Evidence map›Paper›PMID 24196323›Full record

ArticleThe ISME journal2014

Top-down controls on bacterial community structure: microbial network analysis of bacteria, T4-like viruses and protists.

Cheryl-Emiliane T Chow, Diane Y Kim, Rohan Sachdeva, David A Caron, Jed A Fuhrman

Open access · bronzeAbstract read
In one paragraph

Article in The ISME journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 117 papers.

0numbers the graph read from it
0cells of the map it votes in
117citing papers in PubMed
18.6field-weighted citation impact, top 1% 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

117 citing papers in PubMed, 372 citations in OpenAlex.

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  15. Bottom-up and top-down controls onISME communications · 2024
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  17. Exploring the impact ofCurrent research in parasitology & vector-borne diseases · 2024
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57 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

5 authors at 1 institution in 1 country.

Cheryl-Emiliane T ChowDepartment of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
Diane Y KimDepartment of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
Rohan SachdevaDepartment of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
David A CaronDepartment of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
Jed A FuhrmanDepartment of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
University of Southern California · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Characterizing ecological relationships between viruses, bacteria and protists in the ocean are critical to understanding ecosystem function, yet these relationships are infrequently investigated together. We evaluated these relationships through microbial association network analysis of samples collected approximately monthly from March 2008 to January 2011 in the surface ocean (0-5 m) at the San Pedro Ocean Time series station. Bacterial, T4-like myoviral and protistan communities were described by Automated Ribosomal Intergenic Spacer Analysis and terminal restriction fragment length polymorphism of the gene encoding the major capsid protein (g23) and 18S ribosomal DNA, respectively. Concurrent shifts in community structure suggested similar timing of responses to environmental and biological parameters. We linked T4-like myoviral, bacterial and protistan operational taxonomic units by local similarity correlations, which were then visualized as association networks. Network links (correlations) potentially represent synergistic and antagonistic relationships such as viral lysis, grazing, competition or other interactions. We found that virus-bacteria relationships were more cross-linked than protist-bacteria relationships, suggestive of increased taxonomic specificity in virus-bacteria relationships. We also found that 80% of bacterial-protist and 74% of bacterial-viral correlations were positive, with the latter suggesting that at monthly and seasonal timescales, viruses may be following their hosts more often than controlling host abundance.

Indexed as

Bacterial Physiological PhenomenaEcosystemWater MicrobiologyBacteriaBacteriophage T4Capsid ProteinsEukaryotaOceans and SeasPolymorphism, Restriction Fragment LengthRNA, Ribosomal, 18SCapsid ProteinsRNA, Ribosomal, 18S

Identifiers

PMID24196323
PMCPMC3960540
OpenAlexW2039594706

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.