Fig. 8: Proteomics and N-terminomics/TAILS analyses of synovial fluids human OA and non-OA patients.

a Workflow schematic of proteomics experiments. Human synovial fluids from healthy/non-OA patients (n = 3) were compared to OA patients (n = 3). Graphic created using BioRender. b The numbers of unique and shared peptides between TAILS and preTAILS analysis. For a complete list, see Supplementary Tables 7–11. c The numbers of statistically changing peptides using an interquartile boxplot analysis between in the preTAILS samples. For a complete list, see Supplementary Table 7. d Left, Distribution of N-terminal peptides in the TAILS enrichment. Middle, The numbers of statistically changing peptides using an interquartile boxplot analysis between in the TAILS samples. Right, Distribution of post-translational peptide modifications, as analyzed using TopFINDER⁹³. For a complete list of N-termini identified, see Supplementary Tables 9–11. e All identified PRG4 peptides. The ¹³⁰⁶R↓A¹³⁰⁷ N-termini was significantly elevated in the OA samples as compared to non-OA/healthy synovial fluid. f STRING-db⁵⁹ analysis of all N-termini elevated in the OA samples from Supplementary Table 11. An enrichment was detected for Activation of C3 and C5 (red), SHC-related events triggered by IGF1R (green), Scavenging by Class B Receptors (blue), and Folate metabolism (pale blue). Metascape⁴⁸ g pathway enrichment and h TRRUST analysis of the TAILS data and i Metascape⁴⁸ analysis of the preTAILS data of different pathways between non-OA/healthy and OA synovial fluids. Accumulative hypergeometric p-values and enrichment factors were calculated and used for filtering as performed as a two-sided analysis (for g, h and i). Remaining significant terms were then hierarchically clustered into a tree based on Kappa-statistical similarities among their gene’s memberships. Then, 0.3 kappa score was applied as the threshold to cast the tree into term clusters.