Evidence map›Paper›PMID 23564253›Full record

ArticleGenome research2013

Genome of the pathogen Porphyromonas gingivalis recovered from a biofilm in a hospital sink using a high-throughput single-cell genomics platform.

Jeffrey S McLean, Mary-Jane Lombardo, Michael G Ziegler, Mark Novotny, Joyclyn Yee-Greenbaum, Jonathan H Badger, Glenn Tesler, Sergey Nurk, Valery Lesin, Daniel Brami and 11 more

Open access · bronzeAbstract read
In one paragraph

Article in Genome research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed, 63 citations in OpenAlex.

  1. Review
  2. Review
  3. Comparative analysis ofMicrobiology spectrum · 2024
    Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Single-Cell Genomics and the Oral Microbiome.Journal of dental research · 2020
    Review
  13. Observational
  14. Article
  15. Frontiers in cellular and infection microbiology · 2019
    Article
  16. Review
  17. Article
  18. Review
  19. Article
  20. Frontiers in cellular and infection microbiology · 2017
    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

21 authors at 4 institutions in 2 countries.

Jeffrey S McLeanMicrobial and Environmental Genomics, J. Craig Venter Institute, San Diego, California 92121, USA. jmclean@jcvi.org
Mary-Jane Lombardo
Michael G Ziegler
Mark Novotny
Joyclyn Yee-Greenbaum
Jonathan H Badger
Glenn Tesler
Sergey Nurk
Valery Lesin
Daniel Brami
Adam P Hall
Anna Edlund
Lisa Z Allen
Scott Durkin
Sharon Reed
Francesca Torriani
Kenneth H Nealson
Pavel A Pevzner
Robert Friedman
J Craig Venter
Roger S Lasken
J. Craig Venter Institute · USUniversity of California San Diego · USSaint Petersburg Academic University · RUUniversity of Southern California · US

Funding

San Diego Clinical and Translational Research InstituteUL1TR000100 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FIRESTEIN, GARY S · 2012 to 2015
$19.7M
CENTER FOR COMPUTATIONAL MASS-SPECTROMETRYP41RR024851 · NCRR · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2008 to 2011
$5.2M
Making a quantum leap in plaque research with modern sciencesR01DE020102 · NIDCR · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HE, XUESONG, MCLEAN, JEFFREY SCOTT · 2010 to 2020
$3.7M
Moving Beyond Diversity by Revealing Biological Functions of Uncultured BacteriaR01GM095373 · NIGMS · J. CRAIG VENTER INSTITUTE, INC. · PI MCLEAN, JEFFREY SCOTT, YOOSEPH, SHIBU · 2011 to 2014
$1.7M
NCATS NIH HHS UL1 TR000100NCATS NIH HHS UL1TR000100NCRR NIH HHS 3P41RR024851-02S1NCRR NIH HHS P41 RR024851NIDCR NIH HHS 1R01DE020102NIDCR NIH HHS R01 DE020102NIGMS NIH HHS 1R01GM095373NIGMS NIH HHS R01 GM095373
6 · The paper itself

Abstract

Although biofilms have been shown to be reservoirs of pathogens, our knowledge of the microbial diversity in biofilms within critical areas, such as health care facilities, is limited. Available methods for pathogen identification and strain typing have some inherent restrictions. In particular, culturing will yield only a fraction of the species present, PCR of virulence or marker genes is mainly focused on a handful of known species, and shotgun metagenomics is limited in the ability to detect strain variations. In this study, we present a single-cell genome sequencing approach to address these limitations and demonstrate it by specifically targeting bacterial cells within a complex biofilm from a hospital bathroom sink drain. A newly developed, automated platform was used to generate genomic DNA by the multiple displacement amplification (MDA) technique from hundreds of single cells in parallel. MDA reactions were screened and classified by 16S rRNA gene PCR sequence, which revealed a broad range of bacteria covering 25 different genera representing environmental species, human commensals, and opportunistic human pathogens. Here we focus on the recovery of a nearly complete genome representing a novel strain of the periodontal pathogen Porphyromonas gingivalis (P. gingivalis JCVI SC001) using the single-cell assembly tool SPAdes. Single-cell genomics is becoming an accepted method to capture novel genomes, primarily in the marine and soil environments. Here we show for the first time that it also enables comparative genomic analysis of strain variation in a pathogen captured from complex biofilm samples in a healthcare facility.

Indexed as

BiofilmsHigh-Throughput Nucleotide SequencingSingle-Cell AnalysisBacteroidaceae InfectionsCross InfectionGenome, BacterialHumansPorphyromonas gingivalis

Identifiers

PMID23564253
PMCPMC3638142
OpenAlexW2169242924

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.