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249 results for “Fungal pathogens”
Lab disease outcomes data evaluating how antibiotic tolerant vs. non-tolerant cell-free supernatant from Pseudomonas aeruginosa affects the interaction between a fungal pathogen (Batrachochytrium dendrobatidis) and amphibian (Rana sylvaticus), 2022.
Microbes living on hosts and in the environment can play a key role in helping hosts to combat pathogens. However, antibiotic-induced alterations to microbial metabolite production could disrupt this dynamic. Here, we investigated whether antibiotic tolerance influences the anti-pathogenic properties of host-associated (living on the host; biofilms) and environmental (living in the soil of water column; planktonic) microbes in vitro and in vivo. For our model host and pathogen, we used the amphibian (Rana sylvatica)-Batrachochytrium dendrobatidis (Bd) system. For our model host-associated (biofilm) and environmental (planktonic) microbes, we used four strains of Pseudomonas aeruginosa that vary in their tolerance to antibiotics and their biofilm-forming capabilities: Planktonic, non-antibiotic tolerant (ΔsagS/VC); Planktonic, antibiotic tolerant (ΔsagS::sagS_L154A); Biofilm, non-antibiotic tolerant (ΔsagS::sagS_D105A); Biofilm, antibiotic tolerant (ΔsagS::sagS). We collected cell-free supernatants (CFS) from each strain to examine the effects of metabolites. We conducted four experiments. In our pathogen-only exposures to test direct effects of metabolites on Bd, we exposed Bd zoospores to each P. aeruginosa CFS at six concentrations. After 11 days of growth, we measured relative abundance of Bd across each treatment. In our host-only exposures to test effects of metabolites on host disease outcomes, we placed R. sylvatica tadpoles in individual units containing each P. aeruginosa CFS. After 48 hours, water was changed into clean well water (no CFS). Bd zoospores were immediately added to each experimental unit following the water change. After 5 days of Bd exposure, we measured snout-vent length (SVL), mass, developmental stage, and Bd quantification in the mouthparts using qPCR for each tadpole. In our host-pathogen exposures to test interactive effects of metabolites on hosts in the presence of the pathogen, we conducted the same experiment as above. However, ins
Simulated NGS read datasets for prediction of novel fungal pathogens and multiple pathogen classes
<p>This repository contains simulated Illumina read datasets for novel fungal pathogen prediction and real-time detection of multiple pathogen classes. They were used to train the models hosted at <a href="https://zenodo.org/record/5711877">https://zenodo.org/record/5711877</a>.<br> The reads were simulated with Mason (<a href="https://www.seqan.de/apps/mason/">https://www.seqan.de/apps/mason/</a>) from genomes downloaded from NCBI, based on metadata stored in a manually curated database (<a href="https://zenodo.org/record/5846345">https://zenodo.org/record/5846345</a>).</p> <p>We provide the following:</p> <p>1) An rds file describing assignment of fungal species from the database (<a href="https://zenodo.org/record/5846345">https://zenodo.org/record/5846345</a>) to training, validation and test sets (TrainValTest_fungi.rds). A second rds file (TrainValTest_temporal.rds) includes species added within 12 weeks after the original datasets were compiled. Those species were used for a temporal benchmark.</p> <p>2) Fungal validation and test sets. Each contains 1.25 million, 250bp-long reads simulated from non-overlapping sets of human ("pathogenic") or non-human ("nonpathogenic") pathogens. The test set contains paired reads ("_1" and "_2" for the first and second mate). The number of reads per species is proportional to the respective genome length. An additional, temporal test set (*temporal*fasta.gz) includes 15 species added after 12 weeks from the consturction of the original datasets.</p> <p>3) Fungal training sets. They contain 250bp-long reads simulated from species not present in the validation or test sets. There are four variants:<br> 3a) "low-coverage, linear" - 20 million reads, number of reads per species proportional to genome length<br> 3b) "low-coverage, logarithmic" - 20 million reads, number of reads per species proportional to the logarithm of genome length ("log")<br> 3c) "high-coverage, linear" - 240 million reads, number of reads per species proportional to genome length ("24")<br> 3d) "high-coverage, logarithmic" - 240 million reads, number of reads per species proportional to the logarithm of genome length ("24log")</p> <p>4) Training, validation and test sets for the multiclass models. They should be used together with the "pathogenic" read sets hosted at <a href="https://zenodo.org/record/4456857">https://zenodo.org/record/4456857</a>. Here, we share sets for two of the four total classes:<br> 4a) The 'non-pathogen' class is a mixture of "nonpathogenic" biacterial and viral read sets, concatenated and downsampled to the original read number (20M for training, 1.25M for validation and test). The training and validation sets contain mixed-length (25-20bp) simulated subreads (original sets hosted here: <a href="https://zenodo.org/record/4456857">https://zenodo.org/record/4456857</a>). The test set contains 250bp long reads based on the test sets from here: <a href="https://zenodo.org/record/3678563">https://zenodo.org/record/3678563</a> and here: <a href="https://zenodo.org/record/4312525">https://zenodo.org/record/4312525</a>; it was also sorted by species.<br> 4b) Mixed-length versions of the "pathogenic" fungal training and validation sets, prepared by random shortening of the "low-coverage" read sets in the "linear" (_rn_) and "logarithmic" (_rn_*log_) flavours.</p> <p>See also the preprint: <a href="https://www.biorxiv.org/content/10.1101/2021.11.30.470625">https://www.biorxiv.org/content/10.1101/2021.11.30.470625</a></p>
A curated database of fungal pathogens and their host range
<p>This database contains a manually curated set of human, animal and plant pathogens, annotated with their confirmed host range and relevant sources. In addition to that, we include additional sets of plant-associated fungi (which may include non-pathogens), as well as fungi with an automatically assigned, putative human, animal or plant host. The labelled fungal species are linked to their representative GenBank genomes wherever possible. Genomes that were screened, but no label was found, are also included.</p> <p><strong>[Last update on: 11 Dec 2022]</strong><br> [Home page: <a href="https://dacs-hpi.gitlab.io/pathogenic-fungi/">https://dacs-hpi.gitlab.io/pathogenic-fungi/</a>]<br> <br> The database is stored in a flat-file format. All metadata are stored in all_data_[date].csv, and all_data_[date].rds contains the same data in a compressed format that can be easily loaded in R. The database was first compiled on 9 Oct 2021 (v1.0), and then updated on 2 Jan 2022 (v1.1) and 11 Dec 2022 (v1.2).</p> <p>The core database is limited to manually confirmed human, animal and plant pathogens with available genomes as of 9 Oct 2021. Those data are a subset of all_data, and are stored in core_fungal_pathogens.csv and core_fungal_pathogens.rds.</p> <p>The temporal-test subset contains confirmed pathogens with genomes added to GenBank between 9 Oct 2021 and 2 Jan 2022.</p> <p>You may also be interested in trained neural network models predicting pathogenic potentials of novel fungi from DNA sequences (<a href="https://zenodo.org/record/5711877">https://zenodo.org/record/5711877</a>) and simulated Illumina read sets used to train them (<a href="https://zenodo.org/record/5846397">https://zenodo.org/record/5846397</a>).<br> <br> See also the preprint: <a href="https://www.biorxiv.org/content/10.1101/2021.11.30.470625">https://www.biorxiv.org/content/10.1101/2021.11.30.470625</a> and <strong>the paper</strong> presented at ECCB '22 and published in <em>Bioinformatics:</em> <a href="https://doi.org/10.1093/bioinformatics/btac495">https://doi.org/10.1093/bioinformatics/btac495.</a></p>
H4K20me3 is important for Ash1-mediated H3K36me3 and transcriptional silencing in facultative heterochromatin in a fungal pathogen
<p>Normalized ChIP-seq datasets for visualization in IGV. The tracks contain means of pooled replicate datasets.</p> <p>ChIP-seq data were quality-filtered and adapters removed with trimmomatic v.0.39 (Bolger et al., 2014). Mapping was performed with bowtie2 v.2.4.4 (Langmead and Salzberg, 2012), and sorting and indexing with samtools v.1.9 (Li, 2011). Normalized coverage bigwig files and heatmaps were created with deeptools v.3.5.1 (Ramírez et al., 2016). Wiggletools v.1.2 and the UCSC Genome Browser tools were used to calculate means for replicates and converting wig to bigwig files.</p> <p>Reference genome file is modified from Goodwin et al., 2011. Chromosome 18 was removed from the genome as our reference isolate is missing chromosome 18. </p> <p>Gene annotation file was obtained from FungiDB (release 53) and is based on the annotation published by Grandaubert et al., 2015.</p> <p>In this version, we have added new ChIP-seq bw tracks for ∆ash1::ash1-gfp-V5 and ∆kmt5::kmt5 complementation experiments. All tracks coming from this experiment are labeled *_compl_exp_mean.bw.</p> <p>We also added ChIP peak files (peaks called with HOMER: Heinz et al., 2010) for H4K20me3, H3K36me3 and H3K27me3 in WT, ∆kmt5 and ∆ash1, as well as H3K36me3 peak files for Set2- and Ash1-mediated H3K36me3.</p> <p>We have also added bed files (500 bp windows) containing facultative heterochromatin clusters 1 (Zt09_500bp_K27filtered_K36_K20_cluster1.bed) and 2 (Zt09_500bp_K27filtered_K36_K20_cluster2.bed). </p>
Decomposition of Microstegium vimineum litter, plants grew through the Big Oaks National Wildlife Refuge in 2019. Litter used in this experiment naturally senesced in the fall 2019, decomposition data collected through 2020. Plants were infected or not-infected with the foliar fungal pathogen Bipolaris gigantea during the 2019 growing season.
Decomposition of plant litter, facilitated primarily by microbial decomposers, plays a critical role in biogeochemical cycling and ecosystem function. Emerging pathogens have the potential to impact litter decomposition by altering the chemical composition and associated microbial community of host tissue. Here, we compared litter decomposition of the invasive grass Microstegium vimineum collected from sites with Bipolaris leaf spot symptoms and sites with no apparent disease symptoms in a common garden experiment. Our results revealed that leaf tissue from litter from non-infected sites decomposed more rapidly through the spring than litter from infected sites. Differences in fungal composition between infected and non-infected litter at the start of the experiment largely persisted through the summer. Our work demonstrates that pathogen colonization may facilitate the persistence of infected host litter, potentially slowing the return of nutrients to the environmental pool while also promoting the survival and dispersal of primary inoculum the following season.
Emerging fungal pathogen of an invasive grass: Implications for competition with native plant species
This data package includes data and code from an experiment testing the effects of a leaf spot fungal infection and competition from the invasive (to the U.S.) grass Microstegium vimineum on the performance of three native grass species: Dichanthelium clandestinum, Elymus virginicus, and Eragrostis spectabilis. The experiment was performed between June and September of 2019 in a greenhouse on the University of Florida campus in Gainesville, FL, USA. The leaf spot infection is caused by the fungal pathogen Bipolaris gigantea, which has recently emerged on populations of M. vimineum in the U.S. We tested the hypothesis that infection of B. gigantea would both directly and indirectly affect the native grass species by measuring the change in biomass of each species with and without pathogen inoculation (direct effects) and by measuring the effect of pathogen inoculation on M. vimineum competition through changes in native grass biomass across a density gradient of M. vimneum (indirect effects). The code includes statistical analyses and figures. The code was run using R (version 4.0.1).
Population genomics reveals molecular determinants of specialization to tomato in the polyphagous fungal pathogen Botrytis cinerea
<p>Single nucleotide polymorphisms detected in Illumina-sequenced isolates of B. cinerea collected from tomato, grape, hydrangea and bramble in France.</p>
Regional Centromere Configuration in the Fungal Pathogens of Pneumocystis Genus
<p>Supplementary material </p>
Implications of the three-dimensional chromatin organization for genome evolution in a fungal plant pathogen
<p><span>The spatial organization of eukaryotic genomes is linked to their biological functions, although it is not clear how this impacts the overall evolution of a genome. Here, we uncover the three-dimensional (3D) genome organization of the phytopathogen <em>Verticillium dahliae</em>,<em> </em>known to possess distinct genomic regions, designated adaptive genomic regions (AGRs), enriched in transposable elements and genes that mediate host infection. Short-range DNA interactions form clear topologically associating domains (TADs) with gene-rich boundaries that show reduced levels of gene expression and reduced genomic variation. Intriguingly, TADs are less clearly insulated in AGRs than in the core genome. At a global scale, the genome contains bipartite long-range interactions, particularly enriched for AGRs and more generally containing segmental duplications. Notably, the patterns observed for <em>V. dahliae </em>are also present in other <em>Verticillium</em> species. Thus, our analysis links 3D genome organization to evolutionary features conserved throughout the <em>Verticillium</em> genus.</span></p>
Invasibility of a North American soil ecosystem to amphibian-killing fungal pathogens
<p>North American salamanders are threatened by the intercontinental spread of chytridiomycosis, a deadly disease caused by the fungal pathogen <em>Batrachochytrium salamandrivorans</em> (<em>Bsal</em>). To predict the potential dispersal of <em>Bsal</em> spores to salamander habitats, we evaluated the capacity of soil microbial communities to resist invasion. We determined the degree of habitat invasibility using soils from five locations throughout the Great Smoky Mountains National Park, a region with a high abundance of susceptible hosts. Our experimental design consisted of replicate soil microcosms exposed to different propagule pressures of the non-native pathogen, <em>Bsal</em>, and an introduced but endemic pathogen, <em>B. dendrobatidis</em> (<em>Bd</em>). To compare growth and competitive interactions, we used quantitative PCR, live/dead cell viability assays, and 16S rRNA amplicon sequencing. We found that soil microcosms with intact bacterial communities inhibited both <em>Bsal</em> and <em>Bd</em> growth, but inhibitory capacity diminished with increased propagule pressure. <em>Bsal</em> showed greater persistence than <em>Bd</em>. Linear discriminant analysis (LDA) identified the family Burkolderiaceae as increasing in relative abundance with the decline of both pathogens. Although our findings provide evidence of environmental filtering in soils, such barriers weakened in response to pathogen type and propagule pressure, showing that habitats vary their invasibility based on the properties of their local microbial communities.</p>
SBF-SEM datasets related to the manuscript "Trans-cellular tunnels induced by the fungal pathogen Candida albicans facilitate invasion through successive epithelial cells without host damage" by Lachat et al, 2022.
<p>11 serial block face- scanning electron microscopy (SBF-SEM) datasets described in the manuscript "Trans-cellular tunnels induced by the fungal pathogen Candida albicans facilitate invasion through successive epithelial cells without host damage" by Lachat et al, 2022.</p> <p>Resolution: 10 nm x,y, 100 nm Z.</p> <p>Datasets description and quantification can be found in the Supplementary information.</p>
Deciphering the interactions between plant species and their main fungal root pathogens in mixed grassland communities
<p>1. Plant diversity can reduce the risk of plant disease, but positive, and neutral effects have also been reported. These contrasting relationships suggest that plant community composition, rather than diversity per se, affects disease risk. Here, we investigated how diversity and composition of plant communities drive root-associated pathogen accumulation belowground.</p> <p>2. In a temperate grassland biodiversity experiment, containing 16 plant species (forbs and grasses), we determined the abundance of root-associated fungal pathogens in individual plant species growing in monocultures and in 4-species mixtures through Illumina MiSeq amplicon sequencing.</p> <p>3. In the plant monocultures, we identified three major fungal pathogens that differed in host range: <em>Paraphoma chrysanthemicola</em>, associated with roots of forb species of the Asteraceae family, <em>Slopeiomyces cylindrosporus</em>, associated with grass species, and <em>Rhizoctonia solani</em>, associated with multiple forb and grass species. In mixtures, there was no significant reduction in relative abundance of these pathogens in their host species as compared to monocultures. However, in mixtures, there was a significant increase in relative abundance of each pathogen in several non-host and host plant species. Across mixtures, plant community composition affected pathogen relative abundance in individual plant species. This effect was driven by the presence of a particular neighbouring plant species (depending on the pathogen), rather than functional group composition (i.e. grass/forb ratio) or averaged pathogen pressure (based on monocultures) of all neighbours. Specifically, the presence of neighbour host species <em>Achillea millefolium</em> significantly increased <em>P. chrysanthemicola</em>, but decreased <em>R. solani</em> relative abundance in several host and non-host plant species in mixtures.</p> <p>4. Synthesis: Our results indicate that interactions between different plant species – both host and non-hosts – and fungal pathogens underlie effects of plant diversity on root pathogen abundance. Non-host species may act as pathogen reservoirs in diverse plant communities, as they harboured certain pathogens in mixtures, but not in monocultures. Additionally, particular host species can strongly affect pathogen abundance in other (host and non-host) plant species in plant mixtures, suggesting clear effects of species identity in the diversity-disease relationship. Belowground disease risk thus depends on plant community composition rather than diversity per se, via specific interactions between plant species and their root-associated pathogens.</p>
High temperatures reduce growth, infection, and transmission of a naturally occurring fungal plant pathogen
<p>Climate change is rapidly altering the distribution of suitable habitats for many species as well as their pathogenic microbes. For many pathogens, including vector-borne diseases of humans and agricultural pathogens, climate change is expected to increase transmission and lead to pathogen range expansions. However, if pathogens have a lower heat tolerance than their host, increased warming could generate 'thermal refugia' for hosts. Predicting the outcomes of warming on disease transmission requires detailed knowledge of the thermal tolerances of both the host and the pathogen. Such thermal tolerance studies are generally lacking for fungal pathogens of wild plant populations, despite the fact that plants form the base of all terrestrial communities. Here, we quantified three aspects of the thermal tolerance (growth, infection, and propagule production) of the naturally occurring fungal pathogen <em>Microbotryum lychnidis-dioicae</em>, which causes a sterilizing anther-smut disease on the herbaceous plant <em>Silene latifolia</em>. We also quantified two aspects of host thermal tolerance: seedling survival and flowering rate. We found that temperatures >30 degreeC reduced the ability of anther-smut spores to germinate, grow, and conjugate in vitro. In addition, we found that high temperatures (30 degreeC) during, or shortly after the time of inoculation strongly reduced the likelihood of infection in seedlings. Finally, we found that high summer temperatures in the field temporarily cured infected plants, likely reducing transmission. Notably, high temperatures did not reduce survival or flowering of the host plants. Taken together, our results show that the fungus is considerably more sensitive to high temperatures than its host plant. A warming climate could therefore result in reduced disease spread or even local pathogen extirpation, leading to thermal refugia for the host.</p>
Part 1: Dataset and script for a manuscript entitled 'Host-specific subtelomere: structural variation and horizontal transfer in asexual filamentous fungal pathogens'
<p>Datasets, scripts and instructions for reproducing some of the results in the manuscript. The file subtelomere.tar needs to be unpacked on a Linux system. After unpacking it, go to the directory subtelomere, which contains a number of subdirectories. One subdirectory is named data, which contains genome assemblies and is used to hold datasets of short reads; the datasets of short reads in the files Data.One.Focb.tar, Data.One.Focb-2.tar and reads.tar on the four-part depository need to be placed in the subdirectory subtelomere/data/reads/. The other subdirectories under the directory subtelomere contain instructions and scripts for reproducing some of the results in the manuscript. Please see the README and z.cmd files in each subdirectory.</p> <p>The file Data.One.Focb-2.tar contains 22 files of paired-end reads from F. oxysporum f.sp. cubense tropical race 1 isolate N2 (SRA accession: SRR550150, SRR550151), and F. oxysporum f.sp. cubense TR4 isolates Hainan.B2 (SRR550152), My-1 (SRR7226877), La-2 (SRR7226878), Vn-2 (SRR7226879), Leb1.2C (SRR7226880), JV11 (SRR7226881), Phi2.6C (SRR7226882), Pak1.1A (SRR7226883), UK0001 (SRR9733598).</p>
Part 2: Dataset and script for a manuscript entitled 'Host-specific subtelomere: structural variation and horizontal transfer in asexual filamentous fungal pathogens'
<p>Datasets, scripts and instructions for reproducing some of the results in the manuscript. The file subtelomere.tar needs to be unpacked on a Linux system. After unpacking it, go to the directory subtelomere, which contains a number of subdirectories. One subdirectory is named data, which contains genome assemblies and is used to hold datasets of short reads; the datasets of short reads in the files Data.One.Focb.tar, Data.One.Focb-2.tar and reads.tar on the four-part depository need to be placed in the subdirectory subtelomere/data/reads/. The other subdirectories under the directory subtelomere contain instructions and scripts for reproducing some of the results in the manuscript. Please see the README and z.cmd files in each subdirectory.</p> <p>The file Data.One.Focb.tar contains 16 files of paired-end reads from F. oxysporum f.sp. cubense TR4 isolates II-5 (SRA accession: SRR10054446), S1B8 (SRR10054447), JV14 (SRR10054448), FOC.TR4-5 (SRR10054449), FOC.TR4-1 (SRR10054450), Col2 (SRR10103605), Col4 (SRR10125423), Col17 (SRR10747097).</p> <p> </p>
Part 4: Dataset and script for a manuscript entitled 'Host-specific subtelomere: structural variation and horizontal transfer in asexual filamentous fungal pathogen
<p>Datasets, scripts and instructions for reproducing some of the results in the manuscript. The file subtelomere.tar needs to be unpacked on a Linux system. After unpacking it, go to the directory subtelomere, which contains a number of subdirectories. One subdirectory is named data, which contains genome assemblies and is used to hold datasets of short reads; the datasets of short reads in the files Data.One.Focb.tar, Data.One.Focb-2.tar and reads.tar on the four-part depository need to be placed in the subdirectory subtelomere/data/reads/. The other subdirectories under the directory subtelomere contain instructions and scripts for reproducing some of the results in the manuscript. Please see the README and z.cmd files in each subdirectory.</p> <p>The file reads.tar contains 44 files of paired-end reads from <em>F. oxysporum </em>f.sp. <em>lycopersici</em> isolate Fol069 (SRA accession: SRR307106, SRR307107, SRR307113, SRR307115, SRR307123, SRR307257, SRR307266), isolate Fol072 (SRR307122, SRR307092, SRR307091, SRR307090, SRR307086, SRR307281, SRR307250), isolate Fol4287 (SRR7690004, SRR3139043), and F. oxysporum f.sp. radicis-cucumerinum isolate Forc016 (SRR3139027, SRR3139028), isolate Forc024 (SRR3139029, SRR3139030), isolate Forc031 (SRR3139031, SRR3139032).</p>
Single-molecule Fluorescent In Situ Hybridization (smFISH) for RNA detection in the fungal pathogen Candida albicans dataset
<p><strong>This dataset is connected to the protocol article titled:</strong></p> <p>Single-molecule Fluorescent <em>In Situ</em> Hybridization (smFISH) for RNA detection in the fungal pathogen <em>Candida albicans</em></p> <p><strong>Abstract:</strong></p> <p><em>Candida albicans</em> is the most prevalent human fungal pathogen. Its pathogenicity is linked to the ability of <em>C. albicans</em> to reversibly change morphology and to grow as yeast, pseudohyphal or hyphal cells in response to environmental stimuli. Understanding the molecular regulation controlling those morphological switches remains a challenge that, if solved, could help fight <em>C. albicans</em> infections.</p> <p>While numerous studies investigated gene expression changes occurring during <em>C. albicans</em> morphological switches using bulk approaches (e.g., RNA sequencing), here we describe a single-cell and single-molecule RNA imaging and analysis protocol to measure absolute mRNA counts in morphologically intact cells. To detect endogenous mRNAs in single fixed cells, we optimized a single molecule fluorescent <em>in situ</em> hybridization (smFISH) protocol for <em>C. albicans</em>, which allows one to quantify the differential expression of mRNAs in yeast, pseudohyphae or hyphal cells. We quantified the expression of two mRNAs, cell cycle-controlled mRNA (<em>CLB2)</em> and a transcription regulator (<em>EFG1</em>), which show differential expression in the different morphological cell types and in different nutrient conditions. In this protocol we described in detail the major steps of this approach: growth and fixation, hybridization, imaging, cell-segmentation and mRNA spot analysis. Raw data is provided with the protocol to favour reproducibility. This approach could benefit the molecular characterization of <em>C. albicans</em> and other filamentous fungi, pathogenic or non-pathogenic.</p> <p><strong>Data description:</strong></p> <p>This dataset consists of a FISH experiment spanning two different mRNAs, EFG1 and CLB2, and two different nutrient condition, being SPIDER37 and TSB37 in Candida albicans. For culturing, the C. albicans wildtype strain SC5314 was inoculated at 30 degrees overnight (~15 hours) in 10 mL of TSB medium in a 30 degree (celsius) shaking incubator. Next, samples were diluted to a density of 10^5 cells/ mL and inoculated for 6 hours in either 30 mL TSB medium or Spider medium at 37 degrees in falcon tubes on an orbital microplate shaker. Then, samples were fixated by adding PFA to a final concentration of 4% to the medium. For hybridization, both mRNAs were hybridized independently by specific DNA oligo labelled with a Quasar670 dye to enable the visualisation of single mRNA molecules. As both genes are labelled by the same dye, these oligos were not co-applied to the same sample but to independent samples.</p> <p><strong>Microscopy</strong></p> <p>For smFISH imaging we use an Olympus BX-63 epifluorescence microscope equipped with Ultrasonic stage and UPlanApo 100x 1.35NA oil-immersion objective (Olympus). Lumencore SOLA FISH light source, a Hamamatsu ORCA-Fusion sCMOS camera (6.5 µm-pixel size) mounted using U-CMT C-Mount Adapter, and zero-pixel shift filter sets: F36-500 DAPI HC Brightline Bandpass Filter, F36-502 FITC HC BrightLine Filter, F36-542 Cy3 HC BrightLine Filter, and F36-523 Cy5 HC BrightLine Filter. Images are acquired across 61-81 optical sections (depending on the sample thickness) with a z-step size of 0.2 μm. The CellSens software (Olympus) is used for instrument control and image acquisition. For the DAPI channel 10-50 ms of exposure was used. Whilst, for the CY5 channel, used imaging the FISH probes, 750 ms was applied. </p> <p> </p>
Single-molecule Fluorescent In Situ Hybridization (smFISH) for RNA detection in the fungal pathogen Candida albicans small example dataset
<p><strong>This small example dataset is connected to the protocol article titled:</strong></p> <p>Single-molecule Fluorescent <em>In Situ</em> Hybridization (smFISH) for RNA detection in the fungal pathogen <em>Candida albicans</em></p> <p><strong>Abstract:</strong></p> <p><em>Candida albicans</em> is the most prevalent human fungal pathogen. Its pathogenicity is linked to the ability of <em>C. albicans</em> to reversibly change morphology and to grow as yeast, pseudohyphal or hyphal cells in response to environmental stimuli. Understanding the molecular regulation controlling those morphological switches remains a challenge that, if solved, could help fight <em>C. albicans</em> infections.</p> <p>While numerous studies investigated gene expression changes occurring during <em>C. albicans</em> morphological switches using bulk approaches (e.g., RNA sequencing), here we describe a single-cell and single-molecule RNA imaging and analysis protocol to measure absolute mRNA counts in morphologically intact cells. To detect endogenous mRNAs in single fixed cells, we optimized a single molecule fluorescent <em>in situ</em> hybridization (smFISH) protocol for <em>C. albicans</em>, which allows one to quantify the differential expression of mRNAs in yeast, pseudohyphae or hyphal cells. We quantified the expression of two mRNAs, cell cycle-controlled mRNA (<em>CLB2)</em> and a transcription regulator (<em>EFG1</em>), which show differential expression in the different morphological cell types and in different nutrient conditions. In this protocol, we described in detail the major steps of this approach: growth and fixation, hybridization, imaging, cell-segmentation and mRNA spot analysis. Raw data is provided with the protocol to favour reproducibility. This approach could benefit the molecular characterization of <em>C. albicans</em> and other filamentous fungi, pathogenic or non-pathogenic.</p> <p><strong>Data description:</strong></p> <p>This dataset consists of a FISH experiment spanning two different mRNAs, EFG1 and CLB2, and one nutrient condition, SPIDER37, in Candida albicans. For culturing, the C. albicans wildtype strain SC5314 was inoculated at 30 degrees overnight (~15 hours) in 10 mL of TSB medium in a 30 °C shaking incubator. Next, samples were diluted to a density of 10^5 cells/ mL and inoculated for 6 hours in 30 mL Spider medium at 37 °C in falcon tubes on an orbital microplate shaker. Then, samples were fixated by adding PFA to a final concentration of 4% to the medium. For hybridization, both mRNAs were hybridized independently by specific DNA oligo labelled with a Quasar670 dye to enable the visualisation of single mRNA molecules. As both genes are labelled by the same dye, these oligos were not co-applied to the same sample but to independent samples.</p> <p><strong>Microscopy</strong></p> <p>For smFISH imaging we use an Olympus BX-63 epifluorescence microscope equipped with Ultrasonic stage and UPlanApo 100x 1.35NA oil-immersion objective (Olympus). Lumencore SOLA FISH light source, a Hamamatsu ORCA-Fusion sCMOS camera (6.5 µm-pixel size) mounted using U-CMT C-Mount Adapter, and zero-pixel shift filter sets: F36-500 DAPI HC Brightline Bandpass Filter, F36-502 FITC HC BrightLine Filter, F36-542 Cy3 HC BrightLine Filter, and F36-523 Cy5 HC BrightLine Filter. Images are acquired across 61-81 optical sections (depending on the sample thickness) with a z-step size of 0.2 μm. The CellSens software (Olympus) is used for instrument control and image acquisition. For the DAPI channel 10-50 ms of exposure was used. Whilst, for the CY5 channel, used for imaging the FISH probes, 750 ms was applied. </p>
High temperatures reduce growth, infection, and transmission of a naturally occurring fungal plant pathogen
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Indirect pathogen transmission underlies an emerging infectious fungal disease outbreak in a wild reptile population
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.