Computational protocol: Systematic phenome analysis of Escherichia coli multiple-knockout mutants reveals hidden reactions in central carbon metabolism

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Protocol publication

[…] Ec_iAF1260 (), which contains 1260 ORF information of E. coli, was used as a base model. When a target reaction in this study involved two or more isozymes, only one gene considered to be the main isozyme was kept. Basically, thermodynamic constraint and gene expression information for aerobic growth on glucose reported in reference were used as an initial constraint and additional changes depending on the carbon source and gene deletion were considered. Modifications to this default are listed in . The maximum rate of the carbon source import (lower bound) was set to −6. The maximum rate for each amino-acid import was set to match the molar ratio calculated from the composition of casamino acids (supplied by Becton, Dickinson), and total amount was adjusted to match the observed growth of icdA and gltA single-knockout mutants, which required amino acids for growth. A solution that optimized the rate of biomass production in a given model condition was obtained by FBA or linearMoMA using COBRA toolbox (). For prediction by MoMA, solution by the FBA using the same model, except that using the wild type pathway instead of the single or double deletion, was used for comparison. The maximum rate of biomass production was used as the simulated growth rate. The initial model included many reactions that could bypass known central carbon metabolism. However, many of these possible bypasses did not seem functional in the living cells, because most of the reactions cannot support the amount of flux required for central carbon metabolism. To validate these possible bypasses and refine the model, growth of the single-knockout strains, having first series of deletion, was compared with the prediction using the RGIe and RGIs value against the wild type. If difference between RGIe and RGIs was grater than 2, reactions that could result in false predictions were examined and maximum or minimum flux of the reaction was adjusted to match the prediction with the experimentally measured growth rate. The script used for the predictions using COBRA toolbox is shown in . [...] DNA microarrays were produced by spotting of the E. coli AROS V2.0 oligo-DNA set (Operon Biotechnologies, Huntsville, USA) on a GeneSlide (Toyo Kohan, Tokyo) according to the manufacturer's protocol. Cells were cultured and sampled under the same conditions as described for metabolome sampling. During sampling, RNA was stabilized by mixing with RNAprotect Bacteria reagent (Qiagen), and total RNA was isolated using the RNeasy Mini kit (Qiagen). Duplicate experiments employing dye swapping were performed. The protocol and conditions used for hybridization and washing were previously described (). Images were scanned by Affymetrix 428 in 10-μm resolution using Jaguar 2.0 software and processed by the Imagene 4.0 software (BioDiscovery, Segundo, USA) using the default settings. The raw numerical data files from Imagene were further processed using the GeneSpring 7.3 (Agilent) software package. A Lowess curve was fit to the log-intensity versus log-ratio plot. Twenty percent of the data was used to calculate the Lowess fit at each point. This curve was used to adjust the control value for each measurement.The microarray data had been submitted to MIAMEexpress under accession no. E-MEXP-1841. […]

Pipeline specifications

Software tools COBRA Toolbox, MOMA
Application Metabolic engineering
Organisms Escherichia coli
Chemicals Adenosine Triphosphate, Carbon, Dihydroxyacetone Phosphate