Polymorphisms in multiple genes contribute to the spontaneous mitochondrial genome instability of Saccharomyces cerevisiae S288C strains

Spontaneous single-nucleotide substitutions and microsatellite mutations have distinct distributions of fitness effects

The fitness effects of new mutations determine key properties of evolutionary processes. Beneficial mutations drive evolution, yet selection is also shaped by the frequency of small-effect deleterious mutations, whose combined effect can burden otherwise adaptive lineages and alter evolutionary trajectories and outcomes in clonally evolving organisms such as viruses, microbes, and tumors. The small effect sizes of these important mutations have made accurate measurements of their rates difficult. In microbes, assessing the effect of mutations on growth can be especially instructive, as this complex phenotype is closely linked to fitness in clonally evolving organisms. Here, we perform high-throughput time-lapse microscopy on cells from mutation-accumulation strains to precisely infer the distribution of mutational effects on growth rate in the budding yeast, Saccharomyces cerevisiae. We show that mutational effects on growth rate are overwhelmingly negative, highly skewed towards very small effect sizes, and frequent enough to suggest that deleterious hitchhikers may impose a significant burden on evolving lineages. By using lines that accumulated mutations in either wild-type or slippage repair-defective backgrounds, we further disentangle the effects of 2 common types of mutations, single-nucleotide substitutions and simple sequence repeat indels, and show that they have distinct effects on yeast growth rate. Although the average effect of a simple sequence repeat mutation is very small (approximately 0.3%), many do alter growth rate, implying that this class of frequent mutations has an important evolutionary impact.

Spontaneous single-nucleotide substitutions and microsatellite mutations have distinct distributions of fitness effects

The fitness effects of new mutations determine key properties of evolutionary processes. Beneficial mutations drive evolution, yet selection is also shaped by the frequency of small-effect deleterious mutations, whose combined effect can burden otherwise adaptive lineages and alter evolutionary trajectories and outcomes in clonally evolving organisms such as viruses, microbes, and tumors. The small effect sizes of these important mutations have made accurate measurements of their rates difficult. In microbes, assessing the effect of mutations on growth can be especially instructive, as this complex phenotype is closely linked to fitness in clonally evolving organisms. Here, we perform high-throughput time-lapse microscopy on cells from mutation-accumulation strains to precisely infer the distribution of mutational effects on growth rate in the budding yeast, Saccharomyces cerevisiae. We show that mutational effects on growth rate are overwhelmingly negative, highly skewed towards very small effect sizes, and frequent enough to suggest that deleterious hitchhikers may impose a significant burden on evolving lineages. By using lines that accumulated mutations in either wild-type or slippage repair-defective backgrounds, we further disentangle the effects of two common types of mutations, single-nucleotide substitutions and simple sequence repeat indels, and show that they have distinct effects on yeast growth rate. Although the average effect of a simple sequence repeat mutation is very small (~0.3%), many do alter growth rate, implying that this class of frequent mutations has an important evolutionary impact.

Loss of mitochondrial DNA is associated with reduced DNA content variability in Saccharomyces cerevisiae

DNA content measurement by fluorescence-assisted cell sorting (FACS) provides information on cell cycle progression and DNA content variability. Saccharomyces cerevisiae mutants with DNA content variability that was reduced relative to wild-type strains had defects in mitochondrial DNA (mtDNA) maintenance and mitochondrial gene expression and were correlated with strains found to lack mtDNA ([ rho 0 ] cells) by genome sequencing and fluorescence microscopy. In contrast, mutants with increased variability had defects in cell cycle progression, which may indicate a loss of coordination between mtDNA and nuclear DNA replication. Thus, FACS measurement of DNA content variability can provide insight into cell-to-cell heterogeneity in mtDNA copy number.

Spontaneous Mutations in Saccharomyces cerevisiae mtDNA Increase Cell-to-Cell Variation in mtDNA Amount

In a eukaryotic cell, the ratio of mitochondrial DNA (mtDNA) to nuclear DNA (nDNA) is usually maintained within a specific range. This suggests the presence of a negative feedback loop mechanism preventing extensive mtDNA replication and depletion. However, the experimental data on this hypothetical mechanism are limited. In this study, we suggested that deletions in mtDNA, known to increase mtDNA abundance, can disrupt this mechanism, and thus, increase cell-to-cell variance in the mtDNA copy numbers. To test this, we generated Saccharomyces cerevisiae rho- strains with large deletions in the mtDNA and rho0 strains depleted of mtDNA. Given that mtDNA contributes to the total DNA content of exponentially growing yeast cells, we showed that it can be quantified in individual cells by flow cytometry using the DNA-intercalating fluorescent dye SYTOX green. We found that the rho- mutations increased both the levels and cell-to-cell heterogeneity in the total DNA content of G1 and G2/M yeast cells, with no association with the cell size. Furthermore, the depletion of mtDNA in both the rho+ and rho- strains significantly decreased the SYTOX green signal variance. The high cell-to-cell heterogeneity of the mtDNA amount in the rho- strains suggests that mtDNA copy number regulation relies on full-length mtDNA, whereas the rho- mtDNAs partially escape this regulation.

Schrödinger's yeast: the challenge of using transformation to compare fitness among Saccharomyces cerevisiae that differ in ploidy or zygosity

How the number of genome copies modifies the effect of random mutations remains poorly known. In yeast, researchers have investigated these effects for knock-out or other large-effect mutations, but have not accounted for differences at the mating-type locus. We set out to compare fitness differences among strains that differ in ploidy and/or zygosity using a panel of spontaneously arising mutations acquired in haploid yeast from a previous study. To ensure no genetic differences, even at the mating-type locus, we embarked on a series of transformations, which first sterilized and then temporarily introduced plasmid-borne mating types. Despite these attempts to equalize the haplotypes, fitness variation introduced during transformation swamped the differences among the original mutation-accumulation lines. While colony size looked normal, we observed a bi-modality in the maximum growth rate of our transformed yeast and determined that many of the slow growing lines were respiratory deficient ("petite"). Not previously reported, we found that yeast that were TID1/RDH54 knockouts were less likely to become petite. Even for lines with the same petite status, however, we found no correlation in fitness between the two replicate transformations performed. These results pose a challenge for any study using transformation to measure the fitness effect of genetic differences among strains. By attempting to hold haplotypes constant, we introduced more mutations that overwhelmed our ability to measure fitness differences between the genetic states. In this study, we transformed over one hundred different lines of yeast, using two independent transformations, and found that this common laboratory procedure can cause large changes to the microbe studied. Our study provides a cautionary tale of the need to use multiple transformants in fitness assays.

Haem's relevance genuine? Re-visiting the roles of TANGO2 homologues including HRG-9 and HRG-10 in C. elegans

Mutations in the TANGO2 gene cause severe illness in humans, including life-threatening metabolic crises; however, the function of TANGO2 protein remains unknown. In a recent publication in Nature, Sun et al. proposed that TANGO2 helps transport haem within and between cells, from areas with high haem concentrations to those with lower concentrations. Caenorhabditis elegans has two versions of TANGO2 that Sun et al. called HRG-9 and HRG-10. They demonstrated that worms deficient in these proteins show increased survival upon exposure to a toxic haem analog, which Sun et al. interpreted as evidence of decreased haem uptake from intestinal cells into the rest of the organism. We repeated several experiments using the same C. elegans strain as Sun et al. and believe that their findings are better explained by reduced feeding behavior in these worms. We demonstrate that hrg-9 in particular is highly responsive to oxidative stress, independent of haem status. Our group also performed several experiments in yeast and zebrafish models of TANGO2 deficiency and was unable to replicate key findings from these models reported in Sun et al.'s original study. Overall, we believe there is insufficient evidence to support haem transport as the primary function for TANGO2.

MKT1 alleles regulate stress responses through posttranscriptional modulation of Puf3 targets in budding yeast

MKT1 is a pleiotropic stress response gene identified by several quantitative trait studies with MKT189G as a causal variant, contributing to growth advantage in multiple stress environments. MKT1 has been shown to regulate HO endonuclease posttranscriptionally via the Pbp1-Pab1 complex. RNA-binding protein Puf3 modulates a set of nuclear-encoded mitochondrial transcripts whose expression was found to be affected by MKT1 alleles. This study attempts to relate the MKT1 allele-derived growth advantage with the stability of Puf3 targets during stress and elucidate the roles of Pbp1 and Puf3 in this mechanism. Our results showed that the growth advantage of the MKT189G allele in cycloheximide and H2 O2 was PBP1-dependent, whereas in 4-nitroquinoline 1-oxide, the growth advantage was dependent on both PUF3 and PBP1. We compared the messenger RNA decay kinetics of a set of Puf3 targets in multiple stress environments to understand the allele-specific regulation by MKT1. In oxidative stress, the MKT189G allele modulated the differential expression of nuclear-encoded mitochondrial genes in a PBP1- and PUF3-dependent manner. Additionally, MKT189G stabilised Puf3 targets, namely, COX17, MRS1 and RDL2, in an allele and stress-specific manner. Our results showed that COX17, MRS1 and RDL2 had a stress-specific response in stress environments, with the MKT189G allele contributing to better growth; this response was both PBP1- and PUF3-dependent. Our results indicate that the common allele, MKT189G , regulates stress responses by differentially stabilising Puf3-target mitochondrial genes, which allows for the strain's better growth in stress environments.

The Saccharomyces cerevisiae mitochondrial DNA polymerase and its contribution to the knowledge about human POLG-related disorders

Most eukaryotes possess a mitochondrial genome, called mtDNA. In animals and fungi, the replication of mtDNA is entrusted by the DNA polymerase γ, or Pol γ. The yeast Pol γ is composed only of a catalytic subunit encoded by MIP1. In humans, Pol γ is a heterotrimer composed of a catalytic subunit homolog to Mip1, encoded by POLG, and two accessory subunits. In the last 25 years, more than 300 pathological mutations in POLG have been identified as the cause of several mitochondrial diseases, called POLG-related disorders, which are characterized by multiple mtDNA deletions and/or depletion in affected tissues. In this review, at first, we summarize the biochemical properties of yeast Mip1, and how mutations, especially those introduced recently in the N-terminal and C-terminal regions of the enzyme, affect the in vitro activity of the enzyme and the in vivo phenotype connected to the mtDNA stability and to the mtDNA extended and point mutability. Then, we focus on the use of yeast harboring Mip1 mutations equivalent to the human ones to confirm their pathogenicity, identify the phenotypic defects caused by these mutations, and find both mechanisms and molecular compounds able to rescue the detrimental phenotype. A closing chapter will be dedicated to other polymerases found in yeast mitochondria, namely Pol ζ, Rev1 and Pol η, and to their genetic interactions with Mip1 necessary to maintain mtDNA stability and to avoid the accumulation of spontaneous or induced point mutations.

Genome mining yields putative disease-associated ROMK variants with distinct defects

Bartter syndrome is a group of rare genetic disorders that compromise kidney function by impairing electrolyte reabsorption. Left untreated, the resulting hyponatremia, hypokalemia, and dehydration can be fatal, and there is currently no cure. Bartter syndrome type II specifically arises from mutations in KCNJ1, which encodes the renal outer medullary potassium channel, ROMK. Over 40 Bartter syndrome-associated mutations in KCNJ1 have been identified, yet their molecular defects are mostly uncharacterized. Nevertheless, a subset of disease-linked mutations compromise ROMK folding in the endoplasmic reticulum (ER), which in turn results in premature degradation via the ER associated degradation (ERAD) pathway. To identify uncharacterized human variants that might similarly lead to premature degradation and thus disease, we mined three genomic databases. First, phenotypic data in the UK Biobank were analyzed using a recently developed computational platform to identify individuals carrying KCNJ1 variants with clinical features consistent with Bartter syndrome type II. In parallel, we examined genomic data in both the NIH TOPMed and ClinVar databases with the aid of Rhapsody, a verified computational algorithm that predicts mutation pathogenicity and disease severity. Subsequent phenotypic studies using a yeast screen to assess ROMK function-and analyses of ROMK biogenesis in yeast and human cells-identified four previously uncharacterized mutations. Among these, one mutation uncovered from the two parallel approaches (G228E) destabilized ROMK and targeted it for ERAD, resulting in reduced cell surface expression. Another mutation (T300R) was ERAD-resistant, but defects in channel activity were apparent based on two-electrode voltage clamp measurements in X. laevis oocytes. Together, our results outline a new computational and experimental pipeline that can be applied to identify disease-associated alleles linked to a range of other potassium channels, and further our understanding of the ROMK structure-function relationship that may aid future therapeutic strategies to advance precision medicine.

A physicochemical perspective on cellular ageing

Cellular ageing described at the molecular level is a multifactorial process that leads to a spectrum of ageing trajectories. There has been recent discussion about whether a decline in physicochemical homeostasis causes aberrant phase transitions, which are a driver of ageing. Indeed, the function of all biological macromolecules, regardless of their participation in biomolecular condensates, depends on parameters such as pH, crowding, and redox state. We expand on the physicochemical homeostasis hypothesis and summarise recent evidence that the intracellular milieu influences molecular processes involved in ageing.

Gene-by-environment interactions influence the fitness cost of gene copy-number variation in yeast

Variation in gene copy number can alter gene expression and influence downstream phenotypes; thus copy-number variation provides a route for rapid evolution if the benefits outweigh the cost. We recently showed that genetic background significantly influences how yeast cells respond to gene overexpression, revealing that the fitness costs of copy-number variation can vary substantially with genetic background in a common-garden environment. But the interplay between copy-number variation tolerance and environment remains unexplored on a genomic scale. Here, we measured the tolerance to gene overexpression in four genetically distinct Saccharomyces cerevisiae strains grown under sodium chloride stress. Overexpressed genes that are commonly deleterious during sodium chloride stress recapitulated those commonly deleterious under standard conditions. However, sodium chloride stress uncovered novel differences in strain responses to gene overexpression. West African strain NCYC3290 and North American oak isolate YPS128 are more sensitive to sodium chloride stress than vineyard BC187 and laboratory strain BY4743. Consistently, NCYC3290 and YPS128 showed the greatest sensitivities to overexpression of specific genes. Although most genes were deleterious, hundreds were beneficial when overexpressed-remarkably, most of these effects were strain specific. Few beneficial genes were shared between the sodium chloride-sensitive isolates, implicating mechanistic differences behind their sodium chloride sensitivity. Transcriptomic analysis suggested underlying vulnerabilities and tolerances across strains, and pointed to natural copy-number variation of a sodium export pump that likely contributes to strain-specific responses to overexpression of other genes. Our results reveal extensive strain-by-environment interactions in the response to gene copy-number variation, raising important implications for the accessibility of copy-number variation-dependent evolutionary routes under times of stress.

Role of genetic architecture in phenotypic plasticity

Phenotypic plasticity, the ability of an organism to display different phenotypes across environments, is widespread in nature. Plasticity aids survival in novel environments. Herein, we review studies from yeast that allow us to start uncovering the genetic architecture of phenotypic plasticity. Genetic variants and their interactions impact the phenotype in different environments, and distinct environments modulate the impact of genetic variants and their interactions on the phenotype. Because of this, certain hidden genetic variation is expressed in specific genetic and environmental backgrounds. A better understanding of the genetic mechanisms of phenotypic plasticity will help to determine short- and long-term responses to selection and how wide variation in disease manifestation occurs in human populations.

Plant biochemical genetics in the multiomics era

Our understanding of plant biology has been revolutionized by modern genetics and biochemistry. However, biochemical genetics can be traced back to the foundation of Mendelian genetics; indeed, one of Mendel's milestone discoveries of seven characteristics of pea plants later came to be ascribed to a mutation in a starch branching enzyme. Here, we review both current and historical strategies for the elucidation of plant metabolic pathways and the genes that encode their component enzymes and regulators. We use this historical review to discuss a range of classical genetic phenomena including epistasis, canalization, and heterosis as viewed through the lens of contemporary high-throughput data obtained via the array of approaches currently adopted in multiomics studies.

Genetic effects on molecular network states explain complex traits

The complexity of many cellular and organismal traits results from the integration of genetic and environmental factors via molecular networks. Network structure and effect propagation are best understood at the level of functional modules, but so far, no concept has been established to include the global network state. Here, we show when and how genetic perturbations lead to molecular changes that are confined to small parts of a network versus when they lead to modulation of network states. Integrating multi-omics profiling of genetically heterogeneous budding and fission yeast strains with an array of cellular traits identified a central state transition of the yeast molecular network that is related to PKA and TOR (PT) signaling. Genetic variants affecting this PT state globally shifted the molecular network along a single-dimensional axis, thereby modulating processes including energy and amino acid metabolism, transcription, translation, cell cycle control, and cellular stress response. We propose that genetic effects can propagate through large parts of molecular networks because of the functional requirement to centrally coordinate the activity of fundamental cellular processes.

Gene-by-environment interactions influence the fitness cost of gene copy-number variation in yeast

Variation in gene copy number can alter gene expression and influence downstream phenotypes; thus copy-number variation (CNV) provides a route for rapid evolution if the benefits outweigh the cost. We recently showed that genetic background significantly influences how yeast cells respond to gene over-expression (OE), revealing that the fitness costs of CNV can vary substantially with genetic background in a common-garden environment. But the interplay between CNV tolerance and environment remains unexplored on a genomic scale. Here we measured the tolerance to gene OE in four genetically distinct Saccharomyces cerevisiae strains grown under sodium chloride (NaCl) stress. OE genes that are commonly deleterious during NaCl stress recapitulated those commonly deleterious under standard conditions. However, NaCl stress uncovered novel differences in strain responses to gene OE. West African strain NCYC3290 and North American oak isolate YPS128 are more sensitive to NaCl stress than vineyard BC187 and laboratory strain BY4743. Consistently, NCYC3290 and YPS128 showed the greatest sensitivities to gene OE. Although most genes were deleterious, hundreds were beneficial when overexpressed - remarkably, most of these effects were strain specific. Few beneficial genes were shared between the NaCl-sensitive isolates, implicating mechanistic differences behind their NaCl sensitivity. Transcriptomic analysis suggested underlying vulnerabilities and tolerances across strains, and pointed to natural CNV of a sodium export pump that likely contributes to strain-specific responses to OE of other genes. Our results reveal extensive strain-by-environment interaction in the response to gene CNV, raising important implications for the accessibility of CNV-dependent evolutionary routes under times of stress.

Formation of Transient Protein Aggregate-like Centers Is a General Strategy Postponing Degradation of Misfolded Intermediates

When misfolded intermediates accumulate during heat shock, the protein quality control system promotes cellular adaptation strategies. In Schizosaccharomyces pombe, thermo-sensitive proteins assemble upon stress into protein aggregate-like centers, PACs, to escape from degradation. The role of this protein deposition strategy has been elusive due to the use of different model systems and reporters, and to the addition of artificial inhibitors, which made interpretation of the results difficult. Here, we compare fission and budding yeast model systems, expressing the same misfolding reporters in experiments lacking proteasome or translation inhibitors. We demonstrate that mild heat shock triggers reversible PAC formation, with the collapse of both reporters and chaperones in a process largely mediated by chaperones. This assembly postpones proteasomal degradation of the misfolding reporters, and their Hsp104-dependent disassembly occurs during stress recovery. Severe heat shock induces formation of cytosolic PACs, but also of nuclear structures resembling nucleolar rings, NuRs, presumably to halt nuclear functions. Our study demonstrates that these distantly related yeasts use very similar strategies to adapt and survive to mild and severe heat shock and that aggregate-like formation is a general cellular scheme to postpone protein degradation and facilitate exit from stress.

Contributions of mutation and selection to regulatory variation: lessons from the Saccharomyces cerevisiae TDH3 gene

Heritable variation in gene expression is common within and among species and contributes to phenotypic diversity. Mutations affecting either cis- or trans-regulatory sequences controlling gene expression give rise to variation in gene expression, and natural selection acting on this variation causes some regulatory variants to persist in a population for longer than others. To understand how mutation and selection interact to produce the patterns of regulatory variation we see within and among species, my colleagues and I have been systematically determining the effects of new mutations on expression of the TDH3 gene in Saccharomyces cerevisiae and comparing them to the effects of polymorphisms segregating within this species. We have also investigated the molecular mechanisms by which regulatory variants act. Over the past decade, this work has revealed properties of cis- and trans-regulatory mutations including their relative frequency, effects, dominance, pleiotropy and fitness consequences. Comparing these mutational effects to the effects of polymorphisms in natural populations, we have inferred selection acting on expression level, expression noise and phenotypic plasticity. Here, I summarize this body of work and synthesize its findings to make inferences not readily discernible from the individual studies alone. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Genome mining yields new disease-associated ROMK variants with distinct defects

Bartter syndrome is a group of rare genetic disorders that compromise kidney function by impairing electrolyte reabsorption. Left untreated, the resulting hyponatremia, hypokalemia, and dehydration can be fatal. Although there is no cure for this disease, specific genes that lead to different Bartter syndrome subtypes have been identified. Bartter syndrome type II specifically arises from mutations in the KCNJ1 gene, which encodes the renal outer medullary potassium channel, ROMK. To date, over 40 Bartter syndrome-associated mutations in KCNJ1 have been identified. Yet, their molecular defects are mostly uncharacterized. Nevertheless, a subset of disease-linked mutations compromise ROMK folding in the endoplasmic reticulum (ER), which in turn results in premature degradation via the ER associated degradation (ERAD) pathway. To identify uncharacterized human variants that might similarly lead to premature degradation and thus disease, we mined three genomic databases. First, phenotypic data in the UK Biobank were analyzed using a recently developed computational platform to identify individuals carrying KCNJ1 variants with clinical features consistent with Bartter syndrome type II. In parallel, we examined ROMK genomic data in both the NIH TOPMed and ClinVar databases with the aid of a computational algorithm that predicts protein misfolding and disease severity. Subsequent phenotypic studies using a high throughput yeast screen to assess ROMK function-and analyses of ROMK biogenesis in yeast and human cells-identified four previously uncharacterized mutations. Among these, one mutation uncovered from the two parallel approaches (G228E) destabilized ROMK and targeted it for ERAD, resulting in reduced protein expression at the cell surface. Another ERAD-targeted ROMK mutant (L320P) was found in only one of the screens. In contrast, another mutation (T300R) was ERAD-resistant, but defects in ROMK activity were apparent after expression and two-electrode voltage clamp measurements in Xenopus oocytes. Together, our results outline a new computational and experimental pipeline that can be applied to identify disease-associated alleles linked to a range of other potassium channels, and further our understanding of the ROMK structure-function relationship that may aid future therapeutic strategies.

Author Summary

Bartter syndrome is a rare genetic disorder characterized by defective renal electrolyte handing, leading to debilitating symptoms and, in some patients, death in infancy. Currently, there is no cure for this disease. Bartter syndrome is divided into five types based on the causative gene. Bartter syndrome type II results from genetic variants in the gene encoding the ROMK protein, which is expressed in the kidney and assists in regulating sodium, potassium, and water homeostasis. Prior work established that some disease-associated ROMK mutants misfold and are destroyed soon after their synthesis in the endoplasmic reticulum (ER). Because a growing number of drugs have been identified that correct defective protein folding, we wished to identify an expanded cohort of similarly misshapen and unstable disease-associated ROMK variants. To this end, we developed a pipeline that employs computational analyses of human genome databases with genetic and biochemical assays. Next, we both confirmed the identity of known variants and uncovered previously uncharacterized ROMK variants associated with Bartter syndrome type II. Further analyses indicated that select mutants are targeted for ER-associated degradation, while another mutant compromises ROMK function. This work sets-the-stage for continued mining for ROMK loss of function alleles as well as other potassium channels, and positions select Bartter syndrome mutations for correction using emerging pharmaceuticals.

Mapping mitonuclear epistasis using a novel recombinant yeast population

Genetic variation in mitochondrial and nuclear genomes can perturb mitonuclear interactions and lead to phenotypic differences between individuals and populations. Despite their importance to most complex traits, it has been difficult to identify the interacting mitonuclear loci. Here, we present a novel advanced intercrossed population of Saccharomyces cerevisiae yeasts, called the Mitonuclear Recombinant Collection (MNRC), designed explicitly for detecting mitonuclear loci contributing to complex traits. For validation, we focused on mapping genes that contribute to the spontaneous loss of mitochondrial DNA (mtDNA) that leads to the petite phenotype in yeast. We found that rates of petite formation in natural populations are variable and influenced by genetic variation in nuclear DNA, mtDNA and mitonuclear interactions. We mapped nuclear and mitonuclear alleles contributing to mtDNA stability using the MNRC by integrating a term for mitonuclear epistasis into a genome-wide association model. We found that the associated mitonuclear loci play roles in mitotic growth most likely responding to retrograde signals from mitochondria, while the associated nuclear loci with main effects are involved in genome replication. We observed a positive correlation between growth rates and petite frequencies, suggesting a fitness tradeoff between mitotic growth and mtDNA stability. We also found that mtDNA stability was correlated with a mobile mitochondrial GC-cluster that is present in certain populations of yeast and that selection for nuclear alleles that stabilize mtDNA may be rapidly occurring. The MNRC provides a powerful tool for identifying mitonuclear interacting loci that will help us to better understand genotype-phenotype relationships and coevolutionary trajectories.

Spontaneous Mutation Rates and Spectra of Respiratory-Deficient Yeast

The yeast petite mutant was first discovered in the yeast Saccharomyces cerevisiae, which shows growth stress due to defects in genes encoding the respiratory chain. In a previous study, we described that deletion of the nuclear-encoded gene MRPL25 leads to mitochondrial genome (mtDNA) loss and the petite phenotype, which can be rescued by acquiring ATP3 mutations. The mrpl25Δ strain showed an elevated SNV (single nucleotide variant) rate, suggesting genome instability occurred during the crisis of mtDNA loss. However, the genome-wide mutation landscape and mutational signatures of mitochondrial dysfunction are unknown. In this study we profiled the mutation spectra in yeast strains with the genotype combination of MRPL25 and ATP3 in their wildtype and mutated status, along with the wildtype and cytoplasmic petite rho0 strains as controls. In addition to the previously described elevated SNV rate, we found the INDEL (insertion/deletion) rate also increased in the mrpl25Δ strain, reinforcing the occurrence of genome instability. Notably, although both are petites, the mrpl25Δ and rho0 strains exhibited different INDEL rates and transition/transversion ratios, suggesting differences in the mutational signatures underlying these two types of petites. Interestingly, the petite-related mutagenesis effect disappeared when ATP3 suppressor mutations were acquired, suggesting a cost-effective mechanism for restoring both fitness and genome stability. Taken together, we present an unbiased genome-wide characterization of the mutation rates and spectra of yeast strains with respiratory deficiency, which provides valuable insights into the impact of respiratory deficiency on genome instability.

petiteFinder: an automated computer vision tool to compute Petite colony frequencies in baker's yeast

BACKGROUND

Mitochondrial respiration is central to cellular and organismal health in eukaryotes. In baker's yeast, however, respiration is dispensable under fermentation conditions. Because yeast are tolerant of this mitochondrial dysfunction, yeast are widely used by biologists as a model organism to ask a variety of questions about the integrity of mitochondrial respiration. Fortunately, baker's yeast also display a visually identifiable Petite colony phenotype that indicates when cells are incapable of respiration. Petite colonies are smaller than their Grande (wild-type) counterparts, and their frequency can be used to infer the integrity of mitochondrial respiration in populations of cells. Unfortunately, the computation of Petite colony frequencies currently relies on laborious manual colony counting methods which limit both experimental throughput and reproducibility.

RESULTS

To address these problems, we introduce a deep learning enabled tool, petiteFinder, that increases the throughput of the Petite frequency assay. This automated computer vision tool detects Grande and Petite colonies and computes Petite colony frequencies from scanned images of Petri dishes. It achieves accuracy comparable to human annotation but at up to 100 times the speed and outperforms semi-supervised Grande/Petite colony classification approaches. Combined with the detailed experimental protocols we provide, we believe this study can serve as a foundation to standardize this assay. Finally, we comment on how Petite colony detection as a computer vision problem highlights ongoing difficulties with small object detection in existing object detection architectures.

CONCLUSION

Colony detection with petiteFinder results in high accuracy Petite and Grande detection in images in a completely automated fashion. It addresses issues in scalability and reproducibility of the Petite colony assay which currently relies on manual colony counting. By constructing this tool and providing details of experimental conditions, we hope this study will enable larger-scale experiments that rely on Petite colony frequencies to infer mitochondrial function in yeast.

Maize cytolines as models to study the impact of different cytoplasms on gene expression under heat stress conditions

BACKGROUND

Crops are under constant pressure due to global warming, which unfolds at a much faster pace than their ability to adapt through evolution. Agronomic traits are linked to cytoplasmic-nuclear genome interactions. It thus becomes important to understand the influence exerted by the organelles on gene expression under heat stress conditions and profit from the available genetic diversity. Maize (Zea mays) cytolines allow us to investigate how the gene expression changes under heat stress conditions in three different cytoplasmic environments, but each having the same nucleus. Analyzing retrograde signaling in such an experimental set-up has never been done before. Here, we quantified the response of three cytolines to heat stress as differentially expressed genes (DEGs), and studied gene expression patterns in the context of existing polymorphism in their organellar genomes.

RESULTS

Our study unveils a plethora of new genes and GO terms that are differentially expressed or enriched, respectively, in response to heat stress. We report 19,600 DEGs as responding to heat stress (out of 30,331 analyzed), which significantly enrich 164 GO biological processes, 30 GO molecular functions, and 83 GO cell components. Our approach allowed for the discovery of a significant number of DEGs and GO terms that are not common in the three cytolines and could therefore be linked to retrograde signaling. Filtering for DEGs with a fold regulation > 2 (absolute values) that are exclusive to just one of the cytolines, we find a total of 391 up- and down-DEGs. Similarly, there are 19 GO terms with a fold enrichment > 2 that are cytoline-specific. Using GBS data we report contrasting differences in the number of DEGs and GO terms in each cytoline, which correlate with the genetic distances between the mitochondrial genomes (but not chloroplast) and the original nuclei of the cytolines, respectively.

CONCLUSIONS

The experimental design used here adds a new facet to the paradigm used to explain how gene expression changes in response to heat stress, capturing the influence exerted by different organelles upon one nucleus rather than investigating the response of several nuclei in their innate cytoplasmic environments.

Nab3 nuclear granule accumulation is driven by respiratory capacity

Numerous biological processes involve proteins capable of transiently assembling into subcellular compartments necessary for cellular functions. One process is the RNA polymerase II transcription cycle which involves initiation, elongation, co-transcriptional modification of nascent RNA, and termination. The essential yeast transcription termination factor Nab3 is required for termination of small non-coding RNAs and accumulates into a compact nuclear granule upon glucose removal. Nab3 nuclear granule accumulation varies in penetrance across yeast strains and a higher Nab3 granule accumulation phenotype is associated with petite strains, suggesting a possible ATP-dependent mechanism for granule disassembly. Here, we demonstrate the uncoupling of mitochondrial oxidative phosphorylation by drug treatment or deletions of nuclear-encoded ATP synthase subunit genes were sufficient to increase Nab3 granule accumulation and led to an inability to proliferate during prolonged glucose deprivation, which requires respiration. Additionally, by enriching for respiration competent cells from a petite-prone strain, we generated a low granule-accumulating strain from a relatively high one, providing another link between respiratory competency and Nab3 granules. Consistent with the resulting idea that ATP is involved in granule accumulation, the addition of extracellular ATP to semi-permeabilized cells was sufficient to reduce Nab3 granule accumulation. Deleting the SKY1 gene, which encodes a kinase that phosphorylates nuclear SR repeat-containing proteins and is involved in efficient stress granule disassembly, also resulted in increased granule accumulation. This observation implicates Sky1 in Nab3 granule biogenesis. Taken together, these findings suggest there is normally an equilibrium between termination factor granule assembly and disassembly mediated by ATP-requiring nuclear machinery.

High-throughput approaches to functional characterization of genetic variation in yeast

Expansion of sequencing efforts to include thousands of genomes is providing a fundamental resource for determining the genetic diversity that exists in a population. Now, high-throughput approaches are necessary to begin to understand the role these genotypic changes play in affecting phenotypic variation. Saccharomyces cerevisiae maintains its position as an excellent model system to determine the function of unknown variants with its exceptional genetic diversity, phenotypic diversity, and reliable genetic manipulation tools. Here, we review strategies and techniques developed in yeast that scale classic approaches of assessing variant function. These approaches improve our ability to better map quantitative trait loci at a higher resolution, even for rare variants, and are already providing greater insight into the role that different types of mutations play in phenotypic variation and evolution not just in yeast but across taxa.

Complex genetics cause and constrain fungal persistence in different parts of the mammalian body

Determining how genetic polymorphisms enable certain fungi to persist in mammalian hosts can improve understanding of opportunistic fungal pathogenesis, a source of substantial human morbidity and mortality. We examined the genetic basis of fungal persistence in mice using a cross between a clinical isolate and the lab reference strain of the budding yeast Saccharomyces cerevisiae. Employing chromosomally encoded DNA barcodes, we tracked the relative abundances of 822 genotyped, haploid segregants in multiple organs over time and performed linkage mapping of their persistence in hosts. Detected loci showed a mix of general and antagonistically pleiotropic effects across organs. General loci showed similar effects across all organs, while antagonistically pleiotropic loci showed contrasting effects in the brain vs the kidneys, liver, and spleen. Persistence in an organ required both generally beneficial alleles and organ-appropriate pleiotropic alleles. This genetic architecture resulted in many segregants persisting in the brain or in nonbrain organs, but few segregants persisting in all organs. These results show complex combinations of genetic polymorphisms collectively cause and constrain fungal persistence in different parts of the mammalian body.

CRISPR/Cas9-mediated point mutations improve α-amylase secretion in Saccharomyces cerevisiae

The rapid expansion of the application of pharmaceutical proteins and industrial enzymes requires robust microbial workhorses for high protein production. The budding yeast Saccharomyces cerevisiae is an attractive cell factory due to its ability to perform eukaryotic post-translational modifications and to secrete proteins. Many strategies have been used to engineer yeast platform strains for higher protein secretion capacity. Herein, we investigated a line of strains that have previously been selected after UV random mutagenesis for improved α-amylase secretion. A total of 42 amino acid altering point mutations identified in this strain line were reintroduced into the parental strain AAC to study their individual effects on protein secretion. These point mutations included missense mutations (amino acid substitution), nonsense mutations (stop codon generation), and frameshift mutations. For comparison, single gene deletions for the corresponding target genes were also performed in this study. A total of 11 point mutations and seven gene deletions were found to effectively improve α-amylase secretion. These targets were involved in several bioprocesses, including cellular stresses, protein degradation, transportation, mRNA processing and export, DNA replication, and repair, which indicates that the improved protein secretion capacity in the evolved strains is the result of the interaction of multiple intracellular processes. Our findings will contribute to the construction of novel cell factories for recombinant protein secretion.

Comparative functional genomics identifies an iron-limited bottleneck in a Saccharomyces cerevisiae strain with a cytosolic-localized isobutanol pathway

Metabolic engineering strategies have been successfully implemented to improve the production of isobutanol, a next-generation biofuel, in Saccharomyces cerevisiae. Here, we explore how two of these strategies, pathway re-localization and redox cofactor-balancing, affect the performance and physiology of isobutanol producing strains. We equipped yeast with isobutanol cassettes which had either a mitochondrial or cytosolic localized isobutanol pathway and used either a redox-imbalanced (NADPH-dependent) or redox-balanced (NADH-dependent) ketol-acid reductoisomerase enzyme. We then conducted transcriptomic, proteomic and metabolomic analyses to elucidate molecular differences between the engineered strains. Pathway localization had a large effect on isobutanol production with the strain expressing the mitochondrial-localized enzymes producing 3.8-fold more isobutanol than strains expressing the cytosolic enzymes. Cofactor-balancing did not improve isobutanol titers and instead the strain with the redox-imbalanced pathway produced 1.5-fold more isobutanol than the balanced version, albeit at low overall pathway flux. Functional genomic analyses suggested that the poor performances of the cytosolic pathway strains were in part due to a shortage in cytosolic Fe-S clusters, which are required cofactors for the dihydroxyacid dehydratase enzyme. We then demonstrated that this cofactor limitation may be partially recovered by disrupting iron homeostasis with a fra2 mutation, thereby increasing cellular iron levels. The resulting isobutanol titer of the fra2 null strain harboring a cytosolic-localized isobutanol pathway outperformed the strain with the mitochondrial-localized pathway by 1.3-fold, demonstrating that both localizations can support flux to isobutanol.

Contingency and selection in mitochondrial genome dynamics

High frequencies of mutant mitochondrial DNA (mtDNA) in human cells lead to cellular defects that are associated with aging and disease. Yet much remains to be understood about the dynamics of the generation of mutant mtDNAs and their relative replicative fitness that informs their fate within cells and tissues. To address this, we utilize long-read single-molecule sequencing to track mutational trajectories of mtDNA in the model organism Saccharomyces cerevisiae. This model has numerous advantages over mammalian systems due to its much larger mtDNA and ease of artificially competing mutant and wild-type mtDNA copies in cells. We show a previously unseen pattern that constrains subsequent excision events in mtDNA fragmentation in yeast. We also provide evidence for the generation of rare and contentious non-periodic mtDNA structures that lead to persistent diversity within individual cells. Finally, we show that measurements of relative fitness of mtDNA fit a phenomenological model that highlights important biophysical parameters governing mtDNA fitness. Altogether, our study provides techniques and insights into the dynamics of large structural changes in genomes that we show are applicable to more complex organisms like humans.

Genetic basis of a spontaneous mutation’s expressivity

Genetic background often influences the phenotypic consequences of mutations, resulting in variable expressivity. How standing genetic variants collectively cause this phenomenon is not fully understood. Here, we comprehensively identify loci in a budding yeast cross that impact the growth of individuals carrying a spontaneous missense mutation in the nuclear-encoded mitochondrial ribosomal gene MRP20. Initial results suggested that a single large effect locus influences the mutation’s expressivity, with one allele causing inviability in mutants. However, further experiments revealed this simplicity was an illusion. In fact, many additional loci shape the mutation’s expressivity, collectively leading to a wide spectrum of mutational responses. These results exemplify how complex combinations of alleles can produce a diversity of qualitative and quantitative responses to the same mutation.

From Genome Variation to Molecular Mechanisms: What we Have Learned From Yeast Mitochondrial Genomes?

Analysis of genome variation provides insights into mechanisms in genome evolution. This is increasingly appreciated with the rapid growth of genomic data. Mitochondrial genomes (mitogenomes) are well known to vary substantially in many genomic aspects, such as genome size, sequence context, nucleotide base composition and substitution rate. Such substantial variation makes mitogenomes an excellent model system to study the mechanisms dictating mitogenome variation. Recent sequencing efforts have not only covered a rich number of yeast species but also generated genomes from abundant strains within the same species. The rich yeast genomic data have enabled detailed investigation from genome variation into molecular mechanisms in genome evolution. This mini-review highlights some recent progresses in yeast mitogenome studies.

Monitoring single-cell dynamics of entry into quiescence during an unperturbed life cycle

The life cycle of microorganisms is associated with dynamic metabolic transitions and complex cellular responses. In yeast, how metabolic signals control the progressive choreography of structural reorganizations observed in quiescent cells during a natural life cycle remains unclear. We have developed an integrated microfluidic device to address this question, enabling continuous single-cell tracking in a batch culture experiencing unperturbed nutrient exhaustion to unravel the coordination between metabolic and structural transitions within cells. Our technique reveals an abrupt fate divergence in the population, whereby a fraction of cells is unable to transition to respiratory metabolism and undergoes a reversible entry into a quiescence-like state leading to premature cell death. Further observations reveal that nonmonotonous internal pH fluctuations in respiration-competent cells orchestrate the successive waves of protein superassemblies formation that accompany the entry into a bona fide quiescent state. This ultimately leads to an abrupt cytosolic glass transition that occurs stochastically long after proliferation cessation. This new experimental framework provides a unique way to track single-cell fate dynamics over a long timescale in a population of cells that continuously modify their ecological niche.

Mutational sources of trans-regulatory variation affecting gene expression in Saccharomyces cerevisiae

Heritable variation in a gene’s expression arises from mutations impacting cis- and trans-acting components of its regulatory network. Here, we investigate how trans-regulatory mutations are distributed within the genome and within a gene regulatory network by identifying and characterizing 69 mutations with trans-regulatory effects on expression of the same focal gene in Saccharomyces cerevisiae. Relative to 1766 mutations without effects on expression of this focal gene, we found that these trans-regulatory mutations were enriched in coding sequences of transcription factors previously predicted to regulate expression of the focal gene. However, over 90% of the trans-regulatory mutations identified mapped to other types of genes involved in diverse biological processes including chromatin state, metabolism, and signal transduction. These data show how genetic changes in diverse types of genes can impact a gene’s expression in trans, revealing properties of trans-regulatory mutations that provide the raw material for trans-regulatory variation segregating within natural populations.

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.

Novel Insights into Quantitative Proteomics from an Innovative Bottom-Up Simple Light Isotope Metabolic (bSLIM) Labeling Data Processing Strategy

Simple light isotope metabolic labeling (SLIM labeling) is an innovative method to quantify variations in the proteome based on an original in vivo labeling strategy. Heterotrophic cells grown in U-[12C] as the sole source of carbon synthesize U-[12C]-amino acids, which are incorporated into proteins, giving rise to U-[12C]-proteins. This results in a large increase in the intensity of the monoisotope ion of peptides and proteins, thus allowing higher identification scores and protein sequence coverage in mass spectrometry experiments. This method, initially developed for signal processing and quantification of the incorporation rate of 12C into peptides, was based on a multistep process that was difficult to implement for many laboratories. To overcome these limitations, we developed a new theoretical background to analyze bottom-up proteomics data using SLIM-labeling (bSLIM) and established simple procedures based on open-source software, using dedicated OpenMS modules, and embedded R scripts to process the bSLIM experimental data. These new tools allow computation of both the 12C abundance in peptides to follow the kinetics of protein labeling and the molar fraction of unlabeled and 12C-labeled peptides in multiplexing experiments to determine the relative abundance of proteins extracted under different biological conditions. They also make it possible to consider incomplete 12C labeling, such as that observed in cells with nutritional requirements for nonlabeled amino acids. These tools were validated on an experimental dataset produced using various yeast strains of Saccharomyces cerevisiae and growth conditions. The workflows are built on the implementation of appropriate calculation modules in a KNIME working environment. These new integrated tools provide a convenient framework for the wider use of the SLIM-labeling strategy.

Population Analysis and Evolution of Saccharomyces cerevisiae Mitogenomes

The study of mitogenomes allows the unraveling of some paths of yeast evolution that are often not exposed when analyzing the nuclear genome. Although both nuclear and mitochondrial genomes are known to determine phenotypic diversity and fitness, no concordance has yet established between the two, mainly regarding strains' technological uses and/or geographical distribution. In the current work, we proposed a new method to align and analyze yeast mitogenomes, overcoming current difficulties that make it impossible to obtain comparable mitogenomes for a large number of isolates. To this end, 12,016 mitogenomes were considered, and we developed a novel approach consisting of the design of a reference sequence intended to be comparable between all mitogenomes. Subsequently, the population structure of 6646 Saccharomyces cerevisiae mitogenomes was assessed. Results revealed the existence of particular clusters associated with the technological use of the strains, in particular regarding clinical isolates, laboratory strains, and yeasts used for wine-associated activities. As far as we know, this is the first time that a positive concordance between nuclear and mitogenomes has been reported for S. cerevisiae, in terms of strains' technological applications. The results obtained highlighted the importance of including the mtDNA genome in evolutionary analysis, in order to clarify the origin and history of yeast species.

A yeast platform for high-level synthesis of tetrahydroisoquinoline alkaloids

The tetrahydroisoquinoline (THIQ) moiety is a privileged substructure of many bioactive natural products and semi-synthetic analogs. Plants manufacture more than 3,000 THIQ alkaloids, including the opioids morphine and codeine. While microbial species have been engineered to synthesize a few compounds from the benzylisoquinoline alkaloid (BIA) family of THIQs, low product titers impede industrial viability and limit access to the full chemical space. Here we report a yeast THIQ platform by increasing production of the central BIA intermediate (S)-reticuline to 4.6 g L⁻¹, a 57,000-fold improvement over our first-generation strain. We show that gains in BIA output coincide with the formation of several substituted THIQs derived from amino acid catabolism. We use these insights to repurpose the Ehrlich pathway and synthesize an array of THIQ structures. This work provides a blueprint for building diverse alkaloid scaffolds and enables the targeted overproduction of thousands of THIQ products, including natural and semi-synthetic opioids.

Plants synthesize more than 3000 tetrahydroisoquinoline (THIQ) alkaloids, but only a few of them have been produced by engineered microbes and titers are very low. Here, the authors increase (S)-reticuline titer to 4.6 g/L and repurpose the yeast Ehrlich pathway to synthesize a diverse array of THIQ scaffolds.

Mitochondrial metabolism is central for response and resistance of Saccharomyces cerevisiae to exposure to a glyphosate-based herbicide

Glyphosate-based herbicides, the most extensively used herbicides in the world, are available in an enormous number of commercial formulations with varying additives and adjuvants. Here, we study the effects of one such formulation, Credit41, in two genetically diverse yeast strains. A quantitative trait loci (QTL) analysis between a sensitive laboratory strain and a resistant strain linked mitochondrial function to Credit41 resistance. Two genes encoding mitochondrial proteins identified through the QTL analysis were HFA1, a gene that encodes a mitochondrial acetyl CoA carboxylase, and AAC3, which encodes a mitochondrial inner membrane ATP/ADP translocator. Further analysis of previously studied whole-genome sequencing data showed that, although each strain uses varying routes to attain glyphosate resistance, most strains have duplications of mitochondrial genes. One of the most well-studied functions of the mitochondria is the assembly of Fe-S clusters. In the current study, the expression of iron transporters in the transcriptome increased in cells resistant to Credit41. The levels of iron within the cell also increased in cells exposed to Credit41 but not pure glyphosate. Hence, the additives in glyphosate-based herbicides have a significant contribution to the negative effects of these commercial formulations on biological systems.

Systematic analysis of nuclear gene function in respiratory growth and expression of the mitochondrial genome in S. cerevisiae

The production of metabolic energy in form of ATP by oxidative phosphorylation depends on the coordinated action of hundreds of nuclear-encoded mitochondrial proteins and a handful of proteins encoded by the mitochondrial genome (mtDNA). We used the yeast Saccharomyces cerevisiae as a model system to systematically identify the genes contributing to this process. Integration of genome-wide high-throughput growth assays with previously published large data sets allowed us to define with high confidence a set of 254 nuclear genes that are indispensable for respiratory growth. Next, we induced loss of mtDNA in the yeast deletion collection by growth on ethidium bromide-containing medium and identified twelve genes that are essential for viability in the absence of mtDNA (i.e. petite-negative). Replenishment of mtDNA by cytoduction showed that respiratory-deficient phenotypes are highly variable in many yeast mutants. Using a mitochondrial genome carrying a selectable marker, ARG8^m, we screened for mutants that are specifically defective in maintenance of mtDNA and mitochondrial protein synthesis. We found that up to 176 nuclear genes are required for expression of mitochondria-encoded proteins during fermentative growth. Taken together, our data provide a comprehensive picture of the molecular processes that are required for respiratory metabolism in a simple eukaryotic cell.

The RNA-associated proteins MKT1 and MKT1L form alternative PBP1-containing complexes in Trypanosoma brucei

Control of gene expression in kinetoplastids such as trypanosomes depends heavily on RNA-binding proteins that influence mRNA decay and translation. We previously showed that the trypanosome protein MKT1 forms a multicomponent protein complex: MKT1 interacts with PBP1, which in turn recruits LSM12 and poly(A)-binding protein. MKT1 is recruited to mRNAs by sequence-specific RNA-binding proteins, resulting in stabilization of the bound mRNA. We here show that PBP1, LSM12, and a 117-residue protein, XAC1 (Tb927.7.2780), are present in complexes that contain either MKT1 or an MKT1-like protein, MKT1L (Tb927.10.1490). All five proteins are present predominantly in the complexes, and we found evidence for a minor subset of complexes containing both MKT1 and MKT1L. XAC1-containing complexes reproducibly contained RNA-binding proteins that were previously found associated with MKT1. Moreover, XAC1- or MKT1-containing complexes specifically recruited one of the two poly(A)-binding proteins, PABP2, and one of the six cap-binding translation initiation complexes, EIF4E6-EIF4G5. Yeast two-hybrid assay results indicated that MKT1 directly interacts with EIF4G5. MKT1-PBP1 complexes can therefore interact with mRNAs via their poly(A) tails and caps, as well as through sequence-specific RNA-binding proteins. Correspondingly, MKT1 is associated with many mRNAs, although not with those encoding ribosomal proteins. Meanwhile, MKT1L resembles MKT1 at the C terminus but additionally features an N-terminal extension with low-complexity regions. Although MKT1L depletion inhibited cell proliferation, we found no evidence that it specifically interacts with RNA-binding proteins or mRNA. We speculate that MKT1L may compete with MKT1 for PBP1 binding and thereby modulate the function of MKT1-containing complexes.

Two Synthetic 18-Way Outcrossed Populations of Diploid Budding Yeast with Utility for Complex Trait Dissection

Advanced-generation multiparent populations (MPPs) are a valuable tool for dissecting complex traits, having more power than genome-wide association studies to detect rare variants and higher resolution than F2 linkage mapping. To extend the advantages of MPPs in budding yeast, we describe the creation and characterization of two outbred MPPs derived from 18 genetically diverse founding strains. We carried out de novo assemblies of the genomes of the 18 founder strains, such that virtually all variation segregating between these strains is known, and represented those assemblies as Santa Cruz Genome Browser tracks. We discovered complex patterns of structural variation segregating among the founders, including a large deletion within the vacuolar ATPase VMA1, several different deletions within the osmosensor MSB2, a series of deletions and insertions at PRM7 and the adjacent BSC1, as well as copy number variation at the dehydrogenase ALD2 Resequenced haploid recombinant clones from the two MPPs have a median unrecombined block size of 66 kb, demonstrating that the population is highly recombined. We pool-sequenced the two MPPs to 3270× and 2226× coverage and demonstrated that we can accurately estimate local haplotype frequencies using pooled data. We further downsampled the pool-sequenced data to ∼20-40× and showed that local haplotype frequency estimates remained accurate, with median error rates 0.8 and 0.6% at 20× and 40×, respectively. Haplotypes frequencies are estimated much more accurately than SNP frequencies obtained directly from the same data. Deep sequencing of the two populations revealed that 10 or more founders are present at a detectable frequency for > 98% of the genome, validating the utility of this resource for the exploration of the role of standing variation in the architecture of complex traits.

A tps1Δ persister-like state in Saccharomyces cerevisiae is regulated by MKT1

Trehalose metabolism in yeast has been linked to a variety of phenotypes, including heat resistance, desiccation tolerance, carbon-source utilization, and sporulation. The relationships among the several phenotypes of mutants unable to synthesize trehalose are not understood, even though the pathway is highly conserved. One of these phenotypes is that tps1Δ strains cannot reportedly grow on media containing glucose or fructose, even when another carbon source they can use (e.g. galactose) is present. Here we corroborate the recent observation that a small fraction of yeast tps1Δ cells do grow on glucose, unlike the majority of the population. This is not due to a genetic alteration, but instead resembles the persister phenotype documented in many microorganisms and cancer cells undergoing lethal stress. We extend these observations to show that this phenomenon is glucose-specific, as it does not occur on another highly fermented carbon source, fructose. We further demonstrate that this phenomenon appears to be related to mitochondrial complex III function, but unrelated to inorganic phosphate levels in the cell, as had previously been suggested. Finally, we found that this phenomenon is specific to S288C-derived strains, and is the consequence of a variant in the MKT1 gene.

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.

Discordant evolution of mitochondrial and nuclear yeast genomes at population level

Background

Mitochondria are essential organelles partially regulated by their own genomes. The mitochondrial genome maintenance and inheritance differ from the nuclear genome, potentially uncoupling their evolutionary trajectories. Here, we analysed mitochondrial sequences obtained from the 1011 Saccharomyces cerevisiae strain collection and identified pronounced differences with their nuclear genome counterparts.

Results

In contrast with pre-whole genome duplication fungal species, S. cerevisiae mitochondrial genomes show higher genetic diversity compared to the nuclear genomes. Strikingly, mitochondrial genomes appear to be highly admixed, resulting in a complex interconnected phylogeny with a weak grouping of isolates, whereas interspecies introgressions are very rare. Complete genome assemblies revealed that structural rearrangements are nearly absent with rare inversions detected. We tracked intron variation in COX1 and COB to infer gain and loss events throughout the species evolutionary history. Mitochondrial genome copy number is connected with the nuclear genome and linearly scale up with ploidy. We observed rare cases of naturally occurring mitochondrial DNA loss, petite, with a subset of them that do not suffer the expected growth defect in fermentable rich media.

Conclusions

Overall, our results illustrate how differences in the biology of two genomes coexisting in the same cells can lead to discordant evolutionary histories.

Pbp1-Interacting Protein Mkt1 Regulates Virulence and Sexual Reproduction in Cryptococcus neoformans

The Mkt1–Pbp1 complex promotes mating-type switching by regulating the translation of HO mRNA in Saccharomyces cerevisiae. Here, we performed in vivo immunoprecipitation assays and mass spectrometry analyses in the human fungal pathogen Cryptococcus neoformans to show that Pbp1, a poly(A)-binding protein-binding protein, interacts with Mkt1 containing a PIN like-domain. Association of Pbp1 with Mkt1 was confirmed by co-immunoprecipitation assays. Results of spot dilution growth assays showed that unlike pbp1 deletion mutant strains, mkt1 deletion mutant strains were not resistant to heat stress compared with wild-type. However, similar to the pbp1 deletion mutant strains, the mkt1 deletion mutants exhibited both, defective dikaryotic hyphal production and reduced pheromone gene (MFα1) expression during mating. In addition, deletion of mkt1 caused attenuated virulence in a murine intranasal inhalation model. Taken together, our findings reveal that Mkt1 plays a crucial role in sexual reproduction and virulence in C. neoformans.

Empirical measures of mutational effects define neutral models of regulatory evolution in Saccharomyces cerevisiae

Understanding how phenotypes evolve requires disentangling the effects of mutation generating new variation from the effects of selection filtering it. Tests for selection frequently assume that mutation introduces phenotypic variation symmetrically around the population mean, yet few studies have tested this assumption by deeply sampling the distributions of mutational effects for particular traits. Here, we examine distributions of mutational effects for gene expression in the budding yeast Saccharomyces cerevisiae by measuring the effects of thousands of point mutations introduced randomly throughout the genome. We find that the distributions of mutational effects differ for the 10 genes surveyed and are inconsistent with normality. For example, all 10 distributions of mutational effects included more mutations with large effects than expected for normally distributed phenotypes. In addition, some genes also showed asymmetries in their distribution of mutational effects, with new mutations more likely to increase than decrease the gene's expression or vice versa. Neutral models of regulatory evolution that take these empirically determined distributions into account suggest that neutral processes may explain more expression variation within natural populations than currently appreciated.

Compensatory trans-regulatory alleles minimizing variation in TDH3 expression are common within Saccharomyces cerevisiae

Heritable variation in gene expression is common within species. Much of this variation is due to genetic differences outside of the gene with altered expression and is trans-acting. This trans-regulatory variation is often polygenic, with individual variants typically having small effects, making the genetic architecture and evolution of trans-regulatory variation challenging to study. Consequently, key questions about trans-regulatory variation remain, including the variability of trans-regulatory variation within a species, how selection affects trans-regulatory variation, and how trans-regulatory variants are distributed throughout the genome and within a species. To address these questions, we isolated and measured trans-regulatory differences affecting TDH3 promoter activity among 56 strains of Saccharomyces cerevisiae, finding that trans-regulatory backgrounds varied approximately twofold in their effects on TDH3 promoter activity. Comparing this variation to neutral models of trans-regulatory evolution based on empirical measures of mutational effects revealed that despite this variability in the effects of trans-regulatory backgrounds, stabilizing selection has constrained trans-regulatory differences within this species. Using a powerful quantitative trait locus mapping method, we identified ∼100 trans-acting expression quantitative trait locus in each of three crosses to a common reference strain, indicating that regulatory variation is more polygenic than previous studies have suggested. Loci altering expression were located throughout the genome, and many loci were strain specific. This distribution and prevalence of alleles is consistent with recent theories about the genetic architecture of complex traits. In all mapping experiments, the nonreference strain alleles increased and decreased TDH3 promoter activity with similar frequencies, suggesting that stabilizing selection maintained many trans-acting variants with opposing effects. This variation may provide the raw material for compensatory evolution and larger scale regulatory rewiring observed in developmental systems drift among species.

Amino and carboxy-terminal extensions of yeast mitochondrial DNA polymerase assemble both the polymerization and exonuclease active sites

Human and yeast mitochondrial DNA polymerases (DNAPs), POLG and Mip1, are related by evolution to bacteriophage DNAPs. However, mitochondrial DNAPs contain unique amino and carboxyl-terminal extensions that physically interact. Here we describe that N-terminal deletions in Mip1 polymerases abolish polymerization and decrease exonucleolytic degradation, whereas moderate C-terminal deletions reduce polymerization. Similarly, to the N-terminal deletions, an extended C-terminal deletion of 298 amino acids is deficient in nucleotide addition and exonucleolytic degradation of double and single-stranded DNA. The latter observation suggests that the physical interaction between the amino and carboxyl-terminal regions of Mip1 may be related to the spread of pathogenic POLG mutant along its primary sequence.

Proteome response of two natural strains of Saccharomyces cerevisiae with divergent lignocellulosic inhibitor stress tolerance

Strains of Saccharomyces cerevisiae with improved tolerance to plant hydrolysates are of utmost importance for the cost-competitive production of value-added chemicals and fuels. However, engineering strategies are constrained by a lack of understanding of the yeast response to complex inhibitor mixtures. Natural S. cerevisiae isolates display niche-specific phenotypic and metabolic diversity, encoded in their DNA, which has evolved to overcome external stresses, utilise available resources and ultimately thrive in their challenging environments. Industrial and laboratory strains, however, lack these adaptations due to domestication. Natural strains can serve as a valuable resource to mitigate engineering constraints by studying the molecular mechanisms involved in phenotypic variance and instruct future industrial strain improvement to lignocellulosic hydrolysates. We, therefore, investigated the proteomic changes between two natural S. cerevisiae isolates when exposed to a lignocellulosic inhibitor mixture. Comparative shotgun proteomics revealed that isolates respond by regulating a similar core set of proteins in response to inhibitor stress. Furthermore, superior tolerance was linked to NAD(P)/H and energy homeostasis, concurrent with inhibitor and reactive oxygen species detoxification processes. We present several candidate proteins within the redox homeostasis and energy management cellular processes as possible targets for future modification and study. Data are available via ProteomeXchange with identifier PXD010868.

Genome-Wide Studies of Rho5-Interacting Proteins That Are Involved in Oxidant-Induced Cell Death in Budding Yeast

Rho GTPases play critical roles in cell proliferation and cell death in many species. As in animal cells, cells of the budding yeast Saccharomyces cerevisiae undergo regulated cell death under various physiological conditions and upon exposure to external stress. The Rho5 GTPase is necessary for oxidant-induced cell death, and cells expressing a constitutively active GTP-locked Rho5 are hypersensitive to oxidants. Yet how Rho5 regulates yeast cell death has been poorly understood. To identify genes that are involved in the Rho5-mediated cell death program, we performed two complementary genome-wide screens: one screen for oxidant-resistant deletion mutants and another screen for Rho5-associated proteins. Functional enrichment and interaction network analysis revealed enrichment for genes in pathways related to metabolism, transport, and plasma membrane organization. In particular, we find that ATG21, which is known to be involved in the CVT (Cytoplasm-to-Vacuole Targeting) pathway and mitophagy, is necessary for cell death induced by oxidants. Cells lacking Atg21 exhibit little cell death upon exposure to oxidants even when the GTP-locked Rho5 is expressed. Moreover, Atg21 interacts with Rho5 preferentially in its GTP-bound state, suggesting that Atg21 is a downstream target of Rho5 in oxidant-induced cell death. Given the high degree of conservation of Rho GTPases and autophagy from yeast to human, this study may provide insight into regulated cell death in eukaryotes in general.

Uncovering and resolving challenges of quantitative modeling in a simplified community of interacting cells

Quantitative modeling is useful for predicting behaviors of a system and for rationally constructing or modifying the system. The predictive power of a model relies on accurate quantification of model parameters. Here, we illustrate challenges in parameter quantification and offer means to overcome these challenges, using a case example in which we quantitatively predict the growth rate of a cooperative community. Specifically, the community consists of two Saccharomyces cerevisiae strains, each engineered to release a metabolite required and consumed by its partner. The initial model, employing parameters measured in batch monocultures with zero or excess metabolite, failed to quantitatively predict experimental results. To resolve the model-experiment discrepancy, we chemically identified the correct exchanged metabolites, but this did not improve model performance. We then remeasured strain phenotypes in chemostats mimicking the metabolite-limited community environments, while mitigating or incorporating effects of rapid evolution. Almost all phenotypes we measured, including death rate, metabolite release rate, and the amount of metabolite consumed per cell birth, varied significantly with the metabolite environment. Once we used parameters measured in a range of community-like chemostat environments, prediction quantitatively agreed with experimental results. In summary, using a simplified community, we uncovered and devised means to resolve modeling challenges that are likely general to living systems.