Evidence map›Paper›PMID 39900484›Full record

ArticleEnvironmental microbiology2025

Genetic Transfer in Action: Uncovering DNA Flow in an Extremophilic Microbial Community.

Julia Van Etten, Timothy G Stephens, Debashish Bhattacharya

Abstract read
In one paragraph

Article in Environmental microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Julia Van EttenDepartment of Biochemistry and Microbiology, Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA.
Timothy G StephensDepartment of Biochemistry and Microbiology, Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA.
Debashish BhattacharyaDepartment of Biochemistry and Microbiology, Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA.

Funding

Joint Genome Institute 10.46936/10.25585/60000481NASA 80NSSC19K1542NASA NASA (80NSSC19K0462)National Institute of Food and Agriculture NJ01180U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231
6 · The paper itself

Abstract

Horizontal genetic transfer (HGT) is a significant driver of genomic novelty in all domains of life. HGT has been investigated in many studies however, the focus has been on conspicuous protein-coding DNA transfers that often prove to be adaptive in recipient organisms and are therefore fixed longer-term in lineages. These results comprise a subclass of HGTs and do not represent exhaustive (coding and non-coding) DNA transfer and its impact on ecology. Uncovering exhaustive HGT can provide key insights into the connectivity of genomes in communities and how these transfers may occur. In this study, we use the term frequency-inverse document frequency (TF-IDF) technique, that has been used successfully to mine DNA transfers within real and simulated high-quality prokaryote genomes, to search for exhaustive HGTs within an extremophilic microbial community. We establish a pipeline for validating transfers identified using this approach. We find that most DNA transfers are within-domain and involve non-coding DNA. A relatively high proportion of the predicted protein-coding HGTs appear to encode transposase activity, restriction-modification system components, and biofilm formation functions. Our study demonstrates the utility of the TF-IDF approach for HGT detection and provides insights into the mechanisms of recent DNA transfer.

Indexed as

BacteriaDNA, BacterialExtremophilesGene Transfer, HorizontalMicrobiotaGenome, BacterialDNA, Bacterialcommunity ecologyextremophileshorizontal gene transferk‐mer analysismetagenomicsmobile genetic elements

Identifiers

PMID39900484
PMCPMC11790422

What OpenQuestion holds

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Registered trials

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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.