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137 results for “aspergillus fumigatus”
The pan-genome of Aspergillus fumigatus provides a high-resolution view of its population structure revealing high-levels of lineage-specific diversity driven by recombination
<p><em>Aspergillus fumigatus </em>is a deadly agent of human fungal disease, where virulence heterogeneity is thought to be at least partially structured by genetic variation between strains. While population genomic analyses based on reference genome alignments offer valuable insights into how gene variants are distributed across populations, these approaches fail to capture intraspecific variation in genes absent from the reference genome. Pan-genomic analyses based on <em>de novo</em> assemblies offer a promising alternative to reference-based genomics, with the potential to address the full genetic repertoire of a species. Here, we use a combination of population genomics, phylogenomics, and pan-genomics to assess population structure and recombination frequency, phylogenetically structured gene presence-absence variation, evidence for metabolic specificity, and the distribution of putative antifungal resistance genes in <em>A. fumigatus</em>. We provide evidence for three distinct populations of <em>A. fumigatus</em>, structured by both gene variation (SNPs and indels) and distinct gene presence-absence variation with unique suites of accessory genes present exclusively in each clade. Accessory genes displayed functional enrichment for nitrogen and carbohydrate metabolism, hinting that populations may be stratified by environmental niche specialization. Similarly, the distribution of antifungal resistance genes and resistance alleles were often structured by phylogeny. Despite low levels of outcrossing, <em>A. fumigatus</em> demonstrated a large pan-genome including many genes unrepresented in the Af293 reference genome. These results highlight the inadequacy of relying on a single-reference based approach for evaluating intraspecific variation, and the power of combined genomic approaches to elucidate population structure, genetic diversity, and the putative ecological drivers of clinically relevant fungi.</p> <p>Accompanying manuscript is available as preprint at <a href="https://dx.doi.org/10.1101/2021.12.12.472145">https://dx.doi.org/10.1101/2021.12.12.472145</a> </p> <p>Lotus A. Lofgren, Brandon S. Ross, Robert A. Cramer, Jason E. Stajich. Combined Pan-, Population-, and Phylo-Genomic Analysis of <em>Aspergillus fumigatus</em> Reveals Population Structure and Lineage-Specific Diversity bioRxiv 2021.12.12.472145; doi: https://doi.org/10.1101/2021.12.12.472145</p>
Azole resistance mechanisms and population structure of Aspergillus fumigatus on retail plant products
<p><em>Aspergillus fumigatus </em>is a ubiquitous saprotroph and human-pathogenic fungus that is life-threatening to the immunocompromised. Triazole-resistant <em>A. fumigatus</em><em> </em>was found in patients without prior treatment with azoles, leading researchers to conclude that resistance had developed in agricultural environments where azoles are used against plant pathogens. Previous studies have documented azole-resistant <em>A. fumigatus </em>across agricultural environments, but few have looked at retail plant products. Our objectives were to determine if azole-resistant <em>A. fumigatus </em>is prevalent<em> </em>in retail plant products produced in the United States (U.S.), as well as to identify the resistance mechanism(s) and population genetic structure of these isolates. Five hundred twenty-five isolates were collected from retail plant products and screened for azole resistance. Twenty-four isolates collected from compost, soil, flower bulbs, and raw peanuts were pan-azole resistant. Resistant isolates had the TR<sub>34</sub>/L98H, TR<sub>46</sub>/Y121F/T289A, G448S, and H147Y <em>cyp51A </em>alleles, all known to underly pan-azole resistance, as well as WT alleles, suggesting that non-cyp51A-mechanisms contribute to pan-azole resistance in some isolates. Minimum spanning networks showed two lineages containing isolates with TR alleles or the F46Y/M172V/E427K allele, and discriminant analysis of principle components (DAPC) identified three primary clusters. This is consistent with previous studies detecting three clades of <em>A. fumigatus</em> and identifying pan-azole-resistant isolates with TR alleles in a single clade. We found pan-azole resistance in U.S. retail plant products, particularly compost and flower bulbs, which indicates the risk of exposure to these products for susceptible populations and that highly resistant isolates are likely distributed worldwide on these products.</p>
Data and code AEM article: Catching some air: A method to spatially quantify aerial triazole resistance in Aspergillus fumigatus
<h2>Name</h2> <p>Catching_some_air</p> <h2><a href="#description"></a>Description</h2> <p>This script project was written to visualise and analyse the data used in the manuscript: Catching some air: A method to spatially quantify aerial triazole resistance in <em>Aspergillus fumigatus</em>.</p> <p>In the R script we load and clean the data from the international air sampling pilot, analyse it, generate figures of the sampled regions, the CFU totals and resistance fractions. The genotyping and phenotyping data of isolated resistant strains.</p> <p>The following files are required to run this R script:</p> <ul> <li>RF_air_IP_cleaned.csv This fine contains total and resistance counts as well as metadata on samples from international air sampling pilot and includes the following variables:</li> </ul> <p>Sample ID: an arbitrary number given to the packages prior to them being handed out</p> <p> </p> <p>Country: Country in which sample was taken</p> <p>Region: Circular area with a 50 km radius within which the samples were clustered for analysis</p> <p>City/Town: City/Town in which the sample was taken</p> <p>Start date: date on which the trap was deployed and the stickers exposed to the air</p> <p>End date: date on which the trap was taken down and the stickers were re-covered and no longer exposed to the air</p> <p>Total.ITR: A. fumigatus CFU count in the permissive layer of the itraconazole-treated plate</p> <p>Res.ITR: CFU count of colonies that had breached the surface of the itraconazole-treated layer after incubation and were visually (with the unaided eye) sporulating.</p> <p>RF.ITR: The itraconazole (~4 mg/L) resistance fraction = Res.ITR/Total.ITR</p> <p>Total.VOR: A. fumigatus CFU count in the permissive layer of the voriconazole-treated plate</p> <p>Res.VOR: CFU count of colonies that had breached the surface of the voriconazole-treated layer after incubation and were visually (with the unaided eye) sporulating.</p> <p>RF.VOR: The voriconazole (~2 mg/L) resistance fraction = Res.VOR/Total.VOR</p> <p>Total control: CFU count on the untreated growth control plate</p> <p>Date.Batch: The date on which proccessing of the sample was started. To be more specific, the date at which Flamingo medium was poured over the seals of the sample and incubation was started.</p> <p>Note: note on the sample based on either information given the participant or observations in the lab.</p> <p>Exclude: Binary to quickly filter out samples that were considered unsuitable for further analysis either because low or high CFU counts. See manuscript for rationale.</p> <p>Lat: Latitude at the centre of the sampled region, does not relate to sample-specific location.</p> <p>Long: Longitude at the centre of the sampled region, does not relate to sample specific location.</p> <ul> <li>Weather_data_IP_study_nov_dec_jan22_23.csv : contains raw weather data of the sampled regions during the sampling interval of the pilot downloaded from: <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels-monthly-means?tab=overview" target="_blank" rel="nofollow noreferrer noopener">https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels-monthly-means?tab=overview</a> (see link for full description of the data and the units). Contains the following variables:</li> </ul> <p>Region: Circular area with a 50 km radius within which the samples were clustered for analysis</p> <p>Wind Nov : 10 m Wind speed (m/S) for the month november 2022 This parameter is the horizontal speed of the wind, or movement of air, at a height of ten metres above the surface of the Earth.</p> <p>Wind Dec : 10 m Wind speed (m/S) for the month december 2022 This parameter is the horizontal speed of the wind, or movement of air, at a height of ten metres above the surface of the Earth.</p> <p>Wind Jan : 10 m Wind speed (m/S) for the month januari 2023 This parameter is the horizontal speed of the wind, or movement of air, at a height of ten metres above the surface of the Earth.</p> <p>UV Nov: UV radiation at the surface (J/m^2) for the month november 2022. This parameter is the amount of ultraviolet (UV) radiation reaching the surface. It is the amount of radiation passing through a horizontal plane.</p> <p>UV Dec: UV radiation at the surface (J/m^2) for the month december 2022. This parameter is the amount of ultraviolet (UV) radiation reaching the surface. It is the amount of radiation passing through a horizontal plane.</p> <p>UV Jan: UV radiation at the surface (J/m^2) for the month januari 2023. This parameter is the amount of ultraviolet (UV) radiation reaching the surface. It is the amount of radiation passing through a horizontal plane.</p> <p>Temp Nov: Temperature (K) for the month november 2022. This parameter is the temperature of air at 2m above the surface of land, sea or inland waters. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions.</p> <p>Temp Dec: Temperature (K) for the month december 2022. This parameter is the temperature of air at 2m above the surface of land, sea or inland waters. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions.</p> <p>Temp Jan: Temperature (K) for the month januari 2023. This parameter is the temperature of air at 2m above the surface of land, sea or inland waters. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions.</p> <p>Precipitation Nov: Total precipitation (m) for the month november 2022. This parameter is the accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation.</p> <p>Precipitation Dec: Total precipitation (m) for the month december 2022. This parameter is the accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation.</p> <p>Precipitation Jan: Total precipitation (m) for the month januari 2023. This parameter is the accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation.</p> <p>lat_rep: Latitude at the centre of the sampled region, does not relate to sample specific location.</p> <p>lon_rep: Longitude at the centre of the sampled region, does not relate to sample specific location.</p> <ul> <li>Genotyping_IP_cleaned.csv : contains the TR-type genotypes of the isolated resistant strains Contains the following variable:</li> </ul> <p>Order: Ordering variable included in the file to readily be able to order the isolates by the order in which they were isolated. Contains the following variables:</p> <p>Strain: Strain code with "I" for strains isolated from itraconazole and V for strains isolated from voriconazole followed by a number indicating the order in which they were isolated from the air sample plate.</p> <p>Air sample: The plate/air sample from which the isolate originates</p> <p>Triazole: The triazole treatment the resistant strain grew on can be ITRA (itraconazole) or VORI (voriconazole)</p> <p>Country: Country in which sample was taken</p> <p>Region: Circular area with a 50 km radius within which the samples were clustered for analysis</p> <h2><a href="#project-status"></a>Project status</h2> <p>The manuscript has been published in AEM under the DOI: https://doi.org/10.1128/aem.00271-24</p>
Adaptative Survival of Aspergillus fumigatus to Echinocandins Arises from Cell Wall Remodeling Beyond β-1,3-glucan Synthesis Inhibition
<p>Unprocessed Solid-state NMR and Molecular Dynamics data sets for the manuscript titled "Adaptative Survival of Aspergillus fumigatus to Echinocandins Arises from Cell Wall Remodeling Beyond β-1,3-glucan Synthesis Inhibition"</p>
Treatment of Aspergillus Fumigatus (a Fungal Infection) in Patients With Cystic Fibrosis
ClinicalTrials.gov study NCT00528190. IPD Sharing: NO. Countries: 1. Publications: 1.
Azole resistance mechanisms and population structure of Aspergillus fumigatus on retail plant products
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Data from: Asexual sporulation facilitates adaptation: the emergence of azole resistance in Aspergillus fumigatus
Understanding the occurrence and spread of azole resistance in Aspergillus fumigatus is crucial for public health. It has been hypothesized that asexual sporulation, which is abundant in nature, is essential for phenotypic expression of azole-resistance mutations in A. fumigatus facilitating subsequent spread through natural selection. Furthermore, the disease aspergilloma is associated with asexual sporulation within the lungs of patients and the emergence of azole resistance. This study assessed the evolutionary advantage of asexual sporulation by growing the fungus under pressure of one of five different azole fungicides over seven weeks and by comparing the rate of adaptation between scenarios of culturing with and without asexual sporulation. Results unequivocally show that asexual sporulation facilitates adaptation. This can be explained by the combination of more effective selection because of the transition from a multicellular to a unicellular stage, and by increased mutation supply due to the production of spores, which involves numerous mitotic divisions. Insights from this study are essential to unravel the resistance mechanisms of sporulating pathogens to chemical compounds and disease agents in general, and for designing strategies that prevent or overcome the emerging threat of azole resistance in particular.
Data from: Evidence for structure and variable recombination rates among Dutch populations of the opportunistic human pathogen Aspergillus fumigatus
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Data from: Asexual sporulation facilitates adaptation: the emergence of azole resistance in Aspergillus fumigatus
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Data from: Evolution of cross-resistance to medical triazoles in Aspergillus fumigatus through selection pressure of environmental fungicides
Resistance to medical triazoles in Aspergillus fumigatus is an emerging problem for patients at risk of aspergillus diseases. There are currently two presumed routes for medical triazole-resistance selection: (i) through selection pressure of medical triazoles when treating patients and (ii) through selection pressure from non-medical sterol-biosynthesis-inhibiting (SI) triazole fungicides which are used in the environment. Previous studies have suggested that SI fungicides can induce cross-resistance to medical triazoles. Therefore, to assess the potential of selection of resistance to medical triazoles in the environment, we assessed cross-resistance to three medical triazoles in lineages of A. fumigatus from previous work where we applied an experimental evolution approach with one of five different SI fungicides to select for resistance. In our evolved lines we found widespread cross-resistance indicating that resistance to medical triazoles rapidly arises through selection pressure of SI fungicides. All evolved lineages showed similar evolutionary dynamics to SI fungicides and medical triazoles, which suggests that the mutations inducing resistance to both SI fungicides and medical triazoles are likely to be the same. Whole-genome sequencing revealed that a variety of mutations were putatively involved in the resistance mechanism, some of which are in known target genes.
Data from: Relevance of heterokaryosis for adaptation and azole-resistance development in Aspergillus fumigatus
Aspergillus fumigatus causes a range of diseases in humans, some of which are characterized by fungal persistence. A. fumigatus, being a generalist saprotroph, may initially establish lung colonisation due to its physiological versatility and subsequently adapt through genetic changes to the human lung environment and antifungal treatments. Human lung-adapted genotypes can arise by spontaneous mutation and/or recombination and subsequent selection of the fittest genotypes. Sexual and asexual spores are considered crucial contributors to the genetic diversity and adaptive potential of aspergilli by recombination and mutation supply respectively. However, in certain Aspergillus diseases, such as cystic fibrosis and chronic pulmonary aspergillosis, A. fumigatus may not sporulate but persist as a network of fungal mycelium. During azole therapy, such mycelia may develop patient-acquired resistance and become heterokaryotic by mutations in one of the nuclei. We investigated the relevance of heterokaryosis for azole-resistance development in A. fumigatus. We found evidence for heterokaryosis of A. fumigatus in patients with chronic Aspergillus diseases. Mycelium from patient-tissue biopsies segregated different homokaryons, from which heterokaryons could be reconstructed. Whereas all variant homokaryons recovered from the same patient were capable of forming a heterokaryon, those from different patients were heterokaryon-incompatible. We furthermore compared heterokaryons and heterozygous diploids constructed from environmental isolates with different levels of azole resistance. When exposed to azole, the heterokaryons revealed remarkable shifts in their nuclear ratio, and the resistance level of heterokaryons exceeded that of the corresponding heterozygous diploids.
Data from: Relevance of heterokaryosis for adaptation and azole-resistance development in Aspergillus fumigatus
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Data from: Evolution of cross-resistance to medical triazoles in Aspergillus fumigatus through selection pressure of environmental fungicides
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Gene expression in Aspergillus fumigatus at different developmental stages
GEO Series GSE75412. Aspergillus fumigatus. 15 samples. Type: Expression profiling by array.
RNA-seq analysis of alleles of the atrR transcription factor-encoding gene in Aspergillus fumigatus
GEO Series GSE123445. Aspergillus fumigatus Af293. 8 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic analysis of interactions between Aspergillus fumigatus conidiospores and human bronchial epithelial cells
GEO Series GSE16637. Aspergillus fumigatus; Homo sapiens. 20 samples. Type: Expression profiling by array.
Small RNA profiles of three different mycovirus-infected Aspergillus fumigatus isolates, created using Illumina high definition adapters
GEO Series GSE61680. Aspergillus fumigatus. 3 samples. Type: Non-coding RNA profiling by high throughput sequencing.
AtrR is an essential determinant of azole resistance in Aspergillus fumigatus
GEO Series GSE123446. Aspergillus fumigatus Af293. 14 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Quantification of Bir1-dependent differential gene expression in swollen Aspergillus fumigatus conidia
GEO Series GSE233942. Aspergillus fumigatus. 12 samples. Type: Expression profiling by high throughput sequencing.
The Negative Cofactor 2 complex is a master regulator of drug resistance in Aspergillus fumigatus [RNA-seq]
GEO Series GSE133464. Aspergillus fumigatus. 18 samples. Type: Expression profiling by high throughput sequencing.
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