Evidence map›Paper›PMID 32150564›Full record

ArticlePloS one2020

Genome-scale approach to study the genetic relatedness among Brucella melitensis strains.

Ana Pelerito, Alexandra Nunes, Maria Sofia Núncio, João Paulo Gomes

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Genomic epidemiology ofFrontiers in veterinary science · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. Genomic Epidemiology of ClinicalMicroorganisms · 2022
    Article
  7. Article
  8. Article
  9. Genetic Characterization ofFrontiers in microbiology · 2021
    Article
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

4 authors.

Ana PeleritoDepartment of Infectious Diseases, Emergency Response and Biopreparedness Unit, National Institute of Health, Lisbon, Portugal.ORCID 0000-0003-4770-9079
Alexandra NunesDepartment of Infectious Diseases, Bioinformatics Unit, National Institute of Health (INSA), Lisbon, Portugal.
Maria Sofia NúncioDepartment of Infectious Diseases, Emergency Response and Biopreparedness Unit, National Institute of Health, Lisbon, Portugal.
João Paulo GomesDepartment of Infectious Diseases, Bioinformatics Unit, National Institute of Health (INSA), Lisbon, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brucellosis is an important zoonotic disease that affects both humans and animals. To date, laboratory surveillance is still essentially based on the traditional MLVA-16 methodology and the associated epidemiological information is frequently scarce. Our goal was to contribute to the improvement of Brucella spp. surveillance through the implementation of a whole genome sequencing (WGS) approach. We created a curated ready-to-use species-specific wgMLST scheme enrolling a panel of 2656 targets (http://doi.org/10.5281/zenodo.3575026) and used this schema to perform a retrospective analysis of the genetic relatedness among B. melitensis strains causing human infection in Portugal (a country where brucellosis is an endemic disease) from 2010 to 2018. The strains showed a phylogenetic clustering within genotype II (25 out of 36) and IV (4 out of 36), and shared clades with strains isolated from countries with which Portugal has intense food trading, tourism and similar eating habits, such as Spain, Italy and Greece. In addition, our results point to the identification of strong associations between B. melitensis strains, likely underlying missed "outbreaks" as 22 out of the 36 strains showed genetic linkage with others. In fact, the applied gene-by-gene approach grouped these strains into six genetic clusters each one containing putative epidemiological links. Nevertheless, more studies will be needed in order to define the appropriate range of cut-offs (probable non-static cut-offs) that best illustrate the association between genetic linkage and epidemiological information and may serve as alerts for the health authorities. The release of this freely available and scalable schema contributes to the required technological transition for laboratorial surveillance of brucellosis and will facilitate the assessment of ongoing and future outbreaks in order to prevent the transmission spread.

Indexed as

Genome, BacterialBrucella melitensisBrucellosisHumansPhylogenyPortugalWhole Genome Sequencing

Identifiers

PMID32150564
PMCPMC7062273

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Registered trials

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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.