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

Supplementary Materials for

Altered sterol composition renders yeast thermotolerant

Luis Caspeta, Yun Chen, Payam Ghiaci, Amir Feizi, Steen Buskov, Björn M. Hallström, Dina Petranovic, Jens Nielsen*

*Corresponding author: E-mail: nielsenj@chalmers.se

Published 3 October 2014, Science 346, 75 (2014)

DOI: 10.1126/science.1258137

This PDF file includes:

Materials and Methods Figs. S1 to S8 Tables S1 to S4 Captions for databases S1 and S2 References

Other Supplementary Material for this manuscript includes the following: (available at www.sciencemag.org/content/346/6205/75/suppl/DC1)

Databases S1 and S2 as zipped archives

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Materials and Methods 1 Adaptive laboratory evolution (ALE): yeast strains, media and growth conditions 2

Laboratory evolution experiments with Saccharomyces cerevisiae wild-type haploid 3 yeast strain CEN.PK113-7D were carried out by serial dilutions in shake flasks. Cells 4 from three independent colonies were grown for one day at 39.5±0.3°C and then diluted 5 by factors from 1:6 to 1:10, into fresh medium (4-7 generations per dilution) to give an 6 optical density at 600nm (OD600) of about 0.2. This procedure was repeated daily, for 90 7 days, until a significant increase (50%) in the specific growth rate was detected (see also 8 Fig. 1A). Aeration by agitation was set at 200 revolutions per minute (rpm) in an orbital 9 incubator. 10

ALE was performed on three clonal populations (thermotolerant; TT1, TT2, TT3) 11 and three strains were randomly selected from each line of evolution: from the first, 12 TT11, TT12 and TT13, from the second TT21, TT22 and TT23, and from the third TT31, 13 TT31 and TT33. The specific growth rate of the nine TTSs was determined in shake-14 flasks with the parental strain as control. Out of the nine strains, seven (TT11, TT12, 15 TT13, TT21, TT22, TT31 and TT33) were sequenced and characterized in bioreactors at 16 40±0.1°C. TT23 and TT32 did not grow after three freezing/unfreezing cycles and were 17 discarded from cultivations in bioreactors. 18

The medium used for adaptive laboratory evolution and characterization of 19 thermotolerant yeast strains (TTSs) and parental strain in shake flasks and bioreactors 20 was the same. This contained 2% glucose and 5 g (NH3)2SO4, 3 g (NH4)2PO4 and 0.5 g 21 MgSO4 per liter, in addition to 1 mL of trace elements solution and 1 mL of vitamin 22 solution. The trace element solution contained, per liter (pH=4): EDTA (sodium salt), 23 15.0 g; ZnSO4•7H2O, 4.5 g; MnCl2•2H2O, 0.84 g; CoCl2•6H2O, 0.3 g; CuSO4•5H2O, 0.3 24 g; Na2MoO4•2H2O, 0.4 g; CaCl2•2H2O, 4.5 g; FeSO4•7H2O, 3.0 g; H3BO3, 1.0 g; and KI, 25 0.10 g.). The vitamin solution contained, per liter (pH=6.5): biotin, 0.05 g; p-amino 26 benzoic acid, 0.2 g; nicotinic acid, 1 g; Ca-pantothenate, 1 g; pyridoxine-HCl, 1 g; 27 thiamine-HCl, 1 g and myo-inositol, 25 g. Initial pH of the medium was 5.2. 28

29 Cultivations in bioreactors 30

Aerobic batch cultivations of parental and TTSs strains were performed in 1.0 L 31 vessels using the Dasbox System (DASGIP, Juelich, Deutschland), containing 0.7 L of 32 media. DASware Software Solutions (DASGIP, Juelich, Deutschland) was used to 33 monitor and control fermentation variables. Temperature was set up to 30°C, 40°C or 34 42°C according to the aim of the study. Air flow rate was kept constant at 0.5 volumes of 35 air per volume of media (vvm). Initial agitation was fixed at 500 rpm and increased by 36 demand to keep dissolved oxygen (DO) tension higher than 40% of air saturation. 37 Monitoring of oxygen consumption and carbon dioxide production was performed with 38 the DasGip fedbatch pro gas analysis system (DASGIP, Juelich, Deutschland). Automatic 39 control of pH at 5.0 was carried out with 2 M KOH. 40

41 Analytics: Biomass, glucose consumption, fermentation metabolites and sterol analyses 42

Biomass production, glucose uptake and fermentation metabolites: Cultivation 43 samples for biomass, glucose and fermentation metabolites analyses were taken from 44 bioreactors and shake flasks experiments and processed at 4˚C every 1-2 hrs. Optical 45

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density of sample was determined at 600nm. Samples were vacuum filtered and the 1 resulting biomass was washed twice with isotonic solution, dried in a microwave oven for 2 15 min at medium power and kept in a desiccator until constant weight. Supernatant was 3 stored at -20°C for further analysis of fermentation metabolites by HPLC. An Aminex 4 HPX-87H column (Bio-Rad, California, USA) connected to refractive index and 5 photodiode array detectors was used to separate and quantify glucose and fermentation 6 metabolites. A mobile phase of 8 mM H2SO4 was used at 0.5 mL/min, and the assay was 7 run at 50°C. Sigma Aldrich pure glucose, organic acids, glycerol and ethanol were used 8 to construct the calibration curve used to quantify these compounds in the culture. 9

Sterol analysis: Yeast cells were collected by centrifugation (3000g for 5 min at 10 4°C) taken from shake flasks cultivations and washed twice with distilled water. These 11 samples were then frozen at -80°C and freeze-dried. Dried cells were weighed before 12 sterol analysis. Ten mg of dried yeast cells were suspended in methanol:1-propanol (1:1) 13 and homogenized using an Ultra Turrax homogenizer for 5 min. After centrifugation, the 14 supernatant was transferred to HPLC vials. Reference sterols were obtained from Sigma 15 Aldrich. A standard curve were prepared in Methanol:1-Propanol (1:1) at concentrations 16 from 0.001 mg/L to 5.00 mg/L. 17

The samples were analyzed by liquid chromatography–mass spectrometry (LC-MS). 18 The system comprised of an Accela 1250 gradient pump (Thermo Scientific, MA, USA), 19 a Thermo PAL-HTC Accela autosampler with 100µL loop (Thermo Scientific, MA, 20 USA), a Phenomenex TS-130 column oven (Phenomenex, California, USA) and a Q 21 Exactive mass spectrometer with APCI-source (Thermo Scientific, MA, USA). The 22 column was a HSS T3, 2.1 x 50mm, 1.8µm particles (Waters, MA, USA). Injection 23 volume 10µL. Flow rate was 0.500mL/min and column temperature maintained at 50°C. 24 The mobile phase comprised a gradient from 0.1% formic acid in LC-MS grade water, to 25 0.1% formic acid in LC-MS grade acetonitrile. 20% methanol was added to the mobile 26 phase. At the end of the run the column was washed using 1-propanol. From 0.0 min to 1 27 min, mobile phase was water: acetonitrile:methanol (20:60:20) with 0.1% formic acid. 28 From 1 to 4 min, the composition was linearly changed to water: acetonitrile:methanol 29 (1:80:20) with 0.1% formic acid. From 4 to 8 min, the composition was linearly changed 30 to water: acetonitrile:methanol (0:80:20) with 0.1% formic acid. From 8 to 12 min, the 31 composition was linearly changed to 1-propanol:methanol (80:20), then increased to 32 100% 1-propanol in 4 minutes and then returned to initial settings. The Q Exactive mass 33 spectrometer was operated in positive scan mode (scan range 350 – 1000 m/z) at 34 resolution 70000. Sheath gas was 50, Aux gas flow rate 20 and sweep gas flow rate 0. 35 Spray voltage was 5 kV, capillary temperature was 250°C and probe temperature 400°C. 36 Sterols were quantified from external standards after extraction of respective ion 37 chromatograms (20 ppm window). 38

39 Total mRNA extraction, microarray preparation and processing 40

Samples of 10 mL were taken in the middle of exponential phase of cultivation in 41 bioreactors at 40°C for transcriptome profiling. They were quickly put on ice and 42 centrifuged at 3000g for 5 min and 4°C. Supernatant was discarded and biomass pellet 43 was frozen in liquid nitrogen, and then stored at -80°C. Total RNA was extracted from 44 pellets using the RiboPure™-Yeast Kit (Ambion, TX, USA) with the help of RNAse free 45

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solvents (Ambion, TX, USA). Affymetrix Yeast Genome 2.0 Array was used for 1 transcriptome analysis. 2

The CEL-files were preprocessed using Bioconductor (31) and R version 2.15.3 The 3 Affymetrix chip description file (CDF-file) was obtained from the microarray developers 4 and imported to R using the Bioconductor package makecdfenv. The raw data were 5 normalized using Probe Logarithmic Intensity Error (PLIER) normalization (32) using 6 only perfect match probes (pm-only). The moderated t-statistic was applied to identify 7 pairwise differences in gene expression between each of the evolved strains. Correction 8 for multiple testing of the p-values was done using the Benjamini-Hochberg’s method 9 (33). The cut off <0.05 was used for adjusted p-value to get differentially expressed genes 10 between each of the two conditions. The PIANO package was used for reporter GO-term 11 and gene set enrichment analysis (34). heatmap.plus and VennDiagram (35) packages 12 were used for generating heat maps and Venn plots. 13

14 DNA sequencing 15

Total chromosomal DNA was extracted with the E.Z.N.A. Yeast DNA Kit 16 (OMEGA, GA, USA) from TTS and parental yeast strains that were cultivated in yeast-17 peptone-dextrose 2% (YPD) medium in shake flasks. Libraries for genome sequencing 18 were prepared using the Illumina TruSeq DNA sample preparation kit and sequenced 19 multiplexed on a single lane on an Illumina Hiseq2000, with paired-end, 2x100 bp reads. 20 The reads were mapped to the CEN.PK113-7D reference genome (http://cenpk.tudelft.nl) 21 using MosaikAligner version 2.1.32 (http://code.google.com/p/mosaik-aligner/). Each 22 sample gave over 30 million mappable reads, providing an average mapped sequence 23 coverage above 240x for all samples. After alignment, potential indels were identified 24 and realigned using the Genome Analysis Toolkit (GATK) (36) tools 25 RealignerTargetCreator and IndelRealigner, whereby suspected PCR duplicates were 26 discarded using the Picard (http://picard.sourceforge.net) tool MarkDuplicates. Finally 27 single nucleotide variants and small indels were detected using GATK UnifiedGenotyper. 28

Potential large scale chromosomal duplications were examined by recording the read 29 depth at each position and deviations from the normal read depth were detected by 30 plotting histograms of read depths over each chromosome. In order to pin-point the 31 breakpoints of the chromosomal duplications a sliding window of 1000 bp, moving 200 32 bp per step, was used to approximate where the read depth starts to deviate, and to 33 visualize the duplications in plots showing the read depth over the length of the 34 chromosome. 35

36 Re-construction of selected point mutations 37

The wild-type CEN.PK113-7D strain used as the initial parental strain for adaptive 38 laboratory evolution was used as background. The wild type target gene was replaced by 39 the amdSYM marker cassette (37). This was done by fusion PCR of a homologous 40 sequence upstream of the gene, amdSYM marker cassette and a homologous sequence 41 downstream of the gene. The obtained cassette was subsequently transformed to the wild 42 type CEN.PK113-7D strain for targeted homologous recombination. The replacement 43 was checked by PCR. In the next step, the replaced gene was reconstructed by the design 44 of specific point mutation primers. The cassette containing a homologous sequence 45 upstream of the gene, site-directed mutated gene and a homologous sequence 46

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downstream of the gene was created through fusion PCR and transformed into the 1 corresponding amdSYM strain. The counter selection was done using fluorocaetamide. 2 The introduced point mutation was checked by sequencing. All primers used for 3 construction of site-directed mutagenesis are listed in Table S4. 4

5 Metabolic flux analysis 6

We used the RAVEN toolbox (38) and the Random Sampling algorithm (39) to 7 identify enzymes which show significant correlations between changes in their 8 expressions at 40°C in both the wild type and TTSs and the rate of their associated 9 reactions. We first constrained the genome scale metabolic model (GEM) iIN800 with 10 external experimental fluxes (e.g. specific rates of growth, glucose consumption and 11 ethanol production) obtained from cultivations in bioreactors. Specific rates of CO2 12 production and O2 consumption were not used to constrain the GEM. Using the RAVEN 13 toolbox, the constrained GEM was transformed into a SBML model which was used in 14 simulations with the random sampling toolbox to calculate a two columns matrix with 15 average fluxes and variances for every reaction. These results were used to evaluate 16 standard deviations between two conditions and get Z scores for variations in every 17 reaction of the GEM. Scores from the Student t analysis of gene expression between wild 18 type and TTSs cultivated at 40°C were used to calculate p-values. Both Z scores and p-19 values were used to identify reactions showing better correlation between the flux and the 20 expression changes in wild type and TTS. 21

22

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1

Fig. S1 2 Genes duplicated by ChrIII segment duplication and their influence on cell cycle stages. 3 Names of duplicated genes are underlined. Genes that are regulated by the duplicated 4 genes are also shown. Cell cycle stages are specified at the right side. HMC1, TUP1 and 5 SRB8 are positive (arrow) or negative (bar) regulators of listed genes. Red and blue 6 quadrants represent gene up- or down-regulation. 7 8

9

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1

Fig. S2 2 Overview of the MAPK pathways in yeast (A) and their involvement in resistance of 3 TTSs to osmotic stress (B) and invasive growth phenotype (C). The bar graph shows 4 results from challenging yeast cells growing at 30°C with 1 M of KCl. The specific 5 growth rate under osmotic stress was divided by the specific growth rate at 30°C without 6 stress and multiplied by 100. The pathway figure shows a few genes of the HOG pathway 7 (shown to the right) being up-regulated in the TTS, whereas some genes of the other two 8 MAPK pathways were down-regulated (red and blue squares). 9

10

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1

Fig. S3 2 Comparison of sterol structures from yeast (A) with sitosterol, cholesterol and 3 bacteriohopanetetrol (B) from plants, animals and Archaea, respectively. 3D sterols 4 structures were generated with ChemSpider (http://www.chemspider.com/). 5

6

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1

2

Fig. S4 3 Total sterol content in the parental strain CEN.PK113-7D (WT), evolved strain TT11 and 4 the parental strain with the reconstructed point mutation (M7) in ERG3 (Erg3Tyr185). 5

6

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1

2

Fig. S5 3 Oxygen and carbon dioxide transfer rates of TTSs and WT cultivated in bioreactors at 4 40°C (A) and 30°C (B) with 2% glucose. TTSs and wild type strains did not show 5 diauxic shift at 40°C. WT strain, but not the TTSs, consumed ethanol, glycerol and 6 acetate after glucose depletion at 30°C which increased the carbon dioxide production 7 rate. 8

9

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1

Fig. S6 2 Effect of 1 mM H2O2 on growth of TTSs and parental strains. All yeast strains grew at 3 30°C in minimal medium with glucose until OD600 ~1 and then were challenged with 1 4 mM H2O2 at the time indicated with the arrow (dashed lines). Cultivations at 30°C 5 without stress are showed as continuous lines. Standard deviations from three 6 independent cultivations were less than 6%. 7

8

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1

Fig. S7 2 Cultivation of TTSs, parental strain (WT) and parental with mutation in ERG3 (M7, 3 Erg3Tyr185). All strains were cultivated in shake flaks using minimal medium with glucose 4 at 30°C. Error bars corresponding to standard deviations from three independent 5 cultivations are less than 6% 6

7

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1

Fig. S8 2 Results from the macroscopic metabolic flux analysis. Using measured specific rates, the 3 fluxes to the different products were calculated, relative to the uptake of 100 mmole of 4 glucose. The flux from pyruvate to carbon dioxide was calculated from a balance around 5 the specific carbon dioxide production rate and assuming that there is formed 0.1 mole 6 CO2/C-mol biomass. The flux to biomass is in unit mgDCW/mmole of glucose. In all cases 7 the carbon and degree of reduction balances closed within 92-95%. The specific glucose 8 uptake rate, in mmole/gDCW/h, is shown in the box at the upper left corner. Color code for 9 the strains is shown on the box at the lower left corner. All data are shown as average 10 values for the analyzed strains. 11 12

13

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Table S1. 1 Substitution rates and SNVs analysis of genome rearrangements in S. cerevisiae CEN.PK 2 113-7D after growth and selection at 39.5±0.3°C. 3 4

Generations Strain

Single nucleotide polymorphisms *µb &µg Total Synonymous Stop-

codons Noncoding

Flask 1 326 TT11 7 0 3 1 1.7E-09 0.021 TT12 7 0 3 1 1.7E-09 0.021 TT13 8 0 3 2 1.7E-09 0.021

Flask 2 344 TT21 7 0 1 1 1.6E-09 0.020 TT22 9 0 2 1 2.1E-09 0.026

Flask 3 375 TT31 10 1 1 2 2.1E-09 0.027 TT33 11 2 1 2 2.3E-09 0.029

*µb=substitution per base pair per genome duplication; & µg=substitution per genome 5 per genome duplication.6

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Table S2. Single nucleotide variations in thermotolerant S. cerevisiae strains (TTS) isolated from three populations after selection at 39.5±0.3°C.

Location Population 1 Population 2 Population 3 Mutation Gene Effect on protein TT11 TT12 TT13 TT21 TT22 TT31 TT32 chr2:311159 SNV SNV AGA -> ATA ATP3 Arg -> Ile chr2:311179 SNV SNV SNV GAA -> TAA ATP3 novel stop codon chr2:333591 SNV AAG -> GAG RFS1 chr3:287736 SNV Non-coding chr4:436674 SNV SNV SNV Non-coding chr4:442511 SNV Non-coding chr4:902216 SNV SNV SNV CGA -> TGA RAD9 novel stop codon chr5:101560 SNV SNV TCT -> TAT YEL025C Ser -> Tyr chr5:536329 SNV SNV AGT -> AAT RAD24 Ser -> Asn chr7:328799 SNV SNV G -> T tRNA chr7:332322 SNV ACG -> ATG PAN2 Thr -> Met chr7:792854 SNV SNV SNV CCC -> CTC CCM1 Pro -> Leu chr7:1005999 SNV AAA -> AGA MTM1 Lys -> Arg chr9:142223 SNV 300-400 bp upstream of YIL117C, YIL116W chr10:141047 SNV CCT->TCT LCB3 Pro -> Ser chr10:141123 SNV SNV AGT -> AAT LCB3 Ser -> Asn chr10:141267 SNV SNV SNV CTC -> CCC LCB3 Leu -> Pro chr10:361283 SNV SNV 54 bp upstream of YJL036W chr10:631255 SNV SNV GTC -> TTC ATP2 Val -> Phe chr11:56193 SNV ATC -> ATT TOR2 Synonymous (Ile) chr11:303015 SNV SNV Non-coding chr12:233249 SNV SNV SNV CAG ->TAG ERG3 novel stop codon chr12:233299 SNV SNV TAC -> TAA ERG3 novel stop codon chr12:233656 SNV SNV TAC -> TAA ERG3 novel stop codon chr12:356038 SNV Non-coding chr13:356445 SNV CCT -> TCT CSM3 Pro -> Ser chr14:632586 SNV TCG -> TCA VPS27 Synonymous (Ser) chr15:172171 SNV TCC -> CCC IRA2 Ser -> Pro chr15:294904 SNV TCA -> TAA CMK2 novel stop codon chr16:31233 SNV CAA -> CAG MDL2 Synonymous (Gln)

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Table S3. Expression of genes duplicated by ChrIII segment duplication, from TTSs TT11, TT12 and TT13 isolated in population one, and TT31 and TT33 from population three. Genes in duplicated ChrIII regions of TT11, TT12 and TT13 Gene Log FC P.Value adj.P.Val TAF2 0.5651050 0.00129 0.012404 IMG1 0.3618632 0.02016 0.075643 RSC6 0.5579463 0.00181 0.015362 CTR86 0.6566859 0.00036 0.005312 PWP2 0.6647965 0.00066 0.007980 BUD31 0.4894658 0.00468 0.028858 HCM1 0.3941344 0.00769 0.039756 TUP1 0.5117957 0.00141 0.013188 CDC39 0.5694420 0.00043 0.005888 CDC50 0.6796011 0.00103 0.010892 PER1 0.5373062 0.00360 0.024490 BUD23 0.6833280 0.00101 0.010690 YCR043C 0.6149857 0.00036 0.005312 RRT12 0.2721203 0.00282 0.021116 ARE1 0.8847944 0.00003 0.001124 YCR051W 0.5260012 0.00466 0.028767 THR4 0.3633245 0.02917 0.096825 YIH1 0.4496406 0.00820 0.041684 TAH1 0.5685929 0.00070 0.008275 YCR061W 0.5459060 0.00108 0.011209 RAD18 0.7574614 0.00008 0.001971 SED4 0.6529552 0.00015 0.003085 ATG15 0.3064119 0.01794 0.070146 CPR4 0.5283127 0.00283 0.021156 IMG2 0.4340913 0.00573 0.033028 RSA4 0.6396765 0.00069 0.008214 SSK22 0.5481683 0.02473 0.086666 YCR073W-A 0.4299161 0.01960 0.074187 ERS1 0.6562146 0.00084 0.009527 YCR075W-A 0.8156254 0.00001 0.000493 FUB1 0.5593663 0.00223 0.017797 PTC6 0.4866302 0.00312 0.022370 SRB8 0.4825278 0.00445 0.027796 AHC2 0.5884770 0.00017 0.003269 TRX3 0.5897081 0.00028 0.004488 CSM1 0.6726712 0.00556 0.032428 YCR087C-A 0.7376025 0.00028 0.004547 ABP1 0.5047722 0.00125 0.012197 YCR090C 0.8077813 0.00002 0.000929 KIN82 0.6031530 0.00160 0.014155 MSH3 0.6301797 0.00017 0.003281 OCA4 0.8494927 0.00005 0.001433

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Table S3 continuation. Genes in duplicated ChrIII regions of TT31 and TT33 Gene Log FC P.Value adj.P.Val YCR007C 0.221531 0.129191 0.271291 SAT4 0.137794 0.390679 0.564832 RVS161 0.188953 0.168465 0.324036 ADY2 0.032018 0.680668 0.801489 ADP1 0.164616 0.233597 0.404699 PGK1 0.002400 0.953858 0.973307 POL4 0.420531 0.017341 0.068704 YCR015C 0.411885 0.028988 0.096656 MAK32 0.287224 0.035973 0.111029 MAK31 0.367724 0.024270 0.085386 YCR020C-A 0.460934 0.024702 0.086618 YCR020W-B 0.502113 0.013742 0.058780 HSP30 -0.175170 0.383932 0.557908 YCR023C 0.307866 0.029666 0.097472 PMP1 -0.055970 0.743624 0.846981 YCR024C-A 0.149793 0.050086 0.140649 NPP1 0.116357 0.459917 0.626511 RHB1 0.203146 0.119437 0.256806

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Table S4. Primers used for the reconstruction of selected mutants. Name Target Sequence AM1UF ATP3-Up ACCAAATGTTTTCCACAAAAAGGGC AM1UR ATP3-Up GTATTCTGGGCCTCCATGTCTGGTGGCACATTACGGAGC AM1DF ATP3-Down GAATGCTGGTCGCTATACTGTACTGGTGCTTCCTCTTTG AM1DR ATP3-Down TCCAAGTCTCTGTATAAGGGAAC A1F amdSYM GCTCCGTAATGTGCCACCAGACATGGAGGCCCAGAATAC A1R amdSYM CAAAGAGGAAGCACCAGTACAGTATAGCGACCAGCATTC M11 ATP3-Up TGCTATCAAATACATACTAAGGAGAA M12 ATP3 E298STOP CCAGTAATAATATCAACCAGTTAATTAG M13 ATP3 E298STOP ACAAGCTGTCATTACTAATTAACTGGTTG M14 ATP3-Down CTTGATTGGGTTTTGGAGCTGGA AM7UF ERG3-Up ACAGCCTTTTACAGCCCAGCA AM7UR ERG 3-Up GTATTCTGGGCCTCCATGTCAAGACCAAATCCATATCTC AM7DF ERG 3-Down GAATGCTGGTCGCTATACTGTGCCTTGTTTGTCTCATCT AM7DR ERG 3-Down CTGGCTTATAGAAGTTAAGGAAGGTG A7F amdSYM GAGATATGGATTTGGTCTTGACATGGAGGCCCAGAATAC A7R amdSYM AGATGAGACAAACAAGGCACAGTATAGCGACCAGCATTC M71 ERG 3-Up ACAGCCTTTTACAGCCCAG M72 ERG 3 Y185STOP AAGATGAAAGTGAATTACTCG M73 ERG 3 Y185STOP GGAAGCTCATTATCGAGTAATTCAC M74 ERG 3-Down AACCTTCTGTATTGTGCTCATAG

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Additional Data table S1 (separate file) Transcriptional analysis of gene expression from wild type and thermotolerant yeast strains cultivated at 40°C in bioreactors.

Additional Data table S2 (separate file) Flux balance analysis. We used the random sampling algorithm to reveal whether transcriptional changes are associated with changes in metabolic fluxes, and discern regulation of key enzymes.

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