Raghothama Chaerkady

Human Protein Reference Database—2009 update

Human Protein Reference Database (HPRD—http://www.hprd.org/), initially described in 2003, is a database of curated proteomic information pertaining to human proteins. We have recently added a number of new features in HPRD. These include PhosphoMotif Finder, which allows users to find the presence of over 320 experimentally verified phosphorylation motifs in proteins of interest. Another new feature is a protein distributed annotation system—Human Proteinpedia (http://www.humanproteinpedia.org/)—through which laboratories can submit their data, which is mapped onto protein entries in HPRD. Over 75 laboratories involved in proteomics research have already participated in this effort by submitting data for over 15 000 human proteins. The submitted data includes mass spectrometry and protein microarray-derived data, among other data types. Finally, HPRD is also linked to a compendium of human signaling pathways developed by our group, NetPath (http://www.netpath.org/), which currently contains annotations for several cancer and immune signaling pathways. Since the last update, more than 5500 new protein sequences have been added, making HPRD a comprehensive resource for studying the human proteome.

A draft map of the human proteome

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

Mutant proteins as cancer-specific biomarkers

Cancer biomarkers are currently the subject of intense research because of their potential utility for diagnosis, prognosis, and targeted therapy. In theory, the gene products resulting from somatic mutations are the ultimate protein biomarkers, being not simply associated with tumors but actually responsible for tumorigenesis. We show here that the altered protein products resulting from somatic mutations can be identified directly and quantified by mass spectrometry. The peptides expressed from normal and mutant alleles were detected by selected reaction monitoring (SRM) of their product ions using a triple-quadrupole mass spectrometer. As a prototypical example of this approach, we demonstrated that it is possible to quantify the number and fraction of mutant Ras protein present in cancer cell lines. There were an average of 1.3 million molecules of Ras protein per cell, and the ratio of mutant to normal Ras proteins ranged from 0.49 to 5.6. Similarly, we found that mutant Ras proteins could be detected and quantified in clinical specimens such as colorectal and pancreatic tumor tissues as well as in premalignant pancreatic cyst fluids. In addition to answering basic questions about the relative levels of genetically abnormal proteins in tumors, this approach could prove useful for diagnostic applications.

A quantitative proteomic approach for identification of potential biomarkers in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide. In this study, our objective was to identify differentially regulated proteins in HCC through a quantitative proteomic approach using iTRAQ. More than 600 proteins were quantitated of which 59 proteins were overexpressed and 92 proteins were underexpressed in HCC as compared to adjacent normal tissue. Several differentially expressed proteins were not implicated previously in HCC. A subset of these proteins (six each from upregulated and downregulated groups) was further validated using immunoblotting and immunohistochemical labeling. Some of the overexpressed proteins with no previous description in the context of HCC include fibroleukin, interferon induced 56 kDa protein, milk fat globule-EGF factor 8, and myeloid-associated differentiation marker. Interestingly, all the enzymes of urea metabolic pathway were dramatically downregulated. Immunohistochemical labeling confirmed differential expression of fibroleukin, myeloid associated differentiation marker and ornithine carbamoyl transferase in majority of HCC samples analyzed. Our results demonstrate quantitative proteomics as a robust discovery tool for the identification of differentially regulated proteins in cancers.

Temporal profiling of the adipocyte proteome during differentiation using a five-plex SILAC based strategy

The adipose tissue has important secretory and endocrine functions in humans. The regulation of adipocyte differentiation has been actively pursued using transcriptomic methods over the last several years. Quantitative proteomics has emerged as a promising approach to obtain temporal profiles of biological processes such as differentiation. Stable isotope labeling with amino acids in cell culture (SILAC) is a simple and robust method for labeling proteins in vivo. Here, we describe the development and application of a five-plex SILAC experiment using four different heavy stable isotopic forms of arginine to study the nuclear proteome and the secretome during the course of adipocyte differentiation. Tandem mass spectrometry analysis using a quadrupole time-of-flight instrument resulted in identification of a total 882 proteins from these two proteomes. Of these proteins, 427 were identified on the basis of one or more arginine-containing peptides that allowed quantitation. In addition to previously reported molecules that are differentially expressed during the process of adipogenesis (e.g., adiponectin and lipoprotein lipase), we identified several proteins whose differential expression during adipocyte differentiation has not been documented previously. For example, THO complex 4, a context-dependent transcriptional activator in the T-cell receptor alpha enhancer complex, showed highest expression at middle stage of adipogenesis, while SNF2 alpha, a chromatin remodeling protein, was downregulated upon initiation of adipogenesis and remained so during subsequent time points. This study using a 5-plex SILAC to investigate dynamics illustrates the power of this approach to identify differentially expressed proteins in a temporal fashion.

Comparisons of tyrosine phosphorylated proteins in cells expressing lung cancer-specific alleles of EGFR and KRAS.

We have used unbiased phosphoproteomic approaches, based on quantitative mass spectrometry using stable isotope labeling with amino acids in cell culture (SILAC), to identify tyrosine phosphorylated proteins in isogenic human bronchial epithelial cells (HBECs) and human lung adenocarcinoma cell lines, expressing either of the two mutant alleles of EGFR (L858R and Del E746-A750), or a mutant KRAS allele, which are common in human lung adenocarcinomas. Tyrosine phosphorylation of signaling molecules was greater in HBECs expressing the mutant EGFRs than in cells expressing WT EGFR or mutant KRAS. Receptor tyrosine kinases (such as EGFR, ERBB2, MET, and IGF1R), and Mig-6, an inhibitor of EGFR signaling, were more phosphorylated in HBECs expressing mutant EGFR than in cells expressing WT EGFR or mutant RAS. Phosphorylation of some proteins differed in the two EGFR mutant-expressing cells; for example, some cell junction proteins (β-catenin, plakoglobin, and E-cadherin) were more phosphorylated in HBECs expressing L858R EGFR than in cells expressing Del EGFR. There were also differences in degree of phosphorylation at individual tyrosine sites within a protein; for example, a previously uncharacterized phosphorylation site in the nucleotide-binding loop of the kinase domains of EGFR (Y727), ERBB2 (Y735), or ERBB4 (Y733), is phosphorylated significantly more in HBECs expressing the deletion mutant than in cells expressing the wild type or L858R EGFR. Signaling molecules not previously implicated in ERBB signaling, such as polymerase transcript release factor (PTRF), were also phosphorylated in cells expressing mutant EGFR. Bayesian network analysis of these and other datasets revealed that PTRF might be a potentially important component of the ERBB signaling network.

A comprehensive map of the human urinary proteome.

The study of the human urinary proteome has the potential to offer significant insights into normal physiology as well as disease pathology. The information obtained from such studies could be applied to the diagnosis of various diseases. The high sensitivity, resolution, and mass accuracy of the latest generation of mass spectrometers provides an opportunity to accurately catalog the proteins present in human urine, including those present at low levels. To this end, we carried out a comprehensive analysis of human urinary proteome from healthy individuals using high-resolution Fourier transform mass spectrometry. Importantly, we used the Orbitrap for detecting ions in both MS (resolution 60 000) and MS/MS (resolution 15 000) modes. To increase the depth of our analysis, we characterized both unfractionated as well as lectin-enriched proteins in our experiments. In all, we identified 1,823 proteins with less than 1% false discovery rate, of which 671 proteins have not previously been reported as constituents of human urine. This data set should serve as a comprehensive reference list for future studies aimed at identification and characterization of urinary biomarkers for various diseases.

Proteomic Analysis of Chinese Hamster Ovary Cells

To complement the recent genomic sequencing of Chinese hamster ovary (CHO) cells, proteomic analysis was performed on CHO cells including the cellular proteome, secretome, and glycoproteome using tandem mass spectrometry (MS/MS) of multiple fractions obtained from gel electrophoresis, multidimensional liquid chromatography, and solid phase extraction of glycopeptides (SPEG). From the 120 different mass spectrometry analyses generating 682,097 MS/MS spectra, 93,548 unique peptide sequences were identified with at most 0.02 false discovery rate (FDR). A total of 6164 grouped proteins were identified from both glycoproteome and proteome analysis, representing an 8-fold increase in the number of proteins currently identified in the CHO proteome. Furthermore, this is the first proteomic study done using the CHO genome exclusively, which provides for more accurate identification of proteins. From this analysis, the CHO codon frequency was determined and found to be distinct from humans, which will facilitate expression of human proteins in CHO cells. Analysis of the combined proteomic and mRNA data sets indicated the enrichment of a number of pathways including protein processing and apoptosis but depletion of proteins involved in steroid hormone and glycosphingolipid metabolism. Five-hundred four of the detected proteins included N-acetylation modifications, and 1292 different proteins were observed to be N-glycosylated. This first large-scale proteomic analysis will enhance the knowledge base about CHO capabilities for recombinant expression and provide information useful in cell engineering efforts aimed at modifying CHO cellular functions.

Proteogenomic Analysis of Mycobacterium tuberculosis By High Resolution Mass Spectrometry

The genome sequencing of H37Rv strain of Mycobacterium tuberculosis was completed in 1998 followed by the whole genome sequencing of a clinical isolate, CDC1551 in 2002. Since then, the genomic sequences of a number of other strains have become available making it one of the better studied pathogenic bacterial species at the genomic level. However, annotation of its genome remains challenging because of high GC content and dissimilarity to other model prokaryotes. To this end, we carried out an in-depth proteogenomic analysis of the M. tuberculosis H37Rv strain using Fourier transform mass spectrometry with high resolution at both MS and tandem MS levels. In all, we identified 3176 proteins from Mycobacterium tuberculosis representing ∼80% of its total predicted gene count. In addition to protein database search, we carried out a genome database search, which led to identification of ∼250 novel peptides. Based on these novel genome search-specific peptides, we discovered 41 novel protein coding genes in the H37Rv genome. Using peptide evidence and alternative gene prediction tools, we also corrected 79 gene models. Finally, mass spectrometric data from N terminus-derived peptides confirmed 727 existing annotations for translational start sites while correcting those for 33 proteins. We report creation of a high confidence set of protein coding regions in Mycobacterium tuberculosis genome obtained by high resolution tandem mass-spectrometry at both precursor and fragment detection steps for the first time. This proteogenomic approach should be generally applicable to other organisms whose genomes have already been sequenced for obtaining a more accurate catalogue of protein-coding genes.

Identification of miR-21 targets in breast cancer cells using a quantitative proteomic approach

MicroRNA (miRNA) play essential roles in biological processes ranging from cellular proliferation to apoptosis. Recently, miRNA have also been implicated in a number of diseases including cancers. However, the targets of most miRNA remain unknown. The majority of reports describing identification of miRNA targets are based on computational approaches or detection of altered mRNA levels despite the fact that most miRNA are thought to regulate their targets primarily at the level of translational inhibition in animals. miR‐21 is a miRNA with oncogenic activity that is involved in various cancer‐related processes such as invasion and migration. Given the importance of miR‐21 in tumorigenesis, we employed a quantitative proteomic strategy to systematically identify potential targets of miR‐21. By knocking down the expression of endogenous miR‐21 in MCF‐7 breast cancer cells, we observed an increase in the abundance of 58 proteins, implying that they could be potential targets of miR‐21. Validation of 12 of these candidate targets in luciferase assays showed that 6 of them were likely direct targets of miR‐21. Importantly, the mRNA of the majority of the candidate targets tested did not show a concomitant increase in abundance. Overall, our results demonstrate that miR‐21 affects the expression of many of its targets through translational inhibition and highlights the utility of proteomic approaches for identifying miRNA targets.