Conclusions
Our circadian proteomics study reveals that articular cartilage is a much more dynamic tissue than previously thought, with chondrocytes driving circadian rhythms not only in gene transcription but also in protein abundance. Our results clearly call for the consideration of circadian timing mechanisms not only in cartilage biology, but also in the pathogenesis, treatment strategies and biomarker detection in osteoarthritis.
Methods
We investigated daily changes of protein abundance in mouse femoral head articular cartilage by performing a 48-h time-series LC-MS/MS analysis.
Objective
Cartilage in joints such as the hip and knee experiences repeated phases of heavy loading and low load recovery during the 24-h day/night cycle. Our previous work has shown 24 h rhythmic changes in gene expression at transcript level between night and day in wild type mouse cartilage which is lost in a circadian clock knock-out mouse model. However, it remains unknown to what extent circadian rhythms also regulate protein level gene expression in this matrix rich tissue.
Results
Out of the 1,177 proteins we identified across all time points, 145 proteins showed rhythmic changes in their abundance within the femoral head cartilage. Among these were molecules that have been implicated in key cartilage functions, including CTGF, MATN1, PAI-1 and PLOD1 & 2. Pathway analysis revealed that protein synthesis, cytoskeleton and glucose metabolism exhibited time-of-day dependent functions. Analysis of published cartilage proteomics datasets revealed that a significant portion of rhythmic proteins were dysregulated in osteoarthritis and/or ageing. Conclusions: Our circadian proteomics study reveals that articular cartilage is a much more dynamic tissue than previously thought, with chondrocytes driving circadian rhythms not only in gene transcription but also in protein abundance. Our results clearly call for the consideration of circadian timing mechanisms not only in cartilage biology, but also in the pathogenesis, treatment strategies and biomarker detection in osteoarthritis.