The value of information gathering in phage-bacteria warfare.

bacteria infection strategy lysis lysogen phage

Journal

PNAS nexus
ISSN: 2752-6542
Titre abrégé: PNAS Nexus
Pays: England
ID NLM: 9918367777906676

Informations de publication

Date de publication:
Jan 2024
Historique:
received: 12 09 2023
accepted: 29 11 2023
medline: 10 1 2024
pubmed: 10 1 2024
entrez: 10 1 2024
Statut: epublish

Résumé

Phages-viruses that infect bacteria-have evolved over billions of years to overcome bacterial defenses. Temperate phage, upon infection, can "choose" between two pathways: lysis-in which the phage create multiple new phage particles, which are then liberated by cell lysis, and lysogeny-where the phage's genetic material is added to the bacterial DNA and transmitted to the bacterial progeny. It was recently discovered that some phages can read information from the environment related to the density of bacteria or the number of nearby infection attempts. Such information may help phage make the right choice between the two pathways. Here, we develop a theoretical model that allows an infecting phage to change its strategy (i.e. the ratio of lysis to lysogeny) depending on an outside signal, and we find the optimal strategy that maximizes phage proliferation. While phages that exploit extra information naturally win in competition against phages with a fixed strategy, there may be costs to information, e.g. as the necessary extra genes may affect the growth rate of a lysogen or the burst size of new phage for the lysis pathway. Surprisingly, even when phages pay a large price for information, they can still maintain an advantage over phages that lack this information, indicating the high benefit of intelligence gathering in phage-bacteria warfare.

Identifiants

pubmed: 38196923
doi: 10.1093/pnasnexus/pgad431
pii: pgad431
pmc: PMC10776245
doi:

Types de publication

Journal Article

Langues

eng

Pagination

pgad431

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of National Academy of Sciences.

Auteurs

Yuval Dahan (Y)

Department of Physics, Ben Gurion University of the Negev, Beer Sheva, 84105, Israel.

Ned S Wingreen (NS)

Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.
Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.

Yigal Meir (Y)

Department of Physics, Ben Gurion University of the Negev, Beer Sheva, 84105, Israel.
Department of Physics, Princeton University, Princeton, NJ 08544, USA.

Classifications MeSH