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Leveraging shotgun proteomics for optimised interpretation of data-independent acquisition data: identification of diagnostic biomarkers for paediatric tuberculosis

Thesis (MScMedSc)--Stellenbosch University, 2020.

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Main Author: Ehlers, Ashley
Other Authors: Tabb, David
Format: Thesis
Language:en_ZA
Published: Stellenbosch : Stellenbosch University 2020
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access_status_str Open Access
author Ehlers, Ashley
author2 Tabb, David
author_browse Ehlers, Ashley
Tabb, David
author_facet Tabb, David
Ehlers, Ashley
author_sort Ehlers, Ashley
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (MScMedSc)--Stellenbosch University, 2020.
format Thesis
id oai:scholar.sun.ac.za:10019.1/109276
institution Stellenbosch University (South Africa)
language en_ZA
last_indexed 2026-06-10T12:45:00.328Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2020
publishDateRange 2020
publishDateSort 2020
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/109276 Leveraging shotgun proteomics for optimised interpretation of data-independent acquisition data: identification of diagnostic biomarkers for paediatric tuberculosis Ehlers, Ashley Tabb, David Steen, Hanno Stellenbosch University. Faculty of Medicine and Health Sciences. Dept. of Biomedical Sciences: Molecular Biology and Human Genetics. Tuberculosis in children Tuberculosis -- Diagnosis Biochemical markers UCTD Thesis (MScMedSc)--Stellenbosch University, 2020. ENGLISH ABSTRACT: Althoughdiagnostic tests for paediatric tuberculosis (TB)are available,no specific test has been tailored to fit the diagnostic challenges children present as well as cater to limited resource settings. The high mortality rates recorded annually are associated with late diagnosis as well as insufficient household contact management (HCM). Further, urine has been identified as an attractive biofluid for urine protein biomarker discovery. Urine is non-invasive, easily attainablein large quantities and is associated with a low cost of collection. Improved data analysis approaches for protein and peptide identification and quantification has paved the way for the development of novel urine protein biomarkers for paediatric TB.Data-dependent acquisition (DDA) is a powerful approach in discovery of possible urine protein markers. By leveraging the shotgun proteome capabilities of protein and peptide identification using database search algorithms, an optimized data-independent acquisition (DIA) analysis method was developed. In this study, prior to data analysis, the quality of the DDA and DIA approach was evaluated by identifying batch effects and assessing the dissimilarity to allow abnormal runs to be identified and subsequently excluded. It is hypothesized that the quantity of specific host proteins in urine is different for children with TB compared to symptomatic control children who do not have TB. Using an optimised DIA data analysis method leveraging DDA data will allow a statistical identification of differentially abundant proteins in comparative proteomics. In this study,the MSstatsR-package for protein-level abundance testing was employed to generate comparisons between two groups, TB cases and controls,for a South African human-immunodeficiency virus (HIV) negative cohort.Three human proteins, leucine-rich alpha-2-glycoprotein (A2GL), aggrecan core protein (PGCA) and cartilage intermediate layer protein 2 (CILP2) were identified as significantly different. The findings of this study support the hypothesis that using an optimised DIA data analysis method leveraging DDA data will identify the differential proteins, potentiallyleading to validation for useas discovery phase urine protein markersin the clinical settings. AFRIKAANSE OPSOMMING: Alhoewel diagnostiese toetse vir pediatriese tuberkulose (TB) beskikbaar is, is geen spesifieke toets aangepas om te pas by die diagnostiese uitdagings wat kinders bied nie asook om te voorsien na beperkte hulpbroninstellings. Die hoë sterftesyfers wat jaarliks aangeteken word, hou verband met laat diagnose sowel as onvoldoende huishoudelike kontakbestuur (HCM). Verder is urine geïdentifiseer as 'n aantreklike biovloeistof vir die ontdekking van proteïen bio-merkers. Urine kolleksie is nie-indringend nie,dis maklik bereikbaar in groot hoeveelhede en hou verband met lae versamelingskoste. Verbeterde benaderings vir data-analise vir die identifisering en kwantifisering van proteïene en peptiede, het die weg gebaan vir die ontwikkeling van nuwe urienproteïen-biomerkers vir TB inkinders.Data-afhanklike verkryging (DDA) is 'n kragtige benadering om moontlike urienproteïenmerkers te ontdek. Deur gebruik te maak van shotgun-proteoomse vermoëns omproteïen-en peptiedidentifikasie met behulp van databasis-soekalgoritmeste maak, is 'n geoptimaliseerde data-onafhanklike verkrygingsontledingsmetode(DIA)ontwikkel. In hierdie studie, voordatdata-analiseuitgevoer was, is die kwaliteit van die DDA-en DIA-benadering geëvalueer deur bondel-effekte te identifiseer en die verskille te beoordeel sodat abnormale monsters (uitskieters)geïdentifiseer en daarna uitgesluit kan word. Daar word veronderstel dat die hoeveelheid spesifieke proteïene in urine verskil vir kinders met TB in vergelyking met simptomatiese kontrolekinders wat nie TB het nie. Deur gebruik te maak van 'n geoptimaliseerde DIA-data-ontledingsmetode, wat gebruik maak van DDA-data, kan statistiese identifikasie van proteïene wat in verskillende mate in vergelykende proteomika bestaan, identifiseerword.In hierdie studie is die MSstatsR-pakket vir proteïenvlak-oorvloedtoetse gebruik om vergelykings tussen twee groepe, TB-gevalle en kontroles, te genereer vir 'n Suid-Afrikaanse mens-immuungebrekvirus (MIV) negatiewe groep. Drie menslike proteïene, leucienryke alfa-2-glikoproteïen (A2GL), aggrecan-kernproteïen (PGCA) en kraakbeen-tussenlaagproteïen 2(CILP2) is geïdentifiseer as beduidend verskillend. Die bevindinge van hierdie studie ondersteun die hipotese dat die gebruik van 'n geoptimaliseerde DIA-data-ontledingsmetode wat gebruik maak van DDA-data, die differensiële proteïene sal identifiseer,wat moontlik kan lei tot validering vir gebruik as ontdekkingsfase-urienproteïenmerkers in die kliniese omgewing. Masters 2020-12-04T08:32:34Z 2021-01-31T19:42:26Z 2020-12-04T08:32:34Z 2021-01-31T19:42:26Z 2020-12 Thesis http://hdl.handle.net/10019.1/109276 en_ZA Stellenbosch University 81 pages application/pdf Stellenbosch : Stellenbosch University
spellingShingle Tuberculosis in children
Tuberculosis -- Diagnosis
Biochemical markers
UCTD
Ehlers, Ashley
Leveraging shotgun proteomics for optimised interpretation of data-independent acquisition data: identification of diagnostic biomarkers for paediatric tuberculosis
title Leveraging shotgun proteomics for optimised interpretation of data-independent acquisition data: identification of diagnostic biomarkers for paediatric tuberculosis
title_full Leveraging shotgun proteomics for optimised interpretation of data-independent acquisition data: identification of diagnostic biomarkers for paediatric tuberculosis
title_fullStr Leveraging shotgun proteomics for optimised interpretation of data-independent acquisition data: identification of diagnostic biomarkers for paediatric tuberculosis
title_full_unstemmed Leveraging shotgun proteomics for optimised interpretation of data-independent acquisition data: identification of diagnostic biomarkers for paediatric tuberculosis
title_short Leveraging shotgun proteomics for optimised interpretation of data-independent acquisition data: identification of diagnostic biomarkers for paediatric tuberculosis
title_sort leveraging shotgun proteomics for optimised interpretation of data independent acquisition data identification of diagnostic biomarkers for paediatric tuberculosis
topic Tuberculosis in children
Tuberculosis -- Diagnosis
Biochemical markers
UCTD
url http://hdl.handle.net/10019.1/109276
work_keys_str_mv AT ehlersashley leveragingshotgunproteomicsforoptimisedinterpretationofdataindependentacquisitiondataidentificationofdiagnosticbiomarkersforpaediatrictuberculosis