An Equine Protein Atlas Highlights Synovial Fluid Proteome Dynamics during Experimentally LPS-Induced Arthritis
Bundgaard, Louise LU ; Årman, Filip LU ; Åhrman, Emma LU ; Walters, Marie ; Auf dem Keller, Ulrich ; Malmström, Johan LU
and Jacobsen, Stine
(2024)
In Journal of Proteome Research
23(11).
p.4849-4863
- Abstract
In human proteomics, substantial efforts are ongoing to leverage large collections of mass spectrometry (MS) fragment ion spectra into extensive spectral libraries (SL) as a resource for data independent acquisition (DIA) analysis. Currently, such initiatives in equine research are still missing. Here we present a large-scale equine SL, comprising 6394 canonical proteins and 89,329 unique peptides, based on data dependent acquisition analysis of 75 tissue and body fluid samples from horses. The SL enabled large-scale DIA-MS based quantification of the same samples to generate a quantitative equine protein distribution atlas to infer dominant proteins in different organs and body fluids. Data mining revealed 163 proteins uniquely... (More)
In human proteomics, substantial efforts are ongoing to leverage large collections of mass spectrometry (MS) fragment ion spectra into extensive spectral libraries (SL) as a resource for data independent acquisition (DIA) analysis. Currently, such initiatives in equine research are still missing. Here we present a large-scale equine SL, comprising 6394 canonical proteins and 89,329 unique peptides, based on data dependent acquisition analysis of 75 tissue and body fluid samples from horses. The SL enabled large-scale DIA-MS based quantification of the same samples to generate a quantitative equine protein distribution atlas to infer dominant proteins in different organs and body fluids. Data mining revealed 163 proteins uniquely identified in a specific type of tissue or body fluid, serving as a starting point to determine tissue-specific or tissue-type-specific proteins. We showcase the SL by highlighting proteome dynamics in equine synovial fluid samples during experimental lipopolysaccharide-induced arthritis. A fuzzy c-means cluster analysis pinpointed SERPINB1, ATRN, NGAL, LTF, MMP1, and LBP as putative biomarkers for joint inflammation. This SL provides an extendable resource for future equine studies employing DIA-MS.
(Less)
- author
- Bundgaard, Louise
LU
; Årman, Filip
LU
; Åhrman, Emma
LU
; Walters, Marie
; Auf dem Keller, Ulrich
; Malmström, Johan
LU
and Jacobsen, Stine
- organization
- publishing date
- 2024-10-12
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Proteome Research
- volume
- 23
- issue
- 11
- pages
- 4849 - 4863
- publisher
- The American Chemical Society (ACS)
- external identifiers
-
- scopus:85206946319
- pmid:39395021
- ISSN
- 1535-3893
- DOI
- 10.1021/acs.jproteome.4c00125
- language
- English
- LU publication?
- yes
- id
- fd189f67-c018-403b-a424-6da5e36cc2b3
- date added to LUP
- 2024-10-17 06:59:53
- date last changed
- 2025-07-12 10:26:55
@article{fd189f67-c018-403b-a424-6da5e36cc2b3,
abstract = {{<p>In human proteomics, substantial efforts are ongoing to leverage large collections of mass spectrometry (MS) fragment ion spectra into extensive spectral libraries (SL) as a resource for data independent acquisition (DIA) analysis. Currently, such initiatives in equine research are still missing. Here we present a large-scale equine SL, comprising 6394 canonical proteins and 89,329 unique peptides, based on data dependent acquisition analysis of 75 tissue and body fluid samples from horses. The SL enabled large-scale DIA-MS based quantification of the same samples to generate a quantitative equine protein distribution atlas to infer dominant proteins in different organs and body fluids. Data mining revealed 163 proteins uniquely identified in a specific type of tissue or body fluid, serving as a starting point to determine tissue-specific or tissue-type-specific proteins. We showcase the SL by highlighting proteome dynamics in equine synovial fluid samples during experimental lipopolysaccharide-induced arthritis. A fuzzy c-means cluster analysis pinpointed SERPINB1, ATRN, NGAL, LTF, MMP1, and LBP as putative biomarkers for joint inflammation. This SL provides an extendable resource for future equine studies employing DIA-MS.</p>}},
author = {{Bundgaard, Louise and Årman, Filip and Åhrman, Emma and Walters, Marie and Auf dem Keller, Ulrich and Malmström, Johan and Jacobsen, Stine}},
issn = {{1535-3893}},
language = {{eng}},
month = {{10}},
number = {{11}},
pages = {{4849--4863}},
publisher = {{The American Chemical Society (ACS)}},
series = {{Journal of Proteome Research}},
title = {{An Equine Protein Atlas Highlights Synovial Fluid Proteome Dynamics during Experimentally LPS-Induced Arthritis}},
url = {{http://dx.doi.org/10.1021/acs.jproteome.4c00125}},
doi = {{10.1021/acs.jproteome.4c00125}},
volume = {{23}},
year = {{2024}},
}