Computational Methods to Model Persistence.

TitleComputational Methods to Model Persistence.
Publication TypeJournal Article
Year of Publication2016
AuthorsVandervelde, A., R. Loris, J. Danckaert, and L. Gelens
JournalMethods Mol Biol
Volume1333
Pagination207-40
Date Published2016
ISSN1940-6029
KeywordsAnti-Bacterial Agents, Bacteria, Biofilms, Computational Biology, Drug Resistance, Bacterial, Humans
Abstract

Bacterial persister cells are dormant cells, tolerant to multiple antibiotics, that are involved in several chronic infections. Toxin-antitoxin modules play a significant role in the generation of such persister cells. Toxin-antitoxin modules are small genetic elements, omnipresent in the genomes of bacteria, which code for an intracellular toxin and its neutralizing antitoxin. In the past decade, mathematical modeling has become an important tool to study the regulation of toxin-antitoxin modules and their relation to the emergence of persister cells. Here, we provide an overview of several numerical methods to simulate toxin-antitoxin modules. We cover both deterministic modeling using ordinary differential equations and stochastic modeling using stochastic differential equations and the Gillespie method. Several characteristics of toxin-antitoxin modules such as protein production and degradation, negative autoregulation through DNA binding, toxin-antitoxin complex formation and conditional cooperativity are gradually integrated in these models. Finally, by including growth rate modulation, we link toxin-antitoxin module expression to the generation of persister cells.

DOI10.1007/978-1-4939-2854-5_17
Alternate JournalMethods Mol. Biol.
PubMed ID26468111
Research group: