A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES)

Biology Direct

Marcelino Campos²  Carlos Llorens¹  José M. Sempere²  Ricardo Futami¹  Irene Rodriguez⁵  Purificación Carrasco⁴  Rafael Capilla¹  Amparo Latorre³  Teresa M. Coque⁵  Andres Moya³  Fernando Baquero⁵ 

[1] Biotechvana, Valencia, CEEI Building, Benjamin Franklin Av. 12, Valencia Technological Park, Paterna, 46980, Spain

[2] Department of Information Systems and Computation (DSIC), Polytechnic University of Valencia, Camino de Vera, Valencia, 46022, Spain

[3] Foundation for the Promotion of Health and Biomedical Research in the Valencian Community (FISABIO) - Public Health, Avenida de Cataluña 21, Valencia, 46020, Spain

[4] Cavanilles Institute of Biodiversity and Evolutionary Biology, University of Valencia, C/ Catedrático José Beltrán 2, Paterna, 46980, Valencia, Spain

[5] Network Research Center for Epidemiology and Public Health (CIBER-ESP), Madrid, Spain

关键词: Essential nesting;    Antibiotic resistance;    P-system;    Membrane computing;   

Others  :  1225803
DOI  :  10.1186/s13062-015-0070-9

 received in 2015-04-08, accepted in 2015-07-31,  发布年份 2015

【 摘 要 】

Background

Antibiotic resistance is a major biomedical problem upon which public health systems demand solutions to construe the dynamics and epidemiological risk of resistant bacteria in anthropogenically-altered environments. The implementation of computable models with reciprocity within and between levels of biological organization (i.e. essential nesting) is central for studying antibiotic resistances. Antibiotic resistance is not just the result of antibiotic-driven selection but more properly the consequence of a complex hierarchy of processes shaping the ecology and evolution of the distinct subcellular, cellular and supra-cellular vehicles involved in the dissemination of resistance genes. Such a complex background motivated us to explore the P-system standards of membrane computing an innovative natural computing formalism that abstracts the notion of movement across membranes to simulate antibiotic resistance evolution processes across nested levels of micro- and macro-environmental organization in a given ecosystem.

Results

In this article, we introduce ARES (Antibiotic Resistance Evolution Simulator) a software device that simulates P-system model scenarios with five types of nested computing membranes oriented to emulate a hierarchy of eco-biological compartments, i.e. a) peripheral ecosystem; b) local environment; c) reservoir of supplies; d) animal host; and e) host’s associated bacterial organisms (microbiome). Computational objects emulating molecular entities such as plasmids, antibiotic resistance genes, antimicrobials, and/or other substances can be introduced into this framework and may interact and evolve together with the membranes, according to a set of pre-established rules and specifications. ARES has been implemented as an online server and offers additional tools for storage and model editing and downstream analysis.

Conclusions

The stochastic nature of the P-system model implemented in ARES explicitly links within and between host dynamics into a simulation, with feedback reciprocity among the different units of selection influenced by antibiotic exposure at various ecological levels. ARES offers the possibility of modeling predictive multilevel scenarios of antibiotic resistance evolution that can be interrogated, edited and re-simulated if necessary, with different parameters, until a correct model description of the process in the real world is convincingly approached. ARES can be accessed at http//gydb.org/ares.

Reviewers

This article was reviewed by Eugene V. Koonin, and Eric Bapteste.

【 授权许可】

   
2015 Campos et al.

【 图 表 】

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