Adaptive evolution of nontransitive fitness in yeast

Inhibition of diastatic yeasts by Saccharomyces killer toxins to prevent hyperattenuation during brewing

Secondary fermentation in beer can result in undesirable consequences, such as off-flavors, increased alcohol content, hyperattenuation, gushing, and the spontaneous explosion of packaging. Strains of Saccharomyces cerevisiae var. diastaticus are a major contributor to such spoilage due to their production of extracellular glucoamylase enzyme encoded by the STA1 gene. Saccharomyces yeasts can naturally produce antifungal proteins named "killer" toxins that inhibit the growth of competing yeasts. Challenging diastatic yeasts with killer toxins revealed that 91% of strains are susceptible to the K1 killer toxin produced by S. cerevisiae. Screening of 192 killer yeasts identified novel K2 toxins that could inhibit all K1-resistant diastatic yeasts. Variant K2 killer toxins were more potent than the K1 and K2 toxins, inhibiting 95% of diastatic yeast strains tested. Brewing trials demonstrated that adding killer yeast during a simulated diastatic contamination event could prevent hyperattenuation. Currently, most craft breweries can only safeguard against diastatic yeast contamination by good hygiene and monitoring for the presence of diastatic yeasts. The detection of diastatic yeasts will often lead to the destruction of contaminated products and the aggressive decontamination of brewing facilities. Using killer yeasts in brewing offers an approach to safeguard against product loss and potentially remediate contaminated beer.IMPORTANCEThe rise of craft brewing means that more domestic beer in the marketplace is being produced in facilities lacking the means for pasteurization, which increases the risk of microbial spoilage. The most damaging spoilage yeasts are "diastatic" strains of Saccharomyces cerevisiae that cause increased fermentation (hyperattenuation), resulting in unpalatable flavors such as phenolic off-flavor, as well as over-carbonation that can cause exploding packaging. In the absence of a pasteurizer, there are no methods available that would avert the loss of beer due to contamination by diastatic yeasts. This manuscript has found that diastatic yeasts are sensitive to antifungal proteins named "killer toxins" produced by Saccharomyces yeasts, and in industrial-scale fermentation trials, killer yeasts can remediate diastatic yeast contamination. Using killer toxins to prevent diastatic contamination is a unique and innovative approach that could prevent lost revenue to yeast spoilage and save many breweries the time and cost of purchasing and installing a pasteurizer.

Genetic conflicts in budding yeast: The 2μ plasmid as a model selfish element

Antagonistic coevolution, arising from genetic conflict, can drive rapid evolution and biological innovation. Conflict can arise both between organisms and within genomes. This review focuses on budding yeasts as a model system for exploring intra- and inter-genomic genetic conflict, highlighting in particular the 2-micron (2μ) plasmid as a model selfish element. The 2μ is found widely in laboratory strains and industrial isolates of Saccharomyces cerevisiae and has long been known to cause host fitness defects. Nevertheless, the plasmid is frequently ignored in the context of genetic, fitness, and evolution studies. Here, I make a case for further exploring the evolutionary impact of the 2μ plasmid as well as other selfish elements of budding yeasts, discuss recent advances, and, finally, future directions for the field.

Overcoming toxicity: why boom-and-bust cycles are good for non-antagonistic microbes

Antagonistic interactions are critical determinants of microbial community stability and composition, offering host benefits such as pathogen protection and providing avenues for antimicrobial control. While the ability to eliminate competitors confers an advantage to antagonistic microbes, it often incurs a fitness cost. Consequently, many microbes only produce toxins or engage in antagonistic behavior in response to specific cues like population density or environmental stress. In laboratory settings, antagonistic microbes typically dominate over sensitive ones, raising the question of why both antagonistic and non-antagonistic microbes are found in natural environments and host microbiomes. Here, using both theoretical models and experiments with killer strains of Saccharomyces cerevisiae , we show that boom-and-bust dynamics caused by temporal environmental fluctuations can favor non-antagonistic microbes that do not incur the growth rate cost of toxin production. Additionally, using control theory, we derive bounds on the competitive performance and identify optimal regulatory toxin-production strategies in various boom-and-bust environments where population dilutions occur either deterministically or stochastically over time. Our findings offer a new perspective on how both antagonistic and non-antagonistic microbes can thrive under varying environmental conditions.

Discovery of a rapidly evolving yeast defense factor, KTD1, against the secreted killer toxin K28

Secreted protein toxins are widely used weapons in conflicts between organisms. Elucidating how organisms genetically adapt to defend themselves against these toxins is fundamental to understanding the coevolutionary dynamics of competing organisms. Within yeast communities, "killer" toxins are secreted to kill nearby sensitive yeast, providing a fitness advantage in competitive growth environments. Natural yeast isolates vary in their sensitivity to these toxins, but to date, no polymorphic genetic factors contributing to defense have been identified. We investigated the variation in resistance to the killer toxin K28 across diverse natural isolates of the Saccharomyces cerevisiae population. Using large-scale linkage mapping, we discovered a novel defense factor, which we named KTD1. We identified many KTD1 alleles, which provided different levels of K28 resistance. KTD1 is a member of the DUP240 gene family of unknown function, which is rapidly evolving in a region spanning its two encoded transmembrane helices. We found that this domain is critical to KTD1's protective ability. Our findings implicate KTD1 as a key polymorphic factor in the defense against K28 toxin.

Pervasive Selection for Clinically Relevant Resistance and Media Adaptive Mutations at Very Low Antibiotic Concentrations

Experimental evolution studies have shown that weak antibiotic selective pressures (i.e., when the antibiotic concentrations are far below the minimum inhibitory concentration, MIC) can select resistant mutants, raising several unanswered questions. First, what are the lowest antibiotic concentrations at which selection for de novo resistance mutations can occur? Second, with weak antibiotic selections, which other types of adaptive mutations unrelated to the antibiotic selective pressure are concurrently enriched? Third, are the mutations selected under laboratory settings at subMIC also observed in clinical isolates? We addressed these questions using Escherichia coli populations evolving at subMICs in the presence of either of four clinically used antibiotics: fosfomycin, nitrofurantoin, tetracycline, and ciprofloxacin. Antibiotic resistance evolution was investigated at concentrations ranging from 1/4th to 1/2000th of the MIC of the susceptible strain (MICsusceptible). Our results show that evolution was rapid across all the antibiotics tested, and selection for fosfomycin- and nitrofurantoin-resistant mutants was observed at a concentration as low as 1/2000th of MICsusceptible. Several of the evolved resistant mutants showed increased growth yield and exponential growth rates, and outcompeted the susceptible ancestral strain in the absence of antibiotics as well, suggesting that adaptation to the growth environment occurred in parallel with the selection for resistance. Genomic analysis of the resistant mutants showed that several of the mutations selected under these conditions are also found in clinical isolates, demonstrating that experimental evolution at very low antibiotic levels can help in identifying novel mutations that contribute to bacterial adaptation during subMIC exposure in real-life settings.

The prevalence of killer yeasts and double-stranded RNAs in the budding yeast Saccharomyces cerevisiae

Killer toxins are antifungal proteins produced by many species of "killer" yeasts, including the brewer's and baker's yeast Saccharomyces cerevisiae. Screening 1270 strains of S. cerevisiae for killer toxin production found that 50% are killer yeasts, with a higher prevalence of yeasts isolated from human clinical samples and winemaking processes. Since many killer toxins are encoded by satellite double-stranded RNAs (dsRNAs) associated with mycoviruses, S. cerevisiae strains were also assayed for the presence of dsRNAs. This screen identified that 51% of strains contained dsRNAs from the mycovirus families Totiviridae and Partitiviridae, as well as satellite dsRNAs. Killer toxin production was correlated with the presence of satellite dsRNAs but not mycoviruses. However, in most killer yeasts, whole genome analysis identified the killer toxin gene KHS1 as significantly associated with killer toxin production. Most killer yeasts had unique spectrums of antifungal activities compared to canonical killer toxins, and sequence analysis identified mutations that altered their antifungal activities. The prevalence of mycoviruses and killer toxins in S. cerevisiae is important because of their known impact on yeast fitness, with implications for academic research and industrial application of this yeast species.

Long-Term Adaptation to Galactose as a Sole Carbon Source Selects for Mutations Outside the Canonical GAL Pathway

Galactose is a secondary fermentable sugar that requires specific regulatory and structural genes for its assimilation, which are under catabolite repression by glucose. When glucose is absent, the catabolic repression is attenuated, and the structural GAL genes are fully activated. In Saccharomyces cerevisiae, the GAL pathway is under selection in environments where galactose is present. However, it is unclear the adaptive strategies in response to long-term propagation in galactose as a sole carbon source in laboratory evolution experiments. Here, we performed a 4,000-generation evolution experiment using 48 diploid Saccharomyces cerevisiae populations to study adaptation in galactose. We show that fitness gains were greater in the galactose-evolved population than in identically evolved populations with glucose as a sole carbon source. Whole-genome sequencing of 96 evolved clones revealed recurrent de novo single nucleotide mutations in candidate targets of selection, copy number variations, and ploidy changes. We find that most mutations that improve fitness in galactose lie outside of the canonical GAL pathway. Reconstruction of specific evolved alleles in candidate target of selection, SEC23 and IRA1, showed a significant increase in fitness in galactose compared to glucose. In addition, most of our evolved populations (28/46; 61%) fixed aneuploidies on Chromosome VIII, suggesting a parallel adaptive amplification. Finally, we show greater loss of extrachromosomal elements in our glucose-evolved lineages compared with previous glucose evolution. Broadly, these data further our understanding of the evolutionary pressures that drive adaptation to less-preferred carbon sources.

Using colony size to measure fitness in Saccharomyces cerevisiae

Competitive fitness assays in liquid culture have been a mainstay for characterizing experimental evolution of microbial populations. Growth of microbial strains has also been extensively characterized by colony size and could serve as a useful alternative if translated to per generation measurements of relative fitness. To examine fitness based on colony size, we established a relationship between cell number and colony size for strains of Saccharomyces cerevisiae robotically pinned onto solid agar plates in a high-density format. This was used to measure growth rates and estimate relative fitness differences between evolved strains and their ancestors. After controlling for edge effects through both normalization and agar-trimming, we found that colony size is a sensitive measure of fitness, capable of detecting 1% differences. While fitnesses determined from liquid and solid mediums were not equivalent, our results demonstrate that colony size provides a sensitive means of measuring fitness that is particularly well suited to measurements across many environments.

Microbial experimental evolution in a massively multiplexed and high-throughput era

Experimental evolution with microbial model systems has transformed our understanding of the basic rules underlying ecology and evolution. Experiments leveraging evolution as a central feature put evolutionary theories to the test, and modern sequencing and engineering tools then characterized the molecular basis of adaptation. As theory and experimentations refined our understanding of evolution, a need to increase throughput and experimental complexity has emerged. Here, we summarize recent technologies that have made high-throughput experiments practical and highlight studies that have capitalized on these tools, defining an exciting new era in microbial experimental evolution. Multiple research directions previously limited by experimental scale are now accessible for study and we believe applying evolutionary lessons from in vitro studies onto these applied settings has the potential for major innovations and discoveries across ecology and medicine.

Overdominant and partially dominant mutations drive clonal adaptation in diploid Saccharomyces cerevisiae

Identification of adaptive targets in experimental evolution typically relies on extensive replication and genetic reconstruction. An alternative approach is to directly assay all mutations in an evolved clone by generating pools of segregants that contain random combinations of evolved mutations. Here, we apply this method to six Saccharomyces cerevisiae clones isolated from four diploid populations that were clonally evolved for 2,000 generations in rich glucose medium. Each clone contains 17-26 mutations relative to the ancestor. We derived intermediate genotypes between the founder and the evolved clones by bulk mating sporulated cultures of the evolved clones to a barcoded haploid version of the ancestor. We competed the resulting barcoded diploids en masse and quantified fitness in the experimental and alternative environments by barcode sequencing. We estimated average fitness effects of evolved mutations using barcode-based fitness assays and whole genome sequencing for a subset of segregants. In contrast to our previous work with haploid evolved clones, we find that diploids carry fewer beneficial mutations, with modest fitness effects (up to 5.4%) in the environment in which they arose. In agreement with theoretical expectations, reconstruction experiments show that all mutations with a detectable fitness effect manifest some degree of dominance over the ancestral allele, and most are overdominant. Genotypes with lower fitness effects in alternative environments allowed us to identify conditions that drive adaptation in our system.

Evolution of innate behavioral strategies through competitive population dynamics

Many organism behaviors are innate or instinctual and have been "hard-coded" through evolution. Current approaches to understanding these behaviors model evolution as an optimization problem in which the traits of organisms are assumed to optimize an objective function representing evolutionary fitness. Here, we use a mechanistic birth-death dynamics approach to study the evolution of innate behavioral strategies in a simulated population of organisms. In particular, we performed agent-based stochastic simulations and mean-field analyses of organisms exploring random environments and competing with each other to find locations with plentiful resources. We find that when organism density is low, the mean-field model allows us to derive an effective objective function, predicting how the most competitive phenotypes depend on the exploration-exploitation trade-off between the scarcity of high-resource sites and the increase in birth rate those sites offer organisms. However, increasing organism density alters the most competitive behavioral strategies and precludes the derivation of a well-defined objective function. Moreover, there exists a range of densities for which the coexistence of many phenotypes persists for evolutionarily long times.

Natural selection for imprecise vertical transmission in host-microbiota systems

How and when the microbiome modulates host adaptation remains an evolutionary puzzle, despite evidence that the extended genetic repertoire of the microbiome can shape host phenotypes and fitness. One complicating factor is that the microbiome is often transmitted imperfectly across host generations, leading to questions about the degree to which the microbiome contributes to host adaptation. Here, using an evolutionary model, we demonstrate that decreasing vertical transmission fidelity can increase microbiome variation, and thus phenotypic variation, across hosts. When the most beneficial microbial genotypes change unpredictably from one generation to the next (for example, in variable environments), hosts can maximize fitness by increasing the microbiome variation among offspring, as this improves the chance of there being an offspring with the right microbial combination for the next generation. Imperfect vertical transmission can therefore be adaptive in varying environments. We characterize how selection on vertical transmission is shaped by environmental conditions, microbiome changes during host development and the contribution of other factors to trait variation. We illustrate how environmentally dependent microbial effects can favour intermediate transmission and set our results in the context of examples from natural systems. We also suggest research avenues to empirically test our predictions. Our model provides a basis to understand the evolutionary pathways that potentially led to the wide diversity of microbe transmission patterns found in nature.

Antagonism between killer yeast strains as an experimental model for biological nucleation dynamics

Antagonistic interactions are widespread in the microbial world and affect microbial evolutionary dynamics. Natural microbial communities often display spatial structure, which affects biological interactions, but much of what we know about microbial antagonism comes from laboratory studies of well-mixed communities. To overcome this limitation, we manipulated two killer strains of the budding yeast Saccharomyces cerevisiae, expressing different toxins, to independently control the rate at which they released their toxins. We developed mathematical models that predict the experimental dynamics of competition between toxin-producing strains in both well-mixed and spatially structured populations. In both situations, we experimentally verified theory's prediction that a stronger antagonist can invade a weaker one only if the initial invading population exceeds a critical frequency or size. Finally, we found that toxin-resistant cells and weaker killers arose in spatially structured competitions between toxin-producing strains, suggesting that adaptive evolution can affect the outcome of microbial antagonism in spatial settings.

The Role of Ancestral Duplicated Genes in Adaptation to Growth on Lactate, a Non-Fermentable Carbon Source for the Yeast Saccharomyces cerevisiae

The cell central metabolism has been shaped throughout evolutionary times when facing challenges from the availability of resources. In the budding yeast, Saccharomyces cerevisiae, a set of duplicated genes originating from an ancestral whole-genome and several coetaneous small-scale duplication events drive energy transfer through glucose metabolism as the main carbon source either by fermentation or respiration. These duplicates (~a third of the genome) have been dated back to approximately 100 MY, allowing for enough evolutionary time to diverge in both sequence and function. Gene duplication has been proposed as a molecular mechanism of biological innovation, maintaining balance between mutational robustness and evolvability of the system. However, some questions concerning the molecular mechanisms behind duplicated genes transcriptional plasticity and functional divergence remain unresolved. In this work we challenged S. cerevisiae to the use of lactic acid/lactate as the sole carbon source and performed a small adaptive laboratory evolution to this non-fermentative carbon source, determining phenotypic and transcriptomic changes. We observed growth adaptation to acidic stress, by reduction of growth rate and increase in biomass production, while the transcriptomic response was mainly driven by repression of the whole-genome duplicates, those implied in glycolysis and overexpression of ROS response. The contribution of several duplicated pairs to this carbon source switch and acidic stress is also discussed.

Segregational drift constrains the evolutionary rate of prokaryotic plasmids

Plasmids are extrachromosomal genetic elements in prokaryotes that have been recognized as important drivers of microbial ecology and evolution. Plasmids are found in multiple copies inside their host cell where independent emergence of mutations may lead to intracellular genetic heterogeneity. The intracellular plasmid diversity is thus subject to changes upon cell division. However, the effect of plasmid segregation on plasmid evolution remains understudied. Here, we show that genetic drift during cell division—segregational drift—leads to the rapid extinction of novel plasmid alleles. We established a novel experimental approach to control plasmid allele frequency at the levels of a single cell and the whole population. Following the dynamics of plasmid alleles in an evolution experiment, we find that the mode of plasmid inheritance—random or clustered—is an important determinant of plasmid allele dynamics. Phylogenetic reconstruction of our model plasmid in clinical isolates furthermore reveals a slow evolutionary rate of plasmid-encoded genes in comparison to chromosomal genes. Our study provides empirical evidence that genetic drift in plasmid evolution occurs at multiple levels: the host cell and the population of hosts. Segregational drift has implications for the evolutionary rate heterogeneity of extrachromosomal genetic elements.

Failure to progress

Experiments on yeast cells that are hosts to a killer virus confirm that natural selection can sometimes reduce fitness.

Phenotypic and molecular evolution across 10,000 generations in laboratory budding yeast populations

Laboratory experimental evolution provides a window into the details of the evolutionary process. To investigate the consequences of long-term adaptation, we evolved 205 Saccharomyces cerevisiae populations (124 haploid and 81 diploid) for ~10,000,000 generations in three environments. We measured the dynamics of fitness changes over time, finding repeatable patterns of declining adaptability. Sequencing revealed that this phenotypic adaptation is coupled with a steady accumulation of mutations, widespread genetic parallelism, and historical contingency. In contrast to long-term evolution in E. coli, we do not observe long-term coexistence or populations with highly elevated mutation rates. We find that evolution in diploid populations involves both fixation of heterozygous mutations and frequent loss-of-heterozygosity events. Together, these results help distinguish aspects of evolutionary dynamics that are likely to be general features of adaptation across many systems from those that are specific to individual organisms and environmental conditions.