ORCID Profile
0000-0003-1099-8735
Current Organisation
Institut Pasteur
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Publisher: Springer Science and Business Media LLC
Date: 23-07-2021
DOI: 10.1038/S41467-021-24515-9
Abstract: High-throughput short-read metagenomics has enabled large-scale species-level analysis and functional characterization of microbial communities. Microbiomes often contain multiple strains of the same species, and different strains have been shown to have important differences in their functional roles. Recent advances on long-read based methods enabled accurate assembly of bacterial genomes from complex microbiomes and an as-yet-unrealized opportunity to resolve strains. Here we present Strainberry, a metagenome assembly pipeline that performs strain separation in single-s le low-complexity metagenomes and that relies uniquely on long-read data. We benchmarked Strainberry on mock communities for which it produces strain-resolved assemblies with near-complete reference coverage and 99.9% base accuracy. We also applied Strainberry on real datasets for which it improved assemblies generating 20-118% additional genomic material than conventional metagenome assemblies on in idual strain genomes. We show that Strainberry is also able to refine microbial ersity in a complex microbiome, with complete separation of strain genomes. We anticipate this work to be a starting point for further methodological improvements on strain-resolved metagenome assembly in environments of higher complexities.
Publisher: Springer Science and Business Media LLC
Date: 04-2022
DOI: 10.1038/S41592-022-01431-4
Abstract: Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.
Publisher: Cold Spring Harbor Laboratory
Date: 25-02-2021
DOI: 10.1101/2021.02.24.429166
Abstract: High-throughput short-read metagenomics has enabled large-scale species-level analysis and functional characterization of microbial communities. Microbiomes often contain multiple strains of the same species, and different strains have been shown to have important differences in their functional roles. Despite this, strain-level resolution from metagenomic sequencing remains challenging. Recent advances on long-read based methods enabled accurate assembly of bacterial genomes from complex microbiomes and an as-yet-unrealized opportunity to resolve strains. Here we present Strainberry, a metagenome assembly method that performs strain separation in single-s le low-complexity metagenomes and that relies uniquely on long-read data. We benchmarked Strainberry on mock communities and showed it consistently produces strain-resolved assemblies with near-complete reference coverage and 99.9% base accuracy. We also applied Strainberry on real datasets for which it improved assemblies generating 20-118% additional genomic material than conventional metagenome assemblies on in idual strain genomes. Our results hence demonstrate that strain separation is possible in low-complexity microbiomes using a single regular long read dataset. We show that Strainberry is also able to refine microbial ersity in a complex microbiome, with complete separation of strain genomes. We anticipate this work to be a starting point for further methodological improvements aiming to provide better strain-resolved metagenome assemblies in environments of higher complexities.
No related grants have been discovered for Rayan Chikhi.