An Equine Protein Atlas Highlights Synovial Fluid Proteome Dynamics during Experimentally LPS-Induced Arthritis

J Proteome Res. 2024 Nov 1;23(11):4849-4863. doi: 10.1021/acs.jproteome.4c00125. Epub 2024 Oct 12.

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 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.

Keywords: DIA; LPS-induced arthritis; SWATH-MS; biomarkers; equine; synovial fluid; tissue-specific proteins.

MeSH terms

  • Animals
  • Arthritis, Experimental / metabolism
  • Biomarkers / analysis
  • Biomarkers / metabolism
  • Data Mining
  • Horses
  • Lipopolysaccharides*
  • Proteome* / analysis
  • Proteome* / metabolism
  • Proteomics* / methods
  • Synovial Fluid* / chemistry
  • Synovial Fluid* / metabolism

Substances

  • Proteome
  • Lipopolysaccharides
  • Biomarkers