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 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.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 16, 2018
Accession Number
AD1079482

Entities

People

  • Eric W. Jones
  • Jean M. Carlson

Organizations

  • University of California, Santa Barbara

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Anti-Bacterial Agents
  • Anti-Infective Agents
  • Applied Mathematics
  • Bacteria
  • Bile
  • Computational Science
  • Differential Equations
  • Equations
  • Gut Microbiome
  • Health Services
  • Infection
  • Mathematical Analysis
  • Microbiology
  • Microbiomes
  • Microorganisms
  • Therapy
  • Tissue Donors

Readers

  • Microbial Pathology
  • Neural Network Machine Learning.
  • Oncology

Technology Areas

  • Biotechnology