Biology subjects

Gopalan, V.

Publications and source records attributed to Gopalan, V..

4 recordsLinked to original sources

bioRxiv2021

miRSCAPE - Inferring miRNA expression in single-cell clusters

Micro-RNAs (miRNA) are critical in development, homeostasis, and diseases, including cancer. However, our understanding of miRNA function at cellular resolution is thwarted by the inability of the standard single cell RNA-seq protocols to capture miRNAs. Here we introduce a machine learning tool -- miRSCAPE -- to infer miRNA expression in a sample from its RNA-seq profile. We establish miRSCAPEs accuracy separately in 10 tissues comprising ~10,000 tumor and normal bulk samples and demonstrate that miRSCAPE accurately infers cell type-specific miRNA activities (predicted vs observed fold-difference correlation ~ 0.81) in two independent datasets where miRNA profiles of specific cell types are available (HEK-GBM, Kidney-Breast-Skin). When trained on human hematopoietic cancers, miRSCAPE can identify active miRNAs in 8 hematopoietic cell lines in mouse with a reasonable accuracy (auROC = 0.67). Finally, we apply miRSCAPE to infer miRNA activities in scRNA clusters in Pancreatic and Lung cancers, as well as in 56 cell types in the Human Cell Landscape (HCL). Across the board, miRSCAPE recapitulates and provides a refined view of known miRNA biology. miRSCAPE is freely available and promises to substantially expand our understanding of gene regulatory networks at cellular resolution.

bioinformatics↗

bioRxiv2021

Immunoinformatic Approach for the identification of T Cell and B Cell Epitopes in the Surface Glycoprotein and Designing a Potent Multiepitope Vaccine Construct Against SARS-CoV-2 including the new UK variant

The emergence of a novel coronavirus in China in late 2019 has turned into a SARS-CoV-2 pandemic affecting several millions of people worldwide in a short span of time with high fatality. The crisis is further aggravated by the emergence and evolution of new variant SARS-CoV-2 strains in UK during December, 2020 followed by their transmission to other countries. A major concern is that prophylaxis and therapeutics are not available yet to control and prevent the virus which is spreading at an alarming rate, though several vaccine trials are in the final stage. As vaccines are developed through various strategies, their immunogenic potential may drastically vary and thus pose several challenges in offering both arms of immunity such as humoral and cell-mediated immune responses against the virus. In this study, we adopted an immunoinformatics-aided identification of B cell and T cell epitopes in the Spike protein, which is a surface glycoprotein of SARS-CoV-2, for developing a new Multiepitope vaccine construct (MEVC). MEVC has 575 amino acids and comprises adjuvants and various cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes that possess the highest affinity for the respective HLA alleles, assembled and joined by linkers. The computational data suggest that the MEVC is non-toxic, non-allergenic and thermostable with the capability to elicit both humoral and cell-mediated immune responses. The population coverage of various countries affected by COVID-19 with respect to the selected B and T cell epitopes in MEVC was also investigated. Subsequently, the biological activity of MEVC was assessed by bioinformatic tools using the interaction between the vaccine candidate and the innate immune system receptors TLR3 and TLR4. The epitopes of the construct were analyzed with that of the strains belonging to various clades including the new variant UK strain having multiple unique mutations in S protein. Due to the advantageous features, the MEVC can be tested in vitro for more practical validation and the study offers immense scope for developing a potential vaccine candidate against SARS-CoV-2 in view of the public health emergency associated with COVID-19 disease caused by SARS-CoV-2.

bioinformatics↗

bioRxiv2021

A transcriptionally distinct subpopulation of healthy acinar cells exhibit features of pancreatic progenitors and PDAC

Pancreatic ductal adenocarcinoma (PDAC) tumors can originate either from acinar or ductal cells in the adult pancreas. We re-analyze multiple pancreas and PDAC single-cell RNA-seq datasets and find a subset of non-malignant acinar cells, which we refer to as acinar edge (AE) cells, whose transcriptomes highly diverge from a typical acinar cell in each dataset. Genes up-regulated among AE cells are enriched for transcriptomic signatures of pancreatic progenitors, acinar dedifferentiation, and several oncogenic programs. AE-upregulated genes are up-regulated in human PDAC tumors, and consistently, their promoters are hypo-methylated. High expression of these genes is associated with poor patient survival. The fraction of AE-like cells increases with age in healthy pancreatic tissue, which is not explained by clonal mutations, thus pointing to a non-genetic source of variation. We also find edge-like states in lung and liver tissues, suggesting that sub-populations of healthy cells across tissues can exist in pre-malignant states.

genomics↗

bioRxiv2020

Rapamycin as a potent and selective inhibitor of vascular endothelial growth factor receptor in breast carcinoma

Angiogenesis is the process of new vascular formation, which is derived from various factors. For suppressing cancer cell growth, targeting angiogenesis is one of the therapeutic approaches. Vascular endothelial growth factor family receptors, including Flt-1, Flk-1, and Flt-4, have been found to play an essential role in regulating angiogenesis. In the present study, we evaluated the effects of rapamycin and platelet factor-4 toward breast carcinoma at the proteomic and genomic levels. A total of 60 N-Methyl-N-Nitrosourea-induced rat breast carcinomas were treated with rapamycin, platelet factor-4, and rapamycin+platelet factor-4. The tumors were subsequently subjected to immunohistological protein analysis and polymerase chain reaction gene analysis. Protein analysis was performed using a semi-quantitative scoring method, while the mRNA expression levels were analyzed based on the relative expression ratio. There was a significant difference in the protein and mRNA expression levels for the selected markers. In the rapamycin+platelet factor-4 treated group, the Flt-4 marker was downregulated, whereas there were no differences in the expression levels of other markers, such as Flt-1 and Flk-1. On the other hand, platelet factor-4 did not exhibit a superior angiogenic inhibiting ability in this study. Rapamycin is a potent anti-angiogenic drug; however, platelet factor-4 proved to be a less effective drug of anti-angiogenesis on rat breast carcinoma model.

pathology↗