Evidence map›Paper›PMID 23303373›Full record

ArticleThe ISME journal2013

A novel approach, based on BLSOMs (Batch Learning Self-Organizing Maps), to the microbiome analysis of ticks.

Ryo Nakao, Takashi Abe, Ard M Nijhof, Seigo Yamamoto, Frans Jongejan, Toshimichi Ikemura, Chihiro Sugimoto

Erratum issuedOpen access · bronzeAbstract read
In one paragraph

Article in The ISME journal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 60 papers.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed
6.3field-weighted citation impact, top 3% 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

60 citing papers in PubMed, 118 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Skin infectome of patients with a tick bite history.Frontiers in cellular and infection microbiology · 2023
    Article
  8. Article
  9. Article
  10. Article
  11. Molecular Detection and Genotyping ofPathogens (Basel, Switzerland) · 2021
    Article
  12. Comparative genomics ofLife science alliance · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. Current debates and advances in tick microbiome research.Current research in parasitology & vector-borne diseases · 2021
    Review
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

7 authors at 6 institutions in 4 countries.

Ryo NakaoDivision of Collaboration and Education, Research Center for Zoonosis Control, Hokkaido University, Sapporo, Hokkaido, Japan.
Takashi Abe
Ard M Nijhof
Seigo Yamamoto
Frans Jongejan
Toshimichi Ikemura
Chihiro Sugimoto
Hokkaido University · JPFreie Universität Berlin · DEMiyazaki Prefectural Hospital · JPNagahama Institute of Bio-Science and Technology · JPNiigata University · JPOnderstepoort Veterinary Academic Hospital · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ticks transmit a variety of viral, bacterial and protozoal pathogens, which are often zoonotic. The aim of this study was to identify diverse tick microbiomes, which may contain as-yet unidentified pathogens, using a metagenomic approach. DNA prepared from bacteria/archaea-enriched fractions obtained from seven tick species, namely Amblyomma testudinarium, Amblyomma variegatum, Haemaphysalis formosensis, Haemaphysalis longicornis, Ixodes ovatus, Ixodes persulcatus and Ixodes ricinus, was subjected to pyrosequencing after whole-genome amplification. The resulting sequence reads were phylotyped using a Batch Learning Self-Organizing Map (BLSOM) program, which allowed phylogenetic estimation based on similarity of oligonucleotide frequencies, and functional annotation by BLASTX similarity searches. In addition to bacteria previously associated with human/animal diseases, such as Anaplasma, Bartonella, Borrelia, Ehrlichia, Francisella and Rickettsia, BLSOM analysis detected microorganisms belonging to the phylum Chlamydiae in some tick species. This was confirmed by pan-Chlamydia PCR and sequencing analysis. Gene sequences associated with bacterial pathogenesis were also identified, some of which were suspected to originate from horizontal gene transfer. These efforts to construct a database of tick microbes may lead to the ability to predict emerging tick-borne diseases. Furthermore, a comprehensive understanding of tick microbiomes will be useful for understanding tick biology, including vector competency and interactions with pathogens and symbionts.

Indexed as

MicrobiotaAnimalsArchaeaBacteriaEukaryotaHumansMetagenomicsPhylogenyTick-Borne DiseasesTicksViruses

Identifiers

PMID23303373
PMCPMC3635243
OpenAlexW2046938180

What OpenQuestion holds

Textmetadata
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.