Automated Cell Evaluation for Single-Cell RNA-seq Analysis
#Single-cell omics sequencing #single-cell isolation #accurate cell concentration #viability measurement #cell cluster graph #cell size histogram #analyzing intact nucleidownload pdf
- Figure 1. Singe-cell sequencing workflow: 1) Tissue Collection, 2) Isolated Cell Preparation, 3) Sequencing Library Preparation, 4) Sequencing and 5) Analysis.
- *IMPORTANT* Generating isolated cells from whole tissues suitable for both counting and single-cell sequencing requires complete dissociation. Cell clusters can not only yield inaccurate counts but negatively influence sequencing results. The composition of the extracellular matrix (ECM) of each tissue type can vary; thus, the enzymatic and chemical composition of the dissociation methods must be optimized accordingly to ensure dissociated tissue to obtain isolated cells.
- Figure 2. The B cells appeared well prepared for the single-cell library, including all positive green cells without dead cells (RF) or debris of particles (BF) with an excellent tag of 100% viability. These healthy cells demonstrated an average cell size of 10.7 µm, 100% single-cell separation in the cell cluster plot at a concentration of 3.00E+05 cells/mL as cell counting
- Figure 3. Example of inadequately prepped cell sample for single-cell sequencing. The AsPC-1 cells of inadequate cell profiles for single-cell sequences have been described. ‘Failing’ cell preps show both a high content of dead cells and contain incompletely dissociated clusters of cells. The cluster histogram feature of the LUNA-FX7™ allows the accurate assessment of cell cluster percentages vs. isolated cells.
- Figure 4. Possible results from nuclei isolation processes of HL 60 cells. Brightfield (BF) images and overlaid fluorescence images with tag allow you to distinguish the different cell ‘states easily’. Intact cells appear noticeably more prominent and darker than the isolated nuclei in BF images. At the same time, the fluorescent images and counts allow accurate quantitative assessment.
- Figure 5. Differentiation between live, dead, and intact nuclei. Because both dead cells and intact nuclei lack an intact cell membrane, the red fluorescent would be perceived from propidium iodide staining. However, the BF images and size measurements generated by the LUNA-FX7™ enable the routinely distinguish between dead cells and intact, isolated nuclei.
- Figure 5. Evaluation of isolated nuclei and possible results. Brightfield (BF) images and overlaid fluorescence images allow you to distinguish the different cell ‘states easily’. Intact cells appear noticeably more prominent and darker borders than the isolated nuclei in BF images. At the same time, the fluorescent images and counts allow accurate quantitative assessment. Live intact cells are stained with acridine orange (GF), and separated nuclei are stained red. The LUNA-FX7™ can accurately discriminate from samples with large cytoplasm and small nuclei (HeLa) and cell types with large nuclei relative to the cytoplasm (HEK293).
- Table 1. The counting slide options and their specifications.
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