论文标题
通过延时共聚焦激光显微镜从生物膜基质中推断出细菌游泳的特征
Inferring characteristics of bacterial swimming in biofilm matrix from time-lapse confocal laser scanning microscopy
论文作者
论文摘要
生物膜是嵌入自生产基质中的空间有组织的微生物菌落,赋予微生物群落对环境压力的抗性。已经观察到在致病外宿主生物膜的基质中观察到运动细菌。这种观察为有害生物膜生物防治开辟了新的有希望的途径:这些细菌游泳者增强了化学处理的生物膜血管化,或者可以通过微生物携带或局部合成提供生物防治剂。 %\ cite {muok2021microbial,yu2020hitchhiking,samad2017swimming}。因此,表征生物膜基质中的游泳运动员轨迹特别感兴趣的是了解和优化其生物防治。在这项研究中,开发了一种新的方法来分析延时的共聚焦激光扫描图像,以描述和比较细菌游泳者种群的游泳轨迹及其适应性构造biofilm结构。该方法基于游泳者人群动力学模型的推断,包括与宿主生物膜的机械相互作用。在验证合成数据后,该方法将在三种不同的摩托车{芽孢杆菌物种在金黄色葡萄球菌生物膜中游泳的图像实现。拟合的模型允许游泳者通过游泳行为对人群进行分层,并提供有关微武器机部署机制以使其游泳特质适应生物膜基质的机制。
Biofilms are spatially organized microorganism colonies embedded in a self-produced matrix, conferring to the microbial community resistance to environmental stresses. Motile bacteria have been observed swimming in the matrix of pathogenic exogeneous host biofilms. This observation opened new promising routes for deleterious biofilms biocontrol: these bacterial swimmers enhance biofilm vascularization for chemical treatment or could deliver biocontrol agent by microbial hitchhiking or local synthesis. %\cite{muok2021microbial,yu2020hitchhiking,samad2017swimming}. Hence, characterizing swimmer trajectories in the biofilm matrix is of particular interest to understand and optimize its biocontrol.In this study, a new methodology is developed to analyze time-lapse confocal laser scanning images to describe and compare the swimming trajectories of bacterial swimmers populations and their adaptations to the biofilm structure. The method is based on the inference of a kinetic model of swimmer population including mechanistic interactions with the host biofilm. After validation on synthetic data, the methodology is implemented on images of three different motile {Bacillus species swimming in a Staphylococcus aureus biofilm. The fitted model allows to stratify the swimmer populations by their swimming behavior and provides insights into the mechanisms deployed by the micro-swimmers to adapt their swimming traits to the biofilm matrix.