Amoeba predation of Cryptococcus: A quantitative and population genomic evaluation of the accidental pathogen hypothesis.

The "Amoeboid Predator-Fungal Animal Virulence Hypothesis" posits that interactions with environmental phagocytes shape the evolution of virulence traits in fungal pathogens. In this hypothesis, selection to avoid predation by amoeba inadvertently selects for traits that contribute to fungal escape from phagocytic immune cells. Here, we investigate this hypothesis in the human fungal pathogens Cryptococcus neoformans and Cryptococcus deneoformans. Applying quantitative trait locus (QTL) mapping and comparative genomics, we discovered a cross-species QTL region that is responsible for variation in resistance to amoeba predation. In C. neoformans, this same QTL was found to have pleiotropic effects on melanization, an established virulence factor. Through fine mapping and population genomic comparisons, we identified the gene encoding the transcription factor Bzp4 that underlies this pleiotropic QTL and we show that decreased expression of this gene reduces melanization and increases susceptibility to amoeba predation. Despite the joint effects of BZP4 on amoeba resistance and melanin production, we find no relationship between BZP4 genotype and escape from macrophages or virulence in murine models of disease. Our findings provide new perspectives on how microbial ecology shapes the genetic architecture of fungal virulence, and suggests the need for more nuanced models for the evolution of pathogenesis that account for the complexities of both microbe-microbe and microbe-host interactions.

RNA viruses, M satellites, chromosomal killer genes, and killer/nonkiller phenotypes in the 100-genomes S. cerevisiae strains.

We characterized previously identified RNA viruses (L-A, L-BC, 20S, and 23S), L-A-dependent M satellites (M1, M2, M28, and Mlus), and M satellite-dependent killer phenotypes in the Saccharomyces cerevisiae 100-genomes genetic resource population. L-BC was present in all strains, albeit in 2 distinct levels, L-BChi and L-BClo; the L-BC level is associated with the L-BC genotype. L-BChi, L-A, 20S, 23S, M1, M2, and Mlus (M28 was absent) were in fewer strains than the similarly inherited 2µ plasmid. Novel L-A-dependent phenotypes were identified. Ten M+ strains exhibited M satellite-dependent killing (K+) of at least 1 of the naturally M0 and cured M0 derivatives of the 100-genomes strains; in these M0 strains, sensitivities to K1+, K2+, and K28+ strains varied. Finally, to complement our M satellite-encoded killer toxin analysis, we assembled the chromosomal KHS1 and KHR1 killer genes and used naturally M0 and cured M0 derivatives of the 100-genomes strains to assess and characterize the chromosomal killer phenotypes.

Uncontrolled transposition following RNAi loss causes hypermutation and antifungal drug resistance in clinical isolates of Cryptococcus neoformans.

Cryptococcus neoformans infections cause approximately 15% of AIDS-related deaths owing to a combination of limited antifungal therapies and drug resistance. A collection of clinical and environmental C. neoformans isolates were assayed for increased mutation rates via fluctuation analysis, and we identified two hypermutator C. neoformans clinical isolates with increased mutation rates when exposed to the combination of rapamycin and FK506. Sequencing of drug target genes found that Cnl1 transposon insertions conferred the majority of resistance to rapamycin and FK506 and could also independently cause resistance to 5-fluoroorotic acid and the clinically relevant antifungal 5-flucytosine. Whole-genome sequencing revealed both hypermutator genomes harbour a nonsense mutation in the RNA-interference component ZNF3 and hundreds of Cnl1 elements organized into massive subtelomeric arrays on each of the fourteen chromosomes. Quantitative trait locus mapping in 28 progeny derived from a cross between a hypermutator and wild-type identified a locus associated with hypermutation that included znf3. CRISPR editing of the znf3 nonsense mutation abolished hypermutation and restored small-interfering-RNA production. We conclude that hypermutation and drug resistance in these clinical isolates result from RNA-interference loss and accumulation of Cnl1 elements.

Epistatic genetic interactions govern morphogenesis during sexual reproduction and infection in a global human fungal pathogen.

Cellular development is orchestrated by evolutionarily conserved signaling pathways, which are often pleiotropic and involve intra- and interpathway epistatic interactions that form intricate, complex regulatory networks. Cryptococcus species are a group of closely related human fungal pathogens that grow as yeasts yet transition to hyphae during sexual reproduction. Additionally, during infection they can form large, polyploid titan cells that evade immunity and develop drug resistance. Multiple known signaling pathways regulate cellular development, yet how these are coordinated and interact with genetic variation is less well understood. Here, we conducted quantitative trait locus (QTL) analyses of a mapping population generated by sexual reproduction of two parents, only one of which is unisexually fertile. We observed transgressive segregation of the unisexual phenotype among progeny, as well as a large-cell phenotype under mating-inducing conditions. These large-cell progeny were found to produce titan cells both in vitro and in infected animals. Two major QTLs and corresponding quantitative trait genes (QTGs) were identified: RIC8 (encoding a guanine-exchange factor) and CNC06490 (encoding a putative Rho-GTPase activator), both involved in G protein signaling. The two QTGs interact epistatically with each other and with the mating-type locus in phenotypic determination. These findings provide insights into the complex genetics of morphogenesis during unisexual reproduction and pathogenic titan cell formation and illustrate how QTL analysis can be applied to identify epistasis between genes. This study shows that phenotypic outcomes are influenced by the genetic background upon which mutations arise, implicating dynamic, complex genotype-to-phenotype landscapes in fungal pathogens and beyond.

Associations between Cryptococcus Genotypes, Phenotypes, and Clinical Parameters of Human Disease: A Review.

The genus Cryptococcus contains two primary species complexes that are significant opportunistic human fungal pathogens: C. neoformans and C. gattii. In humans, cryptococcosis can manifest in many ways, but most often results in either pulmonary or central nervous system disease. Patients with cryptococcosis can display a variety of symptoms on a spectrum of severity because of the interaction between yeast and host. The bulk of our knowledge regarding Cryptococcus and the mechanisms of disease stem from in vitro experiments and in vivo animal models that make a fair attempt, but do not recapitulate the conditions inside the human host. To better understand the dynamics of initiation and progression in cryptococcal disease, it is important to study the genetic and phenotypic differences in the context of human infection to identify the human and fungal risk factors that contribute to pathogenesis and poor clinical outcomes. In this review, we summarize the current understanding of the different clinical presentations and health outcomes that are associated with pathogenicity and virulence of cryptococcal strains with respect to specific genotypes and phenotypes.

Pleiotropy and epistasis within and between signaling pathways defines the genetic architecture of fungal virulence.

Cryptococcal disease is estimated to affect nearly a quarter of a million people annually. Environmental isolates of Cryptococcus deneoformans, which make up 15 to 30% of clinical infections in temperate climates such as Europe, vary in their pathogenicity, ranging from benign to hyper-virulent. Key traits that contribute to virulence, such as the production of the pigment melanin, an extracellular polysaccharide capsule, and the ability to grow at human body temperature have been identified, yet little is known about the genetic basis of variation in such traits. Here we investigate the genetic basis of melanization, capsule size, thermal tolerance, oxidative stress resistance, and antifungal drug sensitivity using quantitative trait locus (QTL) mapping in progeny derived from a cross between two divergent C. deneoformans strains. Using a "function-valued" QTL analysis framework that exploits both time-series information and growth differences across multiple environments, we identified QTL for each of these virulence traits and drug susceptibility. For three QTL we identified the underlying genes and nucleotide differences that govern variation in virulence traits. One of these genes, RIC8, which encodes a regulator of cAMP-PKA signaling, contributes to variation in four virulence traits: melanization, capsule size, thermal tolerance, and resistance to oxidative stress. Two major effect QTL for amphotericin B resistance map to the genes SSK1 and SSK2, which encode key components of the HOG pathway, a fungal-specific signal transduction network that orchestrates cellular responses to osmotic and other stresses. We also discovered complex epistatic interactions within and between genes in the HOG and cAMP-PKA pathways that regulate antifungal drug resistance and resistance to oxidative stress. Our findings advance the understanding of virulence traits among diverse lineages of Cryptococcus, and highlight the role of genetic variation in key stress-responsive signaling pathways as a major contributor to phenotypic variation.

Mitochondrial Genome Variation Affects Multiple Respiration and Nonrespiration Phenotypes in Saccharomyces cerevisiae.

Mitochondrial genome variation and its effects on phenotypes have been widely analyzed in higher eukaryotes but less so in the model eukaryote Saccharomyces cerevisiae Here, we describe mitochondrial genome variation in 96 diverse S. cerevisiae strains and assess associations between mitochondrial genotype and phenotypes as well as nuclear-mitochondrial epistasis. We associate sensitivity to the ATP synthase inhibitor oligomycin with SNPs in the mitochondrially encoded ATP6 gene. We describe the use of iso-nuclear F1 pairs, the mitochondrial genome equivalent of reciprocal hemizygosity analysis, to identify and analyze mitochondrial genotype-dependent phenotypes. Using iso-nuclear F1 pairs, we analyze the oligomycin phenotype-ATP6 association and find extensive nuclear-mitochondrial epistasis. Similarly, in iso-nuclear F1 pairs, we identify many additional mitochondrial genotype-dependent respiration phenotypes, for which there was no association in the 96 strains, and again find extensive nuclear-mitochondrial epistasis that likely contributes to the lack of association in the 96 strains. Finally, in iso-nuclear F1 pairs, we identify novel mitochondrial genotype-dependent nonrespiration phenotypes: resistance to cycloheximide, ketoconazole, and copper. We discuss potential mechanisms and the implications of mitochondrial genotype and of nuclear-mitochondrial epistasis effects on respiratory and nonrespiratory quantitative traits.

Divergent Roles for cAMP-PKA Signaling in the Regulation of Filamentous Growth in Saccharomyces cerevisiae and Saccharomyces bayanus.

The cyclic AMP - Protein Kinase A (cAMP-PKA) pathway is an evolutionarily conserved eukaryotic signaling network that is essential for growth and development. In the fungi, cAMP-PKA signaling plays a critical role in regulating cellular physiology and morphological switches in response to nutrient availability. We undertook a comparative investigation of the role that cAMP-PKA signaling plays in the regulation of filamentous growth in two closely related budding yeast species, Saccharomyces cerevisiae and Saccharomyces bayanus Using chemical and genetic perturbations of this pathway and its downstream targets we discovered divergent roles for cAMP-PKA signaling in the regulation of filamentous growth. While cAMP-PKA signaling is required for the filamentous growth response in both species, increasing or decreasing the activity of this pathway leads to drastically different phenotypic outcomes. In S. cerevisiae, cAMP-PKA inhibition ameliorates the filamentous growth response while hyper-activation of the pathway leads to increased filamentous growth; the same perturbations in S. bayanus result in the obverse. Divergence in the regulation of filamentous growth between S. cerevisiae and S. bayanus extends to downstream targets of PKA, including several kinases, transcription factors, and effector proteins. Our findings highlight the potential for significant evolutionary divergence in gene network function, even when the constituent parts of such networks are well conserved.

A High-Resolution Map of Meiotic Recombination in Cryptococcus deneoformans Demonstrates Decreased Recombination in Unisexual Reproduction.

Multiple species within the basidiomycete genus Cryptococcus cause cryptococcal disease. These species are estimated to affect nearly a quarter of a million people leading to ∼180,000 mortalities, annually. Sexual reproduction, which can occur between haploid yeasts of the same or opposite mating type, is a potentially important contributor to pathogenesis as recombination can generate novel genotypes and transgressive phenotypes. However, our quantitative understanding of recombination in this clinically important yeast is limited. Here, we describe genome-wide estimates of recombination rates in Cryptococcus deneoformans and compare recombination between progeny from α-α unisexual and a-α bisexual crosses. We find that offspring from bisexual crosses have modestly higher average rates of recombination than those derived from unisexual crosses. Recombination hot and cold spots across the C. deneoformans genome are also identified and are associated with increased GC content. Finally, we observed regions genome-wide with allele frequencies deviating from the expected parental ratio. These findings and observations advance our quantitative understanding of the genetic events that occur during sexual reproduction in C. deneoformans, and the impact that different forms of sexual reproduction are likely to have on genetic diversity in this important fungal pathogen.

Genetic Dissection of Heritable Traits in Yeast Using Bulk Segregant Analysis.

Bulk segregant analysis (BSA) is commonly used to determine the genetic basis of complex traits in yeast. This technique involves phenotyping progeny from a cross and then selectively genotyping pooled subsets of offspring with extreme phenotypes. Analysis of these genotype data can identify loci that show skewed allele frequencies in a group of phenotypically extreme individuals and that are likely to contribute to a trait. BSA can be applied to diverse strain crosses, including ones involving nonreference isolates. Further, given the high throughput of next-generation sequencing, it is possible to conduct many BSA experiments in parallel. Here, we present a BSA protocol for the generation of recombinant cross progeny. We then describe general BSA strategies for conducting phenotyping, causal loci detection, and candidate gene identification in a statistically powerful manner.

Genetic Analysis of Complex Traits in Saccharomyces cerevisiae.

Defining the relationship between genotype and phenotype is a central challenge in biology. A powerful approach to this problem is to determine the genetic architecture and molecular basis of phenotypic differences among genetically diverse individuals. Saccharomyces cerevisiae is an important model system for such work. Current genetic mapping approaches for this species exploit high-throughput phenotyping and sequencing to facilitate the detection of a large fraction of the genomic loci that underlie trait variation among isolates. Once identified, several methods exist to determine the specific genes and genetic variants that underlie these loci and cause phenotypic variations. In this introduction, we provide a brief overview of research on complex traits in yeast and discuss different genetic mapping approaches applied to yeast studies.

Known mutator alleles do not markedly increase mutation rate in clinical Saccharomyces cerevisiae strains.

Natural selection has the potential to act on all phenotypes, including genomic mutation rate. Classic evolutionary theory predicts that in asexual populations, mutator alleles, which cause high mutation rates, can fix due to linkage with beneficial mutations. This phenomenon has been demonstrated experimentally and may explain the frequency of mutators found in bacterial pathogens. By contrast, in sexual populations, recombination decouples mutator alleles from beneficial mutations, preventing mutator fixation. In the facultatively sexual yeast Saccharomyces cerevisiae, segregating alleles of MLH1 and PMS1 have been shown to be incompatible, causing a high mutation rate when combined. These alleles had never been found together naturally, but were recently discovered in a cluster of clinical isolates. Here we report that the incompatible mutator allele combination only marginally elevates mutation rate in these clinical strains. Genomic and phylogenetic analyses provide no evidence of a historically elevated mutation rate. We conclude that the effect of the mutator alleles is dampened by background genetic modifiers. Thus, the relationship between mutation rate and microbial pathogenicity may be more complex than once thought. Our findings provide rare observational evidence that supports evolutionary theory suggesting that sexual organisms are unlikely to harbour alleles that increase their genomic mutation rate.

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

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

The quick and the dead: microbial demography at the yeast thermal limit.

The niche of microorganisms is determined by where their populations can expand. Populations can fail to grow because of high death or low birth rates, but these are challenging to measure in microorganisms. We developed a novel technique that enables single-cell measurement of age-structured birth and death rates in the budding yeast, Saccharomyces cerevisiae, and used this method to study responses to heat stress in a genetically diverse panel of strains. We find that individual cells show significant heterogeneity in their rates of birth and death during heat stress. Genotype-by-environment effects on processes that regulate asymmetric cell division contribute to this heterogeneity. These lead to either premature senescence or early life mortality during heat stress, and we find that a mitochondrial inheritance defect explains the early life mortality phenotype of one of the strains we studied. This study demonstrates how the interplay of physiology, genetic variation and environmental variables influence where microbial populations survive and flourish.

Population perspectives on functional genomic variation in yeast.

Advances in high-throughput sequencing have facilitated large-scale surveys of genomic variation in the budding yeast,Saccharomyces cerevisiae These surveys have revealed extensive sequence variation between yeast strains. However, much less is known about how such variation influences the amount and nature of variation for functional genomic traits within and between yeast lineages. We review population-level studies of functional genomic variation, with a particular focus on how population functional genomic approaches can provide insights into both genome function and the evolutionary process. Although variation in functional genomics phenotypes is pervasive, our understanding of the consequences of this variation, either in physiological or evolutionary terms, is still rudimentary and thus motivates increased attention to appropriate null models. To date, much of the focus of population functional genomic studies has been on gene expression variation, but other functional genomic data types are just as likely to reveal important insights at the population level, suggesting a pressing need for more studies that go beyond transcription. Finally, we discuss how a population functional genomic perspective can be a powerful approach for developing a mechanistic understanding of the processes that link genomic variation to organismal phenotypes through gene networks.

Sporadic, Global Linkage Disequilibrium Between Unlinked Segregating Sites.

Demographic, genetic, or stochastic factors can lead to perfect linkage disequilibrium (LD) between alleles at two loci without respect to the extent of their physical distance, a phenomenon that Lawrence et al. (2005a) refer to as "genetic indistinguishability." This phenomenon can complicate genotype-phenotype association testing by hindering the ability to localize causal alleles, but has not been thoroughly explored from a theoretical perspective or using large, dense whole-genome polymorphism data sets. We derive a simple theoretical model of the prevalence of genetic indistinguishability between unlinked loci and verify its accuracy via simulation. We show that sample size and minor allele frequency are the major determinants of the prevalence of perfect LD between unlinked loci but that demographic factors, such as deviations from random mating, can produce significant effects as well. Finally, we quantify this phenomenon in three model organisms and find thousands of pairs of moderate-frequency ([Formula: see text]) genetically indistinguishable variants in relatively large data sets. These results clarify a previously underexplored population genetic phenomenon with important implications for association studies and define conditions under which it is likely to manifest.

2µ plasmid in Saccharomyces species and in Saccharomyces cerevisiae.

We determined that extrachromosomal 2µ plasmid was present in 67 of the Saccharomyces cerevisiae 100-genome strains; in addition to variation in the size and copy number of 2µ, we identified three distinct classes of 2µ. We identified 2µ presence/absence and class associations with populations, clinical origin and nuclear genotypes. We also screened genome sequences of S. paradoxus, S. kudriavzevii, S. uvarum, S. eubayanus, S. mikatae, S. arboricolus and S. bayanus strains for both integrated and extrachromosomal 2µ. Similar to S. cerevisiae, we found no integrated 2µ sequences in any S. paradoxus strains. However, we identified part of 2µ integrated into the genomes of some S. uvarum, S. kudriavzevii, S. mikatae and S. bayanus strains, which were distinct from each other and from all extrachromosomal 2µ. We identified extrachromosomal 2µ in one S. paradoxus, one S. eubayanus, two S. bayanus and 13 S. uvarum strains. The extrachromosomal 2µ in S. paradoxus, S. eubayanus and S. cerevisiae were distinct from each other. In contrast, the extrachromosomal 2µ in S. bayanus and S. uvarum strains were identical with each other and with one of the three classes of S. cerevisiae 2µ, consistent with interspecific transfer.

The 100-genomes strains, an S. cerevisiae resource that illuminates its natural phenotypic and genotypic variation and emergence as an opportunistic pathogen.

Saccharomyces cerevisiae, a well-established model for species as diverse as humans and pathogenic fungi, is more recently a model for population and quantitative genetics. S. cerevisiae is found in multiple environments-one of which is the human body-as an opportunistic pathogen. To aid in the understanding of the S. cerevisiae population and quantitative genetics, as well as its emergence as an opportunistic pathogen, we sequenced, de novo assembled, and extensively manually edited and annotated the genomes of 93 S. cerevisiae strains from multiple geographic and environmental origins, including many clinical origin strains. These 93 S. cerevisiae strains, the genomes of which are near-reference quality, together with seven previously sequenced strains, constitute a novel genetic resource, the "100-genomes" strains. Our sequencing coverage, high-quality assemblies, and annotation provide unprecedented opportunities for detailed interrogation of complex genomic loci, examples of which we demonstrate. We found most phenotypic variation to be quantitative and identified population, genotype, and phenotype associations. Importantly, we identified clinical origin associations. For example, we found that an introgressed PDR5 was present exclusively in clinical origin mosaic group strains; that the mosaic group was significantly enriched for clinical origin strains; and that clinical origin strains were much more copper resistant, suggesting that copper resistance contributes to fitness in the human host. The 100-genomes strains are a novel, multipurpose resource to advance the study of S. cerevisiae population genetics, quantitative genetics, and the emergence of an opportunistic pathogen.

Revisiting Mortimer's Genome Renewal Hypothesis: heterozygosity, homothallism, and the potential for adaptation in yeast.

In diploid organisms, the frequency and nature of sexual cycles have a major impact on genome-wide patterns of heterozygosity. Recent population genomic surveys in the budding yeast, Saccharomyces cerevisiae, have revealed surprising levels of genomic heterozygosity in what has been traditionally considered a highly inbred organism. I review evidence and hypotheses regarding the generation, maintenance, and evolutionary consequences of genomic heterozygosity in S. cerevisiae. I propose that high levels of heterozygosity in S. cerevisiae, arising from population admixture due to human domestication, coupled with selfing during rare sexual cycles, can facilitate rapid adaptation to novel environments.

Modeling mutant phenotypes and oscillatory dynamics in the Saccharomyces cerevisiae cAMP-PKA pathway.

BACKGROUND: The cyclic AMP-Protein Kinase A (cAMP-PKA) pathway is an evolutionarily conserved signal transduction mechanism that regulates cellular growth and differentiation in animals and fungi. We present a mathematical model that recapitulates the short-term and long-term dynamics of this pathway in the budding yeast, Saccharomyces cerevisiae. Our model is aimed at recapitulating the dynamics of cAMP signaling for wild-type cells as well as single (pde1Δ and pde2Δ) and double (pde1Δpde2Δ) phosphodiesterase mutants. RESULTS: Our model focuses on PKA-mediated negative feedback on the activity of phosphodiesterases and the Ras branch of the cAMP-PKA pathway. We show that both of these types of negative feedback are required to reproduce the wild-type signaling behavior that occurs on both short and long time scales, as well as the the observed responses of phosphodiesterase mutants. A novel feature of our model is that, for a wide range of parameters, it predicts that intracellular cAMP concentrations should exhibit decaying oscillatory dynamics in their approach to steady state following glucose stimulation. Experimental measurements of cAMP levels in two genetic backgrounds of S. cerevisiae confirmed the presence of decaying cAMP oscillations as predicted by the model. CONCLUSIONS: Our model of the cAMP-PKA pathway provides new insights into how yeast respond to alterations in their nutrient environment. Because the model has both predictive and explanatory power it will serve as a foundation for future mathematical and experimental studies of this important signaling network.