(512a) A Genomic Approach for Elucidating and Improving Isobutanol Tolerance in Escherichia Coli

Minty, J. J., University of Michigan
Lesnefsky, A., University of Michigan
Lin, F., University of Michigan
Gao, Y., Virginia Commonwealth University
Rouillard, J., University of Michigan
Chen, Y., University of Michigan
Gulari, E., University of Michigan
Lin, X. N., University of Michigan
Xie, B., Virginia Commonwealth University

Advances in microbial engineering have led to the development of metabolic pathways for producing higher molecular weight alcohols as next-generation biofuels [1]. In particular, Escherichia coli has been successfully engineered to produce isobutanol in high yield (86% of theoretical maximum) from carbohydrates [1], and direct photosynthetic conversion of CO2 to isobutanol has been demonstrated with engineered strains of Synechococcus elongates [2]. However isobutanol is highly toxic to microbes, which limits product titer and reduces volumetric productivity [1]. Solvent tolerance is a complex phenotype with a poorly understood genetic basis, precluding the use of rational approaches for improving tolerance [3]. We are working to develop a systematic and comprehensive approach to uncover the genetic basis of isobutanol tolerance, and then subsequently utilize this information for engineering improved tolerance. The essence of our approach entails i) experimentally evolving parallel populations of E. coli for isobutanol tolerance, ii) characterizing highly tolerant evolved isolates using genome resequencing and global gene expression studies, iii) using these data to hypothesize and elucidate mechanisms of adaptation to isobutanol toxicity, and iv) predicting candidate genetic loci for multiplex targeted mutagenesis to further improve isobutanol tolerance.

We evolved isobutanol tolerant lines of E. coli EcNR1 by serial culturing replicate populations on isobutanol spiked minimal media for approximately five hundred generations. Samples from each population were cryopreserved every 35 to 70 generations. Populations were evolved on different carbon sources (glucose and xylose, which are important constituents of cellulosic feedstocks) to investigate adaptations in different metabolic contexts. Clones capable of growth at 2% isobutanol in glucose media and 1.75% isobutanol in xylose media were obtained from the evolved populations, representing 60% and 40% improvements in tolerance respectively, compared to the parental E. coli strain. The genomes of several highly tolerant clones were resequenced using the Illumina platform, revealing mutations in diverse genes. Mutations in the acrAB-tolC multidrug efflux pump, gatZABCD galactitol metabolism operon, NADH dependent malate dehydrogenase mdh, and rph locus were discovered in multiple lineages; presumably some of these loci are under strong selective pressure and may play crucial roles in isobutanol tolerance. Cryopreserved samples from intermediate generations were genotyped to determine the temporal order of mutation acquisition, providing clues about possible fitness benefits and epistatic interactions between mutations. Key mutations identified in the highly isobutanol tolerant isolates were reconstructed in the parent E. coli EcNR1 strain singly and in various combinations to assess phenotypic and functional effects. Loss of function of acrAB was correlated with improved isobutanol tolerance, a surprising finding given that the acrAB-tolC efflux pump is an important mechanism of tolerance to other organic solvents [3]. Gene expression studies in isobutanol tolerant isolates have provided additional insights into mechanisms of adaptation.

In an effort to further improve isobutanol tolerance, putative crucial loci are being subjected to targeted mutagenesis. For loci that appear to be under selective pressure for enhanced or altered function, we attempt to predict additional mutations that can further enhance the desirable phenotype, using protein design algorithms for instance. This approach is combinatorial in nature, involving site-directed mutagenesis at many loci. We utilize Multiplex Automated Genome Engineering (MAGE), a recently developed technique that entails repeated cycles of high efficiency homologous recombination using large libraries of mutagenic DNA oligonucleotides [4], for this targeted engineering.

[1] Atsumi, Shota, Taizo Hanai, and James C. Liao. "Non-Fermentative Pathways for Synthesis of Branched-Chain Higher Alcohols as Biofuels." Nature 451 (2008): 86-91.

[2] Atsumi, Shota, Wendy Higashide, and James C. Liao. "Direct Photosynthetic Recycling of Carbon Dioxide to Isobutyraldehyde." Nature Biotechnology 27 (2009): 1177-180.

[3] Nicolaou, Sergios A., Stefan M. Gaida, and Eleftherios T. Papoutsakis. "A Comparative View of Metabolite and Substrate Stress and Tolerance in Microbial Bioprocessing: From Biofuels and Chemicals, to Biocatalysis and Bioremediation." Metabolic Engineering (2010) In Press.

[4] Wang, Harris H., Farren J. Isaacs, Peter A. Carr, Zachary Z. Sun, George Xu, Craig R. Forest, and George M. Church. "Programming Cells by Multiplex Genome Engineering and Accelerated Evolution." Nature 460 (2009): 894-99