By the same authors

From the same journal

Guest editors' introduction: Flow Cytometry Methods and Approaches

Research output: Contribution to journalArticle

Published copy (DOI)



Publication details

DatePublished - 1 Jul 2015
Pages (from-to)1-2
Original languageEnglish


This issue of Methods highlights some of the recent advances in flow cytometry. Flow cytometry has been a mainstay of research, clinical, and biotechnology arenas for many years since its commercialisation in the late 1970s [1], [2] and [3]. It has a routine place in many laboratories, and sometimes we can forget that cytometry needs to adapt and to evolve. The great advantage of flow cytometry is that we can make robust metrics on large numbers of cells so can look at whole populations, but we do so in a true cytometric sense—i.e., cell by cell. Recent advances have taken the number of parameters measured from the single figures to 20-plus; in addition high throughput systems have greatly increased the amount of data produced and, with it, a concomitant need for handling and analysing it in an efficient and effective way. In this issue we have attempted to pull together some of the newer and more novel approaches to flow cytometry—not all are traditionally flow cytometry as we know it, but all fulfil the remit of ‘making measurements on single cells’.

It is often the case that a cytometric experiment depends absolutely on the way cells are prepared. Sample preparation will vary whether we are dealing with suspension cells, adherent cultured cells, or cells extracted from solid tissue, e.g., fresh or archived biopsy material. No matter how good the procedure, there will always be dead or non-viable cells, debris and unwanted artefacts (chiefly, clumps of cells). The first paper in this issue, from Donnenberg and Donnenberg [4], shows how it is possible to clean up samples to define more accurately the populations of interest. We have to remember that cytometers are unintelligent—they will measure whatever we put through them, and it is up to us to determine what is real and what is wanted. The approach taken here, using a combination of a DNA dye to identify whole cells, light scatter properties, and time as a gating parameter, allows a more specifically defined population to be identified for further study.

The expansion of fluorochromes at a researcher’s disposal has developed hand-in-hand with the range of laser wavelengths available for their excitation. More pertinently, wavelengths of light that give a better excitation of current fluorochromes have become more affordable and widespread in recent years. William Telford has long been a proponent of alternative light sources [5] and [6] and in this issue describes recent advances in the near-infrared range [7]. At present the number of fluorescent probes that can be excited and detected above 650 nm is limited, but with the development of cheaper, small and stable lasers, this area of the spectrum will open up to researchers and will expand the number of targets that can be detected.

One of the earliest applications of flow cytometry was using DNA content to study proliferation, specifically in human tumours [8]. Cell death is equally important both in health, where it is regulated, and in disease where it becomes unregulated. However, it is little studied by flow cytometric methods, despite many having been available. In this issue, Gary Warnes discusses the methods that are available to researchers that can not only quantitate autophagic pathways and response within individual cells, but how these can be multiplexed to begin the dissection of heterogenous populations [9]. This paper also shows how the wider effects of organelle phagy may be correlated over time and also within specific phases of the cell cycle.

The opposite side of the coin—or the opposing side of the balance—is the ability to track cell proliferation. This may be achieved in a number of ways by flow cytometry: simple DNA content analysis; nucleotide, e.g., Bromodeoxyuridine uptake and staining; Hoechst quenching; or dye dilution. All these techniques are established but in recent years the dyes that enable tracking of dye dilution in particular have themselves proliferated. The end user may wish to establish the optimal criteria for a successful labelling of dye—Filby et al. [10] have developed a pragmatic approach to assessment of the suitability of dyes to track dilution, which includes obvious parameters such as toxicity, optimal concentration and affect on functionality or the ability to divide post-labelling, but also looks at the ability of cells to apportion dyes symmetrically at division, which will be important in the resolution of division peaks. This method allows researchers to assess whether protein-binding dyes or lipophilic dyes would be appropriate for their experiments and also expands the repertoire of fluorescent dyes that are available, thereby making easy the design of multiparameter experiments.

Quantification of antigen expression is often the end point of an assay, but absolute quantification can be difficult to achieve in a flow system, especially if antibody quality is not strictly controlled—an alternative approach to quantification is the use of mass spectroscopy. Although this may be more quantitative, it makes no distinction of the localisation of a target. Pharmacokinetic and pharmacodynamic studies often rely on quantification of targets which may be on the surface of cells or in the cytosol or even intranuclear. Hogg et al. [11] use a system to detect, by flow cytometry and mass spectroscopy, two transporter proteins that are well characterised. They found that although the amounts of detectable proteins showed the same trends, flow cytometry was preferable as it will be able to potentially differentiate between different locations of the proteins and, given that the staining conditions are correctly controlled, that it can also quantitate active transporters which could lead to improved drug metabolism or influx/efflux assays.

Expression of proteins is, in general, the main application of flow cytometric assays, but recent advances in detection systems has allowed the identification of specific mRNA fragments which will allow researchers to follow the replication and transcription of genes before translation into protein. McClellan et al. [12] have used this technique in a stem cell context to detect mRNA for two specific proteins, Nanog and Klf4, in biopsy material from several cancers. As cells that express the mRNA can be flow sorted, this enables functional assays to be performed on specifically-defined cell types and leads the way to further dissection of the differentiation pathways in many different pluripotent cells.

Even with advances in technology and fluorochromes, flow cytometers are currently limited to probably a maximum of 30 colours; to expand this, recent developments in the field of mass cytometry using a time of flight mass spectrometer and heavy-metal labelled antibodies has allowed expansion of the number of targets that can be detected in a single cell. However with this increase in data has come the requirement for high dimensional analysis, the interface of biology and bioinformatics, and the ability to use unsupervised learning to dissect out populations of interest from increasingly large data sets. Given that this approach will work best on large cohorts of samples, new approaches are needed. One such approach is described by Diggins et al. [13], who use a comparison between healthy cells and cells from a patient with AML (acute myeloblastic leukaemia) to present a bioinformatics workflow for the analysis of high-dimensional datasets. As this is largely unsupervised, it can lead to the discovery of unique and possibly unexpected phenotypes as well as providing unique tools for quantitating cell to cell variation within heterogenous populations.

One obvious disadvantage of mass cytometry is the destruction of the cell, leaving no room for sorting specifically defined populations. Cell sorting using electrostatic drop deflection is the standard way of recovering populations of interest from a heterogeneous population. Cell sorting has a relatively simple premise, but it is important to maximise cell purity, cell recovery, and cell yield—the latter being the most important, especially in cases where sample is limiting or where the population of interest is increasingly rare. Riddell et al. [14] here show how a simple adjustment and calculation to the way cell sorters are optimised (RMax) can increase the cell yield. The method described will be applicable to any commercially available cell sorter and can be used to assess both the efficiency of the sorter and the efficiency of the sample preparation.

Cell measurement in its widest sense begins with microscopy and making assessments of what we see—being able to add fluorescent probes expands this—but, while in flow cytometry we gain the ability to look at multiple parameters simultaneously, we lose the relational status of the fluorochromes and the pattern of expression. In the past few years Imaging Flow Cytometry has become more widespread, as it allows not only morphology and localisation of fluorescence to be easily determined (just like conventional light microscopy), but it also harnesses the quantitative power of flow cytometry combined with the statistical power of high throughput. In addition, once images are obtained it is possible to derive any parameter based on that image to separate cells of interest. One area of interest is the cell cycle of fission yeast (Schizosaccharomyces pombe)—this is possible by flow cytometry, but there are some drawbacks given the size of the particles and the distribution of fluorescence. Here Patterson et al. [15] use an imaging flow cytometer to dissect out the cell cycle on the basis of total fluorescence, cell morphology, and distribution of the DNA within cells, and they correlate this with populations that have been sorted on conventional cytometric parameters. This has a clear advantage over visual inspection and the current flow approaches.

The novel studies presented in this issue show just some of the latest developments in the broad field of cytometry. We hope that readers of this issue will be able to appreciate the insights that the novel applications can bring and show that, although the technique of flow cytometry is well established, the field still has much to offer by adaptation and adoption of novel approaches, and we hope that these papers stimulate readers in their own research areas.

    Research areas

  • Flow Cytometry

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations