Escher-FBA: a web application for interactive flux balance analysis

The mitis group of streptococci (MGS) is a member of the healthy human microbiome in the oral cavity and upper respiratory tract. Troublingly, some MGS are able to escape this niche and cause infective endocarditis, a severe and devastating disease. Genome-scale models have been shown to be valuable in investigating metabolism of bacteria. Here we present the first genome-scale model, iCJ415, for Streptococcus oralis SK141. We validated the model using gene essentiality and amino acid auxotrophy data from closely related species. iCJ415 has 71-76% accuracy in predicting gene essentiality and 85% accuracy in predicting amino acid auxotrophy. Further, the phenotype of S. oralis was tested using the Biolog Phenotype microarrays, giving iCJ415 a 82% accuracy in predicting carbon sources. iCJ415 can be used to explore the metabolic differences within the MGS, and to explore the complicated metabolic interactions between different species in the human oral cavity.

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“…These calculations were visualized and calculated using the Escher FBA webapplication (Rowe et al, 2018).…”

Section: Biomass Yieldmentioning

confidence: 99%

Reconstruction and Validation of a Genome-Scale Metabolic Model of Streptococcus oralis (iCJ415), a Human Commensal and Opportunistic Pathogen

et al. 2020

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“…Flux maps were created using Escher web application (https://escher.github.io/#/). 72,73 It has also been observed previously that deficiency in glucose and glutamine impairs CD4+ T cell activation and proliferation. 74,75 We performed this experiment in silico, whereby we varied the flux through exchange reactions of glucose (EX_glc[e]) and glutamine (EX_gln_L[e]) in the models and analyzed the effect on growth rate.…”

Section: Model Validationmentioning

confidence: 73%

Integrative computational approach identifies new targets in CD4+ T cell-mediated immune disorders

Puniya

Lichter

Moore

et al. 2020

Preprint

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CD4+ T cells, which provide adaptive immunity against pathogens and abnormal cells, are also associated with various immune related diseases. CD4+ T cells' metabolism is dysregulated in these pathologies and represents an opportunity for drug discovery and development. However, we currently lack clear view of the target space in this area. Genome-scale metabolic modeling offers an opportunity to accelerate drug discovery by providing high-quality information about

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“…Thus, we obtained the flux distribution of metabolic pathways under wild-type conditions using Flux Balance Analysis (FBA) and searched the non-zero fluxes through the aforementioned pathways in all the models. Flux maps were created using Escher web application ( https://escher.github.io/#/ ) 78 , 79 . It has also been observed previously that deficiency in glucose and glutamine impairs CD4 + T-cell activation and proliferation 37 , 80 .…”

Section: Methodsmentioning

confidence: 99%

Integrative computational approach identifies drug targets in CD4+ T-cell-mediated immune disorders

et al. 2021

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CD4+ T cells provide adaptive immunity against pathogens and abnormal cells, and they are also associated with various immune-related diseases. CD4+ T cells’ metabolism is dysregulated in these pathologies and represents an opportunity for drug discovery and development. Genome-scale metabolic modeling offers an opportunity to accelerate drug discovery by providing high-quality information about possible target space in the context of a modeled disease. Here, we develop genome-scale models of naïve, Th1, Th2, and Th17 CD4+ T-cell subtypes to map metabolic perturbations in rheumatoid arthritis, multiple sclerosis, and primary biliary cholangitis. We subjected these models to in silico simulations for drug response analysis of existing FDA-approved drugs and compounds. Integration of disease-specific differentially expressed genes with altered reactions in response to metabolic perturbations identified 68 drug targets for the three autoimmune diseases. In vitro experimental validation, together with literature-based evidence, showed that modulation of fifty percent of identified drug targets suppressed CD4+ T cells, further increasing their potential impact as therapeutic interventions. Our approach can be generalized in the context of other diseases, and the metabolic models can be further used to dissect CD4+ T-cell metabolism.

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Escher-FBA: a web application for interactive flux balance analysis

Cited by 45 publications

References 24 publications

Reconstruction and Validation of a Genome-Scale Metabolic Model of Streptococcus oralis (iCJ415), a Human Commensal and Opportunistic Pathogen

Reconstruction and Validation of a Genome-Scale Metabolic Model of Streptococcus oralis (iCJ415), a Human Commensal and Opportunistic Pathogen

Integrative computational approach identifies new targets in CD4+ T cell-mediated immune disorders

Integrative computational approach identifies drug targets in CD4+ T-cell-mediated immune disorders

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