Determination of the optimal bacteriophage dose to control Pseudomonas aeruginosa using evolutionary programming and stochastic kinetics

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1 Department of Chemical Engineering, Universidad de Los Andes, Bogota, CUNDINAMARCA, Colombia
2 Department of Biological Sciences, Universidad de Los Andes, Bogota, CUNDINAMARCA, Colombia
DOI
10.7287/peerj.preprints.2359v1
Published
Accepted
Subject Areas
Computational Biology, Microbiology
Keywords
Bacteriophage, model, dose, stochastic
Copyright
© 2016 Ardila et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Ardila DC, Castro JD, Holguín AV, Clavijo V, Prada C, Vives MJ, Gonzalez Barrios AFA. 2016. Determination of the optimal bacteriophage dose to control Pseudomonas aeruginosa using evolutionary programming and stochastic kinetics. PeerJ Preprints 4:e2359v1

Abstract

Phage-therapy is a promising alternative against pathogenic, multiple drug resistant bacteria. In this work we propose an algorithm to determine the optimal bacteriophage dose able to minimize a population of Pseudomonas aeruginosa. Reverse engineering was used to determine the kinetic parameters; subsequently, a bi-level optimization platform was implemented for a model based on evolutionary programming. Our prediction of optimal dose was tested in vitro with planktonic cultures of P. aeruginosa. From the data obtained, we conclude that reverse engineering and stochastic simulations are a useful approach to find optimal phage doses against pathogenic bacteria, an important step for the implementation of phage-therapy.

Author Comment

This is a submission to PeerJ for review.