Label-free proteomic analysis of the hydrophobic membrane protein complement in articular chondrocytes: a technique for identification of membrane biomarkers

The clusterin connectome: Emerging players in chondrocyte biology and putative exploratory biomarkers of osteoarthritis

Introduction

Clusterin is amoonlighting protein that hasmany functions. It is amultifunctional Q6 holdase chaperone glycoprotein that is present intracellularly and extracellularly in almost all bodily fluids. Clusterin is involved in lipid transport, cell differentiation, regulation of apoptosis, and clearance of cellular debris, and plays a protective role in ensuring cellular survival. However, the possible involvement of clusterin in arthritic disease remains unclear. Given the significant potential of clusterin as a biomarker of osteoarthritis (OA), a more detailed analysis of its complex network in an inflammatory environment, specifically in the context of OA, is required. Based on the molecular network of clusterin, this study aimed to identify interacting partners that could be developed into biomarker panels for OA.

Methods

The STRING database and Cytoscape were used to map and visualize the clusterin connectome. The Qiagen Ingenuity Pathway Analysis (IPA) software was used to analyze and study clusterinassociated signaling networks in OA. We also analyzed transcription factors known to modulate clusterin expression, which may be altered in OA.

Results

The top hits in the clusterin network were intracellular chaperones, aggregate-forming proteins, apoptosis regulators and complement proteins. Using a text-mining approach in Cytoscape, we identified additional interacting partners, including serum proteins, apolipoproteins, and heat shock proteins.

Discussion

Based on known interactions with proteins, we predicted potential novel components of the clusterin connectome in OA, including selenoprotein R, semaphorins, and meprins, which may be important for designing new prognostic or diagnostic biomarker panels.

Effects of microplastics alone and with adsorbed benzo(a)pyrene on the gills proteome of Scrobicularia plana

Microplastics (MPs) are globally present in the marine environment, but the biological effects on marine organisms at the molecular and cellular levels remain scarce. Due to their lipophilic nature, MPs can adsorb other contaminants present in the marine environment, which may increase their detrimental effects once ingested by organisms. This study investigates the effects of low-density polyethylene (PE) MPs with and without adsorbed benzo[a]pyrene (BaP) in the gills proteome of the peppery furrow shell clam, Scrobicularia plana. Clams were exposed to PE MPs (11-13 μm; 1 mg L^-1) for 14 days. BaP was analyzed in whole clams' soft tissues, and a proteomic approach was applied in the gills using SWATH/DIA analysis. Proteomic responses suggest that virgin MPs cause disturbance by altering cytoskeleton and cell structure, energy metabolism, conformational changes, oxidative stress, fatty acids, DNA binding and, neurotransmission highlighting the potential risk of this type of MPs for the clam health. Conversely, when clam gills were exposed to MPs adsorbed with BaP a higher differentiation of protein expression was observed that besides changes in cytoskeleton and cell structure, oxidative stress, energy metabolism and DNA binding also induce changes in glucose metabolism, RNA binding and apoptosis. These results indicate that the presence of both stressors (MPs and BaP) have a higher toxicological risk to the health of S. plana.

Identification of Candidate Synovial Fluid Biomarkers for the Prediction of Patient Outcome After Microfracture or Osteotomy

BACKGROUND

Biomarkers are needed to predict clinical outcomes for microfracture and osteotomy surgeries to ensure patients can be better stratified to receive the most appropriate treatment.

PURPOSE

To identify novel biomarker candidates and to investigate the potential of a panel of protein biomarkers for the prediction of clinical outcome after treatment with microfracture or osteotomy.

STUDY DESIGN

Descriptive laboratory study.

METHODS

To identify novel candidate biomarker proteins, we used label-free quantitation after liquid chromatography-tandem mass spectrometry of dynamic range-compressed synovial fluids (SFs) from individuals who responded excellently or poorly (based on change in Lysholm score) to microfracture (n = 6) or osteotomy (n = 7). Biomarkers that were identified in this proteomic analysis or that relate to osteoarthritis (OA) severity or have predictive value in another early OA therapy (autologous cell implantation) were measured in the SF of 19 and 13 patients before microfracture or osteotomy, respectively, using commercial immunoassays, and were normalized to urea. These were aggrecanase-1 (ADAMTS-4), cartilage oligomeric matrix protein (COMP), hyaluronan (HA), lymphatic vessel endothelial hyaluronan receptor 1 (LYVE-1), matrix metalloproteinase 1 and 3, soluble CD14, S100 calcium binding protein A13, and 14-3-3 protein theta (YWHAQ). Levels of COMP and HA were also measured in the plasma of these patients. To find predictors of postoperative function, multivariable regression analyses were performed.

RESULTS

Proteomic analyses highlighted YWHAQ and LYVE-1 as being differentially abundant between the clinical responders/improvers and nonresponders after microfracture. A linear regression model after backward variable selection could relate preoperative concentrations of SF proteins (HA, YWHAQ, LYVE-1), activity of ADAMTS-4, and patient demographic characteristics (smoker status and sex) with Lysholm score 12 months after microfracture. Further, a generalized linear model with elastic net penalization indicated that lower preoperative activity of ADAMTS-4 in SF, being a nonsmoker, and being younger at the time of operation were indicative of a higher postoperative Lysholm score (improved joint function) after osteotomy surgery.

CONCLUSION

We have identified biomarkers and generated regression models with the potential to predict clinical outcome in patients treated with microfracture or osteotomy of the knee.

CLINICAL RELEVANCE

Candidate protein biomarkers identified in this study have the potential to help determine which patients will be best suited to treatment with microfracture or osteotomy.

Identification of potential diagnostic gene biomarkers in patients with osteoarthritis

The current study was aimed to identify diagnostic gene signature for osteoarthritis (OA). The differentially expressed genes (DEGs) in synovial membrane samples and blood samples were respectively identified from the GEO dataset. The intersection DEGs between synovial membrane and blood were further screened out, followed by the functional annotation of these common DEGs. The optimal intersection gene biomarkers for OA diagnostics were determined. The GSE51588 dataset of articular cartilage was used for expression validation and further diagnostic analysis validation of identified gene biomarkers for OA diagnostics. There were 379 intersection DEGs were obtained between the synovial membrane and blood samples of OA. 22 DEGs had a diagnostic value for OA. After further screening, a total of 9 DEGs including TLR7, RTP4, CRIP1, ZNF688, TOP1, EIF1AY, RAB2A, ZNF281 and UIMC1 were identified for OA diagnostic. The identified DEGs could be considered as potential diagnostic biomarkers for OA.

Alterations in the chondrocyte surfaceome in response to pro-inflammatory cytokines

Background

Chondrocytes are exposed to an inflammatory micro-environment in the extracellular matrix (ECM) of articular cartilage in joint diseases such as osteoarthritis (OA) and rheumatoid arthritis (RA). In OA, degenerative changes and low-grade inflammation within the joint transform the behaviour and metabolism of chondrocytes, disturb the balance between ECM synthesis and degradation, and alter the osmolality and ionic composition of the micro-environment. We hypothesize that chondrocytes adjust their physiology to the inflammatory microenvironment by modulating the expression of cell surface proteins, collectively referred to as the ‘surfaceome’. Therefore, the aim of this study was to characterize the surfaceome of primary equine chondrocytes isolated from healthy joints following exposure to the pro-inflammatory cytokines interleukin-1-beta (IL-1β) and tumour necrosis factor-alpha (TNF-α). We employed combined methodology that we recently developed for investigating the surfaceome in stem cells. Membrane proteins were isolated using an aminooxy-biotinylation technique and analysed by mass spectrometry using high throughput shotgun proteomics. Selected proteins were validated by western blotting.

Results

Amongst the 431 unique cell surface proteins identified, a high percentage of low-abundance proteins, such as ion channels, receptors and transporter molecules were detected. Data are available via ProteomeXchange with identifier PXD014773. A high number of proteins exhibited different expression patterns following chondrocyte stimulation with pro-inflammatory cytokines. Low density lipoprotein related protein 1 (LPR-1), thrombospondin-1 (TSP-1), voltage dependent anion channel (VDAC) 1–2 and annexin A1 were considered to be of special interest and were analysed further by western blotting.

Conclusions

Our results provide, for the first time, a repository for proteomic data on differentially expressed low-abundance membrane proteins on the surface of chondrocytes in response to pro-inflammatory stimuli.

Molecular phenotyping of the surfaceome of migratory chondroprogenitors and mesenchymal stem cells using biotinylation, glycocapture and quantitative LC-MS/MS proteomic analysis

The complement of cell surface proteins, collectively referred to as the surfaceome, is a useful indicator of normal differentiation processes, and the development of pathologies such as osteoarthritis (OA). We employed biochemical and proteomic tools to explore the surfaceome and to define biomarkers in chondrogenic progenitor cells (CPC) derived from human OA knee articular cartilage. These cells have great therapeutic potential, but their unexplored biology limits their clinical application. We performed biotinylation combined with glycocapture and high throughput shotgun proteomics to define the surface proteome of human bone marrow mesenchymal stem cells (MSCs) and human CPCs. We prepared cell surface protein-enriched fractions from MSCs and CPCs, and then a proteomic approach was used to compare and evaluate protein changes between undifferentiated MSCs and CPCs. 1256 proteins were identified in the study, of which 791 (63%) were plasma membrane, cell surface or extracellular matrix proteins. Proteins constituting the surfaceome were annotated and categorized. Our results provide, for the first time, a repository of quantitative proteomic data on the surfaceome of two closely related cell types relevant to cartilage biology and OA. These results may provide novel insights into the transformation of the surfaceome during chondrogenic differentiation and phenotypic changes during OA development.

Osteoarthritis Year in Review 2016: biomarkers (biochemical markers)

PURPOSE

The aim of this "Year in Review" article is to summarize and discuss the implications of biochemical marker related articles published between the Osteoarthritis Research Society International (OARSI) 2015 Congress in Seattle and the OARSI 2016 Congress in Amsterdam.

METHODS

The PubMed/MEDLINE bibliographic database was searched using the combined keywords: 'biomarker' and 'osteoarthritis'. The PubMed/MEDLINE literature search was conducted using the Advanced Search Builder function (http://www.ncbi.nlm.nih.gov/pubmed/advanced).

RESULTS

Over two hundred new biomarker-related papers were published during the literature search period. Some papers identified new biomarkers whereas others explored the biological properties and clinical utility of existing markers. There were specific references to several adipocytokines including leptin and adiponectin. ADAM Metallopeptidase with Thrombospondin Type 1 motif 4 (ADAMTS-4) and aggrecan ARGS neo-epitope fragment (ARGS) in synovial fluid (SF) and plasma chemokine (CeC motif) ligand 3 (CCL3) were reported as potential new knee biomarkers. New and refined proteomic technologies and novel assays including a fluoro-microbead guiding chip (FMGC) for measuring C-telopeptide of type II collagen (CTX-II) in serum and urine and a novel magnetic nanoparticle-based technology (termed magnetic capture) for collecting and concentrating CTX-II, were described this past year.

CONCLUSION

There has been steady progress in osteoarthritis (OA) biomarker research in 2016. Several novel biomarkers were identified and new technologies have been developed for measuring existing biomarkers. However, there has been no "quantum leap" this past year and identification of novel early OA biomarkers remains challenging. During the past year, OARSI published a set of recommendations for the use of soluble biomarkers in clinical trials, which is a major step forward in the clinical use of OA biomarkers and bodes well for future OA biomarker development.

Biomarkers of (osteo)arthritis

Arthritic diseases are a major cause of disability and morbidity, and cause an enormous burden for health and social care systems globally. Osteoarthritis (OA) is the most common form of arthritis. The key risk factors for the development of OA are age, obesity, joint trauma or instability. Metabolic and endocrine diseases can also contribute to the pathogenesis of OA. There is accumulating evidence to suggest that OA is a whole-organ disease that is influenced by systemic mediators, inflammaging, innate immunity and the low-grade inflammation induced by metabolic syndrome. Although all joint tissues are implicated in disease progression in OA, articular cartilage has received the most attention in the context of aging, injury and disease. There is increasing emphasis on the early detection of OA as it has the capacity to target and treat the disease more effectively. Indeed it has been suggested that this is the era of "personalized prevention" for OA. However, the development of strategies for the prevention of OA require new and sensitive biomarker tools that can detect the disease in its molecular and pre-radiographic stage, before structural and functional alterations in cartilage integrity have occurred. There is also evidence to support a role for biomarkers in OA drug discovery, specifically the development of disease modifying osteoarthritis drugs. This Special Issue of Biomarkers is dedicated to recent progress in the field of OA biomarkers. The papers in this Special Issue review the current state-of-the-art and discuss the utility of OA biomarkers as diagnostic and prognostic tools.