Ray, A. K. | Search bioRxiv

bioRxiv2023

Distinct composition of plasma virome in HIV-infected subjects on antiretroviral therapy compared to controls

Microbiome study during HIV infection is widely documented with major emphasis on bacteriome, while virome studies are few. The alteration of plasma virome is reported in HIV patients who are either treatment naive or have a weak immune system. Less is known about the plasma virome in HIV-infected patients on ART with preserved CD4 counts. In our pilot study, viral DNA isolated from plasma was sequenced on Illumina Nextseq500 platform. With the help of VIROMATCH pipeline, we observed that the plasma virome of HIV patients were significantly distinct from controls on the basis of Bray-Curtis dissimilarity index. The species, Human gammaherpesvirus 4 and families, Herpesviridae and Siphoviridae were found to be significantly enriched and differentially abundant in HIV patients. Hence, plasma virome is an important component for future study that might influence disease progression among HIV patients during therapy.

microbiology↗

bioRxiv2021

CDK1 and HSP90AA1 appears as novel regulatory gene in Non-Small Cell Lung Cancer: A Bioinformatics Approach

Lung cancer is one of the most invasive cancer affecting over a million of population. Non-small cell lung cancer constitutes up to 85% of all lung cancer cases. Therefore, it is important to identify prognostic biomarkers of NSCLC for therapeutic purpose. The complex behaviour of the NSCLC gene-regulatory network interaction is investigated using a network theoretical approach. We used eight NSCLC microarray datasets GSE19188, GSE118370, GSE10072, GSE101929, GSE7670, GSE33532, GSE31547, GSE31210 and meta analyse them to find differentially expressed genes (DEGs), construct protein-protein interaction (PPI) network, analysed its topological properties, significant modules using network analyser with MCODE, construct a PPI-MCODE network using the genes of the significant modules. We used topological properties such as Maximal Clique Centrality (MCC) and bottleneck from the PPI-MCODE network. We compare them with hub genes (those with highest degrees) to find key regulator (KR) gene. This result is also validated by finding of common genes among top twenty hub genes, genes with highest betweenness, closeness centrality and eigenvector values. It was found that two genes, CDK1 and HSP90AA1 were common in PPI-MCODE combined analysis, and it was also found that CDK1, HSP90AA1 and HSPA8 were common among hub and bottle neck properties and suggesting significant regulatory role of CDK1 in non-small cell lung cancer. After validation, the common genes among top twenty hubs and centrality values like Betweenness Centrality, Closeness Centrality and eigen vector properties, CDK1 again appeared as the common gene. Our study as a summary suggested CDK1 as key regulator gene in complex NSCLC network interaction using network theoretical approach and described the complex topological properties of the network.

systems biology↗