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Metagenomic and HT-qPCR analysis reveal the microbiome and resistome in pig slurry under storage, composting, and anaerobic digestion

  • Thi Thuy Do
  • , Stephen Nolan
  • , Nicky Hayes
  • , Vincent O'Flaherty
  • , Catherine Burgess
  • , Fiona Brennan
  • , Fiona Walsh
  • Maynooth University
  • University of Galway
  • Teagasc - Irish Agriculture and Food Development Authority
  • Teagasc Food Research Centre

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

31 Citations (Scopus)

Abstract

Direct application of pig slurry to agricultural land, as a means of nutrient recycling, introduces pathogens, antibiotic resistant bacteria, or genes, to the environment. With global environmental sustainability policies mandating a reduction in synthetic fertilisation and a commitment to a circular economy it is imperative to find effective on-farm treatments of slurry that maximises its fertilisation value and minimises risk to health and the environment. We assessed and compared the effect of storage, composting, and anaerobic digestion (AD) on pig slurry microbiome, resistome and nutrient content. Shotgun metagenomic sequencing and HT-qPCR arrays were implemented to understand the dynamics across the treatments. Our results identified that each treatment methods have advantages and disadvantages in removal pollutants or increasing nutrients. The data suggests that storage and composting are optimal for the removal of human pathogens and anaerobic digestion for the reduction in antibiotic resistance (AMR) genes and mobile genetic elements. The nitrogen content is increased in storage and AD, while reduced in composting. Thus, depending on the requirement for increased or reduced nitrogen the optimum treatment varies. Combining the results indicates that composting provides the greatest gain by reducing risk to human health and the environment. Network analysis revealed reducing Proteobacteria and Bacteroidetes while increasing Firmicutes will reduce the AMR content. KEGG analysis identified no significant change in the pathways across all treatments. This novel study provides a data driven decision tree to determine the optimal treatment for best practice to minimise pathogen, AMR and excess or increasing nutrient transfer from slurry to environment.

Original languageEnglish
Article number119271
JournalEnvironmental Pollution
Volume305
DOIs
Publication statusPublished - 15 Jul 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  3. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • Antibiotic resistance
  • Metagenomics
  • Microbiome
  • Pig slurry treatments
  • Resistome

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