Genomic epidemiology links azole-resistant Aspergillus fumigatus hospital bioaerosols to chronic respiratory aspergillosis

Genomic epidemiology links azole-resistant Aspergillus fumigatus hospital bioaerosols to chronic respiratory aspergillosis | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Genomic epidemiology links azole-resistant Aspergillus fumigatus hospital bioaerosols to chronic respiratory aspergillosis Amélie P Brackin , Rodrigo Leitao , Johanna Rhodes , Zain Chaudhry , David Connell , Samuel Hemmings , Jennifer M G Shelton , View ORCID Profile Matthew C Fisher , Darius Armstrong-James , Anand Shah doi: https://doi.org/10.1101/2025.07.04.25330042 Amélie P Brackin 1 Imperial Fungal Science Network, Department of Infectious Disease, Imperial College London UK 2 Royal Brompton and Harefield Hospitals, Guy’s and St. Thomas’ NHS Foundation Trust , London UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Rodrigo Leitao 1 Imperial Fungal Science Network, Department of Infectious Disease, Imperial College London UK 3 MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Johanna Rhodes 4 School of Biosciences, University of Birmingham , Birmingham UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zain Chaudhry 3 MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London , UK 6 Research Department of Infection, Division of Infection and Immunity, University College London , London, UK 7 Parasites and Microbes Programme, Wellcome Sanger Institute, Hinxton, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site David Connell 5 NHS Tayside, Dundee , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Samuel Hemmings 3 MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jennifer M G Shelton 3 MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Matthew C Fisher 1 Imperial Fungal Science Network, Department of Infectious Disease, Imperial College London UK 3 MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London , UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Matthew C Fisher Darius Armstrong-James 1 Imperial Fungal Science Network, Department of Infectious Disease, Imperial College London UK 2 Royal Brompton and Harefield Hospitals, Guy’s and St. Thomas’ NHS Foundation Trust , London UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anand Shah 1 Imperial Fungal Science Network, Department of Infectious Disease, Imperial College London UK 2 Royal Brompton and Harefield Hospitals, Guy’s and St. Thomas’ NHS Foundation Trust , London UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: s.anand{at}imperial.ac.uk Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Drug-resistant infections caused by spores of the mould Aspergillus fumigatus pose a major challenge in managing chronic respiratory disease. Evidence shows that a substantial burden of aspergillosis is caused by strains that have evolved resistance to azole antifungal chemicals in the environment, however the contribution of local exposures to the colonisation of patients remains unclear. To investigate routes of acquisition, we whole-genome sequenced A. fumigatus isolates from individuals with chronic pulmonary fungal disease ( n =182, 15 individuals), their homes ( n =101, 10 homes), and hospital environments ( n =102). These data were then integrated with retrospective sequence datasets enabling phylogenetic resolution across 912 genomes of UK A. fumigatus . We found high genetic diversity in clinical isolates, frequent mixed colonisation, and azole resistance in ∼25% of infections, particularly in those patients with cystic fibrosis (CF) and chronic pulmonary aspergillosis (CPA). The TR 34 /L98H cyp51A resistance allele, a well characterised marker of environmental adaptation to azole agricultural fungicides, was present in 25% of clinical azole-resistant strains. While azole-resistant A. fumigatus was detected in 6/10 homes, phylogenomic analysis revealed no clear genetic link between the home environment and clinical fungal lung isolates. A. fumigatus was prevalent in hospital environments, with azole-resistant isolates comprising 4.5% ( n =9/202) of air and 3.4% ( n =6/178) of soil isolates, predominantly harbouring the TR 34 /L98H allele. In contrast to homes, phylogenomic and pairwise SNP analysis revealed numerous clinical isolates with >97% genetic identity when compared to those isolated from the hospital environment and randomly chosen pairs of UK isolates. These findings indicate widespread exposure and potential nosocomial acquisition of drug-resistant genotypes of A. fumigatus , supporting the need for targeted environmental surveillance and mitigation of exposures in healthcare settings. Introduction On October 25th, 2022, the World Health Organization (WHO) released its inaugural fungal priority pathogens list, calling for advanced diagnostics, robust surveillance, and accelerated antifungal development to address the escalating threat of drug resistance 1 . Aspergillus fumigatus , designated as one of four critical fungal pathogens of clinical priority, constitutes around 50% of the worldwide fungal disease burden, with high mortality rates and escalating drug resistance that disproportionately affects individuals with chronic respiratory diseases and viral pneumonias 2 . Triazole antifungal drugs are considered first-line therapy for aspergillosis, valued for their broad-spectrum antifungal activity, low toxicity, and oral availability, which has led to widespread clinical use 3 – 6 . However, the emergence of azole-resistant A. fumigatus (AR Af ), characterised by polymorphisms in the cyp51A drug target, has significantly compromised treatment efficacy and worsened clinical outcomes. The widespread application of azoles in agriculture, horticulture, and various industrial biocides, including paints, coatings, wallpaper adhesives, textiles, and wood preservatives, has widely contaminated natural reservoirs 7 , accelerating the dissemination of resistance traits and further complicating patient management. Chronic respiratory diseases complicated by fungal infection carry a heightened risk of AR Af acquisition as host defences often fail to fully eradicate the pathogen, frequently necessitating prolonged azole therapy. The resulting selective pressures, within a complex mosaic of physiological microenvironments shaped by spatial heterogeneity in immune responses, pharmacokinetics, and pharmacodynamics 8 – 10 , contribute to genetic diversity within the lung by driving evolution and persistence of azole-resistant populations 11 . In London respiratory disease cohorts, AR Af has been detected in approximately 13% of individuals with aspergillosis, with over 40% of cystic fibrosis (CF) resistant cases attributed to the environmentally derived TR 34 /L98H genotype 12 , reflecting the substantial influence of environmental transmission on resistance patterns 13 – 15 . Genomic evidence of shared clonal backgrounds between clinical and environmental AR Af isolates 16 , 17 implicates environmental transmission as a key pathway for resistance acquisition. UK-wide surveillance identified AR Af in ∼4% of air and ∼14% of soil samples, with minimal genomic differentiation between environmental and clinical strains, suggesting that over 40% of human AR Af infections may originate from environmental sources 18 . However, specific reservoirs and routes of acquisition remain incompletely defined, requiring further study to better understand the drivers of AR Af acquisition. The TR 34 /L98H polymorphism has been detected in indoor environments, including soil and air from homes 19 , 20 and healthcare settings 21 – 23 positioning these spaces as significant sources of human exposure to AR Af . Multiple factors likely influence the introduction and persistence of AR Af indoors, such as building characteristics, occupant behaviours, air conditioning systems and outdoor spore infiltration 24 , 25 . Residual azoles present in commonly consumed foods, including teas, spices, and fruits 26 – 28 may carry AR Af spores into indoor spaces, while damp, water-damaged areas create niches for fungal proliferation on substrates like wallpaper and paint, often treated with azole-based biocides 29 . Routine domestic activities, such as vacuuming, dusting, and potting plants, further disperse spores, exacerbating exposure to A. fumigatus within indoor environments 30 , 31 . Environmental persistence may be exacerbated by host-derived transmission, where resistant inocula are released into the surroundings through coughing or exhalation 32 . Although in-host adaptation by A. fumigatus often results in traits such as reduced sporulation and slower growth 33 , 34 which can impact fitness outside the host, compensatory mutations can mitigate these effects. Such mechanisms may sustain a cycle of azole resistance transmission and acquisition in high-exposure settings, creating distinct reservoirs of AR Af . These pathways are comparable to those observed in multidrug-resistant respiratory bacterial pathogens such as Pseudomonas aeruginosa and Staphylococcus aureus , which are known to contaminate healthcare environments via aerosolisation and contact 35 – 37 . Currently, mycological surveillance in healthcare settings is limited by the high costs of implementation, the absence of standardised sampling protocols, and an emphasis on monitoring high-risk patient groups and a focus on specific, largely bacterial, pathogens 38 , 39 . Routine screening is typically restricted to environments such as intensive care units, haemato-oncology, and burns wards, with fungal surveillance often limited to outbreak investigations or targeted research studies. This narrow approach may fail to detect clinically relevant fungal exposures among non-target patient populations, including those with chronic respiratory diseases, where risk of acquisition remains substantial. In order to better understand acquisition of drug-resistant aspergillosis, we conducted a two-year ‘real-time’ epidemiological surveillance of A. fumigatus exposures by measuring the prevalence and type of azole resistance in individuals with chronic respiratory diseases and their close environments. High-resolution whole-genome sequencing (WGS) was conducted on clinical isolates from participants and combined with environmental WGS data from their homes and the hospital they attended to investigate possible ‘hot-spots’ of resistance in high-exposure settings. Comparator isolates from a UK-wide clinical and environmental A. fumigatus dataset of 616 genomes were included to contextualise phylogenomic diversity. This genomics-based approach enabled differentiation between clinical and environmental isolates with very high power, providing nuanced insights to inform targeted interventions for enhanced public health control measures. Results Clinical sample collection and characterisation of AR Af Between September 2020 and April 2022, 296 remote (home) sputum sampling kits were distributed monthly to 55 individuals with chronic respiratory fungal disease attending a UK specialist tertiary respiratory centre for molecular epidemiology surveillance ( Figure 1a ). The cohort included individuals with cystic fibrosis (CF) ( n = 9, 16.4%), chronic pulmonary aspergillosis (CPA) ( n = 21, 38.2%), allergic bronchopulmonary aspergillosis (ABPA) ( n = 23, 41.8%), A. fumigatus colonisation ( n = 1, 1.8%), and chronic obstructive pulmonary disease (COPD) ( n = 1, 1.8%) (Supplementary Table 1). Of the 296 kits distributed, 235 sputum samples were returned (achieving a 79% response rate), with A. fumigatus cultured from 27 participants (49%). Susceptibility testing of 321 A. fumigatus isolates against itraconazole (4 mg/L), voriconazole (2 mg/L), and posaconazole (0.5 mg/L) identified AR Af in 14 participants, corresponding to an overall prevalence of 25.5% (14/55) in the study cohort ( Figure 1b ). AR Af prevalence was highest in the 40–59 age group; CPA participants had the highest resistance rate (42.9%), followed by CF (33.3%) and ABPA (4.3%). Multivariate logistic regression (Supplementary Figure 1) confirmed CPA and CF as strong independent predictors of resistance. Download figure Open in new tab Figure 1. Prospective surveillance of azole resistance in individuals with chronic respiratory diseases. (a) Schematic representation of the study design and experimental framework. Workflow included sample kit preparation and delivery, sputum sample processing and fungal culture, drug susceptibility testing and DNA extraction for WGS analysis. See methods section for detailed information. (b) Prevalence of azole resistance among participants in the respiratory disease cohort who had at least one azole-resistant isolate recovered from longitudinal samples. Resistance prevalence is further categorised by gender, age, and clinical diagnosis. (c) Distribution of cyp51a polymorphisms detected during prospective surveillance. (d) Phylogenetic tree illustrating the evolutionary relationships of clinical A. fumigatus isolates. Coloured circles on the branches represent the Case ID for prospective study participants. To strengthen phylogenetic analysis, genome sequences were integrated into an existing WGS data repository, which included 118 clinical genomes (white circles) from individuals with chronic respiratory diseases attending the same hospital. A subset of 182 clinical isolates from 15 individuals, each with at least two sequential isolates sampled 1–8 months apart, underwent WGS (Supplementary Table 2). Sixteen distinct cyp51A genotypes were identified, indicating within-cohort genetic diversity ( Figure 1c ). Five individuals (Cases 34, 39, 41, 42, 43) harboured isolates distributed across multiple phylogenetic clusters, consistent with intrahost genetic diversity ( Figure 1d ). In contrast, 10 individuals harboured sequential isolates that clustered phylogenetically, suggesting possible strain stability and persistence. The TR 120 polymorphism, recently reported in Dutch isolates 40 , was identified in a UK CF patient, marking its first documented case in the UK. These isolates, collected over 11 months, exhibited distinct SNP profiles and resistance phenotypes yet clustered phylogenetically. Inclusion of retrospective genomes identified a TR 120 /M172/F46Y isolate from Case 30, collected in 2016, clustering with both prospective TR 120 /M172/F46Y isolates and TR 120 isolates with or without additional polymorphisms, indicating long-term persistence and micro-evolution of the variant. Similarly, a retrospective TR 34 /L98H isolate from Case 31 clustered with prospective azole-resistant isolates, indicating likely intra-host persistence. Case 31 also harboured a phylogenetically distinct TR 34 variant without L98H, highlighting the coexistence of multiple genetically distinct strains within the host. Among the 15 individuals, the TR 34 /L98H genotype was identified in 26.6% ( n = 4) of cases, with all isolates resistant to at least one clinically-used azole. An isolate carrying a TR 46 /Y121F/T289A genotype isolate was recovered from Case 32, marking the first report of this genotype in London cohorts. Home environmental surveillance and characterisation of AR Af To understand whether home environments were important in AR Af acquisition, targeted home environmental surveillance was performed in specific participants isolating AR Af and non-AR Af clinical A. fumigatus isolates to enable genome sequencing for molecular epidemiology. A schematic of the experimental workflow is shown in Figure 2a . A. fumigatus bioburden varied across homes ( Figure 2b ), with no significant association between environmental and sputum CFU counts (Spearman’s ρ = 0.267, p = 0.455). Of 438 A. fumigatus isolates, AR Af was detected in 6 of 10 homes, representing 3.9% (17/438) overall: 2.7% (12/438) in soil, 0.7% (3/438) in air, and 0.5% (2/438) in dust. WGS of 101 isolates, selected to represent both wildtype and azole-resistant A. fumigatus in the home environment, revealed eight cyp51A genotypes (Supplementary Table 3). Multivariate Discriminant Analysis of Principal Components (DAPC) was performed to evaluate household-specific adaptation or transmission, but no clustering was observed ( Figure 2c ). Phylogenetic analysis (median bootstrap support 98%) showed that home isolates were distributed across multiple branches, consistent with extensive genetic diversity and a cosmopolitan population structure. Inclusion of participants’ clinical isolates in the phylogenetic analysis revealed no close genetic relationships between clinical and home-derived isolates ( Figure 2d ). Download figure Open in new tab Figure 2. Environmental surveillance of azole resistance in study participants homes. (a) Schematic representation of the study design and experimental framework. Workflow included sample kit preparation and delivery, environmental sample processing and fungal culture, drug susceptibility testing and DNA extraction for WGS analysis. See methods section for detailed information. (b) Average CFU counts across participating home environments. (c) DAPC based on SNP variants from of A. fumigatus isolates collected from air, soil and dust of participant homes. Coloured points represent the homes of each Case ID. The Af293 refence genomes ( n =10) are shown as purple points. The inset shows the cumulative variance explained by the principal component axes, indicating the proportion of total variance captured by the analysis. (d) Phylogenetic tree showing evolutionary relationships between A. fumigatus isolates from participant homes and corresponding clinical samples. Coloured circles on the branches represent the source of the isolate (Case ID). The inner circle indicates the source, either clinical or home environment. The outer rings indicate susceptibility profiles for tebuconazole (green) and the clinical azoles (blue), with darker colours representing resistance. Hospital environment surveillance and characterisation of AR Af We subsequently performed environmental surveillance across multiple sites at a London hospital attended by study participants ( Figure 3 ) in order to analyse azole-resistance incidence within healthcare settings and their potential importance in the acquisition of AR Af . A schematic of the experimental workflow is shown in Figure 4a . A. fumigatus bioburden varied across sites ( Figure 4b ), with the highest airborne concentrations observed in a reception area (median 6 CFUs/m³), followed by basement areas, staff offices (both with median 3 CFUs/m³), and outpatient departments (median 2.5 CFUs/m³). Indoor flower beds had a higher proportion of A. fumigatus positive samples, with those in the reception area showing the highest concentration (median 3.5 CFUs/g; range 0–75 CFUs/g). Tebuconazole-resistance was analysed using the TebuCheck protocol to screen for AR Af 41 with detection in 4.5% ( n =9/202) of air isolates and 3.4% ( n =6/178) of soil isolates. All clinical azole-resistant isolates also exhibited cross-resistance to tebuconazole (6 mg/L). Resistant isolates were spatiotemporally distributed, predominantly in the hospital basement, outpatient department and reception area. Download figure Open in new tab Figure 3. Hospital sampling locations. Soil and air samples were collected from multiple locations within the hospital to assess the presence and distribution of A. fumigatus . Soil samples were collected from indoor and outdoor potted plants and garden spaces, including patient waiting areas (a-c), a reception area (d) and outdoor courtyards (e-f). Air samples were also collected from locations with potential air quality issues, including areas with signs of dampness or old air conditioning units: ceiling with water damage (g) and a window-mounted old air conditioning unit (h). External control located at the back of the hospital in a staff car park (i). Download figure Open in new tab Figure 4. Environmental surveillance of azole resistance in a central London Hospital. (a) Schematic overview of the study design and experimental workflow, including environmental sampling, fungal culture, drug susceptibility testing, and DNA extraction for whole-genome sequencing. Full methodological details are provided in the Methods section. (b) Spatial distribution of A. fumigatus in hospital air and soil samples. Left: percentage of culture-positive air samples collected from two hospital sites, the Victorian-era Site A (red) and the modern Site B (blue), with an external control site (beige). Colony forming units (CFUs/m³) in air samples from the same locations, shown as box plots indicating the median, interquartile range, and outliers. Right: percentage of culture-positive soil samples collected from internal (orange) and external (green) flower beds, with a private London park included as an external control (beige). Colony-forming units (CFUs/g) for soil samples are shown as box plots. (c) Phylogenetic tree showing evolutionary relationships among hospital environment A. fumigatus isolates. Cyp51A alleles are marked by grey points (tandem repeats) and blue points (amino acid substitutions). (d) Discriminant analysis of principal components (DAPC) plot showing genetic clustering of hospital environmental isolates, study participant isolates and UK-wide environmental and clinical isolates. (e) Counts of pairwise comparisons with >97% genomic similarity, including their source. WGS of a representative set of 102 hospital-derived environmental isolates was performed to investigate the genetic background of AR Af and to identify potential nosocomial acquisition. Genotypes and their resistance profiles are shown in Supplementary Table 4. Pairwise SNP analysis among hospital environmental isolates showed an average divergence of 47,971 SNPs, which is similar to that found more widely in the UK (average divergence 48,838 SNPs). Ten isolate pairs met the genetic similarity threshold (97% of maximum observed diversity). Four pairs originated from the same sample, likely due to replication during culture, while the remaining six pairs were recovered from different locations or time points, indicating the widespread circulation of highly-related isolates. The TR 34 /L98H polymorphism was identified in 8/102 (8%) isolates, primarily from air samples collected in the basement, outpatients department, and reception, all of which clustered phylogenetically ( Figure 4c ), making this the second most common genetic polymorphism after M172V/F46Y. Six of the TR 34 /L98H isolates were resistant to at least one clinical azole and tebuconazole (up to 16 mg/L). Azole-susceptible isolate pairs harbouring the G448S mutation (exhibiting >94% genetic similarity), showed a comparable spatiotemporal distribution and were recovered from air samples in staff offices and outpatient areas in December 2020 and March 2021, respectively. Incorporation of 616 UK comparator whole-genome sequences To achieve greater longitudinal resolution of intra-host AR Af dynamics, an additional 118 retrospective clinical genomes from respiratory disease cohorts at the same central London hospital were incorporated, expanding the clinical dataset to 300 genomes from 83 individuals collected between 2015–2022. To further enhance phylogenetic resolution and investigate environmental AR Af transmission, 151 UK-wide clinical isolates and 347 environmental isolates were included as comparators. DAPC analysis was used to illustrate the genetic relationships between the clinical and environmental clusters ( Figure 4d ). Study participants’ isolates overlapped with UK clinical and environmental isolates, indicating acquisition from multiple sources. Hospital environmental isolates clustered separately but showed partial overlap with study participants’ isolates, supporting the role of hospital environments as potential reservoirs for AR Af exposure and acquisition. This observation was in sharp contrast with participants’ homes, where no closely-related isolates were identified ( Figure 2c ). Pairwise genetic similarity (>97% identity, <1,474 unique SNPs) identified 994 closely-related isolate pairs in the UK dataset. Analysis of these pairs aimed to resolve the most likely environmental source of clinical A. fumigatus isolates. Most clinical pairs across the wider UK dataset ( n = 290/994) showed close relationships to isolates from the wider environment, indicating this as the predominant reservoir of exposure ( Figure 4e ). However, 49 pairs showed >97% identity between clinical isolates from this study’s participants, and their London hospital environment, suggesting possible intra-hospital transmission. Of these, 28 comparisons showed clinical TR 34 /L98H, G448S, and D262Y that were also identified in the hospital environment, with >97% identity amongst clinical and environmental isolates. Strikingly, within the Central London Hospital cohort, 41% ( n = 7/17) of individuals carried isolates with >97% genetic identity that were exclusive to the hospital environment, while 35% ( n = 6) had isolates linked to the wider UK environment but not their homes. Notably, phylogenomic analysis of the complete UK dataset, comprising 912 isolates, revealed tightly clustered clinical and hospital environmental isolates from this study, indicative of nosocomial acquisition of infection ( Figure 5a ). The UK phylogeny, accessible via a Microreact project ( https://microreact.org/project/ohanRa45Se2kRQQugq6mK9-uk ), showed a median bootstrap support of 78% across the tree, with nosocomial clusters supported by 100% bootstrap values (Supplementary Figure 2). Download figure Open in new tab Figure 5. Phylogenetic analysis and genotypic characterisation of UK A. fumigatus clinical and environmental isolates. Phylogenetic relationships among UK clinical and environmental isolates (a) with highlighted phylogenetic clusters showing epidemiological links between clinical and hospital environmental A. fumigatus (b-d). Case 33 (a CPA participant) harboured AR Af isolates with the cyp51A G448S allele over ten months (October 2020 – July 2021), showing an average pairwise divergence of 2,438 SNPs (95% identity) and phylogenetic clustering across this time-series ( Figure 5b ). The G448S allele is normally associated with in-host evolution 42 yet occurred in hospital air samples collected in December 2020 and March 2021. These G448S-bearing isolates from the hospital environment were shown to phylogenetically cluster with Case 33 isolates, but were separated by an average of 4,199 SNPs (91.4% genetic similarity; Figure 5b ). This phylogenetic clustering indicates possible hospital acquisition; however, the genetic distance suggests the absence of recent demonstrable direct transmission. Other clusters of hospital clinical and environmental TR 34 /L98H isolates similarly point to potential hospital acquisition ( Figures 5c-d ). However, the presence of closely-related isolates from other UK clinical and environmental sources indicates broader occurrence of these genotypes and acquisition from exposures outside the hospital cannot be ruled out. Discussion Azole-resistant A. fumigatus is an increasing global health threat, particularly complicating chronic Aspergillus- related lung disease and resulting in significant morbidity and mortality. In this study, using real-time microbiological surveillance integrated with WGS, we identify healthcare environments as reservoirs of AR Af bioaerosol exposures. That several clinical isolates shared >95% genetic similarity to hospital-derived environmental isolates is consistent with nosocomial transmission pathways in settings where there is a concentration of at-risk individuals. Environmental nosocomial surveillance in high-traffic areas performed in our study demonstrated the pervasive presence of A. fumigatus and AR Af within healthcare settings, including those areas of the hospital with stringent protective measures 43 – 47 (but not intensive care settings). Surveillance of the hospital environment revealed genetically-similar AR Af across multiple locations and time points, demonstrating that AR Af strains can survive long-term in hospital settings. These findings clearly highlight the need for robust surveillance in order to determine the extent that such exposures occur in this, and other, healthcare settings and, where observed, what strategies to mitigate exposures in vulnerable patient populations can be used. Triazole-resistant isolates in the hospital setting were found at prevalences that broadly matched those reported in the wider UK environment of 3–6% 18 , 48 – 50 confirming that AR Af strains were well-established in particular healthcare environments – the hospital basement, outpatient department and reception area - highlighting the potential for localised transmission and an ongoing risk of repeated patient exposure to AR Af . Patients with lung disease and aspergillosis may further transmit strains into the hospital environment through coughing and expectoration 32 . If patients harbour isolates that are drug-resistant (either from in-host evolution or environment acquisition), these inocula may contribute to the establishment of distinct healthcare-specific environmental reservoirs of azole-resistance and a bidirectional cycle of contamination and acquisition. High genetic similarity between clinical and hospital environmental isolates characterised by TR 34 /L98H and G448S suggest interlinked transmission pathways facilitated through direct or indirect routes of exposure. Although G448S is predominantly linked to in-host evolution, independent studies documenting cyp51a point mutations in environmental samples suggest that such mutations can arise independently of clinical pressures, complicating the distinction between patient-derived and environmental resistance pathways 51 – 55 . This is further supported by our detection of the first UK hospital environmental isolate carrying the TR 120 allele, previously documented only in Dutch CF isolates and associated with de novo evolution during prolonged azole therapy 40 . In Case 30, phylogenetic analysis of isolates collected over 11 months showed high relatedness (100% bootstrap support), with variable non-synonymous SNP profiles both with and without TR 120 . Genomic analysis confirmed that clinical TR 120 isolates were genetically distinct from the hospital environment-derived TR 120 isolate, suggesting either patient-to-environment transmission followed by compensatory adaptation, independent emergence under hospital selective pressures (challenging the assumption that TR 120 mutations arise exclusively within the host), or the existence of unsampled intermediary isolates linking these reservoirs. The absence of a reliable molecular clock for A. fumigatus limits precise reconstruction of transmission pathways. While targeted interventions to mitigate exposure and acquisition of AR Af by at-risk individuals may be achievable in controlled hospital environments, high-traffic areas such as outpatient clinics and waiting areas present greater challenges for effective regulation. In this context, the integration of remote patient monitoring, including at-home testing, offers a practical strategy to reduce hospital visits, limit exposure in high-risk settings and disrupt potential nosocomial transmission networks. Although surveillance efforts often intensify during periods of hospital construction 56 , the persistent presence of Aspergillus spores as shown in our study highlights the importance of continuous environmental monitoring. Long-term mitigation will require infrastructure modifications to minimise fungal persistence and a reassessment of environmental features such as indoor planting, even in areas not traditionally classified as high risk 57 . Further mitigation strategies such as air filtration, ventilation and specific infection control protocols for individuals with known AR Af additionally require consideration in this context. Our study further demonstrates the high incidence of AR Af in individuals with chronic respiratory fungal disease such as CPA with variable intra-host A. fumigatus phylogenetic diversity reflecting dynamic pathogen populations within the human host. Our study employed frequent high-volume culture sampling previously shown to improve microbiological A. fumigatus yield emphasising the need for comprehensive sampling to support robust epidemiological conclusions on resistance acquisition 58 , 59 . Closely-related serial isolates in chronic respiratory aspergillosis suggest repeated environmental acquisition or (more likely) intra-host persistence under prolonged selective drug pressure. In Case 31, TR 34 /L98H isolates detected from 2016-2023 exhibited high phylogenetic relatedness (100% bootstrap support), with a TR 34 isolate lacking L98H also identified, marking the first clinical report of this allele. High rates of recombination caused by the sexual cycle of A. fumigatus , primarily described in environmental settings 60 , 61 , have been shown to generate resistance genotypes such as TR 34 /L98H from parental strains carrying separate TR 34 and L98H alleles 62 – 64 . The phylogenetic relationship between TR 34 and TR 34 /L98H isolates raises the possibility of acquisition from a persistent environmental source or, alternatively, a recombination event occurring within the host. These findings demonstrate the adaptive versatility of AR Af, whether through environmental persistence, recombination, or repeated acquisition. The detection of TR 34 /L98H in hospital environments, despite no phylogenetic link to Case 31 clinical isolates, suggests episodic exposure may lead to recurrent acquisition and potential within-host adaptation. Genomic analysis identified the TR 34 /L98H resistance mechanism in 25% of azole-resistant clinical cases and confirmed the second occurrence of the TR 46 /Y121F/T289A mutation within a UK clinical cohort, underscoring the contribution of environmental AR Af to resistance acquisition. The high prevalence of TR 34 /L98H in the chronic Aspergillus -related lung disease cohort reflects its widespread occurrence as a globally-dominant resistance mechanism 16 , 17 , 65 , 66 – 68 . Detection of the TR 46 /Y121F/T289A allele, a resistance mechanism with high-level voriconazole resistance in Case 32 signals its emergence in the UK, echoing reports from Europe 59 , 69 – 72 , Asia 73 – 75 and Africa 76 . Although first identified in a clinical isolate in Manchester in 2017 77 , retrospective surveillance from 1998–2017 found no cases among 1,469 isolates in London cohorts 78 . The first environmental detection in 2019, involving six isolates from soil, compost, and hospital flower beds in London, confirmed local presence of TR 46 /Y121F/T289A 48 . By 2023, a national surveillance study found TR 46 /Y121F/T289A in 6% of aerosolised A. fumigatus isolates, compared to 59% for TR 34 /L98H 49 , suggesting a trajectory of broader dissemination similar to that previously observed for TR 34 /L98H. This is of significant concern for global use of voriconazole which is a first-line antifungal therapy for invasive aspergillosis. In conclusion, using real-time epidemiological surveillance we show that hospital environments may serve as unique reservoirs of AR Af , maintained through the introduction of host-derived isolates and sustained local transmission cycles. The complex pathological landscape of chronic respiratory diseases, marked by fluctuating inflammation, microbial burden, and prolonged antifungal exposure, may further facilitate the persistence of genetically diverse populations and contribute to resistance evolution across both environmental and clinical reservoirs. The role of nosocomial AR Af reservoirs in sustaining resistant populations within healthcare environments where at-risk patients concentrate, underscores the need for expanded genomic surveillance across diverse settings and cohorts in order to better understand the mitigation strategies that are needed to protect at-risk patients. Methods Participant selection and inclusion criteria for prospective surveillance Participants aged ≥16 years with a confirmed diagnosis of chronic Aspergillus -related lung disease on a background of CF, non-CF bronchiectasis, CPA, COPD or other chronic lung conditions were recruited within the domains of a central London Hospital. Informed consent was obtained before enrolment, and detailed clinical data were collected, including demographics, medical history, respiratory health, and antifungal treatment history. Sputum samples were collected at the initial screening visit and monthly via remote sampling. Sputum sample collection and processing Monthly sputum samples were collected remotely from 55 participants diagnosed with chronic Aspergillus -related lung disease. Each participant received a home sampling kit containing a sterile 30 mL collection tube (Thermo Scientific™, Sterilin™), Category 2 UN73373 packaging, and a leaflet with collection and mailing instructions. Samples were homogenized in a 1:1 (v:v) ratio with Mucolyse Sputum Digestant (Pro-Lab Diagnostics, UK) and incubated at room temperature for 20 minutes. A 200 µL aliquot of digested sputum was inoculated onto Sabouraud dextrose agar (SDA) supplemented with 50 mg/L chloramphenicol (Oxoid, Basingstoke, UK) and incubated at 45°C to select for A. fumigatus . Home Surveillance: Participant selection criteria Participants were contacted via phone or email to explain the study’s purpose and assess their interest. Thirteen individuals were selected for home environmental monitoring, prioritising those with ≥3 culture-positive samples to examine A. fumigatus diversity. This included eight participants with AR Af or confirmed cyp51A resistance alleles to investigate potential home transmission pathways. As controls, three participants with azole-susceptible cyp51A wildtype isolates and two with culture-negative samples were included to assess AR Af burden in non-resistant cases. Among the selected participants, diagnoses included CF ( n = 1), CPA ( n = 7), ABPA ( n = 4), and bronchiectasis ( n = 1). During the study, one participant withdrew due to regular inpatient stays, and one died. Home surveillance: Sample Collection Surveillance kits were provided every three months to capture seasonal variation and included materials for collecting indoor air, soil, dust, and swab samples, along with pre-labelled packaging for traceability and a detailed instruction leaflet. Samples collected from January– February, April–May, June–July, and October–November were classified as winter, spring, summer, and autumn, respectively. Returned samples were processed immediately or stored at 4°C until analysis. To optimise A. fumigatus recovery, participants used two validated passive air samplers 49 , 79 , 80 : MicroAmp™ clear adhesive film (Thermo Fisher Scientific, UK) and electrostatic dust collectors (EDCs) (Liefheit, UK). The EDCs were sterilised by autoclaving at 121°C for 15 minutes prior to distribution. Each kit contained two of each sampler, which were placed at ∼1.2 meters height to simulate breathing zone exposure. The adhesive film and EDCs were exposed to indoor air for 14 days before being sealed in sterile ziplock bags. Settled dust was collected using an EDC attached to a vacuum nozzle or by sweeping surfaces. Surface soil samples were collected from indoor potted plants or, if unavailable, from outdoor flower beds, using sterile 50 mL Falcon tubes. Kits included FFP2 NR face masks (Medisave, UK) and latex-free gloves for safety during collection. Home surveillance: Sample processing A. fumigatus colonies were recovered from MicroAmp™ adhesive air samplers (Applied Biosystems, UK) using previously described protocols 49 . EDC samples were washed in 50 mL of 0.85% NaCl with 0.5% Tween-20, shaken at 250 rpm for 60 minutes at room temperature, centrifuged, and the supernatant removed to concentrate particulate matter before resuspension. Aliquots (150 µL) were inoculated in triplicate onto culture plates. Surface swab samples were washed in 1 mL of 0.85% NaCl with 0.5% Tween-20, vortexed for 1 minute, and 200 µL aliquots were plated in triplicate. Soil samples (2 g) were suspended in 8 mL of 0.85% NaCl with 0.5% Tween-20, vortexed, and 200 µL of supernatant was plated in triplicate. All culture plates were incubated at 45°C and inspected daily for fungal growth. Hospital surveillance: Sampling locations Seasonal air and soil samples were collected between November 2020 and February 2022 from a central London hospital comprising two sites: Site A, a Victorian-era building still in use for outpatient clinics, and Site B, a modern extension constructed in the early 1990s housing inpatient respiratory and cardiac wards. Air samples from Site A were collected from three outpatient clinics, a staff office, and the basement. Soil samples were obtained from internal flower beds adjacent to an outpatient clinic and external flower beds near the staff entrance. In Site B, air samples were collected from two inpatient wards, the Intensive Care Unit (ICU), and the hospital reception. Soil samples were taken from internal and external flower beds at the hospital reception and two external courtyards. Additional air samples were collected from an external staff car park. Hospital surveillance: Sample Collection and processing Air samples were collected using a ‘SAS Super 180’ (Cherwell Laboratories, UK) air sampler positioned at approximately 1.2 meters height. Contact plates (90 mm) containing SDA supplemented with antibiotics (16 mg/L penicillin and 16 mg/L streptomycin) were placed on the aspirating head, sampling 1000 L of air over 5 minutes. Plates were sealed with Parafilm, stored in ziplock bags, and incubated at 45°C for 7 days, with daily inspections for colony growth. For soil sampling, 2 g of surface soil from internal and external hospital flower beds was suspended in 8 mL of sterile suspension buffer (0.85% NaCl, 0.01% Tween®-20, ThermoFisher Scientific) as previously described 81 . Briefly, a 200 µL supernatant aliquot was plated onto SDA with antibiotics and incubated at 45°C for up to 7 days to isolate A. fumigatus . A. fumigatus isolate collection and azole susceptibility screening Colony counts were recorded for clinical and environmental samples, with up to five colonies per morphology isolated onto SDA plates to capture diversity. Azole susceptibility profiles of 321 clinical and 826 environmental isolates were assessed using 4-well VIPCheck™ plates (Mediaproducts BV, Netherlands) containing agar supplemented with itraconazole (4 mg/L), voriconazole (2 mg/L), posaconazole (0.5 mg/L), and an azole-free control, following established protocols 82 DNA extraction and WGS Clinical and environmental isolates were selected to represent host-specific and spatiotemporal diversity, ensuring a 1:1 ratio of azole-susceptible to azole-resistant isolates per sample type. DNA was extracted using MasterPure Yeast Cell Lysis Solution (Epicentre Biotechnologies, UK) with bead-beating (1.0 mm zirconia beads, Thistle Scientific, UK) in a FastPrep™-24 system (MP Biomedicals, OH) at 6.0 m/s for 40 seconds (two cycles, 5-minute cooling period). The homogenized solution was centrifuged (14,000 rpm, 2 min), and the supernatant treated with 1 µL RNase Cocktail™ (Thermo Fisher Scientific) at 65°C for 15 minutes, then cooled on ice (15 min). After adding 20 µL Proteinase K, samples were vortexed with Qiagen AL lysis buffer (Qiagen, Netherlands) and incubated at 56°C for 10 minutes. DNA was precipitated with 96–100% ethanol, purified using Qiagen spin columns, and eluted in 40 µL Elution Buffer. DNA concentration was measured via Qubit 2.0 fluorometer (Thermo Fisher Scientific). Library preparation followed LITE and LITE 2.0 protocols, and WGS was performed on the Illumina NovaSeq platform, generating 150 base pair (bp) paired end reads. Samples with <30× coverage were excluded to ensure data quality. Prospective A. fumigatus WGS data were consolidated with an existing UK WGS collection (616 genomes). Sequence alignment and variant calling Raw 150 bp paired-end reads were quality-checked using FastQC (Babraham Institute, v0.10.1) and aligned to the A. fumigatus AF293 reference genome 83 using BWA-MEM (v0.7.15) 84 . SAMtools was used for BAM conversion, sorting and indexing, while Picard Tools (v2.6.0) was used to assign read group information and mark duplicate reads for exclusion. Variant calling was performed with GATK HaplotypeCaller (v4.0) using a ploidy setting of 1, excluding repetitive regions identified by RepeatMasker 85 via the ‘-XL’ parameter. Variants were filtered with a minimum confidence threshold of 30 and base quality of 20, and Base Quality Score Recalibration was applied. High-confidence SNPs were retained using GATK VariantFiltration with the following thresholds: QD 60.0, MQ < 40.0, MQRankSum < - 12.5, ReadPosRankSum 4.0. SNPs failing these criteria were removed. Non-synonymous SNPs (nsSNPs) were annotated using VCFannotator (Broad Institute). After quality filtering, clinical and environmental WGS data were integrated into a UK-wide genomic repository, expanding the dataset to 912 genomes. Genomes were compared using genome-wide SNP analysis and phylogenetics to identify closely related isolate pairs and infer potential transmission pathways Genomic diversity analysis Phylogenetic trees were inferred from whole genome SNP alignments using RAxML-NG 86 with the GTR+G substitution model. Bootstrap replicates were concatenated until convergence was reached, determined by the by the --bsconverge command. Trees were visualised in R v4.3.1 via ggTree 87 and ggTreeExtra 88 . Multivariate analyses were performed in R v4.3.1 using adegenet (v2.1.10) following established protocols 89 –92 . FASTA alignments were converted into a genind object, applying a polymorphism threshold of 0.01 to account for low frequency variants. Population groups were assigned, and missing data were imputed using mean allele frequencies via the NA.method=’mean’ function. Discriminate analysis of principle components (DAPC) based on SNPs was conducted to assess genetic differentiation among isolates. The optimal number of principal components (PCs) was selected using cross-validation (‘xvalDapc’), based on the lowest mean squared error (MSE). DAPC results were visualized as scatter plots, with population groups mapped to data points and an inset plot showing the cumulative variance explained by PCs. Reference genomes were included as controls. Data Availability All data produced in the present study are available upon reasonable request to the authors https://microreact.org/project/ohanRa45Se2kRQQugq6mK9-uk Ethics The London–Brent Research Ethics Committee of the United Kingdom Health Research Authority gave ethical approval for this work (REC reference: 19/LO/1663). Funding This work was supported by a MRC Clinical Academic Research Partnership fellowship (MR/T005572/1 to AS. AS and MF were further supported by the MRC centre grant (MR/X020258/1). DAJ supported by the Fungal One Health and Anti microbial resistance Network BBSRC BB/Z515619/1 and Cystic Fibrosis Trust Strategic Research Centre SRC015 Targeting Immunotherapy in Fungal Infections in Cystic Fibrosis. MCF, DAJ, APB, JR received funding from Wellcome Trust grant 219551/Z/19/Z. JMGS, SH, RL, MCF received funding from NERC grant NE/X00547X/1. MCF is a fellow in the CIFAR ‘Fungal Kingdoms’ program Conflicts of interest A. Shah reports consultancy fees from AstraZeneca, Mundipharma and Gilead Sciences, speaker fees from Insmed, and research grants from AstraZeneca, Gilead Sciences and Pfizer. MCF reports speaker fees from Gilead Sciences References 1. ↵ WHO . WHO Fungal Priority Pathogens List to Guide Research , Development and Public Health Action . Geneva: World Health Organisation . ( 2022 ). 2. ↵ Kudymowa , J. , Hu , J & Hird , T . Fungal Diseases: Health Burden , Neglectedness, and Potential Interventions ( 2024 ). https://rethinkpriorities.org/publications/fungal-diseases . [Accessed 1 st September 2024] 3. ↵ Alqahtani , M. S. , Kazi , M. , Alsenaidy , M. A. & Ahmad , M. Z . Advances in oral drug delivery . Frontiers in Pharmacology 12 , 618411 ( 2021 ). OpenUrl PubMed 4. Verweij , P. E. et al. Dual use of antifungals in medicine and agriculture: How do we help prevent resistance developing in human pathogens? Drug Resistance Updates 65 , 100885 ( 2022 ). OpenUrl PubMed 5. Kharb , R. , Sharma , P. C. & Yar , M. S . Pharmacological significance of triazole scaffold . Journal of Enzyme Inhibition and Medical Chemistry 26 , 1 – 21 ( 2011 ). OpenUrl 6. ↵ Nywening , A. V. , Rybak , J. M. , Rogers , P. D. & Fortwendel , J. R . Mechanisms of triazole resistance in Aspergillus fumigatus . Environmental Microbiology 22 , 4934 – 4952 ( 2020 ). OpenUrl 7. ↵ Martínez-Matías , N. & Rodríguez-Medina , J. R . Fundamental concepts of azole compounds and triazole antifungals: A beginner’s review . Puerto Rico Health Science Journal 37 , ( 2018 ). 8. ↵ Chen , L. et al. Pharmacokinetics and pharmacodynamics of posaconazole . Drugs 80 , 671 – 695 ( 2020 ). OpenUrl CrossRef PubMed 9. Faure , E. , Kwong , K. & Nguyen , D . Pseudomonas aeruginosa in Chronic Lung Infections: How to Adapt Within the Host? Frontiers in Immunology 9 , 2416 ( 2018 ). OpenUrl PubMed 10. ↵ Sehgal , I. S. et al. Efficacy of 12-months oral itraconazole versus 6-months oral itraconazole to prevent relapses of chronic pulmonary aspergillosis: an open-label, randomised controlled trial in India . Lancet Infectious Diseases 22 , 1052 – 1061 ( 2022 ). OpenUrl CrossRef PubMed 11. ↵ Markussen , T. et al. Environmental heterogeneity drives within-host diversification and evolution of Pseudomonas aeruginosa . mBio 5 , 10 – 1128 ( 2014 ). OpenUrl CrossRef 12. ↵ Abdolrasouli , A. et al. High prevalence of triazole resistance in clinical Aspergillus fumigatus isolates in a specialist cardiothoracic centre . International Journal of Antimicrobial Agents 52 , 637 – 642 ( 2018 ). OpenUrl CrossRef PubMed 13. ↵ Latgé , J.-P. & Chamilos , G. Aspergillus fumigatus and Aspergillosis in 2019 . Clinical Microbiology Reviews 33 , e00140 – 18 ( 2019 ). OpenUrl CrossRef PubMed 14. Lestrade , P. P. et al. Voriconazole resistance and mortality in invasive aspergillosis: a multicenter retrospective cohort study . Clinical Infectious Diseases 68 , 1463 – 1471 ( 2019 ). OpenUrl CrossRef PubMed 15. ↵ Patterson , T. F. et al. Practice guidelines for the diagnosis and management of aspergillosis: 2016 update by the Infectious Diseases Society of America . Clinical Infectious Diseases 63 , e1 – e60 ( 2016 ). OpenUrl CrossRef PubMed 16. ↵ Rhodes , J. et al. Population genomics confirms acquisition of drug-resistant Aspergillus fumigatus infection by humans from the environment . Nature Microbiology 7 , 663 – 674 ( 2022 ). OpenUrl CrossRef PubMed 17. ↵ Sewell , T. R. et al. Nonrandom distribution of azole resistance across the global population of Aspergillus fumigatus . mBio 10 , e00392 – 19 ( 2019 ). OpenUrl PubMed 18. ↵ Shelton , J. M. G. et al. Citizen science surveillance of triazole-resistant Aspergillus fumigatus in United Kingdom residential garden soils . Applied and Environmental Microbiology 88 , e02061 – 21 ( 2022 ). OpenUrl PubMed 19. ↵ Paluch , M. et al. High airborne level of Aspergillus fumigatus and presence of azole-resistant TR 34 /L98H isolates in the home of a cystic fibrosis patient harbouring chronic colonisation with azole-resistant H285Y A. fumigatus . Journal of Cystic Fibrosis 18 , 364 – 367 ( 2019 ). OpenUrl PubMed 20. ↵ Lavergne , R. A. et al. Home environment as a source of life-threatening azole-resistant Aspergillus fumigatus in immunocompromised patients . Clinical Infectious Diseases 64 , 76 – 78 ( 2017 ). OpenUrl CrossRef PubMed 21. ↵ Godeau , C. et al. Azole-resistant Aspergillus fumigatus in the hospital: Surveillance from flower beds to corridors . American Journal of Infection Control 48 , 702 – 704 ( 2020 ). OpenUrl CrossRef PubMed 22. Vaghar , Z. , Khodavaisy , S. , Badali , H. & Sabokbar , A . Molecular detection of azole-resistant Aspergillus fumigatus isolates carrying TR 34 /L98H mutations in soil samples from the critical hospitals. Molecular Genetics , Microbiology and Virology 37 , 49 – 53 ( 2022 ). OpenUrl 23. ↵ Gonzalez-Jimenez , I. , Lucio , J. , Menéndez-Fraga , M. D. , Mellado , E. & Peláez , T . Hospital environment as a source of azole-resistant Aspergillus fumigatus strains with TR 34 /L98H and G448A cyp51a mutations . Journal of Fungi 7 , 22 ( 2021 ). OpenUrl PubMed 24. ↵ Adams , R. I. , Miletto , M. , Taylor , J. W. & Bruns , T. D . Dispersal in microbes: fungi in indoor air are dominated by outdoor air and show dispersal limitation at short distances . ISME Journal 7 , 1262 – 1273 ( 2013 ). OpenUrl PubMed 25. ↵ Liu , W. et al. Associations of building characteristics and lifestyle behaviours with home dampness-related exposures in Shanghai dwellings . Building and Environment 88 , 106 – 115 ( 2015 ). OpenUrl 26. ↵ Bouakline , A. , Lacroix , C. , Roux , N. , Gangneux , J. P. & Derouin , F . Fungal contamination of food in hematology units . Journal of Clinical Microbiology 38 , 4272 – 4273 ( 2000 ). OpenUrl Abstract / FREE Full Text 27. De Bock , R. , Gyssens , I. , Peetermans , M. & Nolard , N. Aspergillus in pepper . The Lancet 334 , 331 – 332 ( 1989 ). OpenUrl 28. ↵ Paterson , R. R. M. & Lima , N . Filamentous fungal human pathogens from food emphasising Aspergillus, Fusarium and Mucor . Microorganisms 5 , 44 ( 2017 ). OpenUrl PubMed 29. ↵ Levinskaitė , L. & Paškevičius , A . Fungi in water-damaged buildings of Vilnius Old City and their susceptibility towards disinfectants and essential oils . Indoor and Built Environment 22 , 766 – 775 ( 2013 ). OpenUrl CrossRef 30. ↵ Millner , P. D. , et al. Bioaerosols associated with composting facilities . ( 1994 ). 31. ↵ Rhame , F. S. , Streifel , A. J. , Kersey Jr , J. H. & McGlave , P. B . Extrinsic risk factors for pneumonia in the patient at high risk of infection . American Journal of Medicine 76 , 42 – 52 ( 1984 ). OpenUrl CrossRef PubMed Web of Science 32. ↵ Engel , T. G. P. et al. Aerosol transmission of Aspergillus fumigatus in cystic fibrosis patients in the Netherlands . Emerging Infectious Diseases 25 , 797 – 799 ( 2019 ). OpenUrl CrossRef PubMed 33. ↵ Zhang , J. et al. Relevance of heterokaryosis for adaptation and azole-resistance development in Aspergillus fumigatus . Proceedings of the Royal Society B 286 , 20182886 ( 2019 ). OpenUrl PubMed 34. ↵ Verweij , P. E. et al. In-host adaptation and acquired triazole resistance in Aspergillus fumigatus : a dilemma for clinical management . Lancet Infectious Diseases 16 , e251 – e260 ( 2016 ). OpenUrl CrossRef PubMed 35. ↵ Ferroni , A. et al. Bacterial contamination in the environment of hospitalised children with cystic fibrosis . Journal of Cystic Fibrosis 7 , 477 – 482 ( 2008 ). OpenUrl PubMed 36. Tanner , W. D. et al. Environmental contamination of contact precaution and non-contact precaution patient rooms in six acute care facilities . Clinical Infectious Diseases 72 , S8 – S16 ( 2021 ). OpenUrl CrossRef PubMed 37. ↵ Zuckerman , J. B. et al. Bacterial contamination of cystic fibrosis clinics . Journal of Cystic Fibrosis 8 , 186 – 192 ( 2009 ). OpenUrl PubMed 38. ↵ ECDC . Surveillance of healthcare-associated infections and prevention indicators in European intensive care units . Preprint at https://www.ecdc.europa.eu/sites/default/files/documents/HAI-Net-ICU-protocol-v2.2_0.pdf . ( 2017 ). 39. ↵ CDC . National Healthcare Safety Network (NHSN) patient safety component manual . Preprint at https://www.cdc.gov/nhsn/pdfs/pscmanual/pcsmanual_current.pdf ( 2024 ). 40. ↵ Hare , R. K. et al. In vivo selection of a unique tandem repeat mediated azole resistance mechanism (TR 120 ) in Aspergillus fumigatus cyp51A, Denmark . Emerging Infectious Diseases 25 , 577 ( 2019 ). OpenUrl CrossRef PubMed 41. ↵ Chazalet , V. et al. Molecular typing of environmental and patient isolates of Aspergillus fumigatus from various hospital settings . Journal of Clinical Microbiology 36 , 1494 – 1500 ( 1998 ). OpenUrl Abstract / FREE Full Text 42. ↵ Araujo , R. et al. Fungal infections after haematology unit renovation: evidence of clinical, environmental and economical impact . European Journal of Haematology 80 , 436 – 443 ( 2008 ). OpenUrl CrossRef PubMed 43. ↵ Cho , S.-Y. et al. Profiles of environmental mold: indoor and outdoor air sampling in a hematology hospital in Seoul, South Korea . International Journal of Environmental Research and Public Health 15 , 2560 ( 2018 ). OpenUrl 44. Ghazanfari , M. et al. Indoor environment assessment of special wards of educational hospitals for the detection of fungal contamination sources: A multi-center study (2019-2021) . Current Medical Mycology 8 , 1 ( 2022 ). 45. Hassan , A. & Zeeshan , M . Microbiological indoor air quality of hospital buildings with different ventilation systems, cleaning frequencies and occupancy levels . Atmospheric Pollution Research 13 , 101382 ( 2022 ). OpenUrl 46. Sewell , T. R. et al. Elevated prevalence of azole-resistant Aspergillus fumigatus in urban versus rural environments in the United Kingdom . Antimicrobial Agents and Chemotherapy 63 , ( 2019 ). 47. ↵ Shelton , J. M. G. et al. Citizen science surveillance of triazole-resistant Aspergillus fumigatus in United Kingdom residential garden soils . Applied and Environmental Microbiology 88 , e02061 – 21 ( 2022 ). OpenUrl PubMed 48. ↵ Shelton , J. M. G. et al. Citizen science reveals landscape-scale exposures to multiazole-resistant Aspergillus fumigatus bioaerosols . Science Advances 9 , eadh8839 ( 2023 ). OpenUrl CrossRef PubMed 49. ↵ Tsitsopoulou , A. et al. Determination of the prevalence of triazole resistance in environmental Aspergillus fumigatus strains isolated in South Wales, UK . Frontiers in Microbiology 9 , ( 2018 ). 50. ↵ Bader , O. et al. Environmental isolates of azole-resistant Aspergillus fumigatus in Germany . Antimicrobial Agents and Chemotherapy 59 , 4356 – 4359 ( 2015 ). OpenUrl Abstract / FREE Full Text 51. ↵ Prigitano , A. , Esposto , M. C. , Romanò , L. , Auxilia , F. & Tortorano , A. M . Azole-resistant Aspergillus fumigatus in the Italian environment . Journal of Global Antimicrobial Resistance 16 , 220 – 224 ( 2019 ). OpenUrl PubMed 52. Dladla , M. , Gyzenhout , M. , Marias , G. & Ghosh , S . Azole resistance in Aspergillus fumigatus -comprehensive review . Archives of Microbiology 206 , 305 ( 2024 ). OpenUrl PubMed 53. Buil , J. B. et al. The fading boundaries between patient and environmental routes of triazole resistance selection in Aspergillus fumigatus . PLoS Pathogogens 15 , e1007858 ( 2019 ). OpenUrl 54. Wiederhold , N. P . Epidemiology and prevalence of azole-resistant Aspergillus fumigatus : What is our understanding of the situation? Current Fungal Infection Reports 17 , 177 – 187 ( 2023 ). OpenUrl 55. ↵ Douglas , A. P. , Stewart , A. G. , Halliday , C. L. & Chen , S. C.-A . Outbreaks of fungal infections in hospitals: Epidemiology, detection, and management . Journal of Fungi 9 , 1059 ( 2023 ). OpenUrl PubMed 56. ↵ Beauvais , B. et al. A reason to renovate: The association between hospital age of plant and value-based purchasing performance . Health Care Management Reviews 46 , 66 – 74 ( 2021 ). OpenUrl 57. ↵ van Leer-Buter , C. , Takes , R. P. , Hebeda , K. M. , Melchers , W. J. G. & Verweij , P. E. Aspergillosis—and a misleading sensitivity result . The Lancet 370 , 102 ( 2007 ). OpenUrl 58. ↵ Astvad , K. M. T. et al. First detection of TR 46 /Y121F/T289A and TR 34 /L98H alterations in Aspergillus fumigatus isolates from azole-naive patients in Denmark despite negative findings in the environment . Antimicrobial Agents and Chemotherapy 58 , 5096 – 5101 ( 2014 ). OpenUrl Abstract / FREE Full Text 59. ↵ Auxier , B. et al. The human fungal pathogen Aspergillus fumigatus can produce the highest known number of meiotic crossovers . PLoS Biology 21 , e3002278 ( 2023 ). OpenUrl PubMed 60. ↵ O’Gorman , C. M. , Fuller , H. T. & Dyer , P. S . Discovery of a sexual cycle in the opportunistic fungal pathogen Aspergillus fumigatus . Nature 457 , 471 – 474 ( 2009 ). OpenUrl CrossRef PubMed Web of Science 61. ↵ Zhang , J. et al. A novel environmental azole resistance mutation in Aspergillus fumigatus and a possible role of sexual reproduction in its emergence . mBio 8 , ( 2017 ). 62. ↵ Abdolrasouli , A. et al. Genomic context of azole resistance mutations in Aspergillus fumigatus determined using whole-genome sequencing . mBio 6 , e00536 ( 2015 ). OpenUrl CrossRef PubMed 63. Fisher , M. C. , Hawkins , N. J. , Sanglard , D. & Gurr , S. J . Worldwide emergence of resistance to antifungal drugs challenges human health and food security . Science 360 739 – 742 ( 2018 ). OpenUrl Abstract / FREE Full Text 64. ↵ Ghazanfari , M. et al. Electronic equipment and appliances in special wards of hospitals as a source of azole-resistant Aspergillus fumigatus : a multi-centre study from Iran . Journal of Hospital Infection 145 , 65 – 76 ( 2024 ). OpenUrl PubMed 65. ↵ Chowdhary , A. et al. Clonal expansion and emergence of environmental multiple-triazole-resistant Aspergillus fumigatus strains carrying the TR 34 /L98H mutations in the cyp51A gene in India . PLoS One 7 , ( 2012 ). 66. ↵ Burks , C. , Darby , A. , Gómez Londoño , L. , Momany , M. & Brewer , M. T . Azole-resistant Aspergillus fumigatus in the environment: Identifying key reservoirs and hotspots of antifungal resistance . PLoS Pathogogens 17 , e1009711 ( 2021 ). OpenUrl 67. Rocchi , S. et al. Molecular epidemiology of azole-resistant Aspergillus fumigatus in France shows patient and healthcare links to environmentally occurring genotypes . Frontiers in Cellular Infection and Microbiology 11 , 729476 ( 2021 ). OpenUrl 68. ↵ Fischer , J. et al. Prevalence and molecular characterization of azole resistance in Aspergillus spp . isolates from German cystic fibrosis patients . Journal of Antimicrobial Chemotherapy 69 , 1533 – 1536 ( 2014 ). OpenUrl CrossRef PubMed Web of Science 69. ↵ van der Linden , J. W. M. et al. Aspergillosis due to voriconazole highly resistant Aspergillus fumigatus and recovery of genetically related resistant isolates from domiciles . Clinical infectious diseases 57 , 513 – 520 ( 2013 ). OpenUrl CrossRef PubMed 70. Vermeulen , E. , Maertens , J. , Schoemans , H. & Lagrou , K . Azole-resistant Aspergillus fumigatus due to TR 46 /Y121F/T289A mutation emerging in Belgium, July 2012 . Eurosurveillance 17 , 20326 ( 2012 ). OpenUrl PubMed 71. Wiederhold , N. P. et al. First detection of TR 34 /L98H and TR 46 /Y121F/T289A cyp51 mutations in Aspergillus fumigatus isolates in the United States . Journal of Clinical Microbiology 54 , 168 – 171 ( 2016 ). OpenUrl Abstract / FREE Full Text 72. ↵ Chowdhary , A. , Sharma , C. , Kathuria , S. , Hagen , F. & Meis , J. F . Azole-resistant Aspergillus fumigatus with the environmental TR 46 /Y121F/T289A mutation in India . Journal of Antimicrobial Chemotherapy 69 , 555 – 557 ( 2014 ). OpenUrl CrossRef PubMed Web of Science 73. ↵ Chen , Y. et al. Emergence of TR 46 /Y121F/T289A in an Aspergillus fumigatus isolate from a Chinese patient . Antimicrob Agents and Chemotherapy 59 , 7148 – 7150 ( 2015 ). OpenUrl FREE Full Text 74. Ren , J. et al. Fungicides induced triazole-resistance in Aspergillus fumigatus associated with mutations of TR 46 /Y121F/T289A and its appearance in agricultural fields . Journal of Hazardous Materials 326 , 54 – 60 ( 2017 ). OpenUrl CrossRef PubMed 75. ↵ Chowdhary , A. et al. Multi-azole-resistant Aspergillus fumigatus in the environment in Tanzania . Journal of Antimicrobial Chemotherapy 69 , 2979 – 2983 ( 2014 ). OpenUrl CrossRef PubMed 76. ↵ Moore , C. B. et al. First isolation of the pan-azole-resistant Aspergillus fumigatus cyp51A TR 46 /Y121F/T289A mutant in a UK patient . International Journal of Antimicrobial Agents 49 , 512 – 514 ( 2017 ). OpenUrl CrossRef PubMed 77. ↵ Abdolrasouli , A. et al. Surveillance for azole-resistant Aspergillus fumigatus in a centralized diagnostic mycology service, London, United Kingdom, 1998–2017 . Frontiers in Microbiology 9 , 2234 ( 2018 ). OpenUrl PubMed 78. ↵ Noss , I. et al. Evaluation of a low-cost electrostatic dust fall collector for indoor air endotoxin exposure assessment . Applied and Environmental Microbiology 74 , 5621 – 5627 ( 2008 ). OpenUrl Abstract / FREE Full Text 79. ↵ Normand , A.-C. et al. Comparison of air impaction and electrostatic dust collector sampling methods to assess airborne fungal contamination in public buildings . Annals of Occupational Hygiene 60 , 161 – 175 ( 2016 ). OpenUrl CrossRef PubMed 80. ↵ Tsitsopoulou , A. et al. Determination of the prevalence of triazole resistance in environmental Aspergillus fumigatus strains isolated in South Wales , UK. Frontiers in Microbiol 9 , ( 2018 ). 81. ↵ Buil , J. B. et al. Single-center evaluation of an agar-based screening for azole resistance in Aspergillus fumigatus by using VIPcheck . Antimicrobial Agents and Chemotherapy 61 , ( 2017 ). 82. ↵ Nierman , W. C. et al. Genomic sequence of the pathogenic and allergenic filamentous fungus Aspergillus fumigatus . Nature 438 , 1151 – 1156 ( 2005 ). OpenUrl CrossRef PubMed Web of Science 83. ↵ Li , H. & Durbin , R. Fast and accurate short read alignment with Burrows–Wheeler transform . bioinformatics 25 , 1754 – 1760 ( 2009 ). OpenUrl CrossRef PubMed Web of Science 84. ↵ Smit , A. F. A. , Hubley , R. & Green , P. RepeatMasker Open-4.0 . 2013 – 2015 ( 2015 ). [ https://www.repeatmasker.org ] 85. ↵ Kozlov , A. M. , Darriba , D. , Flouri , T. , Morel , B. & Stamatakis , A . RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference . Bioinformatics 35 , 4453 – 4455 ( 2019 ). OpenUrl CrossRef PubMed 86. ↵ Yu , G. , Smith , D. K. , Zhu , H. , Guan , Y. & Lam , T . T. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data . Methods in Ecology and Evolution 8 , 28 – 36 ( 2017 ). OpenUrl CrossRef 87. ↵ Xu , S. et al. ggtreeExtra: compact visualization of richly annotated phylogenetic data . Molecular Biology and Evolution 38 , 4039 – 4042 ( 2021 ). OpenUrl CrossRef PubMed 88. ↵ Jombart , T. , et al. Package ‘adegenet’. Github repository :< https://github.com/thibautjombart/adegenet ( 2018 ). 89. ↵ Jombart , T. adegenet: a R package for the multivariate analysis of genetic markers . Bioinformatics 24 , 1403 – 1405 ( 2008 ). OpenUrl CrossRef PubMed Web of Science 90. Jombart , T. & Collins , C. A tutorial for Discriminant Analysis of Principal Components (DAPC) using adegenet 2.1. 0 . https://adegenet.r-forge.r-project.org/files/tutorial-dapc.pdf ( 2015 ). 91. Jombart , T. & Collins , C. Analysing genome-wide SNP data using adegenet 2.0. 0 . https://adegenet.r-forge.r-project.org/files/tutorial-basics.pdf ( 2015 ). View the discussion thread. Back to top Previous Next Posted July 06, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Genomic epidemiology links azole-resistant Aspergillus fumigatus hospital bioaerosols to chronic respiratory aspergillosis Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Genomic epidemiology links azole-resistant Aspergillus fumigatus hospital bioaerosols to chronic respiratory aspergillosis Amélie P Brackin , Rodrigo Leitao , Johanna Rhodes , Zain Chaudhry , David Connell , Samuel Hemmings , Jennifer M G Shelton , Matthew C Fisher , Darius Armstrong-James , Anand Shah medRxiv 2025.07.04.25330042; doi: https://doi.org/10.1101/2025.07.04.25330042 Share This Article: Copy Citation Tools Genomic epidemiology links azole-resistant Aspergillus fumigatus hospital bioaerosols to chronic respiratory aspergillosis Amélie P Brackin , Rodrigo Leitao , Johanna Rhodes , Zain Chaudhry , David Connell , Samuel Hemmings , Jennifer M G Shelton , Matthew C Fisher , Darius Armstrong-James , Anand Shah medRxiv 2025.07.04.25330042; doi: https://doi.org/10.1101/2025.07.04.25330042 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Epidemiology Subject Areas All Articles Addiction Medicine (568) Allergy and Immunology (863) Anesthesia (298) Cardiovascular Medicine (4421) Dentistry and Oral Medicine (443) Dermatology (382) Emergency Medicine (607) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1507) Epidemiology (15215) Forensic Medicine (30) Gastroenterology (1122) Genetic and Genomic Medicine (6582) Geriatric Medicine (667) Health Economics (996) Health Informatics (4522) Health Policy (1366) Health Systems and Quality Improvement (1611) Hematology (540) HIV/AIDS (1264) Infectious Diseases (except HIV/AIDS) (15907) Intensive Care and Critical Care Medicine (1103) Medical Education (621) Medical Ethics (144) Nephrology (667) Neurology (6580) Nursing (345) Nutrition (998) Obstetrics and Gynecology (1143) Occupational and Environmental Health (956) Oncology (3328) Ophthalmology (970) Orthopedics (369) Otolaryngology (420) Pain Medicine (435) Palliative Medicine (129) Pathology (663) Pediatrics (1690) Pharmacology and Therapeutics (691) Primary Care Research (710) Psychiatry and Clinical Psychology (5436) Public and Global Health (9215) Radiology and Imaging (2193) Rehabilitation Medicine and Physical Therapy (1368) Respiratory Medicine (1194) Rheumatology (593) Sexual and Reproductive Health (709) Sports Medicine (529) Surgery (709) Toxicology (99) Transplantation (288) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9ff6dc11af98df88',t:'MTc3OTQwMDg4Ng=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();