Trayambak Basak

Bio: Trayambak Basak is an academic researcher from Institute of Genomics and Integrative Biology. The author has contributed to research in topics: Proteomics & Medicine. The author has an hindex of 16, co-authored 34 publications receiving 696 citations. Previous affiliations of Trayambak Basak include Academy of Scientific and Innovative Research & Council of Scientific and Industrial Research.

Integrating transcriptome and proteome profiling: Strategies and applications

Abstract: Discovering the gene expression signature associated with a cellular state is one of the basic quests in majority of biological studies. For most of the clinical and cellular manifestations, these molecular differences may be exhibited across multiple layers of gene regulation like genomic variations, gene expression, protein translation and post-translational modifications. These system wide variations are dynamic in nature and their crosstalk is overwhelmingly complex, thus analyzing them separately may not be very informative. This necessitates the integrative analysis of such multiple layers of information to understand the interplay of the individual components of the biological system. Recent developments in high throughput RNA sequencing and mass spectrometric (MS) technologies to probe transcripts and proteins made these as preferred methods for understanding global gene regulation. Subsequently, improvements in "big-data" analysis techniques enable novel conclusions to be drawn from integrative transcriptomic-proteomic analysis. The unified analyses of both these data types have been rewarding for several biological objectives like improving genome annotation, predicting RNA-protein quantities, deciphering gene regulations, discovering disease markers and drug targets. There are different ways in which transcriptomics and proteomics data can be integrated; each aiming for different research objectives. Here, we review various studies, approaches and computational tools targeted for integrative analysis of these two high-throughput omics methods.

Role of α-crystallin B as a regulatory switch in modulating cardiomyocyte apoptosis by mitochondria or endoplasmic reticulum during cardiac hypertrophy and myocardial infarction

Abstract: Cardiac hypertrophy and myocardial infarction (MI) are two major causes of heart failure with different etiologies. However, the molecular mechanisms associated with these two diseases are not yet fully understood. So, this study was designed to decipher the process of cardiomyocyte apoptosis during cardiac hypertrophy and MI in vivo. Our study revealed that mitochondrial outer membrane channel protein voltage-dependent anion channel-1 (VDAC1) was upregulated exclusively during cardiac hypertrophy, whereas 78 kDa glucose-regulated protein (GRP78) was exclusively upregulated during MI, which is an important upstream regulator of the endoplasmic reticulum (ER) stress pathway. Further downstream analysis revealed that mitochondrial pathway of apoptosis is instrumental in case of hypertrophy, whereas ER stress-induced apoptosis is predominant during MI, which was confirmed by treatment with either siRNA against VDAC1 or ER stress inhibitor tauroursodeoxycholic acid (TUDCA). Very interestingly, our data also showed that the expression and interaction of small heat-shock protein α-crystallin B (CRYAB) with VDAC1 was much more pronounced during MI compared with either hypertrophy or control. The study demonstrated for the first time that two different organelles--mitochondria and ER have predominant roles in mediating cardiomyocyte death signaling during hypertrophy and MI, respectively, and activation of CRYAB acts as a molecular switch in bypassing mitochondrial pathway of apoptosis during MI.

A systematic analysis of eluted fraction of plasma post immunoaffinity depletion: implications in biomarker discovery.

Abstract: Plasma is the most easily accessible source for biomarker discovery in clinical proteomics. However, identifying potential biomarkers from plasma is a challenge given the large dynamic range of proteins. The potential biomarkers in plasma are generally present at very low abundance levels and hence identification of these low abundance proteins necessitates the depletion of highly abundant proteins. Sample pre-fractionation using immuno-depletion of high abundance proteins using multi-affinity removal system (MARS) has been a popular method to deplete multiple high abundance proteins. However, depletion of these abundant proteins can result in concomitant removal of low abundant proteins. Although there are some reports suggesting the removal of non-targeted proteins, the predominant view is that number of such proteins is small. In this study, we identified proteins that are removed along with the targeted high abundant proteins. Three plasma samples were depleted using each of the three MARS (Hu-6, Hu-14 and Proteoprep 20) cartridges. The affinity bound fractions were subjected to gelC-MS using an LTQ-Orbitrap instrument. Using four database search algorithms including MassWiz (developed in house), we selected the peptides identified at <1% FDR. Peptides identified by at least two algorithms were selected for protein identification. After this rigorous bioinformatics analysis, we identified 101 proteins with high confidence. Thus, we believe that for biomarker discovery and proper quantitation of proteins, it might be better to study both bound and depleted fractions from any MARS depleted plasma sample.

Comprehensive Characterization of Glycosylation and Hydroxylation of Basement Membrane Collagen IV by High-Resolution Mass Spectrometry

Abstract: Collagen IV is the main structural protein that provides a scaffold for assembly of basement membrane proteins. Posttranslational modifications such as hydroxylation of proline and lysine and glycosylation of lysine are essential for the functioning of collagen IV triple-helical molecules. These modifications are highly abundant posing a difficult challenge for in-depth characterization of collagen IV using conventional proteomics approaches. Herein, we implemented an integrated pipeline combining high-resolution mass spectrometry with different fragmentation techniques and an optimized bioinformatics workflow to study posttranslational modifications in mouse collagen IV. We achieved 82% sequence coverage for the α1 chain, mapping 39 glycosylated hydroxylysine, 148 4-hydroxyproline, and seven 3-hydroxyproline residues. Further, we employed our pipeline to map the modifications on human collagen IV and achieved 85% sequence coverage for the α1 chain, mapping 35 glycosylated hydroxylysine, 163 4-hydroxyproline, and 14 3-hydroxyproline residues. Although lysine glycosylation heterogeneity was observed in both mouse and human, 21 conserved sites were identified. Likewise, five 3-hydroxyproline residues were conserved between mouse and human, suggesting that these modification sites are important for collagen IV function. Collectively, these are the first comprehensive maps of hydroxylation and glycosylation sites in collagen IV, which lay the foundation for dissecting the key role of these modifications in health and disease.

Quantitative proteomic profiling of extracellular matrix and site-specific collagen post-translational modifications in an in vitro model of lung fibrosis

Abstract: Lung fibrosis is characterized by excessive deposition of extracellular matrix (ECM), in particular collagens, by fibroblasts in the interstitium. Transforming growth factor-β1 (TGF-β1) alters the expression of many extracellular matrix (ECM) components produced by fibroblasts, but such changes in ECM composition as well as modulation of collagen post-translational modification (PTM) levels have not been comprehensively investigated. Here, we performed mass spectrometry (MS)-based proteomics analyses to assess changes in the ECM deposited by cultured lung fibroblasts from idiopathic pulmonary fibrosis (IPF) patients upon stimulation with transforming growth factor β1 (TGF-β1). In addition to the ECM changes commonly associated with lung fibrosis, MS-based label-free quantification revealed profound effects on enzymes involved in ECM crosslinking and turnover as well as multiple positive and negative feedback mechanisms of TGF-β1 signaling. Notably, the ECM changes observed in this in vitro model correlated significantly with ECM changes observed in patient samples. Because collagens are subject to multiple PTMs with major implications in disease, we implemented a new bioinformatic platform to analyze MS data that allows for the comprehensive mapping and site-specific quantitation of collagen PTMs in crude ECM preparations. These analyses yielded a comprehensive map of prolyl and lysyl hydroxylations as well as lysyl glycosylations for 15 collagen chains. In addition, site-specific PTM analysis revealed novel sites of prolyl-3-hydroxylation and lysyl glycosylation in type I collagen. Interestingly, the results show, for the first time, that TGF-β1 can modulate prolyl-3-hydroxylation and glycosylation in a site-specific manner. Taken together, this proof of concept study not only reveals unanticipated TGF-β1 mediated regulation of collagen PTMs and other ECM components but also lays the foundation for dissecting their key roles in health and disease. The proteomic data has been deposited to the ProteomeXchange Consortium via the MassIVE partner repository with the data set identifier MSV000082958.

Addressing accuracy and precision issues in iTRAQ quantitation

Abstract: iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

Cardiovascular consequences of metabolic syndrome

Abstract: The metabolic syndrome (MetS) is defined as the concurrence of obesity-associated cardiovascular risk factors including abdominal obesity, impaired glucose tolerance, hypertriglyceridemia, decreased HDL cholesterol, and/or hypertension. Earlier conceptualizations of the MetS focused on insulin resistance as a core feature, and it is clearly coincident with the above list of features. Each component of the MetS is an independent risk factor for cardiovascular disease and the combination of these risk factors elevates rates and severity of cardiovascular disease, related to a spectrum of cardiovascular conditions including microvascular dysfunction, coronary atherosclerosis and calcification, cardiac dysfunction, myocardial infarction, and heart failure. While advances in understanding the etiology and consequences of this complex disorder have been made, the underlying pathophysiological mechanisms remain incompletely understood, and it is unclear how these concurrent risk factors conspire to produce the variety of obesity-associated adverse cardiovascular diseases. In this review, we highlight current knowledge regarding the pathophysiological consequences of obesity and the MetS on cardiovascular function and disease, including considerations of potential physiological and molecular mechanisms that may contribute to these adverse outcomes.