DOI: 10.5281/zenodo.15488703
title: Contribution of DNA metabarcoding to the environmental fungal assessments in hospitals

description: 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.
description: 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.