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Lymph Node Colonization Dynamics after Oral Salmonella Typhimurium Infection in Mice

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  • Patrick Kaiser
  • Emma Slack
  • Andrew J Grant
  • Wolf-Dietrich Hardt
  • Roland R Regoes

Abstract

An understanding of how pathogens colonize their hosts is crucial for the rational design of vaccines or therapy. While the molecular factors facilitating the invasion and systemic infection by pathogens are a central focus of research in microbiology, the population biological aspects of colonization are still poorly understood. Here, we investigated the early colonization dynamics of Salmonella enterica subspecies 1 serovar Typhimurium (S. Tm) in the streptomycin mouse model for diarrhea. We focused on the first step on the way to systemic infection — the colonization of the cecal lymph node (cLN) from the gut — and studied roles of inflammation, dendritic cells and innate immune effectors in the colonization process. To this end, we inoculated mice with mixtures of seven wild type isogenic tagged strains (WITS) of S. Tm. The experimental data were analyzed with a newly developed mathematical model describing the stochastic immigration, replication and clearance of bacteria in the cLN. We estimated that in the beginning of infection only 300 bacterial cells arrive in the cLN per day. We further found that inflammation decreases the net replication rate in the cLN by 23%. In mice, in which dendritic cell movement is impaired, the bacterial migration rate was reduced 10-fold. In contrast, mice that cannot generate toxic reactive oxygen species displayed a 4-fold higher migration rate from gut to cLN than wild type mice. Thus, combining infections with mixed inocula of barcoded strains and mathematical analysis represents a powerful method for disentangling immigration into the cLN from replication in this compartment. The estimated parameters provide an important baseline to assess and predict the efficacy of interventions.Author Summary: Like humans, pathogens have a demography. Within their hosts, they migrate, replicate, and die. Understanding these processes quantitatively can help designing vaccines and treatment by identifying vulnerabilities of the pathogen population. For most pathogens, however, quantitative information on how they replicate and spread in their hosts is lacking. Here, we investigate the early colonization of hosts by Salmonella bacteria after oral infection in a mouse model for complicated Salmonella diarrhea. To estimate migration and replication rates, we infected the mice with mixtures of identical, but distinguishable strains of the bacterium and analyzed the results with a mathematical model that describes the demography of the bacterial population. Random loss of some of these strains during colonization of the mice allows us to estimate migration rates between anatomical compartments. We find that approximately 300 bacteria migrate per day from the gut to the cecal lymph node – the first step towards systemic infection. We further investigate how bacterial migration and replication is affected by inflammation and various agents of the immune system. Our study provides unprecedented information on the colonization dynamics of this bacterial infection and introduces a framework for further improving therapy and vaccination.

Suggested Citation

  • Patrick Kaiser & Emma Slack & Andrew J Grant & Wolf-Dietrich Hardt & Roland R Regoes, 2013. "Lymph Node Colonization Dynamics after Oral Salmonella Typhimurium Infection in Mice," PLOS Pathogens, Public Library of Science, vol. 9(9), pages 1-12, September.
  • Handle: RePEc:plo:ppat00:1003532
    DOI: 10.1371/journal.ppat.1003532
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    References listed on IDEAS

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    1. Martin Ackermann & Bärbel Stecher & Nikki E. Freed & Pascal Songhet & Wolf-Dietrich Hardt & Michael Doebeli, 2008. "Self-destructive cooperation mediated by phenotypic noise," Nature, Nature, vol. 454(7207), pages 987-990, August.
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    1. David J Price & Alexandre Breuzé & Richard Dybowski & Piero Mastroeni & Olivier Restif, 2017. "An efficient moments-based inference method for within-host bacterial infection dynamics," PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-27, November.

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