Degradomics defines proteolysis information flow from human knee osteoarthritis cartilage to matched synovial fluid and the contributions of secreted proteases ADAMTS5, MMP13 and CMA1 to articular cartilage breakdown

Abstract

Objectives

Proteolytic cartilage extracellular matrix breakdown is a major mechanism of articular cartilage loss in osteoarthritis (OA) pathogenesis. We sought to determine the overlap of proteolytic peptides in matched knee OA cartilage and synovial fluid on a proteome-wide scale to increase the prospective biomarker repertoire and to attribute proteolytic cleavages to specific secreted proteases.

Design

Matched human knee OA cartilage and synovial fluid (n = 5) were analyzed by N-terminomics using Terminal Amine Isotopic Labeling of Substrates (TAILS), comprising labeling and enrichment of protein N-termini, high-resolution mass spectrometry and positional peptide mapping. Donor non-OA articular cartilage was digested with CMA1, MMP13 or ADAMTS5, and TAILS was used to identify cleavage sites, which were matched against cartilage and synovial fluid degradomes.

Results

Of over 20,000 cleaved peptides in the combined OA cartilage and synovial fluid degradomes, 677 peptides, originating from 153 proteins, were present in all cartilage and synovial fluid samples. CMA1, MMP13 and ADAMTS5 digestion of cartilage identified numerous cleavage sites for each protease and distinct cleavage site preferences. Peptides resulting from the activities of these proteases were detected in OA cartilage and synovial fluid.

Conclusions

Proteolytic fragments from both cartilage and circulating proteins are detectable by synovial fluid degradomics. CMA1, MMP13 and ADAMTS5 activity profiles in cartilage are distinct from each other and the previously determined HtrA1 profile. This work expands the proteolytic biomarker space for OA investigation, suggests that multiple, diverse proteases contribute to cartilage destruction, and demonstrates that their specific contributions can each be defined by multiple biomarkers.