Bioinformatics Applications to Reveal Molecular Mechanisms of Gene Expression Regulation in Model Organisms

Research Topics of the Bioinformatics of Gene Regulation

The study of gene expression regulation raises the challenge of developing bioinformatics tools and algorithms, demanding data integration [...].

Meiotic nuclear divisions 1 promotes proliferation and metastasis in hepatocellular carcinoma and is a potential diagnostic and therapeutic target gene

Hepatocellular carcinoma is the cancer with the highest incidence among liver cancers and how to treat this cancer effectively is still a difficult problem we must face. We selected meiotic nuclear divisions 1 (MND1) as the study object by combining data from The Cancer Genome Atlas (TCGA) database with prognostic survival analysis. We validated the value of MND1 in evaluating the prognosis of hepatocellular carcinoma through a diagnostic and prognostic model. At the same time, cellular experiments were used to demonstrate the effect of MND1 on hepatocellular carcinoma proliferation and migration. We used short hairpin RNA (shRNA) to knock down MND1 in Hun7 and HCCLM3 cell lines. Through 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and colony formation assays, we found that knocking down MND1 reduced the proliferation of cells. Through wound healing and Transwell assays, we found that knocking down MND1 reduced cell migration and invasion. Moreover, we found that MND1 can promote the proliferation, migration, and invasion of Hep3B cells by overexpressing MND1. Therefore, in general, MND1 is expected to be a gene that can effectively diagnose and treat hepatocellular carcinoma.

Identification of common molecular signatures of SARS-CoV-2 infection and its influence on acute kidney injury and chronic kidney disease

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the main cause of COVID-19, causing hundreds of millions of confirmed cases and more than 18.2 million deaths worldwide. Acute kidney injury (AKI) is a common complication of COVID-19 that leads to an increase in mortality, especially in intensive care unit (ICU) settings, and chronic kidney disease (CKD) is a high risk factor for COVID-19 and its related mortality. However, the underlying molecular mechanisms among AKI, CKD, and COVID-19 are unclear. Therefore, transcriptome analysis was performed to examine common pathways and molecular biomarkers for AKI, CKD, and COVID-19 in an attempt to understand the association of SARS-CoV-2 infection with AKI and CKD. Three RNA-seq datasets (GSE147507, GSE1563, and GSE66494) from the GEO database were used to detect differentially expressed genes (DEGs) for COVID-19 with AKI and CKD to search for shared pathways and candidate targets. A total of 17 common DEGs were confirmed, and their biological functions and signaling pathways were characterized by enrichment analysis. MAPK signaling, the structural pathway of interleukin 1 (IL-1), and the Toll-like receptor pathway appear to be involved in the occurrence of these diseases. Hub genes identified from the protein-protein interaction (PPI) network, including DUSP6, BHLHE40, RASGRP1, and TAB2, are potential therapeutic targets in COVID-19 with AKI and CKD. Common genes and pathways may play pathogenic roles in these three diseases mainly through the activation of immune inflammation. Networks of transcription factor (TF)-gene, miRNA-gene, and gene-disease interactions from the datasets were also constructed, and key gene regulators influencing the progression of these three diseases were further identified among the DEGs. Moreover, new drug targets were predicted based on these common DEGs, and molecular docking and molecular dynamics (MD) simulations were performed. Finally, a diagnostic model of COVID-19 was established based on these common DEGs. Taken together, the molecular and signaling pathways identified in this study may be related to the mechanisms by which SARS-CoV-2 infection affects renal function. These findings are significant for the effective treatment of COVID-19 in patients with kidney diseases.

Plant Biology and Biotechnology: Focus on Genomics and Bioinformatics

The study of molecular mechanisms of plant stress response is important for agrobiotechnology applications as it was discussed at series of recent bioinformatics conferences [...].

Bioinformatics analysis of the potential regulatory mechanisms of renal fibrosis and the screening and identification of factors related to human renal fibrosis

Background

This paper aimed to identify the key genes and potential mechanisms of renal fibrosis, and provide methods of evaluation and new ideas for the early diagnosis and treatment of renal fibrosis.

Methods

The GSE102515 dataset was searched from the Gene Expression Omnibus (GEO) database was searched, the differential genes were screened out, and the down-regulated and up-regulated genes were identified. Enrichment analysis of differential genes in the development of renal fibrosis was carried out using the DAVID database, differential genes were analyzed using the STRING database, and Cytoscape software was used for visual processing.

Results

Eighteen up-regulated genes and ten down-regulated genes were screened. Differential genes are mainly involved in the integrin-mediated signaling pathway and mitotic sister chromatid binding, etc. We found that the molecular functions (MFs) of the differential genes are phospholipid binding and regulatory region DNA binding, etc. Moreover, the cellular components (CCs) of the differential genes are mainly related to low-density lipoprotein (LDL) particles and nuclei. Screening revealed that ADM, ARRB1, AVPR2, CCR1, MTNR1A, PTH, and S1PR2 were core genes in the interaction network of renal fibrosis risk-related proteins.

Conclusions

In this study, the differential genes in the occurrence of renal fibrosis were screened out via dataset analysis. It was found that ADM, ARRB1, AVPR2, CCR1, MTNR1A, PTH, and S1PR2 may be important participants in the development of renal fibrosis, which provides analytical support for the identification of valuable markers of renal fibrosis.