title: Modelling conjugation with stochastic differential equations.
abstract: Conjugation is an important mechanism involved in the transfer of resistance between bacteria. In this article a stochastic differential equation based model consisting of a continuous time state equation and a discrete time measurement equation is introduced to model growth and conjugation of two Enterococcus faecium strains in a rich exhaustible media. The model contains a new expression for a substrate dependent conjugation rate. A maximum likelihood based method is used to estimate the model parameters. Different models including different noise structure for the system and observations are compared using a likelihood-ratio test and Akaike's information criterion. Experiments indicating conjugation on the agar plates selecting for transconjugants motivates the introduction of an extended model, for which conjugation on the agar plate is described in the measurement equation. This model is compared to the model without plate conjugation. The modelling approach described in this article can be applied generally when modelling dynamical systems.
authors: DTU Informatics, Technical University of Denmark, Richard Petersens Plads, Building 321, DK-2800, Kgs. Lyngby, Denmark. krp@imm.dtu.dk
authors: K R
authors: KR
authors: Philipsen
authors: L E
authors: LE
authors: Christiansen
authors: H
authors: H
authors: Hasman
authors: H
authors: H
authors: Madsen
mesh_terms: D000362:Agar / Q000737:chemistry; D000465:Algorithms; D003227:Conjugation, Genetic; D024881:Drug Resistance, Bacterial; D013293:Enterococcus faecalis / Q000378:metabolism*; D005821:Genetic Techniques; D006801:Humans; D016013:Likelihood Functions; D008390:Markov Chains; D008954:Models, Biological; D015233:Models, Statistical; D008962:Models, Theoretical; D013269:Stochastic Processes; D013997:Time Factors
chemical_list: D000362:Agar