患有腹水的伴侣猫感染组多样性的人口和动物学驱动因素。

IF 5 2区 生物学 Q1 MICROBIOLOGY mSystems Pub Date : 2024-09-17 Epub Date: 2024-08-09 DOI:10.1128/msystems.00636-24
Yankuo Sun, Jiabao Xing, Sijia Xu, Yue Li, Jianhao Zhong, Han Gao, Song Cheng, Jun Dong, Tianyou Zhang, Gang Lu, Guy Baele, Guihong Zhang
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引用次数: 0

摘要

猫科动物已成为许多家庭不可或缺的一部分。然而,我们对影响猫的全部病原体(称为感染组)的了解还很有限,这主要是由于常用诊断工具不足以捕捉潜在病原体的全部多样性以及病原体合并感染的普遍性。在这项研究中,我们采用了元转录组学方法,同时描述了导致不同疾病综合征的感染组的特征,并调查了影响 27 只住院猫和 7 只流浪猫的病原体多样性和群落组成的空间、人口和生态因素。我们发现了 15 种病原体,其中塔拉塞维奇立克次体和胎生三联单胞菌具有潜在的外溢风险。重要的是,虽然大多数腹水增生病例都是由多种病原体共同感染引起的,但我们发现了猫感染 M. aubagnense 可能带来的新的临床结果。我们证明,感染组多样性的增加可以用多种预测因素来解释,包括年龄增长、温度升高和雌性比例增加,其中年龄增长的影响最大。精细分析表明,幼猫体内的感染组多样性高于成年猫。我们的研究结果表明,病毒-细菌或病毒-病毒共感染能更好地解释大多数猫科动物疾病。这项研究为兽医的临床诊断提供了及时的支持,即根据一组隐性合并感染病原体而不是单个感染病原体来考虑疾病的原因:重要性:经常有研究报告称,猫是人畜共患病原体(如 SARS-CoV-2)的中间宿主。猫通过抚摸、亲吻、舔舐脸颊和手等活动与主人进行亲密的身体接触。然而,系统研究猫感染组结构的研究仍然有限。在这项研究中,我们采用元转录组学方法描述了猫体内15种病原体的特征,其中塔拉塞维奇立克次体首先描述了病猫感染的特征。病毒-细菌或病毒-病毒共感染能更好地解释大多数猫科动物疾病。感染组多样性的增加可能受到多种因素的影响,包括年龄增长、温度升高和雌性比例增加。幼猫体内的病原体多样性高于成年猫。重要的是,我们展示了将现代大量涌入的元转录组学与比较生态学和人口统计学联系起来的价值,以及利用元转录组学确认生态学和人口统计学变化对总感染组产生影响的价值。
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Demographic and zoological drivers of infectome diversity in companion cats with ascites.

Cats (Felidae) have become an integral part of many households. However, our understanding of the full spectrum of pathogens affecting cats (referred to as the infectome) is limited, mainly due to the inadequacy of commonly used diagnostic tools in capturing the complete diversity of potential pathogens and the prevalence of pathogen co-infections. In this study, we employed a meta-transcriptomic approach to simultaneously characterize the infectome contributing to different disease syndromes and to investigate spatial, demographic, and ecological factors influencing pathogen diversity and community composition in a cohort of 27 hospitalized cats and seven stray cats. We identified 15 species of pathogens, with Candidatus Rickettsia tarasevichiae and Tritrichomonas foetus representing potential spillover risks. Importantly, although most cases of ascites hyperplasia were explained by coinfection with multiple pathogens, we identified the potential novel clinical outcomes of M. aubagnense infection among cats. We demonstrated that the increase in infectome diversity can be explained by a variety of predictors including age growth, temperature increase, and a higher proportion of females, with age growth presenting the strongest effect. Fine-scale analysis indicated that a higher diversity of infectomes were harbored in young cats rather than adult ones. Our results demonstrated that most feline diseases are better explained by the presence of virus-bacteria or virus-virus coinfection. This study serves as a timely endorsement for clinical diagnosis by vets to consider the cause of a disease based on a panel of cryptical co-infecting pathogens rather than on individual infectious agents.

Importance: Frequent studies reported the risks of cats as an intermediate host of zoonotic pathogens (e.g., SARS-CoV-2). Cats have a physically close interaction with their owners through activities like petting, kissing, and being licked on the cheek and hands. However, there are still limited studies that systematically investigate the infectome structure of cats. In this study, we employed a meta-transcriptomics approach to characterize 15 species of pathogens in cats, with Candidatus Rickettsia tarasevichiae first characterizing infection in diseased cats. Most feline diseases were better explained by the presence of virus-bacteria or virus-virus coinfection. The increase in infectome diversity could be influenced by a variety of predictors including age growth, temperature increase, and a higher proportion of females. A higher diversity of pathogens was harbored in young cats rather than adults. Importantly, we showed the value of linking the modern influx of meta-transcriptomics with comparative ecology and demography and of utilizing it to affirm that ecological and demographic variations impact the total infectome.

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来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
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