Aims. Staphylococcus aureus is a major cause of septic arthritis, and in vitro studies suggest α haemolysin (Hla) is responsible for chondrocyte death. We used an in vivo murine joint model to compare inoculation with wild type S. aureus 8325-4 with a Hla-deficient strain DU1090 on chondrocyte viability, tissue histology, and joint biomechanics. The aim was to compare the actions of S. aureus Hla alone with those of the animal’s immune response to infection. Methods. Adult male C57Bl/6 mice (n = 75) were randomized into three groups to receive 1.0 to 1.4 × 10. 7. colony-forming units (CFUs)/ml of 8325-4, DU1090, or saline into the right stifle joint. Chondrocyte death was assessed by confocal microscopy. Histological changes to inoculated joints were graded for inflammatory responses along with gait, weight changes, and limb swelling. Results. Chondrocyte death was greater with 8325-4 (96.2% (SD 5.5%); p < 0.001) than DU1090 (28.9% (SD 16.0%); p = 0.009) and both were higher than controls (3.8% (SD 1.2%)). Histology revealed cartilage/bone damage with 8325-4 or DU1090 compared to controls (p = 0.010). Both infected groups lost weight (p = 0.006 for both) and experienced limb swelling (p = 0.043 and p = 0.018, respectively). Joints inoculated with bacteria showed significant alterations in gait cycle with a decreased stance phase, increased swing phase, and a corresponding decrease in swing speed. Conclusion. Murine joints inoculated with Hla-producing 8325-4 experienced significantly more chondrocyte death than those with DU1090, which lack the toxin. This was despite similar immune responses, indicating that Hla was the major cause of chondrocyte death. Hla-deficient DU1090 also elevated chondrocyte death compared to controls, suggesting a smaller additional deleterious role of the immune system on cartilage. Cite this article: Bone Joint Res 2022;11(9):669–678

Aims

The lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA).