M-CAMP^TM: A Cloud-based Web Platform with a Novel Approach for Species-level Classification of 16S rRNA Microbiome Sequences

Background: The M-CAMP^TM (Microbiome Computational Analysis for Multi-omic Profiling) Cloud Platform was designed to provide users with an easy-to-use web interface to access best in class microbiome analysis tools. This interface allows bench scientists to conduct bioinformatic analysis on their samples and then download publication-ready graphics and reports. Objective: In this study, we aim to describe the M-CAMP^TM platform and demonstrate that the taxonomic classification is more accurate than previously described methods on a wide range of microbiome samples. Methods: The core pipeline of the platform is the 16S-seq taxonomic classification algorithm which provides species-level classification of Illumina 16s sequencing. This algorithm uses a novel approach combining alignment and kmer-based taxonomic classification methodologies to produce a highly accurate and comprehensive profile. Additionally, a comprehensive proprietary database combining reference sequences from multiple sources was curated and contained 18056 unique V3-V4 sequences covering 11527 species. Results and Discussion: The M-CAMP^TM 16S taxonomic classification algorithm evaluated 52 sequencing samples from both public and in-house standard sample mixtures with known fractions. The same evaluation process was also performed on 5 well-known 16S taxonomic classification algorithms, including Qiime2, Kraken2, Mapseq, Idtaxa and Spingo, using the same dataset. Results have been discussed in terms of evaluation metrics and classified taxonomic levels. Conclusion: Compared to current popular publicly accessible classification algorithms, M-CAMP^TM 16S taxonomic classification algorithm provides the most accurate species-level classification of 16S rRNA sequencing data.