000200179 001__ 200179
000200179 005__ 20180913062553.0
000200179 037__ $$aPOST_TALK
000200179 245__ $$aEngineering improved productivity of 1,4-butanediol in E. coli – a kinetic modeling approach
000200179 269__ $$a2014
000200179 260__ $$c2014
000200179 336__ $$aPosters
000200179 520__ $$aMicrobial cell factories are becoming a norm for commercially viable production of chemicals for pharmaceutical, biotechnology, food and beverage industries. However, engineering of microbial cell factories requires a simultaneous optimization of several criteria such as productivity, yield, titer, stress tolerance, all the while retaining the efficient, cost-effective and robust process. One of the most prominent examples where a rational metabolic engineering strategy played a key role is in the production of 1,4-butanediol (BDO) in E. coli. In this study, we used the ORACLE (Optimization and Risk Analysis of Complex Living Entities) framework to analyze possible enhancements of the E. coli strain engineered for improved production of BDO. ORACLE framework allowed us to integrate thermodynamics, available omics and kinetic data into a population of large-scale kinetic models. Analysis of the engineered E. coli strain led to the identification of three critical modules within the metabolic network which contained the enzymes that primarily control the fluxes leading to BDO production. The enzymes in these modules are focused around: a) central glycolysis, b) the lower branch of tricarboxyclic acid cycle, and c) novel BDO production route. However, the manipulation of the enzymes in the identified modules - while possibly leading to the increased BDO production - had complex effects on other intracellular states like redox state, energy charge, cofactor levels, cellular growth and byproduct formation. We used the large-scale kinetic models generated by ORACLE to postulate successfully metabolic engineering alternatives for optimal performance with reduced byproduct secretion and fine-tuned redox balance, energy charge and cofactor levels. While in the current study, the aim was to improve BDO production, the methodology presented here can readily be applied to other products and organisms of interest.
000200179 6531_ $$a1
000200179 6531_ $$a4-butanediol
000200179 6531_ $$aE. coli
000200179 6531_ $$aKinetic models
000200179 6531_ $$aMetabolic Control Analysis
000200179 700__ $$0244258$$g193203$$aAndreozzi, Stefano
000200179 700__ $$0246141$$g221171$$aChakrabarti, Anirikh
000200179 700__ $$0243874$$g177860$$aSoh, Keng Cher
000200179 700__ $$aBurgard, Anthony
000200179 700__ $$aVan Dien, Steve
000200179 700__ $$0240448$$g133818$$aMiskovic, Ljubisa
000200179 700__ $$0240657$$g174688$$aHatzimanikatis, Vassily
000200179 700__ $$aYang, Tae Hoon
000200179 7112_ $$dJune 15-19, 2014$$cVancouver, Canada$$aMetabolic Engineering X
000200179 909C0 $$xU11422$$0252131$$pLCSB
000200179 909CO $$pSB$$pposter$$ooai:infoscience.tind.io:200179
000200179 917Z8 $$x133818
000200179 917Z8 $$x133818
000200179 917Z8 $$x193203
000200179 937__ $$aEPFL-POSTER-200179
000200179 973__ $$aEPFL
000200179 980__ $$aPOSTER