Developmental imaging of bacterial biofilms with advanced microscopy, image processing and machine learning

生物膜是包裹在聚合物基质中的密集、空间复杂的细菌群落。据估计，超过65%的人类感染与生物被膜有关，包括囊性纤维化相关的铜绿假单胞菌肺部感染和大肠杆菌尿路感染。尽管生物膜的复杂结构使其具有显著的健壮性，但目前我们对决定生物膜结构的发育和物理原理的了解非常有限。其中一个重要原因是，目前很难在足够的分辨率下观察生物膜的发育。为了解决这个问题，我们需要建立工具来观察微米级的细菌是如何繁殖并分化成高度结构化的毫米级群落的。在这个博士期间，你将建立广泛有用的显微镜和图像处理工具，用于生物膜成像。你将对生长发育过程中的生物膜进行单细胞分辨显微镜观察。然后，您将开发用于高分辨率3D细菌细胞分割和谱系追踪的开源图像分析工具和软件，使用深度学习来实现高健壮性和敏感度。该项目的成果将是广泛有用的开源软件和开放科学协议，用于通过显微镜跟踪结构化生物膜社区中的细菌发展。你将为你的博士研究做些什么？你将从事高度跨学科的工作，从事定量生物成像(生物物理学和计算机科学)和微生物学。这将包括使用先进的显微镜和微流控技术在单细胞分辨率下对生物膜的发育进行成像，以及开发新的图像处理方法，用于在空间和时间上追踪生长细菌的三维单细胞谱系。

Biofilms are dense, spatially complex communities of bacteria enclosed in a polymer matrix. Over 65% of all human infections are estimated to be biofilm-related, include cystic-fibrosis related Pseudomonas aeruginosa lung infections and Escherichia coli urinary tract infections. Although the complex structure of biofilms is responsible for their remarkable robustness, our understanding of the developmental and physical principles which determine biofilm structure is currently very limited. One important reason for this is that it is currently difficult to observe the development of a biofilm at sufficient resolution. To solve this, we need to build tools to observe how a micron sized bacterium multiplies and differentiates into a highly structured millimetre scale community. During this PhD you will establish widely useful microscopy and image processing tools for biofilm imaging. You will perform single cell resolution microscopy of biofilms as they grow and develop. You will then develop open source image analysis tools and software for high resolution 3D bacterial cell segmentation and lineage tracing using deep learning to achieve high robustness and sensitivity. The outcome of this project will be widely useful open source software & open science protocols for tracing bacterial development in structured biofilm communities via microscopy. What will you be doing for your PhD research? You will perform highly interdisciplinary work, working on both quantitative bioimaging (biophysics & computer science) and microbiology. This will include using advanced microscopy and microfluidics to image the development of biofilms at single cell resolution, and developing new image processing methods for three dimensional single cell lineage tracing of growing bacteria in space and time.