The presence of fungi in the indoor environment is associated with allergies and other respiratory symptoms. The aim of this study was to use sequencing and molecular methods, including next-generation sequencing (NGS) approaches, to explore the bacterial and fungal communities and their abundance in the indoor environment of houses (n = 20) with visible "moldy" (HVM) and nonvisible "non-moldy" (HNM) in Memphis, TN, USA. Dust samples were collected from air vents and ground surfaces, and the total DNA was analyzed for bacteria and fungi by amplifying 16S rRNA and ITS genes on the Illumina Miseq. Results indicated that Leptosphaerulina was the most abundant fungal genus present in the air vent and ground samples from HNM and HVM. At the same time, the most abundant bacterial genera in the air vent and ground samples were Propionibacterium and Streptococcus. The fungi community diversity was significantly different in the air vent samples. The abundance of fungal species known to be associated with respiratory diseases in indoor dust samples was similar, regardless of the visibility of fungi in the houses. The existence of fungi associated with respiratory symptoms was compared with several parameters like dust particulate matter (PM), CO2 level, temperature, and humidity. Most of these parameters are either positively or negatively correlated with the existence of fungi associated with respiratory diseases; however, none of these correlations were significant at p = 0.05. Our results indicate that implementing molecular methods for detecting indoor fungi may strengthen common exposure and risk assessment practices.
Keywords: NGS; bacterial communities; fungal communities; indoor environments; qRT-PCR.