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Mathematical relationship between cytokine concentrations and pathogen levels during infection

  • Stony Brook University

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The relationship between concentrations of cytokines and microbial pathogen levels during infection is not clear. In a sub-lethal murine infection model using Gram-negative bacterial pathogen Yersinia pseudotuberculosis, the serum concentrations (C) of pro-inflammatory cytokines tumor necrosis factor α (TNFα), interferon γ (IFNγ), interleukine-1β (IL-1β) and interleukine-18 (IL-18) formed a mathematical relationship with the splenic pathogen levels (P) as measured by colony forming unit. Naming parameters "m" and "k" for magnitude and kinetics, respectively, the relationship is depicted as C= mPk. When reanalyzing the TNFα and IFNγ concentrations and the bacterial levels that were determined by other groups during infection with another strain of Y. pseudotuberculosis or with Yersinia pestis, this relationship was maintained. Interestingly, the changes in the values of "m" and "k" were consistent with the progress of the host immune response during infection; while deviation from this relationship was observed in individuals that seemed to be unable to control infection. Furthermore, in a murine model of ricin intoxication the local concentrations of the cytokine monocyte chemotactic protein 1 (MCP-1) and the concentrations of injected castor bean toxin ricin also conform to this relationship. C= mPk could be a general relationship in host cytokine response to pathogens or pathogen-associated molecular patterns. If confirmed, this type of analysis will be very useful in identifying the steps in a host immune response with which a pathogen interferes. It will also help to determine the specific functions of a host factor in the immune response.

Original languageEnglish
Pages (from-to)158-162
Number of pages5
JournalCytokine
Volume53
Issue number2
DOIs
StatePublished - Feb 2011

Keywords

  • Bacterial infection
  • Bioinformatics analysis
  • Cytokine
  • Pathogen level

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