Evidence map›Paper›PMID 29183281›Full record

ArticleBMC genomics2017

Optimizing and evaluating the reconstruction of Metagenome-assembled microbial genomes.

Bhavya Papudeshi, J Matthew Haggerty, Michael Doane, Megan M Morris, Kevin Walsh, Douglas T Beattie, Dnyanada Pande, Parisa Zaeri, Genivaldo G Z Silva, Fabiano Thompson and 2 more

Abstract readEvaluation Study
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Biomimetic COEnvironmental science & technology · 2024
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Metagenome-Assembled Genomes ofJournal of microbiology and biotechnology · 2022
    Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Article
  19. EvaluatingMicrobiology spectrum · 2021
    Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Bhavya PapudeshiBioinformatics and Medical Informatics, San Diego State University, San Diego, California, USA.ORCID http://orcid.org/0000-0001-5359-3100
J Matthew HaggertyDepartment of Biology, San Diego State University, 5500 Campanile Drive, San Diego, 92115, California, USA.
Michael DoaneDepartment of Biology, San Diego State University, 5500 Campanile Drive, San Diego, 92115, California, USA.
Megan M MorrisDepartment of Biology, San Diego State University, 5500 Campanile Drive, San Diego, 92115, California, USA.
Kevin WalshDepartment of Biology, San Diego State University, 5500 Campanile Drive, San Diego, 92115, California, USA.
Douglas T BeattieDepartment of Biology, University of New South Wales, Sydney, New South Wales, Australia.
Dnyanada PandeBioinformatics and Medical Informatics, San Diego State University, San Diego, California, USA.
Parisa ZaeriDepartment of Mathematics and Statistics, San Diego State University, San Diego, California, USA.
Genivaldo G Z SilvaComputational Science Research Center, San Diego State University, San Diego, California, USA.
Fabiano ThompsonInstitute of Biology, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil.
Robert A EdwardsDepartment of Computer Science, San Diego State University, 5500 Campanile Drive, San Diego, California, USA.
Elizabeth A DinsdaleDepartment of Biology, San Diego State University, 5500 Campanile Drive, San Diego, 92115, California, USA. elizabeth_dinsdale@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMicrobiome/host interactions describe characteristics that affect the host's health. Shotgun metagenomics includes sequencing a random subset of the microbiome to analyze its taxonomic and metabolic potential. Reconstruction of DNA fragments into genomes from metagenomes (called metagenome-assembled genomes) assigns unknown fragments to taxa/function and facilitates discovery of novel organisms. Genome reconstruction incorporates sequence assembly and sorting of assembled sequences into bins, characteristic of a genome. However, the microbial community composition, including taxonomic and phylogenetic diversity may influence genome reconstruction. We determine the optimal reconstruction method for four microbiome projects that had variable sequencing platforms (IonTorrent and Illumina), diversity (high or low), and environment (coral reefs and kelp forests), using a set of parameters to select for optimal assembly and binning tools.

methodsWe tested the effects of the assembly and binning processes on population genome reconstruction using 105 marine metagenomes from 4 projects. Reconstructed genomes were obtained from each project using 3 assemblers (IDBA, MetaVelvet, and SPAdes) and 2 binning tools (GroopM and MetaBat). We assessed the efficiency of assemblers using statistics that including contig continuity and contig chimerism and the effectiveness of binning tools using genome completeness and taxonomic identification.

resultsWe concluded that SPAdes, assembled more contigs (143,718 ± 124 contigs) of longer length (N50 = 1632 ± 108 bp), and incorporated the most sequences (sequences-assembled = 19.65%). The microbial richness and evenness were maintained across the assembly, suggesting low contig chimeras. SPAdes assembly was responsive to the biological and technological variations within the project, compared with other assemblers. Among binning tools, we conclude that MetaBat produced bins with less variation in GC content (average standard deviation: 1.49), low species richness (4.91 ± 0.66), and higher genome completeness (40.92 ± 1.75) across all projects. MetaBat extracted 115 bins from the 4 projects of which 66 bins were identified as reconstructed metagenome-assembled genomes with sequences belonging to a specific genus. We identified 13 novel genomes, some of which were 100% complete, but show low similarity to genomes within databases.

conclusionsIn conclusion, we present a set of biologically relevant parameters for evaluation to select for optimal assembly and binning tools. For the tools we tested, SPAdes assembler and MetaBat binning tools reconstructed quality metagenome-assembled genomes for the four projects. We also conclude that metagenomes from microbial communities that have high coverage of phylogenetically distinct, and low taxonomic diversity results in highest quality metagenome-assembled genomes.

Indexed as

Genome, MicrobialMetagenomeAlgorithmsPhylogenySequence Analysis, DNASoftware

Identifiers

PMID29183281
PMCPMC5706307

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.