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

Premature aging in aneuploid yeast is caused in part by aneuploidy-induced defects in Ribosome Quality Control

Premature aging is a hallmark of Down syndrome, caused by trisomy of human chromosome 21, but the reason is unclear and difficult to study in humans. We used an aneuploid model in wild yeast to show that chromosome amplification disrupts nutrient-induced cell-cycle arrest, quiescence entry, and healthy aging, across genetic backgrounds and amplified chromosomes. We discovered that these defects are due in part to aneuploidy-induced dysfunction in Ribosome Quality Control (RQC). Compared to euploids, aneuploids entering quiescence display aberrant ribosome profiles, accumulate RQC intermediates, and harbor an increased load of protein aggregates. Although they have normal proteasome capacity, aneuploids show signs of ubiquitin dysregulation, which impacts cyclin abundance to disrupt arrest. Remarkably, inducing ribosome stalling in euploids produces similar aberrations, while up-regulating limiting RQC subunits or proteins in ubiquitin metabolism alleviates many of the aneuploid defects. Our results provide implications for other aneuploidy disorders including Down syndrome.

Saccharomyces cerevisiae strains performing similarly during fermentation of lignocellulosic hydrolysates show pronounced differences in transcriptional stress responses

Improving our understanding of the transcriptional changes of Saccharomyces cerevisiae during fermentation of lignocellulosic hydrolysates is crucial for the creation of more efficient strains to be used in biorefineries. We performed RNA sequencing of a CEN.PK laboratory strain, two industrial strains (KE6-12 and Ethanol Red), and two wild-type isolates of the LBCM collection when cultivated anaerobically in wheat straw hydrolysate. Many of the differently expressed genes identified among the strains have previously been reported to be important for tolerance to lignocellulosic hydrolysates or inhibitors therein. Our study demonstrates that stress responses typically identified during aerobic conditions such as glutathione metabolism, osmotolerance, and detoxification processes also are important for anaerobic processes. Overall, the transcriptomic responses were largely strain dependent, and we focused our study on similarities and differences in the transcriptomes of the LBCM strains. The expression of sugar transporter-encoding genes was higher in LBCM31 compared with LBCM109 that showed high expression of genes involved in iron metabolism and genes promoting the accumulation of sphingolipids, phospholipids, and ergosterol. These results highlight different evolutionary adaptations enabling S. cerevisiae to strive in lignocellulosic hydrolysates and suggest novel gene targets for improving fermentation performance and robustness.

IMPORTANCE

The need for sustainable alternatives to oil-based production of biochemicals and biofuels is undisputable. Saccharomyces cerevisiae is the most commonly used industrial fermentation workhorse. The fermentation of lignocellulosic hydrolysates, second-generation biomass unsuited for food and feed, is still hampered by lowered productivities as the raw material is inhibitory for the cells. In order to map the genetic responses of different S. cerevisiae strains, we performed RNA sequencing of a CEN.PK laboratory strain, two industrial strains (KE6-12 and Ethanol Red), and two wild-type isolates of the LBCM collection when cultivated anaerobically in wheat straw hydrolysate. While the response to inhibitors of S. cerevisiae has been studied earlier, this has in previous studies been done in aerobic conditions. The transcriptomic analysis highlights different evolutionary adaptations among the different S. cerevisiae strains and suggests novel gene targets for improving fermentation performance and robustness.

Metabolic engineering of a stable haploid strain derived from lignocellulosic inhibitor tolerant Saccharomyces cerevisiae natural isolate YB-2625

BACKGROUND

Significant genetic diversity exists across Saccharomyces strains. Natural isolates and domesticated brewery and industrial strains are typically more robust than laboratory strains when challenged with inhibitory lignocellulosic hydrolysates. These strains also contain genes that are not present in lab strains and likely contribute to their superior inhibitor tolerance. However, many of these strains have poor sporulation efficiencies and low spore viability making subsequent gene analysis, further metabolic engineering, and genomic analyses of the strains challenging. This work aimed to develop an inhibitor tolerant haploid with stable mating type from S. cerevisiae YB-2625, which was originally isolated from bagasse.

RESULTS

Haploid spores isolated from four tetrads from strain YB-2625 were tested for tolerance to furfural and HMF. Due to natural mutations present in the HO-endonuclease, all haploid strains maintained a stable mating type. One of the haploids, YRH1946, did not flocculate and showed enhanced tolerance to furfural and HMF. The tolerant haploid strain was further engineered for xylose fermentation by integration of the genes for xylose metabolism at two separate genomic locations (ho∆ and pho13∆). In fermentations supplemented with inhibitors from acid hydrolyzed corn stover, the engineered haploid strain derived from YB-2625 was able to ferment all of the glucose and 19% of the xylose, whereas the engineered lab strains performed poorly in fermentations.

CONCLUSIONS

Understanding the molecular mechanisms of inhibitor tolerance will aid in developing strains with improved growth and fermentation performance using biomass-derived sugars. The inhibitor tolerant, xylose fermenting, haploid strain described in this work has potential to serve as a platform strain for identifying pathways required for inhibitor tolerance, and for metabolic engineering to produce fuels and chemicals from undiluted lignocellulosic hydrolysates.

Gene-by-environment interactions influence the fitness cost of gene copy-number variation in yeast

Variation in gene copy number can alter gene expression and influence downstream phenotypes; thus copy-number variation provides a route for rapid evolution if the benefits outweigh the cost. We recently showed that genetic background significantly influences how yeast cells respond to gene overexpression, revealing that the fitness costs of copy-number variation can vary substantially with genetic background in a common-garden environment. But the interplay between copy-number variation tolerance and environment remains unexplored on a genomic scale. Here, we measured the tolerance to gene overexpression in four genetically distinct Saccharomyces cerevisiae strains grown under sodium chloride stress. Overexpressed genes that are commonly deleterious during sodium chloride stress recapitulated those commonly deleterious under standard conditions. However, sodium chloride stress uncovered novel differences in strain responses to gene overexpression. West African strain NCYC3290 and North American oak isolate YPS128 are more sensitive to sodium chloride stress than vineyard BC187 and laboratory strain BY4743. Consistently, NCYC3290 and YPS128 showed the greatest sensitivities to overexpression of specific genes. Although most genes were deleterious, hundreds were beneficial when overexpressed-remarkably, most of these effects were strain specific. Few beneficial genes were shared between the sodium chloride-sensitive isolates, implicating mechanistic differences behind their sodium chloride sensitivity. Transcriptomic analysis suggested underlying vulnerabilities and tolerances across strains, and pointed to natural copy-number variation of a sodium export pump that likely contributes to strain-specific responses to overexpression of other genes. Our results reveal extensive strain-by-environment interactions in the response to gene copy-number variation, raising important implications for the accessibility of copy-number variation-dependent evolutionary routes under times of stress.

High quality de novo genome assembly of the non-conventional yeast Kazachstania bulderi describes a potential low pH production host for biorefineries

Kazachstania bulderi is a non-conventional yeast species able to grow efficiently on glucose and δ-gluconolactone at low pH. These unique traits make K. bulderi an ideal candidate for use in sustainable biotechnology processes including low pH fermentations and the production of green chemicals including organic acids. To accelerate strain development with this species, detailed information of its genetics is needed. Here, by employing long read sequencing we report a high-quality phased genome assembly for three strains of K. bulderi species, including the type strain. The sequences were assembled into 12 chromosomes with a total length of 14 Mb, and the genome was fully annotated at structural and functional levels, including allelic and structural variants, ribosomal array and mating type locus. This high-quality reference genome provides a resource to advance our fundamental knowledge of biotechnologically relevant non-conventional yeasts and to support the development of genetic tools for manipulating such strains towards their use as production hosts in biotechnological processes.

Gene-by-environment interactions influence the fitness cost of gene copy-number variation in yeast

Variation in gene copy number can alter gene expression and influence downstream phenotypes; thus copy-number variation (CNV) provides a route for rapid evolution if the benefits outweigh the cost. We recently showed that genetic background significantly influences how yeast cells respond to gene over-expression (OE), revealing that the fitness costs of CNV can vary substantially with genetic background in a common-garden environment. But the interplay between CNV tolerance and environment remains unexplored on a genomic scale. Here we measured the tolerance to gene OE in four genetically distinct Saccharomyces cerevisiae strains grown under sodium chloride (NaCl) stress. OE genes that are commonly deleterious during NaCl stress recapitulated those commonly deleterious under standard conditions. However, NaCl stress uncovered novel differences in strain responses to gene OE. West African strain NCYC3290 and North American oak isolate YPS128 are more sensitive to NaCl stress than vineyard BC187 and laboratory strain BY4743. Consistently, NCYC3290 and YPS128 showed the greatest sensitivities to gene OE. Although most genes were deleterious, hundreds were beneficial when overexpressed - remarkably, most of these effects were strain specific. Few beneficial genes were shared between the NaCl-sensitive isolates, implicating mechanistic differences behind their NaCl sensitivity. Transcriptomic analysis suggested underlying vulnerabilities and tolerances across strains, and pointed to natural CNV of a sodium export pump that likely contributes to strain-specific responses to OE of other genes. Our results reveal extensive strain-by-environment interaction in the response to gene CNV, raising important implications for the accessibility of CNV-dependent evolutionary routes under times of stress.

Genomic and Molecular Identification of Genes Contributing to the Caspofungin Paradoxical Effect in Aspergillus fumigatus

Aspergillus fumigatus is a deadly opportunistic fungal pathogen responsible for ~100,000 annual deaths. Azoles are the first line antifungal agent used against A. fumigatus, but azole resistance has rapidly evolved making treatment challenging. Caspofungin is an important second-line therapy against invasive pulmonary aspergillosis, a severe A. fumigatus infection. Caspofungin functions by inhibiting β-1,3-glucan synthesis, a primary and essential component of the fungal cell wall. A phenomenon termed the caspofungin paradoxical effect (CPE) has been observed in several fungal species where at higher concentrations of caspofungin, chitin replaces β-1,3-glucan, morphology returns to normal, and growth rate increases. CPE appears to occur in vivo, and it is therefore clinically important to better understand the genetic contributors to CPE. We applied genomewide association (GWA) analysis and molecular genetics to identify and validate candidate genes involved in CPE. We quantified CPE across 67 clinical isolates and conducted three independent GWA analyses to identify genetic variants associated with CPE. We identified 48 single nucleotide polymorphisms (SNPs) associated with CPE. We used a CRISPR/Cas9 approach to generate gene deletion mutants for seven genes harboring candidate SNPs. Two null mutants, ΔAfu3g13230 and ΔAfu4g07080 (dscP), resulted in reduced basal growth rate and a loss of CPE. We further characterized the dscP phosphatase-null mutant and observed a significant reduction in conidia production and extremely high sensitivity to caspofungin at both low and high concentrations. Collectively, our work reveals the contribution of Afu3g13230 and dscP in CPE and sheds new light on the complex genetic interactions governing this phenotype. IMPORTANCE This is one of the first studies to apply genomewide association (GWA) analysis to identify genes involved in an Aspergillus fumigatus phenotype. A. fumigatus is an opportunistic fungal pathogen that causes hundreds of thousands of infections and ~100,000 deaths each year, and antifungal resistance has rapidly evolved in this species. A phenomenon called the caspofungin paradoxical effect (CPE) occurs in some isolates, where high concentrations of the drug lead to increased growth rate. There is clinical relevance in understanding the genetic basis of this phenotype, since caspofungin concentrations could lead to unintended adverse clinical outcomes in certain cases. Using GWA analysis, we identified several interesting candidate polymorphisms and genes and then generated gene deletion mutants to determine whether these genes were important for CPE. Two of these mutant strains (ΔAfu3g13230 and ΔAfu4g07080/ΔdscP) displayed a loss of the CPE. This study sheds light on the genes involved in clinically important phenotype CPE.

High-throughput approaches to functional characterization of genetic variation in yeast

Expansion of sequencing efforts to include thousands of genomes is providing a fundamental resource for determining the genetic diversity that exists in a population. Now, high-throughput approaches are necessary to begin to understand the role these genotypic changes play in affecting phenotypic variation. Saccharomyces cerevisiae maintains its position as an excellent model system to determine the function of unknown variants with its exceptional genetic diversity, phenotypic diversity, and reliable genetic manipulation tools. Here, we review strategies and techniques developed in yeast that scale classic approaches of assessing variant function. These approaches improve our ability to better map quantitative trait loci at a higher resolution, even for rare variants, and are already providing greater insight into the role that different types of mutations play in phenotypic variation and evolution not just in yeast but across taxa.

Extensive simulations assess the performance of genome-wide association mapping in various Saccharomyces cerevisiae subpopulations

With the advent of high throughput sequencing technologies, genome-wide association studies (GWAS) have become a powerful paradigm for dissecting the genetic origins of the observed phenotypic variation. We recently completely sequenced the genome of 1011 Saccharomyces cerevisiae isolates, laying a strong foundation for GWAS. To assess the feasibility and the limits of this approach, we performed extensive simulations using five selected subpopulations as well as the total set of 1011 genomes. We measured the ability to detect the causal genetic variants involved in Mendelian and more complex traits using a linear mixed model approach. The results showed that population structure is well accounted for and is not the main problem when the sample size is high enough. While the genetic determinant of a Mendelian trait is easily mapped in all studied subpopulations, discrepancies are seen between datasets when performing GWAS on a complex trait in terms of detection, false positive and false negative rate. Finally, we performed GWAS on the different defined subpopulations using a real quantitative trait (resistance to copper sulfate) and showed the feasibility of this approach. The performance of each dataset depends simultaneously on several factors such as sample size, relatedness and population evolutionary history.

This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’.

Strategies to increase tolerance and robustness of industrial microorganisms

The development of a cost-competitive bioprocess requires that the cell factory converts the feedstock into the product of interest at high rates and yields. However, microbial cell factories are exposed to a variety of different stresses during the fermentation process. These stresses can be derived from feedstocks, metabolism, or industrial production processes, limiting production capacity and diminishing competitiveness. Improving stress tolerance and robustness allows for more efficient production and ultimately makes a process more economically viable. This review summarises general trends and updates the most recent developments in technologies to improve the stress tolerance of microorganisms. We first look at evolutionary, systems biology and computational methods as examples of non-rational approaches. Then we review the (semi-)rational approaches of membrane and transcription factor engineering for improving tolerance phenotypes. We further discuss challenges and perspectives associated with these different approaches.

Population genomics provides insights into the genetic basis of adaptive evolution in the mushroom-forming fungus Lentinula edodes

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We detected three subgroups of L. edodes with robust phenotypic differentiation.

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The three subgroups were diverged 36,871 generations ago.

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L. edodes cultivars in China might originate from the vicinity of Northeast China.

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We dissected the genetic basis of adaptive evolution in L. edodes.

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Genes related to fruiting body development are involved in adaptive evolution.

Introduction

Mushroom-forming fungi comprise diverse species that develop complex multicellular structures. In cultivated species, both ecological adaptation and artificial selection have driven genome evolution. However, little is known about the connections among genotype, phenotype and adaptation in mushroom-forming fungi.

Objectives

This study aimed to (1) uncover the population structure and demographic history of Lentinula edodes, (2) dissect the genetic basis of adaptive evolution in L. edodes, and (3) determine if genes related to fruiting body development are involved in adaptive evolution.

Methods

We analyzed genomes and fruiting body-related traits (FBRTs) in 133 L. edodes strains and conducted RNA-seq analysis of fruiting body development in the YS69 strain. Combined methods of genomic scan for divergence, genome-wide association studies (GWAS), and RNA-seq were used to dissect the genetic basis of adaptive evolution.

Results

We detected three distinct subgroups of L. edodes via single nucleotide polymorphisms, which showed robust phenotypic and temperature response differentiation and correlation with geographical distribution. Demographic history inference suggests that the subgroups diverged 36,871 generations ago. Moreover, L. edodes cultivars in China may have originated from the vicinity of Northeast China. A total of 942 genes were found to be related to genetic divergence by genomic scan, and 719 genes were identified to be candidates underlying FBRTs by GWAS. Integrating results of genomic scan and GWAS, 80 genes were detected to be related to phenotypic differentiation. A total of 364 genes related to fruiting body development were involved in genetic divergence and phenotypic differentiation.

Conclusion

Adaptation to the local environment, especially temperature, triggered genetic divergence and phenotypic differentiation of L. edodes. A general model for genetic divergence and phenotypic differentiation during adaptive evolution in L. edodes, which involves in signal perception and transduction, transcriptional regulation, and fruiting body morphogenesis, was also integrated here.

Natural variation in the consequences of gene overexpression and its implications for evolutionary trajectories

Copy number variation through gene or chromosome amplification provides a route for rapid phenotypic variation and supports the long-term evolution of gene functions. Although the evolutionary importance of copy-number variation is known, little is understood about how genetic background influences its tolerance. Here, we measured fitness costs of over 4000 overexpressed genes in 15 Saccharomyces cerevisiae strains representing different lineages, to explore natural variation in tolerating gene overexpression (OE). Strain-specific effects dominated the fitness costs of gene OE. We report global differences in the consequences of gene OE, independent of the amplified gene, as well as gene-specific effects that were dependent on the genetic background. Natural variation in the response to gene OE could be explained by several models, including strain-specific physiological differences, resource limitations, and regulatory sensitivities. This work provides new insight on how genetic background influences tolerance to gene amplification and the evolutionary trajectories accessible to different backgrounds.

Stress tolerance enhancement via SPT15 base editing in Saccharomyces cerevisiae

BACKGROUND

Saccharomyces cerevisiae is widely used in traditional brewing and modern fermentation industries to produce biofuels, chemicals and other bioproducts, but challenged by various harsh industrial conditions, such as hyperosmotic, thermal and ethanol stresses. Thus, its stress tolerance enhancement has been attracting broad interests. Recently, CRISPR/Cas-based genome editing technology offers unprecedented tools to explore genetic modifications and performance improvement of S. cerevisiae.

RESULTS

Here, we presented that the Target-AID (activation-induced cytidine deaminase) base editor of enabling C-to-T substitutions could be harnessed to generate in situ nucleotide changes on the S. cerevisiae genome, thereby introducing protein point mutations in cells. The general transcription factor gene SPT15 was targeted, and total 36 mutants with diversified stress tolerances were obtained. Among them, the 18 tolerant mutants against hyperosmotic, thermal and ethanol stresses showed more than 1.5-fold increases of fermentation capacities. These mutations were mainly enriched at the N-terminal region and the convex surface of the saddle-shaped structure of Spt15. Comparative transcriptome analysis of three most stress-tolerant (A140G, P169A and R238K) and two most stress-sensitive (S118L and L214V) mutants revealed common and distinctive impacted global transcription reprogramming and transcriptional regulatory hubs in response to stresses, and these five amino acid changes had different effects on the interactions of Spt15 with DNA and other proteins in the RNA Polymerase II transcription machinery according to protein structure alignment analysis.

CONCLUSIONS

Taken together, our results demonstrated that the Target-AID base editor provided a powerful tool for targeted in situ mutagenesis in S. cerevisiae and more potential targets of Spt15 residues for enhancing yeast stress tolerance.

Stress modulation as a means to improve yeasts for lignocellulose bioconversion

The second-generation (2G) fermentation environment for lignocellulose conversion presents unique challenges to the fermentative organism that do not necessarily exist in other industrial fermentations. While extreme osmotic, heat, and nutrient starvation stresses are observed in sugar- and starch-based fermentation environments, additional pre-treatment-derived inhibitor stress, potentially exacerbated by stresses such as pH and product tolerance, exist in the 2G environment. Furthermore, in a consolidated bioprocessing (CBP) context, the organism is also challenged to secrete enzymes that may themselves lead to unfolded protein response and other stresses. This review will discuss responses of the yeast Saccharomyces cerevisiae to 2G-specific stresses and stress modulation strategies that can be followed to improve yeasts for this application. We also explore published -omics data and discuss relevant rational engineering, reverse engineering, and adaptation strategies, with the view of identifying genes or alleles that will make positive contributions to the overall robustness of 2G industrial strains. KEYPOINTS: • Stress tolerance is a key driver to successful application of yeast strains in biorefineries. • A wealth of data regarding stress responses has been gained through omics studies. • Integration of this knowledge could inform engineering of fit for purpose strains.

Variation of the response to metal ions and nonsense-mediated mRNA decay across different Saccharomyces cerevisiae genetic backgrounds

Regulation of mRNA steady-state levels is important in controlling gene expression particularly in response to environmental stimuli. This allows cells to rapidly respond to environment changes. The highly conserved nonsense-mediated mRNA decay (NMD) pathway was initially identified as a pathway that degrades aberrant mRNAs. NMD is now recognized as a pathway with additional functions including precisely regulating the expression of select natural mRNAs. Majority of these natural mRNAs encode fully functional proteins. Regulation of natural mRNAs by NMD is activated by NMD targeting features and environmental cues. Here, we show that Saccharomyces cerevisiae strains from three genetic backgrounds respond differentially to NMD depending on the environmental stimuli. We found that wild type and NMD mutant W303a, BY4741, and RM11-1a yeast strains respond similarly to copper in the environment but respond differentially to toxic cadmium. Furthermore, the PCA1 alleles encoding different mRNAs from W303a and RM11-1a strains are regulated similarly by NMD in response to the bio-metal copper but differentially in response to toxic cadmium.

Genome-Wide Association for Itraconazole Sensitivity in Non-resistant Clinical Isolates of Aspergillus fumigatus

Aspergillus fumigatus is a potentially lethal opportunistic pathogen that infects over ~200,000 people and causes ~100,000 deaths per year globally. Treating A. fumigatus infections is particularly challenging because of the recent emergence of azole-resistance. The majority of studies focusing on the molecular mechanisms underlying azole resistance have examined azole-resistant isolates. However, isolates that are susceptible to azoles also display variation in their sensitivity, presenting a unique opportunity to identify genes contributing to azole sensitivity. Here, we used genome-wide association (GWA) analysis to identify loci involved in azole sensitivity by analyzing the association between 68,853 SNPs and itraconazole (ITCZ) minimum inhibitory concentration (MIC) in 76 clinical isolates of A. fumigatus from Japan. Population structure analysis suggests the presence of four distinct populations, with ITCZ MICs distributed relatively evenly across populations. We independently conducted GWA when treating ITCZ MIC as a quantitative trait and a binary trait, and identified two SNPs with strong associations in both analyses. These SNPs fell within the coding regions of Afu2g02220 and Afu2g02140. We functionally validated Afu2g02220 by knocking it out using a CRISPR/Cas9 approach, because orthologs of this gene are involved in sterol modification and ITCZ targets the ergosterol biosynthesis pathway. Knockout strains displayed no difference in growth compared to the parent strain in minimal media, yet a minor but consistent inhibition of growth in the presence of 0.15 μg/ml ITCZ. Our results suggest that GWA paired with efficient gene deletion is a powerful and unbiased strategy for identifying the genetic basis of complex traits in A. fumigatus.

CRISpy-Pop: A Web Tool for Designing CRISPR/Cas9-Driven Genetic Modifications in Diverse Populations

CRISPR/Cas9 is a powerful tool for editing genomes, but design decisions are generally made with respect to a single reference genome. With population genomic data becoming available for an increasing number of model organisms, researchers are interested in manipulating multiple strains and lines. CRISpy-pop is a web application that generates and filters guide RNA sequences for CRISPR/Cas9 genome editing for diverse yeast and bacterial strains. The current implementation designs and predicts the activity of guide RNAs against more than 1000 Saccharomyces cerevisiae genomes, including 167 strains frequently used in bioenergy research. Zymomonas mobilis, an increasingly popular bacterial bioenergy research model, is also supported. CRISpy-pop is available as a web application (https://CRISpy-pop.glbrc.org/) with an intuitive graphical user interface. CRISpy-pop also cross-references the human genome to allow users to avoid the selection of guide RNAs with potential biosafety concerns. Additionally, CRISpy-pop predicts the strain coverage of each guide RNA within the supported strain sets, which aids in functional population genetic studies. Finally, we validate how CRISpy-pop can accurately predict the activity of guide RNAs across strains using population genomic data.

Impact of stress-response related transcription factor overexpression on lignocellulosic inhibitor tolerance of Saccharomyces cerevisiae environmental isolates

Numerous transcription factor genes associated with stress response are upregulated in Saccharomyces cerevisiae grown in the presence of inhibitors that result from pretreatment processes to unlock simple sugars from biomass. To determine if overexpression of transcription factors could improve inhibitor tolerance in robust S. cerevisiae environmental isolates as has been demonstrated in S. cerevisiae haploid laboratory strains, transcription factors were overexpressed at three different expression levels in three S. cerevisiae environmental isolates. Overexpression of the YAP1 transcription factor in these isolates did not lead to increased growth rate or reduced lag in growth, and in some cases was detrimental, when grown in the presence of either lignocellulosic hydrolysates or furfural and 5-hydroxymethyl furfural individually. The expressed Yap1p localized correctly and the expression construct improved inhibitor tolerance of a laboratory strain as previously reported, indicating that lack of improvement in the environmental isolates was due to factors other than nonfunctional expression constructs or mis-folded protein. Additional stress-related transcription factors, MSN2, MSN4, HSF1, PDR1, and RPN4, were also overexpressed at three different expression levels and all failed to improve inhibitor tolerance. Transcription factor overexpression alone is unlikely to be a viable route toward increased inhibitor tolerance of robust environmental S. cerevisiae strains.

Multi-Faceted Systems Biology Approaches Present a Cellular Landscape of Phenolic Compound Inhibition in Saccharomyces cerevisiae

Synthetic biology has played a major role in engineering microbial cell factories to convert plant biomass (lignocellulose) to fuels and bioproducts by fermentation. However, the final product yield is limited by inhibition of microbial growth and fermentation by toxic phenolic compounds generated during lignocellulosic pre-treatment and hydrolysis. Advances in the development of systems biology technologies (genomics, transcriptomics, proteomics, metabolomics) have rapidly resulted in large datasets which are necessary to obtain a holistic understanding of complex biological processes underlying phenolic compound toxicity. Here, we review and compare different systems biology tools that have been utilized to identify molecular mechanisms that modulate phenolic compound toxicity in Saccharomyces cerevisiae. By focusing on and comparing functional genomics and transcriptomics approaches we identify common mechanisms potentially underlying phenolic toxicity. Additionally, we discuss possible ways by which integration of data obtained across multiple unbiased approaches can result in new avenues to develop yeast strains with a significant improvement in tolerance to phenolic fermentation inhibitors.

Mitochondrial-nuclear coadaptation revealed through mtDNA replacements in Saccharomyces cerevisiae

BACKGROUND

Mitochondrial function requires numerous genetic interactions between mitochondrial- and nuclear- encoded genes. While selection for optimal mitonuclear interactions should result in coevolution between both genomes, evidence for mitonuclear coadaptation is challenging to document. Genetic models where mitonuclear interactions can be explored are needed.

RESULTS

We systematically exchanged mtDNAs between 15 Saccharomyces cerevisiae isolates from a variety of ecological niches to create 225 unique mitochondrial-nuclear genotypes. Analysis of phenotypic profiles confirmed that environmentally-sensitive interactions between mitochondrial and nuclear genotype contributed to growth differences. Exchanges of mtDNAs between strains of the same or different clades were just as likely to demonstrate mitonuclear epistasis although epistatic effect sizes increased with genetic distances. Strains with their original mtDNAs were more fit than strains with synthetic mitonuclear combinations when grown in media that resembled isolation habitats.

CONCLUSIONS

This study shows that natural variation in mitonuclear interactions contributes to fitness landscapes. Multiple examples of coadapted mitochondrial-nuclear genotypes suggest that selection for mitonuclear interactions may play a role in helping yeasts adapt to novel environments and promote coevolution.

QTL analysis of natural Saccharomyces cerevisiae isolates reveals unique alleles involved in lignocellulosic inhibitor tolerance

Decoding the genetic basis of lignocellulosic inhibitor tolerance in Saccharomyces cerevisiae is crucial for rational engineering of bioethanol strains with enhanced robustness. The genetic diversity of natural strains present an invaluable resource for the exploration of complex traits of industrial importance from a pan-genomic perspective to complement the limited range of specialised, tolerant industrial strains. Natural S. cerevisiae isolates have lately garnered interest as a promising toolbox for engineering novel, genetically encoded tolerance phenotypes into commercial strains. To this end, we investigated the genetic basis for lignocellulosic inhibitor tolerance of natural S. cerevisiae isolates. A total of 12 quantitative trait loci underpinning tolerance were identified by next-generation sequencing linked bulk-segregant analysis of superior interbred pools. Our findings corroborate the current perspective of lignocellulosic inhibitor tolerance as a multigenic, complex trait. Apart from a core set of genetic variants required for inhibitor tolerance, an additional genetic background-specific response was observed. Functional analyses of the identified genetic loci revealed the uncharacterised ORF, YGL176C and the bud-site selection XRN1/BUD13 as potentially beneficial alleles contributing to tolerance to a complex lignocellulosic inhibitor mixture. We present evidence for the consideration of both regulatory and coding sequence variants for strain improvement.

Effects of a high-cultivation temperature on the physiology of three different Yarrowia lipolytica strains

Despite the increasing relevance, ranging from academic research to industrial applications, only a limited number of non-conventional, oleaginous Yarrowia lipolytica strains are characterized in detail. Therefore, we analyzed three strains in regard to their metabolic and physiological properties, especially with respect to important characteristics of a production strain. By investigating different cultivation conditions and media compositions, similarities and differences between the distinct strain backgrounds could be derived. Especially sugar alcohol production, as well as an agglomeration of cells were found to be connected with growth at high temperatures. In addition, sugar alcohol production was independent of high substrate concentrations under these conditions. To investigate the genotypic basis of particular traits, including growth characteristics and metabolite concentrations, genomic analysis were performed. We found sequence variations for one third of the annotated proteins but no obvious link to all phenotypic features.

Improvement of cis,cis-Muconic Acid Production in Saccharomyces cerevisiae through Biosensor-Aided Genome Engineering

Muconic acid is a potential platform chemical for the production of nylon, polyurethanes, and terephthalic acid. It is also an attractive functional copolymer in plastics due to its two double bonds. At this time, no economically viable process for the production of muconic acid exists. To harness novel genetic targets for improved production of cis,cis-muconic acid (CCM) in the yeast Saccharomyces cerevisiae, we employed a CCM-biosensor coupled to GFP expression with a broad dynamic response to screen UV-mutagenesis libraries of CCM-producing yeast. Via fluorescence activated cell sorting we identified a clone Mut131 with a 49.7% higher CCM titer and 164% higher titer of biosynthetic intermediate-protocatechuic acid (PCA). Genome resequencing of the Mut131 and reverse engineering identified seven causal missense mutations of the native genes (PWP2, EST2, ATG1, DIT1, CDC15, CTS2, and MNE1) and a duplication of two CCM biosynthetic genes, encoding dehydroshikimate dehydratase and catechol 1,2-dioxygenase, which were not recognized as flux controlling before. The Mut131 strain was further rationally engineered by overexpression of the genes encoding for PCA decarboxylase and AROM protein without shikimate dehydrogenase domain (Aro1p^ΔE), and by restoring URA3 prototrophy. The resulting engineered strain produced 20.8 g/L CCM in controlled fed-batch fermentation, with a yield of 66.2 mg/g glucose and a productivity of 139 mg/L/h, representing the highest reported performance metrics in a yeast for de novo CCM production to date and the highest production of an aromatic compound in yeast. The study illustrates the benefit of biosensor-based selection and brings closer the prospect of biobased muconic acid.

The genetic basis of aneuploidy tolerance in wild yeast

Aneuploidy is highly detrimental during development yet common in cancers and pathogenic fungi – what gives rise to differences in aneuploidy tolerance remains unclear. We previously showed that wild isolates of Saccharomyces cerevisiae tolerate chromosome amplification while laboratory strains used as a model for aneuploid syndromes do not. Here, we mapped the genetic basis to Ssd1, an RNA-binding translational regulator that is functional in wild aneuploids but defective in laboratory strain W303. Loss of SSD1 recapitulates myriad aneuploidy signatures previously taken as eukaryotic responses. We show that aneuploidy tolerance is enabled via a role for Ssd1 in mitochondrial physiology, including binding and regulating nuclear-encoded mitochondrial mRNAs, coupled with a role in mitigating proteostasis stress. Recapitulating ssd1Δ defects with combinatorial drug treatment selectively blocked proliferation of wild-type aneuploids compared to euploids. Our work adds to elegant studies in the sensitized laboratory strain to present a mechanistic understanding of eukaryotic aneuploidy tolerance.

Membrane Fluidity of Saccharomyces cerevisiae from Huangjiu (Chinese Rice Wine) Is Variably Regulated by OLE1 To Offset the Disruptive Effect of Ethanol

An evolution and resequencing strategy was used to research the genetic basis of Saccharomyces cerevisiae BR20 (with 18 vol% ethanol tolerance) and the evolved strain F23 (with 25 vol% ethanol tolerance). Whole-genome sequencing and RNA sequencing (RNA-seq) indicated that the enhanced ethanol tolerance under 10 vol% ethanol could be attributed to amino acid metabolism, whereas 18 vol% ethanol tolerance was due to fatty acid metabolism. Ultrastructural analysis indicated that F23 exhibited better membrane integrity than did BR20 under ethanol stress. At low concentrations (<5 vol%), the partition of ethanol into the membrane increased the membrane fluidity, which had little effect on cell growth. However, the toxic effects of medium and high ethanol concentrations (5 to 20 vol%) tended to decrease the membrane fluidity. Under high ethanol stress (>10 vol%), the highly tolerant strain was able to maintain a relatively constant fluidity by increasing the content of unsaturated fatty acid (UFA), whereas less-tolerant strains show a continuous decrease in fluidity and UFA content. OLE1, which was identified as the only gene with a differential single-nucleotide polymorphism (SNP) mutation site related to fatty acid metabolism, was significantly changed in response to ethanol. The role of OLE1 in membrane fluidity was positively validated in its overexpressed transformants. Therefore, OLE1 lowered the rate of decline in membrane fluidity and thus enabled the yeast to better fight the deleterious effects of ethanol.IMPORTANCE Yeasts with superior ethanol tolerance are desirable for winemakers and wine industries. In our previous work, strain F23 was evolved with superior ethanol tolerance and fermentation activity to improve the flavor profiles of Chinese rice wine. Therefore, exploring the genomic variations and ethanol tolerance mechanism of strain F23 could contribute to an understanding of its effect on the flavor characteristics in the resulting Chinese rice wine. The cellular membrane plays a vital role in the ethanol tolerance of yeasts; however, how the membrane is regulated to fight the toxic effect of ethanol remains to be elucidated. This study suggests that the membrane fluidity is variably regulated by OLE1 to offset the disruptive effect of ethanol. Current work will help develop more ethanol-tolerant yeast strains for wine industries and contribute to a deep understanding of its high flavor-producing ability.

Quantitative Trait Nucleotides Impacting the Technological Performances of Industrial Saccharomyces cerevisiae Strains

The budding yeast Saccharomyces cerevisiae is certainly the prime industrial microorganism and is related to many biotechnological applications including food fermentations, biofuel production, green chemistry, and drug production. A noteworthy characteristic of this species is the existence of subgroups well adapted to specific processes with some individuals showing optimal technological traits. In the last 20 years, many studies have established a link between quantitative traits and single-nucleotide polymorphisms found in hundreds of genes. These natural variations constitute a pool of QTNs (quantitative trait nucleotides) that modulate yeast traits of economic interest for industry. By selecting a subset of genes functionally validated, a total of 284 QTNs were inventoried. Their distribution across pan and core genome and their frequency within the 1,011 Saccharomyces cerevisiae genomes were analyzed. We found that 150 of the 284 QTNs have a frequency lower than 5%, meaning that these variants would be undetectable by genome-wide association studies (GWAS). This analysis also suggests that most of the functional variants are private to a subpopulation, possibly due to their adaptive role to specific industrial environment. In this review, we provide a literature survey of their phenotypic impact and discuss the opportunities and the limits of their use for industrial strain selection.

Proteome response of two natural strains of Saccharomyces cerevisiae with divergent lignocellulosic inhibitor stress tolerance

Strains of Saccharomyces cerevisiae with improved tolerance to plant hydrolysates are of utmost importance for the cost-competitive production of value-added chemicals and fuels. However, engineering strategies are constrained by a lack of understanding of the yeast response to complex inhibitor mixtures. Natural S. cerevisiae isolates display niche-specific phenotypic and metabolic diversity, encoded in their DNA, which has evolved to overcome external stresses, utilise available resources and ultimately thrive in their challenging environments. Industrial and laboratory strains, however, lack these adaptations due to domestication. Natural strains can serve as a valuable resource to mitigate engineering constraints by studying the molecular mechanisms involved in phenotypic variance and instruct future industrial strain improvement to lignocellulosic hydrolysates. We, therefore, investigated the proteomic changes between two natural S. cerevisiae isolates when exposed to a lignocellulosic inhibitor mixture. Comparative shotgun proteomics revealed that isolates respond by regulating a similar core set of proteins in response to inhibitor stress. Furthermore, superior tolerance was linked to NAD(P)/H and energy homeostasis, concurrent with inhibitor and reactive oxygen species detoxification processes. We present several candidate proteins within the redox homeostasis and energy management cellular processes as possible targets for future modification and study. Data are available via ProteomeXchange with identifier PXD010868.

QTL analysis reveals genomic variants linked to high-temperature fermentation performance in the industrial yeast

BACKGROUND

High-temperature fermentation is desirable for the industrial production of ethanol, which requires thermotolerant yeast strains. However, yeast thermotolerance is a complicated quantitative trait. The understanding of genetic basis behind high-temperature fermentation performance is still limited. Quantitative trait locus (QTL) mapping by pooled-segregant whole genome sequencing has been proved to be a powerful and reliable approach to identify the loci, genes and single nucleotide polymorphism (SNP) variants linked to quantitative traits of yeast.

RESULTS

One superior thermotolerant industrial strain and one inferior thermosensitive natural strain with distinct high-temperature fermentation performances were screened from 124 Saccharomyces cerevisiae strains as parent strains for crossing and segregant isolation. Based on QTL mapping by pooled-segregant whole genome sequencing as well as the subsequent reciprocal hemizygosity analysis (RHA) and allele replacement analysis, we identified and validated total eight causative genes in four QTLs that linked to high-temperature fermentation of yeast. Interestingly, loss of heterozygosity in five of the eight causative genes including RXT2, ECM24, CSC1, IRA2 and AVO1 exhibited positive effects on high-temperature fermentation. Principal component analysis (PCA) of high-temperature fermentation data from all the RHA and allele replacement strains of those eight genes distinguished three superior parent alleles including VPS34, VID24 and DAP1 to be greatly beneficial to high-temperature fermentation in contrast to their inferior parent alleles. Strikingly, physiological impacts of the superior parent alleles of VPS34, VID24 and DAP1 converged on cell membrane by increasing trehalose accumulation or reducing membrane fluidity.

CONCLUSIONS

This work revealed eight novel causative genes and SNP variants closely associated with high-temperature fermentation performance. Among these genes, VPS34 and DAP1 would be good targets for improving high-temperature fermentation of the industrial yeast. It also showed that loss of heterozygosity of causative genes could contribute to the improvement of high-temperature fermentation capacities. Our findings would provide guides to develop more robust and thermotolerant strains for the industrial production of ethanol.

Development of Robust Yeast Strains for Lignocellulosic Biorefineries Based on Genome-Wide Studies

Lignocellulosic biomass has been widely studied as the renewable feedstock for the production of biofuels and biochemicals. Budding yeast Saccharomyces cerevisiae is commonly used as a cell factory for bioconversion of lignocellulosic biomass. However, economic bioproduction using fermentable sugars released from lignocellulosic feedstocks is still challenging. Due to impaired cell viability and fermentation performance by various inhibitors that are present in the cellulosic hydrolysates, robust yeast strains resistant to various stress environments are highly desired. Here, we summarize recent progress on yeast strain development for the production of biofuels and biochemical using lignocellulosic biomass. Genome-wide studies which have contributed to the elucidation of mechanisms of yeast stress tolerance are reviewed. Key gene targets recently identified based on multiomics analysis such as transcriptomic, proteomic, and metabolomics studies are summarized. Physiological genomic studies based on zinc sulfate supplementation are highlighted, and novel zinc-responsive genes involved in yeast stress tolerance are focused. The dependence of host genetic background of yeast stress tolerance and roles of histones and their modifications are emphasized. The development of robust yeast strains based on multiomics analysis benefits economic bioconversion of lignocellulosic biomass.

Genotype-by-Environment-by-Environment Interactions in the Saccharomyces cerevisiae Transcriptomic Response to Alcohols and Anaerobiosis

Next generation biofuels including longer-chain alcohols such as butanol are attractive as renewable, high-energy fuels. A barrier to microbial production of butanols is the increased toxicity compared to ethanol; however, the cellular targets and microbial defense mechanisms remain poorly understood, especially under anaerobic conditions used frequently in industry. Here we took a comparative approach to understand the response of Saccharomyces cerevisiae to 1-butanol, isobutanol, or ethanol, across three genetic backgrounds of varying tolerance in aerobic and anaerobic conditions. We find that strains have different growth properties and alcohol tolerances with and without oxygen availability, as well as unique and common responses to each of the three alcohols. Our results provide evidence for strain-by-alcohol-by-oxygen interactions that moderate how cells respond to alcohol stress.

Determinants of selection in yeast evolved by genome shuffling

BACKGROUND

Genome shuffling (GS) is a widely adopted methodology for the evolutionary engineering of desirable traits in industrially relevant microorganisms. We have previously used genome shuffling to generate a strain of Saccharomyces cerevisiae that is tolerant to the growth inhibitors found in a lignocellulosic hydrolysate. In this study, we expand on previous work by performing a population-wide genomic survey of our genome shuffling experiment and dissecting the molecular determinants of the evolved phenotype.

RESULTS

Whole population whole-genome sequencing was used to survey mutations selected during the experiment and extract allele frequency time series. Using growth curve assays on single point mutants and backcrossed derivatives, we explored the genetic architecture of the selected phenotype and detected examples of epistasis. Our results reveal cohorts of strongly correlated mutations, suggesting prevalent genetic hitchhiking and the presence of pre-existing founder mutations. From the patterns of apparent selection and the results of direct phenotypic assays, our results identify key driver mutations and deleterious hitchhikers.

CONCLUSIONS

We use these data to propose a model of inhibitor tolerance in our GS mutants. Our results also suggest a role for compensatory evolution and epistasis in our genome shuffling experiment and illustrate the impact of historical contingency on the outcomes of evolutionary engineering.

Natural Variation in the Multidrug Efflux Pump SGE1 Underlies Ionic Liquid Tolerance in Yeast

Imidazolium ionic liquids (IILs) have a range of biotechnological applications, including as pretreatment solvents that extract cellulose from plant biomass for microbial fermentation into sustainable bioenergy. However, residual levels of IILs, such as 1-ethyl-3-methylimidazolium chloride ([C2C1im]Cl), are toxic to biofuel-producing microbes, including the yeast Saccharomyces cerevisiae. S. cerevisiae strains isolated from diverse ecological niches differ in genomic sequence and in phenotypes potentially beneficial for industrial applications, including tolerance to inhibitory compounds present in hydrolyzed plant feedstocks. We evaluated >100 genome-sequenced S. cerevisiae strains for tolerance to [C2C1im]Cl and identified one strain with exceptional tolerance. By screening a library of genomic DNA fragments from the [C2C1im]Cl-tolerant strain for improved IIL tolerance, we identified SGE1, which encodes a plasma membrane multidrug efflux pump, and a previously uncharacterized gene that we named ionic liquid tolerance 1 (ILT1), which encodes a predicted membrane protein. Analyses of SGE1 sequences from our panel of S. cerevisiae strains together with growth phenotypes implicated two single nucleotide polymorphisms (SNPs) that associated with IIL tolerance and sensitivity. We confirmed these phenotypic effects by transferring the SGE1 SNPs into a [C2C1im]Cl-sensitive yeast strain using CRISPR/Cas9 genome editing. Further studies indicated that these SNPs affect Sge1 protein stability and cell surface localization, influencing the amount of toxic IILs that cells can pump out of the cytoplasm. Our results highlight the general potential for discovering useful biotechnological functions from untapped natural sequence variation and provide functional insight into emergent SGE1 alleles with reduced capacities to protect against IIL toxicity.

Linkage mapping of yeast cross protection connects gene expression variation to a higher-order organismal trait

Gene expression variation is extensive in nature, and is hypothesized to play a major role in shaping phenotypic diversity. However, connecting differences in gene expression across individuals to higher-order organismal traits is not trivial. In many cases, gene expression variation may be evolutionarily neutral, and in other cases expression variation may only affect phenotype under specific conditions. To understand connections between gene expression variation and stress defense phenotypes, we have been leveraging extensive natural variation in the gene expression response to acute ethanol in laboratory and wild Saccharomyces cerevisiae strains. Previous work found that the genetic architecture underlying these expression differences included dozens of “hotspot” loci that affected many transcripts in trans. In the present study, we provide new evidence that one of these expression QTL hotspot loci affects natural variation in one particular stress defense phenotype—ethanol-induced cross protection against severe doses of H₂O₂. A major causative polymorphism is in the heme-activated transcription factor Hap1p, which we show directly impacts cross protection, but not the basal H₂O₂ resistance of unstressed cells. This provides further support that distinct cellular mechanisms underlie basal and acquired stress resistance. We also show that Hap1p-dependent cross protection relies on novel regulation of cytosolic catalase T (Ctt1p) during ethanol stress in a wild oak strain. Because ethanol accumulation precedes aerobic respiration and accompanying reactive oxygen species formation, wild strains with the ability to anticipate impending oxidative stress would likely be at an advantage. This study highlights how strategically chosen traits that better correlate with gene expression changes can improve our power to identify novel connections between gene expression variation and higher-order organismal phenotypes.

A major goal in genetics is to understand how individuals with different genetic makeups respond to their environment. Understanding these “gene-environment interactions” is important for the development of personalized medicine. For example, gene-environment interactions can explain why some people are more sensitive to certain drugs or are more likely to get certain cancers. While the underlying causes of gene-environment interactions are unclear, one possibility is that differences in gene expression across individuals are responsible. In this study, we examined that possibility using baker’s yeast as a model. We were interested in a phenomenon called acquired stress resistance, where cells exposed to a mild dose of one stress can become resistant to an otherwise lethal dose of severe stress. This response is observed in diverse organisms ranging from bacteria to humans, though the specific mechanisms governing acquisition of higher stress resistance are poorly understood. To understand the differences between yeast strains with and without the ability to acquire further stress resistance, we employed genetic mapping. We found that part of the variation in acquired stress resistance was due to sequence differences in a key regulatory protein, thus providing new insight into how different individuals respond to acute environmental change.

Genetic background effects in quantitative genetics: gene-by-system interactions

Proper cell function depends on networks of proteins that interact physically and functionally to carry out physiological processes. Thus, it seems logical that the impact of sequence variation in one protein could be significantly influenced by genetic variants at other loci in a genome. Nonetheless, the importance of such genetic interactions, known as epistasis, in explaining phenotypic variation remains a matter of debate in genetics. Recent work from our lab revealed that genes implicated from an association study of toxin tolerance in Saccharomyces cerevisiae show extensive interactions with the genetic background: most implicated genes, regardless of allele, are important for toxin tolerance in only one of two tested strains. The prevalence of background effects in our study adds to other reports of widespread genetic-background interactions in model organisms. We suggest that these effects represent many-way interactions with myriad features of the cellular system that vary across classes of individuals. Such gene-by-system interactions may influence diverse traits and require new modeling approaches to accurately represent genotype-phenotype relationships across individuals.