Mutational robustness and the role of buffer genes in evolvability.

Organisms rely on mutations to fuel adaptive evolution. However, many mutations impose a negative effect on fitness. Cells may have therefore evolved mechanisms that affect the phenotypic effects of mutations, thus conferring mutational robustness. Specifically, so-called buffer genes are hypothesized to interact directly or indirectly with genetic variation and reduce its effect on fitness. Environmental or genetic perturbations can change the interaction between buffer genes and genetic variation, thereby unmasking the genetic variation's phenotypic effects and thus providing a source of variation for natural selection to act on. This review provides an overview of our understanding of mutational robustness and buffer genes, with the chaperone gene HSP90 as a key example. It discusses whether buffer genes merely affect standing variation or also interact with de novo mutations, how mutational robustness could influence evolution, and whether mutational robustness might be an evolved trait or rather a mere side-effect of complex genetic interactions.

Mutagenesis techniques for evolutionary engineering of microbes - exploiting CRISPR-Cas, oligonucleotides, recombinases, and polymerases.

The natural process of evolutionary adaptation is often exploited as a powerful tool to obtain microbes with desirable traits. For industrial microbes, evolutionary engineering is often used to generate variants that show increased yields or resistance to stressful industrial environments, thus obtaining superior microbial cell factories. However, even in large populations, the natural supply of beneficial mutations is typically low, which implies that obtaining improved microbes is often time-consuming and inefficient. To overcome this limitation, different techniques have been developed that boost mutation rates. While some of these methods simply increase the overall mutation rate across a genome, others use recent developments in DNA synthesis, synthetic biology, and CRISPR-Cas techniques to control the type and location of mutations. This review summarizes the most important recent developments and methods in the field of evolutionary engineering in model microorganisms. It discusses how both in vitro and in vivo approaches can increase the genetic diversity of the host, with a special emphasis on in vivo techniques for the optimization of metabolic pathways for precision fermentation.

Rational evolution for altering the ligand preference of estrogen receptor alpha.

Estrogen receptor α is commonly used in synthetic biology to control the activity of genome editing tools. The activating ligands, estrogens, however, interfere with various cellular processes, thereby limiting the applicability of this receptor. Altering its ligand preference to chemicals of choice solves this hurdle but requires adaptation of unspecified ligand-interacting residues. Here, we provide a solution by combining rational protein design with multi-site-directed mutagenesis and directed evolution of stably integrated variants in Saccharomyces cerevisiae. This method yielded an estrogen receptor variant, named TERRA, that lost its estrogen responsiveness and became activated by tamoxifen, an anti-estrogenic drug used for breast cancer treatment. This tamoxifen preference of TERRA was maintained in mammalian cells and mice, even when fused to Cre recombinase, expanding the mammalian synthetic biology toolbox. Not only is our platform transferable to engineer ligand preference of any steroid receptor, it can also profile drug-resistance landscapes for steroid receptor-targeted therapies.

Ethanol induces replication fork stalling and membrane stress in immortalized laryngeal cells.

Although ethanol is a class I carcinogen and is linked to more than 700,000 cancer incidences, a clear understanding of the molecular mechanisms underlying ethanol-related carcinogenesis is still lacking. Further understanding of ethanol-related cell damage can contribute to reducing or treating alcohol-related cancers. Here, we investigated the effects of both short- and long-term exposure of human laryngeal epithelial cells to different ethanol concentrations. RNA sequencing shows that ethanol altered gene expression patterns in a time- and concentration-dependent way, affecting genes involved in ribosome biogenesis, cytoskeleton remodeling, Wnt signaling, and transmembrane ion transport. Additionally, ethanol induced a slower cell proliferation, a delayed cell cycle progression, and replication fork stalling. In addition, ethanol exposure resulted in morphological changes, which could be associated with membrane stress. Taken together, our data yields a comprehensive view of molecular changes associated with ethanol stress in epithelial cells of the upper aerodigestive tract.

Saccharomyces cerevisiae as a Model System for Eukaryotic Cell Biology, from Cell Cycle Control to DNA Damage Response.

The yeast Saccharomyces cerevisiae has been used for bread making and beer brewing for thousands of years. In addition, its ease of manipulation, well-annotated genome, expansive molecular toolbox, and its strong conservation of basic eukaryotic biology also make it a prime model for eukaryotic cell biology and genetics. In this review, we discuss the characteristics that made yeast such an extensively used model organism and specifically focus on the DNA damage response pathway as a prime example of how research in S. cerevisiae helped elucidate a highly conserved biological process. In addition, we also highlight differences in the DNA damage response of S. cerevisiae and humans and discuss the challenges of using S. cerevisiae as a model system.

Do microbes have a memory? History-dependent behavior in the adaptation to variable environments.

Microbes are constantly confronted with changes and challenges in their environment. A proper response to these environmental cues is needed for optimal cellular functioning and fitness. Interestingly, past exposure to environmental cues can accelerate or boost the response when this condition returns, even in daughter cells that have not directly encountered the initial cue. Moreover, this behavior is mostly epigenetic and often goes hand in hand with strong heterogeneity in the strength and speed of the response between isogenic cells of the same population, which might function as a bet-hedging strategy. In this review, we discuss examples of history-dependent behavior (HDB) or "memory," with a specific focus on HDB in fluctuating environments. In most examples discussed, the lag time before the response to an environmental change is used as an experimentally measurable proxy for HDB. We highlight different mechanisms already implicated in HDB, and by using HDB in fluctuating carbon conditions as a case study, we showcase how the metabolic state of a cell can be a key determining factor for HDB. Finally, we consider possible evolutionary causes and consequences of such HDB.

An Integrated Approach Reveals DNA Damage and Proteotoxic Stress as Main Effects of Proton Radiation in S. cerevisiae.

Proton radiotherapy (PRT) has the potential to reduce the normal tissue toxicity associated with conventional photon-based radiotherapy (X-ray therapy, XRT) because the active dose can be more directly targeted to a tumor. Although this dosimetric advantage of PRT is well known, the molecular mechanisms affected by PRT remain largely elusive. Here, we combined the molecular toolbox of the eukaryotic model Saccharomyces cerevisiae with a systems biology approach to investigate the physiological effects of PRT compared to XRT. Our data show that the DNA damage response and protein stress response are the major molecular mechanisms activated after both PRT and XRT. However, RNA-Seq revealed that PRT treatment evoked a stronger activation of genes involved in the response to proteotoxic stress, highlighting the molecular differences between PRT and XRT. Moreover, inhibition of the proteasome resulted in decreased survival in combination with PRT compared to XRT, not only further confirming that protons induced a stronger proteotoxic stress response, but also hinting at the potential of using proteasome inhibitors in combination with proton radiotherapy in clinical settings.

Integrated Multi-Omics Analysis of Mechanisms Underlying Yeast Ethanol Tolerance.

For yeast cells, tolerance to high levels of ethanol is vital both in their natural environment and in industrially relevant conditions. We recently genotyped experimentally evolved yeast strains adapted to high levels of ethanol and identified mutations linked to ethanol tolerance. In this study, by integrating genomic sequencing data with quantitative proteomics profiles from six evolved strains (data set identifier PXD006631) and construction of protein interaction networks, we elucidate exactly how the genotype and phenotype are related at the molecular level. Our multi-omics approach points to the rewiring of numerous metabolic pathways affected by genomic and proteomic level changes, from energy-producing and lipid pathways to differential regulation of transposons and proteins involved in cell cycle progression. One of the key differences is found in the energy-producing metabolism, where the ancestral yeast strain responds to ethanol by switching to respiration and employing the mitochondrial electron transport chain. In contrast, the ethanol-adapted strains appear to have returned back to energy production mainly via glycolysis and ethanol fermentation, as supported by genomic and proteomic level changes. This work is relevant for synthetic biology where systems need to function under stressful conditions, as well as for industry and in cancer biology, where it is important to understand how the genotype relates to the phenotype.

Ethanol exposure increases mutation rate through error-prone polymerases.

Ethanol is a ubiquitous environmental stressor that is toxic to all lifeforms. Here, we use the model eukaryote Saccharomyces cerevisiae to show that exposure to sublethal ethanol concentrations causes DNA replication stress and an increased mutation rate. Specifically, we find that ethanol slows down replication and affects localization of Mrc1, a conserved protein that helps stabilize the replisome. In addition, ethanol exposure also results in the recruitment of error-prone DNA polymerases to the replication fork. Interestingly, preventing this recruitment through mutagenesis of the PCNA/Pol30 polymerase clamp or deleting specific error-prone polymerases abolishes the mutagenic effect of ethanol. Taken together, this suggests that the mutagenic effect depends on a complex mechanism, where dysfunctional replication forks lead to recruitment of error-prone polymerases. Apart from providing a general mechanistic framework for the mutagenic effect of ethanol, our findings may also provide a route to better understand and prevent ethanol-associated carcinogenesis in higher eukaryotes.

Gene Loss Predictably Drives Evolutionary Adaptation.

Loss of gene function is common throughout evolution, even though it often leads to reduced fitness. In this study, we systematically evaluated how an organism adapts after deleting genes that are important for growth under oxidative stress. By evolving, sequencing, and phenotyping over 200 yeast lineages, we found that gene loss can enhance an organism's capacity to evolve and adapt. Although gene loss often led to an immediate decrease in fitness, many mutants rapidly acquired suppressor mutations that restored fitness. Depending on the strain's genotype, some ultimately even attained higher fitness levels than similarly adapted wild-type cells. Further, cells with deletions in different modules of the genetic network followed distinct and predictable mutational trajectories. Finally, losing highly connected genes increased evolvability by facilitating the emergence of a more diverse array of phenotypes after adaptation. Together, our findings show that loss of specific parts of a genetic network can facilitate adaptation by opening alternative evolutionary paths.

A new protocol for single-cell RNA-seq reveals stochastic gene expression during lag phase in budding yeast.

Current methods for single-cell RNA sequencing (scRNA-seq) of yeast cells do not match the throughput and relative simplicity of the state-of-the-art techniques that are available for mammalian cells. In this study, we report how 10x Genomics' droplet-based single-cell RNA sequencing technology can be modified to allow analysis of yeast cells. The protocol, which is based on in-droplet spheroplasting of the cells, yields an order-of-magnitude higher throughput in comparison to existing methods. After extensive validation of the method, we demonstrate its use by studying the dynamics of the response of isogenic yeast populations to a shift in carbon source, revealing the heterogeneity and underlying molecular processes during this shift. The method we describe opens new avenues for studies focusing on yeast cells, as well as other cells with a degradable cell wall.

A Hands-On Guide to Brewing and Analyzing Beer in the Laboratory.

Beer would not exist without microbes. During fermentation, yeast cells convert cereal-derived sugars into ethanol and CO2 . Yeast also produces a wide array of aroma compounds that influence beer taste and aroma. The complex interaction between all these aroma compounds results in each beer having its own distinctive palette. This article contains all protocols needed to brew beer in a standard lab environment and focuses on the use of yeast in beer brewing. More specifically, it provides protocols for yeast propagation, brewing calculations and, of course, beer brewing. At the end, we have also included protocols for analyses that can be performed on the resulting brew, with a focus on yeast-derived aroma compounds. © 2019 The Authors.

Domestication of Industrial Microbes.

Domestication refers to artificial selection and breeding of wild species to obtain cultivated variants that thrive in man-made niches and meet human or industrial requirements. Several genotypic and phenotypic signatures of domestication have been described in crops, livestock and pets. However, domestication is not unique to plants and animals. Microbial diversity has also been shaped by the emergence of novel and highly specific man-made environments, like food and beverage fermentations. This allowed rapid adaptation and diversification of various microbes, such as certain Lactococcus, Lactobacillus, Oenococcus, Saccharomyces and Aspergillus species. During the domestication process, microbes gained the capacity to efficiently consume particular nutrients, cope with a multitude of industry-specific stress factors and produce desirable compounds, often at the cost of a reduction in fitness in their original, natural environments. Moreover, different lineages of the same species adapted to highly diverse niches, resulting in genetically and phenotypically distinct strains. In this Review, we discuss the basic principles of microbial domestication and describe how recent research is uncovering its genetic underpinnings.

On the duration of the microbial lag phase.

When faced with environmental changes, microbes enter a lag phase during which cell growth is arrested, allowing cells to adapt to the new situation. The discovery of the lag phase started the field of gene regulation and led to the unraveling of underlying mechanisms. However, the factors determining the exact duration and dynamics of the lag phase remain largely elusive. Naively, one would expect that cells adapt as quickly as possible, so they can resume growth and compete with other organisms. However, recent studies show that the lag phase can last from several hours up to several days. Moreover, some cells within the same population take much longer than others, despite being genetically identical. In addition, the lag phase duration is also influenced by the past, with recent exposure to a given environment leading to a quicker adaptation when that environment returns. Genome-wide screens in Saccharomyces cerevisiae on carbon source shifts now suggest that the length of the lag phase, the heterogeneity in lag times of individual cells, and the history-dependent behavior are not determined by the time it takes to induce a few specific genes related to uptake and metabolism of a new carbon source. Instead, a major shift in general metabolism, and in particular a switch between fermentation and respiration, is the major bottleneck that determines lag duration. This suggests that there may be a fitness trade-off between complete adaptation of a cell's metabolism to a given environment, and a short lag phase when the environment changes.

Variable repeats in the eukaryotic polyubiquitin gene ubi4 modulate proteostasis and stress survival.

Ubiquitin conjugation signals for selective protein degradation by the proteasome. In eukaryotes, ubiquitin is encoded both as a monomeric ubiquitin unit fused to a ribosomal gene and as multiple ubiquitin units in tandem. The polyubiquitin gene is a unique, highly conserved open reading frame composed solely of tandem repeats, yet it is still unclear why cells utilize this unusual gene structure. Using the Saccharomyces cerevisiae UBI4 gene, we show that this multi-unit structure allows cells to rapidly produce large amounts of ubiquitin needed to respond to sudden stress. The number of ubiquitin units encoded by UBI4 influences cellular survival and the rate of ubiquitin-proteasome system (UPS)-mediated proteolysis following heat stress. Interestingly, the optimal number of repeats varies under different types of stress indicating that natural variation in repeat numbers may optimize the chance for survival. Our results demonstrate how a variable polycistronic transcript provides an evolutionary alternative for gene copy number variation.Eukaryotic cells rely on the ubiquitin-proteasome system for selective degradation of proteins, a process vital to organismal fitness. Here the authors show that the number of repeats in the polyubiquitin gene is evolutionarily unstable within and between yeast species, and that this variability may tune the cell's capacity to respond to sudden environmental perturbations.

Adaptive tuning of mutation rates allows fast response to lethal stress in Escherichia coli.

While specific mutations allow organisms to adapt to stressful environments, most changes in an organism's DNA negatively impact fitness. The mutation rate is therefore strictly regulated and often considered a slowly-evolving parameter. In contrast, we demonstrate an unexpected flexibility in cellular mutation rates as a response to changes in selective pressure. We show that hypermutation independently evolves when different Escherichia coli cultures adapt to high ethanol stress. Furthermore, hypermutator states are transitory and repeatedly alternate with decreases in mutation rate. Specifically, population mutation rates rise when cells experience higher stress and decline again once cells are adapted. Interestingly, we identified cellular mortality as the major force driving the quick evolution of mutation rates. Together, these findings show how organisms balance robustness and evolvability and help explain the prevalence of hypermutation in various settings, ranging from emergence of antibiotic resistance in microbes to cancer relapses upon chemotherapy.

Dual loss of succinate dehydrogenase (SDH) and complex I activity is necessary to recapitulate the metabolic phenotype of SDH mutant tumors.

Mutations in succinate dehydrogenase (SDH) are associated with tumor development and neurodegenerative diseases. Only in tumors, loss of SDH activity is accompanied with the loss of complex I activity. Yet, it remains unknown whether the metabolic phenotype of SDH mutant tumors is driven by loss of complex I function, and whether this contributes to the peculiarity of tumor development versus neurodegeneration. We addressed this question by decoupling loss of SDH and complex I activity in cancer cells and neurons. We found that sole loss of SDH activity was not sufficient to recapitulate the metabolic phenotype of SDH mutant tumors, because it failed to decrease mitochondrial respiration and to activate reductive glutamine metabolism. These metabolic phenotypes were only induced upon the additional loss of complex I activity. Thus, we show that complex I function defines the metabolic differences between SDH mutation associated tumors and neurodegenerative diseases, which could open novel therapeutic options against both diseases.

Domestication and Divergence of Saccharomyces cerevisiae Beer Yeasts.

Whereas domestication of livestock, pets, and crops is well documented, it is still unclear to what extent microbes associated with the production of food have also undergone human selection and where the plethora of industrial strains originates from. Here, we present the genomes and phenomes of 157 industrial Saccharomyces cerevisiae yeasts. Our analyses reveal that today's industrial yeasts can be divided into five sublineages that are genetically and phenotypically separated from wild strains and originate from only a few ancestors through complex patterns of domestication and local divergence. Large-scale phenotyping and genome analysis further show strong industry-specific selection for stress tolerance, sugar utilization, and flavor production, while the sexual cycle and other phenotypes related to survival in nature show decay, particularly in beer yeasts. Together, these results shed light on the origins, evolutionary history, and phenotypic diversity of industrial yeasts and provide a resource for further selection of superior strains. PAPERCLIP.

How do yeast cells become tolerant to high ethanol concentrations?

The brewer's yeast Saccharomyces cerevisiae displays a much higher ethanol tolerance compared to most other organisms, and it is therefore commonly used for the industrial production of bioethanol and alcoholic beverages. However, the genetic determinants underlying this yeast's exceptional ethanol tolerance have proven difficult to elucidate. In this perspective, we discuss how different types of experiments have contributed to our understanding of the toxic effects of ethanol and the mechanisms and complex genetics underlying ethanol tolerance. In a second part, we summarize the different routes and challenges involved in obtaining superior industrial yeasts with improved ethanol tolerance.

Adaptation to High Ethanol Reveals Complex Evolutionary Pathways.

Tolerance to high levels of ethanol is an ecologically and industrially relevant phenotype of microbes, but the molecular mechanisms underlying this complex trait remain largely unknown. Here, we use long-term experimental evolution of isogenic yeast populations of different initial ploidy to study adaptation to increasing levels of ethanol. Whole-genome sequencing of more than 30 evolved populations and over 100 adapted clones isolated throughout this two-year evolution experiment revealed how a complex interplay of de novo single nucleotide mutations, copy number variation, ploidy changes, mutator phenotypes, and clonal interference led to a significant increase in ethanol tolerance. Although the specific mutations differ between different evolved lineages, application of a novel computational pipeline, PheNetic, revealed that many mutations target functional modules involved in stress response, cell cycle regulation, DNA repair and respiration. Measuring the fitness effects of selected mutations introduced in non-evolved ethanol-sensitive cells revealed several adaptive mutations that had previously not been implicated in ethanol tolerance, including mutations in PRT1, VPS70 and MEX67. Interestingly, variation in VPS70 was recently identified as a QTL for ethanol tolerance in an industrial bio-ethanol strain. Taken together, our results show how, in contrast to adaptation to some other stresses, adaptation to a continuous complex and severe stress involves interplay of different evolutionary mechanisms. In addition, our study reveals functional modules involved in ethanol resistance and identifies several mutations that could help to improve the ethanol tolerance of industrial yeasts.