Augenstreich Jacques, Shuster Michael, Fan Yongqiang, Lyu Zhihui, Ling Jiqiang, Briken Volker
Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20742 USA.
Current affiliation: College of Life and Health Sciences, Northeastern University, Shenyang 110819, People's Republic of China.
bioRxiv. 2023 Oct 2:2023.10.01.560379. doi: 10.1101/2023.10.01.560379.
Accurate quantification of bacterial burden within macrophages, termed Bacterial Burden Quantification (BBQ), is crucial for understanding host-pathogen interactions. Various methods have been employed, each with strengths and weaknesses. This article addresses limitations in existing techniques and introduces two novel automated methods for BBQ within macrophages based on confocal microscopy data analysis. The first method refines total fluorescence quantification by incorporating filtering steps to exclude uninfected cells, while the second method calculates total bacterial volume per cell to mitigate potential biases in fluorescence-based readouts. These workflows utilize PyImageJ and Cellpose software, providing reliable, unbiased, and rapid quantification of bacterial load. The proposed workflows were validated using Salmonella enterica serovar Typhimurium and Mycobacterium tuberculosis models, demonstrating their effectiveness in accurately assessing bacterial burden. These automated workflows offer valuable tools for studying bacterial interactions within host cells and provide insights for various research applications.
准确量化巨噬细胞内的细菌载量，即细菌载量定量（BBQ），对于理解宿主与病原体的相互作用至关重要。已经采用了各种方法，每种方法都有其优缺点。本文探讨了现有技术的局限性，并基于共聚焦显微镜数据分析介绍了两种用于巨噬细胞内BBQ的新型自动化方法。第一种方法通过纳入过滤步骤以排除未感染细胞来优化总荧光定量，而第二种方法计算每个细胞的总细菌体积以减轻基于荧光读数的潜在偏差。这些工作流程利用了PyImageJ和Cellpose软件，能够可靠、无偏差且快速地定量细菌载量。所提出的工作流程使用肠炎沙门氏菌鼠伤寒血清型和结核分枝杆菌模型进行了验证，证明了它们在准确评估细菌载量方面的有效性。这些自动化工作流程为研究宿主细胞内的细菌相互作用提供了有价值的工具，并为各种研究应用提供了见解。
