ArticlePLoS computational biology2022
INTEGRATE: Model-based multi-omics data integration to characterize multi-level metabolic regulation.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
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- FGFR3 oncogenic activation drives oxidative metabolic reprogramming in bladder cancer: a systems metabolomics approach.Communications biology · 2026Article
- The crosstalk between epigenetics and metabolism in the malignant cell.Discover oncology · 2026Review
- Integrated transcriptomic and metabolomic analyses uncover novel genetic targets for enhanced l-tryptophan production inSynthetic and systems biotechnology · 2026Article
- COBRAxy: constraint-based metabolic modeling in Galaxy.Bioinformatics (Oxford, England) · 2026Article
- Flux sampling and context-specific genome-scale metabolic models for biotechnological applications.Trends in biotechnology · 2026Review
- Gas Chromatography-Mass Spectrometry (GC-MS) in the Plant Metabolomics Toolbox: GC-MS in Multi-Platform Metabolomics and Integrated Multi-Omics Research.International journal of molecular sciences · 2026Review
- Spatial FBA reveals heterogeneous Warburg niches in renal tumors and lactate consumption in colorectal cancer.NPJ systems biology and applications · 2026Article
- Transcriptome-informed metabolic modeling reveals astrocyte-specific vulnerabilities in mild cognitive impairment and Alzheimer's disease progression.Frontiers in bioinformatics · 2026Article
- Productive chaos and precision engineering: decoupling discovery from manufacturing to revolutionize plant-inspired therapeutics.Frontiers in plant science · 2026Article
- Metabolomics and Precision Medicine in Resistant Hypertension: Pathophysiological Insights, Biomarker Discovery, and Translational Strategies.International journal of hypertension · 2026Review
- The kynurenine pathway in depression and schizophrenia: convergent signals, divergent states, and clinical signatures.EXCLI journal · 2026Review
- Mechanistically informed machine learning links non-canonical TCA cycle activity to Warburg metabolism and hallmarks of malignancy.PLoS computational biology · 2025Article
- Systems biology and microbiome innovations for personalized diabetic retinopathy management.NPJ systems biology and applications · 2025Review
- Genome-scale metabolic model-guided systematic framework for designing customized live biotherapeutic products.NPJ systems biology and applications · 2025Review
- Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- MiNEApy: enhancing enrichment network analysis in metabolic networks.Bioinformatics (Oxford, England) · 2025Article
- UnifiedGreatMod: a new holistic modelling paradigm for studying biological systems on a complete and harmonious scale.Bioinformatics (Oxford, England) · 2025Article
- The Inflammatory Mechanism of Parkinson's Disease: Gut Microbiota Metabolites Affect the Development of the Disease Through the Gut-Brain Axis.Brain sciences · 2025Review
- Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025Review
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10 authors.
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Abstract
Metabolism is directly and indirectly fine-tuned by a complex web of interacting regulatory mechanisms that fall into two major classes. On the one hand, the expression level of the catalyzing enzyme sets the maximal theoretical flux level (i.e., the net rate of the reaction) for each enzyme-controlled reaction. On the other hand, metabolic regulation controls the metabolic flux through the interactions of metabolites (substrates, cofactors, allosteric modulators) with the responsible enzyme. High-throughput data, such as metabolomics and transcriptomics data, if analyzed separately, do not accurately characterize the hierarchical regulation of metabolism outlined above. They must be integrated to disassemble the interdependence between different regulatory layers controlling metabolism. To this aim, we propose INTEGRATE, a computational pipeline that integrates metabolomics and transcriptomics data, using constraint-based stoichiometric metabolic models as a scaffold. We compute differential reaction expression from transcriptomics data and use constraint-based modeling to predict if the differential expression of metabolic enzymes directly originates differences in metabolic fluxes. In parallel, we use metabolomics to predict how differences in substrate availability translate into differences in metabolic fluxes. We discriminate fluxes regulated at the metabolic and/or gene expression level by intersecting these two output datasets. We demonstrate the pipeline using a set of immortalized normal and cancer breast cell lines. In a clinical setting, knowing the regulatory level at which a given metabolic reaction is controlled will be valuable to inform targeted, truly personalized therapies in cancer patients.
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