Use flux balance analysis to simulate multiple growth phenotypes.
This method uses an input metabolic model to simulate growth in a set of media conditions, with a specified set of gene knockouts, and with specified media supplements. A metabolic model can be curated using phenotypic data such as Biolog growth data or gene essentiality data generated on a specific set of media conditions. The method reports differences between growth predictions and experimentally measured growth rates. This method can be applied to test the accuracy of a model in replicating experimental observations, as well as exploring the set of metabolites that an organism can utilize as nutrient sources. The Simulate Growth on Phenotype Data method carries out flux balance analysis (FBA) for each medium and knockout in the phenotype dataset and displays the output (growth/no growth) as a side-by-side comparison of model predictions and experimental results. To begin, the user uploads a table of phenotype data (e.g., Biolog or gene essentiality data) into the app. The user also either uploads a metabolic model or selects a model already present in KBase. KBase uses the selected model to simulate the uploaded phenotypes, presenting simulation results in a detailed exportable report. This method also conducts some reconciliation of models with phenotype data.
For information about how to upload your own phenotype data, see the Data Upload and Download Guide.
The columns in the phenotype files are as follows:
- media ID of the media condition loaded in KBase where the phenotype was observed.
- mediaws Workspace where the media for the phenotype data was loaded into KBase.
- growth Indication of whether or not the organism grew in the specified media with the specified knockouts. 1 means growth; 0 means no growth.
- geneko List of genes knocked out in the phenotype; use none for wild-type phenotypes.
- addtlCpd Additional media components added along with the primary media formulation.
Team members who developed & deployed algorithm in KBase: Chris Henry, Janaka Edirisinghe, Sam Seaver, and Neal Conrad. For questions, e-mail email@example.com
- Henry CS, DeJongh M, Best AA, Frybarger PM, Linsay B, Stevens RL. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol. 2010;28: 977 982. doi:10.1038/nbt.1672 , http://www.ncbi.nlm.nih.gov/pubmed/20802497
- Orth JD, Thiele I, Palsson B . What is flux balance analysis? Nature Biotechnology. 2010;28: 245 248. doi:10.1038/nbt.1614 , http://www.nature.com/nbt/journal/v28/n3/abs/nbt.1614.html
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