Spatial and temporal dynamics of microbiomes and resistomes in broiler litter stockpiles

Comput Struct Biotechnol J. 2021 Nov 18:19:6201-6211. doi: 10.1016/j.csbj.2021.11.020. eCollection 2021.

Abstract

Farmers apply broiler chicken litter to soils to enrich organic matter and provide crops with nutrients, following varying periods of stockpiling. However, litter frequently harbors fecal-derived microbial pathogens and associated antibiotic resistance genes (ARGs), and may be a source of microbial contamination of produce. We coupled a cutting-edge Loop Genomics long-read 16S rRNA amplicon-sequencing platform with high-throughput qPCR that targeted a suite of ARGs, to assess temporal (five time points over a 60-day period) and spatial (top, middle and bottom layers) microbiome and resistome dynamics in a broiler litter stockpile. We focused on potentially pathogenic species from the Enterobacteriaceae, Enterococcaceae and Staphylococcaceae families associated with food-borne disease. Bacterial diversity was significantly lower in the middle of the stockpile, where targeted pathogens were lowest and Bacillaceae were abundant. E. coli was the most abundant Enterobacteriaceae species, and high levels of the opportunistic pathogen Enterococcus faecium were detected. Correlation analyses revealed that the latter was significantly associated with aminoglycoside (aac(6')-Ib(aka aacA4), aadA5), tetracycline (tetG), vancomycin (vanC), phenicol (floR) and MLSB (mphB) resistance genes. Staphylococcaceae were primarily non-pathogenic, but extremely low levels of the opportunistic pathogen S. aureus were detected, as was the opportunistic pathogen S. saprophyticus, which was linked to vancomycin (vanSA, vanC1), MLSB (vatE, ermB) and tetracycline (tetK) resistance genes. Collectively, we found that stockpile microbiomes and resistomes are strongly dictated by temporal fluctuations and spatial heterogeneity. Insights from this study can be exploited to improve stockpile management practice to support sustainable antimicrobial resistance mitigation policies in the future.

Keywords: Antibiotic resistance bacteria; Antibiotic resistance gene; Bioinformatics; Broiler litter; Long-read sequencing; Microbiome.