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.

WITHDRAWN: Demographic and ecological drivers of infectome diversity in companion cats

“…A pathogen was considered as "positive" in a sample if its abundance level was greater than 1 RPM (36). To identify potential false-positives resulting from index hopping, we used a threshold of 0.1% for pathogens present in the libraries from the same sequencing lane: any read numbers < 0.1% of the most abundant library were treated as "negative" as previously deployed (36,40). In addition, marker genes (groEL for Rickettsia, 5.8S ribosomal RNA for Tritrichomonas foetus) were mapped to conduct phylogenetic analysis for determination of evolutionary groups (see phylogenetic analysis).…”

“…Meta-transcriptomics enables the synchronous targeting of all types of microorganisms, identification of potential pathogens without prior knowledge, examination of the expressed genomic evolutionary patterns during infection, and precise identification of pathogenic co-infection dynamics and loads. This technique has been successful in revealing the entire pathogen spectrum -including viruses, bacteria, fungi, and parasites (i.e., total infectome) -in a single infection case, making it a powerful tool for modern pathogen discovery efforts (35)(36)(37)(38)(39)(40).…”

A Longitudinal Study of NADC34-Like Strains in an Intensive Farm Unravels Divergent Evolution

“…It can be presumed that the increased abundance of microbiota with a synergistic effect after PRRSV infection was the cause. Previous studies have suggested that correlation analysis performed on respiratory samples from immune-deficient individuals with infections provided insight into the synergistic relationship between respiratory pathogens [49]. The infection of PRRSV causes changes in animal organism functions, which may lead to secondary infections by other pathogens.…”