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Altered sterol composition renders yeast thermotolerant

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Science  03 Oct 2014:
Vol. 346, Issue 6205, pp. 75-78
DOI: 10.1126/science.1258137

Tricks for boosting yeast's ethanol yields

To become a widely used source of fuel, widespread industrial production of ethanol using yeast needs to be simple and efficient. However, two conditions ideal for boosting production—tolerance of higher temperatures and high concentrations of ethanol—have been limiting (see the Perspective by Cheng and Kao). Now, Caspeta et al. have used adaptive laboratory evolution to find yeast strains that can tolerate high temperatures and Lam et al. have identified a route to improve yeast's resistance to high concentrations of ethanol.

Science, this issue p. 75, p. 71; see also p. 35

Abstract

Ethanol production for use as a biofuel is mainly achieved through simultaneous saccharification and fermentation by yeast. Operating at ≥40°C would be beneficial in terms of increasing efficiency of the process and reducing costs, but yeast does not grow efficiently at those temperatures. We used adaptive laboratory evolution to select yeast strains with improved growth and ethanol production at ≥40°C. Sequencing of the whole genome, genome-wide gene expression, and metabolic-flux analyses revealed a change in sterol composition, from ergosterol to fecosterol, caused by mutations in the C-5 sterol desaturase gene, and increased expression of genes involved in sterol biosynthesis. Additionally, large chromosome III rearrangements and mutations in genes associated with DNA damage and respiration were found, but contributed less to the thermotolerant phenotype.

Microbial fermentation of biomass-derived feedstocks represents an attractive solution for production of sustainable liquid transportation fuels (1, 2). About 100 billion liters of ethanol are produced annually by fermentation of mainly sugarcane saccharose and corn starch by the yeast Saccharomyces cerevisiae (3, 4). There is also a growing interest in using this yeast for production of advanced biofuels with properties more similar to those of petroleum-derived fuels, and for using other biomass for fermentation, such as lignocellulose from residual biomass (2, 57). The production of ethanol or advanced biofuels benefits greatly from fermentations at high temperature (≥40°C), because this reduces cooling costs and helps prevent contamination (3, 8). High operating temperature also enables more efficient hydrolysis of the feedstock, thus leading to improved productivities in simultaneous saccharification and fermentation (810). In these processes, thermophilic enzymes and yeast are added simultaneously to ensure concurrent hydrolysis of starch or biomass into monosaccharides, and their further conversion to biofuels by yeast fermentation. However, temperatures ≥34°C seriously impair yeast viability and growth.

Thermotolerance in yeast S. cerevisiae can be induced by short-term exposure to nonlethal stress conditions including low pH, high osmolarity, elevated ethanol concentrations, and superoptimal temperatures (≥37°C) (11, 12). The acquired thermal protection is, however, nonheritable and is attributable to induction of cellular responses including the accumulation of heat-shock proteins (Hsp) and/or trehalose, which can provoke cell cycle arrest at the G1 phase, and low adenosine 3′,5′-monophosphate–protein kinase (cAMP-PK) activity concomitant with reduced glycolytic fluxes (11, 12). Thus, adaptation due to the activation of the heat-shock response is not the most suitable strategy for biofuel production. Industrial thermotolerant yeast strains currently used for bioethanol production were selected in the production processes, where they were exposed to high temperatures for longer periods of time (3, 4). These strains can grow and consume glucose faster at higher temperatures than strains that have just been adapted by stress induction. Although the industrial strains have been used globally for ethanol production, little is known about the genomics of the strains and what makes them thermotolerant (4).

We established three independent yeast populations from three individual clones of the haploid wild-type S. cerevisiae yeast strain CEN.PK113-7D, and we used adaptive laboratory evolution (ALE) to select thermotolerant strains that were extensively characterized (13).

Our ALE approach resulted in three parallel selections: Three clonal populations grew at 39.5 ± 0.3°C for more than 90 days, producing over 300 generations (Fig. 1A). After 326, 344, and 375 generations, the specific growth rate (μ) increased on average 1.57 ± 0.11 times in all three populations. We determined the specific growth rate of nine thermotolerant strains (TTSs), three randomly picked from each population (Fig. 1A). Seven TTSs had very similar growth kinetics at 40 ± 0.1°C under fully aerobic conditions (Fig. 1B). These strains grew on average 1.91 ± 0.12 times faster, consumed glucose on average 1.50 ± 0.2 times faster, and excreted ethanol and glycerol on average 1.6 ± 0.09 and 1.3 ± 0.08 times faster, respectively, than the parental strain (Fig. 1, B and C). The biomass yield on glucose increased by an average of 18 ± 0.5% (Fig. 1D).

Fig. 1 Adaptive laboratory evolution and physiological characterization of thermotolerant S. cerevisiae strains.

(A) Experimental setup for selecting thermotolerant S. cerevisiae strains using adaptive laboratory evolution in shake flasks. Evolved mutants from flask/population 1 have the same sequence (Fig. 2A). Physiological responses in bioreactors at 40 ± 0.1°C are plotted in the graphs (B to D). Samples were taken from bioreactors in the middle exponential phase of growth for transcriptomics profiling using microarrays.

We sequenced the genomes of the seven strains (TT11, TT12, TT13, TT21 TT22, TT31, and TT33) and performed whole-genome transcriptional profiling during exponential growth on glucose in bioreactors at 40 ± 0.1°C. Whole-genome sequencing revealed a total of 30 single-nucleotide variations (SNVs) in 18 genes (tables S1 and S2). The average number of SNVs per genome duplication was 1.9 × 10–9 ± 2.6 × 10–10, and the average number of SNVs per 100 generations was 2.43 ± 0.3, which is higher than that reported for adaptation to other stresses (1.13 to 2.13 per 100 generations) (14). Most SNVs were detected in genes affecting membrane composition and structure, respiration, DNA repair, and replication (Fig. 2A). Nonsense mutations in the C-5 sterol desaturase gene ERG3 were present in all lineages (table S2). Large genetic duplications were also found in five out of the seven strains. These consisted of two different types of segmental duplications of chromosome III (ChrIII), each found in strains isolated from two of the lineages (Fig. 2, B and C). It was previously reported that complete duplication of ChrIII in the diploid S. cerevisiae strains was selected during growth at 39°C, but this reported duplication was unstable and disappeared after 600 generations (15).

Fig. 2 Specific mutations and duplications of chromosome segments were selected independently during the evolution of three populations of S. cerevisiae.

(A) Distribution of 19 genes, with 31 SNVs among 7 TTSs, encoding proteins involved in three cellular processes. (B) Segmental duplications in chromosomes were identified from gene-coverage analysis. (C) TT11 genome shown as an example.

The three evolved yeast strains isolated from population 1, TT11, TT12, and TT13 all had a duplicated ChrIII region containing the HCM1, RRT12, IMG1, IMG2, PER1, and YCR007 genes (fig. S1). A previous study showed that overexpression of these genes contributed to up to 23.5% of the thermotolerant phenotype (15). We did not find that duplications of some of these genes on ChrIII resulted in higher gene transcription, as was shown in (15) (table S3). HSP30, which negatively regulates H(+)-ATPase (adenosine triphosphatase), thereby avoiding excessive consumption of ATP during heat shock (16), was duplicated on ChrIII (in TT31 and TT33) but was expressed less than in the control.

HCM1, CDC39, KRE28, SLK19, DYN2, CGR1, LSM8, LSM2, and PAT1—genes that have an important role in M and G1 phases—were all overexpressed (fig. S1). Products of LSM8, LSM2, PAT1, and PWP2 and RSA4 (ChrIII duplication) perform key tasks in ribosome pre–ribosomal RNA (rRNA) processing and 60S ribosome subunit synthesis (17) and are overexpressed upon DNA damage (18). Furthermore, mutations in genes for cell-cycle check point regulations and DNA damage networks (RAD9, RAD24, and PAN2) (Fig. 2A) could suggest that the DNA damage response may facilitate yeast to grow at superoptimal temperatures. However, TT21 did not accumulate mutations in any of these networks and was as fit at 40°C as other TT strains.

TUP1 and SRB8 (ChrIII duplication) were overexpressed in TT11, TT12, and TT13 (table S3). The Tup1-Cyc8 co-repressor is important for repression of many genes (19); it also interacts with the transcription machinery, including SRB8. Transcription factors YAP6, CIN5, NRG1, and ROX1 (fig. S1), which are regulated by TUP1 and SRB8 and mediate glucose repression and aerobic transcriptional repression, were down-regulated. Higher tolerance to osmotic stress could be related to the duplication of the mitogen-activated protein kinase (MAPK) gene SSK22 (part of the Hog1 signaling pathway) in TT11, TT12, and TT13 strains (fig. S2). The MAPK cascade involved in control of mating was down-regulated in TTSs together with the cell-cycle factor arrest genes FAR1 and STE12 (fig. S2A), which activate genes involved in mating or pseudohyphal and invasive growth pathways, along with the transcription factor TEC1. Consequently, TTSs had fewer invasive phenotypes (fig. S2C).

Twenty-six percent of SNVs located in coding regions resulted in stop codons (table S2), with 66% of those being in the ATP3 and ERG3 genes. ATP3 codes for the γ subunit of the F1 complex of the mitochondrial F1F0-ATP synthase, and ERG3 codes for C-5 sterol desaturase. We reconstructed the point mutations in these genes, in the parental background. The mutation in the ATP synthase gene ATP3 negatively affected thermotolerance, and the strain grew poorly at 40°C (Fig. 3A). By contrast, the reconstructed ERG3 mutations (nonsense mutation at position 185, replacing Tyr185 with a stop codon) conferred to the parental strain up to 86% of the specific growth rate of the TTSs (Fig. 3A). Sterols contribute to the fluidity of lipid membranes and lipid rafts, which are important for many cellular processes including cellular sorting, cytoskeleton organization, and mating (20, 21). Membrane fluidity is also affected by the ratio, composition, and structure of sterols that are found in membranes. Thus, regulation of type and amount of sterols has an important modulatory role and may serve as an adaptive response to variations in temperature (22). Branched sterols such as sitosterol and bended sterol-like lipids such as bacteriohopanetetrol were found to protect membranes of plant cells and Archaea from temperature fluctuations and high temperatures (fig. S3) (22). The thermotolerant strains and the strain with the ERG3 point mutations accumulated total sterols in amounts similar to that accumulated by the wild type (fig. S4). ERG3 deletions have been reported to cause augmented activity of the sterol methyltransferase Erg6 that catalyzes the conversion of zymosterol to fecosterol (23, 24), and we found that the TTSs and the ERG3 reconstructed mutant accumulated the “bended” sterol, fecosterol (Fig. 3C and fig. S3A). Previously, ergosterol substitution by other “flat” sterols such as 8(9),22-ergostadiene-3β-ol or 5,7,22,24(28)-ergostatetraene-3β-ol did not increase thermotolerance in S. cerevisiae (24). This suggests that increased presence of “bended” sterols (as opposed to “flat” sterols that are normally found in membranes) could confer thermotolerance in the evolved S. cerevisiae strains.

Fig. 3 Specific growth rate and total sterols composition of selected and reconstructed thermotolerant S. cerevisiae strains.

(A) Specific growth rate of the selected thermotolerant strain TT11, wild-type strain carrying point-mutation M7 (coding for Erg3Tyr185), wild-type strain carrying point-mutation M22 (coding for Atp3Glu299), and wild-type strain (WT). (B) Sterol analysis was carried out on the same strains. All characterizations were done on strains cultivated in shake-flasks at 39.5° ± 0.3°C in minimal medium with glucose. Samples for sterol analysis in strains TT11, M7, and WT were taken at the end of the exponential phase. (C) Fecosterol and ergosterol three-dimensional structures.

Lack of ergosterol (due to the ERG3 mutations) in the evolved strains induced overexpression of genes involved in sterol biosynthesis from acetyl–coenzyme A (CoA)—i.e., the gene encoding cytosolic acetyl-CoA synthetase ACS2, key genes of the mevalonate pathway (ERG10 and HMG1), and many genes involved in sterol biosynthesis (Fig. 4). There was also increased expression of UPC2, which codes for a sterol regulatory element–-binding protein (SREBP) that regulates expression of genes coding for enzymes involved in sterol biosynthesis. Despite the up-regulation of these genes, the sterol content in TTSs was not changed compared to the parental strain (fig. S4).

Fig. 4 Changes in gene expression and metabolic fluxes in thermotolerant strains.

Transcriptional profiling of TTSs was performed at 40°C in bioreactors and compared to the parental strain in the same conditions. The yeast genome-scale model iIN800 and external fluxes were used to calculate metabolic fluxes, which were then used in combination with transcriptional profiling to analyze changes in flux using the Random sampling algorithm (additional data tables S1 and S2). (A) Gene transcription and metabolic fluxes of the central metabolism are changed in the selected strains (TTSs) when compared to the WT. (B) Gene transcription and metabolic fluxes of the mevalonate pathway and sterol biosynthesis are up-regulated and have increased flux in the selected strains when compared to the WT.

The thermotolerant yeast strains did not metabolize nonfermentable carbon sources and did not show diauxic shift at 40° or 30°C (fig. S5). All evolved strains accumulated mutations in either ATP2 or ATP3 genes that are essential for growth on nonfermentable carbon sources (Fig. 2A and table S2). This suggests that the optimal thermotolerant phenotype could not arise through evolution while oxidative respiration is fully functional, possibly because it would generate more reactive oxygen species (ROS) and induce oxidative stress. Indeed, the thermotolerant strains have lower resistance to oxidative stress induced with H2O2, compared to the parental strain (fig. S6). It has been reported that thermotolerant yeasts are facultative anaerobes susceptible to form respiratory-deficient mutants, in contrast to the psychrophilic yeasts that are strict aerobes (25). Indeed, thermotolerant S. cerevisiae strains generated by short-term exposure to 54°C or adaptation to grow at 40°C also acquired a respiratory-deficient phenotype concomitant with lack of growing on nonfermentable carbon sources (26, 27). The inability to grow on nonfermentative carbon sources in the temperature-tolerant yeast strains is an undesirable trade-off, as this increases the costs associated with propagation of yeast during the industrial process. However, the strain with the reconstructed point mutation in the ERG3 gene, which has a thermotolerant phenotype, has maintained the ability to grow on nonfermentable carbon sources and shows a typical diauxic growth (fig. S7).

Despite the inability of the TTSs to grow on nonfermentable carbon sources, they all had a ~30% increased oxygen uptake rate and increased flux through the respiratory chain (fig. S8). Metabolic flux analysis shows that these strains have residual tricarboxylic acid cycle activity, and the increased oxygen consumption is solely used for oxidation of the cytosolic NADH (nicotinamide adenine dinucleotide, reduced) generated by the increased biomass yield. Consequently, the TTSs have a reduced glycerol yield (fig. S8).

The TTSs have an improved specific glucose consumption rate, which has increased by 60% at 40°C and by 300% at 42°C when compared to the parental strain at 40°C or 42°C. Interestingly, TTSs could consume glucose at temperatures as high as 50°C. The increased glucose uptake rate and the increased ethanol production and yield (fig. S8) result in higher ATP production that supports faster growth. Glucose consumption rate is controlled by transcriptional regulation of glucose transporter genes (HXT) (28). MTH1 interacts with the transcription factor RGT1 and thereby causes transcriptional repression of the HXT genes (29). MTH1 was down-regulated in TTSs, suggesting less repression of the HXT genes, which was consistent with increased expression of the putative hexose transporters Hxt9, Hxt11, and Hxt14. Expression of glycolytic genes was not changed in in TTSs cultivated at 40°C (Fig. 4A).

Our multilayer genome-scale characterization of yeast strains revealed several mechanisms needed to acquire thermotolerance, involving cell cycle, DNA replication stress, and altered sterol metabolism. The latter was the most important, as it appeared in all the isolated strains from three independent populations. Because sterols have an important role in regulation of membrane fluidity, allowing vital process such as vesicular sorting and transport, cytoskeleton organization, and asymmetric growth, we hypothesize that these functions are mainly impaired at high temperature. Substitution of “flat” ergosterol by the “bended” fecosterol in evolved yeast strains may be responsible for the optimal membrane fluidity, as occurs in thermophiles and hyperthermophiles (30).

Supplementary Materials

www.sciencemag.org/content/346/6205/75/suppl/DC1

Materials and Methods

Figs. S1 to S8

Tables S1 to S4

References (3139)

Databases S1 and S2

References and Notes

  1. Materials and methods are available on Science Online
  2. Acknowledgments: This work was funded by the Novo Nordisk Foundation, the European Research Council (grant no. 247013), and Vetenskapsrådet. We acknowledge the Science for Life Laboratory, the National Genomics Infrastructure, and Uppmax for providing assistance in massive parallel sequencing and computational infrastructure. Data are provided in the supplementary materials.
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