Development of a computational mechanistic modelling framework for prediction of the development of antimicrobial resistance in homogenous populations

抗微生物剂耐药性被认为是工业和医学面临的主要问题。然而，对于消费品中使用的其他抗菌剂在产生耐药性方面的作用，共识较少。三氯生是消费品中广泛使用的抗菌剂，消费者安全科学委员会1发表了关于三氯生和抗菌剂耐药性的公众意见。尽管进行了大量的努力，但没有定量框架来描述和预测对“活性物质”的耐药性的发展。在这个项目中，我们将开发一个建模框架，使用微生物和分子技术的数据生成和国家的最先进的建模方法和计算能力的框架开发。这将为博士生提供微生物生理学和系统生物学方面的良好培训。同时，学生将通过调查一个对科学和社会都很重要的问题来获得工业研究的经验。拟议的项目将使用系统生物学方法和实验室生成的数据来为将要开发的模型提供信息和参数化。将使用分子动力学、动力学建模和其他方法建立模型。联合利华拥有高性能计算能力（包括公司内部和外部），将用于开发和运行此类模型。三氯生将被用作案例研究。这种化合物是一种经过充分研究的“活性物质”，具有非常特定的靶点和作用机制。主要产出分为以下几类：一个建模框架，整合分子动力学，能够预测突变对三氯生亲和力的影响的FabIA建模框架，该框架将能够预测在三氯生存在下FabI整合到代谢途径中的动力学，该框架考虑了FabI和途径的其他成员中的瞬时细胞间变异，这些变异通过基因复制和基因表达中的随机效应产生。规模模型，该模型将预测均质微生物种群对暴露于抗菌剂的反应，并纳入新模型。

Resistance to antimicrobial agents is recognized as the major issue facing both industry and medicine. However, there is less consensus on the role, in generation of resistance, of other antimicrobials that are used in consumer products. Triclosan is a widely used antimicrobial in consumer products and a public opinion on it and antimicrobial resistance was published by the Scientific Committee on Consumer Safety1. Despite intensive effort, there is no quantitative framework available to describe and predict the development of resistance to 'actives'. In this project we will develop a modelling framework using microbiological and molecular techniques for the data generation and state-of-the art modelling approaches and computational capabilities for the framework development. This will provide the PhD student with an excellent training in microbial physiology and in systems biology. In parallel, the student will gain experience of industrial research through investigating a problem that is important both scientifically and for society.The proposed project will use systems biology approaches and laboratory generated data to inform and parameterise the models that will be developed. Models will be created using molecular dynamics, kinetic modelling and other methodologies. Unilever has access to high performance computing capabilities (both company-based and externally-located), that will be used for development and running of such models. Triclosan will be used as a case study. This compound is a well-studied 'active' with a very specific target and mechanism of action.The key outputs fall under the following categories:A modelling framework, integrating molecular dynamics, that can predict the effect of mutations on the affinity of Triclosan for FabIA modelling framework that will be able to predict the kinetics of FabI integrated into the metabolic pathway in the presence of Triclosan that takes into account transient cell to cell variations in FabI and the other members of the pathway that arise via gene duplications and the stochastic effects in gene expressionAn integrated multi-scale model that will predict the reaction of a homogenous population of microorganisms to the exposure to an antimicrobial agent, incorporating the new models.