Biospectroscopic investigation on bacterial response to antimicrobials

Jin, Naifu and Martin, Frank and Zhang, Dayi and Semple, Kirk (2018) Biospectroscopic investigation on bacterial response to antimicrobials. PhD thesis, Lancaster University.

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Overuse and abuse of antimicrobial-associated materials in human activities may lead to microbes acquire resistance to antimicrobials since antimicrobials not only act as an eliminator for microbes but also a selective agent for the microorganisms with resistant abilities. Moreover, over 95% of bacteria living on earth are unculturable, and most of their living style is functioning as the microbiome, e.g., bacterial biofilms, which therefore substantially increase the difficulty regarding the investigation on microbial response to antimicrobials, or in other words, functional microbes under exposure of antimicrobials. Biospectroscopy, as an interdisciplinary tool including Raman and infrared spectroscopies, can generate conclusive information regarding the biological constituents, including lipids, proteins, carbohydrates and DNA/RNA, etc. Such biochemical information can be used to fingerprint microbiome and then assess the microbial functions which remain a challenge due to more conventional approaches are too expensive and/or time-consuming and often predicated on prior knowledge of the microorganisms one wishes to study. Additionally, computational analysis is subsequently applied to process and analyze the raw spectra generated by Raman and IR spectroscopies to obtain meaningful information and get a deeper insight into the wavenumbers-related biochemical alterations. This extra step may provide a solution of assessing a significant amount of complicated biochemical information derived from heterogeneous biological samples. The current project summarized the drawbacks within the conventional approaches and proposes a new perspective that using spectroscopic tools coupled with various of computational analysis such as multivariant analysis and a newly developed dispersion model to investigate microbial functions (primarily on antibiotic resistance) as well as set up a baseline to determine the factors may influence the microbiome; and ultimately develop a noninvasive sensor-based tool that could be applied to monitor the emergence of antibiotic-resistant microorganisms in real-time. This would be hugely cost-efficient and allow for monitoring of antibiotic usage, a major problem currently.

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Thesis (PhD)
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31 May 2018 08:56
Last Modified:
31 Dec 2023 00:07