dc.contributor.author |
Govender, Ireshyn S
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|
dc.contributor.author |
Mokoena, Rethabile
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|
dc.contributor.author |
Stoychev, Stoyan
|
|
dc.contributor.author |
Naicker, Previn
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|
dc.date.accessioned |
2024-01-12T06:36:02Z |
|
dc.date.available |
2024-01-12T06:36:02Z |
|
dc.date.issued |
2023-09 |
|
dc.identifier.citation |
Govender, I.S., Mokoena, R., Stoychev, S. & Naicker, P. 2023. Urine-HILIC: Automated sample preparation for bottom-up urinary proteome profiling in clinical proteomics. <i>Proteomes, 11(4).</i> http://hdl.handle.net/10204/13521 |
en_ZA |
dc.identifier.issn |
2227-7382 |
|
dc.identifier.uri |
https://doi.org/10.3390/proteomes11040029
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|
dc.identifier.uri |
http://hdl.handle.net/10204/13521
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|
dc.description.abstract |
Urine provides a diverse source of information related to a patient’s health status and is ideal for clinical proteomics due to its ease of collection. To date, most methods for the preparation of urine samples lack the throughput required to analyze large clinical cohorts. To this end, we developed a novel workflow, urine-HILIC (uHLC), based on an on-bead protein capture, clean-up, and digestion without the need for bottleneck processing steps such as protein precipitation or centrifugation. The workflow was applied to an acute kidney injury (AKI) pilot study. Urine from clinical samples and a pooled sample was subjected to automated sample preparation in a KingFisher™ Flex magnetic handling station using the novel approach based on MagReSyn® HILIC microspheres. For benchmarking, the pooled sample was also prepared using a published protocol based on an on-membrane (OM) protein capture and digestion workflow. Peptides were analyzed by LCMS in data-independent acquisition (DIA) mode using a Dionex Ultimate 3000 UPLC coupled to a Sciex 5600 mass spectrometer. The data were searched in Spectronaut™ 17. Both workflows showed similar peptide and protein identifications in the pooled sample. The uHLC workflow was easier to set up and complete, having less hands-on time than the OM method, with fewer manual processing steps. Lower peptide and protein coefficient of variation was observed in the uHLC technical replicates. Following statistical analysis, candidate protein markers were filtered, at =8.35-fold change in abundance, =2 unique peptides and =1% false discovery rate, and revealed 121 significant, differentially abundant proteins, some of which have known associations with kidney injury. The pilot data derived using this novel workflow provide information on the urinary proteome of patients with AKI. Further exploration in a larger cohort using this novel high-throughput method is warranted. |
en_US |
dc.format |
Fulltext |
en_US |
dc.language.iso |
en |
en_US |
dc.relation.uri |
https://www.mdpi.com/2227-7382/11/4/29 |
en_US |
dc.source |
Proteomes, 11(4) |
en_US |
dc.subject |
Automated sample preparation |
en_US |
dc.subject |
Clinical proteomics |
en_US |
dc.subject |
SWATH-MS |
en_US |
dc.subject |
Urinary proteomics |
en_US |
dc.subject |
HILIC |
en_US |
dc.title |
Urine-HILIC: Automated sample preparation for bottom-up urinary proteome profiling in clinical proteomics |
en_US |
dc.type |
Article |
en_US |
dc.description.pages |
13 |
en_US |
dc.description.note |
Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
en_US |
dc.description.cluster |
Next Generation Health |
en_US |
dc.description.impactarea |
Human Molecular Diagnostics |
en_US |
dc.identifier.apacitation |
Govender, I. S., Mokoena, R., Stoychev, S., & Naicker, P. (2023). Urine-HILIC: Automated sample preparation for bottom-up urinary proteome profiling in clinical proteomics. <i>Proteomes, 11(4)</i>, http://hdl.handle.net/10204/13521 |
en_ZA |
dc.identifier.chicagocitation |
Govender, Ireshyn S, Rethabile Mokoena, Stoyan Stoychev, and Previn Naicker "Urine-HILIC: Automated sample preparation for bottom-up urinary proteome profiling in clinical proteomics." <i>Proteomes, 11(4)</i> (2023) http://hdl.handle.net/10204/13521 |
en_ZA |
dc.identifier.vancouvercitation |
Govender IS, Mokoena R, Stoychev S, Naicker P. Urine-HILIC: Automated sample preparation for bottom-up urinary proteome profiling in clinical proteomics. Proteomes, 11(4). 2023; http://hdl.handle.net/10204/13521. |
en_ZA |
dc.identifier.ris |
TY - Article
AU - Govender, Ireshyn S
AU - Mokoena, Rethabile
AU - Stoychev, Stoyan
AU - Naicker, Previn
AB - Urine provides a diverse source of information related to a patient’s health status and is ideal for clinical proteomics due to its ease of collection. To date, most methods for the preparation of urine samples lack the throughput required to analyze large clinical cohorts. To this end, we developed a novel workflow, urine-HILIC (uHLC), based on an on-bead protein capture, clean-up, and digestion without the need for bottleneck processing steps such as protein precipitation or centrifugation. The workflow was applied to an acute kidney injury (AKI) pilot study. Urine from clinical samples and a pooled sample was subjected to automated sample preparation in a KingFisher™ Flex magnetic handling station using the novel approach based on MagReSyn® HILIC microspheres. For benchmarking, the pooled sample was also prepared using a published protocol based on an on-membrane (OM) protein capture and digestion workflow. Peptides were analyzed by LCMS in data-independent acquisition (DIA) mode using a Dionex Ultimate 3000 UPLC coupled to a Sciex 5600 mass spectrometer. The data were searched in Spectronaut™ 17. Both workflows showed similar peptide and protein identifications in the pooled sample. The uHLC workflow was easier to set up and complete, having less hands-on time than the OM method, with fewer manual processing steps. Lower peptide and protein coefficient of variation was observed in the uHLC technical replicates. Following statistical analysis, candidate protein markers were filtered, at =8.35-fold change in abundance, =2 unique peptides and =1% false discovery rate, and revealed 121 significant, differentially abundant proteins, some of which have known associations with kidney injury. The pilot data derived using this novel workflow provide information on the urinary proteome of patients with AKI. Further exploration in a larger cohort using this novel high-throughput method is warranted.
DA - 2023-09
DB - ResearchSpace
DP - CSIR
J1 - Proteomes, 11(4)
KW - Automated sample preparation
KW - Clinical proteomics
KW - SWATH-MS
KW - Urinary proteomics
KW - HILIC
LK - https://researchspace.csir.co.za
PY - 2023
SM - 2227-7382
T1 - Urine-HILIC: Automated sample preparation for bottom-up urinary proteome profiling in clinical proteomics
TI - Urine-HILIC: Automated sample preparation for bottom-up urinary proteome profiling in clinical proteomics
UR - http://hdl.handle.net/10204/13521
ER -
|
en_ZA |
dc.identifier.worklist |
27200 |
en_US |