Miller, A. E. | Search bioRxiv

bioRxiv2024

Sirt5 regulates chondrocyte metabolism and osteoarthritis development through protein lysine malonylation

ObjectivesChondrocyte metabolic dysfunction plays an important role in osteoarthritis (OA) development during aging and obesity. Protein post-translational modifications (PTMs) have recently emerged as an important regulator of cellular metabolism. We aim to study one type of PTM, lysine malonylation (MaK) and its regulator Sirt5 in OA development. MethodsHuman and mouse cartilage tissues were used to measure SIRT5 and MaK levels. Both systemic and cartilage-specific conditional knockout mouse models were subject to high-fat diet (HFD) treatment to induce obesity and OA. Proteomics analysis was performed in Sirt5-/- and WT chondrocytes. SIRT5 mutation was identified in the Utah Population Database (UPDB). ResultsWe found that SIRT5 decreases while MAK increases in the cartilage during aging. A combination of Sirt5 deficiency and obesity exacerbates joint degeneration in a sex dependent manner in mice. We further delineate the malonylome in chondrocytes, pinpointing MaKs predominant impact on various metabolic pathways such as carbon metabolism and glycolysis. Lastly, we identified a rare coding mutation in SIRT5 that dominantly segregates in a family with OA. The mutation results in substitution of an evolutionally invariant phenylalanine (Phe-F) to leucine (Leu-L) (F101L) in the catalytic domain. The mutant protein results in higher MaK level and decreased expression of cartilage ECM genes and upregulation of inflammation associated genes. ConclusionsWe found that Sirt5 mediated MaK is an important regulator of chondrocyte cellular metabolism and dysregulation of Sirt5-MaK could be an important mechanism underlying aging and obesity associated OA development.

cell biology↗

bioRxiv2022

Characterizing the extracellular matrix transcriptome of cervical, endometrial, anduterine cancers

Increasingly, the matrisome, a set of proteins that form the core of the extracellular matrix (ECM) or are closely associated with it, has been demonstrated to play a key role in tumor progression. However, in the context of gynecological cancers, the matrisome has not been well characterized. A holistic, yet targeted, exploration of the tumor microenvironment is critical for better understanding the progression of gynecological cancers, identifying key biomarkers for cancer progression, establishing the role of gene expression in patient survival, and for assisting in the development of new targeted therapies. In this work, we explored the matrisome gene expression profiles of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), uterine corpus endometrial carcinoma (UCEC), and uterine carcinosarcoma (UCS) using publicly available RNA-seq data from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) portal. We hypothesized that the matrisomal expression patterns of CESC, UCEC, and UCS would be highly distinct with respect to genes which are differentially expressed and hold inferential significance with respect to tumor progression, patient survival, or both. Through a combination of statistical and machine learning analysis techniques, we identified sets of genes and gene networks which characterized each of the gynecological cancer cohorts. Our findings demonstrate that the matrisome is critical for characterizing gynecological cancers and transcriptomic mechanisms of cancer progression and outcome. Furthermore, while the goal of pan-cancer transcriptional analyses is often to highlight the shared attributes of these cancer types, we demonstrate that they are highly distinct diseases which require separate analysis, modeling, and treatment approaches. In future studies, matrisome genes and gene ontology terms that were identified as critical for predicting patient survival or cancer stage can be evaluated as potential drug targets and incorporated into in vitro models of disease.

cancer biology↗