Show simple item record

dc.contributor.authorCharles, Philip David
dc.date.accessioned2020-01-31T15:20:03Z
dc.date.available2020-01-31T15:20:03Z
dc.date.issued2020-02-22
dc.date.submitted2018-09-27
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/301515
dc.description.abstractElemental metabolic labelling using 15N stable isotopes is a technique used in peptide-centric proteomics that allows samples to be mixed before preparation and analysis (minimising technical variance) without introducing sample ambiguity to the results. Labelling with 15N induces a mass shift in labelled peptides that, when analysed by mass spectrometry (MS), allows the signal associated with differently labelled samples to be differentiated. When compared to similar labelling techniques such as Stable Isotope Labelling by Amino acids in Cell culture (SILAC), 15N poses unique challenges for analysis because the level of label incorporation affects not only the relative intensity of signals in MS analysis, but also how that signal is distributed. A computational signal extraction algorithm is not easily generalised to all peptides, especially if there are differences in the level of incorporation. Analysis of 15N data has been neglected by the general pace of software development in proteomic MS. Furthermore, the current 15N analysis options have relatively complex installation procedures and are limited to a command-line interface. I describe the development of a cross-platform 15N quantification software package (HeavyMetL) which runs inside a web browser, requiring no installation procedure and providing a graphical interface for both the analysis of data and visual interrogation of results (in addition to a more typical text-format table output). The optimisation (using experimental data) of a core part of the algorithm to determine the level of 15N incorporation is described in detail. Finally, the performance of HeavyMetL is benchmarked against published 15N labelled data from Arabidopsis seedlings quantified by a previously published algorithm, showing that HeavyMetL produces quantification of equivalent or better quality.
dc.language.isoen
dc.rightsAll rights reserved
dc.subjectProteomics
dc.subjectBioinformatics
dc.subjectBiochemistry
dc.subjectNitrogen-15
dc.subject15N
dc.subjectMass Spectrometry
dc.subjectQuantitation
dc.subjectQuantification
dc.titleDevelopment of a Software Package for the Quantitative Analysis of Proteomic Mass Spectrometry Datasets Labelled with Nitrogen-15
dc.typeThesis
dc.type.qualificationlevelDoctoral
dc.type.qualificationnameDoctor of Philosophy (PhD)
dc.publisher.institutionUniversity of Cambridge
dc.publisher.departmentBiochemistry
dc.date.updated2020-01-31T12:02:00Z
dc.identifier.doi10.17863/CAM.48584
dc.contributor.orcidCharles, Philip David [0000-0001-5278-5354]
dc.publisher.collegeDowning
dc.type.qualificationtitlePhD in Biochemistry
cam.supervisorLilley, Kathryn Susan
cam.supervisor.orcidLilley, Kathryn Susan [0000-0003-0594-6543]
cam.thesis.fundingtrue
rioxxterms.freetoread.startdate2021-01-31


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record