Despite osteoarthritis (OA) and rheumatoid arthritis (RA) being typically age-related, their underlying aetiologies are markedly different. We used 1H Nuclear Magnetic Resonance (NMR) spectroscopy to identify differences in metabolite profiles in low volumes of OA and RA synovial fluid (SF). SF was aspirated from knee joints of 10 OA and 14 RA patients. 100µL SF was analysed using a 700 MHz Avance IIIHD Bruker NMR spectrometer with a TCI cryoprobe. Spectra were analysed by Chenomx, Bruker TopSpin and AMIX software. Statistical analysis was undertaken using Metaboanalyst®. 50 metabolites were annotated, including amino acids, saccharides, nucleotides and soluble lipids. Discriminant analysis identified group separation between OA and RA cohorts, with 32 metabolites significantly different between OA and RA SF (False Discovery Rate (FDR)<0.05). Metabolites of glycolysis and the tricarboxylic acid cycle were lower in RA compared to OA; these results concur with higher levels of inflammation, synovial proliferation and hypoxia found in RA compared to OA. Elevated taurine in OA may indicate increased subchondral bone sclerosis. We demonstrate that quantifiable differences in metabolite abundance can be measured in low volumes of SF by 1H NMR spectroscopy, which may be clinically useful to aid diagnosis and improve understanding of disease pathogenesis.

Osteoarthritis (OA), osteochondrosis (OC) and synovial sepsis in horses cause loss of function and pain. Reliable biomarkers are required to achieve accurate and rapid diagnosis, with synovial fluid (SF) holding a unique source of biochemical information. Nuclear magnetic resonance (NMR) spectroscopy allows global metabolite analysis of a small volume of SF, with minimal sample pre-processing using a non-invasive and non-destructive method. Equine SF metabolic profiles from both non-septic joints (OA and OC) and septic joints were analysed using 1D ¹H NMR spectroscopy. Univariate and multivariate statistical analyses were used to identify differential metabolite abundance between groups. Metabolites were annotated via ¹H NMR using 1D NMR identification software Chenomx, with identities confirmed using 1D ¹H and 2D ¹H ¹³C NMR. Multivariate analysis identified separation between septic and non-septic groups. Acetate, alanine, citrate, creatine phosphate, creatinine, glucose, glutamate, glutamine, glycine, phenylalanine, pyruvate and valine were higher in the non-septic group whilst glycylproline was higher in sepsis. Multivariate separation was primarily driven by glucose; however PLS-DA plots with glucose excluded demonstrated the remaining metabolites were still able to discriminate the groups. This study demonstrates a panel of synovial metabolites can distinguish between septic and non-septic equine SF, with glucose the main discriminator.

Introduction: Synovial fluid (SF) is in close proximity to tissues which are primarily altered during articular disease and has significant potential to better understand the underlying disease pathogeneses of articular pathologies and biomarker discovery. Although development of mass spectrometry-based methods has allowed faster and higher sensitivity techniques, interrogation of the SF proteome has been hindered by its large protein concentration dynamic range, impeding quantification of lower abundant proteins. Areas covered: Recent advances have developed methodologies to reduce the large protein concentration dynamic range of SF and subsequently allow deeper exploration of the SF proteome. This review concentrates on methods to overcome biofluid complexity, mass spectrometry proteomics methodologies, extracellular vesicles proteomics and the application of advances within the field in clinical disease, including osteoarthritis, rheumatoid arthritis, spondyloarthritis and juvenile arthritis. A narrative review was conducted with articles searched using PubMed, 1991–2018. Expert opinion: The SF proteomics field faces various challenges, including the requirement for rigorous and standardised methods of sample collection/storage, the sensitivity and specificity of proteomic assays, techniques to combat the large protein concentration dynamic range and comprehensive data analysis to reduce falsely identified markers. Additionally, there are challenges in developing multi ‘omic’ integration techniques, with computational integration enhancing analysis.

Extracellular vesicles comprise an as yet inadequately investigated intercellular communication pathway in the field of early osteoarthritis. We hypothesised that the small non-coding RNA expression pattern in synovial fluid and plasma would change during progression of experimental osteoarthritis. In this study, we conducted small RNA sequencing to provide a comprehensive overview of the temporal expression profiles of small non-coding transcripts carried by extracellular vesicles derived from plasma and synovial fluid for the first time in a posttraumatic model of equine osteoarthritis. Additionally, we characterised synovial fluid and plasma-derived extracellular vesicles with respect to quantity, size, and surface markers. The different temporal expressions of seven microRNAs in plasma and synovial fluid-derived extracellular vesicles, eca-miR-451, eca-miR-25, eca-miR-215, eca-miR-92a, eca-miR-let-7c, eca-miR-486-5p, and eca-miR-23a, and four snoRNAs, U3, snord15, snord46, and snord58, represent potential biomarkers for early osteoarthritis. Bioinformatics analysis of the differentially expressed microRNAs in synovial fluid highlighted that in early osteoarthritis these related to the inhibition of cell cycle, cell cycle progression, DNA damage and cell proliferation as well as increased cell viability and differentiation of stem cells. Plasma and synovial fluid-derived extracellular vesicle small non-coding signatures have been established for the first time in a temporal model of osteoarthritis. These could serve as novel biomarkers for evaluation of osteoarthritis progression or act as potential therapeutic targets.

Synovial fluid (SF) is of great interest for the investigation of orthopaedic pathologies as it is in close proximity to various tissues which 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 standard protocols which 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. Whilst combinational ligand libraries (ProteoMiner^TM columns) have been developed to reduce this dynamic range, their reproducibility when used in conjunction with SF, or on-bead protein digestion protocols, have yet to be investigated. Here we employ optimised 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^TM digestion.

Inorganic polyphosphate (polyP) is an ancient, ubiquitous, and well-conserved polymer which is present in all the studied organisms. It is formed by individual subunits of orthophosphate which are linked by structurally similar bonds and isoenergetic to those found in ATP. While the metabolism and the physiological roles of polyP have already been described in some organisms, including bacteria and yeast, the exact role of this polymer in mammalian physiology still remains poorly understood. In these organisms, polyP shows a co-localization with mitochondria, and its role as a key regulator of the stress responses, including the maintenance of appropriate bioenergetics, has already been demonstrated by our group and others. Here, using Wild-type (Wt) and MitoPPX (cells enzymatically depleted of mitochondrial polyP) SH-SY5Y cells, we have conducted a comprehensive study of the status of cellular physiology, using proteomics and metabolomics approaches. Our results suggest a clear dysregulation of mitochondrial physiology, especially of bioenergetics, in MitoPPX cells when compared with Wt cells. Moreover, the effects induced by the enzymatic depletion of polyP are similar to those present in the mitochondrial dysfunction that is observed in neurodegenerative disorders and in neuronal aging. Based on our findings, the metabolism of mitochondrial polyP could be a valid and innovative pharmacological target in these conditions.