Genome-Scale Metabolic Modeling of Escherichia coli and Its Chassis Design for Synthetic Biology Applications

Mienda, Bashir Sajo; Dräger, Andreas

doi:10.1007/978-1-0716-0822-7_16

Cited by 10 publications

(8 citation statements)

References 47 publications

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“…Since 2015, tenths of high-quality GSMM were reconstructed using merlin and at least 11 were published (30)(31)(32)(33)(34)(35)(36). A list of models completely developed in merlin is provided in Table S2.3 (Supplementary material).…”

Section: Validationmentioning

confidence: 99%

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merlin v4.0: an updated platform for the reconstruction of high-quality genome-scale metabolic models

Capela

Lagoa

Rodrigues

et al. 2021

Preprint

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Genome-scale metabolic models have been recognized as useful tools for better understanding living organism's metabolism. Merlin (https://merlin-sysbio.org/) is an open-source and user-friendly resource that hastens these models' reconstruction process, conjugating manual, and automatic procedures, while leveraging user's expertise with a curation-oriented graphical interface. An updated and redesigned version of merlin is herein presented. Since 2015, several features were implemented in merlin, along with profound changes in the software architecture, operating flow, and graphical interface. The current version (4.0) includes the implementation of novel algorithms and third-party tools for genome functional annotation, draft assembly, model refinement, and curation. Such updates led to an increase in the user-base, resulting in multiple published works including genome metabolic (re-)annotation and model reconstruction of multiple (lower and higher) eukaryotes and prokaryotes.

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Section: Validationmentioning

confidence: 99%

“…Besides the ones published previously, since 2015, tens of high-quality GSMMs have been reconstructed using merlin, and at least 11 have been published (55)(56)(57)(58)(59)(60). A list of models developed in merlin is provided in Table S3 (Supplementary data 1).…”

Section: Merlin's Impact On Researchmentioning

confidence: 99%

merlin v4.0: an updated platform for the reconstruction of high-quality genome-scale metabolic models

Capela

Lagoa

Rodrigues

et al. 2021

Preprint

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“…Metabolic modeling techniques (especially constraint-based stoichiometric models) have proven extremely useful in minimizing the time it takes to develop heterotrophic production strains ( 29 – 32 ). One of the main assumptions in stoichiometric modeling approaches is steady state; this means that metabolite pool sizes are assumed to stay constant.…”

Section: Introductionmentioning

confidence: 99%

Rhythm of the Night (and Day): Predictive Metabolic Modeling of Diurnal Growth in Chlamydomonas

Metcalf

Boyle

2022

mSystems

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We have developed the first transient metabolic model for diurnal growth of algae based on experimental data and capable of predicting phenotype from genotype. This model enables us to evaluate the impact of genetic and environmental changes on the growth, biomass composition and intracellular fluxes of the model green alga, Chlamydomonas reinhardtii . The availability of this model will enable faster and more efficient design of cells for production of fuels, chemicals, and pharmaceuticals.

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“…Consequently, any attempt to fully grasp the functions and simultaneously operating processes within a living organism nowadays heavily relies on computational tools and simulation. Building computer models in biology has already demonstrated its potential in many application areas, such as the contextualization and visualization of high-throughput data, e.g., [2], guiding metabolic engineering in biotechnology, e.g., [3], the directed search for potential antiviral targets, e.g., [4,5], or to mathematically describe measures to effectively control the spread of infections, e.g., [6]. Since computational modeling of biological systems remains a challenging task, several different approaches exist to derive model representations with varying simplifying assumptions, each of which tackles the underlying complexities in many ways.…”

Section: Introductionmentioning

confidence: 99%

“…qualitative models, e.g., [9,10], which offer a flexible framework to delineate the main properties of complex biological regulatory networks [11]. 3.…”

Section: Introductionmentioning

confidence: 99%

SBMLWebApp: Web-Based Simulation, Steady-State Analysis, and Parameter Estimation of Systems Biology Models

Yamada

König

et al. 2021

Processes

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In systems biology, biological phenomena are often modeled by Ordinary Differential Equations (ODEs) and distributed in the de facto standard file format SBML. The primary analyses performed with such models are dynamic simulation, steady-state analysis, and parameter estimation. These methodologies are mathematically formalized, and libraries for such analyses have been published. Several tools exist to create, simulate, or visualize models encoded in SBML. However, setting up and establishing analysis environments is a crucial hurdle for non-modelers. Therefore, easy access to perform fundamental analyses of ODE models is a significant challenge. We developed SBMLWebApp, a web-based service to execute SBML-based simulation, steady-state analysis, and parameter estimation directly in the browser without the need for any setup or prior knowledge to address this issue. SBMLWebApp visualizes the result and numerical table of each analysis and provides a download of the results. SBMLWebApp allows users to select and analyze SBML models directly from the BioModels Database. Taken together, SBMLWebApp provides barrier-free access to an SBML analysis environment for simulation, steady-state analysis, and parameter estimation for SBML models. SBMLWebApp is implemented in Java™ based on an Apache Tomcat® web server using COPASI, the Systems Biology Simulation Core Library (SBSCL), and LibSBMLSim as simulation engines. SBMLWebApp is licensed under MIT with source code freely available. At the end of this article, the Data Availability Statement gives the internet links to the two websites to find the source code and run the program online.

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Genome-Scale Metabolic Modeling of Escherichia coli and Its Chassis Design for Synthetic Biology Applications

Cited by 10 publications

References 47 publications

merlin v4.0: an updated platform for the reconstruction of high-quality genome-scale metabolic models

merlin v4.0: an updated platform for the reconstruction of high-quality genome-scale metabolic models

Rhythm of the Night (and Day): Predictive Metabolic Modeling of Diurnal Growth in Chlamydomonas

SBMLWebApp: Web-Based Simulation, Steady-State Analysis, and Parameter Estimation of Systems Biology Models

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