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Bioinformatics tools to assess metagenomic data for applied microbiology


The reduction of the price of DNA sequencing has resulted in the emergence of large data sets to handle and analyze, especially in microbial ecosystems, which are characterized by high taxonomic and functional diversities. To assess the properties of these complex ecosystems, a conceptual background of the application of NGS technology and bioinformatics analysis to metagenomics is required. Accordingly, this article presents an overview of the evolution of knowledge of microbial ecology from traditional culture-dependent methods to culture-independent methods and the last frontier in knowledge, metagenomics. Topics that will be covered include sample preparation for NGS, starting with total DNA extraction and library preparation, followed by a brief discussion of the chemistry of NGS to help provide an understanding of which bioinformatics pipeline approach may be helpful for achieving a researcher’s goals. The importance of selecting appropriate sequencing coverage and depth parameters to obtain a suitable measure of microbial diversity is discussed. As all DNA sequencing processes produce base-calling errors that compromise data analysis, including genome assembly and microbial functional analysis, dedicated software is presented and conceptually discussed with regard to potential applications in the general microbial ecology field.

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ECP De Martinis is a fellow of National Council for Scientific and Technological Development, Brazil (grant #6762/2006-4) and she is grateful for a Research Grant from São Paulo Research Foundation (FAPESP), Brazil (grant # 2017/18928-0). OGG Almeida is grateful to São Paulo Research Foundation (FAPESP), Brazil, for a Ph.D. fellowship (grant #2017/13759-6).


This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

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Correspondence to Elaine C. P. De Martinis.

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Almeida, O.G.G., De Martinis, E.C.P. Bioinformatics tools to assess metagenomic data for applied microbiology. Appl Microbiol Biotechnol 103, 69–82 (2019).

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  • Metagenomics
  • NGS
  • Applied bioinformatics
  • Microbial diversity