Mitochondrial dysfunction triggers a catabolic response in chondrocytes via ROS-mediated activation of the JNK/AP1 pathway.

Mitochondrial function is impaired in osteoarthritis (OA) but its impact on cartilage catabolism is not fully understood. Here, we investigated the molecular mechanism of mitochondrial dysfunction-induced activation of the catabolic response in chondrocytes. Using cartilage slices from normal and OA cartilage, we showed that mitochondrial membrane potential was lower in OA cartilage, and that this was associated with increased production of mitochondrial superoxide and catabolic genes [interleukin 6 (IL-6), COX-2 (also known as PTGS2), MMP-3, -9, -13 and ADAMTS5]. Pharmacological induction of mitochondrial dysfunction in chondrocytes and cartilage explants using carbonyl cyanide 3-chlorophenylhydrazone increased mitochondrial superoxide production and the expression of IL-6, COX-2, MMP-3, -9, -13 and ADAMTS5, and cartilage matrix degradation. Mitochondrial dysfunction-induced expression of catabolic genes was dependent on the JNK (herein referring to the JNK family)/activator protein 1 (AP1) pathway but not the NFκB pathway. Scavenging of mitochondrial superoxide with MitoTEMPO, or pharmacological inhibition of JNK or cFos and cJun, blocked the mitochondrial dysfunction-induced expression of the catabolic genes in chondrocytes. We demonstrate here that mitochondrial dysfunction contributes to OA pathogenesis via JNK/AP1-mediated expression of catabolic genes. Our data shows that AP1 could be used as a therapeutic target for OA management.This article has an associated First Person interview with the first author of the paper.

OBIF: an omics-based interaction framework to reveal molecular drivers of synergy.

Bioactive molecule library screening may empirically identify effective combination therapies, but molecular mechanisms underlying favorable drug-drug interactions often remain unclear, precluding further rational design. In the absence of an accepted systems theory to interrogate synergistic responses, we introduce Omics-Based Interaction Framework (OBIF) to reveal molecular drivers of synergy through integration of statistical and biological interactions in synergistic biological responses. OBIF performs full factorial analysis of feature expression data from single versus dual exposures to identify molecular clusters that reveal synergy-mediating pathways, functions and regulators. As a practical demonstration, OBIF analyzed transcriptomic and proteomic data of a dyad of immunostimulatory molecules that induces synergistic protection against influenza A and revealed unanticipated NF-κB/AP-1 cooperation that is required for antiviral protection. To demonstrate generalizability, OBIF analyzed data from a diverse array of Omics platforms and experimental conditions, successfully identifying the molecular clusters driving their synergistic responses. Hence, unlike existing synergy quantification and prediction methods, OBIF is a phenotype-driven systems model that supports multiplatform interrogation of synergy mechanisms.