Computational methods for 16S metabarcoding studies using Nanopore sequencing data

Assessment of bacterial diversity through sequencing of 16S ribosomal RNA (16S rRNA) genes has been an approach widely used in environmental microbiology, particularly since the advent of high-throughput sequencing technologies. An additional innovation introduced by these technologies was the need of developing new strategies to manage and investigate the massive amount of sequencing data generated. This situation stimulated the rapid expansion of the field of bioinformatics with the release of new tools to be applied to the downstream analysis and interpretation of sequencing data mainly generated using Illumina technology. In recent years, a third generation of sequencing technologies has been developed and have been applied in parallel and complementarily to the former sequencing strategies. In particular, Oxford Nanopore Technologies (ONT) introduced nanopore sequencing which has become very popular among molecular ecologists. Nanopore technology offers a low price, portability and fast sequencing throughput. This powerful technology has been recently tested for 16S rRNA analyses showing promising results. However, compared with previous technologies, there is a scarcity of bioinformatic tools and protocols designed specifically for the analysis of Nanopore 16S sequences. Due its notable characteristics, researchers have recently started performing assessments regarding the suitability MinION on 16S rRNA sequencing studies, and have obtained remarkable results. Here we present a review of the state-of-the-art of MinION technology applied to microbiome studies, the current possible application and main challenges for its use on 16S rRNA metabarcoding. Crown Copyright (C) 2020 Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.