GutUDB: A comprehensive multiomics database for intestinal diseases.

Gut Universe Database (GutUDB) provides a comprehensive, systematic, and practical platform for researchers, and is dedicated to the management, analysis, and visualization of knowledge related to intestinal diseases. Based on this database, eight major categories of omics data analyses are carried out to explore the genotype-phenotype characteristics of a certain intestinal disease. The first tool for comprehensive omics data research on intestinal diseases will help each researcher better understand intestinal diseases.

Dynamic m6 A profiles reveal the role of YTHDC2-TLR2 signaling axis in Talaromyces marneffei infection.

Talaromyces marneffei (TM) immune evasion is an important factor leading to the high mortality rate of Penicilliosis marneffei. N6 -methyladenosine (m6 A) plays important roles in host immune response to various pathogen infections, yet its role in TM and HIV/TM coinfection remains largely unexplored. Here we reported genome-wide transcriptional m6 A profiles of TM mono-infection and HIV/TM coinfection. Our finding revealed dynamic alterations in global m6 A levels and upregulation of the m6 A reader YTH N6 -methyladenosine RNA binding protein C2 (YTHDC2) in TM-infected macrophages. Knockdown of YTHDC2 in TM-infected cells showed an elevated expression of TLR2 through m6 A-dependence, along with upregulation of TNF-α and IL1-ß. Overall, we characterized the m6 A profiles of the host and fungus before and after TM infection, and demonstrated that YTHDC2 mediates the key m6 A site of TLR2 to exert its function. These findings provide new insights into the underlying mechanisms and novel therapeutic approaches for TM diseases.

Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients.

The risk of severe condition caused by Corona Virus Disease 2019 (COVID-19) increases with age. However, the underlying mechanisms have not been clearly understood. The dataset GSE157103 was used to perform weighted gene co-expression network analysis on 100 COVID-19 patients in our analysis. Through weighted gene co-expression network analysis, we identified a key module which was significantly related with age. This age-related module could predict Intensive Care Unit status and mechanical-ventilation usage, and enriched with positive regulation of T cell receptor signaling pathway biological progress. Moreover, 10 hub genes were identified as crucial gene of the age-related module. Protein-protein interaction network and transcription factors-gene interactions were established. Lastly, independent data sets and RT-qPCR were used to validate the key module and hub genes. Our conclusion revealed that key genes were associated with the age-related phenotypes in COVID-19 patients, and it would be beneficial for clinical doctors to develop reasonable therapeutic strategies in elderly COVID-19 patients.

CASA: a comprehensive database resource for the COVID-19 Alternative Splicing Atlas.

BACKGROUND: As a key process in transcriptional regulatory mechanisms, alternative splicing (AS) plays a crucial role in maintaining the diversity of RNA and protein expression, and mediates the immune response in infectious diseases, especially for the COVID-19. Therefore, urgent data gathering and more research of AS profiles in microbe-infected human cells are needed to improve understanding of COVID-19 and related infectious diseases. Herein, we have created CASA, the COVID-19 Alternative Splicing Atlas to provide a convenient computing platform for studies of AS in COVID-19 and COVID-19-related infectious diseases. METHODS: In CASA, we reanalyzed thousands of RNA-seq datasets generated from 65 different tissues, organoids and cell lines to systematically obtain quantitative data on AS events under different conditions. A total of 262,994 AS events from various infectious diseases with differing severity were detected and visualized in this database. In order to explore the potential function of dynamics AS events, we performed analysis of functional annotations and drug-target interactions affected by AS in each dataset. RNA-binding proteins (RBPs), which may regulate these dynamic AS events are also provided for users in this database. RESULTS: CASA displays microbe-induced alterations of the host cell splicing landscape across different virus families and helps users identify condition-specific splicing patterns, as well as their potential regulators. CASA may greatly facilitate the exploration of AS profiles and novel mechanisms of host cell splicing by viral manipulation. CASA is freely available at http://www.splicedb.net/casa/ .