$$\rightleftharpoonup{xx}$$
$$\longleftharp{xx}$$,
$$\longrightharp{xx}$$,
Flow cytometry has been extensively exploited in immunology, hematology and oncology to define cell populations via intrinsic scatter properties, cell surface antigen expression, and other fluorescence parameters1-3. Our insights into blood lineage development and disease are a result to a significant degree of the continuous refinement of this methodology after its initial implementation4,5. Increased awareness of the quantitative and overall analytic potential of flow cytometry has recently encouraged its more widespread use in stem cell research and may enable similarly profound progress in a shorter time frame6. However, the application of flow cytometry to specifically analyze and isolate neural populations has long been perceived as challenging. In contrast to hematopoietic cells that naturally exist in suspension, neural cell types are typically harvested from excessively complex sources that may include glia and various other surrounding cells as well as an intricate network of process-bearing neurons. Consequently, neurobiology has yet to implement the versatility of flow cytometry to its complete potential in daily research routines. However, as long as a viable single cell suspension can be generated (and protocols have been devised and optimized for that purpose7), flow cytometry and fluorescence-activated cell sorting (FACS) can be considered a valuable element of the analytical repertoire in neurobiology8-11.

Figure 1. Principle of flow cytometric analysis and components of a flow cytometer. Flow cytometers comprise three main systems: fluidics, optics and electronics. A streamlined flow of cells in suspension (prepared from primary tissue or in vitro culture) is accomplished by the sheath fluid via hydrodynamic focusing, restricting the sample to its center core. The optical parts are composed of lasers that illuminate the stream of cells and optical filters that direct the signal to the appropriate detectors. The light signals detected are converted to electronic signals, subsequently processed by a computer and visualized on a monitor for data analysis and gating. Please click here to view a larger version of this figure.
Users of flow cytometric methods profit from at least a basic understanding of the underlying fundamentals including a cytometer’s building blocks (for review see12,13; also see Figure 1). A laser beam intersects with a hydrodynamically focused fluidic stream that contains the cells in suspension, which in turn pass through the laser beam in ‘single file’ one after another. The interception of a cell (or any other particle, for that matter) with the laser results in the scattering of light from this interrogation point. Scattered light can be detected in continuation of the laser direction (forward scatter, associated with the size of the particle), as well as perpendicular to its direction (side scatter; reflecting the granulosity of the particle/cell). These aforementioned scatter properties do not require specific labeling, which is why an unlabeled sample (or also cellular debris, air bubbles, etc.) will generate a signal (event) on the bivariate forward scatter versus side scatter plot commonly used for initial gating. By using the appropriate lasers and filters specific for the corresponding excitation and emission spectra, a cell can be analyzed for its positivity, level of intensity, or absence of fluorescent markers. The majority of flow cytometric applications have focused on characterization via cell surface antigens. Unlike the hematopoietic lineage, the neural lineage has remained less extensively defined according to surface epitope expression patterns5. One advantage of exploiting surface antigens is that live cells can be subjected to cell sorting paradigms such as FACS. In contrast, intracellular antigen staining requires fixation and permeabilization steps to mediate the epitope-antibody interaction, precluding downstream applications that require viable cells. Of note, such approaches still allow for numerous quantitative assays14 as well as downstream analyses for RNA and protein expression15. Hematology, immunology and oncology have often used more than a dozen markers in conjunction to define particular subpopulations16. Additionally, mass cytometry or CyTOF can now be used to analyze up to 30 parameters simultaneously17,18.
For neural stem cell applications as well as primary cultures14,19,20 the heterogeneity of cells in vitro is a common phenomenon21-23. The cells not representing the target population of interest embody a potentially confounding factor for experimental readout24,25. Conveniently, the different cellular subsets present within a heterogeneous cell suspension bear distinct (known or yet to be deciphered) antigen expression profiles, which can be utilized to define these various populations. Flow cytometry can hence play a crucial role in resolving cellular heterogeneity and, thereby, facilitate biomedical applications (in vitro assays, cell therapy) and optimize quantitative readout by focusing on the most relevant subset24,26. Various surface antigen combinations have been identified over the past few years to allow the quantitation and isolation of specific neural cell types. This includes CD133 for the enrichment of neural stem cells27, a combination of the CD15/CD24/CD29 surface antigens for the isolation of NSC, differentiated neuron and neural crest cells28 or CD15/CD24/CD44/CD184/CD271 to isolate neural and glial subsets25, among other signatures29,30. Beyond neurons, glial markers include A2B531, CD4425, NG232 and GLAST33. A recent publication has exploited the midbrain floorplate precursor marker CORIN34,35 to enrich for dopaminergic precursors in Parkinson cell transplantation paradigms36. CD molecules are not only markers, but functionally relevant mediators of cell-cell interactions and of a cell’s ability to respond to cues from extracellular matrix molecules and growth factors37. One strategy of further enhancing the arsenal of combinatorial CD antigens to characterize neural lineage development is to use known intracellular markers to screen for and define CD antigen combinations for a particular cell type of interest. We have recently exploited such an approach and identified CD49f–/CD200high combinatorial expression patterns as a novel approach for enriching neuronal subsets from neurally differentiated induced pluripotent stem cell culture systems38. Here, we include and discuss the latter protocol (and optional variations thereof) in which surface staining and intracellular staining can be used simultaneously for defining neural cell subpopulations by flow cytometry.

Figure 2. Flow diagram of experimental protocol options. The figure depicts a schematic representation of the major steps involved in the protocol. Optional steps (CFSE dye or intracellular antigen labeling) are indicated by light grey boxes. After harvesting, it is essential to assess the viability and cell number of neural cell suspensions prior to cell surface staining. Positive as well as negative controls need to be included in addition to the samples of interest. Samples can be analyzed by flow cytometric analysis and/or used in cell sorting paradigms. Please click here to view a larger version of this figure.
While we have previously used primary antibody in combination with secondary antibody for intracellular staining38, we now introduce non-covalent labeling of the primary antibody via fluorescent Fab fragments (Zenon labeling) as a slight variation, thereby reducing the steps of cell manipulation39. Moreover, as a further example of the protocol’s versatility, we employ an optional labeling of one experimental subset by carboxyfluorescein succinimidyl ester (CFSE) prior to surface antigen staining. Such CFSE pre-labeling enables the immediate direct comparison of two cell lines or experimental conditions (CFSE-labeled vs. unlabeled) within a single sample tube, reducing variance or subtle differences in incubation time and saving antibody. CFSE is an established fluorescent dye that is commonly used for cell tracking40, in proliferation41,42 and barcoding experiments43,44. Finally, while actual sorting steps (FACS, immunomagnetic cell separation or immunopanning) are not part of this protocol, in principle, the harvesting and labeling procedures described here do yield samples that can be subjected to surface antigen- or intracellular labeling-based sorting applications15 25,28.
With this article, we aim to: summarize a viable surface antigen staining protocol25,28, summarize a protocol for detection of intracellular targets as well as combined surface and intracellular antigen analysis38, present an intracellular CFSE dye labeling step41,45 as an experimental option for comparative analyses of neural cell populations, and summarize approaches to flow cytometric analysis (appropriate controls13,46, gating strategy and data presentation47).