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Convergence of resistance and evolutionary responses in Escherichia coli and Salmonella enterica co-inhabiting chicken farms in China

Baker, Michelle; Zhang, Xibin; Maciel-Guerra, Alexandre; Babaarslan, Kubra; Dong, Yinping; Wang, Wei; Hu, Yujie; Renney, David; Liu, Longhai; Li, Hui; Hossain, Muhammad; Heeb, Stephan; Tong, Zhiqin; Pearcy, Nicole; Zhang, Meimei; Geng, Yingzhi; Zhao, Li; Hao, Zhihui; Senin, Nicola; Chen, Junshi; Peng, Zixin; Li, Fengqin; Dottorini, Tania

Convergence of resistance and evolutionary responses in Escherichia coli and Salmonella enterica co-inhabiting chicken farms in China Thumbnail


Authors

Xibin Zhang

Alexandre Maciel-Guerra

Kubra Babaarslan

Yinping Dong

Wei Wang

Yujie Hu

David Renney

Longhai Liu

Hui Li

Muhammad Hossain

Zhiqin Tong

Nicole Pearcy

Meimei Zhang

Yingzhi Geng

Li Zhao

Zhihui Hao

Nicola Senin

Junshi Chen

Zixin Peng

Fengqin Li



Contributors

Xibin Zhang
Data Collector

Alexandre Maciel-Guerra
Data Curator

Kubra Babaarslan
Data Curator

Yinping Dong
Data Collector

Wei Wang
Data Collector

Yujie Hu
Data Collector

David Renney
Research Group

Longhai Liu
Research Group

Hui Li
Data Collector

Muhammad Hossain
Data Collector

Zhiqin Tong
Data Collector

Nicole Pearcy
Data Curator

Meimei Zhang
Data Collector

Yingzhi Geng
Data Collector

Li Zhao
Data Collector

Zhihui Hao
Editor

Nicola Senin
Supervisor

Junshi Chen
Supervisor

Zixin Peng
Supervisor

Fengqin Li
Supervisor

Abstract

Sharing of genetic elements among different pathogens and commensals inhabiting same hosts and environments has significant implications for antimicrobial resistance (AMR), especially in settings with high antimicrobial exposure. We analysed 661 Escherichia coli and Salmonella enterica isolates collected within and across hosts and environments, in 10 Chinese chicken farms over 2.5 years using novel data-mining methods. Most isolates within same hosts possessed same clinically relevant AMR-carrying mobile genetic elements (plasmids: 70.6%, transposons: 78%), which also showed recent common evolution. Machine learning revealed known and novel AMR-associated mutations and genes underlying resistance to 28 antimicrobials and primarily associated with resistance in E. coli and susceptibility in S. enterica. Many were essential and affected same metabolic processes in both species, albeit with varying degrees of phylogenetic penetration. Multi-modal strategies are crucial to investigate the interplay of mobilome, resistance and metabolism in cohabiting bacteria, especially in ecological settings where community-driven resistance selection occurs.

Journal Article Type Article
Acceptance Date Dec 6, 2023
Online Publication Date Jan 5, 2024
Publication Date Jan 5, 2024
Deposit Date Nov 27, 2023
Publicly Available Date Jan 9, 2024
Journal Nature Communications
Electronic ISSN 2041-1723
Publisher Nature Publishing Group
Peer Reviewed Peer Reviewed
Volume 15
Article Number 206
DOI https://doi.org/10.1038/s41467-023-44272-1
Public URL https://nottingham-repository.worktribe.com/output/27858919
Publisher URL https://www.nature.com/articles/s41467-023-44272-1
Additional Information Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.