Evolutionary inference reveals global natural histories and predicted pathways of antimicrobial resistance in <i>Klebsiella pneumoniae</i>

by Olav N. L. Aga, Sabrina J. Moyo, Joel Manyahi, Upendo Kibwana, Iren H. Löhr, Nina Langeland, Bjørn Blomberg, Iain G. Johnston

Antimicrobial resistance (AMR) is a substantial and growing global health burden. Understanding, and predicting, its evolution in specific pathogens will help responses across scales from individual patient cases to large-scale policy. Here, we use global data on AMR features, predicted from 47k Klebsiella pneumoniae genomes, with hypercubic transition path sampling to infer the evolutionary pathways by which AMR features in K. pneumoniae (KpAMR) are acquired across 102 countries, territories, and areas. We identify “globally consistent” evolutionary behaviors that hold across countries, and “globally divergent” behaviors including carbapenem and fluoroquinolone resistance that vary across countries. We show how these divergent dynamics covary both with public health superregion and drug use policy, and reveal competing evolutionary pathways within and between countries. Using newly sequenced data across several decades from sub-Saharan Africa, we show that this inferred global roadmap of KpAMR evolution successfully predicts prospective evolutionary dynamics. Together, we hope that the ability to characterize and predict evolutionary dynamics of AMR acquisition, connected to socio-economic and drug policy predictors, will help strengthen our understanding of AMR evolution worldwide.