Evidence map›Paper›PMID 29927994›Full record

ArticlePloS one2018

In silico characterisation of the two-component system regulators of Streptococcus pyogenes.

Sean J Buckley, Peter Timms, Mark R Davies, David J McMillan

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
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

7 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. 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 at 2 institutions in 1 country.

Sean J BuckleyInflammation and Healing Biomedical Research Cluster, and School of Health and Sports Sciences, Faculty of Science, University of the Sunshine Coast, Sippy Downs, Queensland, Australia.
Peter TimmsInflammation and Healing Biomedical Research Cluster, and School of Health and Sports Sciences, Faculty of Science, University of the Sunshine Coast, Sippy Downs, Queensland, Australia.
Mark R DaviesDepartment of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Victoria, Australia.
David J McMillanInflammation and Healing Biomedical Research Cluster, and School of Health and Sports Sciences, Faculty of Science, University of the Sunshine Coast, Sippy Downs, Queensland, Australia.ORCID 0000-0002-9339-0639
University of the Sunshine Coast · AUThe University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacteria respond to environmental changes through the co-ordinated regulation of gene expression, often mediated by two-component regulatory systems (TCS). Group A Streptococcus (GAS), a bacterium which infects multiple human body sites and causes multiple diseases, possesses up to 14 TCS. In this study we examined genetic variation in the coding sequences and non-coding DNA upstream of these TCS as a method for evaluating relationships between different GAS emm-types, and potential associations with GAS disease. Twelve of the 14 TCS were present in 90% of the genomes examined. The length of the intergenic regions (IGRs) upstream of TCS coding regions varied from 39 to 345 nucleotides, with an average nucleotide diversity of 0.0064. Overall, IGR allelic variation was generally conserved with an emm-type. Subsequent phylogenetic analysis of concatenated sequences based on all TCS IGR sequences grouped genomes of the same emm-type together. However grouping with emm-pattern and emm-cluster-types was much weaker, suggesting epidemiological and functional properties associated with the latter are not due to evolutionary relatedness of emm-types. All emm5, emm6 and most of the emm18 genomes, all historically considered rheumatogenic emm-types clustered together, suggesting a shared evolutionary history. However emm1, emm3 and several emm18 genomes did not cluster within this group. These latter emm18 isolates were epidemiologically distinct from other emm18 genomes in study, providing evidence for local variation. emm-types associated with invasive disease or nephritogenicity also did not cluster together. Considering the TCS coding sequences (cds), correlation with emm-type was weaker than for the IGRs, and no strong correlation with disease was observed. Deletion of the malate transporter, maeP, was identified that serves as a putative marker for the emm89.0 subtype, which has been implicated in invasive outbreaks. A recombination-related, subclade-forming DNA motif was identified in the putative receiver domain of the Spy1556 response regulator that correlated with throat-associated emm-pattern-type A-C strains.

Indexed as

Gene Expression Regulation, BacterialGenome, BacterialAllelesComputer SimulationDNA, IntergenicRegulatory Sequences, Nucleic AcidStreptococcus pyogenesDNA, Intergenic

Identifiers

PMID29927994
PMCPMC6013163
OpenAlexW2809485668

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.