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Ma, Luyao

University of British Columbia

Antimicrobial-resistant Campylobacter has been regarded as a high priority of public health concern worldwide. This microbe asymptomatically resides in the intestinal tract of animals and may transmit to humans through the consumption of contaminated animal products. It is not fully understood how Campylobacter develops and spreads antimicrobial resistance (AMR) in agri-food systems. This knowledge gap is partially due to a lack of rapid detection methods, inefficient data integration in current surveillance programs, rapid evolution of AMR variants, and insufficient studies in AMR gene transfer. This dissertation focused on addressing the aforementioned problems to better tackle the global AMR crisis. A microfluidic device was developed to identify Campylobacter, with 100% specificity and detection limits down to 10² CFU/mL in milk and 10⁴ CFU/25 g in chicken meat. On-chip antimicrobial susceptibility testing (AST) showed a good agreement (>90%) with the conventional culture-based method. This miniaturized device enabled on-site detection, consumed ~99% fewer reagents, and saved >50% of analysis time. This microfluidic device was further integrated into an internet of things (IoT)-based AMR surveillance program. A machine learning algorithm was employed for classifying on-chip AST results, providing 99.5% accuracy in determining Campylobacter AMR profiles. Both spatial and temporal AMR trends were uploaded to a cloud database for real-time data integration and presentation. Alternatively, Raman spectroscopy and chemometrics reduced the analysis time of AST to 5 h with acceptable accuracy. Raman spectroscopy-based approach deciphered distinct phenotypic responses of antimicrobial-susceptible and resistant Campylobacter to antibiotics. The spread of AMR genes in Campylobacter biofilms was 17-fold more efficient than planktonic cells, which was commonly used as an AMR evolution model. Campylobacter might develop AMR more frequently in the environment than previously expected. When co-cultivating with other foodborne pathogens, Campylobacter showed distinct gene transfer trends, ranging from 3.5×10⁻⁸ in Escherichia coli-C. jejuni biofilms to no detectable transmission in Salmonella-C. jejuni biofilms. This dissertation provides the technique and knowledge to monitor the prevalence of Campylobacter AMR in agri-food systems.

Text

2021-08-11

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/79269

Food Science

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/