Vereecke Nick, Zwickl Sophia, Gumbert Sophie, Graaf Annika, Harder Timm, Ritzmann Mathias, Lillie-Jaschniski Kathrin, Theuns Sebastiaan, Stadler Julia
Laboratory of Virology, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium.
PathoSense BV, Lier, Belgium.
Microbiol Spectr. 2023 Feb 28;11(2):e0009823. doi: 10.1128/spectrum.00098-23.
Swine influenza A virus (swIAV) plays an important role in porcine respiratory infections. In addition to its ability to cause severe disease by itself, it is important in the multietiological porcine respiratory disease complex. Still, to date, no comprehensive diagnostics with which to study polymicrobial infections in detail have been offered. Hence, veterinary practitioners rely on monospecific and costly diagnostics, such as Reverse Transcription quantitative PCR (RT-qPCR), antigen detection, and serology. This prevents the proper understanding of the entire disease context, thereby hampering effective preventive and therapeutic actions. A new, nanopore-based, metagenomic diagnostic platform was applied to study viral and bacterial profiles across 4 age groups on 25 endemic swIAV-infected German farms with respiratory distress in the nursery. Farms were screened for swIAV using RT-qPCR on nasal and tracheobronchial swabs (TBS). TBS samples were pooled per age, prior to metagenomic characterization. The resulting data showed a correlation between the swIAV loads and the normalized reads, supporting a (semi-)quantitative interpretation of the metagenomic data. Interestingly, an in-depth characterization using beta diversity and PERMANOVA analyses allowed for the observation of an age-dependent interplay of known microbial agents. Also, lesser-known microbes, such as porcine polyoma, parainfluenza, and hemagglutinating encephalomyelitis viruses, were observed. Analyses of swIAV incidence and clinical signs showed differing microbial communities, highlighting age-specific observations of various microbes in porcine respiratory disease. In conclusion, nanopore metagenomics were shown to enable a panoramic view on viral and bacterial profiles as well as putative pathogen dynamics in endemic swIAV-infected herds. The results also highlighted the need for better insights into lesser studied agents that are potentially associated with porcine respiratory disease. To date, no comprehensive diagnostics for the study of polymicrobial infections that are associated with porcine respiratory disease have been offered. This precludes the proper understanding of the entire disease landscape, thereby hampering effective preventive and therapeutic actions. Compared to the often-costly diagnostic procedures that are applied for the diagnostics of porcine respiratory disease nowadays, a third-generation nanopore sequencing diagnostics workflow presents a cost-efficient and informative tool. This approach offers a panoramic view of microbial agents and contributes to the in-depth observation and characterization of viral and bacterial profiles within the respiratory disease context. While these data allow for the study of age-associated, swIAV-associated, and clinical symptom-associated observations, it also suggests that more effort should be put toward the investigation of coinfections and lesser-known pathogens (e.g., PHEV and PPIV), along with their potential roles in porcine respiratory disease. Overall, this approach will allow veterinary practitioners to tailor treatment and/or management changes on farms in a quicker, more complete, and cost-efficient way.
甲型猪流感病毒(swIAV)在猪呼吸道感染中起着重要作用。除了自身能够引发严重疾病外,它在多病因的猪呼吸道疾病综合征中也很重要。然而,迄今为止,尚未提供用于详细研究混合微生物感染的全面诊断方法。因此,兽医从业者依赖于单特异性且成本高昂的诊断方法,如逆转录定量聚合酶链反应(RT-qPCR)、抗原检测和血清学检测。这阻碍了对整个疾病背景的正确理解,从而妨碍了有效的预防和治疗措施。一种新的基于纳米孔的宏基因组诊断平台被应用于研究25个德国地方性swIAV感染猪场中4个年龄组的病毒和细菌谱,这些猪场的保育猪有呼吸窘迫症状。使用RT-qPCR对鼻拭子和气管支气管拭子(TBS)进行swIAV筛查。在进行宏基因组特征分析之前,按年龄将TBS样本合并。所得数据显示swIAV载量与标准化读数之间存在相关性,支持对宏基因组数据进行(半)定量解释。有趣的是,使用β多样性和PERMANOVA分析进行深入表征,能够观察到已知微生物因子的年龄依赖性相互作用。此外,还观察到了一些不太知名的微生物,如猪多瘤病毒、副流感病毒和血凝性脑脊髓炎病毒。对swIAV发病率和临床症状的分析显示出不同的微生物群落,突出了猪呼吸道疾病中不同微生物的年龄特异性观察结果。总之,纳米孔宏基因组学能够全景展示地方性swIAV感染猪群中的病毒和细菌谱以及假定的病原体动态。研究结果还强调了需要更好地了解那些可能与猪呼吸道疾病相关但研究较少的病原体。迄今为止,尚未提供用于研究与猪呼吸道疾病相关的混合微生物感染的全面诊断方法。这妨碍了对整个疾病情况的正确理解,从而阻碍了有效的预防和治疗措施。与目前用于诊断猪呼吸道疾病的通常成本高昂的诊断程序相比,第三代纳米孔测序诊断工作流程是一种具有成本效益且信息丰富的工具。这种方法提供了微生物因子的全景视图,并有助于在呼吸道疾病背景下深入观察和表征病毒和细菌谱。虽然这些数据有助于研究与年龄相关、与swIAV相关以及与临床症状相关的观察结果,但也表明应更加努力地研究合并感染和不太知名的病原体(如猪血凝性脑脊髓炎病毒和猪副流感病毒)及其在猪呼吸道疾病中的潜在作用。总体而言,这种方法将使兽医从业者能够以更快、更全面且成本效益更高的方式调整农场的治疗和/或管理措施。