4.7 Article

Optimization of Synovial Fluid Collection and Processing for NMR Metabolomics and LC-MS/MS Proteomics

期刊

JOURNAL OF PROTEOME RESEARCH
卷 19, 期 7, 页码 2585-2597

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.0c00035

关键词

synovial fluid; metabolomics; nuclear magnetic resonance; proteomics; mass spectrometry; Lys-C endopeptidase

资金

  1. Horse Trust Ph.D. studentship [G1015]
  2. Wellcome Trust Intermediate Clinical Fellowship [107471/Z/15/Z]
  3. Kennel Club Charitable Trust International Canine Health Award
  4. MRC Clinical Research Capabilities and Technologies Initiative [MR/M009114/1]
  5. MRC [MR/M009114/1, MR/P020941/1] Funding Source: UKRI

向作者/读者索取更多资源

Synovial fluid (SF) is of great interest for the investigation of orthopedic pathologies, as it is in close proximity to various tissues that are primarily altered during these disease processes and can be collected using minimally invasive protocols. Multi-omic approaches are commonplace, although little consideration is often given for multiple analysis techniques at sample collection. Nuclear magnetic resonance (NMR) metabolomics and liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics are two complementary techniques particularly suited to the study of SF. However, currently there are no agreed upon standard protocols that are published for SF collection and processing for use with NMR metabolomic analysis. Furthermore, the large protein concentration dynamic range present within SF can mask the detection of lower abundance proteins in proteomics. While combinational ligand libraries (ProteoMiner columns) have been developed to reduce this dynamic range, their reproducibility when used in conjunction with SF, or on-bead protein digestion protocols, has yet to be investigated. Here we employ optimized protocols for the collection, processing, and storage of SF for NMR metabolite analysis and LC-MS/MS proteome analysis, including a Lys-C endopeptidase digestion step prior to tryptic digestion, which increased the number of protein identifications and improved reproducibility for on-bead ProteoMiner digestion.

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