Epigenetic mechanisms and metabolic reprogramming in fibrogenesis: dual targeting of G9a and DNMT1 for the inhibition of liver fibrosis

OBJECTIVE: Hepatic stellate cells (HSC) transdifferentiation into myofibroblasts is central to fibrogenesis. Epigenetic mechanisms, including histone and DNA methylation, play a key role in this process. Concerted action between histone and DNA-mehyltransferases like G9a and DNMT1 is a common theme in gene expression regulation. We aimed to study the efficacy of CM272, a first-in-class dual and reversible G9a/DNMT1 inhibitor, in halting fibrogenesis. DESIGN: G9a and DNMT1 were analysed in cirrhotic human livers, mouse models of liver fibrosis and cultured mouse HSC. G9a and DNMT1 expression was knocked down or inhibited with CM272 in human HSC (hHSC), and transcriptomic responses to transforming growth factor-β1 (TGFβ1) were examined. Glycolytic metabolism and mitochondrial function were analysed with Seahorse-XF technology. Gene expression regulation was analysed by chromatin immunoprecipitation and methylation-specific PCR. Antifibrogenic activity and safety of CM272 were studied in mouse chronic CCl4 administration and bile duct ligation (BDL), and in human precision-cut liver slices (PCLSs) in a new bioreactor technology. RESULTS: G9a and DNMT1 were detected in stromal cells in areas of active fibrosis in human and mouse livers. G9a and DNMT1 expression was induced during mouse HSC activation, and TGFβ1 triggered their chromatin recruitment in hHSC. G9a/DNMT1 knockdown and CM272 inhibited TGFβ1 fibrogenic responses in hHSC. TGFβ1-mediated profibrogenic metabolic reprogramming was abrogated by CM272, which restored gluconeogenic gene expression and mitochondrial function through on-target epigenetic effects. CM272 inhibited fibrogenesis in mice and PCLSs without toxicity. CONCLUSIONS: Dual G9a/DNMT1 inhibition by compounds like CM272 may be a novel therapeutic strategy for treating liver fibrosis

Fine Tuning of the Lactate and Diacetyl Production through Promoter Engineering in Lactococcus lactis

Lactococcus lactis is a well-studied bacterium widely used in dairy fermentation and capable of producing metabolites with organoleptic and nutritional characteristics. For fine tuning of the distribution of glycolytic flux at the pyruvate branch from lactate to diacetyl and balancing the production of the two metabolites under aerobic conditions, a constitutive promoter library was constructed by randomizing the promoter sequence of the H2O-forming NADH oxidase gene in L. lactis. The library consisted of 30 promoters covering a wide range of activities from 7,000 to 380,000 relative fluorescence units using a green fluorescent protein as reporter. Eleven typical promoters of the library were selected for the constitutive expression of the H2O-forming NADH oxidase gene in L. lactis, and the NADH oxidase activity increased from 9.43 to 58.17-fold of the wild-type strain in small steps of activity change under aerobic conditions. Meanwhile, the lactate yield decreased from 21.15±0.08 mM to 9.94±0.07 mM, and the corresponding diacetyl production increased from 1.07±0.03 mM to 4.16±0.06 mM with the intracellular NADH/NAD+ ratios varying from 0.711±0.005 to 0.383±0.003. The results indicated that the reduced pyruvate to lactate flux was rerouted to the diacetyl with an almost linear flux variation via altered NADH/NAD+ ratios. Therefore, we provided a novel strategy to precisely control the pyruvate distribution for fine tuning of the lactate and diacetyl production through promoter engineering in L. lactis. Interestingly, the increased H2O-forming NADH oxidase activity led to 76.95% lower H2O2 concentration in the recombinant strain than that of the wild-type strain after 24 h of aerated cultivation. The viable cells were significantly elevated by four orders of magnitude within 28 days of storage at 4°C, suggesting that the increased enzyme activity could eliminate H2O2 accumulation and prolong cell survival

Incremental Tree-Based Missing Data Imputation with Lexicographic Ordering

Missing data, Classification and regression tree, FAST splitting algorithm, Lexicographic order, Nonparametric imputation, Data editing,