Bhatttacharyya, M.; Rauer, L.; Reiger, M.; Afgani, J.; Huelpuesch, C.; Traidl-Hoffmann, C.; Neumann, A. U.

Identification of microbial species is essential for the generation of meaningful results from microbiome analysis. However, annotation of 16S microbial sequences down to the species level presents a challenge because most available databases of 16S sequences are not well curated. AnnotIEM is a new tool for species level annotation of sequences derived from 16S rRNA sequencing. A novel hit selection algorithm is used to combine the alignment results from multiple databases. Benchmarking using mock community control datasets proved that AnnotIEM annotation precision is greater than 80% on species level, better than any currently available annotation tool. Benchmarking using a number of real microbiome studies demonstrated that annotation by AnnotIEM gave rise to higher fraction of sequences annotated on species level (60-80%), as compared to any other currently available tool. In conclusion, AnnotIEM significantly improves microbiome annotation, which can greatly enhance the results of any microbiome analysis study, and can be potentially used also for other organisms