The ecology and genetic diversity of model yeast Saccharomyces cerevisiae prior to human domestication remain poorly understood. Taiwan is regarded as part of this yeast's geographic birthplace where the most divergent natural lineage was discovered. Here, we extensively sampled the broad-leaf forests across this continental island to probe the ancestral species diversity. We found that S. cerevisiae is distributed ubiquitously at low abundance in the forests. Whole-genome sequencing of 121 isolates revealed nine distinct lineages that diverged from Asian lineages during the Pleistocene, when a transient continental shelf land bridge connected Taiwan to other major landmasses. Three lineages are endemic to Taiwan and six are widespread in Asia, making this region a focal biodiversity hotspot. Both ancient and recent admixture events were detected between natural lineages and a genetic ancestry component associated with isolates from fruits was detected in most admixed isolates. Collectively, Taiwanese isolates harbor genetic diversity comparable to that of the whole Asia continent, and different lineages have coexisted at a fine spatial scale even on the same tree. Patterns of variations within each lineage revealed that S. cerevisiae is highly clonal and predominantly reproduces asexually in nature. We identified different selection patterns shaping the coding sequences of natural lineages and found fewer gene family expansion and contractions which contrast with domesticated lineages. This study establishes that S. cerevisiae has rich natural diversity sheltered from human influences, making it a powerful model system in microbial ecology.
Mushroom-forming fungi in the order Agaricales represent an independent origin of bioluminescence in the tree of life; yet the diversity, evolutionary history, and timing of the origin of fungal luciferases remain elusive. We sequenced the genomes and transcriptomes of five bonnet mushroom species (Mycena spp.), a diverse lineage comprising the majority of bioluminescent fungi. Two species with haploid genome assemblies ∼150 Mb are among the largest in Agaricales, and we found that a variety of repeats between Mycena species were differentially mediated by DNA methylation. We show that bioluminescence evolved in the last common ancestor of mycenoid and the marasmioid clade of Agaricales and was maintained through at least 160 million years of evolution. Analyses of synteny across genomes of bioluminescent species resolved how the luciferase cluster was derived by duplication and translocation, frequently rearranged and lost in most Mycena species, but conserved in the Armillaria lineage. Luciferase cluster members were coexpressed across developmental stages, with the highest expression in fruiting body caps and stipes, suggesting fruiting-related adaptive functions. Our results contribute to understanding a de novo origin of bioluminescence and the corresponding gene cluster in a diverse group of enigmatic fungal species.
Japanese encephalitis virus (JEV), a mosquito-borne flavivirus, has five genotypes (I, II, III, IV, and V). JEV genotype I circulates widely in some Asian countries. However, current JEV vaccines based on genotype III strains show low neutralizing capacities against genotype I variants. In addition, JE has no specific treatment, except a few supportive treatments. Compound CW-33, an intermediate synthesized derivative of furoquinolines, was investigated for its antiviral activities against JEV in this study. CW-33 exhibited the less cytotoxicity to Syrian baby hamster kidney (BHK-21) and human medulloblastoma (TE761) cells. CW-33 dose-dependently reduced the cytopathic effect and apoptosis of JEV-infected cells. Supernatant virus yield assay pinpointed CW-33 as having potential anti-JEV activity with IC50 values ranging from 12.7 to 38.5 μM. Time-of-addition assay with CW-33 indicated that simultaneous and post-treatment had no plaque reduction activity, but continuous and simultaneous treatments proved to have highly effective antiviral activity, with IC50 values of 32.7 and 48.5 μM, respectively. CW-33 significantly moderated JEV-triggered Ca2+ overload, which correlated with the recovery of mitochondria membrane potential as well as the activation of Akt/mTOR and Jak/STAT1 signals in treated infected cells. Phosphopeptide profiling by LC-MS/MS revealed that CW-33 upregulated proteins from the enzyme modulator category, such as protein phosphatase inhibitor 2 (I-2), Rho GTPase-activating protein 35, ARF GTPase-activating protein GIT2, and putative 3-phosphoinositide-dependent protein kinase 2. These enzyme modulators identified were associated with the activation of Akt/mTOR and Jak/STAT1 signals. Meanwhile, I-2 treatment substantially inhibited the apoptosis of JEV-infected cells. The results demonstrated that CW-33 exhibited a significant potential in the development of anti-JEV agents.
24Mushroom-forming fungi in the order Agaricales represent an independent origin of 25 bioluminescence in the tree of life, yet the diversity, evolutionary history, and timing of 26 the origin of fungal luciferases remain elusive. We sequenced the genomes and 27transcriptomes of five bonnet mushroom species (Mycena spp.), a diverse lineage 28comprising the majority of bioluminescent fungi. We show that bioluminescence 29 evolved in the common ancestor of Mycena spp. and the marasmioid clade of 30Agaricales and was maintained through at least 160 million years of evolution. We 31revealed Mycena exhibit two-speed genomes and resolve how the luciferase cluster was 32 derived by duplication and translocation, frequently rearranged and lost in most Mycena 33 species, but conserved in the Armillaria lineage. Luciferase cluster members were co-34 expressed across developmental stages, with highest expression in fruiting body caps 35and stipes, suggesting fruiting-related adaptive functions. Our results contribute to 36 understanding a de novo origin of bioluminescence and the corresponding gene cluster 37 in a diverse group of enigmatic fungal species. 38
Over 20,000 clinical MSSA and MRSA isolates were collected to build a machine learning (ML) model to identify MSSA/MRSA and their markers. This model was tested across four external clinical sites to ensure the model’s usability.
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