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Adaptation to High Ethanol Reveals Complex Evolutionary Pathways.

Voordeckers K, Kominek J, Das A, Espinosa-Cantú A, De Maeyer D, Arslan A, Van Pee M, van der Zande E, Meert W, Yang Y, Zhu B, Marchal K, DeLuna A, Van Noort V, Jelier R, Verstrepen KJ - PLoS Genet. (2015)

Bottom Line: Whole-genome sequencing of more than 30 evolved populations and over 100 adapted clones isolated throughout this two-year evolution experiment revealed how a complex interplay of de novo single nucleotide mutations, copy number variation, ploidy changes, mutator phenotypes, and clonal interference led to a significant increase in ethanol tolerance.Although the specific mutations differ between different evolved lineages, application of a novel computational pipeline, PheNetic, revealed that many mutations target functional modules involved in stress response, cell cycle regulation, DNA repair and respiration.Measuring the fitness effects of selected mutations introduced in non-evolved ethanol-sensitive cells revealed several adaptive mutations that had previously not been implicated in ethanol tolerance, including mutations in PRT1, VPS70 and MEX67.

View Article: PubMed Central - PubMed

Affiliation: VIB Laboratory for Systems Biology, Leuven, Belgium.

ABSTRACT
Tolerance to high levels of ethanol is an ecologically and industrially relevant phenotype of microbes, but the molecular mechanisms underlying this complex trait remain largely unknown. Here, we use long-term experimental evolution of isogenic yeast populations of different initial ploidy to study adaptation to increasing levels of ethanol. Whole-genome sequencing of more than 30 evolved populations and over 100 adapted clones isolated throughout this two-year evolution experiment revealed how a complex interplay of de novo single nucleotide mutations, copy number variation, ploidy changes, mutator phenotypes, and clonal interference led to a significant increase in ethanol tolerance. Although the specific mutations differ between different evolved lineages, application of a novel computational pipeline, PheNetic, revealed that many mutations target functional modules involved in stress response, cell cycle regulation, DNA repair and respiration. Measuring the fitness effects of selected mutations introduced in non-evolved ethanol-sensitive cells revealed several adaptive mutations that had previously not been implicated in ethanol tolerance, including mutations in PRT1, VPS70 and MEX67. Interestingly, variation in VPS70 was recently identified as a QTL for ethanol tolerance in an industrial bio-ethanol strain. Taken together, our results show how, in contrast to adaptation to some other stresses, adaptation to a continuous complex and severe stress involves interplay of different evolutionary mechanisms. In addition, our study reveals functional modules involved in ethanol resistance and identifies several mutations that could help to improve the ethanol tolerance of industrial yeasts.

No MeSH data available.


Related in: MedlinePlus

Single mutations present in evolved populations can increase ethanol tolerance of a non-adapted strain.Plots show the average selection coefficient (smut) as a function of ethanol concentration for (A) pca1C1583T, (B) prt1A1384G, (C) ybl059wG479T, (D) intergenic ChrIV A1489310T, (E) hem13G700C, (F) intergenic ChrXII C747403T, (G) hst4G262C, (H) vps70C595A, and (I) mex67G456A. Superscripts denote the exact nucleotide change in each of the mutants tested. YECitrine-tagged mutants were competed with the mCherry-tagged parental strain (orange dots); dye-swap experiments were carried out by competing the mCherry-tagged mutants with the YECitrine parental strain (blue dots), except for (I). Error bars show the S.E.M. from three experimental replicates. Asterisk show P-values from the one-way ANOVA tests of the mean differences in 4–8% ethanol compared to fitness in 0% ethanol: * p < 0.05; ** p < 0.01; ***p < 0.005. P values can be found in S7 Table.
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pgen.1005635.g008: Single mutations present in evolved populations can increase ethanol tolerance of a non-adapted strain.Plots show the average selection coefficient (smut) as a function of ethanol concentration for (A) pca1C1583T, (B) prt1A1384G, (C) ybl059wG479T, (D) intergenic ChrIV A1489310T, (E) hem13G700C, (F) intergenic ChrXII C747403T, (G) hst4G262C, (H) vps70C595A, and (I) mex67G456A. Superscripts denote the exact nucleotide change in each of the mutants tested. YECitrine-tagged mutants were competed with the mCherry-tagged parental strain (orange dots); dye-swap experiments were carried out by competing the mCherry-tagged mutants with the YECitrine parental strain (blue dots), except for (I). Error bars show the S.E.M. from three experimental replicates. Asterisk show P-values from the one-way ANOVA tests of the mean differences in 4–8% ethanol compared to fitness in 0% ethanol: * p < 0.05; ** p < 0.01; ***p < 0.005. P values can be found in S7 Table.

Mentions: These nine SNPs were subsequently introduced into the ancestral haploid strain. The effect of these mutations was assessed by high-throughput competition experiments [64], in 0, 4, 6 and 8% (v/v) EtOH conditions, with glucose as a carbon source (Fig 8, S14 and S15 Figs and S6 Table). Several mutants show a clear increase in fitness, with the fitness effect often depending on the concentration of ethanol in the medium. Most mutants show slightly increased fitness in medium without added ethanol, with further increases in relative fitness with increasing exogeneous ethanol concentrations. Mutants in PRT1 and MEX67 are less fit than the WT in non-ethanol conditions, but show increased fitness in higher ethanol levels. MEX67 is a poly (A) RNA binding protein involved in nuclear mRNA export. PRT1 encodes the eIF3b subunit of the eukaryotic translation initiation factor 3 (eIF3). The increased ethanol tolerance associated with these mutations hints at translation processes as targets of ethanol. Interestingly, a recent study in E. coli showed that ethanol negatively impacts transcription as well as translation [6]. However, if and how mutations in MEX67 and PRT1 might mitigate this effect and contribute to ethanol tolerance remains unknown.


Adaptation to High Ethanol Reveals Complex Evolutionary Pathways.

Voordeckers K, Kominek J, Das A, Espinosa-Cantú A, De Maeyer D, Arslan A, Van Pee M, van der Zande E, Meert W, Yang Y, Zhu B, Marchal K, DeLuna A, Van Noort V, Jelier R, Verstrepen KJ - PLoS Genet. (2015)

Single mutations present in evolved populations can increase ethanol tolerance of a non-adapted strain.Plots show the average selection coefficient (smut) as a function of ethanol concentration for (A) pca1C1583T, (B) prt1A1384G, (C) ybl059wG479T, (D) intergenic ChrIV A1489310T, (E) hem13G700C, (F) intergenic ChrXII C747403T, (G) hst4G262C, (H) vps70C595A, and (I) mex67G456A. Superscripts denote the exact nucleotide change in each of the mutants tested. YECitrine-tagged mutants were competed with the mCherry-tagged parental strain (orange dots); dye-swap experiments were carried out by competing the mCherry-tagged mutants with the YECitrine parental strain (blue dots), except for (I). Error bars show the S.E.M. from three experimental replicates. Asterisk show P-values from the one-way ANOVA tests of the mean differences in 4–8% ethanol compared to fitness in 0% ethanol: * p < 0.05; ** p < 0.01; ***p < 0.005. P values can be found in S7 Table.
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pgen.1005635.g008: Single mutations present in evolved populations can increase ethanol tolerance of a non-adapted strain.Plots show the average selection coefficient (smut) as a function of ethanol concentration for (A) pca1C1583T, (B) prt1A1384G, (C) ybl059wG479T, (D) intergenic ChrIV A1489310T, (E) hem13G700C, (F) intergenic ChrXII C747403T, (G) hst4G262C, (H) vps70C595A, and (I) mex67G456A. Superscripts denote the exact nucleotide change in each of the mutants tested. YECitrine-tagged mutants were competed with the mCherry-tagged parental strain (orange dots); dye-swap experiments were carried out by competing the mCherry-tagged mutants with the YECitrine parental strain (blue dots), except for (I). Error bars show the S.E.M. from three experimental replicates. Asterisk show P-values from the one-way ANOVA tests of the mean differences in 4–8% ethanol compared to fitness in 0% ethanol: * p < 0.05; ** p < 0.01; ***p < 0.005. P values can be found in S7 Table.
Mentions: These nine SNPs were subsequently introduced into the ancestral haploid strain. The effect of these mutations was assessed by high-throughput competition experiments [64], in 0, 4, 6 and 8% (v/v) EtOH conditions, with glucose as a carbon source (Fig 8, S14 and S15 Figs and S6 Table). Several mutants show a clear increase in fitness, with the fitness effect often depending on the concentration of ethanol in the medium. Most mutants show slightly increased fitness in medium without added ethanol, with further increases in relative fitness with increasing exogeneous ethanol concentrations. Mutants in PRT1 and MEX67 are less fit than the WT in non-ethanol conditions, but show increased fitness in higher ethanol levels. MEX67 is a poly (A) RNA binding protein involved in nuclear mRNA export. PRT1 encodes the eIF3b subunit of the eukaryotic translation initiation factor 3 (eIF3). The increased ethanol tolerance associated with these mutations hints at translation processes as targets of ethanol. Interestingly, a recent study in E. coli showed that ethanol negatively impacts transcription as well as translation [6]. However, if and how mutations in MEX67 and PRT1 might mitigate this effect and contribute to ethanol tolerance remains unknown.

Bottom Line: Whole-genome sequencing of more than 30 evolved populations and over 100 adapted clones isolated throughout this two-year evolution experiment revealed how a complex interplay of de novo single nucleotide mutations, copy number variation, ploidy changes, mutator phenotypes, and clonal interference led to a significant increase in ethanol tolerance.Although the specific mutations differ between different evolved lineages, application of a novel computational pipeline, PheNetic, revealed that many mutations target functional modules involved in stress response, cell cycle regulation, DNA repair and respiration.Measuring the fitness effects of selected mutations introduced in non-evolved ethanol-sensitive cells revealed several adaptive mutations that had previously not been implicated in ethanol tolerance, including mutations in PRT1, VPS70 and MEX67.

View Article: PubMed Central - PubMed

Affiliation: VIB Laboratory for Systems Biology, Leuven, Belgium.

ABSTRACT
Tolerance to high levels of ethanol is an ecologically and industrially relevant phenotype of microbes, but the molecular mechanisms underlying this complex trait remain largely unknown. Here, we use long-term experimental evolution of isogenic yeast populations of different initial ploidy to study adaptation to increasing levels of ethanol. Whole-genome sequencing of more than 30 evolved populations and over 100 adapted clones isolated throughout this two-year evolution experiment revealed how a complex interplay of de novo single nucleotide mutations, copy number variation, ploidy changes, mutator phenotypes, and clonal interference led to a significant increase in ethanol tolerance. Although the specific mutations differ between different evolved lineages, application of a novel computational pipeline, PheNetic, revealed that many mutations target functional modules involved in stress response, cell cycle regulation, DNA repair and respiration. Measuring the fitness effects of selected mutations introduced in non-evolved ethanol-sensitive cells revealed several adaptive mutations that had previously not been implicated in ethanol tolerance, including mutations in PRT1, VPS70 and MEX67. Interestingly, variation in VPS70 was recently identified as a QTL for ethanol tolerance in an industrial bio-ethanol strain. Taken together, our results show how, in contrast to adaptation to some other stresses, adaptation to a continuous complex and severe stress involves interplay of different evolutionary mechanisms. In addition, our study reveals functional modules involved in ethanol resistance and identifies several mutations that could help to improve the ethanol tolerance of industrial yeasts.

No MeSH data available.


Related in: MedlinePlus