Published April 30, 2024 | Version v1
Journal article Open

How flexible parasites can outsmart their hosts for evolutionary dominance

  • 1. Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, S637371, Singapore
  • 2. National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA

Description

Antagonistic coevolution between hosts and parasites substantially impacts community structure, with parasites displaying fluctuating selection or arms race dynamics during coevolution. The traditional matching alleles (MA) and gene-for-gene (GFG) models have been used to describe the dynamics and interaction of host-parasite coevolution, with these models assuming that parasites adopt a single strategy when competing with other parasites. We present a nonlinear dynamic population model that challenges this assumption, showing how a parasite that is disadvantaged under either the MA or the GFG model can win the competition by switching between the two losing strategies based on an external environmental cue, internal processes, or stochastic decision-making. This counterintuitive outcome is analogous to Parrondo's paradox, a game-theoretic concept that shows how alternating between two losing strategies can result in a winning outcome. Our numerical experiments support the validity of this model, suggesting that parasites can greatly benefit from maximum flexibility in their interactions with hosts. The flexibility of successful parasites puts an extra burden on the host defenses that have to adapt to different strategies of the parasites. These findings contribute to a deeper understanding of the coevolution of parasites and hosts, with broad implications for the evolution of complex ecological systems.

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10.1103_PhysRevResearch.6.023104.pdf

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Additional details

Identifiers

DOI
10.1103/PhysRevResearch.6.023104;
Crossref Funder ID
10.13039/501100001459; 10.13039/100000002;

Publishing Information

Journal Title
Physical Review Research
Journal Volume
6
Journal Issue
2
Journal Page Range
9 pgs.
ISSN
2643-1564

INIS

Country of Publication
United States
Country of Input or Organization
International Atomic Energy Agency (IAEA)
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING; S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
DECISION MAKING; DYNAMICS; EVOLUTION; FLEXIBILITY; GENES; HOST; INTERACTIONS; NONLINEAR PROBLEMS; NUMERICAL ANALYSIS; PARASITES; POPULATIONS; STOCHASTIC PROCESSES
Descriptors DEC
MATHEMATICS; MECHANICAL PROPERTIES; MECHANICS; TENSILE PROPERTIES

Optional Information

Contract/Grant/Project number
MOET2EP50120-0021
Notes
Contact Email: kanghao.cheong@ntu.edu.sg; Record automatically processed
Funding organization
Ministry of Education - Singapore; National Institutes of Health; Academic Research Fund