Optimal evolutionary decision-making to store immune memory

  1. Oskar H Schnaack
  2. Armita Nourmohammad  Is a corresponding author
  1. Max Planck Institute for Dynamics and Self-organization, Germany
  2. University of Washington, United States


The adaptive immune system provides a diverse set of molecules that can mount specific responses against a multitude of pathogens. Memory is a key feature of adaptive immunity, which allows organisms to respond more readily upon re-infections. However, differentiation of memory cells is still one of the least understood cell fate decisions. Here, we introduce a mathematical framework to characterize optimal strategies to store memory to maximize the utility of immune response over an organism's lifetime. We show that memory production should be actively regulated to balance between affinity and cross-reactivity of immune receptors for an effective protection against evolving pathogens. Moreover, we predict that specificity of memory should depend on the organism's lifespan, and shorter-lived organisms with fewer pathogenic encounters should store more cross-reactive memory. Our framework provides a baseline to gauge the efficacy of immune memory in light of an organism's coevolutionary history with pathogens.

Data availability

Numerical data generated for all figures and the corresponding code will be provided for publication.

Article and author information

Author details

  1. Oskar H Schnaack

    Statistical Physics of Evolving Systems, Max Planck Institute for Dynamics and Self-organization, Göttingen, Germany
    Competing interests
    No competing interests declared.
  2. Armita Nourmohammad

    Physics, University of Washington, Seattle, United States
    For correspondence
    Competing interests
    Armita Nourmohammad, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6245-3553


Deutsche Forschungsgemeinschaft (SFB1310)

  • Armita Nourmohammad

Max Planck Society (MPRG funding)

  • Armita Nourmohammad

University of Washington (Royalty Research Fund: A153352)

  • Armita Nourmohammad

Max Planck Institute for Dynamics and Self-organization (Open-access funding)

  • Armita Nourmohammad

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Arvind Murugan, University of Chicago, United States

Version history

  1. Received: July 22, 2020
  2. Accepted: April 23, 2021
  3. Accepted Manuscript published: April 28, 2021 (version 1)
  4. Version of Record published: May 12, 2021 (version 2)
  5. Version of Record updated: June 10, 2021 (version 3)


© 2021, Schnaack & Nourmohammad

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.


  • 1,511
    Page views
  • 230
  • 8

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Oskar H Schnaack
  2. Armita Nourmohammad
Optimal evolutionary decision-making to store immune memory
eLife 10:e61346.

Further reading

    1. Neuroscience
    2. Physics of Living Systems
    Kevin S Chen, Rui Wu ... Andrew M Leifer
    Tools and Resources Updated

    Olfactory navigation is observed across species and plays a crucial role in locating resources for survival. In the laboratory, understanding the behavioral strategies and neural circuits underlying odor-taxis requires a detailed understanding of the animal’s sensory environment. For small model organisms like Caenorhabditis elegans and larval Drosophila melanogaster, controlling and measuring the odor environment experienced by the animal can be challenging, especially for airborne odors, which are subject to subtle effects from airflow, temperature variation, and from the odor’s adhesion, adsorption, or reemission. Here, we present a method to control and measure airborne odor concentration in an arena compatible with an agar substrate. Our method allows continuous controlling and monitoring of the odor profile while imaging animal behavior. We construct stationary chemical landscapes in an odor flow chamber through spatially patterned odorized air. The odor concentration is measured with a spatially distributed array of digital gas sensors. Careful placement of the sensors allows the odor concentration across the arena to be continuously inferred in space and monitored through time. We use this approach to measure the odor concentration that each animal experiences as it undergoes chemotaxis behavior and report chemotaxis strategies for C. elegans and D. melanogaster larvae populations as they navigate spatial odor landscapes.

    1. Physics of Living Systems
    2. Structural Biology and Molecular Biophysics
    Anton A Polyansky, Laura D Gallego ... Bojan Zagrovic
    Research Article Updated

    Non-membrane-bound biomolecular condensates have been proposed to represent an important mode of subcellular organization in diverse biological settings. However, the fundamental principles governing the spatial organization and dynamics of condensates at the atomistic level remain unclear. The Saccharomyces cerevisiae Lge1 protein is required for histone H2B ubiquitination and its N-terminal intrinsically disordered fragment (Lge11-80) undergoes robust phase separation. This study connects single- and multi-chain all-atom molecular dynamics simulations of Lge11-80 with the in vitro behavior of Lge11-80 condensates. Analysis of modeled protein-protein interactions elucidates the key determinants of Lge11-80 condensate formation and links configurational entropy, valency, and compactness of proteins inside the condensates. A newly derived analytical formalism, related to colloid fractal cluster formation, describes condensate architecture across length scales as a function of protein valency and compactness. In particular, the formalism provides an atomistically resolved model of Lge11-80 condensates on the scale of hundreds of nanometers starting from individual protein conformers captured in simulations. The simulation-derived fractal dimensions of condensates of Lge11-80 and its mutants agree with their in vitro morphologies. The presented framework enables a multiscale description of biomolecular condensates and embeds their study in a wider context of colloid self-organization.