Delineating protein biomarkers for gastric cancers: A catalogue of mass spectrometry-based markers and assessing their suitability for targeted proteomics applications.

Gastric cancer (GC) is a global health concern. To facilitate improved management of GCs protein biomarkers have been identified through mass spectrometry-based proteomics platforms. In order to exhibit clinical utility of such data, we congregated over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the mass spectrometry platforms, association of the protein with infectious agents, protein identifiers, sample size and clinical characters of samples used with details on validation. Development of targeted proteomics methods is the cornerstone for pursuing these markers into clinical utility. Therefore, we developed Protein Biomarker Matrix for Gastric Cancer (PBMGC), a simple catalogue of robustness of each protein. This analysis yielded the identification of robust tissue, serum, urine and prognostic protein panels which can be further tested for their clinical utility. We also ascertained proteotypic tryptic peptides of 5631 proteins suitable for developing MRM assays. Extensive characterization of these peptides was carried out to record peptide ions, mass/charge and enhanced specific peptide features. With the vision of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). Users can browse and download the data and improve GCPDB by submitting recently published data. SIGNIFICANCE: Mass spectrometry-based proteomics platforms have accumulated substantial data on protein differential regulation in gastric cancer (GC) clinical samples. The utility of such data in clinical applications is limited by search for suitable biomarker panels for assessing GCs. We assembled over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the corresponding details including mass spectrometry platforms, status on the association of the protein with infectious agents, protein identifiers from different databases, sample size and clinical characters of samples used in test and control conditions along with details on their validation. Towards the vision of utilizing these markers in clinical assays, Protein Biomarker Matrix for Gastric Cancer (PBMGC) was developed and clinically relevant multi-protein panels were identified. We also demonstrated identification and characterization of tryptic proteotypic tryptic peptides of 5631 proteins biomarkers of GCs which are suitable for development of multiple reaction monitoring (MRM) assays in a SCIEX QTRAP instrument. With the moto of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). The users can browse and download details on different markers and improve GCPDB by submitting recently published data. Such an analysis could lay a cornerstone for building more such resources or conduct such analysis in different clinical conditions to uptake and develop targeted proteomics as the method of choice for clinical applications.

Proteomics Analysis of Duck Lung Tissues in Response to Highly Pathogenic Avian Influenza Virus.

Domestic ducks (Anas platyrhynchos domesticus) are resistant to most of the highly pathogenic avian influenza virus (HPAIV) infections. In this study, we characterized the lung proteome and phosphoproteome of ducks infected with the HPAI H5N1 virus (A/duck/India/02CA10/2011/Agartala) at 12 h, 48 h, and 5 days post-infection. A total of 2082 proteins were differentially expressed and 320 phosphorylation sites mapping to 199 phosphopeptides, corresponding to 129 proteins were identified. The functional annotation of the proteome data analysis revealed the activation of the RIG-I-like receptor and Jak-STAT signaling pathways, which led to the induction of interferon-stimulated gene (ISG) expression. The pathway analysis of the phosphoproteome datasets also confirmed the activation of RIG-I, Jak-STAT signaling, NF-kappa B signaling, and MAPK signaling pathways in the lung tissues. The induction of ISG proteins (STAT1, STAT3, STAT5B, STAT6, IFIT5, and PKR) established a protective anti-viral immune response in duck lung tissue. Further, the protein-protein interaction network analysis identified proteins like AKT1, STAT3, JAK2, RAC1, STAT1, PTPN11, RPS27A, NFKB1, and MAPK1 as the main hub proteins that might play important roles in disease progression in ducks. Together, the functional annotation of the proteome and phosphoproteome datasets revealed the molecular basis of the disease progression and disease resistance mechanism in ducks infected with the HPAI H5N1 virus.

Mass Spectrometric and Artificial Intelligence-Based Identification of the Secretome of Plasmodium falciparum Merozoites to Provide Novel Candidates for Vaccine Development Pipeline.

PURPOSE: Merozoites are the only extracellular form of blood stage parasites, making it a worthwhile target. Multiple invasins that are stored in the merozoite apical organelles, are secreted just prior to invasion, and mediates its interaction with RBC. A comprehensive identification of all these secreted invasins is lacking and this study addresses that gap. EXPERIMENTAL DESIGN: Pf3D7 merozoites were enriched and triggered to discharge apical organelle contents by exposure to ionic conditions mimicking that of blood plasma. The secreted proteins were separated from cellular contents and both the fractions were subjected to proteomic analysis. Also, the identified secreted proteins were subjected to GO, PPI network analysis, and AI-based in silico approach to understand their vaccine candidacy. RESULTS: A total of 63 proteins were identified in the secretory fraction with membrane and apical organellar localization. This includes various MSPs, micronemal EBAs and rhoptry bulb proteins, which play a crucial role in initial and late merozoite attachment, and majority of them qualified as vaccine candidates. CONCLUSION AND CLINICAL RELEVANCE: We, for the first time, report the secretory repertoire of merozoite and its status for vaccine candidacy. This information can be utilized to develop better invasion blocking multisubunit vaccines, comprising of immunological epitopes from several secreted invasins.

REMEMProt: a resource of membrane-enriched proteome profiles, their disease associations, and biomarker status.

The differential expression of plasma membrane proteins is integrally analyzed for their diagnosis, prognosis, and therapeutic applications in diverse clinical manifestations. Necessarily, distinct membrane protein enrichment methods and mass spectrometry platforms are employed for their global and relative quantitation. First of its kind to explore, we compiled membrane-associated proteomes in human and mouse systems into a database named, Resource of Experimental Membrane-Enriched Mass spectrometry-derived Proteome (REMEMProt). It currently hosts 14,626 proteins (9,507 proteins in Homo sapiens; 5,119 proteins in Mus musculus) with information on their membrane-protein enrichment methods, experimental/physiological context of detection in cells or tissues, transmembrane domain analysis, and their current attribution as biomarkers. Based on these annotations and the transmembrane domain analysis in proteins or their binary/complex protein-protein interactors, REMEMProt facilitates the assessment of the plasma membrane localization potential of proteins through batch query. A cross-study enrichment analysis platform is enabled in REMEMProt for comparative analysis of proteomes using novel/modified membrane enrichment methods and evaluation of methods for targeted enrichment of membrane proteins. REMEMProt data are made freely accessible to explore and download at https://rememprot.ciods.in/.

Machine Learning Strategies in MicroRNA Research: Bridging Genome to Phenome.

MicroRNAs (miRNAs) have emerged as a prominent layer of regulation of gene expression. This article offers the salient and current aspects of machine learning (ML) tools and approaches from genome to phenome in miRNA research. First, we underline that the complexity in the analysis of miRNA function ranges from their modes of biogenesis to the target diversity in diverse biological conditions. Therefore, it is imperative to first ascertain the miRNA coding potential of genomes and understand the regulatory mechanisms of their expression. This knowledge enables the efficient classification of miRNA precursors and the identification of their mature forms and respective target genes. Second, and because one miRNA can target multiple mRNAs and vice versa, another challenge is the assessment of the miRNA-mRNA target interaction network. Furthermore, long-noncoding RNA (lncRNA)and circular RNAs (circRNAs) also contribute to this complexity. ML has been used to tackle these challenges at the high-dimensional data level. The present expert review covers more than 100 tools adopting various ML approaches pertaining to, for example, (1) miRNA promoter prediction, (2) precursor classification, (3) mature miRNA prediction, (4) miRNA target prediction, (5) miRNA- lncRNA and miRNA-circRNA interactions, (6) miRNA-mRNA expression profiling, (7) miRNA regulatory module detection, (8) miRNA-disease association, and (9) miRNA essentiality prediction. Taken together, we unpack, critically examine, and highlight the cutting-edge synergy of ML approaches and miRNA research so as to develop a dynamic and microlevel understanding of human health and diseases.

Guardians Turned Culprits: NETosis and Its Influence on Pulmonary Fibrosis Development.

Idiopathic pulmonary fibrosis (IPF) is a debilitating, life-threatening irreversible lung disease characterized by the excessive accumulation of fibrotic tissue in the lungs, impairing their function. The exact mechanisms underlying Pulmonary fibrosis (PF) are multifaceted and not yet fully understood. Reports show that during COVID-19 pandemic, PF was dramatically increased due to the hyperactivation of the immune system. Neutrophils and macrophages are the patrolling immune cells that keep the microenvironment balanced. Neutrophil extracellular traps (NETs) are a normal protective mechanism of neutrophils. The chief components of the NETs include DNA, citrullinated histones, and anti-microbial peptides which are released by the activated neutrophils. However, it is becoming increasingly evident that hyperactivation of immune cells can also turn into criminals when it comes to pathological state. Dysregulated NETosis may contribute to sustained inflammation, overactivation of fibroblasts, and ultimately promoting collagen deposition which is the characteristic feature of PF. The role of NETs along with inflammation is attaining greater attention. However, seldom researches are related to the relationship between NETs causing PF. This review highlights the cellular mechanism of NETs-induced pulmonary fibrosis, which could give a better understanding of molecular targets which may be helpful for treating NETs-induced PF.

Comparative Metabolomics and Network Pharmacology Analysis Reveal Shared Neuroprotective Mechanisms of Bacopa monnieri (L.) Wettst and Centella asiatica (L.) Urb.

Bacopa monnieri (L.) Wettst and Centella asiatica (L.) Urb., two nootropics, are recognized in Indian Ayurvedic texts. Studies have attempted to understand their action as memory enhancers and neuroprotectants, but many molecular aspects remain unknown. We propose that Bacopa monnieri (L.) Wettst and Centella asiatica (L.) Urb. share common neuroprotective mechanisms. Mass spectrometry-based untargeted metabolomics and network pharmacology approach were used to identify potential protein targets for the metabolites from each extract. Phytochemical analyses and cell culture validation studies were also used to assess apoptosis and ROS activity using aqueous extracts prepared from both herbal powders. Further, docking studies were also performed using the LibDock protocol. Untargeted metabolomics and network pharmacology approach unveiled 2751 shared metabolites and 3439 and 2928 non-redundant metabolites from Bacopa monnieri and Centella asiatica extracts, respectively, suggesting a potential common neuroprotective mechanism among these extracts. Protein-target prediction highlighted 92.4% similarity among the proteins interacting with metabolites for these extracts. Among them, kinases mapped to MAPK, mTOR, and PI3K-AKT signaling pathways represented a predominant population. Our results highlight a significant similarity in the metabolome of Bacopa monnieri (L.) Wettst and Centella asiatica (L.) Urb., and their potential protein targets may be attributed to their common neuroprotective functions.

Neutrophils display distinct post-translational modifications in response to varied pathological stimuli.

Neutrophils play a vital role in the innate immunity by perform effector functions through phagocytosis, degranulation, and forming extracellular traps. However, over-functioning of neutrophils has been associated with sterile inflammation such as Type 2 Diabetes, atherosclerosis, cancer and autoimmune disorders. Neutrophils exhibiting phenotypical and functional heterogeneity in both homeostatic and pathological conditions suggests distinct signaling pathways are activated in disease-specific stimuli and alter neutrophil functions. Hence, we examined mass spectrometry based post-translational modifications (PTM) of neutrophil proteins in response to pathologically significant stimuli, including high glucose, homocysteine and bacterial lipopolysaccharides representing diabetes-indicator, an activator of thrombosis and pathogen-associated molecule, respectively. Our data revealed that these aforesaid stimulators differentially deamidate, citrullinate, acetylate and methylate neutrophil proteins and align to distinct biological functions associated with degranulation, platelet activation, innate immune responses and metabolic alterations. The PTM patterns in response to high glucose showed an association with neutrophils extracellular traps (NETs) formation, homocysteine induced proteins PTM associated with signaling of systemic lupus erythematosus and lipopolysaccharides induced PTMs were involved in pathways related to cardiomyopathies. Our study provides novel insights into neutrophil PTM patterns and functions in response to varied pathological stimuli, which may serve as a resource to design therapeutic strategies for the management of neutrophil-centred diseases.

A global phosphosite-correlated network map of Thousand And One Kinase 1 (TAOK1).

Thousand and one amino acid kinase 1 (TAOK1) is a sterile 20 family Serine/Threonine kinase linked to microtubule dynamics, checkpoint signaling, DNA damage response, and neurological functions. Molecular-level alterations of TAOK1 have been associated with neurodevelopment disorders and cancers. Despite their known involvement in physiological and pathophysiological processes, and as a core member of the hippo signaling pathway, the phosphoregulatory network of TAOK1 has not been visualized. Aimed to explore this network, we first analyzed the predominantly detected and differentially regulated TAOK1 phosphosites in global phosphoproteome datasets across diverse experimental conditions. Based on 709 qualitative and 210 quantitative differential cellular phosphoproteome datasets that were systematically assembled, we identified that phosphorylation at Ser421, Ser9, Ser965, and Ser445 predominantly represented TAOK1 in almost 75% of these datasets. Surprisingly, the functional role of all these phosphosites in TAOK1 remains unexplored. Hence, we employed a robust strategy to extract the phosphosites in proteins that significantly correlated in expression with predominant TAOK1 phosphosites. This led to the first categorization of the phosphosites including those in the currently known and predicted interactors, kinases, and substrates, that positively/negatively correlated with the expression status of each predominant TAOK1 phosphosites. Subsequently, we also analyzed the phosphosites in core proteins of the hippo signaling pathway. Based on the TAOK1 phosphoregulatory network analysis, we inferred the potential role of the predominant TAOK1 phosphosites. Especially, we propose pSer9 as an autophosphorylation and TAOK1 kinase activity-associated phosphosite and pS421, the most frequently detected phosphosite in TAOK1, as a significant regulatory phosphosite involved in the maintenance of genome integrity. Considering that the impact of all phosphosites that predominantly represent each kinase is essential for the efficient interpretation of global phosphoproteome datasets, we believe that the approach undertaken in this study is suitable to be extended to other kinases for accelerated research.

Unpacking Immune Modulation as a Site of Therapeutics Innovation for Nematode Parasite Wuchereria bancrofti: A Temporal Quantitative Phosphoproteomics Profiling of Macrophage Migration Inhibitory Factor 2.

Nematode infections are common in both humans and livestock, with major adverse planetary health and economic impacts. Wuchereria bancrofti is a parasitic nematode that causes lymphatic filariasis, a neglected tropical disease that can lead to severe disability and deformity worldwide. For the long-term survival of the bancroftian parasites in the host, a complex immune invasion strategy is involved through immunomodulation. Therefore, immunomodulation can serve as a site of research and innovation for molecular targets. Macrophage migration inhibitory factor (MIF) is a pleiotropic cytokine crucial to the host antimicrobial alarm system and stress response. Interestingly, the nematode parasite W. bancrofti also produces two homologs of MIF (Wba-MIF1 and 2). Using a mass spectrometry-based phosphoproteomics approach, we report new findings on the immunomodulatory effect and signaling mechanism of Wba-MIF2 in macrophage cells. Accordingly, we observed 1201 phosphorylated sites on 467 proteins. Out of the 1201 phosphorylated sites, 1075, 117, and 9 were found on serine (S), threonine (T), and tyrosine (Y) residues, respectively. Our bioinformatics analysis led to identification of major pathways, including spliceosomes, T cell receptor signaling pathway, Th17 differentiation pathway, interleukin-17 signaling pathway, and insulin signaling pathway upon Wba-MIF2 treatment. Wba-MIF2 treatment also enriched CDK4, CDK1, and DNAPK kinases. The comparison of the signaling pathway of Wba-MIF2 with that of human-MIF suggests both share similar signaling pathways. These findings collectively offer new insights into the role and mechanism of Wba-MIF2 as an immunomodulator and inform future diagnostics and drug discovery research for W. bancrofti.

Discovery of Species-Specific Proteotypic Peptides To Establish a Spectral Library Platform for Identification of Nontuberculosis Mycobacteria from Mass Spectrometry-Based Proteomics.

Nontuberculous mycobacteria are opportunistic bacteria pulmonary and extra-pulmonary infections in humans that closely resemble Mycobacterium tuberculosis. Although genome sequencing strategies helped determine NTMs, a common assay for the detection of coinfection by multiple NTMs with M. tuberculosis in the primary attempt of diagnosis is still elusive. Such a lack of efficiency leads to delayed therapy, an inappropriate choice of drugs, drug resistance, disease complications, morbidity, and mortality. Although a high-resolution LC-MS/MS-based multiprotein panel assay can be developed due to its specificity and sensitivity, it needs a library of species-specific peptides as a platform. Toward this, we performed an analysis of proteomes of 9 NTM species with more than 20 million peptide spectrum matches gathered from 26 proteome data sets. Our metaproteomic analyses determined 48,172 species-specific proteotypic peptides across 9 NTMs. Notably, M. smegmatis (26,008), M. abscessus (12,442), M. vaccae (6487), M. fortuitum (1623), M. avium subsp. paratuberculosis (844), M. avium subsp. hominissuis (580), and M. marinum (112) displayed >100 species-specific proteotypic peptides. Finally, these peptides and corresponding spectra have been compiled into a spectral library, FASTA, and JSON formats for future reference and validation in clinical cohorts by the biomedical community for further translation.

Role of Hemigraphis alternata in wound healing: metabolomic profiling and molecular insights into mechanisms.

Hemigraphis alternata (H. alternata), commonly known as Red Flame Ivy, is widely recognized for its wound healing capabilities. However, the pharmacologically active plant components and their mechanisms of action in wound healing are yet to be determined. This study presents the mass spectrometry-based global metabolite profiling of aqueous and ethanolic extract of H. alternata leaves. The analysis identified 2285 metabolites from 24,203 spectra obtained in both positive and negative polarities. The identified metabolites were classified under ketones, carboxylic acids, primary aliphatic amines, steroids and steroid derivatives. We performed network pharmacology analysis to explore metabolite-protein interactions and identified 124 human proteins as targets for H. alternata metabolites. Among these, several of them were implicated in wound healing including prothrombin (F2), alpha-2A adrenergic receptor (ADRA2A) and fibroblast growth factor receptor 1 (FGFR1). Gene ontology analysis of target proteins enriched cellular functions related to glucose metabolic process, platelet activation, membrane organization and response to wounding. Additionally, pathway enrichment analysis revealed potential molecular network involved in wound healing. Moreover, in-silico docking analysis showed strong binding energy between H. alternata metabolites with identified protein targets (F2 and PTPN11). Furthermore, the key metabolites involved in wound healing were further validated by multiple reaction monitoring-based targeted analysis.

Cisplatin and Procaterol Combination in Gastric Cancer? Targeting Checkpoint Kinase 1 for Cancer Drug Discovery and Repurposing by an Integrated Computational and Experimental Approach.

Checkpoint kinase 1 (CHK1), a serine/threonine kinase, plays a crucial role in cell cycle arrest and is a promising therapeutic target for drug development against cancers. CHK1 coordinates cell cycle checkpoints in response to DNA damage, facilitating repair of single-strand breaks, and maintains the genome integrity in response to replication stress. In this study, we employed an integrated computational and experimental approach to drug discovery and repurposing, aiming to identify a potent CHK1 inhibitor among existing drugs. An e-pharmacophore model was developed based on the three-dimensional crystal structure of the CHK1 protein in complex with CCT245737. This model, characterized by seven key molecular features, guided the screening of a library of drugs through molecular docking. The top 10% of scored ligands were further examined, with procaterol emerging as the leading candidate. Procaterol demonstrated interaction patterns with the CHK1 active site similar to CHK1 inhibitor (CCT245737), as shown by molecular dynamics analysis. Subsequent in vitro assays, including cell proliferation, colony formation, and cell cycle analysis, were conducted on gastric adenocarcinoma cells treated with procaterol, both as a monotherapy and in combination with cisplatin. Procaterol, in synergy with cisplatin, significantly inhibited cell growth, suggesting a potentiated therapeutic effect. Thus, we propose the combined application of cisplatin and procaterol as a novel potential therapeutic strategy against human gastric cancer. The findings also highlight the relevance of CHK1 kinase as a drug target for enhancing the sensitivity of cytotoxic agents in cancer.

Physiological Temperature and Osmotic Changes Drive Dynamic Proteome Alterations in the Leptospiral Outer Membrane and Enhance Protein Export Systems.

Leptospirosis, a remerging zoonosis, has no effective vaccine or an unambiguous early diagnostic reagent. Proteins differentially expressed (DE) under pathogenic conditions will be useful candidates for antileptospiral measures. We employed a multipronged approach comprising high-resolution TMT-labeled LC-MS/MS-based proteome analysis coupled with bioinformatics on leptospiral proteins following Triton X-114 subcellular fractionation of leptospires treated under physiological temperature and osmolarity that mimic infection. Although there were significant changes in the DE proteins at the level of the entire cell, there were notable changes in proteins at the subcellular level, particularly on the outer membrane (OM), that show the significance of subcellular proteome analysis. The detergent-enriched proteins, representing outer membrane proteins (OMPs), exhibited a dynamic nature and upregulation under various physiological conditions. It was found that pathogenic proteins showed a higher proportion of upregulation compared to the nonpathogenic proteins in the OM. Further analysis identified 17 virulent proteins exclusively upregulated in the outer membrane during infection that could be useful for vaccine and diagnostic targets. The DE proteins may aid in metabolic adaptation and are enriched in pathways related to signal transduction and antibiotic biosynthesis. Many upregulated proteins belong to protein export systems such as SEC translocase, T2SSs, and T1SSs, indicating their sequential participation in protein transport to the outer leaflet of the OM. Further studies on OM-localized proteins may shed light on the pathogenesis of leptospirosis and serve as the basis for effective countermeasures.

VirhostlncR: A comprehensive database to explore lncRNAs and their targets in viral infections.

Long non-coding-RNAs (lncRNAs) are an expanding set of cis-/trans-regulatory RNA genes that outnumber the protein-coding genes. Although being increasingly discovered, the functional role of the majority of lncRNAs in diverse biological conditions is undefined. Increasing evidence supports the critical role of lncRNAs in the emergence, regulation, and progression of various viral infections including influenza, hepatitis, coronavirus, and human immunodeficiency virus. Hence, the identification of signature lncRNAs would facilitate focused analysis of their functional roles accounting for their targets and regulatory mechanisms associated with infections. Towards this, we compiled 2803 lncRNAs identified to be modulated by 33 viral strains in various mammalian cell types and are provided through the resource named VirhostlncR (http://ciods.in/VirhostlncR/). The information on each of the viral strains, their multiplicity of infection, duration of infection, host cell name and cell types, fold change of lncRNA expression, and their specific identification methods are integrated into VirhostlncR. Based on the current datasets, we report 150 lncRNAs including differentiation antagonizing non-protein coding RNA (DANCR), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), maternally expressed gene 3 (MEG3), nuclear paraspeckle assembly transcript 1 (NEAT1), and plasmacytoma variant translocation 1 (PVT1) to be perturbed by two or more viruses. Analysis of viral protein interactions with human transcription factors (TFs) or TF-containing protein complexes identified that distinct viruses can transcriptionally regulate many of these lncRNAs through multiple protein complexes. Together, we believe that the current dataset will enable priority selection of lncRNAs for identification of their targets and serve as an effective platform for the analysis of noncoding RNA-mediated regulations in viral infections.

Astaxanthin and DHA supplementation ameliorates the proteomic profile of perinatal undernutrition-induced adipose tissue dysfunction in adult life.

Maternal diet is an essential factor that directly and indirectly regulates fetal growth. Exposure to certain environmental conditions substantially impacts an individual's short- and long-term health. Adipose tissue dysfunction is a worldwide chronic disease caused by improper lipid build-up in adipose tissue leading to obesity. Therefore, it is the need of the hour to invent anti-obesity agents. As a keto-carotenoid, Astaxanthin (AsX) has been shown to have preventive effects against problems associated with obesity. A crucial role in the pathogenesis of obesity has been attributed to dietary polyunsaturated fatty acids. Adipose tissue plays a vital role in maintaining overall body homeostasis. Metabolic dysfunction of white adipocytes forms a critical step in the emergence of insulin resistance and related diseases. Here we aim to investigate the effect of AsX and Docosahexaenoic acid (DHA) supplementation on the proteomic profile of perinatal undernutrition-induced adipose tissue dysfunction in adult life using a rat model. The LC-MS/MS quantitative proteomics enabled us to identify differentially expressed proteins in perinatal undernourished but AsX and DHA-supplemented animal models. Data are available via ProteomeXchange with identifier PXD041772.This study explored biological roles, molecular functions of differentially expressed proteins, and pathways related to adipose tissue dysfunction induced by undernutrition and its effective modulation by AsX and DHA.

Exploring molecular dynamic indicators associated with reproductive performance of Bos indicus cattle in blood plasma samples through data-independent acquisition mass spectrometry.

Improving reproductive performance of cattle is of paramount importance for sustainable dairy farming. Poor reproduction performance (RP) hinders the genetic improvement of important Bos indicus cattle breeds. It is well known that incorporation of molecular information along with conventional breeding method is far better than use of conventional method alone for the genetic improvement of reproductive performance traits in cattle. Therefore, the present study sought to investigate the plasma proteome of the Deoni cows in cyclical (n = 6) and pregnant (n = 6) reproductive phases with varying reproductive performance (high and low). High-throughput data independent acquisition (DIA) based proteomics was performed to understand corresponding proteome. We identified a total of 430 plasma proteins. Among cyclic cows, twenty proteins were differentially regulated in low RP as compared to high RP. BARD1 and AFP proteins were observed upregulated in cyclical cows whose upregulation reported to affect reproductive performance in cattle. Among the pregnant cows, thirty-five proteins were differentially regulated, including the downregulation of FGL2 and ZNFX1 that modulates the maternal immune response mechanism which is required for successful implantation of the embryo. Also, proteins such as AHSG, CLU and SERPINA6 were upregulated in the pregnant cows whose upregulation reported to reduced reproductive performance. The results of this study will be helpful in establishing a framework for future research on the aspect of improving reproductive performance in Bos indicus cattle breeds. SIGNIFICANCE: The Indian subcontinent is the center of domestication for Bos indicus cattle breeds and they are known for their disease resistance, heat tolerance, ability to survive in low input regime and harsh climatic conditions. In recent times, population of many important Bos indicus breeds including Deoni cattle is declining due to various factors, especially due to reproductive performance. Traditional breeding methods are not sufficient enough to understand and improve the reproductive performance traits in important Bos indicus cattle breeds. Proteomics approach is a promising technology to understand the complex biological factors which leads to poor reproductive performance in cattle. The present study utilized DIA based LC- MS/MS analysis to identify the plasma proteins associated with reproductive performance in cyclical and pregnant cows. This study if improved further, can be used to develop potential protein markers associated with reproductive performance which is useful for the selection and genetic improvement of important Bos indicus breeds.

Temporal phosphoproteomic analysis of VEGF-A signaling in HUVECs: an insight into early signaling events associated with angiogenesis.

Vascular endothelial growth factor-A (VEGF-A) is one of the primary factors promoting angiogenesis in endothelial cells. Although defects in VEGF-A signaling are linked to diverse pathophysiological conditions, the early phosphorylation-dependent signaling events pertinent to VEGF-A signaling remain poorly defined. Hence, a temporal quantitative phosphoproteomic analysis was performed in human umbilical vein endothelial cells (HUVECs) treated with VEGF-A-165 for 1, 5 and 10 min. This led to the identification and quantification of 1971 unique phosphopeptides corresponding to 961 phosphoproteins and 2771 phosphorylation sites in total. Specifically, 69, 153, and 133 phosphopeptides corresponding to 62, 125, and 110 phosphoproteins respectively, were temporally phosphorylated at 1, 5, and 10 min upon addition of VEGF-A. These phosphopeptides included 14 kinases, among others. This study also captured the phosphosignaling events directed through RAC, FAK, PI3K-AKT-MTOR, ERK, and P38 MAPK modules with reference to our previously assembled VEGF-A/VEGFR2 signaling pathway map in HUVECs. Apart from a significant enrichment of biological processes such as cytoskeleton organization and actin filament binding, our results also suggest a role of AAK1-AP2M1 in the regulation of VEGFR endocytosis. Taken together, the temporal quantitative phosphoproteomics analysis of VEGF signaling in HUVECs revealed early signaling events and we believe that this analysis will serve as a starting point for the analysis of differential signaling across VEGF members toward the full elucidation of their role in the angiogenesis processes. Workflow for the identification of early phosphorylation events induced by VEGF-A-165 in HUVEC cells.

Development of a Spectral Library for the Discovery of Altered Genomic Events in Mycobacterium avium Associated With Virulence Using Mass Spectrometry-Based Proteogenomic Analysis.

Mycobacterium avium is one of the prominent disease-causing bacteria in humans. It causes lymphadenitis, chronic and extrapulmonary, and disseminated infections in adults, children, and immunocompromised patients. M. avium has ∼4500 predicted protein-coding regions on average, which can help discover several variants at the proteome level. Many of them are potentially associated with virulence; thus, identifying such proteins can be a helpful feature in developing panel-based theranostics. In line with such a long-term goal, we carried out an in-depth proteomic analysis of M. avium with both data-dependent and data-independent acquisition methods. Further, a set of proteogenomic investigations were carried out using (i) a protein database for Mycobacterium tuberculosis, (ii) an M. avium genome six-frame-translated database, and (iii) a variant protein database of M. avium. A search of mass spectrometry data against M. avium protein database resulted in identifying 2954 proteins. Further, proteogenomic analyses aided in identifying 1301 novel peptide sequences and correcting translation start sites for 15 proteins. Ultimately, we created a spectral library of M. avium proteins, including novel genome search-specific peptides and variant peptides detected in this study. We validated the spectral library by a data-independent acquisition of the M. avium proteome. Thus, we present an M. avium spectral library of 29,033 peptide precursors supported by 0.4 million fragment ions for further use by the biomedical community.

Computational tools for exploring peptide-membrane interactions in gram-positive bacteria.

The vital cellular functions in Gram-positive bacteria are controlled by signaling molecules known as quorum sensing peptides (QSPs), considered promising therapeutic interventions for bacterial infections. In the bacterial system QSPs bind to membrane-coupled receptors, which then auto-phosphorylate and activate intracellular response regulators. These response regulators induce target gene expression in bacteria. One of the most reliable trends in drug discovery research for virulence-associated molecular targets is the use of peptide drugs or new functionalities. In this perspective, computational methods act as auxiliary aids for biologists, where methodologies based on machine learning and in silico analysis are developed as suitable tools for target peptide identification. Therefore, the development of quick and reliable computational resources to identify or predict these QSPs along with their receptors and inhibitors is receiving considerable attention. The databases such as Quorumpeps and Quorum Sensing of Human Gut Microbes (QSHGM) provide a detailed overview of the structures and functions of QSPs. The tools and algorithms such as QSPpred, QSPred-FL, iQSP, EnsembleQS and PEPred-Suite have been used for the generic prediction of QSPs and feature representation. The availability of compiled key resources for utilizing peptide features based on amino acid composition, positional preferences, and motifs as well as structural and physicochemical properties, including biofilm inhibitory peptides, can aid in elucidating the QSP and membrane receptor interactions in infectious Gram-positive pathogens. Herein, we present a comprehensive survey of diverse computational approaches that are suitable for detecting QSPs and QS interference molecules. This review highlights the utility of these methods for developing potential biomarkers against infectious Gram-positive pathogens.