Posts Tagged ‘normoxia’

Mitochondrial Pyridine Nucleotides and Electron Transport Chain

Larry H Bernstein, MD, FCAP, writer and curator

2.1.5 Mitochondrial Pyridine Nucleotides and Electron Transport Chain Mitochondrial function in vivo evaluated by NADH fluorescence

Mayevsky A1, Rogatsky GG.
Am J Physiol Cell Physiol. 2007 Feb; 292(2):C615-40

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 (5657), 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

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 (152161). 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. 1Aright 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 (54201). 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 (4350).

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. 1B 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 (4254). 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 (38434459), Dora and Kovach’s group (7192), Rievich’s group (93), Jobsis and collaborators (108110111213), Gosalvez et al. (89), and Anderson and Sundt (5232). 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 (1319).

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 (48157) 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

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

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 (5657). 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 3right, 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


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 (5657), 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 4C 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.


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 (150,152153167177). 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).


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).


Responses to energy consumption changes

As shown by Chance and Williams (5758), 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).


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 (194195) 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 (3140).

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 (8283) 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.


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 (5758). 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.


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 (157159) or decapitation (160259). 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 (168183). 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 (3349) 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. A microscale mathematical model for metabolic symbiosis: Investigating the effects of metabolic inhibition on ATP turnover in tumors

Colin Phipps, Hamid Molavian, Mohammad Kohandel
J Theoret Biol 2015; 366: 103-114

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+ + 3O2 kLà  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.


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. 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.


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:
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.


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