Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “proteomic profiling”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,243 records · Page 69Linked to original sources
PubMed2006

Molecular dynamics of the Shewanella oneidensis response to chromate stress.

Temporal genomic profiling and whole-cell proteomic analyses were performed to characterize the dynamic molecular response of the metal-reducing bacterium Shewanella oneidensis MR-1 to an acute chromate shock. The complex dynamics of cellular processes demand the integration of methodologies that describe biological systems at the levels of regulation, gene and protein expression, and metabolite production. Genomic microarray analysis of the transcriptome dynamics of midexponential phase cells subjected to 1 mm potassium chromate (K(2)CrO(4)) at exposure time intervals of 5, 30, 60, and 90 min revealed 910 genes that were differentially expressed at one or more time points. Strongly induced genes included those encoding components of a TonB1 iron transport system (tonB1-exbB1-exbD1), hemin ATP-binding cassette transporters (hmuTUV), TonB-dependent receptors as well as sulfate transporters (cysP, cysW-2, and cysA-2), and enzymes involved in assimilative sulfur metabolism (cysC, cysN, cysD, cysH, cysI, and cysJ). Transcript levels for genes with annotated functions in DNA repair (lexA, recX, recA, recN, dinP, and umuD), cellular detoxification (so1756, so3585, and so3586), and two-component signal transduction systems (so2426) were also significantly up-regulated (p < 0.05) in Cr(VI)-exposed cells relative to untreated cells. By contrast, genes with functions linked to energy metabolism, particularly electron transport (e.g. so0902-03-04, mtrA, omcA, and omcB), showed dramatic temporal alterations in expression with the majority exhibiting repression. Differential proteomics based on multidimensional HPLC-MS/MS was used to complement the transcriptome data, resulting in comparable induction and repression patterns for a subset of corresponding proteins. In total, expression of 2,370 proteins were confidently verified with 624 (26%) of these annotated as hypothetical or conserved hypothetical proteins. The initial response of S. oneidensis to chromate shock appears to require a combination of different regulatory networks that involve genes with annotated functions in oxidative stress protection, detoxification, protein stress protection, iron and sulfur acquisition, and SOS-controlled DNA repair mechanisms.

Anion Transport Proteins↗
PubMed2006

The burden of scientific progress: growing inequalities in the delivery of cancer care.

Novel targeted therapies are now a reality in oncology. The monoclonal antibodies trastuzumab, rituximab, cetuximab and bevacizumab have a proven benefit in both advanced and early stage cancers. Furthermore impressive new technologies such as gene profiling, circulating tumour cells and proteomics are becoming major tools for prognostic assessment and prediction of response to certain treatments. Whilst this is certainly good news for patients it comes at a price, many of these technologies are very expensive and may result in unprecedented inequalities in the delivery of cancer care. The largest impact may be on developing countries, but inequalities are starting to be felt in some developed nations. Strategies to tackle the resource implications need to be addressed alongside the development of these technologies.

Antibodies, Monoclonal↗
PubMed2006

The molecular diagnosis of hepatitis B virus-associated hepatocellular carcinoma.

Hepatitis B virus (HBV) infection is the major cause of hepatocellular carcinoma (HCC) worldwide. The pathogenesis of HBV-associated HCC has been studied extensively, and molecular changes during malignant transformation have been identified. It has been proposed that the insertion of HBV DNA into the human genome results in chromosomal instability and inactivation of tumor suppressor genes. Transactivation of oncogenes, inactivation of tumor suppressor genes, and alteration of the cell cycle by HBV proteins are also involved in the progression of hepatocellular carcinogenesis. Traditional clinical examinations of HCC, such as biopsy, computer tomography, ultrasonic imaging, and detection of such biomarkers as a-fetoprotein, are currently the "gold standard" in diagnosis. These tests diagnose HCC only in the late stages of disease. This limitation has greatly reduced the chance of survival of HCC patients. To resolve this problem, new biomarkers that can diagnose HCC in earlier stages are necessary. Based on recent molecular studies of the effects of HBV on cellular transformation, differentially expressed biomarkers of HBV infection have been elucidated. With the analyses of the HBV replication profile, the viral load (HBV DNA levels) of patients, and the viral protein expression, the severity of hepatitis in the preneoplastic stages can be assessed. In the future, with the molecular profiles identified by genomic and proteomic approaches, stage-specific biomarkers should be identified to monitor the progression and prognosis of HCC.

Animals↗
PubMed2001

Individual metabolism should guide agriculture toward foods for improved health and nutrition.

Genomics and bioinformatics have the vast potential to identify genes that cause disease by investigating whole-genome databases. Comparison of an individual's geno-type with a genomic database will allow the prescription of drugs to be tailored to an individual's genotype. This same bioinformatic approach, applied to the study of human metabolites, has the potential to identify and validate targets to improve personalized nutritional health and thus serve to define the added value for the next generation of foods and crops. Advances in high-throughput analytic chemistry and computing technologies make the creation of a vast database of metabolites possible for several subsets of metabolites, including lipids and organic acids. In creating integrative databases of metabolites for bioinformatic investigation, the current concept of measuring single biomarkers must be expanded to 3 dimensions to 1) include a highly comprehensive set of metabolite measurements (a profile) by multiparallel analyses, 2) measure the metabolic profile of individuals over time rather than simply in the fasted state, and 3) integrate these metabolic profiles with genomic, expression, and proteomic databases. Application of the knowledge of individual metabolism will revolutionize the ability of nutrition to deliver health benefits through food in the same way that knowledge of genomics will revolutionize individual treatment of dis-ease with pharmaceuticals.

Biomarkers↗
PubMed2005

Biomarkers for neurodegenerative diseases.

PURPOSE OF REVIEW: A major goal of current clinical research in neurodegenerative diseases is to improve early detection of disease and presymptomatic detection of neuronal dysfunction. We also need better tools to assess disease progression in this group of disorders. Currently, many potential disease-modifying therapies are being developed and evaluated at the preclinical stage, and will lead to clinical trials in the near future for which biomarkers are urgently needed. This review summarizes the field of biomarker research in the major neurodegenerative diseases. RECENT FINDINGS: Many different approaches are being undertaken to identify biomarkers and include imaging, neurophysiological and cognitive testing in addition to newer technologies such as biochemical, proteomic, metabanomic and gene array profiling of tissue and biofluids from patients. Key recent findings in each of these areas are discussed. SUMMARY: The ideal biomarker needs to be easy to quantify and measure, reproducible, not subject to wide variation in the general population and unaffected by co-morbid factors. For evaluation of therapies the biomarker needs to change linearly with disease progression and closely correlate with established clinico-pathological parameters of the disease. It is unlikely that any one biomarker will fulfil all these characteristics, and it is likely that more than one biomarker will be needed for early diagnosis and similarly for evaluation of disease progression for therapeutic trials. For example, the combination of more detailed clinical assessments encompassing specific cognitive and neurophysiological testing, in addition to imaging, biochemical and genomic profiling, is likely to be needed.

Animals↗
PubMed2005

Mining the tumor phosphoproteome for cancer markers.

Despite decades of cancer research, mortality rates remain high largely due to the failure of early detection, poor understanding of the epidemiology of rational drug targets, and molecular etiology of human cancers. The discovery of disease markers promises to deliver some solutions to these formidable challenges. Gene and protein expression profiling through DNA microarray and proteomics have already made a tremendous effect in this area. However, protein/gene expression does not necessarily reflect protein activity, which is often regulated via post-translation modifications, of which phosphorylation is one of the most prominent. This is an important consideration because the activity of protein is a more relevant phenotype than its expression during pathogenesis. Tyrosine kinases represent a very important class of enzymes that are critical regulators of mitogenic and angiogenic signaling, hence attractive targets for anticancer drugs as exemplified by BCR-ABL and ErbB2. More than 50% of them are overexpressed or mutated resulting in a gain of function in various human cancers. In this review, we discuss the potential effect of phosphoproteins as cancer markers in cancer diagnosis and therapeutics. Phosphoproteomics strategies that might pave the way to high-throughput analysis for routine clinical applications are also described.

Biomarkers, Tumor↗
PubMed2007

Reciprocal modifications of CLIC4 in tumor epithelium and stroma mark malignant progression of multiple human cancers.

PURPOSE: CLIC4, a member of a family of intracellular chloride channels, is regulated by p53, c-Myc, and tumor necrosis factor-alpha. Regulation by factors involved in cancer pathogenesis, together with the previously shown proapoptotic activity of CLIC4, suggests that the protein may have a tumor suppressor function. To address this possibility, we characterized the expression profile, subcellular localization, and gene integrity of CLIC4 in human cancers and determined the functional consequences of CLIC4 expression in tumor epithelium and stromal cells. EXPERIMENTAL DESIGN: CLIC4 expression profiles were analyzed by genomics, proteomics, bioinformatics, and tissue microarrays. CLIC4 expression, as a consequence of crosstalk between stroma and epithelium, was tested in vitro by coculture of breast epithelial tumor cells and normal fibroblasts, and the functional consequences of CLIC4 expression was tested in vivo in xenografts of human breast tumor cell lines reconstituted with CLIC4 or mixed with fibroblasts that overexpress CLIC4 transgenically. RESULTS: In cDNA arrays of matched human normal and tumor tissues, CLIC4 expression was reduced in renal, ovarian, and breast cancers. However, CLIC4 protein levels were variable in tumor lysate arrays. Transcript sequences of CLIC4 from the human expressed sequence tag database and manual sequencing of cDNA from 60 human cancer cell lines (NCI60) failed to reveal deletion or mutations in the CLIC4 gene. On matched tissue arrays, CLIC4 was predominantly nuclear in normal human epithelial tissues but not cancers. With advancing malignant progression, CLIC4 staining became undetectable in tumor cells, but expression increased in stromal cells coincident with up-regulation of alpha-smooth muscle actin, suggesting that CLIC4 is up-regulated in myofibroblasts. Coculture of cancer cells and fibroblasts induced the expression of both CLIC4 and alpha-smooth muscle actin in fibroblasts adjacent to tumor nests. Introduction of CLIC4 or nuclear targeted CLIC4 via adenovirus into human breast cancer xenografts inhibited tumor growth, whereas overexpression of CLIC4 in stromal cells of xenografts enhanced tumor growth. CONCLUSION: Loss of CLIC4 in tumor cells and gain in tumor stroma is common to many human cancers and marks malignant progression. Up-regulation of CLIC4 in tumor stroma is coincident with myofibroblast conversion, generally a poor prognostic indicator. Reactivation and restoration of CLIC4 in tumor cells or the converse in tumor stromal cells could provide a novel approach to inhibit tumor growth.

Actins↗
PubMed2003

PlasmoDB: exploring genomics and post-genomics data of the malaria parasite, Plasmodium falciparum.

The recent completion of the genome sequence of Plasmodium falciparum 3D7 provides the foundation for genome-wide analysis of the parasite. In addition to DNA and gene sequence data, postgenomic methods including microarray-based transcript profiling and high-throughput proteomics are now accessible to Plasmodium researchers. The Plasmodium Genome database ( ) was developed to provide rapid and convenient access to the terabytes of genomic-scale data now being generated around the world. All data are available in a relational framework, permitting convenient downloading, browsing, and analysis. Combinatorial use of data analysis tools enables powerful data mining queries, such as combining gene and protein expression data to monitor changes through various life-cycle stages. Functional predictions can be used to explore potential targets for antimalarial drug development. This report outlines the use of PlasmoDB to examine redox-active functions in Plasmodium.

Animals↗
PubMed2005

Is Melanoma a stem cell tumor? Identification of neurogenic proteins in trans-differentiated cells.

BACKGROUND: Although several genes and proteins have been implicated in the development of melanomas, the molecular mechanisms involved in the development of these tumors are not well understood. To gain a better understanding of the relationship between the cell growth, tumorigenesis and differentiation, we have studied a highly malignant cat melanoma cell line that trans-differentiates into neuronal cells after exposure to a feline endogenous retrovirus RD114. METHODS: To define the repertoire of proteins responsible for the phenotypic differences between melanoma and its counterpart trans-differentiated neuronal cells we have applied proteomics technology and compared protein profiles of the two cell types and identified differentially expressed proteins by 2D-gel electrophoresis, image analyses and mass spectrometry. RESULTS: The melanoma and trans-differentiated neuronal cells could be distinguished by the presence of distinct sets of proteins in each. Although approximately 60-70% of the expressed proteins were shared between the two cell types, twelve proteins were induced de novo after infection of melanoma cells with RD114 virus in vitro. Expression of these proteins in trans-differentiated cells was significantly associated with concomitant down regulation of growth promoting proteins and up-regulation of neurogenic proteins (p = < 0.001). Based on their physiologic properties, >95% proteins expressed in trans-differentiated cells could be associated with the development, differentiation and regulation of nervous system cells. CONCLUSION: Our results indicate that the cat melanoma cells have the ability to differentiate into distinct neuronal cell types and they express proteins that are essential for self-renewal. Since melanocytes arise from the neural crest of the embryo, we conclude that this melanoma arose from embryonic precursor stem cells. This model system provides a unique opportunity to identify domains of interactions between the expressed proteins that halt the tumorigenic potential of melanoma cells and drive them toward neurogenerative pathways involved in early neurogenesis. A better understanding of these proteins in a well-coordinated signaling network would also help in developing novel approaches for suppression of highly malignant tumors that arise from stem-like embryonic cells.

Journal Article↗
PubMed2005

Identification of serum amyloid A as a biomarker to distinguish prostate cancer patients with bone lesions.

BACKGROUND: Prostate cancer has a propensity to metastasize to the bone. Currently, there are no curative treatments for this stage of the disease. Sensitive biomarkers that can be monitored in the blood to indicate the presence or development of bone metastases and/or response to therapies are lacking. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) is an affinity-based approach that allows sensitive and high-throughput protein profiling and screening of biological samples. METHODS: We used SELDI-TOF MS for protein profiling of sera from prostate cancer patients (n = 38) with and without bone metastases in our effort to identify individual or multiple serum markers that may be of added benefit to those in current use. Serum was applied to ProteinChip surfaces (H4 and IMAC) to quickly screen samples and detect peaks predominating in the samples obtained from patients with bone metastases. Unique proteins in the bone metastasis cohort observed by SELDI-TOF MS were identified by two-dimensional gel electrophoresis, in-gel trypsin digestion, and tandem MS. The identities of the proteins were confirmed by ELISA and immunodepletion assays. RESULTS: The cluster of unique proteins in the sera of patients with bone metastases was identified as isoforms of serum amyloid A. Machine-learning algorithms were also used to identify patients with bone metastases with a sensitivity and specificity of 89.5%. CONCLUSIONS: SELDI-TOF MS protein profiling in combination with other proteomic approaches may provide diagnostic tools with potential clinical applications and serve as tools to aid in the discovery of biomarkers associated with various diseases.

Aged↗
PubMed2003

Pharmacogenomics, genetic testing and ethnic variability: tackling the ethical questions.

Dr Winkelmann is the Head of the Cooperation Unit for Pharmacogenomics and Applied Genomics in Heidelberg, which was founded in 2001 by the Department of Internal Medicine VI and the Coordination Centre for Clinical Trials at the University of Heidelberg. His main interests are sophisticated phenotyping procedures for patient characterization and the conduct of multicenter clinical trials according to international standards with state-of-the-art data management. He currently applies new genomic tools in order to achieve progress in personalized medicine using collaborating networks of general practitioners for patient enrollment. The focus of his research group is on the common complex genetic cardiovascular and metabolic diseases ranging from coronary artery disease, dyslipidemia and hypertension, to metabolic syndrome and diabetes mellitus. In collaboration with partners from biotech, the genomic techniques used in clinical studies include haplotyping of candidate genes, gene expression profiling of peripheral leucocytes and proteomics in order to identify new biomarkers of effect in therapeutic studies or pathway/target gene identification in disease-specific family studies using microarray-based linkage approaches. An innovative web-based remote data entry system with an integrated pedigree drawing tool is used in the family studies. Dr Winkelmann is also involved as the clinical database coordinator for a European Framework VI research initiative of leading European centers in cardiovascular genetics for identification of risk genes for atherothrombosis in coronary artery disease by transcriptome and proteome analysis and high throughput exon resequencing at the Wellcome Trust Sanger Institute, Cambridge, UK.

Cardiovascular Diseases↗
PubMed2005

Microarray-based functional protein profiling using peptide nucleic acid-encoded libraries.

The availability of complete genome sequences from numerous organisms has provided investigators with the challenge of assigning physiologic functions to the encoded gene products. To facilitate this process, multiple technologies have been developed to profile the transcriptome and the proteome, including methods to monitor the function of enzymes in complex biologic systems. These methods typically target specific classes of enzymes and attempt to correlate the enzymatic activity with the specific phenotype of interest. Here, technologies to measure enzymatic activity on a subproteomic scale are reviewed, including the authors' own efforts, which are based on self-assembled microarrays utilizing peptide nucleic acid-encoded small-molecule libraries.

Animals↗
PubMed2002

Molecular markers in prostate cancer: the role in preoperative staging.

Radical prostatectomy as a primary treatment for clinically localized prostate cancer has increased dramatically over the past decade due to prostate-specific antigen (PSA) screening and the awareness of the increased incidence of localized disease. Despite the stage migration to increase clinically localized disease, there are still vast numbers of men who harbor occult extraprostatic extension and develop recurrence after surgery. The study of molecular markers in the blood or tissue of surgical patients prior to treatment, called " molecular staging, " is the focus of this review. The reverse transcriptase- polymerase chain reaction (RT-PCR) test for PSA gene expression in peripheral blood or bone marrow has received considerable attention since its first report in 1992. The test detects messenger RNA species for prostate-specific/abundant genes such as PSA and prostate-specific membrane antigen. These messenger RNAs were not detected in normal blood or bone marrow, but were detected in some prostate cancer patients presumably due to circulating prostatic epithelial cells. These prostate epithelial cells are thought to be occult metastases cells, and early studies correlated a positive RT-PCR test with surgical pathology adverse features such as positive margins. Despite the many studies over the past few years, there have been inconsistent results, and the most recent studies have not been able to confirm clinical utility. Bone marrow RT-PCR has been more promising; however, it is still a research tool that needs further study. The study of molecular markers in tissue material, ie, prostate biopsy samples prior to radical prostatectomy, is problematic due to the sampling error inherent in a multifocal heterogeneous tumor such as prostate cancer. The tumor suppressor proteins p53 and p27, Bcl-2 oncoprotein, Ki-67 proliferation index protein, E-cadherin, and microvessel density have been assessed in preradical prostatectomy needle biopsy. Results have been conflicting, and none are yet accepted as a clinically useful marker. Current and future work is focusing on analysis of multiple gene expressions or proteins simultaneously via gene chip or proteomics technology. While these expression profiles might be of value in whole prostate surgical specimens where tissues are well characterized, it is unclear how this new technology will be applied to the needle biopsy samples. Although molecular staging of radical prostatectomy patients has been under study for a decade, all assays remain research tools. Still, this area holds great promise for improving the accuracy of staging and providing a more accurate prognosis of individual men with clinically localized prostate cancer.

Biomarkers, Tumor↗
PubMedDate not supplied

The immunopathogenesis of multiple sclerosis.

Multiple sclerosis (MS) is a T cell-mediated autoimmune disease that is triggered by unknown exogenous agents in subjects with a specific genetic background. Genes of the major histocompatibility complex class II region are the only ones that have been consistently associated with the disease. However, susceptibility is probably mediated by a heterogeneous array of genes, which demonstrate epistatic interactions. Furthermore, an infectious etiology of MS has been suggested, and it is likely that infectious agents shape the immune response against self-antigens. Composition of plaques, response to therapy, and data from animal models indicate that MS is mediated by myelin-specific CD4 T cells that, upon activation, invade the central nervous system and initiate the disease. Different patterns of tissue damage have been shown in active MS lesions, suggesting that the mechanisms of injury are probably distinct in different subgroups of patients. Heterogeneity in clinical characteristics, magnetic resonance imaging, and response to therapies support this notion. The experience gained during several pharmacological studies has improved our understanding of the pathogenesis of MS. New tools, such as gene expression profiling with cDNA microarrays and proteomics, together with advancements in imaging techniques may help us to identify susceptibility genes and disease markers, which may enable us to design more effective therapies and to tailor them according to different disease forms or stages.

Autoimmune Diseases↗
PubMed2006

Proteomic analysis of malignant ovarian cancer effusions as a tool for biologic and prognostic profiling.

PURPOSE: Malignant epithelial ovarian cancer effusions are important in disease dissemination and clinical outcome. The identification of biochemical events active in effusions may improve our identification and application of targeted therapeutics. EXPERIMENTAL DESIGN: Archival effusion samples for which outcome information was known were studied. Clinical variables were comparable between these groups. Two cohorts of patients with malignant effusion were assessed: those with effusion at presentation (Tap1) or at first recurrence (Tap2). Expression and activated fraction of selected signaling proteins were quantitated on serial protein microarrays using validated antibodies. Proteomic results and clinical variables were analyzed by univariate analysis followed by Cox proportional hazards model analysis. RESULTS: Malignant effusions (>80% malignant cells) were distinguished from benign effusions by higher expression of AKT, activated extracellular signal-regulated kinase, activated (P < or = 0.001) and total cAMP-responsive element binding protein (P = 0.01), and JNK (P = 0.03). Malignant pleural effusions could not be differentiated from ascites by signaling profiles. Both had signal expression clusters for survival, proliferation and metastasis, and injury pathways. Cox proportional hazards model analysis revealed high p38 and pEGFR/EGFR ratio as jointly associated with poor survival in Tap1 cases (both P < or = 0.002). Phospho-JNK quantity was associated with worse outcome in Tap2 patients (P = 0.004), when taking other factors into consideration. CONCLUSIONS: Proliferation, survival, and apoptosis signaling dysregulation can be identified in ovarian cancer effusion samples. Biochemical characterization of clinical effusions may provide either predictive and/or correlative information on patient outcome from which to further understand the mechanisms of effusion development and target clinical intervention.

Apoptosis↗
PubMed2004

Identification of patients with head and neck cancer using serum protein profiles.

BACKGROUND: New and more consistent biomarkers of head and neck squamous cell carcinoma (HNSCC) are needed to improve early detection of disease and to monitor successful patient management. OBJECTIVE: To determine if a new proteomic technology can correctly identify protein expression profiles for cancer in patient serum samples as well as detect the presence of a known tumor marker. DESIGN: Direct proteomic analysis and comparison. METHODS: The surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF) ProteinChip system was used to screen for differentially expressed proteins in serum samples from 99 patients with HNSCC, 25 "healthy" smokers, and 102 healthy (normal) controls. Protein peak clustering and classification analyses of the SELDI spectral data were performed. RESULTS: Several proteins, with masses ranging from 2778 to 20,800 Da, were differentially expressed between patients with HNSCC and the normal controls. The serum protein expression profiles were used to develop a classification tree algorithm, which achieved a sensitivity of 83.3% and a specificity of 90% in discriminating HNSCC from normal and healthy smoker controls. The positive and negative predictive values were 80% and 92%, respectively. A peak with an average mass of 10,068 Da was detected in sera from HNSCC patients and identified as the known biomarker metallopanstimulin-1 (MPS-1), based on mass. Peak relative intensity of the 10,068-Da protein correlated consistently with MPS-1 levels detected by radioimmunoassay in serum samples of HNSCC patients and controls. The 10,068-Da peak was provisionally identified as MPS-1 by SELDI immunoassay. CONCLUSION: We propose that this technique may allow for the development of a reliable screening test for the early detection and diagnosis of HNSCC, as well as the potential identification of tumor biomarkers.

Biomarkers, Tumor↗
PubMed2005

Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression.

Molecular profiling of cancer at the transcript level has become routine. Large-scale analysis of proteomic alterations during cancer progression has been a more daunting task. Here, we employed high-throughput immunoblotting in order to interrogate tissue extracts derived from prostate cancer. We identified 64 proteins that were altered in prostate cancer relative to benign prostate and 156 additional proteins that were altered in metastatic disease. An integrative analysis of this compendium of proteomic alterations and transcriptomic data was performed, revealing only 48%-64% concordance between protein and transcript levels. Importantly, differential proteomic alterations between metastatic and clinically localized prostate cancer that mapped concordantly to gene transcripts served as predictors of clinical outcome in prostate cancer as well as other solid tumors.

Disease Progression↗
PubMed2004

Mapping enzyme active sites in complex proteomes.

Genome sequencing projects have uncovered many novel enzymes and enzyme classes for which knowledge of active site structure and mechanism is limited. To facilitate mechanistic investigations of the numerous enzymes encoded by prokaryotic and eukaryotic genomes, new methods are needed to analyze enzyme function in samples of high biocomplexity. Here, we describe a general strategy for profiling enzyme active sites in whole proteomes that utilizes activity-based chemical probes coupled with a gel-free analysis platform. We apply this gel-free strategy to identify the sites of labeling on enzymes targeted by sulfonate ester probes. For each enzyme examined, probe labeling was found to occur on a conserved active site residue, including catalytic nucleophiles (e.g., C32 in glutathione S-transferase omega) and bases/acids (e.g., E269 in aldehyde dehydrogenase-1; D204 in enoyl CoA hydratase-1), as well as residues of unknown function (e.g., D127 in 3 beta-hydroxysteroid dehydrogenase/isomerase-1). These results reveal that sulfonate ester probes are remarkably versatile activity-based profiling reagents capable of labeling a diversity of catalytic residues in a range of mechanistically distinct enzymes. More generally, the gel-free strategy described herein, by consolidating into a single step the identification of both protein targets of activity-based probes and the specific residues labeled by these reagents, provides a novel platform in which the proteomic comparison of enzymes can be accomplished in unison with a mechanistic analysis of their active sites.

Aldehyde Dehydrogenase↗