Background: The gut microbiome plays a major role in chronic diseases, several of which are characterized by an altered diversity and composition of bacterial communities. Large-scale sequencing projects allowed the characterization of these microbial community perturbations. However, a gap remains in how these discoveries can be translated into clinical applications. 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 the human gut microbiome with Oxford Nanopore sequencing technology (ONT). We developed a bioinformatic pipeline to process ONT sequences based on the evaluation of different alignment parameters in the estimation of microbial diversity and composition. We also optimized stool collection and DNA extraction methods to maximize read length, a critical parameter for the sequence alignment and classification. Our analytical pipeline was evaluated using simulations of metagenomic communities to reflect naturally occuring compositional variations. We then validated our experimental and analytical pipeline with stool samples from a bariatric surgery cohort sequenced with ONT and Illumina, revealing comparable diversity and microbial composition profiles. These results were compared to those previously obtained with SOLiD sequencing, where differences were observed, possibly explained by variations in library preparation steps. Finally, we found that sequences obtained with ONT allowed assembly of complete genomes for disease-related species.
Conclusion: This protocol can be implemented in the clinical or individual 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.