Evidence map›Paper›PMID 27651451›Full record

ArticleNucleic acids research2017

MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples.

Moreno Zolfo, Adrian Tett, Olivier Jousson, Claudio Donati, Nicola Segata

Abstract read
In one paragraph

Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing 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

62 citing papers in PubMed.

  1. Trial
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  3. Review
  4. Article
  5. Early detection and population dynamics ofFrontiers in microbiology · 2025
    Article
  6. Article
  7. Genome assembly ofFrontiers in microbiology · 2025
    Article
  8. The oral-gut microbiome axis in health and disease.Nature reviews. Microbiology · 2024
    Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

2 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

5 authors.

Moreno ZolfoCentre for Integrative Biology, University of Trento, Trento, TN 38123, Italy.
Adrian TettCentre for Integrative Biology, University of Trento, Trento, TN 38123, Italy.
Olivier JoussonCentre for Integrative Biology, University of Trento, Trento, TN 38123, Italy.
Claudio DonatiComputational Biology Unit, Research and Innovation Centre, Fondazione Edmund Mach, Via Edmund Mach 1, San Michele all'Adige 38010, Italy.
Nicola SegataCentre for Integrative Biology, University of Trento, Trento, TN 38123, Italy nicola.segata@unitn.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metagenomic characterization of microbial communities has the potential to become a tool to identify pathogens in human samples. However, software tools able to extract strain-level typing information from metagenomic data are needed. Low-throughput molecular typing schema such as Multilocus Sequence Typing (MLST) are still widely used and provide a wealth of strain-level information that is currently not exploited by metagenomic methods. We introduce MetaMLST, a software tool that reconstructs the MLST loci of microorganisms present in microbial communities from metagenomic data. Tested on synthetic and spiked-in real metagenomes, the pipeline was able to reconstruct the MLST sequences with >98.5% accuracy at coverages as low as 1×. On real samples, the pipeline showed higher sensitivity than assembly-based approaches and it proved successful in identifying strains in epidemic outbreaks as well as in intestinal, skin and gastrointestinal microbiome samples.

Indexed as

SoftwareAlgorithmsAllelesBacteriaGastrointestinal MicrobiomeGenome, BacterialHumansMetagenomeMetagenomicsMultilocus Sequence TypingReproducibility of ResultsWeb Browser

Identifiers

PMID27651451
PMCPMC5314789

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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.