Characteristics and Traceability Analysis of Microbial Assemblage in Fine Particulate Matter from a Pig House.

Fine particulate matter (PM2.5) can carry numerous substances and penetrate deep into the respiratory tract due to its small particle size; associated harmful microorganisms are suspected to increase health risks for humans and animals. To find out the microbial compositions of PM2.5 in piggeries, their interaction and traceability, we collected PM2.5 samples from a piggery while continuously monitoring the environmental indicators. We also identified pathogenic bacteria and allergens in the samples using high-throughput sequencing technology. We analyzed the microbial differences of PM2.5 samples at different heights and during different times of day and investigated the microbial dynamics among the PM2.5 samples. To better understand the interaction between microorganisms and environmental factors among different microbial communities, we applied the network analysis method to identify the correlation among various variables. Finally, SourceTracker, a commonly used microbial traceability tool, was used to predict the source of airborne microorganisms in the pig house. We identified 14 potential pathogenic bacteria and 5 allergens from PM2.5 in the pig houses, of which Acinetobacter was the dominant bacterium in all samples (relative abundance > 1%), which warrants attention. We found that bacteria and fungi directly affected the the microbial community. The bacterial community mainly played a positive role in the microbial community. Environmental variables mainly indirectly and positively affected microbial abundance. In the SourceTracker analysis using fecal matter and feed as sources and PM2.5 sample as sink, we found that fecal matter made the greatest contribution to both bacterial and fungal components of PM2.5. Our findings provide important insights into the potential risks of pathogens in PM2.5 to human and animal health and their main sources.

Identifying geographic origins of the Escherichia coli isolates from food by a method based on single-nucleotide polymorphisms.

BACKGROUND: E.coli is an important foodborne pathogen. Rapid and robust tracking of the source of E. coli is the key step to control foodborne infections. RESULTS: In this study, a genotyping and tracing method based on highly discriminatory single nucleotide polymorphisms (SNPs) was developed to investigate the geographical origin of E. coli in food. A highly informative set of 12 SNPs was derived from 4 housekeeping genes in E. coli multilocus sequence typing (MLST) database. A collection of 253 E. coli isolates from food in 12 countries and regions were screened, resulting in a total of 61 profiles, 35 geographically specific SNP profiles were revealed and further verified by blind sample test. Also, the evolutionary relationship of 61 SNP profiles with different geographical origins was established by the enhanced analysis Based Upon Related Sequence Types (eBURST) analysis, which provided evidence that strains of different geographical origins owned the same ancestor strain. CONCLUSIONS: Our study established a powerful method based on a set of 12 SNPs for identifying geographical origins. The blind sample analysis proved that this SNPs panel had a high traceability of E. coli in food. Furthermore, this method based on SNPs combined with eBURST analysis revealed the potential evolutionary relationship between E.coli strains of different geographical origins.