Image-Based Spatially-Resolved Laser-Activated Cell Sorting

Significant advances in imaging technologies and molecular cellular biology have brought biological discoveries that boosted the understanding of biological phenomenon. Ranging from hematoxylin and eosin (H&E) staining to immunofluorescent staining (IF), different staining modalities have laid foundations for modern medicine, and next generation sequencing (NGS) (Metzker, 2009) caused a quantum leap in biological discoveries in a decade. While the imaging technologies provide information of the biological circuitry by providing spatial and structural information of a biological system, molecular cellular biology technologies provide the state of the biological cells in a more microscopic manner. However, to fully understand how the cells are functioning within spatial context, there needs to be a tool to connect the imaging technologies to molecular cellular biology. Such integrated technologies that can sort out cells with preserved spatial information will connect the data from spatial assays to that from the molecular assays.<br/>Conventional cell sorting technologies, however, are mostly based on microfluidic cell sorting. Fluorescence activated cell sorter (FACS) is perhaps the most widely used cell sorter (Givan, 2013). FACS utilizes laser source to sort cells with the same fluorescence spectrum. These technologies require the cells to be dissociated into solution phase, losing the spatial information during the process. Intelligent image-activated cell sorting (Nitta et al., 2018) and Raman image activated cell sorting (Nitta et al., 2020) measured the cell image with machine learning and Raman image of the cells, respectively. These techniques are able to preserve the cellular phenotype information because the cells are sorted according to their images, but these cell sorting techniques still require dissociation of the cells and therefore the spatial context is lost before the cells are sorted. Spatially targeting cell isolating devices such as laser capture microdissection (LCM) (Espina et al., 2006) or similar methods are able to dissect out the regions of interest. Some platforms offer high resolution cell microdissection down to single cell level (Schütze and Lahr, 1998). However, the throughput for these platforms is three target retrievals per run (which takes approximately one hour), hindering their usage in cell sorting.<br/>In this talk, we present a novel cell sorting methodology called spatially-resolved laser-activated cell sorting (SLACS) that preserves spatial information and demonstrate its usage in bridging spatial assay to various molecular assay.This is achieved by developing an innovative SLACS device which isolate cells on an indium tin oxide (ITO) coated slide glass into commercialized PCR tubes based on their image. The properties of cell sorting such as accuracy are demonstrated and the possibilities of post-processing such as DNA sequencing, RNA sequencing, or other molecular biology techniques are validated, proving the potential of SLACS for novel biological discovery tool by sorting mammalian cells to bacteria. Especially, we have reported a method of sequencing the genomes of small number of cells or single cell through this methodology (Kim et al., 2019, 2018).