Biology subjects

Zhu, Y.-G.

Publications and source records attributed to Zhu, Y.-G..

4 recordsLinked to original sources

bioRxiv2025

Coexistence of Virome-Encoded Human Probiotic Genes and Pathogenic Genes in Global Habitats

Some probiotic genes for humans obtained through horizontal gene transfer (HGT) have been screened in viral genomes, yet the occurrence mode, geographic distribution, and functional characteristics of these genes in viruses and the coexistence between pathogenic virulence genes and probiotic genes in the viral genome, remain insufficiently understood and verified. In this study, using IMG/VR v4 database, 4,556 viruses carrying probiotic gene segments have been discovered in eight habitat types (humans, animals, freshwater, marine, other water bodies, soil, and plants), 13 regions of 76 countries around the world. Among them, the 478 viruses carrying probiotic genes that distributed in humans account for the highest proportion among the viruses with predictable hosts. In viruses carrying probiotic genes, BCO1, bioB, COQ2, GPX1, GSTs, GSTT1, GULO, and menA are not only probiotic genes encoded by viruses, but also auxiliary metabolic genes. Four virulence genes harmful to humans in viral sequences carrying probiotic genes with transcription and expression potential, have been found, indicating that virulence genes encoded by viruses can coexist with probiotic genes. Further metagenome sequencing revealed the consistency between the probiotic gene asd in the bacillus prophage and the corresponding phage auxiliary metabolic genes. This study integrates probiotic gene databases into viral genomics, revealing the compatibility between viral probiotic and virulence genes, and offering new insights for viral applications. IMPORTANCEProbiotic genes acquired by humans through horizontal gene transfer (HGT) have been identified within viral genomes. However, their occurrence, distribution, and functions, along with the coexistence of pathogenic and probiotic genes in viruses, remain poorly understood. This study advocates for the utilization of probiotic gene databases in viral genomes and innovatively elucidates the phenomenon of compatibility between viral probiotic genes and virulence genes, offering fresh perspectives on the diverse applications of viruses. By promoting the application of these databases, the study reveals the compatibility between probiotic and pathogenic genes in viruses, providing novel and insightful implications for the various utilizations of viruses.

bioinformatics↗

bioRxiv2024

Comparative Metagenomics Provide Mechanistic Insights into the Biodegradation of the Non-hydrolysable Plastic Polyvinyl Chloride in Gut Microbiota of Insect Larvae

Using microbiomes to mitigate global plastic pollution is of paramount importance. Insect microbiomes have garnered emerging interest for their ability to biodegrade non-hydrolysable plastic polymers. The larvae of Spodoptera frugiperda, a globally prevalent migratory crop pest, are accidentally discovered to consume polyvinyl chloride (PVC) plastic films, highlighting the role of their gut microbiome. Following the migration of S. frugiperd in China, this study displays a comprehensive geographical profile of its larval gut microbiota and a significant shift after PVC feeding. Using comparative metagenomics we revealed the functional redundancy within the larval gut microbiomes of two distinct insects after PVC ingestion, we discovered a surprisingly potent PVC-dechlorinating activity of an NADH peroxidase (6.48 mg/L chlorine produced in 96 hours with NADH as a cofactor) encoded by Enterococcus casseliflavus EMBL-3. These findings open a new avenue for understanding plastic biodegradation mechanism and enable the development of biotechnologies to mitigate global plastic pollution.

microbiology↗

bioRxiv2022

The global distribution and environmental drivers of the soil antibiotic resistome

BackgroundLittle is known about the global distribution and environmental drivers of key microbial functional traits such as antibiotic resistance genes (ARGs). Soils are one of Earths largest reservoirs of ARGs, which are integral for soil microbial competition, and have potential implications for plant and human health. Yet, their diversity and global patterns remain poorly described. Here, we analyzed 285 ARGs in soils from 1012 sites across all continents, and created the first global atlas with the distributions of topsoil ARGs. ResultsWe show that ARGs peaked in high latitude cold and boreal forests. Climatic seasonality and mobile genetic elements, associated with the transmission of antibiotic resistance, were also key drivers of their global distribution. Dominant ARGs were mainly related to multidrug resistance genes and efflux pump machineries. We further pinpointed the global hotspots of the diversity and proportions of soil ARGs. ConclusionsTogether, our work provides the foundation for a better understanding of the ecology and global distribution of the environmental soil antibiotic resistome.

ecology↗

bioRxiv2017

DirtyGenes: significance testing for gene or bacterial population composition changes using the Dirichlet distribution

High throughput sequencing, and quantitative polymerase chain reaction (qPCR), can detect changes in bacterial communities or the genes that they carry, between different environments or treatments. These methods are applied widely to microbiomes in humans, animals, soil and water; an important application is for changes in antimicrobial resistance genes (ARGs). However, at present, there is no statistical method to determine whether observed changes in the overall composition are significant, or result from random variations between samples. Therefore researchers are limited to graphical descriptions. We describe a novel statistical method to determine whether or not observed differences in bacterial populations or their genes are significant. It can be used with data from shotgun metagenomics, 16S characterisation or qPCR. It can also be used for experimental design, to calculate the number of samples needed in future experiments. We show its application to two example data sets. The first is published data on bacterial communities and ARGs in the environment, in which we show that there are significant changes in both ARG and community composition. The second is a new data set on seasonality in bacterial communities and ARGs in hooves from four sheep. While the observed differences are not significant, we show that a minimum group size of eight sheep in a future experiment would provide sufficient power to observe significant changes, should the already observed changes be true. This method has broad uses for statistical testing and experimental design in experiments on changing microbiomes, including for studies on antimicrobial resistance.

bioinformatics↗