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.

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.

Data-Independent Acquisition Approach to Proteome: A Case Study and a Spectral Library for Mass Spectrometry-Based Investigation of Mycobacterium tuberculosis.

Currently, mass spectrometry-based data-dependent acquisition protocols require several micrograms to milligram amounts of proteins to start with, and needs fractionation and enrichment or depletion protocols to identify low abundant proteins and their modifications. However, a data-independent acquisition (DIA) approach can help us to identify a large number of proteins irrespective of their abundance, from even a very low amount of protein. In the DIA protocol, mass spectrometry data are matched against a previously established tandem mass spectrometry (MS/MS) spectra for each peptide. Therefore, establishing a spectral library is a prerequisite for successful DIA protocol. However, the DIA protocol becomes extremely important to investigate biological systems, where there is a difficulty in gathering reasonable amounts of proteins. In this context, DIA can become a valuable tool to investigate proteome dynamics of slow growing pathogen such as Mycobacterium tuberculosis that causes tuberculosis. We report here a case study of the DIA approach that is ideal for M. tuberculosis, which cannot be scaled up easily as it requires specific BSL3 laboratory facilities to be grown. We generated a spectral library for M. tuberculosis proteome using six publicly available proteomic data sets. The in-house M. tuberculosis proteome spectral library contains MS/MS spectra for peptides corresponding to 88% of proteins when compared with the M. tuberculosis H37Rv proteome. We believe that the public availability of the M. tuberculosis spectral library is an important step forward to facilitate the research community to adopt DIA approaches, for example, to investigate M. tuberculosis proteome with greater depth and efficiency.

Multiple G-quadruplex binding ligand induced transcriptomic map of cancer cell lines.

The G-quadruplexes (G4s) are a class of DNA secondary structures with guanine rich DNA sequences that can fold into four stranded non-canonical structures. At the genomic level, their pivotal role is well established in DNA replication, telomerase functions, constitution of topologically associating domains, and the regulation of gene expression. Genome instability mediated by altered G4 formation and assembly has been associated with multiple disorders including cancers and neurodegenerative disorders. Multiple tools have also been developed to predict the potential G4 regions in genomes and the whole genome G4 maps are also being derived through sequencing approaches. Enrichment of G4s in the cis-regulatory elements of genes associated with tumorigenesis has accelerated the quest for identification of G4-DNA binding ligands (G4DBLs) that can selectively bind and regulate the expression of such specific genes. In this context, the analysis of G4DBL responsive transcriptome in diverse cancer cell lines is inevitable for assessment of the specificity of novel G4DBLs. Towards this, we assembled the transcripts differentially regulated by different G4DBLs and have also identified a core set of genes regulated in diverse cancer cell lines in response to 3 or more of these ligands. With the mode of action of G4DBLs towards topology shifts, folding, or disruption of G4 structure being currently visualized, we believe that this dataset will serve as a platform for assembly of G4DBL responsive transcriptome for comparative analysis of G4DBLs in multiple cancer cells based on the expression of specific cis-regulatory G4 associated genes in the future.

A multi-cellular molecular signaling and functional network map of C-C motif chemokine ligand 18 (CCL18): a chemokine with immunosuppressive and pro-tumor functions.

The C-C Motif Chemokine Ligand 18 (CCL18) is a beta-chemokine sub-family member with immunomodulatory functions in primates. CCL18-dependent migration and epithelial-to-mesenchymal transition of oral squamous cell carcinoma, squamous cell carcinoma of head and neck, breast cancer, hepatocellular carcinoma, non-small cell lung carcinoma, ovarian cancer, pancreatic ductal carcinoma and bladder cancer cells are well-established. In the tumor niche, tumor-associated macrophages produce CCL18 and its overexpression is correlated with reduced patient survival in multiple cancers. Although multiple receptors including C-C chemokine receptor type 3 (CCR3), type 6 (CCR6), type 8 (CCR8) and G-protein coupled estrogen receptor (GPER1) are reported for CCL18, the Phosphatidylinositol Transfer Protein, Membrane-Associated 3 (PITPNM3) receptor is currently considered as its predominant receptor. Characterization of the molecular events and check points associated with the immunosuppressive and cancer progression support functions induced by CCL18 for their potential towards therapeutic applications is an area of active research. Hence, in this study, we assembled 917 signaling events reported to be induced by CCL18 through their studied receptors in diverse cell types as an integrated knowledgebase for reference, data integration and gene-set enrichment analysis of global transcriptomic and/or proteomics datasets.

Hyperactivation of MEK/ERK pathway by Ca2+ /calmodulin-dependent protein kinase kinase 2 promotes cellular proliferation by activating cyclin-dependent kinases and minichromosome maintenance protein in gastric cancer cells.

Although CAMKK2 is overexpressed in several cancers, its role and relevant downstream signaling pathways in gastric cancer (GC) are poorly understood. Treatment of AGS GC cells with a CAMKK2 inhibitor, STO-609, resulted in decreased cell proliferation, cell migration, invasion, colony-forming ability, and G1/S-phase arrest. Quantitative phosphoproteomics in AGS cells with the CAMKK2 inhibitor led to the identification of 9603 unique phosphosites mapping to 3120 proteins. We observed decreased phosphorylation of 1101 phosphopeptides (1.5-fold) corresponding to 752 proteins upon CAMKK2 inhibition. Bioinformatics analysis of hypo-phosphorylated proteins revealed enrichment of MAPK1/MAPK3 signaling. Kinase enrichment analysis of hypo-phosphorylated proteins using the X2K Web tool identified ERK1, cyclin-dependant kinase 1 (CDK1), and CDK2 as downstream substrates of CAMKK2. Moreover, inhibition of CAMKK2 and MEK1 resulted in decreased phosphorylation of ERK1, CDK1, MCM2, and MCM3. Immunofluorescence results were in concordance with our mass spectroscopy data and Western blot analysis results. Taken together, our data reveal the essential role of CAMKK2 in the pathobiology of GC through the activation of the MEK/ERK1 signaling cascade.

Omics Data Mining for multiPTMs in Oral Cancer: Cellular Proteome and Secretome of Chronic Tobacco-Treated Oral Keratinocytes.

Oral cancer is common worldwide but lacks robust diagnostics and therapeutics. Lifestyle factors, such as tobacco chewing and smoking, are significantly associated with oral cancers. Mapping the changes in the global proteome, secretome and post-translational modifications (PTMs) during tobacco exposure of oral keratinocytes hold great potential for understanding the mechanisms of oral carcinogenesis, not to mention for innovation toward clinical interventions in the future. On the other hand, although advances in mass spectrometry (MS)-based techniques have enabled the deep mining of complex proteomes, a large portion of the mass spectrometric data remains unassigned. These unassigned spectral data can be researched for multiple post-translational modifications (multiPTMs). Using data mining of publicly available proteomics data, we report, in this study, a multiPTM analysis of high-resolution MS-derived datasets on cellular proteome and secretome of chronic tobacco-treated oral keratinocytes. We identified 800 PTM sites in 496 proteins. Among them, 43 PTM sites in 37 proteins were found to be differentially expressed, accounting for their protein-level expression. Enrichment analysis of the proteins with altered phosphosite expression and the known kinases of these phosphosites discovered the overrepresentation of certain biological processes such as splicing and hemidesmosome assembly. These findings contribute to a deeper understanding of omics level changes in chronic tobacco-treated oral keratinocytes, and by extension, pathophysiology of oral cancers.