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In silico analysis of antibiotic-induced Clostridium difficile infection: Remediation techniques and biological adaptations.

ABSTRACT: In this paper we study antibiotic-induced C. difficile infection (CDI), caused by the toxin-producing C. difficile (CD), and implement clinically-inspired simulated treatments in a computational framework that synthesizes a generalized Lotka-Volterra (gLV) model with SIR modeling techniques. The gLV model uses parameters derived from an experimental mouse model, in which the mice are administered antibiotics and subsequently dosed with CD. We numerically identify which of the experimentally measured initial conditions are vulnerable to CD colonization, then formalize the notion of CD susceptibility analytically. We simulate fecal transplantation, a clinically successful treatment for CDI, and discover that both the transplant timing and transplant donor are relevant to the the efficacy of the treatment, a result which has clinical implications. We incorporate two nongeneric yet dangerous attributes of CD into the gLV model, sporulation and antibiotic-resistant mutation, and for each identify relevant SIR techniques that describe the desired attribute. Finally, we rely on the results of our framework to analyze an experimental study of fecal transplants in mice, and are able to explain observed experimental results, validate our simulated results, and suggest model-motivated experiments.

SUBMITTER: Jones EW

PROVIDER: S-EPMC5833281 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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In silico analysis of antibiotic-induced Clostridium difficile infection: Remediation techniques and biological adaptations.

Jones Eric W EW Carlson Jean M JM

PLoS computational biology 20180216 2

In this paper we study antibiotic-induced C. difficile infection (CDI), caused by the toxin-producing C. difficile (CD), and implement clinically-inspired simulated treatments in a computational framework that synthesizes a generalized Lotka-Volterra (gLV) model with SIR modeling techniques. The gLV model uses parameters derived from an experimental mouse model, in which the mice are administered antibiotics and subsequently dosed with CD. We numerically identify which of the experimentally meas ...[more]

PMID: 29451873

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Project description:Clostridium difficile epidemiology has changed in recent years, with the emergence of highly virulent types associated with severe infections, high rates of recurrences and mortality. Antibiotic resistance plays an important role in driving these epidemiological changes and the emergence of new types. While clindamycin resistance was driving historical endemic types, new types are associated with resistance to fluoroquinolones. Furthermore, resistance to multiple antibiotics is a common feature of the newly emergent strains and, in general, of many epidemic isolates. A reduced susceptibility to antibiotics used for C. difficile infection (CDI) treatment, in particular to metronidazole, has recently been described in several studies. Furthermore, an increased number of strains show resistance to rifamycins, used for the treatment of relapsing CDI. Several mechanisms of resistance have been identified in C. difficile, including acquisition of genetic elements and alterations of the antibiotic target sites. The C. difficile genome contains a plethora of mobile genetic elements, many of them involved in antibiotic resistance. Transfer of genetic elements among C. difficile strains or between C. difficile and other bacterial species can occur through different mechanisms that facilitate their spread. Investigations of the fitness cost in C. difficile indicate that both genetic elements and mutations in the molecular targets of antibiotics can be maintained regardless of the burden imposed on fitness, suggesting that resistances may persist in the C. difficile population also in absence of antibiotic selective pressure. The rapid evolution of antibiotic resistance and its composite nature complicate strategies in the treatment and prevention of CDI. The rapid identification of new phenotypic and genotypic traits, the implementation of effective antimicrobial stewardship and infection control programs, and the development of alternative therapies are needed to prevent and contain the spread of resistance and to ensure an efficacious therapy for CDI.

Dataset Information

In silico analysis of antibiotic-induced Clostridium difficile infection: Remediation techniques and biological adaptations.

Publications

In silico analysis of antibiotic-induced Clostridium difficile infection: Remediation techniques and biological adaptations.

Similar Datasets

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