Evidence map›Paper›PMID 24432015›Full record

ReviewFrontiers in microbiology2014

Detecting rare gene transfer events in bacterial populations.

Kaare M Nielsen, Thomas Bøhn, Jeffrey P Townsend

Abstract readReview
In one paragraph

Review in Frontiers in microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Review
  2. Article
  3. Safety and efficacy of a feed additive consisting of viable cells ofEFSA journal. European Food Safety Authority · 2025
    Article
  4. Review
  5. Comparative genomic analysis of 255Microbiology spectrum · 2025
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
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  18. Review
  19. Article
  20. Horizontal transfer of short and degraded DNA has evolutionary implications for microbes and eukaryotic sexual reproduction.BioEssays : news and reviews in molecular, cellular and developmental biology · 2014
    Review
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

3 authors.

Kaare M NielsenDepartment of Pharmacy, Faculty of Health Sciences, University of Tromsø Tromsø, Norway ; GenØk-Centre for Biosafety, The Science Park Tromsø, Norway.
Thomas BøhnDepartment of Pharmacy, Faculty of Health Sciences, University of Tromsø Tromsø, Norway ; GenØk-Centre for Biosafety, The Science Park Tromsø, Norway.
Jeffrey P TownsendDepartment of Biostatistics, Yale University New Haven, CT, USA ; Program in Computational Biology and Bioinformatics, Yale University New Haven, CT, USA ; Program in Microbiology, Yale University New Haven, CT, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Horizontal gene transfer (HGT) enables bacteria to access, share, and recombine genetic variation, resulting in genetic diversity that cannot be obtained through mutational processes alone. In most cases, the observation of evolutionary successful HGT events relies on the outcome of initially rare events that lead to novel functions in the new host, and that exhibit a positive effect on host fitness. Conversely, the large majority of HGT events occurring in bacterial populations will go undetected due to lack of replication success of transformants. Moreover, other HGT events that would be highly beneficial to new hosts can fail to ensue due to lack of physical proximity to the donor organism, lack of a suitable gene transfer mechanism, genetic compatibility, and stochasticity in tempo-spatial occurrence. Experimental attempts to detect HGT events in bacterial populations have typically focused on the transformed cells or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to reach relative population sizes that will allow their immediate identification; the exception being the unusually strong positive selection conferred by antibiotics. Most HGT events are not expected to alter the likelihood of host survival to such an extreme extent, and will confer only minor changes in host fitness. Due to the large population sizes of bacteria and the time scales involved, the process and outcome of HGT are often not amenable to experimental investigation. Population genetic modeling of the growth dynamics of bacteria with differing HGT rates and resulting fitness changes is therefore necessary to guide sampling design and predict realistic time frames for detection of HGT, as it occurs in laboratory or natural settings. Here we review the key population genetic parameters, consider their complexity and highlight knowledge gaps for further research.

Indexed as

antibiotic resistancebiosafetyDNA uptakeGMOlateral or horizontal gene transfermodelingmonitoringsampling

Identifiers

PMID24432015
PMCPMC3882822

What OpenQuestion holds

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LicenceCC BY
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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.