Abstract
BackgroundSubstantial advances in microbiology, molecular evolution and biodiversity have been carried out in recent years thanks to Metagenomics, which allows to unveil the composition and functions of mixed microbial communities in any environmental niche. If the investigation is aimed only at the microbiome taxonomic structure, a target-based metagenomic approach, here also referred as Meta-barcoding, is generally applied. This approach commonly involves the selective amplification of a species-specific genetic marker (DNA meta-barcode) in the whole taxonomic range of interest and the exploration of its taxon-related variants through High-Throughput Sequencing (HTS) technologies. The accessibility to proper computational systems for the large-scale bioinformatic analysis of HTS data represents, currently, one of the major challenges in advanced Meta-barcoding projects.ResultsBioMaS (Bioinformatic analysis of Metagenomic AmpliconS) is a new bioinformatic pipeline designed to support biomolecular researchers involved in taxonomic studies of environmental microbial communities by a completely automated workflow, comprehensive of all the fundamental steps, from raw sequence data upload and cleaning to final taxonomic identification, that are absolutely required in an appropriately designed Meta-barcoding HTS-based experiment. In its current version, BioMaS allows the analysis of both bacterial and fungal environments starting directly from the raw sequencing data from either Roche 454 or Illumina HTS platforms, following two alternative paths, respectively. BioMaS is implemented into a public web service available at https://recasgateway.ba.infn.it/ and is also available in Galaxy at http://galaxy.cloud.ba.infn.it:8080 (only for Illumina data).ConclusionBioMaS is a friendly pipeline for Meta-barcoding HTS data analysis specifically designed for users without particular computing skills. A comparative benchmark, carried out by using a simulated dataset suitably designed to broadly represent the currently known bacterial and fungal world, showed that BioMaS outperforms QIIME and MOTHUR in terms of extent and accuracy of deep taxonomic sequence assignments.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0595-z) contains supplementary material, which is available to authorized users.
Highlights
Substantial advances in microbiology, molecular evolution and biodiversity have been carried out in recent years thanks to Metagenomics, which allows to unveil the composition and functions of mixed microbial communities in any environmental niche
Bioinformatic analysis of Metagenomic ampliconS (BioMaS) web service BioMaS has been implemented as web-application at https://recasgateway.ba.infn.it/ and its Illumina version is available in Galaxy at http://galaxy.cloud.ba.infn. it
Researchers face with the non-trivial difficulty to select, use and integrate all the most suitable tools to obtain correct inferences, and in some cases new software development is needed for such purpose
Summary
Substantial advances in microbiology, molecular evolution and biodiversity have been carried out in recent years thanks to Metagenomics, which allows to unveil the composition and functions of mixed microbial communities in any environmental niche. Researchers involved in advanced metagenomics projects need both powerful computational infrastructures and, in most cases, robust informatics know-how in order to use and combine the most suitable tools needed for filtering, denoising, clustering, and assigning to taxonomic ranks the huge amount of sequence reads generated by HTS. These computational operations are all essential in order to obtain a consistent taxonomic classification starting from raw Meta-barcoding HTS data. The possible occurrence of sequencing errors, specific for each HTS platform used in the experiment requires suitable preliminary steps for quality check and denoising in order to avoid misleading inferences
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