The cost of gene expression underlies a fitness trade-off in yeast

Comparative fitness trade-offs associated with azole resistance in Candida auris clinical isolates

Multidrug-resistant yeast Candida auris is a serious threat to public health with documented survival in various hospital niches. The dynamics of this survival benefit and its trade off with drug resistance are still unknown for this pathogen. In this study we investigate the oxidative stress response (OSR) in fluconazole-resistant C. auris and compare its relative fitness with fluconazole-susceptible strains. A total of 351 C. auris clinical isolates (61 fluconazole-susceptible and 290 fluconazole-resistant) were screened for stress tolerance by spot assay and 95.08 % fluconazole-susceptible isolates were hyper-resistant to oxidative stress while majority (94.5 %) fluconazole-resistant isolates had lower oxidative tolerance. Expression of Hog1 and Cta1 gene transcript levels and cellular catalase levels were significantly higher in fluconazole-susceptible isolates and a corresponding higher intracellular reactive oxygen species level (iROS) was accumulated in the fluconazole-resistant isolates. Biofilm formation and cell viability under oxidative stress revealed higher biofilm formation and better viability in fluconazole-susceptible isolates. Fluconazole-resistant isolates had higher basal cell wall chitin. On comparison of virulence, the % cytotoxicity in A549 cell line was higher in fluconazole-susceptible isolates and the median survival of the infected larvae in G. mellonella infection model was higher in fluconazole-resistant (5; IQR:4.5-5 days) vs. fluconazole-susceptible C. auris (2; IQR:1.5-2.5 days). All organisms evolve with changes in their environmental conditions, to ensure an optimal balance between proliferation and survival. Development of tolerance to a certain kind of stress example antifungal exposure in yeast can leads to a compensatory decrease in tolerance for other stresses. This study provides useful insights into the comparative fitness and antifungal susceptibility trade off in C. auris. We report a negative association between H2O2 tolerance and fluconazole susceptibility. Using in-vitro cell cytotoxicity and in-vivo survival assays we also demonstrate the higher virulence potential of fluconazole-susceptible C. auris isolates corroborating the negative correlation between susceptibility and pathogen survival or virulence. These findings could also be translated to clinical practice by investigating the possibility of using molecules targeting stress response and fitness regulating pathways for management of this serious infection.

Shaping of microbial phenotypes by trade-offs

Growth rate maximization is an important fitness strategy for microbes. However, the wide distribution of slow-growing oligotrophic microbes in ecosystems suggests that rapid growth is often not favored across ecological environments. In many circumstances, there exist trade-offs between growth and other important traits (e.g., adaptability and survival) due to physiological and proteome constraints. Investments on alternative traits could compromise growth rate and microbes need to adopt bet-hedging strategies to improve fitness in fluctuating environments. Here we review the mechanistic role of trade-offs in controlling bacterial growth and further highlight its ecological implications in driving the emergences of many important ecological phenomena such as co-existence, population heterogeneity and oligotrophic/copiotrophic lifestyles.

Competition for resources can reshape the evolutionary properties of spatial structure

Many evolving ecosystems have spatial structures that can be conceptualized as networks, with nodes representing individuals or homogeneous subpopulations and links the patterns of interaction and replacement between them. Prior models of evolution on networks do not take ecological niche differences and eco-evolutionary interplay into account. Here, we combine a resource competition model with evolutionary graph theory to study how heterogeneous topological structure shapes evolutionary dynamics under global frequency-dependent ecological interactions. We find that the addition of ecological competition for resources can produce a reversal of roles between amplifier and suppressor networks for deleterious mutants entering the population. Moreover, we show that this effect is a non-linear function of ecological niche overlap and discuss intuition for the observed dynamics using simulations and analytical approximations.

Adaptive advantages of restorative RNA editing in fungi for resolving survival-reproduction trade-offs

RNA editing in various organisms commonly restores RNA sequences to their ancestral state, but its adaptive advantages are debated. In fungi, restorative editing corrects premature stop codons in pseudogenes specifically during sexual reproduction. We characterized 71 pseudogenes and their restorative editing in Fusarium graminearum, demonstrating that restorative editing of 16 pseudogenes is crucial for germ tissue development in fruiting bodies. Our results also revealed that the emergence of premature stop codons is facilitated by restorative editing and that premature stop codons corrected by restorative editing are selectively favored over ancestral amino acid codons. Furthermore, we found that ancestral versions of pseudogenes have antagonistic effects on reproduction and survival. Restorative editing eliminates the survival costs of reproduction caused by antagonistic pleiotropy and provides a selective advantage in fungi. Our findings highlight the importance of restorative editing in the evolution of fungal complex multicellularity and provide empirical evidence that restorative editing serves as an adaptive mechanism enabling the resolution of genetic trade-offs.

Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction

Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs in Saccharomyces cerevisiae by single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the gene GPA1, which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.

Ploidy evolution in a wild yeast is linked to an interaction between cell type and metabolism

Ploidy is an evolutionarily labile trait, and its variation across the tree of life has profound impacts on evolutionary trajectories and life histories. The immediate consequences and molecular causes of ploidy variation on organismal fitness are frequently less clear, although extreme mating type skews in some fungi hint at links between cell type and adaptive traits. Here, we report an unusual recurrent ploidy reduction in replicate populations of the budding yeast Saccharomyces eubayanus experimentally evolved for improvement of a key metabolic trait, the ability to use maltose as a carbon source. We find that haploids have a substantial, but conditional, fitness advantage in the absence of other genetic variation. Using engineered genotypes that decouple the effects of ploidy and cell type, we show that increased fitness is primarily due to the distinct transcriptional program deployed by haploid-like cell types, with a significant but smaller contribution from absolute ploidy. The link between cell-type specification and the carbon metabolism adaptation can be traced to the noncanonical regulation of a maltose transporter by a haploid-specific gene. This study provides novel mechanistic insight into the molecular basis of an environment-cell type fitness interaction and illustrates how selection on traits unexpectedly linked to ploidy states or cell types can drive karyotypic evolution in fungi.

A fitness trade-off between growth and survival governed by Spo0A-mediated proteome allocation constraints in Bacillus subtilis

Growth and survival are key determinants of bacterial fitness. However, how resource allocation of bacteria could reconcile these two traits to maximize fitness remains poorly understood. Here, we find that the resource allocation strategy of Bacillus subtilis does not lead to growth maximization on various carbon sources. Survival-related pathways impose strong proteome constraints on B. subtilis. Knockout of a master regulator gene, spo0A, triggers a global resource reallocation from survival-related pathways to biosynthesis pathways, further strongly stimulating the growth of B. subtilis. However, the fitness of spo0A-null strain is severely compromised because of various disadvantageous phenotypes (e.g., abolished sporulation and enhanced cell lysis). In particular, it also exhibits a strong defect in peptide utilization, being unable to efficiently recycle nutrients from the lysed cell debris to maintain long-term viability. Our work uncovers a fitness trade-off between growth and survival that governed by Spo0A-mediated proteome allocation constraints in B. subtilis, further shedding light on the fundamental design principle of bacteria.

Identifying Targets of Selection in Laboratory Evolution Experiments

Adaptive evolution navigates a balance between chance and determinism. The stochastic processes of mutation and drift generate phenotypic variation; however, once mutations reach an appreciable frequency in the population, their fate is governed by the deterministic action of selection, enriching for favorable genotypes and purging the less-favorable ones. The net result is that replicate populations will traverse similar-but not identical-pathways to higher fitness. This parallelism in evolutionary outcomes can be leveraged to identify the genes and pathways under selection. However, distinguishing between beneficial and neutral mutations is challenging because many beneficial mutations will be lost due to drift and clonal interference, and many neutral (and even deleterious) mutations will fix by hitchhiking. Here, we review the best practices that our laboratory uses to identify genetic targets of selection from next-generation sequencing data of evolved yeast populations. The general principles for identifying the mutations driving adaptation will apply more broadly.

The Genetics of Fitness Reorganization during the Transition to Multicellularity: The Volvocine regA-like Family as a Model

The evolutionary transition from single-celled to multicellular individuality requires organismal fitness to shift from the cell level to a cell group. This reorganization of fitness occurs by re-allocating the two components of fitness, survival and reproduction, between two specialized cell types in the multicellular group: soma and germ, respectively. How does the genetic basis for such fitness reorganization evolve? One possible mechanism is the co-option of life history genes present in the unicellular ancestors of a multicellular lineage. For instance, single-celled organisms must regulate their investment in survival and reproduction in response to environmental changes, particularly decreasing reproduction to ensure survival under stress. Such stress response life history genes can provide the genetic basis for the evolution of cellular differentiation in multicellular lineages. The regA-like gene family in the volvocine green algal lineage provides an excellent model system to study how this co-option can occur. We discuss the origin and evolution of the volvocine regA-like gene family, including regA-the gene that controls somatic cell development in the model organism Volvox carteri. We hypothesize that the co-option of life history trade-off genes is a general mechanism involved in the transition to multicellular individuality, making volvocine algae and the regA-like family a useful template for similar investigations in other lineages.

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.

A personal cost of cheating can stabilize reproductive altruism during the early evolution of clonal multicellularity

Understanding how cooperation evolved and is maintained remains an important and often controversial topic because cheaters that reap the benefits of cooperation without paying the costs can threaten the evolutionary stability of cooperative traits. Cooperation-and especially reproductive altruism-is particularly relevant to the evolution of multicellularity, as somatic cells give up their reproductive potential in order to contribute to the fitness of the newly emerged multicellular individual. Here, we investigated cheating in a simple multicellular species-the green alga Volvox carteri, in the context of the mechanisms that can stabilize reproductive altruism during the early evolution of clonal multicellularity. We found that the benefits cheater mutants can gain in terms of their own reproduction are pre-empted by a cost in survival due to increased sensitivity to stress. This personal cost of cheating reflects the antagonistic pleiotropic effects that the gene coding for reproductive altruism-regA-has at the cell level. Specifically, the expression of regA in somatic cells results in the suppression of their reproduction potential but also confers them with increased resistance to stress. Since regA evolved from a life-history trade-off gene, we suggest that co-opting trade-off genes into cooperative traits can provide a built-in safety system against cheaters in other clonal multicellular lineages.

A Saccharomyces eubayanus haploid resource for research studies

Since its identification, Saccharomyces eubayanus has been recognized as the missing parent of the lager hybrid, S. pastorianus. This wild yeast has never been isolated from fermentation environments, thus representing an interesting candidate for evolutionary, ecological and genetic studies. However, it is imperative to develop additional molecular genetics tools to ease manipulation and thus facilitate future studies. With this in mind, we generated a collection of stable haploid strains representative of three main lineages described in S. eubayanus (PB-1, PB-2 and PB-3), by deleting the HO gene using CRISPR-Cas9 and tetrad micromanipulation. Phenotypic characterization under different conditions demonstrated that the haploid derivates were extremely similar to their parental strains. Genomic analysis in three strains highlighted a likely low frequency of off-targets, and sequencing of a single tetrad evidenced no structural variants in any of the haploid spores. Finally, we demonstrate the utilization of the haploid set by challenging the strains under mass-mating conditions. In this way, we found that S. eubayanus under liquid conditions has a preference to remain in a haploid state, unlike S. cerevisiae that mates rapidly. This haploid resource is a novel set of strains for future yeast molecular genetics studies.

Robustness: linking strain design to viable bioprocesses

Microbial cell factories are becoming increasingly popular for the sustainable production of various chemicals. Metabolic engineering has led to the design of advanced cell factories; however, their long-term yield, titer, and productivity falter when scaled up and subjected to industrial conditions. This limitation arises from a lack of robustness - the ability to maintain a constant phenotype despite the perturbations of such processes. This review describes predictable and stochastic industrial perturbations as well as state-of-the-art technologies to counter process variability. Moreover, we distinguish robustness from tolerance and discuss the potential of single-cell studies for improving system robustness. Finally, we highlight ways of achieving consistent and comparable quantification of robustness that can guide the selection of strains for industrial bioprocesses.

Phenotypic and transcriptomic responses of the rotifer Brachionus koreanus by single and combined exposures to nano-sized microplastics and water-accommodated fractions of crude oil

Sorption of organic pollutants on microplastics can be an alternative uptake route for organic pollutants in aquatic organisms. To assess the combined effects of microplastics and organic pollutants, we employed phenotypic and transcriptomic analyses to the responses of the marine rotifer Brachionus koreanus to environmentally relevant concentrations of nano-sized microplastic (0.05 µm), water-accommodated fractions of crude oil, and binary mixtures thereof. Our multigenerational in vivo experiments revealed more than additive effects on population growth of B. koreanus in response to combined exposure, while a single exposure to nano-sized microplastic did not induce observable adverse effects. Synergistic transcriptome deregulation was consistently associated with dramatically higher numbers of differentially expressed genes, and increased gene expression was associated with combined exposure. The majority of synergistic transcriptional alteration was related to metabolism and transcription, with impaired reproduction resulting from energetic reallocation toward adaptation. As further supported by chemistry analysis for polycyclic aromatic hydrocarbons sorption on microplastic, our findings imply that nano-sized microplastics can synergistically mediate the effects of organic pollutants in aquatic organisms.

Overdominant Mutations Restrict Adaptive Loss of Heterozygosity at Linked Loci

Loss of heterozygosity is a common mode of adaptation in asexual diploid populations. Because mitotic recombination frequently extends the full length of a chromosome arm, the selective benefit of loss of heterozygosity may be constrained by linked heterozygous mutations. In a previous laboratory evolution experiment with diploid yeast, we frequently observed homozygous mutations in the WHI2 gene on the right arm of Chromosome XV. However, when heterozygous mutations arose in the STE4 gene, another common target on Chromosome XV, loss of heterozygosity at WHI2 was not observed. Here, we show that mutations at WHI2 are partially dominant and that mutations at STE4 are overdominant. We test whether beneficial heterozygous mutations at these two loci interfere with one another by measuring loss of heterozygosity at WHI2 over 1,000 generations for ∼300 populations that differed initially only at STE4 and WHI2. We show that the presence of an overdominant mutation in STE4 reduces, but does not eliminate, loss of heterozygosity at WHI2. By sequencing 40 evolved clones, we show that populations with linked overdominant and partially dominant mutations show less parallelism at the gene level, more varied evolutionary outcomes, and increased rates of aneuploidy. Our results show that the degree of dominance and the phasing of heterozygous beneficial mutations can constrain loss of heterozygosity along a chromosome arm, and that conflicts between partially dominant and overdominant mutations can affect evolutionary outcomes.

Resource uptake and the evolution of moderately efficient enzymes

Enzymes speed up reactions that would otherwise be too slow to sustain the metabolism of selfreplicators. Yet, most enzymes seem only moderately efficient, exhibiting kinetic parameters orders of magnitude lower than their expected physically achievable maxima and spanning over surprisingly large ranges of values. Here, we question how these parameters evolve using a mechanistic model where enzyme efficiency is a key component of individual competition for resources. We show that kinetic parameters are under strong directional selection only up to a point, above which enzymes appear to evolve under near-neutrality, thereby confirming the qualitative observation of other modeling approaches. While the existence of a large fitness plateau could potentially explain the extensive variation in enzyme features reported, we show using a population genetics model that such a widespread distribution is an unlikely outcome of evolution on a common landscape, as mutation–selection–drift balance occupy a narrow area even when very moderate biases towards lower efficiency are considered. Instead, differences in the evolutionary context encountered by each enzyme should be involved, such that each evolves on an individual, unique landscape. Our results point to drift and effective population size playing an important role, along with the kinetics of nutrient transporters, the tolerance to high concentrations of intermediate metabolites, and the reversibility of reactions. Enzyme concentration also shapes selection on kinetic parameters, but we show that the joint evolution of concentration and efficiency does not yield extensive variance in evolutionary outcomes when documented costs to protein expression are applied.

Decoupling transcription factor expression and activity enables dimmer switch gene regulation

Gene-regulatory networks achieve complex mappings of inputs to outputs through mechanisms that are poorly understood. We found that in the galactose-responsive pathway in Saccharomyces cerevisiae, the decision to activate the transcription of genes encoding pathway components is controlled independently from the expression level, resulting in behavior resembling that of a mechanical dimmer switch. This was not a direct result of chromatin regulation or combinatorial control at galactose-responsive promoters; rather, this behavior was achieved by hierarchical regulation of the expression and activity of a single transcription factor. Hierarchical regulation is ubiquitous, and thus dimmer switch regulation is likely a key feature of many biological systems. Dimmer switch gene regulation may allow cells to fine-tune their responses to multi-input environments on both physiological and evolutionary time scales.

Exploring a Local Genetic Interaction Network Using Evolutionary Replay Experiments

Understanding how genes interact is a central challenge in biology. Experimental evolution provides a useful, but underutilized, tool for identifying genetic interactions, particularly those that involve non-loss-of-function mutations or mutations in essential genes. We previously identified a strong positive genetic interaction between specific mutations in KEL1 (P344T) and HSL7 (A695fs) that arose in an experimentally evolved Saccharomyces cerevisiae population. Because this genetic interaction is not phenocopied by gene deletion, it was previously unknown. Using “evolutionary replay” experiments, we identified additional mutations that have positive genetic interactions with the kel1-P344T mutation. We replayed the evolution of this population 672 times from six timepoints. We identified 30 populations where the kel1-P344T mutation reached high frequency. We performed whole-genome sequencing on these populations to identify genes in which mutations arose specifically in the kel1-P344T background. We reconstructed mutations in the ancestral and kel1-P344T backgrounds to validate positive genetic interactions. We identify several genetic interactors with KEL1, we validate these interactions by reconstruction experiments, and we show these interactions are not recapitulated by loss-of-function mutations. Our results demonstrate the power of experimental evolution to identify genetic interactions that are positive, allele specific, and not readily detected by other methods, shedding light on an underexplored region of the yeast genetic interaction network.

Ancient balancing selection maintains incompatible versions of the galactose pathway in yeast

Metabolic pathways differ across species but are expected to be similar within a species. We discovered two functional, incompatible versions of the galactose pathway in Saccharomyces cerevisiae We identified a three-locus genetic interaction for growth in galactose, and used precisely engineered alleles to show that it arises from variation in the galactose utilization genes GAL2, GAL1/10/7, and phosphoglucomutase (PGM1), and that the reference allele of PGM1 is incompatible with the alternative alleles of the other genes. Multiloci balancing selection has maintained the two incompatible versions of the pathway for millions of years. Strains with alternative alleles are found primarily in galactose-rich dairy environments, and they grow faster in galactose but slower in glucose, revealing a trade-off on which balancing selection may have acted.

Unique genomic traits for cold adaptation in Naganishia vishniacii, a polyextremophile yeast isolated from Antarctica

Cold environments impose challenges to organisms. Polyextremophile microorganisms can survive in these conditions thanks to an array of counteracting mechanisms. Naganishia vishniacii, a yeast species hitherto only isolated from McMurdo Dry Valleys, Antarctica, is an example of a polyextremophile. Here we present the first draft genomic sequence of N. vishniacii. Using comparative genomics, we unraveled unique characteristics of cold associated adaptations. 336 putative genes (total: 6183) encoding solute transfers and chaperones, among others, were absent in sister species. Among genes shared by N. vishniacii and its closest related species we found orthologs encompassing possible evidence of positive selection (dN/dS > 1). Genes associated with photoprotection were found in agreement with high solar irradiation exposure. Also genes coding for desaturases and genomic features associated with cold tolerance (i.e. trehalose synthesis and lipid metabolism) were explored. Finally, biases in amino acid usage (namely an enrichment of glutamine and a trend in proline reduction) were observed, possibly conferring increased protein flexibility. To the best of our knowledge, such a combination of mechanisms for cold tolerance has not been previously reported in fungi, making N. vishniacii a unique model for the study of the genetic basis and evolution of cold adaptation strategies.

The Genetic Architecture of Emerging Fungicide Resistance in Populations of a Global Wheat Pathogen

Containing fungal diseases often depends on the application of fungicidal compounds. Fungicides can rapidly lose effectiveness due to the rise of resistant individuals in populations. However, the lack of knowledge about resistance mutations beyond known target genes challenges investigations into pathways to resistance. We used whole-genome sequencing data and association mapping to reveal the multilocus genetic architecture of fungicide resistance in a global panel of 159 isolates of Parastagonospora nodorum, an important fungal pathogen of wheat. We found significant differences in azole resistance among global field populations. The populations evolved distinctive combinations of resistance alleles which can interact when co-occurring in the same genetic background. We identified 34 significantly associated single nucleotide polymorphisms located in close proximity to genes associated with fungicide resistance in other fungi, including a major facilitator superfamily transporter. Using fungal colony growth rates and melanin production at different temperatures as fitness proxies, we found no evidence that resistance was constrained by genetic trade-offs. Our study demonstrates how genome-wide association studies of a global collection of pathogen strains can recapitulate the emergence of fungicide resistance. The distinct complement of resistance mutations found among populations illustrates how the evolutionary trajectory of fungicide adaptation can be complex and challenging to predict.

A parallelized strategy for epistasis analysis based on Empirical Bayesian Elastic Net models

MOTIVATION

Epistasis reflects the distortion on a particular trait or phenotype resulting from the combinatorial effect of two or more genes or genetic variants. Epistasis is an important genetic foundation underlying quantitative traits in many organisms as well as in complex human diseases. However, there are two major barriers in identifying epistasis using large genomic datasets. One is that epistasis analysis will induce over-fitting of an over-saturated model with the high-dimensionality of a genomic dataset. Therefore, the problem of identifying epistasis demands efficient statistical methods. The second barrier comes from the intensive computing time for epistasis analysis, even when the appropriate model and data are specified.

RESULTS

In this study, we combine statistical techniques and computational techniques to scale up epistasis analysis using Empirical Bayesian Elastic Net (EBEN) models. Specifically, we first apply a matrix manipulation strategy for pre-computing the correlation matrix and pre-filter to narrow down the search space for epistasis analysis. We then develop a parallelized approach to further accelerate the modeling process. Our experiments on synthetic and empirical genomic data demonstrate that our parallelized methods offer tens of fold speed up in comparison with the classical EBEN method which runs in a sequential manner. We applied our parallelized approach to a yeast dataset, and we were able to identify both main and epistatic effects of genetic variants associated with traits such as fitness.

AVAILABILITY AND IMPLEMENTATION

The software is available at github.com/shilab/parEBEN.

Metabolic transcriptional memory

Background

Organisms can be primed by metabolic exposures to continue expressing response genes even once the metabolite is no longer available, and can affect the speed and magnitude of responsive gene expression during subsequent exposures. This “metabolic transcriptional memory” can have a profound impact on the survivability of organisms in fluctuating environments.

Scope of review

Here I present several examples of metabolic transcriptional memory in the microbial world and discuss what is known so far regarding the underlying mechanisms, which mainly focus on chromatin modifications, protein inheritance, and broad changes in metabolic network. From these lessons learned in microbes, some insights into the yet understudied human metabolic memory can be gained. I thus discuss the implications of metabolic memory in disease progression in humans – i.e., the memory of high blood sugar exposure and the resulting effects on diabetic complications.

Major conclusions

Carbon source shifts from glucose to other less preferred sugars such as lactose, galactose, and maltose for energy metabolism as well as starvation of a signal transduction precursor sugar inositol are well-studied examples of metabolic transcriptional memory in Escherichia coli and Saccharomyces cerevisiae. Although the specific factors guiding metabolic transcriptional memory are not necessarily conserved from microbes to humans, the same basic mechanisms are in play, as is observed in hyperglycemic memory. Exploration of new metabolic transcriptional memory systems as well as further detailed mechanistic analyses of known memory contexts in microbes is therefore central to understanding metabolic memory in humans, and may be of relevance for the successful treatment of the ever-growing epidemic of diabetes.

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Metabolic exposures can prime genes to have memory.

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Memory of carbon source shifts occurs in all kingdoms of life.

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Memory is maintained through multiple mechanisms including chromatin modifications, proteins, and metabolic network.

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Metabolic transcriptional memory in unicellular organisms is a part of “bet-hedging” strategies to ensure survival.

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Hyperglycemic memory in humans contributes to diabetes and aging.

Evolutionary regain of lost gene circuit function

Natural or synthetic genetic modules can lose their function over long-term evolution if the function is costly. How populations can evolve to restore such broken function is poorly understood. To test the reversibility of evolutionary breakdown, we use yeast cell populations with a chromosomally integrated synthetic gene circuit. In previous evolution experiments the gene circuit lost its costly function through various mutations. By exposing such mutant populations to conditions where regaining gene circuit function would be beneficial, we find adaptation scenarios with or without repairing lost gene circuit function. These results are important for drug resistance or future synthetic biology applications where evolutionary loss and regain of function play a significant role.

Evolutionary reversibility—the ability to regain a lost function—is an important problem both in evolutionary and synthetic biology, where repairing natural or synthetic systems broken by evolutionary processes may be valuable. Here, we use a synthetic positive-feedback (PF) gene circuit integrated into haploid Saccharomyces cerevisiae cells to test if the population can restore lost PF function. In previous evolution experiments, mutations in a gene eliminated the fitness costs of PF activation. Since PF activation also provides drug resistance, exposing such compromised or broken mutants to both drug and inducer should create selection pressure to regain drug resistance and possibly PF function. Indeed, evolving 7 PF mutant strains in the presence of drug revealed 3 adaptation scenarios through genomic, PF-external mutations that elevate PF basal expression, possibly by affecting transcription, translation, degradation, and other fundamental cellular processes. Nonfunctional mutants gained drug resistance without ever developing high expression, while quasifunctional and dysfunctional PF mutants developed high expression nongenetically, which then diminished, although more slowly for dysfunctional mutants where revertant clones arose. These results highlight how intracellular context, such as the growth rate, can affect regulatory network dynamics and evolutionary dynamics, which has important consequences for understanding the evolution of drug resistance and developing future synthetic biology applications.

Drift and Directional Selection Are the Evolutionary Forces Driving Gene Expression Divergence in Eye and Brain Tissue of Heliconius Butterflies

Investigating gene expression evolution over micro- and macroevolutionary timescales will expand our understanding of the role of gene expression in adaptation and speciation. In this study, we characterized the evolutionary forces acting on gene expression levels in eye and brain tissue of five Heliconius butterflies with divergence times of ∼5-12 MYA. We developed and applied Brownian motion (BM) and Ornstein-Uhlenbeck (OU) models to identify genes whose expression levels are evolving through drift, stabilizing selection, or a lineage-specific shift. We found that 81% of the genes evolve under genetic drift. When testing for branch-specific shifts in gene expression, we detected 368 (16%) shift events. Genes showing a shift toward upregulation have significantly lower gene expression variance than those genes showing a shift leading toward downregulation. We hypothesize that directional selection is acting in shifts causing upregulation, since transcription is costly. We further uncovered through simulations that parameter estimation of OU models is biased when using small phylogenies and only becomes reliable with phylogenies having ≥ 50 taxa. Therefore, we developed a new statistical test based on BM to identify highly conserved genes (i.e., evolving under strong stabilizing selection), which comprised 3% of the orthoclusters. In conclusion, we found that drift is the dominant evolutionary force driving gene expression evolution in eye and brain tissue in Heliconius Nevertheless, the higher proportion of genes evolving under directional than under stabilizing selection might reflect species-specific selective pressures on vision and the brain that are necessary to fulfill species-specific requirements.

Genetics of Adaptation of the Ascomycetous Fungus Podospora anserina to Submerged Cultivation

Podospora anserina is a model ascomycetous fungus which shows pronounced phenotypic senescence when grown on solid medium but possesses unlimited lifespan under submerged cultivation. In order to study the genetic aspects of adaptation of P. anserina to submerged cultivation, we initiated a long-term evolution experiment. In the course of the first 4 years of the experiment, 125 single-nucleotide substitutions and 23 short indels were fixed in eight independently evolving populations. Six proteins that affect fungal growth and development evolved in more than one population; in particular, in the G-protein alpha subunit FadA, new alleles fixed in seven out of eight experimental populations, and these fixations affected just four amino acid sites, which is an unprecedented level of parallelism in experimental evolution. Parallel evolution at the level of genes and pathways, an excess of nonsense and missense substitutions, and an elevated conservation of proteins and their sites where the changes occurred suggest that many of the observed fixations were adaptive and driven by positive selection.

Unisexual reproduction promotes competition for mating partners in the global human fungal pathogen Cryptococcus deneoformans

Courtship is pivotal for successful mating. However, courtship is challenging for the Cryptococcus neoformans species complex, comprised of opportunistic fungal pathogens, as the majority of isolates are α mating type. In the absence of mating partners of the opposite mating type, C. deneoformans can undergo unisexual reproduction, during which a yeast-to-hyphal morphological transition occurs. Hyphal growth during unisexual reproduction is a quantitative trait, which reflects a strain's ability to undergo unisexual reproduction. In this study, we determined whether unisexual reproduction confers an ecological benefit by promoting foraging for mating partners. Through competitive mating assays using strains with different abilities to produce hyphae, we showed that unisexual reproduction potential did not enhance competition for mating partners of the same mating type, but when cells of the opposite mating type were present, cells with enhanced hyphal growth were more competitive for mating partners of either the same or opposite mating type. Enhanced mating competition was also observed in a strain with increased hyphal production that lacks the mating repressor gene GPA3, which contributes to the pheromone response. Hyphal growth in unisexual strains also enables contact between adjacent colonies and enhances mating efficiency during mating confrontation assays. The pheromone response pathway activation positively correlated with unisexual reproduction hyphal growth during bisexual mating and exogenous pheromone promoted bisexual cell fusion. Despite the benefit in competing for mating partners, unisexual reproduction conferred a fitness cost. Taken together, these findings suggest C. deneoformans employs hyphal growth to facilitate contact between colonies at long distances and utilizes pheromone sensing to enhance mating competition.

Microbial Experimental Evolution - a proving ground for evolutionary theory and a tool for discovery

Microbial experimental evolution uses controlled laboratory populations to study the mechanisms of evolution. The molecular analysis of evolved populations enables empirical tests that can confirm the predictions of evolutionary theory, but can also lead to surprising discoveries. As with other fields in the life sciences, microbial experimental evolution has become a tool, deployed as part of the suite of techniques available to the molecular biologist. Here, I provide a review of the general findings of microbial experimental evolution, especially those relevant to molecular microbiologists that are new to the field. I also relate these results to design considerations for an evolution experiment and suggest future directions for those working at the intersection of experimental evolution and molecular biology.

Chromosomal genome assembly of the ethanol production strain CBS 11270 indicates a highly dynamic genome structure in the yeast species Brettanomyces bruxellensis

Here, we present the genome of the industrial ethanol production strain Brettanomyces bruxellensis CBS 11270. The nuclear genome was found to be diploid, containing four chromosomes with sizes of ranging from 2.2 to 4.0 Mbp. A 75 Kbp mitochondrial genome was also identified. Comparing the homologous chromosomes, we detected that 0.32% of nucleotides were polymorphic, i.e. formed single nucleotide polymorphisms (SNPs), 40.6% of them were found in coding regions (i.e. 0.13% of all nucleotides formed SNPs and were in coding regions). In addition, 8,538 indels were found. The total number of protein coding genes was 4897, of them, 4,284 were annotated on chromosomes; and the mitochondrial genome contained 18 protein coding genes. Additionally, 595 genes, which were annotated, were on contigs not associated with chromosomes. A number of genes was duplicated, most of them as tandem repeats, including a six-gene cluster located on chromosome 3. There were also examples of interchromosomal gene duplications, including a duplication of a six-gene cluster, which was found on both chromosomes 1 and 4. Gene copy number analysis suggested loss of heterozygosity for 372 genes. This may reflect adaptation to relatively harsh but constant conditions of continuous fermentation. Analysis of gene topology showed that most of these losses occurred in clusters of more than one gene, the largest cluster comprising 33 genes. Comparative analysis against the wine isolate CBS 2499 revealed 88,534 SNPs and 8,133 indels. Moreover, when the scaffolds of the CBS 2499 genome assembly were aligned against the chromosomes of CBS 11270, many of them aligned completely, some have chunks aligned to different chromosomes, and some were in fact rearranged. Our findings indicate a highly dynamic genome within the species B. bruxellensis and a tendency towards reduction of gene number in long-term continuous cultivation.

Adaptation limits ecological diversification and promotes ecological tinkering during the competition for substitutable resources

Microbial communities can evade competitive exclusion by diversifying into distinct ecological niches. This spontaneous diversification often occurs amid a backdrop of directional selection on other microbial traits, where competitive exclusion would normally apply. Yet despite their empirical relevance, little is known about how diversification and directional selection combine to determine the ecological and evolutionary dynamics within a community. To address this gap, we introduce a simple, empirically motivated model of eco-evolutionary feedback based on the competition for substitutable resources. Individuals acquire heritable mutations that alter resource uptake rates, either by shifting metabolic effort between resources or by increasing the overall growth rate. While these constitutively beneficial mutations are trivially favored to invade, we show that the accumulated fitness differences can dramatically influence the ecological structure and evolutionary dynamics that emerge within the community. Competition between ecological diversification and ongoing fitness evolution leads to a state of diversification-selection balance, in which the number of extant ecotypes can be pinned below the maximum capacity of the ecosystem, while the ecotype frequencies and genealogies are constantly in flux. Interestingly, we find that fitness differences generate emergent selection pressures to shift metabolic effort toward resources with lower effective competition, even in saturated ecosystems. We argue that similar dynamical features should emerge in a wide range of models with a mixture of directional and diversifying selection.

Adaptive genome duplication affects patterns of molecular evolution in Saccharomyces cerevisiae

Genome duplications are important evolutionary events that impact the rate and spectrum of beneficial mutations and thus the rate of adaptation. Laboratory evolution experiments initiated with haploid Saccharomyces cerevisiae cultures repeatedly experience whole-genome duplication (WGD). We report recurrent genome duplication in 46 haploid yeast populations evolved for 4,000 generations. We find that WGD confers a fitness advantage, and this immediate fitness gain is accompanied by a shift in genomic and phenotypic evolution. The presence of ploidy-enriched targets of selection and structural variants reveals that autodiploids utilize adaptive paths inaccessible to haploids. We find that autodiploids accumulate recessive deleterious mutations, indicating an increased susceptibility for nonadaptive evolution. Finally, we report that WGD results in a reduced adaptation rate, indicating a trade-off between immediate fitness gains and long-term adaptability.

Whole genome duplications—the simultaneous doubling of each chromosome—can have a profound influence on evolution. Evidence of ancient whole genome duplications can be seen in most modern genomes. Experimental evolution, the long-term propagation of organisms under well-controlled laboratory conditions, yields valuable insight into the processes of adaptation and genome evolution. One interesting, and common, outcome of laboratory evolution experiments that start with haploid yeast populations is the emergence of diploid lineages via whole genome duplication. We show that, under our laboratory conditions, whole genome duplication provides a direct fitness benefit, and we identify several consequences of whole genome duplication on adaptation. Following whole-genome duplication, the rate of adaptation slows, the biological targets of selection change, and aneuploidies, copy-number variants and recessive lethal mutations accumulate. By studying the effect of whole genome duplication on adaptation, we can better understand how selection acts on ploidy, a fundamental biological parameter that varies considerably across life.

Genomic tools for behavioural ecologists to understand repeatable individual differences in behaviour

Behaviour is a key interface between an animal's genome and its environment. Repeatable individual differences in behaviour have been extensively documented in animals, but the molecular underpinnings of behavioural variation among individuals within natural populations remain largely unknown. Here, we offer a critical review of when molecular techniques may yield new insights, and we provide specific guidance on how and whether the latest tools available are appropriate given different resources, system and organismal constraints, and experimental designs. Integrating molecular genetic techniques with other strategies to study the proximal causes of behaviour provides opportunities to expand rapidly into new avenues of exploration. Such endeavours will enable us to better understand how repeatable individual differences in behaviour have evolved, how they are expressed and how they can be maintained within natural populations of animals.

Beneficial Mutations from Evolution Experiments Increase Rates of Growth and Fermentation

A major goal of evolutionary biology is to understand how beneficial mutations translate into increased fitness. Here, we study beneficial mutations that arise in experimental populations of yeast evolved in glucose-rich media. We find that fitness increases are caused by enhanced maximum growth rate (R) that come at the cost of reduced yield (K). We show that for some of these mutants, high R coincides with higher rates of ethanol secretion, suggesting that higher growth rates are due to an increased preference to utilize glucose through the fermentation pathway, instead of respiration. We examine the performance of mutants across gradients of glucose and nitrogen concentrations and show that the preference for fermentation over respiration is influenced by the availability of glucose and nitrogen. Overall, our data show that selection for high growth rates can lead to an enhanced Crabtree phenotype by the way of beneficial mutations that permit aerobic fermentation at a greater range of glucose concentrations.

Recombination Alters the Dynamics of Adaptation on Standing Variation in Laboratory Yeast Populations

The rates and selective effects of beneficial mutations, together with population genetic factors such as population size and recombination rate, determine the outcomes of adaptation and the signatures this process leaves in patterns of genetic diversity. Previous experimental studies of microbial evolution have focused primarily on initially clonal populations, finding that adaptation is characterized by new strongly selected beneficial mutations that sweep rapidly to fixation. Here, we study evolution in diverse outcrossed yeast populations, tracking the rate and genetic basis of adaptation over time. We combine time-serial measurements of fitness and allele frequency changes in 18 populations of budding yeast evolved at different outcrossing rates to infer the drivers of adaptation on standing genetic variation. In contrast to initially clonal populations, we find that adaptation is driven by a large number of weakly selected, linked variants. Populations undergoing different rates of outcrossing make use of this selected variation differently: whereas asexual populations evolve via rapid, inefficient, and highly variable fixation of clones, sexual populations adapt continuously by gradually breaking down linkage disequilibrium between selected variants. Our results demonstrate how recombination can sustain adaptation over long timescales by inducing a transition from selection on genotypes to selection on individual alleles, and show how pervasive linked selection can affect evolutionary dynamics.

Epigenetic control of pheromone MAPK signaling determines sexual fecundity in Candida albicans

Several pathogenic Candida species are capable of heritable and reversible switching between two epigenetic states, "white" and "opaque." In Candida albicans, white cells are essentially sterile, whereas opaque cells are mating-proficient. Here, we interrogate the mechanism by which the white-opaque switch regulates sexual fecundity and identify four genes in the pheromone MAPK pathway that are expressed at significantly higher levels in opaque cells than in white cells. These genes encode the β subunit of the G-protein complex (STE4), the pheromone MAPK scaffold (CST5), and the two terminal MAP kinases (CEK1/CEK2). To define the contribution of each factor to mating, C. albicans white cells were reverse-engineered to express elevated, opaque-like levels of these factors, either singly or in combination. We show that white cells co-overexpressing STE4, CST5, and CEK2 undergo mating four orders of magnitude more efficiently than control white cells and at a frequency approaching that of opaque cells. Moreover, engineered white cells recapitulate the transcriptional and morphological responses of opaque cells to pheromone. These results therefore reveal multiple bottlenecks in pheromone MAPK signaling in white cells and that alleviation of these bottlenecks enables efficient mating by these "sterile" cell types. Taken together, our findings establish that differential expression of several MAPK factors underlies the epigenetic control of mating in C. albicans We also discuss how fitness advantages could have driven the evolution of a toggle switch to regulate sexual reproduction in pathogenic Candida species.

Genetic drift and selection in many-allele range expansions

We experimentally and numerically investigate the evolutionary dynamics of four competing strains of E. coli with differing expansion velocities in radially expanding colonies. We compare experimental measurements of the average fraction, correlation functions between strains, and the relative rates of genetic domain wall annihilations and coalescences to simulations modeling the population as a one-dimensional ring of annihilating and coalescing random walkers with deterministic biases due to selection. The simulations reveal that the evolutionary dynamics can be collapsed onto master curves governed by three essential parameters: (1) an expansion length beyond which selection dominates over genetic drift; (2) a characteristic angular correlation describing the size of genetic domains; and (3) a dimensionless constant quantifying the interplay between a colony’s curvature at the frontier and its selection length scale. We measure these parameters with a new technique that precisely measures small selective differences between spatially competing strains and show that our simulations accurately predict the dynamics without additional fitting. Our results suggest that the random walk model can act as a useful predictive tool for describing the evolutionary dynamics of range expansions composed of an arbitrary number of genotypes with different fitnesses.

Population expansions occur naturally during the spread of invasive species and have played a role in our evolutionary history when humans migrated out of Africa. We use a colony of non-motile bacteria expanding into unoccupied, nutrient-rich territory on an agar plate as a model system to explore how an expanding population’s spatial structure impacts its evolutionary dynamics. Spatial structure is present in expanding microbial colonies because daughter cells migrate only a small distance away from their mothers each generation. Generally, the constituents of expansions occurring in nature and in the lab have different genetic compositions (genotypes, or alleles if a single gene differs), each instilling different fitnesses, which compete to proliferate at the frontier. Here, we show that a random-walk model can accurately predict the dynamics of four expanding strains of E. coli with different fitnesses; each strain represents a competing allele. Our results can be extended to describe any number of competing genotypes with different fitnesses in a naturally occurring expansion as long as the underlying motility of the organisms does not cause our model to break down. Our model can also be used to precisely measure small selective differences between spatially competing genotypes in controlled laboratory settings.

Hitchhiking and epistasis give rise to cohort dynamics in adapting populations

Beneficial mutations are the driving force of adaptive evolution. In asexual populations, the identification of beneficial alleles is confounded by the presence of genetically linked hitchhiker mutations. Parallel evolution experiments enable the recognition of common targets of selection; yet these targets are inherently enriched for genes of large target size and mutations of large effect. A comprehensive study of individual mutations is necessary to create a realistic picture of the evolutionarily significant spectrum of beneficial mutations. Here we use a bulk-segregant approach to identify the beneficial mutations across 11 lineages of experimentally evolved yeast populations. We report that nearly 80% of detected mutations have no discernible effects on fitness and less than 1% are deleterious. We determine the distribution of driver and hitchhiker mutations in 31 mutational cohorts, groups of mutations that arise synchronously from low frequency and track tightly with one another. Surprisingly, we find that one-third of cohorts lack identifiable driver mutations. In addition, we identify intracohort synergistic epistasis between alleles of hsl7 and kel1, which arose together in a low-frequency lineage.

Engineering tolerance to industrially relevant stress factors in yeast cell factories

The main focus in development of yeast cell factories has generally been on establishing optimal activity of heterologous pathways and further metabolic engineering of the host strain to maximize product yield and titer. Adequate stress tolerance of the host strain has turned out to be another major challenge for obtaining economically viable performance in industrial production. Although general robustness is a universal requirement for industrial microorganisms, production of novel compounds using artificial metabolic pathways presents additional challenges. Many of the bio-based compounds desirable for production by cell factories are highly toxic to the host cells in the titers required for economic viability. Artificial metabolic pathways also turn out to be much more sensitive to stress factors than endogenous pathways, likely because regulation of the latter has been optimized in evolution in myriads of environmental conditions. We discuss different environmental and metabolic stress factors with high relevance for industrial utilization of yeast cell factories and the experimental approaches used to engineer higher stress tolerance. Improving stress tolerance in a predictable manner in yeast cell factories should facilitate their widespread utilization in the bio-based economy and extend the range of products successfully produced in large scale in a sustainable and economically profitable way.

Parallel reorganization of protein function in the spindle checkpoint pathway through evolutionary paths in the fitness landscape that appear neutral in laboratory experiments

Regulatory networks often increase in complexity during evolution through gene duplication and divergence of component proteins. Two models that explain this increase in complexity are: 1) adaptive changes after gene duplication, such as resolution of adaptive conflicts, and 2) non-adaptive processes such as duplication, degeneration and complementation. Both of these models predict complementary changes in the retained duplicates, but they can be distinguished by direct fitness measurements in organisms with short generation times. Previously, it has been observed that repeated duplication of an essential protein in the spindle checkpoint pathway has occurred multiple times over the eukaryotic tree of life, leading to convergent protein domain organization in its duplicates. Here, we replace the paralog pair in S. cerevisiae with a single-copy protein from a species that did not undergo gene duplication. Surprisingly, using quantitative fitness measurements in laboratory conditions stressful for the spindle-checkpoint pathway, we find no evidence that reorganization of protein function after gene duplication is beneficial. We then reconstruct several evolutionary intermediates from the inferred ancestral network to the extant one, and find that, at the resolution of our assay, there exist stepwise mutational paths from the single protein to the divergent pair of extant proteins with no apparent fitness defects. Parallel evolution has been taken as strong evidence for natural selection, but our results suggest that even in these cases, reorganization of protein function after gene duplication may be explained by neutral processes.

When sensing is gambling: An experimental system reveals how plasticity can generate tunable bet-hedging strategies

Genotypes can persist in unpredictable environments by "hedging their bets" and producing diverse phenotypes. Theoretical studies have shown that the phenotypic variability needed for a bet-hedging strategy can be generated by factors either inside or outside an organism. However, sensing the environment and bet hedging are frequently treated as distinct evolutionary strategies. Furthermore, nearly all empirical studies of the molecular underpinnings of bet-hedging strategies to date have focused on internal sources of variability. We took a synthetic approach and constructed an experimental system where a phenotypic trade-off is mediated by actively sensing a cue present in the environment. We show that active sensing can generate a diversified bet-hedging strategy. Mutations affecting the norm of reaction to the cue alter the diversification strategy, indicating that bet hedging by active sensing is evolvable. Our results indicate that a broader class of biological systems should be considered as potential examples of bet-hedging strategies, and that research into the structure of environmental variability is needed to distinguish bet-hedging strategies from adaptive plasticity.

Accounting for genetic interactions improves modeling of individual quantitative trait phenotypes in yeast

Experiments in model organisms report abundant genetic interactions underlying biologically important traits, whereas quantitative genetics theory predicts, and data support, the notion that most genetic variance in populations is additive. Here we describe networks of capacitating genetic interactions that contribute to quantitative trait variation in a large yeast intercross population. The additive variance explained by individual loci in a network is highly dependent on the allele frequencies of the interacting loci. Modeling of phenotypes for multilocus genotype classes in the epistatic networks is often improved by accounting for the interactions. We discuss the implications of these results for attempts to dissect genetic architectures and to predict individual phenotypes and long-term responses to selection.

Spatial and temporal signal processing and decision making by MAPK pathways

Recent studies show that MAPK pathways perform exquisite spatial and temporal signal processing. This review discusses the mechanisms that process dynamic inputs into graded output responses, the role of positive and negative feedbacks, and feedforward regulation.

Mitogen-activated protein kinase (MAPK) pathways are conserved from yeast to man and regulate a variety of cellular processes, including proliferation and differentiation. Recent developments show how MAPK pathways perform exquisite spatial and temporal signal processing and underscores the importance of studying the dynamics of signaling pathways to understand their physiological response. The importance of dynamic mechanisms that process input signals into graded downstream responses has been demonstrated in the pheromone-induced and osmotic stress–induced MAPK pathways in yeast and in the mammalian extracellular signal-regulated kinase MAPK pathway. Particularly, recent studies in the yeast pheromone response have shown how positive feedback generates switches, negative feedback enables gradient detection, and coherent feedforward regulation underlies cellular memory. More generally, a new wave of quantitative single-cell studies has begun to elucidate how signaling dynamics determine cell physiology and represents a paradigm shift from descriptive to predictive biology.

Transient Duplication-Dependent Divergence and Horizontal Transfer Underlie the Evolutionary Dynamics of Bacterial Cell-Cell Signaling

Evolutionary expansion of signaling pathway families often underlies the evolution of regulatory complexity. Expansion requires the acquisition of a novel homologous pathway and the diversification of pathway specificity. Acquisition can occur either vertically, by duplication, or through horizontal transfer, while divergence of specificity is thought to occur through a promiscuous protein intermediate. The way by which these mechanisms shape the evolution of rapidly diverging signaling families is unclear. Here, we examine this question using the highly diversified Rap-Phr cell-cell signaling system, which has undergone massive expansion in the genus Bacillus. To this end, genomic sequence analysis of >300 Bacilli genomes was combined with experimental analysis of the interaction of Rap receptors with Phr autoinducers and downstream targets. Rap-Phr expansion is shown to have occurred independently in multiple Bacillus lineages, with >80 different putative rap-phr alleles evolving in the Bacillius subtilis group alone. The specificity of many rap-phr alleles and the rapid gain and loss of Rap targets are experimentally demonstrated. Strikingly, both horizontal and vertical processes were shown to participate in this expansion, each with a distinct role. Horizontal gene transfer governs the acquisition of already diverged rap-phr alleles, while intralocus duplication and divergence of the phr gene create the promiscuous intermediate required for the divergence of Rap-Phr specificity. Our results suggest a novel role for transient gene duplication and divergence during evolutionary shifts in specificity.

Impact of ocean acidification on the hypoxia tolerance of the woolly sculpin, Clinocottus analis

As we move into the Anthropocene, organisms inhabiting marine environments will continue to face growing challenges associated with changes in ocean pH (ocean acidification), dissolved oxygen (dead zones) and temperature. These factors, in combination with naturally variable environments such as the rocky intertidal zone, may create extreme physiological challenges for organisms that are already performing near their biological limits. Although numerous studies have examined the impacts of climate-related stressors on intertidal animals, little is known about the underlying physiological mechanisms driving adaptation to ocean acidification and how this may alter organism interactions, particularly in marine vertebrates. Therefore, we have investigated the effects of decreased ocean pH on the hypoxia response of an intertidal sculpin, Clinocottus analis. We used both whole-animal and biochemistry-based analyses to examine how the energetic demands associated with acclimation to low-pH environments may impact the fish's reliance on facultative air breathing in low-oxygen environments. Our study demonstrated that acclimation to ocean acidification resulted in elevated routine metabolic rates and acid-base regulatory capacity (Na+,K+-ATPase activity). These, in turn, had downstream effects that resulted in decreased hypoxia tolerance (i.e. elevated critical oxygen tension). Furthermore, we present evidence that these fish may be living near their physiological capacity when challenged by ocean acidification. This serves as a reminder that the susceptibility of teleost fish to changes in ocean pH may be underestimated, particularly when considering the multiple stressors that many experience in their natural environments.

Gene expression clines reveal local adaptation and associated trade-offs at a continental scale

Local adaptation, where fitness in one environment comes at a cost in another, should lead to spatial variation in trade-offs between life history traits and may be critical for population persistence. Recent studies have sought genomic signals of local adaptation, but often have been limited to laboratory populations representing two environmentally different locations of a species’ distribution. We measured gene expression, as a proxy for fitness, in males of Drosophila subobscura, occupying a 20° latitudinal and 11 °C thermal range. Uniquely, we sampled six populations and studied both common garden and semi-natural responses to identify signals of local adaptation. We found contrasting patterns of investment: transcripts with expression positively correlated to latitude were enriched for metabolic processes, expressed across all tissues whereas negatively correlated transcripts were enriched for reproductive processes, expressed primarily in testes. When using only the end populations, to compare our results to previous studies, we found that locally adaptive patterns were obscured. While phenotypic trade-offs between metabolic and reproductive functions across widespread species are well-known, our results identify underlying genetic and tissue responses at a continental scale that may be responsible for this. This may contribute to understanding population persistence under environmental change.

Exploiting Single-Cell Quantitative Data to Map Genetic Variants Having Probabilistic Effects

Despite the recent progress in sequencing technologies, genome-wide association studies (GWAS) remain limited by a statistical-power issue: many polymorphisms contribute little to common trait variation and therefore escape detection. The small contribution sometimes corresponds to incomplete penetrance, which may result from probabilistic effects on molecular regulations. In such cases, genetic mapping may benefit from the wealth of data produced by single-cell technologies. We present here the development of a novel genetic mapping method that allows to scan genomes for single-cell Probabilistic Trait Loci that modify the statistical properties of cellular-level quantitative traits. Phenotypic values are acquired on thousands of individual cells, and genetic association is obtained from a multivariate analysis of a matrix of Kantorovich distances. No prior assumption is required on the mode of action of the genetic loci involved and, by exploiting all single-cell values, the method can reveal non-deterministic effects. Using both simulations and yeast experimental datasets, we show that it can detect linkages that are missed by classical genetic mapping. A probabilistic effect of a single SNP on cell shape was detected and validated. The method also detected a novel locus associated with elevated gene expression noise of the yeast galactose regulon. Our results illustrate how single-cell technologies can be exploited to improve the genetic dissection of certain common traits. The method is available as an open source R package called ptlmapper.

Experimental evolution in fungi: An untapped resource

Historically, evolutionary biology has been considered an observational science. Examining populations and inferring evolutionary histories mold evolutionary theories. In contrast, laboratory evolution experiments make use of the amenability of traditional model organisms to study fundamental processes underlying evolution in real time in simple, but well-controlled, environments. With advances in high-throughput biology and next generation sequencing, it is now possible to propagate hundreds of parallel populations over thousands of generations and to quantify precisely the frequencies of various mutations over time. Experimental evolution combines the ability to simultaneously monitor replicate populations with the power to vary individual parameters to test specific evolutionary hypotheses, something that is impractical or infeasible in natural populations. Many labs are now conducting laboratory evolution experiments in nearly all model systems including viruses, bacteria, yeast, nematodes, and fruit flies. Among these systems, fungi occupy a unique niche: with a short generation time, small compact genomes, and sexual cycles, fungi are a particularly valuable and largely untapped resource for propelling future growth in the field of experimental evolution. Here, we describe the current state of fungal experimental evolution and why fungi are uniquely positioned to answer many of the outstanding questions in the field. We also review which fungal species are most well suited for experimental evolution.