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Updated: Oct 29, 2026

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
Published on: November 12, 2012
Single-gene knockout analysis in an Escherichia coli whole-cell model reveals medium, temperature, and generational
Jiaqi Wei1,2, Weiping Lin3,4
1Faculty of Science and Engineering, School of Engineering Mathematics and Technology, University of Bristol, Bristol BS8 1TW, UK.
Abstract:
Whole-cell models serve as powerful tools to predict cellular phenotype from genotype by integrating genome-scale processes within a single computational framework. Single-gene knockout (KO) growth is a stringent benchmark, but comparisons to experimental resources require close alignment of assay conditions, especially temperature and growth medium. We benchmark an Escherichia coli (E. coli) whole-cell model by simulating multi-generation single-gene KOs in glucose minimal and amino-acid-supplemented media at 37 °C and by analyzing two independent eight-generation KO cohorts. For each KO we estimated generation-specific growth rates and harmonic-mean summaries across early generations. Experimental KO growth rates measured at 30°C were converted to s-1 and scaled to 37°C using an explicit Q10 correction Essential versus nonessential effects were tested using Welch's t comparisons with 95% confidence intervals based on the Welch-Satterthwaite t approximation, and false discovery rate control across generations. Cross-medium generalization was evaluated using correlations and stratified regression for further prediction. Temperature adjustment shifted the experimental growth-rate distribution toward the simulated distribution. Essential KOs showed lower growth in the earliest generations, while the two eight-generation cohorts exhibited an overall decline in mean growth with substantial heterogeneity. Cross-medium correlations were weak, and in the held-out predictive comparison the global linear model achieved lower RMSE than the stratified SVR.
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