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A New Improved and Extended Version of the Multicell Bacterial Simulator gro
Martín Gutiérrez1,2, Paula Gregorio-Godoy1, Guillermo Pérez Del Pulgar1
1Departamento de Inteligencia Artificial, ETSIINF, Universidad Politécnica de Madrid , 28040 Madrid, Spain.
ACS Synthetic Biology
|April 26, 2017
Summary
The enhanced gro simulator now runs 10-100x faster, simulating large microbial colonies and complex cell behaviors. New features improve synthetic biology and evolutionary microbiology research.
Area of Science:
- Synthetic Biology
- Computational Biology
- Microbiology
Background:
- The gro programming language is a synthetic biology tool for simulating cell growth and communication.
- Existing limitations in simulation speed and functionality hindered complex biological system modeling.
Purpose of the Study:
- To present significant performance and feature enhancements to the gro cell programming language and simulator.
- To expand gro's capabilities for simulating multicellular systems, gene expression, and intercellular communication.
Main Methods:
- Implemented a new shoving algorithm in the CellEngine library for faster spatial interaction resolution.
- Introduced CellPro for probabilistic timed automata-based gene expression simulation and ProSpec for protein-driven behavior specification.
- Added CellNutrient for Monod-based growth modeling and enhanced CellSignals for intercellular communication, including bacterial conjugation.
Main Results:
- Achieved 1-2 orders of magnitude performance improvement, enabling simulation of 10^5 cells in under 10 minutes.
- Integrated new libraries for enhanced spatial interactions, gene expression, nutrient uptake, and intercellular signaling.
- Demonstrated versatility through studies in synthetic biology and evolutionary microbiology.
Conclusions:
- The upgraded gro simulator is a powerful, fast prototyping tool for diverse biological systems.
- New functionalities significantly enhance capabilities for modeling synthetic biology designs and evolutionary processes.
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