Development of microbial identification platform for industrial pharmaceutical microbiology using high-throughput Laser-Assisted Rapid Evaporative Ionisation Mass Spectrometry (LA-REIMS)
Author(s)
Ramonaite, Toma
Type
Thesis or dissertation
Abstract
Pharmaceutical microbiology studies microorganisms to help with drug production or to control the environment around a procedure. The primary goals of pharmaceutical microbiology are to minimise the presence of microorganisms in a processing environment and to prevent the contamination of water and other starting materials with microorganisms and their by-products. As a result, the pharmaceutical industry has devoted substantial effort to the development of quick, sensitive, and accurate methods of identifying indicator bacteria. Due to their inherent advantages of quick data capture, high sensitivity, and specificity, mass spectrometry methods have emerged as one of the main means of building rapid microbiology platforms and are being utilised more frequently in clinical and pharmaceutical microbiology laboratories.
This research projects focuses on developing a LA-REIMS based microbial detection tool for pharmaceutical microbiology that can offer rapid high-accuracy results in as little as a few minutes without any sample pre-processing, performing analysis directly from a microbial petri dish on the sample in its native form. A large library of microbial spectroscopic fingerprints was generated using the prototype automated LA-REIMS platform and utilised to develop training and validation sets for machine learning based multivariate classification models.
LA- REIMS improves analytical throughput and sensitivity with full automation, maximizing the impact for industrial microbiology and direct-from-sample isolate detection. Using single MS technique, a wide range of microorganisms were identified at a remarkable classification accuracy of 100%.
By utilising direct, rapid, real-time, and high-throughput sampling/ionisation of analytes from direct samples without any sample pre-processing LA-REIMS provides substantially enhanced analytical efficiency and offers a powerful and efficient tool for pharmaceutical microbiology.
This research projects focuses on developing a LA-REIMS based microbial detection tool for pharmaceutical microbiology that can offer rapid high-accuracy results in as little as a few minutes without any sample pre-processing, performing analysis directly from a microbial petri dish on the sample in its native form. A large library of microbial spectroscopic fingerprints was generated using the prototype automated LA-REIMS platform and utilised to develop training and validation sets for machine learning based multivariate classification models.
LA- REIMS improves analytical throughput and sensitivity with full automation, maximizing the impact for industrial microbiology and direct-from-sample isolate detection. Using single MS technique, a wide range of microorganisms were identified at a remarkable classification accuracy of 100%.
By utilising direct, rapid, real-time, and high-throughput sampling/ionisation of analytes from direct samples without any sample pre-processing LA-REIMS provides substantially enhanced analytical efficiency and offers a powerful and efficient tool for pharmaceutical microbiology.
Version
Open Access
Date Issued
2023-06-29
Date Awarded
2024-08-01
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Takats, Zoltan
Guest, Miriam
Ray, Andrew
Sponsor
Engineering and Physical Sciences Research Council
Grant Number
EPSRC iCase 2017
Publisher Department
Department of Metabolism, Digestion and Reproduction
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)