A total infectome approach to understand the etiology of infectious disease in pigs

文献类型： 外文期刊

第一作者： Huang, Xinyi

作者： Huang, Xinyi;Tian, Xiaoxiao;Cui, Xingyang;Sun, Yue;Yang, Yongbo;Cai, Xuehui;An, Tongqing;Wu, Weichen;Hou, Xin;Shi, Mang;Xiao, Yihong;Jiao, Qiulin;Zhou, Pei;Chen, Jianxin;Zhang, Guihong;Liu, Liqiang;Shi, Weilin;Chen, Ligong;Liu, Jinling;Holmes, Edward C.;Holmes, Edward C.

作者机构：

关键词： Infectome; Meta-transcriptomics; Animal disease; Pathogens

期刊名称：MICROBIOME （ 影响因子：16.837； 五年影响因子：19.813 ）

ISSN： 2049-2618

年卷期： 2022 年 10 卷 1 期

页码：

收录情况： SCI

摘要： Background: The global pork industry is continuously affected by infectious diseases that can result in large-scale mortality, trade restrictions, and major reductions in production. Nevertheless, the cause of many infectious diseases in pigs remains unclear, largely because commonly used diagnostic tools fail to capture the full diversity of potential pathogens and because pathogen co-infection is common. Results: We used a meta-transcriptomic approach to systematically characterize the pathogens in 136 clinical cases representing different disease syndromes in pigs, as well as in 12 non-diseased controls. This enabled us to simultaneously determine the diversity, abundance, genomic information, and detailed epidemiological history of a wide range of potential pathogens. We identified 34 species of RNA viruses, nine species of DNA viruses, seven species of bacteria, and three species of fungi, including two novel divergent members of the genus Pneumocystis. While most of these pathogens were only apparent in diseased animals or were at higher abundance in diseased animals than in healthy animals, others were present in healthy controls, suggesting opportunistic infections. Importantly, most of the cases examined here were characterized by co-infection with more than two species of viral, bacterial, or fungal pathogens, some with highly correlated occurrence and abundance levels. Examination of clinical signs and necropsy results in the context of relevant pathogens revealed that a multiple-pathogen model was better associated with the data than a single-pathogen model was. Conclusions: Our data demonstrate that most of the pig diseases examined were better explained by the presence of multiple rather than single pathogens and that infection with one pathogen can facilitate infection or increase the prevalence/abundance of another. Consequently, it is generally preferable to consider the cause of a disease based on a panel of co-infecting pathogens rather than on individual infectious agents.

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