Microbial contamination in firefighter headquarters’: a neglected occupational exposure scenario

Project “Occupational exposure of ambulance drivers to bioburden” (IPL/2020/BIO-AmbuDrivers_ESTeSL)FCT_UIDB/05608/2020. FCT_UIDP/05608/2020.One of the occupational environments that need intervention to overcome the lack of information concerning exposure to biological agents is the Firefighter Headquarters’ (FFH). This study intends to assess the microbial contamination in Portuguese FFH with a multi-approach protocol for sampling and analyses using active (air samples by impaction and impingement) and passive (surface swabs collected as swabs, settled dust, cleaning cloths and mops, electrostatic dust cloths, and identification badges) sampling methods. The fungal contamination was also characterized through molecular detection of toxigenic species, antifungal resistance, and mycotoxins profile. Cytotoxicity assessment was included in specific cells line using the MTT assay in order to recognize the possible health effects. It was raised concern regarding the following findings: a) microbial contamination didn't comply with Portuguese IAQ legal requirements in most of the FFH (bacteria load 63.63%, fungal load 45.45%); b) fungal exposure through inhalation underlining a possible risk factor for respiratory diseases; c) prevalence of Aspergillus sp. in cleaning materials that might represent a potential source of cross-contamination; d) widespread of Aspergillus section Fumigati in all the FFH analysed; e) trend of multidrug resistance found among fungi with a focus on Fumigati isolates; f) detection of several mycotoxins (fumonisin B2, nivalenol, mycophenolic acid, and sterigmatocystin) and; g) potential role of Aspergillus genus in the cytotoxicity found, particularly in lung cells. The multi-approach on sampling methods (active and passive) and laboratory assays (culture based-methods, molecular tools, mycotoxins detection, cytotoxicity evaluation) improved data findings, enabling a more detailed and accurate risk characterization.