Nantes Université, Inserm UMR 1307, CNRS UMR 6075, Université d'Angers, CRCI2NA, Nantes, F-44000, France.
LabEx IGO "Immunotherapy, Graft, Oncology", Nantes, France.
F1000Res. 2022 Sep 29;11:1121. doi: 10.12688/f1000research.124990.1. eCollection 2022.
Multiplexing tissue imaging is developing as a complement for single cell analysis, bringing the spatial information of cells in tissue in addition to multiple parameters measurements. More and more commercial or home-made systems are available. These techniques allow the imaging of tens of fluorescent reporters, where the spectral overlap is solved by imaging by cycles the fluorophores using microfluidics to change the reporters between each cycle. For several systems, the acquisition system coupled to the microfluidic system is a wide field microscope, and the acquisition process is done by mosaicking to cover a large field of view, relying on image processing to obtain the data set to be analysed in intensity. The processed data set allows the identification of different populations, quite similarly to cytometry analysis, but with spatial information in addition. To obtain the final image for analysis from the raw acquisitions, several preprocessing steps are needed for inter-cycle registration, tissue autofluorescence correction or mosaicking. We propose a workflow for this preprocessing, implemented as an open source software (as a library, command line tool and standalone). We exemplify the workflow on the commercial system PhenoCycler (formerly named CODEX®) and provide a reduced size data set for testing. We compare our processor with the commercially provided processor and show that we solve some problems also reported by other users.
多重组织成像技术作为单细胞分析的补充正在发展,它为组织中的细胞提供了空间信息,同时还可以测量多个参数。越来越多的商业或自制系统已经问世。这些技术允许对数十种荧光报告蛋白进行成像,其中通过使用微流控技术循环成像来解决荧光团的光谱重叠问题,在每个循环之间改变报告蛋白。 对于几个系统,与微流控系统耦合的采集系统是宽场显微镜,采集过程是通过拼接来覆盖大视场,依靠图像处理来获得以强度分析的数据。处理后的数据集允许识别不同的群体,与细胞术分析非常相似,但除此之外还有空间信息。为了从原始采集数据中获得最终用于分析的图像,需要进行几个预处理步骤,例如循环间注册、组织自发荧光校正或拼接。我们为此预处理提出了一个工作流程,实现为开源软件(作为库、命令行工具和独立工具)。 我们在商业系统 PhenoCycler(以前称为 CODEX®)上例举了该工作流程,并提供了一个用于测试的简化数据集。我们将我们的处理器与商业提供的处理器进行了比较,并证明我们解决了其他用户也报告的一些问题。