Evidence map›Paper›PMID 31239539›Full record

ArticleThe ISME journal2019

Visualization and prediction of CRISPR incidence in microbial trait-space to identify drivers of antiviral immune strategy.

J L Weissman, Rohan M R Laljani, William F Fagan, Philip L F Johnson

Abstract read
In one paragraph

Article in The ISME journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Phage defence-system abundances vary across environments and increase with viral density.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025
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  12. Breaking the Ice: A Review of Phages in Polar Ecosystems.Methods in molecular biology (Clifton, N.J.) · 2024
    Review
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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

4 authors.

J L WeissmanDepartment of Biology, University of Maryland, College Park, MD, USA.ORCID http://orcid.org/0000-0002-4237-4807
Rohan M R LaljaniDepartment of Biology, University of Maryland, College Park, MD, USA.
William F FaganDepartment of Biology, University of Maryland, College Park, MD, USA.
Philip L F JohnsonDepartment of Biology, University of Maryland, College Park, MD, USA. plfj@umd.edu.ORCID http://orcid.org/0000-0001-6087-7064

Funding

Population genetic inference from the adaptive immune systemR00GM104158 · NIGMS · UNIV OF MARYLAND, COLLEGE PARK · PI JOHNSON, PHILIP LEE FALK · 2015 to 2017
$747k
NIGMS NIH HHS R00 GM104158
6 · The paper itself

Abstract

Bacteria and archaea are locked in a near-constant battle with their viral pathogens. Despite previous mechanistic characterization of numerous prokaryotic defense strategies, the underlying ecological drivers of different strategies remain largely unknown and predicting which species will take which strategies remains a challenge. Here, we focus on the CRISPR immune strategy and develop a phylogenetically-corrected machine learning approach to build a predictive model of CRISPR incidence using data on over 100 traits across over 2600 species. We discover a strong but hitherto-unknown negative interaction between CRISPR and aerobicity, which we hypothesize may result from interference between CRISPR-associated proteins and non-homologous end-joining DNA repair due to oxidative stress. Our predictive model also quantitatively confirms previous observations of an association between CRISPR and temperature. Finally, we contrast the environmental associations of different CRISPR system types (I, II, III) and restriction modification systems, all of which act as intracellular immune systems.

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsArchaeaBacteriaPhylogenyVirusesVirus Physiological Phenomena

Identifiers

PMID31239539
PMCPMC6776019

What OpenQuestion holds

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LicenceCC BY
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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.