Data based slurry treatment decision tree to minimise antibiotic resistance and pathogen transfer while maximising nutrient recycling

Abstract

Direct application of pig slurry to agricultural land introduces pathogens, antibiotic resistant bacteria, or genes, to the envi-ronment. With global environmental sustainability policies mandating a reduction in synthetic fertilization and a commit-ment to a circular economy it is imperative to find effective on-farm treatments of slurry that maximizes its fertilization val-ue and minimizes risk to health and the environment. We compared the effect of storage, composting, and anaerobic diges-tion on pig slurry microbiome, resistome and nutrient content using shotgun metagenomic sequencing and HT-qPCR arrays. Our results identified that each treatment method had advantages and disadvantages, depending on the parameter measured. Storage and composting were optimal for the removal of human pathogens and anaerobic digestion (AD) for the reduction in antimicrobial resistance (AMR) genes and mobile genetic elements. The nitrogen content was increased in storage and AD and reduced in composting. Our data indicates that composting provided the reduction in risk to human health and the envi-ronment. Network analysis revealed reducing Proteobacteria and Bacteroidetes while increasing Firmicutes reduced AMR content. This novel study provides a data driven decision tree to determine the optimal treatment for best practice to mini-mize pathogen, AMR, and optimum nutrient transfer from slurry to environment.