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SINGULATOR

In silico simulator of cellular phenomena of biotechnological and biomedical interest

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Features


Powerful & Lightweight

Capable of simulate diffusing and reacting particles with realistic dimensions, and incorporating stochasticity and spatial dependence in a three-dimensional continuous environment.

Validated biological results

All the generated results from various scenarios were validated against theoretical data by expert biologists. This implies being able to perform simulations taking into account basic biophysical and biochemical paradigms.

Powered by MASON

MASON is a fast discrete-event multiagent simulation library core in Java, designed to be the foundation for large custom-purpose Java simulations.

Example cases


Agent-based modelling is being used to represent biological systems with increasing frequency and success. This paper presents the implementation of a new tool for biomolecular reaction modelling in the open source Multiagent Simulator of Neighborhoods framework.The rationale behind this new tool is the necessity to describe interactions at the molecular level to be able to grasp emergent and meaningful biological behaviour. We are particularly interested in characterising and quantifying the various effects that facilitate biocatalysis. Enzymes may display high specificity for their substrates and this information is crucial to the engineering and optimisation of bioprocesses.

Simulation results demonstrate that molecule distributions, reaction rate parameters, and structural parameters can be adjusted separately in the simulation allowing a comprehensive study of individual effects in the context of realistic cell environments. While higher percentage of collisions with occurrence of reaction increases the affinity of the enzyme to the substrate, a faster reaction (i.e., turnover number) leads to a smaller number of time steps. Slower diffusion rates and molecular crowding (physical hurdles) decrease the collision rate of reactants, hence reducing the reaction rate, as expected. Also, the random distribution of molecules affects the results significantly.

Recent computational methodologies, such as individual-based modelling, pave the way to the search for explanatory insight into the collective behaviour of molecules. Many reviews offer an up-to-date perspective about such methodologies, but little is discussed about the practical information requirements involved. The biological information used as input should be easily and routinely determined in the laboratory, publicly available and, preferably, organized in programmatically accessible databases.

This review is the first to provide a systematic and comprehensive overview of available resources for the modelling of metabolic events at the molecular scale. The glycolysis pathway of Escherichia coli , which is one of the most studied pathways in Microbiology, serves as case study. This curation addressed structural information about E. coli (i.e. defining the simulation environment), the reactions forming the glycolysis pathway including the enzymes and the metabolites (i.e. the molecules to be represented), the kinetics of each reaction (i.e. behavioural logic of the molecules) and diffusion parameters for all enzymes and metabolites (i.e. molecule movement in the environment).

Furthermore, the interpretation of relevant biological features, such as molecular diffusion and enzyme kinetics, and the connection of experimental determination and simulation validation are detailed. Notably, the information from classical theories, such as enzymatic rates and diffusion coefficients, is translated to simulation parameters, such as collision efficiency and particle velocity.

This work presents a molecular-scale agent-based model for the simulation of enzymatic reactions at experimentally measured concentrations. The model incorporates stochasticity and spatial dependence, using diffusing and reacting particles with physical dimensions. We developed strategies to adjust and validate the enzymatic rates and diffusion coefficients to the information required by the computational agents, i.e., collision efficiency, interaction logic between agents, the time scale associated with interactions (e.g., kinetics), and agent velocity. Also, we tested the impact of molecular location (a source of biological noise) in the speed at which the reactions take place.

Simulations were conducted for experimental data on the 2-hydroxymuconate tautomerase (EC 5.3.2.6, UniProt ID Q01468) and the Steroid Delta-isomerase (EC 5.3.3.1, UniProt ID P07445). Obtained results demonstrate that our approach is in accordance to existing experimental data and long-term biophysical and biochemical assumptions.

Agent-based simulations are increasingly popular in exploring and understanding cellular systems, but the natural complexity of these systems and the desire to grasp different modelling levels demand cost-effective simulation strategies and tools.

In this context, the present paper introduces novel sequential and distributed approaches for the three-dimensional agent-based simulation of individual molecules in cellular events. These approaches are able to describe the dimensions and position of the molecules with high accuracy and thus, study the critical effect of spatial distribution on cellular events. Moreover, two of the approaches allow multi-thread high performance simulations, distributing the three-dimensional model in a platform independent and computationally efficient way.

Evaluation addressed the reproduction of molecular scenarios and different scalability aspects of agent creation and agent interaction. The three approaches simulate common biophysical and biochemical laws faithfully. The distributed approaches show improved performance when dealing with large agent populations while the sequential approach is better suited for small to medium size agent populations.

Evaluation addressed the reproduction of molecular scenarios and different scalability aspects of agent creation and agent interaction. The three approaches simulate common biophysical and biochemical laws faithfully. The distributed approaches show improved performance when dealing with large agent populations while the sequential approach is better suited for small to medium size agent populations.

Experimental incapacity to track microbe-microbe interactions in structures like biofilms, and the complexity inherent to the mathematical modelling of those interactions, raises the need for feasible, alternative modelling approaches.

This work proposes an agent-based representation of the diffusion of N-acyl homoserine lactones (AHL) in a multicellular environment formed by Pseudomonas aeruginosa and Candida albicans. Depending on the spatial location, C. albicans cells were variably exposed to AHLs, an observation that might help explain why phenotypic switching of individual cells in biofilms occurred at different time points. The simulation and algebraic results were similar for simpler scenarios, although some statistical differences could be observed (p < 0.05).

The model was also successfully applied to a more complex scenario representing a small multicellular environment containing C. albicans and P. aeruginosa cells encased in a 3-D matrix. Further development of this model may help create a predictive tool to depict biofilm heterogeneity at the single-cell level.

Publication's timeline


  • Hindawi journal

    October 2014

    Agent-Based Spatiotemporal Simulation of Biomolecular Systems within the Open Source MASON Framework

    Gael Pérez-Rodríguez, Martín Pérez-Pérez, Daniel Glez-Peña, Florentino Fdez-Riverola, Nuno F. Azevedo, and Anália Lourenço, “Agent-Based Spatiotemporal Simulation of Biomolecular Systems within the Open Source MASON Framework,” BioMed Research International, vol. 2015, Article ID 769471, 12 pages, 2015. https://doi.org/10.1155/2015/769471.

    See the publication in the Journal website.

  • Oxford journal

    October 2015

    Computational resources and strategies to construct single-molecule metabolic models of microbial cells

    Denise Gameiro, Martín Pérez-Pérez, Gael Pérez-Rodríguez, Gonçalo Monteiro, Nuno F. Azevedo, Anália Lourenço; Computational resources and strategies to construct single-molecule metabolic models of microbial cells, Briefings in Bioinformatics, Volume 17, Issue 5, 1 September 2016, Pages 863–876, https://doi.org/10.1093/bib/bbv096

    See the publication in the Journal website.

  • EMBL symposium

    October 2015

    Modelling Biological Noise in Microbial Cells: Single Particular Simulation of Molecular Diffusion and Enzyme Kinetics

    Lourenço A, Gameiro D, Perez Perez M, Perez Rodriguez G, Monteiro G, Fdez-Riverola F, Azevedo NF. Modelling Biological Noise in Microbial Cells: Single Particular Simulation of Molecular Diffusion and Enzyme Kinetics. 17th EMBL PhD Symp Heidelberg; 2015. p. 34.

    See the short talk in the Symposium website.

  • @AMS conferences

    March 2016

    Variable spatial molecular location as source of biological noise

    Azevedo NF, Perez Rodriguez G, Gameiro D, Perez Perez M, Lourenço A. Variable spatial molecular location as source of biological noise. Individ Microbe Single-cell Anal Agent-based Model Whasington, DC: American Society for Microbiology; 2016. p. 18.

    See the short talk in the Conference website.

  • American Chemistry Society journal

    April 2016

    Single Molecule Simulation of Diffusion and Enzyme Kinetics

    Single Molecule Simulation of Diffusion and Enzyme Kinetics Gael Pérez-Rodríguez, Denise Gameiro, Martín Pérez-Pérez, Anália Lourenço, and Nuno F. Azevedo The Journal of Physical Chemistry B 2016 120 (16), 3809-3820 DOI: 10.1021/acs.jpcb.5b12544

    See the publication in the Journal website.

  • Elsevier journal

    June 2016

    High performance computing for three-dimensional agent-based molecular models

    G. Pérez-Rodríguez, M. Pérez-Pérez, F. Fdez-Riverola, A. Lourenço, High performance computing for three-dimensional agent-based molecular models, Journal of Molecular Graphics and Modelling, Volume 68, 2016, Pages 68-77, ISSN 1093-3263, https://doi.org/10.1016/j.jmgm.2016.06.001.

    See the publication in the Journal website.

  • Taylor & Francis journal

    February 2018

    Agent-based model of diffusion of N-acyl homoserine lactones in a multicellular environment of Pseudomonas aeruginosa and Candida albicans

    Gael Pérez-Rodríguez, Sónia Dias, Martín Pérez-Pérez, Florentino Fdez-Riverola, Nuno F. Azevedo & Anália Lourenço (2018) Agent-based model of diffusion of N-acyl homoserine lactones in a multicellular environment of Pseudomonas aeruginosa and Candida albicans, Biofouling, 34:3, 335-345, DOI: 10.1080/08927014.2018.1440392

    See the publication in the Journal website.

  • Elsevier journal

    March 2019

    Application of agent-based modelling to assess single-molecule transport across the cell envelope of E. coli

    P. Maia, G. Pérez-Rodríguez, M. Pérez-Pérez, F. Fdez-Riverola, A. Lourenço, N.F. Azevedo, Application of agent-based modelling to assess single-molecule transport across the cell envelope of E. coli, Comput. Biol. Med. (2019). doi:10.1016/J.COMPBIOMED.2019.02.020.

    See the publication in the Journal website.

  • To be continued...

Team


Nuno Azevedo


nazevedo@fe.up.pt

Project leader

Anália Lourenço


analia@uvigo.es

Project leader

Florentino Fdez-Riverola


riverola@uvigo.es

Since 2013

Gael Pérez Rodríguez


gaeperez@uvigo.es

Main developer

Martín Pérez Pérez


martiperez@uvigo.es

Since 2013

Denise Gameiro


Since 2015

Gonçalo Monteiro


Since 2015

Sónia Dias


Since 2018

Paulo Maia


Since 2018

Location


Department of Computer Science, University of Vigo ESEI - Escuela Superior de Ingeniería Informática (Edificio politécnico) Campus Universitario As Lagoas s/n 32004 Ourense, Spain

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