Biological resolution at the level of individual cells is powering the next phase of precision health. The HIVE™ scRNAseq Solution integrates sample storage and single cell profiling into a single workflow, solving issues associated with the logistics of sample collection across multiple sites. The HIVE™ scRNAseq Solution enables the generation of biologically complete and high-quality data from samples that require storage prior to processing for single-cell RNA libraries.
1) Sample Preparation
Commercially available blood from a healthy human donor was delivered same day to the Honeycomb Biotechnologies lab. Red blood cells were depleted by size selection using a sterile Acrodisc® White Blood Cell Syringe Filter (Pall Laboratory, # AP-4951), preserving all leukocyte populations, including granulocytes.
2) Sample Capture
Six HIVE™ devices were each loaded with approximately 15,000 cells in 1 mL of cell media. Single-cells settled into picowells of the HIVE containing 3’ transcript-capture beads. Three cell-loaded HIVE™ devices were processed immediately without storage, and three were frozen at -20°C for two weeks after the addition of Cell Preservation Solution, before being processed through to single-cell NGS libraries.
3) HIVE Processing and Library Preparation
Following standard protocol, cell-loaded HIVE devices were sealed with a semi-permeable membrane, allowing for the use of the strong Lysis Solution followed by the addition of Hybridization Solution. After collection with or without storage, beads with captured transcripts were extracted from the HIVE™ device by centrifugation. The remaining HIVE™ library preparation steps were conducted in a 96-well plate format. PerkinElmer’s LabChip® GX Touch™ nucleic acid analyzer was used for accurate assessment of individual library sizes, and the concentration of final pooled libraries was determined by qPCR.
4) Sequencing & Analysis
HIVE™ scRNAseq libraries were sequenced using specific primers contained in the kit on an Illumina® NovaSeq® 6000 sequencer. Demultiplexed FASTQ files were input for analysis with the BeeNet™ software solution, which has been specifically designed for the HIVE™ scRNAseq libraries and is provided with the HIVE™ system, outputting count matrix files. Seurat was used for secondary analysis. Cells that fell below a threshold of 400 genes and 800 transcripts identified were excluded. Additional filtering was done to remove low quality cells as indicated by greater than 0.1% mapping to mitochondrial reads and to remove mixed clusters based on co-expression of mutually exclusive lineage markers with the same barcode, which suggests more than one cell settled into the same nanowell.
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