Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Exploring Quantitative Metagenomics Studies Using Oxford Nanopore Sequencing: A Computational and Experimental Protocol

Version 1 : Received: 3 August 2021 / Approved: 4 August 2021 / Online: 4 August 2021 (09:44:24 CEST)

How to cite: Alili, R.; Belda, E.; Le, P.; Wirth, T.; Zucker, J.; Prifti, E.; Clement, K. Exploring Quantitative Metagenomics Studies Using Oxford Nanopore Sequencing: A Computational and Experimental Protocol. Preprints 2021, 2021080104 (doi: 10.20944/preprints202108.0104.v1). Alili, R.; Belda, E.; Le, P.; Wirth, T.; Zucker, J.; Prifti, E.; Clement, K. Exploring Quantitative Metagenomics Studies Using Oxford Nanopore Sequencing: A Computational and Experimental Protocol. Preprints 2021, 2021080104 (doi: 10.20944/preprints202108.0104.v1).

Abstract

Background: The gut microbiome plays a major role in chronic diseases, of which several are characterized by an altered composition and diversity of bacterial communities. Large-scale sequencing projects allowed characterizing the perturbations of these communities. However, translating these discoveries into clinical applications remains a challenges. To facilitate routine implementation of microbiome profiling in clinical settings, portable, real-time, and low-cost sequencing technologies are needed. Results: Here, we propose a computational and experimental protocol for whole genome quantitative metagenomics studies of human gut microbiome with Oxford Nanopore sequencing technology (ONT) that could be applied to other microbial ecosystems. We developed a bioinformatic protocol to analyse ONT sequences taxonomically and functionally and optimized pre-analytic protocols including stool collection and DNA extraction methods to maximize read length. This is a critical parameter for the sequence alignment and classification. Our protocol was evaluated using simulations of metagenomic communities which reflect naturally occuring compositional variations. Next, we validated both protocols using stool samples from a bariatric surgery cohort, sequenced with ONT, Illumina and SOLiD technologies. Results revealed similar diversity and microbial composition profiles. Conclusion: This protocol can be implemented in the clinical or research setting, bringing rapid personalized whole genome profiling of target microbiome species.

Keywords

quantitative metagenomics; microbiome; obesity; gut microbiota; microbial DNA extraction; sequencing; Simulation; Oxford Nanopore Technologies; MinION

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