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The Within-Host Population Dynamics of Normal Flora in the Presence of an Invading Pathogen and Antibiotic Treatments  

Kim, Jung-Mo (Department of Chemical and Biological Engineering, Korea University)
Lee, Dong-Hwan (Department of Chemical and Biological Engineering, Korea University)
Song, Yoon-Seok (Department of Chemical and Biological Engineering, Korea University)
Kang, Seong-Woo (Department of Chemical and Biological Engineering, Korea University)
Kim, Seung-Wook (Department of Chemical and Biological Engineering, Korea University)
Publication Information
Journal of Microbiology and Biotechnology / v.17, no.1, 2007 , pp. 146-153 More about this Journal
Abstract
A mathematical competition model between normal flora and an invading pathogen was devised to allow analysis of bacterial infections in a host. The normal flora includes the various microorganisms that live on or within the host and act as a primary human immune system. Despite the important role of the normal flora, no mathematical study has been undertaken on models of the interaction between it and invading pathogens against a background of antibiotic treatment. To quantify key elements of bacterial behavior in a host, pairs of nonlinear differential equations were used to describe three categories of human health conditions, namely, healthy, latent infection, and active infection. In addition, a cutoff value was proposed to represent the minimum population level required for survival. The recovery of normal flora after antibiotic treatment was also included in the simulation because of its relation to human health recovery. The significance of each simulation parameter for the bacterial growth model was investigated. The devised simulation showed that bacterial proliferation rate, carrying capacity, initial population levels, and competition intensity have a significant effect on bacterial behavior. Consequently, a model was established to describe competition between normal flora and an infiltrating pathogen. Unlike other population models, the recovery process described by the devised model can describe the human health recovery mechanism.
Keywords
Population dynamics; antibiotic treatments; recovery process; normal flora; cutoff value;
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Times Cited By Web Of Science : 1  (Related Records In Web of Science)
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1 Cooper, B. S., G. F. Medley, S. P. Stone, C. C. Kibbler, B. D. Cookson, J. A. Roberts, G. Duckworth, R. Lai, and S. Ebrahim. 2004. Methicillin-resistant Staphylococcus aureus in hospitals and the community: Stealth dynamics and control catastrophes. Proc. Natl. Acad. Sci. USA 101: 10223-10228
2 Keitt, T. H., M. A. Lewis, and R. D. Holt. 2001. Allee effects, invasion pinning, and species' borders. Am. Nat. 157: 203-216   DOI   ScienceOn
3 Kim, J. N., S. J. Lee, H. S. Lee, and H. G. Rihe. 2005. Inactivation of mutS leads to multiple-drug resistance in Pseudomonas putida ATCC 12633. J. Microbiol. Biotechnol. 15: 1214-1220   과학기술학회마을
4 Kuperman, M. N. and M. Kenkre. 2003. Applicability of the Fisher equation to bacterial population dynamics. Phys. Rev. E. 67: 051921:1-5
5 Levin, B. R., M. Lipsitch, and S. Bonhoeffer. 1999. Population biology, evolution, and infectious disease: Convergence and synthesis. Science 283: 806-809   DOI
6 Prescott, L., J. Harley, and D. Kelin. 2003. Microbiology, 5th Ed. New York, McGraw-Hill
7 Smith, D. L., J. Dushoff, E. Perencevich, A. D. Harris, and S. A. Levin. 2004. Persistent colonization and the spread of antibiotic resistance in nosocomial pathogens: Resistance is a regional problem. Proc. Natl. Acad. Sci. USA 101: 3709- 3714
8 Bergstrom, C. T., M. Lo, and M. Lipsitch. 2004. Ecological theory suggests that antimicrobial cycling will not reduce antimicrobial resistance in hospitals. Proc. Natl. Acad. Sci. USA 101: 13285-13290
9 Bonten, M. J. M., D. J. Austin, and M. Lipsitch. 2001. Understanding the spread of antibiotic resistant pathogens in hospitals: Mathematical models as a tool for control. Clin. Infect. Dis. 33: 1739-1746   DOI   ScienceOn
10 Drusano, G. L. 2004. Antimicrobial pharmacodynamics: Critical interactions of 'bug and drug'. Nature Rev. 2: 289- 300   DOI   ScienceOn
11 Martinez, J. L. and F. Baquero. 2002. Interactions among strategies associated with bacterial infection: Pathogenicity, epidemicity, and antibiotic resistance. Clin. Microbiol. Rev. 15: 647-679   DOI   ScienceOn
12 Lee, K., H. S. Joo, H. S. Joo, Y. H. Yang, E. J. Song, and B. G. Kim. 2006. Proteomics for Streptomyces: 'Industrial proteomics' for antibiotics. J. Microbiol. Biotechnol. 16: 331-348   과학기술학회마을
13 Cho, B. G., C. H. Kim, B. K. Lee, and S. H. Cho. 2005. Comparison of antibiotic resistance of blood culture strains and saprophytic isolates in the presence of biofilms, formed by the intercellular adhesion (ica) gene cluster in Staphylococcus epidermidis. J. Microbiol. Biotechnol. 15: 728-733   과학기술학회마을
14 Pelupessy, I., M. J. M. Bonten, and O. Diekmann. 2002. How to assess the relative importance of different colonization routes of pathogens within hospital settings. Proc. Natl. Acad. Sci. USA 99: 5601-5605
15 Webb, G. F., E. M. C. D'Agata, P. Magal, and S. Ruan. 2005. A model of antibiotic-resistant bacterial epidemics in hospitals. Proc. Natl. Acad. Sci. USA 102: 13343-13348
16 Lipsitch, M., C. T. Bergstrom, and R. Levin. 2005. The epidemiology of antibiotic resistance in hospitals: Paradoxes and prescriptions. Proc. Natl. Acad. Sci. USA 97: 1938- 1943
17 Jung, H. K. and S. D. Kim. 2005. An antifungal antibiotic purified from Bacillus megaterium KL39, a biocontrol agent of red-pepper phytophtora-blight disease. J. Microbiol. Biotechnol. 15: 1001-1010   과학기술학회마을
18 Dugatkin, L. A., M. Perin, and R. Atlas. 2005. Antibiotic resistance and the evolution of group-beneficial traits II: A metapopulation model. J. Theor. Biol. 236: 392-396   DOI   ScienceOn
19 Centers for disease control and prevention NNIS system. 2001. National Nosocomial Infections Surveillance (NNIS) system report, data summary from January 1992-June 2001, issued August 2001. Am. J. Infect. Control 29: 404- 421   DOI   ScienceOn
20 Ganusov, V. V., C. T. Bergstrom, and R. Antia. 2002. Withinhost population dynamics and the evolution of microparasites in a heterogeneous host population. Evolution 56: 213- 222   DOI
21 Levin, B. R. and R. Antia. 2001. Why we don't get sick: The within-host population dynamics of bacterial infection. Science 292: 1112-1115   DOI
22 Austin, D. J., K. G. Kristinsson, and M. R. Anderson. 1999. The relationship between the volume of antimicrobial consumption in human communities and the frequency of resistance. Proc. Natl. Acad. Sci. USA 96: 1152-1156