Evidence map›Paper›PMID 38896653›Full record

ArticleThe ISME journal2024

Conditions for the spread of CRISPR-Cas immune systems into bacterial populations.

Josie F K Elliott, David V McLeod, Tiffany B Taylor, Edze R Westra, Sylvain Gandon, Bridget N J Watson

Abstract read
In one paragraph

Article in The ISME journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. 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

6 authors.

Josie F K ElliottMilner Centre for Evolution, Department of Life Sciences, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom.
David V McLeodDépartement de mathématiques et statistique, Université de Montréal, Montréal, Canada.
Tiffany B TaylorMilner Centre for Evolution, Department of Life Sciences, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom.
Edze R WestraESI, Biosciences, University of Exeter, Cornwall Campus, Penryn TR10 9FE, United Kingdom.
Sylvain GandonCEFE, CNRS, Univ Montpellier, EPHE, IRD, Montpellier, France.
Bridget N J WatsonESI, Biosciences, University of Exeter, Cornwall Campus, Penryn TR10 9FE, United Kingdom.

Funding

Biotechnology and Biological Sciences Research Council Discovery Fellowship BB/X010600/1Biotechnology and Biological Sciences Research Council SWBio DTP BB/T008741/1Natural Environment Research Council NE/S001921/1Royal Society Dorothy Hodgkin Fellowship DH150169
6 · The paper itself

Abstract

Bacteria contain a wide variety of innate and adaptive immune systems which provide protection to the host against invading genetic material, including bacteriophages (phages). It is becoming increasingly clear that bacterial immune systems are frequently lost and gained through horizontal gene transfer. However, how and when new immune systems can become established in a bacterial population have remained largely unstudied. We developed a joint epidemiological and evolutionary model that predicts the conditions necessary for the spread of a CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated) immune system into a bacterial population lacking this system. We found that whether bacteria carrying CRISPR-Cas will spread (increase in frequency) into a bacterial population depends on the abundance of phages and the difference in the frequency of phage resistance mechanisms between bacteria carrying a CRISPR-Cas immune system and those not (denoted as ${f}_{\Delta }$). Specifically, the abundance of cells carrying CRISPR-Cas will increase if there is a higher proportion of phage resistance (either via CRISPR-Cas immunity or surface modification) in the CRISPR-Cas-possessing population than in the cells lacking CRISPR-Cas. We experimentally validated these predictions in a model using Pseudomonas aeruginosa PA14 and phage DMS3vir. Specifically, by varying the initial ratios of different strains of bacteria that carry alternative forms of phage resistance, we confirmed that the spread of cells carrying CRISPR-Cas through a population can be predicted based on phage density and the relative frequency of resistance phenotypes. Understanding which conditions promote the spread of CRISPR-Cas systems helps to predict when and where these defences can become established in bacterial populations after a horizontal gene transfer event, both in ecological and clinical contexts.

Indexed as

BacteriaBacteriophagesCRISPR-Cas SystemsClustered Regularly Interspaced Short Palindromic RepeatsGene Transfer, HorizontalPseudomonas aeruginosabacteria–phage interactionsCRISPR-Casecologyevolutionary epidemiologyhorizontal gene transfermathematical theorymicrobial ecology and evolutionresistance evolution

Identifiers

PMID38896653
PMCPMC11285788

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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.