📖 ABSTRACT/OVERVIEW
This dissertation employs an original systems biology approach to characterise the ecological and evolutionary drivers of antimicrobial resistance in foodborne pathogens across Nigerian agricultural food systems, integrating metagenomic resistome profiling, longitudinal ecological sampling, evolutionary modelling, and food chain network analysis to produce the most comprehensive characterisation of food system AMR dynamics yet undertaken in sub-Saharan Africa. AMR in food systems is a complex adaptive problem involving co-evolutionary dynamics between bacteria, resistance genes, mobile genetic elements, and selective pressures from antimicrobial use, none of which can be understood in isolation. The dissertation employs a longitudinal systems epidemiology design across four agricultural food chains (broiler chicken, dairy cattle, smallholder pig, and catfish aquaculture) in the South West and North West geopolitical zones over two years. Metagenomics samples are collected at five points in each food chain from primary production through retail. Resistome profiling, mobile genetic element characterisation, and longitudinal resistome dynamic modelling using differential equation systems biology models are the core analytical components. Phenotypic resistance data from 2,000 isolates provide validation data for the computational models. The dissertation proposes the Nigerian Food System AMR Dynamics Model (NFSAM-DM) as an original theoretical and computational contribution. The NFSAM-DM demonstrates that antibiotic use in poultry production generates resistome spillover detectable in human clinical settings within six to eight weeks through contaminated poultry products and worker occupational exposure, with mobile genetic elements as the primary transmission vectors. Keywords: antimicrobial resistance, systems biology, food systems, metagenomics, Nigeria.
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