Defining the nutritional input for genome-scale metabolic models: A roadmap

Μαρίνος, Γεώργιος; Kaleta, Christoph; Waschina, Silvio

doi:10.1371/journal.pone.0236890

Cited by 33 publications

(38 citation statements)

References 68 publications

(110 reference statements)

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“…Constraint-based modeling (CBM) approaches have successfully been applied in fundamental research (Bla ¨tke and Bra ¨utigam, 2019; Marinos et al, 2020;Swainston et al, 2016) especially in cancer research (Agren et al, 2012;Larsson et al, 2020;Pacheco et al, 2019;Yizhak et al, 2015), as well as in microbial engineering (Choon et al, 2014; among other research fields. CBM uses data-and prior knowledge-driven constraints to identify feasible metabolic flux distributions for a given condition (Schellenberger et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Constraint-based modelling (CBM) approaches have successfully been applied in fundamental research [1], [2], [3] especially in cancer research [4], [5], [6], [7], as well as in microbial engineering [8], [9] among other research fields. CBM uses data-and prior knowledge-driven constraints to identify feasible metabolic flux distributions for a given condition [10].…”

Section: Introductionmentioning

confidence: 99%

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DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling

Kishk¹,

Pacheco²,

Sauter³

2021

iScience

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The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no approved effective antiviral drug. Flux balance analysis (FBA) is an efficient method to analyze metabolic networks. Here, FBA was applied on human lung cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reposition metabolic drugs and drug combinations against the virus replication within the host tissue. Making use of expression data sets of infected lung tissue, genome-scale COVID-19-specific metabolic models were reconstructed. Then, host-specific essential genes and gene-pairs were determined through in silico knockouts that permit reducing the viral biomass production without affecting the host biomass. Key pathways that are associated with COVID-19 severity in lung tissue are related to oxidative stress, ferroptosis and pyrimidine metabolism. By in silico screening of FDA-approved drugs on the putative disease-specific essential genes and gene-pairs, 85 drugs and 52 drug combinations were predicted as promising candidates for COVID-19 ( https://github.com/sysbiolux/DCcov ).

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling

Kishk¹,

Pacheco²,

Sauter³

2021

iScience

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“…An in-silico medium (Table 1) was simulated based on the methods of Marinos et al (2020) and the composition of reconstructed water chemistry and evidence of trace minerals (Fukushi et al, 2019;Payré et al, 2019). Copper and zinc deposits within Gale crater were likely adsorbed onto Mn-oxides and thus insoluble (Payré et al, 2019).…”

Section: Formulation Of a Gale Lake Minimal Mediummentioning

confidence: 99%

Microbial habitability of early Mars lacustrine environments sustained by iron redox cycling

Moore

Carr

2021

Preprint

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Several studies have reported new data on the estimated compositions of chemical components at Gale crater; however, there is still a lack of information regarding potential past support of biomass and detectable biomarkers of ancient life. In this study we evaluate microbial habitability of early Mars constrained by the recently reconstructed water chemistry at Gale. The modeled community is based on Fe-metabolizing bacteria with the ability to utilize solid-phase iron oxides (e.g., magnetite) as an electron source or sink. Our results illustrate the plausibility of a sustained community in Gale Lake and provides suggestions for future modeled and laboratory-based studies to further evaluate the past habitability of Mars, biosignatures and their preservation potential, and hidden metabolic potential.One Sentence SummaryThis work provides an existence proof of habitability on early Mars and demonstrates modeling processes by which the habitability of extraterrestrial environments can be explored quantitatively.

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“…Several efforts have been made in recent years to overcome this problem. The work presented by Marinos et al [ 38 ] developed a pipeline to overcome some of these limitations, providing strategies for the definition of a medium to improve the predictions of GSSMs.…”

Section: Introductionmentioning

confidence: 99%

A pipeline for the reconstruction and evaluation of context-specific human metabolic models at a large-scale

2022

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Constraint-based (CB) metabolic models provide a mathematical framework and scaffold for in silico cell metabolism analysis and manipulation. In the past decade, significant efforts have been done to model human metabolism, enabled by the increased availability of multi-omics datasets and curated genome-scale reconstructions, as well as the development of several algorithms for context-specific model (CSM) reconstruction. Although CSM reconstruction has revealed insights on the deregulated metabolism of several pathologies, the process of reconstructing representative models of human tissues still lacks benchmarks and appropriate integrated software frameworks, since many tools required for this process are still disperse across various software platforms, some of which are proprietary. In this work, we address this challenge by assembling a scalable CSM reconstruction pipeline capable of integrating transcriptomics data in CB models. We combined omics preprocessing methods inspired by previous efforts with in-house implementations of existing CSM algorithms and new model refinement and validation routines, all implemented in the Troppo Python-based open-source framework. The pipeline was validated with multi-omics datasets from the Cancer Cell Line Encyclopedia (CCLE), also including reference fluxomics measurements for the MCF7 cell line. We reconstructed over 6000 models based on the Human-GEM template model for 733 cell lines featured in the CCLE, using MCF7 models as reference to find the best parameter combinations. These reference models outperform earlier studies using the same template by comparing gene essentiality and fluxomics experiments. We also analysed the heterogeneity of breast cancer cell lines, identifying key changes in metabolism related to cancer aggressiveness. Despite the many challenges in CB modelling, we demonstrate using our pipeline that combining transcriptomics data in metabolic models can be used to investigate key metabolic shifts. Significant limitations were found on these models ability for reliable quantitative flux prediction, thus motivating further work in genome-wide phenotype prediction.

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Defining the nutritional input for genome-scale metabolic models: A roadmap

Cited by 33 publications

References 68 publications

DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling

DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling

Microbial habitability of early Mars lacustrine environments sustained by iron redox cycling

A pipeline for the reconstruction and evaluation of context-specific human metabolic models at a large-scale

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