Genome-wide association across <i>Saccharomyces cerevisiae</i> strains reveals substantial variation in underlying gene requirements for toxin tolerance

<div><p>Cellulosic plant biomass is a promising sustainable resource for generating alternative biofuels and biochemicals with microbial factories. But a remaining bottleneck is engineering microbes that are tolerant of toxins generated during biomass processing, because mechanisms of toxin defense are only beginning to emerge. Here, we exploited natural diversity in 165 <i>Saccharomyces cerevisiae</i> strains isolated from diverse geographical and ecological niches, to identify mechanisms of hydrolysate-toxin tolerance. We performed genome-wide association (GWA) analysis to identify genetic variants underlying toxin tolerance, and gene knockouts and allele-swap experiments to validate the involvement of implicated genes. In the process of this work, we uncovered a surprising difference in genetic architecture depending on strain background: in all but one case, knockout of implicated genes had a significant effect on toxin tolerance in one strain, but no significant effect in another strain. In fact, whether or not the gene was involved in tolerance in each strain background had a bigger contribution to strain-specific variation than allelic differences. Our results suggest a major difference in the underlying network of causal genes in different strains, suggesting that mechanisms of hydrolysate tolerance are very dependent on the genetic background. These results could have significant implications for interpreting GWA results and raise important considerations for engineering strategies for industrial strain improvement.</p></div

Knockout effects of genes containing SNPs found in GWA.

<p>Genes linked to SNPs implicated by GWA were deleted in one or two genetic backgrounds, tolerant strain YPS128 (A) and sensitive strain YJM1444 (B). Significance was determined by paired T-test (where experiments were paired by replicate date, see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007217#sec010" target="_blank">Methods</a>) with FDR correction compared to respective wild type strain. Asterisks indicate FDR < 0.05 or p< 0.05 (which corresponds to FDR of ~13%), according to the key. Deletion strains in (B) are ordered as in (A); NA indicates missing data due our inability to make the gene deletion in that background. <i>zrt1-adh4Δ</i> indicates the deletion of an intergenic sequence between these genes.</p

SNPs associated with SynH tolerance.

<p>SNPs associated with SynH tolerance.</p

Strain-specific difference for SynH and HT tolerance.

<p>Tolerance to lignocellulosic hydrolysate across strains (left) and across each population (right) measured as glucose consumption in SynH (A) and HT tolerance based on glucose consumption (B), calculated as described in Methods for 165 strains. Individual strains in B were ordered based on the quantitative scores in A. Population distributions shown in the boxplots are indicated for named populations from <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007217#pgen.1007217.g001" target="_blank">Fig 1</a>.</p

<i>LEU3</i> is important for SynH tolerance.

<p>(A) Wild-type YPS128 and a YPS128 <i>leu3Δ</i> mutant were grown in Synthetic Complete medium (SC), SynH without toxins (SynH -HT), or SynH with toxins, and final OD₆₀₀ was measured after 24 hours. (B) Final OD₆₀₀ was also measured in strains grown in media with 10X SC concentration of branched amino acids (leucine, isoleucine, and valine) in SynH -HT and SynH. Data represent average of 3 replicates with standard deviation. Significance was determined by paired t-test.</p

Increased SynH performance in the <i>mne1Δ</i> mutant is independent of oxygen availability.

<p>Wild type YPS128 and the <i>mne1Δ</i> mutant were grown anaerobically as described in Methods, and media was sampled over time to determine (A) cell density, (B) glucose consumption, and (C) ethanol production over time. Plots represent the average and standard deviation of 3 replicates.</p

Genetic diversity found in the 165-strain collection.

<p>The entire collection of high quality SNPs (486,302) was used as input for principal component analysis (PCA) (A) and to generate a neighbor-joining (NJ) tree (B). Populations assigned in circles were defined manually using published population structure data. Strains are color-coded according to genetic similarity, with matching colors between the PCA and NJ tree (generated by Adegenet [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007217#pgen.1007217.ref110" target="_blank">110</a>]). The population and/or niche is represented by the key, with the number of strains in each group indicated in parentheses.</p

Distribution of SNP alleles.

<p>(A) A heat map of the 38 SNPs found in the GWA analysis (columns) in each strain (rows), where the alleles associated with the sensitive or resistance phenotypes are color-coded according to the key. Strains were organized from tolerant (top) to sensitive (bottom). (B) Percent glucose consumed in SynH + HTs was plotted against the number of sensitive alleles identified in each strain. Correlation of the two is indicated by the R² and linear fit line.</p

Little allele-specific contribution to SynH tolerance.

<p>(A) YPS128 strains lacking individual genes were complemented with a plasmid carrying the tolerant allele (T) or the sensitive allele (S) of each gene. Cells were grown in synthetic complete medium (SC) with HTs and nourseothricin (NAT) to allow for drug-based plasmid selection. Significance was determined by paired t-test comparing strains carrying the tolerant versus sensitive allele. Data represent the average and standard deviation of three replicates. (B) Relative phenotype based on reciprocal hemizygosity analysis (RHA) where the ratio of glucose consumption of strains carrying the tolerant versus sensitive allele was calculated across 7 biological replicates. (C) Relative percent glucose consumed in wild-type YJM1444 x YPS128 hybrid and homozygous deletion strains compared to the average of the wild-type YJM1444 x YPS128 hybrids, in SynH as described in Methods. Data represent the average and standard deviation of three replicates. One of the <i>bna6Δ</i> cultures did not grow; the other two replicates looked indistinguishable from the wild-type culture. (D) Phenotypic improvement achieved by crossing strains with diverse phenotypic and genetic characteristics was investigated by measuring percent of glucose consumption in SynH. Significance was determined by paired t-test comparing each hybrid and the most tolerant strain, YPS128.</p

Single-cell RNA sequencing reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress

<div><p>From bacteria to humans, individual cells within isogenic populations can show significant variation in stress tolerance, but the nature of this heterogeneity is not clear. To investigate this, we used single-cell RNA sequencing to quantify transcript heterogeneity in single <i>Saccharomyces cerevisiae</i> cells treated with and without salt stress to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. Leveraging the extensive knowledge of yeast transcriptional regulation, we uncovered significant regulatory variation in individual yeast cells, both before and after stress. We also discovered that a subset of cells appears to decouple expression of ribosomal protein genes from the environmental stress response in a manner partly correlated with the cell cycle but unrelated to the yeast ultradian metabolic cycle. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1, revealed both coordinated and decoupled nucleocytoplasmic shuttling. Together with transcriptomic analysis, our results suggest that cells maintain a cellular filter against decoupled bursts of transcription factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells.</p></div