Posts Tagged ‘cell regulation’

RNAi – On Transcription and Metabolic Control

Writer and Curator: Larry H Bernstein, MD, FCAP



This is the third contribution to a series on transcription and metabolic control. It reveals the enormous complexity in this emerging research.


mRNA, small RNAs, long RNAs, RNAi and DicAR

Aberrant mRNA translation in cancer pathogenesis
Pier Paolo Pandolfi
Oncogene (2004) 23, 3134–3137

As the molecular processes that control mRNA translation and ribosome biogenesis in the eukaryotic cell are extremely complex and multilayered, their deregulation can in principle occur at multiple levels, leading to both disease and cancer pathogenesis. For a long time, it was speculated that disruption of these processes may participate in tumorigenesis, but this notion was, until recently, solely supported by correlative studies. Strong genetic support is now being accrued, while new molecular links between tumor-suppressive and oncogenic pathways and the control of protein synthetic machinery are being unraveled. The importance of aberrant protein synthesis in tumorigenesis is further underscored by the discovery that compounds such as Rapamycin, known to modulate signaling pathways regulatory of this process, are effective anticancer drugs. A number of fundamental questions remain to be addressed and a number of novel ones emerge as this exciting field evolves.


mRNA Translation and Energy Metabolism in Cancer
I. Topisirovic and N. Sonenberg
Cold Spring Harbor Symposia on Quantitative Biology, Volume LXXVI

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).In mammalian cells it consumes >20% of cellular ATP, not considering the energy that is required for the biosynthesis of the components of the translational machinery (e.g., ribosome biogenesis; Buttgereit and Brand 1995). Control of mRNA translation plays a pivotal role in the regulation of gene expression (Sonenberg and Hinnebusch 2009). In fact, a recent study demonstrated that mammalian proteome is mostly governed at the mRNA translation level (Schwanhausser et al. 2011). Malfunction of mRNA translation critically contributes to human disease, including diabetes, heart disease, blood disorders, and, most notably, cancer (Fig. 1; Crozier et al. 2006; Narla and Ebert 2010; Silvera et al. 2010; Spriggs et al. 2010). The first account of changes in the translational apparatus in cancer dates back to 1896, showing enlarged and irregularly shaped nucleoli that are the site of ribosome biogenesis (Pianese 1896). Rapidly proliferating cancer cells have more ribosomes than normal cells.

Figure 1. Dysregulated mRNA translation plays a pivotal role in cancer. Malignant cells are characterized by enlarged nucleoli and a larger number of ribosomes than their normal counterparts. Mutations and/or altered expression of ribosomal proteins (e.g., RPS19, RPS 24), rRNA-modifying enzymes (e.g., dyskerin), translation initiation factors (e.g., eIF4E), or the initiator tRNA (tRNAiMet) result in malignant transformation. Signaling pathways whose dysfunction is frequent in cancer (e.g., MAPK, PI3K/AKT) affect mRNA translation. Perturbations in the translatome result in aberrant cellular growth, proliferation, and survival characteristic of tumorigenesis.


In stark contrast to normal cells, in cancer cells ribosomal biogenesis is uncoupled from cell proliferation (Stanners et al. 1979). Accordingly, cancer cells exhibit abnormally high rates of protein synthesis (Silvera et al. 2010). That ribosomal dysfunction plays a central role in cancer is further corroborated by the findings that genetic alterations, which encompass the components of the ribosome machinery (i.e., “ribosomopathies”), are characterized by elevated cancer risk (Narla and Ebert 2010).

mRNA translation is the most energy-consuming process in the cell and strongly correlates with cellular metabolic activity. Translation and energy metabolism play important roles in homeostatic cell growth and proliferation, and when dysregulated lead to cancer. eIF4E is a key regulator of translation, which promotes oncogenesis by selectively enhancing translation of a subset of tumor-promoting mRNAs (e.g., cyclins and c-myc). PI3K/AKT and mitogen-activated protein kinase (MAPK) pathways, which are strongly implicated in cancer etiology, exert a number of their biological effects by modulating translation. The PI3K/AKT pathway regulates eIF4E function by inactivating the inhibitory 4E-BPs via mTORC1, whereas MAPKs activate MAP kinase signal-integrating kinases 1 and 2, which phosphorylate eIF4E. In addition, AMP-activated protein kinase, which is a central sensor of the cellular energy balance, impairs translation by inhibiting mTORC1. Thus, eIF4E plays a major role in mediating the effects of PI3K/AKT, MAPK, and cellular energetics on mRNA translation.Figure 2. eIF4E is regulated by multiple mechanisms. The expression of eIF4E is regulated by several transcription factors (e.g., c-myc, hnRNPK, p53) and adenine-uracil-rich element binding proteins (i.e., HuR and AUF1). eIF4E is suppressed by 4E-BPs, which are regulated by mTORC1. MAP kinase signal integrating kinases 1 and 2 (MNKs) phosphorylate eIF4E.


Figure 3. Ras/MAPK and PI3K/AKT/mTORC1 regulate the activity of eIF4E. Various stimuli activate phosphoinositide-3-kinase (PI3K) through the receptor tyrosine kinases (RTKs). Upon activation, PI3K converts phosphatidylinositol 4,5-bisphosphate (PIP2) into phosphatidylinositol-3,4,5-triphosphate (PIP3). This reaction is reversed by PTEN. Phosphoinositide-dependent protein kinase 1 (PDK1) and AKT bind to PIP3 via their pleckstrin homology domains, which allows for the phosphorylation and activation of AKT by PDK1. In addition, the mammalian target of rapamycin complex 2 (mTORC2) modulates the activity of AKT by phosphorylating its hydrophobic motif. AKT phosphorylates tuberous sclerosis complex 2 (TSC2) at multiple sites, which results in its inhibition and consequent activation of Ras homolog enriched in brain (Rheb), which is a small GTPase that activates mTORC1. mTORC1 phosphorylates 4E-BPs leading to their dissociation from eIF4E. In addition to the PI3K/AKT pathway, the activity of mTORC1 is regulated by the serine/threonine kinase 11/LKB1/AMP-kinase (LKB1/AMPK) pathway, regulated in development and DNA damage response 1 (REDD1) and Rag GTPases in response to the changes in cellular energy balance, oxygen and amino acid availability, respectively. Ras and the MAPK pathways are activated by various stimuli through receptor tyrosine kinases (RTKs). In addition the MAPK pathway isactivatedthrough theGprotein–coupled receptors(GPCRs) and byproteinkinaseC (PKC;notshown).TheMAPK pathways encompass an initial GTPase-regulated kinase (MAPKKK), which activates an effector kinase (MAPK) via an intermediate kinase (MAPKK). In response to stimuli such as growth factors, hormones, and phorbol-esters, Ras GTPase stimulates Raf kinase (MAPKKK), which activates extracellular signal-regulated kinases 1 and 2 (ERK 1 and 2) via extracellular signal-regulated kinase activator kinases MEK1 and 2 (MAPKK). Cellular stresses, including osmotic shock, inflammatory cytokines, and UV light, activate p38 MAPKs via multiple mechanisms including Rac kinase (MAPKKK) and MKK3 and 6 (MAPKK). p38 MAPK and ERK activate the MAPK signal–integrating kinases 1 and 2 (MNK1/2), which phosphorylate eIF4E. Additional abbreviations are provided in the text.


Cancer Exosomes Perform Cell-Independent MicroRNA Biogenesis and Promote Tumorigenesis
Cancer Cell Nov, 2014; 26: 707–721.

Breast cancer cells secrete exosomes with specific capacity for cell-independent miRNA biogenesis, while normal cellderivedexosomes lack thisability. Exosomes derivedfrom cancer cellsand serum frompatients withbreast cancer contain the RISC loading complex proteins, Dicer, TRBP, and AGO2, which process pre-miRNAs into mature miRNAs. Cancer exosomes alter the transcriptome of target cells in a Dicer-dependent manner, which stimulate nontumorigenic epithelial cells to form tumors.This study identifies a mechanism whereby cancer cells impart an oncogenic field effect by manipulating the surrounding cells via exosomes. Presence of Dicer in exosomes may serve as biomarker for detection of cancer.

Dicers at RISC. The Mechanism of RNAi

Marcel Tijsterman and Ronald H.A. Plasterk
Cell, Apr 2014; 117:1–4

Figure 1. Model for RNA Silencing in Drosophila In an ordered biochemical pathway, miRNAs (left panel) and siRNAs (right panel) are processed from double-stranded precursor molecules by Dcr-1and Dcr-2, respectively, and stay attached to Dicer-containing complexes, which assemble into RISC. The degree of complementarity between the RNA silencing molecule (in red) and its cognate target determines the fate of the mRNA: blocked translation or immediate destruction.

Argonaute2 Cleaves the Anti-Guide Strand of siRNA during RISC Activation
Cell 2005; 123:621-629
Dicing and slicing- The core machinery of the RNA interference pathway
Scott C Hammond
FEBS Letters 579 (2005) 5822–5829

Fig. 1. Domain organization of RNaseIII gene family. Three classes of RNaseIII genes are shown. The PAZ domain in Dm-Dicer-2 contains mutations in several residues required for RNA binding and may not be functional.

Fig. 2. Model for Dicer catalysis. The PAZ domain binds the 2 nt 30 overhang of a dsRNA terminus. The RNaseIII domains form a pseudo-dimer. Each domain hydrolyzes one strand of the substrate. The binding site of the dsRBD is not defined. The function of the helicase domain is not known.

Fig. 3. Biogenesis pathway of microRNAs. MicroRNA genes are transcribed by RNA polymerase II. The primary transcript is referred to as ‘‘primicroRNA’’. Drosha processing occurs in the nucleus. The resulting precursor, ‘‘pre-microRNA’’, is exported to the cytoplasm for Dicer processing. In a coordinated manner, the mature microRNA is transferred to RISC and unwound by a helicase. mRNA targets that duplex in the Slicer scissile site are cleaved and degraded, if the microRNA is loaded into an Ago2 RISC. Mismatched targets are translationally suppressed. All Ago family members are believed to function in translational suppression.

Fig. 4. Model for Slicer catalysis. The siRNA guide strand is bound at the 50 end by the PIWI domain and at the 30 end by the PAZ domain. The 50 phosphate is coordinated by conserved basic residues. mRNA targets are initially bound by the seed region of the siRNA and pairing is extended to the 30 end. The RNaseH fold hydrolyzes the target in a cation dependent manner. Slicer cleavage is measured from the 50 end of the siRNA. Product is released by an unknown mechanism and the enzyme recycles.



RNA interference (RNAi) is a biological process in which RNA molecules inhibit gene expression, typically by causing the destruction of specific mRNA molecules. Historically, it was known by other names, including co-suppression, post transcriptional gene silencing (PTGS), and quelling. Only after these apparently unrelated processes were fully understood did it become clear that they all described the RNAi phenomenon. Andrew Fire and Craig C. Mello shared the 2006 Nobel Prize in Physiology or Medicine for their work on RNA interference in the nematode worm Caenorhabditis elegans, which they published in 1998.


Two types of small ribonucleic acid (RNA) molecules – microRNA (miRNA) and small interfering RNA (siRNA) – are central to RNA interference. RNAs are the direct products of genes, and these small RNAs can bind to other specific messenger RNA (mRNA) molecules and either increase or decrease their activity, for example by preventing an mRNA from producing a protein. RNA interference has an important role in defending cells against parasitic nucleotide sequences – viruses and transposons. It also influences development.


The RNAi pathway is found in many eukaryotes, including animals, and is initiated by the enzyme Dicer, which cleaves long double-stranded RNA (dsRNA) molecules into short double stranded fragments of ~20 nucleotide siRNAs. Each siRNA is unwound into two single-stranded RNAs (ssRNAs), the passenger strand and the guide strand. The passenger strand is degraded and the guide strand is incorporated into the RNA-induced silencing complex (RISC). The most well-studied outcome is post-transcriptional gene silencing, which occurs when the guide strand pairs with a complementary sequence in a messenger RNA molecule and induces cleavage by Argonaute, the catalytic component of the RISC complex. In some organisms, this process spreads systemically, despite the initially limited molar concentrations of siRNA.

The enzyme dicer trims double stranded RNA, to form small interfering RNA or microRNA. These processed RNAs are incorporated into the RNA-induced silencing.
MiRNA biogenesis and function. (A) The canonical miRNA biogenesis pathway is Drosha- and Dicer-dependent. It begins with RNA Pol II-mediated transcription..


Dicer Promotes Transcription Termination

Dicer Promotes Transcription Termination

Dicer Promotes Transcription Termination at Sites of Replication Stress to Maintain Genome Stability
Cell Oct 2014; 159(3): 572–583


18-13 miRNA- protein complex ap-chap-18-pp-42-728

18-13 miRNA- protein complex ap-chap-18-pp-42-728

18-13 miRNA- protein complex (a) Primary miRNA transcript Translation blocked Hydrogen bond (b) Generation and function of miRNAs Hairpin miRNA miRNA Dicer …



Identification and characterization of small RNAs involved in RNA silencing
FEBS Letters 579 (2005) 5830–5840

Fig. 1. Small RNA cloning procedure. Outline of the small RNA cloning procedure. RNA is dephosphorylated (step 1) for joining the 30 adapter by T4 RNA ligase 1 in the presence of ATP (step 2). The use of a chemically adenylated adapter and truncated form of T4 RNA ligase 2 (Rnl2) allows eliminating the dephosphorylation step (step 4). If the RNA was dephosphorylated, it is re-phosphorylated (step 3) prior to 50 adapter ligation with T4 RNA ligase 1 and ATP (step 5). After 50 adapter ligation, a standard reverse transcription is performed (step 6). Alternatively, after 30 adapter ligation, the RNA is used directly for reverse transcription simultaneously with 50 adaptor joining (step 7). In this case, the property of reverse transcriptase to add non-templated cytidine residues at the 50 end of synthesized DNA is used to facilitate template switch of the reverse transcriptase to the 30 guanosine residues of the 50 adapter (SMART technology, Invitrogen). Abbreviations: P and OH indicate phosphate and hydroxyl ends of the RNA; App indicates 50 chemically adenylated adapter; L, 30 blocking group; CIP, calf alkaline phosphatase and PNK, polynucleotide kinase.


Transcriptional regulatory functions of nuclear long noncoding RNAs
Trends in Genetics, Aug 2014; 30(8):348-356

Cis-acting lncRNAEnhancer-associated lncRNAIntergenic lncRNA


Promoter-associated lncRNA

Proximity transfer

Trans-acting lncRNA


Functional interactions among microRNAs and long noncoding RNAs
Sem Cell Dev Biol 2014; 34:9-14
Genome-wide application of RNAi to the discovery of potential drug targets
FEBS Letters 579 (2005) 5988–599

Fig. 1. Schematic representation of gene silencing by an shRNA-expression vector. The shRNA is processed by Dicer. The processed siRNA enters the RNA-induced silencing complex (RISC), where it targets mRNA for degradation.

Fig. 2. Schematic representation of a transcription system for production of siRNA

Fig. 3. (A) Schematic representation of the proposed siRNA-expression system. Three or four C to U or A to G mutations are introduced into the sense strand. (B) Schematic representation of the discovery of a novel gene using an siRNA library.


Imperfect centered miRNA binding sites are common and can mediate repression of target mRNAs
Martin et al. Genome Biology 2014, 15:R51





Table 1 Number of inferred targets for each miRNA tested

miRNA Probes Transcripts Genes
miR-10a 2,206 5,963 1,887
miR-10a-iso 1,648 1,468 4,211
miR-10b 1,588 3,940 1,365
miR-10b-iso 963 2,235 889
miR-17-5p 1,223 2,862 1,137
miR-17-5p-iso 1,656 3,731 1,461
miR-182 2,261 6,423 2,008
miR-182-iso 1,569 4,316 1,444
miR-23b 2,248 5,383 1,990
miR-27a 2,334 5,310 2,069

Probes: number of probes significantly enriched in pull-downs compared to controls (5% FDR). Transcripts: number of transcripts to which those probes map exactly. Genes: number of genes from which those transcripts originate

Figure 2 Biotin pull-downs identify bone fide miRNA targets. (A) Volcano plot showing the significance of the difference in expression between the miR-17-5p pull-down and the mock-transfected control, for all transcripts expressed in HEK293T cells. Both targets predicted by TargetScan or validated previously via luciferase assay were significantly enriched in the pull-down compared to the controls. (B) Results from luciferase assays on previously untested targets predicted using TargetScan and uncovered using the biotin pull-down. The plot indicates mean luciferase activity from either the empty plasmid or from pMIR containing a miRNA binding site in the 3′ UTR, relative to a negative control. Asterisks indicate a significant reduction in luciferase activity (one-sided t-test; P<0.05) and error bars the standard error of the mean over three replicates. (C-E) Targets identified through PAR-CLIP or through miRNA over-expression studies show greater enrichment in the pull-down. Cumulative distribution of log fold-change in the pull-down for transcripts identified as targets by the indicated miRNA over-expression study or not. Red, canonical transcripts found to be miR-17-5p targets in the indicated study (Table S5 in Additional file 1); black, all other canonical transcripts; p, one-sided P-value from Kolmogorov-Smirnov test for a difference in distributions. (F) To confirm that our results were dependent on RISC association, cells were transfected with either single or double-stranded synthetic miRNAs, then subjected to AGO2 immunoprecipitation. The biotin pull-down was performed in the AGO2-enriched and AGO2-depleted fractions. (G-H) Quantitative RT-PCR revealed that, with double-stranded (ds) miRNA (G), four out of five known targets were enriched relative to input mRNA (*P≤0.05, **P<0.01, ***P<0.001) in the AGO2-enriched but not in the AGO2-depleted fractions, but this enrichment was not seen for the cells transfected with a single-stranded (ss) miRNA (H). The numbers on the x-axis correspond to those in Figure 2F. Error bars represent the standard error of mean (sem).

Figure 5 IsomiRs and canonical miRNAs target many of the same transcripts.

Hammerhead ribozymes in therapeutic target discovery and validation
Drug Disc Today 2009; 14(15/16): 776-783

Figure 1. Features of hammerhead ribozymes. A generic diagram of a hammerhead ribozyme bound to its target substrate: NUH is the cleavage triplet on target sequence, stems I and III are sites of the specific interactions between ribozyme and target, stem II is the structural element connecting separate parts of the catalytic core. Arrows represent the cleavage site, numbering system according to Hertel et al. [60].

hammerhead ribozyme

hammerhead ribozyme


Figure 1  Schematic (A) and ribbon (B) diagrams depicting the crystal structure of the full-length hammerhead ribozyme. The sequence and secondary structure


TABLE 1 Typical examples of successful applications of hammerhead ribozymes. Most of the data are derived from [10] and [11], the others are expressly specified.

  • Growth factors, receptors, transduction elements
  • Oncogenes, protoncogenes, fusion genes
  • Apoptosis, survival factors, drug resistance
  • Transcription factors
  • Extracellular matrix, matrix modulating factors
  • Circulating factors
  • Viral genome, viral genes

Figure 2.Target–ribozyme interactions. (a) As cheme of ribozyme binding to full substrate. The calculated energy of this binding ensures the formation of a stable complex. At the denaturating temperature, Tm, will allow this complex to survive to biological conditions. Conversely, after cleavage, binding energies calculated on single, (b) and (c), ribozyme arms are very low and no longer stable. These properties will ensure both the efficient release of cleavage fragments and the prevention of binding to unrelated targets. RNAs complementary to one binding arm only will not be bound or cleaved by the hammerhead catalytic sequence.

Figure 3. ‘Chemical omics’ approach. According to this target discovery strategy: (1) a first round of ‘omic’ study (proteomic, genomic, metabolomic, …) will enable the discovery of a set of (2) putative markers. A series of hammerhead ribozymes will then be prepared in order to target each marker. (4) A second ‘omic’ study round will be performed on (3) knocked down samples obtained after ribozymes administration. (5) A new series of markers will then be produced. An expanding analytical process of this type may be further repeated. Finally, a robust bioinformatic algorithm will make it possible to connect the different markers and draw new hypothetical links and pathways.



ADAR Enzyme and miRNA Story
Sara Tomaselli, Barbara Bonamassa, Anna Alisi, et al.
Int. J. Mol. Sci. 2013, 14, 22796-22816;

Adenosine deaminase acting on RNA (ADAR) enzymes convert adenosine (A) to inosine (I) in double-stranded (ds) RNAs. Since Inosine is read as Guanosine, the biological consequence of ADAR enzyme activity is an A/G conversion within RNA molecules. A-to-I editing events can occur on both coding and non-coding RNAs, including microRNAs (miRNAs), which are small regulatory RNAs of ~20–23 nucleotides that regulate several cell processes by annealing to target mRNAs and inhibiting their translation. Both miRNA precursors and mature miRNAs undergo A-to-I RNA editing, affecting the miRNA maturation process and activity. ADARs can also edit 3′ UTR of mRNAs, further increasing the interplay between mRNA targets and miRNAs. In this review, we provide a general overview of the ADAR enzymes and their mechanisms of action as well as miRNA processing and function. We then review the more recent findings about the impact of ADAR-mediated activity on the miRNA pathway in terms of biogenesis, target recognition, and gene expression regulation.

Figure 1. Structure of ADAR family proteins: ADAR1, ADAR2, and ADAR3. The ADAR enzymes contain a C-terminal conserved catalytic deaminase domain (DM), two or three dsRBDs in the N-terminal portion. ADAR1 full-length protein also contains a N-terminal Zα domain with a nuclear export signal (NES) and a Zβ domain, while ADAR3 has a  R-domain. A nuclear localization signal is also indicated.


Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites
Doron Betel, Anjali Koppal, Phaedra Agius, Chris Sander, Christina Leslie
Genome Biology 2010, 11:R90

microRNAs are a class of small regulatory RNAs that are involved in post-transcriptional gene silencing. These small (approximately 22 nucleotide) single-strand RNAs guide a gene silencing complex to an mRNA by complementary base pairing, mostly at the 3′ untranslated region (3′ UTR). The association of the RNAinduced silencing complex (RISC) to the conjugate mRNA results in silencing the gene either by translational repression or by degradation of the mRNA. Reliable microRNA target prediction is an important and still unsolved computational challenge, hampered both by insufficient knowledge of microRNA biology as well as the limited number of experimentally validated targets.

mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.
Human RISC – MicroRNA Biogenesis and Posttranscriptional Gene Silencing
Cell 2005; 123:631-640
Development of microRNA therapeutics
Eva van Rooij & Sakari Kauppinen
EMBO Mol Med (2014) 6: 851–864

MicroRNAs (miRNAs) play key regulatory roles in diverse biological processes and are frequently dysregulated in human diseases. Thus, miRNAs have emerged as a class of promising targets for therapeutic intervention. Here, we describe the current strategies for therapeutic modulation of miRNAs and provide an update on the development of miRNA-based therapeutics for the treatment of cancer, cardiovascular disease and hepatitis C virus (HCV) infection.

Figure 1. miRNA biogenesis and modulation of miRNA activity by miRNA mimics and antimiR oligonucleotides. MiRNA genes are transcribed by RNA polymerase II from intergenic, intronic or polycistronic loci to long primary miRNA transcripts (pri-miRNAs) and processed in the nucleus by the Drosha–DGCR8 complex to approximately 70 nt pre-miRNA hairpin structures. The most common alternative miRNA biogenesis pathway involves short intronic hairpins, termed mirtrons, that are spliced and debranched to form pre-miRNA hairpins. Pre-miRNAs are exported into the cytoplasm and then cleaved by the Dicer–TRBP complex to imperfect miRNA: miRNA* duplexes about 22 nucleotides in length. In the cytoplasm, miRNA duplexes are incorporated into Argonaute-containing miRNA induced silencing complex (miRISC), followed by unwinding of the duplex and retention of the mature miRNA strand in miRISC, while the complementary strand is released and degraded. The mature miRNA functions as a guide molecule for miRISC by directing it to partially complementary sites in the target mRNAs, resulting in translational repression and/or mRNA degradation. Currently, two strategies are employed to modulate miRNA activity: restoring the function of a miRNA using double-stranded miRNA mimics, and inhibition of miRNA function using single-stranded anti-miR oligonucleotides.

Figure 2. Design of chemically modified miRNA modulators. (A) Structures of chemical modifications used in miRNA modulators. A number of different sugar modifications are used to increase the duplex melting temperature (Tm) of anti-miR oligonucleotides. The20-O-methyl(20-O-Me), 20-O-methoxyethyl(20-MOE )and 20-fluoro(20-F) nucleotides are modified at the 20 position of the sugar moiety, whereas locked nucleic acid (LNA) is a bicyclic RNA analogue in which the ribose is locked in a C30-endo conformation by introduction of a 20-O,40-C methylene bridge. To increase nuclease resistance and enhance the pharmacokinetic properties, most anti-miR oligonucleotides harbor phosphorothioate (PS) backbone linkages, in which sulfur replaces one of the non-bridging oxygen atoms in the phosphate group. In morpholino oligomers, a six-membered morpholine ring replaces the sugar moiety. Morpholinos are uncharged and exhibit a slight increase in binding affinity to their cognate miRNAs. PNA oligomers are uncharged oligonucleotide analogues, in which the sugar–phosphate backbone has been replaced by a peptide-like backbone consisting of N-(2-aminoethyl)-glycine units. (B) An example of a synthetic double-stranded miRNA mimic described in this review. One way to therapeutically mimic a miRNA is by using synthetic RNA duplexes that harbor chemical modifications for improved stability and cellular uptake. In such constructs, the antisense (guide) strand is identical to the miRNA of interest, while the sense (passenger) strand is modified and can be linked to a molecule, such as cholesterol, for enhanced cellular uptake. The sense strand contains chemical modifications to prevent mi-RISC loading. Several mismatches can be introduced to prevent this strand from functioning as an anti-miR, while it is further left unmodified to ensure rapid degradation.The20-F modification helps to protect the antisense strand against exonucleases, hence making the guide strand more stable, while it does not interfere with mi-RISC loading. (C) Design of chemically modified anti-miR oligonucleotides described in this review. Antagomirs are30 cholesterol-conjugated,20-O-Me oligonucleotides fully complementary to the mature miRNA sequence with several PS moieties to increase their in vivo stability. The use of unconjugated 20-F/MOE-, 20-MOE- or LNA-modified anti-miR oligonucleotides harboring a complete PS backbone represents another approach for inhibition of miRNA function in vivo. The high duplex melting temperature of LNA-modified oligonucleotides allows efficient miRNA inhibition using truncated, high-affinity 15–16-nucleotide LNA/DNA anti-miR oligonucleotides targeting the 50 region of the mature miRNA. Furthermore, the high binding affinity of fully LNA-modified 8-mer PS oligonucleotides, designated as tiny LNAs, facilitates simultaneous inhibition of entire miRNA seed families by targeting the shared seed sequence.

Human MicroRNA Targets
Bino John, Anton J. Enright, Alexei Aravin, Thomas Tuschl,.., Debora S. Mark
PLoS Biol 2004; 2(11): e363

More than ten years after the discovery of the first miRNA gene, lin-4 (Chalfie et al. 1981; Lee et al. 1993), we know that miRNA genes constitute about 1%–2% of the known genes in eukaryotes. Investigation of miRNA expression combined with genetic and molecular studies in Caenorhabditis elegans, Drosophila melanogaster, and Arabidopsis thaliana have identified the biological functions of several miRNAs (recent review, Bartel 2004). In C. elegans, lin-4 and let-7 were first discovered as key regulators of developmental timing in early larval developmental transitions (Ambros 2000; Abrahante et al. 2003; Lin et al. 2003; Vella et al. 2004). More recently lsy-6 was shown to determine the left–right asymmetry of chemoreceptor expression (Johnston and Hobert 2003). In D. melanogaster, miR-14 has a role in apoptosis and fat metabolism (Xu et al. 2003) and the bantam miRNA targets the gene hid involved in apoptosis and growth control (Brennecke et al. 2003).

MicroRNAs (miRNAs) interact with target mRNAs at specific sites to induce cleavage of the message or inhibit translation. The specific function of most mammalian miRNAs is unknown. We have predicted target sites on the 39 untranslated regions of human gene transcripts for all currently known 218 mammalian miRNAs to facilitate focused experiments. We report about 2,000 human genes with miRNA target sites conserved in mammals and about 250 human genes conserved as targets between mammals and fish. The prediction algorithm optimizes sequence complementarity using position-specific rules and relies on strict requirements of interspecies conservation. Experimental support for the validity of the method comes from known targets and from strong enrichment of predicted targets in mRNAs associated with the fragile X mental retardation protein in mammals. This is consistent with the hypothesis that miRNAs act as sequence-specific adaptors in the interaction of ribonuclear particles with translationally regulated messages. Overrepresented groups of targets include mRNAs coding for transcription factors, components of the miRNA machinery, and other proteins involved in translational regulation, as well as components of the ubiquitin machinery, representing novel feedback loops in gene regulation. Detailed information about target genes, target processes, and open-source software for target prediction (miRanda) is available at Our analysis suggests that miRNA genes, which are about 1% of all human genes, regulate protein production for 10% or more of all human genes.

Figure 1. Target Prediction Pipeline for miRNA Targets in Vertebrates The mammalian (human, mouse, and rat) and fish (zebra and fugu) 39 UTRs were first scanned for miRNA target sites using position specific rules of sequence complementarity. Next, aligned UTRs of orthologous genes were used to check for conservation of miRNA– target relationships (‘‘target conservation’’) between mammalian genomes and, separately, between fish genomes. The main results (bottom) are the conserved mammalian and conserved fish targets, for each miRNA,as well as a smaller set of super-conserved vertebrate targets.
Figure 2. Distribution of Transcripts with Cooperativity of Target Sites and Estimated Number of False Positives Each bar reflects the number of human transcripts with a given number of target sites on their UTR. Estimated rate of false positives(e.g., 39%for2 targets) is given by the number of target sites predicted using shuffled miRNAs processed in a way identical to real miRNAs, including the use of interspecies conservation filter.

Conserved Seed Pairing, Often improved an-Flanked by Adenosines, Indicates Thousands of Human Genes are MicroRNA Targets
Cell, Jan 2005; 120: 15–20

Integrated analysis of microRNA and mRNA expression. adding biological significance to microRNA target predictions.
Maarten van Iterson, Sander Bervoets, Emile J. de Meijer, et al.
Nucleic Acids Research, 2013; 41(15), e146

Current microRNA target predictions are based on sequence information and empirically derived rules but do not make use of the expression of microRNAs and their targets. This study aimed to improve microRNA target predictions in a given biological context, using in silico predictions, microRNA and mRNA expression. We used target prediction tools to produce lists of predicted targets and used a gene set test designed to detect consistent effects of microRNAs on the joint expression of multiple targets. In a single test, association between microRNA expression and target gene set expression as well as the contribution of the individual target genes on the association are determined. The strongest negatively associated mRNAs as measured by the test were prioritized. We applied our integration method to a well-defined muscle differentiation model. Validation of our predictions in C2C12 cells confirmed predicted targets of known as well as novel muscle-related microRNAs. We further studied associations between microRNA–mRNA pairs in human prostate cancer, finding some pairs that have been recently experimentally validated by others. Using the same study, we showed the advantages of the global test over Pearson correlation and lasso. We conclude that our integrated approach successfully identifies regulated microRNAs and their targets.

Long non-coding RNA and microRNAs might act in regulating the expression of BARD1 mRNAs
Int J Biol & Cell Biol 2014; 54:356-367


Passenger-Strand Cleavage Facilitates Assembly of siRNA into Ago2-Containing RNAi Enzyme Complexes
Cell 2006; 123:607-620


RNAi- RISC Gets Loaded
Cell 2005; 123:543-553
RNAi- The Nuts and Bolts of the RISC Machine
Cell 2005; 122:17-20
Structural domains in RNAi
FEBS Letters 579 (2005) 5841–5849

Fig. 1. A ‘‘Domain-centric’’ view of RNAi. (A) The conserved pathways of RNA silencing. The domain structure of each protein in (hypothetical) interaction with its RNA is shown. For clarity, the second column lists domains in order N- to C-terminal. Figures are not to scale. In brief, Drosha, an RNase III enzyme, and its obligate binding partner, Pasha recognize pri-mRNA loops, and cut these into 70 nt hairpin pre-miRNAs. Dicer utilizes a PAZ domain to sense the 30 2-nt overhang created, and further processes these, and dsRNAs into miRNAs and siRNAs. Argonaute binds the 50 end of guide RNAs via its PIWI domain, and the 30 end via a PAZ domain, yielding RISCs that effect RNA silencing through several mechanisms. A Viral protein, VP19 can suppress RNA silencing by sequestering siRNAs. (B) A summary of known siRNA structural biology. Listed by domain are solved structures, their protein/organism of origin, and ligands, where applicable. Also shown are PDB codes.

Fig. 2. Novel modes of RNA recognition. (A) A typical dsRBD: Xenopus binding protein A (1DI2). A RNA helix is modeled pink, and the protein is rendered in transparent electrostatic contours (blue is basic, red acidic). Note the interaction of helices along the major groove, and the position of helix 1. A second dsRBD protein is visible, in the lower right. (B) A dsRBD, Saccharomyces Rnt1P (1T4L), recognizes hairpin loops. A novel third helix (top) pushes helix one into the loop of a hairpin RNA. (C) 30-OH recognition by PAZ. Human Eif2c1 (1SI3) bound to RNA (pink) is shown. PAZ is green, with transparent electrostatic surface plot. The OB-fold (nucleotide binding fold) and the insertion domain are labeled. Note the glove-and-thumb like cleft they form, that the 30-OH is inserted into. A basic groove (blue) the RNA binds along outside the cleft is visible. (D) A close-up view of PAZ, as in C (surface not-transparent, slightly rotated). See white arrows for orientation, and location of 30-OH binding site. RNA is shown red in sticks. The terminal –OH is barely visible, buried in a cleft. It and the carbon it bonds have been colored yellow for clarity. (E) The PIWI domain (2BGG). Note the insertion of the 50P red (labeled) into the binding site. Its complimentary strand (pink) is not annealed to it, and the 30 overhang and first complimentary bases sit on the protein surface. (F) An enlarged view of (E), with protein in slate and RNA modeled as red sticks. The coordinated magnesium is a grey sphere, which is coordinated by the terminal carboxylate of the protein, protein side chains, and RNA phosphate oxygens. The 50 base stacks against a conserved Tyr. Several other sidechain contacts are shown.

Fig. 3. Argonaute/RISC. (A) P. furiosus Argonaute (PDB 1Z26). A color-guided key to the domains is presented. PAZ sits over the PIWI/N/MID bowl and active site. The liganding atoms for the catalytic metal are depicted as yellow balls for clarity. The tungstate binding site (50P surrogate) is shown as tan spheres. (B) A guide strand channel. Looking down from the PAZ domain towards the active site, Z-sections are clipped off. Colors of domains are as in the key in (A). Wrapping down along a basic cleft from the PAZ 30OH binding site (approximate position labeled), a RNA binding groove passes the active site (yellow), and runs down to the 50P binding site (tan balls). A second cleft running perpendicular to this one at its entry may accommodate target strand RNA. For more detail, and models of siRNA placed into the grooves, see [27,29].

Fig. 4. VP19 sequestration of siRNA. (A) CIRV VP19 (1RPU, RNA removed). Two monomers (blue and cyan) form an 8 strand, concave b-sheet with bracketing helices at the ends. (B) Tombus viral VP19 bound to siRNA (1 monomer shown). RNA strands are modeled as sticks, with one strand pink and one red. The bracketing helix places two tryptophans in position to stack over the terminal RNA bases. On the b-sheet surface, and Arg and a Lys interact with the phosphate backbone, and at the center of the RNA binding surface, a number of Ser and Thr mediate an extensive hydrogen bond network. Both the Trp brackets and RNA binding by an extended b-sheet are unique.


Small RNA asymmetry in RNAi- Function in RISC assembly and gene regulation
FEBS Letters 579 (2005) 5850–5857


The role of the oncofetal IGF2 mRNA-binding protein 3 (IGF2BP3) in cancer
Seminars in Cancer Biol 2014; 29:3-12

Table 1 – Target mRNAs of IGF2BP3.

Target cis-Element Regulation
CD44 3’ -utr Control of mRNA stability
IGF2 5’ -utr Translational control
H19 ncRNA Unknown
ACTB 3’ -utr Unknown
MYC CRD Unknown
CD164 Unknown Control of mRNA stability
MMP9 Unknown Control of mRNA stability
ABCG2 Unknown Unknown
PDPN 3’ -utr Control of mRNA stability
HMGA2 3’ -utr Protection from miR directed degradation
CCND1 3’ -utr translational control
CCND3 3’ -utr translational control
CCNG1 3’ -utr translationalcontrol


Targeting glucose uptake with siRNA-based nanomedicine for cancer therapy
Biomaterials 2015; 51:1-11
The therapeutic potential of RNA interference
FEBS Letters 579 (2005) 5996–6007

Table 1 Companies developing RNAi therapeutics that includes cancer

Company name Primary areas of interest
Atugen AG Metabolic disease; cancer ocular disease; skin disease
Benitec Australia Limited Hepatitis C virus; HIV/AIDS; cancer; diabetes/obesity
Calando Pharmaceuticals Nanoparticle technology
Genta Incorporated Cancer
Intradigm Corporation Cancer; SARS; arthritis
Sirna Therapeutics, Inc. AMD; Hepatitis C virus; asthma; diabetes; cancer; Huntington s disease; hearing loss


The Noncoding RNA Revolution—Trashing Old Rules to Forge New Ones
Cell 2014; 157:77-94

Figure 1. Noncoding RNAs Function in Diverse Contexts Noncoding RNAs function in all domains of life, regulating gene expression from transcription to splicing to translation and contributing to genome organization and stability. Self-splicing RNAs, ribosomes, and riboswitches function in both eukaryotes and bacteria. Archaea (not shown) also utilize ncRNA systems including ribosomes, riboswitches, snoRNPs, and CRISPR. Orange strands, ncRNA performing the action indicated; red strands, the RNA acted upon by the ncRNA. Blue strands, DNA. Triangle, small-molecule metabolite bound by a riboswitch. Ovals indicate protein components of an RNP, such as the spliceosome (white oval), ribosome (two purple subunits), or other RNPs (yellow ovals). Because of the importance of RNA structure in these ncRNAs, some structures are shown but they are not meant to be realistic.


miRNAs and cancer targeting

Table 1 of targets

miRNA Cancer type reference
NA GI cancer Current status of miRNA-targeting therapeutics and preclinical studies against gastroenterological carcinoma
NA Renal cell Differential expression profiling of microRNAs and their potential involvement in renal cell carcinoma pathogenesis
NA urothelial
A microRNA expression ratio defining the invasive phenotype in bladder tumors
miR-31 breast A Pleiotropically Acting MicroRNA, miR-31, inhibits breast cancer growth
miR-512-3p NSCLC Inhibition of RAC1-GEF DOCK3 by miR-512-3p contributes to suppression of metastasis in non-small cell lung cancer
miR-495 gastric Methylation-associated silencing of miR-495 inhibit the migration and invasion of human gastric cancer cells
microRNA-218 prostate microRNA-218 inhibits prostate cancer cell growth and promotes apoptosis by repressing TPD52 expression
MicroRNA-373 cervical cancer MicroRNA-373 functions as an oncogene and targets YOD1 gene in cervical cancer
miR-25 NSCLC miR-25 modulates NSCLC cell radio-sensitivity – inhibiting BTG2 expression
miR-92a cervical cancer miR-92a. upregulated in cervical cancer & promotes cell proliferation and invasion by targeting FBXW7
MiR-153 NSCLC MiR-153 inhibits migration and invasion of human non-small-cell lung cancer by targeting ADAM19
miR-203 melanoma miR-203 inhibits melanoma invasive and proliferative abilities by targeting the polycomb group gene BMI1
miR-204-5p Papillary thyroid miR-204-5p suppresses cell proliferation by inhibiting IGFBP5 in papillary thyroid carcinoma
miR-342-3p Hepato-cellular miR-342-3p affects hepatocellular carcinoma cell proliferation via regulating NF-κB pathway
miR-1271 NSCLC miR-1271 promotes non-small-cell lung cancer cell proliferation and invasion via targeting HOXA5
miR-203 pancreas Pancreatic cancer derived exosomes regulate the expression of TLR4 in dendritic cells via miR-203
miR-203 metastatic SCC Rewiring of an Epithelial Differentiation Factor, miR-203, to Inhibit Human SCC Metastasis
miR-204 RCC TRPM3 and miR-204 Establish a Regulatory Circuit that Controls Oncogenic Autophagy in Clear Cell Renal Cell Carcinoma
NA urologic MicroRNAs and cancer. Current and future perspectives in urologic oncology
NA RCC MicroRNAs and their target gene networks in renal cell carcinoma
NA osteoSA MicroRNAs in osteosarcoma
NA urologic MicroRNA in Prostate, Bladder, and Kidney Cancer
NA urologic Micro-RNA profiling in kidney and bladder cancers


Current status of miRNA-targeting therapeutics and preclinical studies against gastroenterological carcinoma
Shibata et al. Molecular and Cellular Therapies 2013, 1:5

Differential expression profiling of microRNAs and their potential involvement in renal cell carcinoma pathogenesis
Clinical Biochemistry 43 (2010) 150–158

A microRNA expression ratio defining the invasive phenotype in bladder tumors
Urologic Oncology: Seminars and Original Investigations 28 (2010) 39–48

A Pleiotropically Acting MicroRNA, miR-31, inhibits breast cancer growth
Cell 137, 1032–1046, June 12, 2009

Inhibition of RAC1-GEF DOCK3 by miR-512-3p contributes to suppression of metastasis in non-small cell lung cancer
Intl JBiochem & Cell Biol 2015; 61:103-114

Methylation-associated silencing of miR-495 inhibit the migration and invasion of human gastric cancer cells by directly targeting PRL-3
Biochem Biochem Res Commun 2014; 456:344-350

microRNA-218 inhibits prostate cancer cell growth and promotes apoptosis by repressing TPD52 expression
Biochem Biophys Res Commun 2015; 456:804-809

MicroRNA-373 functions as an oncogene and targets YOD1 gene in cervical cancer
BBRC 2015; xx:1-6

miR-25 modulates NSCLC cell radio-sensitivity – inhibiting BTG2 expression
BBRC 2015; 457:235-241

miR-92a. upregulated in cervical cancer & promotes cell proliferation and invasion by targeting FBXW7
BBRC 2015; 458:63-69

MiR-153 inhibits migration and invasion of human non-small-cell lung cancer by targeting ADAM19
BBRC 2015; 456:381-385

miR-203 inhibits melanoma invasive and proliferative abilities by targeting the polycomb group gene BMI1
BBMC 2015; 456: 361-366

miR-204-5p suppresses cell proliferation by inhibiting IGFBP5 in papillary thyroid carcinoma
BBRC 2015; 457:621-627

miR-342-3p affects hepatocellular carcinoma cell proliferation via regulating NF-κB pathway
BBRC 2015; 457:370-377

miR-1271 promotes non-small-cell lung cancer cell proliferation and invasion via targeting HOXA5
BBRC 2015; 458:714-719

Pancreatic cancer derived exosomes regulate the expression of TLR4 in dendritic cells via miR-203
Cell Immunol 2014; 292:65-69

Rewiring of an Epithelial Differentiation Factor, miR-203, to Inhibit Human Squamous Cell Carcinoma Metastasis
Cell Reports 2014; 9:104-117

TRPM3 and miR-204 Establish a Regulatory Circuit that Controls Oncogenic Autophagy in Clear Cell Renal Cell Carcinoma
Cancer Cell Nov 10, 2014; 26: 738–753

MicroRNA in Prostate, Bladder, and Kidney Cancer
Eur Urol 2011; 59:671-681

Micro-RNA profiling in kidney and bladder cancers
Urologic Oncology: Seminars and Original Investigations 2007; 25:387–392

MicroRNAs and cancer. Current and future perspectives in urologic oncology
Urologic Oncology: Seminars and Original Investigations 2010; 28:4–13

MicroRNAs and their target gene networks in renal cell carcinoma
BBRC 2011; 405:153-156

MicroRNAs in osteosarcoma
Clin Chim Acta 2015; 444:9-17


Table 2. miRNA cancer therapeutics



  • miRNA and mRNA cancer signatures determined by analysis of expression levels in large cohorts of patients
    | PNAS | Nov 19, 2013; 110(47): 19160–19165 study of mRNA and microRNA (miRNA) expression profiles of cells and tissue has become a major tool for therapeutic development. The results of such experiments are expected to change the methods used in the diagnosis and prognosis of disease. We introduce surprisal analysis, an information-theoretic approach grounded in thermodynamics, to compactly transform the information acquired from microarray studies into applicable knowledge about the cancer phenotypic state. The analysis of mRNA and miRNA expression data from ovarian serous carcinoma, prostate adenocarcinoma, breast invasive carcinoma, and lung adenocarcinoma cancer patients and organ specific control patients identifies cancer-specific signatures. We experimentally examine these signatures and their respective networks as possible therapeutic targets for cancer in single cell experiments.



RNA editing is vital to provide the RNA and protein complexity to regulate the gene expression. Correct RNA editing maintains the cell function and organism development. Imbalance of the RNA editing machinery may lead to diseases and cancers. Recently,RNA editing has been recognized as a target for drug discovery although few studies targeting RNA editing for disease and cancer therapy were reported in the field of natural products. Therefore, RNA  editing may be a potential target for therapeutic natural products


Aberrant microRNA (miRNA) expression is implicated in tumorigenesis. The underlying mechanisms are unclear because the regulations of each miRNA on potentially hundreds of mRNAs are sample specific.


We describe a novel approach to infer Probabilistic Mi RNA–mRNA  Interaction Signature (‘ProMISe’) from a single pair of miRNA–mRNA expression profile. Our model considers mRNA and miRNA competition as a probabilistic function of the expressed seeds (matches). To demonstrate ProMISe, we extensively exploited The Cancer Genome Atlas data. As a target predictor, ProMISe identifies more confidence/validated targets than other methods. Importantly, ProMISe confers higher cancer diagnostic power than using expression profiles alone.

Gene set enrichment analysis on averaged ProMISe uniquely revealed respective target enrichments of oncomirs miR-21 and 145 in glioblastoma and ovarian cancers. Moreover, comparing matched breast (BRCA) and thyroid (THCA) tumor/normal samples uncovered thousands of tumor-related interactions. For example, ProMISe– BRCA network involves miR-155/183/21, which exhibits higher ProMISe coupled with coherently higher miRNA expression and lower target expression; oncomirs miR-221/222 in the ProMISe–THCA network engage with many downregulated target genes. Together, our probabilistic approach of integrating expression and sequence scores establishes a functional link between the aberrant miRNA and mRNA expression, which was previously under-appreciated due to the methodological differences.






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Introduction to Metabolomics

Introduction to Metabolomics

Author and Curator: Larry H. Bernstein, MD, FCAP 

This concludes a long step-by-step journey into rediscovering biological processes from the genome as a framework to the remodeled and reconstituted cell through a number of posttranscription and posttranslation processes that modify the proteome and determine the metabolome.  The remodeling process continues over a lifetime. The process requires a balance between nutrient intake, energy utilization for work in the lean body mass, energy reserves, endocrine, paracrine and autocrine mechanisms, and autophagy.  It is true when we look at this in its full scope – What a creature is man?
 Recommended Readings and Historical Perspectives

Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the “systematic study of the unique chemical fingerprints that specific cellular processes leave behind”, the study of their small-molecule metabolite profiles.[1] The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes.[2] mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell. One of the challenges of systems biology and functional genomics is to integrate proteomic, transcriptomic, and metabolomic information to provide a better understanding of cellular biology.

The term “metabolic profile” was introduced by Horning, et al. in 1971 after they demonstrated that gas chromatography-mass spectrometry (GC-MS) could be used to measure compounds present in human urine and tissue extracts. The Horning group, along with that of Linus Pauling and Arthur B. Robinson led the development of GC-MS methods to monitor the metabolites present in urine through the 1970s.

Concurrently, NMR spectroscopy, which was discovered in the 1940s, was also undergoing rapid advances. In 1974, Seeley et al. demonstrated the utility of using NMR to detect metabolites in unmodified biological samples.This first study on muscle highlighted the value of NMR in that it was determined that 90% of cellular ATP is complexed with magnesium. As sensitivity has improved with the evolution of higher magnetic field strengths and magic angle spinning, NMR continues to be a leading analytical tool to investigate metabolism. Efforts to utilize NMR for metabolomics have been influenced by the laboratory of Dr. Jeremy Nicholson at Birkbeck College, University of London and later at Imperial College London. In 1984, Nicholson showed 1H NMR spectroscopy could potentially be used to diagnose diabetes mellitus, and later pioneered the application of pattern recognition methods to NMR spectroscopic data.

In 2005, the first metabolomics web database, METLIN, for characterizing human metabolites was developed in the Siuzdak laboratory at The Scripps Research Institute and contained over 10,000 metabolites and tandem mass spectral data. As of September 2012, METLIN contains over 60,000 metabolites as well as the largest repository of tandem mass spectrometry data in metabolomics.

On 23 January 2007, the Human Metabolome Project, led by Dr. David Wishart of the University of Alberta, Canada, completed the first draft of the human metabolome, consisting of a database of approximately 2500 metabolites, 1200 drugs and 3500 food components. Similar projects have been underway in several plant species, most notably Medicago truncatula and Arabidopsis thaliana for several years.

As late as mid-2010, metabolomics was still considered an “emerging field”. Further, it was noted that further progress in the field depended in large part, through addressing otherwise “irresolvable technical challenges”, by technical evolution of mass spectrometry instrumentation.

Metabolome refers to the complete set of small-molecule metabolites (such as metabolic intermediates, hormones and other signaling molecules, and secondary metabolites) to be found within a biological sample, such as a single organism. The word was coined in analogy with transcriptomics and proteomics; like the transcriptome and the proteome, the metabolome is dynamic, changing from second to second. Although the metabolome can be defined readily enough, it is not currently possible to analyse the entire range of metabolites by a single analytical method. The first metabolite database(called METLIN) for searching m/z values from mass spectrometry data was developed by scientists at The Scripps Research Institute in 2005. In January 2007, scientists at the University of Alberta and the University of Calgary completed the first draft of the human metabolome. They catalogued approximately 2500 metabolites, 1200 drugs and 3500 food components that can be found in the human body, as reported in the literature. This information, available at the Human Metabolome Database ( and based on analysis of information available in the current scientific literature, is far from complete.

Each type of cell and tissue has a unique metabolic ‘fingerprint’ that can elucidate organ or tissue-specific information, while the study of biofluids can give more generalized though less specialized information. Commonly used biofluids are urine and plasma, as they can be obtained non-invasively or relatively non-invasively, respectively. The ease of collection facilitates high temporal resolution, and because they are always at dynamic equilibrium with the body, they can describe the host as a whole.

Metabolites are the intermediates and products of metabolism. Within the context of metabolomics, a metabolite is usually defined as any molecule less than 1 kDa in size.
A primary metabolite is directly involved in the normal growth, development, and reproduction. A secondary metabolite is not directly involved in those processes.  By contrast, in human-based metabolomics, it is more common to describe metabolites as being either endogenous (produced by the host organism) or exogenous. Metabolites of foreign substances such as drugs are termed xenometabolites. The metabolome forms a large network of metabolic reactions, where outputs from one enzymatic chemical reaction are inputs to other chemical reactions.

Metabonomics is defined as “the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification”. The word origin is from the Greek μεταβολή meaning change and nomos meaning a rule set or set of laws. This approach was pioneered by Jeremy Nicholson at Imperial College London and has been used in toxicology, disease diagnosis and a number of other fields. Historically, the metabonomics approach was one of the first methods to apply the scope of systems biology to studies of metabolism.

There is a growing consensus that ‘metabolomics’ places a greater emphasis on metabolic profiling at a cellular or organ level and is primarily concerned with normal endogenous metabolism. ‘Metabonomics’ extends metabolic profiling to include information about perturbations of metabolism caused by environmental factors (including diet and toxins), disease processes, and the involvement of extragenomic influences, such as gut microflora. This is not a trivial difference; metabolomic studies should, by definition, exclude metabolic contributions from extragenomic sources, because these are external to the system being studied.

Toxicity assessment/toxicology. Metabolic profiling (especially of urine or blood plasma samples) detects the physiological changes caused by toxic insult of a chemical (or mixture of chemicals).

Functional genomics. Metabolomics can be an excellent tool for determining the phenotype caused by a genetic manipulation, such as gene deletion or insertion. Sometimes this can be a sufficient goal in itself—for instance, to detect any phenotypic changes in a genetically-modified plant intended for human or animal consumption. More exciting is the prospect of predicting the function of unknown genes by comparison with the metabolic perturbations caused by deletion/insertion of known genes.

Nutrigenomics is a generalised term which links genomics, transcriptomics, proteomics and metabolomics to human nutrition. In general a metabolome in a given body fluid is influenced by endogenous factors such as age, sex, body composition and genetics as well as underlying pathologies. The large bowel microflora are also a very significant potential confounder of metabolic profiles and could be classified as either an endogenous or exogenous factor. The main exogenous factors are diet and drugs. Diet can then be broken down to nutrients and non- nutrients.

Jose Eduardo des Salles Roselino

The problem with genomics was it was set as explanation for everything. In fact, when something is genetic in nature the genomic reasoning works fine. However, this means whenever an inborn error is found and only in this case the genomic knowledge afterwards may indicate what is wrong and not the completely way to put biology upside down by reading everything in the DNA genetic as well as non-genetic problems.

Coordination of the transcriptome and metabolome by the circadian clock PNAS 2012

Coordination of the transcriptome and metabolome by the circadian clock PNAS 2012

analysis of metabolomic data and differential metabolic regulation for fetal lungs, and maternal blood plasma

conformational changes leading to substrate efflux.img

conformational changes leading to substrate efflux.img

The cellular response is defined by a network of chemogenomic response signatures.

The cellular response is defined by a network of chemogenomic response signatures.

Dynamic Construct of the –Omics

Dynamic Construct of the –Omics

 genome cartoon

genome cartoon

central dogma phenotype

central dogma phenotype

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Introduction to Subcellular Structure

Author and Curator: Larry H. Bernstein, MD, FCAP  



The following chapter of the metabolism/transcriptomics/proteomics/metabolomics series deals with the subcellular structure of the cell.  This would have to include the cytoskeleton, which has a key role in substrate and ion efflux and influx, and in cell movement mediated by tubulins.  It has been extensively covered already.  Much of the contributions here are concerned with the mitochondrion, which is also covered in metabolic pathways.  The ribosome is the organelle that we have discussed with respect to the transcription and translation of the genetic code through mRNA and tRNA, and the therapeutic implications of SiRNA as well as the chromatin regulation of lncRNA.

We have also encountered the mitochondrion and the lysosome in the discussion of apoptosis and autophagy, maintaining the balance between cell regeneration and cell death.

I here list the organelles:

  1. Nucleus
  2. Centrosome
  3. Nuclear Membrane
  4. Ribososome
  5. Endoplasmic Reticulum
  6. Mitochondria
  7. Lysosome
  8. Cytoskeleton
  9. Golgi apparatus
  10. Cytoplasm


Golgi Apparatus

Found within the cytoplasm of both plant and animal cells, the Golgi is composed of stacks of membrane-bound structures known as cisternae (singular: cisterna). An individual stack is sometimes called a dictyosome (from Greek dictyon: net + soma: body), especially in plant cells. A mammalian cell typically contains 40 to 100 stacks. Between four and eight cisternae are usually present in a stack; however, in some protists as many as sixty have been observed. Each cisterna comprises a flat, membrane-enclosed disc that includes special Golgi enzymes which modify or help to modify cargo proteins that travel through it.

The cisternae stack has four functional regions: the cis-Golgi network, medial-Golgi, endo-Golgi, and trans-Golgi network. Vesicles from the endoplasmic reticulum (via the vesicular-tubular clusters) fuse with the network and subsequently progress through the stack to the trans-Golgi network, where they are packaged and sent to their destination.

The Golgi apparatus is integral in modifying, sorting, and packaging these macromolecules for cell secretion (exocytosis) or use within the cell. It primarily modifies proteins delivered from the rough endoplasmic reticulum, but is also involved in the transport of lipids around the cell, and the creation of lysosomes.  Enzymes within the cisternae are able to modify the proteins by addition of carbohydrates (glycosylation) and phosphates (phosphorylation). In order to do so, the Golgi imports substances such as nucleotide sugars from the cytosol. These modifications may also form a signal sequence which determines the final destination of the protein. For example, the Golgi apparatus adds a mannose-6-phosphate label to proteins destined for lysosomes.

The Golgi plays an important role in the synthesis of proteoglycans, which are molecules present in the extracellular matrix of animals. It is also a major site of carbohydrate synthesis. This includes the production of glycosaminoglycans (GAGs), long unbranched polysaccharides which the Golgi then attaches to a protein synthesised in the endoplasmic reticulum to form proteoglycans. Enzymes in the Golgi polymerize several of these GAGs via a xylose link onto the core protein. Another task of the Golgi involves the sulfation of certain molecules passing through its lumen via sulfotranferases that gain their sulfur molecule from a donor called PAPS. This process occurs on the GAGs of proteoglycans as well as on the core protein. Sulfation is generally performed in the trans-Golgi network. The level of sulfation is very important to the proteoglycans’ signalling abilities, as well as giving the proteoglycan its overall negative charge.

The phosphorylation of molecules requires that ATP is imported into the lumen of the Golgi and utilised by resident kinases such as casein kinase 1 and casein kinase 2. One molecule that is phosphorylated in the Golgi is apolipoprotein, which forms a molecule known as VLDL that is found in plasma. It is thought that the phosphorylation of these molecules labels them for secretion into the blood.

The Golgi has a putative role in apoptosis, with several Bcl-2 family members localised there, as well as to the mitochondria. A newly characterized protein, GAAP (Golgi anti-apoptotic protein), almost exclusively resides in the Golgi and protects cells from apoptosis by an as-yet undefined mechanism.

The vesicles that leave the rough endoplasmic reticulum are transported to the cis face of the Golgi apparatus, where they fuse with the Golgi membrane and empty their contents into the lumen. Once inside the lumen, the molecules are modified, then sorted for transport to their next destinations. The Golgi apparatus tends to be larger and more numerous in cells that synthesize and secrete large amounts of substances; for example, the plasma B cells and the antibody-secreting cells of the immune system have prominent Golgi complexes.

Those proteins destined for areas of the cell other than either the endoplasmic reticulum or Golgi apparatus are moved towards the trans face, to a complex network of membranes and associated vesicles known as the trans-Golgi network (TGN). This area of the Golgi is the point at which proteins are sorted and shipped to their intended destinations by their placement into one of at least three different types of vesicles, depending upon the molecular marker they carry.



Diagram of secretory process from endoplasmic reticulum (orange) to Golgi apparatus (pink). 1. Nuclear membrane; 2. Nuclear pore; 3. Rough endoplasmic reticulum (RER); 4. Smooth endoplasmic reticulum (SER); 5. Ribosome attached to RER; 6. Macromolecules; 7. Transport vesicles; 8. Golgi apparatus; 9. Cis face of Golgi apparatus; 10. Trans face of Golgi apparatus; 11. Cisternae of the Golgi Apparatus

Exocytotic vesicles

After packaging, the vesicles bud off and immediately move towards the plasma membrane, where they fuse and release the contents into the extracellular space in a process known as constitutive secretion. (Antibody release by activated plasma B cells)

Secretory vesicles

After packaging, the vesicles bud off and are stored in the cell until a signal is given for their release. When the appropriate signal is received they move towards the membrane and fuse to release their contents. This process is known as regulated secretion. (Neurotransmitter release from neurons)

Lysosomal vesicles

Vesicle contains proteins and ribosomes destined for the lysosome, an organelle of degradation containing many acid hydrolases, or to lysosome-like storage organelles. These proteins include both digestive enzymes and membrane proteins. The vesicle first fuses with the late endosome, and the contents are then transferred to the lysosome via unknown mechanisms.

Lysosome (derived from the Greek words lysis, meaning “to loosen”, and soma, “body”) is a membrane-bound cell organelle found in animal cells (they are absent in red blood cells). They are structurally and chemically spherical vesicles containing hydrolytic enzymes, which are capable of breaking down virtually all kinds of biomolecules, including proteins, nucleic acids, carbohydrates, lipids, and cellular debris.  Lysosomes are responsible for cellular homeostasis for their involvements in secretion, plasma membrane repair, cell signalling and energy metabolism, which are related to health and diseases. Depending on their functional activity their sizes can be very different, as the biggest ones can be more than 10 times bigger than the smallest ones. They were discovered and named by Belgian biologist Christian de Duve, who eventually received the Nobel Prize in Physiology or Medicine in 1974.

Enzymes of the lysosomes are synthesised in the rough endoplasmic reticulum. The enzymes are released from Golgi apparatus in small vesicles which ultimately fuse with acidic vesicles called endosomes, thus becoming full lysosomes. In the process the enzymes are specifically tagged with mannose 6-phosphate to differentiate them from other enzymes. Lysosomes are interlinked with three intracellular processes namely phagocytosis, endocytosis and autophagy. Extracellular materials such as microorganisms taken up by phagocytosis, macromolecules by endocytosis, and unwanted cell organelles are fused with lysosomes in which they are broken down to their basic molecules. Thus lysosomes are the recycling units of a cell.

The endoplasmic reticulum (ER) is a type of organelle in the cells of eukaryotic organisms that forms an interconnected network of flattened, membrane-enclosed sacs or tubes known as cisternae. The membranes of the ER are continuous with the outer membrane of the nuclear envelope. Endoplasmic reticulum occurs in most types of eukaryotic cells, including the most primitive Giardia, but is absent from red blood cells and spermatozoa. There are two types of endoplasmic reticulum, rough endoplasmic reticulum (RER) and smooth endoplasmic reticulum (SER). The outer (cytosolic) face of the rough endoplasmic reticulum is studded with ribosomes that are the sites of protein synthesis. The rough endoplasmic reticulum is especially prominent in cells such as hepatocytes where active smooth endoplasmic reticulum lacks ribosomes and functions in lipid metabolism, carbohydrate metabolism, and detoxification and is especially abundant in mammalian liver and gonad cells. The lacey membranes of the endoplasmic reticulum were first seen in 1945 by Keith R. Porter, Albert Claude, Brody Meskers and Ernest F. Fullam, using electron microscopy.




The Effects of Actomyosin Tension on Nuclear Pore Transport
Rachel Sammons
Undergraduate Honors Thesis
Spring 2011

The cytoskeleton maintains cellular structure and tension through a force balance with the nucleus, where actomyosin is anchored to the nuclear envelope by nesprin integral proteins. It is hypothesized that the presence or absence of this tension alters the transport of molecules through the nuclear pore complex. We tested the effects of cytoskeletal tension on nuclear transport in human umbilical vein endothelial cells (HUVECs) by performing fluorescence recovery after photo-bleaching (FRAP) experiments on the nuclei to monitor the passive transport of the molecules through nuclear pores.

Using myosin inhibitors, as well as siRNA transfections to reduce the expression of nesprin-1, we altered the nucleo-cytoskeletal force balance and monitored the effect of each on the nuclear pore. FRAP data was fit to a diffusion model by assuming pseudo-steady state inside the nuclear pore, perfect mixing within both the cytoplasm and the nucleus, and no intracellular binding of the fluorescent probes. From these results and a model from the current literature relating diffusion rate constants to nuclear pore radii, we were able to determine that changing cytoskeletal tension alters nuclear pore size and passive transport.

nuclear pores in nuclear envelope

nuclear pores in nuclear envelope

image of nuclear pores on the external surface of the nuclear envelope

nuclear envelope and FG filaments

nuclear envelope and FG filaments

nuclear envelope and FG filaments

Figure 1: The structure and location of the nuclear pore, shown by (a) AFM image of nuclear pores on the external surface of the nuclear envelope[5] and (b) computer model cross-section. The nuclear envelope is shown in cyan, and FG filaments in blue can be seen throughout the channel. The nuclear basket extends into the nucleoplasm.

Fusion-pore expansion during syncytium formation is restricted by an actin network

A Chen, E Leikina, K Melikov, B Podbilewicz, MM. Kozlov and LV. Chernomordik,*
J Cell Sci 1 Nov 2008;121: 3619-3628.​jcs.032169

Effects of actin-modifying agents indicate that the actin cortex slows down pore expansion. We propose that the growth of the strongly bent fusion-pore rim is restricted by a dynamic resistance of the actin network and driven by membrane-bending proteins that are involved in the generation of highly curved intracellular membrane compartments.

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The role and importance of transcription factors

Larry H. Bernstein, MD, FCAP, Writer and Curator

The following is a second in the 2nd series that is focused on the topic of the impact of genomics and transcriptomics in the evolution of 21st century of medicine, which shall have to be more efficient and more effective by the end of this decade, if the prediction for the funding of Medicare is expected to run out. Even so, Social Security was devised by none other than the Otto von Bismarck, who unified Germany, and United Kingdom has had a charity hospital care system begun to protect the widows of the ravages of war, and nursing was developed by Florence Nightengale as a result of the experience of war. It can only be concluded that the care for the elderly, the infirm, and those who have little resources to live on has a long history in western civilization, and it will not cease to exist as a public social obligation anytime soon. The 20th century saw an explosive development of physics; organic, inorganic, biochemistry, and medicinal chemistry, and the elucidation of the genetic code and its mechanism of translation in plants, microorganisms, and eukaryotes.  All of which occurred irrespective of the most horrendous wars that have reshaped the world map.

The following are the second portions of a puzzle in construction that is intended to move into deeper complexities introduced by proteomics, cell metabolism, metabolomics, and signaling.  This is the only manner by which I can begin to appreciate what a wonder it is to view and live in this world with all its imperfections.

We have already visited the transcription process, by which an RNA sequence is read.  This is essential for protein synthesis through the ordering of the amino acids in the primary structure. However, there are microRNAs and noncoding RNAs, and there are transcription factors.  The transcription factors bind to chromatin, and the RNAs also have some role in regulating the transcription process. We shall examine this further.

  1. RNA and the transcription the genetic code

Larry H. Bernstein, MD, FCAP, Writer and Curator

  1. The role and importance of transcription factors?
    Larry H. Bernstein, MD, FCAP, Writer and Curator
  2. What is the meaning of so many RNAs?

Larry H. Bernstein, MD, FCAP, Writer and Curator

  1. Pathology Emergence in the 21st Century
    Larry Bernstein, MD, FCAP, Author and Curator
  2. The Arnold Relman Challenge: US HealthCare Costs vs US HealthCare Outcomes

Larry H. Bernstein, MD, FCAP, Reviewer and Curator; and
Aviva Lev-Ari, PhD, RN, Curator




Quantifying transcription factor kinetics: At work or at play?

Posted online on September 11, 2013. (doi:10.3109/10409238.2013.833891)

Florian Mueller1,2, Timothy J. Stasevich3, Davide Mazza4, and James G. McNally5
1Institut Pasteur, Computational Imaging and Modeling Unit, CNRS, Paris, Fr
2Functional Imaging of Transcription, Institut de Biologie de l’Ecole Normale Supérieure, Paris, Fr
3Graduate School of Frontier Biosciences, Osaka University, Osaka, Jp
4Istituto Scientifico Ospedale San Raffaele, Centro di Imaging Sperimentale e Università Vita-Salute
San Raffaele, Milano, It, and
5Fluorescence Imaging Group, National Cancer Institute, NIH, Bethesda, MD, USA

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Transcription factors (TFs) interact dynamically in vivo with chromatin binding sites. Here we summarize and compare the four different techniques that are currently used to measure these kinetics in live cells, namely fluorescence recovery after photobleaching (FRAP), fluorescence correlation spectroscopy (FCS), single molecule tracking (SMT) and competition ChIP (CC). We highlight the principles underlying each of these approaches as well as their advantages and disadvantages. A comparison of data from each of these techniques raises an important question: do measured transcription kinetics reflect biologically functional interactions at specific sites (i.e. working TFs) or do they reflect non-specific interactions (i.e. playing TFs)? To help resolve this dilemma we discuss five key unresolved biological questions related to the functionality of transient and prolonged binding events at both specific promoter response elements as well as non-specific sites. In support of functionality, we review data suggesting that TF residence times are tightly regulated, and that this regulation modulates transcriptional output at single genes. We argue that in addition to this site-specific regulatory role, TF residence times also determine the fraction of promoter targets occupied within a cell thereby impacting the functional status of cellular gene networks. Thus, TF residence times are key parameters that could influence transcription in multiple ways.

Keywords: Competition-ChIP, kinetic modeling, live-cell imaging, non-specific binding, specific binding, transcription, transcription factor dynamics

The Transcription Factor Titration Effect Dictates Level of Gene ExpressionCalifornia Institute of Technology

Robert C. Brewster, Franz M. Weinert, Hernan G. Garcia, Dan Song, Mattias Rydenfelt, and Rob Phillips  CalTech
 Cell Mar 13, 2014; 156:1312–1323,.

Models of transcription are often built around a picture of RNA polymerase and transcription factors (TFs) acting on a single copy of a promoter. However, most TFs are shared between multiple genes with varying binding affinities. Beyond that, genes often exist at high copy number—in multiple identical copies on the chromosome or on plasmids or viral vectors with copy numbers in the hundreds. Using a thermodynamic model, we characterize the interplay between TF copy number and the demand for that TF. We demonstrate the parameter-free predictive power of this model as a function of the copy number of the TF and the number and affinities of the available specific binding sites; such predictive control is important for the understanding of transcription and the desire to quantitatively design the output of genetic circuits. Finally, we use these experiments to dynamically measure plasmid copy number through the cell cycle.



Optimal reference genes for normalization of qRT-PCR data from archival formalin-fixed, paraffin-embedded breast tumors controlling for tumor cell content and decay of mRNA.

Tramm TSørensen BSOvergaard JAlsner J.

Diagn Mol Pathol. 2013 Sep;22(3):181-7.

Gene-expression analysis is increasingly performed on degraded mRNA from formalin-fixed, paraffin-embedded tissue (FFPE), giving the option of examining retrospective cohorts. The aim of this study was to select robust reference genes showing stable expression over time in FFPE, controlling for various content of tumor tissue and decay of mRNA because of variable length of storage of the tissue.

Sixteen reference genes were quantified by qRT-PCR in 40 FFPE breast tumor samples, stored for 1 to 29 years. Samples included 2 benign lesions and 38 carcinomas with varying tumor content. Stability of the reference genes were determined by the geNorm algorithm. mRNA was successfully extracted from all samples, and the 16 genes quantified in the majority of samples.

Results showed 14% loss of amplifiable mRNA per year, corresponding to a half-life of 4.6 years. The 4 most stable expressed genes were CALM2, RPL37A, ACTB, and RPLP0. Several of the other examined genes showed considerably instability over time (GAPDH, PSMC4, OAZ1, IPO8).

In conclusion, we identified 4 genes robustly expressed over time and independent of neoplastic tissue content in the FFPE block.   PMID:23846446


Structures of Cas9 Endonucleases Reveal RNA-Mediated Conformational Activation

Martin Jinek1,*,Fuguo Jiang2,*David W. Taylor3,4,*Samuel H. Sternberg5,*Emine Kaya2, et al.


1Department of Biochemistry, University of Zurich, CH-8057 Zurich, Switzerland. 2Department of Molecular and Cell Biology,3Howard Hughes Medical Institute, 4California Institute for Quantitative Biosciences, 5Department of Chemistry, 6Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720,. 7The Laboratory for Molecular Infection Medicine Sweden, Umeå University, Umeå S-90187, Sweden. 8Helmholtz Centre for Infection Research, Department of Regulation in Infection Biology, D-38124 Braunschweig, Germany. 9Hannover Medical School, D-30625 Hannover, Germany. 10Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720.

‡ Present address: Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66 CH-4058 Basel, Switzerland.

§ Present address: Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA.




Type II CRISPR-Cas systems use an RNA-guided DNA endonuclease, Cas9,

  • to generate double-strand breaks in invasive DNA during an adaptive bacterial immune response.

Cas9 has been harnessed as a powerful tool for genome editing and gene regulation in many eukaryotic organisms.

Here, we report 2.6 and 2.2 Å resolution crystal structures of two major Cas9 enzymes subtypes,

  • revealing the structural core shared by all Cas9 family members.

The architectures of Cas9 enzymes define nucleic acid binding clefts, and

single-particle electron microscopy reconstructions show that the two structural lobes harboring these clefts undergo guide

  • RNA-induced reorientation to form a central channel where DNA substrates are bound.

The observation that extensive structural rearrangements occur before target DNA duplex binding

  • implicates guide RNA loading as a key step in Cas9 activation.

MicroRNA function in endothelial cells
Dr. Virginie Mattot
Angiogenesis, endothelium activation
Solving the mystery of an unknown target gene using microRNA Target Site Blockers

Dr. Virgine Mattot works in the team “Angiogenesis, endothelium activation and Cancer” directed by Dr. Fabrice Soncin at the Institut de Biologie de Lille in France where she studies the roles played by microRNAs in endothelial cells during physiological and pathological processes such as angiogenesis or endothelium activation. She has been using Target Site Blockers to investigate the role of microRNAs on putative targets which functions are yet unknown.

What is the main focus of the research conducted in your lab?

We are studying endothelial cell functions with a particular interest in angiogenesis and endothelium activation during physiological and tumoral vascular development.

How did your research lead to the study of microRNAs?

A few years ago, we identified

  • an endothelial cell-specific gene which
  • harbors a microRNA in its intronic sequence.

We have since been working on understanding the functions of

  • both this new gene and its intronic microRNA in endothelial cells.

What is the aim of your current project?

While we were searching for the functions of the intronic microRNA,

  • we identified an unknown gene as a putative target.

The aim of my project was to investigate if this unknown gene was actually a genuine target and if regulation of this gene by the microRNA was involved in endothelial cell function. We had already characterized the endothelial cell phenotype associated with the inhibition of our intronic microRNA. We then used miRCURY LNA™ Target Site Blockers to demonstrate

  • the expression of this unknown gene is actually controlled by this microRNA.
  • the microRNA regulates specific endothelial cell properties through regulation of this unknown gene.

How did you perform the experiments and analyze the results?

LNA™ enhanced target site blockers (TSB) for our microRNA were designed by Exiqon. We

  • transfected the TSBs into endothelial cells using our standard procedure and
  • analysed the induced phenotype.

As a control for these experiments, a mutated version of the TSB was designed by Exiqon and transfected into endothelial cells. We first verified that this TSB was functional by analyzing

  • the expression of the miRNA target against which the TSB was directed
  • we then showed the TSB induced similar phenotypes as those when we inhibited the microRNA in the same cells.

What do you find to be the main benefits/advantage of the LNA™ microRNA target site blockers from Exiqon?

Target Site Blockers are efficient tools to demonstrate the specific involvement of

  • putative microRNA targets in the function played by this microRNA.

What would be your advice to colleagues about getting started with microRNA functional analysis?

  • it is essential to perform both gain and loss of functions experiments.

 Changing the core of transcription

Different members of the TAF family of proteins work in differentiated cells, such as motor neurons or brown fat cells, to control the expression of genes that are specific to each cell type.

Katherine A Jones
Jones. eLife 2014;3:e03575.


Related research articles: Herrera FJ, Yamaguchi T, Roelink H, Tjian R. 2014. Core promoter factor TAF9B regulates neuronal gene expression. eLife 3:e02559.

Zhou H, Wan B, Grubisic I, Kaplan T, Tjian R. 2014. TAF7L modulates brown adipose tissue formation. eLife 3:e02811. Http://


Motor neurons (green) being grown in vitro

Motor neurons (green) being grown in vitro

Image Motor neurons (green) being grown in vitro


In a developing organism, different genes are expressed at different times


  • the pattern of gene expression can often change abruptly.


Expressing a gene involves multiple steps:


  • the DNA must be transcribed into a molecule of messenger RNA,
  • which is then trans­lated into a protein.


The mechanisms that start the transcription of protein-coding genes in rap­idly growing cells are reasonably well understood: two types of proteins—


  • DNA-binding activators and general transcription factors—


cooperate to recruit an enzyme called RNA polymerase, which then transcribes the gene (Kadonaga, 2012).


These proteins bind to a region of the gene called the promoter, which is


  • upstream from the protein-coding region of the gene.


TATA-binding protein is a general transcrip­tion factor that

  • binds to certain sequences of DNA bases found within promoters

14 TATA-binding protein associated factors (TAFs) are included into two different protein complexes called TFIID and SAGA (Müller et al., 2010). which, in budding yeast, can recruit TATA-binding protein to gene promoters (Basehoar et al., 2004), but not all genes require all of the general transcription factors, and some genes require both TFIID and SAGA complexes.

Although the steps that are required to switch on genes when cells are rapidly dividing are fairly well known,

  • the same is not true for cells that are differentiating into specialised cell types.

In these cells, many transcription factors are downregulated and

  • the entire pattern of gene expression changes dramatically.

Moreover, certain TAFs are strongly up-regulated during differentiation. The core transcriptional machinery is essentially rebuilt at the genes that are expressed in differentiated cells.

Over the years Robert Tjian of the University of California Berkeley and co-workers have illu­minated how individual TAFs can affect how a cell differentiates in different contexts (Figure 1). Now, in eLife, Francisco Herrera of UC Berkeley and co-workers—including Teppei Yamaguchi, Henk Roelink and Tjian—have identified a critical role for a TAF called TAF9B in the expression of genes in motor neurons (Herrera et al., 2014).

Herrera et al. found that TAF9B predominantly associates with the SAGA complex, rather than the TFIID complex, in the motor neuron cells. Mice in which the gene for TAF9B had been deleted had less neuronal tissue in the developing spinal cord. Moreover, the genes that are involved in forming the branches of neurons were not properly regu¬lated in these mice.

Recently, in another eLife paper, Tjian and co-workers at Berkeley, Fudan University and the Hebrew University of Jerusalem—including Haiying Zhou as first author, Bo Wan, Ivan Grubisic and Tommy Kaplan—reported that another TAF protein, called TAF7L, works as part of the TFIID complex to up-regulate genes that direct cells to become brown adipose tissue (Zhou et al., 2014).


TATA-binding protein associated factors

TATA-binding protein associated factors

Figure 1. TATA-binding protein associated factors (TAFs) regulate transcription in specific cell types. TAF3, for example, works with another transcription factor to regulate the expression of genes that are critical for the differentiation of the endoderm in the early embryo (Liu et al., 2011). TAF3 also forms a complex with the TATA-related factor, TRF3, to regulate Myogenin and other muscle-specific genes to form myotubes (Deato et al., 2008). TAF7L interacts with another transcription factor to activate genes involved in the formation of adipocytes (‘fat cells’) and adipose tissue (Zhou et al., 2013; Zhou et al., 2014). Finally, TAF9B is a key regulator of transcription in motor neurons (Herrera et al., 2014). The names of some of the genes regulated by the TAFs are shown in brackets.


Deleting the gene for TAF9B in mouse embryonic stem cells revealed that this TAF

  • is not needed for the growth of stem cells, or
  • required for the expression of genes that prevent differentiation:

both of these processes are known to be highly-dependent upon the TFIID complex
(Pijnappel et al., 2013). However,

  • genes that would normally be expressed specifically in neurons were not
  • up-regulated when cells without the TAF9B gene started to specialise.

Herrera et al. identified numerous genes that can only be switched on when the TAF9B protein is present, which means that it joins a growing list of TAF proteins that are dedicated to controllingthe expression of genes in specialised cell types.

TAF9B activates neuron-specific genes by binding to sites that

  • reside outside of these genes’ core promoters.

Further, many of these sites were also bound by a master regulator of motor neuron-specific genes.



Whilst most of the fat tissue in humans is white adipose tissue, which contains cells that store fatty molecules, some is brown adipose tissue, or ‘brown fat’, that instead generates heat. When TAF7L promotes the differentiation of brown fat, it up-regulates genes that are targeted by a tran­scription

factor called PPAR-γ; last year it was shown that this transcription factor also promotes the differentiation of white adipose tissue (Zhou et al., 2013).
Mice without the TAF7L gene had 40% less brown fat than wild-type mice, and also grew too much skeletal muscle tissue. TAF7L was specifi­cally required to activate genes that control how brown fat develops and functions. Thus TAF7L expression appears to shift the fate of a stem cell towards brown adipose tissue, potentially at the expense of skeletal muscle, as both cell types develop from the same group of stem cells.

When stem cells with less TAF7L than normal are differentiated in vitro, they yield more muscle than fat cells. Conversely, cells with an excess of TAF7L express brown fat-specific genes and switch off muscle-specific genes.

The work of Herrera et al. and Zhou et al. reinforces the idea that different TAFs

  • provide the flexibility needed to control gene expression in a tissue-specific manner, and
  • enable differenti­ating cells to change which genes they express rapidly.

However many interesting questions remain:

Which signals lead to the destruction of core transcription factors?
Are core promoter ele­ments at tissue-specific genes designed to rec­ognise variant TAFs?
What determines whether variant TAFs are incorporated within TFIID, SAGA, or other complexes?

Shortly after RNA polymerase II starts to tran­scribe a gene, it briefly pauses. Interestingly, a DNA sequence associated with this pausing, called the pause button, closely matches the sequences that bind to two subunits of TFIID (TAF6 and TAF9; Kadonaga, 2012). Consequently, TAF6 and TAF9 might be involved in pausing transcription, and if so, the variant TAF9B could play a similar role at motor neuron genes.

Molecular basis of transcription pausing

Jeffrey W. Roberts
Science 344, 1226 (2014);

During RNA synthesis, RNA polymerase moves erratically along DNA, frequently
resting as it produces an RNA copy of the DNA sequence. Such pausing helps coordinate the appearance of a transcript with its utilization by cellular processes; to this end,

  • the movement of RNA polymerase is modulated by mechanisms that determine its rate. For example,
  • pausing is critical to regulatory activities of the enzyme such as the termination of transcription. It is also
  • essential during early modifications of eukaryotic RNA polymerase II that activate the enzyme for elongation.


Two reports analyzing transcription pausing on a global scale in Escherichia coli, by Larson et al. ( 1) and by Vvedenskaya et al. ( 2) on page 1285 of this issue, suggest


  • new functions of pausing and important aspects of its molecular basis.


The studies of Larson et al. and Vvedenskaya et al. follow decades of analysis of

bacterial transcription that has illuminated the molecular basis of polymerase pausing

events that serve critical regulatory functions.


A transcription pause specified by the DNA sequence synchronizes the translation of RNA into protein


  • with the transcription of leader regions of operons (groups of genes transcribed together) for amino acid biosynthesis;


  • this coordination controls amino acid synthesis in response to amino acid availability ( 3).

A protein induced pause occurs when the E. coli initiation factor σ70 restrains RNA polymerase by binding a second occurrence of the “–10” promoter element.


This paused polymerase provides a structure for engaging a transcription antiterminator (the bacteriophage λ Q protein) ( 4) that, in turn, inhibits transcription

pauses, including those essential for transcription termination.


Biochemical and structural analyses have identified an endpoint of the pausing process called the “elemental pause” in which the catalytic structure in the active site is distorted,


  • preventing further nucleotide addition ( 7).


The elemental paused state also involves distinct


  • conformational changes in the polymerase that may favor transcription termination
  • and allow the his and related pauses to be stabilized by RNA hairpins ( 8).

A consensus sequence for ubiquitous pauses was identified, with two important elements:


  • a preference for pyrimidine [mostly cytosine (C)] at the newly formed RNA end
  • followed by G to be incorporated next—just as found for the his pause; and a preference for G at position –10 of the RNA (10 nucleotides before the 3’ end)



Polymerase, paused

Polymerase, paused

Polymerase, paused. During transcription, RNA exists in two states as RNA polymerase progresses: pretranslocated, just after the addition of the last nucleotide [here, cytosine (C)];

and posttranslocated, after all nucleic acids have shifted in register by one nucleotide relative

to the enzyme, exposing the active site for binding of the next substrate molecule [here, guanine (G)]. The pretranslocated state is dominant in the pause. The critical G-C base (RNA-DNA) pair at position –10 in the pretranslocated state and the nontemplate DNA strand G bound in the

polymerase in the posttranslocated state are marked with an asterisk.
Binding of G at position 􀀀1 to CRE only occurs in the posttranslocated state, which would thus

be favored over the pretranslocated state. Hence, if G binding inhibits pausing, then the rate-limiting paused structure must be in the pretranslocated state (a conclusion also made by Larson et al. from biochemical experiments).
This is an important insight into the sequence of protein–nucleic acid interactions that occur in pausing. Vvedenskaya et al. suggest that the actual role of the G binding site is to promote translocation and thus

inhibit pausing, to smooth out adventitious pauses in genomic DNA.
The studies by Larson et al. and Vvedenskaya et al. provide a refined and detailed analysis of DNA sequence–induced transcription pausing.
Processive Antitermination

Robert A. Weisberg1* and Max E. Gottesman2

Section on Microbial Genetics, Laboratory of Molecular Genetics, National Institute of Child Health and

Human Development, National Institutes of Health, Bethesda, Maryland 20892-2785,1 and

Institute of Cancer Research, Columbia University, New York, New York 100322

Journal Of Bacteriology, Jan. 1999; 181(2): 359–367.
After initiating synthesis of RNA at a promoter, RNA polymerase (RNAP) normally continues to elongate the transcript until it reaches a termination site. Important elements of termination sites are transcribed before polymerase translocation stops, and the resulting RNA is an active element of the termination pathway. Nascent transcripts of intrinsic sites can halt transcription without the assistance of additional factors, and

those of Rho-dependent sites recruit the Rho termination protein to the elongation complex. In both cases, RNAP, the transcript, and the template dissociate (reviewed in references 76 and 80).


Termination is rarely, if ever, completely efficient, and the expression of downstream genes can be controlled by altering the efficiency of terminator readthrough. Two distinct mechanisms of elongation control have been reported for bacterial RNA polymerases. In one, exemplified by attenuation of the his and trp operons of Salmonella typhimurium and Escherichia coli, respectively,

  • a single terminator is inactivated by interaction with an upstream sequence in the transcript, with a terminator-specific protein, or with a translating ribosome that follows closely behind RNAP (reviewed in references 35 and 104).

In a second, whose prototype is antitermination of phage l early transcription,

  • polymerase is stably modified to a terminator-resistant form after it leaves the promoter.

In this case, the modified enzyme not only transcribes through sequential downstream terminators,

  • but also it is less sensitive to the pause sites that normally delay transcript elongation.

Both pathways are widespread in nature, but in this minireview we consider only the second,

  • known as processive antitermination
    (for previous reviews, see references 22, 23, 27, and 32).

The recent explosive growth in our understanding of transcription elongation (reviewed in references 57, 96, and 99) make this an especially appropriate time to survey regulatory elements that target the transcription elongation complex.

Antitermination in l is induced by two quite distinct mechanisms.

  • the result of interaction between l N protein and its targets in the early phage transcripts,
  • an interaction between the l Q protein and its target in the late phage promoter.

We describe the N mechanism first. Lambda N, a small basic protein of the arginine- rich motif (ARM) (Fig. 1) family of RNA binding proteins, binds to a 15-nucleotide (nt) stem-loop called BOXB (17) (Fig. 2).


FIG. 1. [not shown] (A) Alignment of phage N proteins and the HK022 Nun protein. The color groupings reflect the frequency of amino acid substitutions in evolutionarily related protein domains: an amino acid is more likely to be replaced by one in the same color group than by one in a different color group in related proteins (34).

The amino-proximal ARM regions were aligned by eye and according to the structures of the P22 and l ARMs complexed to their cognate nut sites (see text and Fig. 2), and the remainder of the proteins was aligned by ClustalW (38). The dots indicate gaps introduced to improve the alignment. Aside from the ARM regions, the

proteins fall into three very distantly related (or unrelated) families: (i) l and phage 21; (ii) P22, phage L, and HK97; and (iii) HK022 Nun.


FIG. 2. [not shown] BOXA and BOXB RNAs and their interaction with the ARM of their cognate N proteins. The amino acid-nucleotide interactions are shown to the left except for BOXB of phage 21, for which the structure of the complex is unknown. The sequences of BOXA and BOXA-BOXB spacer are shown to the right. The dots

to the left and right of the spacer sequences are for alignment. (A) l N-ARM-BOXB complex (adapted from reference 48 with permission of the publisher). Open circles, pentagons, and rectangles represent phosphates, riboses, and bases, respectively. Watson-Crick base pairs (????) are indicated. The zigzag line denotes a sheared

G z A base pair. Open circles, open rectangles, and arrowheads depict ionic, hydrophobic, and hydrogen-bonding interactions, respectively. Guanine-11, indicated by a bold rectangle, is extruded from the BOXB loop (see text). (B) P22 N-ARM-BOXB complex (adapted from reference 15 with permission of the publisher). Open

circles, pentagons, rectangles, and ovals represent phosphates, riboses, bases, and amino acids, respectively. The solid pentagons indicate riboses with a C29-endo pucker.

Base stacking ( ), intermolecular hydrogen bonding or electrostatic interactions (,—–), intermolecular hydrophobic or van der Waals interactions (4), intramolecular hydrogen bonds (– – – –) and Watson-Crick base pairs (?????) are indicated. Cytosine-11 is extruded from the loop (see text). Note that the amino-terminal amino acid

residue in the complex corresponds to Asn-14 in the complete protein (Fig. 1), and the displayed amino acids are numbered accordingly. (C) NUTL site of phage 21. The arrows indicate the inverted sequence repeats of BOXB.


FIG. 3. [not skown] HK022 put sites and folded PUT RNAs. (A) Alignment of putL and putR (43). The numbers give distances from the start sites of the PL and PR promoters, respectively, and the pairs of arrows indicate inverted sequence repeats. (B) Folded PUTL and PUTR RNAs. The structures, which were generated by energy

minimization as described (43), have been partially confirmed by genetic and biochemical studies (7, 43).
The active bacterial elongation complex consists of

  • core RNAP,
  • template, and
  • RNA product.

The 39 end of the RNA

  • is engaged in the active site of the enzyme,
  • The following ;8 nt are hybridized to the template strand of the DNA, and
  • the next ;9 nt remain closely associated with RNAP (64).
  • About 17 nt of the nontemplate DNA strand are separated from the template strand in the transcription bubble.

Elongation complexes can also contain NusA and/or NusG. These proteins, which

  • increase the stability of the N-mediated antitermination complex (see above),
  • have different effects on elongation.
  • NusA decreases and NusG increases the elongation rate, and
  • both proteins alter termination efficiency in a terminator-specific manner (13, 14, 86; see reference 76).

An elongation complex, unless located at a terminator, is extraordinarily stable,

  • even when translocation is prevented by removal of substrates.

Recent observations suggest that this stability depends mainly on

  • interactions between RNAP and the RNA-DNA hybrid as well as
  • between polymerase and the downstream duplex DNA template (63, 87).

Nascent RNA emerging from the hybrid region and upstream duplex DNA

  • do not appear to be required.

The strength of the RNA-DNA hybrid is believed to

  • assure the lateral stability of the complex.


Reducing the strength of the RNA-DNA bonds, for example

  • by incorporation of nucleotide analogs,
  • favors backsliding of RNAP on the template, with consequent
  • disengagement of the 39 RNA end from the active site, and
  • concerted retreat of the RNA-DNA hybrid region from the 39 end (65).

Such a disengaged complex retains its resistance to dissociation and

  • is capable of resuming elongation if the original or a newly created 39 end reengages with the active site (10, 44, 45, 65, 71, 95).

Intrinsic terminators consist of a guanine- and cytosine-rich RNA hairpin stem

  • immediately followed by a short uracil-rich segment
  • within which termination can occur.


If termination does not occur at this point,

  • polymerase continues to elongate the transcript with normal processivity
  • until it reaches the next terminator.

Neither the stem nor the uracil-rich segment

  • is sufficient for termination, although
  • either can transiently slow elongation.

The weakness of base pairing between rU and dA

  • destabilizes the RNA-DNA hybrid in the uracil-rich segment, and
  • this probably contributes to termination.

Formation of the hairpin stem as nascent terminator RNA emerges from polymerase

  • destabilizes the RNA-DNA hybrid and
  • interrupts contacts between the emerging nascent RNA and RNAP (62a).

It might also interfere with the stabilizing interactions between

  • RNAP and the hybrid or those between RNAP and
  • the downstream region of the template.

Cross-linking of nucleic acid to RNAP suggests that

  • both the downstream DNA and the nascent RNA
  • that emerges from the hybrid region, and
  • within which the terminator hairpin might form,
  • are located close to the same regions of the enzyme (64).

Conversely, modifications that render RNAP termination resistant

  • could prevent the terminator stem from destabilizing one or more of these targets,
  • at least while the 39 end of the RNA is within the uracil rich segment of the terminator.

The l N and Q proteins and HK022 PUT RNA

  • also suppress Rho-dependent terminators (43a, 79, 103) which,
  • in contrast to intrinsic terminators, lack a precisely determined termination point.

Rho is an RNA-dependent ATPase that binds to cytosine-rich, unstructured regions in nascent RNA and acts preferentially

  • to terminate elongation complexes that are paused at nearby downstream sites
    (19, 29, 46, 47, 59, 60).

Rho possesses RNA-DNA helicase activity, and this activity is directional,

  • unwinding DNA paired to the 39 end of the RNA molecule (11, 90).
  • This corresponds to the location of the hybrid and of RNAP
    in an active ternary elongation complex.

The ability of antiterminators to suppress Rho-dependent and -independent terminators

  • suggests that they prevent a step that is common to both classes.

Given the helicase activity of Rho, a likely candidate for this step is disruption of the RNA-DNA

hybrid. However, other candidates, such as destabilization of RNAP-template or RNAP-hybrid interactions, are also plausible.

Alternatively, the ability of N, Q, and PUT to suppress RNAP pausing (31, 43, 54, 74)

  • suggests that they prevent Rho-dependent termination
  • by accelerating polymerase away from Rho bound at upstream RNA sites.

This explanation raises the problem of why NusG,

  • which also accelerates polymerase,
  • enhances rather than suppresses Rho-dependent termination (see above).

Clearly, the molecular details of processive antitermination remain poorly understood despite the 30 years that have elapsed since its discovery.



System wide analyses have underestimated protein abundances and the importance of transcription in mammals


Jingyi Jessica Li1, 2, Peter J Bickel1 and Mark D Biggin3

1Department of Statistics, University of California, Berkeley, CA, USA

2Departments of Statistics and Human Genetics, University of California, Los Angeles, CA, USA

3Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

Academic editor – Barbara Engelhardt

Distributed under Creative-Commons CC-0


Large scale surveys in mammalian tissue culture cells suggest that the protein ex-

pressed at the median abundance is present at 8,000_16,000 molecules per cell and

that differences in mRNA expression between genes explain only 10_40% of the dif-

ferences in protein levels. We find, however, that these surveys have significantly un-

derestimated protein abundances and the relative importance of transcription.

Using individual measurements for 61 housekeeping proteins to rescale whole proteome

data from Schwanhausser et al. (2011), we find that the median protein detected is

expressed at 170,000 molecules per cell and that our corrected protein abundance

estimates show a higher correlation with mRNA abundances than do the uncorrected

protein data. In addition, we estimated the impact of further errors in mRNA and

protein abundances using direct experimental measurements of these errors.

The resulting analysis suggests that mRNA levels explain at least

  • 56% of the differences in protein abundance for the 4,212 genes

detected by Schwanhausser et al. (2011), though because one major source of error

could not be estimated the true percent contribution should be higher.
We also employed a second, independent strategy to

  • determine the contribution of mRNA levels to protein expression.

The variance in translation rates directly measured by ribosome profiling is only 12%

of that inferred by Schwanhausser et al. (2011), and

  • the measured and inferred translation rates correlate poorly (R2 D 13).

Based on this, our second strategy suggests that

  • mRNA levels explain _81% of the variance in protein levels.

We also determined the percent contributions of

  • transcription,
  • RNA degradation,
  • translation
  • and protein degradation

to the variance in protein abundances using both of our strategies.

While the magnitudes of the two estimates vary, they both suggest that

  • transcription plays a more important role than the earlier studies implied and
  • translation a much smaller role.

Finally, the above estimates only apply to those genes whose mRNA and protein expression was detected. Based on a detailed analysis by Hebenstreit et al. (2012), we estimate that approximately

  • 40% of genes in a given cell within a population express no mRNA.

Since there can be no translation in the absence of mRNA, we argue that

  • differences in translation rates can play no role in determining the expression levels for the _40% of genes that are non-expressed.

Subjects Bioinformatics, Computational Biology

Keywords Transcription, Translation, Mass spectrometry, Gene expression, Protein abundance

How to cite this article Li et al. (2014), System wide analyses have underestimated protein abundances and the importance of transcription in mammals. PeerJ 2:e270;



Assessing quality and completeness of human transcriptional regulatory pathways on a genome-wide scale

Evgeny Shmelkov1,2, Zuojian Tang2, Iannis Aifantis3, Alexander Statnikov2,4

Shmelkov et al. Biology Direct 2011, 6:15


Background: Pathway databases are becoming increasingly important and almost omnipresent in most types of biological and translational research. However, little is known about the quality and completeness of pathways stored in these databases. The present study conducts a comprehensive assessment of transcriptional regulatory pathways in humans for seven well-studied transcription factors: MYC, NOTCH1, BCL6, TP53, AR, STAT1, and RELA.

The employed benchmarking methodology first

  • involves integrating genome-wide binding with functional gene expression data to derive direct targets of transcription factors.
  • Then the lists of experimentally obtained direct targets are compared with relevant lists of transcriptional targets from 10 commonly used pathway databases.

Results: The results of this study show that for the majority of pathway databases,

  • the overlap between experimentally obtained target genes and targets reported in transcriptional regulatory pathway databases is surprisingly small and often is not statistically significant.

The only exception is MetaCore pathway database which yields statistically significant intersection with experimental results in 84% cases. Additionally, we suggest that

  • the lists of experimentally derived direct targets obtained in this study can be used to reveal new biological insight in transcriptional regulation and
  • suggest novel putative therapeutic targets in cancer.

Conclusions: Our study opens a debate on validity of using many popular pathway databases to obtain transcriptional regulatory targets. We conclude that the choice of pathway databases should be informed by solid scientific evidence and rigorous empirical evaluation.


Illustration of statistical methodology

Illustration of statistical methodology


Figure 2 Illustration of statistical methodology for comparison

between a gold-standard and a pathway database


Additional material

Additional file 1: Supplementary Information. Table S1: Functional gene expression data. Table 2: Transcription factor-DNA binding data. Table S3: Most confident direct transcriptional targets of each of the four transcription factors. These targets were obtained by overlapping several gold-standards obtained with different datasets for the same transcription factor. Table S4: Genes directly regulated by two or more of the three transcription factors: MYC, NOTCH1, and RELA. Figure S1: Comparison of gene sets of transcriptional targets derived from ten different pathway databases by Jaccard index. In case, where Jaccard index of an overlap could not be determined due to comparison of two empty gene lists, we assigned value 0. Cells are colored according to the Jaccard index, from white (Jaccard index equal to 0) to dark-orange (Jaccard index equal to 1). Each sub-figure gives results for a different transcription factor: (a) AR, (b) BCL6, (c) MYC, (d) NOTCH1, (e) RELA, (f) STAT1, (g) TP53


Cite this article as: Shmelkov et al.: Assessing quality and completeness of human transcriptional regulatory pathways on a genome-wide scale. Biology Direct 2011 6:15



The Functional Consequences of Variation in Transcription Factor Binding
Darren A. Cusanovich1, Bryan Pavlovic1,2, Jonathan K. Pritchard1,2,3*, Yoav Gilad1*

1 Department of Human Genetics, University of Chicago, 2 Howard Hughes Medical Institute, University of Chicago, Chicago,

Illinois, 3 Departments of Genetics and Biology and Howard Hughes Medical Institute, Stanford University, Stanford, California,


One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly play an important role in determining gene expression outputs, yet the regulatory logic underlying functional transcription factor binding is poorly understood. Many studies have focused on characterizing the genomic locations of TF binding, yet it is unclear to what extent TF binding at any specific locus has functional consequences with respect to gene expression output.

To evaluate the context of functional TF binding we knocked down

  • 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line.
  • We identified genes whose expression was affected by the knockdowns.
  • We intersected the gene expression data with transcription factor binding data
    (based on ChIP-seq and DNase-seq) within 10 kb of the transcription start sites

This combination of data allowed us to infer functional TF binding.

  • we found that only a small subset of genes bound by a factor were differentially expressed following the knockdown of that factor, suggesting that
  • most interactions between TF and chromatin do not result in measurable changes in gene expression levels of putative target genes.
  • functional TF binding is enriched in regulatory elements that harbor
    • a large number of TF binding sites,
    • at sites with predicted higher binding affinity, and
    • at sites that are enriched in genomic regions annotated as ‘‘active enhancers.’’

Author Summary

An important question in genomics is to understand how a class of proteins called ‘‘transcription factors’’ controls the expression level of other genes in the genome in a cell type-specific manner – a process that is essential to human development. One major approach to this problem is to

study where these transcription factors bind in the genome, but this does not tell us about the effect of that binding on gene expression levels and it is generally accepted that much of the binding does not strongly influence gene expression. To address this issue, we artificially reduced the concentration of 59 different transcription factors in the cell and then examined which genes were impacted by the reduced transcription factor level. Our results implicate some attributes that might

influence what binding is functional, but they also suggest that a simple model of functional vs. non-functional binding may not suffice.

Citation: Cusanovich DA, Pavlovic B, Pritchard JK, Gilad Y (2014) The Functional Consequences of Variation in Transcription Factor Binding. PLoS Genet 10(3):e1004226.

Editor: Yitzhak Pilpel, Weizmann Institute of Science, Israel



Effect sizes for differentially expressed genes

Effect sizes for differentially expressed genes

Figure 2. Effect sizes for differentially expressed genes.

Boxplots of absolute Log2(fold-change) between knockdown arrays

and control arrays for all genes identified as differentially expressed in

each experiment. Outliers are not plotted. The gray bar indicates the

interquartile range across all genes differentially expressed in all

knockdowns. Boxplots are ordered by the number of genes differentially

expressed in each experiment. Outliers were not plotted.



Intersecting binding data and expression data for each knockdown

Intersecting binding data and expression data for each knockdown






Figure 3. Intersecting binding data and expression data for each knockdown. (a) Example Venn diagrams showing the overlap of binding and differential expression for the knockdowns of HCST and IRF4 (the same genes as in Figure 1). (b) Boxplot summarizing the distribution of the fraction of all expressed genes that are bound by the targeted gene or downstream factors. (c) Boxplot summarizing the distribution of the fraction of

bound genes that are classified as differentially expressed, using an FDR of either 5% or 20%.


Degree of binding correlated with function

Degree of binding correlated with function


Figure 4. Degree of binding correlated with function. Boxplots comparing (a) the number of sites bound, and (b) the number of differentially expressed transcription factors binding events near functionally or non-functionally bound genes. We considered binding for siRNA-targeted factor and any factor differentially expressed in the knockdown. (c) Focusing only on genes differentially expressed in common between each pairwise set of knockdowns we tested for enrichments of functional binding (y-axis). Pairwise comparisons between knock-down experiments were binned by the fraction of differentially expressed transcription factors in common between the two experiments. For these boxplots, outliers were not plotted.


Distribution of functional binding about the TSS

Distribution of functional binding about the TSS


Figure 5. Distribution of functional binding about the TSS. (a) A density plot of the distribution of bound sites within 10 kb of the TSS for both functional and non-functional genes. Inset is a zoom-in of the region +/21 kb from the TSS (b) Boxplots comparing the distances from the TSS to the binding sites for functionally bound genes and non-functionally bound genes. For the boxplots, 0.001 was added before log10 transforming

the distances and outliers were not plotted.


Magnitude and direction of differential expression after knockdown

Magnitude and direction of differential expression after knockdown



Figure 6. Magnitude and direction of differential expression after knockdown. (a) Density plot of all Log2(fold-changes) between the knockdown arrays and controls for genes that are differentially expressed at 5% FDR in one of the knockdown experiments as well as bound by the targeted transcription factor. (b) Plot of the fraction of differentially expressed putative direct targets that were up-regulated in each of the knockdown experiments.


To test whether the number of paralogs or the degree of similarity with the closest paralog for each transcription factor knocked down might influence the number of genes differentially expressed in our experiments, we obtained definitions of paralogy and the calculations of percent identity for 29 different factors from Ensembl’s BioMart ( [31]. We used genome build GRCh37.p13.

For each gene, we counted the number of paralogs classified as a ‘‘within_species_paralog’’. After selecting only genes considered a ‘‘within_species_paralog’’, we also assigned the maximum percent identity as the closest paralog.

To evaluate the effect that an independent assignment of target genes to regulatory regions might have on our analyses, we used the definition of target genes defined by Thurman et al. (…)

which use correlations in DNase hypersensitivity between distal and proximal regulatory regions across different cell types to link distal elements to putative target genes [38].

We intersected the midpoints of our called binding events (defined above) with these regulatory elements in order to assign our binding events to specific target genes and then re-analyzed the overlap between

binding and differential expression in our experiments.

PLOS Genetics 6 Mar 2014; 10 (3), e1004226




The essential biology of the endoplasmic reticulum stress response

for structural and computational biologists

Sadao Wakabayashia, Hiderou Yoshidaa,*

aDepartment of Molecular Biochemistry, Graduate School of Life Science,

University of Hyogo, Hyogo 678-1297, Japan

CSBJ Mar 2013; 6(7), e201303010,


Abstract: The endoplasmic reticulum (ER) stress response is a cytoprotective mechanism that maintains homeostasis of the ER by

  • upregulating the capacity of the ER in accordance with cellular demands.

If the ER stress response cannot function correctly, because of reasons such as aging, genetic mutation or environmental stress,

  • unfolded proteins accumulate in the ER and cause ER stress-induced apoptosis,
  • resulting in the onset of folding diseases,
    • including Alzheimer’s disease and diabetes mellitus.

Although the mechanism of the ER stress response has been analyzed extensively by biochemists, cell biologists and molecular biologists, many aspects remain to be elucidated. For example,

  • it is unclear how sensor molecules detect ER stress, or
  • how cells choose the two opposite cell fates
    (survival or apoptosis) during the ER stress response.

To resolve these critical issues, structural and computational approaches will be indispensable, although the mechanism of the ER stress response is complicated and difficult to understand holistically at a glance. Here, we provide a concise introduction to the mammalian ER stress response for structural and computational biologists.

The basic mechanism of the mammalian ER stress response

The mammalian ER stress response consists of three pathways: the ATF6, IRE1 and PERK pathways, of which the main functions are

  • augmentation of folding and ERAD capacity, and
  • translational attenuation, respectively.

Although these response pathways cross-talk with each other and have several branched subpathways, we focus on the main pathways in this section.

  • The ATF6 pathway regulates the transcriptional induction of ER chaperone genes
  • pATF6(P) is a sensor molecule comprising a type II transmembrane protein residing on the ER membrane (Figure 2).

When pATF6(P) detects ER stress,

  • the protein is transported to the Golgi apparatus through vesicular transport in a COP-II vesicle
  • and is sequentially cleaved by two proteases residing in the Golgi,
    • namely site 1 protease (S1P) and site 2 protease (S2P)

The cytoplasmic portion of pATF6(P) (pATF6(N)) is

  1. released from the Golgi membrane,
  2. translocates into the nucleus,
  3. binds to an enhancer element called the ER stress response element (ERSE),
  4. and activates the transcription of ER chaperone genes,
  • including BiP, GRP94, calreticulin and protein disulfide isomerase (PDI)

The consensus nucleotide sequence of ERSE is CCAAT(N9)CCACG, and pATF6(N) recognizes both the CCACG portion and another transcription factor NF-Y,

  • which binds to the CCAAT portion

NF-Y is a general transcription factor required for

  • the transcription of various human genes


Figure 2. The ATF6 pathway. The sensor molecule pATF6(P) located on the ER membrane is transported to the Golgi apparatus by transport vesicles in response to ER stress. In the Golgi apparatus, pATF6(P) is sequentially cleaved by two proteases, S1P and S2P, resulting in release of the cytoplasmic portion pATF6(N) from the ER membrane. pATF6(N) translocates into the nucleus and activates transcription of ER chaperone genes through binding to the cis-acting enhancer ERSE.


Figure 3. The IRE1 pathway. In normal growth conditions, the sensor molecule IRE1 is an inactive monomer, whereas IRE1 forms an active oligomer in response to ER stress. Activated IRE1 converts unspliced XBP1 mRNA to mature mRNA by the cytoplasmic mRNA splicing. From mature XBP1 mRNA, an active transcription factor pXBP1(S) is translated and activates the transcription of ERAD genes through binding to the enhancer UPRE.


Figure 4. The PERK pathway. When PERK detects unfolded proteins in the ER, PERK phosphorylates eIF2α, resulting in translational attenuation and translational induction of ATF4. ATF4 activates the transcription of target genes encoding translation factors, anti-oxidation factors and a transcription factor CHOP. Other kinases such as PKR, GCN2 and HRI also phosphorylate eIF2α, and phosphorylated eIF2α is dephosphorylated by CReP, PP1C-GADD34 and p58IPK


Figure 7. Three functions of pXBP1(U). pXBP1(U) translated from XBP1(U) mRNA binds to pXBP1(S) and enhances its degradation. The CTR region of pXBP1(U) interacts with the ribosome tunnel and slows translation, while the HR2 region anchors XBP1(U) mRNA to the ER membrane, in order to enhance splicing of XBP1(U) mRNA by IRE1.


Figure 8. Major pathways of ER stress-induced apoptosis. ER stress induces apoptosis through various pathways, including transcriptional induction of CHOP by the PERK and ATF6 pathways, the IRE1-TRAF2 pathway and the caspase-12 pathway.

If cells are damaged by strong and sustained ER stress that they cannot deal with and ER stress still persists and hampers the survival of the organism, the ER stress response activates the apoptotic pathways and disposes of damaged cells from the body.

Computational simulation of response pathways to analyze the decision mechanism that determines cell fate (survival or apoptosis) provides a valuable analysis tool, although there have been few such studies to date.

Read Full Post »

Larry H. Bernstein, MD, FCAP, Curator! Are fruitflies like us?

We are following closely the developments in genomics that have had a progression since the Double-Helix dogma served the Nobel Prize to Watson and Crick, and that achievement led to the completion of a provisional Human Genome at the birth of the 21st century.  Since then there has been exploration of cellular regulation, signaling pathways, and protein-protein as well as protein membrane interactions in eukaryotes.  But we can go further back prior to the double-helix and remind ourselves of the huge contributions that led up to the double helix.  This was a time of great research that set the tone for what is now called molecular biology.  We associate the work with the genetic studies of Thomas Hunt Morgan on the fruit fly.  There may yet be a new chapter that is stradling the gap between DNA, RNA and transcription turning toward a deeper understanding of gene expression and organ specificities.  Is it a new beginning?  There is certainly going to be a deeper understanding of the several roles of RNA as well as proteins.


The Gateway Opens

Genes, Chromosomes, and the Origins of Modern Biology
Eric R. Kandel, MD
2000 recipent of Nobel Prize in Medicine

University Professor & Kavli Professor of Brain Science,
Co-director, Mind Brain Behavior Initiative
Director, The Kavli Institute for Brain Science
Senior Investigator, Howard Hughes Medical Institute
Columnia University

When future historians turn to examine the major intellectual accomplishments of the twentieth century, they will undoubtedly give a special place to the extraordinary achievements in biology, achievements that have revolutionized our understanding of life’s processes and of disease. Important intimations of what was to happen in biology were already apparent in the second half of the nineteenth century. Darwin had delineated the evolution of animal species, Mendel had discovered some basic rules about inheritance, and Weissman, Roux, Driesch, de Vries, and other embryologists were beginning to decipher how an organism develops from a single cell. What was lacking at the end of the nineteenth century, however, was an overarching sense of how these bold advances were related to one another.

The insight that unified these three fields- heredity, evolution, and development- and set biology on the course toward its current success came only at the beginning of the twentieth century. It derived from the discovery that the gene, localized to specific positions on the chromosome, was at once the unit of Mendelian heredity, the driving force for Darwinian evolution, and the control switch for development. This remarkable discovery can be traced directly to one person and to one institution: Thomas Hunt Morgan and Columbia University. Much as Darwin’s insights into the evolution of animal species first gave coherence to nineteenth-century biology as a descriptive science, Morgan’s findings about genes and their location on chromosomes helped transform biology into an experimental science.

aware that abstract thinking, remote from, and even antagonistic to the study of nature, leads easily into dogma, taboos and fettering of free thinking because it does not carry its own corrective, the recourse to factual evidence. The scientist, therefore, with all respect for the many facets of the human mind, is more impressed by the revolutions in thinking brought about by great factual discoveries, which by their very nature lead to generalizations which change at once the outlook of many, if not all, lines of thought.”

. . . . the rise and development of genetics to mature age is another instance of an all-comprising and all-affecting generalization based upon an overwhelming body of integrated facts, . . . [and] will rank in the history of science with such other great events ..”

Richard B. Goldschmidt, The Impact of Genetics Upon Science (1950)

Even more important, Morgan’s discoveries made it possible to address a series of questions regarding the function and structure of genes. What is their chemical nature? How do genes duplicate themselves? What goes wrong when genes mutate? How do genes provide the basis for understanding genetic disease? How do genes determine the properties of cells, the development of organisms, and the course of evolution?

Thomas Hunt Morgan

Thomas Hunt Morgan





Eric Kandel

Eric Kandel


New Study of Fruit Fly Genome Reveals Complexity of RNA and Provides a Model for Studying Mechanisms for Hereditary Diseases in Humans

July 7, 2014

This investigation of the fruit fly’s transcriptome—the complete collection of the genome’s RNA—unearthed thousands of new genes, transcripts, and proteins

Scientists have teased another level of information out of the genome. This time, the new insights were developed from studies of the fruit fly’s transcriptome. This knowledge will give pathologists another channel of information that may be useful in developing assays to support more precise diagnosis and therapeutic decisions.

The findings were published in a recent issue of Nature. The study focused on the transcriptome—a complete collection of the genome’s RNA—of the common fruit fly−Drosophila melangogaster.

Why Studies of the Fruit Fly Are Useful

The fruit fly has been used as a genetics model to study human genetics for more than a 100 years. Not only are they easy to care for and work with, but they share 75% of the same genes as humans. Today, the fruit fly genome has emerged as a critical tool tor understanding human biology and disease, by providing an understanding of genes and life processes that are conserved over extensive evolutionary changes.

The research consortium included 41 researchers from 11 universities and institutes that are members of the National Human Genome Research Institute’s Model Organism Encyclopedia of DNA Elements, called modENCODE for short. This project used state-of-the-art gene sequencing to study all of the expressed RNAs produced by a genome in greater detail than ever before accomplished.

RNA Sequenced in Diverse Tissues at Different Stages of Development

RNA was sequenced at different stages of development, in diverse tissues, in cells growing in culture, and in flies stressed by environmental contaminants, stated a IU press release issued by Indiana University Bloomington (IUB).

The modENCODE study revealed that the fruit fly genome is far more complex than previously suspected. These new findings suggest that this also may be true for the genomes of higher animals. Specifically, the researchers found that:

  • a small set of genes in the nervous system is responsible for much of the complexity;
  • long regulatory and antisense RNA (asRNA), a single-stranded RNA complementary to a messenger RNA transcribed within a cell, are prominent during gonadal development;
  • splicing factors, proteins involved in controlling maturation of RNAs, are themselves spliced in complex ways; and,
  • the fruit fly transcriptome undergoes major changes in response toenvironmental stressors.

How Study of Fruit Fly RNA Benefits Human Genome Research

“The modENCODE work is intended to provide a new baseline for research using Drosophila,” declared Peter Cherbas, Ph.D., an IUB Professor Emeritus of Biology and one of 10 IUB researchers who served as co-authors of the study. “The goal is to provide researchers working on particular processes with much of the detailed background information they would otherwise need to collect for themselves.

Click here for photo
Peter Cherbas, Ph.D. (pictured), Professor Emeritus of Biology at Indiana University Bloomington, says that the modENCORE study of the fruit fly’s complete RNA answered a lot of questions about the genome of organisms, but raised even more questions that science will want to answer. (Photo copyright Indiana University Bloomington.)

“As usual in science, we’ve answered a number of questions and raised even more,” observed Cherbas. “For example, we identified 1,468 new genes, of which 536 were found to reside in previously uncharacterized gene-free zones.”

“We think these results could influence gene regulation research in all animals,” added Thom Kaufman, Ph.D., IUB Distinguished Professor of Biology who also co-authored the study. “This exhaustive study also identified a number of phenomena previously reported only in mammals, and that alone is really telling about the versatility of Drosophila melanogaster as a model organism. The new work provides a number of new potential uses for this powerful model system,” he stressed.

Click here for photo
Thom Kaufman, Ph.D. (pictured), Indiana University Bloomington Distinguished Professor of Biology, says that the modENCORE study provides a powerful model for studying gene regulation in all organisms. (Photo copyright Indiana University Bloomington.)

Impact of Environmental Stressors on Gene Expression

Both Kaufman and Cherbas cited perturbation experiments that identified genes and transcripts. The new genes were identified after subjecting adult fruit flies to heat and cold shock, then exposing them to heavy metals, caffeine and the herbicide paraquat. Fruit fly larvae were treated with heavy metals, caffeine, ethanol, or the insecticide rotenone.

These environmental stressors generated small changes in the expression level of thousands of genes. One treatment experiment resulted in four newly modeled genes being expressed altogether differently, noted the researchers. Perturbation experiments, in fact, revealed a total of 5,249 transcript models for 811 genes.

In fact, the findings from these perturbation experiments mirror similar findings made following the 2010 British Petroleum Deepwater Horizon oil spill in the Gulf of Mexico. Researchers studying the impact on marsh fishes found that, similar to the fruit flies, these fish responded to chronic hydrocarbon exposure with a number of expressions beyond the heat shock pathway. These expressions included the down regulation of genes encoding eggshell and yolk proteins.

The response overlap between species indicates that the modENCODE consortium may have identified a conserved metazoan [animal] stress response that enhances metabolism and suppresses genes involved in reproduction.

What This Means for Pathologists and Laboratory Professionals

This study is significant for pathologists and medical laboratory professionals because it peels away another layer of information encoded in DNA and RNA. The findings of this study also show how genomic knowledge is moving to the next level in the quest to understand the origins of disease.
—by Patricia Kirk


Study of complete RNA collection of fruit fly uncovers unprecedented complexity

IU plays key role in consortium; 1,468 new genes discovered March 17, 2014  

BLOOMINGTON, Ind. — Scientists from Indiana University are part of a consortium that has described the transcriptome of the fruit fly Drosophila melanogaster in unprecedented detail, identifying thousands of new genes, transcripts and proteins.

In the new work, published Sunday in the journal Nature, scientists studied the transcriptome — the complete collection of RNAs produced by a genome — at different stages of development, in diverse tissues, in cells growing in culture, and in flies stressed by environmental contaminants. To do so, they used contemporary sequencing technology to sequence all of the expressed RNAs in greater detail than ever before possible.

The paper shows that the Drosophila genome is far more complex than previously suspected and suggests that the same will be true of the genomes of other higher organisms. The paper also reports a number of novel, particular results: that a small set of genes used in the nervous system are responsible for a disproportionate level of complexity; that long regulatory and so-called “antisense” RNAs are especially prominent during gonadal development; that “splicing factors” (proteins that control the maturation of RNAs by splicing) are themselves spliced in complex ways; and that the Drosophila transcriptome undergoes large and interesting changes in response to environmental stresses.

The importance of Drosophila melanogaster as a model system cannot be overstated. Using it, the mechanisms of heredity were worked out about 100 years ago. Today, as biologists have developed increasing appreciation of how well genes and critical life processes are conserved over long evolutionary distances, flies have emerged as critical tools for understanding human biology and disease. Drosophila research is an area that has long had associations with IU, beginning with Nobel Laureate Herman J. Muller.

IU has 10 co-authors on the paper from the IU Bloomington College of Arts and Sciences’ Department of Biology and the university’s Center for Genomics and Bioinformatics. They are included among the 41 co-authors from 11 universities and institutes that are members of the National Human Genome Research Institute’s Model Organism Encyclopedia of DNA Elements project, or modENCODE. Among the IU co-authors are Professor Emeritus of Biology Peter Cherbas, who helped manage the expansive project, and Distinguished Professor of Biology Thom Kaufman, who helped oversee design of the project and the production of biological samples.

“The modENCODE work is intended to provide a new baseline for research using Drosophila,” Cherbas said. “The goal is to provide researchers working on particular processes with much of the detailed background information they would otherwise need to collect for themselves.

“As usual in science, we’ve answered a number of questions and raised even more. For example, we identified 1,468 new genes, of which 536 were found to reside in previously uncharacterized gene-free zones.”

“We think these results could influence gene regulation research in all animals,” Kaufman said. “This exhaustive study also identified a number of phenomena previously reported only in mammals, and that alone is really telling about the versatility of Drosophila melanogaster as a model organism. The new work provides a number of new potential uses for this powerful model system.”

An example they pointed to was the perturbation experiments that identified new genes and transcripts. New genes were identified in experiments where adults were challenged with heat shock, cold shock, exposure to heavy metals, the drug caffeine and the herbicide paraquat, while larvae were treated with heavy metals, caffeine, ethanol or the insecticide rotenone.

Those environmental stresses resulted in small changes in expression level at thousands of genes; and in one treatment, four newly modeled genes were expressed altogether differently. In total, 5,249 transcript models for 811 genes were revealed only under perturbed conditions.

As did the flies in this new research, scientists who studied the Deepwater Horizon incident in the Gulf of Mexico found that marsh fishes responding to chronic hydrocarbon exposure had a number of expressional responses beyond the heat shock pathway, including the down regulation of genes encoding eggshell and yolk proteins as did the flies. To see this response overlap across phyla means the consortium may have identified a conserved metazoan stress response involving enhanced metabolism and the suppression of genes involved in reproduction.

Indiana University co-authors with Cherbas and Kaufman were co-first author Robert Eisman, Justen Andrews, Lucy Cherbas, Brian D. Eads, David Miller, Keithanne Mockaitis, Johnny Roberts and Dayu Zhang. All were associated with the Department of Biology and/or the Center for Genomics and Bioinformatics.

“Diversity and dynamics of the Drosophila transcriptome,” published March 16 in the journal Nature, also included 31 other co-authors whose affiliations were with the University of California, Berkeley; Lawrence Berkeley National Laboratory; University of Connecticut Health Center; Cold Spring Harbor Laboratory; Sloan-Kettering Institute; National Institute of Diabetes and Digestive and Kidney Diseases; RIKEN Yokohama Institute (Japan); Harvard Medical School; and Howard Hughes Medical Institute.

Antisense RNA

From Wikipedia, the free encyclopedia

Antisense RNA (asRNA) is a single-stranded RNA that is complementary to a messenger RNA (mRNA) strand transcribed within a cell. Some authors have used the term micRNA (mRNA-interfering complementary RNA) to refer to these RNAs but it is not widely used.[1]

Antisense RNA may be introduced into a cell to inhibit translation of a complementary mRNA by base pairing to it and physically obstructing the translation machinery.[2] [3] This effect is therefore stoichiometric. An example of naturally occurring mRNA antisense mechanism is the hok/sok system of the E. coli R1 plasmid. Antisense RNA has long been thought of as a promising technique for disease therapy; the only such case to have reached the market is the drug fomivirsen. One commentator has characterized antisense RNA as one of “dozens of technologies that are gorgeous in concept, but exasperating in [commercialization]”.[4] Generally, antisense RNA still lack effective design, biological activity, and efficient route of administration.[5]

Historically, the effects of antisense RNA have often been confused with the effects of RNA interference (RNAi), a related process in which double-stranded RNA fragments called small interfering RNAs trigger catalytically mediated gene silencing, most typically by targeting the RNA-induced silencing complex (RISC) to bind to and degrade the mRNA. Attempts to genetically engineer transgenic plants to express antisense RNA instead activate the RNAi pathway, although the processes result in differing magnitudes of the same downstream effect; gene silencing. Well-known examples include the Flavr Savr tomato and two cultivars of ringspot-resistant papaya.[6][7]

Transcription of longer cis-antisense transcripts is a common phenomenon in the mammalian transcriptome.[8] Although the function of some cases have been described, such as the Zeb2/Sip1 antisense RNA, no general function has been elucidated. In the case of Zeb2/Sip1,[9] the antisense noncoding RNA is opposite the 5′ splice site of an intron in the 5’UTR of the Zeb2 mRNA. Expression of the antisense ncRNA prevents splicing of an intron that contains a ribosome entry site necessary for efficient expression of the Zeb2 protein. Transcription of long antisense ncRNAs is often concordant with the associated protein-coding gene,[10] but more detailed studies have revealed that the relative expression patterns of the mRNA and antisense ncRNA are complex.[11][12]



Histidine kinase-, DNA gyrase B-, and HSP90-like ATPase

Histidine kinase-, DNA gyrase B-, and HSP90-like ATPase


Structure of the N-terminal domain of the yeast Hsp90 chaperone

Structure of the N-terminal domain of the yeast Hsp90 chaperone



Pincer movement of Hsp90 coupled to the ATPase cycle. NTD = N-terminal domain, MD = middle domain, CTD = C-terminal domain.

Pincer movement of Hsp90 coupled to the ATPase cycle. NTD = N-terminal domain, MD = middle domain, CTD = C-terminal domain.
































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Introduction – The Evolution of Cancer Therapy and Cancer Research: How We Got Here?

Introduction – The Evolution of Cancer Therapy and Cancer Research: How We Got Here?

Author and Curator: Larry H Bernstein, MD, FCAP

The evolution of progress we have achieved in cancer research, diagnosis, and therapeutics has  originated from an emergence of scientific disciplines and the focus on cancer has been recent. We can imagine this from a historical perspective with respect to two observations. The first is that the oldest concepts of medicine lie with the anatomic dissection of animals and the repeated recurrence of war, pestilence, and plague throughout the middle ages, and including the renaissance.  In the awakening, architecture, arts, music, math, architecture and science that accompanied the invention of printing blossomed, a unique collaboration of individuals working in disparate disciplines occurred, and those who were privileged received an education, which led to exploration, and with it, colonialism.  This also led to the need to increasingly, if not without reprisal, questioning long-held church doctrines.

It was in Vienna that Rokitansky developed the discipline of pathology, and his student Semelweis identified an association between then unknown infection and childbirth fever. The extraordinary accomplishments of John Hunter in anatomy and surgery came during the twelve years war, and his student, Edward Jenner, observed the association between cowpox and smallpox resistance. The development of a nursing profession is associated with the work of Florence Nightengale during the Crimean War (at the same time as Leo Tolstoy). These events preceded the work of Pasteur, Metchnikoff, and Koch in developing a germ theory, although Semelweis had committed suicide by infecting himself with syphilis. The first decade of the Nobel Prize was dominated by discoveries in infectious disease and public health (Ronald Ross, Walter Reed) and we know that the Civil War in America saw an epidemic of Yellow Fever, and the Armed Services Medical Museum was endowed with a large repository of osteomyelitis specimens. We also recall that the Russian physician and playwriter, Anton Checkov, wrote about the conditions in prison camps.

But the pharmacopeia was about to open with the discoveries of insulin, antibiotics, vitamins, thyroid action (Mayo brothers pioneered thyroid surgery in the thyroid iodine-deficient midwest), and pitutitary and sex hormones (isolatation, crystal structure, and synthesis years later), and Karl Landsteiner’s discovery of red cell antigenic groups (but he also pioneered in discoveries in meningitis and poliomyelitis, and conceived of the term hapten) with the introduction of transfusion therapy that would lead to transplantation medicine.  The next phase would be heralded by the discovery of cancer, which was highlighted by the identification of leukemia by Rudolph Virchow, who cautioned about the limitations of microscopy. This period is highlighted by the classic work – “Microbe Hunters”.

John Hunter

John Hunter

Walter Reed

Walter Reed

Robert Koch

Robert Koch

goldberger 1916 Pellagra

goldberger 1916 Pellagra

Louis Pasteur

Louis Pasteur

A multidisciplinary approach has led us to a unique multidisciplinary or systems view of cancer, with different fields of study offering their unique expertise, contributions, and viewpoints on the etiology of cancer.  Diverse fields in immunology, biology, biochemistry, toxicology, molecular biology, virology, mathematics, social activism and policy, and engineering have made such important contributions to our understanding of cancer, that without cooperation among these diverse fields our knowledge of cancer would never had evolved as it has. In a series of posts “Heroes in Medical Research:” the work of researchers are highlighted as examples of how disparate scientific disciplines converged to produce seminal discoveries which propelled the cancer field, although, at the time, they seemed like serendipitous findings.  In the post Heroes in Medical Research: Barnett Rosenberg and the Discovery of Cisplatin (Translating Basic Research to the Clinic) discusses the seminal yet serendipitous discoveries by bacteriologist Dr. Barnett Rosenberg, which eventually led to the development of cisplatin, a staple of many chemotherapeutic regimens. Molecular biologist Dr. Robert Ting, working with soon-to-be Nobel Laureate virologist Dr. James Gallo on AIDS research and the associated Karposi’s sarcoma identified one of the first retroviral oncogenes, revolutionizing previous held misconceptions of the origins of cancer (described in Heroes in Medical Research: Dr. Robert Ting, Ph.D. and Retrovirus in AIDS and Cancer).   Located here will be a MONTAGE of PHOTOS of PEOPLE who made seminal discoveries and contributions in every field to cancer   Each of these paths of discovery in cancer research have led to the unique strategies of cancer therapeutics and detection for the purpose of reducing the burden of human cancer.  However, we must recall that this work has come at great cost, while it is indeed cause for celebration. The current failure rate of clinical trials at over 70 percent, has been a cause for disappointment, and has led to serious reconsideration of how we can proceed with greater success. The result of the evolution of the cancer field is evident in the many parts and chapters of this ebook.  Volume 4 contains chapters that are in a predetermined order:

  1. The concepts of neoplasm, malignancy, carcinogenesis,  and metastatic potential, which encompass:

(a)     How cancer cells bathed in an oxygen rich environment rely on anaerobic glycolysis for energy, and the secondary consequences of cachexia and sarcopenia associated with progression



ARTS protein and cancer

ARTS protein and cancer



Krebs cycle

Krebs cycle

Metabolic control analysis of respiration in human cancer tissue

Metabolic control analysis of respiration in human cancer tissue



(b)     How advances in genetic analysis, molecular and cellular biology, metabolomics have expanded our basic knowledge of the mechanisms which are involved in cellular transformation to the cancerous state.



Methylation of adenine

Methylation of adenine





(c)  How molecular techniques continue to advance our understanding  of how genetics, epigenetics, and alterations in cellular metabolism contribute to cancer and afford new pathways for therapeutic intervention.

 genomic effects

genomic effects

LKB1AMPK pathway

LKB1AMPK pathway



AMPK-activating drugs metformin or phenformin might provide protection against cancer

AMPK-activating drugs metformin or phenformin might provide protection against cancer





2. The distinct features of cancers of specific tissue sites of origin

3.  The diagnosis of cancer by

(a)     Clinical presentation

(b)     Age of onset and stage of life

(c)     Biomarker features

hairy cell leukemia

hairy cell leukemia

lymphoma leukemia

lymphoma leukemia

(d)     Radiological and ultrasound imaging

  1. Treatments
  2. Prognostic differences within and between cancer types

We have introduced the emergence of a disease of great complexity that has been clouded in more questions than answers until the emergence of molecular biology in the mid 20th century, and then had to await further discoveries going into the 21st century.  What gave the research impetus was the revelation of

1     the mechanism of transcription of the DNA into amino acid sequences

Proteins in Disease

Proteins in Disease

2     the identification of stresses imposed on cellular function

NO beneficial effects

NO beneficial effects

3     the elucidation of the substructure of the cell – cell membrane, mitochondria, ribosomes, lysosomes – and their functions, respectively

pone.0080815.g006  AKIP1 Expression Modulates Mitochondrial Function

AKIP1 Expression Modulates Mitochondrial Function

4     the elucidation of oligonucleotide sequences

















5     the further elucidation of functionally relevant noncoding lncDNA

lncRNA-s   A summary of the various functions described for lncRNA

6     the technology to synthesis mRNA and siRNA sequences

RNAi_Q4 Primary research objectives

Figure. RNAi and gene silencing

7     the repeated discovery of isoforms of critical enzymes and their pleiotropic properties

8.     the regulatory pathways involved in signaling

signaling pathjways map

Figure. Signaling Pathways Map

This is a brief outline of the modern progression of advances in our understanding of cancer.  Let us go back to the beginning and check out a sequence of  Nobel Prizes awarded and related discoveries that have a historical relationship to what we know.  The first discovery was the finding by Louis Pasteur that fungi that grew in an oxygen poor environment did not put down filaments.  They did not utilize oxygen and they produced used energy by fermentation.  This was the basis for Otto Warburg sixty years later to make the comparison to cancer cells that grew in the presence of oxygen, but relied on anaerobic glycolysis. He used a manometer to measure respiration in tissue one cell layer thick to measure CO2 production in an adiabatic system.

video width=”1280″ height=”720″ caption=”1741-7007-11-65-s1 Macromolecular juggling by ubiquitylation enzymes.” mp4=”“][/video]

An Introduction to the Warburg Apparatus

Lavoisier Antoine-Laurent and Laplace Pierre-Simon (1783) Memoir on heat. Mémoirs de l’Académie des sciences. Translated by Guerlac H, Neale Watson Academic Publications, New York, 1982.

Instrumental background 200 years later:   Gnaiger E (1983) The twin-flow microrespirometer and simultaneous calorimetry. In Gnaiger E, Forstner H, eds. Polarographic Oxygen Sensors. Springer, Heidelberg, Berlin, New York: 134-166.



Warburg apparatus

The Warburg apparatus is a manometric respirometer which was used for decades in biochemistry for measuring oxygen consumption of tissue homogenates or tissue slices.

The Warburg apparatus has its name from the German biochemist Otto Heinrich Warburg (1883-1970) who was awarded the Nobel Prize in physiology or medicine in 1931 for his “discovery of the nature and mode of action of the respiratory enzyme” [1].

The aqueous phase is vigorously shaken to equilibrate with a gas phase, from which oxygen is consumed while the evolved carbon dioxide is trapped, such that the pressure in the constant-volume gas phase drops proportional to oxygen consumption. The Warburg apparatus was introduced to study cell respiration, i.e. the uptake of molecular oxygen and the production of carbon dioxide by cells or tissues. Its applications were extended to the study of fermentation, when gas exchange takes place in the absence of oxygen. Thus the Warburg apparatus became established as an instrument for both aerobic and anaerobic biochemical studies [2, 3].

The respiration chamber was a detachable glass flask (F) equipped with one or more sidearms (S) for additions of chemicals and an open connection to a manometer (M; pressure gauge). A constant temperature was provided by immersion of the Warburg chamber in a constant temperature water bath. At thermal mass transfer equilibrium, an initial reading is obtained on the manometer, and the volume of gas produced or absorbed is determined at specific time intervals. A limited number of ‘titrations’ can be performed by adding the liquid contained in a side arm into the main reaction chamber. A Warburg apparatus may be equipped with more than 10 respiration chambers shaking in a common water bath.   Since temperature has to be controlled very precisely in a manometric approach, the early studies on mammalian tissue respiration were generally carried out at a physiological temperature of 37 °C.

The Warburg apparatus has been replaced by polarographic instruments introduced by Britton Chance in the 1950s. Since Chance and Williams (1955) measured respiration of isolated mitochondria simultaneously with the spectrophotometric determination of cytochrome redox states, a water chacket could not be used, and measurements were carried out at room temperature (or 25 °C). Thus most later studies on isolated mitochondria were shifted to the artifical temperature of 25 °C.

Today, the importance of investigating mitochondrial performance at in vivo temperatures is recognized again in mitochondrial physiology.  Incubation times of 1 hour were typical in experiments with the Warburg apparatus, but were reduced to a few or up to 20 min, following Chance and Williams, due to rapid oxygen depletion in closed, aqueous phase oxygraphs with high sample concentrations.  Today, incubation times of 1 hour are typical again in high-resolution respirometry, with low sample concentrations and the option of reoxygenations.

“The Nobel Prize in Physiology or Medicine 1931”. 27 Dec 2011

  1. Oesper P (1964) The history of the Warburg apparatus: Some reminiscences on its use. J Chem Educ 41: 294.
  2. Koppenol WH, Bounds PL, Dang CV (2011) Otto Warburg’s contributions to current concepts of cancer metabolism. Nature Reviews Cancer 11: 325-337.
  3. Gnaiger E, Kemp RB (1990) Anaerobic metabolism in aerobic mammalian cells: information from the ratio of calorimetric heat flux and respirometric oxygen flux. Biochim Biophys Acta 1016: 328-332. – “At high fructose concen­trations, respiration is inhibited while glycolytic end products accumulate, a phenomenon known as the Crabtree effect. It is commonly believed that this effect is restric­ted to microbial and tumour cells with uniquely high glycolytic capaci­ties (Sussman et al, 1980). How­ever, inhibition of respiration and increase of lactate production are observed under aerobic condi­tions in beating rat heart cell cultures (Frelin et al, 1974) and in isolated rat lung cells (Ayuso-Parrilla et al, 1978). Thus, the same general mechanisms respon­sible for the integra­tion of respiration and glycolysis in tumour cells (Sussman et al, 1980) appear to be operating to some extent in several isolated mammalian cells.”

Mitochondria are sometimes described as “cellular power plants” because they generate most of the cell’s supply of adenosine triphosphate (ATP), used as a source of chemical energy.[2] In addition to supplying cellular energy, mitochondria are involved in other tasks such as signalingcellular differentiationcell death, as well as the control of the cell cycle and cell growth.[3]   The organelle is composed of compartments that carry out specialized functions. These compartments or regions include the outer membrane, the intermembrane space, the inner membrane, and the cristae and matrix. Mitochondrial proteins vary depending on the tissue and the species. In humans, 615 distinct types of proteins have been identified from cardiac mitochondria,[9   Leonor Michaelis discovered that Janus green can be used as a supravital stain for mitochondria in 1900.  Benjamin F. Kingsbury, in 1912, first related them with cell respiration, but almost exclusively based on morphological observations.[13] In 1913 particles from extracts of guinea-pig liver were linked to respiration by Otto Heinrich Warburg, which he called “grana”. Warburg and Heinrich Otto Wieland, who had also postulated a similar particle mechanism, disagreed on the chemical nature of the respiration. It was not until 1925 when David Keilin discovered cytochromes that the respiratory chain was described.[13]    

The Clark Oxygen Sensor

Dr. Leland Clark – inventor of the “Clark Oxygen Sensor” (1954); the Clark type polarographic oxygen sensor remains the gold standard for measuring dissolved oxygen in biomedical, environmental and industrial applications .   ‘The convenience and simplicity of the polarographic ‘oxygen electrode’ technique for measuring rapid changes in the rate of oxygen utilization by cellular and subcellular systems is now leading to its more general application in many laboratories. The types and design of oxygen electrodes vary, depending on the investigator’s ingenuity and specific requirements of the system under investigation.’Estabrook R (1967) Mitochondrial respiratory control and the polarographic measurement of ADP:O ratios. Methods Enzymol. 10: 41-47.   “one approach that is underutilized in whole-cell bioenergetics, and that is accessible as long as cells can be obtained in suspension, is the oxygen electrode, which can obtain more precise information on the bioenergetic status of the in situ mitochondria than more ‘high-tech’ approaches such as fluorescent monitoring of Δψm.” Nicholls DG, Ferguson S (2002) Bioenergetics 3. Academic Press, London.

Great Figures in Cancer

Dr. Elizabeth Blackburn,

Dr. Elizabeth Blackburn,

j_michael_bishop onogene

j_michael_bishop onogene

Harold Varmus

Harold Varmus

Potts and Habener (PTH mRNA, Harvard MIT)  JCI

Potts and Habener (PTH mRNA, Harvard MIT) JCI

JCI Fuller Albright and hPTH AA sequence

JCI Fuller Albright and hPTH AA sequence

Dr. E. Donnall Thomas  Bone Marrow Transplants

Dr. E. Donnall Thomas Bone Marrow Transplants

Dr Haraldzur Hausen  EBV HPV

Dr Haraldzur Hausen EBV HPV

Dr. Craig Mello

Dr. Craig Mello

Dorothy Hodgkin  protein crystallography

Lee Hartwell - Hutchinson Cancer Res Center

Lee Hartwell – Hutchinson Cancer Res Center

Judah Folkman, MD

Judah Folkman, MD

Gertrude B. Elien (1918-1999)

Gertrude B. Elien (1918-1999)

The Nobel Prize in Physiology or Medicine 1922   

Archibald V. Hill, Otto Meyerhof

AV Hill –

“the production of heat in the muscle” Hill started his research work in 1909. It was due to J.N. Langley, Head of the Department of Physiology at that time that Hill took up the study on the nature of muscular contraction. Langley drew his attention to the important (later to become classic) work carried out by Fletcher and Hopkins on the problem of lactic acid in muscle, particularly in relation to the effect of oxygen upon its removal in recovery. In 1919 he took up again his study of the physiology of muscle, and came into close contact with Meyerhof of Kiel who, approaching the problem differently, arrived at results closely analogous to his study. In 1919 Hill’s friend W. Hartree, mathematician and engineer, joined in the myothermic investigations – a cooperation which had rewarding results.

Otto Meyerhof



lactic acid production in muscle contraction Under the influence of Otto Warburg, then at Heidelberg, Meyerhof became more and more interested in cell physiology.  In 1923 he was offered a Professorship of Biochemistry in the United States, but Germany was unwilling to lose him.  In 1929 he was he was placed in charge of the newly founded Kaiser Wilhelm Institute for Medical Research at Heidelberg.  From 1938 to 1940 he was Director of Research at the Institut de Biologie physico-chimique at Paris, but in 1940 he moved to the United States, where the post of Research Professor of Physiological Chemistry had been created for him by the University of Pennsylvania and the Rockefeller Foundation.  Meyerhof’s own account states that he was occupied chiefly with oxidation mechanisms in cells and with extending methods of gas analysis through the calorimetric measurement of heat production, and especially the respiratory processes of nitrifying bacteria. The physico-chemical analogy between oxygen respiration and alcoholic fermentation caused him to study both these processes in the same subject, namely, yeast extract. By this work he discovered a co-enzyme of respiration, which could be found in all the cells and tissues up till then investigated. At the same time he also found a co-enzyme of alcoholic fermentation. He also discovered the capacity of the SH-group to transfer oxygen; after Hopkins had isolated from cells the SH bodies concerned, Meyerhof showed that the unsaturated fatty acids in the cell are oxidized with the help of the sulfhydryl group. After studying closer the respiration of muscle, Meyerhof investigated the energy changes in muscle. Considerable progress had been achieved by the English scientists Fletcher and Hopkins by their recognition of the fact that lactic acid formation in the muscle is closely connected with the contraction process. These investigations were the first to throw light upon the highly paradoxical fact, already established by the physiologist Hermann, that the muscle can perform a considerable part of its external function in the complete absence of oxygen.

But it was indisputable that in the last resort the energy for muscle activity comes from oxidation, so the connection between activity and combustion must be an indirect one, and observed that in the absence of oxygen in the muscle, lactic acid appears, slowly in the relaxed state and rapidly in the active state, disappearing in the presence of oxygen. Obviously, then, oxygen is involved when muscle is in the relaxed state.

The Nobel Prize committee had been receiving nominations intermittently for the previous 14 years (for Eijkman, Funk, Goldberger, Grijns, Hopkins and Suzuki but, strangely, not for McCollum in this period). Tthe Committee for the 1929 awards apparently agreed that it was high time to honor the discoverer(s) of vitamins; but who were they? There was a clear case for Grijns, but he had not been re-nominated for that particular year, and it could be said that he was just taking the relatively obvious next steps along the new trail that had been laid down by Eijkman, who was also now an old man in poor health, but there was no doubt that he had taken the first steps in the use of an animal model to investigate the nutritional basis of a clinical disorder affecting millions. Goldberger had been another important contributor, but his recent death put him out of consideration. The clearest evidence for lack of an unknown “something” in a mammalian diet was presented by Gowland Hopkins in 1912. This Cambridge biochemist was already well known for having isolated the amino acid tryptophan from a protein and demonstrated its essential nature. He fed young rats on an experimental diet, half of them receiving a daily milk supplement, and only those receiving milk grew well, Hopkins suggested that this was analogous to human diseases related to diet, as he had suggested already in a lecture published in 1906. Hopkins, the leader of the “dynamic biochemistry” school in Britain and an influential advocate for the importance of vitamins, was awarded the prize jointly with Eijkman. A door was opened. Recognition of work on the fat-soluble vitamins begun by McCollum. The next award related to vitamins was given in 1934 to George WhippleGeorge Minot and William Murphy “for their discoveries concerning liver therapy in cases of [then incurable pernicious] anemia,” The essential liver factor (cobalamin, or vitamin B12) was isolated in 1948, and Vitamin B12  was absent from plant foods. But William Castle in 1928 had demonstrated that the stomachs of pernicious anemia patients were abnormal in failing to secrete an “intrinsic factor”.

1937   Albert von Szent-Györgyi Nagyrápolt

” the biological combustion processes, with special reference to vitamin C and the catalysis of fumaric acid”

structure of fumarate

Szent-Györgyi was a Hungarian biochemist who had worked with Otto Warburg and had a special interest in oxidation-reduction mechanisms. He was invited to Cambridge in England in 1927 after detecting an antioxidant compound in the adrenal cortex, and there, he isolated a compound that he named hexuronic acid. Charles Glen King of the University of Pittsburgh reported success In isolating the anti-scorbutic factor in 1932, and added that his crystals had all the properties reported by Szent-Györgyi for hexuronic acid. But his work on oxidation reactions was also important. Fumarate is an intermediate in the citric acid cycle used by cells to produce energy in the form of adenosine triphosphate (ATP) from food. It is formed by the oxidation of succinate by the enzyme succinate dehydrogenase. Fumarate is then converted by the enzyme fumarase to malate. An enzyme adds water to the fumarate molecule to form malate. The malate is created by adding one hydrogen atom to a carbon atom and then adding a hydroxyl group to a carbon next to a terminal carbonyl group.

In the same year, Norman Haworth from the University of Birmingham in England received a Nobel prize from the Chemistry Committee for having advanced carbohydrate chemistry and, specifically, for having worked out the structure of Szent-Györgyi’s crystals, and then been able to synthesize the vitamin. This was a considerable achievement. The Nobel Prize in Chemistry was shared with the Swiss organic chemist Paul Karrer, cited for his work on the structures of riboflavin and vitamins A and E as well as other biologically interesting compounds. This was followed in 1938 by a further Chemistry award to the German biochemist Richard Kuhn, who had also worked on carotenoids and B-vitamins, including riboflavin and pyridoxine. But Karrer was not permitted to leave Germany at that time by the Nazi regime. However, the American work with radioisotopes at Lawrence Livermore Laboratory, UC Berkeley, was already ushering in a new era of biochemistry that would enrich our studies of metabolic pathways. The importance of work involving vitamins was acknowledged in at least ten awards in the 20th century.

1.   Carpenter, K.J., Beriberi, White Rice and Vitamin B, University of California Press, Berkeley (2000).

2.  Weatherall, M.W. and Kamminga, H., The making of a biochemist: the construction of Frederick Gowland Hopkins’ reputation. Medical History vol.40, pp. 415-436 (1996).

3.  Becker, S.L., Will milk make them grow? An episode in the discovery of the vitamins. In Chemistry and Modern Society (J. Parascandela, editor) pp. 61-83, American Chemical Society,

Washington, D.C. (1983).

4.  Carpenter, K.J., The History of Scurvy and Vitamin C, Cambridge University Press, New York (1986).

Transport and metabolism of exogenous fumarate and 3-phosphoglycerate in vascular smooth muscle.

D R FinderC D Hardin

Molecular and Cellular Biochemistry (Impact Factor: 2.33). 05/1999; 195(1-2):113-21.

The keto (linear) form of exogenous fructose 1,6-bisphosphate, a highly charged glycolytic intermediate, may utilize a dicarboxylate transporter to cross the cell membrane, support glycolysis, and produce ATP anaerobically. We tested the hypothesis that fumarate, a dicarboxylate, and 3-phosphoglycerate (3-PG), an intermediate structurally similar to a dicarboxylate, can support contraction in vascular smooth muscle during hypoxia. 3-PG improved maintenance of force (p < 0.05) during the 30-80 min period of hypoxia. Fumarate decreased peak isometric force development by 9.5% (p = 0.008) but modestly improved maintenance of force (p < 0.05) throughout the first 80 min of hypoxia. 13C-NMR on tissue extracts and superfusates revealed 1,2,3,4-(13)C-fumarate (5 mM) metabolism to 1,2,3,4-(13)C-malate under oxygenated and hypoxic conditions suggesting uptake and metabolism of fumarate. In conclusion, exogenous fumarate and 3-PG readily enter vascular smooth muscle cells, presumably by a dicarboxylate transporter, and support energetically important pathways.

Comparison of endogenous and exogenous sources of ATP in fueling Ca2+ uptake in smooth muscle plasma membrane vesicles.

C D HardinL RaeymaekersR J Paul

The Journal of General Physiology (Impact Factor: 4.73). 12/1991; 99(1):21-40.

A smooth muscle plasma membrane vesicular fraction (PMV) purified for the (Ca2+/Mg2+)-ATPase has endogenous glycolytic enzyme activity. In the presence of glycolytic substrate (fructose 1,6-diphosphate) and cofactors, PMV produced ATP and lactate and supported calcium uptake. The endogenous glycolytic cascade supports calcium uptake independent of bath [ATP]. A 10-fold dilution of PMV, with the resultant 10-fold dilution of glycolytically produced bath [ATP] did not change glycolytically fueled calcium uptake (nanomoles per milligram protein). Furthermore, the calcium uptake fueled by the endogenous glycolytic cascade persisted in the presence of a hexokinase-based ATP trap which eliminated calcium uptake fueled by exogenously added ATP. Thus, it appears that the endogenous glycolytic cascade fuels calcium uptake in PMV via a membrane-associated pool of ATP and not via an exchange of ATP with the bulk solution. To determine whether ATP produced endogenously was utilized preferentially by the calcium pump, the ATP production rates of the endogenous creatine kinase and pyruvate kinase were matched to that of glycolysis and the calcium uptake fueled by the endogenous sources was compared with that fueled by exogenous ATP added at the same rate. The rate of calcium uptake fueled by endogenous sources of ATP was approximately twice that supported by exogenously added ATP, indicating that the calcium pump preferentially utilizes ATP produced by membrane-bound enzymes.

Evidence for succinate production by reduction of fumarate during hypoxia in isolated adult rat heart cells.

C HohlR OestreichP RösenR WiesnerM Grieshaber

Archives of Biochemistry and Biophysics (Impact Factor: 3.37). 01/1988; 259(2):527-35.   It has been demonstrated that perfusion of myocardium with glutamic acid or tricarboxylic acid cycle intermediates during hypoxia or ischemia, improves cardiac function, increases ATP levels, and stimulates succinate production. In this study isolated adult rat heart cells were used to investigate the mechanism of anaerobic succinate formation and examine beneficial effects attributed to ATP generated by this pathway. Myocytes incubated for 60 min under hypoxic conditions showed a slight loss of ATP from an initial value of 21 +/- 1 nmol/mg protein, a decline of CP from 42 to 17 nmol/mg protein and a fourfold increase in lactic acid production to 1.8 +/- 0.2 mumol/mg protein/h. These metabolite contents were not altered by the addition of malate and 2-oxoglutarate to the incubation medium nor were differences in cell viability observed; however, succinate release was substantially accelerated to 241 +/- 53 nmol/mg protein. Incubation of cells with [U-14C]malate or [2-U-14C]oxoglutarate indicates that succinate is formed directly from malate but not from 2-oxoglutarate. Moreover, anaerobic succinate formation was rotenone sensitive.

We conclude that malate reduction to succinate occurs via the reverse action of succinate dehydrogenase in a coupled reaction where NADH is oxidized (and FAD reduced) and ADP is phosphorylated. Furthermore, by transaminating with aspartate to produce oxaloacetate, 2-oxoglutarate stimulates cytosolic malic dehydrogenase activity, whereby malate is formed and NADH is oxidized.

In the form of malate, reducing equivalents and substrate are transported into the mitochondria where they are utilized for succinate synthesis.

1953 Hans Adolf Krebs –

 ” discovery of the citric acid cycle” and In the course of the 1920’s and 1930’s great progress was made in the study of the intermediary reactions by which sugar is anaerobically fermented to lactic acid or to ethanol and carbon dioxide. The success was mainly due to the joint efforts of the schools of Meyerhof, Embden, Parnas, von Euler, Warburg and the Coris, who built on the pioneer work of Harden and of Neuberg. This work brought to light the main intermediary steps of anaerobic fermentations.

In contrast, very little was known in the earlier 1930’s about the intermediary stages through which sugar is oxidized in living cells. When, in 1930, I left the laboratory of Otto Warburg (under whose guidance I had worked since 1926 and from whom I have learnt more than from any other single teacher), I was confronted with the question of selecting a major field of study and I felt greatly attracted by the problem of the intermediary pathway of oxidations.

These reactions represent the main energy source in higher organisms, and in view of the importance of energy production to living organisms (whose activities all depend on a continuous supply of energy) the problem seemed well worthwhile studying.

Interactive Krebs cycle

There are different points where metabolites enter the Krebs’ cycle. Most of the products of protein, carbohydrates and fat metabolism are reduced to the molecule acetyl coenzyme A that enters the Krebs’ cycle. Glucose, the primary fuel in the body, is first metabolized into pyruvic acid and then into acetyl coenzyme A. The breakdown of the glucose molecule forms two molecules of ATP for energy in the Embden Meyerhof pathway process of glycolysis.

On the other hand, amino acids and some chained fatty acids can be metabolized into Krebs intermediates and enter the cycle at several points. When oxygen is unavailable or the Krebs’ cycle is inhibited, the body shifts its energy production from the Krebs’ cycle to the Embden Meyerhof pathway of glycolysis, a very inefficient way of making energy.  

Fritz Albert Lipmann –

 “discovery of co-enzyme A and its importance for intermediary metabolism”.

In my development, the recognition of facts and the rationalization of these facts into a unified picture, have interplayed continuously. After my apprenticeship with Otto Meyerhof, a first interest on my own became the phenomenon we call the Pasteur effect, this peculiar depression of the wasteful fermentation in the respiring cell. By looking for a chemical explanation of this economy measure on the cellular level, I was prompted into a study of the mechanism of pyruvic acid oxidation, since it is at the pyruvic stage where respiration branches off from fermentation.

For this study I chose as a promising system a relatively simple looking pyruvic acid oxidation enzyme in a certain strain of Lactobacillus delbrueckii1.   In 1939, experiments using minced muscle cells demonstrated that one oxygen atom can form two adenosine triphosphate molecules, and, in 1941, the concept of phosphate bonds being a form of energy in cellular metabolism was developed by Fritz Albert Lipmann.

In the following years, the mechanism behind cellular respiration was further elaborated, although its link to the mitochondria was not known.[13]The introduction of tissue fractionation by Albert Claude allowed mitochondria to be isolated from other cell fractions and biochemical analysis to be conducted on them alone. In 1946, he concluded that cytochrome oxidase and other enzymes responsible for the respiratory chain were isolated to the mitchondria. Over time, the fractionation method was tweaked, improving the quality of the mitochondria isolated, and other elements of cell respiration were determined to occur in the mitochondria.[13]

The most important event during this whole period, I now feel, was the accidental observation that in the L. delbrueckii system, pyruvic acid oxidation was completely dependent on the presence of inorganic phosphate. This observation was made in the course of attempts to replace oxygen by methylene blue. To measure the methylene blue reduction manometrically, I had to switch to a bicarbonate buffer instead of the otherwise routinely used phosphate. In bicarbonate, pyruvate oxidation was very slow, but the addition of a little phosphate caused a remarkable increase in rate. The phosphate effect was removed by washing with a phosphate free acetate buffer. Then it appeared that the reaction was really fully dependent on phosphate.

A coupling of this pyruvate oxidation with adenylic acid phosphorylation was attempted. Addition of adenylic acid to the pyruvic oxidation system brought out a net disappearance of inorganic phosphate, accounted for as adenosine triphosphate.   The acetic acid subunit of acetyl CoA is combined with oxaloacetate to form a molecule of citrate. Acetyl coenzyme A acts only as a transporter of acetic acid from one enzyme to another. After Step 1, the coenzyme is released by hydrolysis to combine with another acetic acid molecule and begin the Krebs’ Cycle again.

Hugo Theorell

the nature and effects of oxidation enzymes”

From 1933 until 1935 Theorell held a Rockefeller Fellowship and worked with Otto Warburg at Berlin-Dahlem, and here he became interested in oxidation enzymes. At Berlin-Dahlem he produced, for the first time, the oxidation enzyme called «the yellow ferment» and he succeeded in splitting it reversibly into a coenzyme part, which was found to be flavin mononucleotide, and a colourless protein part. On return to Sweden, he was appointed Head of the newly established Biochemical Department of the Nobel Medical Institute, which was opened in 1937.

Succinate is oxidized by a molecule of FAD (Flavin Adenine Dinucleotide). The FAD removes two hydrogen atoms from the succinate and forms a double bond between the two carbon atoms to create fumarate.






Watson & Crick double helix model 

A landmark in this journey

They followed the path that became clear from intense collaborative work in California by George Beadle, by Avery and McCarthy, Max Delbruck, TH Morgan, Max Delbruck and by Chargaff that indicated that genetics would be important.


François Jacob, André Lwoff and Jacques Monod  –

” genetic control of enzyme and virus synthesis”.

In 1958 the remarkable analogy revealed by genetic analysis of lysogeny and that of the induced biosynthesis of ß-galactosidase led François Jacob, with Jacques Monod, to study the mechanisms responsible for the transfer of genetic information as well as the regulatory pathways which, in the bacterial cell, adjust the activity and synthesis of macromolecules. Following this analysis, Jacob and Monod proposed a series of new concepts, those of messenger RNA, regulator genes, operons and allosteric proteins.

Francois Jacob

Having determined the constants of growth in the presence of different carbohydrates, it occurred to me that it would be interesting to determine the same constants in paired mixtures of carbohydrates. From the first experiment on, I noticed that, whereas the growth was kinetically normal in the presence of certain mixtures (that is, it exhibited a single exponential phase), two complete growth cycles could be observed in other carbohydrate mixtures, these cycles consisting of two exponential phases separated by a-complete cessation of growth.

Lwoff, after considering this strange result for a moment, said to me, “That could have something to do with enzyme adaptation.”

“Enzyme adaptation? Never heard of it!” I said.

Lwoff’s only reply was to give me a copy of the then recent work of Marjorie Stephenson, in which a chapter summarized with great insight the still few studies concerning this phenomenon, which had been discovered by Duclaux at the end of the last century.  Studied by Dienert and by Went as early as 1901 and then by Euler and Josephson, it was more or less rediscovered by Karström, who should be credited with giving it a name and attracting attention to its existence.

Lwoff’s intuition was correct. The phenomenon of “diauxy” that I had discovered was indeed closely related to enzyme adaptation, as my experiments, included in the second part of my doctoral dissertation, soon convinced me. It was actually a case of the “glucose effect” discovered by Dienert as early as 1900.   That agents that uncouple oxidative phosphorylation, such as 2,4-dinitrophenol, completely inhibit adaptation to lactose or other carbohydrates suggested that “adaptation” implied an expenditure of chemical potential and therefore probably involved the true synthesis of an enzyme.

With Alice Audureau, I sought to discover the still quite obscure relations between this phenomenon and the one Massini, Lewis, and others had discovered: the appearance and selection of “spontaneous” mutants.   We showed that an apparently spontaneous mutation was allowing these originally “lactose-negative” bacteria to become “lactose-positive”. However, we proved that the original strain (Lac-) and the mutant strain (Lac+) did not differ from each other by the presence of a specific enzyme system, but rather by the ability to produce this system in the presence of lactose.  This mutation involved the selective control of an enzyme by a gene, and the conditions necessary for its expression seemed directly linked to the chemical activity of the system.


Albert Claude, Christian de Duve and George E. Palade –

” the structural and functional organization of the cell”.

I returned to Louvain in March 1947 after a period of working with Theorell in Sweden, the Cori’s, and E Southerland in St. Louis, fortunate in the choice of my mentors, all sticklers for technical excellence and intellectual rigor, those prerequisites of good scientific work. Insulin, together with glucagon which I had helped rediscover, was still my main focus of interest, and our first investigations were accordingly directed on certain enzymatic aspects of carbohydrate metabolism in liver, which were expected to throw light on the broader problem of insulin action. But I became distracted by an accidental finding related to acid phosphatase, drawing most of my collaborators along with me. The studies led to the discovery of the lysosome, and later of the peroxisome.

In 1962, I was appointed a professor at the Rockefeller Institute in New York, now the Rockefeller University, the institution where Albert Claude had made his pioneering studies between 1929 and 1949, and where George Palade had been working since 1946.  In New York, I was able to develop a second flourishing group, which follows the same general lines of research as the Belgian group, but with a program of its own.


Robert W. Holley, Har Gobind Khorana and Marshall W. Nirenberg –

“interpretation of the genetic code and its function in protein synthesis”.


Max Delbrück, Alfred D. Hershey and Salvador E. Luria –

” the replication mechanism and the genetic structure of viruses”.

1975 David Baltimore, Renato Dulbecco and Howard Martin Temin –

” the interaction between tumor viruses and the genetic material of the cell”.


Baruch S. Blumberg and D. Carleton Gajdusek –

” new mechanisms for the origin and dissemination of infectious diseases” The editors of the website of the Nobel Foundation have asked me to provide a supplement to the autobiography that I wrote in 1976 and to recount the events that happened after the award. Much of what I will have to say relates to the scientific developments since the last essay. These are described in greater detail in a scientific memoir first published in 2002 (Blumberg, B. S., Hepatitis B. The Hunt for a Killer Virus, Princeton University Press, 2002, 2004).


Baruj Benacerraf, Jean Dausset and George D. Snell 

” genetically determined structures on the cell surface that regulate immunological reactions”.


Edmond H. Fischer and Edwin G. Krebs 

“for their discoveries concerning reversible protein phosphorylation as a biological regulatory mechanism”


Alfred G. Gilman and Martin Rodbell –

“G-proteins and the role of these proteins in signal transduction in cells”


Bruce A. Beutler and Jules A. Hoffmann –

the activation of innate immunity and the other half to Ralph M. Steinman – “the dendritic cell and its role in adaptive immunity”.

Renato L. Baserga, M.D.

Kimmel Cancer Center and Keck School of Medicine

Dr. Baserga’s research focuses on the multiple roles of the type 1 insulin-like growth factor receptor (IGF-IR) in the proliferation of mammalian cells. The IGF-IR activated by its ligands is mitogenic, is required for the establishment and the maintenance of the transformed phenotype, and protects tumor cells from apoptosis. It, therefore, serves as an excellent target for therapeutic interventions aimed at inhibiting abnormal growth. In basic investigations, this group is presently studying the effects that the number of IGF-IRs and specific mutations in the receptor itself have on its ability to protect cells from apoptosis.

This investigation is strictly correlated with IGF-IR signaling, and part of this work tries to elucidate the pathways originating from the IGF-IR that are important for its functional effects. Baserga’s group has recently discovered a new signaling pathway used by the IGF-IR to protect cells from apoptosis, a unique pathway that is not used by other growth factor receptors. This pathway depends on the integrity of serines 1280-1283 in the C-terminus of the receptor, which bind 14.3.3 and cause the mitochondrial translocation of Raf-1.

Another recent discovery of this group has been the identification of a mechanism by which the IGF-IR can actually induce differentiation in certain types of cells. When cells have IRS-1 (a major substrate of the IGF-IR), the IGF-IR sends a proliferative signal; in the absence of IRS-1, the receptor induces cell differentiation. The extinction of IRS-1 expression is usually achieved by DNA methylation.

Janardan Reddy, MD

Northwestern University

The central effort of our research has been on a detailed analysis at the cellular and molecular levels of the pleiotropic responses in liver induced by structurally diverse classes of chemicals that include fibrate class of hypolipidemic drugs, and phthalate ester plasticizers, which we designated hepatic peroxisome proliferators. Our work has been central to the establishment of several principles, namely that hepatic peroxisome proliferation is associated with increases in fatty acid oxidation systems in liver, and that peroxisome proliferators, as a class, are novel nongenotoxic hepatocarcinogens.

We introduced the concept that sustained generation of reactive oxygen species leads to oxidative stress and serves as the basis for peroxisome proliferator-induced liver cancer development. Furthermore, based on the tissue/cell specificity of pleiotropic responses and the coordinated transcriptional regulation of fatty acid oxidation system genes, we postulated that peroxisome proliferators exert their action by a receptor-mediated mechanism. This receptor concept laid the foundation for the discovery of

  • a three member peroxisome proliferator-activated receptor (PPARalpha-, ß-, and gamma) subfamily of nuclear receptors.
  •  PPARalpha is responsible for peroxisome proliferator-induced pleiotropic responses, including
    • hepatocarcinogenesis and energy combustion as it serves as a fatty acid sensor and regulates fatty acid oxidation.

Our current work focuses on the molecular mechanisms responsible for PPAR action and generation of fatty acid oxidation deficient mouse knockout models. Transcription of specific genes by nuclear receptors is a complex process involving the participation of multiprotein complexes composed of transcription coactivators.  

Jose Delgado de Salles Roselino, Ph.D.

Leloir Institute, Brazil

Warburg effect, in reality “Pasteur-effect” was the first example of metabolic regulation described. A decrease in the carbon flux originated at the sugar molecule towards the end metabolic products, ethanol and carbon dioxide that was observed when yeast cells were transferred from anaerobic environmental condition to an aerobic one. In Pasteur´s works, 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 condition 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 time, since most of the undesirable outcomes in the industrial use of yeast were perceived when yeasts cells took very long time to create a rather selective anaerobic condition. This selective culture media was led by the carbon dioxide higher levels produced by fast growing yeast cells and by a great alcohol content in the yeast culture media. This finding was required to understand Lavoisier’s results indicating that chemical and biological oxidation of sugars produced the same calorimetric 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 indicates the major reasons that led Warburg to test failure in control mechanisms in cancer cells in comparison with the ones observed in normal cells. Biology inside classical thermo dynamics poses 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 decrease in V (volume) all this 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 from A to B or B to A. This observation confirms the important contribution of E Schrodinger in his What´s 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.”

Hans Krebs describes the cyclic nature of the citrate metabolism. Two major research lines search to understand the mechanism of energy transfer that explains how ADP is converted into ATP. One followed the organic chemistry line of reasoning and therefore, searched how the breakdown of carbon-carbon link could have its energy transferred to ATP synthesis. A major leader of this research line was B. Chance who tried to account for two carbon atoms of acetyl released as carbon dioxide in the series of Krebs cycle reactions. 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. Alternatively, under the possible influence of the excellent results of Hodgkin and Huxley a second line of research appears.

The work of Hodgkin & Huxley indicated 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 P Mitchell postulated a mechanism for the transfer of oxide/reductive power of organic molecules oxidation through electron transfer as the key for energetic transfer mechanism required for ATP synthesis. 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). Nonetheless, a victorious Peter Mitchell obtained the correct result in the conceptual dispute, over the B. Chance point of view, after he used E. Coli mutants to show H gradients in membrane and its use as energy source.

However, this should not detract from the important work of Chance. B. Chance got the simple and rapid polarographic assay method of oxidative phosphorylation and the idea of control of energy metabolism that bring us back to Pasteur. This second result seems to have been neglected in searching for a single molecular mechanism required for the understanding of the buildup of chemical reserve in our body. In respiring mitochondria the rate of electron transport, and thus 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 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 very low respiratory rate.

I have had an ongoing discussion with Jose Eduardo de Salles Roselino, inBrazil. He has made important points that need to be noted.

  1. The constancy of composition which animals maintain in the environment surrounding their cells is one of the dominant features of their physiology. Although this phenomenon, homeostasis, has held the interest of biologists over a long period of time, the elucidation of the molecular basis for complex processes such as temperature control and the maintenance of various substances at constant levels in the blood has not yet been achieved. By comparison, metabolic regulation in microorganisms is much better understood, in part because the microbial physiologist has focused his attention on enzyme-catalyzed reactions and their control, as these are among the few activities of microorganisms amenable to quantitative study. Furthermore, bacteria are characterized by their ability to make rapid and efficient adjustments to extensive variations in most parameters of their environment; therefore, they exhibit a surprising lack of rigid requirements for their environment, and appears to influence it only as an incidental result of their metabolism. Animal cells on the other hand have only a limited capacity for adjustment and therefore require a constant milieu. Maintenance of such constancy appears to be a major goal in their physiology (Regulation of Biosynthetic Pathways H.S. Moyed and H EUmbarger Phys Rev,42 444 (1962)).
  2. A living cell consists in a large part of a concentrated mixture of hundreds of different enzymes, each a highly effective catalyst for one or more chemical reactions involving other components of the cell. The paradox of intense and highly diverse chemical activity on the one hand and strongly poised chemical stability (biological homeostasis) on the other is one of the most challenging problems of biology (Biological feedback Control at the molecular Level D.E. Atkinson Science vol. 150: 851, 1965). Almost nothing is known concerning the actual molecular basis for modulation of an enzyme`s kinetic behavior by interaction with a small molecule. (Biological feedback Control at the molecular Level D.E. Atkinson Science vol. 150: 851, 1965). In the same article, since the core of Atkinson´s thinking seems to be strongly linked with Adenylates as regulatory effectors, the previous phrases seems to indicate a first step towards the conversion of homeostasis to an intracellular phenomenon and therefore, one that contrary to Umbarger´s consideration could be also studied in microorganisms.
  3.  Most biochemical studies using bacteria, were made before the end of the third upper part of log growth phase. Therefore, they could be considered as time-independent as S Luria presented biochemistry in Life an Unfinished Experiment. The sole ingredient on the missing side of the events that led us into the molecular biology construction was to consider that proteins, a macromolecule, would never be affected by small molecules translational kinetic energy. This, despite the fact that in a catalytic environment and its biological implications S Grisolia incorporated A K Balls observation indicating that the word proteins could be related to Proteus an old sea god that changed its form whenever he was subjected to inquiry (Phys Rev v 4,657 (1964).
  1. In D.E. Atkinson´s work (Science vol 150 p 851, 1965), changes in protein synthesis acting together with factors that interfere with enzyme activity will lead to “fine-tuned” regulation better than enzymatic activity regulation alone. Comparison of glycemic regulation in granivorous and carnivorous birds indicate that when no important nutritional source of glucose is available, glycemic levels can be kept constant in fasted and fed birds. The same was found in rats and cats fed on high protein diets. Gluconeogenesis is controlled by pyruvate kinase inhibition. Therefore, the fact that it can discriminate between fasting alone and fasting plus exercise (carbachol) requirement of gluconeogenic activity (correspondent level of pyruvate kinase inhibition) the control of enzyme activity can be made fast and efficient without need for changes in genetic expression (20 minute after stimulus) ( Migliorini,R.H. et al Am J. Physiol.257 (Endocrinol. Met. 20): E486, 1989). Regrettably, this was not discussed in the quoted work. So, when the control is not affected by the absorption of nutritional glucose it can be very fast, less energy intensive and very sensitive mechanism of control despite its action being made in the extracellular medium (homeostasis).

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