Jayshree Advani

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.

A network map of FGF-1/FGFR signaling system

Fibroblast growth factor-1 (FGF-1) is a well characterized growth factor among the 22 members of the FGF superfamily in humans. It binds to all the four known FGF receptors and regulates a plethora of functions including cell growth, proliferation, migration, differentiation, and survival in different cell types. FGF-1 is involved in the regulation of diverse physiological processes such as development, angiogenesis, wound healing, adipogenesis, and neurogenesis. Deregulation of FGF-1 signaling is not only implicated in tumorigenesis but also is associated with tumor invasion and metastasis. Given the biomedical significance of FGFs and the fact that individual FGFs have different roles in diverse physiological processes, the analysis of signaling pathways induced by the binding of specific FGFs to their cognate receptors demands more focused efforts. Currently, there are no resources in the public domain that facilitate the analysis of signaling pathways induced by individual FGFs in the FGF/FGFR signaling system. Towards this, we have developed a resource of signaling reactions triggered by FGF-1/FGFR system in various cell types/tissues. The pathway data and the reaction map are made available for download in different community standard data exchange formats through NetPath and NetSlim signaling pathway resources.

Annotation of the Zebrafish Genome through an Integrated Transcriptomic and Proteomic Analysis

Accurate annotation of protein-coding genes is one of the primary tasks upon the completion of whole genome sequencing of any organism. In this study, we used an integrated transcriptomic and proteomic strategy to validate and improve the existing zebrafish genome annotation. We undertook high-resolution mass-spectrometry-based proteomic profiling of 10 adult organs, whole adult fish body, and two developmental stages of zebrafish (SAT line), in addition to transcriptomic profiling of six organs. More than 7,000 proteins were identified from proteomic analyses, and ∼69,000 high-confidence transcripts were assembled from the RNA sequencing data. Approximately 15% of the transcripts mapped to intergenic regions, the majority of which are likely long non-coding RNAs. These high-quality transcriptomic and proteomic data were used to manually reannotate the zebrafish genome. We report the identification of 157 novel protein-coding genes. In addition, our data led to modification of existing gene structures including novel exons, changes in exon coordinates, changes in frame of translation, translation in annotated UTRs, and joining of genes. Finally, we discovered four instances of genome assembly errors that were supported by both proteomic and transcriptomic data. Our study shows how an integrative analysis of the transcriptome and the proteome can extend our understanding of even well-annotated genomes.

A multicellular signal transduction network of AGE/RAGE signaling.

Advanced glycation end products (AGEs) are heterogeneous glycated products of proteins, lipids and nucleotides. The major receptor for AGEs, known as receptor for advanced glycation end products (RAGE or AGER), is a multi-ligand transmembrane receptor of immunoglobulin superfamily. It has an extracellular region, a transmembrane domain and a short cytoplasmic domain. Extracellular region of RAGE consists of one V type (critical for ligand binding) and two C type immunoglobulin domains (Schmidt et al. 1994a, b). Although the short cytoplasmic tail of 43 amino acid residues is found to be important for the signaling events mediated by RAGE, it does not have any known domain or motif (Neeper et al. 1992). The other cell surface receptors for AGEs include dolichyl-diphosphooligosaccharide-protein glycosyltransferase (AGE-R1) (Li et al. 1996), protein kinase C substrate, 80KH phosphoprotein (AGE-R2) (Goh et al. 1996), galectin-3 (AGE-R3) (Vlassara et al. 1995), and class A macrophage scavenger receptors type I and II. RAGE is also considered as a pattern recognition receptor due to its ability to bind different AGEs. RAGE has numerous extracellular ligands in addition to AGEs, which include extracellular high mobility group box-1 (HMGB1), S100 family of calcium binding proteins and amyloid-beta peptide (Fritz 2011). RAGE is expressed in diverse tissues such as lung, heart, kidney, brain, and skeletal muscle and in a variety of cells including endothelial cells, macrophages/monocytes, neutrophils, and lymphocytes (Brett et al. 1993; Ding and Keller 2005; Neeper et al. 1992). RAGE has been implicated in the pathogenesis of diverse diseases such as diabetes, cardiovascular disorders, arthritis, cancers and neurological disorders (Yan et al. 2009). Interactions of AGEs with their receptors alter cell function through the generation of free radicals (Schmidt et al. 1994a, b). In diabetes, interaction of AGEs with RAGE induces oxidative stress and inflammatory reactions thereby resulting in vascular damage and related complications (Yamagishi 2011). RAGE also plays an important role in the progression of atherosclerosis through oxidative stress and proinflammatory responses (Sun et al. 2009). Expression of RAGE in synovial tissue, T cells, B cells and macrophages of arthritic patients implies its significance in inflammatory joint disorders (Drinda et al. 2005). Overexpression of RAGE has also been reported in various types of cancers such as pancreatic, gastric, breast, lung cancers and lymphoma (Logsdon et al. 2007). Knockdown of RAGE expression was shown to inhibit ductal neoplasia in an animal model of pancreatic cancer (DiNorcia et al. 2012). A recent study by Liang et al. reported that the inactivation of RAGE in colorectal cancer cells reduced angiogenesis (Liang et al. 2011). The signaling events mediated by RAGE are complex due to the diversity of its ligands and their diverse effects mediated in different cell types. AGE/RAGE signaling in endothelial cells is reported to modulate oxidative stress, inflammation, apoptosis, autophagy, endothelial-mesenchymal-transition, endothelial permeability and dysfunction (Toma et al. 2009; Xu et al. 2010; Li et al. 2011; Xie et al. 2011; Ma et al. 2010; Del Turco et al. 2011). In smooth muscle cells, AGE/RAGE interaction leads to generation of reactive oxygen species, autophagy, proliferation and calcification (Yoon et al. 2009; Hu et al. 2012; Yuan et al. 2011; Tanikawa et al. 2009). AGE/RAGE signaling is reported to mediate proliferation in lymphocytes (Takahashi et al. 2010). In fibroblasts, it induces migration, inflammation and apoptosis (Liu et al. 2010; Shimoda et al. 2011). A diverse array of molecules and signaling modules were identified to be activated by RAGE depending on the intensity and duration of RAGE ligation. Specific signaling modules such as ERK1/2 (Lander et al. 1997), p38 MAPK (Lander et al. 1997), CDC42/RAC (Bondeva et al. 2011), SAPK/JNK (Hu et al. 2012) and NF-κB (Liu et al. 2010) have been shown to be triggered by AGE/RAGE interaction in different cell types. Currently, there are no resources, which contain RAGE signaling pathway data for visualization and analysis. Therefore, we have gathered signaling pathway reactions induced by AGE/RAGE interaction in diverse cell types and tissues from literature. We have also cataloged genes transcriptionally regulated by AGE/RAGE system in humans along with their transcriptional regulators. We have provided the AGE/RAGE signaling pathway data to scientific community through NetPath (http://www.netpath.org), a resource of signaling pathways developed by us (Kandasamy et al. 2010).

Signaling Network Map of Endothelial TEK Tyrosine Kinase

TEK tyrosine kinase is primarily expressed on endothelial cells and is most commonly referred to as TIE2. TIE2 is a receptor tyrosine kinase modulated by its ligands, angiopoietins, to regulate the development and remodeling of vascular system. It is also one of the critical pathways associated with tumor angiogenesis and familial venous malformations. Apart from the vascular system, TIE2 signaling is also associated with postnatal hematopoiesis. Despite the involvement of TIE2-angiopoietin system in several diseases, the downstream molecular events of TIE2-angiopoietin signaling are not reported in any pathway repository. Therefore, carrying out a detailed review of published literature, we have documented molecular signaling events mediated by TIE2 in response to angiopoietins and developed a network map of TIE2 signaling. The pathway information is freely available to the scientific community through NetPath, a manually curated resource of signaling pathways. We hope that this pathway resource will provide an in-depth view of TIE2-angiopoietin signaling and will lead to identification of potential therapeutic targets for TIE2-angiopoietin associated disorders.

Identification of prosaposin and transgelin as potential biomarkers for gallbladder cancer using quantitative proteomics

Gallbladder cancer is an uncommon but lethal malignancy with particularly high incidence in Chile, India, Japan and China. There is a paucity of unbiased large-scale studies investigating molecular basis of gallbladder cancer. To systematically identify differentially regulated proteins in gallbladder cancer, iTRAQ-based quantitative proteomics of gallbladder cancer was carried out using Fourier transform high resolution mass spectrometry. Of the 2575 proteins identified, proteins upregulated in gallbladder cancer included several lysosomal proteins such as prosaposin, cathepsin Z and cathepsin H. Downregulated proteins included serine protease HTRA1 and transgelin, which have been reported to be downregulated in several other cancers. Novel biomarker candidates including prosaposin and transgelin were validated to be upregulated and downregulated, respectively, in gallbladder cancer using tissue microarrays. Our study provides the first large scale proteomic characterization of gallbladder cancer which will serve as a resource for future discovery of biomarkers for gallbladder cancer.

A network map of Interleukin-10 signaling pathway.

Interleukin-10 (IL-10) is an anti-inflammatory cytokine with important immunoregulatory functions. It is primarily secreted by antigen-presenting cells such as activated T-cells, monocytes, B-cells and macrophages. In biologically functional form, it exists as a homodimer that binds to tetrameric heterodimer IL-10 receptor and induces downstream signaling. IL-10 is associated with survival, proliferation and anti-apoptotic activities of various cancers such as Burkitt lymphoma, non-Hodgkins lymphoma and non-small scell lung cancer. In addition, it plays a central role in survival and persistence of intracellular pathogens such as Leishmania donovani, Mycobacterium tuberculosis and Trypanosoma cruzi inside the host. The signaling mechanisms of IL-10 cytokine are not well explored and a well annotated pathway map has been lacking. To this end, we developed a pathway resource by manually annotating the IL-10 induced signaling molecules derived from literature. The reactions were categorized under molecular associations, activation/inhibition, catalysis, transport and gene regulation. In all, 37 molecules and 76 reactions were annotated. The IL-10 signaling pathway can be freely accessed through NetPath, a resource of signal transduction pathways previously developed by our group.

Quantitative Proteomic and Phosphoproteomic Analysis of H37Ra and H37Rv Strains of Mycobacterium tuberculosis

Mycobacterium tuberculosis, the causative agent of tuberculosis, accounts for 1.5 million human deaths annually worldwide. Despite efforts to eradicate tuberculosis, it still remains a deadly disease. The two best characterized strains of M. tuberculosis, virulent H37Rv and avirulent H37Ra, provide a unique platform to investigate biochemical and signaling pathways associated with pathogenicity. To delineate the biomolecular dynamics that may account for pathogenicity and attenuation of virulence in M. tuberculosis, we compared the proteome and phosphoproteome profiles of H37Rv and H37Ra strains. Quantitative phosphoproteomic analysis was performed using high-resolution Fourier transform mass spectrometry. Analysis of exponential and stationary phases of these strains resulted in identification and quantitation of 2709 proteins along with 512 phosphorylation sites derived from 257 proteins. In addition to confirming the presence of previously described M. tuberculosis phosphorylated proteins, we identified 265 novel phosphorylation sites. Quantitative proteomic analysis revealed more than five-fold upregulation of proteins belonging to virulence associated type VII bacterial secretion system in H37Rv when compared to those in H37Ra. We also identified 84 proteins, which exhibited changes in phosphorylation levels between the virulent and avirulent strains. Bioinformatics analysis of the proteins altered in their level of expression or phosphorylation revealed enrichment of pathways involved in fatty acid biosynthesis and two-component regulatory system. Our data provides a resource for further exploration of functional differences at molecular level between H37Rv and H37Ra, which will ultimately explain the molecular underpinnings that determine virulence in tuberculosis.

Synovial fluid proteome in rheumatoid arthritis

BackgroundRheumatoid arthritis (RA) is a chronic autoinflammatory disorder that affects small joints. Despite intense efforts, there are currently no definitive markers for early diagnosis of RA and for monitoring the progression of this disease, though some of the markers like anti CCP antibodies and anti vimentin antibodies are promising. We sought to catalogue the proteins present in the synovial fluid of patients with RA. It was done with the aim of identifying newer biomarkers, if any, that might prove promising in future.MethodsTo enrich the low abundance proteins, we undertook two approaches—multiple affinity removal system (MARS14) to deplete some of the most abundant proteins and lectin affinity chromatography for enrichment of glycoproteins. The peptides were analyzed by LC–MS/MS on a high resolution Fourier transform mass spectrometer.ResultsThis effort was the first total profiling of the synovial fluid proteome in RA that led to identification of 956 proteins. From the list, we identified a number of functionally significant proteins including vascular cell adhesion molecule-1, S100 proteins, AXL receptor protein tyrosine kinase, macrophage colony stimulating factor (M-CSF), programmed cell death ligand 2 (PDCD1LG2), TNF receptor 2, (TNFRSF1B) and many novel proteins including hyaluronan-binding protein 2, semaphorin 4A (SEMA4D) and osteoclast stimulating factor 1. Overall, our findings illustrate the complex and dynamic nature of RA in which multiple pathways seems to be participating actively.ConclusionsThe use of high resolution mass spectrometry thus, enabled identification of proteins which might be critical to the progression of RA.

An integrated map of corticotropin-releasing hormone signaling pathway

Corticotropin-releasing hormone (CRH), also known as corticotropin-releasing factor (CRF), is a 41-amino acid neuropeptide, expressed abundantly by CRH neurons present in the paraventricular nucleus (PVN) of the hypothalamus, and other parts of the brain (Aguilera and Liu 2012; Vale et al. 1981). CRH is also expressed in adrenal gland, immune cells, placenta, testis, spleen, gut, thymus and skin (Dautzenberg and Hauger 2002; Aguilera and Liu 2012). The activity of the hypothalamic CRH neurons varies in resting and stress conditions. Circadian variations have an effect on CRH neuron activity. On stressful stimuli, sensory information is either transmitted directly to the PVN or integrated by the limbic system and transmitted to the CRH neurons via complex monoaminergic and peptidergic neural pathways. This is dependent on the nature, intensity and duration of the stressor. Systemic and metabolic stressors including blood loss, pain, immune challenge and hypoglycemia, which require immediate response, utilize monosynaptic pathways, whereas, psychogenic stressors utilize complex multisynaptic pathways. These neural pathways trigger signaling in CRH neurons, increasing CRH gene transcription and rapid CRH secretion (Aguilera and Liu 2012). The actions of CRH are transduced through CRH receptors, which belong to the class II/secretin-like family of the G-protein coupled receptor (GPCR) superfamily (Martin et al. 2005). There are three types of CRH receptors – type 1 (CRHR1), type 2 (CRHR2) and type 3 (CRHR3). Among these, CRHR3 has not been identified in mammals. CRHR1 and CRHR2 are encoded by different genes. CRHR1 mRNA has several splice variants encoding different isoforms – R1α, R1β, R1c, R1d, R1e, R1f, R1g and R1h, predominant of which is CRHR1α (Chen et al. 1993; Ross et al. 1994; Grammatopoulos et al. 1999; Pisarchik and Slominski 2001, 2004). CRHR1 is expressed predominantly in the CNS, pituitary, heart (Chen et al. 1993) and also in adrenal gland, ovary, and placenta (Grammatopoulos et al. 1999; Seres et al. 2004; Asakura et al. 1997). The gene encoding the human CRHR2 has three mRNA splice variants which encodes 3 isoforms - R2α, R2β and R2γ and is expressed predominantly in brain and heart (Kostich et al. 1998; Yang et al. 2010). CRH is a high-affinity ligand of CRHR1. It also binds to CRHR2, but with lower affinity (Hsu and Hsueh 2001; Grammatopoulos et al. 1999; Wille et al. 1999). CRH receptors do not have any intrinsic kinase activity and the signal is transduced via the heterotrimeric G-proteins (Freissmuth et al. 1989). Biological activity of CRH is regulated by CRH binding protein (CRHBP), which by binding to the former with high affinity, makes it unavailable for binding to CRH receptors (Potter et al. 1991; Behan et al. 1995; Seasholtz et al. 2002). CRHBP is expressed in high levels in the brain, heart, lungs, and placenta (Potter et al. 1991; Behan et al. 1995; Binder and Nemeroff 2010). CRH exerts its functions through activation of several signaling pathways including adenylate cyclase/protein kinase A (PKA), phospholipase C (PLC)/protein kinase C (PKC), and mitogen-activated protein kinase (MAPK) pathways. CRH, as a principal mediator of endocrine stress response, activates the HPA axis (Hypothalamic–pituitary–adrenal axis) by binding to the CRHR1 in the anterior pituitary. This, through a cascade of reactions, increases the expression of proopiomelanocortin (POMC) gene and the subsequent release of POMC-derived peptides, adrenocorticotropic hormone (ACTH) and β-endorphin. ACTH, in turn, stimulates the secretion of glucocorticoids from adrenal cortex (Vale et al. 1981). CRH is involved in the etiologies of several stress-related physiological responses and behavioral responses, such as altered blood pressure, increased arousal, enhanced learning, thermogenesis, anxiogenesis, anhendonia, reduced sleep, psychomotor alterations, decreased appetite and libido (Binder and Nemeroff 2010). CRH, upon binding to hippocampal CRHR1, mediates stress-induced enhancement of fear conditioning and learning. In contrast, CRH by binding to the lateral septal CRHR2 mediates stress-induced anxiety and impairs fear conditioning and learning (Radulovic et al. 1999). Pro-inflammatory and anti-inflammatory responses are exerted through peripheral and central CRH, respectively (Karalis et al. 1991; Friedman and Irwin 2001). Binding of peripheral and central CRH to their receptors were implicated in hemodynamic actions (Yang et al. 2010). Endometrial CRH was found to be involved in stromal cell decidualization during estrus cycle (Zoumakis et al. 2000) and also in implantation of blastocyst (Athanassakis et al. 1999). Placental CRH is involved in the maintenance of pregnancy and onset of labor (McLean et al. 1995). Excess secretion of CRH during severe depression and its association with increased levels of cortisol have been observed (Widerlov et al. 1988). CRH was also reported to be involved in anxiety disorders (Roy-Byrne et al. 1986), and anorexia nervosa (Connan et al. 2007). Decrease in cortical CRH content was observed in Alzheimer’s disease (Heilig et al. 1995) and Parkinson’s disease (Suemaru et al. 1995). Diverse aspects of CRH signaling have been well-studied. Owing to its high biological significance, a detailed documentation of all molecular reactions in a centralized resource and depiction of these reactions into a pathway map is desired in the public domain. Therefore, we have curated each pathway reaction reported downstream to CRH-CRHR interaction and submitted a detailed CRH signaling pathway data to the NetPath (http://www.netpath.org) (Kandasamy et al. 2010). Several such ligand-receptor signaling pathways including Leptin (Nanjappa et al. 2011), TWEAK (Bhattacharjee et al. 2012) and Prolactin (Radhakrishnan et al. 2012), had been developed by our group and submitted to NetPath. Here, we describe the generation of an integrated pathway map of CRH signaling by manual curation.