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Gou, Q.-Y.

Publications and source records attributed to Gou, Q.-Y..

2 recordsLinked to original sources

Multi-kingdom microbial diversity and interaction landscapes in mosquitoes revealed by 5,163 individual meta-transcriptomes

Mosquitoes are pathogen vectors embedded within diverse microbial ecosystems. However, the nature and interactions among their multi-kingdom microbiome remain poorly understood. We conducted a nationwide single-mosquito meta-transcriptomic survey of 5,163 mosquitoes representing 100 species across China, integrating viral discovery with marker-gene profiling of bacteria, archaea, fungi, and other eukaryotic microbes. From this, we identified 1,606 microbial species-level taxa, including extensive novel diversity, and revealed pronounced host species-specific organization of mosquito-associated communities. We detected 34 pathogens or potential pathogens of human or animal relevance, whose prevalence, abundance, host range, and geographic distribution defined distinct epidemiological patterns. Network analysis uncovered pervasive cross-kingdom microbial associations, including candidate antiviral relationships involving Wolbachia and other microbial taxa. Our study establishes a detailed view of the full-spectrum microbiome and provides a resource and conceptual framework for studying vector competence, pathogen emergence, and microbiome-informed mosquito-borne disease control.

microbiology↗

Artificial intelligence redefines RNA virus discovery

Current metagenomic tools can fail to identify highly divergent RNA viruses. We developed a deep learning algorithm, termed LucaProt, to discover highly divergent RNA-dependent RNA polymerase (RdRP) sequences in 10,487 metatranscriptomes generated from diverse global ecosystems. LucaProt integrates both sequence and predicted structural information, enabling the accurate detection of RdRP sequences. Using this approach we identified 161,979 potential RNA virus species and 180 RNA virus supergroups, including many previously poorly studied groups, as well as RNA virus genomes of exceptional length (up to 47,250 nucleotides) and genomic complexity. A subset of these novel RNA viruses were confirmed by RT-PCR and RNA/DNA sequencing. Newly discovered RNA viruses were present in diverse environments, including air, hot springs and hydrothermal vents, and both virus diversity and abundance varied substantially among ecosystems. This study advances virus discovery, highlights the scale of the virosphere, and provides computational tools to better document the global RNA virome. In briefA deep learning algorithm (LucaProt) that integrates both sequence and predicted structural information was employed to identify highly divergent RNA viral "dark matter" in 10,487 metatranscriptomes from diverse global ecosystems. A total of 161,979 potential RNA virus species and 180 RNA virus supergroups was unveiled using this AI approach, including many understudied groups.

microbiology↗