Publications by Colleges and Departments (MSU - Bozeman)

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    Metabolomic profiles of cartilage and bone reflect tissue type, radiography-confirmed osteoarthritis, and spatial location within the joint
    (Elsevier BV, 2024-04) Welhaven, Hope D.; Viles, Ethan; Starke, Jenna; Wallace, Cameron; Bothner, Brian; June, Ronald K.; Hahn, Alyssa K.
    Osteoarthritis is the most common chronic joint disease, characterized by the abnormal remodeling of joint tissues including articular cartilage and subchondral bone. However, there are currently no therapeutic drug targets to slow the progression of disease because disease pathogenesis is largely unknown. Thus, the goals of this study were to identify metabolic differences between articular cartilage and subchondral bone, compare the metabolic shifts in osteoarthritic grade III and IV tissues, and spatially map metabolic shifts across regions of osteoarthritic hip joints. Articular cartilage and subchondral bone from 9 human femoral heads were obtained after total joint arthroplasty, homogenized and metabolites were extracted for liquid chromatography-mass spectrometry analysis. Metabolomic profiling revealed that distinct metabolic endotypes exist between osteoarthritic tissues, late-stage grades, and regions of the diseased joint. The pathways that contributed the most to these differences between tissues were associated with lipid and amino acid metabolism. Differences between grades were associated with nucleotide, lipid, and sugar metabolism. Specific metabolic pathways such as glycosaminoglycan degradation and amino acid metabolism, were spatially constrained to more superior regions of the femoral head. These results suggest that radiography-confirmed grades III and IV osteoarthritis are associated with distinct global metabolic and that metabolic shifts are not uniform across the joint. The results of this study enhance our understanding of osteoarthritis pathogenesis and may lead to potential drug targets to slow, halt, or reverse tissue damage in late stages of osteoarthritis.
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    A DeoR-Type Transcription Regulator Is Required for Sugar-Induced Expression of Type III Secretion-Encoding Genes in Pseudomonas syringae pv. tomato DC3000
    (Scientific Societies, 2020-03) Turner, Sydney E.; Pang, Yin-Yuin; O’Malley, Megan R.; Weisberg, Alexandra J.; Fraser, Valerie N.; Yan, Qing; Chang, Jeff H.; Anderson, Anderson
    The type III secretion system (T3SS) of plant-pathogenic Pseudomonas syringae is essential for virulence. Genes encoding the T3SS are not constitutively expressed and must be induced upon infection. Plant-derived metabolites, including sugars such as fructose and sucrose, are inducers of T3SS-encoding genes, yet the molecular mechanisms underlying perception of these host signals by P. syringae are unknown. Here, we report that sugar-induced expression of type III secretion A (setA), predicted to encode a DeoR-type transcription factor, is required for maximal sugar-induced expression of T3SS-associated genes in P. syringae DC3000. From a Tn5 transposon mutagenesis screen, we identified two independent mutants with insertions in setA. When both setA::Tn5 mutants were cultured in minimal medium containing fructose, genes encoding the T3SS master regulator HrpL and effector AvrRpm1 were expressed at lower levels relative to that of a wild-type strain. Decreased hrpL and avrRpm1 expression also occurred in a setA::Tn5 mutant in response to glucose, sucrose, galactose, and mannitol, demonstrating that setA is genetically required for T3SS induction by many different sugars. Expression of upstream regulators hrpR/S and rpoN was not altered in setA::Tn5, indicating that SetA positively regulates hrpL expression independently of increased transcription of these genes. In addition to decreased response to defined sugar signals, a setA::Tn5 mutant had decreased T3SS deployment during infection and was compromised in its ability to grow in planta and cause disease. These data suggest that SetA is necessary for P. syringae to effectively respond to T3SS-inducing sugar signals encountered during infection.
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