Controlling Information Propagation in Biofilms with Molecular Communication - 1=Biomaterials and tissue engineering - 2 = Engineering

背景：我们已经开始认识到细菌不仅是严格意义上的单细胞生物，而且对环境条件具有复杂的协调适应性。细菌的局部菌落具有多细胞组织和细胞分化的能力。一种常见的结构是生物膜，它在某些情况下（例如，医学）是一种障碍，但在其他情况下（例如，微生物燃料电池，废物修复）可能是有益的。虽然生物膜具有抵御外部威胁的能力，但它们保持着复杂的内部结构，可能有助于协调行为和信息共享。这些结构作为通信渠道的使用还没有得到很好的理解，但提供了对信息传播建模和控制如何有效地进行传播的机会。目的：本项目旨在引入一种通信理论方法来理解和控制生物膜内部信号。目的：1)建立分子信号在嵌入式生物膜通道中传播的数学模型。2)建立通信模型，量化生物膜通道的可靠信息吞吐量。3)设计通过破坏或增强生物膜通讯通道来控制生物膜功效的策略。4)生物膜通道湿实验室成像物理模型验证。方法论的新颖性：生物膜通道的以交流为中心的模型尚不存在。我们将基于现有的生物膜通道图像，开发越来越复杂的新型物理系统模型。通道几何结构的简化将使现有的信号传播模型和为理想分子通信系统开发的结果得以应用，这样我们就可以将端到端通道的统计数据描述为简化系统的聚合。新的端到端信道模型将实现相应的通信分析，其中我们提出现实的信令方案，然后描述成功信息传输的可能性。一旦我们对生物膜通道的通信能力有了理解和直觉，我们将能够确定系统对参数扰动最敏感的地方。这将使我们能够预测控制生物膜信号和设计物理验证实验的合适策略。

Context: We have begun to recognize bacteria as not strictly unicellular organisms but also having complex coordinated adaptability to environmental conditions. Localised colonies of bacteria have the capacity of a multicellular organization and cellular differentiation. One common structure is the biofilm, which is a hindrance in some circumstances (e.g., medicine) but could be beneficial in others (e.g., microbial fuel cells, waste remediation). While biofilms have the resilience to external threats, they maintain sophisticated internal structures that likely facilitate coordinated behaviour and information sharing. The use of these structures as communication channels is not well understood, but provide opportunities to model the propagation of information and control how effectively this can be done.Aims:This project aims to introduce a communication theoretic approach to the understanding and control of internal biofilm signalling.Objectives:1) Develop a mathematical model of how molecular signals propagate in embedded biofilm channels.2) Develop a communication model to quantify the reliable information throughput of biofilm channels.3) Design strategies to control biofilm efficacy by disrupting or enhancing biofilm communication channels.4) Validation of the physical modelling with wet lab imaging of biofilm channels.Novelty of Methodology:A communication-centric model for biofilm channels does not yet exist. We will develop novel physical system models of increasing complexity, based on existing images of biofilm channels. Simplifications of the channel geometry will enable the application of existing signal propagation models and results developed for idealised molecular communication systems, such that we can describe the statistics of an end-to-end channel as an aggregation of simplified systems. The new end-to-end channel model will enable corresponding communications analysis, where we propose realistic signalling schemes and then describe the likelihood of successful information transfer. Once we develop an understanding and intuition about the communication capability of biofilm channels, we will be able to identify where the system is most sensitive to parameter perturbations. This will enable us to predict suitable strategies to control biofilm signalling and design experiments for physical validation.