Evidence map›Paper›PMID 31359005›Full record

ArticleNature biotechnology2019

Hybrid metagenomic assembly enables high-resolution analysis of resistance determinants and mobile elements in human microbiomes.

Denis Bertrand, Jim Shaw, Manesh Kalathiyappan, Amanda Hui Qi Ng, M Senthil Kumar, Chenhao Li, Mirta Dvornicic, Janja Paliska Soldo, Jia Yu Koh, Chengxuan Tong and 7 more

Abstract read
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In one paragraph

Article in Nature biotechnology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 197 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
197citing papers in PubMed, 1 pooled it
–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

197 citing papers in PubMed, 1 synthesis or guideline pooled it.

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137 more citing papers are in PubMed but not listed here.

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

17 authors.

Denis BertrandComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore.
Jim ShawComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore.
Manesh KalathiyappanComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore.
Amanda Hui Qi NgComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore.
M Senthil KumarComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore.
Chenhao LiComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0003-1182-6804
Mirta DvornicicComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore.
Janja Paliska SoldoComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore.
Jia Yu KohComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore.
Chengxuan TongComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore.
Oon Tek NgNational Centre for Infectious Disease, Tan Tock Seng Hospital, Singapore, Singapore.
Timothy BarkhamDepartment of Laboratory Medicine, Tan Tock Seng Hospital, Singapore, Singapore.ORCID http://orcid.org/0000-0003-0975-2244
Barnaby YoungNational Centre for Infectious Disease, Tan Tock Seng Hospital, Singapore, Singapore.
Kalisvar MarimuthuInstitute of Infectious Diseases and Epidemiology, Tan Tock Seng Hospital, Singapore, Singapore.
Kern Rei ChngComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore.
Mile SikicFaculty of Electrical Engineering and Computing, Department of Electronic Systems and Information Processing, University of Zagreb, Zagreb, Croatia.ORCID http://orcid.org/0000-0002-8370-0891
Niranjan NagarajanComputational & Systems Biology, Genome Institute of Singapore, Singapore, Singapore. nagarajann@gis.a-star.edu.sg.ORCID http://orcid.org/0000-0003-0850-5604

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Characterization of microbiomes has been enabled by high-throughput metagenomic sequencing. However, existing methods are not designed to combine reads from short- and long-read technologies. We present a hybrid metagenomic assembler named OPERA-MS that integrates assembly-based metagenome clustering with repeat-aware, exact scaffolding to accurately assemble complex communities. Evaluation using defined in vitro and virtual gut microbiomes revealed that OPERA-MS assembles metagenomes with greater base pair accuracy than long-read (>5×; Canu), higher contiguity than short-read (~10× NGA50; MEGAHIT, IDBA-UD, metaSPAdes) and fewer assembly errors than non-metagenomic hybrid assemblers (2×; hybridSPAdes). OPERA-MS provides strain-resolved assembly in the presence of multiple genomes of the same species, high-quality reference genomes for rare species (<1%) with ~9× long-read coverage and near-complete genomes with higher coverage. We used OPERA-MS to assemble 28 gut metagenomes of antibiotic-treated patients, and showed that the inclusion of long nanopore reads produces more contiguous assemblies (200× improvement over short-read assemblies), including more than 80 closed plasmid or phage sequences and a new 263 kbp jumbo phage. High-quality hybrid assemblies enable an exquisitely detailed view of the gut resistome in human patients.

Indexed as

Anti-Bacterial AgentsBacteriaDrug Resistance, BacterialFecesHigh-Throughput Nucleotide SequencingHumansMetagenomeMetagenomicsMicrobiotaNanoporesSequence Analysis, DNASoftwareAnti-Bacterial Agents

Identifiers

What OpenQuestion holds

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Read underepoch 390

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.