Genome shuffling to generate recombinant yeasts for tolerance to inhibitors present in lignocellulosic hydrolysates.

OBJECTIVES: To investigate the use of genome shuffling to generate recombinants from previously generated hydrolysates-tolerant strains to improve tolerance of Saccharomyces cerevisiae to one or more inhibitory by-products present in lignocellulosic hydrolysates. RESULTS: Recombinants of previously evolved strains of S. cerevisiae were generated and analyzed for their relative performance in the individual inhibitors furfural, acetic acid, 5-(hydroxymethyl)-furfural (HMF) and in synthetic hydrolysates. One recombinant exhibited a 100 % fitness increase in the presence of HMF as compared to the wild-type diploid, while another stain exhibited a 13 % fitness increase in the presence of furfural. Furthermore, for one of these recombinants, these increases in fitness were specific to the inhibitor HMF and to synthetic hydrolysates rather than being due to a general increase in fitness. Mutations present in the evolved hydrolysates-tolerant mutants were identified via whole-genome resequencing. CONCLUSION: Recombinants of S. cerevisiae were produced with increased tolerance to inhibitory by-products present in hydrolysates of lignocellulosic biomass and identified potential genetic determinants associated with this phenotype.

Evolutionary engineering of Saccharomyces cerevisiae for enhanced tolerance to hydrolysates of lignocellulosic biomass.

Lignocellulosic biomass has become an important feedstock to mitigate current ethical and economical concerns related to the bio-based production of fuels and chemicals. During the pre-treatment and hydrolysis of the lignocellulosic biomass, a complex mixture of sugars and inhibitors are formed. The inhibitors interfere with microbial growth and product yields. This study uses an adaptive laboratory evolution method called visualizing evolution in real-time (VERT) to uncover the molecular mechanisms associated with tolerance to hydrolysates of lignocellulosic biomass in Saccharomyces cerevisiae. VERT enables a more rational scheme for isolating adaptive mutants for characterization and molecular analyses. Subsequent growth kinetic analyses of the mutants in individual and combinations of common inhibitors present in hydrolysates (acetic acid, furfural, and hydroxymethylfurfural) showed differential levels of resistance to different inhibitors, with enhanced growth rates up to 57%, 12%, 22%, and 24% in hydrolysates, acetic acid, HMF and furfural, respectively. Interestingly, some of the adaptive mutants exhibited reduced fitness in the presence of individual inhibitors, but showed enhanced fitness in the presence of combinations of inhibitors compared to the parental strains. Transcriptomic analysis revealed different mechanisms for resistance to hydrolysates and a potential cross adaptation between oxidative stress and hydrolysates tolerance in several of the mutants.

Visualizing evolution in real time to determine the molecular mechanisms of n-butanol tolerance in Escherichia coli.

Toxicity of products or feedstock components poses a challenge in the biocatalyst-based production of fuels and chemicals. The genetic determinants that are involved in increased resistance to an inhibitor form the adaptive landscape for the phenotype; so in order to engineer more robust biocatalysts, a better understanding of the adaptive landscape is required. Here, we used an adaptive laboratory evolution method called visualizing evolution in real time (VERT) to help map out part of the adaptive landscape of Escherichia coli tolerance to the biofuel n-butanol. VERT enables identification of adaptive events (population expansions triggered by adaptive mutants) via visualization of the relative proportions of different fluorescently-labeled cells. Knowledge of the occurrence of adaptive events allows for a more systematic isolation of adaptive mutants while simultaneously reducing the number of missed adaptive mutants (and the underlying adaptive mechanisms) that result from clonal interference during the course of in vitro evolution. Based on the evolutionary dynamics observed, clonal interference was found to play a significant role in shaping the population structure of E. coli during exposure to n-butanol, and VERT helped to facilitate the isolation of adaptive mutants from the population. We further combined adaptive laboratory evolution with genome shuffling to significantly enhance the desired n-butanol tolerance phenotype. Subsequent transcriptome analysis of the isolated adaptive mutants revealed different mechanisms of n-butanol resistance in different lineages. In one fluorescently-marked subpopulation, members of the Fur regulon were upregulated; which was not observed in the other subpopulation. In addition, genome sequencing of several adaptive mutants revealed the genetic basis for some of the observed transcriptome profiles. We further elucidated the potential role of the iron-related gene in n-butanol tolerance via overexpression and deletion studies and hypothesized that the upregulation of the iron-related genes indirectly led to modifications in the outer membrane, which contributed to enhanced n-butanol tolerance.

Genomic library screens for genes involved in n-butanol tolerance in Escherichia coli.

BACKGROUND: n-Butanol is a promising emerging biofuel, and recent metabolic engineering efforts have demonstrated the use of several microbial hosts for its production. However, most organisms have very low tolerance to n-butanol (up to 2% (v/v)), limiting the economic viability of this biofuel. The rational engineering of more robust n-butanol production hosts relies upon understanding the mechanisms involved in tolerance. However, the existing knowledge of genes involved in n-butanol tolerance is limited. The goal of this study is therefore to identify E. coli genes that are involved in n-butanol tolerance. METHODOLOGY/PRINCIPAL FINDINGS: Using a genomic library enrichment strategy, we identified approximately 270 genes that were enriched or depleted in n-butanol challenge. The effects of these candidate genes on n-butanol tolerance were experimentally determined using overexpression or deletion libraries. Among the 55 enriched genes tested, 11 were experimentally shown to confer enhanced tolerance to n-butanol when overexpressed compared to the wild-type. Among the 84 depleted genes tested, three conferred increased n-butanol resistance when deleted. The overexpressed genes that conferred the largest increase in n-butanol tolerance were related to iron transport and metabolism, entC and feoA, which increased the n-butanol tolerance by 32.8±4.0% and 49.1±3.3%, respectively. The deleted gene that resulted in the largest increase in resistance to n-butanol was astE, which enhanced n-butanol tolerance by 48.7±6.3%. CONCLUSIONS/SIGNIFICANCE: We identified and experimentally verified 14 genes that decreased the inhibitory effect of n-butanol tolerance on E. coli. From the data, we were able to expand the current knowledge on the genes involved in n-butanol tolerance; the results suggest that an increased iron transport and metabolism and decreased acid resistance may enhance n-butanol tolerance. The genes and mechanisms identified in this study will be helpful in the rational engineering of more robust biofuel producers.