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Large-scale Robot-Assisted Genome Shuffling Yields Industrial Saccharomyces Cerevisiae Yeasts With Increased Ethanol Tolerance

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Large-scale Robot-Assisted Genome Shuffling Yields Industrial Saccharomyces Cerevisiae Yeasts With Increased Ethanol Tolerance

Tim Snoek et al. Biotechnol Biofuels.

Abstract

Background: During the final phases of bioethanol fermentation, yeast cells face high ethanol concentrations. This stress results in slower or arrested fermentations and limits ethanol production. Novel Saccharomyces cerevisiae strains with superior ethanol tolerance may therefore allow increased yield and efficiency. Genome shuffling has emerged as a powerful approach to rapidly enhance complex traits including ethanol tolerance, yet previous efforts have mostly relied on a mutagenized pool of a single strain, which can potentially limit the effectiveness. Here, we explore novel robot-assisted strategies that allow to shuffle the genomes of multiple parental yeasts on an unprecedented scale.

Results: Screening of 318 different yeasts for ethanol accumulation, sporulation efficiency, and genetic relatedness yielded eight heterothallic strains that served as parents for genome shuffling. In a first approach, the parental strains were subjected to multiple consecutive rounds of random genome shuffling with different selection methods, yielding several hybrids that showed increased ethanol tolerance. Interestingly, on average, hybrids from the first generation (F1) showed higher ethanol production than hybrids from the third generation (F3). In a second approach, we applied several successive rounds of robot-assisted targeted genome shuffling, yielding more than 3,000 targeted crosses. Hybrids selected for ethanol tolerance showed increased ethanol tolerance and production as compared to unselected hybrids, and F1 hybrids were on average superior to F3 hybrids. In total, 135 individual F1 and F3 hybrids were tested in small-scale very high gravity fermentations. Eight hybrids demonstrated superior fermentation performance over the commercial biofuel strain Ethanol Red, showing a 2 to 7% increase in maximal ethanol accumulation. In an 8-l pilot-scale test, the best-performing hybrid fermented medium containing 32% (w/v) glucose to dryness, yielding 18.7% (v/v) ethanol with a productivity of 0.90 g ethanol/l/h and a yield of 0.45 g ethanol/g glucose.

Conclusions: We report the use of several different large-scale genome shuffling strategies to obtain novel hybrids with increased ethanol tolerance and fermentation capacity. Several of the novel hybrids show best-parent heterosis and outperform the commonly used bioethanol strain Ethanol Red, making them interesting candidate strains for industrial production.

Keywords: Bioethanol; Breeding; Complex phenotype; Ethanol tolerance; Evolutionary engineering; Fermentation; Genome shuffling; Heterosis; Hybridization; Very high gravity.

Figures

Figure 1
Figure 1
Large-scale genotypic and phenotypic screening of Saccharomyces yeasts to select parental strains for genome shuffling. Strains that show good sporulation were clustered according to their genetic relatedness as estimated by interdelta fingerprinting (see ‘Methods’). Phenotypes shown include sporulation capacity, spore viability, and ethanol production from a VHG substrate. Each of these phenotypes was measured for all the strains, and the measurements were then normalized and displayed using a color scale (heat map) as indicated in the figure. Eight genetically divergent heterothallic strains were selected that could sporulate and displayed high spore viability (indicated with arrows and codes P1-P8). This strain set included the commonly-used bioethanol strain Ethanol Red (P7); the best-fermenting strain out of the collection.
Figure 2
Figure 2
Two different genome shuffling strategies used to generate hybrids starting from the eight parental strains. (A) Conceptual outline of targeted and random genome shuffling. Genome shuffling based on random mating (left) allows random mating between spores form the eight parental strains (F1) and between spores derived from genome-shuffled hybrid populations (F2 and F3). Genome shuffling based on targeted mating (right) exploits the selection of true outcrossed hybrids using plasmid-based markers at each stage, ensuring the presence of the eight initial genomes in the final F3 hybrids. For simplicity, homologous chromosomes of the parental strains have been given the same color, although parental strains were heterozygous diploids. (B) Details of the experimental procedures used for genome shuffling strategies. Genome shuffling based on random mating (left) was performed using two different types of selection after each round of mating. First, hybrids were selected for their capacity to grow in the presence of ethanol by first inoculating them into medium containing 5% (v/v) ethanol followed by growth in the presence of 10 to 12% (v/v) ethanol (referred to as ‘growth selection,’ similar to the selection applied for targeted mating). Alternatively, the hybrids were selected for survival in medium containing very high (18 to 22% (v/v)) ethanol levels (‘survival selection’). In parallel to these two approaches, we also carried out shuffling without any selection in between the different rounds of hybridization (‘no selection’). For targeted mating (right), a robot is used to perform specific crosses between the eight parental strains in all pairwise combinations, followed by screening for ethanol tolerance (growth capacity in the presence of ethanol). The best-performing hybrids were used as parental strains for the next round of robot-based targeted mating, and in parallel similar breeding schemes were carried out without applying any selection after each round of shuffling. See ‘Methods’ and Additional file 1: Figure S5 for more details about these procedures.
Figure 3
Figure 3
Genome shuffling based on random mating generates hybrids with increased ethanol tolerance. (A) Growth capacity in the presence of ethanol of clones obtained before selection (F1), after one round (F2) and two rounds of shuffling and selection (F3). Whereas F2 hybrids show a clear increase in growth capacity, F3 hybrids do not show further increases. (B) Same data as Figure 3A for the individual isolates at 12% (v/v) ethanol and the parental strains (n = 2 for each parent). F2 and F3 isolates on average performed better than F1 isolates, but did not show statistical differences between different replicates and generations (unpaired t-test P > 0.05). A, B, and C are biological replicates. (C) Selection for survival in high ethanol yields hybrids with increased survival capacity which further increases after each round of shuffling. Each bar represents the average and standard deviation of three biological replicates, except for F1 19% (v/v) where n = 2. Survival after exposure to 21% (v/v) and 22% (v/v) was only measured for F3 populations. The data for the strongest parental strain (P1) is displayed for 18% (v/v); this strain completely lost its viability after exposure to 19% (v/v). (D) Fermentation performance of F3 populations in YP + 35% (w/v) glucose. The cumulative weight loss, a proxy for CO2 production, during the fermentations is shown. Each line represents the average of two replicate fermentations for the reference strain (Ethanol Red), six replicates for growth-selected and survival-selected populations, or twelve replicates for unselected populations. Error bars represent standard deviations. (E) Selected isolates from several pools of hybrids were tested for their maximal ethanol accumulation in YP + 35% (w/v) glucose. On average, F1 hybrids showed the highest average ethanol production levels. Unselected and growth-selected F3 hybrids on average performed similar, but better than survival-selected F3 hybrids. The dotted line indicates the ethanol production of Ethanol Red. Unpaired t-test: ns, not significant; **P ≤ 0.01; ***P ≤ 0.001.
Figure 4
Figure 4
Schematic overview of targeted genome shuffling. For the first round of targeted genome shuffling (creating pools of F1 hybrids), the eight parental strains (numbered 1 to 8) were crossed in all pairwise combinations, including inbreeding. After screening and selection (see main text), isolated F1 hybrids were used to create three funnels (A, B, C). In each funnel, the F1 hybrids were crossed in all pairwise combinations to make F2 hybrids, followed by screening and selection for ethanol tolerance. For the last round of genome shuffling, F2 hybrids were crossed in such a way that F3 hybrids incorporated genetic material from all eight initial parental strains. Note that these funnel schemes were also carried out for F1 hybrids from the same parental strains that were not selected for growth in the presence of ethanol, and for which no selection was performed in between the different rounds of hybridization.
Figure 5
Figure 5
Genome shuffling based on targeted mating yields hybrids with increased growth and fermentation capacity. (A) The eight parental strains were crossed in all pairwise combinations. Each horizontal line represents the average growth in medium with different concentrations of ethanol for all hybrid populations, as well as the parental strains. The data was normalized and converted to a heat map, and strains were ranked from low to high based on their growth in 13% (v/v) ethanol. (B) Outcrossed F1 hybrids display higher ethanol tolerance than F1 inbreds (Mann-Whitney test: ****P ≤ 0.0001). (C) Most isolated F1 outcrossed hybrids show heterosis for ethanol tolerance, whereas most inbreds perform poorer than their parents (‘inbreeding depression’). Each horizontal line represents the average performance of all single clones from a certain cross, inbred or parental strain on different concentrations of ethanol. Strains were ranked from low to high based on 12% (v/v) ethanol data. (D) F3 hybrids subjected to selection for ethanol tolerance (measured by the capacity to grow in the presence of ethanol) after each round of genome shuffling show higher ethanol tolerance than unselected F3 hybrids (Mann-Whitney test: ****P ≤ 0.0001). The dot plots show the relative growth of all F3 isolates, obtained with and without selection after each round of shuffling, respectively, on 12% (v/v) ethanol. The data from the strongest parental strains (P3, P2, and P7) are shown for comparison. (E) Individual hybrids show different maximal ethanol accumulation in VHG fermentations. F1 hybrids selected for their capacity to grow in the presence of high ethanol levels on average show the highest ethanol production. Next, F3 hybrids subjected to selection after each round of shuffling on average show higher ethanol production that unselected F3 hybrids. The dotted line indicates the ethanol production level of Ethanol Red. Unpaired t-test: *P ≤ 0.05; ****P ≤ 0.0001.
Figure 6
Figure 6
A targeted hybrid (H1) generated by genome shuffling excels in pilot scale fermentations. H1 and three high-ethanol producing industrial strains (Y145, Y116 and Y111) were each inoculated into 8 l VHG medium with 32% (w/v) glucose in a bioreactor. On regular time points the ethanol concentration was determined.

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