Comparison of QIIME1 and QIIME2 for Analyzing Fungal Samples from Various Built Environments

This study evaluates the differences between bioinformatics pipelines by analyzing samples collected from various built environments. Previous comparative studies of microbial community analysis pipelines have largely focused on bacterial communities, mock communities, or soil fungi, often with small sample sizes, and have not specifically targeted built environments. Our results highlight key differences between OTU (QIIME1) and ASV (QIIME2) analyses. OTU analysis clusters OTUs at 97% similarity and tends to show higher diversity values in diversity analyses. Regarding abundantly detected fungi, OTU analysis identified more genera than ASV analysis. However, the OTU method has a high rate of false positives and false negatives, indicating low error-removal capability and suggesting that many fungal genera may have been detected. Therefore, a combined approach using OTU analysis combined with ASV analysis allows for both the comprehensive detection of dominant taxa and the inclusion of rare species. Overall, our findings emphasize that the choice of pipeline significantly influences the composition of the observed fungal community in built environments. Careful consideration of both OTU and ASV strategies can enhance the reliability and completeness of fungal metabarcoding studies, particularly when studying complex indoor microbial communities.