Back

Antimicrobial Resistance Gene Distribution and Population Structure of Escherichia coli Isolated from Humans, Livestock, and the Environment: Insights from a One Health Approach

Lyimo, B.; Sonola, V.

2025-04-09 genetic and genomic medicine
10.1101/2025.04.07.25325408 medRxiv
Show abstract

Antimicrobial resistance (AMR) is an escalating public health threat, with evidence highlighting the exchange of resistance genes among humans, animals, and the environment. Whole-genome sequence (WGS) offers high-resolution pathogen subtyping and provides extensive insights into AMRs early emergence and spread. This study investigates the distribution of AMR genes, plasmid types, and the population structure of Escherichia coli isolates from humans, livestock, fish, and the environment. A total of 244 WGS datasets of E. coli isolates were pulled from a public database from multiple studies and analyzed to characterize AMR gene distribution, plasmid diversity, and population structure across humans, livestock and the environment. The findings reveal widespread dissemination of AMR genes across all sources. Aminoglycoside resistance genes (aac(3)-IId, aph(3)-Ib, aph(6)-Id, aadA1, aadA5) and {beta}-lactam resistance genes (blaTEM-1, blaOXA-1, blaCTX-M-15) were prevalent across all environments. Quinolone resistance mutations (gyrA_S83L, gyrA_D87N, parC_S80I) were also shared among human, livestock, fish, and environmental isolates, indicating cross-species transmission. Tetracycline resistance genes (tet(A), tet(B), tet(D)) were found in humans, livestock, and fish. Plasmid types IncFIA, IncI1, and IncFII exhibited extensive cross-source sharing, with strong connectivity between humans and livestock. Principal Component Analysis (PCA) revealed that E. coli isolates from Kenya formed a tight, distinct cluster, while others were more dispersed. The Minimum Spanning Tree (MST) network showed the clusters where human and livestock isolates were closely connected, it further showed some human isolates cluster with fish and environmental isolates. The MST network demonstrated close clustering of human and livestock isolates, indicating possible cross-species transmission. These findings showed the interconnected nature of AMR across human, animal, and environmental sectors and underscored the need for integrated surveillance under a One Health framework to monitor and control the spread of clinically significant AMR genes.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.