PubMed Health⌕ Search

Biomedical subjects

Akhilesh Pandey

Publications and source records attributed to Akhilesh Pandey.

At least 37 records · Page 2Linked to original sources
PubMed2005

A proteomic analysis of salivary glands of female Anopheles gambiae mosquito.

Understanding the development of the malaria parasite within the mosquito vector at the molecular level should provide novel targets for interrupting parasitic life cycle and subsequent transmission. Availability of the complete genomic sequence of the major African malaria vector, Anopheles gambiae, allows discovery of such targets through experimental as well as computational methods. In the female mosquito, the salivary gland tissue plays an important role in the maturation of the infective form of the malaria parasite. Therefore, we carried out a proteomic analysis of salivary glands from female An. gambiae mosquitoes. Salivary gland extracts were digested with trypsin using two complementary approaches and analyzed by LC-MS/MS. This led to identification of 69 unique proteins, 57 of which were novel. We carried out a functional annotation of all proteins identified in this study through a detailed bioinformatics analysis. Even though a number of cDNA and Edman degradation-based approaches to catalog transcripts and proteins from salivary glands of mosquitoes have been published previously, this is the first report describing the application of MS for characterization of the salivary gland proteome. Our approach should prove valuable for characterizing proteomes of parasites and vectors with sequenced genomes as well as those whose genomes are yet to be fully sequenced.

Animals↗
PubMed2005

Plasma Proteome Database as a resource for proteomics research.

Plasma is one of the best studied compartments in the human body and serves as an ideal body fluid for the diagnosis of diseases. This report provides a detailed functional annotation of all the plasma proteins identified to date. In all, gene products encoded by 3778 distinct genes were annotated based on proteins previously published in the literature as plasma proteins and the identification of multiple peptides from proteins under HUPO's Plasma Proteome Project. Our analysis revealed that 51% of these genes encoded more than one protein isoform. All single nucleotide polymorphisms involving protein-coding regions were mapped onto the protein sequences. We found a number of examples of isoform-specific subcellular localization as well as tissue expression. This database is an attempt at comprehensive annotation of a complex subproteome and is available on the web at http://www.plasmaproteomedatabase.org.

Amino Acid Motifs↗
PubMed2005

A functional annotation of subproteomes in human plasma.

The data collected by Human Proteome Organization's Plasma Proteome Pilot project phase was analyzed by members of our working group. Accordingly, a functional annotation of the human plasma proteome was carried out. Here, we report the findings of our analyses. First, bioinformatic analyses were undertaken to determine the likely sources of plasma proteins and to develop a protein interaction network of proteins identified in this project. Second, annotation of these proteins was performed in the context of functional subproteomes involved in the coagulation pathway, the mononuclear phagocytic system, the inflammation pathway, the cardiovascular system, and the liver; as well as the subset of proteins associated with DNA binding activities. Our analyses contributed to the Plasma Proteome Database (http://www.plasmaproteomedatabase.org), an annotated database of plasma proteins identified by HPPP as well as from other published studies. In addition, we address several methodological considerations including the selective enrichment of post-translationally modified proteins by the use of multi-lectin chromatography as well as the use of peptidomic techniques to characterize the low molecular weight proteins in plasma. Furthermore, we have performed additional analyses of peptide identification data to annotate cleavage of signal peptides, sites of intra-membrane proteolysis and post-translational modifications. The HPPP-organized, multi-laboratory effort, as described herein, resulted in much synergy and was essential to the success of this project.

Blood Coagulation↗
PubMed2005

Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

Algorithms↗
PubMed2005

Bioinformatics and proteomics approaches for aging research.

Aging is a natural phenomenon that affects the entire physiology of an organism. Elucidating the molecular mechanisms underlying this complex process remains a major challenge today. Humans make poor models for research into aging because of their long life span. Thus, most of the current knowledge is through studies conducted in lower organisms. Large differences in life spans make it difficult to extrapolate the results of experiments carried out in model organisms to humans. Recent advances in genomic and proteomic technologies now permit generation of data pertaining to aging on a large-scale. In addition, several web-based community resources and databases are available that provide easy access to the available data. Use of bioinformatics and systems biology type of approaches provide a framework to start dissecting this complex biological phenomenon. Here, we discuss various genomic, transcriptomic and proteomic approaches that have the potential to provide a comprehensive mechanistic insight into the aging process.

Aging↗
PubMed2005

Probabilistic model of the human protein-protein interaction network.

A catalog of all human protein-protein interactions would provide scientists with a framework to study protein deregulation in complex diseases such as cancer. Here we demonstrate that a probabilistic analysis integrating model organism interactome data, protein domain data, genome-wide gene expression data and functional annotation data predicts nearly 40,000 protein-protein interactions in humans-a result comparable to those obtained with experimental and computational approaches in model organisms. We validated the accuracy of the predictive model on an independent test set of known interactions and also experimentally confirmed two predicted interactions relevant to human cancer, implicating uncharacterized proteins into definitive pathways. We also applied the human interactome network to cancer genomics data and identified several interaction subnetworks activated in cancer. This integrative analysis provides a comprehensive framework for exploring the human protein interaction network.

Chromosome Mapping↗
PubMed2005

A bioinformatics analysis of protein tyrosine phosphatases in humans.

Protein tyrosine phosphatases (PTPs) cooperate with protein tyrosine kinases to regulate signal transduction pathways. Genome-wide surveys cataloging protein tyrosine phosphatases in humans have recently been carried out. Here, we present a bioinformatics analysis of protein tyrosine phosphatases in the human genome to examine their domain architecture, alternative splicing and pseudogenes. We present evidence that alternative transcripts exist for 25 out of 35 PTPs analyzed. These alternative transcripts include novel exons; skipped exons as well as cryptic donor/acceptor splice sites. We discovered a novel isoform of PTPN18 based on analysis of expressed sequence tags (ESTs). The deletion of 4 exons in the catalytic domain of the novel isoform may alter the enzymatic activity toward its substrates. We were able to experimentally validate 2 of our novel isoform predictions through RT-PCR. Finally, a user-friendly web-based resource that consolidates the gene and protein annotations for all human protein tyrosine phosphatases has been developed and is freely available at http://ptpr.ibioinformatics.org.

Alternative Splicing↗
PubMed2005

Insights into the role of histone H3 and histone H4 core modifiable residues in Saccharomyces cerevisiae.

The biological significance of recently described modifiable residues in the globular core of the bovine nucleosome remains elusive. We have mapped these modification sites onto the Saccharomyces cerevisiae histones and used a genetic approach to probe their potential roles both in heterochromatic regions of the genome and in the DNA repair response. By mutating these residues to mimic their modified and unmodified states, we have generated a total of 39 alleles affecting 14 residues in histones H3 and H4. Remarkably, despite the apparent evolutionary pressure to conserve these near-invariant histone amino acid sequences, the vast majority of mutant alleles are viable. However, a subset of these variant proteins elicit an effect on transcriptional silencing both at the ribosomal DNA locus and at telomeres, suggesting that posttranslational modification(s) at these sites regulates formation and/or maintenance of heterochromatin. Furthermore, we provide direct mass spectrometry evidence for the existence of histone H3 K56 acetylation in yeast. We also show that substitutions at histone H4 K91, K59, S47, and R92 and histone H3 K56 and K115 lead to hypersensitivity to DNA-damaging agents, linking the significance of the chemical identity of these modifiable residues to DNA metabolism. Finally, we allude to the possible molecular mechanisms underlying the effects of these modifications.

Alleles↗
PubMed2004

Differentially expressed genes in pancreatic ductal adenocarcinomas identified through serial analysis of gene expression.

Serial analysis of gene expression (SAGE) is a powerful tool for the discovery of novel tumor markers. The publicly available online SAGE libraries of normal and neoplastic tissues (http://www.ncbi.nlm.nih.gov/SAGE/) have recently been expanded; in addition, a more complete annotation of the human genome and better biocomputational techniques have substantially improved the assignment of differentially expressed SAGE "tags" to human genes. These improvements have provided us with an opportunity to re-evaluate global gene expression in pancreatic cancer using existing SAGE libraries. SAGE libraries generated from six pancreatic cancers were compared to SAGE libraries generated from 11 non-neoplastic tissues. Compared to normal tissue libraries, we identified 453 SAGE tags as differentially expressed in pancreatic cancer, including 395 that mapped to known genes and 58 "uncharacterized" tags. Of the 395 SAGE tags assigned to known genes, 223 were overexpressed in pancreatic cancer, and 172 were underexpressed. In order to map the 58 uncharacterized differentially expressed SAGE tags to genes, we used a newly developed resource called TAGmapper (http://tagmapper.ibioinformatics.org), to identify 16 additional differentially expressed genes. The differential expression of seven genes, involved in multiple cellular processes such as signal transduction (MIC-1), differentiation (DMBT1 and Neugrin), immune response (CD74), inflammation (CXCL2), cell cycle (CEB1) and enzymatic activity (Kallikrein 6), was confirmed by either immunohistochemical labeling of tissue microarrays (Kallikrein 6, CD74 and DMBT1) or by RT-PCR (CEB1, Neugrin, MIC1 and CXCL2). Of note, Neugrin was one of the genes whose previously uncharacterized SAGE tag was correctly assigned using TAGmapper, validating the utility of this program. Novel differentially expressed genes in a cancer type can be identified by revisiting updated and expanded SAGE databases. TAGmapper should prove to be a powerful tool for the discovery of novel tumor markers through assignment of uncharacterized SAGE tags.

Adenocarcinoma↗
PubMed2004

Identification of novel highly expressed genes in pancreatic ductal adenocarcinomas through a bioinformatics analysis of expressed sequence tags.

In most microarray experiments, a significant fraction of the differentially expressed mRNAs identified correspond to expressed sequence tags (ESTs) and are generally discarded from further analyses. We used careful bioinformatics analyses to characterize those ESTs that were found to be highly overexpressed in a series of pancreatic adenocarcinomas. cDNA was prepared from 60 non-neoplastic samples (normal pancreas [n = 20], normal colon [n = 10], or normal duodenal mucosal [n = 30]) and from 64 pancreatic cancers (resected cancers [n = 50] or cancer cell lines [n = 14]) and hybridized to the complete Affymetrix Human Genome U133 GeneChip(R) set (arrays U133A and B) for simultaneous analysis of 45,000 fragments corresponding to 33,000 known genes and 6,000 ESTs. The GeneExpress(R) software system Fold Change Analysis Tool was used and 60 ESTs were identified that were expressed at levels at least 3-fold greater in the pancreatic cancers as compared to normal tissues. Searches against the human genomic sequence and comparative genomic analysis of human and mouse genomes was carried out using basic local alignment search tools (BLAST), BLASTN, and BLASTX, for identifying protein coding genes corresponding to the ESTs. Subsequently, in order to pick the most relevant candidate genes for a more detailed analysis, we looked for domains/motifs in the open reading frames using SMART and Pfam programs. We were able to definitively map 43 of the 60 ESTs to known or novel genes, and 15 of the ESTs could be localized in close proximity to a gene in the human genome although we were unable to establish that the EST was indeed derived from those genes. The differential expression of a subset of genes was confirmed at the protein level by immunohistochemical labeling of tissue microarrays (inhibin beta A [INHBA] and CD29) and/or at the transcript level by RT-PCR (INHBA, AKAP12, ELK3, FOXQ1, EIF5A2, and EFNA5). We conclude that bioinformatics tools can be used to characterize differentially overexpressed ESTs, and that some of these ESTs may represent diagnostically and therapeutically useful targets that might be missed using data solely from currently annotated databases.

Adenocarcinoma↗
PubMed2004

Mac-2-binding protein is a diagnostic marker for biliary tract carcinoma.

BACKGROUND: Biliary tract carcinoma is a deadly disease, accounting for nearly 4500 malignancy-related deaths each year in the United States. Early detection has the potential to improve survival for patients with biliary tract malignancies, enabling curative surgical resection. Early detection approaches would benefit from an accurate, minimally invasive diagnostic test. To identify novel diagnostic markers, the authors recently completed a comprehensive proteomic study of bile samples from patients with biliary carcinoma. One of the proteins identified by tandem mass spectrometry was Mac-2-binding protein (Mac-2BP). The authors evaluated the performance of Mac-2BP and its ligand, galectin-3, as diagnostic markers for patients with biliary carcinoma. METHODS: Levels of Mac-2BP, galectin-3, and CA19-9 were measured using an enzyme-linked immunosorbent assay (ELISA) in bile samples from patients with biliary tract carcinoma (n = 26), benign biliary conditions (n = 32), and primary sclerosing cholangitis (n = 20). Serum levels of Mac-2BP and galectin-3 also were determined using ELISA. Mac-2BP tissue expression was investigated by immunohistochemical methods using a biliary carcinoma tissue microarray. RESULTS: Biliary Mac-2BP levels were elevated by a factor of approximately 3 in the biliary carcinoma group compared with the group of patients who had PSC or another type of nonneoplastic biliary disease. In contrast, Mac-2BP levels were not elevated in serum samples from patients with biliary carcinoma. According to the immunohistochemical analysis, Mac-2BP was expressed in 34 of 36 patients (94.4%) with biliary tract carcinoma. As a diagnostic marker for biliary carcinoma, Mac-2BP levels were as accurate as biliary CA19-9 levels, with an area under the curve (AUC) of 0.70 on receiver operator characteristic analysis. The use of both of these bile markers in combination, however, led to significantly better diagnostic accuracy compared with the accuracy achieved using CA19-9 alone (AUC, 0.75; P < 0.001). Serum and biliary galectin-3 levels did not differ in the biliary carcinoma group relative to the control groups. CONCLUSIONS: Biliary Mac-2BP levels, especially when used in conjunction with biliary CA19-9 levels, showed promise as a novel diagnostic marker for biliary tract carcinoma.

Aged↗
PubMed2004

Mouse embryonic fibroblasts derived from Odin deficient mice display a hyperproliiferative phenotype.

Odin is a recently identified cytosolic phosphotyrosine binding (PTB) domain containing negative regulatory protein, that was discovered on the basis of its ability to undergo tyrosine phosphorylation upon stimulation by epidermal growth factor in HeLa cells. The protein was originally obtained as a KIAA clone (KIAA 0229) from the Kazusa DNA Research Institute which maintains the HUGE protein database--a database devoted to the analysis of long cDNA clones encoding large proteins (>50 kDa). Odin has been demonstrated to cause downregulation of c-Fos promoter activity and to inhibit PDGF-induced mitogenesis in cell lines. To further investigate the role of Odin in growth factor receptor signaling and to elucidate its biological function in vivo, we have generated mice deficient in Odin by gene targeting. Odin-deficient mice do not display any obvious phenotype, and histological examination of the kidney, lung and liver does not show any major abnormalities as compared to wild-type controls. However, mouse embryonic fibroblasts (MEFs) generated from Odin-deficient mice exhibit a hyperproliferative phenotype compared to wild-type-derived MEFs, consistent with its role as a negative regulator of growth factor receptor signaling. Our results confirm that although Odin expression in mice is not essential for any major developmental pathway, it could play a significant functional role to negatively regulate growth factor receptor signaling pathways.

Adaptor Proteins, Signal Transducing↗
PubMed2004

A role for thymic stromal lymphopoietin in CD4(+) T cell development.

Thymic stromal lymphopoietin (TSLP) signals via a receptor comprising the interleukin (IL)-7 receptor alpha chain and a distinctive subunit, TSLP receptor (TSLPR), which is most related to the common cytokine receptor gamma chain, gamma(c). We have generated TSLPR knockout (KO) mice and found that although these mice had normal lymphocyte numbers, gamma(c)/TSLPR double KO mice had a greater lymphoid defect than gamma(c) KO mice. This indicates that TSLP contributes to lymphoid development and accounts for some of the residual lymphoid development in gamma(c) KO mice and presumably in patients with X-linked severe combined immunodeficiency. Injection of TSLP into gamma(c) KO mice induced the expansion of T and B cells. Moreover, sublethally irradiated TSLPR KO mice showed weaker recovery of lymphocyte populations than wild-type (WT) littermates, even when neutralizing anti-IL-7 antibodies were injected. Interestingly, TSLP preferentially stimulated the proliferation and survival of CD4(+) single positive thymocytes and peripheral T cells in vitro. Additionally, CD4(+) T cells from TSLPR KO mice expanded less efficiently than WT CD4(+) T cells in irradiated hosts, and TSLP preferentially expanded CD4(+) T cells both in vitro and in vivo. Thus, as compared with other known cytokines, TSLP is distinctive in exhibiting a lineage preference for the expansion and survival of CD4(+) T cells.

Animals↗
PubMed2004

Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression.

Many studies have used DNA microarrays to identify the gene expression signatures of human cancer, yet the critical features of these often unmanageably large signatures remain elusive. To address this, we developed a statistical method, comparative metaprofiling, which identifies and assesses the intersection of multiple gene expression signatures from a diverse collection of microarray data sets. We collected and analyzed 40 published cancer microarray data sets, comprising 38 million gene expression measurements from >3,700 cancer samples. From this, we characterized a common transcriptional profile that is universally activated in most cancer types relative to the normal tissues from which they arose, likely reflecting essential transcriptional features of neoplastic transformation. In addition, we characterized a transcriptional profile that is commonly activated in various types of undifferentiated cancer, suggesting common molecular mechanisms by which cancer cells progress and avoid differentiation. Finally, we validated these transcriptional profiles on independent data sets.

Cell Transformation, Neoplastic↗
PubMed2004

Universality in the vibrational spectra of single-component amorphous clusters.

We have numerically investigated the vibrational spectra of amorphous single-component clusters for several types of interactions among the particles. For all the potentials we have studied, we find that the density of states can be described, except at the two ends of the spectrum, by the same functional form to a very good approximation, and that the fluctuation properties of the spectra in this central region converge to those of the Gaussian orthogonal ensemble of random matrices with increasing system size. We conjecture that this scenario is true for a broad class of potentials.

Journal Article↗
PubMed2004

BioBuilder as a database development and functional annotation platform for proteins.

BACKGROUND: The explosion in biological information creates the need for databases that are easy to develop, easy to maintain and can be easily manipulated by annotators who are most likely to be biologists. However, deployment of scalable and extensible databases is not an easy task and generally requires substantial expertise in database development. RESULTS: BioBuilder is a Zope-based software tool that was developed to facilitate intuitive creation of protein databases. Protein data can be entered and annotated through web forms along with the flexibility to add customized annotation features to protein entries. A built-in review system permits a global team of scientists to coordinate their annotation efforts. We have already used BioBuilder to develop Human Protein Reference Database http://www.hprd.org, a comprehensive annotated repository of the human proteome. The data can be exported in the extensible markup language (XML) format, which is rapidly becoming as the standard format for data exchange. CONCLUSIONS: As the proteomic data for several organisms begins to accumulate, BioBuilder will prove to be an invaluable platform for functional annotation and development of customizable protein centric databases. BioBuilder is open source and is available under the terms of LGPL.

Computational Biology↗