AUTHOR=Kilonzo-Nthenge Agnes , Rafiqullah Iftekhar , Netherland Michael , Nzomo Maureen , Mafiz Abdullah , Nahashon Samuel , Hasan Nur A. TITLE=Comparative metagenomics of microbial communities and resistome in southern farming systems: implications for antimicrobial stewardship and public health JOURNAL=Frontiers in Microbiology VOLUME=15 YEAR=2024 URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2024.1443292 DOI=10.3389/fmicb.2024.1443292 ISSN=1664-302X ABSTRACT=
Agricultural practices significantly influence microbial diversity and the distribution of virulence and antimicrobial resistance (AMR) genes, with implications for ecosystem health and food safety. This study used metagenomic sequencing to analyze 60 samples (30 per state) including water, soil, and manure (10 each) from Alabama (a mix of cattle and poultry sources) and Tennessee (primarily from cattle). The results highlighted a rich microbial diversity, predominantly comprising Bacteria (67%) and Viruses (33%), with a total of over 1,950 microbial species identified. The dominant bacterial phyla were Proteobacteria, Cyanobacteria, Actinobacteria, Firmicutes, and Bacteroidetes, with the viral communities primarily represented by Phixviricota and Uroviricota. Distinct state-specific microbial profiles were evident, with Alabama demonstrating a higher prevalence of viral populations and unique bacterial phyla compared to Tennessee. The influence of environmental and agricultural practices was reflected in the microbial compositions: soil samples were notably rich in Actinobacteria, water samples were dominated by Proteobacteria and Cyanobacteria, and manure samples from Alabama showed a predominance of Actinobacteria. Further analyses, including diversity assessment and enterotype clustering, revealed complex microbial structures. Tennessee showed higher microbial diversity and phylogenetic complexity across most sample types compared to Alabama, with poultry-related samples displaying distinct diversity trends. Principal Coordinate Analysis (PCoA) highlighted notable state-specific variations, particularly in manure samples. Differential abundance analysis demonstrated elevated levels of