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Objective: Exercise is known to induce beneficial effects in synovial joints. However, the mechanisms underlying these are unclear. Synovial joints experience repeated mechanical loading during exercise. These mechanical stimuli are transduced into biological responses through cellular mechanotransduction. Mechanotransduction in synovial joints is typically studied in tissues. However, synovial fluid directly contacts all components of the joint, and thus may produce a whole-joint picture of the mechanotransduction response to loading. The objective of this study was to determine if metabolic phenotypes are present in the synovial fluid after acute exercise as a first step to understanding the beneficial effects of exercise on the joint., Material and Methods: Mice underwent a single night of voluntary wheel running or standard housing and synovial fluid was harvested for global metabolomic profiling by LC-MS. Hierarchical unsupervised clustering, partial least squares discriminant, and pathway analysis provided insight into exercise-induced mechanotransduction., Results: Acute exercise produced a distinct metabolic phenotype in synovial fluid. Mechanosensitive metabolites included coenzyme A derivatives, prostaglandin derivatives, phospholipid species, tryptophan, methionine, vitamin D3, fatty acids, and thiocholesterol. Enrichment analysis identified several pathways previously linked to exercise including amino acid metabolism, inflammatory pathways, citrulline-nitric oxide cycle, catecholamine biosynthesis, ubiquinol biosynthesis, and phospholipid metabolism., Conclusion: To our knowledge, this is the first study to investigate metabolomic profiles of synovial fluid during in vivo mechanotransduction. These profiles indicate that exercise induced stress-response processes including both pro- and anti-inflammatory pathways. Further research will expand these results and define the relationship between the synovial fluid and the serum., (© 2021 Published by Elsevier Ltd on behalf of Osteoarthritis Research Society International (OARSI).)

Objective: To explore how systemic factors that modify knee osteoarthritis risk are connected to 'whole-joint' structural changes by evaluating the effects of high-fat diet and wheel running exercise on synovial fluid (SF) metabolomics., Methods: Male mice were fed a defined control or high-fat (60% kcal fat) diet from 6 to 52 weeks of age, and half the animals were housed with running wheels from 26 to 52 weeks of age (n = 9-13 per group). Joint tissue structure and osteoarthritis pathology were evaluated by histology and micro-computed tomography. Systemic metabolic and inflammatory changes were evaluated by body composition, glucose tolerance testing, and serum biomarkers. SF metabolites were analyzed by high performance-liquid chromatography mass spectrometry. We built correlation-based network models to evaluate the connectivity between systemic and local metabolic biomarkers and osteoarthritis structural pathology within each experimental group., Results: High-fat diet caused moderate osteoarthritis, including cartilage pathology, synovitis and increased subchondral bone density. In contrast, voluntary exercise had a negligible effect on these joint structure components. 1,412 SF metabolite features were detected, with high-fat sedentary mice being the most distinct. Diet and activity uniquely altered SF metabolites attributed to amino acids, lipids, and steroids. Notably, high-fat diet increased network connections to systemic biomarkers such as interleukin-1β and glucose intolerance. In contrast, exercise increased local joint-level network connections, especially among subchondral bone features and SF metabolites., Conclusion: Network mapping showed that obesity strengthened SF metabolite links to blood glucose and inflammation, whereas exercise strengthened SF metabolite links to subchondral bone structure., (Published by Elsevier Ltd.)

Arsenite (As III ) oxidation is a microbially-catalyzed transformation that directly impacts arsenic toxicity, bioaccumulation, and bioavailability in environmental systems. The genes for As III oxidation ( aio ) encode a periplasmic As III sensor AioX, transmembrane histidine kinase AioS, and cognate regulatory partner AioR, which control expression of the As III oxidase AioBA. The aio genes are under ultimate control of the phosphate stress response via histidine kinase PhoR. To better understand the cell-wide impacts exerted by these key histidine kinases, we employed 1 H nuclear magnetic resonance ( 1 H NMR) and liquid chromatography-coupled mass spectrometry (LC-MS) metabolomics to characterize the metabolic profiles of Δ phoR and Δ aioS mutants of Agrobacterium tumefaciens 5A during As III oxidation. The data reveals a smaller group of metabolites impacted by the Δ aioS mutation, including hypoxanthine and various maltose derivatives, while a larger impact is observed for the Δ phoR mutation, influencing betaine, glutamate, and different sugars. The metabolomics data were integrated with previously published transcriptomics analyses to detail pathways perturbed during As III oxidation and those modulated by PhoR and/or AioS. The results highlight considerable disruptions in central carbon metabolism in the Δ phoR mutant. These data provide a detailed map of the metabolic impacts of As III , PhoR, and/or AioS, and inform current paradigms concerning arsenic-microbe interactions and nutrient cycling in contaminated environments.

In environments where arsenic and microbes coexist, microbes are the principal drivers of arsenic speciation, which directly affects bioavailability, toxicity and bioaccumulation. Speciation reactions influence arsenic behaviour in environmental systems, directly affecting human and agricultural exposures. Arsenite oxidation decreases arsenic toxicity and mobility in the environment, and therefore understanding its regulation and overall influence on cellular metabolism is of significant interest. The arsenite oxidase (AioBA) is regulated by a three-component signal transduction system AioXSR, which is in turn regulated by the phosphate stress response, with PhoR acting as the master regulator. Using RNA-sequencing, we characterized the global effects of arsenite on gene expression in Agrobacterium tumefaciens 5A. To further elucidate regulatory controls, mutant strains for histidine kinases PhoR and AioS were employed, and illustrate that in addition to arsenic metabolism, a host of other functional responses are regulated in parallel. Impacted functions include arsenic and phosphate metabolism, carbohydrate metabolism, solute transport systems and iron metabolism, in addition to others. These findings contribute significantly to the current understanding of the metabolic impact and genetic circuitry involved during arsenite exposure in bacteria. This informs how arsenic contamination will impact microbial activities involving several biogeochemical cycles in nature., (© 2019 Society for Applied Microbiology and John Wiley & Sons Ltd.)

Objective: Osteoarthritis (OA) is a multifactorial disease with etiological heterogeneity. The objective of this study was to classify OA subgroups by generating metabolomic phenotypes from human synovial fluid., Design: Post mortem synovial fluids (n = 75) were analyzed by high performance-liquid chromatography mass spectrometry (LC-MS) to measure changes in the global metabolome. Comparisons of healthy (grade 0), early OA (grades I-II), and late OA (grades III-IV) donor populations were considered to reveal phenotypes throughout disease progression., Results: Global metabolomic profiles in synovial fluid were distinct between healthy, early OA, and late OA donors. Pathways differentially activated among these groups included structural deterioration, glycerophospholipid metabolism, inflammation, central energy metabolism, oxidative stress, and vitamin metabolism. Within disease states (early and late OA), subgroups of donors revealed distinct phenotypes. Synovial fluid metabolomic phenotypes exhibited increased inflammation (early and late OA), oxidative stress (late OA), or structural deterioration (early and late OA) in the synovial fluid., Conclusion: These results revealed distinct metabolic phenotypes in human synovial fluid, provide insight into pathogenesis, represent novel biomarkers, and can move toward developing personalized interventions for subgroups of OA patients., (Copyright © 2019 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.)

Objectives: The objective of this study was to analyse the metabolomic profiles of rheumatoid arthritis synovial fluid to test the use of global metabolomics by liquid chromatography-mass spectrometry for clinical analysis of synovial fluid., Methods: Metabolites were extracted from rheumatoid arthritis (n=3) and healthy (n=5) synovial fluid samples using 50:50 water: acetonitrile. Metabolite extracts were analysed in positive mode by normal phase liquid chromatography-mass spectrometry for global metabolomics. Statistical analyses included hierarchical clustering analysis, principal component analysis, Student's t-test, and volcano plot analysis. Metabolites were matched with known metabolite identities using METLIN and enriched for relevant pathways using IMPaLA., Results: 1018 metabolites were detected by LC-MS analysis in synovial fluid from rheumatoid arthritis and healthy patients, with 162 metabolites identified as significantly different between diseased and control. Pathways upregulated with disease included ibuprofen metabolism, glucocorticoid and mineralocorticoid metabolism, alpha-linolenic acid metabolism, and steroid hormone biosynthesis. Pathways downregulated with disease included purine and pyrimidine metabolism, biological oxidations, arginine and proline metabolism, the citrulline-nitric oxide cycle, and glutathione metabolism. Receiver operating characteristic analysis identified 30 metabolites as putative rheumatoid arthritis biomarkers including various phospholipids, diol and its derivatives, arsonoacetate, oleananoic acid acetate, docosahexaenoic acid methyl ester, and linolenic acid and eicosatrienoic acid derivatives., Conclusions: This study supports the use of global metabolomic profiling by liquid chromatography-mass spectrometry for synovial fluid analysis to provide insight into the aetiology of disease.

Osteoarthritis affects over 250 million individuals worldwide. Currently, there are no options for early diagnosis of osteoarthritis, demonstrating the need for biomarker discovery. To find biomarkers of osteoarthritis in human synovial fluid, we used high performance liquid-chromatography mass spectrometry for global metabolomic profiling. Metabolites were extracted from human osteoarthritic (n = 5), rheumatoid arthritic (n = 3), and healthy (n = 5) synovial fluid, and a total of 1233 metabolites were detected. Principal components analysis clearly distinguished the metabolomic profiles of diseased from healthy synovial fluid. Synovial fluid from rheumatoid arthritis patients contained expected metabolites consistent with the inflammatory nature of the disease. Similarly, unsupervised clustering analysis found that each disease state was associated with distinct metabolomic profiles and clusters of co-regulated metabolites. For osteoarthritis, co-regulated metabolites that were upregulated compared to healthy synovial fluid mapped to known disease processes including chondroitin sulfate degradation, arginine and proline metabolism, and nitric oxide metabolism. We utilized receiver operating characteristic analysis to determine the diagnostic value of each metabolite and identified 35 metabolites as potential biomarkers of osteoarthritis, with an area under the receiver operating characteristic curve >0.9. These metabolites included phosphatidylcholine, lysophosphatidylcholine, ceramides, myristate derivatives, and carnitine derivatives. This pilot study provides strong justification for a larger cohort-based study of human osteoarthritic synovial fluid using global metabolomics. The significance of these data is the demonstration that metabolomic profiling of synovial fluid can identify relevant biomarkers of joint disease., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted 'omics' analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea., Methods: We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized using interaction maps generated using STRING., Results: Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis-N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans., Conclusions: This multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis-N. equitans association., General Significance: Our study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies., (Copyright © 2017 Elsevier B.V. All rights reserved.)