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Sorting Single Cells – What Do You Need to Consider?

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Sorting Single Cells – What Do You Need to Consider?

Flow cytometer and cell sorter manufacturers have invested considerable resources to design instruments that are the “fastest in the ‘hood” either in terms of cells analyzed per second, or in total throughput. The general idea is the faster you can go, the quicker you can identify rare cells, and produce sorted populations containing large numbers of cells.

More recently the focus has changed; developments at various ‘omics levels have opened up the possibility of making measurements on single sorted cells.  The way that we use flow sorters now has to shift, to deal with identifying and sorting individual cells.

So what do you need to consider when thinking about single cell sorting?  The first thing you need to consider is what you plan to do with these single cells.

Sorting cells for culture

Do you want to grow your cells in culture in after sorting? If so, maintaining cellular viability is crucial.

There are many things you can do to enhance viability:

  • Use  large flow tips and slower flow stream velocities
  • Chill the cells prior to and after sorting
  • Replace the standard sheath fluid with media more compatible with cellular growth
  • Sort directly into mineral oil to create microdroplet incubation chambers containing single cells
  • Avoid sheath fluids containing antimicrobials and/or detergents, or having unusual pH values
  • Use “feeder cells” in various configurations

Sorting for DNA and RNA measurements

Perhaps you are planning various ‘omics measurements?  If you are not interested in growing the sorted cells, and instead want to use them for ‘omics measurements, then maintaining cellular integrity may not be high on your list. Most ‘omics measurements are destructive so keeping the cells alive is no longer the prime consideration.

Examples of successful ‘omics measurements using single cells include:

  • Genomics, in which the entire nuclear genome is amplified and sequenced
  • Transcriptomics, in which the polyadenylated RNA is employed for cDNA production, amplification, and sequencing (see Jaitin et al., 2014, for an excellent recent example of single-cell transcriptomics)

Sorting nuclei

Genomics and transcriptomics can also be done on nuclei isolated by flow sorting (Grindberg et al., 2013).  In these situations, since extensive amplification is involved, maintenance of sample purity is particularly important. This requires scrupulous cleanliness when operating the sorter, as well as using single droplet, and not multiple droplet, sorting (see Rinke et al., 2014).

As a general rule, it is a good idea to verify that any amplification events are due to the presence of the desired cell and not a consequence of general contamination of the sample or sheath fluids. This can be easily done by spiking fluorescent microspheres into the sample, then sorting these, and subjecting them to the downstream ‘omics manipulations. No signal should be seen (see  Grindberg et al., 2013).

Sorting for proteomic and metablomic measurements  – not quite there yet

Extending other ‘omics technologies to single sorted cells or organelles has attracted much attention but this has been particularly challenging (Galler et al., 2014) and progress has been slow. For example, applying analytical methods of proteomics to characterize the complement of proteins within single cells is hampered by the low abundances of these proteins, the unavailability of methods of protein amplification analogous to methods used for amplification of nucleic acids, and the dynamic ranges of the individual proteins.

Similarly, the application of analytical methods of metabolomics to single cells suffers from the complex diversity of small molecules present within an individual cell, the dynamic ranges of the individual molecules, and the requirement for methods of pre-enrichment and separation of these molecules prior to detection.

Sorting in the future

For both proteomics and metabolomics, methods based on mass spectrometry (MS) provide the greatest detection sensitivity, and a good deal of work is underway relating to interfacing single cell flow analysis and sorting with downstream MS-based analytical pipelines.  Microfluidic platforms show particular promise in this area (Liu and Singh, 2013).

No end is in sight for developments in the area of single cell sorting. Significant advances in flow sorting technologies, particularly chip-based sorters, offer improved user interfaces at lower costs and with smaller laboratory footprints. We can confidently look forward to continued progress in this exciting area.

For further information, the following recent references to single cell analytics may be useful:


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