The evolution of the GALactose utilization pathway in budding yeasts

Development of a quinic acid-induced CRISPR/Cas9 genome editing system and its application for the activation of ilicicolin H biosynthesis in Trichoderma reesei

The CRISPR/Cas9 genome editing tool has been extensively utilized in filamentous fungi, including Trichoderma reesei. However, most existing systems employ constitutive promoters for the expression of Cas9 protein within the cells or directly introduce Cas9 protein into the cells, which often leads to continuous expression of Cas9 resulting in undesired phenotypes or increased operational cost. In this study, we identified a quinic acid (QA)-induced qai5 promoter and employed it to express Cas9, thereby establishing an inducible genome editing system in T. reesei. By utilizing this system, we successfully edited the ypr1 gene and the silent gene cluster involved in ilicicolin H synthesis using donor DNA labeling 41-bp homology arm (HA), resulting in an editing efficiency ranging from 29.2 % to 46.7 %. Consequently, biosynthesis of ilicicolin H was achieved in T. reesei. To summarize, this study presents a novel form of CRISPR/Cas9 genome editing system that enables efficient and controllable genetic modifications in T. reesei.

A unique metabolic gene cluster regulates lactose and galactose metabolism in the yeast Candida intermedia

Lactose assimilation is a relatively rare trait in yeasts, and Kluyveromyces yeast species have long served as model organisms for studying lactose metabolism. Meanwhile, the metabolic strategies of most other lactose-assimilating yeasts remain unknown. In this work, we have elucidated the genetic determinants of the superior lactose-growing yeast Candida intermedia. Through genomic and transcriptomic analyses, we identified three interdependent gene clusters responsible for the metabolism of lactose and its hydrolysis product galactose: the conserved LAC cluster (LAC12, LAC4) for lactose uptake and hydrolysis, the conserved GAL cluster (GAL1, GAL7, and GAL10) for galactose catabolism through the Leloir pathway, and a "GALLAC" cluster containing the transcriptional activator gene LAC9, second copies of GAL1 and GAL10, and a XYL1 gene encoding an aldose reductase involved in carbon overflow metabolism. Bioinformatic analysis suggests that the GALLAC cluster is unique to C. intermedia and has evolved through gene duplication and divergence, and deletion mutant phenotyping proved that the cluster is indispensable for C. intermedia's growth on lactose and galactose. We also show that the regulatory network in C. intermedia, governed by Lac9 and Gal1 from the GALLAC cluster, differs significantly from the galactose and lactose regulons in Saccharomyces cerevisiae, Kluyveromyces lactis, and Candida albicans. Moreover, although lactose and galactose metabolism are closely linked in C. intermedia, our results also point to important regulatory differences.IMPORTANCEThis study paves the way to a better understanding of lactose and galactose metabolism in the non-conventional yeast C. intermedia. Notably, the unique GALLAC cluster represents a new, interesting example of metabolic network rewiring and likely helps to explain how C. intermedia has evolved into an efficient lactose-assimilating yeast. With the Leloir pathway of budding yeasts acting like a model system for understanding the function, evolution, and regulation of eukaryotic metabolism, this work provides new evolutionary insights into yeast metabolic pathways and regulatory networks. In extension, the results will facilitate future development and use of C. intermedia as a cell-factory for conversion of lactose-rich whey into value-added products.

Differential adaptation of the yeast Candida anglica to fermented food

A single strain of Candida anglica, isolated from cider, is available in international yeast collections. We present here seven new strains isolated from French PDO cheeses. For one of the cheese strains, we achieved a high-quality genome assembly of 13.7 Mb with eight near-complete telomere-to-telomere chromosomes. The genomes of two additional cheese strains and of the cider strain were also assembled and annotated, resulting in a core genome of 5966 coding sequences. Phylogenetic analysis showed that the seven cheese strains clustered together, away from the cider strain. Mating-type locus analysis revealed the presence of a MATa locus in the cider strain but a MATalpha locus in all cheese strains. The presence of LINE retrotransposons at identical genome position in the cheese strains, and two different karyotypic profiles resulting from chromosomal rearrangements were observed. Together, these findings are consistent with clonal propagation of the cheese strains. Phenotypic trait variations were observed within the cheese population under stress conditions whereas the cider strain was found to have a much greater capacity for growth in all conditions tested.

Tunable cell differentiation via reprogrammed mating-type switching

This study introduces a synthetic biology approach that reprograms the yeast mating-type switching mechanism for tunable cell differentiation, facilitating synthetic microbial consortia formation and cooperativity. The underlying mechanism was engineered into a genetic logic gate capable of inducing asymmetric sexual differentiation within a haploid yeast population, resulting in a consortium characterized by mating-type heterogeneity and tunable population composition. The utility of this approach in microbial consortia cooperativity was demonstrated through the sequential conversion of xylan into xylose, employing haploids of opposite mating types each expressing a different enzyme of the xylanolytic pathway. This strategy provides a versatile framework for producing and fine-tuning functionally heterogeneous yet isogenic yeast consortia, furthering the advancement of microbial consortia cooperativity and offering additional avenues for biotechnological applications.

Chromosome-level genome assembly of the yeast Lodderomyces beijingensis reveals the genetic nature of metabolic adaptations and identifies subtelomeres as hotspots for amplification of mating type loci

Lodderomyces beijingensis is an ascosporic ascomycetous yeast. In contrast to related species Lodderomyces elongisporus, which is a recently emerging human pathogen, L. beijingensis is associated with insects. To provide an insight into its genetic makeup, we investigated the genome of its type strain, CBS 14171. We demonstrate that this yeast is diploid and describe the high contiguity nuclear genome assembly consisting of eight chromosome-sized contigs with a total size of about 15.1 Mbp. We find that the genome sequence contains multiple copies of the mating type loci and codes for essential components of the mating pheromone response pathway, however, the missing orthologs of several genes involved in the meiotic program raise questions about the mode of sexual reproduction. We also show that L. beijingensis genome codes for the 3-oxoadipate pathway enzymes, which allow the assimilation of protocatechuate. In contrast, the GAL gene cluster underwent a decay resulting in an inability of L. beijingensis to utilize galactose. Moreover, we find that the 56.5 kbp long mitochondrial DNA is structurally similar to known linear mitochondrial genomes terminating on both sides with covalently closed single-stranded hairpins. Finally, we discovered a new double-stranded RNA mycovirus from the Totiviridae family and characterized its genome sequence.

Machine learning enables identification of an alternative yeast galactose utilization pathway

How genomic differences contribute to phenotypic differences is a major question in biology. The recently characterized genomes, isolation environments, and qualitative patterns of growth on 122 sources and conditions of 1,154 strains from 1,049 fungal species (nearly all known) in the yeast subphylum Saccharomycotina provide a powerful, yet complex, dataset for addressing this question. We used a random forest algorithm trained on these genomic, metabolic, and environmental data to predict growth on several carbon sources with high accuracy. Known structural genes involved in assimilation of these sources and presence/absence patterns of growth in other sources were important features contributing to prediction accuracy. By further examining growth on galactose, we found that it can be predicted with high accuracy from either genomic (92.2%) or growth data (82.6%) but not from isolation environment data (65.6%). Prediction accuracy was even higher (93.3%) when we combined genomic and growth data. After the GALactose utilization genes, the most important feature for predicting growth on galactose was growth on galactitol, raising the hypothesis that several species in two orders, Serinales and Pichiales (containing the emerging pathogen Candida auris and the genus Ogataea, respectively), have an alternative galactose utilization pathway because they lack the GAL genes. Growth and biochemical assays confirmed that several of these species utilize galactose through an alternative oxidoreductive D-galactose pathway, rather than the canonical GAL pathway. Machine learning approaches are powerful for investigating the evolution of the yeast genotype-phenotype map, and their application will uncover novel biology, even in well-studied traits.

Ecological inducers of the yeast filamentous growth pathway reveal environment-dependent roles for pathway components

Signaling modules, such as mitogen-activated protein kinase (MAPK) pathways, are evolutionarily conserved drivers of cell differentiation and stress responses. In many fungal species including pathogens, MAPK pathways control filamentous growth, where cells differentiate into an elongated cell type. The convenient model budding yeast Saccharomyces cerevisiae undergoes filamentous growth by the filamentous growth (fMAPK) pathway; however, the inducers of the pathway remain unclear, perhaps because pathway activity has been mainly studied in laboratory conditions. To address this knowledge gap, an ecological framework was used, which uncovered new fMAPK pathway inducers, including pectin, a material found in plants, and the metabolic byproduct ethanol. We also show that induction by a known inducer of the pathway, the non-preferred carbon source galactose, required galactose metabolism and induced the pathway differently than glucose limitation or other non-preferred carbon sources. By exploring fMAPK pathway function in fruit, we found that induction of the pathway led to visible digestion of fruit rind through a known target, PGU1, which encodes a pectolytic enzyme. Combinations of inducers (galactose and ethanol) stimulated the pathway to near-maximal levels, which showed dispensability of several fMAPK pathway components (e.g., mucin sensor, p21-activated kinase), but not others (e.g., adaptor, MAPKKK) and required the Ras2-protein kinase A pathway. This included a difference between the transcription factor binding partners for the pathway, as Tec1p, but not Ste12p, was partly dispensable for fMAPK pathway activity. Thus, by exploring ecologically relevant stimuli, new modes of MAPK pathway signaling were uncovered, perhaps revealing how a pathway can respond differently to specific environments. IMPORTANCE Filamentous growth is a cell differentiation response and important aspect of fungal biology. In plant and animal fungal pathogens, filamentous growth contributes to virulence. One signaling pathway that regulates filamentous growth is an evolutionarily conserved MAPK pathway. The yeast Saccharomyces cerevisiae is a convenient model to study MAPK-dependent regulation of filamentous growth, although the inducers of the pathway are not clear. Here, we exposed yeast cells to ecologically relevant compounds (e.g., plant compounds), which identified new inducers of the MAPK pathway. In combination, the inducers activated the pathway to near-maximal levels but did not cause detrimental phenotypes associated with previously identified hyperactive alleles. This context allowed us to identify conditional bypass for multiple pathway components. Thus, near-maximal induction of a MAPK pathway by ecologically relevant inducers provides a powerful tool to assess cellular signaling during a fungal differentiation response.

Engineering an Efficient Expression Using Heterologous GAL Promoters and Transcriptional Activators in Saccharomyces cerevisiae

Galactose-inducible (GAL) promoters have been widely used in metabolic engineering in Saccharomyces cerevisiae for production of valuable products. Endogenous GAL promoters and GAL transcription factors have often been engineered to improve GAL promoter activities. Heterologous GAL promoters and GAL activator (Gal4p-like transcriptional activators), although existing in other yeasts or fungi, have not been well explored. In this study, we comprehensively characterized the activation effects of Gal4p activators from different yeasts or fungi on a variant of GAL promoters. Overexpressing endogenous Gal4p driven by PHHF1 increased the activities of native PGAL1 and heterologous PSkGAL2 by 131.20% and 72.45%, respectively. Furthermore, eight transcriptional activators from different organisms were characterized and most of them exhibited functions that were consistent with ScGal4p. Expression of KlLac9p from Kluyveromyces lactis further increased the activity of PScGAL1 and PSkGAL2 by 41.56% and 100.63%, respectively, compared to ScGal4p expression, and was able to evade Gal80p inhibition. This optimized GAL expression system can be used to increase the production of β-carotene by 9.02-fold in S. cerevisiae. Our study demonstrated that a combination of heterologous transcriptional activators and GAL promoters provided novel insights into the optimization of the GAL expression system.

Functional Clustering of Metabolically Related Genes Is Conserved across Dikarya

Transcriptional regulation is vital for organismal survival, with many layers and mechanisms collaborating to balance gene expression. One layer of this regulation is genome organization, specifically the clustering of functionally related, co-expressed genes along the chromosomes. Spatial organization allows for position effects to stabilize RNA expression and balance transcription, which can be advantageous for a number of reasons, including reductions in stochastic influences between the gene products. The organization of co-regulated gene families into functional clusters occurs extensively in Ascomycota fungi. However, this is less characterized within the related Basidiomycota fungi despite the many uses and applications for the species within this clade. This review will provide insight into the prevalence, purpose, and significance of the clustering of functionally related genes across Dikarya, including foundational studies from Ascomycetes and the current state of our understanding throughout representative Basidiomycete species.

Divergence of alternative sugar preferences through modulation of the expression and activity of the Gal3 sensor in yeast

Optimized nutrient utilization is crucial for the progression of microorganisms in competing communities. Here we investigate how different budding yeast species and ecological isolates have established divergent preferences for two alternative sugar substrates: Glucose, which is fermented preferentially by yeast, and galactose, which is alternatively used upon induction of the relevant GAL metabolic genes. We quantified the dose-dependent induction of the GAL1 gene encoding the central galactokinase enzyme and found that a very large diversification exists between different yeast ecotypes and species. The sensitivity of GAL1 induction correlates with the growth performance of the respective yeasts with the alternative sugar. We further define some of the mechanisms, which have established different glucose/galactose consumption strategies in representative yeast strains by modulating the activity of the Gal3 inducer. (1) Optimal galactose consumers, such as Saccharomyces uvarum, contain a hyperactive GAL3 promoter, sustaining highly sensitive GAL1 expression, which is not further improved upon repetitive galactose encounters. (2) Desensitized galactose consumers, such as S. cerevisiae Y12, contain a less sensitive Gal3 sensor, causing a shift of the galactose response towards higher sugar concentrations even in galactose experienced cells. (3) Galactose insensitive sugar consumers, such as S. cerevisiae DBVPG6044, contain an interrupted GAL3 gene, causing extremely reluctant galactose consumption, which is, however, improved upon repeated galactose availability. In summary, different yeast strains and natural isolates have evolved galactose utilization strategies, which cover the whole range of possible sensitivities by modulating the expression and/or activity of the inducible galactose sensor Gal3.

The cyclic peptide G4CP2 enables the modulation of galactose metabolism in yeast by interfering with GAL4 transcriptional activity

Genetically-encoded combinatorial peptide libraries are convenient tools to identify peptides to be used as therapeutics, antimicrobials and functional synthetic biology modules. Here, we report the identification and characterization of a cyclic peptide, G4CP2, that interferes with the GAL4 protein, a transcription factor responsible for the activation of galactose catabolism in yeast and widely exploited in molecular biology. G4CP2 was identified by screening CYCLIC, a Yeast Two-Hybrid-based combinatorial library of cyclic peptides developed in our laboratory. G4CP2 interferes with GAL4-mediated activation of galactose metabolic enzymes both when expressed intracellularly, as a recombinant peptide, and when provided exogenously, as a chemically-synthesized cyclic peptide. Our results support the application of G4CP2 in microbial biotechnology and, additionally, demonstrate that CYCLIC can be used as a tool for the rapid identification of peptides, virtually without any limitations with respect to the target protein. The possible biotechnological applications of cyclic peptides are also discussed.

Macroevolutionary diversity of traits and genomes in the model yeast genus Saccharomyces

Species is the fundamental unit to quantify biodiversity. In recent years, the model yeast Saccharomyces cerevisiae has seen an increased number of studies related to its geographical distribution, population structure, and phenotypic diversity. However, seven additional species from the same genus have been less thoroughly studied, which has limited our understanding of the macroevolutionary events leading to the diversification of this genus over the last 20 million years. Here, we show the geographies, hosts, substrates, and phylogenetic relationships for approximately 1,800 Saccharomyces strains, covering the complete genus with unprecedented breadth and depth. We generated and analyzed complete genome sequences of 163 strains and phenotyped 128 phylogenetically diverse strains. This dataset provides insights about genetic and phenotypic diversity within and between species and populations, quantifies reticulation and incomplete lineage sorting, and demonstrates how gene flow and selection have affected traits, such as galactose metabolism. These findings elevate the genus Saccharomyces as a model to understand biodiversity and evolution in microbial eukaryotes.

Recognition of galactose by a scaffold protein recruits a transcriptional activator for the GAL regulon induction in Candida albicans

The GAL pathway of yeasts has long served as a model system for understanding of how regulatory mode of eukaryotic metabolic pathways evolves. While Gal4 mode has been well-characterized in Saccharomycetaceae clade, little is known about the regulation of the GAL pathway in other yeasts. Here, we find that Rep1, a Ndt80-like family transcription factor, serves as a galactose sensor in the commensal-pathogenic fungus Candida albicans. It is presented at the GAL gene promoters independent of the presence of galactose. Rep1 recognizes galactose via a direct physical interaction. The net result of this interaction is the recruitment of a transcriptional activator Cga1 (Candida galactose gene activator, orf19.4959) and transcription of the GAL genes proceeds. Rep1 and Cga1 are conserved across the CTG species. Rep1 itself does not possess transcriptional activity. Instead, it provides a scaffold to recruit different factors for transcriptional regulation. Rep1-Cga1 mode of regulation represents a new example of network rewiring in fungi, which provides insight into how C. albicans evolves transcriptional programs to colonize diverse host niches.

Long-Term Adaptation to Galactose as a Sole Carbon Source Selects for Mutations Outside the Canonical GAL Pathway

Galactose is a secondary fermentable sugar that requires specific regulatory and structural genes for its assimilation, which are under catabolite repression by glucose. When glucose is absent, the catabolic repression is attenuated, and the structural GAL genes are fully activated. In Saccharomyces cerevisiae, the GAL pathway is under selection in environments where galactose is present. However, it is unclear the adaptive strategies in response to long-term propagation in galactose as a sole carbon source in laboratory evolution experiments. Here, we performed a 4,000-generation evolution experiment using 48 diploid Saccharomyces cerevisiae populations to study adaptation in galactose. We show that fitness gains were greater in the galactose-evolved population than in identically evolved populations with glucose as a sole carbon source. Whole-genome sequencing of 96 evolved clones revealed recurrent de novo single nucleotide mutations in candidate targets of selection, copy number variations, and ploidy changes. We find that most mutations that improve fitness in galactose lie outside of the canonical GAL pathway. Reconstruction of specific evolved alleles in candidate target of selection, SEC23 and IRA1, showed a significant increase in fitness in galactose compared to glucose. In addition, most of our evolved populations (28/46; 61%) fixed aneuploidies on Chromosome VIII, suggesting a parallel adaptive amplification. Finally, we show greater loss of extrachromosomal elements in our glucose-evolved lineages compared with previous glucose evolution. Broadly, these data further our understanding of the evolutionary pressures that drive adaptation to less-preferred carbon sources.

Contrasting modes of macro and microsynteny evolution in a eukaryotic subphylum

Examination of the changes in order and arrangement of homologous genes is key for understanding the mechanisms of genome evolution in eukaryotes. Previous comparisons between eukaryotic genomes have revealed considerable conservation across species that diverged hundreds of millions of years ago (e.g., vertebrates,1,2,3 bilaterian animals,4,5 and filamentous fungi6). However, understanding how genome organization evolves within and between eukaryotic major lineages remains underexplored. We analyzed high-quality genomes of 120 representative budding yeast species (subphylum Saccharomycotina) spanning ∼400 million years of eukaryotic evolution to examine how their genome organization evolved and to compare it with the evolution of animal and plant genome organization.7 We found that the decay of both macrosynteny (the conservation of homologous chromosomes) and microsynteny (the conservation of local gene content and order) was strongly associated with evolutionary divergence across budding yeast major clades. However, although macrosynteny decayed very fast, within ∼100 million years, the microsynteny of many genes-especially genes in metabolic clusters (e.g., in the GAL gene cluster8)-was much more deeply conserved both within major clades and across the subphylum. We further found that when genomes with similar evolutionary divergence times were compared, budding yeasts had lower macrosynteny conservation than animals and filamentous fungi but higher conservation than angiosperms. In contrast, budding yeasts had levels of microsynteny conservation on par with mammals, whereas angiosperms exhibited very low conservation. Our results provide new insight into the tempo and mode of the evolution of gene and genome organization across an entire eukaryotic subphylum.

Mechanisms of regulatory evolution in yeast

Studies of regulatory variation in yeast - at the level of new mutations, polymorphisms within a species, and divergence between species - have provided great insight into the molecular and evolutionary processes responsible for the evolution of gene expression in eukaryotes. The increasing ease with which yeast genomes can be manipulated and expression quantified in a high-throughput manner has recently accelerated mechanistic studies of cis- and trans-regulatory variation at multiple evolutionary timescales. These studies have, for example, identified differences in the properties of cis- and trans-acting mutations that affect their evolutionary fate, experimentally characterized the molecular mechanisms through which cis- and trans-regulatory variants act, and illustrated how regulatory networks can diverge between species with or without changes in gene expression.

Neural networks enable efficient and accurate simulation-based inference of evolutionary parameters from adaptation dynamics

The rate of adaptive evolution depends on the rate at which beneficial mutations are introduced into a population and the fitness effects of those mutations. The rate of beneficial mutations and their expected fitness effects is often difficult to empirically quantify. As these 2 parameters determine the pace of evolutionary change in a population, the dynamics of adaptive evolution may enable inference of their values. Copy number variants (CNVs) are a pervasive source of heritable variation that can facilitate rapid adaptive evolution. Previously, we developed a locus-specific fluorescent CNV reporter to quantify CNV dynamics in evolving populations maintained in nutrient-limiting conditions using chemostats. Here, we use CNV adaptation dynamics to estimate the rate at which beneficial CNVs are introduced through de novo mutation and their fitness effects using simulation-based likelihood-free inference approaches. We tested the suitability of 2 evolutionary models: a standard Wright-Fisher model and a chemostat model. We evaluated 2 likelihood-free inference algorithms: the well-established Approximate Bayesian Computation with Sequential Monte Carlo (ABC-SMC) algorithm, and the recently developed Neural Posterior Estimation (NPE) algorithm, which applies an artificial neural network to directly estimate the posterior distribution. By systematically evaluating the suitability of different inference methods and models, we show that NPE has several advantages over ABC-SMC and that a Wright-Fisher evolutionary model suffices in most cases. Using our validated inference framework, we estimate the CNV formation rate at the GAP1 locus in the yeast Saccharomyces cerevisiae to be 10-4.7 to 10-4 CNVs per cell division and a fitness coefficient of 0.04 to 0.1 per generation for GAP1 CNVs in glutamine-limited chemostats. We experimentally validated our inference-based estimates using 2 distinct experimental methods-barcode lineage tracking and pairwise fitness assays-which provide independent confirmation of the accuracy of our approach. Our results are consistent with a beneficial CNV supply rate that is 10-fold greater than the estimated rates of beneficial single-nucleotide mutations, explaining the outsized importance of CNVs in rapid adaptive evolution. More generally, our study demonstrates the utility of novel neural network-based likelihood-free inference methods for inferring the rates and effects of evolutionary processes from empirical data with possible applications ranging from tumor to viral evolution.

Past, Present, and Future Perspectives on Whey as a Promising Feedstock for Bioethanol Production by Yeast

Concerns about fossil fuel depletion and the environmental effects of greenhouse gas emissions have led to widespread fermentation-based production of bioethanol from corn starch or sugarcane. However, competition for arable land with food production has led to the extensive investigation of lignocellulosic sources and waste products of the food industry as alternative sources of fermentable sugars. In particular, whey, a lactose-rich, inexpensive byproduct of dairy production, is available in stable, high quantities worldwide. This review summarizes strategies and specific factors essential for efficient lactose/whey fermentation to ethanol. In particular, we cover the most commonly used strains and approaches for developing high-performance strains that tolerate fermentation conditions. The relevant genes and regulatory systems controlling lactose utilization and sources of new genes are also discussed in detail. Moreover, this review covers the optimal conditions, various feedstocks that can be coupled with whey substrates, and enzyme supplements for increasing efficiency and yield. In addition to the historical advances in bioethanol production from whey, this review explores the future of yeast-based fermentation of lactose or whey products for beverage or fuel ethanol as a fertile research area for advanced, environmentally friendly uses of industrial waste products.