Ecological determinants of altruism in prokaryote antivirus defense

Prokaryote evolution is driven in large part by the incessant arms race with viruses. Genomic investments in antivirus defense can be coarsely classified into two categories, immune systems that abrogate virus reproduction resulting in clearance, and programmed cell death (PCD) systems. Prokaryotic defense systems are enormously diverse, as revealed by an avalanche of recent discoveries, but the basic ecological determinants of defense strategy remain poorly understood. Through mathematical modeling of defense against lytic virus infection, we identify two principal determinants of optimal defense strategy and, through comparative genomics, we test this model by measuring the genomic investment into immunity vs. PCD among diverse bacteria and archaea. First, as viral pressure grows, immunity becomes the preferred defense strategy. Second, as host population size grows, PCD becomes the preferred strategy. We additionally predict that, although optimal strategy typically involves investment in both PCD and immunity, investment in immunity can also result in antagonism, increasing the likelihood that a PCD-competent cell will lyse due to infection. Together, these findings indicate that, generally, PCD is preferred at low multiplicity of infection (MOI) and immunity is preferred at high MOI. Finally, we demonstrate that PCD, which is typically considered to be an altruistic trait, is in some cases neutral and can be maintained in an unstructured population over an evolutionary timescale. Our work shows that the landscape of prokaryotic antivirus defense is substantially more complex than previously suspected.

Authors

Institutions

Publication Details

Journal
Biology Direct
Published
2025-12-20
DOI
https://doi.org/10.1186/s13062-025-00699-8
Primary Topic
Evolution and Genetic Dynamics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ecological determinants of altruism in prokaryote antivirus defense

Yuri I. Wolf, Kira S. Makarova, Eugene V. Koonin, Levi Waldron et al.
Biology Direct
Evolution and Genetic Dynamics
article

Ecological determinants of altruism in prokaryote antivirus defense

Yuri I. Wolf, Kira S. Makarova, Eugene V. Koonin, Levi Waldron, Nash D. Rochman, Dmitry Biba
article en

Abstract

Prokaryote evolution is driven in large part by the incessant arms race with viruses. Genomic investments in antivirus defense can be coarsely classified into two categories, immune systems that abrogate virus reproduction resulting in clearance, and programmed cell death (PCD) systems. Prokaryotic defense systems are enormously diverse, as revealed by an avalanche of recent discoveries, but the basic ecological determinants of defense strategy remain poorly understood. Through mathematical modeling of defense against lytic virus infection, we identify two principal determinants of optimal defense strategy and, through comparative genomics, we test this model by measuring the genomic investment into immunity vs. PCD among diverse bacteria and archaea. First, as viral pressure grows, immunity becomes the preferred defense strategy. Second, as host population size grows, PCD becomes the preferred strategy. We additionally predict that, although optimal strategy typically involves investment in both PCD and immunity, investment in immunity can also result in antagonism, increasing the likelihood that a PCD-competent cell will lyse due to infection. Together, these findings indicate that, generally, PCD is preferred at low multiplicity of infection (MOI) and immunity is preferred at high MOI. Finally, we demonstrate that PCD, which is typically considered to be an altruistic trait, is in some cases neutral and can be maintained in an unstructured population over an evolutionary timescale. Our work shows that the landscape of prokaryotic antivirus defense is substantially more complex than previously suspected.

Biology DirectVol. 21(1)
Oak Ridge Associated Universities (US), Oak Ridge National Laboratory (US), City University of New York (US), University of Trento (IT), CUNY School of Law (US), United States National Library of Medicine (US), Institute for Family Health (US), National Center for Biotechnology Information (US)
National Institutes of Health
Openalex Percentile: Top 57%
Evolution and Genetic Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.