Screening and construction of Saccharomyces cerevisiae strains with improved multi-tolerance and bioethanol fermentation performance

Zheng, Dao-Qiong; Wu, Ximei; Tao, Xiang-Lin; Wang, Pin-Mei; Li, Ping; Chi, Xiaoqin; Li, Yudong; Yan, Qingfeng; Zhao, Yong

doi:10.1016/j.biortech.2010.09.122

Cited by 80 publications

(42 citation statements)

References 36 publications

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“…Our results demonstrate that selecting for growth capacity in the presence of ethanol offers an efficient way to perform a first screening to select variants that are more likely to show increased fermentation capacity. Previously, Zheng et al [12] explored the correlation between different industrially relevant phenotypes and did not find a significant correlation between growth in the presence of ethanol and ethanol production. However, we tested a much higher number of different yeast strains (308 versus 15).…”

Section: Discussionmentioning

confidence: 99%

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Large-scale robot-assisted genome shuffling yields industrial Saccharomyces cerevisiae yeasts with increased ethanol tolerance

Snoek¹,

Nicolino²,

Bremt

et al. 2015

Biotechnol Biofuels

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BackgroundDuring 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.ResultsScreening 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.ConclusionsWe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s13068-015-0216-0) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

“…Some researchers used laboratory strains [10,11], which likely do not perform well under industrial conditions. In other studies, the novel hybrids were not tested on a pilot scale [12-15]. Moreover, genome shuffling is often combined with genetic engineering [16,17], making some industrial applications problematic.…”

Section: Introductionmentioning

confidence: 99%

Large-scale robot-assisted genome shuffling yields industrial Saccharomyces cerevisiae yeasts with increased ethanol tolerance

Snoek¹,

Nicolino²,

Bremt

et al. 2015

Biotechnol Biofuels

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“…Although the production of inferior, so-called crippled strains (cf. infra) is a potential disadvantage of genome shuffling because the prevalence of deleterious alleles may result in a majority of variants that perform better at the task they are selected for, but not other important traits, the first proof-of-principle use of a genome-shuffled S. cerevisiae strain in an industrial fermentation environment was recently published (Zheng et al ., 2011a, b). …”

Section: Natural and Artificial Diversitymentioning

confidence: 99%

“…Firstly, it is possible to carry out a prescreening by subjecting the hybrid population to a severe stress by plating the cells on medium that contains for instance high ethanol or acetic acid levels, conditions encountered during fermentation. Next, only fast-growing colonies are tested individually in small-scale fermentations, and only superior hybrids are used for a next round of shuffling (Shi et al ., 2009; Zheng et al ., 2011a, b, 2013a, b; Tao et al ., 2012). Other investigators have instead tried to first improve stress tolerance and found that hybrids generated after multiple rounds of genome shuffling and selection also showed increased general fermentation performance (Wei et al ., 2008; Cao et al ., 2009, 2010, 2012; Hou, 2009; Wang & Hou, 2010; Jingping et al ., 2012; Lu et al ., 2012; Wang et al ., 2012a).…”

Section: Natural and Artificial Diversitymentioning

confidence: 99%

Improving industrial yeast strains: exploiting natural and artificial diversity

Steensels¹,

Snoek²,

Meersman³

et al. 2014

FEMS Microbiol Rev

404

288

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Yeasts have been used for thousands of years to make fermented foods and beverages, such as beer, wine, sake, and bread. However, the choice for a particular yeast strain or species for a specific industrial application is often based on historical, rather than scientific grounds. Moreover, new biotechnological yeast applications, such as the production of second-generation biofuels, confront yeast with environments and challenges that differ from those encountered in traditional food fermentations. Together, this implies that there are interesting opportunities to isolate or generate yeast variants that perform better than the currently used strains. Here, we discuss the different strategies of strain selection and improvement available for both conventional and nonconventional yeasts. Exploiting the existing natural diversity and using techniques such as mutagenesis, protoplast fusion, breeding, genome shuffling and directed evolution to generate artificial diversity, or the use of genetic modification strategies to alter traits in a more targeted way, have led to the selection of superior industrial yeasts. Furthermore, recent technological advances allowed the development of high-throughput techniques, such as ‘global transcription machinery engineering’ (gTME), to induce genetic variation, providing a new source of yeast genetic diversity.

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“…Another strategy for improving fermentation performance of microorganisms is to enhance their tolerance to environmental stress, including thermo-tolerance and inhibitors (e.g., ethanol, acids, furans, phenolics) tolerance [34, [154][155][156]. Various effective strategies, such as random mutagenesis [157], genome shuffling [158][159][160][161], artificial transcription factor engineering [162], global transcription machinery engineering [163][164][165], error-prone whole genome amplification (ep-WGA) [166], have also been developed for this purpose. Among these, genome shuffling is one of the efficient tools to construct combinatorial libraries of complex progeny from a few previously selected parental strains.…”

Section: Strain Improvementmentioning

confidence: 99%

Bioconversion of Lignocellulose into Bioethanol: Process Intensification and Mechanism Research

Huang

et al. 2011

Bioenerg. Res.

125

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Biofuels produced from lignocellulosic biomass can significantly reduce the energy dependency on fossil fuels and the resulting effects on environment. In this respect, cellulosic ethanol as an alternative fuel has the potential to become a viable energy source in the near future. Over the past few decades, tremendous effort has been undertaken to make cellulosic ethanol cost competitive with conventional fossil fuels. The pretreatment step is always necessary to deconstruct the recalcitrant structures and to make cellulose more accessible to enzymes. A large number of pretreatment technologies involving physical, chemical, biological, and combined approaches have been developed and tested at the pilot scale. Furthermore, various strategies and methods, including multi-enzyme complex, non-catalytic additives, enzyme recycling, high solids operation, design of novel bioreactors, and strain improvement have also been implemented to improve the efficiency of subsequent enzymatic hydrolysis and fermentation. These technologies provide significant opportunities for lower total cost, thus making large-scale production of cellulosic ethanol possible. Meanwhile, many researchers have focused on the key factors that limit cellulose hydrolysis, and analyzing the reaction mechanisms of cellulase. This review describes the most recent advances on process intensification and mechanism research of pretreatment, enzymatic hydrolysis, and fermentation during the production of cellulosic ethanol.

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Screening and construction of Saccharomyces cerevisiae strains with improved multi-tolerance and bioethanol fermentation performance

Cited by 80 publications

References 36 publications

Large-scale robot-assisted genome shuffling yields industrial Saccharomyces cerevisiae yeasts with increased ethanol tolerance

Large-scale robot-assisted genome shuffling yields industrial Saccharomyces cerevisiae yeasts with increased ethanol tolerance

Improving industrial yeast strains: exploiting natural and artificial diversity

Bioconversion of Lignocellulose into Bioethanol: Process Intensification and Mechanism Research

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