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   PARK7/DJ-1 promotes pyruvate dehydrogenase activity and maintains T(reg) homeostasis during ageing.; ; et al in Nature metabolism (2022), 4(5), 589-607 Pyruvate dehydrogenase (PDH) is the gatekeeper enzyme of the tricarboxylic acid (TCA) cycle. Here we show that the deglycase DJ-1 (encoded by PARK7, a key familial Parkinson's disease gene) is a pacemaker ... [more ▼] Pyruvate dehydrogenase (PDH) is the gatekeeper enzyme of the tricarboxylic acid (TCA) cycle. Here we show that the deglycase DJ-1 (encoded by PARK7, a key familial Parkinson's disease gene) is a pacemaker regulating PDH activity in CD4(+) regulatory T cells (T(reg) cells). DJ-1 binds to PDHE1-β (PDHB), inhibiting phosphorylation of PDHE1-α (PDHA), thus promoting PDH activity and oxidative phosphorylation (OXPHOS). Park7 (Dj-1) deletion impairs T(reg) survival starting in young mice and reduces T(reg) homeostatic proliferation and cellularity only in aged mice. This leads to increased severity in aged mice during the remission of experimental autoimmune encephalomyelitis (EAE). Dj-1 deletion also compromises differentiation of inducible T(reg) cells especially in aged mice, and the impairment occurs via regulation of PDHB. These findings provide unforeseen insight into the complicated regulatory machinery of the PDH complex. As T(reg) homeostasis is dysregulated in many complex diseases, the DJ-1-PDHB axis represents a potential target to maintain or re-establish T(reg) homeostasis. [less ▲] Detailed reference viewed: 62 (6 UL) Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases.Kishk, Ali  ; Pires Pacheco, Maria Irene ; Heurtaux, Tony et alin Cells (2022), 11(16), Brain disorders represent 32% of the global disease burden, with 169 million Europeans affected. Constraint-based metabolic modelling and other approaches have been applied to predict new treatments for ... [more ▼] Brain disorders represent 32% of the global disease burden, with 169 million Europeans affected. Constraint-based metabolic modelling and other approaches have been applied to predict new treatments for these and other diseases. Many recent studies focused on enhancing, among others, drug predictions by generating generic metabolic models of brain cells and on the contextualisation of the genome-scale metabolic models with expression data. Experimental flux rates were primarily used to constrain or validate the model inputs. Bi-cellular models were reconstructed to study the interaction between different cell types. This review highlights the evolution of genome-scale models for neurodegenerative diseases and glioma. We discuss the advantages and drawbacks of each approach and propose improvements, such as building bi-cellular models, tailoring the biomass formulations for glioma and refinement of the cerebrospinal fluid composition. [less ▲] Detailed reference viewed: 82 (9 UL)Stem cell-associated heterogeneity in Glioblastoma results from intrinsic tumor plasticity shaped by the microenvironment; ; et al in Nature communications (2019), 10(1), 1787 Detailed reference viewed: 177 (16 UL) |
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