Single-cell RNA-sequencing (scRNA-seq) is a powerful tool for unraveling complex biological systems, giving researchers the ability to study gene expression dynamics on a cell-by-cell basis. The ability to dissect cell-type specific differences in complex biological systems is critical in understanding cellular processes during disease development and progression. Analyzing gene expression in samples composed of mixed cell populations presents a level of complexity that historically has been difficult to overcome.
The technological advancements of scRNA-seq allow researchers to explore the true diversity of gene expression at the single-cell level, providing access to critical data that is often masked by bulk RNA-seq methods (Figure 1). To take full advantage of this transformative technology, however, it is essential to properly prepare single-cell samples. This article outlines recommendations for the preparation of single-cell samples for use with the Chromium™ Single Cell 3’ Solution by 10x Genomics®, but the protocols discussed can be adapted for other systems as necessary.
Figure 1. scRNA-seq reveals cellular heterogeneity that is masked by traditional bulk RNA-seq methods.
Sample preparation protocols will differ for every sample type, but whichever protocol is utilized, steps should be taken to ensure that cells loaded into the system are viable and fully dissociated into single cells. Whether working with cell lines or tissue, optimizing the cell dissociation protocol for your particular sample type will be critical in order to retrieve highly viable cells and minimize cell death and lysis. Dead cells can lyse, resulting in the release of ambient RNA. This cell-free RNA can contribute to the background noise of the assay and will compromise the quality of single-cell data.
Understanding the limitations and requirements of a given sample type will result in more robust data. A number of available sample preparation protocols address these issues, but may need to be adapted for your particular sample type. For example, suspension cell lines, bead-enriched cells, and flow-sorted cells are already suspended and only need to be washed and counted before use with the Chromium™ Single Cell 3’ Solution. However, when working with tissue, it is important to optimize the dissociation protocol well in advance of your first library preparation to ensure maximum data quality.
Another consideration is that different cell types display a wide range of initial RNA content, and accurate RNA input measurements will impact several key workflow decisions, such as the number of PCR cycles used in library preparation. For example, human peripheral blood mononuclear cells (PBMCs) are RNA poor with about 0.75 pg/cell, while HCC38 cell lines are very RNA rich with 21.6 pg/cell (Table 1).
Table 1. Cell types tested by 10x Genomics. Determined by Qubit™ assay & extracted using Maxwell® RSC SimplyRNA cells kit.
Pipetting
Pipetting technique is critical when dissociating tissue or working with cells already in suspension. For example, as cells sit in a tube, they begin to settle, and when pulling from either the top or the bottom of the solution, it is possible to aspirate very different numbers of cells, especially if the cells settle quickly. Instead, cell suspensions should be pipette-mixed immediately prior to transfer and then aspirated from the middle of the tube each time, generally below the halfway mark of the solution.
Additionally, it is critical that the cells are handled gently when pipetting. Pipette mixing roughly, even with a wide-bore pipette tip, can negatively impact sample quality. Table 2 compares key single-cell data metrics from four different cell-mixing experiments performed on HEK293T cells. Both rough pipette mixing and vortexing can cause premature cell lysis, creating high ambient RNA levels that contribute to background noise in the system and ultimately decreasing the fraction of reads in cells (highlighted in blue). Similarly, the number of median genes per cell also decreases as a result of rough cell handling (Table 2). Instead, the cell suspension should be mixed gently with a wide-bore pipette tip. This will yield cleaner data, increase library complexity (i.e. increase number of median genes per cell) and result in a higher fraction of reads in cells.
Table 2. Pipette mixing roughly, regardless of pipette tip size, can negatively affect sample quality.
Washing
When working with suspension cell lines, dissociated tissues, or large numbers of cells, it is highly recommended that a thorough washing protocol is followed. This can vary based on sample type as well as scRNA-seq method. Our scRNA-seq washing protocol calls for pelleting and resuspending cells twice in PBS containing 0.04% BSA, and then resuspending in a final volume of PBS and 0.04% BSA.
Straining
Large cell aggregates or debris can increase the risk of clogs on a microfluidic chip. To avoid this, we recommend using a cell strainer, with pore sizes of 30 to 40 microns, before loading the cell suspension onto the microfluidic chip. A number of strainers have been successfully tested on samples loaded into our scRNA-seq solution.
It is important to note that each straining will result in cell suspension volume loss as well as changes in cell concentration. If straining is required, the single-cell suspension should be counted again after straining is complete.
Counting and viability assessment
To assess sample quality, it is crucial to measure cell viability after washing and straining. There are a number of methods, but we have found that the Trypan blue exclusion method works well to identify the proportion of live cells to dead cells.
The accuracy of the final cell count and, ultimately, the agreement between targeted and calculated cell recovery is dependent on knowing how many cells are in a sample. Once the straining and washing steps have been completed, a cell counting device, such as a hemocytometer or a Countess® II FL Automated Cell Counter, can be used for quantification. These devices not only provide accurate counts but are also critical to calculate the volume of cell suspension required to load the desired number of cells onto the microfluidic chip. Another important factor that can impact the accuracy of the final cell count is cell stock concentration. We found cell stock concentrations between 700 and 1200 cells/µl to be optimal to achieve the targeted number of recovered cells (Figure 2). Cell suspensions that are outside this optimal concentration range may result in unreliable cell counts. If samples are outside this range, we recommend adjusting the cell stock concentrations accordingly.
Figure 2. Relative difference of recovered cells from targeted cell counts, calculated by Cell Ranger™ Analysis Pipelines vs. the targeted cell counts for each library. Cell Suspensions #1 (blue, 340 cells/µl) and #2 (orange, 500 cells/µl) showed the greatest deviation from the targeted cell counts, 16-23% and 8-10% respectively. Target accuracy was improved with cell suspensions that were prepared at higher stock concentrations, Cell Suspensions #3 (green, 780 cells/µl) and #4 (purple, 1180 cells/µl).
Dead cell removal
A high percentage of non-viable cells may impact the targeted cell recovery numbers, and in samples with a high fraction of dead cells (>30%), we recommend using our Demonstrated Protocol on Removal of Dead Cells from Single Cell Suspensions. This protocol outlines best practices for reducing the percentage of dead cells in a single-cell suspension.
Storage after preparation
To minimize changes to the transcriptome, once the cells are washed and counted, single-cell suspensions should be stored on ice until they are used in partitioning and library construction. Ideally, once samples are prepared, they should be utilized for downstream steps within 30 minutes.
It is important, however, to be aware of a cell type's unique characteristics as these will impact both how long your cells should be left on ice and how quickly they should be used after preparation. For example, some cells, such as PBMCs, will begin to form clumps if they are sitting on ice for extended periods of time. These clumps are difficult to dissociate, increasing the risk of clogs and, with each clump being counted as a single cell, decreasing counting accuracy. Additionally, some cells are stickier than others and clump at a faster rate. For these, it is particularly important to minimize the time between preparation and use.
Having a plan in place for the best handling and preparation of your samples is key when preparing single-cell suspensions as there are many factors that need to be considered in order to get high quality data. For additional guidance on single-cell sample preparation, there are a number of Demonstrated Protocols available, which provide cell-type specific protocols. If you’re dealing with cells that are difficult to isolate as whole intact cells, nuclei isolation may be an effective alternative approach. Guidelines are also available for the steps following sample preparation, such as library preparation, sequencing, and data analysis and visualization. Furthermore, our how-to videos, especially Chapters 4 through 7, should help walk you through the sample and library preparation processes. Additional Demonstrated Protocols and webinars with tips for best practices will be posted on the 10x Genomics Website or the 10x Community as they become available.