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.

The Core Human MicroRNAs Regulated by Toxoplasma gondii.

BACKGROUND: Toxoplasma gondii (T. gondii) is an intracellular zoonotic protozoan parasite known to effectively modulate the host system for its survival. A large number of microRNAs (miRNAs) regulated by different strains of T. gondii in diverse types of host cells/tissues/organs have been reported across multiple studies. OBJECTIVE: We aimed to decipher the complexity of T. gondii regulated spectrum of miRNAs to derive a set of core miRNAs central to different strains of T. gondii infection in diverse human cell lines. METHODS: We first assembled miRNAs hat are regulated by T. gondii altered across the various assortment of infections and time points of T. gondii infection in multiple cell types. For these assembled datasets, we employed specific criteria to filter the core miRNAs regulated by T. gondii. Subsequently, accounting for the spectrum of miRNA-mRNA target combinations, we applied a novel confidence criterion to extract their core experimentally-validated mRNA targets in human cell systems. RESULTS: This analysis resulted in the extraction of 74 core differentially regulated miRNAs and their 319 high-confidence mRNA targets. Based on these core miRNA-mRNA pairs, we derived the central biological processes perturbed by T. gondii in diverse human cell systems. Further, our analysis also resulted in the identification of novel autocrine/paracrine signalling factors that could be associated with host response modulated by T. gondii. CONCLUSION: The current analysis derived a set of core miRNAs, their targets, and associated biological processes fine-tuned by T. gondii for its survival within the invaded cells.

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.

Proteome dataset of chili pepper plant (Capsicum frutescens) infested by broad mite (Polyphagotarsonemus latus).

The dataset presented in this article is associated with the TMT (Tandem mass tag) labeled proteomics of chili pepper plant (Capsicum frutescens) infested by a broad mite (Polyphagotarsonemus latus). Data was captured using a nano liquid chromatography system coupled with high-resolution Orbitrap FusionTribridmass spectrometer. Proteomics data was analyzed using the Proteome Discoverer version 2.4 tool using MASCOT and SequestHT algorithms. We have identified a total of 5,807 proteins supported by 48,555 unique peptides and 1,279,655 peptide-spectrum matches. Individually, 5,186 proteins were detected in healthy leaf samples, 5,193 in infested leaf sample, 5,194 proteins in healthy meristem sample, and 5,196 proteins in infested meristem samples. Datasets obtained from reciprocal blast against the Arabidopsis thaliana proteome database enabled the prediction of protein-protein interactions, and subcellular localization of differentially expressed proteins, which are also included in this article. Data presented in this article has been deposited in the ProteomeXchange Consortium via the PRIDE repository, which can be accessed through the accession ID: PXD018653.

Plant-Pathogen Interactions: Broad Mite (Polyphagotarsonemus latus)-Induced Proteomic Changes in Chili Pepper Plant (Capsicum frutescens).

Plant-pathogen interactions are key biological events that shape ecological dynamics, food production, agriculture and economy. In this context, Capsicum frutescens is an economically and culturally significant chili pepper plant grown widely across the globe as an essential ingredient of hot sauces, chili concentrates, oleoresin flavors, and also in traditional medicines. An important pathogen that limits chili cultivation causing low yield and economic loss is the broad mite, Polyphagotarsonemus latus. Broad mite-infested chili plants have stunted growth and leaves appear coppery and dark, which show symptoms of leaf curl and more importantly the smaller fruits unfit for consumption. The molecular mechanisms of how broad mite affect chili remain poorly understood. In this study, we report a tandem mass tag (TMT)-labeled mass spectrometry-based quantitative proteomic analysis of leaves and apical meristems of healthy and infected chili pepper plants. In total, we identified 5799 proteins, of which 1677 proteins were found to be differentially regulated in infested plants. Related signaling pathways of the differentially expressed proteins were examined using bioinformatics tools. Predominantly, we identified pathways associated with jasmonic acid synthesis, mitogen-activated protein kinase, and plant defense and hormone signal transduction. We also observed upregulation of several enzymes of the phenylpropanoid and carotenoid biosynthetic pathways. This study provides the first in-depth proteomic analysis that correlates broad mite infestation in chili and dysregulation of various pathways that take part in plant defense. In the future, data can be extrapolated for innovation in pest management methods whose ecological footprints are better understood.