Enabling superior performance with 10X Genomics Single Cell Sequencing
Introduction
The 10X single cell sequencing platforms have helped to revolutionize our understanding of biology and how the measurement of individual cells’ gene expression can uncover the previously hidden messages commonly unseen in bulk mRNA experiments.
Unfortunately while the single cell sequencing workflow has proven to be fast, simple and reliable, obtaining the most complete and accurate single cell data depends on up-front sample preparation steps. Traditional methods currently in use tend to damage cells, have low capture efficiency, and often completely fail to process sensitive and difficult to work with samples such as dissociated tissue samples. The most common sample enrichment methods, Flow Cytometry and Bead-based enrichment methods, both often lead to significant cell stress and gene expression changes due to the high pressures used (Xiong et al., 2002; Romero-santacreu et al., 2009; Van Den Brink et al., 2017) or cell signaling effects due to the cell surface binding required by these methods (Kornbluth and Hoover, 1989; Christaki et al., 2011). Due to these shortcomings many promising single cell experiments delivered biased results or fail to delivery results entirely.
The urgency for technological platforms that are gentle (to minimize cell damage), and efficient (to maximize the capture of all live cells in the population while maintaining the original cellular representation) is imperative to realize the scientific and clinical potential of single-cell analysis.
The LeviCellTM demonstrates such a promise.
Methods
Results
Library Preparation
Sequencing
All samples were sequenced on the Illumina 6000 S2 sequencer to a depth of ~500 million read per sample. Sequencing metrics, including Q30 bases in reads, barcodes, and UMI’s were nearly identical across all samples. The fraction of reads mapped overall were very similar across all samples, and only small differences were observed in the fraction of reads mapping to intergenic, intronic, and exonic regions of the genome.
The most striking differences were seen when comparing the detected genes in the non-enriched sample to its corresponding live-enriched sample. This figure highlights the fact that the early stage bladder cancer had a nearly three-fold increase in the median number of genes detected per cell, while the late stage cancer sample showed a 50% increase.
Sequencing Analysis
Sequencing results were analyzed using Cell Ranger from 10X Genomics. The plots below demonstrate the clear benefits of using the LeviCell to prepare samples for single cell sequencing. Samples enriched on the LeviCell produced a significantly larger number of genes detected per cell. This, combined with the better distribution of UMI counts, leads to a more complete picture for samples prepared using the LeviCell.
Early Stage Cancer Sample
The distribution of UMI counts per cell in the standard method shows a small cluster of cells with the majority of the UMI counts. This same cluster of cells is represented by a single cluster when grouped by gene expression changes. In contrast, in the LeviCell enrichment sample there is a larger number of cells with significant numbers of UMI counts. This same group of cells is represented by four gene expression clusters (lower right), indicating a larger range of cellular diversity captured in the sequencing results.
Late Stage Cancer Sample
A similar trend is observed with the late stage cancer sample, although the trends are less pronounced. Here, the sample processing with the standard method shows a large number of cells with high diversity of UMI counts, and correspondingly five clusters of gene expression. The sample after LeviCell enrichment has a larger number of cells with high diversity of UMI counts, and six clusters of gene expression clusters, indicating a superior view of the expression profiles.
Conclusion
The innovative label-free separation technology of the LeviCell facilitates complete debris and dead cell removal without affecting the original population representation of gene expression (please see our Population Representation application note for additional data on how the LeviCell maintains the original population representation). When it comes to single-cell study, purity and viability of cells harvested from the sample preparation stage is a determining factor for generating high quality data in downstream assays such as NGS (Next Generation Sequencing). The LeviCell’s ability to seamlessly enrich for target cells and produce robust yields of viable cells without preferentially depleting or changing the frequency or expression of cell types gives it the necessary technological characteristics that many scientists have been waiting for to take them to the next level.
