Dr JING ZHANG's Outputs (2)

Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock (2022)
Journal Article
Maciel-Guerra, A., Baker, M., Hu, Y., Wang, W., Zhang, X., Rong, J., Zhang, Y., Zhang, J., Kaler, J., Renney, D., Loose, M., Emes, R. D., Liu, L., Chen, J., Peng, Z., Li, F., & Dottorini, T. (2023). Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock. ISME Journal, 17(1), 21-35. https://doi.org/10.1038/s41396-022-01315-7

A debate is currently ongoing as to whether intensive livestock farms may constitute reservoirs of clinically relevant antimicrobial resistance (AMR), thus posing a threat to surrounding communities. Here, combining shotgun metagenome sequencing, mac... Read More about Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock.

Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming (2022)
Journal Article
Peng, Z., Maciel-Guerra, A., Baker, M., Zhang, X., Hu, Y., Wang, W., Rong, J., Zhang, J., Xue, N., Barrow, P., Renney, D., Stekel, D., Williams, P., Liu, L., Chen, J., Li, F., & Dottorini, T. (2022). Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming. PLoS Computational Biology, 18(3), Article e1010018. https://doi.org/10.1371/journal.pcbi.1010018

Anthropogenic environments such as those created by intensive farming of livestock, have been proposed to provide ideal selection pressure for the emergence of antimicrobial-resistant Escherichia coli bacteria and antimicrobial resistance genes (ARGs... Read More about Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming.