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

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.

Fungal diseases cause devastating crop infestations and millions of deaths annually. To improve disease treatment development, we must understand the biological processes these treatments target and the fungal cellular responses they elicit. Current methods to identify genetic responses of fungi to antifungal drugs and fungicides typically involve laborious molecular genetics experiments or transcriptomics. We utilized high-throughput screens in the basidiomycete yeast Rhodotorula (Rhodosporidium) toruloides to rapidly identify genes associated with the fungal response to a copper-zinc fungicide developed by VM Agritech and compared identified genes to those transcriptionally activated in response to the fungicide in R. toruloides and the filamentous ascomycete Neurospora crassa. These 'omics technologies combined with molecular genetics and biochemical analyses showed copper and zinc synergize to inhibit fungal growth due, at least in part, to an increase in cellular zinc concentrations when copper is present. Intriguingly, although we identified genes involved in the copper-zinc fungicide response using both high-throughput screens and transcriptomics, there was little overlap in genes identified through the two methods. Our findings demonstrate the power of combining functional genomics and transcriptomics approaches in identifying a more comprehensive map of the genetic mechanisms necessary for responding to fungicides.

To reduce health risks for human space exploration, it is important to model the effects of deep-space radiation on biological systems. The budding yeast Saccharomyces cerevisiae is a common model organism in space radiobiology, but little is known about how radiation damage to individual cells translates into the population-level effects that experiments measure. The Agent-Based Model for Microbial Populations Exposed to Radiation (AMMPER) is a spatially explicit agent-based model that simulates the effects of ionizing radiation on S. cerevisiae cells and produces population-level results. Its goal is to improve experiment design and data interpretation. AMMPER-1 demonstrated that agent-based simulations can qualitatively reproduce the effects of proton radiation on the growth rate of wild-type and DNA-repair mutant yeast. Here, we present AMMPER-2, which addresses limitations of the first model and expands its capabilities. AMMPER-2 incorporates the dynamics of the redox dye alamarBlue, a data type commonly generated in spaceflight microbiology experiments, and models the fate of reactive oxygen species in more detail. It also adds an improved graphical interface and runs faster. AMMPER-2 remains easy to execute in Python on a standard personal laptop, providing space biologists a tool to explore experimental conditions, generate hypotheses, and interpret data from microbial space radiation experiments.

Antifreeze proteins and peptides adhere to ice crystals and inhibit their growth, resulting in freezing point depression. AFP6 is an abundant antifreeze peptide in the blood serum of winter flounder (Pseudopleuronectes americanus). This 37-residue peptide forms an amphiphilic -helix with a hydrophobic ice-binding surface. In this study, prediction of the peptide structure suggested the formation of an antiparallel dimer burying the hydrophobic surfaces of both subunits. The oligomerisation of AFP6 was therefore examined in aqueous solutions using size-exclusion chromatography and chemical crosslinking along with ice-binding evaluation. Crosslinking of non-amidated AFP6, followed by denaturing electrophoresis, revealed bands consistent with monomers and dimers, whereas results for the amidated form and a recombinant mutant suggested additional larger forms. Bands consistent with the presence of monomers and dimers were also predominant following non-amidated AFP6 crosslinking under a variety of solution conditions, with smaller proportions of peptide assembled up to tetrameric sizes; however, the larger oligomers appeared to be absent from AFP6 treated with sodium bicarbonate. Isolated oligomers of non-amidated AFP6 produced ice crystal morphologies and thermal hysteresis comparable to those for the unfractionated peptide suggesting similar interaction with ice. Oligomerisation of AFP6 may allow greater solubility of this amphiphilic -helical peptide in aqueous solutions.

Epigenetic information is required for the maintenance of gene expression states through cell division. Some epigenetic information can also persist through generations, raising the possibility that epigenetic differences may arise in populations and contribute to evolutionary processes such as drift and natural selection. Evaluating this requires characterising the properties of such epimutations, so that their rate, stability and genome-wide distribution can be assessed. Recent experiments in many organisms have demonstrated that epimutations occur, but have limited stability relative to DNA sequence mutations. However, the extent to which epimutations contribute to evolution is still unclear, in part because it is not clear whether epimutations respond dynamically to environmental conditions. Here, we use the fission yeast S. pombe, in which evolutionarily relevant epimutations have been observed, but not yet systematically characterised, to test whether a physiologically relevant stress, ethanol exposure, leads to changes in the properties of epimutations. Using laboratory evolution experiments with repeated population bottlenecks to minimise selection, we show that epimutations associated with changes in small interfering (si)RNAs occur at a greater rate in ethanol. Ethanol-induced epimutations are enriched at transposable element loci and correlate with changes in transposon expression. Ethanol exposure also increases gene expression noise genome-wide and variability in growth rate; importantly, both these increases are suppressed in mutants lacking siRNAs. Together, these results demonstrate that stress can alter the generation of heritable epigenetic information, and suggest that siRNAs may have a role in promoting phenotypic variability in response to environmental stress.

Bacterial mutation rates are traditionally inferred from phenotypic data using fluctuation assays. Mutation rate computation from these assays relies on a mathematical model describing the emergence of mutants during population growth. However, this standard model relies on restrictive assumptions that are often transgressed in real biological setups. Key assumptions include equal growth rate of the wild-type and the mutant population, no cell death during the growth phase, and no post-growth sampling. Although several refined mathematical models have been proposed over the last decades to circumvent some of these assumptions, none can fully account for the complex ecological scenarios frequently observed in the lab or in the wild, such as the combination of cell death and an unknown fitness effect of the mutation, or non-constant death rates. In this work, we propose to replace these standard mathematical models by a stochastic simulation framework, which can circumvent all these assumptions. We provide a fast and accurate implementation of this stochastic model, and combine it with an Approximate Bayesian Computation scheme to perform simulation-based, likelihood-free parameter inference. Our approach can simultaneously infer mutation rate and fitness effect of the mutation while accounting for death and partial plating, and could be extended to arbitrary complex conditions that can be efficiently simulated.

Understanding floral visitor dynamics along elevational gradients is essential for assessing potential implications for pollen limitation and population genetic processes in fragmented populations of cliff-dwelling alpine endemics. Physoplexis comosa (Campanulaceae) is a chasmophytic paleoendemic restricted to vertical rock faces on dolomitic and limestone bedrock from 200 to 2,800 m a.s.l. The species exhibits a specific floral morphology with fused corolla apices, basal openings for nectar access, and secondary pollen presentation, yet its functional floral visitor assemblage has remained poorly characterized across the species' elevational range. In this pilot study, we tested a two-tier camera-monitoring setup combining action cameras for diurnal monitoring with Raspberry Pi-based systems equipped with IR illumination for combined diurnal and nocturnal recording. We conducted monitoring across five elevational sites (1,480 to 2,400 m a.s.l.) in the Eastern Alps. Recorded video material was downsampled and annotated using the Addax platform alongside manual cross-validation to record physical contact events. Preliminary results confirm the technical feasibility of continuous monitoring in steep terrain and suggest possible elevational variation in diurnal visitors, alongside nocturnal activity by Geometridae moths. Camera-based observations provided higher functional resolution and revealed a different visitor assemblage than previous eDNA metabarcoding trials. This proof-of-concept establishes a methodological foundation for forthcoming multi-day monitoring campaigns and complements ongoing studies of the mating system and population-genetic analyses.

Bacterial genomes are dynamic and harbour accessory regions that can be gained, lost, or rearranged in response to selective pressures. Members of the genus Komagataeibacter are used for bacterial cellulose production and researched as platforms for engineered living materials. However, their genomes are rich in mobile genetic elements (MGEs), including insertion sequences (ISs), genomic islands and prophage remnants, which drive genome rearrangements under agitated cultivation conditions. Whether this genome architecture contributes to genomic changes during routine strain maintenance and distribution remains poorly understood. Comparative genome sequencing of independent Komagataeibacter rhaeticus iGEM stocks revealed recurrent loss of a 210 kbp chromosomal region flanked by homologous IS5 sequences. This deletion was identified in a stock received as an agar stab and reproduced from an intact-genome population subjected to simulated agar-stab handling. Phylogenomic analysis of the affected locus revealed gene-tree/species-tree discordance, heterogeneous GC content and multiple ISs, supporting its characterization as a dynamic accessory region. Populations carrying the larger genome reduction showed improved growth and cellulose production relative to the intact genome reference, whereas populations carrying a smaller nested deletion showed reduced performance. These findings demonstrate that routine strain handling is not necessarily genomically neutral and can expose structural genomic variabilities that generate population-level genomic heterogeneity with phenotypic consequences. For bacteria with MGE-rich genomes, handling history may represent an underappreciated source of genomic and phenotypic variation between laboratories. More broadly, identifying unstable accessory regions may highlight genomic content that is dispensable under laboratory conditions, providing candidates for genome streamlining and strain improvement.

Stemflow transports water and biological material from forest canopies to the stem base, yet fungal studies of this flux have largely relied on microscopy of conidia. We used ITS2 metabarcoding to characterize fungal environmental DNA (eDNA) in stemflow from 15 trees - five each of American beech (Fagus grandifolia), sugar maple (Acer saccharum), and tulip poplar (Liriodendron tulipifera) in a closed-canopy forest in northeastern Ohio, USA. Stemflow was sampled during eight rain events in the leafless season (November 2024-May 2025), along with simulated bark and gutter washes to assess near-collar and collector signals. Natural stemflow communities were compositionally distinct from both controls and occupied greater ordination space. Ascomycota dominated across all samples, with Parafenestella, Cytospora, Microcera, Nectria, and Aureobasidium among the most abundant resolved genera and 13 of the 25 most abundant taxa differed significantly among host species. Woody-plant-associated endophytes, canker fungi, and saprobes dominated ecological guild composition. Storm event explained 28.6% of taxonomic variation, host tree species 24.1%, and their interaction 10.0%. Guild composition was more strongly structured by host species (35.4%) than storm event (20.4%). Lichenized fungi and lichen-associated fungi were detected. Thus, leafless-season stemflow integrates broad bark-associated fungal eDNA, including recurrent lichen-derived material, beyond the morphologically distinctive conidia captured by traditional methods. Stemflow eDNA therefore offers a minimally invasive means of monitoring canopy fungal diversity and the strong host and temporal filtering of DNA exported from woody surfaces.

Mutation spectra vary among populations, and a comprehensive view of this variation requires broad sampling and fine-scale population resolution. Here, we profile mutation spectra from single-nucleotide polymorphisms and small insertions and deletions in a uniformly processed collection of 3,034 globally sampled Saccharomyces cerevisiae genomes, and an extended dataset including the previously sampled global 1,011-genome collection. Major mutation spectrum patterns reported from the 1,011 genomes remain evident in the extended dataset, including the pronounced mutation-spectrum differentiation of African Beer strains. At finer population resolution, we identify additional variation among wine-associated populations, including a Georgian Wine-associated signal that is strongest among rare variants and is therefore consistent with a comparatively recent change in mutation processes. We further apply a sequence-context-aware classification to characterize small-indel profiles across the 3,034 natural yeast genomes. Together, our analyses show that expanded sampling and refined population assignments provide a more comprehensive view of mutation-spectrum variation within S. cerevisiae.

Data curation-the process of collecting, cleaning, and joining raw datasets for unified analysis-is a time-consuming yet crucial part of any data science project. With the emergence of powerful agentic coding tools, it is tempting to "vibe curate"-i.e., to prompt AI agents to perform data curation operations and blindly trust their outputs in order to finish work more quickly. However, this can exacerbate two key challenges that already plague manual data curation workflows: reproducibility-the ability to trace the exact set of modifications applied to raw datasets-and verifiability-the ability to audit changes and confirm that data is processed properly. To address these issues, we introduce Scrub Data, a framework that enables the use of AI agents in data curation workflows while transparently maintaining both reproducibility and verifiability. The framework involves an interactive data curation loop between a user and an AI agent, backed by a data provenance graph that tracks and versions all dataset updates. The data graph requires that all updates are formatted as self-contained executable steps, allowing any version of a dataset to be reconstructed from raw data by playing forward the transformations stored in the graph. This workflow takes place within a lightweight web application that is designed to be modified by users and agents in real-time to create custom visualization tools for identifying data curation needs and verifying outcomes. We demonstrate the usefulness of the framework with a real data curation use case from animal movement ecology. Starting with 89M raw GPS coordinates, we use the framework to curate a benchmark dataset of 2.5M coordinates to be used for machine learning or statistical analysis. The framework is available for use and extension at https://github.com/justinkay/scrubdata.

Gene duplication is an important evolutionary mechanism contributing to genomic innovation and adaptation. While the long term fate of duplicated genes has been extensively studied, immediate effects such as those resulting from increase in gene dosage remain understudied. Of particular interest is the question of how expression level relates to the optimum after a duplication, as it could fall short, exceed or directly reach the optimal expression. In this study, we investigated the relationship between expression and fitness for 11 genes previously reported to increase fitness when duplicated in Saccharomyces cerevisiae to compare the expression level achieved by duplication to the one maximizing fitness. While most of the studied genes show little fitness variation across the expression levels tested, we found that ESP1, which encodes a separase essential to anaphase initiation, exhibits a clear fitness optimum at an expression level above the native single-copy state. However, the expression level associated with gene duplication exceeds the optimum. We find that ESP1 overexpression is associated with a reduced cell size and a lower proportion of the cell cycle spent in G2 phase, consistent with its role in cell cycle progression. We propose that the duplication of ESP1 accelerates the cell cycle, resulting in smaller, faster-dividing cells. When measured in different environments, the fitness functions also exhibit similar shapes, with slight variation in the optimal expression. Our findings highlight how gene duplication can confer an immediate selective advantage through dosage increase while being non-optimal, reversing the directionality of natural selection on expression level after duplication.

BACKGROUND: The protein 4.1a/4.1b ratio is an intrinsic molecular marker of mean red blood cell (RBC) age resulting from progressive deamidation of protein 4.1b during RBC circulation. Despite its potential for estimating mean RBC age from a single blood sample, its application has been limited by labor-intensive RBC membrane preparation, and its interindividual variability has not been characterized in a large human population. METHODS: We developed a low-volume method for direct RBC membrane isolation from whole blood using saponin permeabilization and differential centrifugation without prior RBC washing. Membrane proteins were separated by SDS-PAGE, and protein 4.1a/4.1b ratios were determined by densitometric analysis with Gaussian peak fitting. Assay conditions, sample-volume requirements, membrane protein recovery, and analytical reproducibility were evaluated. The method was subsequently applied to 114 anonymized residual samples from routine diagnostic testing selected for complete blood count parameters within the corresponding laboratory reference intervals. RESULTS: The optimized procedure used 50 uL of whole blood, 0.06% saponin, and centrifugation at 9000 g, although protein 4.1a/4.1b remained measurable from starting volumes as low as 5 uL. Mean within-subject CVs were 3.90% for electrophoretic/densitometric determination and 5.39% for membrane protein recovery; whole-procedure CVs in 3 subjects were 1.40% to 3.50%. In the population analysis, the mean protein 4.1a/4.1b ratio was 1.428 (SD 0.146), with an observed range of 1.052 to1.799 and a central 95% interval of 1.151 to 1.695. Ratios did not differ significantly between females and males (P=0.246) or among females aged 18 to 50 years, females aged >50 years, and males (P=0.151). The ratio showed modest positive correlations with chronological age in females (Spearman p=0.26, P=0.047) and males (p=0.33, P=0.015), while substantial interindividual variability remained across the age range. CONCLUSIONS: Direct isolation of RBC membranes from small volumes of whole blood enables reproducible determination of the protein 4.1a/4.1b ratio using a simplified workflow. Application of the assay to a comparatively large human population revealed substantial interindividual variation in this molecular marker of mean RBC age that was not explained by sex or chronological age alone. The method provides a practical approach for investigating biological variation in mean RBC age and its potential contribution to laboratory measurements influenced by RBC survival.

Numerous CRISPR-Cas systems have been developed for molecular detection of genetic elements exploiting the trans-cleavage activity of LbCas12a combined with short fluorescent probes. Alongside, a large variability of buffer conditions has been reported. However, how solution chemistry balances enzymatic turnover, signal stability, and detection performance have not been systematically defined. Here, we evaluated how the interplay between anions (chloride vs. acetate), additives, sequence probes, and ionic strength contributes to LbCas12a trans-cleavage activity. Buffer composition screening revealed that chloride-based buffers maintain a low background but slow catalytic rates, meanwhile acetate-based buffers accelerate enzymatic turnover with and without the target DNA sequence, increasing non-specific signals. Reducing agents and surfactants were the best enhancer combinations, improving cleavage performance by increasing ternary complex formation (Km). High salt concentrations only slightly improved the reaction kinetics. Finally, the 5FAM-TTATT-3BHQ-1 reporter showed the best balance between signal intensity and nonspecific background. Our findings indicate that LbCas12a tolerates a vast buffer composition landscape, maintaining robust trans-cleavage activity and detection performance. However, conditions that enhance catalytic activity simultaneously increase nonspecific probe cleavage and higher background, resulting in lower detection performance. Therefore, assay optimization should prioritize detection performance rather than maximal fluorescence output, where solution chemistry is a critical determinant.

Jeongeupia sacculi (HS-3) is a novel {beta}-proteobacterium with a unique multicellular life cycle. The genetic tractability and mechanisms underlying differentiation are unknown. Here, we adapt a method of homologous recombination for genetic modification in HS-3 and generate a disruption mutant of rpoS, which encodes the alternative sigma factor{sigma} S commonly associated with general stress response or major behavioral switches. We then characterize phenotypes associated with rpoS disruption. Under low-nutrient conditions, rpoS disruption reduced Congo red binding, consistent with rpoS acting as a regulator of low-nutrient response by upregulating production of biofilm-associated materials. Surprisingly, rpoS disruption did not significantly alter survival in response to other stressors in general stress response assays tested. Our work establishes a method for genetic manipulation in HS-3 and enables future investigation into the life cycle of HS-3, including whether rpoS has a role in differentiation triggered by low-nutrient response.

Pseudohyphal growth in skin-associated fungi is often considered a morphological response to environmental stress, but whether it represents a coordinated metabolic state that influences host immunity remains unclear. Using Malassezia furfur, we combined synchronized morphogenesis, temporal metabolomics, stable-isotope tracing, targeted metabolite measurements, transcriptional profiling, and functional immune assays to compare yeast and pseudohyphal states. Yeast cells maintained an active tryptophan-aldehyde metabolic program that partitioned carbon between oxidative and reductive branches associated with redox balance and methylation potential. Pseudohyphal cells attenuated this program and instead underwent sequential metabolic remodeling, characterized by early changes in one-carbon and amino acid metabolism followed by sulfur-pathway remodeling and increased glutathione biosynthesis. These distinct fungal states generated extracellular environments that altered THP-1 innate immune responsiveness without directly inducing canonical macrophage polarization. Yeast-conditioned cells responded preferentially to tissue-repair signals, whereas pseudohypha-conditioned cells displayed enhanced responses to inflammatory stimuli. Individual metabolites did not reproduce these effects, suggesting that immune conditioning depends on the integrated extracellular milieu. Together, these findings identify pseudohyphal growth as an organized adaptive metabolic state and establish a framework linking fungal morphogenetic potential to context-dependent host immune responses.

1. Thermal performance curves (TPCs) are widely used to quantify temperature dependence of biological traits, but estimating them requires experiments across multiple temperatures. Because these experiments can be costly, researchers must balance the number and placement of temperature treatments against replication within treatments. Evenly spaced temperatures are a common default, but may allocate effort inefficiently when thermal responses are nonlinear or strongly asymmetric. 2. We developed TPCdesign, an R package for planning temperature-trait experiments. TPCdesign uses a pseudo-Bayesian (robust) D-optimal experimental design to identify sets of temperatures expected to provide the most information about a TPC, while allowing users to incorporate prior knowledge of thermal limits and curve shape, uncertainty in that knowledge, available numbers of treatments, and practical restrictions on temperature spacing. 3. Using simulation-based worked examples, we show that optimized designs can recover TPCs more accurately than evenly spaced designs, particularly for asymmetric curves and when the number of available temperature treatments is modest. Optimization primarily improves resolution of regions where performance changes rapidly and can substantially improve estimation of upper thermal limits while retaining information across the rest of the curve. 4. TPCdesign provides a practical framework for allocating limited experimental resources according to the biological response researchers seek to estimate. Rather than prescribing a universal set of temperatures, it allows experimental designs to reflect existing biological knowledge, uncertainty, and logistical constraints, improving the information gained from costly thermal performance experiments.

Introduction. Histoplasma capsulatum is an important fungal pathogen of humans, especially in immunocompromised patients, and the World Health Organisation has listed Histoplasma as a High Priority fungal pathogen. The taxonomy of the genus Histoplasma is still under development, but its only species H. capsulatum has at least of seven lineages, and a range of sublineages. Gap Statement. Allelic multilocus sequence typing (MLST) has been very successfully applied for typing and epidemiology of pathogenic bacteria, but its adoption for fungal pathogens is more limited. Genome sequence-based MLST approaches promise much a higher resolution for comparative phylogenetics, but there are only a small number of genome assemblies available for H. capsulatum. Aim. To develop and validate genome-based MLST typing for H. capsulatum. Methodology. A total of 406 genome assemblies were generated from publicly available Illumina short-read sequencing samples. Selected genome assemblies were subsequently used to generate MLST schemes with chewBBACA, based on whole genome sequences (wgMLST), NCBI-obtained annotations (annMLST) and annotations obtained with Funannotate (fanMLST), and used for lineage identification, and comparative analyses of population structure. Results. Genome assemblies were successfully generated for 406 H. capsulatum samples, with BUSCO completeness scores of over 98%. A subset of 60 genome assemblies was used to generate and validate MLST schemes based on the 60 genome assemblies, 5 genome annotations obtained from Genbank, and 13 genome annotations generated using Funannotate, resulting in schemes with > 8,000 markers. Each of the MLST schemes allowed reproducible separation of all 7 lineages and 6 H. capsulatum Suramericanum sublineages, without the need for high-performance clusters or powerful computing equipment. Comparison of the different schemes using tanglegrams and scatter plots showed good reproducibility (r2 values of 0.8-1.0). Comparison of total sizes of genome assemblies showed significant lineage-dependent size differences, with the Suramericanum, LAmB, India, Capsulatum and Mississippiense lineages averaging a total genome size of 30-33 million bp, and the Africa and Ohiense lineages averaging at 39 million bp. Conclusion. Genome sequence- and especially genome annotation-based MLST analyses are a promising approach that can be adapted as a rapid, high-throughput method for genomic clustering and epidemiological tracing of pathogenic fungi.

Aims Honey represents a distinct microbial habitat, imposing physicochemical stresses on its resident microbiota while also serving as a potential source of beneficial microorganisms. This study aimed to isolate lactic acid bacteria (LAB) from Korean wildflower honey and characterize their gastrointestinal (GI) and physiological stress tolerance, adhesion-related properties, functional characteristics, and safety to evaluate their potential as probiotic candidates. Methods and Results Two Streptococcus salivarius strains, DOW-5A and DOW-10, were isolated from Korean wildflower honey and identified by phenotypic and molecular analyses. Both strains survived in sequential exposure to simulated GI conditions and showed tolerance to physiological stresses. DOW-5A maintained higher viability during the simulated gastric phase, whereas DOW-10 showed an initial decrease in viable counts followed by an increase during the simulated intestinal phase. The two strains also exhibited various probiotic characteristics, including mucin adhesion and antioxidant activity. Atypical, crystalline colony morphologies associated with EPS production were observed when sucrose was supplied as a carbon source. Both strains formed biofilms, while DOW-5A showed a marked increase in biofilm formation upon sucrose supplementation. Neither strain showed gelatinase or hemolytic activity or significant cytotoxicity toward Caco-2 cells. Impact Statement In this study, we isolated two honey-derived S. salivarius strains with high probiotic potential. Our findings highlight wildflower honey as a potential reservoir of LAB with traits relevant to survival under GI and physiological stresses, as well as various probiotic traits.