Simulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model

ABSTRACT Membrane computing is a bio-inspired computing paradigm whose devices are the so-called membrane systems or P systems. The P system designed in this work reproduces complex biological landscapes in the computer world. It uses nested “membrane-surrounded entities” able to divide, propagate,...

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Autores principales:	Marcelino Campos, Rafael Capilla, Fernando Naya, Ricardo Futami, Teresa Coque, Andrés Moya, Val Fernandez-Lanza, Rafael Cantón, José M. Sempere, Carlos Llorens, Fernando Baquero
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2019
Materias:	antibiotic resistance membrane computing multilevel computer modeling mathematical modeling Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/fb5a7ede72e248dcbf7571f3e935de0c
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spelling	oai:doaj.org-article:fb5a7ede72e248dcbf7571f3e935de0c2021-11-15T15:55:14ZSimulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model10.1128/mBio.02460-182150-7511https://doaj.org/article/fb5a7ede72e248dcbf7571f3e935de0c2019-02-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mBio.02460-18https://doaj.org/toc/2150-7511ABSTRACT Membrane computing is a bio-inspired computing paradigm whose devices are the so-called membrane systems or P systems. The P system designed in this work reproduces complex biological landscapes in the computer world. It uses nested “membrane-surrounded entities” able to divide, propagate, and die; to be transferred into other membranes; to exchange informative material according to flexible rules; and to mutate and be selected by external agents. This allows the exploration of hierarchical interactive dynamics resulting from the probabilistic interaction of genes (phenotypes), clones, species, hosts, environments, and antibiotic challenges. Our model facilitates analysis of several aspects of the rules that govern the multilevel evolutionary biology of antibiotic resistance. We examined a number of selected landscapes where we predict the effects of different rates of patient flow from hospital to the community and vice versa, the cross-transmission rates between patients with bacterial propagules of different sizes, the proportion of patients treated with antibiotics, and the antibiotics and dosing found in the opening spaces in the microbiota where resistant phenotypes multiply. We also evaluated the selective strengths of some drugs and the influence of the time 0 resistance composition of the species and bacterial clones in the evolution of resistance phenotypes. In summary, we provide case studies analyzing the hierarchical dynamics of antibiotic resistance using a novel computing model with reciprocity within and between levels of biological organization, a type of approach that may be expanded in the multilevel analysis of complex microbial landscapes. IMPORTANCE The work that we present here represents the culmination of many years of investigation in looking for a suitable methodology to simulate the multihierarchical processes involved in antibiotic resistance. Everything started with our early appreciation of the different independent but embedded biological units that shape the biology, ecology, and evolution of antibiotic-resistant microorganisms. Genes, plasmids carrying these genes, cells hosting plasmids, populations of cells, microbial communities, and host's populations constitute a complex system where changes in one component might influence the other ones. How would it be possible to simulate such a complexity of antibiotic resistance as it occurs in the real world? Can the process be predicted, at least at the local level? A few years ago, and because of their structural resemblance to biological systems, we realized that membrane computing procedures could provide a suitable frame to approach these questions. Our manuscript describes the first application of this modeling methodology to the field of antibiotic resistance and offers a bunch of examples—just a limited number of them in comparison with the possible ones to illustrate its unprecedented explanatory power.Marcelino CamposRafael CapillaFernando NayaRicardo FutamiTeresa CoqueAndrés MoyaVal Fernandez-LanzaRafael CantónJosé M. SempereCarlos LlorensFernando BaqueroAmerican Society for Microbiologyarticleantibiotic resistancemembrane computingmultilevelcomputer modelingmathematical modelingMicrobiologyQR1-502ENmBio, Vol 10, Iss 1 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	antibiotic resistance membrane computing multilevel computer modeling mathematical modeling Microbiology QR1-502
spellingShingle	antibiotic resistance membrane computing multilevel computer modeling mathematical modeling Microbiology QR1-502 Marcelino Campos Rafael Capilla Fernando Naya Ricardo Futami Teresa Coque Andrés Moya Val Fernandez-Lanza Rafael Cantón José M. Sempere Carlos Llorens Fernando Baquero Simulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model
description	ABSTRACT Membrane computing is a bio-inspired computing paradigm whose devices are the so-called membrane systems or P systems. The P system designed in this work reproduces complex biological landscapes in the computer world. It uses nested “membrane-surrounded entities” able to divide, propagate, and die; to be transferred into other membranes; to exchange informative material according to flexible rules; and to mutate and be selected by external agents. This allows the exploration of hierarchical interactive dynamics resulting from the probabilistic interaction of genes (phenotypes), clones, species, hosts, environments, and antibiotic challenges. Our model facilitates analysis of several aspects of the rules that govern the multilevel evolutionary biology of antibiotic resistance. We examined a number of selected landscapes where we predict the effects of different rates of patient flow from hospital to the community and vice versa, the cross-transmission rates between patients with bacterial propagules of different sizes, the proportion of patients treated with antibiotics, and the antibiotics and dosing found in the opening spaces in the microbiota where resistant phenotypes multiply. We also evaluated the selective strengths of some drugs and the influence of the time 0 resistance composition of the species and bacterial clones in the evolution of resistance phenotypes. In summary, we provide case studies analyzing the hierarchical dynamics of antibiotic resistance using a novel computing model with reciprocity within and between levels of biological organization, a type of approach that may be expanded in the multilevel analysis of complex microbial landscapes. IMPORTANCE The work that we present here represents the culmination of many years of investigation in looking for a suitable methodology to simulate the multihierarchical processes involved in antibiotic resistance. Everything started with our early appreciation of the different independent but embedded biological units that shape the biology, ecology, and evolution of antibiotic-resistant microorganisms. Genes, plasmids carrying these genes, cells hosting plasmids, populations of cells, microbial communities, and host's populations constitute a complex system where changes in one component might influence the other ones. How would it be possible to simulate such a complexity of antibiotic resistance as it occurs in the real world? Can the process be predicted, at least at the local level? A few years ago, and because of their structural resemblance to biological systems, we realized that membrane computing procedures could provide a suitable frame to approach these questions. Our manuscript describes the first application of this modeling methodology to the field of antibiotic resistance and offers a bunch of examples—just a limited number of them in comparison with the possible ones to illustrate its unprecedented explanatory power.
format	article
author	Marcelino Campos Rafael Capilla Fernando Naya Ricardo Futami Teresa Coque Andrés Moya Val Fernandez-Lanza Rafael Cantón José M. Sempere Carlos Llorens Fernando Baquero
author_facet	Marcelino Campos Rafael Capilla Fernando Naya Ricardo Futami Teresa Coque Andrés Moya Val Fernandez-Lanza Rafael Cantón José M. Sempere Carlos Llorens Fernando Baquero
author_sort	Marcelino Campos
title	Simulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model
title_short	Simulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model
title_full	Simulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model
title_fullStr	Simulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model
title_full_unstemmed	Simulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model
title_sort	simulating multilevel dynamics of antimicrobial resistance in a membrane computing model
publisher	American Society for Microbiology
publishDate	2019
url	https://doaj.org/article/fb5a7ede72e248dcbf7571f3e935de0c
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Simulating Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model

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