11 results on '"Pan, Yuan-Fei"'
Search Results
2. Individual bat virome analysis reveals co-infection and spillover among bats and virus zoonotic potential
- Author
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Wang, Jing, Pan, Yuan-fei, Yang, Li-fen, Yang, Wei-hong, Lv, Kexin, Luo, Chu-ming, Wang, Juan, Kuang, Guo-peng, Wu, Wei-chen, Gou, Qin-yu, Xin, Gen-yang, Li, Bo, Luo, Huan-le, Chen, Shoudeng, Shu, Yue-long, Guo, Deyin, Gao, Zi-Hou, Liang, Guodong, Li, Jun, Chen, Yao-qing, Holmes, Edward C., Feng, Yun, and Shi, Mang
- Published
- 2023
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3. Meta-transcriptomic analysis of companion animal infectomes reveals their diversity and potential roles in animal and human disease
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Wu, Wei-Chen, primary, Pan, Yuan-Fei, additional, Zhou, Wu-Di, additional, Liao, Yu-Qi, additional, Peng, Min-Wu, additional, Luo, Geng-Yan, additional, Xin, Gen-Yang, additional, Peng, Ya-Ni, additional, An, Tongqing, additional, Li, Bo, additional, Luo, Huanle, additional, Barrs, Vanessa R., additional, Beatty, Julia A., additional, Holmes, Edward C., additional, Zhao, Wenjing, additional, and Shu, Yuelong, additional
- Published
- 2024
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4. Metagenomic analysis of individual mosquitos reveals the ecology of insect viruses
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Pan, Yuan-fei, primary, Zhao, Hailong, additional, Gou, Qin-yu, additional, Shi, Pei-bo, additional, Tian, Jun-hua, additional, Feng, Yun, additional, Li, Kun, additional, Yang, Wei-hong, additional, Wu, De, additional, Tang, Guangpeng, additional, Zhang, Bing, additional, Ren, Zirui, additional, Peng, Shiqin, additional, Luo, Geng-yan, additional, Le, Shi-jia, additional, Xin, Gen-yang, additional, Wang, Jing, additional, Hou, Xin, additional, Peng, Min-wu, additional, Kong, Jian-bin, additional, Chen, Xin-xin, additional, Yang, Chun-hui, additional, Mei, Shi-qiang, additional, Liao, Yu-qi, additional, Cheng, Jing-xia, additional, Wang, Juan, additional, n/a, Chaolemen, additional, Wu, Yu-hui, additional, Wang, Jian-bo, additional, An, Tongqing, additional, Huang, Xinyi, additional, Eden, John-Sebastian, additional, Li, Jun, additional, Guo, Deyin, additional, Liang, Guodong, additional, Jin, Xin, additional, Holmes, Edward C, additional, Li, Bo, additional, Wang, Daxi, additional, Li, Junhua, additional, Wu, Wei-chen, additional, and Shi, Mang, additional
- Published
- 2023
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5. Artificial intelligence redefines RNA virus discovery
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Shi, Mang, primary, Hou, Xin, additional, He, Yong, additional, Fang, Pan, additional, Mei, Shi-Qiang, additional, Xu, Zan, additional, Wu, Wei-Chen, additional, Tian, Jun-hua, additional, Zhang, Shun, additional, Zeng, Zhen-Yu, additional, Gou, Qin-Yu, additional, Xin, Gen-Yang, additional, Le, Shi-Jia, additional, Xia, Yinyue, additional, Zhou, Yu-Lan, additional, Hui, Feng-Ming, additional, Pan, Yuan-Fei, additional, Eden, John-Sebastian, additional, Yang, Zhaohui, additional, Han, Chong, additional, Shu, Yuelong, additional, Guo, Deyin, additional, Li, Jun, additional, Holmes, Edward, additional, and Li, Zhaorong, additional
- Published
- 2023
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6. Artificial intelligence redefines RNA virus discovery
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Hou, Xin, primary, He, Yong, additional, Fang, Pan, additional, Mei, Shi-Qiang, additional, Xu, Zan, additional, Wu, Wei-Chen, additional, Tian, Jun-Hua, additional, Zhang, Shun, additional, Zeng, Zhen-Yu, additional, Gou, Qin-Yu, additional, Xin, Gen-Yang, additional, Le, Shi-Jia, additional, Xia, Yin-Yue, additional, Zhou, Yu-Lan, additional, Hui, Feng-Ming, additional, Pan, Yuan-Fei, additional, Eden, John-Sebastian, additional, Yang, Zhao-Hui, additional, Han, Chong, additional, Shu, Yue-Long, additional, Guo, Deyin, additional, Li, Jun, additional, Holmes, Edward C., additional, Li, Zhao-Rong, additional, and Shi, Mang, additional
- Published
- 2023
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7. Individual bat viromes reveal the co-infection, spillover and emergence risk of potential zoonotic viruses
- Author
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Wang, Jing, primary, Pan, Yuan-fei, additional, Yang, Li-fen, additional, Yang, Wei-hong, additional, Luo, Chu-ming, additional, Wang, Juan, additional, Kuang, Guo-peng, additional, Wu, Wei-chen, additional, Gou, Qin-yu, additional, Xin, Gen-yang, additional, Li, Bo, additional, Luo, Huan-le, additional, Chen, Yao-qing, additional, Shu, Yue-long, additional, Guo, Deyin, additional, Gao, Zi-Hou, additional, Liang, Guodong, additional, Li, Jun, additional, Holmes, Edward C., additional, Feng, Yun, additional, and Shi, Mang, additional
- Published
- 2022
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8. Using artificial intelligence to document the hidden RNA virosphere.
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Hou X, He Y, Fang P, Mei SQ, Xu Z, Wu WC, Tian JH, Zhang S, Zeng ZY, Gou QY, Xin GY, Le SJ, Xia YY, Zhou YL, Hui FM, Pan YF, Eden JS, Yang ZH, Han C, Shu YL, Guo D, Li J, Holmes EC, Li ZR, and Shi M
- Abstract
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 was confirmed by RT-PCR and RNA/DNA sequencing. Newly discovered RNA viruses were present in diverse environments, including air, hot springs, and hydrothermal vents, with virus diversity and abundance varying 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., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
- Published
- 2024
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9. Meta-transcriptomic analysis of companion animal infectomes reveals their diversity and potential roles in animal and human disease.
- Author
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Wu W-C, Pan Y-F, Zhou W-D, Liao Y-Q, Peng M-W, Luo G-Y, Xin G-Y, Peng Y-N, An T, Li B, Luo H, Barrs VR, Beatty JA, Holmes EC, Zhao W, Shi M, and Shu Y
- Subjects
- Animals, Cats, Dogs, Humans, Microbiota genetics, China, Viruses classification, Viruses genetics, Viruses isolation & purification, Viruses pathogenicity, Fungi classification, Fungi genetics, Fungi isolation & purification, Fungi pathogenicity, Gene Expression Profiling, Transcriptome, Pets virology, Pets microbiology, Dog Diseases microbiology, Dog Diseases virology, Dog Diseases transmission, Zoonoses microbiology, Zoonoses virology, Zoonoses transmission, Cat Diseases virology, Cat Diseases microbiology, Bacteria classification, Bacteria genetics, Bacteria isolation & purification
- Abstract
Companion animals such as cats and dogs harbor diverse microbial communities that can potentially impact human health due to close and frequent contact. To better characterize their total infectomes and assess zoonotic risks, we characterized the overall infectomes of companion animals (cats and dogs) and evaluated their potential zoonotic risks. Meta-transcriptomic analyses were performed on 239 samples from cats and dogs collected across China, identifying 24 viral species, 270 bacterial genera, and two fungal genera. Differences in the overall microbiome and infectome composition were compared across different animal species (cats or dogs), sampling sites (rectal or oropharyngeal), and health status (healthy or diseased). Diversity analyses revealed that viral abundance was generally higher in diseased animals compared to healthy ones, while differences in microbial composition were mainly driven by sampling site, followed by animal species and health status. Disease association analyses validated the pathogenicity of known pathogens and suggested potential pathogenic roles of previously undescribed bacteria and newly discovered viruses. Cross-species transmission analyses identified seven pathogens shared between cats and dogs, such as alphacoronavirus 1, which was detected in both oropharyngeal and rectal swabs albeit with differential pathogenicity. Further analyses showed that some viruses, like alphacoronavirus 1, harbored multiple lineages exhibiting distinct pathogenicity, tissue, or host preferences. Ultimately, a systematic evolutionary screening identified 27 potential zoonotic pathogens in this sample set, with far more bacterial than viral species, implying potential health threats to humans. Overall, our meta-transcriptomic analysis reveals a landscape of actively transcribing microorganisms in major companion animals, highlighting key pathogens, those with the potential for cross-species transmission, and possible zoonotic threats., Importance: This study provides a comprehensive characterization of the entire community of infectious microbes (viruses, bacteria, and fungi) in companion animals like cats and dogs, termed the "infectome." By analyzing hundreds of samples from across China, the researchers identified numerous known and novel pathogens, including 27 potential zoonotic agents that could pose health risks to both animals and humans. Notably, some of these zoonotic pathogens were detected even in apparently healthy pets, highlighting the importance of surveillance. The study also revealed key microbial factors associated with respiratory and gastrointestinal diseases in pets, as well as potential cross-species transmission events between cats and dogs. Overall, this work sheds light on the complex microbial landscapes of companion animals and their potential impacts on animal and human health, underscoring the need for monitoring and management of these infectious agents., Competing Interests: The authors declare no conflict of interest.
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- 2024
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10. Metagenomic analysis of individual mosquitos reveals the ecology of insect viruses.
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Pan YF, Zhao H, Gou QY, Shi PB, Tian JH, Feng Y, Li K, Yang WH, Wu, Tang G, Zhang B, Ren Z, Peng S, Luo GY, Le SJ, Xin GY, Wang J, Hou X, Peng MW, Kong JB, Chen XX, Yang CH, Mei SQ, Liao YQ, Cheng JX, Wang J, Chaolemen, Wu YH, Wang JB, An T, Huang X, Eden JS, Li J, Guo D, Liang G, Jin X, Holmes EC, Li B, Wang D, Li J, Wu WC, and Shi M
- Abstract
Mosquito transmitted viruses are responsible for an increasing burden of human disease. Despite this, little is known about the diversity and ecology of viruses within individual mosquito hosts. Using a meta-transcriptomic approach, we analysed the virome of 2,438 individual mosquitos (79 species), spanning ~4000 km along latitudes and longitudes in China. From these data we identified 393 core viral species associated with mosquitos, including seven (putative) arbovirus species. We identified potential species and geographic hotspots of viral richness and arbovirus occurrence, and demonstrated that host phylogeny had a strong impact on the composition of individual mosquito viromes. Our data revealed a large number of viruses shared among mosquito species or genera, expanding our knowledge of host specificity of insect-associated viruses. We also detected multiple virus species that were widespread throughout the country, possibly facilitated by long-distance mosquito migrations. Together, our results greatly expand the known mosquito virome, linked the viral diversity at the scale of individual insects to that at a country-wide scale, and offered unique insights into the ecology of viruses of insect vectors., Competing Interests: COMPETING INTERESTS The authors declare no competing interests.
- Published
- 2023
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11. Individual bat viromes reveal the co-infection, spillover and emergence risk of potential zoonotic viruses.
- Author
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Wang J, Pan YF, Yang LF, Yang WH, Luo CM, Wang J, Kuang GP, Wu WC, Gou QY, Xin GY, Li B, Luo HL, Chen YQ, Shu YL, Guo D, Gao ZH, Liang G, Li J, Holmes EC, Feng Y, and Shi M
- Abstract
Bats are reservoir hosts for many zoonotic viruses. Despite this, relatively little is known about the diversity and abundance of viruses within bats at the level of individual animals, and hence the frequency of virus co-infection and inter-species transmission. Using an unbiased meta-transcriptomics approach we characterised the mammalian associated viruses present in 149 individual bats sampled from Yunnan province, China. This revealed a high frequency of virus co-infection and species spillover among the animals studied, with 12 viruses shared among different bat species, which in turn facilitates virus recombination and reassortment. Of note, we identified five viral species that are likely to be pathogenic to humans or livestock, including a novel recombinant SARS-like coronavirus that is closely related to both SARS-CoV-2 and SARS-CoV, with only five amino acid differences between its receptor-binding domain sequence and that of the earliest sequences of SARS-CoV-2. Functional analysis predicts that this recombinant coronavirus can utilize the human ACE2 receptor such that it is likely to be of high zoonotic risk. Our study highlights the common occurrence of inter-species transmission and co-infection of bat viruses, as well as their implications for virus emergence.
- Published
- 2022
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