Abstract/Summary

Rising antimicrobial resistance (AMR) is a challenge to public health, animal health, and the environment. Early detection of phenotypic-based antimicrobial resistance remains an essential step to effectively optimizing antibiotic treatments. By using 3D printed technology and Raspberry Pi - computers, two novel assays were developed for early detection of antimicrobial resistance based on motility and the bacterial response to antibiotics on agar media. Integrating culture steps and determination of minimum inhibitory concentration (MIC) into one single test, this thesis elucidated the identification of bacterial species and their MIC within hours using a frame dip slide, as well as within just 5 minutes of testing to show the results of bacterial susceptibility based on their movement or stop swimming. In addition, the temperature remains a crucial factor for bacterial growth. By designing a mobile incubator, all microbiology tests can be carried out in a variety of settings including next to the bed of patients or in the field, instead of in the laboratory. Automation of image analysis contributes another tool to better understand physiological bacteria when living in vitro conditions. These successful tools contributed alternative approaches to surveying at real-time detection of antimicrobial resistance in the field. Beyond the laboratory, these tools brought the concept to combine all-in-one. Using a frame dip slide combined with a mobile incubator as well as combining Microcapillary Film (MCF) with 3D printed microscopy created a portable kit for affordable phenotypic assays for rapid detection of bacterial antibiotic resistance anywhere, not just for performing in the laboratory.