Single-cell sequencing technologies allow researchers to study the genomes and transcriptomes of individual cells. They can reveal low-frequency genetic alterations within a heterogeneous population (that might be missed using bulk sequencing techniques) and offer insights into gene expression under conditions of both health and disease. Isolating individual cells is the first step of any single-cell sequencing workflow and will determine the success of downstream experiments. This article explains how automated cell counting improves the results of single-cell sequencing and notes some key features to look for when selecting an automated cell counter for your research.
A typical single-cell sequencing workflow involves isolating individual cells from sample material, extracting and amplifying the DNA or RNA to construct a sequencing library, then applying next-generation sequencing technologies for sample characterization. Single-cell isolation—the first step in this process—can be achieved via various techniques. These include limiting dilution, fluorescence-activated cell sorting (FACS), magnetic cell separation, and a range of microfluidic technologies, each of which has its own advantages and limitations. Determining the effectiveness of single-cell isolation is critical to avoid misleading results and prevent wasted time, resources, and precious sample material further downstream.
Performing a cell count provides information for establishing whether a single-cell sequencing experiment should proceed. This includes the cell number, which must often be above a certain threshold level to yield reliable results, and the viability, which can highlight any damaging effects of sample-preparation techniques. Cell counting also helps confirm that clumps have been removed (a key consideration for techniques such as single-cell RNA sequencing, where doublets and multiplets can complicate data analysis) or that nuclei have been properly isolated following cell lysis.
Hemocytometry is a widely used method for performing manual cell counts; however, it is notoriously prone to error. Incorrect placement of the glass coverslip, confusion over whether cells should be classified as live or dead, and mistakes during the calculation stage can all lead to inaccurate results. Additionally, because hemocytometry counts only a small sample volume, the presence of clumps may be overlooked. By addressing these problems, automated cell counting has become a preferred approach for counting cells, especially for single-cell sequencing applications where precision and experimental reproducibility are essential.
A main advantage of automated cell counting over manual counting is that it allows for the adoption of standardized methods to eliminate user-bias and provide faster time to results. Automated cell counting also produces more statistically relevant data as it can handle larger counting volumes than manual methods; instruments are available that can count up to 5 µL per sample, corresponding to 10 times the counting volume of a standard hemocytometer. Moreover, because some automated cell counters measure parameters beyond cell number and viability, researchers can gain a better idea of sample quality for more accurate single-cell sequencing results.
Cell size is a key parameter that can be monitored to enhance a broad range of single-cell sequencing applications. For techniques requiring whole cells, using cell size to identify clumps or debris provides confirmation that the single-cell isolation method is performing as expected. And for applications that use isolated nuclei, cell size measurements can be combined with acridine orange/propidium iodide (AO/PI) staining to both prevent isolated nuclei from being misidentified as dead cells and enable researchers to calculate unlyzed cells as a percent of the total cell number.
Factors to consider when selecting an automated cell counter for general use include instrument size, ease of operation, and the level of support provided by the manufacturer. However, for single-cell sequencing applications, certain instrument features can offer particular benefits. First, with cell counting accuracy being crucial to the success of single-cell sequencing, it is worth checking the limit of quantification (LOQ) and CV, including for common sample types such as dissociated tissues, whole blood, and cultured cell lines.
Equally important is the need to establish whether cell size information is generated. Where a cell size histogram is available, researchers can readily determine the distribution of single cells in a sample, monitor the presence of clumps or debris, and evaluate the quality of single nuclei isolation in combination with AO/PI staining. For some workflows, the ability to perform high-throughput cell counting is vital; for others, ensuring the automated cell counter is GMP-ready is important. Manufacturers will be able to advise on instrument selection and, in many cases, may suggest relevant upgrades for specific single-cell sequencing applications.
The LUNA FX7™ is an automated cell counter that can be used to improve the quality of single-cell sequencing data. To learn more, visit logosbio.com