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. 2015 Jul 1:16:203.
doi: 10.1186/s12859-015-0595-z.

BioMaS: a modular pipeline for Bioinformatic analysis of Metagenomic AmpliconS

Bruno Fosso  1 , Monica Santamaria  2 , Marinella Marzano  3 , Daniel Alonso-Alemany  4 , Gabriel Valiente  5 , Giacinto Donvito  6 , Alfonso Monaco  7 , Pasquale Notarangelo  8 , Graziano Pesole  9   10   11
Affiliations

BioMaS: a modular pipeline for Bioinformatic analysis of Metagenomic AmpliconS

Bruno Fosso et al. BMC Bioinformatics. .

Abstract

Background: 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. 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.

Results: BioMaS (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).

Conclusion: BioMaS 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.

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Figures

Figure 1
Figure 1
BioMaS 454 version. BioMaS workflow for the analysis of Roche 454 data.
Figure 2
Figure 2
BioMaS Illumina version. BioMaS workflow for the analysis of Illumina paired-end reads.
Figure 3
Figure 3
Results of the comparative analysis of BioMaS, QIIME and Mothur platforms. Red, blue and green columns indicate the total number of assigned sequences by BioMaS, QIIME and Mothur, respectively. Alternating with the first ones, light red, light blue and light green columns indicate the number of sequences that are correctly annotated by the three methods. The figure is divided in 4 sections, as follows: a) Illumina Bacteria test case, b) Roche 454 Bacteria test case, c) Illumina Fungi test case, and d) Roche 454 Fungi test case.
See this image and copyright information in PMC

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