Metabolic Model Research Articles

The opportunistic human fungal pathogen Candida albicans possesses a remarkable metabolic plasticity, which is essential for both fungal commensalism and virulence and influences its physiology and behavior in multiple ways. The investigation of such processes particularly benefits from the emergence of multi-omics and in silico approaches. In this study, we combined a multi-omics approach with genome-scale metabolic modeling to investigate the fungal metabolic adaptation to amino acid utilization and starvation. Most strikingly, we found an altered activity of the shikimate pathway upon amino acid starvation, accompanied by a simultaneous induction of two metabolic gene clusters required for the metabolism of hydroxybenzenes. Further analyses revealed so far unknown potential functional and regulatory links between both metabolic pathways, which provide starting points for future research leading to a better understanding of the fungal adaptation to dynamic host conditions.

BackgroundMetabolic surgery is a well-established intervention for managing severe obesity and type 2 diabetes, offering significant long-term health benefits. In Europe, procedures such as sleeve gastrectomy and Roux-en-Y gastric bypass have been shown to improve glycemic control, reduce obesity-related comorbidities, and enhance quality of life. Given the high prevalence of obesity in Romania, evaluating the cost-effectiveness of these surgical interventions is crucial for potential public funding inclusion.MethodsWe adapted a Central European type 2 diabetes—metabolic surgery cost-utility model using Romanian epidemiological and healthcare cost data to assess the cost-effectiveness of weight-loss surgery. The model incorporated three Body Mass Index strata (30–34.9, 35–39.9, ≥40 kg/m2) and tracked outcomes over a lifetime horizon. Cost and quality-adjusted life years were evaluated for sleeve gastrectomy and Roux-en-Y gastric bypass using two costing methodologies: Diagnosis-Related Group-based reimbursement and micro-costing analysis. Scenario analyses, including threshold analysis, were conducted to validate model robustness.ResultsObesity surgery was found to be a dominant strategy, yielding both cost savings and improved health outcomes across all Body Mass Index categories. The intervention led to increased life expectancy, reduced diabetes-related complications, and a significant reduction in healthcare costs. Even under conservative cost assumptions, the surgery remained cost-effective, with an Incremental Cost-Effectiveness Ratio (ICER) well within European funding thresholds.ConclusionThe results support the inclusion of metabolic surgery in Romania’s public healthcare system. Expanding access could reduce long-term healthcare expenditures while improving the quality of life for individuals with obesity and type 2 diabetes.

Cancer cells frequently reprogramme their metabolism to support growth and survival, making metabolic pathways attractive targets for therapy. In this study, we investigated the metabolic effects of three kinase inhibitors and their synergistic combinations in the gastric cancer cell line AGS using genome-scale metabolic models and transcriptomic profiling. We applied the tasks inferred from the differential expression (TIDE) algorithm to infer pathway activity changes in the different conditions. We also explored a variant of TIDE that uses task-essential genes to infer metabolic task changes, providing a complementary perspective to the original algorithm. Our results revealed widespread down-regulation of biosynthetic pathways, particularly in amino acid and nucleotide metabolism. Combinatorial treatments induced condition-specific metabolic alterations, including strong synergistic effects in the PI3Ki–MEKi condition affecting ornithine and polyamine biosynthesis. These metabolic shifts provide insight into drug synergy mechanisms and highlight potential therapeutic vulnerabilities. To support reproducibility, we developed an open-source Python package, MTEApy, implementing both TIDE frameworks.

Abstract Understanding plant temperature responses at a molecular level can speed up the development of climate-resilient crops. However, the threats due to anthropogenic warming necessitate imminent solutions to ensure food security. Modeling plant thermal responses at a molecular level offers a feasible strategy to identify gene targets that can mitigate the negative effects of projected temperature increases. Implementation of this strategy in practice requires the development and usage of temperature-aware models that incorporate a systems-level description of the existing knowledge on plant metabolism. Here, we detail the assumptions and building blocks of the recently assembled ecAraCore, an enzyme-constrained temperature-aware model of central metabolism for the model plant Arabidopsis thaliana. The goal of this study is to provide a primer for building a temperature-aware model of plant metabolism and to offer step-by-step instructions for using the ecAraCore model to simulate metabolic traits, including: relative growth rate, reaction fluxes, and enzyme abundances for specified environmental inputs. In addition, we provide another case study of how the ecAraCore model can be used to simulate temperature-sensitive knockouts. The primer sets the basis for the development of more involved metabolic engineering strategies aimed at the mitigation of the negative effects of temperature increases—the hallmark of future climate scenarios.

Metabolic syndrome, characterized by metabolic dysfunction-associated steatotic liver disease (MASLD) and type 2 diabetes mellitus (T2DM), poses a significant threat to patients’ health worldwide; however, efficient treatment is currently unavailable. Here, we show that oral administration of sodium nitrate (NaNO3) greatly attenuates the development and advancement of MASLD-like and T2DM-like phenotypes in mice induced by choline-deficient high-fat, western, or methionine/choline-deficient diet. NaNO3 attenuates metabolic turbulence by rebalancing CD206+/CD11C+ polarization (anti-inflammatory/pro-inflammatory) and the function of bone marrow-derived macrophages (MoMFs). Using metabolic disorder animal models and bone marrow-reconstituted mice with mutated gene function in Slc17a5, which encodes sialin, we demonstrate that NaNO3 protects against metabolic disorders through the actions of sialin in MoMFs. NaNO3 can directly regulate MoMFs polarization and function in vitro and in mice, in which nitric oxide production from oral and enteral symbiotic bacteria is essentially abolished. At the molecular level, sialin, via the inhibition of the key transcription factor Rel, inhibits cathepsin L (CtsL) expression and thereby activates the Nrf2 pathway to modulate macrophage homeostasis and ameliorate metabolic abnormalities. Interestingly, the sialin-CtsL-Nrf2 pathway is downregulated in human macrophages from metabolic dysfunction-associated steatohepatitis (MASH) patients. Overall, we demonstrate the prophylactic and therapeutic effects of NaNO3 on metabolic syndrome and reveal a new macrophage rebalancing strategy involving NaNO3 through a novel sialin pathway. Our research indicates that NaNO3 may be a pharmaceutical agent for managing and alleviating metabolic turbulence in humans.

Constructing metabolic pathway of lignin monomers and their derivatives based on metabolic recombination models and yield models.

Alginate-driven co-metabolic degradation mechanism of sulfamethoxazole by marine consortia.

Resolving tissue and cellular functions of parasitic nematodes.

The allostatic triage model of psychopathology (ATP Model): How reallocation of brain energetic resources under stress elicits psychiatric symptoms.

Evaluation of CYP3A98 and CYP2B11 Expression and Induction in Duodenal Organoids as an In Vitro Model for Intestinal Drug Metabolism in Dogs

Ultra-endurance athletes and the metabolic ceiling.

Multiparametric CMR identifies macrophage NOS2-mediated benefits of preventive SGLT2 inhibition in a mouse model of metabolic heart disease.

Integrated analysis of mitochondrial ETC inhibition reveals genotype-specific heterogeneity of drug response in glioblastoma.

Methylene-tetrahydrofolate reductase (MTHFR) is an important enzyme for acetogenic carbon fixation, but the redox mechanism driving this reaction is not clearly understood. Previous enzymology work and energetic accounting on species such as Clostridium autoethanogenum has led to confounding results when placed in the context of in vivo experiments. In this work, we create multiple C. autoethanogenum strains harboring alternative MTHFR enzyme complexes as well as genome-scale metabolic models to better understand how these organisms conserve energy on gas substrates. The inclusion of a Type-III MTHFR unexpectedly allows for higher growth than expected and suggests the possibility of an additional redox balancing cycle employed during autotrophic growth.

Genome-scale metabolic modelling in antimicrobial pharmacology: Present and future.

Synthetic biology approaches for restoring gut microbial balance and engineering disease-specific microbiome therapeutics.

Intelligent biomanufacturing of water-soluble vitamins.

Elucidating metabolic mechanisms underlying the influence of specific growth rate on alkaline protease synthesis in Bacillus licheniformis through combined omics and computational modeling analysis.

Development and Validation of a Novel Plasma Metabolomic Signature for the Detection of Renal Cell Carcinoma.

In- silico guided tailoring of whole cells exploring the Genome-scale metabolic model for production of bio-hydrogen using lignocellulose derived sugars: Prioritizing higher growth rate and productivity