Development of liquid AP-MALDI mass spectrometry (MS) for microbial profiling and biotyping
Development of liquid AP-MALDI mass spectrometry (MS) for microbial profiling and biotyping
批准号:
2104529
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2018
资助国家:
英国
项目状态:
已结题
起止时间:
2018 至 --
中文摘要
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英文摘要
Development of liquid AP-MALDI mass spectrometry (MS) for microbial profiling and biotypingMicrobial biotyping using MALDI mass spectral profiles of singly charged peptide ions has been recently established as a superior method to classical clinical microbiology assays for the identification of clinically relevant microbes with substantially increased classification accuracy and speed of analysis. Recently, this has led to two FDA-approved systems for microbial detection and identification by MALDI MS biotyping. This methodology is now under further development for extending it to AMR detection.We propose to advance this methodology even further by using our newly developed laser-based AP-MALDI ion source, exploiting its unique capability to create multiply charged (peptide and protein) analyte ions as well as its greater speed and flexibility in sample preparation through the use of liquid samples and essentially a simpler ion source design.The availability of multiply charged ions through our new methodology will allow superior identification by MS/MS sequencing due to the well-known superior fragmentation of multiply charged ions. It will also allow the efficient elimination of singly charged biological matrix background ions (e.g. from the culture media) by ion mobility filtering and the use of high-performing mass spectrometers such as orbitraps. These and the advantages of a simpler ion source design, and thus increased sample access speed, are not achievable with the current FDA-approved MALDI-TOF MS technologies for biotyping.Thus, the proposed PhD studentship will investigate the (A) superior microbial identification by utilising MS/MS sequencing of multiply charged MALDI ions, (B) increase in the signal-to-noise ratio by greater than or equal to 100 using ion mobility filtering, (C) greater flexibility in liquid matrix compositions and their potential in providing an adequate environment for AMR detection assays, and (D) increase in analytical speed due to the use of an atmospheric pressure (AP) ion source and simpler sample preparations.The assembled supervisory team consists of experts in the field of analytical chemistry, liquids and (clinical) microbiology, linking the University of Reading with the Royal Berkshire Hospital, and includes scientist at different stages of their academic careers.WorkplanAfter H&S and other essential inductions/assessments, the research part of the project will start with testing and optimising extraction protocols for liquid MALDI MS analysis of microbial cultures, initially using lactobacteria, which will be obtained from Prof Gibson's group. These bacteria have several advantages: they are well-characterised and understood here at the University, have a sequenced genome and are safe to handle. In this preliminary work, methods will be tested for shortest culture times and extractions that provide sufficient amounts of specific marker ions that can be used for unambiguous identification by MS/MS sequencing (see objective A).The above work will be extended by using ion mobility filtering, which will further improve the signal-to-noise ratio (see objective B). Here, different filter settings will be investigated such as various combinations of elimination filters for single charged ions and specific filter windows for specific classes of biomolecules (e.g. peptides vs proteins vs lipids). In addition, extraction protocols for clinical isolates will be investigated with the goal to achieve both best extraction and the provision of biologically safe extracts from clinical bacterial strains.Next, AMR assays will be developed that will take advantage of the easily detectable mass shift after hydrolysis of the beta-lactam rings of antibiotics by microbial lactamase activity. Here, the optimal addition of enzyme, substrate and buffers will be determined with a view on efficient substrate recovery and subsequent MS analysis (see objective C).
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