This dataset contains a single Excel file listing all information of the fungal culture collection generated in the Mycospitalomics Project. This culture collection, preserved at IRNAS-CSIC (Seville), includes 504 fungal isolates from diverse environmental samples (air, surface and dust) collected in 2022-2023 from three study hospitals: Virgen del Rocio hospital in Seville (37°21′42″N 5°58′50″O), La Fe hospital in Valencia (39°26′37″N 0°22′32″O) and Severo Ochoa hospital in Leganés, Madrid (40°19′14″N 3°46′09″O)., Funded Ministerio de Ciencia e Innovación (España); Agencia Estatal de Investigación (España) and European Commission, No

Resumen de la comunicación oral presentada en el XXIX Congreso Sociedad Española de Microbiología (SEM-XXIX), Burgos, Spain, June 2023., Los ambientes hospitalarios requieren una atención especial para proteger a los pacientes inmunodeprimidos frente a las infecciones nosocomiales. Los hongos patógenos oportunistas pueden causar infecciones fúngicas invasivas (IFI), las cuales matan anualmente a aproximadamente
un millón y medio de personas en todo el mundo. Además, la creciente resistencia a los compuestos antimicrobianos, incluyendo la resistencia a los anti-fúngicos más usados para combatir los principales agentes causales de IFI (especies de Aspergillus y Candida) y otros patógenos emergentes (Mucorales, Fusarium, Scedosporium, Lomentospora and hongos dematiáceos), señala la necesidad de abordar estudios ambientales que permitan descubrir el origen de este problema. Teniendo en cuenta estos desafíos, el proyecto Mycospitalomics está estudiando la diversidad fúngica en tres hospitales españoles (Virgen del Rocío en Sevilla, La Fé en Valencia y Severo Ochoa en Leganés), con intensos muestreos ambientales (aire, superficies y sistemas de ventilación) y la aplicación de técnicas de cultivo y análisis del ADN ambiental; para abordar cuatro objetivos principales: (i) mejorar el conocimiento de las comunidades de hongos (micobioma) asociadas al ambiente hospitalario mediante el uso de técnicas modernas de ADN (“DNA metabarcoding” y qPCR), (ii) mejorar los métodos de detección/cuantificación fúngica para evaluar la exposición a los hongos presentes en hospitales, (iii) identificar los principales patógenos fúngicos oportunistas aislados de los hospitales de estudio y su resistencia a los compuestos anti-fúngicos, así como (iv) caracterizar las poblaciones de los principales patógenos identificados mediante genómica comparativa. En esta comunicación presentamos el progreso actual del proyecto, incluyendo los primeros resultados de los muestreos de enero a marzo de 2023, así como los desafíos futuros., Ministerio de Ciencia e Innovación (PID2021-123184OA-I00), Peer reviewed

14 páginas.- 4 figuras.- 3 tablas.- 111 referencias.- Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.buildenv.2024.112454, Hospital-dwelling fungi can cause life-threatening invasive infections in patients with impaired immune system. To prevent them, fungal diversity knowledge and environmental monitoring protocols in healthcare settings should be improved. This study contributes to these challenges through a multifaceted approach, combining air and surface sampling, particle counting, cultivation and DNA-based identification of isolates, to characterize fungal load and diversity in three tertiary care hospitals. Three indoor zones with different protection degree (unprotected admission halls and waiting rooms, clean regular patient rooms, and HEPA-protected intensive care units) are compared with the outdoor conditions, and the clinical relevance of the identified hospital fungi is discussed. Results of particle and colony counts were highly correlated and showed a common indoor decreasing gradient, from the most exposed and occupied zone near the entrances to the HEPA-protected zone, in the three hospitals and two 6-month-apart surveys.
They presented a high fungal diversity (74 genera) dominated by Cladosporium, Penicillium, Aspergillus, Alternaria and Aureobasidium, which were prevalent in different zones and substrata (air and surfaces). In addition, skin-associated yeasts such as Naganishia, Moliniella, Rhodotorula and Filobasidium were especially abundant in regular patient rooms. Based on previous clinical literature, 36 species were identified as opportunistic human pathogens including filamentous fungi (e.g. Aspergillus spp. Talaromyces spp. and Mucorales) and yeasts (e.g. Candida parapsilosis, Rhodotorula mucilaginosa, Filobasidium magnum and Clavispora lusitaniae). The generated culture collection, composed of 508 isolates from air (69 %) and surfaces (31 %), is a valuable resource for further research combining environmental and clinical mycology in buildings., This research is part of the Mycospitalomics project (grant PID2021–123184OA-I00), which is funded by MCIN/AEI/ 10.13039/501100011033 and ERDF - A way of making Europe. A.C. R-G's contract was funded by Instituto de Salud Carlos III (grant JR21/00061)., Peer reviewed

This dataset ("Mycospitalomycs_metabarcoding") includes all revevant files and R scripts to reproduce:
1) Data preparation - from the original OTU matrix, including technical replicates and control samples,
to the filtered fungal rarefied matrix; including the following these steps: (i) filtering Fungi, (ii) assessing the negative controls, (iii) assessing the mock community samples, (iv) assessing technical replicates, (v) plot OTUs vs Reads, (vi) rarefying the matrix, and (vii) preliminary NMDS ordination to find outliers.
2) Statistical analyses: (i) alpha diversity - fungal richness and other indices, (ii) beta diversity - NMDS ordination plots, (iii) PERMANOVA analyses to calculate the contribution of the key variables to explain the compositional variation of the mycobiomes, (iv) taxonomical descriptions, (v) Venn diagrams showig the indoor OTUs shared between hospitals and zones, (vi) qPCR data analysis, (vii) correlation matrix comparing variables related to eDNA, culturing and particle data, and (viii) indicator species associated with sample types and hospital zones.
The statistical-analyses R script reproduces all figures and tables showing results from this study. Some relevant output tables have been included in this dataset.
All dataset contents are detailed in the ReadMe file: "README_Mycospitalomics_metabarcoding", as well as other relevant information, Background: Hospitals are particularly sensitive environments where immunosuppressed patients might acquire invasive fungal infections (IFI). Therefore, it is necessary to carry out periodical environmental microbiological assessments that evaluate the fungal bioburden in air and surfaces from different hospital zones. Current microbiological monitoring protocols at healthcare settings are mostly based on cultivation, while environmental DNA (eDNA) assessments are still scarce and should be further evaluated. To fill this gap, this study combines a large sampling scheme, comprising > 200 samples (air, surface, dust and soil) collected from four zones at three Spanish hospitals in two campaigns (winter and autumn), with two eDNA approaches (DNA metabarcoding and quantitative PCR) to characterize the hospital mycobiomes (diversity, community composition and airborne load), compared to a parallel culture-dependent study.

Results: Fungal richness was significantly higher in soil and air samples compared to indoor surface samples (vents and high-touch surfaces), as well as in samples collected in winter compared those taken in autumn. Intensive care units showed lower fungal richness compared to regular patient rooms, waiting rooms and entrance halls. The most important explanatory factors for the variance in community composition were the hospital and zone where samples were collected, the type of sample, and the sampling campaign.

Hospital mycobiomes, represented by 1,900 OTUs, were affiliated to 4 phyla (mostly Ascomycota - 53 % and Basidiomycota - 41.3 %), 35 classes, 114 orders, 305 families, 643 genera, and 535 species. The dominant genera, in both air and surfaces samples from the three hospitals, were Cladosporium Alternaria, Aureobasidium, Penicillium, Neodidymelliopsis, Aspergillus, Pseudopithomyces and Stemphylium. The yeasts Candida and Clavispora were particularly abundant in high-touch surfaces indoors.

Conclusions: DNA metabarcoding revealed a much more comprehensive inventory of hospital fungi compared to culturing, however, both approaches found similar dominant taxa including a variety of potentially opportunistic human pathogens. DNA metabarcoding can assist hospital managers under certain demanding situations, e.g. construction works or reported microbial outbreaks, providing an in-depth characterization of hospital mycobiomes. In addition, qPCR proved to be a reliable method to quantify the fungal load in air samples, which can complement CFU and particle data in environmental assessments., Proyecto PID2021-123184OA-I00, No

Indoor fungi can cause negative health effects due to the production of toxins or volatiles that trigger the immune system of the occupants. To what degree indoor fungi (mycobiomes) differ between buildings with different usage is poorly known. Here, we compare the indoor mycobiomes in 123 children’s daycare centers and 214 private homes throughout Norway, as revealed by metabarcoding of DNA extracted from dust samples collected by community scientists. Although the fungal richness per se was similar in dust samples from daycares and homes, the fungal community composition differed. Yeast fungi, distributed mainly across the orders Saccharomycetales, Filobasidiales and Tremellales, were proportionally more abundant in the daycares, while filamentous fungi, including spore-producing molds such as Aspergillus, Penicillum and Cladosporium, were relatively more abundant in homes. Number of occupants, which is considerably higher in daycares, correlated significantly with the fungal community shift. We hypothesize that the density of occupants and their age distribution drive the systematic difference of yeasts and filamentous fungi in the two building types., European Union’s Horizon 2020 research and innovation program (Marie Skłodowska-Curie Individual Fellowship to PMM-S; grant agreement MycoIndoor No 741332). PMM-S also thanks the grant PID2021-123184OA-I00 funded by MCIN/AEI/ https://doi.org/10.13039/501100011033 and ERDF—A way of making Europe., Peer reviewed

10 páginas.- 4 figuras.- 60 referencias.- The online version contains supplementary material available at https://doi.org/10.1007/s00248-025-02505-4, Worldwide, people spend most of their time indoors; in their homes, workplaces, schools, and daycares. Indoor fungi can cause negative health effects due to the production of toxins or volatiles that trigger the immune system of the occupants. To what degree indoor fungi (mycobiomes) differ between buildings with different usage is poorly known. Here, we compare the indoor mycobiomes in 123 children’s daycare centers and 214 private homes throughout Norway, as revealed by metabarcoding of DNA extracted from dust samples collected by community scientists. Although the fungal richness per se was similar in dust samples from daycares and homes, the fungal community composition differed. Yeast fungi, distributed mainly across the orders Saccharomycetales, Filobasidiales, and Tremellales, were proportionally more abundant in the daycares, while filamentous fungi, including spore-producing molds such as Aspergillus, Penicillum, and Cladosporium, were relatively more abundant in homes. Number of occupants, which is considerably higher in daycares, correlated significantly with the fungal community shift. We hypothesize that the density of occupants and their age distribution drive the systematic difference of yeasts and filamentous fungi in the two building types., Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. The research was financially supported by the University of Oslo, the Norwegian Asthma and Allergy Association (NAAF), and the European Union’s Horizon 2020 research and innovation program (Marie Skłodowska-Curie Individual Fellowship to PMM-S; grant agreement MycoIndoor No 741332). PMM-S also thanks the grant PID2021-123184OA-I00 funded by MCIN/AEI/ https://doi.org/10.13039/501100011033 and ERDF—A way of making Europe., Peer reviewed

This article belongs to the Section Fungal Pathogenesis and Disease Control., [Data Availability Statement]
Raw sequencing data are available at the European Nucleotide Archive (ENA), EMBL-EBI, under the study accession no. PRJEB86993 (https://www.ebi.ac.uk/ena/browser/view/PRJEB86993; accessed on 2 July 2025). More details about the bioinformatics and statistical analyses of the complete DNA metabarcoding dataset are available at Zenodo (https://doi.org/10.5281/zenodo.15488704; accessed on 2 July 2025)., The genus Aspergillus, widely distributed across natural and urban environments, may cause allergies and opportunistic infections such as chronic or invasive pulmonary aspergillosis. Its high pathogenic potential for immunocompromised patients, together with the alarming increase of azole resistance reported in clinical and environmental isolates, claims urgent actions to assess and control the Aspergillus community in hospital environments. To contribute to that, here, we combine a large environmental survey covering numerous air and surface samples from different zones of three hospitals in Spain, with an integrated approach including general and selective culture- and eDNA-based analyses. Despite the high prevalence of Aspergillus observed, present in almost all indoor zones (mostly in air but also on surfaces) of the three hospitals, its relative abundance in the whole fungal community was limited and dependent on the used methods, with median values ranging from 1.4% (eDNA data) and 6.8% (cultivation at 28 °C) to 28.3% (cultivation at 37 °C). Remarkably, the most protected zones (intensive care units) showed the highest proportion of Aspergillus eDNA sequences. A total of 32 species belonging to 10 Aspergillus sections were molecularly identified, including well-known causal agents of invasive pulmonary infections such as A. fumigatus, A. flavus, A. terreus, A. niger, A. oryzae, A. sydowii, and A. tubingensis. This highlights the importance of such environmental assessments for monitoring and controlling the fungal burden in hospitals., This research is part of the Mycospitalomics project (grant PID2021-123184OA-I00), which is funded by MCIN/AEI/10.13039/501100011033 and ERDF—A way of making Europe., Peer reviewed

[Notes]
This dataset ("Mycospitalomycs_metabarcoding") includes all revevant files and R scripts to reproduce:

1) Data preparation - from the original OTU matrix, including technical replicates and control samples,
to the filtered fungal rarefied matrix; including the following these steps: (i) filtering Fungi, (ii) assessing the negative controls, (iii) assessing the mock community samples, (iv) assessing technical replicates, (v) plot OTUs vs Reads, (vi) rarefying the matrix, and (vii) preliminary NMDS ordination to find outliers.

2) Statistical analyses: (i) alpha diversity - fungal richness and other indices, (ii) beta diversity - NMDS ordination plots, (iii) PERMANOVA analyses to calculate the contribution of the key variables to explain the compositional variation of the mycobiomes, (iv) taxonomical descriptions, (v) Venn diagrams showig the indoor OTUs shared between hospitals and zones, (vi) qPCR data analysis, (vii) correlation matrix comparing variables related to eDNA, culturing and particle data, and (viii) indicator species associated with sample types and hospital zones.

The statistical-analyses R script reproduces all figures and tables showing results from this study. Some relevant output tables have been included in this dataset.

All dataset contents are detailed in the ReadMe file: "README_Mycospitalomics_metabarcoding", as well as other relevant information., [Background:]
Hospitals are particularly sensitive environments where immunosuppressed patients might acquire invasive fungal infections (IFI). Therefore, it is necessary to carry out periodical environmental microbiological assessments that evaluate the fungal bioburden in air and surfaces from different hospital zones. Current microbiological monitoring protocols at healthcare settings are mostly based on cultivation, while environmental DNA (eDNA) assessments are still scarce and should be further evaluated. To fill this gap, this study combines a large sampling scheme, comprising > 200 samples (air, surface, dust and soil) collected from four zones at three Spanish hospitals in two campaigns (winter and autumn), with two eDNA approaches (DNA metabarcoding and quantitative PCR) to characterize the hospital mycobiomes (diversity, community composition and airborne load), compared to a parallel culture-dependent study., [Results:]
Fungal richness was significantly higher in soil and air samples compared to indoor surface samples (vents and high-touch surfaces), as well as in samples collected in winter compared those taken in autumn. Intensive care units showed lower fungal richness compared to regular patient rooms, waiting rooms and entrance halls. The most important explanatory factors for the variance in community composition were the hospital and zone where samples were collected, the type of sample, and the sampling campaign., Hospital mycobiomes, represented by 1,900 OTUs, were affiliated to 4 phyla (mostly Ascomycota - 53 % and Basidiomycota - 41.3 %), 35 classes, 114 orders, 305 families, 643 genera, and 535 species. The dominant genera, in both air and surfaces samples from the three hospitals, were Cladosporium Alternaria, Aureobasidium, Penicillium, Neodidymelliopsis, Aspergillus, Pseudopithomyces and Stemphylium. The yeasts Candida and Clavispora were particularly abundant in high-touch surfaces indoors., [Conclusions:]
DNA metabarcoding revealed a much more comprehensive inventory of hospital fungi compared to culturing, however, both approaches found similar dominant taxa including a variety of potentially opportunistic human pathogens. DNA metabarcoding can assist hospital managers under certain demanding situations, e.g. construction works or reported microbial outbreaks, providing an in-depth characterization of hospital mycobiomes. In addition, qPCR proved to be a reliable method to quantify the fungal load in air samples, which can complement CFU and particle data in environmental assessments., Agencia Estatal de Investigación
Unraveling the hospital mycobiomes associated with the invasive fungal infections and the emergence of antimicrobial resistancePID2021-123184OA-I, Peer reviewed

18 páginas.- 5 figuras.- 2 tablas.- 75 referencias.- The online version contains supplementary material available at https://doi.org/10.1007/s00248-025-02626-w, Hospitals are particularly sensitive environments where immunosuppressed patients might acquire invasive fungal infections. Therefore, it is necessary to carry out periodical environmental microbiological assessments that evaluate the fungal bioburden in air and surfaces from different hospital zones. Current microbiological monitoring protocols at healthcare settings are mostly based on cultivation, while environmental DNA (eDNA) assessments are still scarce and should be further evaluated. To fill this gap, this study combines a large sampling scheme, comprising > 200 samples (air, surface, dust and soil) collected from four zones at three Spanish hospitals in two campaigns (winter and autumn), with two eDNA approaches (DNA metabarcoding and quantitative PCR) to characterize the hospital mycobiomes (diversity, community composition and airborne load), compared to a parallel culture-dependent study. DNA metabarcoding revealed a much more comprehensive inventory of hospital fungi compared to culturing; however, both approaches found similar dominant taxa including a variety of potentially opportunistic human pathogens. Hospital mycobiomes were affiliated to 4 phyla (mostly Ascomycota and Basidiomycota), 35 classes, 114 orders, 305 families, 643 genera and 535 species. The dominant genera, in both air and surfaces from the three hospitals, were Cladosporium, Alternaria, Aureobasidium, Penicillium, Neodidymelliopsis, Aspergillus, Pseudopithomyces and Stemphylium. The yeasts Candida and Clavispora were particularly abundant on high-touch surfaces indoors. The most important explanatory factors for the variance in community composition were the hospital and zone where samples were collected, the type of sample and the sampling campaign. DNA metabarcoding can assist hospital managers by providing an in-depth characterization of the baseline hospital mycobiome during normal operating conditions, as well as identifying and controlling community imbalances and associated health risks under demanding situations such as construction works or reported clinical outbreaks., Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This research is part of the Mycospitalomics project (grant PID2021-123184OA-I00), which is funded by MCIN/AEI/https://doi.org/10.13039/501100011033 and ERDF—A way of making Europe., Peer reviewed