Department of Environmental and Resource Engineering, Technical University of Demark, DTU Lyngby campus, Kgs. Lyngby, Denmark.
Centre for Computational Biology & Institute of Microbiology and Infection & School of Biosciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom.
PLoS Comput Biol. 2024 Feb 29;20(2):e1011303. doi: 10.1371/journal.pcbi.1011303. eCollection 2024 Feb.
Microbial communities are found in all habitable environments and often occur in assemblages with self-organized spatial structures developing over time. This complexity can only be understood, predicted, and managed by combining experiments with mathematical modeling. Individual-based models are particularly suited if individual heterogeneity, local interactions, and adaptive behavior are of interest. Here we present the completely overhauled software platform, the individual-based Dynamics of Microbial Communities Simulator, iDynoMiCS 2.0, which enables researchers to specify a range of different models without having to program. Key new features and improvements are: (1) Substantially enhanced ease of use (graphical user interface, editor for model specification, unit conversions, data analysis and visualization and more). (2) Increased performance and scalability enabling simulations of up to 10 million agents in 3D biofilms. (3) Kinetics can be specified with any arithmetic function. (4) Agent properties can be assembled from orthogonal modules for pick and mix flexibility. (5) Force-based mechanical interaction framework enabling attractive forces and non-spherical agent morphologies as an alternative to the shoving algorithm. The new iDynoMiCS 2.0 has undergone intensive testing, from unit tests to a suite of increasingly complex numerical tests and the standard Benchmark 3 based on nitrifying biofilms. A second test case was based on the "biofilms promote altruism" study previously implemented in BacSim because competition outcomes are highly sensitive to the developing spatial structures due to positive feedback between cooperative individuals. We extended this case study by adding morphology to find that (i) filamentous bacteria outcompete spherical bacteria regardless of growth strategy and (ii) non-cooperating filaments outcompete cooperating filaments because filaments can escape the stronger competition between themselves. In conclusion, the new substantially improved iDynoMiCS 2.0 joins a growing number of platforms for individual-based modeling of microbial communities with specific advantages and disadvantages that we discuss, giving users a wider choice.
微生物群落存在于所有可居住的环境中,通常以随时间自组织形成的空间结构聚集体形式存在。这种复杂性只有通过将实验与数学建模相结合才能理解、预测和管理。如果个体异质性、局部相互作用和适应性行为是研究的重点,那么基于个体的模型特别适用。在这里,我们介绍了经过全面检修的软件平台——基于个体的微生物群落动态模拟器 iDynoMiCS 2.0,它使研究人员能够指定一系列不同的模型,而无需编程。其关键的新功能和改进包括:(1)大大提高了易用性(图形用户界面、模型指定编辑器、单位转换、数据分析和可视化等)。(2)提高了性能和可扩展性,能够模拟多达 1000 万个代理在 3D 生物膜中的情况。(3)可以使用任何算术函数指定动力学。(4)代理属性可以从正交模块组装,实现灵活的混合搭配。(5)基于力的机械相互作用框架,能够实现吸引力和非球形代理形态,作为推挤算法的替代方案。新的 iDynoMiCS 2.0 已经经过了密集测试,包括单元测试、一系列越来越复杂的数值测试以及基于硝化生物膜的标准基准测试 3。第二个测试案例基于之前在 BacSim 中实现的“生物膜促进利他主义”研究,因为由于合作个体之间的正反馈,竞争结果对不断发展的空间结构非常敏感。我们通过添加形态学来扩展这个案例研究,发现(i)无论生长策略如何,丝状细菌都比球形细菌具有竞争优势;(ii)不合作的丝状细菌比合作的丝状细菌具有竞争优势,因为丝状细菌可以逃避它们之间更强的竞争。总之,新的 iDynoMiCS 2.0 具有显著的改进,加入了越来越多的用于微生物群落基于个体建模的平台,具有我们讨论的特定优势和劣势,为用户提供了更广泛的选择。