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Related Experiment Video

Updated: Jan 21, 2026

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Published on: August 18, 2023

Multi-Lineage Evolution in Viral Populations Driven by Host Immune Systems.

Jacopo Marchi¹, Michael Lässig², Thierry Mora³

¹Laboratoire de physique de l'École normale supérieure (PSL University), CNRS, Sorbonne Université, and Université de Paris, 75005 Paris, France.

Pathogens (Basel, Switzerland)

|August 1, 2019

Summary

Viruses evolve with host immunity, creating diverse evolutionary patterns. Our model shows mutation rates and jump ranges determine if one or multiple viral lineages stably coexist.

Keywords:

co-evolution stochastic modeling viral-immune dynamics

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Last Updated: Jan 21, 2026

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Published on: October 20, 2020

Area of Science:

Virology
Evolutionary Biology
Immunology

Background:

Host immune systems exert selective pressure on viruses, influencing their evolution.
Different viruses exhibit distinct evolutionary patterns in antigenic space, such as influenza A's one-dimensional escape and influenza B's lineage coexistence.

Purpose of the Study:

To develop an evolutionary model for viruses interacting with immune systems possessing finite memory.
To generate a phase diagram illustrating viral evolutionary patterns in a two-dimensional antigenic space.

Main Methods:

Utilized an evolutionary model incorporating host immune systems with finite memory.
Analyzed the impact of effective mutation rates and mutation jump ranges on viral lineage stability.
Generated a phase diagram to map different evolutionary outcomes.

Main Results:

A single viral lineage is stable under conditions of small effective mutation rates and mutation jump ranges.
Multiple viral lineages can stably coexist over extended evolutionary periods when effective mutation rates and mutational jumps are large.
The model predicts distinct evolutionary regimes based on mutation parameters.

Conclusions:

The interplay between mutation rates and jump ranges in antigenic space dictates viral evolutionary dynamics.
Findings help constrain parameter regimes for viral adaptation, offering insights into pathogens like influenza.
The study provides a framework for understanding virus evolution under immune pressure.