"No two cells are the same” is a saying that many scientists have used to explain the importance of single cell analysis. When looking at cell populations as a whole, the differences between cells are masked and averaged into a single profile. Even though there are many distinct types of cells in a tissue, we routinely grind up the entire tissue to isolate DNA, RNA, and proteins.
Interestingly, the scientific community has been doing single cell analysis for a long time. Microscopy has allowed us to see things like differences in morphology, expression levels, and cell health in single cells. Flow cytometry has been able to do the same, but at a higher throughput using fluorescent dyes and light scattering.
Most dramatically, cell-to-cell differences can be seen with the output from flow cytometry. Often, multiple “populations” of cells are found within each sample of cells. However, use of both microscopy and flow cytometry has been limited to a small number of analytes that can be interrogated at once, as cell size does not necessarily correlate with the amount of DNA in the nucleus.
The isolation of single cells is also a key part of single cell analysis. Fortunately, multiple methods, such as fluorescently activated cell sorting and laser capture microscopy, have evolved to a point which enables all researchers to isolate single cells. Newer techniques such as microfluidics provide researchers with other methods to perform this key analysis step.
The analysis of RNA from large populations of cells has allowed us to interrogate many targets at once. Moreover, with the development of technologies such as quantitative PCR (qPCR), microarrays, and next-generation sequencing, RNA expression analysis has become easy and quantitative. This has made it possible to identify and correlate multiple targets from a single sample. However, the ability to do this type of RNA expression analysis on single cells has been limited by technology. For example, the tools used for the stabilization and detection of 2 µg of RNA from a single sample don’t work for 20 pg of RNA from a single cell. This has caused researchers to turn to techniques such as boiling samples in reverse transcriptase (RT) buffer or freezing and thawing cells, all of which can damage RNA, but are the only available options.