TY - JOUR
T1 - RapidRIP quantifies the intracellular metabolome of 7 industrial strains of E. coli
AU - McCloskey, Douglas
AU - Xu, Julia
AU - Schrübbers, Lars
AU - Christensen, Hanne B.
AU - Herrgård, Markus J.
N1 - This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/)
PY - 2018
Y1 - 2018
N2 - Fast metabolite quantification methods are required for high throughput screening of microbial strains obtained by combinatorial or evolutionary engineering approaches. In this study, a rapid RIP-LC-MS/MS (RapidRIP) method for high-throughput quantitative metabolomics was developed and validated that was capable of quantifying 102 metabolites from central, amino acid, energy, nucleotide, and cofactor metabolism in less than 5 minutes. The method was shown to have comparable sensitivity and resolving capability as compared to a full length RIP-LC-MS/MS method (FullRIP). The RapidRIP method was used to quantify the metabolome of seven industrial strains of E. coli revealing significant differences in glycolytic, pentose phosphate, TCA cycle, amino acid, and energy and cofactor metabolites were found. These differences translated to statistically and biologically significant differences in thermodynamics of biochemical reactions between strains that could have implications when choosing a host for bioprocessing.
AB - Fast metabolite quantification methods are required for high throughput screening of microbial strains obtained by combinatorial or evolutionary engineering approaches. In this study, a rapid RIP-LC-MS/MS (RapidRIP) method for high-throughput quantitative metabolomics was developed and validated that was capable of quantifying 102 metabolites from central, amino acid, energy, nucleotide, and cofactor metabolism in less than 5 minutes. The method was shown to have comparable sensitivity and resolving capability as compared to a full length RIP-LC-MS/MS method (FullRIP). The RapidRIP method was used to quantify the metabolome of seven industrial strains of E. coli revealing significant differences in glycolytic, pentose phosphate, TCA cycle, amino acid, and energy and cofactor metabolites were found. These differences translated to statistically and biologically significant differences in thermodynamics of biochemical reactions between strains that could have implications when choosing a host for bioprocessing.
U2 - 10.1016/j.ymben.2018.04.009
DO - 10.1016/j.ymben.2018.04.009
M3 - Journal article
C2 - 29702276
SN - 1096-7176
VL - 47
SP - 383
EP - 392
JO - Metabolic Engineering
JF - Metabolic Engineering
ER -