Optimisation of synovial fluid collection and processing for NMR metabolomics and LC-MS/MS proteomics

Research output: Contribution to journalArticlepeer-review


  • James Anderson
  • Marie Phelan
  • Luiz Rubino-Martinez
  • mathew Fitzgerald
  • Peter Clegg
  • Mandy Peffers

Colleges, School and Institutes

External organisations

  • University of Liverpool


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.


Original languageEnglish
Pages (from-to)2585–2597
Number of pages13
JournalJournal of Proteome Research
Issue number7
Early online date31 Mar 2020
Publication statusPublished - 2 Jul 2020


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