Mathematical Modeling and Omic Data Integration to Understand Dynamic Adaptation of Apicomplexan Parasites and Identify Pharmaceutical Targets

Sen, Partho; Vial, Henri; Radulescu, Ovidiu

doi:10.1002/9783527694082.ch20

Cited by 2 publications

(2 citation statements)

References 117 publications

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“…Many efforts are ongoing, aiming to couple pharmacokinetic and constraint-based models to study drug-microbe-diet interactions [ 114 ]. However, a limitation of GSMM approach is that GEMs are stoichiometric models, and cannot, in their current form at least, incorporate metabolite concentrations or enzyme kinetics (V max , K m , K cat ) [ 115 , 116 ]. Albeit more limited in scope, kinetic modeling [ 116 ] may help improve understanding of the dynamics of metabolic pathways in the human gut.…”

Section: Concluding Remarks and Future Perspectivesmentioning

confidence: 99%

Metabolic Modeling of Human Gut Microbiota on a Genome Scale: An Overview

Sen

Orešič

2019

Metabolites

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There is growing interest in the metabolic interplay between the gut microbiome and host metabolism. Taxonomic and functional profiling of the gut microbiome by next-generation sequencing (NGS) has unveiled substantial richness and diversity. However, the mechanisms underlying interactions between diet, gut microbiome and host metabolism are still poorly understood. Genome-scale metabolic modeling (GSMM) is an emerging approach that has been increasingly applied to infer diet–microbiome, microbe–microbe and host–microbe interactions under physiological conditions. GSMM can, for example, be applied to estimate the metabolic capabilities of microbes in the gut. Here, we discuss how meta-omics datasets such as shotgun metagenomics, can be processed and integrated to develop large-scale, condition-specific, personalized microbiota models in healthy and disease states. Furthermore, we summarize various tools and resources available for metagenomic data processing and GSMM, highlighting the experimental approaches needed to validate the model predictions.

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Section: Concluding Remarks and Future Perspectivesmentioning

confidence: 99%

Metabolic Modeling of Human Gut Microbiota on a Genome Scale: An Overview

Sen

Orešič

2019

Metabolites

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“…With the rapid advancement of cutting-edge technologies in PBMC research, there is a growing need for development of integrative methods and computational models to cope with the increasing amounts of data. These approaches when applied at the systems level could mechanistically relate entities like gene, proteins and metabolites that might unveil the disease markers and related processes at the systems level (Sen et al, 2016 ).…”

Section: Genome-scale Metabolic Models As a Tool To Study Metabolismmentioning

confidence: 99%

Perspectives on Systems Modeling of Human Peripheral Blood Mononuclear Cells

Sen

Kemppainen

Orešič

2018

Front. Mol. Biosci.

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Human peripheral blood mononuclear cells (PBMCs) are the key drivers of the immune responses. These cells undergo activation, proliferation and differentiation into various subsets. During these processes they initiate metabolic reprogramming, which is coordinated by specific gene and protein activities. PBMCs as a model system have been widely used to study metabolic and autoimmune diseases. Herein we review various omics and systems-based approaches such as transcriptomics, epigenomics, proteomics, and metabolomics as applied to PBMCs, particularly T helper subsets, that unveiled disease markers and the underlying mechanisms. We also discuss and emphasize several aspects of T cell metabolic modeling in healthy and disease states using genome-scale metabolic models.

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Mathematical Modeling and Omic Data Integration to Understand Dynamic Adaptation of Apicomplexan Parasites and Identify Pharmaceutical Targets

Cited by 2 publications

References 117 publications

Metabolic Modeling of Human Gut Microbiota on a Genome Scale: An Overview

Metabolic Modeling of Human Gut Microbiota on a Genome Scale: An Overview

Perspectives on Systems Modeling of Human Peripheral Blood Mononuclear Cells

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