Computational and Structural Biotechnology Journal (Jan 2021)

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

  • Chhedi Lal Gupta,
  • Ran Avidov,
  • Karuppasamy Kattusamy,
  • Ibrahim Saadi,
  • Vempalli Sudharsan Varma,
  • Shlomo E. Blum,
  • Yong‑Guan Zhu,
  • Xin‑Yuan Zhou,
  • Jian‑Qiang Su,
  • Yael Laor,
  • Eddie Cytryn

Journal volume & issue
Vol. 19
pp. 6201 – 6211

Abstract

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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.

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