QTL mapping by pooled-segregant whole-genome sequencing in yeast

Polygenic Analysis of Tolerance to Carbon Dioxide Inhibition of Isoamyl Acetate "Banana" Flavor Production in Yeast Reveals MDS3 as Major Causative Gene

The introduction in modern breweries of tall cylindroconical fermentors, replacing the traditional open fermentation vats, unexpectedly revealed strong inhibition of flavor production by the high CO₂ pressure in the fermentors. We have screened our collection of Saccharomyces cerevisiae strains for strains displaying elevated tolerance to inhibition of flavor production by +0.65 bar CO₂, using a laboratory scale CO₂ pressurized fermentation system. We focused on the production of isoamyl acetate, a highly desirable flavor compound conferring fruity banana flavor in beer and other alcoholic beverages, from its precursor isoamyl alcohol (IAAc/Alc ratio). We selected the most tolerant Saccharomyces cerevisiae strain, saké yeast Kyokai no. 1, isolated a stable haploid segregant seg63 with the same high IAAc/Alc ratio under CO₂ pressure, crossed seg63 with the unrelated inferior strain ER7A and phenotyped 185 haploid segregants, of which 28 displaying a high IAAc/Alc ratio were pooled. Mapping of Quantitative Trait Loci (QTLs) by whole-genome sequence analysis based on SNP variant frequency revealed two QTLs. In the major QTL, reciprocal hemizygosity analysis identified MDS3 as the causative mutant gene, a putative member of the TOR signaling pathway. The MDS3^Seg.63 allele was dominant and contained a single causative point mutation, T2171C, resulting in the F274S substitution. Introduction of MDS3^Seg.63 in an industrial tetraploid lager yeast with CRISPR/Cas9 enhanced isoamyl acetate production by 145% under CO₂ pressure. This work shows the strong potential of polygenic analysis and targeted genetic modification for creation of cisgenic industrial brewer's yeast strains with specifically improved traits.

IMPORTANCE The upscaling of fermentation to very tall cylindroconical tanks is known to negatively impact beer flavor. Most notably, the increased CO₂ pressure in such tanks compromises production by the yeast of the desirable fruity “banana” flavor (isoamyl acetate). The cause of the CO₂ inhibition of yeast flavor production has always remained enigmatic. Our work has brought the first insight into its molecular-genetic basis and provides a specific gene tool for yeast strain improvement. We first identified a yeast strain with superior tolerance to CO₂ inhibition of flavor production, and applied polygenic analysis to identify the responsible gene. We narrowed down the causative element to a single nucleotide difference, MDS3^T2171C, and showed that it can be engineered into brewing yeast to obtain strains with superior flavor production in high CO₂ pressure conditions, apparently without affecting other traits relevant for beer brewing. Alternatively, such a strain could be obtained through marker-assisted breeding.

QTL mapping of a Brazilian bioethanol strain links the cell wall protein-encoding gene GAS1 to low pH tolerance in S. cerevisiae

BACKGROUND

Saccharomyces cerevisiae is largely applied in many biotechnological processes, from traditional food and beverage industries to modern biofuel and biochemicals factories. During the fermentation process, yeast cells are usually challenged in different harsh conditions, which often impact productivity. Regarding bioethanol production, cell exposure to acidic environments is related to productivity loss on both first- and second-generation ethanol. In this scenario, indigenous strains traditionally used in fermentation stand out as a source of complex genetic architecture, mainly due to their highly robust background-including low pH tolerance.

RESULTS

In this work, we pioneer the use of QTL mapping to uncover the genetic basis that confers to the industrial strain Pedra-2 (PE-2) acidic tolerance during growth at low pH. First, we developed a fluorescence-based high-throughput approach to collect a large number of haploid cells using flow cytometry. Then, we were able to apply a bulk segregant analysis to solve the genetic basis of low pH resistance in PE-2, which uncovered a region in chromosome X as the major QTL associated with the evaluated phenotype. A reciprocal hemizygosity analysis revealed the allele GAS1, encoding a β-1,3-glucanosyltransferase, as the casual variant in this region. The GAS1 sequence alignment of distinct S. cerevisiae strains pointed out a non-synonymous mutation (A631G) prevalence in wild-type isolates, which is absent in laboratory strains. We further showcase that GAS1 allele swap between PE-2 and a low pH-susceptible strain can improve cell viability on the latter of up to 12% after a sulfuric acid wash process.

CONCLUSION

This work revealed GAS1 as one of the main causative genes associated with tolerance to growth at low pH in PE-2. We also showcase how GAS1PE-2 can improve acid resistance of a susceptible strain, suggesting that these findings can be a powerful foundation for the development of more robust and acid-tolerant strains. Our results collectively show the importance of tailored industrial isolated strains in discovering the genetic architecture of relevant traits and its implications over productivity.

Mechanisms underlying lactic acid tolerance and its influence on lactic acid production in Saccharomyces cerevisiae

One of the major bottlenecks in lactic acid production using microbial fermentation is the detrimental influence lactic acid accumulation poses on the lactic acid producing cells. The accumulation of lactic acid results in many negative effects on the cell such as intracellular acidification, anion accumulation, membrane perturbation, disturbed amino acid trafficking, increased turgor pressure, ATP depletion, ROS accumulation, metabolic dysregulation and metal chelation. In this review, the manner in which Saccharomyces cerevisiae deals with these issues will be discussed extensively not only for lactic acid as a singular stress factor but also in combination with other stresses. In addition, different methods to improve lactic acid tolerance in S. cerevisiae using targeted and non-targeted engineering methods will be discussed.

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.

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.

Polygenic Analysis in Absence of Major Effector ATF1 Unveils Novel Components in Yeast Flavor Ester Biosynthesis

Flavor production in yeast fermentation is of paramount importance for industrial production of alcoholic beverages. Although major enzymes of flavor compound biosynthesis have been identified, few specific mutations responsible for strain diversity in flavor production are known. The ATF1-encoded alcohol acetyl coenzyme A (acetyl-CoA) transferase (AATase) is responsible for the majority of acetate ester biosynthesis, but other components affecting strain diversity remain unknown. We have performed parallel polygenic analysis of low production of ethyl acetate, a compound with an undesirable solvent-like off-flavor, in strains with and without deletion of ATF1 We identified two unique causative mutations, eat1^K179fs and snf8^E148*, not present in any other sequenced yeast strain and responsible for most ethyl acetate produced in absence of ATF1EAT1 encodes a putative mitochondrial ethanol acetyl-CoA transferase (EATase) and its overexpression, but not that of EAT1^K179fs , and strongly increases ethyl acetate without affecting other flavor acetate esters. Unexpectedly, a higher level of acetate esters (including ethyl acetate) was produced when eat1^K179fs was present together with ATF1 in the same strain, suggesting that the Eat1 and Atf1 enzymes are intertwined. On the other hand, introduction of snf8^E148* lowered ethyl acetate levels also in the presence of ATF1, and it affected other aroma compounds, growth, and fermentation as well. Engineering of snf8^E148* in three industrial yeast strains (for production of wine, saké, and ale beer) and fermentation in an application-relevant medium showed a high but strain-dependent potential for flavor enhancement. Our work has identified EAT1 and SNF8 as new genetic elements determining ethyl acetate production diversity in yeast strains.IMPORTANCE Basic research with laboratory strains of the yeast Saccharomyces cerevisiae has identified the structural genes of most metabolic enzymes, as well as genes encoding major regulators of metabolism. On the other hand, more recent work on polygenic analysis of yeast biodiversity in natural and industrial yeast strains is revealing novel components of yeast metabolism. A major example is the metabolism of flavor compounds, a particularly important property of industrial yeast strains used for the production of alcoholic beverages. In this work, we have performed polygenic analysis of production of ethyl acetate, an important off-flavor compound in beer and other alcoholic beverages. To increase the chances of identifying novel components, we have used in parallel a wild-type strain and a strain with a deletion of ATF1 encoding the main enzyme of acetate ester biosynthesis. This revealed a new structural gene, EAT1, encoding a putative mitochondrial enzyme, which was recently identified as an ethanol acetyl-CoA transferase in another yeast species. We also identified a novel regulatory gene, SNF8, which has not previously been linked to flavor production. Our results show that polygenic analysis of metabolic traits in the absence of major effector genes can reveal novel structural and regulatory genes. The mutant alleles identified can be used to affect the flavor profile in industrial yeast strains for production of alcoholic beverages in more subtle ways than by deletion or overexpression of the already known major effector genes and without significantly altering other industrially important traits. The effect of the novel variants was dependent on the genetic background, with a highly desirable outcome in the flavor profile of an ale brewing yeast.

Target Enrichment Improves Mapping of Complex Traits by Deep Sequencing

Complex traits such as crop performance and human diseases are controlled by multiple genetic loci, many of which have small effects and often go undetected by traditional quantitative trait locus (QTL) mapping. Recently, bulked segregant analysis with large F2 pools and genome-level markers (named extreme-QTL or X-QTL mapping) has been used to identify many QTL. To estimate parameters impacting QTL detection for X-QTL mapping, we simulated the effects of population size, marker density, and sequencing depth of markers on QTL detectability for traits with differing heritabilities. These simulations indicate that a high (>90%) chance of detecting QTL with at least 5% effect requires 5000× sequencing depth for a trait with heritability of 0.4-0.7. For most eukaryotic organisms, whole-genome sequencing at this depth is not economically feasible. Therefore, we tested and confirmed the feasibility of applying deep sequencing of target-enriched markers for X-QTL mapping. We used two traits in Arabidopsis thaliana with different heritabilities: seed size (H(2) = 0.61) and seedling greening in response to salt (H(2) = 0.94). We used a modified G test to identify QTL regions and developed a model-based statistical framework to resolve individual peaks by incorporating recombination rates. Multiple QTL were identified for both traits, including previously undiscovered QTL. We call our method target-enriched X-QTL (TEX-QTL) mapping; this mapping approach is not limited by the genome size or the availability of recombinant inbred populations and should be applicable to many organisms and traits.