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PubMed2001

Transcriptome meets metabolome: hierarchical and metabolic regulation of the glycolytic pathway.

The fact that information flows from DNA to RNA to protein to function suggests that regulation is 'hierarchical', i.e. dominated by regulation of gene expression. In the case of dominant regulation at the metabolic level, however, there is no quantitative relationship between mRNA levels and function. We here develop a method to quantitate the relative contributions of metabolic and hierarchical regulation. Applying this method to the glycolytic flux in three species of parasitic protists, we conclude that it is rarely regulated by gene expression alone. This casts strong doubts on whether transcriptome and proteome analysis suffices to assess biological function.

Animals↗
PubMed2005

Proteomic analysis of protein expression in prostate cancer.

OBJECTIVE: To investigate protein expression in prostate cancer using 2-dimensional gel electrophoresis (2-DE) and mass spectrometry. STUDY DESIGN: Cells were collected from 29 peripheral zone tumors and from benign tissue by scraping cut surfaces of radical prostatectomy specimens. Samples were suspended in a medium with protease inhibitors and prepared for 2-DE. Gels were analyzed, and protein spots that differed quantitatively between tumor and benign tissue were identified via mass spectrometric fingerprinting of tryptic fragments and tandem mass spectrometry sequence analysis. RESULTS: In total, 63 spots differed between cancer and benign samples (p < 0.01); 56 were overexpressed (> 1.5 fold) in cancer and 7 underexpressed (< 0.6 fold). Among overexpressed proteins were transcription factors (nucleoside diphosphate kinase 1) and enzymes involved in gene silencing (chromobox protein), protein synthesis (39S ribosomal protein L12, BiP protein, protein disulfide isomerase), degradation (cytosol aminopeptidase, endopeptidase Clp, inorganic pyrophosphatase) and energy metabolism (acyl-CoA dehydrogenase, isocitrate dehydrogenase, NADH-ubiquinone oxidoreductase, pyruvate dehydrogenase), heat-shock proteins (60 and 70 kd), structural proteins (cytokeratins) and membrane proteins (stomatinlike protein 2). CONCLUSION: The protein profile of prostate cancer differs from that of benign tissue. Several potential target proteins for detection or evaluation of prognosis in prostate cancer were identified.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2001

Proteome, transcriptome and genome: top down or bottom up analysis?

Biological systems are comprised of protein components found at a wide variety of abundances from millions of molecules of a single species per cell to less than one copy per cell. Because of this wide range of concentrations, measurement or a full accounting of each system is presently unavailable. Conventional separation and analytical methods (two-dimensional gel electrophoresis and mass spectrometry) allow identification and quantitation of many of the most abundant gene products (top down methods); and the majority of gene products, which are found at low abundance, can be neither identified nor measured in complex mixtures at present. The gene products that are found at low levels can be characterized and their properties analyzed by preparing ordered gene libraries of limited complexity from mRNA. When such preparations are expressed in cell free systems and analyzed by two-dimensional gel electrophoresis, the features of the gene products are available for analysis. This 'bottom up' approach allows identification of gene product properties so that analytical procedures can be devised and applied to complex mixtures.

Cell Line↗
PubMed2003

Proteomic approach to coronary atherosclerosis shows ferritin light chain as a significant marker: evidence consistent with iron hypothesis in atherosclerosis.

Coronary artery disease (CAD) is the leading cause of mortality and morbidity in developed nations. We hypothesized that CAD is associated with distinct patterns of protein expression in the coronary arteries, and we have begun to employ proteomics to identify differentially expressed proteins in diseased coronary arteries. Two-dimensional (2-D) gel electrophoresis of proteins and subsequent mass spectrometric analysis identified the ferritin light chain as differentially expressed between 10 coronary arteries from patients with CAD and 7 coronary arteries from normal individuals. Western blot analysis indicated significantly increased expression of the ferritin light chain in the diseased coronary arteries (1.41 vs. 0.75; P = 0.01). Quantitative real-time PCR analysis showed that expression of ferritin light chain mRNA was decreased in diseased tissues (0.70 vs. 1.17; P = 0.013), suggesting that increased expression of ferritin light chain in CAD coronary arteries may be related to increased protein stability or upregulation of expression at the posttranscriptional level in the diseased tissues. Ferritin light chain protein mediates storage of iron in cells. We speculate that increased expression of the ferritin light chain may contribute to pathogenesis of CAD by modulating oxidation of lipids within the vessel wall through the generation of reactive oxygen species. Our results provide in situ proteomic evidence consistent with the "iron hypothesis," which proposes an association between excessive iron storage and a high risk of CAD. However, it is also possible that the increased ferritin expression in diseased coronary arteries is a consequence, rather than a cause, of CAD.

Adult↗
PubMed2006

High-throughput functional genomic methods to analyze the effects of dietary lipids.

The applications of 'omics' (genomics, transcriptomics, proteomics and metabolomics) technologies in nutritional studies have opened new possibilities to understand the effects and the action of different diets both in healthy and diseased states and help to define personalized diets and to develop new drugs that revert or prevent the negative dietary effects. Several single nucleotide polymorphisms have already been investigated for potential gene-diet interactions in the response to different lipid diets. It is also well-known that besides the known cellular effects of lipid nutrition, dietary lipids influence gene expression in a tissue, concentration and age-dependent manner. Protein expression and post-translational changes due to different diets have been reported as well. To understand the molecular basis of the effects and roles of dietary lipids high-throughput functional genomic methods such as DNA- or protein microarrays, high-throughput NMR and mass spectrometry are needed to assess the changes in a global way at the genome, at the transcriptome, at the proteome and at the metabolome level. The present review will focus on different high-throughput technologies from the aspects of assessing the effects of dietary fatty acids including cholesterol and polyunsaturated fatty acids. Several genes were identified that exhibited altered expression in response to fish-oil treatment of human lung cancer cells, including protein kinase C, natriuretic peptide receptor-A, PKNbeta, interleukin-1 receptor associated kinase-1 (IRAK-1) and diacylglycerol kinase genes by using high-throughput quantitative real-time PCR. Other results will also be mentioned obtained from cholesterol and polyunsaturated fatty acid fed animals by using DNA- and protein microarrays.

Animals↗
PubMed2001

Advances in proteome analysis by mass spectrometry.

Proteome characterization using mass spectrometry is essential for the systematic investigation of biological systems and for the study of gene function. Recent advances in this multifaceted field have occurred in four general areas: protein and peptide separation methodologies; selective labeling chemistries for quantitative measurement of peptide and protein abundances; characterization of post-translational protein modifications; and instrumentation.

Chromatography, High Pressure Liquid↗
PubMed2001

Computational cell biologists snowed in at Cranwell.

Cell biology is being inundated by an avalanche of data from the genomics and proteomics enterprises. The complexity and sheer volume of information threaten to overwhelm the ability of traditional cell biologists to grasp its implications and develop experimentally testable hypotheses. For this reason, some have begun to explore computational approaches towards organizing complex data into quantitative models. This requires communication and collaboration between the biological science community and and the physical and mathematical sciences communities. A recent meeting [The First International Symposium on Computational Cell Biology, Cranwell Resort, Lenox, MA, USA; 4-6 March 2001. Organizers: J.H. Carson, A. Cowan, and L.M. Loew (www.nrcam.uchc.edu/conference).] made a first attempt to bring these two communities together. Three feet of new snow fell during the meeting, but the 125 attendees, an unusual mixture of cell biologists, computer scientists, mathematicians, physicists, and engineers, were having too much fun defining the new field of computational cell biology to notice that they were literally snowed in.

Animals↗
PubMed2003

Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach.

We have generated Artificial Neural Networks (ANN) capable of performing sensitive, quantitative predictions of peptide binding to the MHC class I molecule, HLA-A*0204. We have shown that such quantitative ANN are superior to conventional classification ANN, that have been trained to predict binding vs non-binding peptides. Furthermore, quantitative ANN allowed a straightforward application of a 'Query by Committee' (QBC) principle whereby particularly information-rich peptides could be identified and subsequently tested experimentally. Iterative training based on QBC-selected peptides considerably increased the sensitivity without compromising the efficiency of the prediction. This suggests a general, rational and unbiased approach to the development of high quality predictions of epitopes restricted to this and other HLA molecules. Due to their quantitative nature, such predictions will cover a wide range of MHC-binding affinities of immunological interest, and they can be readily integrated with predictions of other events involved in generating immunogenic epitopes. These predictions have the capacity to perform rapid proteome-wide searches for epitopes. Finally, it is an example of an iterative feedback loop whereby advanced, computational bioinformatics optimize experimental strategy, and vice versa.

HLA-A Antigens↗
PubMed2006

Metabolic control analysis for large changes: extension to variable elasticity coefficients.

Modular approaches are powerful systems biology strategies to deal with complexity. They consist in lumping conceptually all that is irrelevant to the problem under study, leaving explicit the portions of interest. Modular (or top-down) metabolic control analysis is a theoretical and experimental approach to study the sensitivity properties of complex metabolic systems. Initially, it was conceived for infinitesimal changes but, recently, it started to be developed for large metabolic changes. A central result of this approach is that the systemic properties, represented by control coefficients, can be expressed as a function of the properties of isolated modules, the elasticity coefficients. Here we extend the theory for large changes to the case that the elasticity coefficients depend on the extent of the change. The novel theory is used to analyse experimental data related to the control of glycolytic flux in Escherichia coli. Our analysis shows that the pattern of control for large changes is quantitatively and qualitatively different from the one obtained applying the infinitesimal treatment.

Algorithms↗
PubMed2002

Comments: implications of hormesis for industrial hygienists.

Quantitative health risk assessment is based on extrapolating from the high-dose end of the dose-response curve to points close to the origin or the threshold where the dose levels are closer to the lower environmental or occupational exposures. Hormesis is demonstrated in chronic toxicological studies where the animals treated at the lowest experimental dose appear to be healthier than the controls, as evidenced by longer life spans, less disease and/or increased body weight. If the occupational exposure limit (OEL) or environmental exposure limit (EEL) is in the range of the hormetic effect, or lower than the hormetic effect, then a case could be made that exposure at the OEL or EEL is 'safe.' This idea is controversial because it challenges some of the basic assumptions of quantitative health risk assessment as it has been practiced during the past 50 years. De-emphasis of the dose-response curve in determining OELs and EELs will occur not because of hormesis, but because the emerging sciences of genomics and proteomics will shift the focus from statistical methods to individuals as genetic and protein engineering becomes more sophisticated and powerful.

Animals↗
PubMed2005

Proteomic analysis of chronic pancreatitis and pancreatic adenocarcinoma.

BACKGROUND & AIMS: Markers to differentiate among pancreatic adenocarcinoma, chronic pancreatitis, and normal pancreas would be of significant clinical utility. This study was therefore designed to analyze the proteome of such specimens and identify new candidate proteins for differential diagnosis. METHODS: A PowerBlot analysis with more than 900 well-characterized antibodies was performed with tissue specimens from patients with chronic pancreatitis, pancreatic adenocarcinoma, and normal pancreas. Differential expression of selected proteins was confirmed on a larger scale by quantitative reverse transcription-polymerase chain reaction and immunohistochemistry using tissue arrays. RESULTS: A total of 30 and 102 proteins showed significant deregulation between normal pancreas when compared with chronic pancreatitis and pancreatic adenocarcinoma, respectively, and although a substantial proportion were found similarly dysregulated in both chronic pancreatitis and pancreatic adenocarcinoma, several proteins were identified as potential disease-specific markers. CONCLUSIONS: A large number of proteins are differentially expressed in chronic pancreatitis and pancreatic adenocarcinoma compared with normal pancreas. Among these, expression analysis of UHRF1, ATP7A, and aldehyde oxidase 1 in combination could potentially provide a useful additional diagnostic tool for fine-needle aspirated or cytological specimens obtained during endoscopic investigations.

Adenocarcinoma↗
PubMed2005

Peptidomics biomarker discovery in mouse models of obesity and type 2 diabetes.

Type 2 diabetes mellitus (T2DM) is caused by the failure of the pancreatic beta-cell to secrete sufficient insulin to compensate a decreased response of peripheral tissues to insulin action. The pathological events causing beta-cell dysfunctions are only poorly understood and early markers that would predict islet function are missing. In contrast to immunoassays, unbiased proteomic technologies provide the opportunity to screen for novel marker protein and peptides of T2DM. An important subset of the proteome, peptides and peptide hormones secreted by the pancreas are deregulated in T2DM. The mass range of peptides and small proteins (1-20 kDa) is only sufficiently targeted by peptidomics, a combination of liquid chromatographic and mass spectrometric (MS) peptide analysis. Here, we describe the application of isotope label-free quantitative peptidomics to display and quantify relevant changes in the level of pancreatic peptides and peptide hormones in a preclinical model of T2DM, the Lep(ob)/Lep(ob) mouse. The amino acid sequence of statistical relevant top candidates was determined by MS/MS fragmentation or Edman degradation. The comparison of lean versus obese mice revealed increased levels of islet-specific peptides that can be divided into the following categories 1) the major islet peptide hormones insulin, amylin and glucagon; 2) proinsulin and C-peptide and 3) novel processing products of secretogranin, glucagon and amylin. Furthermore, we found increased levels of proteins and peptides implicated in zymogen granule maturation (syncollin) and nutritional digestion. In summary, our findings demonstrate that peptidomics is a valid approach to screen for novel peptide biomarkers.

Animals↗
PubMed2005

Correlation between mRNA and protein abundance in Desulfovibrio vulgaris: a multiple regression to identify sources of variations.

Parallel profiling of mRNA and protein on a global scale and integrative analysis of these two data types could provide additional insights into the metabolic mechanisms underlying complex biological systems. However, because mRNA and protein abundance are affected by many cellular and physical processes, there have been conflicting results on their correlation. Using whole-genome microarray and LC-MS/MS proteomic data collected from Desulfovibrio vulgaris grown under three different conditions, we systematically investigate the relationship between mRNA and protein abundance by a multiple regression approach, in which some of the key covariates that may affect mRNA-protein relationship were included. The results showed that mRNA abundance alone can explain only 20-28% of the total variation of protein abundance, suggesting mRNA-protein correlation can not be determined by mRNA abundance alone. Among various covariates, analytic variation of protein abundance is the major source for the variation of mRNA-protein correlation, which contributes to 34-44% of the total variation of mRNA-protein correlation. The cellular functional category of genes/proteins contributes 10-15% of the total variation of mRNA-protein correlation, with a more pronounced correlation of the two properties was observed for "central intermediary metabolism" and "energy metabolism" categories. In addition, protein stability also contributes 5% of the total variation of mRNA-protein correlation. The study presents the first quantitative analysis of the contributions of various biochemical and physical sources to the correlation of mRNA and protein abundance in D. vulgaris.

Bacterial Proteins↗
PubMed2006

Quantification of protein half-lives in the budding yeast proteome.

A complete description of protein metabolism requires knowledge of the rates of protein production and destruction within cells. Using an epitope-tagged strain collection, we measured the half-life of >3,750 proteins in the yeast proteome after inhibition of translation. By integrating our data with previous measurements of protein and mRNA abundance and translation rate, we provide evidence that many proteins partition into one of two regimes for protein metabolism: one optimized for efficient production or a second optimized for regulatory efficiency. Incorporation of protein half-life information into a simple quantitative model for protein production improves our ability to predict steady-state protein abundance values. Analysis of a simple dynamic protein production model reveals a remarkable correlation between transcriptional regulation and protein half-life within some groups of coregulated genes, suggesting that cells coordinate these two processes to achieve uniform effects on protein abundances. Our experimental data and theoretical analysis underscore the importance of an integrative approach to the complex interplay between protein degradation, transcriptional regulation, and other determinants of protein metabolism.

Fungal Proteins↗
PubMed2004

Quantitative profiling of plasma peptides in asthmatic mice using liquid chromatography and mass spectrometry.

Asthma is increasing in prevalence worldwide as a result of factors associated with a Western lifestyle. However, simple and reliable diagnostic and prognostic markers are yet to be found. In an attempt to identify protein biomarker profiles among small molecular weight ranges, we employed an approach combining liquid chromatography with mass spectrometry, instead of two-dimensional gel electrophoresis (2-DE), which has previously been used to analyze protein expression patterns. Here we described its application to compare plasma peptides from control and chronic asthma mice. Peptides were quantitatively profiled as a multidimensional peptide mass fingerprint by a combination of reverse-phase high-performance liquid chromatography and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. They were identified by peptide mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight/time-of-flight tandem mass spectrometry. In this study, we quantitatively identified the fragment f of complement 3 (C3f), which is important in inflammation. C3f was significantly higher in controls than chronic asthma mice. Our strategy allowed the detection and identification of different plasma peptides between control and chronic asthma mice on a proteomic scale. Therefore, these results suggest that native small peptides detected by non-2-DE techniques may be useful and specific biomarkers of disease.

Animals↗
PubMed2000

Proteome mapping by two-dimensional polyacrylamide gel electrophoresis in combination with mass spectrometric protein sequence analysis.

The high resolving power of two-dimensional polyacrylamide gel electrophoresis 2D-PAGE and its full analytical and preparative potential have been described with special emphasis on reproducibility and standardization of protein spot patterns, enhanced protein detection sensitivity, and computer analysis database development. New methodologies for peptide mass fingerprinting, peptide, sequence, and fragmentation tagging have been highlighted. Major challenges associated with 2D-PAGE/mass spectrometric protein sequencing were outlined which need to be addressed in the future, including sample enrichment, use of alternative gel matrices, improvements in separation systems interfaced directly to the mass spectrometer, and design of high-sensitivity instruments with very high mass ranges. It is hoped that comparative studies to identify, quantitate, and characterize proteins differentially expressed in normal versus diseased cells would give insight into mechanisms of pathogenesis and allow the development of a way to control both the etiology and the course of diseases.

Electrophoresis, Polyacrylamide Gel↗
PubMedDate not supplied

Combining chemodescriptors and biodescriptors in quantitative structure-activity relationship modeling.

In view of the wide distribution of halocarbons in our world, their toxicity is a public health concern. Previous work has shown that various measures of toxicity can be predicted with standard molecular descriptors. In our work, biodescriptors of the effect of halocarbons on the liver were obtained by exposing hepatocytes to 14 halocarbons and a control and by producing two-dimensional electrophoresis gels to assess the expressed proteome. The resulting spot abundances provide additional biological information that might be used in toxicity prediction. QSAR models were fitted via ridge regression to predict eight dependent toxicity measures: d37, arr, EC50MTT, EC50LDH, EC20SH, LECLP, LECROS, and LECCAT. Three predictor sets were used for each-the chemodescriptors alone, the biodescriptors alone, and the combined set of both chemo- and biodescriptors. The results differed somewhat from one dependent to another, but overall it was shown that better results could be obtained by using both chemo- and biodescriptors in the model than by using either chemo- or biodescriptors alone. The library of compounds used was small and quite homogeneous, so our immediate conclusions are correspondingly limited in scope, but we believe the underlying methodologies have broad applicability at the interface of chemical and biological descriptors.

Animals↗
PubMed2005

Enhanced nuclear factor-kappa B-associated Wnt-1 expression in hepatitis B- and C-related hepatocarcinogenesis: identification by functional proteomics.

Chronic infections with hepatitis B and C viruses (HBV and HCV) are etiologically linked to hepatitis, liver cirrhosis, and hepatocellular carcinoma (HCC). Both viruses may induce activation of nuclear factor-kappa B (NF-kappaB) in hepatocytes that plays a crucial role in the regulation of cell growth and apoptosis. Functional proteomics analysis of proteins associated with NF-kappaB signaling complexes in both viruses-related HCC tumor and non-tumor tissues may disclose possible common mechanisms in hepatocarcinogenesis. By functional proteomics, we analyzed proteins associated with NF-kappaB-signaling complexes in four-paired human HCC tumor and non-tumor tissues from HBV- and HCV-infected patients, respectively, and in one-paired tissue with dual viral infection. The quantity of NF-kappaB-associated proteins was semi-quantitatively measured by protein spot intensity on the gels of two-dimensional polyacrylamide gel electrophoresis. The results showed that overexpression of NF-kappaB-associated Wnt-1 protein in tumor part was detected in the majority of HBV- and HCV-infected HCC samples. These data suggest that enhanced expression of NF-kappaB-associated Wnt-1 protein might be a mechanism of hepatocarcinogenesis common to HBV- and HCV-infected patients. NF-kappaB signaling pathway and Wnt-1 protein could be potential targets for designing highly effective therapeutic agents in treating HCC and for chemoprevention of hepatocarcinogenesis.

Aged↗