Discovery of viruses and bacteria associated with swine respiratory disease on farms at a nationwide scale in China using metatranscriptomic and metagenomic sequencing.

IF 4.6 2区 生物学 Q1 MICROBIOLOGY mSystems Pub Date : 2025-02-18 Epub Date: 2025-01-30 DOI:10.1128/msystems.00025-25
Xi Huang, Xinzhi Yao, Wenbo Song, Mengfei Zhao, Zhanwei Zhu, Hanyuan Liu, Xiaorong Song, Jingwen Huang, Yongrun Chen, Zihao Wang, Changjiang Peng, Wenqing Wu, Hao Yang, Lin Hua, Huanchun Chen, Bin Wu, Zhong Peng
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Abstract

Respiratory disease (RD) is a worldwide leading threat to the pig industry, but there is still limited understanding of the pathogens associated with swine RD. In this study, we conducted a nationwide genomic surveillance on identifying viruses, bacteria, and antimicrobial resistance genes (ARGs) from the lungs of pigs with RD in China. By performing metatranscriptomic sequencing combined with metagenomic sequencing, we identified 21 viral species belonging to 12 viral families. Among them, porcine reproductive and respiratory syndrome virus, influenza A virus, herpes virus, adenovirus, and parvovirus were commonly identified. However, emerging viruses, such as Getah virus and porcine respiratory coronaviruses, were also characterized. Apart from viruses, a total of 164 bacterial species were identified, with Streptococcus suis, Mycoplasma hyorhinis, Mycoplasma hyopneumoniae, Glaesserella parasuis, and Pasteurella multocida being frequently detected in high abundances. Notably, Escherichia coli, Enterococcus faecalis, Staphylococcus aureus, and Klebsiella pneumoniae were also highly detected. Our further analysis revealed a complex interaction between the identified pathogens in swine RD. We also conducted retrospectively analyses to demonstrate the prevalent viral genotypes or bacterial serotypes associated with swine RD in China. Finally, we identified 48 ARGs, which conferred resistance to 13 predicted antimicrobial classes, and many of these ARGs were significantly associated with a substantial number of mobile genetic elements, including transposons (e.g., tnpAIS1, tnpA1353, int3, and ISCau1) and plasmids (e.g., Col(BS512), Col(YC)]. These findings will contribute to further understanding the etiology, epidemiology, and microbial interactions in swine RD, and may also shed a light on the development of effective vaccines.IMPORTANCEIn this study, we identified viruses and bacteria from the lungs of pigs with RD in China at a nationwide farm scale by performing metatranscriptomic sequencing combined with metagenomic sequencing. We also demonstrated the complex interactions between different viral and/or bacterial species in swine RD. Our work provides a comprehensive knowledge about the etiology, epidemiology, and microbial interactions in swine RD and data reference for the research and development of effective vaccines against the disease.

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使用超转录组和宏基因组测序在中国全国范围内的猪场发现与猪呼吸道疾病相关的病毒和细菌。
呼吸道疾病(RD)是世界范围内对养猪业的主要威胁,但人们对与猪RD相关的病原体的了解仍然有限。在本研究中,我们在中国进行了一项全国性的基因组监测,从患有RD的猪的肺部鉴定病毒、细菌和抗微生物药物耐药性基因(ARGs)。通过meta -转录组测序结合meta -基因组测序,我们鉴定出了21种病毒,隶属于12个病毒科。其中常见的有猪繁殖与呼吸综合征病毒、甲型流感病毒、疱疹病毒、腺病毒和细小病毒。然而,新出现的病毒,如盖塔病毒和猪呼吸道冠状病毒,也得到了表征。除病毒外,共鉴定出164种细菌,其中猪链球菌、缩鼻支原体、肺炎支原体、副猪绿脓杆菌和多杀性巴氏杆菌丰度较高。值得注意的是,大肠杆菌、粪肠球菌、金黄色葡萄球菌和肺炎克雷伯菌的检出率也很高。我们的进一步分析揭示了猪RD中已鉴定病原体之间复杂的相互作用。我们还进行了回顾性分析,以证明与中国猪RD相关的流行病毒基因型或细菌血清型。最后,我们确定了48个ARGs,它们对13种预测的抗菌素类具有耐药性,其中许多ARGs与大量移动遗传元件显著相关,包括转座子(如tnpAIS1、tnpA1353、int3和ISCau1)和质粒(如Col(BS512)、Col(YC))。这些发现将有助于进一步了解猪RD的病因学、流行病学和微生物相互作用,也可能有助于开发有效的疫苗。在这项研究中,我们在全国范围内的猪场规模上,通过进行亚转录组测序结合宏基因组测序,从中国患有RD的猪的肺部鉴定出病毒和细菌。我们还展示了不同病毒和/或细菌物种在猪RD中的复杂相互作用。我们的工作为猪RD的病因学,流行病学和微生物相互作用提供了全面的知识,并为研究和开发有效的疫苗提供了数据参考。
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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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