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Omics data was acquired, and the development and research of metabolic simulation and analysis methods using them were also actively carried out. However, it was a laborious task to acquire such data each time the medium composition, culture conditions, and target organism changed. Therefore, in this study, we aimed to extract and estimate important variables and necessary numbers for predicting metabolic flux distribution as the state of cell metabolism by flux sampling using a genome-scale metabolic model (GSM) and its analysis. Acetic acid production from glucose in Escherichia coli with GSM iJO1366 was used as a case study. Flux sampling obtained by OptGP using 1000 pattern constraints on substrate, product, and growth fluxes produced a wider sample than the default case. The analysis also suggested that the fluxes of iron ions, O2, CO2, and NH4+, were important for predicting the metabolic flux distribution. Additionally, the comparison with the literature value of 13C-MFA using CO2 emission flux as an example of an important flux suggested that the important flux obtained by this method was valid for the prediction of flux distribution. In this way, the method of this research was useful for extracting variables that were important for predicting flux distribution, and as a result, the possibility of contributing to the reduction of measurement variables in experiments was suggested.

The number of unannotated protein sequences is explosively increasing due to genome sequence technology. A more comprehensive understanding of protein functions for protein annotation requires the discovery of new features that cannot be captured from conventional methods. Deep learning can extract important features from input data and predict protein functions based on the features. Here, protein feature vectors generated by 3 deep learning models are analyzed using Integrated Gradients to explore important features of amino acid sites. As a case study, prediction and feature extraction models for UbiD enzymes were built using these models. The important amino acid residues extracted from the models were different from secondary structures, conserved regions and active sites of known UbiD information. Interestingly, the different amino acid residues within UbiD sequences were regarded as important factors depending on the type of models and sequences. The Transformer models focused on more specific regions than the other models. These results suggest that each deep learning model understands protein features with different aspects from existing knowledge and has the potential to discover new laws of protein functions. This study will help to extract new protein features for the other protein annotations.

The use of natural products and derivatives for the prevention and control of non-communicable chronic diseases, such as type-2 diabetes (T2D), obesity, and hepatic steatosis is a way to achieve homeostasis through different metabolic pathways. Thus, male C57BL/6 mice were divided into the following groups: high-fat diet (HFD) vehicle, HFD + Supplemented, HFD + Supplemented_S, and isolated compounds. The vehicle and experimental formulations were administered orally by gavage once a day over the four weeks of the diet (28 consecutive days). We evaluated the energy homeostasis, cytokines, and mitochondrial gene expression in these groups of mice. After four weeks of supplementation, only the new nutraceutical group (HFD + Supplemented) experienced reduced fasting glycemia, insulin, HOMA index, HOMA-β, dyslipidemia, ectopic fat deposition, and hepatic fibrosis levels. Additionally, the PPARγ coactivator 1 α (Pgc-1α), interleukin-6 (Il-6), and interleukin-10 (Il-10) gene expression were augmented, while hepatic steatosis decreased and liver parenchyma was recovered. The glutathione-S-transferase activity status was found to be modulated by the supplement. We discovered that the new nutraceutical was able to improve insulin resistance and hepatic steatosis mainly by regulating IL-6, IL-10, and Pgc-1α gene expression.

Obesity is linked with altered microbial short-chain fatty acids (SCFAs), which are a signature of gut dysbiosis and inflammation. In the present study, we investigated whether tributyrin, a prodrug of the SCFA butyrate, could improve metabolic and inflammatory profiles in diet-induced obese mice. Mice fed a high-fat diet for eight weeks were treated with tributyrin or placebo for another six weeks. We show that obese mice treated with tributyrin had lower body weight gain and an improved insulin responsiveness and glucose metabolism, partly via reduced hepatic triglycerides content. Additionally, tributyrin induced an anti-inflammatory state in the adipose tissue by reduction of Il-1β and Tnf-a and increased Il-10, Tregs cells and M2-macrophages. Moreover, improvement in glucose metabolism and reduction of fat inflammatory states associated with tributyrin treatment were dependent on GPR109A activation. Our results indicate that exogenous targeting of SCFA butyrate attenuates metabolic and inflammatory dysfunction, highlighting a potentially novel approach to tackle obesity.

In the present study we investigated the participation of hepatic peroxisome proliferator-activated receptor-gamma coactivator 1 alpha (PGC-1α) in the metabolic programming of newborn rats exposed in utero to dexamethasone (DEX). On the 21st day of life, fasted offspring born to DEX-treated mothers displayed increased conversion of pyruvate into glucose with simultaneous upregulation of PEPCK (phosphoenolpyruvate carboxykinase) and G6Pase (glucose-6-phosphatase). Increased oxidative phosphorylation, higher ATP/ADP ratio and mitochondrial biogenesis and lower pyruvate levels were also found in the progeny of DEX-treated mothers. On the other hand, the 21-day-old progeny of DEX-treated mothers had increased hepatic triglycerides (TAG) and lower CPT-1 activity when subjected to short-term fasting. At the mechanistic level, rats exposed in utero to DEX exhibited increased hepatic PGC-1α protein content with lower miR-29a-c expression. Increased PGC-1α content was concurrent with increased association to HNF-4α and NRF1 and reduced PPARα expression. The data presented herein reveal that changes in the transcription machinery in neonatal liver of rats born to DEX-treated mothers leads to an inflexible metabolic response to fasting. Such programming is hallmarked by increased oxidative phosphorylation of pyruvate with impaired FFA oxidation and hepatic TAG accumulation.

Introduction: Exercise is an important therapeutic strategy for preventing and treating myocardial infarction (MI)-induced cardiac remodeling and heart failure. However, the myocardial effects of resistance exercise on infarcted hearts are not completely established. In this study, we investigated the effects of resistance exercise on structural, functional, and molecular cardiac alterations in infarcted rats. Methods: Three months after MI induction or simulated surgery, Wistar rats were assigned into three groups: Sham (n = 14); MI (n = 9); and exercised MI (MI-Ex, n = 13). Exercised rats performed, 3 times a week for 12 weeks, four climbs on a ladder with progressive loads. Cardiac structure and left ventricle (LV) function were analyzed by echocardiogram. Myocyte diameters were evaluated in hematoxylin- and eosin-stained histological sections as the smallest distance between borders drawn across the nucleus. Myocardial energy metabolism, lipid hydroperoxide, malondialdehyde, protein carbonylation, and antioxidant enzyme activities were evaluated by spectrophotometry. Gene expressions of NADPH oxidase subunits were evaluated by RT-PCR. Statistical analyses were performed using ANOVA and Tukey or Kruskal–Wallis and Dunn’s test. Results: Mortality did not differ between the MI-Ex and MI groups. MI had dilated left atrium and LV, with LV systolic dysfunction. Exercise increased the maximum load-carrying capacity, with no changes in cardiac structure or LV function. Myocyte diameters were lower in MI than in Sham and MI-Ex. Lactate dehydrogenase and creatine kinase activity were lower in MI than in Sham. Citrate synthase and catalase activity were lower in MI and MI-Ex than in Sham. Lipid hydroperoxide concentration was lower in MI-Ex than in MI. Nox2 and p22phox gene expressions were higher in MI-Ex than in Sham. Gene expression of Nox4 was higher in MI and MI-Ex than in Sham, and p47phox was lower in MI than in Sham. Conclusion: Late resistance exercise was safe in infarcted rats. Resistance exercise improved maximum load-carrying capacity, reduced myocardial oxidative stress, and preserved myocardial metabolism, with no changes in cardiac structure or left ventricle function in infarcted rats.