1. Immunology and Inflammation
  2. Microbiology and Infectious Disease
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Trogocytosis-associated cell to cell spread of intracellular bacterial pathogens

  1. Shaun Steele
  2. Lauren Radlinski
  3. Sharon Taft-Benz
  4. Brunton Jason
  5. Thomas H Kawula  Is a corresponding author
  1. University of North Carolina at Chapel Hill, United States
Research Article
  • Cited 32
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Cite this article as: eLife 2016;5:e10625 doi: 10.7554/eLife.10625

Abstract

Macrophages are myeloid-derived phagocytic cells and one of the first immune cell types to respond to microbial infections. However, a number of bacterial pathogens are resistant to the antimicrobial activities of macrophages and can grow within these cells. Macrophages have other immune surveillance roles including the acquisition of cytosolic components from multiple types of cells. We hypothesized that intracellular pathogens that can replicate within macrophages could also exploit cytosolic transfer to facilitate bacterial spread. We found that viable Francisella tularensis, as well as Salmonella enterica bacteria transferred from infected cells to uninfected macrophages along with other cytosolic material through a transient, contact dependent mechanism. Bacterial transfer occurred when the host cells exchanged plasma membrane proteins and cytosol via a trogocytosis related process leaving both donor and recipient cells intact and viable. Trogocytosis was strongly associated with infection in mice, suggesting that direct bacterial transfer occurs by this process in vivo.

Article and author information

Author details

  1. Shaun Steele

    University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Lauren Radlinski

    University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Sharon Taft-Benz

    University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Brunton Jason

    University of North Carolina at Chapel Hill, Chapel Hill, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Thomas H Kawula

    University of North Carolina at Chapel Hill, Chapel Hill, United States
    For correspondence
    kawula@med.unc.edu
    Competing interests
    The authors declare that no competing interests exist.

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#13-213.0) of the University of North Carolina.

Reviewing Editor

  1. Denise Monack, Stanford, United States

Publication history

  1. Received: August 5, 2015
  2. Accepted: January 22, 2016
  3. Accepted Manuscript published: January 23, 2016 (version 1)
  4. Version of Record published: February 26, 2016 (version 2)

Copyright

© 2016, Steele 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.

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Further reading

    1. Immunology and Inflammation
    2. Microbiology and Infectious Disease
    Emilie Bourdonnay, Thomas Henry
    Insight

    Direct contact between host cells allows some bacteria to spread within the body without being attacked by the immune system.

    1. Computational and Systems Biology
    2. Immunology and Inflammation
    James W Opzoomer et al.
    Tools and Resources Updated

    High-dimensional cytometry is an innovative tool for immune monitoring in health and disease, and it has provided novel insight into the underlying biology as well as biomarkers for a variety of diseases. However, the analysis of large multiparametric datasets usually requires specialist computational knowledge. Here, we describe ImmunoCluster (https://github.com/kordastilab/ImmunoCluster), an R package for immune profiling cellular heterogeneity in high-dimensional liquid and imaging mass cytometry, and flow cytometry data, designed to facilitate computational analysis by a nonspecialist. The analysis framework implemented within ImmunoCluster is readily scalable to millions of cells and provides a variety of visualization and analytical approaches, as well as a rich array of plotting tools that can be tailored to users’ needs. The protocol consists of three core computational stages: (1) data import and quality control; (2) dimensionality reduction and unsupervised clustering; and (3) annotation and differential testing, all contained within an R-based open-source framework.