1. Computational and Systems Biology
  2. Immunology and Inflammation
Download icon

Memory CD4 T cell subsets are kinetically heterogeneous and replenished from naive T cells at high levels

  1. Graeme Gossel
  2. Thea Hogan
  3. Daniel Cownden
  4. Benedict Seddon  Is a corresponding author
  5. Andrew J Yates  Is a corresponding author
  1. Hunter College, City University of New York, United States
  2. University College London, United Kingdom
  3. University of Glasgow, United Kingdom
Research Article
  • Cited 33
  • Annotations
Cite this article as: eLife 2017;6:e23013 doi: 10.7554/eLife.23013

Abstract

Characterising the longevity of immunological memory requires establishing the rules underlying the renewal and death of peripheral T cells. However, we lack knowledge of the population structure and how self-renewal and de novo influx contribute to maintenance of memory compartments. Here, we characterise the kinetics and structure of murine CD4 T cell memory subsets by measuring the rates of influx of new cells and using detailed timecourses of DNA labelling that also distinguish the behaviour of recently divided and quiescent cells. We find that both effector and central memory CD4 T cells comprise subpopulations with highly divergent rates of turnover, and show that inflows of new cells sourced from the naive pool strongly impact estimates of memory cell lifetimes and division rates. We also demonstrate that the maintenance of CD4 T cell memory subsets in healthy mice is unexpectedly and strikingly reliant on this replenishment.

Article and author information

Author details

  1. Graeme Gossel

    Department of Physics and Astronomy, Hunter College, City University of New York, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Thea Hogan

    Institute of Immunity and Transplantation, University College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Daniel Cownden

    Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Benedict Seddon

    Institute of Immunity and Transplantation, University College London, London, United Kingdom
    For correspondence
    benedict.seddon@ucl.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
  5. Andrew J Yates

    Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom
    For correspondence
    andrew.yates@glasgow.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4606-4483

Funding

National Institutes of Health (R01 AI093870)

  • Andrew J Yates

Arthritis Research UK

  • Andrew J Yates

Medical Research Council (MC-PC-13055)

  • Thea Hogan
  • Benedict Seddon

National Science Foundation (1548123)

  • Graeme Gossel

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

Ethics

Animal experimentation: All experiments were performed in accordance with UK Home Office regulations, project license number PPL70-8310.

Reviewing Editor

  1. Rob de Boer, University of Utrecht, Netherlands

Publication history

  1. Received: November 5, 2016
  2. Accepted: March 4, 2017
  3. Accepted Manuscript published: March 10, 2017 (version 1)
  4. Version of Record published: May 11, 2017 (version 2)
  5. Version of Record updated: February 8, 2018 (version 3)

Copyright

© 2017, Gossel et al.

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.

Metrics

  • 33
    Citations

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)

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

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

Further reading

    1. Computational and Systems Biology
    2. Immunology and Inflammation
    Jose Borghans, Ruy M Ribeiro
    Insight

    Mathematical modeling reveals that long-term immunological memory is maintained in a manner that is even more dynamic than previously thought.

    1. Computational and Systems Biology
    2. Physics of Living Systems
    Jean-Benoît Lalanne, Gene-Wei Li
    Research Article Updated

    Enzymatic pathways have evolved uniquely preferred protein expression stoichiometry in living cells, but our ability to predict the optimal abundances from basic properties remains underdeveloped. Here, we report a biophysical, first-principles model of growth optimization for core mRNA translation, a multi-enzyme system that involves proteins with a broadly conserved stoichiometry spanning two orders of magnitude. We show that predictions from maximization of ribosome usage in a parsimonious flux model constrained by proteome allocation agree with the conserved ratios of translation factors. The analytical solutions, without free parameters, provide an interpretable framework for the observed hierarchy of expression levels based on simple biophysical properties, such as diffusion constants and protein sizes. Our results provide an intuitive and quantitative understanding for the construction of a central process of life, as well as a path toward rational design of pathway-specific enzyme expression stoichiometry.