Total infectome of etiology and epidemiology unravels a complex infection landscape in Chinese acute diarrheal pig herds

Abstract Background Porcine diarrhea is predominantly caused by infectious pathogens, leading to decreased appetite, poor digestion, intestinal inflammation, dysbiosis, and weight loss. These factors significantly affect productivity and performance in modern farming systems. However, the interactions between these pathogens and their temporal-spatial dynamics, as well as their interactions with other concurrent pathogens in multiorgan complex diseases, are rarely considered. Thus, understanding the relevant etiology of these clinical manifestations is crucial. Results To address this gap, we used a meta-transcriptomics approach to jointly characterize the prevalence, abundance, evolutionary history, and natural diversity of a wide spectrum of pathogens within 122 cases of acute diarrhea from different pig farms, including 47 mixed group samples involving other pathological tissues. We categorized the samples into two groups: "intestine only" and "mixed tissue." We identified 43 species of pathogenic microbes, consisting of 37 species of viruses and six species of prokaryotes that contribute putatively to clinical manifestations. Evolutionary estimation revealed a highly divergent evolutionary dynamic of important swine pathogens that was previously unknown. Diversity analysis revealed that seasonal turnover was a significant factor affecting the structure of enteric pathogen populations. Correlation analysis performed on gut-only samples provided insight into the synergistic relationship between enteric pathogens. Comparative analysis of the infectome against both sampling categories mapped the heterogeneity of the pathogenic community underlying multiorgan complex diseases. Conclusion In summary, our meta-transcriptomics approach revealed a complex infectome of porcine diarrhea, which threatens livestock and humans. It offers valuable prior knowledge of disease interactions for veterinarians prior to clinical diagnosis. Our findings may serve as a reference for understanding microbial communities and could inform disease prevention and control strategies.