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Abstract Despite a rapid expansion of Porcine reproductive and respiratory syndrome virus (PRRSV) sublineage 8.7 over recent years, very little is known about the patterns of virus evolution, dispersal, and the factors influencing this dispersal. Relying on a national PRRSV surveillance project established over 20 years ago, we expand the available genomic data of sublineage 8.7 from China. We perform independent interlineage and intralineage recombination analyses for the entire study period, which showed a heterogeneous recombination pattern. A series of Bayesian phylogeographic analyses uncover the role of Guangdong as an important infection hub within Asia. The spatial spread of PRRSV is highly linked with a composite of human activities and the heterogeneous provincial distribution of the swine industry, largely propelled by the smaller-scale Chinese rural farming systems in the past years. We sequence all four available modified live vaccines (MLVs) and perform genomic analyses with publicly available data, of which our results suggest a key “leaky” period spanning 2011–2017 with two concurrent amino acid mutations in ORF1a 957 and ORF2 250. Overall, our study provides an in-depth overview of the evolution, transmission dynamics, and potential leaky status of HP-PRRS MLVs, providing critical insights into new MLV development.

ABSTRACT 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.IMPORTANCEFrequent 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.