학술논문

Application of phylodynamics to identify spread of antimicrobial-resistant Escherichia coli between humans and canines in an urban environment
Document Type
article
Source
Subject
Medical Microbiology
Biomedical and Clinical Sciences
Antimicrobial Resistance
Prevention
Genetics
Vaccine Related
Emerging Infectious Diseases
Biodefense
2.2 Factors relating to the physical environment
Aetiology
Infection
Animals
Humans
Dogs
Escherichia coli
Escherichia coli Infections
Bayes Theorem
Anti-Bacterial Agents
Anti-Infective Agents
Drug Resistance
Bacterial
Antimicrobial resistance
Canines
ESBL
Environment
Genomic epidemiology
Phylodynamics
Environmental Sciences
Language
Abstract
The transmission of antimicrobial resistant bacteria in the urban environment is poorly understood. We utilized genomic sequencing and phylogenetics to characterize the transmission dynamics of antimicrobial resistant Escherichia coli (AMR-Ec) cultured from putative canine (caninep) and human feces present on urban sidewalks in San Francisco, California. We isolated a total of fifty-six AMR-Ec isolates from human (n = 20) and caninep (n = 36) fecal samples from the Tenderloin and South of Market (SoMa) neighborhoods of San Francisco. We then analyzed phenotypic and genotypic antimicrobial resistance (AMR) of the isolates, as well as clonal relationships based on cgMLST and single nucleotide polymorphisms (SNPs) of the core genomes. Using Bayesian inference, we reconstructed the transmission dynamics between humans and caninesp from multiple local outbreak clusters using the marginal structured coalescent approximation (MASCOT). Our results provide evidence for multiple sharing events of AMR-Ec between humans and caninesp. In particular, we found one instance of likely transmission from caninesp to humans as well as an additional local outbreak cluster consisting of one caninep and one human sample. Based on this analysis, it appears that non-human feces act as an important reservoir of clinically relevant AMR-Ec within the urban environment for this study population. This work showcases the utility of genomic epidemiology to reconstruct potential pathways by which antimicrobial resistance spreads.