GroopM: an automated tool for the recovery of population genomes from related metagenomes

Imelfort, Michael; Parks, Donovan H.; Woodcroft, Ben J.; Dennis, Paul G.; Hugenholtz, Philip; Tyson, Gene W.

doi:10.7717/peerj.603

Cited by 249 publications

(151 citation statements)

References 30 publications

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“…Nonetheless, initial attempts to reconstruct member genomes in very-low-diversity communities or abundant members of complex communities were successful (5, 6). Innovations in sequence assembly (7-9), the use of differential coverage binning (10, 11), parsing mate pair linkages (12), and improved methods of evaluating sequence composition (13,14) continue to improve our ability to reconstruct genomes from community metagenomic samples. These improvements are revolutionizing microbial ecology by enabling species-resolved genomic analysis of organisms without the need for prior cultivation, thus providing a mechanism for prediction and modeling of ecosystem function for communities that were previously intractable.…”

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confidence: 99%

Identification and Resolution of Microdiversity through Metagenomic Sequencing of Parallel Consortia

Nelson

Maezato

et al. 2016

Appl Environ Microbiol

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cTo gain a predictive understanding of the interspecies interactions within microbial communities that govern community function, the genomic complement of every member population must be determined. Although metagenomic sequencing has enabled the de novo reconstruction of some microbial genomes from environmental communities, microdiversity confounds current genome reconstruction techniques. To overcome this issue, we performed short-read metagenomic sequencing on parallel consortia, defined as consortia cultivated under the same conditions from the same natural community with overlapping species composition. The differences in species abundance between the two consortia allowed reconstruction of near-complete (at an estimated >85% of gene complement) genome sequences for 17 of the 20 detected member species. Two Halomonas spp. indistinguishable by amplicon analysis were found to be present within the community. In addition, comparison of metagenomic reads against the consensus scaffolds revealed within-species variation for one of the Halomonas populations, one of the Rhodobacteraceae populations, and the Rhizobiales population. Genomic comparison of these representative instances of inter-and intraspecies microdiversity suggests differences in functional potential that may result in the expression of distinct roles in the community. In addition, isolation and complete genome sequence determination of six member species allowed an investigation into the sensitivity and specificity of genome reconstruction processes, demonstrating robustness across a wide range of sequence coverage (9؋ to 2,700؋) within the metagenomic data set. Microdiversity refers to the diversity of organisms that are closely related phylogenetically yet exhibit different metabolic activities and therefore occupy distinct niches. Genomic studies comparing multiple strains of the same species have revealed that while much of the genome sequence is highly conserved, significant functional variation can exist, arising from changes in gene function due to mutation, the introduction of genes by horizontal gene transfer, or changes in gene regulation due to mutation or genome rearrangement. Microbial community diversity is usually measured via sequencing of either all or a part of the 16S rRNA gene. It is well established that bacteria that have near-identical or identical 16S rRNA sequences can have significantly divergent genome complements, cell morphologies, and metabolic functions (1-4).Recent developments in sequencing technologies and analysis have enabled cultivation-independent sequencing of intact microbial communities (metagenomics) and prediction of functional potential of individual microbial populations within a community. Early metagenomic work employed the same technology used for isolate genome sequencing, the Sanger method, which provided only a limited sequencing depth. Nonetheless, initial attempts to reconstruct member genomes in very-low-diversity communities or abundant members of complex communities were successful (5, 6)....

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confidence: 99%

Identification and Resolution of Microdiversity through Metagenomic Sequencing of Parallel Consortia

Nelson

Maezato

et al. 2016

Appl Environ Microbiol

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“…Some are trained on reference sequences, using contig k-mer frequencies or sequence similarities as sources of information (McHardy et al, 2007;Dröge, Gregor & McHardy, 2014;Wood & Salzberg, 2014;Gregor et al, 2016), which can be adapted to specific ecosystems. Others cluster the contigs into genome bins, using contig k-mer frequencies and read coverage (Chatterji et al, 2008;Kislyuk et al, 2009;Wu et al, 2014;Nielsen et al, 2014;Imelfort et al, 2014;Alneberg et al, 2014;Kang et al, 2015;Lu et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

A probabilistic model to recover individual genomes from metagenomes

Dröge

Schönhuth

McHardy

2017

PeerJ Computer Science

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Shotgun metagenomics of microbial communities reveal information about strains of relevance for applications in medicine, biotechnology and ecology. Recovering their genomes is a crucial but very challenging step due to the complexity of the underlying biological system and technical factors. Microbial communities are heterogeneous, with oftentimes hundreds of present genomes deriving from different species or strains, all at varying abundances and with different degrees of similarity to each other and reference data. We present a versatile probabilistic model for genome recovery and analysis, which aggregates three types of information that are commonly used for genome recovery from metagenomes. As potential applications we showcase metagenome contig classification, genome sample enrichment and genome bin comparisons. The open source implementation MGLEX is available via the Python Package Index and on GitHub and can be embedded into metagenome analysis workflows and programs.

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“…Furthermore, de-novo assembly is increasingly being used to derive nearly complete genomes of previously unknown ecologically important organisms from metagenomes (Garza and Dutilh, 2015;Hugerth et al, 2015). A growing number of assemblers (Boisvert et al, 2012;Peng et al, 2012) and binning tools (Alneberg et al, 2014;Imelfort et al, 2014;Nurk et al, 2017) are available that assemble short sequencing reads into larger contigs and subsequently combine them into bins based on, for example, sequence similarity (Teeling and Glöckner, 2012). In addition to standard biodiversity metrics such as alpha, beta, and gamma diversity (Escobar-Zepeda et al, 2015;Zhou et al, 2015), network analysis tools aid visualization of complex ecological relationships (Mitra et al, 2010;Hurwitz et al, 2014).…”

Section: Dna Sequencing Applied To Marine Monitoring Technical Contextmentioning

confidence: 99%

DNA Sequencing as a Tool to Monitor Marine Ecological Status

et al. 2017

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Many ocean policies mandate integrated, ecosystem-based approaches to marine monitoring, driving a global need for efficient, low-cost bioindicators of marine ecological quality. Most traditional methods to assess biological quality rely on specialized expertise to provide visual identification of a limited set of specific taxonomic groups, a time-consuming process that can provide a narrow view of ecological status. In addition, microbial assemblages drive food webs but are not amenable to visual inspection and thus are largely excluded from detailed inventory. Molecular-based assessments of biodiversity and ecosystem function offer advantages over traditional methods and are increasingly being generated for a suite of taxa using a "microbes to mammals" or "barcodes to biomes" approach. Progress in these efforts coupled with continued improvements in high-throughput sequencing and bioinformatics pave the way for sequence data to be employed in formal integrated ecosystem evaluation, including food web assessments, as called for in the European Union Marine Strategy Framework Directive. DNA sequencing of bioindicators, both traditional (e.g., benthic macroinvertebrates, ichthyoplankton) and emerging (e.g., microbial assemblages, fish via eDNA), promises to improve assessment of marine biological quality by increasing the breadth, depth, and throughput of information and by reducing costs and reliance on specialized taxonomic expertise.

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GroopM: an automated tool for the recovery of population genomes from related metagenomes

Cited by 249 publications

References 30 publications

Identification and Resolution of Microdiversity through Metagenomic Sequencing of Parallel Consortia

Identification and Resolution of Microdiversity through Metagenomic Sequencing of Parallel Consortia

A probabilistic model to recover individual genomes from metagenomes

DNA Sequencing as a Tool to Monitor Marine Ecological Status

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