GutMGene (http://bio-annotation.cn/gutmgene), a manually curated database, aims at providing a comprehensive resource of target genes of gut microbes and microbial metabolites in humans and mice. Metagenomic sequencing of fecal samples has identified 3.3 × 10⁶ non-redundant microbial genes from up to 1500 different species. One of the contributions of gut microbiota to host biology is the circulating pool of bacterially derived small-molecule metabolites. It has been estimated that 10% of metabolites found in mammalian blood are derived from the gut microbiota, where they can produce systemic effects on the host through activating or inhibiting gene expression. The current version of gutMGene documents 1331 curated relationships between 332 gut microbes, 207 microbial metabolites and 223 genes in humans, and 2349 curated relationships between 209 gut microbes, 149 microbial metabolites and 544 genes in mice. Each entry in the gutMGene contains detailed information on a relationship between gut microbe, microbial metabolite and target gene, a brief description of the relationship, experiment technology and platform, literature reference and so on. gutMGene provides a user-friendly interface to browse and retrieve each entry using gut microbes, disorders and intervention measures. It also offers the option to download all the entries and submit new experimentally validated associations.

GutMDisorder (http://bio-annotation.cn/gutMDisorder), a manually curated database, aims at providing a comprehensive resource of dysbiosis of the gut microbiota in disorders and interventions. Alterations in the composition of the gut microbial community play crucial roles in the development of chronic disorders. And the beneficial effects of drugs, foods and other intervention measures on disorders could be microbially mediated. The current version of gutMDisorder documents 2263 curated associations between 579 gut microbes and 123 disorders or 77 intervention measures in Human, and 930 curated associations between 273 gut microbes and 33 disorders or 151 intervention measures in Mouse. Each entry in the gutMDisorder contains detailed information on an association, including an intestinal microbe, a disorder name, intervention measures, experimental technology and platform, characteristic of samples, web sites for downloading the sequencing data, a brief description of the association, a literature reference, and so on. gutMDisorder provides a user-friendly interface to browse, retrieve each entry using gut microbes, disorders, and intervention measures. It also offers pages for downloading all the entries and submitting new experimentally validated associations.

The gut microbiota is essential for various physiological functions in the host, primarily through the metabolites it produces. To support researchers in uncovering how gut microbiota contributes to host homeostasis, we launched the gutMGene database in 2022. In this updated version, we conducted an extensive review of previous papers and incorporated new papers to extract associations among gut microbes, their metabolites, and host genes, carefully classifying these as causal or correlational. Additionally, we performed metabolic reconstructions for representative gut microbial genomes from both human and mouse. gutMGene v2.0 features an upgraded web interface, providing users with improved accessibility and functionality. This upgraded version is freely available at http://bio-computing.hrbmu.edu.cn/gutmgene. We believe that this new version will greatly advance research in the gut microbiota field by offering a comprehensive resource.

Gut microbiota plays a significant role in maintaining host health, and conversely, disorders potentially lead to dysbiosis, an imbalance in the composition of the gut microbial community. Intervention approaches, such as medications, diets, and several others, also alter the gut microbiota in either a beneficial or harmful direction. In 2020, the gutMDisorder was developed to facilitate researchers in the investigation of dysbiosis of gut microbes as occurs in various disorders as well as with therapeutic interventions. The database has been updated this year, following revision of previous publications and newly published reports to manually integrate confirmed associations under multitudinous conditions. Additionally, the microbial contents of downloaded gut microbial raw sequencing data were annotated, the metadata of the corresponding hosts were manually curated, and the interactive charts were developed to enhance visualization. The improvements have assembled into gutMDisorder v2.0, a more advanced search engine and an upgraded web interface, which can be freely accessed via http://bio-annotation.cn/gutMDisorder/.

Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, the COVID-19 pandemic has spread rapidly worldwide. Due to the limited virus strains, few key mutations that would be very important with the evolutionary trends of virus genome were observed in early studies. Here, we downloaded 1809 sequence data of SARS-CoV-2 strains from GISAID before April 2020 to identify mutations and functional alterations caused by these mutations. Totally, we identified 1017 nonsynonymous and 512 synonymous mutations with alignment to reference genome NC_045512, none of which were observed in the receptor-binding domain (RBD) of the spike protein. On average, each of the strains could have about 1.75 new mutations each month. The current mutations may have few impacts on antibodies. Although it shows the purifying selection in whole-genome, ORF3a, ORF8 and ORF10 were under positive selection. Only 36 mutations occurred in 1% and more virus strains were further analyzed to reveal linkage disequilibrium (LD) variants and dominant mutations. As a result, we observed five dominant mutations involving three nonsynonymous mutations C28144T, C14408T and A23403G and two synonymous mutations T8782C, and C3037T. These five mutations occurred in almost all strains in April 2020. Besides, we also observed two potential dominant nonsynonymous mutations C1059T and G25563T, which occurred in most of the strains in April 2020. Further functional analysis shows that these mutations decreased protein stability largely, which could lead to a significant reduction of virus virulence. In addition, the A23403G mutation increases the spike-ACE2 interaction and finally leads to the enhancement of its infectivity. All of these proved that the evolution of SARS-CoV-2 is toward the enhancement of infectivity and reduction of virulence.

The anaerobic ammonium oxidation (anammox) by autotrophic anaerobic ammonia-oxidizing bacteria (AnAOB) is a biological process used to remove reactive nitrogen from wastewater. It has been repeatedly reported that elevated nitrite concentrations can severely inhibit the growth of AnAOB, which renders the anammox process challenging for industrial-scale applications. Both denitrifying (DN) and dissimilatory nitrate reduction to ammonium (DNRA) bacteria can potentially consume excess nitrite in an anammox system to prevent its inhibitory effect on AnAOB. However, metabolic interactions among DN, DNRA, and AnAOB bacteria under elevated nitrite conditions remain to be elucidated at metabolic resolutions. In this study, a laboratory-scale anammox bioreactor was used to conduct an investigation of the microbial shift and functional interactions of AnAOB, DN, and DNRA bacteria during a long-term nitrite inhibition to eventual self-recovery episode. The relative abundance of AnAOB first decreased due to high nitrite concentration, which lowered the system’s nitrogen removal efficiency, but then recovered automatically without any external interference. Based on the relative abundance variations of genomes in the inhibition, adaptation, and recovery periods, we found that DN and DNRA bacteria could be divided into three niche groups: type I (types Ia and Ib) that includes mainly DN bacteria and type II and type III that include primarily DNRA bacteria. Type Ia and type II bacteria outcompeted other bacteria in the inhibition and adaptation periods, respectively. They were recognized as potential nitrite scavengers at high nitrite concentrations, contributing to stabilizing the nitrite concentration and the eventual recovery of the anammox system. These findings shed light on the potential engineering solutions to maintain a robust and efficient industrial-scale anammox process.