Clonal Heterogeneity Influences the Fate of New Adaptive Mutations

Highly parallelized laboratory evolution of wine yeasts for enhanced metabolic phenotypes

Adaptive Laboratory Evolution (ALE) of microorganisms can improve the efficiency of sustainable industrial processes important to the global economy. However, stochasticity and genetic background effects often lead to suboptimal outcomes during laboratory evolution. Here we report an ALE platform to circumvent these shortcomings through parallelized clonal evolution at an unprecedented scale. Using this platform, we evolved 104 yeast populations in parallel from many strains for eight desired wine fermentation-related traits. Expansions of both ALE replicates and lineage numbers broadened the evolutionary search spectrum leading to improved wine yeasts unencumbered by unwanted side effects. At the genomic level, evolutionary gains in metabolic characteristics often coincided with distinct chromosome amplifications and the emergence of side-effect syndromes that were characteristic of each selection niche. Several high-performing ALE strains exhibited desired wine fermentation kinetics when tested in larger liquid cultures, supporting their suitability for application. More broadly, our high-throughput ALE platform opens opportunities for rapid optimization of microbes which otherwise could take many years to accomplish.

Understanding the Temporal Dynamics of Invasive Late Blight Populations in India for Improved Management Practices

The microbial oomycete pathogen Phytophthora infestans causes severe epidemics of potato late blight in crops globally. Disease management benefits from an understanding of the diversity of pathogen populations. In this study, we explore the dynamics of P. infestans populations in the late blight-potato agro-ecosystem across the Indian subcontinent. Investigations of the macroecological observations at the field level and microbial ecological principles provided insights into future pathogen behavior. We use a comprehensive simple sequence repeat allele dataset to demonstrate that an invasive clonal lineage called EU_13_A2 has dominated populations over 14 years across India, Bangladesh, and Pakistan. Increasing levels of subclonal variation were tracked over time and space, and, for the first time, populations in Asia were also compared with the source populations from Europe. Within India, a regional pathogen population structure was observed with evidence for local migration, cross-border movement between surrounding countries, and introductions via imports. There was also evidence of genetic drift and between-season transmission of more strongly pathogenic subclones with a complete displacement of some subclonal types. The limited introduction of novel genotypes and the use of resistant potato cultivars could contribute to the dominance of the 13_A2 lineage. The insights will contribute to the management of the pathogen in these key global potato production regions.

Genome instability footprint under rapamycin and hydroxyurea treatments

The mutational processes dictating the accumulation of mutations in genomes are shaped by genetic background, environment and their interactions. Accurate quantification of mutation rates and spectra under drugs has important implications in disease treatment. Here, we used whole-genome sequencing and time-resolved growth phenotyping of yeast mutation accumulation lines to give a detailed view of the mutagenic effects of rapamycin and hydroxyurea on the genome and cell growth. Mutation rates depended on the genetic backgrounds but were only marginally affected by rapamycin. As a remarkable exception, rapamycin treatment was associated with frequent chromosome XII amplifications, which compensated for rapamycin induced rDNA repeat contraction on this chromosome and served to maintain rDNA content homeostasis and fitness. In hydroxyurea, a wide range of mutation rates were elevated regardless of the genetic backgrounds, with a particularly high occurrence of aneuploidy that associated with dramatic fitness loss. Hydroxyurea also induced a high T-to-G and low C-to-A transversion rate that reversed the common G/C-to-A/T bias in yeast and gave rise to a broad range of structural variants, including mtDNA deletions. The hydroxyurea mutation footprint was consistent with the activation of error-prone DNA polymerase activities and non-homologues end joining repair pathways. Taken together, our study provides an in-depth view of mutation rates and signatures in rapamycin and hydroxyurea and their impact on cell fitness, which brings insights for assessing their chronic effects on genome integrity.

Quantitative systems-based prediction of antimicrobial resistance evolution

Predicting evolution is a fundamental problem in biology with practical implications for treating antimicrobial resistance, which is a complex system-level phenomenon. In this perspective article, we explore the limits of predicting antimicrobial resistance evolution, quantitatively define the predictability and repeatability of microevolutionary processes, and speculate on how these quantities vary across temporal, biological, and complexity scales. The opportunities and challenges for predicting antimicrobial resistance in the context of systems biology are also discussed. Based on recent research, we conclude that the evolution of antimicrobial resistance can be predicted using a systems biology approach integrating quantitative models with multiscale data from microbial evolution experiments.

Long-term evolution of proliferating cells using the eVOLVER platform

Experimental evolution using fast-growing unicellular organisms is a unique strategy for deciphering the principles and mechanisms underlying evolutionary processes as well as the architecture and wiring of basic biological functions. Over the past decade, this approach has benefited from the development of powerful systems for the continuous control of the growth of independently evolving cultures. While the first devices compatible with multiplexed experimental evolution remained challenging to implement and required constant user intervention, the recently developed eVOLVER framework represents a fully automated closed-loop system for laboratory evolution assays. However, it remained difficult to maintain and compare parallel evolving cultures in tightly controlled environments over long periods of time using eVOLVER. Furthermore, a number of tools were lacking to cope with the various issues that inevitably occur when conducting such long-term assays. Here we present a significant upgrade of the eVOLVER framework, providing major modifications of the experimental methodology, hardware and software as well as a new stand-alone protocol. Altogether, these adaptations and improvements make the eVOLVER a versatile and unparalleled set-up for long-term experimental evolution.

Loss of Heterozygosity and Its Importance in Evolution

Loss of heterozygosity (LOH) is a mitotic recombination event that converts heterozygous loci to homozygous loci. This mutation event is widespread in organisms that have asexual reproduction like budding yeasts, and is also an important and frequent mutation event in tumorigenesis. Mutation accumulation studies have demonstrated that LOH occurs at a rate higher than the point mutation rate, and can impact large portions of the genome. Laboratory evolution experiments of heterozygous yeasts have revealed that LOH often unmasks beneficial recessive alleles that can confer large fitness advantages. Here, I highlight advances in understanding dominance, fitness, and phenotypes in laboratory evolved heterozygous yeast strains. I discuss best practices for detecting LOH in intraspecific and interspecific evolved clones and populations. Utilizing heterozygous strain backgrounds in laboratory evolution experiments offers an opportunity to advance our understanding of this important mutation type in shaping adaptation and genome evolution in wild, domesticated, and clinical populations.

Deterministic evolution and stringent selection during preneoplasia

The earliest events during human tumour initiation, although poorly characterized, may hold clues to malignancy detection and prevention1. Here we model occult preneoplasia by biallelic inactivation of TP53, a common early event in gastric cancer, in human gastric organoids. Causal relationships between this initiating genetic lesion and resulting phenotypes were established using experimental evolution in multiple clonally derived cultures over 2 years. TP53 loss elicited progressive aneuploidy, including copy number alterations and structural variants prevalent in gastric cancers, with evident preferred orders. Longitudinal single-cell sequencing of TP53-deficient gastric organoids similarly indicates progression towards malignant transcriptional programmes. Moreover, high-throughput lineage tracing with expressed cellular barcodes demonstrates reproducible dynamics whereby initially rare subclones with shared transcriptional programmes repeatedly attain clonal dominance. This powerful platform for experimental evolution exposes stringent selection, clonal interference and a marked degree of phenotypic convergence in premalignant epithelial organoids. These data imply predictability in the earliest stages of tumorigenesis and show evolutionary constraints and barriers to malignant transformation, with implications for earlier detection and interception of aggressive, genome-instable tumours.

Embracing Complexity: Yeast Evolution Experiments Featuring Standing Genetic Variation

The yeast Saccharomyces cerevisiae has a long and esteemed history as a model system for laboratory selection experiments. The majority of yeast evolution experiments begin with an isogenic ancestor, impose selection as cells divide asexually, and track mutations that arise and accumulate over time. Within the last decade, the popularity of S. cerevisiae as a model system for exploring the evolution of standing genetic variation has grown considerably. As a facultatively sexual microbe, it is possible to initiate experiments with populations that harbor diversity and also to maintain that diversity by promoting sexual recombination as the experiment progresses. These experimental choices expand the scope of evolutionary hypotheses that can be tested with yeast. And, in this review, I argue that yeast is one of the best model systems for testing such hypotheses relevant to eukaryotic species. Here, I compile a list of yeast evolution experiments that involve standing genetic variation, initially and/or by implementing protocols that induce sexual recombination in evolving populations. I also provide an overview of experimental methods required to set up such an experiment and discuss the unique challenges that arise in this type of research. Throughout the article, I emphasize the best practices emerging from this small but growing niche of the literature.

Overexpression profiling reveals cellular requirements in the context of genetic backgrounds and environments

Overexpression can help life adapt to stressful environments, making an examination of overexpressed genes valuable for understanding stress tolerance mechanisms. However, a systematic study of genes whose overexpression is functionally adaptive (GOFAs) under stress has yet to be conducted. We developed a new overexpression profiling method and systematically identified GOFAs in Saccharomyces cerevisiae under stress (heat, salt, and oxidative). Our results show that adaptive overexpression compensates for deficiencies and increases fitness under stress, like calcium under salt stress. We also investigated the impact of different genetic backgrounds on GOFAs, which varied among three S. cerevisiae strains reflecting differing calcium and potassium requirements for salt stress tolerance. Our study of a knockout collection also suggested that calcium prevents mitochondrial outbursts under salt stress. Mitochondria-enhancing GOFAs were only adaptive when adequate calcium was available and non-adaptive when calcium was deficient, supporting this idea. Our findings indicate that adaptive overexpression meets the cell's needs for maximizing the organism's adaptive capacity in the given environment and genetic context.

Long-term evolution of proliferating cells using the eVOLVER platform

Experimental evolution using fast-growing unicellular organisms is a unique strategy for deciphering the principles and mechanisms underlying evolutionary processes as well as the architecture and wiring of basic biological functions. Over the past decade, this approach has benefited from the development of powerful systems for the continuous control of the growth of independently evolving cultures. While the first devices compatible with multiplexed experimental evolution remained challenging to implement and required constant user intervention, the recently-developed eVOLVER framework represents a fully automated closed-loop system for laboratory evolution assays. However, it remained difficult to maintain and compare parallel evolving cultures in tightly controlled environments over long periods of time using eVOLVER. Furthermore, a number of tools were lacking to cope with the various issues that inevitably occur when conducting such long-term assays. Here we present a significant upgrade of the eVOLVER framework, providing major modifications of the experimental methodology, hardware and software as well as a new standalone protocol. Altogether, these adaptations and improvements make the eVOLVER a versatile and unparalleled setup for long-term experimental evolution.

Adaptation in Outbred Sexual Yeast is Repeatable, Polygenic and Favors Rare Haplotypes

We carried out a 200 generation Evolve and Resequence (E&R) experiment initiated from an outbred diploid recombined 18-way synthetic base population. Replicate populations were evolved at large effective population sizes (>105 individuals), exposed to several different chemical challenges over 12 weeks of evolution, and whole-genome resequenced. Weekly forced outcrossing resulted in an average between adjacent-gene per cell division recombination rate of ∼0.0008. Despite attempts to force weekly sex, roughly half of our populations evolved cheaters and appear to be evolving asexually. Focusing on seven chemical stressors and 55 total evolved populations that remained sexual we observed large fitness gains and highly repeatable patterns of genome-wide haplotype change within chemical challenges, with limited levels of repeatability across chemical treatments. Adaptation appears highly polygenic with almost the entire genome showing significant and consistent patterns of haplotype change with little evidence for long-range linkage disequilibrium in a subset of populations for which we sequenced haploid clones. That is, almost the entire genome is under selection or drafting with selected sites. At any given locus adaptation was almost always dominated by one of the 18 founder's alleles, with that allele varying spatially and between treatments, suggesting that selection acts primarily on rare variants private to a founder or haplotype blocks harboring multiple mutations.

Adaptation of the yeast gene knockout collection is near-perfectly predicted by fitness and diminishing return epistasis

Adaptive evolution of clonally dividing cells and microbes is the ultimate cause of cancer and infectious diseases. The possibility of constraining the adaptation of cell populations, by inhibiting proteins enhancing the evolvability, has therefore attracted interest. However, our current understanding of how genes influence adaptation kinetics is limited, partly because accurately measuring adaptation for many cell populations is challenging. We used a high-throughput adaptive laboratory evolution platform to track the adaptation of >18,000 cell populations corresponding to single-gene deletion strains in the haploid yeast deletion collection. We report that the preadaptation fitness of gene knockouts near-perfectly (R2= 0.91) predicts their adaptation to arsenic, leaving at the most a marginal role for dedicated evolvability gene functions. We tracked the adaptation of another >23,000 gene knockout populations to a diverse range of selection pressures and generalized the almost perfect (R2=0.72-0.98) capacity of preadaptation fitness to predict adaptation. We also reconstructed mutations in FPS1, ASK10, and ARR3, which together account for almost all arsenic adaptation in wild-type cells, in gene deletions covering a broad fitness range and show that the predictability of arsenic adaptation can be understood as a by global epistasis, where excluding arsenic is more beneficial to arsenic unfit cells. The paucity of genes with a meaningful evolvability effect on adaptation diminishes the prospects of developing adjuvant drugs aiming to slow antimicrobial and chemotherapy resistance.

Challenges and potential solutions for studying the genetic and phenotypic architecture of adaptation in microbes

All organisms are defined by the makeup of their DNA. Over billions of years, the structure and information contained in that DNA, often referred to as genetic architecture, have been honed by a multitude of evolutionary processes. Mutations that cause genetic elements to change in a way that results in beneficial phenotypic change are more likely to survive and propagate through the population in a process known as adaptation. Recent work reveals that the genetic targets of adaptation are varied and can change with genetic background. Further, seemingly similar adaptive mutations, even within the same gene, can have diverse and unpredictable effects on phenotype. These challenges represent major obstacles in predicting adaptation and evolution. In this review, we cover these concepts in detail and identify three emerging synergistic solutions: higher-throughput evolution experiments combined with updated genotype-phenotype mapping strategies and physiological models. Our review largely focuses on recent literature in yeast, and the field seems to be on the cusp of a new era with regard to studying the predictability of evolution.

Aborting meiosis allows recombination in sterile diploid yeast hybrids

Hybrids between diverged lineages contain novel genetic combinations but an impaired meiosis often makes them evolutionary dead ends. Here, we explore to what extent an aborted meiosis followed by a return-to-growth (RTG) promotes recombination across a panel of 20 Saccharomyces cerevisiae and S. paradoxus diploid hybrids with different genomic structures and levels of sterility. Genome analyses of 275 clones reveal that RTG promotes recombination and generates extensive regions of loss-of-heterozygosity in sterile hybrids with either a defective meiosis or a heavily rearranged karyotype, whereas RTG recombination is reduced by high sequence divergence between parental subgenomes. The RTG recombination preferentially arises in regions with low local heterozygosity and near meiotic recombination hotspots. The loss-of-heterozygosity has a profound impact on sexual and asexual fitness, and enables genetic mapping of phenotypic differences in sterile lineages where linkage analysis would fail. We propose that RTG gives sterile yeast hybrids access to a natural route for genome recombination and adaptation.

Extreme value theory as a framework for understanding mutation frequency distribution in cancer genomes

Currently, the population dynamics of preclonal cancer cells before clonal expansion of tumors has not been sufficiently addressed thus far. By focusing on preclonal cancer cell population as a Darwinian evolutionary system, we formulated and analyzed the observed mutation frequency among tumors (MFaT) as a proxy for the hypothesized sequence read frequency and beneficial fitness effect of a cancer driver mutation. Analogous to intestinal crypts, we assumed that sample donor patients are separate culture tanks where proliferating cells follow certain population dynamics described by extreme value theory (EVT). To validate this, we analyzed three large-scale cancer genome datasets, each harboring > 10000 tumor samples and in total involving > 177898 observed mutation sites. We clarified the necessary premises for the application of EVT in the strong selection and weak mutation (SSWM) regime in relation to cancer genome sequences at scale. We also confirmed that the stochastic distribution of MFaT is likely of the Fréchet type, which challenges the well-known Gumbel hypothesis of beneficial fitness effects. Based on statistical data analysis, we demonstrated the potential of EVT as a population genetics framework to understand and explain the stochastic behavior of driver-mutation frequency in cancer genomes as well as its applicability in real cancer genome sequence data.

How to characterize a strain? Clonal heterogeneity in industrial Saccharomyces influences both phenotypes and heterogeneity in phenotypes

Populations of microbes are constantly evolving heterogeneity that selection acts upon, yet heterogeneity is nontrivial to assess methodologically. The necessary practice of isolating single-cell colonies and thus subclone lineages for establishing, transferring, and using a strain results in single-cell bottlenecks with a generally neglected effect on the characteristics of the strain itself. Here, we present evidence that various subclone lineages for industrial yeasts sequenced for recent genomic studies show considerable differences, ranging from loss of heterozygosity to aneuploidies. Subsequently, we assessed whether phenotypic heterogeneity is also observable in industrial yeast, by individually testing subclone lineages obtained from products. Phenotyping of industrial yeast samples and their newly isolated subclones showed that single-cell bottlenecks during isolation can indeed considerably influence the observable phenotype. Next, we decoupled fitness distributions on the level of individual cells from clonal interference by plating single-cell colonies and quantifying colony area distributions. We describe and apply an approach using statistical modeling to compare the heterogeneity in phenotypes across samples and subclone lineages. One strain was further used to show how individual subclonal lineages are remarkably different not just in phenotype but also in the level of heterogeneity in phenotype. With these observations, we call attention to the fact that choosing an initial clonal lineage from an industrial yeast strain may vastly influence downstream performances and observations on karyotype, on phenotype, and also on heterogeneity.

Rapid selection response to ethanol in Saccharomyces eubayanus emulates the domestication process under brewing conditions

Although the typical genomic and phenotypic changes that characterize the evolution of organisms under the human domestication syndrome represent textbook examples of rapid evolution, the molecular processes that underpin such changes are still poorly understood. Domesticated yeasts for brewing, where short generation times and large phenotypic and genomic plasticity were attained in a few generations under selection, are prime examples. To experimentally emulate the lager yeast domestication process, we created a genetically complex (panmictic) artificial population of multiple Saccharomyces eubayanus genotypes, one of the parents of lager yeast. Then, we imposed a constant selection regime under a high ethanol concentration in 10 replicated populations during 260 generations (6 months) and compared them with propagated controls exposed solely to glucose. Propagated populations exhibited a selection differential of 60% in growth rate in ethanol, mostly explained by the proliferation of a single lineage (CL248.1) that competitively displaced all other clones. Interestingly, the outcome does not require the entire time‐course of adaptation, as four lineages monopolized the culture at generation 120. Sequencing demonstrated that de novo genetic variants were produced in all propagated lines, including SNPs, aneuploidies, INDELs and translocations. In addition, the different propagated populations showed correlated responses resembling the domestication syndrome: genomic rearrangements, faster fermentation rates, lower production of phenolic off‐flavours and lower volatile compound complexity. Expression profiling in beer wort revealed altered expression levels of genes related to methionine metabolism, flocculation, stress tolerance and diauxic shift, likely contributing to higher ethanol and fermentation stress tolerance in the evolved populations. Our study shows that experimental evolution can rebuild the brewing domestication process in ‘fast motion’ in wild yeast, and also provides a powerful tool for studying the genetics of the adaptation process in complex populations.

A yeast living ancestor reveals the origin of genomic introgressions

Genome introgressions drive evolution across the animal¹, plant² and fungal³ kingdoms. Introgressions initiate from archaic admixtures followed by repeated backcrossing to one parental species. However, how introgressions arise in reproductively isolated species, such as yeast⁴, has remained unclear. Here we identify a clonal descendant of the ancestral yeast hybrid that founded the extant Saccharomyces cerevisiae Alpechin lineage⁵, which carries abundant Saccharomyces paradoxus introgressions. We show that this clonal descendant, hereafter defined as a 'living ancestor', retained the ancestral genome structure of the first-generation hybrid with contiguous S. cerevisiae and S. paradoxus subgenomes. The ancestral first-generation hybrid underwent catastrophic genomic instability through more than a hundred mitotic recombination events, mainly manifesting as homozygous genome blocks generated by loss of heterozygosity. These homozygous sequence blocks rescue hybrid fertility by restoring meiotic recombination and are the direct origins of the introgressions present in the Alpechin lineage. We suggest a plausible route for introgression evolution through the reconstruction of extinct stages and propose that genome instability allows hybrids to overcome reproductive isolation and enables introgressions to emerge.

Repeatable ecological dynamics govern the response of experimental communities to antibiotic pulse perturbation

In an era of pervasive anthropogenic ecological disturbances, there is a pressing need to understand the factors that constitute community response and resilience. A detailed understanding of disturbance response needs to go beyond associations and incorporate features of disturbances, species traits, rapid evolution and dispersal. Multispecies microbial communities that experience antibiotic perturbation represent a key system with important medical dimensions. However, previous microbiome studies on this theme have relied on high-throughput sequencing data from uncultured species without the ability to explicitly account for the role of species traits and immigration. Here, we serially passage a 34-species defined bacterial community through different levels of pulse antibiotic disturbance, manipulating the presence or absence of species immigration. To understand the ecological community response measured using amplicon sequencing, we combine initial trait data measured for each species separately and metagenome sequencing data revealing adaptive mutations during the experiment. We found that the ecological community response was highly repeatable within the experimental treatments, which could be attributed in part to key species traits (antibiotic susceptibility and growth rate). Increasing antibiotic levels were also coupled with an increasing probability of species extinction, making species immigration critical for community resilience. Moreover, we detected signals of antibiotic-resistance evolution occurring within species at the same time scale, leaving evolutionary changes in communities despite recovery at the species compositional level. Together, these observations reveal a disturbance response that presents as classic species sorting, but is nevertheless accompanied by rapid within-species evolution.

The multifaceted nature of HIV latency

Although antiretroviral therapies (ARTs) potently inhibit HIV replication, they do not eradicate the virus. HIV persists in cellular and anatomical reservoirs that show minimal decay during ART. A large number of studies conducted during the past 20 years have shown that HIV persists in a small pool of cells harboring integrated and replication-competent viral genomes. The majority of these cells do not produce viral particles and constitute what is referred to as the latent reservoir of HIV infection. Therefore, although HIV is not considered as a typical latent virus, it can establish a state of nonproductive infection under rare circumstances, particularly in memory CD4+ T cells, which represent the main barrier to HIV eradication. While it was originally thought that the pool of latently infected cells was largely composed of cells harboring transcriptionally silent genomes, recent evidence indicates that several blocks contribute to the nonproductive state of these cells. Here, we describe the virological and immunological factors that play a role in the establishment and persistence of the pool of latently infected cells and review the current approaches aimed at eliminating the latent HIV reservoir.

Differential Gene Expression and Allele Frequency Changes Favour Adaptation of a Heterogeneous Yeast Population to Nitrogen-Limited Fermentations

Alcoholic fermentation is fundamentally an adaptation process, in which the yeast Saccharomyces cerevisiae outperforms its competitors and takes over the fermentation process itself. Although wine yeast strains appear to be adapted to the stressful conditions of alcoholic fermentation, nitrogen limitations in grape must cause stuck or slow fermentations, generating significant economic losses for the wine industry. One way to discover the genetic bases that promote yeast adaptation to nitrogen-deficient environments are selection experiments, where a yeast population undergoes selection under conditions of nitrogen restriction for a number of generations, to then identify by sequencing the molecular characteristics that promote this adaptation. In this work, we carried out selection experiments in bioreactors imitating wine fermentation under nitrogen-limited fermentation conditions (SM60), using the heterogeneous SGRP-4X yeast population, to then sequence the transcriptome and the genome of the population at different time points of the selection process. The transcriptomic results showed an overexpression of genes from the NA strain (North American/YPS128), a wild, non-domesticated isolate. In addition, genome sequencing and allele frequency results allowed several QTLs to be mapped for adaptation to nitrogen-limited fermentation. Finally, we validated the ECM38 allele of NA strain as responsible for higher growth efficiency under nitrogen-limited conditions. Taken together, our results revealed a complex pattern of molecular signatures favouring adaptation of the yeast population to nitrogen-limited fermentations, including differential gene expression, allele frequency changes and loss of the mitochondrial genome. Finally, the results suggest that wild alleles from a non-domesticated isolate (NA) may have a relevant role in the adaptation to the assayed fermentation conditions, with the consequent potential of these alleles for the genetic improvement of wine yeast strains.

Intragenic repeat expansion in the cell wall protein gene HPF1 controls yeast chronological aging

Aging varies among individuals due to both genetics and environment, but the underlying molecular mechanisms remain largely unknown. Using a highly recombined Saccharomyces cerevisiae population, we found 30 distinct quantitative trait loci (QTLs) that control chronological life span (CLS) in calorie-rich and calorie-restricted environments and under rapamycin exposure. Calorie restriction and rapamycin extended life span in virtually all genotypes but through different genetic variants. We tracked the two major QTLs to the cell wall glycoprotein genes FLO11 and HPF1 We found that massive expansion of intragenic tandem repeats within the N-terminal domain of HPF1 was sufficient to cause pronounced life span shortening. Life span impairment by HPF1 was buffered by rapamycin but not by calorie restriction. The HPF1 repeat expansion shifted yeast cells from a sedentary to a buoyant state, thereby increasing their exposure to surrounding oxygen. The higher oxygenation altered methionine, lipid, and purine metabolism, and inhibited quiescence, which explains the life span shortening. We conclude that fast-evolving intragenic repeat expansions can fundamentally change the relationship between cells and their environment with profound effects on cellular lifestyle and longevity.

Accurate Tracking of the Mutational Landscape of Diploid Hybrid Genomes

Mutations, recombinations, and genome duplications may promote genetic diversity and trigger evolutionary processes. However, quantifying these events in diploid hybrid genomes is challenging. Here, we present an integrated experimental and computational workflow to accurately track the mutational landscape of yeast diploid hybrids (MuLoYDH) in terms of single-nucleotide variants, small insertions/deletions, copy-number variants, aneuploidies, and loss-of-heterozygosity. Pairs of haploid Saccharomyces parents were combined to generate ancestor hybrids with phased genomes and varying levels of heterozygosity. These diploids were evolved under different laboratory protocols, in particular mutation accumulation experiments. Variant simulations enabled the efficient integration of competitive and standard mapping of short reads, depending on local levels of heterozygosity. Experimental validations proved the high accuracy and resolution of our computational approach. Finally, applying MuLoYDH to four different diploids revealed striking genetic background effects. Homozygous Saccharomyces cerevisiae showed a ∼4-fold higher mutation rate compared with its closely related species S. paradoxus. Intraspecies hybrids unveiled that a substantial fraction of the genome (∼250 bp per generation) was shaped by loss-of-heterozygosity, a process strongly inhibited in interspecies hybrids by high levels of sequence divergence between homologous chromosomes. In contrast, interspecies hybrids exhibited higher single-nucleotide mutation rates compared with intraspecies hybrids. MuLoYDH provided an unprecedented quantitative insight into the evolutionary processes that mold diploid yeast genomes and can be generalized to other genetic systems.

Disentangling the genetic bases of Saccharomyces cerevisiae nitrogen consumption and adaptation to low nitrogen environments in wine fermentation

The budding yeast Saccharomyces cerevisiae has been considered for more than 20 years as a premier model organism for biological sciences, also being the main microorganism used in wide industrial applications, like alcoholic fermentation in the winemaking process. Grape juice is a challenging environment for S. cerevisiae, with nitrogen deficiencies impairing fermentation rate and yeast biomass production, causing stuck or sluggish fermentations, thus generating sizeable economic losses for wine industry. In the present review, we summarize some recent efforts in the search of causative genes that account for yeast adaptation to low nitrogen environments, specially focused in wine fermentation conditions. We start presenting a brief perspective of yeast nitrogen utilization under wine fermentative conditions, highlighting yeast preference for some nitrogen sources above others. Then, we give an outlook of S. cerevisiae genetic diversity studies, paying special attention to efforts in genome sequencing for population structure determination and presenting QTL mapping as a powerful tool for phenotype-genotype correlations. Finally, we do a recapitulation of S. cerevisiae natural diversity related to low nitrogen adaptation, specially showing how different studies have left in evidence the central role of the TORC1 signalling pathway in nitrogen utilization and positioned wild S. cerevisiae strains as a reservoir of beneficial alleles with potential industrial applications (e.g. improvement of industrial yeasts for wine production). More studies focused in disentangling the genetic bases of S. cerevisiae adaptation in wine fermentation will be key to determine the domestication effects over low nitrogen adaptation, as well as to definitely proof that wild S. cerevisiae strains have potential genetic determinants for better adaptation to low nitrogen conditions.

Fungal Endophyte Colonization Patterns Alter Over Time in the Novel Association Between Lolium perenne and Epichloë Endophyte AR37

Infection of the pasture grass Lolium perenne with the seed-transmitted fungal endophyte Epichloë festucae enhances its resilience to biotic and abiotic stress. Agricultural benefits of endophyte infection can be increased by generating novel symbiotic associations through inoculating L. perenne with selected Epichloë strains. Natural symbioses have coevolved over long periods. Thus, artificial symbioses will probably not have static properties, but symbionts will coadapt over time improving the fitness of the association. Here we report for the first time on temporal changes in a novel association of Epichloë strain AR37 and the L. perenne cultivar Grasslands Samson. Over nine generations, a seed maintenance program had increased the endophyte seed transmission rates to > 95% (from an initial 76%). We observed an approximately fivefold decline in endophyte biomass concentration in vegetative tissues over time (between generations 2 and 9). This indicates strong selection pressure toward reducing endophyte-related fitness costs by reducing endophyte biomass, without compromising the frequency of endophyte transmission to seed. We observed no obvious changes in tillering and only minor transcriptomic changes in infected plants over time. Functional analysis of 40 plant genes, showing continuously decreasing expression over time, suggests that adaptation of host metabolism and defense mechanisms are important for increasing the fitness of this association, and possibly fitness of such symbioses in general. Our results indicate that fitness of novel associations is likely to improve over time and that monitoring changes in novel associations can assist in identifying key features of endophyte-mediated enhancement of host fitness.

Genetic mapping of fitness determinants across the malaria parasite Plasmodium falciparum life cycle

Determining the genetic basis of fitness is central to understanding evolution and transmission of microbial pathogens. In human malaria parasites (Plasmodium falciparum), most experimental work on fitness has focused on asexual blood stage parasites, because this stage can be easily cultured, although the transmission of malaria requires both female Anopheles mosquitoes and vertebrate hosts. We explore a powerful approach to identify the genetic determinants of parasite fitness across both invertebrate and vertebrate life-cycle stages of P. falciparum. This combines experimental genetic crosses using humanized mice, with selective whole genome amplification and pooled sequencing to determine genome-wide allele frequencies and identify genomic regions under selection across multiple lifecycle stages. We applied this approach to genetic crosses between artemisinin resistant (ART-R, kelch13-C580Y) and ART-sensitive (ART-S, kelch13-WT) parasites, recently isolated from Southeast Asian patients. Two striking results emerge: we observed (i) a strong genome-wide skew (>80%) towards alleles from the ART-R parent in the mosquito stage, that dropped to ~50% in the blood stage as selfed ART-R parasites were selected against; and (ii) repeatable allele specific skews in blood stage parasites with particularly strong selection (selection coefficient (s) ≤ 0.18/asexual cycle) against alleles from the ART-R parent at loci on chromosome 12 containing MRP2 and chromosome 14 containing ARPS10. This approach robustly identifies selected loci and has strong potential for identifying parasite genes that interact with the mosquito vector or compensatory loci involved in drug resistance.

Adaptation by Loss of Heterozygosity in Saccharomyces cerevisiae Clones Under Divergent Selection

Loss of heterozygosity (LOH) is observed during vegetative growth and reproduction of diploid genotypes through mitotic crossovers, aneuploidy caused by nondisjunction, and gene conversion. We aimed to test the role that LOH plays during adaptation of two highly heterozygous Saccharomyces cerevisiae genotypes to multiple environments over a short time span in the laboratory. We hypothesized that adaptation would be observed through parallel LOH events across replicate populations. Using genome resequencing of 70 clones, we found that LOH was widespread with 5.2 LOH events per clone after ∼500 generations. The most common mode of LOH was gene conversion (51%) followed by crossing over consistent with either break-induced replication or double Holliday junction resolution. There was no evidence that LOH involved nondisjunction of whole chromosomes. We observed parallel LOH in both an environment-specific and environment-independent manner. LOH largely involved recombining existing variation between the parental genotypes, but also was observed after de novo, presumably beneficial, mutations occurred in the presence of canavanine, a toxic analog of arginine. One highly parallel LOH event involved the ENA salt efflux pump locus on chromosome IV, which showed repeated LOH to the allele from the European parent, an allele originally derived by introgression from S. paradoxus Using CRISPR-engineered LOH we showed that the fitness advantage provided by this single LOH event was 27%. Overall, we found extensive evidence that LOH could be adaptive and is likely to be a greater source of initial variation than de novo mutation for rapid evolution of diploid genotypes.

The Mutator Phenotype: Adapting Microbial Evolution to Cancer Biology

The mutator phenotype hypothesis was postulated almost 40 years ago to reconcile the observation that while cancer cells display widespread mutational burden, acquisition of mutations in non-transformed cells is a rare event. Moreover, it also suggested that cancer evolution could be fostered by increased genome instability. Given the evolutionary conservation throughout the tree of life and the genetic tractability of model organisms, yeast and bacterial species pioneered studies to dissect the functions of genes required for genome maintenance (caretaker genes) or for cell growth control (gatekeeper genes). In this review, we first provide an overview of what we learned from model organisms about the roles of these genes and the genome instability that arises as a consequence of their dysregulation. We then discuss our current understanding of how mutator phenotypes shape the evolution of bacteria and yeast species. We end by bringing clinical evidence that lessons learned from single-cell organisms can be applied to tumor evolution.

Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales

Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations.

Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution

In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.