Summary

Exposure to bioaerosols in workplaces can have an impact on the development of respiratory diseases, and moulds appear to play a prominent role in this regard. Some workplaces, owing to the activities conducted there, generate large quantities of aerosols (including moulds) stemming from the materials in the environment. Factors such as the relative humidity and type of ventilation in a building may increase the effect of exposure to moulds in contaminated environments. In this study, the presence of moulds in the air was first confirmed using culture analysis methods. These classical methods introduce a bias, both qualitative and quantitative, in the representation of fungal diversity. Culture analysis methods do not allow assessment of the real risks workers face when exposed to non-viable and/or non-cultivatable moulds in bioaerosols. This is a serious shortcoming in the knowledge available about the fungal diversity of bioaerosols. Unlike culture and quantification by specific PCR (polymerase chain reaction) amplification, taxonomic analysis methods using next-generation DNA sequencing can be used for the quantitative and qualitative study of fungal diversity in the air. These new high-throughput sequencing approaches require the use of a standardized segment of the genome in order to be able to provide a diversity profile for each sample. For the study of bacteria, the universal marker used is the gene coding for 16S rRNA. However, using DNA sequences to identify moulds raises the problem of choosing which region of the genome to use. Unless a perfect genomic region is available, the different sequences proposed as primary fungal barcode markers, which have been studied by the scientific community for many years now, each have advantages and disadvantages. The gene coding for the ITS (Internal Transcribed Spacer) region is the primary fungal barcode marker chosen by the Consortium for the Barcode of Life (CBOL). The ITS is a region on eukaryotic genomic DNA between the genes coding for 28S and 18S rRNA. It consists of three subregions: ITS1, ITS2 and gene 5.8S.

To explore the association between bioaerosols, exposure to moulds and the effects on respiratory health, the main objective of this research project was to propose an analytical method for quantitatively determining the fungal diversity of bioaerosols, regardless of their culture. More specifically, two fungal genomic markers, ITS1 and ITS2, were targeted by the next-generation sequencing approach to compare their effectiveness at describing an environment’s fungal diversity.

To do so, particularly mould-contaminated air was sampled in three work environments. Composting and biomethanation sites were used to develop the sample-processing method, as well as to identify the fungal DNA regions to target to ensure broad diversity. Next, a pilot environment (dairy farms) was used to compare the method’s performance with that of classical culture techniques.

Millions of sequences obtained by sequencing DNA extracted from the samples were processed by following a bioinformatics protocol developed specifically for the project. The results indicated higher fungal richness and diversity when the gene coding for the ITS1 region was used. They were confirmed when the approach developed for compost was applied to the samples taken from biomethanation plants. Thanks to the method’s robustness, it was possible to describe worker exposure in these two environments characterized by waste processing. The identification of mould types having pathogenic or allergenic potential in work environment air samples suggests the need to implement safeguards for workers. Subsequently, adapting the approach developed, including the bioinformatics protocol for data processing and the microbial ecology analysis, helped to describe the fungal composition of the pilot environment. The five dairy farms sampled had different fungal profiles, indicating the influence of the type of building and cow diet on the fungal composition of the air samples. The culture methods made it possible to describe certain species not detected by the sequencing methods, a phenomenon well documented in bacteriology. However, fungal richness and diversity are very low when these culture methods are used. They omit a large number of types of moulds in their description of the fungal diversity of bioaerosols.

As a complement to the technique currently used, the method developed here produced a much more exhaustive and accurate picture of the fungal biodiversity of the air and contributed to an understanding of the strengths, weaknesses and complementarity of the available methods. It could also be used to study the fungal diversity of bioaerosols in indoor and outdoor air.

The use of this approach in a growing number of protocols and environments will help document an essential aspect of our understanding of the role of moulds in the air, in connection with occupational pulmonary diseases, as well as provide solid data essential to studies of human exposure to bioaerosols.