Team:ETH Zurich/Project/Model Relevant
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==== Detailed description of the Modeling Framework ==== | ==== Detailed description of the Modeling Framework ==== | ||
# '''Restriction Enzyme Analysis''' | # '''Restriction Enzyme Analysis''' | ||
- | #:We want to identify a restriction enzyme for genome reduction that maximizes the probability of genome reduction and minimizes the probability to hit an (known) essential gene. Therefore, given a genome data of an E. Coli strain, the genome is digested using ca. 700 different restriction enzymes (with different recognition patterns). | + | #:We want to identify a restriction enzyme for genome reduction that maximizes the probability of genome reduction and minimizes the probability to hit an (known) essential gene. Therefore, given a genome data of an E. Coli strain, the genome is digested using ca. 700 different restriction enzymes (with different recognition patterns). The resulting fragments are analyzed using the available annotation of the genome. The number of genes disrupted is calculated for each fragment. Statistical measures of the restriction enzyme effects, such as average size of the fragments and its variance, and the average number of (all and only essential) genes and its variance are calculated. According to these results, the most suitable restriction enzyme is chosen. |
- | The resulting fragments are analyzed using the available annotation of the genome. The number of genes disrupted is calculated for each fragment. Statistical measures of the restriction enzyme effects, such as average size of the fragments and its variance, and the average number of (all and only essential) genes and its variance are calculated. According to these results, the most suitable restriction enzyme is chosen. | + | |
# '''Genome Scale Model and Flux Balance Analysis''' | # '''Genome Scale Model and Flux Balance Analysis''' | ||
#:We apply Flux Balance Analysis on the state-of-the-art genome scale model for E.Coli iAF1260 (1260 genes included) in order to #: | #:We apply Flux Balance Analysis on the state-of-the-art genome scale model for E.Coli iAF1260 (1260 genes included) in order to #: |
Revision as of 17:12, 25 October 2008
Medal Relevant IssuesSilver RelevantGold RelevantWe propose a novel method of random gene deletion and chemostat-based selection of species with a reduced genome. For this we provide an algorithm described below. Modeling FrameworkThis algorithm requires a modeling framework consisting of four main parts:
Detailed description of the Modeling Framework
calculate the biomass yield (and therefore the corresponding growth rate) for wildtype and reduced strains. In order to apply a selective condition for reduced genome strain, the model is modified by constraining nucleotide availability: this means inactivation of a part of a thymidine synthesis pathway and external uptake of thymidine from the medium. The optimal external thymidine concentration is determined which enables the fastest change in growth rate of a reduced genome mutant.
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