DATA CHALLENGE _MY INNOVATIVE IDEA

Modeling Antimicrobial Resistance Transmission in Acinetobacter baumannii Across Human and Animal Reservoirs: Integrating Plasmid Dynamics and Pseudogene-Targeted Intervention in a One Health Framework

Abstract:

The rise of multidrug-resistant Acinetobacter baumannii in both clinical and veterinary settings emphasizes the urgent need for unified surveillance and control strategies under a One Health paradigm. In this study, we integrate phenotypic resistance profiles from the ATLAS clinical database with whole-genome sequences from the Veterinary Laboratory Investigation and Response Network (Vet-LIRN) to map the genomic architecture of resistance determinants in A. baumannii.

Drawing on established mathematical frameworks of plasmid–host associations, we will quantify the relative prevalence of resistance genes on plasmids versus chromosomes, testing the local adaptation hypothesis and applying stochastic birth-death and population dynamics models (Tazzyman & Bonhoeffer 2014, 2015) to assess the fitness trade-offs of plasmid-borne versus chromosomal loci. We will extend ODE models of horizontal gene transfer (van Dijk et al. 2020) to classify A. baumannii resistance genes into indispensable, enrichable, rescuable, unrescuable, and selfish categories, evaluating their persistence across variable rates of conjugation, plasmid copy number, and chromosomal gene degradation.
Simultaneously, we will deploy a bioinformatics pipeline to identify pseudogenes (frameshifted or truncated gene fragments) in clinical and veterinary isolates. By incorporating pseudogene dynamics into our transmission models, we will simulate targeted “in silico mutagenesis” interventions: restoring function in beneficial genes or disrupting residual resistance determinants to predict their impact on population-level AMR trajectories.

Finally, we will synthesize these elements into coupled deterministic and stochastic transmission models that integrate plasmid transfer rates, gene category stability, pseudogene reversion/disruption scenarios, and realistic antibiotic usage patterns in hospital and farm environments. This comprehensive One Health modeling framework will pinpoint critical surveillance targets and propose candidate genomic interventions to preemptively weaken A. baumannii resistance, guiding both policy and experimental validation for controlling its spread.