Abstract
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 for characterizing the perturbations of these communities. However, translating these discoveries into clinical applications remains a challenge. To facilitate routine implementation of microbiome profiling in clinical settings, portable, real-time, and low-cost sequencing technologies are needed. Here, we propose a computational and experimental protocol for whole-genome semi-quantitative metagenomic studies of human gut microbiome with Oxford Nanopore sequencing technology (ONT) that could be applied to other microbial ecosystems. We developed a bioinformatics protocol to analyze ONT sequences taxonomically and functionally and optimized preanalytic 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 occurring 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. This protocol can be implemented in a clinical or research setting, bringing rapid personalized whole-genome profiling of target microbiome species.
Highlights
In recent years, there has been a burst in knowledge related to gut microbiota screening in chronic diseases
Previous studies have proposed similar approaches based on Centrifuge for the real-time metagenomic profiling from Oxford Nanopore sequencing technology (ONT) data [13] and for the metagenomic profiling of fecal and oral swabs [41], but not allowing functional profiling or metagenomic profiling using nonredundant gut microbiome gene catalogs that maximize the genomic knowledge of the gut microbiome ecosystem
Through accurate assessment of experimental and bioinformatics steps, our current work demonstrates that this technology is suitable to carry out semi-quantitative metagenomic studies in the human gut microbiome
Summary
There has been a burst in knowledge related to gut microbiota screening in chronic diseases. The increasing access to high-throughput sequencing has led to the discovery of alterations in the composition of intestinal microbiota in many human disorders, including metabolic diseases. In mild [8] and severe obesity [9], for instance, we previously showed that reduced microbial gene richness linked to altered composition was found in 40% to 75% of the subjects and was associated with a more deleterious host phenotype. Even with these established signatures in metabolic diseases, the gut microbiome varies greatly in composition and abundance from one individual to another
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