Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories

Cardoso, Joao; Jensen, Kristian; Lieven, Christian; Hansen, Anne Sofie Lærke; Galkina, Svetlana; Beber, Moritz Emanuel; Özdemir, Emre; Herrgård, Markus J.; Redestig, Henning; Sonnenschein, Nikolaus

doi:10.1021/acssynbio.7b00423

Cited by 60 publications

(41 citation statements)

References 22 publications

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“…This model was modified by deleting the PDC reaction to eliminate ethanol production, and the heterologous pathways for each strain were added to the reactions in the model, producing a distinct model for each strain. These models were used to determine the remainder of the fluxes using parsimonious flux balance analysis implemented in the Cameo (v0.11.6) toolbox for Python 3.4 …”

Section: Methodsmentioning

confidence: 99%

The Transcriptome and Flux Profiling of Crabtree‐Negative Hydroxy Acid‐Producing Strains of Saccharomyces cerevisiae Reveals Changes in the Central Carbon Metabolism

Jessop-Fabre

Dahlin

Biron

et al. 2019

Biotechnology Journal

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Saccharomyces cerevisiae (S. cerevisiae) is the yeast cell factory of choice for the production of many biobased chemicals. However, it is a Crabtree‐positive yeast and so shuttles a large portion of carbon into ethanol. Ethanol formation can be eliminated by deleting pyruvate decarboxylase (PDC) activity. It is not yet well understood how PDC‐negative yeasts are affected when engineered to produce other products than ethanol. In this study, pathways are introduced for the production of three hydroxy acids (lactic, malic, or 3‐hydroxypropionic acid [3HP]) into an evolved PDC‐negative strain. These strains are characterized via transcriptome and flux profiling to elucidate the effects that the production of these hydroxy acids has on the host strain. Expression of lactic and malic acid biosynthesis pathways improved the maximum specific growth rate (μmax) of the strain by 64% and 20%, respectively, presumably due to nicotinamide adenine dinucleotide regeneration. All strains show a very high flux ( > 90% of glucose uptake) into the oxidative pentose phosphate pathway under batch fermentation conditions. The study, for the first time, directly compares the flux and transcriptome profiles of several hydroxy acid‐producing strains of an evolved PDC‐negative S. cerevisiae and suggests directions for future metabolic engineering.

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Section: Methodsmentioning

confidence: 99%

The Transcriptome and Flux Profiling of Crabtree‐Negative Hydroxy Acid‐Producing Strains of Saccharomyces cerevisiae Reveals Changes in the Central Carbon Metabolism

Jessop-Fabre

Dahlin

Biron

et al. 2019

Biotechnology Journal

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“…iML1515: For simulation of the constraint-based model iML1515 with lMOMA we used cobrapy (26) and cameo packages (27) . Chemostat culture is simulated as minimization of glucose uptake with constraint on growth to match the experimental dilution rate.…”

Section: Simulation Setupmentioning

confidence: 99%

Benchmarking kinetic models ofEscherichia colimetabolism

Shepelin

Machado

Nielsen

et al. 2020

Preprint

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Predicting phenotype from genotype is the holy grail of quantitative systems biology.Kinetic models of metabolism are among the most mechanistically detailed tools for phenotype prediction. Kinetic models describe changes in metabolite concentrations as a function of enzyme concentration, reaction rates, and concentrations of metabolic effectors uniquely enabling integration of multiple omics data types in a unifying mechanistic framework. While development of such models for Escherichia coli has been going on for almost twenty years, multiple separate models have been established and systematic independent benchmarking studies have not been performed on the full set of models available. In this study we compared systematically all recently published kinetic models of the central carbon metabolism of Escherichia coli . We assess the ease of use of the models, their ability to include omics data as input, and the accuracy of prediction of central carbon metabolic flux phenotypes. We conclude that there is no clear winner among the models when considering the resulting tradeoffs in performance

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“…As a result, FBC Version 2 is the de facto standard for encoding GEMs. Critical to this process is its implementation in a wide range of constraint-based modeling software and adoption by public model repositories 22,[26][27][28][29][30][31][32][33][34] . We believe these factors make SBML3FBC the optimal format for sharing and representing GEMs, thus models encoded in SBML3FBC serve as the input to memote.…”

Section: Sbml: Tool-independent Model Formulationmentioning

confidence: 99%

Memote: A community driven effort towards a standardized genome-scale metabolic model test suite

Lieven¹,

Beber²,

Olivier³

et al. 2018

Preprint

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Several studies have shown that neither the formal representation nor the functional requirements of genome-scale metabolic models (GEMs) are precisely defined. Without a consistent standard, comparability, reproducibility, and interoperability of models across groups and software tools cannot be guaranteed.Here, we present memote (https://github.com/opencobra/memote) an open-source software containing a community-maintained, standardized set of me tabolic mo del te sts. The tests cover a range of aspects from annotations to conceptual integrity and can be extended to include experimental datasets for automatic model validation. In addition to testing a model once, memote can be configured to do so automatically, i.e., while building a GEM. A comprehensive report displays the model's performance parameters, which supports informed model development and facilitates error detection.Memote provides a measure for model quality that is consistent across reconstruction platforms and analysis software and simplifies collaboration within the community by establishing workflows for publicly hosted and version controlled models.A. Richelle: Lilly Innovation Fellowship Award B. García-Jiménez and J.

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Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories

Cited by 60 publications

References 22 publications

The Transcriptome and Flux Profiling of Crabtree‐Negative Hydroxy Acid‐Producing Strains of Saccharomyces cerevisiae Reveals Changes in the Central Carbon Metabolism

The Transcriptome and Flux Profiling of Crabtree‐Negative Hydroxy Acid‐Producing Strains of Saccharomyces cerevisiae Reveals Changes in the Central Carbon Metabolism

Benchmarking kinetic models ofEscherichia colimetabolism

Memote: A community driven effort towards a standardized genome-scale metabolic model test suite

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