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.

Meta-analysis of the serum/plasma proteome identifies significant associations between COVID-19 with Alzheimer's/Parkinson's diseases.

In recent years, we have seen the widespread devastations and serious health complications manifested by COVID-19 globally. Although we have effectively controlled the pandemic, uncertainties persist regarding its potential long-term effects, including prolonged neurological issues. To gain comprehensive insights, we conducted a meta-analysis of mass spectrometry-based proteomics data retrieved from different studies with a total of 538 COVID-19 patients and 523 healthy controls. The meta-analysis revealed that top-enriched pathways were associated with neurological disorders, including Alzheimer's (AD) and Parkinson's disease (PD). Further analysis confirmed a direct correlation in the expression patterns of 24 proteins involved in Alzheimer's and 23 proteins in Parkinson's disease with COVID-19. Protein-protein interaction network and cluster analysis identified SNCA as a hub protein, a known biomarker for Parkinson's disease, in both AD and PD. To the best of our knowledge, this is the first meta-analysis study providing proteomic profiling evidence linking COVID-19 to neurological complications.

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.