Evidence map›Paper›PMID 22412957›Full record

ArticlePloS one2012

Deep sequencing analyses of low density microbial communities: working at the boundary of accurate microbiota detection.

Giske Biesbroek, Elisabeth A M Sanders, Guus Roeselers, Xinhui Wang, Martien P M Caspers, Krzysztof Trzciński, Debby Bogaert, Bart J F Keijser

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 116 papers.

0numbers the graph read from it
0cells of the map it votes in
116citing papers in PubMed
6.0field-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

116 citing papers in PubMed, 200 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review

56 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

8 authors at 1 institution in 1 country.

Giske BiesbroekDepartment of Pediatric Infectious Diseases and Immunity UMC Utrecht, Utrecht, The Netherlands.
Elisabeth A M Sanders
Guus Roeselers
Xinhui Wang
Martien P M Caspers
Krzysztof Trzciński
Debby Bogaert
Bart J F Keijser
University Medical Center Utrecht · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAccurate analyses of microbiota composition of low-density communities (10(3)-10(4) bacteria/sample) can be challenging. Background DNA from chemicals and consumables, extraction biases as well as differences in PCR efficiency can significantly interfere with microbiota assessment. This study was aiming to establish protocols for accurate microbiota analysis at low microbial density.

methodsTo examine possible effects of bacterial density on microbiota analyses we compared microbiota profiles of serial diluted saliva and low (nares, nasopharynx) and high-density (oropharynx) upper airway communities in four healthy individuals. DNA was extracted with four different extraction methods (Epicentre Masterpure, Qiagen DNeasy, Mobio Powersoil and a phenol bead-beating protocol combined with Agowa-Mag-mini). Bacterial DNA recovery was analysed by 16S qPCR and microbiota profiles through GS-FLX-Titanium-Sequencing of 16S rRNA gene amplicons spanning the V5-V7 regions.

resultsLower template concentrations significantly impacted microbiota profiling results. With higher dilutions, low abundant species were overrepresented. In samples of <10(5) bacteria per ml, e.g. DNA <1 pg/µl, microbiota profiling deviated from the original sample and other dilutions showing a significant increase in the taxa Proteobacteria and decrease in Bacteroidetes. In similar low density samples, DNA extraction method determined if DNA levels were below or above 1 pg/µl and, together with lysis preferences per method, had profound impact on microbiota analyses in both relative abundance as well as representation of species.

conclusionThis study aimed to interpret microbiota analyses of low-density communities. Bacterial density seemed to interfere with microbiota analyses at < than 10(6) bacteria per ml or DNA <1 pg/µl. We therefore recommend this threshold for working with low density materials. This study underlines that bias reduction is crucial for adequate profiling of especially low-density bacterial communities.

Indexed as

High-Throughput Nucleotide SequencingBacterial LoadDNA, BacterialDNA, RibosomalHost-Pathogen InteractionsHumansMetagenomeNasopharynxRespiratory SystemDNA, BacterialDNA, Ribosomal

Identifiers

PMID22412957
PMCPMC3295791
OpenAlexW2095135825

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.