.
Figure 4. MPC Re-Expression Alters Growth under Low-Attachment Conditions (A) Cell number of control and MPC1/2 re-expressing cell lines in adherent culture (mean ± SD, n = 7). (B) Cell viability determined by trypan blue exclusion and Annexin V/PI staining (mean ± SD, n = 3). (C–F) (C) EdU incorporation of MPC re-expressing cell lines at 3 hr post EdU pulse. Growth in 3D culture evaluated by (D) soft agar colony formation (mean ± SD, n = 12, see also Table S1) and by ([E] and [F]) spheroid formation ± MPC inhibitor UK5099 (mean ± SEM, n = 12). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.
Figure 7. MPC Re-Expression Alters the Cancer Initiating Cell Population (A) Western blot quantification of ALDHA and Lin28A from control or MPC re-expressing HT29 xenografts (mean ± SEM, n = 10). (B and C) Percentage of ALDHhi (n = 3) and CD44hi (n = 5) cells as determined by flow cytometry (mean ± SEM). (D) Western blot analysis of stem cell markers in control and MPC re-expressing cell lines. (E) Relative MPC1 and MPC2 mRNA levels in ALDH sorted HCT15 cells (n = 4,mean ± SEM). 2D growth of (F) whole-population HCT15 cells and (G) ALDH sorted cells. Area determined by ImageJ after crystal violet staining (mean ± SD, n = 6). (H and I) (H) Adherent and (I) spheroid growth of main population (MP) versus side population (SP) HCT15 cells. (mean ± SD, n = 6). *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001
Our demonstration that the MPC is lost or underexpressed in many cancers might provide clarifying context for earlier attempts to exploit metabolic regulation for cancer therapeutics. The PDH kinase inhibitor dichloroacetate, which impairs PDH phosphorylation and increases pyruvate oxidation, has been explored extensively as a cancer therapy (Bonnet et al., 2007; Olszewski et al., 2010). It has met with mixed results, however, and has typically failed to dramatically decrease tumor burden as a monotherapy (Garon et al., 2014;
Sanchez-Arago et al., 2010; Shahrzadetal.,2010). Is one possible reason for these failures that the MPC has been lost or inactivated, thereby limiting the metabolic effects of PDH activity? The inclusion of the MPC adds additional complexity to targeting cancer metabolism for therapy but has the potential to explain why treatments may be more effective in some studies than in others (Fulda et al., 2010; Hamanaka and Chandel, 2012; Tennant et al., 2010; Vander Heiden, 2011). The redundant measures to limit pyruvate oxidation make it easy to understand why expression of the MPC leads to relatively modest metabolic changes in cells grown in adherent culture conditions. While subtle, we observed a number of changes in metabolic parameters, all of which are consistent with enhanced mitochondrial pyruvate entry and oxidation. There are at least two possible explanations for the discrepancy that we observed between the impact on adherent and nonadherent cell proliferation. One hypothesis is that the stress of nutrient deprivation and detachment combines with these subtle metabolic effects to impair survival and proliferation.
2.1.2.9 ECM1 promotes the Warburg effect through EGF-mediated activation of PKM2
The Warburg effect is an oncogenic metabolic switch that allows cancer cells to take up more glucose than normal cells and favors anaerobic glycolysis. Extracellular matrix protein 1 (ECM1) is a secreted glycoprotein that is overexpressed in various types of carcinoma. Using two-dimensional digest-liquid chromatography-mass spectrometry (LC-MS)/MS, we showed that the expression of proteins associated with the Warburg effect was upregulated in trastuzumab-resistant BT-474 cells that overexpressed ECM1 compared to control cells. We further demonstrated that ECM1 induced the expression of genes that promote the Warburg effect, such as glucose transporter 1 (GLUT1), lactate dehydrogenase A (LDHA), and hypoxia-inducible factor 1 α (HIF-1α). The phosphorylation status of pyruvate kinase M2 (PKM-2) at Ser37, which is responsible for the expression of genes that promote the Warburg effect, was affected by the modulation of ECM1 expression. Moreover, EGF-dependent ERK activation that was regulated by ECM1 induced not only PKM2 phosphorylation but also gene expression of GLUT1 and LDHA. These findings provide evidence that ECM1 plays an important role in promoting the Warburg effect mediated by PKM2.
Fig. 1.ECM1 induces a metabolic shift toward promoting Warburg effect. (A) The levels of glucose uptake were examined with a cell-based assay. (B) Levels of lactate production were measured using a lactate assay kit. (C) Cellular ATP content was determined with a Cell Titer-Glo luminescent cell viability assay. Error bars represent mean ± SD of triplicate experiments (*p b 0.05, ***p b 0.0005).
Fig.2. ECM1 up-regulates expression of gene sassociated with the Warburg effect. (A) Cell lysates were analyzed by western blotting using antibodies specific for ECM1, LDHA, GLUT1,and actin (as a loading control). The intensities of the bands were quantified using 1D Scan software and plotted. (BandC) mRNA levels of each gene were determined by real-time PCR using specific primers. (D) HIF-1α-dependent transcriptional activities were examined using a hypoxia response element (HRE) reporter indual luciferase assays. Error bars represent mean ± SD of triplicate experiments (*p b 0.05, **p b 0.005, ***p b 0.0005).
Fig.3. ECM1-dependent upregulation of gene expression is not mediated byEgr-1.
Fig.4. ECM1 activates PKM2 via EGF-mediated ERK activation
Fig. 5. TheWarburg effect is attenuated by silencing of PKM2 in breast cancer cells
Recently, a non-glycolytic function of PKM2 was reported. Phosphorylated PKM2 at Ser37 is translocated into the nucleus after EGFR and ERK activation and regulates the expression of cyclin D1, c-Myc, LDHA, and GLUT1[19,37]. Here, we showed that ECM1 regulates the phosphorylation level and translocation of PKM2 via the EGFR/ ERK pathway. As we previously showed that ECM1 enhances the EGF response and increases EGFR expression through MUC1-dependent stabilization [17], it seemed likely that activation of the EGFR/ERK pathway by ECM1 is linked to PKM2 phosphorylation. Indeed, we show here that ECM1 regulates the phosphorylation of PKM2 at Ser37 and enhances the Warburg effect through the EGFR/ERK pathway. HIF-1α is known to be responsible for alterations in cancer cell metabolism [38] and our current studies showed that the expression level of HIF-1α is up-regulated by ECM1 (Fig. 2C and D). To determine the mechanism by which ECM1 upregulated HIF-1α expression, we focused on the induction of Egr-1 by EGFR/ERK signaling [39]. However, although Egr-1 expression was regulated by ECM1 we failed to find evidence that Egr-1 affected the expression of genes involved in the Warburg effect (Fig. 3C). Moreover, ERK-dependent PKM2 activation did not regulate HIF-1α expression in BT-474 cells (Fig. 4D and5B). These results suggested that the upregulation of HIF-1α by ECM1 is not mediated by the EGFR/ERK pathway.
Conclusions
In the current study we showed that ECM1 altered metabolic phenotypes of breast cancer cells toward promoting the Warburg effect.
Phosphorylation and nuclear translocation of PKM2 were induced by ECM1 through the EGFR/ERK pathway. Moreover, phosphorylated PKM2 increased the expression of metabolic genes such as LDHA and GLUT1, and promoted glucose uptake and lactate production. These findings provide a new perspective on the distinct functions of ECM1 in cancer cell metabolism. Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.cellsig.2014.11.004
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2.1.2.10 Glutamine Oxidation Maintains the TCA Cycle and Cell Survival during impaired Mitochondrial Pyruvate Transport
Mitochondria produce acetyl-CoA from glutamine during MPC inhibition
•Alanine synthesis is suppressed during MPC inhibition
•MPC inhibition activates GDH to supply pools of TCA cycle intermediates
•GDH supports cell survival during periods of MPC inhibition
Summary
Alternative modes of metabolism enable cells to resist metabolic stress. Inhibiting these compensatory pathways may produce synthetic lethality. We previously demonstrated that glucose deprivation stimulated a pathway in which acetyl-CoA was formed from glutamine downstream of glutamate dehydrogenase (GDH). Here we show that import of pyruvate into the mitochondria suppresses GDH and glutamine-dependent acetyl-CoA formation. Inhibiting the mitochondrial pyruvate carrier (MPC) activates GDH and reroutes glutamine metabolism to generate both oxaloacetate and acetyl-CoA, enabling persistent tricarboxylic acid (TCA) cycle function. Pharmacological blockade of GDH elicited largely cytostatic effects in culture, but these effects became cytotoxic when combined with MPC inhibition. Concomitant administration of MPC and GDH inhibitors significantly impaired tumor growth compared to either inhibitor used as a single agent. Together, the data define a mechanism to induce glutaminolysis and uncover a survival pathway engaged during compromised supply of pyruvate to the mitochondria.
Yang et al, Graphical Abstract
Graphical abstract
Figure 1. Pyruvate Depletion Redirects Glutamine Metabolism to Produce AcetylCoA and Citrate (A) Top: Anaplerosis supplied by [U-13C]glutamine. Glutamine supplies OAA via a-KG, while acetylCoA is predominantly supplied by other nutrients, particularly glucose. Bottom: Glutamine is converted to acetyl-CoA in the absence of glucosederived pyruvate. Red circles represent carbons arising from [U-13C]glutamine, and gray circles are unlabeled. Reductive carboxylation is indicated by the green dashed line. (B) Fraction of succinate, fumarate, malate, and aspartate containing four 13C carbons after culture of SFxL cells for 6 hr with [U-13C]glutamine in the presence or absence of 10 mM unlabeled glucose (Glc). (C) Mass isotopologues of citrate after culture of SFxL cells for 6 hr with [U-13C]glutamine and 10 mM unlabeled glucose, no glucose, or no glucose plus 6 mM unlabeled pyruvate (Pyr). (D) Citrate m+5 and m+6 after culture of HeLa or Huh-7 cells for 6 hr with [U-13C]glutamine and 10 mM unlabeled glucose, no glucose, or no glucose plus 6 mM unlabeled pyruvate. Data are the average and SD of three independent cultures. *p < 0.05; **p < 0.01; ***p < 0.001.
Figure 2. Isolated Mitochondria Convert Glutamine to Citrate (A) Western blot of whole-cell lysates (Cell) and preparations of isolated mitochondria (Mito) or cytosol from SFxL cells. (B) Oxygen consumption in a representative mitochondrial sample. Rates before and after addition of ADP/GDP are indicated. (C) Mass isotopologues of citrate produced by mitochondria cultured for 30 min with [U-13C] glutamine and with or without pyruvate.
Figure 3. Blockade of Mitochondrial Pyruvate Transport Activates Glutamine-Dependent Citrate Formation (A) Dose-dependent effects of UK5099 on citrate labeling from [U-13C]glucose and [U-13C]glutamine in SFxL cells. (B) Time course of citrate labeling from [U-13C] glutamine with or without 200 mM UK5099. (C) Abundance of total citrate and citrate m+6 in cells cultured in [U-13C]glutamine with or without 200 mM UK5099. (D) Mass isotopologues of citrate in cells cultured for 6 hr in [U-13C]glutamine with or without 10 mM CHC or 200 mM UK5099. (E) Effect of silencing ME2 on citrate m+6 after 6 hr of culture in [U-13C]glutamine. Relative abundances of citrate isotopologues were determined by normalizing total citrate abundance measured by mass spectrometry against cellular protein for each sample then multiplying by the fractional abundance of each isotopologue. (F) Effect of silencing MPC1 or MPC2 on formation of citrate m+6 after 6 hr of culture in [U-13C]glutamine. (G) Citrate isotopologues in primary human fibroblasts of varying MPC1 genotypes after culture in [U-13C]glutamine. Data are the average and SD of three independent cultures. *p < 0.05; **p < 0.01; ***p < 0.001. See also Figure S1.
Figure 4. Kinetic Analysis of the Metabolic Effects of Blocking Mitochondrial Pyruvate Transport (A) Summation of 13C spectra acquired over 2 min of exposure of SFxL cells to hyperpolarized [1-13C] pyruvate. Resonances are indicated for [1-13C] pyruvate (Pyr1), the hydrate of [1-13C]pyruvate (Pyr1-Hydr), [1-13C]lactate (Lac1), [1-13C]alanine (Ala1), and H[13C]O3 (Bicarbonate). (B) Time evolution of appearance of Lac1, Ala1, and bicarbonate in control and UK5099-treated cells. (C) Relative 13C NMR signals for Lac1, Ala1, and bicarbonate. Each signal is summed over the entire acquisition and expressed as a fraction of total 13C signal. (D) Quantity of intracellular and secreted alanine in control and UK5099-treated cells. Data are the average and SD of three independent cultures. *p < 0.05; ***p < 0.001. See also Figure S2.
Figure 5. Inhibiting Mitochondrial Pyruvate Transport Enhances the Contribution of Glutamine to Fatty Acid Synthesis (A) Mass isotopologues of palmitate extracted from cells cultured with [U-13C] glucose or [U-13C]glutamine, with or without 200 mM UK5099. For simplicity, only even-labeled isotopologues (m+2, m+4, etc.) are shown. (B) Fraction of lipogenic acetyl-CoA derived from glucose or glutamine with or without 200 mM UK5099. Data are the average and SD of three independent cultures. ***p < 0.001. See also Figure S3.
Figure 6. Blockade of Mitochondrial Pyruvate Transport Induces GDH (A) Two routes by which glutamate can be converted to AKG. Blue and green symbols are the amide (g) and amino (a) nitrogens of glutamine, respectively. (B) Utilization and secretion of glutamine (Gln), glutamate (Glu), and ammonia (NH4+) by SFxL cells with and without 200 mM UK5099. (C) Secretion of 15N-alanine and 15NH4+ derived from [a-15N]glutamine in SFxL cells expressing a control shRNA (shCtrl) or either of two shRNAs directed against GLUD1 (shGLUD1-A and shGLUD1-B). (D) Left: Phosphorylation of AMPK (T172) and acetyl-CoA carboxylase (ACC, S79) during treatment with 200 mM UK5099. Right: Steady-state levels of ATP 24 hr after addition of vehicle or 200 mM UK5099. (E) Fractional contribution of the m+6 isotopologue to total citrate in shCtrl, shGLUD1-A, and shGLUD1-B SFxL cells cultured in [U-13C]glutamine with or without 200 mM UK5099. Data are the average and SD of three independent cultures. *p < 0.05; **p < 0.01; ***p < 0.001. See also Figure S4.
Figure 7. GDH Sustains Growth and Viability during Suppression of Mitochondrial Pyruvate Transport (A) Relative growth inhibition of shCtrl, shGLUD1A, and shGLUD1-B SFxL cells treated with 50 mM UK5099 for 3 days. (B) Relative growth inhibition of SFxL cells treated with combinations of 50 mM of the GDH inhibitor EGCG, 10 mM of the GLS inhibitor BPTES, and 200 mM UK5099 for 3 days. (C) Relative cell death assessed by trypan blue staining in SFxL cells treated as in (B). (D) Relative cell death assessed by trypan blue staining in SF188 cells treated as in (B) for 2 days. (E) (Left) Growth of A549-derived subcutaneous xenografts treated with vehicle (saline), EGCG, CHC, or EGCG plus CHC (n = 4 for each group). Data are the average and SEM. Right: Lactate abundance in extracts of each tumor harvested at the end of the experiment. Data in (A)–(D) are the average and SD of three independent cultures. NS, not significant; *p < 0.05; **p < 0.01; ***p < 0.001. See also Figure S5.
Mitochondrial metabolism complements glycolysis as a source of energy and biosynthetic precursors. Precursors for lipids, proteins, and nucleic acids are derived from the TCA cycle. Maintaining pools of these intermediates is essential, even under circumstances of nutrient limitation or impaired supply of glucose-derived pyruvate to the mitochondria. Glutamine’s ability to produce both acetyl-CoA and OAA allows it to support TCA cycle activity as a sole carbon source and imposes a greater cellular dependence on glutamine metabolism when MPC function or pyruvate supply is impaired. Other anaplerotic amino acids could also supply both OAA and acetyl-CoA, providing flexible support for the TCA cycle when glucose is limiting. Although fatty acids are an important fuel in some cancer cells (Caro et al., 2012), and fatty acid oxidation is induced upon MPC inhibition, this pathway produces acetyl-CoA but not OAA. Thus, fatty acids would need to be oxidized along with an anaplerotic nutrient in order to enable the cycle to function as a biosynthetic hub. Notably, enforced MPC overexpression also impairs growth of some tumors (Schell et al., 2014), suggesting that maximal growth may require MPC activity to be maintained within a narrow window. After decades of research on mitochondrial pyruvate transport, molecular components of the MPC were recently reported (Halestrap, 2012; Schell and Rutter, 2013). MPC1 and MPC2 form a heterocomplex in the inner mitochondrial membrane, and loss of either component impairs pyruvate import, leading to citrate depletion (Bricker et al., 2012; Herzig et al., 2012). Mammalian cells lacking functional MPC1 display normal glutamine-supported respiration (Bricker et al., 2012), consistent with our observation that glutamine supplies the TCA cycle in absence of pyruvate import. We also observed that isolated mitochondria produce fully labeled citrate from glutamine, indicating that this pathway operates as a self-contained mechanism to maintain TCA cycle function. Recently, two well-known classes of drugs have unexpectedly been shown to inhibit MPC. First, thiazolidinediones, commonly used as insulin sensitizers, impair MPC function in myoblasts (Divakaruni et al.,2013). Second, the phosphodiesterase inhibitor Zaprinast inhibits MPC in the retina and brain (Du et al., 2013b). Zaprinast also induced accumulation of aspartate, suggesting that depletion of acetyl-CoA impaired the ability of a new turn of the TCA cycle to be initiated from OAA; as a consequence, OAA was transaminated to aspartate. We noted a similar phenomenon in cancer cells, suggesting that UK5099 elicits a state in which acetyl-CoA supply is insufficient to avoid OAA accumulation. Unlike UK5099, Zaprinast did not induce glutamine-dependent acetyl-CoA formation. This may be related to the reliance of isolated retinas on glucose rather than glutamine to supply TCA cycle intermediates or the exquisite system used by retinas to protect glutamate from oxidation (Du et al., 2013a). Zaprinast was also recently shown to inhibit glutaminase (Elhammali et al., 2014), which would further reduce the contribution of glutamine to the acetyl-CoA pool.
Comment by reader –
The results from these studies served as a good
reason to attempt the vaccination of patients using p53-
derived peptides, and a several clinical trials are currently
in progress. The most advanced work used a long
synthetic peptide mixture derived from p53 (p53-SLP; ISA
Pharmaceuticals, Bilthoven, the Netherlands) (Speetjens
et al., 2009; Shangary et al., 2008; Van der Burg et al.,
2001). The vaccine is delivered in the adjuvant setting
and induces T helper type cells.
One of the great observations of the 20th century was the behavior of cancer cells to proliferate and rely on anaerobic glycolysis for the source of energy. This was a restatement of the Pasteur effect, described 60 years earlier by the great French scientist in yeast experiments. The experiments with yeast were again reperformed by Jose EDS Roselino, a Brazilian biochemist, who established an explanation for it 50 years after Warburg. It is quite amazing the mitochondria were not yet discovered at the time that Warburg carried out the single-cell thickness measurements in his respiratory apparatus. He concluded from the observation that the cancer cells grew in a media that became acidic from producing lactic acid, that the cells were dysfunctional in the utilization of oxygen, as nonmalignant cells efficiently utilized oxygen. He also related the metabolic events to observations made by Meyerhof. The mitochondria and the citric acid cycle at this time had not yet been discovered, and the latter was, worked out by Hans Krebs and Albert Szent-Gyorgi, both of whom worked with him on mitochondrial metabolism. The normal cell utilizes glucose efficiently and lipids as well, generating energy through oxidative phosphorylation, with the production of ATP in a manner previously described in these posts. Greater clarity was achieved with the discovery of Coenzyme A, and finally the electron transport chain (ETC). This requires that the pyruvate be directed into the tricarboxylic acid cycle and to go through a series of reactions producing succinate and finally malate.
The following great achievements were made with regard to elucidating these processes:
Ronald George Wreyford Norrish and Lord George Porter for their studies of extremely fast chemical reactions, effected by disturbing the equlibrium by means of very short pulses of energy.
1965 FRANÇOIS JACOB , ANDRÉ LWOFF And JACQUES MONOD for their discoveries concerning genetic control of enzyme and virus synthesis.
1964 KONRAD BLOCH And FEODOR LYNEN for their discoveries concerning the mechanism and regulation of the cholesterol and fatty acid metabolism.
If there is a more immediate need for energy (as in stressed muscular activity) with net oxygen insufficiency, the pyruvate is converted to lactic acid, with acidemia, and with much less ATP production, but the lactic academia and the energy deficit is subsequently compensated for. The observation made by Jose EDS Rosalino was that yeast grown in a soil deficient in oxygen don’t put down roots.
^I. Topisirovic and N. Sonenberg
Cold Spring Harbor Symposia on Quantitative Biology, Volume LXXVI
http://dx.doi.org:/10.1101/sqb.2011.76.010785 ”A prominent feature of cancer cells is the use of aerobic glycolysis under conditions in which oxygen levels are sufficient to support energy production in the mitochondria (Jones and Thompson 2009; Cairns et al. 2010). This phenomenon, named the “Warburg effect,” after its discoverer Otto Warburg, is thought to fuel the biosynthetic requirements of the neoplastic growth (Warburg 1956; Koppenol et al. 2011) and has recently been acknowledged as one of the hallmarks of cancer (Hanahan and Weinberg 2011). mRNA translation is the most energy-demanding process in the cell (Buttgereit and Brand 1995).
Again, the use of aerobic glycolysis expression has been twisted.”
To understand my critical observation consider this: Aerobic glycolysis is the carbon flow that goes from Glucose to CO2 and water (includes Krens cycle and respiratory chain for the restoration of NAD, FAD etc.
Anerobic glyclysis is the carbon flow that goes from glucose to lactate. It uses conversion of pyruvate to lactate to regenerate NAD.
“Pasteur effect” is an expression coined by Warburg, which refers to the reduction in the carbon flow from glucose when oxygen is offered to yeasts. The major reason for that is in general terms, derived from the fact that carbon flow is regulated by several cell requirements but mainly by the ATP needs of the cell. Therefore, as ATP is generated 10 more efficiently in aerobiosis than under anaerobiosis, less carbon flow is required under aerobiosis than under anaerobiosis to maintain ATP levels. Warburg, after searching for the same regulatory mechanism in normal and cancer cells for comparison found that transformed cell continued their large flow of glucose carbons to lactate despite the presence of oxygen.
So, it is wrong to describe that aerobic glycolysis continues in the presence of oxygen. It is what it is expected to occur. The wrong thing is that anaerobic glycolysis continues under aerobiosis.
^Aurelian Udristioiu (comment)
In cells, the immediate energy sources involve glucose oxidation. In anaerobic metabolism, the donor of the phosphate group is adenosine triphosphate (ATP), and the reaction is catalyzed via the hexokinase or glucokinase: Glucose +ATP-Mg²+ = Glucose-6-phosphate (ΔGo = – 3.4 kcal/mol with hexokinase as the co-enzyme for the reaction.).
In the following step, the conversion of G-6-phosphate into F-1-6-bisphosphate is mediated by the enzyme phosphofructokinase with the co-factor ATP-Mg²+. This reaction has a large negative free energy difference and is irreversible under normal cellular conditions. In the second step of glycolysis, phosphoenolpyruvic acid in the presence of Mg²+ and K+ is transformed into pyruvic acid. In cancer cells or in the absence of oxygen, the transformation of pyruvic acid into lactic acid alters the process of glycolysis.
The energetic sum of anaerobic glycolysis is ΔGo = -34.64 kcal/mol. However a glucose molecule contains 686kcal/mol and, the energy difference (654.51 kcal) allows the potential for un-controlled reactions during carcinogenesis. The transfer of electrons from NADPH in each place of the conserved unit of energy transmits conformational exchanges in the mitochondrial ATPase. The reaction ADP³+ P²¯ + H²à ATP + H2O is reversible. The terminal oxygen from ADP binds the P2¯ by forming an intermediate pentacovalent complex, resulting in the formation of ATP and H2O. This reaction requires Mg²+ and an ATP-synthetase, which is known as the H+-ATPase or the Fo-F1-ATPase complex. Intracellular calcium induces mitochondrial swelling and aging. [12].
The known marker of monitoring of treatment in cancer diseases, lactate dehydrogenase (LDH) is an enzyme that is localized to the cytosol of human cells and catalyzes the reversible reduction of pyruvate to lactate via using hydrogenated nicotinamide deaminase (NADH) as co-enzyme.
The causes of high LDH and high Mg levels in the serum include neoplastic states that promote the high production of intracellular LDH and the increased use of Mg²+ during molecular synthesis in processes pf carcinogenesis (Pyruvate acid>> LDH/NADH >>Lactate acid + NAD), [13].
The material we shall discuss explores in more detail the dysmetabolism that occurs in cancer cells.
The discovery of cancer-associated mutations in genes encoding key metabolic enzymes has provided a direct link between altered metabolism and cancer. Advances in mass spectrometry and nuclear magnetic resonance technologies have facilitated high-resolution metabolite profiling of cells and tumors and identified the accumulation of metabolites associated with specific gene defects. Here we review the potential roles of such “oncometabolites” in tumor evolution and as clinical biomarkers for the detection of cancers characterized by metabolic dysregulation.
The emerging interest in metabolites whose abnormal accumulation causes both metabolic and nonmetabolic dysregulation and potential transformation to malignancy (herein termed “oncometabolites”) has been fueled by the identification of cancerassociated mutations in genes encoding enzymes with significant roles in cellular metabolism (1–5). Loss-of-function mutations in genes encoding the Krebs cycle enzymes fumarate hydratase (FH) and succinate dehydrogenase (SDH) cause the accumulation of fumarate and succinate, respectively (6), whereas gain-offunction isocitrate dehydrogenase (IDH) mutations increase levels of D–2-hydroxyglutarate (D-2HG) (7, 8). These metabolites have been implicated in the dysregulation of cellular processes including the competitive inhibition of α-ketoglutarate–dependent (α-KG–dependent) dioxygenase enzymes (also known as 2-oxoglutarate–dependent dioxgenases) and posttranslational modification of proteins (1, 4, 9–11). To date, several lines of biochemical and genetic evidence support roles for fumarate, succinate, and D-2HG in cellular transformation and oncogenesis (3, 12).
The Journal of Clinical Investigation http://www.jci.org Volume 123 Number 9 September 2013
ventional gene sequencing methods may lead to false positives due to genetic polymorphism and sequencing artifacts (98). In comparison, screening for elevated 2HG levels is a sensitive and specific approach to detect IDH mutations in tumors. Whereas patient sera/plasma can be assessed in the case of AML (7, 8, 21, 99), exciting advances with proton magnetic resonance spectroscopy (MRS) have been made in the noninvasive detection of 2HG in patients with gliomas (100–103). Using MRS sequence optimization and spectral fitting techniques, Maher and colleagues examined 30 patients with glioma and showed that the detection of 2HG correlated 100% with the presence of IDH1 or IDH2 mutations (102). Andronesi et al. further demonstrated that two-dimensional correlation spectroscopy could effectively distinguish 2HG from chemically similar metabolites present in the brain (103). Negative IHC staining for SDHB correlates with the presence of SDH mutations, whether in SDHB, SDHC, or SDHD (104). This finding is most likely explained by the fact that mutations in any of the four subunits of SDH can destabilize the entire enzyme complex. PGLs/PCCs associated with an SDHA mutation show negative staining for SDHA as well as SDHB (105). Therefore, IHC staining for SDHB is a useful diagnostic tool to triage patients for genetic testing of any SDH mutation, and subsequent staining for the other subunits may further narrow the selection of genes to be tested. In contrast, detection of FH protein is often evident in HLRCC tumors due to retention of the nonfunctional mutant allele (106). However, staining of cysts and tumors for 2SC immunoreactivity reveals a striking correlation between FH inactivation and the presence of 2SC-modified protein (2SCP), which is absent in non-HLRCC tumors and normal tissue controls (106). IHC staining for 2SCP thus provides a robust diagnostic biomarker for FH deficiency (107).
Therapeutic targeting Because D-2HG is a product of neomorphic enzyme activities, curtailing the D-2HG supply by specifically inhibiting the mutant IDH enzymes provides an elegant approach to target IDH-mutant cancers. Indeed, recent reports of small-molecule inhibitors against mutant forms of IDH1 and IDH2 demonstrated the feasibility of this method. An inhibitor against IDH2 R140Q was shown to reduce both intracellular and extracellular levels of D-2HG, suppress cell growth, and increase differentiation of primary human AML cells (108). Similarly, small-molecule inhibition of IDH1 R132H suppressed colony formation and increased tumor cell differentiation in a xenograft model for IDH1 R132H glioma (58). The inhibitors exhibited a cytostatic rather than cytotoxic effect, and therefore their therapeutic efficacy over longer time periods may need further assessment (109). Letouzé et al. showed that the DNA methytransferase inhibitor decitabine could repress the migration capacities of SDHB-mutant cells (40). However, for SDH- and FH-associated cancers, a synthetic lethality approach is worth exploring because of the pleiotrophic effects associated with succinate and fumarate accumulation.
Outlook The application of next-generation sequencing technologies in the field of cancer genomics has substantially increased our understanding of cancer biology. Detection of germline and somatic mutations in specific tumor types not only expands the current repertoire of driver mutations and downstream effectors in tumorigenesis, but also sheds light on how oncometabolites may exert their oncogenic roles. For example, the identification of mutually exclusive mutations in IDH1 and TET2 in AML led to the characterization of TET2 as a major pathological target of D-2HG (34, 110). Additionally, the discovery of somatic CUL3, SIRT1, and NRF2 mutations in sporadic PRCC2 converges with FH mutation in HLRCC, in which NRF2 activation is a consequence of fumarate-mediated succination of KEAP1, indicating the functional prominence of the NRF2 pathway in PRCC2 (73). In light of this, the identification of somatic mutations in genes encoding the chromatin-modifying enzymes histone H3K36 methyltransferase (SETD2), histone H3K4 demethylase JARID1C (KDM5C), histone H3K27 demethylase UTX (KDM6A), and the SWI/SNF chromatin remodelling complex gene PBRM1 in clear cell renal cell carcinoma (111–113) highlights the importance of epigenetic modulation in human cancer and raises the potential for systematic testing in other types of tumors such as those associated with FH mutations. Technological advances such as those in gas and liquidchromatography mass spectrometry (114, 115) and nuclear magnetic resonance imaging (102) have greatly improved the ability to measure low-molecular-weight metabolites in tumor samples with high resolution (116). Combined with metabolic flux analyses employing isotope tracers and mathematical modeling, modern-era metabolomic approaches can provide direct pathophysiological insights into tumor metabolism and serve as an excellent tool for biomarker discovery. Using a data-driven approach, Jain and colleagues constructed the metabolic profiles of 60 cancer cell lines and discovered glycine consumption as a key metabolic event in rapidly proliferating cancer cells (117), thus demonstrating the power of metabolomic analyses and the relevance to future cancer research and therapeutics.
Acknowledgments The Cancer Biology and Metabolism Group is funded by Cancer Research UK and the European Research Council under the European Community’s Seventh Framework Programme (FP7/20072013)/ERC grant agreement no. 310837 to Dr. Pollard. Professor Soga receives funding from a Grant-in-Aid for scientific research on Innovative Areas, Japan (no. 22134007), and the Yamagata Prefectural Government and City of Tsuruoka.
Address correspondence to: Patrick J. Pollard, Cancer Biology and Metabolism Group, Nuffield Department of Medicine, Henry Wellcome Building for Molecular Physiology, University of Oxford, Roosevelt Drive, Oxford, OX3 7BN, United Kingdom. Phone: 44.0.1865287780; Fax: 44.0.1865287787; E-mail: patrick.pollard@well.ox.ac.uk.
Yang M, Soga T, Pollard PJ, Adam J. The emerging role of fumarate as an oncometabolite. Front Oncol. 2012;2:85. 2. Ward PS, Thompson CB. Metabolic reprogramming: a cancer hallmark even warburg did not anticipate. Cancer Cell. 2012;21(3):297–308. 3. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science. 2009; 324(5930):1029–1033. 4. Thompson CB. Metabolic enzymes as oncogenes or tumor suppressors. N Engl J Med. 2009; 360(8):813–815. 5. Schulze A, Harris AL. How cancer metabolism is tuned for proliferation and vulnerable to disruption. Nature. 2012;491(7424):364–373.
Pollard PJ, et al. Accumulation of Krebs cycle intermediates and over-expression of HIF1alpha in tumours which result from germline FH and SDH mutations. Hum Mol Genet. 2005; 14(15):2231–2239. 7. Ward PS, et al. The common feature of leukemiaassociated IDH1 and IDH2 mutations is a neomorphic enzyme activity converting alpha-ketoglutarate to 2-hydroxyglutarate. Cancer Cell. 2010; 17(3):225–234.
Because D-2HG is a product of neomorphic enzyme activities, curtailing the D-2HG supply by specifically inhibiting the mutant IDH enzymes provides an elegant approach to target IDH-mutant cancers. Indeed, recent reports of small-molecule inhibitors against mutant forms of IDH1 and IDH2 demonstrated the feasibility of this method. An inhibitor against IDH2 R140Q was shown to reduce both intracellular and extracellular levels of D-2HG, suppress cell growth, and increase differentiation of primary human AML cells (108). Similarly, small-molecule inhibition of IDH1 R132H suppressed colony formation and increased tumor cell differentiation in a xenograft model for IDH1 R132H glioma (58). The inhibitors exhibited a cytostatic rather than cytotoxic effect, and therefore their therapeutic efficacy over longer time periods may need further assessment (109). Letouzé et al. showed that the DNA methytransferase inhibitor decitabine could repress the migration capacities of SDHB-mutant cells (40). However, for SDH- and FH-associated cancers, a synthetic lethality approach is worth exploring because of the pleiotrophic effects associated with succinate and fumarate accumulation.
Technological advances such as those in gas and liquid chromatography mass spectrometry (114, 115) and nuclear magnetic resonance imaging (102) have greatly improved the ability to measure low-molecular-weight metabolites in tumor samples with high resolution (116). Combined with metabolic flux analyses employing isotope tracers and mathematical modeling, modern-era metabolomic approaches can provide direct pathophysiological insights into tumor metabolism and serve as an excellent tool for biomarker discovery. Using a data-driven approach, Jain and colleagues constructed the metabolic profiles of 60 cancer cell lines and discovered glycine consumption as a key metabolic event in rapidly proliferating cancer cells (117), thus demonstrating the power of metabolomic analyses and the relevance to future cancer research and therapeutics.
Figure 1 D-2HG produced by mutant IDH1/2 affects metabolism and epigenetics by modulating activities of α-KG–dependent oxygenases. Wild-type IDH1 and IDH2 catalyze the NADP+-dependent reversible conversion of isocitrate to α-KG, whereas cancer-associated gain-of-function mutations enable mutant IDH1/2 (mIDH1/2) to catalyze the oxidation of α-KG to D-2HG, using NADPH as a cofactor. Because D-2HG is structurally similar to α-KG, its accumulation can modulate the activities of α-KG–utilizing dioxygenases. Inhibition of 5mC hydroxylase TET2 and the KDMs results in increased CpG island methylation and increased histone methylation marks, respectively, thus blocking lineage-specific cell differentiation. Inhibition of collagen prolyl and lysyl hydroxylases (C-P4Hs and PLODs, respectively) leads to impaired collagen maturation and disrupted basement membrane formation. D-2HG can also stimulate the activities of HIF PHDs, leading to enhanced HIF degradation and a diminished HIF response, which are associated with increased soft agar growth of human astrocytes and growth factor independence of leukemic cells. Together these processes exert pleiotrophic effects on cell signaling and gene expression that probably contribute to the malignancy of IDH1/2-mutant cells.
Figure 2 Candidate oncogenic mechanisms of succinate and fumarate accumulation. SDH and FH are Krebs cycle enzymes and tumor suppressors. Loss-of-function mutations in SDH and FH result in abnormal accumulation of Krebs cycle metabolites succinate (Succ) and fumarate (Fum), respectively, both of which can inhibit the activities of α-KG–dependent oxygenases. Inhibition of HIF PHDs leads to activation of HIF-mediated pseudohypoxic response, whereas inhibition of KDMs and TET family of 5mC hydroxylases causes epigenetic alterations. Fumarate is electrophilic and can also irreversibly modify cysteine residues in proteins by succination. Succination of KEAP1 in FH deficiency results in the constitutive activation of the antioxidant defense pathway mediated by NRF2, conferring a reductive milieu that promotes cell proliferation. Succination of the Krebs cycle enzyme Aco2 impairs aconitase activity in Fh1-deficient MEFs. Fumarate accumulation may also affect cytosolic pathways by inhibiting the reactions involved in the biosynthesis of arginine and purine. AcCoA, acetyl CoA; Mal, malate; OAA, oxaloacetate; Succ-CA, succinyl CoA.
2.1.1.2. Emerging concepts: linking hypoxic signaling and cancer metabolism.
The Joint Keystone Symposia on Cancer and Metabolism and Advances in Hypoxic Signaling: From Bench to Bedside were held in Banff, Alberta, Canada from 12 to 17 February 2012. Drs. Reuben Shaw and David Sabatini organized the Cancer and Metabolism section, and Drs. Volker Haase, Cormac Taylor, Johanna Myllyharju and Paul Schumacker organized the Advances in Hypoxic Signaling section. Accumulating data illustrate that both hypoxia and rewired metabolism influence cancer biology. Indeed, these phenomena are tightly coupled, and a joint meeting was held to foster interdisciplinary interactions and enhance our understanding of these two processes in neoplastic disease. In this report, we highlight the major themes of the conference paying particular attention to areas of intersection between hypoxia and metabolism in cancer.
One opening keynote address was delivered by Craig Thompson (Memorial Sloan-Kettering, USA), in which he provided a comprehensive perspective on the current thinking around how altered metabolism supports cancer cell growth and survival, and discussed areas likely to be important for future discovery. In particular, Thompson highlighted the essential roles of glucose and glutamine in cell growth, how glucose- and glutamine-consuming processes are rewired in cancer and how this rewiring facilitates anabolic metabolism. These topics were at the core of many of the metabolism presentations that described in detail how some metabolic alterations contribute to the properties of transformed cells.
The other keynote address was delivered by Peter Ratcliffe (University of Oxford, UK), in which he provided a historical perspective on the progress of how signaling events sense oxygen. Mammals have evolved multiple acute and long-term adaptive responses to low oxygen levels (hypoxia). This response prevents a disparity in ATP utilization and production that would otherwise result in a bioenergetic collapse when oxygen level is low. Multiple effectors have been proposed to mediate the response to hypoxia including prolyl hydroxylases, AMPK, NADPH oxidases and the mitochondrial complex III. Currently, however, the precise mechanism by which oxygen is sensed in various physiological contexts remains unknown. Indeed, this was an active point of debate, with Peter Ratcliffe favoring the prolyl hydroxylase PHD2 as the primary cellular oxygen sensor.
Anabolic glucose metabolism and the Warburg effect
Nearly a century ago, Warburg noted that cancer tissues take up glucose in excess than most normal tissues and secrete much of the carbon as lactate. Recently, headway has been made toward determining how the enhanced glucose conversion to lactate occurs and contributes to cell proliferation and survival. Heather Christofk (University of California, Los Angeles, USA) and John Cleveland (the Scripps Research Institute, USA) described a role for the lactate/pyruvate transporter MCT-1 in carbon secretion, and suggested that blocking lactate or pyruvate transport may be a strategy to target glucose metabolism in cancer cells. Kun-Liang Guan (University of California, San Diego, USA) described a novel feedback loop to control glucose metabolism in highly glycolytic cells. Specifically, he discussed how glucose-derived acetyl-CoA can be used as a substrate to modify two enzymes involved in glucose metabolism, pyruvate kinase M2 (PKM2) and phosphoenolpyruvate carboxylase (PEPCK). In both cases, acetylation leads to protein degradation and decreased glycolysis and gluconeogenesis, respectively. Data presented from Matthew Vander Heiden’s laboratory (Koch Institute/MIT, USA) illustrated that loss of pyruvate kinase activity can accelerate tumor growth, suggesting that the regulation of glycolysis may be more complex than previously appreciated. Almut Schulze (London Research Institute, UK) discussed a novel regulatory role for phosphofructokinase in controlling glucose metabolism and Jeffrey Rathmell (Duke University, USA) discussed parallels between glucose metabolism in cancer cells and lymphocytes that suggest many of these phenotypes could be a feature of rapidly dividing cells.
Glutamine addiction
Cancer cells also consume glutamine to support proliferation and survival. Alfredo Csibi (Harvard Medical School, USA) described how mTORC1 promotes glutamine utilization by indirectly regulating the activity of glutamate dehydrogenase. This work united two major themes at the meeting, mTOR signaling and glutamine metabolism, highlighting the interconnectedness of signal transduction and metabolic regulation. Richard Cerione (Cornell University, USA) described a small molecule inhibitor of glutaminase that can be used to target glutamine-addicted cancer cells. Christian Metallo (University of California, San Diego, USA), Andrew Mullen (University of Texas Southwestern Medical School, USA) and Patrick Ward (Memorial Sloan-Kettering, USA) presented data demonstrating that the carbon skeleton of glutamine can be incorporated into newly synthesized lipids. This contribution of glutamine to lipid synthesis was most pronounced in hypoxia or when the mitochondrial electron transport chain was compromised.
Signal transduction and metabolism
The protein kinases AMPK and mTOR can function as sensors of metabolic impairment, whose activation by energy stress controls multiple cellular functions. Grahame Hardie (University of Dundee, UK) and Reuben Shaw (Salk Institute, USA) highlighted novel roles for AMPK, including inhibition of viral replication, and the control of histone acetylation via phosphorylation of class IIa HDACs, respectively. Brandon Faubert (McGill University, USA) reported on an AMPK-dependent effect on glucose metabolism in unstressed cells. Brendan Manning (Harvard Medical School, USA) found that chronic activation of mTOR in the mouse liver, due to genetic ablation of this complex, promotes the development of liver cancer. Kevin Williams (University of California, Los Angeles, USA) discussed how growth signaling can control both lipid and glucose metabolism by impinging on SREBP-1, a transcription factor downstream of mTOR. AMPK-independent control of mTOR was addressed by John Blenis (Harvard Medical School, USA), who discussed the possible role of mTOR stabilizing proteins as mediators of mTOR inactivation upon energetic stress. David Sabatini (Whitehead Institute/MIT, USA) discussed several aspects of amino-acid sensing by Rag GTPases and showed that constitutive activation of the Rag GTPases leads to metabolic defects in mice.
One of the outcomes of AMPK activation and mTOR inhibition is autophagy, which can provide amino acids and fatty acids to nutrient-deprived cells. Ana Maria Cuervo (Albert Einstein College of Medicine, USA) and Eileen White (Rutgers University, USA) illuminated the role of chaperone-mediated autophagy (CMA) and macroautophagy, respectively, in tumor survival. White described a role for macroautophagy in the regulation of mitochondrial fitness, maintenance of TCA cycle and tumorigenesis induced by oncogenic Ras. Cuervo described how CMA is consistently elevated in tumor cells, and how its inactivation leads to metabolic impairment via p53-mediated downregulation of glycolytic enzymes.
Oncogene-specific changes to metabolism
Lewis Cantley (Harvard Medical School, USA) described a metabolic role for oncogenic Kras in the rewiring of glucose metabolism in pancreatic cancer. Specifically, Myc-mediated transcription (downstream of MEK-ERK signaling) both enhances glucose uptake and diverts glucose carbon into the nonoxidative pentose phosphate pathway to facilitate nucleotide biosynthesis. Alejandro Sweet-Cordero (Stanford University, USA) described how oncogenic Kras increases glycolysis and represses mitochondrial respiration (via decreased pyruvate dehydrogenase phosphatase 1 (PDP1) expression) in colon cancer. While these studies indicate that hyperstimulation of the Erk pathway suppresses PDH flux through suppression of PDP1, Joan Brugge (Harvard Medical School, USA) described studies showing that reduction of Erk signaling in normal epithelial cells also causes suppression of PDH flux, in this case through loss of repression of PDK4. The seemingly contradictory nature of these results highlighted an important theme emphasized throughout the week-long conference—that cellular context has an important role in shaping how oncogenic mutations or pathway activation rewires metabolism.
Targeting cancer metabolism
There was extensive discussion around targeting metabolism for cancer therapy. Metformin and phenformin, which act in part by mitochondrial complex I inhibition, can activate AMPK and influence cancer cell metabolism. Kevin Struhl (Harvard Medical School, USA) described how metformin can selectively target cancer stem cells, whereas Jessica Howell (Harvard Medical School, USA) described how the therapeutic activity of metformin relies on both AMPK and mTOR signaling to mediate its effect. Similarly, David Shackelford (University of California, Los Angeles, USA) demonstrated efficacy for phenformin in LKB1-deficient mouse models.
Several presentations, including those by Taru Muranen (Harvard Medical School, USA), Karen Vousden and Eyal Gottlieb (both from the Beatson Institute for Cancer Research, UK), provided insight into genetic control mechanisms that cancer cells use to promote survival under conditions of increased biosynthesis. As an example, Vousden illustrated how p53 loss can make cancer cells more dependent on exogenous serine. Several additional presentations, including those by Gottlieb, Richard Possemato (Whitehead Institute/MIT, USA), Michael Pollak (McGill University, USA) and Kevin Marks (Agios Pharmaceuticals, USA), also included data highlighting the important role of serine biosynthesis and metabolism in cancer growth. Collectively, these data highlight a metabolic addiction that may be therapeutically exploitable. Similarly, Cristina Muñoz-Pinedo (Institut d’Investigació Biomèdica, Spain) described how mimicking glucose deprivation with 2-deoxyglucose can cause programmed cell death and may be an effective cancer treatment.
Regulation of hypoxic responses
Peter Carmeliet (University of Leuven, Belgium) highlighted the mechanisms of resistance against VEGF-targeted therapies. Roland Wenger (University of Zurich, Switzerland) discussed the oxygen-responsive transcriptional networks and, in particular, the difference between the transcription factors HIF-1α and HIF-2α. Importantly, he demonstrated a rapid role for HIF-1α, and a later and more persistent response for HIF-2α. These results were central to a recurrent theme calling for the distinction of HIF-1α and HIF-2α target genes and how these responses mediate divergent hypoxic adaptations.
Advances in hypoxic signaling
Brooke Emerling (Harvard Medical School, USA) introduced CUB domain-containing protein 1 (CDCP1) and showed persuasive data on CDCP1 being a HIF-2α target gene involved in cell migration and metastasis, and suggested CDCP1 regulation as an attractive therapeutic target. Johannes Schodel (University of Oxford, UK) described an elegant HIF-ChIP-Seq methodology to define direct transcriptional targets of HIF in renal cancer.
Randall Johnson (University of Cambridge, UK) emphasized that loss of HIF-1α results in decreased lung metastasis. Lorenz Poellinger (Karolinska Institutet, Sweden) focused on how hypoxia can alter the epigenetic landscape of cells, and furthermore, how the disruption of the histone demethylase JMJD1A and/or the H3K9 methyltransferase G9a has opposing effects on tumor growth and HIF target gene expression.
Paul Schumacker (Northwestern University, USA) further emphasized the importance of mitochondrial ROS signaling under hypoxic conditions showing that ROS could be detected in the inter-membrane space of the mitochondria before activating signaling cascades in the cytosol. He also presented evidence for mitochondria as a site of oxygen sensing in diverse cell types. Similarly, Margaret Ashcroft (University College London, UK) argued for a critical role of mitochondria in hypoxic signaling. She presented on a family of mitochondrial proteins (CHCHD4) that influence hypoxic signaling and tumorigenesis and suggested that CHCHD4 is important for HIF and tumor progression.
2.1.1.3 Glutaminolysis: supplying carbon or nitrogen or both for cancer cells?
Dang CV
Cell Cycle. 2010 Oct 1; 9(19):3884-6
A cancer cell comprising largely of carbon, hydrogen, oxygen, phosphorus, nitrogen and sulfur requires not only glucose, which is avidly transported and converted to lactate by aerobic glycolysis or the Warburg effect, but also glutamine as a major substrate. Glutamine and essential amino acids, such as methionine, provide energy through the TCA cycle as well as nitrogen, sulfur and carbon skeletons for growing and proliferating cancer cells. The interplay between utilization of glutamine and glucose is likely to depend on the genetic make-up of a cancer cell. While the MYC oncogene induces both aerobic glycolysis and glutaminolysis, activated β-catenin induces glutamine synthesis in hepatocellular carcinoma. Cancer cells that have elevated glutamine synthetase can use glutamate and ammonia to synthesize glutamine and are hence not addicted to glutamine. As such, cancer cells have many degrees of freedom for re-programming cell metabolism, which with better understanding will result in novel therapeutic approaches.
Figure 1. Glutamine, glucose and glutamate are imported into the cytoplasm of a cell. Glucose is depicted to be converted primarily (large powder blue arrow) to lactate via aerobic glycolysis or the Warburg effect or channeled into the mitochondrion as pyruvate and converted to acetyl-CoA for oxidation. Glutamine is shown imported and used for different processes including glutaminolysis, which involves the conversion of glutamine to glutamate and ammonia by glutaminase (GLS). Glutamate is further oxidized via the TCA cycle to produce ATP and contribute anabolic carbon skeletons. Some cells can import glutamate and use ammonia to generate glutamine through glutamine synthetase (GLUL); glutamine could then be used for different purposes including glutathione synthesis (not shown).
The liver is organized into lobules, which have zones of cells around the perivenous region enriched with glutamine synthetase, which detoxifies ammonia by converting it to glutamine through the amination of glutamate (Fig. 1). As such, liver cancers vary in the degree of glutamine synthetase expression depending on the extent of anaplasia or de-differentiation. Highly undifferentiated liver cancers tend to be more glycolytic than those that retain some of the differentiated characteristics of liver cells. Furthermore, glutamine synthetase (considered as a direct target of activated β-catenin, which also induces ornithine aminotransferase and glutamate transporters) expression in liver cancers has been directly linked to β-catenin activation or mutations. Hence, the work by Meng et al. illustrates, first and foremost, the metabolic heterogeneity amongst cancer cell lines, such that the ability to utilize ammonia instead of glutamine by Hep3B cells depends on the expression of glutamine synthetase. The Hep3B cells are capable of producing glutamine from glutamate and ammonia, as suggested by the observation that a glutamine-independent derivative of Hep3B has high expression of glutamine synthetase. In this regard, Hep3B could utilize glutamate directly for the production of α-ketoglutarate or to generate glutamine for protein synthesis or other metabolic processes, such as to import essential amino acids. In contrast to Hep3B, other cell lines in the Meng et al. study were not demonstrated to be glutamine independent and thus become ammonia auxotrophs. Hence, the mode of glutamine or glucose utilization is dependent on the metabolic profile of cancer cells.
The roles of glutamine in different cancer cell lines are likely to be different depending on their genetic and epigenetic composition. In fact, well-documented isotopic labeling studies have demonstrated a role for glutamine to provide anapleurotic carbons in certain cancer and mammalian cell types. But these roles of glutaminolysis, whether providing nitrogen or anabolic carbons, should not be generalized as mutually exclusive features of all cancer cells. From these considerations, it is surmised that the expression of glutamine synthetase in different cancers will determine the extent by which these cancers are addicted to exogenous glutamine.
2.1.1.4 The Warburg effect and mitochondrial stability in cancer cells
The last decade has witnessed a renaissance of Otto Warburg’s fundamental hypothesis, which he put forward more than 80 years ago, that mitochondrial malfunction and subsequent stimulation of cellular glucose utilization lead to the development of cancer. Since most tumor cells demonstrate a remarkable resistance to drugs that kill non-malignant cells, the question has arisen whether such resistance might be a consequence of the abnormalities in tumor mitochondria predicted by Warburg. The present review discusses potential mechanisms underlying the upregulation of glycolysis and silencing of mitochondrial activity in cancer cells, and how pharmaceutical intervention in cellular energy metabolism might make tumor cells more susceptible to anti-cancer treatment.
Fig. 1. (1) Oligomerization of Bax is mediated by the truncated form of the BH3-only, pro-apoptotic protein Bid (tBid); (2) Bcl-2, Bcl-XL, Mcl-1, and Bcl-w, interact with the pro-apoptotic proteins, Bax and Bak, to prevent their oligomerization; (3) The anti-apoptotic protein Bcl-XL prevents tBid-induced closure of VDAC and apoptosis by maintaining VDAC in open configuration allowing ADT/ATP exchange and normal mitochondrial functioning; (4) MPT pore is a multimeric complex, composed of VDAC located in the OMM, ANT, an integral protein of the IMM, and a matrix protein, CyPD; (5) Interaction with VDAC allows hexokinase to use exclusively intramitochondrial ATP to phosphorylate glucose, thereby maintaining high rate of glycolysis.
Fig. 2. Different sites of therapeutic intervention in cancer cell metabolism. (1) The non-metabolizable analog of glucose, 2-deoxyglucose, decreases ATP level in the cell; (2) 3-bromopyruvate suppresses the activity of hexokinase, and respiration in isolated mitochondria; (3) Phloretin a glucose transporter inhibitor, decreases ATP level in the cell and markedly enhances the anti-cancer effect of daunorubicin; (4) Dichloroacetate (DCA) shifts metabolism from glycolysistoglucoseoxidation;(5)Apoptolidin,aninhibitorofmitochondrialATPsynthase,inducescelldeathindifferentmalignantcelllineswhenapplied together with the LDH inhibitor oxamate (6).
►Mitochondrial hallmarks of tumor cells.►Complex I of the respiratory chain is reduced in many cancer cells.►Oligomers of F1F0ATPase are reduced in cancer cells.►Mitochondrial membranes are critical to the life or death of cancer cells.
Evidence suggests that mitochondrial metabolism may play a key role in controlling cancer cells life and proliferation. Recent evidence also indicates how the altered contribution of these organelles to metabolism and the resistance of cancer mitochondria against apoptosis-associated permeabilization are closely related. The hallmarks of cancer growth, increased glycolysis and lactate production in tumours, have raised attention due to recent observations suggesting a wide spectrum of oxidative phosphorylation deficit and decreased availability of ATP associated with malignancies and tumour cell expansion. More specifically, alteration in signal transduction pathways directly affects mitochondrial proteins playing critical roles in controlling the membrane potential as UCP2 and components of both MPTP and oxphos complexes, or in controlling cells life and death as the Bcl-2 proteins family. Moreover, since mitochondrial bioenergetics and dynamics, are also involved in processes of cells life and death, proper regulation of these mitochondrial functions is crucial for tumours to grow. Therefore a better understanding of the key pathophysiological differences between mitochondria in cancer cells and in their non-cancer surrounding tissue is crucial to the finding of tools interfering with these peculiar tumour mitochondrial functions and will disclose novel approaches for the prevention and treatment of malignant diseases. Here, we review the peculiarity of tumour mitochondrial bioenergetics and the mode it is linked to the cell metabolism, providing a short overview of the evidence accumulated so far, but highlighting the more recent advances. This article is part of a Special Issue entitled: Bioenergetics of Cancer.
Mitochondria are essential organelles and key integrators of metabolism, but they also play vital roles in cell death and cell signaling pathways critically influencing cell fate decisions [1], [2] and [3]. Mammalian mitochondria contain their own DNA (mtDNA), which encodes 13 polypeptides of oxidative phosphorylation complexes, 12S and 16S rRNAs, and 22 tRNAs required for mitochondrial function [4]. In order to synthesize ATP through oxidative phosphorylation (oxphos), mitochondria consume most of the cellular oxygen and produce the majority of reactive oxygen species (ROS) as by-products [5]. ROS have been implicated in the etiology of carcinogenesis via oxidative damage to cell macromolecules and through modulation of mitogenic signaling pathways [6], [7] and [8]. In addition, a number of mitochondrial dysfunctions of genetic origin are implicated in a range of age-related diseases, including tumours [9]. How mitochondrial functions are associated with cancer is a crucial and complex issue in biomedicine that is still unravelled [10] and [11], but it warrants an extraordinary importance since mitochondria play a major role not only as energy suppliers and ROS “regulators”, but also because of their control on cellular life and death. This is of particular relevance since tumour cells can acquire resistance to apoptosis by a number of mechanisms, including mitochondrial dysfunction, the expression of anti-apoptotic proteins or by the down-regulation or mutation of pro-apoptotic proteins [12].
Cancer cells must adapt their metabolism to produce all molecules and energy required to promote tumor growth and to possibly modify their environment to survive. These metabolic peculiarities of cancer cells are recognized to be the outcome of mutations in oncogenes and tumor suppressor genes which regulate cellular metabolism. Mutations in genes including P53, RAS, c-MYC, phosphoinosine 3-phosphate kinase (PI3K), and mTOR can directly or through signaling pathways affect metabolic pathways in cancer cells as discussed in several recent reviews [13], [14], [15], [16] and [17]. Cancer cells harboring the genetic mutations are also able to thrive in adverse environments such as hypoxia inducing adaptive metabolic alterations which include glycolysis up-regulation and angiogenesis factor release [18] and [19]. In response to hypoxia, hypoxia-induced factor 1 (HIF-1) [20], a transcription factor, is up-regulated, which enhances expression of glycolytic enzymes and concurrently it down regulates mitochondrial respiration through up-regulation of pyruvate dehydrogenase kinase 1 (PDK1) (see recent reviews [21] and [22]). However, several tumours have been reported to display high HIF-1 activity even in normoxic condition, now referred to as pseudohypoxia [23], [24] and [25]. In addition, not only solid tumours present a changed metabolism with respect to matched normal tissues, hematological cell malignancies also are characterized by peculiar metabolisms, in which changes of mitochondrial functions are significant [26],[27] and [28], therefore indicating a pivotal role of mitochondria in tumours independently from oxygen availability.
Collectively, actual data show a great heterogeneity of metabolism changes in cancer cells, therefore comprehensive cellular and molecular basis for the association of mitochondrial bioenergetics with tumours is still undefined, despite the numerous studies carried out. This review briefly revisits the data which are accumulating to account for this association and highlights the more recent advances, particularly focusing on the metabolic and structural changes of mitochondria.
Mitochondria-related metabolic changes of cancer cells
Accumulating evidence indicate that many cancer cells have an higher glucose consumption under normoxic conditions with respect to normal differentiated cells, the so-called “aerobic glycolysis” (Warburg effect), a phenomenon that is currently exploited to detect and diagnose staging of solid and even hematological malignancies [27]. Since the initial publication by Otto Warburg over half a century ago [29], an enormous amount of studies on many different tumours have been carried out to explain the molecular basis of the Warburg effect. Although the regulatory mechanisms underlying aerobic and glycolytic pathways of energy production are complex, making the prediction of specific cellular responses rather difficult, the actual data seem to support the view that in order to favour the production of biomass, proliferating cells are commonly prone to satisfy the energy requirement utilizing substrates other than the complete oxidation of glucose (to CO2 and H2O). More precisely, only part (40 to 75%, according to [30]) of the cells need of ATP is obtained through the scarcely efficient catabolism of glucose to pyruvate/lactate in the cytoplasm and the rest of the ATP need is synthesized in the mitochondria through both the tricarboxylic acid (TCA) cycle (one ATP produced each acetyl moiety oxidized) and the associated oxidative phosphorylation that regenerates nicotinamide- and flavin-dinucleotides in their oxidized state(NAD+ and FAD). This might be due to the substrate availability as it was shown in HeLa cells, where replacing glucose with galactose/glutamine in the culture medium induced increased expression of oxphos proteins, suggesting an enhanced energy production from glutamine [31]. As a conclusion the authors proposed that energy substrate can modulate mitochondrial oxidative capacity in cancer cells. A direct evidence of this phenomenon was provided a few years later in glioblastoma cells, in which it was demonstrated that the TCA cycle flux is significantly sustained by anaplerotic alfa-ketoglutarate produced from glutamine and by acetyl moieties derived from the pyruvate dehydrogenase reaction where pyruvate may have an origin other than glucose [32]. The above changes are the result of genetic alteration and environmental conditions that induce many cancer cells to change their metabolism in order to synthesize molecules necessary to survive, grow and proliferate, including ribose and NADPH to synthesize nucleotides, and glycerol-3 phosphate to produce phospholipids. The synthesis of the latter molecules requires major amount of acetyl moieties that are derived from beta-oxidation of fatty acids and/or from cytosolic citrate (citrate lyase reaction) and/or from the pyruvate dehydrogenase reaction. Given the important requirement for NADPH in macromolecular synthesis and redox control, NADPH production in cancer cells besides being produced through the phosphate pentose shunt, may be significantly sustained by cytosolic isocitrate dehydrogenases and by the malic enzyme (see Ref. [33] for a recent review). Therefore, many cancer cells tend to have reduced oxphos in the mitochondria due to either or both reduced flux within the tricarboxylic acid cycle and/or respiration (Fig. 1). The latter being also caused by reduced oxygen availability, a typical condition of solid tumors, that will be discussed below.
Schematic illustration of mitochondrial metabolism and metabolic reprogramming in tumours gr1
Fig. 1. Schematic illustration of mitochondrial metabolism and metabolic reprogramming in tumours. In normal cells (A), glucose is phosphorylated by HK-I, then the major part is degraded via glycolysis to pyruvate, which prevalently enters the mitochondria, it is decarboxylated and oxidized by PDH to acetyl-coenzyme A, which enters the TCA cycle where the two carbons are completely oxidized to CO2 whereas hydrogen atoms reduce NAD+ and FAD, which feed the respiratory chain (turquoise). Minor part of glycolytic G-6P is diverted to produce ribose 5-phosphate (R-5P) and NADPH, that will be used to synthesize nucleotides, whereas triose phosphates in minimal part will be used to synthesize lipids and phospholipids with the contribution of NADPH and acetyl-coenzyme A. Amino acids, including glutamine (Gln) will follow the physiological turnover of the proteins, in minimal part will be used to synthesize the nucleotides bases, and the excess after deamination will be used to produce energy. In the mitochondria inner membranes are located the respiratory chain complexes and the ATP synthase (turquoise), which phosphorylates ADP releasing ATP, that in turn is carried to the cytosol by ANT (green) in exchange for ADP. About 1–2% O2 uptaken by the mitochondria is reduced to superoxide anion radical and ROS. In cancer cells (B), where anabolism is enhanced, glucose is mostly phosphorylated by HK-II (red), which is up-regulated and has an easy access to ATP being more strictly bound to the mitochondria. Its product, G-6P, is only in part oxidized to pyruvate. This, in turn, is mostly reduced to lactate being both LDH and PDH kinase up-regulated. A significant part of G-6P is used to synthesize nucleotides that also require amino acids and glutamine. Citrate in part is diverted from the TCA cycle to the cytosol, where it is a substrate of citrate lyase, which supplies acetyl-coenzyme A for lipid and phospholipid synthesis that also requires NADPH. As indicated, ROS levels in many cancer cells increase.
Of particular relevance in the study of the metabolic changes occurring in cancer cells, is the role of hexokinase II. This enzyme is greatly up-regulated in many tumours being its gene promoter sensitive to typical tumour markers such as HIF-1 and P53 [30]. It plays a pivotal role in both the bioenergetic metabolism and the biosynthesis of required molecules for cancer cells proliferation. Hexokinase II phosphorylates glucose using ATP synthesized by the mitochondrial oxphos and it releases the product ADP in close proximity of the adenine nucleotide translocator (ANT) to favour ATP re-synthesis within the matrix (Fig. 1). Obviously, the expression level, the location, the substrate affinity, and the kinetics of the enzyme are crucial to the balancing of the glucose fate, to either allowing intermediates of the glucose oxidation pathway towards required metabolites for tumour growth or coupling cytoplasmic glycolysis with further oxidation of pyruvate through the TCA cycle, that is strictly linked to oxphos. This might be possible if the mitochondrial-bound hexokinase activity is reduced and/or if it limits ADP availability to the mitochondrial matrix, to inhibit the TCA cycle and oxphos. However, the mechanism is still elusive, although it has been shown that elevated oncogene kinase signaling favours the binding of the enzyme to the voltage-dependent anion channel (VDAC) by AKT-dependent phosphorylation [34] (Fig. 2). VDAC is a protein complex of the outer mitochondrial membrane which is in close proximity of ANT that exchanges ADP for ATP through the inner mitochondrial membrane [35]. However, the enzyme may also be detached from the mitochondrial membrane, to be redistributed to the cytosol, through the catalytic action of sirtuin-3 that deacylates cyclophilin D, a protein of the inner mitochondrial membrane required for binding hexokinase II to VDAC (Fig. 2) [36]. Removing hexokinase from the mitochondrial membrane has also another important consequence in cancer cells: whatever mechanism its removal activates, apoptosis is induced [37] and [38]. These observations indicate hexokinase II as an important tool used by cancer cells to survive and proliferate under even adverse conditions, including hypoxia, but it may result an interesting target to hit in order to induce cells cytotoxicity. Indeed, a stable RNA interference of hexokinase II gene showed enhanced apoptosis indices and inhibited growth of human colon cancer cells; in accordance in vivo experiments indicated a decreased tumour growth [39].
Schematic illustration of the main mitochondrial changes frequently occurring in cancer cells gr2
Fig. 2. Schematic illustration of the main mitochondrial changes frequently occurring in cancer cells. The reprogramming of mitochondrial metabolism in many cancer cells comprises reduced pyruvate oxidation by PDH followed by the TCA cycle, increased anaplerotic feeding of the same cycle, mostly from Gln, whose entry in the mitochondrial matrix is facilitated by UCP2 up-regulation. This increases also the free fatty acids uptake by mitochondria, therefore β-oxidation is pushed to produce acetyl-coenzyme A, whose oxidation contributes to ATP production. In cancer cells many signals can converge on the mitochondrion to regulate the mitochondrial membrane permeability, which may respond by elevating the MPTP (PTP) threshold, with consequent enhancement of apoptosis resistance. ROS belong to this class of molecules since it can enhance Bcl2 and may induce DNA mutations. Dotted lines indicate regulation; solid lines indicate reaction(s).
Respiratory chain complexes and ATP synthase
Beyond transcriptional control of metabolic enzyme expression by oncogenes and tumour suppressors, it is becoming evident that environmental conditions affect the mitochondrial energy metabolism, and many studies in the last decade indicate that mitochondrial dysfunction is one of the more recurrent features of cancer cells, as reported at microscopic, molecular, biochemical, and genetic level [7], [40] and [41]. Although cancer cells under several conditions, including hypoxia, oncogene activation, and mDNA mutation, may substantially differ in their ability to use oxygen, only few reports have been able to identify a strict association between metabolic changes and mitochondrial complexes composition and activity. In renal oncocytomas [42] and in lung epidermoid carcinoma [43], the NADH dehydrogenase activity and protein content of Complex I were found to be strongly depressed; subsequently, in a thyroid oncocytoma cell line [44] a similar decrease of Complex I activity was ascribed to a specific mutation in the ND1 gene of mitochondrial DNA. However, among the respiratory chain complexes, significant decrease of the only Complex I content and activity was found in K-ras transformed cells in our laboratory [45], and could not be ascribed to mtDNA mutations, but rather, based on microarray analysis of oxphos genes, we proposed that a combination of genetic (low transcription of some genes) and biochemical events (assembly factors deficiency, disorganization of structured supercomplexes, and ROS-induced structural damage) might cause the Complex I defects.
In some hereditary tumours (renal cell carcinomas) a correlation has been identified between mitochondrial dysfunctions and content of oxphos complexes [46]. For instance, the low content of ATP synthase, often observed in clear cell type renal cell carcinomas and in chromophilic tumours, seems to indicate that the mitochondria are in an inefficient structural and functional state [46]. However, it cannot be excluded that, in some cases, the structural alteration of ATP synthase may offer a functional advantage to cells exhibiting a deficient respiratory chain for instance to preserve the transmembrane electrical potential (Δψm) [47]. It is likely that low levels of ATP synthases may play a significant role in cancer cell metabolism since it has been reported that in tumours from many different tissues, carcinogenesis specifically affects the expression of F1-ATPase β subunit, suggesting alterations in the mechanisms that control mitochondrial differentiation (see for a detailed review [48]). What it seems intriguing is the overexpression of the inhibitor protein, IF1, reported in hepatocellular carcinomas [49] and [50] and in Yoshida sarcoma [51]. Normally, this protein binds to the F1 domain of the ATP synthase inhibiting its activity [52], and it is believed to limit the ATP hydrolysis occurring in the mitochondria of hypoxic cells, avoiding ATP depletion and maintaining Δψm to a level capable to avoid the induction of cell death [5]. But why is its expression in cancer cells enhanced in front of a reduced F1-ATPase β subunit?
The first possibility is that IF1 has a function similar to that in normal cells, simply avoiding excessive ATP hydrolysis therefore limiting Δψm enhancement, but in cancer cells this is unlikely due to both the reduced level of ATP synthase [46] and the high affinity of IF1 for the enzyme. A second possibility might be that cancer cells need strongly reduced oxphos to adapt their metabolism and acquire a selective growth advantage under adverse environmental conditions such as hypoxia, as it has been experimentally shown [53]. Finally, IF1 might contribute to the saving of the inner mitochondrial membrane structure since it has been reported its capability to stabilize oligomers of ATP synthase, which in turn can determine cristae shapes [54]. In this regard, recent experimental evidence has shed some light on a critical role of mitochondrial morphology in the control of important mitochondrial functions including apoptosis [55] and oxidative phosphorylation [56]. In particular, dysregulated mitochondrial fusion and fission events can now be regarded as playing a role in cancer onset and progression [57]. Accordingly, mitochondria-shaping proteins seem to be an appealing target to modulate the mitochondrial phase of apoptosis in cancer cells. In fact, several cancer tissues: breast, head-and-neck, liver, ovarian, pancreatic, prostate, renal, skin, and testis, showed a pattern suggestive of enlarged mitochondria resulting from atypical fusion [58].
Mitochondrial membrane potential in cancer cells
Critical mitochondrial functions, including ATP synthesis, ion homeostasis, metabolites transport, ROS production, and cell death are highly dependent on the electrochemical transmembrane potential, a physico-chemical parameter consisting of two components, the major of which being the transmembrane electrical potential (Δψm) (see for a recent review [59]). In normal cells, under normoxic conditions, Δψm is build up by the respiratory chain and is mainly used to drive ATP synthesis, whereas in anoxia or severe hypoxia it is generated by the hydrolytic activity of the ATP synthase complex and by the electrogenic transport of ATP in exchange for ADP from the cytosol to the matrix, operated by the adenine nucleotide translocator [17]. Dissipation of the mitochondrial membrane potential (proton leak) causes uncoupling of the respiratory chain electron transport from ADP phosphorylation by the ATP synthase complex. Proton leak functions as a regulator of mitochondrial ROS production and its modulation by uncoupling proteins may be involved in pathophysiology, including tumours. In addition, Δψm plays a role in the control of the mitochondrial permeability transition pore (MPTP), that might be critical in determining reduced sensitivity to stress stimuli that were described in neoplastic transformation [60], implying that dysregulation of pore opening might be a strategy used by tumour cells to escape death. Indeed, it has recently been reported that ERK is constitutively activated in the mitochondria of several cancer cell types, where it inhibits glycogen synthase kinase-3-dependent phosphorylation of CyP-D and renders these cells more refractory to pore opening and to the ensuing cell death [61].
It is worth mentioning a second protein of the inner mitochondrial membrane, the uncoupling protein, UCP2 (Fig. 2), which contributes to regulate Δψm. Indeed, recent observations evidenced its overexpression in various chemoresistent cancer cell lines and in primary human colon cancer. This overexpression was associated with an increased apoptotic threshold [62]. Moreover, UCP2 has been reported to be involved in metabolic reprogramming of cells, and appeared necessary for efficient oxidation of glutamine [63]. On the whole, these results led to hypothesize an important role of the uncoupling protein in the molecular mechanism at the basis of the Warburg effect, that suppose a reduced Δψm-dependent entry of pyruvate into the mitochondria accompanied by enhanced fatty acid oxidation and high oxygen consumption (see for a review [64]). However, in breast cancer Sastre-Serra et al. [65] suggested that estrogens by down-regulating UCPs, increase mitochondrial Δψm, that in turn enhances ROS production, therefore increasing tumorigenicity. While the two above points of view concur to support increased tumorigenicity, the mechanisms at the basis of the phenomenon appear on the opposite of the other. Therefore, although promising for the multiplicity of metabolic effects in which UCPs play a role (see for a recent review [66]), at present it seems that much more work is needed to clarify how UCPs are related to cancer.
A novel intriguing hypothesis has recently been put forward regarding effectors of mitochondrial function in tumours. Wegrzyn J et al. [67] demonstrated the location of the transcription factor STAT3 within the mitochondria and its capability to modulate respiration by regulating the activity of Complexes I and II, and Gough et al. [68] reported that human ras oncoproteins depend on mitochondrial STAT3 for full transforming potential, and that cancer cells expressing STAT3 have increased both Δψm and lactate dehydrogenase level, typical hallmarks of malignant transformation (Fig. 2). A similar increase of Δψm was recently demonstrated in K-ras transformed fibroblasts [45]. In this study, the increased Δψm was somehow unexpected since the cells had shown a substantial decrease of NADH-linked substrate respiration rate due to a compatible reduced Complex I activity with respect to normal fibroblasts. The authors associated the reduced activity of the enzyme to its peculiar low level in the extract of the cells that was confirmed by oxphos nuclear gene expression analysis. This significant and peculiar reduction of Complex I activity relative to other respiratory chain complexes, is recurrent in a number of cancer cells of different origin [42], [44], [45] and [69]. Significantly, all those studies evidenced an overproduction of ROS in cancer cells, which was consistent with the mechanisms proposed by Lenaz et al. [70] who suggested that whatever factor (i.e. genetic or environmental) initiate the pathway, if Complex I is altered, it does not associate with Complex III in supercomplexes, consequently it does not channel correctly electrons from NADH through coenzyme Q to Complex III redox centres, determining ROS overproduction. This, in turn, enhances respiratory chain complexes alteration resulting in further ROS production, thus establishing a vicious cycle of oxidative stress and energy depletion, which can contribute to further damaging cells pathways and structures with consequent tumour progression and metastasis [69].
Hypoxia and oxidative phosphorylation in cancer cells
Tumour cells experience an extensive heterogeneity of oxygen levels, from normoxia (around 2–4% oxygen tension), through hypoxia, to anoxia (< 0.1% oxygen tension). The growth of tumours beyond a critical mass > 1–2 mm3 is dependent on adequate blood supply to receive nutrients and oxygen by diffusion [88]. Cells adjacent to capillaries were found to exhibit a mean oxygen concentration of 2%, therefore, beyond this distance, hypoxia occurs: indeed, cells located at 200 μm displayed a mean oxygen concentration of 0.2%, which is a condition of severe hypoxia [89]. Oxygen shortage results in hypoxia-dependent inhibition of mitochondrial activity, mostly mediated by the hypoxia-inducible factor 1 (HIF-1)[90] and [91]. More precisely, hypoxia affects structure, dynamics, and function of the mitochondria, and in particular it has a significant inhibitory effect on the oxidative phosphorylation machinery, which is the main energy supplier of cells (see Ref. [22] for a recent review). The activation of HIF-1 occurs in the cytoplasmic region of the cell, but the contribution of mitochondria is critical being both cells oxygen sensors and suppliers of effectors of HIF-1α prolyl hydroxylase like α-ketoglutarate and probably ROS, that inhibit HIF-1α removal [92]. As reported above, mitochondria can also promote HIF-1α stabilization if the TCA flux is severely inhibited with release of intermediate molecules like succinate and fumarate into the cytosol. On the other hand, HIF-1 can modulate mitochondrial functions through different mechanisms, that besides metabolic reprogramming [7], [22], [93] and [94], include alteration of mitochondrial structure and dynamics[58], induction of microRNA-210 that decreases the cytochrome c oxidase (COX) activity by inhibiting the gene expression of the assembly protein COX10 [95], that also increases ROS generation. Moreover, these stress conditions could induce the anti-apoptotic protein Bcl-2, which has also been reported to regulate COX activity and mitochondrial respiration [96] conferring resistance to cells death in tumours (Fig. 2). This effect might be further enhanced upon severe hypoxia conditions, since COX is also inhibited by NO, the product of activated nitric oxide synthases [97].
The reduced respiration rate occurring in hypoxia favours the release of ROS also by Complex III, which contribute to HIF stabilization and induction of Bcl-2 [98]. In addition, hypoxia reduces oxphos by inhibiting the ATP synthase complex through its natural protein inhibitor IF1 (discussed in a previous section), which contributes to the enhancement of the “aerobic glycolysis”, all signatures of cancer transformation.
The observations reported to date indicate that cancer cells exhibit large varieties of metabolic changes which are associated with alterations in the mitochondrial structure, dynamics and function, and with tumour growth and survival. On one hand, mitochondria can regulate tumour growth through modulation of the TCA cycle and oxidative phosphorylation. The altered TCA cycle provides intermediates for both macromolecular biosynthesis and regulation of transcription factors such as HIF, and it allows cytosolic reductive power enhancement. Oxphos provides significant amounts of ATP which varies among tumour types. On the other hand, mitochondria are crucial in controlling redox homeostasis in the cell, inducing them to be either resistant or sensitive to apoptosis. All these reasons locate mitochondria at central stage to understanding the molecular basis of tumour growth and to seeking for novel therapeutical approaches.
Due to the complexity and variability of mitochondrial roles in cancer, careful evaluation of mitochondrial function in each cancer type is crucial. Deeper and more integrated knowledge of mitochondrial mechanisms and cancer-specific mitochondrial modulating means are expected for reducing tumorigenicity and/or improving anticancer drugs efficacy at the mitochondrial level. Although the great variability of biochemical changes found in tumour mitochondria, some highlighted peculiarities such as reduced TCA cycle flux, reduced oxphos rate, and reduced Complex I activity with respect to tissue specific normal counterparts are more frequent. In addition, deeper examination of supramolecular organization of the complexes in the inner mitochondrial membrane has to be considered in relation to oxphos dysfunction.
2.1.1.6 Oxidation–reduction states of NADH in vivo: From animals to clinical use
Mitochondrial dysfunction is part of many pathological states in patients, such as sepsis or stroke. Presently, the monitoring of mitochondrial function in patients is extremely rare, even though NADH redox state is routinely measured in experimental animals. In this article, we describe the scientific backgrounds and practical use of mitochondrial NADH fluorescence measurement that was applied to patients in the past few years. In addition to NADH, we optically measured the microcirculatory blood flow and volume, as well as HbO(2) oxygenation, from the same tissue area. The four detected parameters provide real time data on tissue viability, which is critical for patients monitoring.
(very important article)
2.1.1.7 Mitochondria in cancer. Not just innocent bystanders
The first half of the 20th century produced substantial breakthroughs in bioenergetics and mitochondria research. During that time, Otto Warburg observed abnormally high glycolysis and lactate production in oxygenated cancer cells, leading him to suggest that defects in mitochondrial functions are at the heart of malignant cell transformation. Warburg’s hypothesis profoundly influenced the present perception of cancer metabolism, positioning what is termed aerobic glycolysis in the mainstream of clinical oncology. While some of his ideas stood the test of time, they also frequently generated misconceptions regarding the biochemical mechanisms of cell transformation. This review examines experimental evidence which supports or refutes the Warburg effect and discusses the possible advantages conferred on cancer cells by ‘metabolic transformation’.
Fig.1. Mitochondria as a crossroad for catabolic and anabolic pathways in normal and cancer cells. Glucose and glutamine are important carbon sources which are metabolized in cells for the generation of energy and anabolic precursors. The pathways discussed in the text are illustrated and colour coded: red, glycolysis; white, TCA cycle; pink, non-essential amino acids synthesis; orange, pentose phosphate pathway and nucleotide synthesis; green, fatty acid and lipid synthesis; blue, pyruvate oxidation in the mitochondria; brown, glutaminolysis; black, malic enzyme reaction. Solid arrows indicate a single step reaction;dashed-dotted arrows indicate transport across membranes and dotted arrows indicate multi-step reactions. Abbreviations: HK, hexokinase; AcCoA, acetyl co-enzyme A; OAA, oxaloacetate; αKG, α-ketoglutarate.
Fig. 2. Mitochondria as a target for multiple metabolic transformation events. Principal metabolic perturbations of cancer cells are induced by genetic reprogramming and environmental changes. The activation of Akt and MYC oncogenes and the loss of p53 tumor suppressor gene are among the most frequent events in cancer. Furthermore, all solid tumors are exposed to oxidative stress and hypoxia hence to HIF activation.These frequent changes in cancer cells trigger a dramatic metabolic shift from oxidative phosphorylation to glycolysis. In addition, direct genetic lesions of mtDNA or of nuclear encoded mitochondrial enzyme (SDH or FH) can directly abrogate oxidative phosphorylation in cancer. 3- D structures of the respiratory complexes in the scheme were retrieved from Protein DataBank (PDB:www.rcsb.org) except for complex I which was retrieved from [87]. PDB codes are as follow: SDH (II), 1 LOV; complex III (III), 1BGY; COX (IV), 1OCC; ATP synthase (V), 1QO1.
Fig. 3. The physiological roles of SDH in the TCA cycle and the ETC and its potential roles in cancer. (A) Ribbon diagram of SDH structure (PBD code: 1LOV). The catalytic subunits: the flavoprotein (SDHA) and the iron-sulphur protein (SDHB) are depicted in red and yellow, respectively, and the membrane anchors and ubiquinone binding proteins SDHC and SDHD are depicted in cyan and green, respectively. (B) Other than being a TCA enzyme, SDH is an additional entry point to the ETC (most electrons are donated from NADH to complex I—not shown in this diagram). The electron flow in and out of complex II and III is depicted by the yellow arrows. During succinate oxidation to fumarate by SDHA, a two-electron reduction of FAD to FADH2 occurs. Electrons are transferred through their on–Sulphur centres on SDHB to ubiquinone (Q) bound to SDHC and SDHD in the inner mitochondrial membrane (IMM), reducing it to ubiquinol (QH2). Ubiquinol transfers its electrons through complex III, in a mechanism named the Q cycle, to cytochrome c (PDB: 1CXA). Electrons then flow from cytochrome c to COX where the final four-electron reduction of molecular oxygen to water occurs (not shown in this diagram). Complex III is the best characterized site of ROS production in the ETC, where a single electron reduction of oxygen to superoxide can occur (red arrow). It was proposed that obstructing electron flow within complex II might support a single electron reduction of oxygen at the FAD site (red arrow). Superoxide is dismutated to hydrogen peroxide which can then leave the mitochondria and inhibit PHD in the cytosol, leading to HIF[1] stabilization. Succinate or fumarate, which accumulate in SDH- or FH-deficient tumors, can also leave the mitochondria and inhibit PHD activity in the cytosol. The red dotted line represents the outer mitochondrial membrane (OMM).
2.1.1.8 Mitochondria in cancer cells: what is so special about them?
The past decade has revealed a new role for the mitochondria in cell metabolism–regulation of cell death pathways. Considering that most tumor cells are resistant to apoptosis, one might question whether such resistance is related to the particular properties of mitochondria in cancer cells that are distinct from those of mitochondria in non-malignant cells. This scenario was originally suggested by Otto Warburg, who put forward the hypothesis that a decrease in mitochondrial energy metabolism might lead to development of cancer. This review is devoted to the analysis of mitochondrial function in cancer cells, including the mechanisms underlying the upregulation of glycolysis, and how intervention with cellular bioenergetic pathways might make tumor cells more susceptible to anticancer treatment and induction of apoptosis.
Figure 1. Glucose utilization pathway. When glucose enters the cell, it is phosphorylated by hexokinase to glucose-6-phosphate, which is further metabolized by glycolysis to pyruvate. Under aerobic conditions, most of the pyruvate in non-malignant cells enters the mitochondria, with only a small amount being metabolized to lactic acid. In mitochondria, pyruvate dehydrogenase (PDH) converts pyruvate into acetyl-CoA, which feeds into the Krebs cycle. Oxidation of Krebs cycle substrates by the mitochondrial respiratory chain builds up the mitochondrial membrane potential (Dc) – the driving force for ATP synthesis. By contrast, in tumor cells, the oxidative (mitochondrial) pathway of glucose utilization is suppressed, and most of the pyruvate is converted into lactate. Thus, the fate of pyruvate is determined by the relative activities of two key enzymes – lactate dehydrogenase and pyruvate dehydrogenase.
Figure 2. Mechanisms of mitochondrial silencing in tumors. The activity of PDH is regulated by pyruvate dehydrogenase kinase 1 (PDK1), the enzyme that phosphorylates and inactivates pyruvate dehydrogenase. HIF-1 inactivates PDH through PDK1 induction, resulting in suppression of the Krebs cycle and mitochondrial respiration. In addition, HIF-1 stimulates expression of the lactate dehydrogenase A gene, facilitating conversion of pyruvate into lactate by lactate dehydrogenase (LDH). Mutation of p53 can suppress the mitochondrial respiratory activity through downregulation of the Synthesis of Cytochrome c Oxidase 2 (SCO2) gene, the product of which is required for the assembly of cytochrome c oxidase (COX) of the mitochondrial respiratory chain. Thus, mutation of p53 can suppress mitochondrial respiration and shift cellular energy metabolism towards glycolysis.
Production of ROS by mitochondria
In any cell, the majority of ROS are by-products of mitochondrial respiration. Approximately 2% of the molecular oxygen consumed during respiration is converted into the superoxide anion radical, the precursor of most ROS. Normally, a four-electron reduction of O2, resulting in the production of two molecules of water, is catalyzed by complex IV (COX) of the mitochondrial respiratory chain. However, the electron transport chain contains several redox centers (e.g. in complex I and III) that can leak electrons to molecular oxygen, serving as the primary source of superoxide production in most tissues. The one-electron reduction of oxygen is thermodynamically favorable for most mitochondrial oxidoreductases. Superoxide-producing sites and enzymes were recently analyzed in detail in a comprehensive review [87]. ROS, if not detoxified, oxidize cellular proteins, lipids, and nucleic acids and, by doing so, cause cell dysfunction or death. A cascade of water and lipid soluble antioxidants and antioxidant enzymes suppresses the harmful ROS activity. An imbalance that favors the production of ROS over antioxidant defenses, defined as oxidative stress, is implicated in a wide variety of pathologies, including malignant diseases. It should be mentioned that mitochondria are not only a major source of ROS but also a sensitive target for the damaging effects of oxygen radicals. ROS produced by mitochondria can oxidize proteins and induce lipid peroxidation, compromising the barrier properties of biological membranes. One of the targets of ROS is mitochondrial DNA (mtDNA), which encodes several proteins essential for the function of the mitochondrial respiratory chain and, hence, for ATP synthesis by oxidative phosphorylation. mtDNA, therefore, represents a crucial cellular target for oxidative damage, which might lead to lethal cell injury through the loss of electron transport and ATP generation. mtDNA is especially susceptible to attack by ROS, owing to its close proximity to the electron transport chain, the major locus for free-radical production, and the lack of protective histones. For example, mitochondrially generated ROS can trigger the formation of 8-hydroxydeoxyguanosine as a result of oxidative DNA damage; the level of oxidatively modified bases in mtDNA is 10- to 20-fold higher than that in nuclear DNA. Oxidative damage induced by ROS is probably a major source of mitochondrial genomic instability leading to respiratory dysfunction.
Figure 3. Stabilization of mitochondria against OMM permeabilization in tumor cells. OMM permeabilization is a key event in apoptotic cell death. (a) During apoptosis, tBid-mediated oligomerization of Bax causes OMM permeabilization and release of cytochrome c (red circles). (b) Bcl-2 protein binds Bax and prevents its oligomerization. A shift in the balance between pro- apoptotic and antiapoptotic proteins in cancer cells, in favor of the latter, reduces the availability of Bax and prevents OMM permeabilization. (c) Upregulation of hexokinase in tumors and its binding to VDAC in the OMM not only facilitates glucose phosphorylation using mitochondrially generated ATP but keeps VDAC in the open state, preventing its interaction with tBid (de).
Figure 4. Shifting metabolism from glycolysis to glucose oxidation. Utilization of pyruvate is controlled by the relative activities of two enzymes, PDH and LDH. In cancer cells, PDH activity is suppressed by PDH kinase-mediated phosphorylation, and, therefore, instead of entering the Krebs cycle, pyruvate is converted into lactate. Several attempts have been made to redirect pyruvate towards oxidation in the mitochondria. Thus, inhibition of PDK1 by dichloroacetate might stimulate the activity of PDH and, hence, direct pyruvate to the mitochondria. A similar effect can be achieved by inhibition of LDH by oxamate. Overall, suppression of PDK1 and LDH activities will stimulate mitochondrial ATP production and might be lethal to tumor cells, even if these inhibitors are used at non-toxic doses. In addition, stimulation of mitochondrial function, for example though overexpression of mitochondrial frataxin, a protein associated with Friedreich ataxia, was shown to stimulate oxidative metabolism and inhibited growth in several cancer cell lines [86].
2.1.1.9 Glucose avidity of carcinomas
The cancer cell phenotype has been summarized in six hallmarks [D. Hanahan, R.A. Weinberg, The hallmarks of cancer, Cell 100 (1) (2000) 57-70]. Following the conceptual trait established in that review towards the comprehension of cancer, herein we summarize the basis of an underlying principle that is fulfilled by cancer cells and tumors: its avidity for glucose. Our purpose is to push forward that the metabolic reprogramming that operates in the cancer cell represents a seventh hallmark of the phenotype that offers a vast array of possibilities for the future treatment of the disease. We summarize the metabolic pathways that extract matter and energy from glucose, paying special attention to the concerted regulation of these pathways by the ATP mass-action ratio. The molecular and functional evidences that support the high glucose uptake and the “abnormal” aerobic glycolysis of the carcinomas are detailed discussing also the role that some oncogenes and tumor suppressors have in these pathways. We overview past and present evidences that sustain that mitochondria of the cancer cell are impaired, supporting the original Warburg’s formulation that ascribed the high glucose uptake of cancer cells to a defective mitochondria. A simple proteomic approach designed to assess the metabolic phenotype of cancer, i.e., its bioenergetic signature, molecularly and functionally supports Warburg’s hypothesis. Furthermore, we discuss the clinical utility that the bioenergetic signature might provide. Glycolysis is presented as the “selfish” pathway used for cellular proliferation, providing both the metabolic precursors and the energy required for biosynthetic purposes, in the context of a plethora of substrates. The glucose avidity of carcinomas is thus presented as the result of both the installment of glycolysis for cellular proliferation and of the impairment of mitochondrial activity in the cancer cell. At the end, the repression of mitochondrial activity affords the cancer cell with a cell-death resistant phenotype making them prone to malignant growth.
Fig. 1. Pathways of glucose metabolism. The model shows some of the relevant aspects of the metabolism of glucose. After entering the cell by specific transporters, glucose can be (i) catabolized by the pentose phosphate pathway (PPP) to obtain reducing power in the form of NADPH, (ii) used for the synthesis of carbohydrates or (iii) utilized by glycolysis to generate pyruvate and other metabolic intermediates that could be used in different anabolic processes (blue rectangles). In the cytoplasm, the generated pyruvate can be reduced to lactate and further exported from the cell or oxidized in the mitochondria by pyruvate dehydrogenase to generate acetyl-CoA, which is condensed with oxaloacetate in the tricarboxylic acid cycle (TCA cycle). The operation of the TCA cycle completes the oxidation of mitochondrial pyruvate. Different pathways that drain intermediates of the TCA cycle (oxaloacetate, succinyl-CoA, a-ketoglutarate and citrate) for biosynthetic purposes (blue rectangles) are represented. The transfer of electrons obtained in biological oxidations (NADH/FADH2) to molecular oxygen by respiratory complexes of the inner mitochondrial membrane (in green) is depicted by yellow lines. The utilization of the proton gradient generated by respiration for the synthesis of ATP by the H+-ATP synthase (in orange) in oxidative phosphorylation (OXPHOS) is also indicated. The incorporation of glutamine carbon skeletons into the TCA cycle is shown. The utilization of NADPH in anabolic pathways is also indicated.
Fig. 3. Fluxes of matter and energy in differentiated, proliferating and cancer cells. In differentiated cells, the flux of glycolysis is low because the requirement for precursors for anabolic purposes is low and there is a high energy yield by the oxidation of pyruvate in mitochondrial oxidative phosphorylation (OXPHOS). In this situation, mitochondrial activity produces large amounts of ROS that are normally quenched by the cellular antioxidant defense. In proliferating and cancer cells, there is a high demand of glucose to provide metabolic precursors for the biosynthesis of the macromolecules of daughter cells and because most of the energy required for anabolic purposes derives from non-efficient non-respiratory modes (glycolysis, pentose phosphate pathway) of energy generation. Limiting mitochondrial activity in these situations ensures less ROS production and their further downstream consequences. In addition, cancer cells have less overall mitochondrial complement or activity than normal cells by repressing the biogenesis of mitochondria.
Fig. 2. Genetic alterations underlying the glycolytic phenotype of cancer cells. The diagram represents the impact of gain-of-function mutations in oncogenes (ovals) and loss-of-function mutations in tumor suppressors (rectangles) in glycolysis and in the mitochondrial utilization of pyruvate in cancer cells. Hypoxia (low O2) induces the stabilization of HIF-1, which promotes transcriptional activation of the glucose transporter, glycolytic genes and PDK1. The expression of PDK1 results in the inactivation of pyruvate dehydrogenase and thus in a decreased oxidation of pyruvate in the TCA cycle concurrent to its enhanced cytoplasmic reduction to lactate by lactate dehydrogenase (LDHA). In addition, HIF1a reciprocally regulates the expression of two isoforms of the cytochrome c oxidase complex. The oncogen myc also supports an enhanced glycolytic pathway by transcriptional activation of glycolytic genes. High levels of c-myc could also promote the production of reactive oxygen species (ROS) that could damage nuclear (nDNA) and mitochondrial (mtDNA). The loss-of-function of the tumor suppressor p53 promotes an enhanced glycolytic phenotype by the repression of TIGAR expression. Likewise, loss-of-function of p53 diminished the expression of SCO2, a gene required for the appropriate assembly of cytochrome c oxidase, and thus limits the activity of mitochondria in the cancer cell.
Discussion:
Warburg Effect revisited
It is very interesting the series of commentaries following Warburg Effect revisited. However, it comes as no surprise that almost all of them have small or greater emphasis in the molecular biology (changes in gene expression) events of the metabolic regulation involved.
I would like to comment on some aspects: 1- Warburg did the initial experiments following Pasteur line of reasoning that aimed at carbon flow through the cell (yeast in his case) instead of describing anything inside the cell. It is worth to recall that for the sake of his study, Pasteur considered anything inside the cell under the domain of divine forces. He, at least in defence of his work, entirely made outside the cell, considered that inside the cells was beyond human capability of understanding – He has followed vitalism as his line of reasoning in defence of his work – Interestingly, the same scientist that has ruled out spontaneous generation when Pasteurization was started. Therefore, Pasteur measured everything outside the cell (mainly sugar, ethanol – the equivalent of our lactic acid end product of anaerobic metabolism) and found that as soon as yeasts were placed in the presence of oxygen, sugar was consumed at low speed in comparison with the speed measured in anaerobiosis and ethanol was also produced at reduced speed. This is an indication of a fast biological regulatory mechanism that obviously, do not require changes in gene expression. As previously said, Warburg work translated for republishing in the Journal Biological Chemistry mentioned “grana” for mitochondria calling attention on an “inside-the-cell” component. It seems that, there is not a unique, single site of metabolism, where the Pasteur Effect – Warburg Effect seems to be elicited by the shift from anaerobiosis to aerobiosis or vice versa.
In order to find a core for the mechanism the best approach seems to take into account one of the most important contributions of one of the greatest north-American biochemists, Briton Chance. He has made it with his polarographic method of following continuously the oxygen consumption of the cell´s mitochondria.
Mitochondria burn organic carbon molecules under a very stringent control mechanism of oxidative-phosphorylation ATP production. Measured in the form of changes in the speed of oxygen consumption over time as Respiratory Control Ratio (RCR). When no ATP is required by the cell, oxygen consumption goes at low speed (basal or state II or IV). When ADP is offered to the mitochondria as an indication that ATP synthesis is necessary, oxygen consumption is activated in state III respiration. Low respiration means low burning activity of organic (carbon) molecules what in this case, means indirectly low glucose consumption. While high respiration is the converse – greater glucose consumption.
Aerobic metabolism of glucose to carbonic acid and water provides a change in free energy enough for 38 molecules of ATP (the real production is +/- 32 ATP in aerobic condition) while glucose to lactic acid metabolism in anaerobiosis leads to 2 ATP production after discounting the other 2 required at initial stages of glucose metabolism.
The low ATP yield in anaerobiosis explains the fast glucose metabolism in anaerobiosis while the control by RCR in mitochondria explains the reduction in glucose metabolism under aerobiosis as long as the ATP requirements of the cell remains the same – This is what it is assumed to happen in quiescent cells. Not necessarily in fast growing cells as cancer cells are. However, this will not be discussed here. In my first experiments in the early seventies, with M. Rouxii a dimorphic mold-yeast biological system the environmental change (aerobic – anaerobic) led to morphogenetic change presented as morphogenetic expression of the Pasteur Effect. In this case, the enzyme that replaces mitochondria in ATP production (Pyruvate Kinase) converting phosphoenolpyruvate into pyruvate together with ADP into ATP, shows changes that can be interpreted as change in gene expression together with new self-assembly of enzyme subunits. (Dimer AA – yeast in anaerobic growth or sporangiospores- converted into dimer AB in aerobic mold). In Leloir opinions at that time, PK I (AA) was only highly glycosylated, while PK II (AB) was less glycosylated without changes in gene expression.
In case you read comments posted, you will see that the reference to aerobic glycolysis, continues to be made together with, new deranged forms of reasoning as is indicated by referring to: Mitochondrial role in ion homeostasis…
Homeostasis is a regulation of something, ions, molecules, pH etc. that is kept outside the cell, therefore any role for mitochondria on it is only made indirectly, by its ATP production.
However, mitochondria has a role together with other cell components in the regulation of for instance, intracellular Ca levels (Something that is not a homeostatic regulation). This is a very important point for the following reason: Homeostasis is maintained as a composite result of several differentiated cellular, tissue and organ functions. Differentiated function is something clearly missing in cancer cells. The best form to refer to the mitochondrial function regarding ions is to indicate a mitochondrial role in ion fluxes.
In short, to indicate how an environmental event or better saying condition could favour genetic changes instead of being caused by genetic changes is to follow the same line of reasoning that is followed in understanding the role of cardioplegia. To stop heart beating is adequate for heart surgery it is also adequate for heart cells by sparing the ATP use during surgery and therefore, offering better recovery condition to the heart afterwards.
In the case, here considered, even assuming that the genome is not made more unstable during hypoxic condition it is quite possible to understand that sharing ATP with both differentiated cell function and replication may led quality control of DNA in short supply of much needed ATP and this led to maintenance of mutations as well as less organized genome.
Thank you. I enjoy reading your comments. They are very instructive. I don’t really think that I comprehend the use of the term “epigenetics” and longer. In fact, it was never clear to me when I first heard it used some years ago.
The term may have been closely wedded to the classic hypothesis of a unidirectional DNA–> RNA–> protein model that really has lost explanatory validity for the regulated cell in its environment. The chromatin has an influence, and protein-protein interactions are everywhere. As you point out, these are adjusting to a fast changing substrate milieu, and the genome is not involved. But in addition, the proteins may well have a role in suppression or activation of signaling pathways, and thereby, may well have an effect on gene expression. I don’t have any idea about how it would work, but mutations would appear to follow the metabolic condition of the cell over time. It would appear to be – genomic modification.
In aerobic glucose metabolism, the oxidation of citric acid requires ADP and Mg²+, which will increase the speed of the reaction: Iso-citric acid + NADP (NAD) — isocitrate dehydrogenase (IDH) = alpha-ketoglutaric acid. In the Krebs cycle (the citric cycle), IDH1 and IDH2 are NADP+-dependent enzymes that normally catalyze the inter-conversion of D-isocitrate and alpha-ketoglutarate (α-KG). The IDH1 and IDH2 genes are mutated in > 75% of different malignant diseases. Two distinct alterations are caused by tumor-derived mutations in IDH1 or IDH2: the loss of normal catalytic activity in the production of α-ketoglutarate (α-KG) and the gain of catalytic activity to produce 2-hydroxyglutarate (2-HG), [22].
This product is a competitive inhibitor of multiple α-KG-dependent dioxygenases, including demethylases, prolyl-4-hydroxylase and the TET enzymes family (Ten-Eleven Translocation-2), resulting in genome-wide alternations in histones and DNA methylation. [23]
IDH1 and IDH2 mutations have been observed in myeloid malignancies, including de novo and secondary AML (15%–30%), and in pre-leukemic clone malignancies, including myelodysplastic syndrome and myeloproliferative neoplasm (85% of the chronic phase and 20% of transformed cases in acute leukemia), [24].
Normally, cells in the body communicate via intra-cytoplasmic channels and maintain the energetic potential across cell membranes, which is 1-2.5 µmol of ATP in the form of ATP-ADP/ATP-ADP-IMP. These normal energetic values occur during normal cell division. If the intra-cellular and extra-cellular levels of Mg2+ are high, the extra-cellular charges of the cells will not be uniformly distributed.
This change in distribution induces a high net positive charge for the cell and induces a loss of contact inhibition via the electromagnetic induction of oscillation [28, 29, 30]. Thereafter, malignant cells become invasive and metastasize.
,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
-22. Hartmann C, Meyer J, Balss J. Capper D, et al. Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differentiation and age: a study of 1,010 diffuse gliomas. Acta Neuropathol 2009; 118: 464-474.
23. Raymakers R.A, Langemeijer S.M., Kuiper R.P, Berends M, et al. Acquired mutations in TET2 are common in myelodysplastic syndromes. Nat. Genet 2009; 41; 838–849.
24 Wagner K, Damm F, Gohring G., Gorlich K et al. Impact of IDH1 R132 mutations and an IDH1 single nucleotide polymorphism in cytogenetically normal acute myeloid leukemia: SNP rs11554137 is an adverse prognostic factor. J. Clin. Oncol.2010; 28: 2356–2364.
Plant Molecular Biology 1989; 1: 271–303.
29. Chien MM, Zahradka CE, Newel MC, Fred JW. Fas induced in B cells apoptosis require an increase in free cytosolic magnesium as in early event. J Biol Chem.1999; 274: 7059-7066.
30. Milionis H J, Bourantas C L, Siamopoulos C K, Elisaf MS. Acid bases and electrolytes abnormalities in Acute Leukemia. Am J Hematol 1999; (62): 201-207.
31. Thomas N Seyfried; Laura M Shelton.Cancer as a Metabolic Disease. Nutr Metab 2010; 7: 7
– Aurelian Udristioiu, M.D,
– Lab Director, EuSpLM,
– City Targu Jiu, Romania
AACC, National Academy of Biochemical Chemistry (NACB) Member, Washington D.C, USA.
Having considered in general terms how a mitochondrion uses electron
transport to create an electrochemical proton gradient, we need to
examine the mechanisms that underlie this membrane-based energy-conversion process. In doing so, we also accomplish a larger purpose.
As emphasized at the beginning of this chapter, very similar chemi-
osmotic mechanisms are used by mitochondria, chloroplasts, archea,
and bacteria. In fact, these mechanisms underlie the function of nearly
all living organisms— including anaerobes that derive all their energy
from electron transfers between two inorganic molecules. It is therefore
rather humbling for scientists to remind themselves that the existence
of chemiosmosis has been recognized for only about 40 years.
mitochondria
Overview of The Electron Transport Chain
We begin with a look at some of the principles that underlie the electron-transport process, with the aim of explaining how it can pump protons
across a membrane.
Although protons resemble other positive ions such as Na+ and K+
in their movement across membranes, in some respects they are unique.
Hydrogen atoms are by far the most abundant type of atom in living
organisms; they are plentiful not only in all carbon-containing
biological molecules, but also in the water molecules that surround
them. The protons in water are highly mobile, flickering through the
hydrogen-bonded network of water molecules by rapidly
dissociating from one water molecule to associate with its neighbor,
as illustrated in Figure 14-20A. Protons are thought to move across a
protein pump embedded in a lipid bilayer in a similar way: they
transfer from one amino acid side chain to another, following a
special channel through the protein.
Protons are also special with respect to electron transport. Whenever
a molecule is reduced by acquiring an electron, the electron (e -) brings
with it a negative charge. In many cases, this charge is rapidly
neutralized by the addition of a proton (H+) from water, so that
the net effect of the reduction is to transfer an entire hydrogen atom,
H+ + e – (Figure 14-20B). Similarly, when a molecule is oxidized,
a hydrogen atom removed from it can be readily dissociated into
its constituent electron and proton—allowing the electron to
be transferred separately to a molecule that accepts electrons,
while the proton is passed to the water. Therefore, in a membrane
in which electrons are being passed along an electron-transport
chain, pumping protons from one side of the membrane to
another can be relatively simple. The electron carrier merely
needs to be arranged in the membrane in a way that causes it to
pick up a proton from one side of the membrane when it accepts
an electron, and to release the proton on the other side of the
membrane as the electron is passed to the next carrier molecule
in the chain (Figure 14-21).
How protons can be pumped across membranes. As an electron
passes along an electron-transport chain embedded in a lipid-bilayer
membrane, it can bind and release a proton at each step.
In this diagram, electron carrier B picks up a proton (H+)
from one (more…)
e_transfer
The Redox Potential Is a Measure of Electron Affinities
In biochemical reactions, any electrons removed from one
molecule are always passed to another, so that whenever one
molecule is oxidized, another is reduced. Like any other chemical r
eaction, the tendency of such oxidation-reduction reactions, or
redox reactions, to proceed spontaneously depends on the free-
energy change (ΔG) for the electron transfer, which in turn
depends on the relative affinities of the two molecules for electrons.
Because electron transfers provide most of the energy for living
things, it is worth spending the time to understand them. Many
readers are already familiar with acids and bases, which donate
and accept protons (see Panel 2-2, pp. 112–113). Acids and bases
exist in conjugate acid-base pairs, in which the acid is readily
converted into the base by the loss of a proton. For example,
acetic acid (CH3COOH) is converted into its conjugate base
(CH3COO-) in the reaction:
Image ch14e3.jpg
In exactly the same way, pairs of compounds such as NADH and
NAD+ are called redox pairs, since NADH is converted to NAD+
by the loss of electrons in the reaction:
Image ch14e4.jpg
NAD+_NADH
NADH is a strong electron donor: because its electrons are held
in a high-energy linkage, the free-energy change for passing its
electrons to many other molecules is favorable (see Figure 14-9).
It is difficult to form a high-energy linkage. Therefore its redox
partner, NAD+, is of necessity a weak electron acceptor.
The tendency to transfer electrons from any redox pair can be
measured experimentally. All that is required is the formation
of an electrical circuit linking a 1:1 (equimolar) mixture of the
redox pair to a second redox pair that has been arbitrarily selected
as a reference standard, so the voltage difference can be measured
between them (Panel 14-1, p. 784). This voltage difference is
defined as the redox potential; as defined, electrons move
spontaneously from a redox pair like NADH/NAD+ with a low
redox potential (a low affinity for electrons) to a redox pair like
O2/H2O with a high redox potential (a high affinity for electrons).
Thus, NADH is a good molecule for donating electrons to the
respiratory chain, while O2 is well suited to act as the “sink” for
electrons at the end of the pathway. As explained in Panel 14-1,
the difference in redox potential, ΔE0′, is a direct measure of
the standard free-energy change (ΔG°) for the transfer of an
electron from one molecule to another.
Proteins of inner space
energetics-of-cellular-respiration
Box Icon
Panel 14-1
Redox Potentials.
Electron Transfers Release Large Amounts of Energy
As just discussed, those pairs of compounds that have the most negative
redox potentials have the weakest affinity for electrons and therefore
contain carriers with the strongest tendency to donate electrons.
Conversely, those pairs that have the most positive redox potentials
have the strongest affinity for electrons and therefore contain carriers
with the strongest tendency to accept electrons. A 1:1 mixture of NADH
and NAD+ has a redox potential of -320 mV, indicating that NADH has
a strong tendency to donate electrons; a 1:1 mixture of H2O and ½O2
has a redox potential of +820 mV, indicating that O2 has a strong
tendency to accept electrons. The difference in redox potential is
1.14 volts (1140 mV), which means that the transfer of each electron
from NADH to O2 under these standard conditions is enormously
favorable, where ΔG° = -26.2 kcal/mole (-52.4 kcal/mole for the two
electrons transferred per NADH molecule; see Panel 14-1). If we
compare this free-energy change with that for the formation of the
phosphoanhydride bonds in ATP (ΔG° = -7.3 kcal/mole, see Figure 2-75), we see that more than enough energy is released by the oxidization
of one NADH molecule to synthesize several molecules of ATP from
ADP and Pi.
Phosphate dependence of pyruvate oxidation
Living systems could certainly have evolved enzymes that would
allow NADH to donate electrons directly to O2 to make water in the reaction:
Image ch14e5.jpg
But because of the huge free-energy drop, this reaction would proceed
with almost explosive force and nearly all of the energy would be released
as heat. Cells do perform this reaction, but they make it proceed much
more gradually by passing the high-energy electrons from NADH to
O2 via the many electron carriers in the electron-transport chain.
Since each successive carrier in the chain holds its electrons more
tightly, the highly energetically favorable reaction 2H+ + 2e – + ½O2
→ H2O is made to occur in many small steps. This enables nearly half
of the released energy to be stored, instead of being lost to the
environment as heat.
Spectroscopic Methods Have Been Used to Identify Many Electron
Carriers in the Respiratory Chain
Many of the electron carriers in the respiratory chain absorb visible
light and change color when they are oxidized or reduced. In general,
each has an absorption spectrum and reactivity that are distinct enough
to allow its behavior to be traced spectroscopically, even in crude mixtures.
It was therefore possible to purify these components long before their
exact functions were known. Thus, the cytochromes were discovered
in 1925 as compounds that undergo rapid oxidation and reduction in
living organisms as disparate as bacteria, yeasts, and insects. By observing
cells and tissues with a spectroscope, three types of cytochromes were
identified by their distinctive absorption spectra and designated
cytochromes a, b, and c. This nomenclature has survived, even though
cells are now known to contain several cytochromes of each type and
the classification into types is not functionally important.
The cytochromes constitute a family of colored proteins that are
related by the presence of a bound heme group, whose iron atom
changes from the ferric oxidation state (Fe3+) to the ferrous oxidation
state (Fe2+) whenever it accepts an electron. The heme group consists
of a porphyrin ring with a tightly bound iron atom held by four nitrogen
atoms at the corners of a square (Figure 14-22). A similar porphyrin ring
is responsible for the red color of blood and for the green color of
leaves, being bound to iron in hemoglobin and to magnesium in
chlorophyll, respectively.
The structure of the heme group attached covalently to cytochrome c ch14f22
Figure 14-22. The structure of the heme group attached covalently
to cytochrome c.
Figure 14-22
The structure of the heme group attached covalently to cytochrome c.
The porphyrin ring is shown in blue. There are five different
cytochromes in the respiratory chain. Because the hemes in different
cytochromes have slightly different structures and (more…)
Iron-sulfur proteins are a second major family of electron carriers. In these
proteins, either two or four iron atoms are bound to an equal number of
sulfur atoms and to cysteine side chains, forming an iron-sulfur center
on the protein (Figure 14-23). There are more iron-sulfur centers than
cytochromes in the respiratory chain. But their spectroscopic detection
requires electron spin resonance (ESR) spectroscopy, and they are less
completely characterized. Like the cytochromes, these centers carry one
electron at a time.
Figure 14-23. The structures of two types of iron-sulfur centers.
Figure 14-23
The structures of two types of iron-sulfur centers. (A) A center of the
2Fe2S type. (B) A center of the 4Fe4S type. Although they contain
multiple iron atoms, each iron-sulfur center can carry only one
electron at a time. There are more than seven different (more…)
The simplest of the electron carriers in the respiratory chain—and
the only one that is not part of a protein—is a small hydrophobic
molecule that is freely mobile in the lipid bilayer known as ubiquinone,
or coenzyme Q. A quinone (Q) can pick up or donate either one or
two electrons; upon reduction, it picks up a proton from the medium
along with each electron it carries (Figure 14-24).
Quinone electron carriers. Ubiquinone in the respiratory chain picks
up one H+ from the aqueous environment for every electron it accepts,
and it can carry either one or two electrons as part of a hydrogen atom
(yellow). When reduced ubiquinone donates (more…)
In addition to six different hemes linked to cytochromes, more than
seven iron-sulfur centers, and ubiquinone, there are also two copper
atoms and a flavin serving as electron carriers tightly bound to respiratory-chain proteins in the pathway from NADH to oxygen. This pathway
involves more than 60 different proteins in all.
As one would expect, the electron carriers have higher and higher
affinities for electrons (greater redox potentials) as one moves along
the respiratory chain. The redox potentials have been fine-tuned
during evolution by the binding of each electron carrier in a particular
protein context, which can alter its normal affinity for electrons. However,
because iron-sulfur centers have a relatively low affinity for electrons,
they predominate in the early part of the respiratory chain; in contrast,
the cytochromes predominate further down the chain, where a higher
affinity for electrons is required.
The order of the individual electron carriers in the chain was
determined by sophisticated spectroscopic measurements (Figure 14-25),
and many of the proteins were initially isolated and characterized as
individual polypeptides. A major advance in understanding the
respiratory chain, however, was the later realization that most of
the proteins are organized into three large enzyme complexes.
Figure 14-25. The general methods used to determine the path of
electrons along an electron-transport chain.
Figure 14-25
The general methods used to determine the path of electrons along
an electron-transport chain. The extent of oxidation of electron
carriers a, b, c, and d is continuously monitored by following their
distinct spectra, which differ in their oxidized and (more…)
The Respiratory Chain Includes Three Large Enzyme Complexes
Embedded in the Inner Membrane
Membrane proteins are difficult to purify as intact complexes
because they are insoluble in aqueous solutions, and some of
the detergents required to solubilize them can destroy normal
protein-protein interactions. In the early 1960s, however, it
was found that relatively mild ionic detergents, such as deoxycholate,
can solubilize selected components of the inner mitochondrial
membrane in their native form. This permitted the identification
and purification of the three major membrane-bound respiratory
enzyme complexes in the pathway from NADH to oxygen (Figure 14-26).
As we shall see in this section, each of these complexes acts as an
electron-transport-driven H+ pump; however, they were
initially characterized in terms of the electron carriers that
they interact with and contain:
Figure 14-26. The path of electrons through the three respiratory
enzyme complexes.
Figure 14-26
The path of electrons through the three respiratory enzyme complexes.
The relative size and shape of each complex are shown. During the
transfer of electrons from NADH to oxygen (red lines), ubiquinone
and cytochrome c serve as mobile carriers that ferry (more…)
The NADH dehydrogenase complex (generally known as complex I)
is the largest of the respiratory enzyme complexes, containing more
than 40 polypeptide chains. It accepts electrons from NADH and
passes them through a flavin and at least seven iron-sulfur centers
to ubiquinone. Ubiquinone then transfers its electrons to a second
respiratory enzyme complex, the cytochrome b-c1 complex.
The cytochrome b-c1 complex contains at least 11 different
polypeptide chains and functions as a dimer. Each monomer
contains three hemes bound to cytochromes and an iron-sulfur
protein. The complex accepts electrons from ubiquinone
and passes them on to cytochrome c, which carries its electron
to the cytochrome oxidase complex.
The cytochrome oxidase complex also functions as a dimer; each
monomer contains 13 different polypeptide chains, including two
cytochromes and two copper atoms. The complex accepts one electron
at a time from cytochrome c and passes them four at a time to oxygen.
The cytochromes, iron-sulfur centers, and copper atoms can carry
only one electron at a time. Yet each NADH donates two electrons,
and each O2 molecule must receive four electrons to produce water.
There are several electron-collecting and electron-dispersing points
along the electron-transport chain where these changes in electron
number are accommodated. The most obvious of these is cytochrome
oxidase.
An Iron-Copper Center in Cytochrome Oxidase Catalyzes Efficient
O2 Reduction
Because oxygen has a high affinity for electrons, it releases a
large amount of free energy when it is reduced to form water.
Thus, the evolution of cellular respiration, in which O2 is
converted to water, enabled organisms to harness much more
energy than can be derived from anaerobic metabolism. This
is presumably why all higher organisms respire. The ability of
biological systems to use O2 in this way, however, requires a
very sophisticated chemistry. We can tolerate O2 in the air we
breathe because it has trouble picking up its first electron; this
fact allows its initial reaction in cells to be controlled closely by
enzymatic catalysis. But once a molecule of O2 has picked up one
electron to form a superoxide radical (O2 -), it becomes dangerously
reactive and rapidly takes up an additional three electrons wherever
it can find them. The cell can use O2 for respiration only because
cytochrome oxidase holds onto oxygen at a special bimetallic
center, where it remains clamped between a heme-linked iron
atom and a copper atom until it has picked up a total of four electrons.
Only then can the two oxygen atoms of the oxygen molecule be
safely released as two molecules of water (Figure 14-27).
Figure 14-27. The reaction of O2 with electrons in cytochrome oxidase.
Figure 14-27
The reaction of O2 with electrons in cytochrome oxidase. As indicated,
the iron atom in heme a serves as an electron queuing point; this
heme feeds four electrons into an O2 molecule held at the bimetallic
center active site, which is formed by the other (more…)
The cytochrome oxidase reaction is estimated to account for 90%
of the total oxygen uptake in most cells. This protein complex is
therefore crucial for all aerobic life. Cyanide and azide are extremely
toxic because they bind tightly to the cell’s cytochrome oxidase
complexes to stop electron transport, thereby greatly reducing
ATP production.
Although the cytochrome oxidase in mammals contains 13
different protein subunits, most of these seem to have a subsidiary
role, helping to regulate either the activity or the assembly of the
three subunits that form the core of the enzyme. The complete
structure of this large enzyme complex has recently been determined
by x-ray crystallography, as illustrated in Figure 14-28. The atomic
resolution structures, combined with mechanistic studies of the effect
of precisely tailored mutations introduced into the enzyme by genetic
engineering of the yeast and bacterial proteins, are revealing the
detailed mechanisms of this finely tuned protein machine.
Figure 14-28. The molecular structure of cytochrome oxidase.
Figure 14-28
The molecular structure of cytochrome oxidase. This protein
is a dimer formed from a monomer with 13 different protein
subunits (monomer mass of 204,000 daltons). The three colored
subunits are encoded by the mitochondrial genome, and they
form the functional (more…)
Electron Transfers Are Mediated by Random Collisions in
the Inner Mitochondrial Membrane
The two components that carry electrons between the three
major enzyme complexes of the respiratory chain—ubiquinone
and cytochrome c—diffuse rapidly in the plane of the inner
mitochondrial membrane. The expected rate of random collisions
between these mobile carriers and the more slowly diffusing
enzyme complexes can account for the observed rates of electron
transfer (each complex donates and receives an electron about
once every 5–20 milliseconds). Thus, there is no need to postulate
a structurally ordered chain of electron-transfer proteins in the
lipid bilayer; indeed, the three enzyme complexes seem to exist as
independent entities in the plane of the inner membrane, being
present in different ratios in different mitochondria.
The ordered transfer of electrons along the respiratory chain
is due entirely to the specificity of the functional interactions
between the components of the chain: each electron carrier is
able to interact only with the carrier adjacent to it in the sequence
shown in Figure 14-26, with no short circuits.
Electrons move between the molecules that carry them in
biological systems not only by moving along covalent bonds
within a molecule, but also by jumping across a gap as large
as 2 nm. The jumps occur by electron “tunneling,” a quantum-
mechanical property that is critical for the processes we are
discussing. Insulation is needed to prevent short circuits that
would otherwise occur when an electron carrier with a low redox
potential collides with a carrier with a high redox potential. This
insulation seems to be provided by carrying an electron deep
enough inside a protein to prevent its tunneling interactions
with an inappropriate partner.
How the changes in redox potential from one electron carrier
to the next are harnessed to pump protons out of the mitochondrial
matrix is the topic we discuss next.
A Large Drop in Redox Potential Across Each of the Three Respiratory
Enzyme Complexes Provides the Energy for H+ Pumping
We have previously discussed how the redox potential reflects
electron affinities (see p. 783). An outline of the redox potentials
measured along the respiratory chain is shown in Figure 14-29.
These potentials drop in three large steps, one across each major
respiratory complex. The change in redox potential between any
two electron carriers is directly proportional to the free energy
released when an electron transfers between them. Each enzyme
complex acts as an energy-conversion device by harnessing some
of this free-energy change to pump H+ across the inner membrane,
thereby creating an electrochemical proton gradient as electrons
pass through that complex. This conversion can be demonstrated
by purifying each respiratory enzyme complex and incorporating
it separately into liposomes: when an appropriate electron donor
and acceptor are added so that electrons can pass through the complex,
H+ is translocated across the liposome membrane.
Figure 14-29. Redox potential changes along the mitochondrial
electron-transport chain.
Figure 14-29
Redox potential changes along the mitochondrial electron-transport
chain. The redox potential (designated E′0) increases as electrons
flow down the respiratory chain to oxygen. The standard free-energy
change, ΔG°, for the transfer (more…)
The Mechanism of H+ Pumping Will Soon Be Understood in
Atomic Detail
Some respiratory enzyme complexes pump one H+ per electron
across the inner mitochondrial membrane, whereas others pump
two. The detailed mechanism by which electron transport is coupled
to H+ pumping is different for the three different enzyme complexes.
In the cytochrome b-c1 complex, the quinones clearly have a role.
As mentioned previously, a quinone picks up a H+ from the aqueous
medium along with each electron it carries and liberates it when it
releases the electron (see Figure 14-24). Since ubiquinone is freely
mobile in the lipid bilayer, it could accept electrons near the inside
surface of the membrane and donate them to the cytochrome b-c1
complex near the outside surface, thereby transferring one H+
across the bilayer for every electron transported. Two protons are
pumped per electron in the cytochrome b-c1 complex, however, and
there is good evidence for a so-called Q-cycle, in which ubiquinone
is recycled through the complex in an ordered way that makes this
two-for-one transfer possible. Exactly how this occurs can now be
worked out at the atomic level, because the complete structure of
the cytochrome b-c1 complex has been determined by x-ray
crystallography (Figure 14-30).
Figure 14-30. The atomic structure of cytochrome b-c 1.
Figure 14-30
The atomic structure of cytochrome b-c 1. This protein is a dimer.
The 240,000-dalton monomer is composed of 11 different protein
molecules in mammals. The three colored proteins form the
functional core of the enzyme: cytochrome b (green), cytochrome (more…)
Allosteric changes in protein conformations driven by electron
transport can also pump H+, just as H+ is pumped when ATP
is hydrolyzed by the ATP synthase running in reverse. For both the
NADH dehydrogenase complex and the cytochrome oxidase complex,
it seems likely that electron transport drives sequential allosteric
changes in protein conformation that cause a portion of the protein
to pump H+ across the mitochondrial inner membrane. A general
mechanism for this type of H+ pumping is presented in Figure 14-31.
Figure 14-31. A general model for H+ pumping.
Figure 14-31
A general model for H+ pumping. This model for H+ pumping
by a transmembrane protein is based on mechanisms that are
thought to be used by both cytochrome oxidase and the light-driven
procaryotic proton pump, bacteriorhodopsin. The protein
is driven through (more…)
H+ Ionophores Uncouple Electron Transport from ATP Synthesis
Since the 1940s, several substances—such as 2,4-dinitrophenol—
have been known to act as uncoupling agents, uncoupling electron
transport from ATP synthesis. The addition of these low-molecular-weight organic compounds to cells stops ATP synthesis by mitochondria
without blocking their uptake of oxygen. In the presence of an
uncoupling agent, electron transport and H+ pumping continue at
a rapid rate, but no H+ gradient is generated. The explanation for
this effect is both simple and elegant: uncoupling agents are lipid-
soluble weak acids that act as H+ carriers (H+ ionophores), and
they provide a pathway for the flow of H+ across the inner mitochondrial
membrane that bypasses the ATP synthase. As a result of this short-
circuiting, the proton-motive force is dissipated completely, and
ATP can no longer be made.
Respiratory Control Normally Restrains Electron Flow
Through the Chain
When an uncoupler such as dinitrophenol is added to cells,
mitochondria increase their oxygen uptake substantially because
of an increased rate of electron transport. This increase reflects
the existence of respiratory control. The control is thought to
act via a direct inhibitory influence of the electrochemical proton
gradient on the rate of electron transport. When the gradient is
collapsed by an uncoupler, electron transport is free to run unchecked
at the maximal rate. As the gradient increases, electron transport
becomes more difficult, and the process slows. Moreover, if an
artificially large electrochemical proton gradient is experimentally
created across the inner membrane, normal electron transport
stops completely, and a reverse electron flow can be detected in
some sections of the respiratory chain. This observation suggests
that respiratory control reflects a simple balance between the
free-energy change for electron-transport-linked proton pumping
and the free-energy change for electron transport—that is, the
magnitude of the electrochemical proton gradient affects both
the rate and the direction of electron transport, just as it affects
the directionality of the ATP synthase (see Figure 14-19).
Respiratory control is just one part of an elaborate interlocking
system of feedback controls that coordinate the rates of glycolysis,
fatty acid breakdown, the citric acid cycle, and electron transport.
The rates of all of these processes are adjusted to the ATP:ADP ratio,
increasing whenever an increased utilization of ATP causes the ratio
to fall. The ATP synthase in the inner mitochondrial membrane,
for example, works faster as the concentrations of its substrates
ADP and Pi increase. As it speeds up, the enzyme lets more H+ flow
into the matrix and thereby dissipates the electrochemical proton
gradient more rapidly. The falling gradient, in turn, enhances the
rate of electron transport.
Similar controls, including feedback inhibition of several key enzymes
by ATP, act to adjust the rates of NADH production to the rate of
NADH utilization by the respiratory chain, and so on. As a result of
these many control mechanisms, the body oxidizes fats and sugars
5–10 times more rapidly during a period of strenuous exercise than
during a period of rest.
Natural Uncouplers Convert the Mitochondria in Brown Fat into
Heat-generating Machines
In some specialized fat cells, mitochondrial respiration is normally
uncoupled from ATP synthesis. In these cells, known as brown fat
cells, most of the energy of oxidation is dissipated as heat rather
than being converted into ATP. The inner membranes of the large
mitochondria in these cells contain a special transport protein that
allows protons to move down their electrochemical gradient, by-
passing ATP synthase. As a result, the cells oxidize their fat stores
at a rapid rate and produce more heat than ATP. Tissues containing
brown fat serve as “heating pads,” helping to revive hibernating animals
and to protect sensitive areas of newborn human babies from the cold.
Bacteria Also Exploit Chemiosmotic Mechanisms to Harness Energy
Bacteria use enormously diverse energy sources. Some, like animal
cells, are aerobic; they synthesize ATP from sugars they oxidize to
CO2 and H2O by glycolysis, the citric acid cycle, and a respiratory
chain in their plasma membrane that is similar to the one in the
inner mitochondrial membrane. Others are strict anaerobes, deriving
their energy either from glycolysis alone (by fermentation) or from an
electron-transport chain that employs a molecule other than oxygen
as the final electron acceptor. The alternative electron acceptor can
be a nitrogen compound (nitrate or nitrite), a sulfur compound
(sulfate or sulfite), or a carbon compound (fumarate or carbonate),
for example. The electrons are transferred to these acceptors by a
series of electron carriers in the plasma membrane that are comparable
to those in mitochondrial respiratory chains.
Despite this diversity, the plasma membrane of the vast majority of
bacteria contains an ATP synthase that is very similar to the one in
mitochondria. In bacteria that use an electron-transport chain to
harvest energy, the electron-transport pumps H+ out of the cell and
thereby establishes a proton-motive force across the plasma membrane
that drives the ATP synthase to make ATP. In other bacteria, the
ATP synthase works in reverse, using the ATP produced by glycolysis
to pump H+ and establish a proton gradient across the plasma
membrane. The ATP used for this process is generated by
fermentation processes (discussed in Chapter 2).
Thus, most bacteria, including the strict anaerobes, maintain a proton
gradient across their plasma membrane. It can be harnessed to drive
a flagellar motor, and it is used to pump Na+ out of the bacterium via
a Na+-H+ antiporter that takes the place of the Na+-K+ pump of
eucaryotic cells. This gradient is also used for the active inward transport
of nutrients, such as most amino acids and many sugars: each nutrient is
dragged into the cell along with one or more H+ through a specific symporter
(Figure 14-32). In animal cells, by contrast, most inward transport across
the plasma membrane is driven by the Na+ gradient that is established by the
Na+-K+ pump.
Figure 14-32. The importance of H+-driven transport in bacteria.
Figure 14-32
The importance of H+-driven transport in bacteria. A proton-motive force
generated across the plasma membrane pumps nutrients into the cell and
expels Na+. (A) In an aerobic bacterium, an electrochemical proton gradient
across the plasma membrane is produced (more…)
Some unusual bacteria have adapted to live in a very alkaline
environment and yet must maintain their cytoplasm at a physiological
pH. For these cells, any attempt to generate an electrochemical H+
gradient would be opposed by a large H+ concentration gradient in
the wrong direction (H+ higher inside than outside). Presumably for
this reason, some of these bacteria substitute Na+ for H+ in all of their
chemiosmotic mechanisms. The respiratory chain pumps Na+ out of
the cell, the transport systems and flagellar motor are driven by an
inward flux of Na+, and a Na+-driven ATP synthase synthesizes
ATP. The existence of such bacteria demonstrates that the principle
of chemiosmosis is more fundamental than the proton-motive force
on which it is normally based.
Summary
The respiratory chain in the inner mitochondrial membrane contains
three respiratory enzyme complexes through which electrons pass on
their way from NADH to O2.
Each of these can be purified, inserted into synthetic lipid vesicles,
and then shown to pump H+ when electrons are transported through it.
In the intact membrane, the mobile electron carriers ubiquinone and
cytochrome c complete the electron-transport chain by shuttling between
the enzyme complexes. The path of electron flow is NADH → NADH
dehydrogenase complex → ubiquinone → cytochrome b-c1 complex →
cytochrome c → cytochrome oxidase complex → molecular oxygen (O2).
The respiratory enzyme complexes couple the energetically favorable
transport of electrons to the pumping of H+ out of the matrix. The
resulting electrochemical proton gradient is harnessed to make ATP
by another transmembrane protein complex, ATP synthase, through
which H+ flows back into the matrix. The ATP synthase is a reversible
coupling device that normally converts a backflow of H+ into ATP
phosphate bond energy by catalyzing the reaction ADP + Pi → ATP,
but it can also work in the opposite direction and hydrolyze ATP to
pump H+ if the electrochemical proton gradient is sufficiently reduced.
Its universal presence in mitochondria, chloroplasts, and procaryotes
testifies to the central importance of chemiosmotic mechanisms in cells.
By agreement with the publisher, this book is accessible by the search
feature, but cannot be browsed.
Prefacing the e-Book Epilogue: Metabolic Genomics and Pharmaceutics
Author and Curator: Larry H. Bernstein, MD, FCAP
Adieu, adieu, adieu …
Sound of Music
Snoopy – Charlie happiness
This work has been a coming to terms with my scientific and medical end of career balancing in a difficult time after retiring, but it has been rewarding. In the clinical laboratories, radiology, anesthesiology, and in pharmacy, there has been some significant progress in support of surgical, gynecological, developmental, medical practices, and even neuroscience directed disciplines, as well as epidemiology over a period of half a century. Even then, cancer and neurological diseases have been most difficult because the scientific basic research has either not yet uncovered a framework, or because that framework has proved to be multidimensional. In the clinical laboratory sciences, there has been enormous progress in instrumental analysis, with the recent opening of molecular methods not yet prepared for routine clinical use, which will be a very great challenge to the profession, which has seen the development of large sample volume, multianalite, high-throughput, low-cost support emerging for decades. The capabilities now underway will also enrrich the the capabilities of the anatomic pathology suite and the capabilities of 3-dimensional radiological examination. In both pathology and radiology, we have seen the division of the fields into major subspecialties. The development of the electronic health record had to take lessons from the first developments in the separate developments of laboratory, radiology, and pharmacy health record systems, to which were added, full cardiology monitoring systems. These have been unintegrated. This made it difficult to bring forth a suitable patient health record because the information needed to support decision-making by practitioners was in separate “silos”. The mathematical methods that are being applied to the -OMICS sciences, can be brought to bear on the simplification and amplification of the clinicians’ ability to make decisions with near “errorless” discrimination, still allowing for an element of “art” in carrying out the history, physical examination, and knowledge unique to every patient.
We are at this time opening a very large, complex, study of biology in relationship to the human condition. This will require sufficient resources to be invested in the development of these for a better society, which I suspect, will go on beyond the life of my grandchildren. Hopefully, the long-term dangers of climate change will be controlled in that time. As a society, or as a group of interdependent societies, we have no long term interest in continuing self-destructive behaviors that have predominated in the history of mankind. I now top off these discussions with some further elucidation of what lies before us.
Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery
Douglas B. Kell and Royston Goodacre
School of Chemistry and Manchester Institute of Biotechnology, The University of Manchester, Manchester, UK
Drug Discovery Today Feb 2014;19(2) http://dx.doi.org/10.1016/j.drudis.2013.07.014
Metabolism represents the ‘sharp end’ of systems biology,
because changes in metabolite concentrations
are necessarily amplified relative to
changes in the transcriptome, proteome and enzyme activities,
which can be modulated by drugs.
To understand such behaviour, we therefore need
(and increasingly have)
reliable consensus (community) models of the human metabolic network
that include the important transporters.
Small molecule ‘drug’ transporters are in fact metabolite transporters,
because drugs bear structural similarities to metabolites known
from the network reconstructions and from measurements of the metabolome.
Recon2 represents the present state-of-the-art human metabolic
network reconstruction; it can predict inter alia:
the effects of inborn errors of metabolism;
which metabolites are exometabolites, and
how metabolism varies between tissues and cellular compartments.
Even these qualitative network models are not yet complete. As our
understanding improves so do we recognize more clearly the need for a systems (poly)pharmacology.
Modelling biochemical networks – why we do so
There are at least four types of reasons as to why one would wish to model a biochemical network:
Assessing whether the model is accurate, in the sense that it
reflects – or can be made to reflect – known experimental facts.
Establishing what changes in the model would improve the
consistency of its behaviour with experimental observations
and improved predictability, such as with respect to metabolite
concentrations or fluxes.
Analyzing the model, typically by some form of sensitivity
analysis, to understand which parts of the system contribute
most to some desired functional properties of interest.
Hypothesis generation and testing, enabling one to analyse
rapidly the effects of manipulating experimental conditions in
the model without having to perform complex and costly
experiments (or to restrict the number that are performed).
In particular, it is normally considerably cheaper to perform
studies of metabolic networks in silico before trying a smaller
number of possibilities experimentally; indeed for combinatorial
reasons it is often the only approach possible. Although
our focus here is on drug discovery, similar principles apply to the
modification of biochemical networks for purposes of ‘industrial’
or ‘white’ biotechnology.
Why we choose to model metabolic networks more than
transcriptomic or proteomic networks
comes from the recognition – made particularly clear
by workers in the field of metabolic control analysis
– that, although changes in the activities of individual enzymes tend to have
rather small effects on metabolic fluxes,
they can and do have very large effects on metabolite concentrations (i.e. the metabolome).
Modelling biochemical networks – how we do so
Although one could seek to understand the
time-dependent spatial distribution of signalling and metabolic substances within indivi
dual cellular compartments and
while spatially discriminating analytical methods such as Raman spectroscopy and
mass spectrometry do exist for the analysis of drugs in situ,
the commonest type of modelling, as in the spread of substances in
ecosystems,
assumes ‘fully mixed’ compartments and thus ‘pools’ of metabolites.
Although an approximation, this ‘bulk’ modelling will be necessary for complex ecosystems such as humans where, in addition to the need for tissue- and cell-specific models, microbial communities inhabit this superorganism and the
gut serves as a source for nutrients courtesy of these symbionts.
Topology and stoichiometry of metabolic networks as major constraints on fluxes
Given their topology, which admits a wide range of parameters for
delivering the same output effects and thereby reflects biological
robustness,
metabolic networks have two especially important constraints that assist their accurate modelling:
(i) the conservation of mass and charge, and
(ii) stoichiometric and thermodynamic constraints.
These are tighter constraints than apply to signalling networks.
New developments in modelling the human metabolic network
Since 2007, several groups have been developing improved but nonidentical models of the human metabolic network at a generalised level and in tissue-specific forms. Following a similar community-driven strategy in Saccharomyces cerevisiae, surprisingly similar to humans, and in Salmonella typhimurium,
we focus in particular on a recent consensus paper that provides a highly curated and semantically annotated model of the human metabolic network, termed
In this work, a substantial number of the major groups active in this area came together to provide a carefully and manually constructed/curated network, consisting of some 1789 enzyme-encoding genes, 7440 reactions and 2626 unique metabolites distributed over eight cellular compartments. A variety of dead-end metabolites and blocked reactions remain (essentially orphans and widows). But Recon2 was able to
account for some 235 inborn errors of metabolism,
a variety of metabolic ‘tasks’ (defined as a non-zero flux through a reaction or through a pathway leading to the production of a metabolite Q from a metabolite P).
filtering based on expression profiling allowed the construction of 65 cell-type-specific models.
Excreted or exometabolites are an interesting set of metabolites,
and Recon2 could predict successfully a substantial fraction of those
Role of transporters in metabolic fluxes
The uptake and excretion of metabolites between cells and their macrocompartments
requires specific transporters and in the order of one third of ‘metabolic’ enzymes,
and indeed of membrane proteins, are in fact transporters or equivalent.
What is of particular interest (to drug discovery), based on their structural similarities, is the increasing recognition (Fig. 3) that pharmaceutical drugs also
get into and out of cells by ‘hitchhiking’ on such transporters, and not –
to any significant extent –
by passing through phospholipid bilayer portions
of cellular membranes.
This makes drug discovery even more a problem of systems biology than of biophysics.
role of solute carriers and other transporters in cellular drug uptake
Two views of the role of solute carriers and other transporters in cellular drug uptake. (a) A more traditional view in which all so-called ‘passive’drug uptake occurs through any unperturbed bilayer portion of membrane that might be present.
(b) A view in which the overwhelming fraction of drug is taken up via solute transporters or other carriers that are normally used for the uptake of intermediary metabolites. Noting that the protein:lipid ratio of biomembranes is typically 3:1 to 1:1 and that proteins vary in mass and density (a typical density is 1.37 g/ml) as does their extension, for example, normal to the ca. 4.5 nm lipid bilayer region, the figure attempts to portray a section of a membrane with realistic or typical sizes and amounts of proteins and lipids. Typical protein areas when viewed normal to the membrane are 30%, membranes are rather more ‘mosaic’ than ‘fluid’ and there is some evidence that there might be no genuinely ‘free’ bulk lipids (typical phospholipid masses are 750 Da) in biomembranes that are uninfluenced by proteins. Also shown is a typical drug: atorvastatin (LipitorW) – with a molecular mass of 558.64 Da – for size comparison purposes. If proteins are modelled as
cylinders, a cylinder with a diameter of 3.6 nm and a length of 6 nm has a molecular mass of ca. 50 kDa. Note of course that in a ‘static’ picture we cannot show the dynamics of either phospholipid chains or lipid or protein diffusion.
‘Newly discovered’ metabolites and/or their roles
To illustrate the ‘unfinished’ nature even of Recon2, which concentrates on the metabolites created via enzymes encoded in the human genome, and leaving aside the more exotic metabolites of drugs and foodstuffs and the ‘secondary’ metabolites of microorganisms, there are several examples of interesting ‘new’ (i.e. more or less recently recognised) human metabolites or roles thereof that are worth highlighting, often from studies seeking biomarkers of various diseases – for caveats of biomarker discovery, which is not a topic that we are covering here, and the need for appropriate experimental design. In addition, classes of metabolites not well represented in Recon2 are oxidised molecules such as those caused by nonenzymatic reaction of metabolites with free radicals such as the hydroxyl radical generated by unliganded iron. There is also significant interest in using methods of determining small molecules such as those in the
metabolome (inter alia) for assessing the ‘exposome’, in other words all the potentially polluting agents to which an
individual has been exposed.
Recently discovered effects of metabolites on enzymes
Another combinatorial problem reflects the fact that in molecular enzymology it is not normally realistic to assess every possible metabolite to determine whether it is an effector (i.e.activator or inhibitor) of the enzyme under study. Typical proteins are highly promiscuous and there is increasing evidence for the comparative promiscuity of metabolites
and pharmaceutical drugs. Certainly the contribution of individual small effects of multiple parameter changes can have substantial effects on the potential flux through an overall pathway, which makes ‘bottom up’ modelling an inexact science. Even merely mimicking the vivo (in Escherichia coli) concentrations of K+, Na+, Mg2+, phosphate, glutamate, sulphate and Cl significantly modulated the activities of several enzymes tested relative to the ‘usual’ assay conditions. Consequently, we need to be alive to the possibility of many (potentially major) interactions of which we are as yet ignorant. One class of example relates to the effects of the very widespread post-translational modification on metabolic
enzyme activities.
A recent and important discovery (Fig. 4) is that a single transcriptome experiment, serving as a surrogate for fluxes through individual steps, provides a huge constraint on possible models, and predicts in a numerically tractable way and
with much improved accuracy the fluxes to exometabolites without the need for such a variable ‘biomass’ term. Other recent and related strategies that exploit modern advances in ‘omics and network biology to limit the search space in constraint-based metabolic modelling.
Fig 4. Workflow for expression-profile-constrained metabolic flux estimation
Genome-scale metabolic model with gene-protein-reaction relationships
Map absolute gene expression levels to reactions
Maximise correlation between absolute gene expression and metabolic flux
Predict fluxes to exometabolites
Compare predicted with experimental fluxes to exometabolites
Drug Discovery Today
The steps in a workflow that uses constraints based on (i) metabolic network stoichiometry and chemical reaction properties (both encoded in the model) plus, and (ii) absolute (RNA-Seq) transcript expression profiles to enable the
accurate modelling of pathway and exometabolite fluxes. .
Concluding remarks – the role of metabolomics in systems pharmacology
What is becoming increasingly clear, as we recognize that to understand living organisms in health and disease we must treat them as systems, is that we must bring together our knowledge of the topologies and kinetics of metabolic networks with our knowledge of the metabolite concentrations (i.e. metabolomes) and fluxes. Because of the huge constraints imposed on metabolism by reaction stoichiometries, mass conservation and thermodynamics, comparatively few well-chosen ‘omics measurements might be needed to do this reliably (Fig. 4). Indeed, a similar approach exploiting constraints has come to the fore in denovo protein folding and interaction studies.
What this leads us to in drug discovery is the need to develop and exploit a ‘systems pharmacology’ where multiple binding targets are chosen purposely and simultaneously. Along with other measures such as phenotypic screening, and the integrating of the full suite of e-science approaches, one can anticipate considerable improvements in the rate of discovery of safe and effective drugs.
Metabolomics: the apogee of the omics trilogy
Gary J.!Patti, Oscar Yanes and Gary Siuzdak
Metabolites, the chemical entities that are transformed during metabolism, provide a functional readout of cellular biochemistry. With emerging technologies in mass spectrometry, thousands of metabolites can now be
quantitatively measured from minimal amounts of biological material, which has thereby enabled systems-level analyses. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanism are being revealed and are shaping our understanding of cell biology, physiology and medicine.
Metabolites are small molecules that are chemically transformed during metabolism and, as such, they provide a functional readout of cellular state. Unlike genes and proteins, the functions of which are subject to epigenetic regulation and posttranslational modifications, respectively, metabolites serve as direct signatures of biochemical activity and are therefore easier to correlate with phenotype. In this context, metabolite profiling, or metabolomics, has become a powerful approach that has been widely adopted for clinical diagnostics.
The field of metabolomics has made remarkable progress within the past decade and has implemented new tools that have offered mechanistic insights by allowing for the correlation of biochemical changes with phenotype.
In this Innovation article, we first define and differentiate between the targeted and untargeted approaches to metabolomics. We then highlight the value of untargeted metabolomics in particular and outline a guide to performing such studies. Finally, we describe selected applications of un targeted metabolomics and discuss their potential in cell biology.
metabolites serve as direct signatures of biochemical activity
In some instances, it may be of interest to examine a defined set of metabolites by using a targeted approach.
In other cases, an untargeted or global approach may be taken in which as many metabolites as possible are measured and compared between samples without bias.
Ultimately, the number and chemical composition of metabolites to be studied is a defining attribute of any metabolomic experiment and shapes experimental design with respect to sample preparation and choice of instrumentation.
The targeted and untargeted workflow for LC/MS-based metabolomics.
a | In the triple quadrupole (QqQ)-based targeted metabolomic workflow, standard compounds for the metabolites of interest are first used to set up selected reaction monitoring methods. Here, optimal instrument voltages are determined and response curves are generated for absolute quantification. After the targeted methods have been established
on the basis of standard metabolites, metabolites are extracted from tissues, biofluids or cell cultures and analysed. The data output provides quantification only of those metabolites for which standard methods have been built.
b | In the untargeted metabolomic workflow, metabolites are first isolated from biological samples and subsequently analysed by liquid chromatography followed by mass spectrometry (LC/MS). After data acquisition, the results are processed by using bioinformatic software such as XCMS to perform nonlinear retention time alignment and identify peaks that are changing between the groups of samples measured. The m/z value s for the peaks of interest are searched in metabolite databases to obtain putative identifications. Putative identifications are then confirmed
by comparing tandem mass spectrometry (MS/MS) data and retention time data to that of standard compounds. The untargeted workflow is global in scope and outputs data related to comprehensive cellular metabolism.
Metabolic Biomarker and Kinase Drug Target Discovery in Cancer Using Stable Isotope-Based Dynamic Metabolic Profiling (SIDMAP)
László G. Boros1*, Daniel J. Brackett2 and George G. Harrigan3
1UCLA School of Medicine, Harbor-UCLA Research and Education Institute, Torrance, CA. 2Department of Surgery, University of Oklahoma Health Sciences Center & VA Medical Center, Oklahoma City, OK, 3Global High Throughput
Screening (HTS), Pharmacia Corporation, Chesterfield, MO.
Current Cancer Drug Targets, 2003, 3, 447-455.
Tumor cells respond to growth signals by the activation of protein kinases, altered gene expression and significant modifications in substrate flow and redistribution among biosynthetic pathways. This results in a proliferating phenotype
with altered cellular function. These transformed cells exhibit unique anabolic characteristics, which includes increased and preferential utilization of glucose through the non-oxidative steps of the pentose cycle for nucleic acid synthesis but limited denovo fatty acid synthesis and TCA cycle glucose oxidation. This primarily nonoxidative anabolic profile reflects an undifferentiated highly proliferative aneuploid cell phenotype and serves as a reliable metabolic biomarker to determine cell proliferation rate and the level of cell transformation/differentiation in response to drug treatment. Novel drugs effective in particular cancers exert their anti-proliferative effects by inducing significant reversions of a few specific non-oxidative anabolic pathways. Here we present evidence that cell transformation of various mechanisms is sustained by a unique
disproportional substrate distribution between the two branches of the pentose cycle for nucleic acid synthesis, glycolysis and the TCA cycle for fatty acid synthesis and glucose oxidation. This can be demonstrated by the broad labeling and unique specificity of [1,2-13C2]glucose to trace a large number of metabolites in the metabolome. Stable isotope-based dynamic metabolic profiles (SIDMAP) serve the drug discovery process by providing a powerful new tool that integrates the metabolome into a functional genomics approach to developing new drugs. It can be used in screening kinases and their metabolic targets, which can therefore be more efficiently characterized, speeding up and improving drug testing, approval and labeling processes by saving trial and error type study costs in drug testing.
Navigating the HumanMetabolome for Biomarker Identification and Design of Pharmaceutical Molecules
Irene Kouskoumvekaki and Gianni Panagiotou
Department of Systems Biology, Center for Biological Sequence Analysis, Building 208, Technical University of Denmark, Lyngby, Denmark
Hindawi Publishing Corporation Journal of Biomedicine and Biotechnology 2011, Article ID 525497, 19 pages http://dx.doi.org:/10.1155/2011/525497
Metabolomics is a rapidly evolving discipline that involves the systematic study of endogenous small molecules that characterize the metabolic pathways of biological systems. The study of metabolism at a global level has the potential to contribute significantly to biomedical research, clinical medical practice, as well as drug discovery. In this paper, we present the most up-to-date metabolite and metabolic pathway resources, and we summarize the statistical, and machine-learning tools used for the analysis of data from clinical metabolomics.
Through specific applications on cancer, diabetes, neurological and other diseases, we demonstrate how these tools can facilitate diagnosis and identification of potential biomarkers for use within disease diagnosis. Additionally, we
discuss the increasing importance of the integration of metabolomics data in drug discovery. On a case-study based on the Human Metabolome Database (HMDB) and the Chinese Natural Product Database (CNPD), we demonstrate the close relatedness of the two data sets of compounds, and we further illustrate how structural similarity with human metabolites could assist in the design of novel pharmaceuticals and the elucidation of the molecular mechanisms of medicinal plants.
Metabolites are the byproducts of metabolism, which is itself the process of converting food energy to mechanical energy
or heat. Experts believe there are at least 3,000 metabolites that are essential for normal growth and development (primary metabolites) and thousands more unidentified (around 20,000, compared to an estimated 30,000 genes and 100,000 proteins) that are not essential for growth and development (secondary metabolites) but could represent prognostic, diagnostic, and surrogate markers for a disease state and a deeper understanding of mechanisms of disease.
Metabolomics, the study of metabolism at the global level, has the potential to contribute significantly to biomedical
research, and ultimately to clinical medical practice. It is a close counterpart to the genome, the transcriptome and the proteome. Metabolomics, genomics, proteomics, and other “-omics” grew out of the Human Genome Project, a massive research effort that began in the mid-1990s and culminated in 2003 with a complete mapping of all the genes in the human body. When discussing the clinical advantages of metabolomics, scientists point to the “real-world” assessment
of patient physiology that the metabolome provides since it can be regarded as the end-point of the “-omics” cascade. Other functional genomics technologies do not necessarily predict drug effects, toxicological response, or disease states at the phenotype but merely indicate the potential cause for phenotypical response. Metabolomics can bridge this information gap. The identification and measurement of metabolite profile dynamics of host changes provides the closest link to the various phenotypic responses. Thus it is clear that the global mapping of metabolic signatures pre- and postdrug treatment is a promising approach to identify possible functional relationships between medication and medical phenotype.
Human Metabolome Database (HMDB). Focusing on quantitative, analytic, or molecular scale information about
metabolites, the enzymes and transporters associated with them, as well as disease related properties the HMDB represents the most complete bioinformatics and chemoinformatics medical information database. It contains records for
thousands of endogenous metabolites identified by literature surveys (PubMed, OMIM, OMMBID, text books), data
mining (KEGG, Metlin, BioCyc) or experimental analyses performed on urine, blood, and cerebrospinal fluid samples.
The annotation effort is aided by chemical parameter calculators and protein annotation tools originally developed for
DrugBank.
A key feature that distinguishes the HMDB from other metabolic resources is its extensive support for higher level database searching and selecting functions. More than 175 hand-drawn-zoomable, fully hyperlinked human
metabolic pathway maps can be found in HMDB and all these maps are quite specific to human metabolism and
explicitly show the subcellular compartments where specific reactions are known to take place. As an equivalent to
BLAST the HMDB contains a structure similarity search tool for chemical structures and users may sketch or
paste a SMILES string of a query compound into the Chem-Query window. Submitting the query launches a
structure similarity search tool that looks for common substructures from the query compound that match the
HMDB’s metabolite database. The wealth of information and especially the extensive linkage to metabolic diseases
to normal and abnormal metabolite concentration ranges, to mutation/SNP data and to the genes, enzymes, reactions
and pathways associated with many diseases of interest makes the HMDB one the most valuable tool in the hands
of clinical chemists, nutritionists, physicians and medical geneticists.
Metabolomics in Drug Discovery and Polypharmacology Studies
Drug molecules generally act on specific targets at the cellular level, and upon binding to the receptors, they exert
a desirable alteration of the cellular activities, regarded as the pharmaceutical effect. Current drug discovery depends
largely on ransom screening, either high-throughput screening (HTS) in vitro, or virtual screening (VS) in silico. Because
the number of available compounds is huge, several druglikeness filters are proposed to reduce the number of compounds that need to be evaluated. The ability to effectively predict if a chemical compound is “drug-like” or “nondruglike” is, thus, a valuable tool in the design, optimization, and selection of drug candidates for development. Druglikeness is a general descriptor of the potential of a small molecule to become a drug. It is not a unified descriptor
but a global property of a compound processing many specific characteristics such as good solubility, membrane
permeability, half-life, and having a pharmacophore pattern to interact specifically with a target protein. These
characteristics can be reflected as molecular descriptors such as molecular weight, log P, the number of hydrogen bond
donors, the number of hydrogen-bond acceptors, the number of rotatable bonds, the number of rigid bonds, the
number of rings in a molecule, and so forth.
Metabolomics for the Study of Polypharmacology of Natural Compounds
Internationally, there is a growing and sustained interest from both pharmaceutical companies and public in medicine
from natural sources. For the public, natural medicine represent a holistic approach to disease treatment, with
potentially less side effects than conventional medicine. For the pharmaceutical companies, bioactive natural products
constitute attractive drug leads, as they have been optimized in a long-term natural selection process for optimal interaction with biomolecules. To promote the ecological survival of plants, structures of secondary products have evolved to interact with molecular targets affecting the cells, tissues and physiological functions in competing microorganisms,
plants, and animals. In this, respect, some plant secondary products may exert their action by resembling endogenous
metabolites, ligands, hormones, signal transduction molecules, or neurotransmitters and thus have beneficial
effects on humans.
Future Perspectives
Metabolomics, the study of metabolism at the global level, is moving to exciting directions.With the development ofmore
sensitive and advanced instrumentation and computational tools for data interpretation in the physiological context,
metabolomics have the potential to impact our understanding of molecular mechanisms of diseases. A state-of-theart
metabolomics study requires knowledge in many areas and especially at the interface of chemistry, biology, and
computer science. High-quality samples, improvements in automated metabolite identification, complete coverage of
the human metabolome, establishment of spectral databases of metabolites and associated biochemical identities, innovative experimental designs to best address a hypothesis, as well as novel computational tools to handle metabolomics data are critical hurdles that must be overcome to drive the inclusion of metabolomics in all steps of drug discovery and drug development. The examples presented above demonstrated that metabolite profiles reflect both environmental and genetic influences in patients and reveal new links between metabolites and diseases providing needed prognostic,diagnostic, and surrogate biomarkers. The integration of these signatures with other omic technologies is of utmost importance to characterize the entire spectrum of malignant phenotype.
Integrins, Cadherins, Signaling and the Cytoskeleton
Curator: Larry H. Bernstein, MD, FCAP
We have reviewed the cytoskeleton, cytoskeleton pores and ionic translocation under lipids. We shall now look at this again, with specific attention to proteins, transporters and signaling.
Integrins and extracellular matrix in mechanotransduction
Lindsay Ramage
Queen’s Medical Research Institute, University of Edinburgh,
Edinburgh, UK
Cell Health and Cytoskeleton 2012; 4: 1–9
Integrins are a family of cell surface receptors which
mediate cell–matrix and cell–cell adhesions.
Among other functions they provide an important
mechanical link between the cells external and intracellular environments while
the adhesions that they form also have critical roles in cellular signal-transduction.
Cell–matrix contacts occur at zones in the cell surface where
adhesion receptors cluster and when activated
the receptors bind to ligands in the extracellular matrix.
The extracellular matrix surrounds the cells of tissues and forms the
structural support of tissue which is particularly important in connective tissues.
Cells attach to the extracellular matrix through
specific cell-surface receptors and molecules
including integrins and transmembrane proteoglycans.
Integrins work alongside other proteins such as
cadherins,
immunoglobulin superfamily
cell adhesion molecules,
selectins, and
syndecans
to mediate
cell–cell and
cell–matrix interactions and communication.
Activation of adhesion receptors triggers the formation of matrix contacts in which
bound matrix components,
adhesion receptors,
and associated intracellular cytoskeletal and signaling molecules
form large functional, localized multiprotein complexes.
Cell–matrix contacts are important in a variety of different cell and
tissue properties including
embryonic development,
inflammatory responses,
wound healing,
and adult tissue homeostasis.
This review summarizes the roles and functions of integrins and extracellular matrix proteins in mechanotransduction.
Integrins are a family of αβ heterodimeric receptors which act as
cell adhesion molecules
connecting the ECM to the actin cytoskeleton.
The actin cytoskeleton is involved in the regulation of
cell motility,
cell polarity,
cell growth, and
cell survival.
The integrin family consists of around 25 members which are composed of differing
combinations of α and β subunits.
The combination of αβ subunits determines
binding specificity and
signaling properties.
In mammals around 19 α and eight β subunits have been characterized.
Both α and β integrin subunits contain two separate tails, which
penetrate the plasma membrane and possess small cytoplasmic domains which facilitate
the signaling functions of the receptor.
There is some evidence that the β subunit is the principal
site for
binding of cytoskeletal and signaling molecules,
whereas the α subunit has a regulatory role. The integrin
tails
link the ECM to the actin cytoskeleton within the cell and with cytoplasmic proteins,
such as talin, tensin, and filamin. The extracellular domains of integrin receptors bind the ECM ligands.
The ECM is a complex mixture of matrix molecules, including -glycoproteins, collagens, laminins, glycosaminoglycans, proteoglycans,
and nonmatrix proteins, – including growth factors.
These can be categorized as insoluble molecules within the ECM, soluble molecules, and/or matrix-associated biochemicals, such as systemic hormones or growth factors and cytokines that act locally.
The integrin receptor formed from the binding of α and β subunits is shaped like a globular head supported by two rod-like legs (Figure 1). Most of the contact between the two subunits occurs in the head region, with the intracellular tails of the subunits forming the legs of the receptor.6 Integrin recognition of ligands is not constitutive but is regulated by alteration of integrin affinity for ligand binding. For integrin binding to ligands to occur the integrin must be primed and activated, both of which involve conformational changes to the receptor.
The integrins are composed of well-defined domains used for protein–protein interactions. The α-I domains of α integrin subunits comprise the ligand binding sites. X-ray crystallography has identified an α-I domain within the β subunit and a β propeller domain within the α subunit which complex to form the ligand-binding head of the integrin.
The use of activating and conformation-specific antibodies also suggests that the β chain is extended in the active integrin. It has since been identified that the hybrid domain in the β chain is critical for integrin activation, and a swing-out movement of this leg activates integrins.
Figure Integrin binding to extracellular matrix (ECM). Conformational changes to integrin structure and clustering of subunits which allow enhanced function of the receptor.
Integrin extracellular binding activity is regulated from inside the cell and binding to the ECM induces signals that are transmitted into the cell.15 This bidirectional signaling requires
dynamic,
spatially, and
temporally regulated formation and
disassembly of multiprotein complexes that
form around the short cytoplasmic tails of integrins.
Ligand binding to integrin family members leads to clustering of integrin molecules in the plasma membrane and recruitment of actin filaments and intracellular signaling molecules to the cytoplasmic domain of the integrins. This forms focal adhesion complexes which are able to maintain
not only adhesion to the ECM
but are involved in complex signaling pathways
which include establishing
cell polarity,
directed cell migration, and
maintaining cell growth and survival.
Initial activation through integrin adhesion to matrix recruits up to around 50 diverse signaling molecules
to assemble the focal adhesion complex
which is capable of responding to environmental stimuli efficiently.
Mapping of the integrin
adhesome binding and signaling interactions
identified a network of 156 components linked together which can be modified by 690 interactions.
The binding of the adaptor protein talin to the β subunit cytoplasmic tail is known to have a key role in integrin activation. This is thought to occur through the disruption of
inhibitory interactions between α and β subunit cytoplasmic tails.
Talin also binds
to actin and to cytoskeletal and signaling proteins.
This allows talin to directly link activated integrins
to signaling events and the cytoskeleton.
Genetic programming occurs with the binding of integrins to the ECM
Signal transduction pathway activation arising from integrin-
ECM binding results in changes in gene expression of cells
and leads to alterations in cell and tissue function. Various
different effects can arise depending on the
cell type,
matrix composition, and
integrins activated.
One way in which integrin expression is important in genetic programming is in the fate and differentiation of stem cells.
Osteoblast differentiation occurs through ECM interactions
with specific integrins
to initiate intracellular signaling pathways leading to osteoblast-specific gene expression
disruption of interactions between integrins and collagen;
fibronectin blocks osteoblast differentiation and
Disruption of α2 integrin prevents osteoblast differentiation, and activation of the transcription factor
It has been suggested that integrin-type I collagen interaction is necessary for the phosphorylation and activation of osteoblast-specific transcription factors present in committed osteoprogenitor cells.
A variety of growth factors and cytokines have been shown to be important in the regulation of integrin expression and function in chondrocytes. Mechanotransduction in chondrocytes occurs through several different receptors and ion channels including integrins. During osteoarthritis the expression of integrins by chondrocytes is altered, resulting in different cellular transduction pathways which contribute to tissue pathology.
In normal adult cartilage, chondrocytes express α1β1, α10β1 (collagen receptors), α5β1, and αvβ5 (fibronectin) receptors. During mechanical loading/stimulation of chondrocytes there is an influx of ions across the cell membrane resulting from activation of mechanosensitive ion channels which can be inhibited by subunit-specific anti-integrin blocking antibodies or RGD peptides. Using these strategies it was identified that α5β1 integrin is a major mechanoreceptor in articular chondrocyte responses to mechanical loading/stimulation.
Osteoarthritic chondrocytes show a depolarization response to 0.33 Hz stimulation in contrast to the hyperpolarization response of normal chondrocytes. The mechanotransduction pathway in chondrocytes derived from normal and osteoarthritic cartilage both involve recognition of the mechanical stimulus by integrin receptors resulting in the activation of integrin signaling pathways leading to the generation of a cytokine loop. Normal and osteoarthritic chondrocytes show differences at multiple stages of the mechanotransduction cascade (Figure 3). Early events are similar; α5β1 integrin and stretch activated ion channels are activated and result in rapid tyrosine phosphorylation events. The actin cytoskeleton is required for the integrin-dependent Mechanotransduction leading to changes in membrane potential in normal but not osteoarthritic chondrocytes.
Cell–matrix interactions are essential for maintaining the integrity of tissues. An intact matrix is essential for cell survival and proliferation and to allow efficient mechanotransduction and tissue homeostasis. Cell–matrix interactions have been extensively studied in many tissues and this knowledge is being used to develop strategies to treat pathology. This is particularly important in tissues subject to abnormal mechanical loading, such as musculoskeletal tissues. Integrin-ECM interactions are being used to enhance tissue repair mechanisms in these tissues through differentiation of progenitor cells for in vitro and in vivo use. Knowledge of how signaling cascades are differentially regulated in response to physiological and pathological external stimuli (including ECM availability and mechanical loading/stimulation) will enable future strategies to be developed to prevent and treat the progression of pathology associated with integrin-ECM interactions.
Cellular adaptation to mechanical stress: role of integrins, Rho, cytoskeletal tension and mechanosensitive ion channels
Matthews, DR. Overby, R Mannix and DE. Ingber
1Vascular Biology Program, Departments of Pathology and Surgery, Children’s Hospital, and 2Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA J Cell Sci 2006; 119: 508-518. http://dx.doi.org:/10.1242/jcs.02760
To understand how cells sense and adapt to mechanical stress, we applied tensional forces to magnetic microbeads bound to cell-surface integrin receptors and measured changes in bead isplacement with sub-micrometer resolution using optical microscopy. Cells exhibited four types of mechanical responses: (1) an immediate viscoelastic response;
(2) early adaptive behavior characterized by pulse-to-pulse attenuation in response to oscillatory forces;
(3) later adaptive cell stiffening with sustained (>15 second) static stresses; and
(4) a large-scale repositioning response with prolonged (>1 minute) stress.
Importantly, these adaptation responses differed biochemically. The immediate and early responses were affected by
inhibiting tension through interference with Rho signaling,
similar to the case of the immediate and early responses, but it was also prevented by
blocking mechanosensitive ion channels or
by inhibiting Src tyrosine kinases.
All adaptive responses were suppressed by cooling cells to 4°C to slow biochemical remodeling. Thus, cells use multiple mechanisms to sense and respond to static and dynamic changes in the level of mechanical stress applied to integrins.
Microtubule-Stimulated ADP Release, ATP Binding, and Force Generation In Transport Kinesins
J Atherton, I Farabella, I-Mei Yu, SS Rosenfeld, A Houdusse, M Topf, CA Moores
1Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, University of London, London, United Kingdom; 2Structural Motility, Institut Curie, Centre National de la Recherche Scientifique, Paris, France; 3Department of Cancer Biology, Lerner Research Institute, Cleveland Clinic, Cleveland, United States
eLife 2014;3:e03680. http://dx.doi.org:/10.7554/eLife.03680
Kinesins are a large family of microtubule (MT)-based motors that play important roles in many cellular activities including
mitosis,
motility, and
intracellular transport
Their involvement in a range of pathological processes also highlights their significance as therapeutic targets and the importance of understanding the molecular basis of their function They are defined by their motor domains that contain both the microtubule (MT) and ATP binding sites. Three ATP binding motifs—the P-loop, switch I, switch II–are highly conserved among kinesins, myosin motors, and small GTPases. They share a conserved mode of MT binding such that MT binding, ATP binding, and hydrolysis are functionally coupled for efficient MT-based work.
The interior of a cell is a hive of activity, filled with proteins and other items moving from one location to another. A network of filaments called microtubules forms tracks along which so-called motor proteins carry these items. Kinesins are one group of motor proteins, and a typical kinesin protein has one end (called the ‘motor domain’) that can attach itself to the microtubules.
The other end links to the cargo being carried, and a ‘neck’ connects the two. When two of these proteins work together, flexible regions of the neck allow the two motor domains to move past one another, which enable the kinesin to essentially walk along a microtubule in a stepwise manner.
Atherton et al. use a technique called cryo-electron microscopy to study—in more detail than previously seen—the structure of the motor domains of two types of kinesin called kinesin-1 and kinesin-3. Images were taken at different stages of the cycle used by the motor domains to extract the energy from ATP molecules. Although the two kinesins have been thought to move along the microtubule tracks in different ways, Atherton et al. find that the core mechanism used by their motor domains is the same.
When a motor domain binds to the microtubule, its shape changes, first stimulating release of the breakdown products of ATP from the previous cycle. This release makes room for a new ATP molecule to bind. The structural changes caused by ATP binding are relatively small but produce larger changes in the flexible neck region that enable individual motor domains within a kinesin pair to co-ordinate their movement and move in a consistent direction. This mechanism involves tight coupling between track binding and fuel usage and makes kinesins highly efficient motors.
A number of kinesins drive long distance transport of cellular cargo with dimerisation allowing them to take multiple 8 nm ATP-driven steps toward MT plus ends. Their processivity depends on communication between the two motor domains, which is achieved via the neck linker that connects each motor domain to the dimer-forming coiled-coil
Kinesins are a superfamily of microtubule-based
ATP-powered motors, important for multiple, essential cellular functions.
How microtubule binding stimulates their ATPase and controls force generation is not understood. To address this fundamental question, we visualized microtubule-bound kinesin-1 and kinesin-3 motor domains at multiple steps in their ATPase cycles—including their nucleotide-free states—at ∼7 Å resolution using cryo-electron microscopy.
All our reconstructions have, as their asymmetric unit, a triangle-shaped motor domain bound to an αβ-tubulin dimer within the MT lattice (Figure 1). The structural comparisons below are made with respect to the MT surface, which, at the resolution of our structures (∼7 Å, Table 1), is the same (CCC > 0.98 for all). As is well established across the superfamily, the major and largely invariant point of contact between kinesin motor domains and the MT is helix-α4, which lies at the tubulin intradimer interface (Figure 1C, Kikkawa et al., 2001).
However, multiple conformational changes are seen throughout the rest of each domain in response to bound nucleotide (Figure 1D). Below, we describe the conformational changes in functionally important regions of each motor domain starting with the nucleotide-binding site, from which all other conformational changes emanate.
The nucleotide-binding site (Figure 2) has three major elements: (1) the P-loop (brown) is visible in all our reconstructions;
(2) loop9 (yellow, contains switch I) undergoes major conformational changes through the ATPase cycle; and
(3) loop11 (red, contains switch II) that connects strand-β7 to helix-α4,
the conformation and flexibility of which is determined by MT binding and motor nucleotide state.
Movement and extension of helix-α6 controls neck linker docking
the N-terminus of helix-α6 is closely associated with elements of the nucleotide binding site suggesting that its conformation alters in response to different nucleotide states. In addition, because the orientation of helix-α6 with respect to helix-α4 controls neck linker docking and because helix-α4 is held against the MT during the ATPase cycle,
conformational changes in helix-α6 control movement of the neck linker.
Mechanical amplification and force generation involves conformational changes across the motor domain
A key conformational change in the motor domain following Mg-ATP binding is peeling of the central β-sheet from the C-terminus of helix-α4 increasing their separation (Figure 3—figure supplement 2); this is required to accommodate rotation of helix-α6 and consequent neck linker docking (Figure 3B–E).
Peeling of the central β-sheet has previously been proposed to arise from tilting of the entire motor domain relative to static MT contacts, pivoting around helix-α4 (the so-called ‘seesaw’ model; Sindelar, 2011). Specifically, this model predicts that the major difference in the motor before and after Mg-ATP binding would be the orientation of the motor domain with respect to helix-α4.
Kinesin mechanochemistry and the extent of mechanistic conservation within the motor superfamily are open questions, critical to explain how MT binding, and ATP binding and hydrolysis drive motor activity. Our structural characterisation of two transport motors now allows us to propose a model that describes the roles of mechanochemical elements that together drive conserved MT-based motor function.
Model of conserved MT-bound kinesin mechanochemistry. Loop11/N-terminus of helix-α4 is flexible in ADP-bound kinesin in solution, the neck linker is also flexible while loop9 chelates ADP. MT binding is sensed by loop11/helix-α4 N-terminus, biasing them towards more ordered conformations.
We propose that this favours crosstalk between loop11 and loop9, stimulating ADP release. In the NN conformation, both loop11 and loop9 are well ordered and primed to favour ATP binding, while helix-α6—which is required for mechanical amplification–is closely associated with the MT on the other side of the motor domain. ATP binding draws loop11 and loop9 closer together; causing
(1) tilting of most of the motor domain not contacting the MT towards the nucleotide-binding site,
(2) rotation, translation, and extension of helix-α6 which we propose contributes to force generation, and
(3) allows neck linker docking and biases movement of the 2nd head towards the MT plus end.
In both motors, microtubule binding promotes
ordered conformations of conserved loops that
stimulate ADP release,
enhance microtubule affinity and
prime the catalytic site for ATP binding.
ATP binding causes only small shifts of these nucleotide-coordinating loops but induces
large conformational changes elsewhere that
allow force generation and
neck linker docking towards the microtubule plus end.
Family-specific differences across the kinesin–microtubule interface account for the
distinctive properties of each motor.
Our data thus provide evidence for a
conserved ATP-driven
mechanism for kinesins and
reveal the critical mechanistic contribution of the microtubule interface.
Phosphorylation at endothelial cell–cell junctions: Implications for VE-cadherin function
I Timmerman, PL Hordijk, JD van Buul
Cell Health and Cytoskeleton 2010; 2: 23–31
Endothelial cell–cell junctions are strictly regulated in order to
control the barrier function of endothelium.
Vascular endothelial (VE)-cadherin is one of the proteins that is crucial in this process. It has been reported that
phosphorylation events control the function of VE-cadherin.
This review summarizes the role of VE-cadherin phosphorylation in the regulation of endothelial cell–cell junctions and highlights how this affects vascular permeability and leukocyte extravasation.
The vascular endothelium is the inner lining of blood vessels and
forms a physical barrier between the vessel lumen and surrounding tissue;
controlling the extravasation of fluids,
plasma proteins and leukocytes.
Changes in the permeability of the endothelium are tightly regulated. Under basal physiological conditions, there is a continuous transfer of substances across the capillary beds. In addition the endothelium can mediate inducible,
transient hyperpermeability
in response to stimulation with inflammatory mediators,
which takes place primarily in postcapillary venules.
However, when severe, inflammation may result in dysfunction of the endothelial barrier in various parts of the vascular tree, including large veins, arterioles and capillaries. Dysregulated permeability is observed in various pathological conditions, such as tumor-induced angiogenesis, cerebrovascular accident and atherosclerosis.
Two fundamentally different pathways regulate endothelial permeability,
the transcellular and paracellular pathways.
Solutes and cells can pass through the body of endothelial cells via the transcellular pathway, which includes
vesicular transport systems, fenestrae, and biochemical transporters.
The paracellular route is controlled by
the coordinated opening and closing of endothelial junctions and
thereby regulates traffic across the intercellular spaces between endothelial cells.
Endothelial cells are connected by
tight, gap and
adherens junctions,
of which the latter, and particularly the adherens junction component,
vascular endothelial (VE)-cadherin,
are of central importance for the initiation and stabilization of cell–cell contacts.
Although multiple adhesion molecules are localized at endothelial junctions, blocking the adhesive function of VE-cadherin using antibodies is sufficient to disrupt endothelial junctions and to increase endothelial monolayer permeability both in vitro and in vivo. Like other cadherins, VE-cadherin mediates adhesion via homophilic, calcium-dependent interactions.
This cell–cell adhesion
is strengthened by binding of cytoplasmic proteins, the catenins,
to the C-terminus of VE-cadherin.
VE-cadherin can directly bind β-catenin and plakoglobin, which
both associate with the actin binding protein α-catenin.
Initially, α-catenin was thought to directly anchor cadherins to the actin cytoskeleton, but recently it became clear that
α-catenin cannot bind to both β-catenin and actin simultaneously.
Data using purified proteins show that
monomeric α-catenin binds strongly to cadherin-bound β-catenin;
in contrast to the dimer which has a higher affinity for actin filaments,
indicating that α-catenin might function as a molecular switch regulating cadherin-mediated cell–cell adhesion and actin assembly.
Thus, interactions between the cadherin complex and the actin cytoskeleton are more complex than previously thought. Recently, Takeichi and colleagues reported that
the actin binding protein EPLIN (epithelial protein lost in neoplasm)
can associate with α-catenin and thereby
link the E-cadherin–catenin complex to the actin cytoskeleton.
Although this study was performed in epithelial cells,
an EPLIN-like molecule might serve as
a bridge between the cadherin–catenin complex and
the actin cytoskeleton in endothelial cells.
Next to β-catenin and plakoglobin, p120-catenin also binds directly to the intracellular tail of VE-cadherin.
Numerous lines of evidence indicate that
p120-catenin promotes VE-cadherin surface expression and stability at the plasma membrane.
Different models are proposed that describe how p120-catenin regulates cadherin membrane dynamics, including the hypothesis
that p120-catenin functions as a ‘cap’ that prevents the interaction of VE-cadherin
with the endocytic membrane trafficking machinery.
In addition, p120-catenin might regulate VE-cadherin internalization through interactions with small GTPases. Cytoplasmic p120-catenin, which is not bound to VE-cadherin, has been shown to
decrease RhoA activity,
elevate active Rac1 and Cdc42, and thereby is thought
to regulate actin cytoskeleton organization and membrane trafficking.
The intact cadherin-catenin complex is required for proper functioning of the adherens junction. Mutant forms of VE-cadherin which
lack either the β-catenin, plakoglobin or p120 binding regions reduce the strength of cell–cell adhesion.
Moreover, our own results showed that
interfering with the interaction between α-catenin and β-catenin,
using a cell-permeable peptide which encodes the binding site in α-catenin for β-catenin,
resulted in an increased permeability of the endothelial monolayer.
Several mechanisms may be involved in the regulation of the organization and function of the cadherin–catenin complex, including endocytosis of the complex, VE-cadherin cleavage and actin cytoskeleton reorganization. The remainder of this review primarily focuses on the
role of tyrosine phosphorylation in the control of VE-cadherin-mediated cell–cell adhesion.
Regulation of the adhesive function of VE-cadherin by tyrosine phosphorylation
It is a widely accepted concept that tyrosine phosphorylation of components of the VE–cadherin-catenin complex
Correlates with the weakening of cell–cell adhesion.
One of the first reports that supported this idea showed that the level of phosphorylation of VE-cadherin was
high in loosely confluent endothelial cells, but
low in tightly confluent monolayers,
when intercellular junctions are stabilized.
In addition, several conditions that induce tyrosine phosphorylation
of adherens junction components, like
v-Src transformation
and inhibition of phosphatase activity by pervanadate,
have been shown to shift cell–cell adhesion from a strong to a weak state. More physiologically relevant;
permeability-increasing agents such as
histamine,
tumor necrosis factor-α (TNF-α),
thrombin,
platelet-activating factor (PAF) and
vascular endothelial growth factor (VEGF)
increase tyrosine phosphorylation of various components of the cadherin–catenin complex.
A general idea has emerged that
tyrosine phosphorylation of the VE-cadherin complex
leads to the uncoupling of VE-cadherin from the actin cytoskeleton
through dissociation of catenins from the cadherin.
However, tyrosine phosphorylation of VE-cadherin is required for efficient transmigration of leukocytes.
This suggests that VE-cadherin-mediated cell–cell contacts
are not just pushed open by the migrating leukocytes, but play
a more active role in the transmigration process.
A schematic overview of leukocyte adhesion-induced signals leading to VE-cadherin phosphorylation
Regulation of the integrity of endothelial cell–cell contacts by phosphorylation of VE-cadherin
Regulation of the integrity of endothelial cell–cell contacts by phosphorylation of VE-cadherin.
Notes: A) Permeability-inducing agents such as thrombin, histamine and VEGF, induce tyrosine phosphorylation (pY) of VE-cadherin and the associated catenins. Although the specific consequences of catenin tyrosine phosphorylation in endothelial cells are still unknown, VE-cadherin tyrosine phosphorylation results in opening of the cell–cell junctions (indicated by arrows) and enhanced vascular permeability. How tyrosine phosphorylation affects VE-cadherin adhesiveness is not yet well understood; disrupted binding of catenins, which link the cadherin to the actin cytoskeleton, may be involved. VEGF induces phosphorylation of VE-cadherin at specific residues, Y658 and Y731, which have been reported to regulate p120-catenin and β-catenin binding, respectively. Moreover, VEGF stimulation results in serine phosphorylation (pSer) of VE-cadherin, specifically at residue S665, which leads to its endocytosis. B) Adhesion of leukocytes to endothelial cells via ICAM-1 increases endothelial permeability by inducing phosphorylation of VE-cadherin on tyrosine residues. Essential mediators, such as the kinases Pyk2 and Src, and signaling routes involving reactive oxygen species (ROS) and Rho, have been shown to act downstream of ICAM-1. Different tyrosine residues within the cytoplasmic domain of VE-cadherin are involved in the extravasation of neutrophils and lymphocytes, including Y658 and Y731. (β: β-catenin, α: α-catenin, γ: γ-catenin/plakoglobin).
N-glycosylation status of E-cadherin controls cytoskeletal dynamics through the organization of distinct β-catenin- and γ-catenin-containing AJs
BT Jamal, MN Nita-Lazar, Z Gao, B Amin, J Walker, MA Kukuruzinska
Cell Health and Cytoskeleton 2009; 1: 67–80
N-glycosylation of E-cadherin has been shown to inhibit cell–cell adhesion. Specifically, our recent studies have provided evidence that the reduction of E-cadherin N-glycosylation promoted the recruitment of stabilizing components, vinculin and serine/ threonine protein phosphatase 2A (PP2A), to adherens junctions (AJs) and enhanced the association of AJs with the actin cytoskeleton. Here, we examined the details of how
N-glycosylation of E-cadherin affected the molecular organization of AJs and their cytoskeletal interactions.
Using the hypoglycosylated E-cadherin variant, V13, we show that
V13/β-catenin complexes preferentially interacted with PP2A and with the microtubule motor protein dynein.
This correlated with dephosphorylation of the microtubule-associated protein tau, suggesting that
increased association of PP2A with V13-containing AJs promoted their tethering to microtubules.
On the other hand, V13/γ-catenin complexes associated more with vinculin, suggesting that they
mediated the interaction of AJs with the actin cytoskeleton.
N-glycosylation driven changes in the molecular organization of AJs were physiologically significant because transfection of V13 into A253 cancer cells, lacking both mature AJs and tight junctions (TJs), promoted the formation of stable AJs and enhanced the function of TJs to a greater extent than wild-type E-cadherin.
These studies provide the first mechanistic insights into how N-glycosylation of E-cadherin drives changes in AJ composition through
the assembly of distinct β-catenin- and γ-catenin-containing scaffolds that impact the interaction with different cytoskeletal components.
Cytoskeletal Basis of Ion Channel Function in Cardiac Muscle
Matteo Vatta, and Georgine Faulkner,
1 Departments of Pediatrics (Cardiology), Baylor College of Medicine, Houston, TX 2 Department of Reproductive and Developmental Sciences, University of Trieste, Trieste, Italy
3 Muscular Molecular Biology Unit, International Centre for Genetic Engineering and Biotechnology, Padriciano, Trieste, Italy
The heart is a force-generating organ that responds to
self-generated electrical stimuli from specialized cardiomyocytes.
This function is modulated
by sympathetic and parasympathetic activity.
In order to contract and accommodate the repetitive morphological changes induced by the cardiac cycle, cardiomyocytes
depend on their highly evolved and specialized cytoskeletal apparatus.
Defects in components of the cytoskeleton, in the long term,
affect the ability of the cell to compensate at both functional and structural levels.
In addition to the structural remodeling,
the myocardium becomes increasingly susceptible to altered electrical activity leading to arrhythmogenesis.
The development of arrhythmias secondary to structural remodeling defects has been noted, although the detailed molecular mechanisms are still elusive. Here I will review
the current knowledge of the molecular and functional relationships between the cytoskeleton and ion channels
and, I will discuss the future impact of new data on molecular cardiology research and clinical practice.
Myocardial dysfunction in the end-stage failing heart is very often associated with increasing
susceptibility to ventricular tachycardia (VT) and ventricular fibrillation (VF),
both of which are common causes of sudden cardiac death (SCD).
Among the various forms of HF,
myocardial remodeling due to ischemic cardiomyopathy (ICM) or dilated cardiomyopathy (DCM)
is characterized by alterations in baseline ECG,
which includes the
prolongation of the QT interval,
as well as QT dispersion,
ST-segment elevation, and
T-wave abnormalities,
especially during exercise. In particular, subjects with
severe left ventricular chamber dilation such as in DCM can have left bundle branch block (LBBB), while right bundle branch block (RBBB) is more characteristic of right ventricular failure. LBBB and RBBB have both been repeatedly associated with AV block in heart failure.
The impact of volume overload on structural and electro-cardiographic alterations has been noted in cardiomyopathy patients treated with left ventricular assist device (LVAD) therapy, which puts the heart at mechanical rest. In LVAD-treated subjects,
QRS- and both QT- and QTc duration decreased,
suggesting that QRS- and QT-duration are significantly influenced by mechanical load and
that the shortening of the action potential duration contributes to the improved contractile performance after LVAD support.
Despite the increasing use of LVAD supporting either continuous or pulsatile blood flow in patients with severe HF, the benefit of this treatment in dealing with the risk of arrhythmias is still controversial.
Large epidemiological studies, such as the REMATCH study, demonstrated that the
employment of LVAD significantly improved survival rate and the quality of life, in comparison to optimal medical management.
An early postoperative period study after cardiac unloading therapy in 17 HF patients showed that in the first two weeks after LVAD implantation,
HF was associated with a relatively high incidence of ventricular arrhythmias associated with QTc interval prolongation.
In addition, a recent retrospective study of 100 adult patients with advanced HF, treated with an axial-flow HeartMate LVAD suggested that
the rate of new-onset monomorphic ventricular tachycardia (MVT) was increased in LVAD treated patients compared to patients given only medical treatment,
while no effect was observed on the development of polymorphic ventricular tachycardia (PVT)/ventricular fibrillation (VF).
The sarcomere
The myocardium is exposed to severe and continuous biomechanical stress during each contraction-relaxation cycle. When fiber tension remains uncompensated or simply unbalanced,
it may represent a trigger for arrhythmogenesis caused by cytoskeletal stretching,
which ultimately leads to altered ion channel localization, and subsequent action potential and conduction alterations.
Cytoskeletal proteins not only provide the backbone of the cellular structure, but they also
maintain the shape and flexibility of the different sub-cellular compartments, including the
plasma membrane,
the double lipid layer, which defines the boundaries of the cell and where
ion channels are mainly localized.
The interaction between the sarcomere, which is the basic for the passive force during diastole and for the restoring force during systole. Titin connects
the Z-line to the M-line of the sarcomeric structure
(Figure 1).
In addition to the strategic
localization and mechanical spring function,
titin is a length-dependent sensor during
stretch and promotes actin-myosin interaction
Titin is stabilized by the cross-linking protein
telethonin (T-Cap), which localizes at the Z-line and is also part of titin sensor machinery (Figure 1).
The complex protein interactions in the sarcomere entwine telethonin to other
Z-line components through the family of the telethonin-binding proteins of the Z-disc, FATZ, also known as calsarcin and myozenin.
FATZ binds to
calcineurin,
γ-filamin as well as the
spectrin-like repeats (R3–R4) of α-actinin-2,
the major component of the Z-line and a pivotal
F-actin cross-linker (Figure 1).contractile unit of striated muscles, and
the sarcolemma,
the plasma membrane surrendering the muscle fibers in skeletal muscle and the muscle cell of the cardiomyocyte,
determines the mechanical plasticity of the cell, enabling it to complete and re-initiate each contraction-relaxation cycle.
At the level of the sarcomere,
actin (thin) and myosin (thick) filaments generate the contractile force,
while other components such as titin, the largest protein known to date, are responsible for
the passive force during diastole and for the restoring force during systole, and (titin).
the Z-line to the M-line of the sarcomeric structure
(Figure 1).
In addition to the strategic
localization and mechanical spring function,
it acts as a length-dependent sensor during stretch and
promotes actin-myosin interaction.
Stabilized by the cross-linking protein telethonin (T-Cap),
titin localizes at the Z-line and is
part of titin sensor machinery
Another cross-linker of α-actinin-2 in the complex Z-line scaffold is
the Z-band alternatively spliced PDZ motif protein (ZASP),
which has an important role in maintaining Z-disc stability
in skeletal and cardiac muscle (Figure 1).
ZASP contains a PDZ motif at its N-terminus,
which interacts with C-terminus of α-actinin-2,
and a conserved sequence called the ZASP like motif (ZM)
found in the alternatively spliced exons 4 and 6.
It has also been reported
to bind to the FATZ (calsarcin) family of Z-disc proteins (Figure 1).
The complex protein interactions in the sarcomere entwine telethonin to other Z-line components through the family of the telethonin-binding proteins of the
Z-disc,
FATZ, also known as calsarcin and
myozenin
FATZ binds to calcineurin,
γ-filamin as well as the
spectrin-like repeats (R3–R4) of α-actinin-2, the major component of the Z-line and a pivotal F-actin cross-linker (Figure 1).
sarcomere structure
Figure 1. Sarcomere structure
The diagram illustrates the sarcomeric structure. The Z-line determines the boundaries of the contractile unit, while Titin connects the Z-line to the M-line and acts as a functional spring during contraction/relaxation cycles.
Sarcomeric Proteins and Ion Channels
In addition to systolic dysfunction characteristic of dilated cardiomyopathy (DCM) and diastolic dysfunction featuring hypertrophic cardiomyopathy (HCM), the clinical phenotype of patients with severe cardiomyopathy is very often associated with a high incidence of cardiac arrhythmias. Therefore, besides fiber stretch associated with mechanical and hemodynamic impairment, cytoskeletal alterations due to primary genetic defects or indirectly to alterations in response to cellular injury can potentially
affect ion channel anchoring, and trafficking, as well as
functional regulation by second messenger pathways,
causing an imbalance in cardiac ionic homeostasis that will trigger arrhythmogenesis.
Intense investigation of
the sarcomeric actin network,
the Z-line structure, and
chaperone molecules docking in the plasma membrane,
has shed new light on the molecular basis of
cytoskeletal interactions in regulating ion channels.
In 1991, Cantiello et al., demonstrated that
although the epithelial sodium channel and F-actin are in close proximity,
they do not co-localize.
Actin disruption using cytochalasin D, an agent that interferes with actin polymerization, increased Na+ channel activity in 90% of excised patches tested within 2 min, which indicated that
the integrity of the filamentous actin (F-actin) network was essential
for the maintenance of normal Na+ channel function.
Later, the group of Dr. Jonathan Makielski demonstrated that
actin disruption induced a dramatic reduction in Na+ peak current and
slowed current decay without affecting steady-state voltage-dependent availability or recovery from inactivation.
These data were the first to support a role for the cytoskeleton in cardiac arrhythmias.
F-actin is intertwined in a multi-protein complex that includes
the composite Z-line structure.
Further, there is a direct binding between
the major protein of the Z-line, α-actinin-2 and
the voltage-gated K+ channel 1.5 (Kv1.5), (Figure 2).
The latter is expressed in human cardiomyocytes and localizes to
the intercalated disk of the cardiomyocyte
in association with connexin and N-cadherin.
Maruoka et al. treated HEK293 cells stably expressing Kv1.5 with cytochalasin D, which led to
a massive increase in ionic and gating IK+ currents.
This was prevented by pre-incubation with phalloidin, an F-actin stabilizing agent. In addition, the Z-line protein telethonin binds to the cytoplasmic domain of minK, the beta subunit of the potassium channel KCNQ1 (Figure 2).
Molecular interactions between the cytoskeleton and ion channels
Figure 2. Molecular interactions between the cytoskeleton and ion channels
The figure illustrates the interactions between the ion channels on the sarcolemma, and the sarcomere in cardiac myocytes. Note that the Z-line is connected to the cardiac T-tubules. The diagram illustrates the complex protein-protein interactions that occur between structural components of the cytoskeleton and ion channels. The cytoskeleton is involved in regulating the metabolism of ion channels, modifying their expression, localization, and electrical properties. The cardiac sodium channel Nav1.5 associates with the DGC, while potassium channels such as Kv1.5, associate with the Z-line.
Ion Channel Subunits and Trafficking
Correct localization is essential for ion channel function and this is dependent upon the ability of auxiliary proteins to
shuttle ion channels from the cytoplasm to their final destination such as
the plasma membrane or other sub-cellular compartments.
In this regard, Kvβ-subunits are
cytoplasmic components known to assemble with the α-subunits of voltage-dependent K+ (Kv) channels
at their N-terminus to form stable Kvα/β hetero-oligomeric channels.
When Kvβ is co-expressed with Kv1.4 or Kv1.5, it enhances Kv1.x channel trafficking to the cell membrane without changing the overall protein channel content. The regulatory Kvβ subunits, which are also expressed in cardiomyocytes, directly decrease K+ current by
accelerating Kv1.x channel inactivation.
Therefore, altered expression or mutations in Kvβ subunits could cause abnormal ion channel transport to the cell surface, thereby increasing the risk of cardiac arrhythmias.
Ion Channel Protein Motifs and Trafficking
Cell membrane trafficking in the Kv1.x family may occur in a Kvβ subunit-independent manner through specific motifs in their C-terminus. Mutagenesis of the final asparagine (N) in the Kv1.2 motif restores the leucine (L) of the Kv1.4 motif
re-establishing high expression levels at the plasma membrane in a Kvβ-independent manner
Cytoskeletal Proteins and Ion Channel Trafficking
Until recently, primary arrhythmias such as LQTS have been almost exclusively regarded as ion channelopathies. Other mutations have been identified with regard to channelopathies. However, the conviction that primary mutations in ion channels were solely responsible for
the electrical defects associated with arrhythmias
has been shaken by the identification of mutations in the
ANK2 gene encoding the cytoskeletal protein ankyrin-B
that is associated with LQTS in animal models and humans.
Ankyrin-B acts as a chaperone protein, which shuttles the cardiac sodium channel from the cytoplasm to the membrane. Immunohistochemical analysis has localized ankyrin-B to the Zlines/T-tubules on the plasma membrane in the myocardium. Mutations in ankyrin-B associated with LQTS
alter sodium channel trafficking due to loss of ankyrin-B localization at the Z-line/transverse (T)-tubules.
Reduced levels of ankyrin-B at cardiac Z-lines/T-tubules were associated with the deficiency of ankyrin-B-associated proteins such as Na/K-ATPase, Na/Ca exchanger (NCX) and inositol-1, 4, 5-trisphosphate receptors (InsP3R).
Dystrophin component of the Dystrophin Glycoprotien Complex (DGC)
Synchronized contraction is essential for cardiomyocytes, which are connected to each other via the extracellular matrix (ECM) through the DGC. The N-terminus domain of dystrophin
binds F-actin, and connects it to the sarcomere, while
the cysteine-rich (CR) C-terminus domain ensures its connection to the sarcolemma (Figure 2).
The central portion of dystrophin, the rod domain, is composed of
rigid spectrin-like repeats and four hinge portions (H1–H4) that determine the flexibility of the protein.
Dystrophin possesses another F-actin binding domain in the Rod domain region, between the basic repeats 11- 17 (DysN-R17).
Dystrophin, originally identified as the gene responsible for Duchenne and Becker muscular dystrophies (DMD/BMD), and later for the X-linked form of dilated cardiomyopathy (XLCM), exerts a major function in physical force transmission in striated muscle. In addition to its structural significance, dystrophin and other DGC proteins such as syntrophins are required for the
correct localization,
clustering and
regulation of ion channel function.
Syntrophins have been implicated in ion channel regulation. Syntrophins contain two pleckstrin homology (PH) domains, a PDZ domain, and a syntrophin-unique (SU) C-terminal region. The interaction between syntrophins and dystrophin occurs at the PH domain distal to the syntrophin N-terminus and through the highly conserved SU domain. Conversely, the PH domain proximal to the N-terminal portion of the protein and the PDZ domain interact with other membrane components such as
phosphatidyl inositol-4, 5-bisphosphate,
neuronal NOS (nNOS),
aquaporin-4,
stress-activated protein kinase-3, and
5,
thereby linking all these molecules to the dystrophin complex (Figure 2).
Among the five known isoforms of syntrophin, the 59 KDa α1-syntrophin isoform is the most highly represented in human heart, whereas in skeletal muscle it is only present on the
sarcolemma of fast type II fibers.
In addition, the skeletal muscle γ2-syntrophin was found at high levels only at the
postsynaptic membrane of the neuromuscular junctions.
In addition to syntrophin, other scaffolding proteins such as caveolin-3 (CAV3), which is present in the caveolae, flask-shaped plasma membrane microdomains, are involved
in signal transduction and vesicle trafficking in myocytes,
modulating cardiac remodeling during heart failure.
CAV3 and α1-syntrophin, localizes at the T-tubule and are part of the DGC. In addition, α1-syntrophin binds Nav1.5, while
caveolin-3 binds the Na+/Ca2+ exchanger, Nav1.5 and the L-type Ca2+ channel as well as nNOS and the DGC (Figure 2).
Although ankyrin-B is the only protein found mutated in patients with primary arrhythmias, other proteins such as caveolin-3 and the syntrophins if mutated may alter ion channel function.
Conclusions
It is important to be aware of the enormous variety of clinical presentations that derive from distinct variants in the same pool of genetic factors. Knowledge of these variants could facilitate tailoring the therapy of choice for each patient. In particular, the recent findings of structural and functional links between
the cytoskeleton and ion channels
could expand the therapeutic interventions in
arrhythmia management in structurally abnormal myocardium, where aberrant binding
between cytoskeletal proteins can directly or indirectly alter ion channel function.
Executive Summary
Arrhythmogenesis and myocardial structure
Rhythm alterations can develop as a secondary consequence of myocardial structural abnormalities or as a result of a primary defect in the cardiac electric machinery.
Until recently, no molecular mechanism has been able to fully explain the occurrence of arrhythmogenesis in heart failure, however genetic defects that are found almost exclusively in ion channel genes account for the majority of primary arrhythmias such as long QT syndromes and Brugada syndrome. The contractile apparatus is linked to ion channels
The sarcomere, which represents the contractile unit of the myocardium not only generates the mechanical force necessary to exert the pump function, but also provides localization and anchorage to ion channels.
Alpha-actinin-2, and telethonin, two members of the Z-line scaffolding protein complex in the striated muscle associate with the potassium voltage-gated channel alpha subunit Kv1.5 and the beta subunit KCNE1 respectively.
Mutations in KCNE1 have previously been associated with the development of arrhythmias in LQTS subjects.
Mutations in both alpha-actinin-2, and telethonin were identified in individuals with cardiomyopathy. The primary defect is structural leading to ventricular dysfunction, but the secondary consequence is arrhythmia.
Ion channel trafficking and sub-cellular compartments
Ion channel trafficking from the endoplasmic reticulum (ER) to the Golgi complex is an important check-point for regulating the functional channel molecules on the plasma membrane. Several molecules acting as chaperones bind to and shuttle the channel proteins to their final localization on the cell surface
Ion channel subunits such as Kvβ enhance Kv1.x ion channel presentation on the sarcolemma. The α subunits of the Kv1.x potassium channels can be shuttled in a Kvβ-independent manner through specific sequence motif at Kv1.x protein level.
In addition, cytoskeletal proteins such as ankyrin-G bind Nav1.5 and are involved in the sodium channel trafficking. Another member of the ankyrin family, ankyrin-B was found mutated in patients with LQTS but the pathological mechanism of ankyrin-B mutations is still obscure, although the sodium current intensity is dramatically reduced.
The sarcolemma and ion channels
The sarcolemma contains a wide range of ion channels, which are responsible for the electrical propagating force in the myocardium.
The DGC is a protein complex, which forms a scaffold for cytoskeletal components and ion channels.
Dystrophin is the major component of the DGC and mutations in dystrophin and DGC cause muscular dystrophies and X-linked cardiomyopathies (XLCM) in humans. Cardiomyopathies are associated with arrhythmias
Caveolin-3 and syntrophins associate with Nav1.5, and are part of the DGC. Syntrophins can directly modulate Nav1.5 channel function.
Conclusions
The role of the cytoskeleton in ion channel function has been hypothesized in the past, but only recently the mechanism underlying the development of arrhythmias in structurally impaired myocardium has become clearer.
The recently acknowledged role of the cytoskeleton in ion channel function suggests that genes encoding cytoskeletal proteins should be regarded as potential candidates for variants involved in the susceptibility to arrhythmias, as well as the primary target of genetic mutations in patients with arrhythmogenic syndromes such as LQTS and Brugada syndrome.
Studies of genotype-phenotype correlation and and patient risk stratification for mutations in cytoskeletal proteins will help to tailor the therapy and management of patients with arrhythmias.
Warburg Effect revisited
It is very interesting the series of commentaries following Warburg Effect revisited. However, it comes as no surprise that almost all of them have small or greater emphasis in the molecular biology (changes in gene expression) events of the metabolic regulation involved.
I would like to comment on some aspects: 1- Warburg did the initial experiments following Pasteur line of reasoning that aimed at carbon flow through the cell (yeast in his case) instead of describing anything inside the cell. It is worth to recall that for the sake of his study, Pasteur considered anything inside the cell under the domain of divine forces. He, at least in defence of his work, entirely made outside the cell, considered that inside the cells was beyond human capability of understanding – He has followed vitalism as his line of reasoning in defence of his work – Interestingly, the same scientist that has ruled out spontaneous generation when Pasteurization was started. Therefore, Pasteur measured everything outside the cell (mainly sugar, ethanol – the equivalent of our lactic acid end product of anaerobic metabolism) and found that as soon as yeasts were placed in the presence of oxygen, sugar was consumed at low speed in comparison with the speed measured in anaerobiosis and ethanol was also produced at reduced speed. This is an indication of a fast biological regulatory mechanism that obviously, do not require changes in gene expression. As previously said, Warburg work translated for republishing in the Journal Biological Chemistry mentioned “grana” for mitochondria calling attention on an “inside-the-cell” component. It seems that, there is not a unique, single site of metabolism, where the Pasteur Effect – Warburg Effect seems to be elicited by the shift from anaerobiosis to aerobiosis or vice versa.
In order to find a core for the mechanism the best approach seems to take into account one of the most important contributions of one of the greatest north-American biochemists, Briton Chance. He has made it with his polarographic method of following continuously the oxygen consumption of the cell´s mitochondria.
Mitochondria burn organic carbon molecules under a very stringent control mechanism of oxidative-phosphorylation ATP production. Measured in the form of changes in the speed of oxygen consumption over time as Respiratory Control Ratio (RCR). When no ATP is required by the cell, oxygen consumption goes at low speed (basal or state II or IV). When ADP is offered to the mitochondria as an indication that ATP synthesis is necessary, oxygen consumption is activated in state III respiration. Low respiration means low burning activity of organic (carbon) molecules what in this case, means indirectly low glucose consumption. While high respiration is the converse – greater glucose consumption.
Aerobic metabolism of glucose to carbonic acid and water provides a change in free energy enough for 38 molecules of ATP (the real production is +/- 32 ATP in aerobic condition) while glucose to lactic acid metabolism in anaerobiosis leads to 2 ATP production after discounting the other 2 required at initial stages of glucose metabolism.
The low ATP yield in anaerobiosis explains the fast glucose metabolism in anaerobiosis while the control by RCR in mitochondria explains the reduction in glucose metabolism under aerobiosis as long as the ATP requirements of the cell remains the same – This is what it is assumed to happen in quiescent cells. Not necessarily in fast growing cells as cancer cells are. However, this will not be discussed here. In my first experiments in the early seventies, with M. Rouxii a dimorphic mold-yeast biological system the environmental change (aerobic – anaerobic) led to morphogenetic change presented as morphogenetic expression of the Pasteur Effect. In this case, the enzyme that replaces mitochondria in ATP production (Pyruvate Kinase) converting phosphoenolpyruvate into pyruvate together with ADP into ATP, shows changes that can be interpreted as change in gene expression together with new self-assembly of enzyme subunits. (Dimer AA – yeast in anaerobic growth or sporangiospores- converted into dimer AB in aerobic mold). In Leloir opinions at that time, PK I (AA) was only highly glycosylated, while PK II (AB) was less glycosylated without changes in gene expression.
In case you read comments posted, you will see that the reference to aerobic glycolysis, continues to be made together with, new deranged forms of reasoning as is indicated by referring to: Mitochondrial role in ion homeostasis…
Homeostasis is a regulation of something, ions, molecules, pH etc. that is kept outside the cell, therefore any role for mitochondria on it is only made indirectly, by its ATP production.
However, mitochondria has a role together with other cell components in the regulation of for instance, intracellular Ca levels (Something that is not a homeostatic regulation). This is a very important point for the following reason: Homeostasis is maintained as a composite result of several differentiated cellular, tissue and organ functions. Differentiated function is something clearly missing in cancer cells. The best form to refer to the mitochondrial function regarding ions is to indicate a mitochondrial role in ion fluxes.
In short, to indicate how an environmental event or better saying condition could favour genetic changes instead of being caused by genetic changes is to follow the same line of reasoning that is followed in understanding the role of cardioplegia. To stop heart beating is adequate for heart surgery it is also adequate for heart cells by sparing the ATP use during surgery and therefore, offering better recovery condition to the heart afterwards.
In the case, here considered, even assuming that the genome is not made more unstable during hypoxic condition it is quite possible to understand that sharing ATP with both differentiated cell function and replication may led quality control of DNA in short supply of much needed ATP and this led to maintenance of mutations as well as less organized genome.
Thank you. I enjoy reading your comments. They are very instructive. I don’t really think that I comprehend the use of the term “epigenetics” and longer. In fact, it was never clear to me when I first heard it used some years ago.
The term may have been closely wedded to the classic hypothesis of a unidirectional DNA–> RNA–> protein model that really has lost explanatory validity for the regulated cell in its environment. The chromatin has an influence, and protein-protein interactions are everywhere. As you point out, these are adjusting to a fast changing substrate milieu, and the genome is not involved. But in addition, the proteins may well have a role in suppression or activation of signaling pathways, and thereby, may well have an effect on gene expression. I don’t have any idea about how it would work, but mutations would appear to follow the metabolic condition of the cell over time. It would appear to be – genomic modification.
In aerobic glucose metabolism, the oxidation of citric acid requires ADP and Mg²+, which will increase the speed of the reaction: Iso-citric acid + NADP (NAD) — isocitrate dehydrogenase (IDH) = alpha-ketoglutaric acid. In the Krebs cycle (the citric cycle), IDH1 and IDH2 are NADP+-dependent enzymes that normally catalyze the inter-conversion of D-isocitrate and alpha-ketoglutarate (α-KG). The IDH1 and IDH2 genes are mutated in > 75% of different malignant diseases. Two distinct alterations are caused by tumor-derived mutations in IDH1 or IDH2: the loss of normal catalytic activity in the production of α-ketoglutarate (α-KG) and the gain of catalytic activity to produce 2-hydroxyglutarate (2-HG), [22].
This product is a competitive inhibitor of multiple α-KG-dependent dioxygenases, including demethylases, prolyl-4-hydroxylase and the TET enzymes family (Ten-Eleven Translocation-2), resulting in genome-wide alternations in histones and DNA methylation. [23]
IDH1 and IDH2 mutations have been observed in myeloid malignancies, including de novo and secondary AML (15%–30%), and in pre-leukemic clone malignancies, including myelodysplastic syndrome and myeloproliferative neoplasm (85% of the chronic phase and 20% of transformed cases in acute leukemia), [24].
Normally, cells in the body communicate via intra-cytoplasmic channels and maintain the energetic potential across cell membranes, which is 1-2.5 µmol of ATP in the form of ATP-ADP/ATP-ADP-IMP. These normal energetic values occur during normal cell division. If the intra-cellular and extra-cellular levels of Mg2+ are high, the extra-cellular charges of the cells will not be uniformly distributed.
This change in distribution induces a high net positive charge for the cell and induces a loss of contact inhibition via the electromagnetic induction of oscillation [28, 29, 30]. Thereafter, malignant cells become invasive and metastasize.
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-22. Hartmann C, Meyer J, Balss J. Capper D, et al. Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differentiation and age: a study of 1,010 diffuse gliomas. Acta Neuropathol 2009; 118: 464-474.
23. Raymakers R.A, Langemeijer S.M., Kuiper R.P, Berends M, et al. Acquired mutations in TET2 are common in myelodysplastic syndromes. Nat. Genet 2009; 41; 838–849.
24 Wagner K, Damm F, Gohring G., Gorlich K et al. Impact of IDH1 R132 mutations and an IDH1 single nucleotide polymorphism in cytogenetically normal acute myeloid leukemia: SNP rs11554137 is an adverse prognostic factor. J. Clin. Oncol.2010; 28: 2356–2364.
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29. Chien MM, Zahradka CE, Newel MC, Fred JW. Fas induced in B cells apoptosis require an increase in free cytosolic magnesium as in early event. J Biol Chem.1999; 274: 7059-7066.
30. Milionis H J, Bourantas C L, Siamopoulos C K, Elisaf MS. Acid bases and electrolytes abnormalities in Acute Leukemia. Am J Hematol 1999; (62): 201-207.
31. Thomas N Seyfried; Laura M Shelton.Cancer as a Metabolic Disease. Nutr Metab 2010; 7: 7
– Aurelian Udristioiu, M.D,
– Lab Director, EuSpLM,
– City Targu Jiu, Romania
AACC, National Academy of Biochemical Chemistry (NACB) Member, Washington D.C, USA.