Yeast

Synthetic allopolyploidization is a powerful strategy for generating strains with novel industrially relevant traits. During the design of select, hybridize, evolved and learn cycle, the mitochondrial inheritance is considered neutral and most studies overcome their phenotypic impact. Here, we generated 168 synthetic allotetraploid strains representing all pairwise parental combinations of eight wild Saccharomyces species, and systematically controlled mitochondrial inheritance in these crosses. These allopolyploids were phenotyped across 31 environmental conditions relevant to biotechnology. In ~50% of all condition-strain combinations conditions, allotetraploids exhibited mid-parent heterosis. In approximately 25% of conditions, we found crosses with hybrid vigor, particularly in combinations involving Saccharomyces arboricola x Saccharomyces mikatae . However, allotetraploids were highly unstable and rapidly sporulated. Our analyses revealed that environmental conditions accounted for the largest effects, follow by its interaction with mitotype. However, mitotype alone showed small effects but significantly affected 42% of the tested conditions, underscoring the importance of mitochondrial inheritance as a key determinant of allopolyploid performance. These findings demonstrate that mitochondrial inheritance is a key, environment-dependent determinant of allopolyploid fitness and should be considered alongside nuclear genome composition in the rational design of industrial allopolyploid strains

Environmental surveys of wild yeasts typically rely on ribosomal barcodes, which cannot resolve cryptic species, interspecific gene flow, mixed cultures, or population structure. To determine what genome-scale characterization adds, we sequenced a representative panel of wild yeasts spanning the genera Saccharomyces, Schizosaccharomyces, and Lachancea using Oxford Nanopore long-read whole-genome sequencing and placed each isolate within published reference datasets. Whole-genome analyses revealed biologically important features that barcoding alone could not detect. A shagbark-hickory isolate resolved as a genuine two-species co-culture. An oak-bark isolate proved to be Schizosaccharomyces versatilis, a recently reinstated species represented by very few known strains, and its analysis demonstrated that standard assembly-quality benchmarks can be misleading for deep-branching taxa. Three Lachancea thermotolerans isolates formed a distinct, previously unsampled population within the wild tree-associated lineage, extending its known geographic range. In contrast, an apparent signal of Saccharomyces eubayanus introgression in two beer-associated S. cerevisiae isolates disappeared after analysis with matched negative controls and de novo assemblies, showing that it reflected mapping artifacts rather than genuine ancestry. Together, these results demonstrate that inexpensive long-read whole-genome sequencing transforms wild-yeast bioprospecting from species identification into a genome-scale framework for resolving cryptic diversity, population structure, and mixed cultures while providing stronger support - and stronger limits - for evolutionary inference. SIGNIFICANCEMost surveys of wild yeasts identify isolates using short DNA barcodes, which are well suited for naming species but often miss the evolutionary relationships and hidden diversity within them. By applying inexpensive whole-genome sequencing to a diverse collection of environmental yeasts, we uncovered previously undetected mixed cultures, a rare recently recognized species, and a distinct wild population, while also showing that an apparent case of interspecies gene exchange was instead a technical artifact. These results demonstrate that genome-scale analysis can both reveal biological diversity that simpler methods overlook and provide the evidence needed to avoid misleading evolutionary conclusions, making it a powerful new approach for studying natural microbial populations.

Lager is the most produced beer style world-wide and makes use of the bottom-fermenting hybrid yeast Saccharomyces pastorianus (S. cerevisiae x S. eubayanus). Previous research showed that flocculation in S. pastorianus, in contrast to the top-fermenting ale yeast S. cerevisiae, is triggered by nitrogen starvation. However, the cellular events leading to flocculation in S. pastorianus are not well characterized. Therefore, we conducted a proteomic screen of S. pastorianus TUM 34/70 and identified the protein kinase Ste20p and protein phosphatase regulatory subunit Ypi1p as higher abundant during flocculation. Overexpression of these genes caused a consistent and strong increase in flocculation rate over the complete duration of beer fermentation. Characterization of Ste20p and Ypi1p via a phospho-proteomics screen showed their targeting of proteins whose S. cerevisiae orthologues are involved in pseudohyphal growth. However, in contrast to this, the overexpression of STE20 and YPI1 led instead to the establishment of a flocculation morphology, giving first-time evidence that S. pastorianus repurposes the pseudohyphal signaling network for this phenotype.

The budding yeast Saccharomyces cerevisiae is a well-established model organism to study cellular stress response and underlying mechanistic regulation. Although glucose starvation fundamentally alters gene regulation and cell behaviour, inconsistent deprivation protocols often trigger gross morphological artefacts. These non-specific changes confound findings by activating pathways independently of true glucose-signalling mechanisms. Furthermore, a thorough transcriptomic profile of glucose starvation using non-confounding conditions remains lacking. Consequently, the precise transcriptional impact of losing key metabolic regulators that mediate adaptation to glucose starvation remains undefined. Here we have employed a refined glucose starvation protocol, utilising raffinose exchange, which shows induction of vast transcriptional stress response with minimal impact on cellular morphology confirmed by label-free imaging. Transcriptomic profiling revealed shifts in metabolic regulation, ATP turnover, and cell-to-cell communication as acute glucose deprivation driving cells towards oxidation-driven metabolism. Additionally, we characterise transcriptional alterations seen in deletion mutants of SNF12 and SPT20, known regulators of cellular metabolism, showing previously unappreciated transcriptional conservation, in part mimicking glucose starvation response. Finally, we identified cargo and stress-specific expression related to both eisosome components and surface transporters that are critical for metabolic adaptation. Overall, this dataset provides a comprehensive transcriptomic resource for dissecting stress signalling and driving novel hypothesis generation.

Three-dimensional live-cell fluorescence imaging of yeast cells is crucial for studying cell-cycle mechanics and regulation. However, extracting multi-channel phenotypes within dense cell clusters remains an image-processing bottleneck. Standard deep-learning models segment cells but fail to track mother-bud boundaries, mitotic spindle shapes and spindle-localizing proteins. Investigators rely on labour-intensive manual coordinate plotting, introducing observer bias and often exclude clustered cell data due to visual complexity. Here, we present an open-source Fiji pipeline for automated yeast cell image processing and deterministic classification of cell-cycle, spindle and protein dynamics. The workflow utilizes a dual-segmentation architecture via custom Cellpose models to capture the mother-bud cell boundaries. Extracted masks are integrated with multi-channel fluorescence data using a Difference-of-Gaussians framework to resolve SPB coordinates and localized protein kinetics, which a rule-based decision-tree maps to precise mitotic phenotypes. Validation demonstrates a 50-fold acceleration with ~6% deviation from manual analysis. Availability: Zenodo at https://doi.org/10.5281/zenodo.22083016.

Brettanomyces bruxellensis is a yeast species associated with diverse fermentation environments and characterized by extensive genetic diversity, including diploid, autotriploid, and allotriploid lineages resulting from independent hybridization events. These lineages are associated with distinct ecological niches and provide a framework for studying metabolic trait evolution in complex genomes. Nitrate assimilation is a relatively uncommon trait among yeasts and has been reported in B. bruxellensis, but its distribution and evolutionary history within the species remain poorly understood. Here, we combined phenotypic characterization of 151 strains with genomic analyses of 946 whole-genome sequences to investigate nitrate assimilation. Growth assays revealed that nitrate assimilation is widespread but unevenly distributed across genetic lineages, with some populations largely retaining the trait whereas others have frequently lost it. Genomic analyses identified extensive variation affecting the nitrate assimilation gene cluster composed of YNR1, YNI1, and YNT1. Nitrate assimilation was strongly associated with both gene copy number and predicted gene functionality, with nitrate-assimilating strains generally carrying more functional copies of the cluster. Leveraging the complex genomic architecture of the species, we independently analyzed primary and acquired genomes in allotriploid lineages and uncovered contrasting evolutionary trajectories following hybridization. While nitrate assimilation genes were generally maintained in primary genomes, acquired genomes showed a higher prevalence of gene loss and predicted loss-of-function variants, revealing asymmetric dynamics between subgenomes. Altogether, our results suggest that nitrate assimilation represents an ancestral trait that has been differentially maintained across B. bruxellensis lineages through a combination of copy number variation, gene degeneration, and genome-specific evolutionary dynamics. These findings provide new insights into how genome architecture and polyploid evolution shape the maintenance and loss of metabolic traits in an industrially relevant yeast species.

The coprophilous agaricomycete Coprinopsis cinerea is a model organism for antagonistic fungal-bacterial interactions. Previous studies showed that C. cinerea responds to antagonistic bacteria with strong induction of a set of genes encoding secreted antibacterial molecules. However, little is known about the elicitors of this response. Key open questions in this respect include whether individual antibacterial defence genes are induced by different bacteria and/or by specific bacterial soluble molecules. Here, we present a new C. cinerea reporter system to monitor antibacterial defence induction and address related outstanding issues with minimal hands-on time. In this system, the promoter of the endogenous bacterial-induced gene cclys1 drives the expression of cnluc, which encodes a secreted variant of the deep-sea shrimp luciferase Nluc. We show that cNluc allows to detect and quantify cclys1 induction by measuring luminescence directly in the culture medium of reporter strain colonies. Building on these features, we successfully leveraged the inducible cNluc reporter strain for the development of a novel 96-well plate assay that allows the high-throughput screening of antibacterial defence elicitors. As cNluc can be subject to degradation by secreted proteases of fungal or bacterial origin in the culture medium, we coupled this assay to confirmatory qRT-PCR. Testing this set-up by confronting the reporter strain with several different bacteria revealed that cclys1 induction occurs independently of the bacterial ecological niche. Based on these results, we also recommend qRT-PCR exclusively for validation of negative results. We conclude that cNluc offers significant advantages over cytoplasmic reporter proteins, especially for preliminary rapid screening of multiple conditions.

Recombinase polymerase amplification (RPA) enables rapid nucleic acid testing in low-resource environments, but poorly characterized byproducts can compromise assay specificity and cause false-positive results. Here, we amplified the thirteen original CODIS core loci and Amelogenin to characterize recurrent RPA artefacts and establish conditions that reduce their formation. First, RPA products were analyzed for two reference samples by Oxford Nanopore Technologies sequencing. This revealed two distinct classes of multimeric products: primer multimers and amplicon multimers, consisting of repeated primer or amplicon sequences, respectively. Individual artefacts contained up to 281 primer copies or 22 amplicon copies, demonstrating the extensive range of these products. Next, we performed an optimization study to evaluate the effects of reaction temperature and reagent concentrations at two representative loci, D3S1358 and D5S818. Among the conditions tested, temperature had the most pronounced effect. Reducing the temperature from 42{degrees}C to 34{degrees}C increased the relative target amplicon fraction from 15% to 83% for D3S1358 and from 84% to 98% for D5S818, while maintaining or increasing absolute target concentration. Lower primer concentrations and higher T4 UvsX concentrations also reduced multimer formation, although lower primer concentrations reduced target yield and caused allelic dropout. Finally, amplification at 34{degrees}C was evaluated across all fourteen loci by sequencing. Relative to 42{degrees}C, the target read fraction increased by more than 5 percentage points for 7/14 loci in one reference sample and 9/14 loci in the other, with the largest improvements at multimer-prone loci. These findings identify multimers as an important class of RPA artefacts and establish reaction temperature and T4 UvsX concentration as promising conditions to improve RPA specificity.

Yeast cells can remain viable for extended periods after entering stationary phase, a survival trait measured as chronological lifespan (CLS). Although CLS is well characterized in Saccharomyces cerevisiae as a model of postmitotic aging, its relevance to human-associated fungi remains poorly understood. Candida species of the CTG (CUG-Ser1) clade vary widely in ecology and clinical importance, raising the question of whether stationary-phase survival is linked to pathogenicity across species or among strains. Here, we combine an optimized CFU-based CLS assay with scalable flow cytometry of membrane integrity across Candida species and genetically diverse Candida albicans isolates. CLS varies extensively across species, yet caloric restriction extends survival in every species examined, revealing a remarkably consistent response to reduced glucose despite marked differences in baseline lifespan. Pathogenic species tend toward longer CLS, but long lifespan is not restricted to them, with the non-pathogenic C. sojae among the longest-lived species examined. Among 20 genetically diverse C. albicans clinical isolates, longer CLS is consistently associates with greater virulence. Our study establishes a methodological framework for comparative CLS analysis, reveals a broadly shared response to caloric restriction, and shows that the association between CLS and virulence emerges within C. albicans but not across Candida species.

Spices contain diverse plant secondary metabolites with antimicrobial and antioxidant activities that can influence plant-microbe interactions. Among these metabolites, curcumin and piperine are major bioactive constituents of turmeric and black pepper, respectively. In this study, we demonstrate that curcumin and piperine enhance alcoholic fermentation in the budding yeast Saccharomyces cerevisiae. Curcumin significantly promoted alcoholic fermentation under high-glucose conditions (20-40% glucose), which impose substantial osmotic stress on yeast cells. Under these conditions, curcumin enhanced yeast growth, improved osmotic stress tolerance, and increased resistance to cell wall digestion, suggesting enhanced stress adaptation during fermentation. Furthermore, deletion of HOG1, which encodes the central MAP kinase of the High-Osmolarity Glycerol (HOG) pathway responsible for the osmotic stress response, abolished the fermentation-enhancing effect of curcumin, indicating that Hog1 function is required for this effect. Consistent with this result, transcriptomic and RT-qPCR analyses revealed increased expression of stress adaptation-related genes, including known HOG pathway-responsive genes. In contrast, the expression of genes involved in amino acid catabolism was decreased at 12 h after the initiation of fermentation, while metabolomic analysis revealed increased intracellular levels of amino acids, including glutamate and asparagine, at 24 h. These coordinated transcriptional and metabolic changes are consistent with reduced amino acid catabolism and a shift toward a metabolic state favorable for sustained fermentation. Together, these findings suggest that curcumin enhances alcoholic fermentation under osmotic stress by promoting stress adaptation that supports yeast growth and sustained fermentation.

High-throughput enzymology enables quantitative characterization of enzyme function across hundreds to thousands of sequence variants and experimental conditions. Nevertheless, the scale and complexity of these datasets create substantial challenges for analysis and quality control. High-Throughput Microfluidic Enzyme Kinetics (HT-MEK), for example, generates large microscopy datasets that must pass through multiple analytical stages, including image processing, initial-rate fitting, and kinetic modeling. Choices or errors made at any stage can propagate into the final kinetic parameters without being evident from fit statistics alone. Here, we provide a broadly applicable guide for analyzing high-throughput enzymology data from the HT-MEK platform, using Michaelis-Menten kinetics as a representative example. We first outline the conceptual workflow from raw fluorescence measurements to estimates of kcat, KM, and kcat/KM. We then discuss common experimental and analytical failure modes and present a framework for deciding when data should be refitted, filtered, qualified, or repeated. Finally, we provide a step-by-step workflow using Mercury, an open-source Python framework that integrates scalable HT-MEK data processing with traceable quality control and diagnostic visualization. This workflow preserves the connection between reported parameters and their underlying measurements and can be adapted to other kinetic models and biochemical assays.

Budding yeast cells can transition from vegetative to filamentous growth under specific environmental stimuli. Saccharomyces cerevisiae has served as a model to understand this process, which is linked to the virulence of many fungal pathogens. One manifestation of filamentation in S. cerevisiae is the formation of pseudohyphal cells, which are elongated and divide in a polarized manner. Here, we established a live-cell imaging assay to monitor this morphogenetic transition and developed a set of fluorescent expression reporters to probe the activity of various signaling pathways during the first 10 hours of this transition. This approach allowed us to identify the stimulus that activates the filamentous growth Mitogen-Activated Protein Kinase (fgMAPK) pathway, which has long evaded identification. Our results indicate that the fgMAPK cascade senses mechanical cues and becomes activated when cells grow on a solid surface. In addition, we have observed that the stimulation of the transcription factor Gln3 regulated by the TOR pathway in low ammonium condition correlates with the elongation of the cells.

Synthetic biologists aim for standardization and simplicity in order to ensure reproducibility and reliability. Toolkits offer both, making it easier to share DNA sequences between labs while minimizing context dependent effects from sequences surrounding the construct of interest. The Yeast Toolkit (YTK) for the model organism Saccharomyces cerevisiae has found wide adoption within the scientific community. While the Toolkit and its existing extensions offer a large variety of different parts, there is a lack of characterized logic gates and insulator containing backbones for the assembly of genetic circuits with the yeast toolkit syntax. In this work, we present the Yeast Logic Toolkit (YLT). YLT contains 40 pre-assembled backbones with dropouts, 109 parts for NOT/NOR gate assembly, and a subdivided promoter Type 2 part that allows more flexible 5'UTR design. For insulation, the backbones contain spacer sequences and self-cleaving ribozymes which buffer against transcriptional read-through from upstream sequences. Due to our subdivision of Type 2 parts, we are able to manipulate the 5' untranslated region without a cloning scar upstream of the start codon. We also characterized the NOT and NOR gates from the Cello library for yeast in the sequence context of the yeast toolkit cloning scheme. This toolkit extension will make it easier and faster for scientists to assemble genetic circuits in yeast while providing a minimum of context dependent effects such as genetic read-trough due to the standardization of up- and downstream sequences surrounding the transcriptional units.

Domestication of molds for cheese production has repeatedly shaped Penicillium fungi, most notably giving rise to the emblematic P. camemberti lineage, derived from P. biforme. Here, we identified a new P. biforme lineage, named cheesy, likely selected from P. biforme for food fermentation, including cheese and sausage production. This lineage exhibits evidence of a severe bottleneck, with little nucleotide polymorphism and a single mating type. The cheesy lineage has evolved advantageous traits for cheesemaking: compared to other P. biforme strains and its wild relative P. fuscoglaucum, it displays faster growth on cheese, galactose and lactose media, higher sporulation and germination rates on cheese, elevated lipolytic activity, enhanced inhibition capacities, and produced specific volatile organic compounds. Additionally, P. camemberti and P. biforme cheesy differ in their content of Starship mobile elements, acquired through horizontal transfers. These elements carry cargo genes potentially relevant for adaptation to cheese. Notably, the cheesy lineage has acquired a 20 kb Starship element (Rattus), nested within a much larger 160 kb Starship (Bilge), and carrying cargo genes with predicted functions involved in antagonistic interactions among micro-organisms. SignificanceO_LIWe identified a new Penicillium biforme lineage, named cheesy, which was likely selected from P. biforme for food fermentation (cheese and sausage), genetically and phenotypically different from the emblematic P. camemberti lineage. This lineage suffered from a severe bottleneck, displaying very little nucleotide polymorphism and a single mating type. C_LIO_LIThis newly identified lineage has evolved advantageous traits for cheesemaking; compared to other P. biforme strains and its wild relative P. fuscoglaucum, it displayed faster growth on cheese, galactose and lactose media, higher sporulation and germination rates on cheese, higher lipolytic activity, better inhibition capacities and specific volatile organic compounds. C_LIO_LIPenicillium camemberti and P. biforme cheesy also differed by their content in Starship mobile elements, acquired through horizontal transfers, and carrying cargo genes potentially relevant for adaptation to cheese. C_LIO_LINotably, the cheesy lineage has acquired a specific 20 kb Starship nested within a much larger 160 kb Starship, and likely involved in antagonistic interactions. C_LI

To face the fungal infections that affect millions of people every year, a better understanding of resistance-conferring mutations is necessary. One obstacle is the considerable time and effort necessary to construct point mutations in pathogenic species, which is required to validate their role in resistance. To overcome this problem, we have constructed a series of heterologous expression plasmids that allow expression of the ERG3, ERG6 and ERG11 orthologs from Candida albicans, Candidozyma auris, Nakaseomyces glabratus, Candida parapsilosis, Candida tropicalis, and the CYP51A and CYP51B genes of Aspergillus fumigatus. All orthologs are codon-optimized and synthesized for expression in the budding yeast Saccharomyces cerevisiae. We also constructed host strains in which the native ERG genes are either deleted or under the control of a repressible promoter. We showed that all orthologs complement the function of the native genes when expressed from the S. cerevisiae native promoters. We recreated previously reported resistance-conferring mutations, and showed that expression in S. cerevisiae replicates known resistance phenotypes. We then used the system to test corresponding mutations across orthologs, and showed that most resistance phenotypes are conserved. The heterologous expression system allows rapid construction of mutants, by taking advantage of the abundant genetic tools available for S. cerevisiae. Screening of mutants can be done within a few experimental steps, greatly increasing the throughput compared to the introduction of mutations in pathogenic fungi. As a proof-of-concept, we used the system to discover new resistance-conferring mutations, using random mutagenesis. All plasmids are made publicly available.

Cell differentiation into distinct cell types generates functional specialization in eukaryotic organisms. Many fungal species undergo filamentous growth, where cells differentiate into elongated and adhesive filaments capable of expansion and invasion into new environments. The budding yeast Saccharomyces cerevisiae also undergoes filamentous growth, and the regulatory pathways that control the response have been well characterized; however, the roles essential proteins play in this response have not been systematically explored. To address this gap in understanding, we constructed a collection of 332 temperature-sensitive (ts) alleles in 320 essential genes in a strain background that undergoes filamentous growth (called {Sigma}1278b or Sigma). The ts Sigma collection showed differences in temperature sensitivity compared to a ts laboratory strain collection, revealing unexpected phenotypic diversity in essential alleles across populations of individuals. Screening the ts Sigma collection for phenotypes related to filamentous growth uncovered new phenotypes for >35% of essential alleles. New regulators of the Mitogen-Activated Protein Kinase (MAPK) pathway that regulates filamentous growth (fMAPK) were identified, including Las17, a homolog of Wiskott-Aldrich Syndrome Protein (WASP) in humans. Las17 regulated the fMAPK pathway by promoting delivery of the sensor protein, Sho1, and Rho GTPase Cdc42 to the plasma membrane. Las17 also functioned as a hub coordinating separate parallel aspects of the filamentation response. The widespread roles for essential proteins in regulating a eukaryotic differentiation response suggest broader roles essential proteins than is currently appreciated.

The crystal violet (CV) microtiter plate assay is widely used to compare microbial biofilm formation because it is inexpensive, simple, and readily adapted to 96-well formats. Its high-throughput design enables multiple strains, growth conditions, and treatments to be tested in parallel, but increasing experimental complexity can make downstream data handling difficult. Plate layouts, absorbance measurements, blank correction, replicate analysis, and visualization are often managed using separate spreadsheets or software, requiring repeated transfer and organization of experimental information. This can compromise consistency in linking measurements with their corresponding conditions and controls. We developed BiofilmQ-HT, a standalone, browser-based workflow that integrates plate annotation with direct import of plate-reader data, condition-specific blank correction, replicate summarization, growth-normalized specific biofilm formation (SBF) analysis, percentage-inhibition analysis, visualization, and data export. The workflow was applied to three representative datasets: a comparison of biofilm formation in 25% and 100% media, an analysis of bacteriophage- and antibiotic-associated antibiofilm activity, and a screening of biofilm formation among natural microbial isolates. These applications demonstrate a common analytical framework for comparative biofilm analysis, antibiofilm screening, and high-throughput isolate screening while retaining experimental conditions and controls. By linking plate organization to quantitative analysis and reporting, BiofilmQ-HT provides a reproducible and traceable approach for processing condition-rich CV assay datasets and facilitates consistent comparisons across experimental groups. The utility therefore improves consistency in data handling without altering the underlying experimental assay or requiring changes to the established assay.

Filamentation, a central virulence trait of the fungal pathogen Candida albicans, is required for host cell damage, tissue invasion, and biofilm formation. The transcription factor Bcr1 was first found to be required for biofilm formation but not filamentation. Subsequent studies revealed a negative role for Bcr1 in filamentation in opaque cells, a cell type that is required for mating, under hypoxic conditions, and in a wor2del/del mutant background. Here we characterize a new context in which Bcr1 negatively regulates filamentation and present its associated gene expression impact. We compared the wild-type and bcr1del/del mutant cells in the SC5314 reference strain background at 30 degrees C in glucose media, conditions that do not induce filamentation. The bcr1del/del mutant displayed increased invasive growth in a solid medium, and some filamentation ability in a liquid medium. The bcr1del/del effect on filamentation was augmented by overexpression of hyphal cyclin gene HGC1, which caused pseudohyphal growth in wild-type, efg1del/del, or brg1del/del strains, yet caused hyphal growth in the bcr1del/del strain. RNA-sequencing (RNA-seq) analysis of 30 degrees C cells shows that the bcr1del/del mutant has elevated expression of two genes that drive filamentation: HGC1 and UME6. In published data these same two genes have decreased expression in the bcr1del/del mutant at 37 degrees C, the temperature at which biofilm formation is typically assayed. A growing cadre of biofilm/hyphal regulators can have both positive and negative effects on hypha-associated gene expression, including Bcr1, Efg1, Ndt80, and Nrg1.

Forest-associated Saccharomycotina occur at low relative abundance, limiting inference about their diversity and dynamics. We sampled leaf litter weekly for 47 weeks across a subtropical forest in northern Taiwan. Enrichment, isolation and ITS sequencing recovered 687 isolates, including 613 Saccharomycotina representing 56 described species and 77 putatively novel operational taxonomic units. Rarefaction indicated unsampled culturable diversity. Among litter traps, community dissimilarity was high and dominated by taxon replacement, but neither topography nor geographic distance was associated with composition, and turnover matched randomised expectations. Richness peaked during warm, wet periods and declined in winter, and minimum temperature showed the strongest statistical association. Composition was associated with maximum temperature, minimum relative humidity, precipitation and solar radiation. Selected isolates' thermal optima covaried with collection-week temperatures, and two October Magnusiomyces magnusii isolates had higher optima than four winter isolates. Together, these findings reveal substantial culturable diversity and seasonal community restructuring consistent with temperature-related filtering.

The Candida Genome Database (CGD; www.candidagenome.org) is both a model organism database and a fungal pathogen database. As a model organism database, CGD stores data for Candida albicans, which serves as a model species both for other Candida spp. and for non-Candida fungi that form biofilms and undergo routine morphogenic switching. As a fungal pathogen database, CGD now hosts locus pages for six species of the best-studied pathogenic fungi in the Candida group. Pathogenic Candida species have become increasingly drug resistant and there is thus a pressing need for research into basic Candida biology, epidemiology, phylogeny, and potential new antifungals, as well as a single location where all of the available data are collected, curated, and made easily searchable. CGD curates the gene-based Candida experimental literature in real time, extracting, organizing and standardizing gene annotations. CGD also links clinical data on disease to relevant Literature Topics to improve searchability for clinical researchers. Because CGD curates the literature for multiple species and most research focuses on aspects related to pathogenicity, we focus our curation efforts on assigning Literature Topic tags, collecting detailed mutant phenotype data, and assigning controlled Gene Ontology terms with accompanying evidence codes. Our Summary pages for each locus include the primary name and all aliases for that locus, a description of the gene and/or gene product, detailed ortholog information with links, a synteny view, a JBrowse window with a visual view of the gene on its chromosome, links to Phenotype, Gene Ontology, Interactions, and Expression pages, as well as sequence information, references cited on the summary page itself, and any locus notes. The database also serves as a community hub, where we link to various types of reference material of relevance to Candida researchers, including colleague information, news, and notice of upcoming meetings. We routinely survey the community to learn how the field is evolving and how needs may have changed. Here we describe CGDs new modern web interface and multiple new tools that have been added in the last 6 months, allowing, among other things, users to better understand the available expression data for a locus and seamlessly switch between species for a given locus.