Many researchers may assume that the cell counting method represents the instrument used to perform the assay. The quality of the cell counting results is actually dependent on the cell counting assay and system, which includes not only the instrument, but also the assay, reagents, consumables, and software analysis algorithms. The entire cell counting method should be treated as a process, where each component can significantly affect the quality of the results.
Choosing a cell counting assay
Once the knowledge collection phase is complete, researchers can consider the intended use and sample composition to determine which cell counting assay is appropriate. There are four categories of cell counting assays relating to how the cells or measurands are assessed: direct total, indirect total, direct differential, and indirect differential (Table 1).
Below are the definitions for each category and a table correlating to cell counting assay example.
- Direct cell counting is the detection of independent signal(s) for each cell.
- Indirect cell counting is the measurement of a signal from a population of cells, which is relayed back to the cell number through a mathematical model.
- Total cell count includes the count of all cells, regardless of attributes.
- Differential cell count refers to a distinguishable subset of cells that is identifiable from other cell subpopulations by some measurable attribute.
| Cell counting categories | Cell counting assay example |
| Direct total | Brightfield counting all cells in hemacytometer |
| Indirect total | MTT or MTS assays to measure viable cells |
| Direct differential | Fluorescent cell counting with live cells stained with acridine orange, dead cells stained with propidium iodide |
| Indirect differential | Luciferase assay to measure cytotoxicity of T cells killing tumor cells |
Table 1. Different counting categories for cell counting measurands
A cell counting assay should be selected to best measure the intended measurands in the target cell sample, and probes should be selected based on the cell sample, application, and biological phenomenon. Researchers have been increasingly moving towards direct cell counting methods for assessing cell concentrations. A publication in PLOS ONE demonstrated that utilizing an indirect counting method such as MTS or MTT assays can yield misleading results because the ATP content can be affected by various drug treatments induced on the target cells1.
The consideration of both measurands and biological phenomenon will then be used to determine the probe of choice for cell counting. The choice of probe and the resulting signal should be carefully considered, not just in terms of the sample biology, but also regarding other potential sample traits such as presence of debris or nonspecific cell types, and sample media. A simple example is shown in Figure 1. The measurands are both live and dead cells, and the biological phenomenon is cell membrane permeability, where the selected probe is Trypan blue for detecting colorimetric visual signals from dead cells. In another example, in Figure 2, the measurands are both live and dead cells, and the biological phenomenon is cell membrane permeability. However, fluorescent probes were selected, both to specifically identify PBMCs from the contaminating cell types and cellular debris, and to easily differentiate the live and dead cells within the sample (Figure 2).
| What is the measurand (objects intended to measure)? | Live and dead cells |
|---|---|
| What is the biological phenomenon you are measuring? | Cell membrane permeable |
| What is the probe of choice? | Trypan blue |
| What are the signals detected? | Live (refractive light), dead (blue color) |
Figure 1. Example assay principle for trypan blue stained CHO cells
There are several important factors to consider when choosing a counting assay. Researchers should consider not only the counting method category, but also the biological phenomenon, ideal probe, and signal to optimally count the cells of interest. Measurands can include live cells, dead cells, and combinations of both, total cells. While biological phenomenon might be cell membrane permeability, metabolic activity, presence/absence of biomarkers, and others.
It is worth noting that there are slight behavioral differences with each nuclear fluorescent probe, and many require long incubation times to properly stain dead cells. Additionally, an incorrect probe choice can have a negative effect on cell counting accuracy, such as in the case of Trypan blue. While this is one of the most used probes to measure live/dead cells and cell viability, it can have adverse morphological effects on dead primary immune cells such as PBMCs or mouse splenocytes2, which can cause cells to rupture, thus decreasing dead cell count and increasing cell viability artificially3. Ultimately, probe choice is extremely context-specific and must be made with respect to all previous considerations of the cell counting method.
| What is the measurand (objects intended to measure)? | Live and dead cells |
|---|---|
| What is the biological phenomenon you are measuring? | Cell membrane permeable |
| What is the probe of choice? | Acridine orange and propidium iodide |
| What are the signals detected? | Live (green fluorescence), dead (red fluorescence) |
Figure 2. Example assay principle for isolated human PBMCs
Important key points for probe selection
- Trypan blue is the most common dye to measure cell viability, but the cell viability must be high, otherwise Trypan blue can affect the morphology of the dead cells, over-estimating viability4
- If your cell sample contains other nonspecific particles such as RBCs, platelets, and debris, use fluorescent probes to help obtain accurate counts5
- All nuclear fluorescent probes behave slightly differently. Apart from PI, most of the dyes require a longer staining time to properly stain the dead cells, specifically with DAPI and 7-AAD6
- For dyes requiring a longer staining time, the cells should be kept in the dark to avoid photobleaching
Questions to consider when selecting your cell counting assay
What is the measurand (the objects intended to be measured)?
- Live cells only
- Dead cells only
- Live and dead cells
- Total cells
- Other (i.e. CD3, CD4, CD8 positive cells)
What is the biological phenomenon you are measuring?
- Cell membrane permeability
- Metabolic activity
- Existence or lack of surface/intracellular biomarkers (e.g. transduction / transfection efficiency)
- Replicability (i.e. colony formation assay)
- Other
What is the probe of choice?
- Trypan blue
- Fluorescent nuclear stains for membrane permeable dead cells
- Propidium Iodide, DAPI, 7AAD, Dead Nuclear Blue/Green/Red/Far Red, DRAQ 7
- Fluorescent nuclear stains for total cells
- Acridine Orange, Hoechst 33342, Total Nuclear Blue/Green/Red/Far Red, DRAQ 5
- Fluorescent metabolic activity stains
- CFDA AM, Calcein AM, CFDA, CMFDA, CFSE
- Combination stains for live and dead cells
- AO/PI, Hoechst/PI, Calcein/PI, AO/DAPI
- Others
- Annexin V-FITC, Caspase 3/7, JC-10, ROS marker
- None (brightfield counting total cells)
What are the signals detected?
- Refractive light in brightfield imaging
- Dark spots in brightfield imaging
- Blue spots in brightfield imaging
- Blue/Green/Red/Far Red fluorescence
- Impedance
Choosing an automated cell counting system
The simplest device for cell counting has been the hemocytometer used with a standard light microscope. The hemocytometer has been used since the 1800’s, and has evolved over the two centuries since then. However, various issues are well- known. For example, the operation is time-consuming and tedious, and variability can result from operator errors.
An automated cell counting system can be used to detect the biological phenomenon and signals from your measurands (cells) and probes. The cell counting system consists of not only the instrument, but also the reagents, consumables, and software algorithms for cell identification. By considering the different components of the cell counting system, an optimal selection can be made for the selected cell counting assay.
| Sample #7 | Sample #6 | Sample #2 | Sample #5 | |
|---|---|---|---|---|
| Total cell count | 49 | 1419 | 10635 | 24245 |
| Live cell concentration | 1.07E+05 | 2.84E+06 | 3.11E+07 | 6.75E+07 |
| Viability | 63.20% | 58.00% | 84.40% | 80.30% |
| Bright field cell image |
 |
 |
 |
 |
| Counted live & dead cell image |
 |
 |
 |
 |
Table 2. Eliminating dilution steps with the Cellometer Auto 2000
A critical consideration for any cell counting instrument is the range without dilution. Some instruments may indicate a large cell concentration range, but may require multiple dilutions, which can increase the Coefficient of Variation (CV) of the cell counting results. Therefore, it is important to know the actual cell counting range in the absence of any dilution steps. Demonstration of this concept is observed in an experiment performed by measuring cell count and viability of lymphocytes from 30 different mice using the acridine orange/propidium iodide. The Cellometer Auto 2000 showed that mouse lymphocytes can be properly measured within a range from 1 x 105 to 6 x 107 cells/mL without additional dilution steps (Table 2). Therefore, researchers can reliably use automated cell counting instrumentation to measure within this range, thus avoiding dilution as a contributing factor.
Beyond dilution range, there are multiple additional factors when choosing a cell counting system, including what reagents and consumables are required. While reagents can affect cell counting itself through the type, fluorescence color, or strength of signal, they also can affect general experimental flow through cost, availability, and ease of access. Additional consumable considerations include sterility and reusability, as well as shelf-life. Finally, researchers must carefully consider the software used to count cells, as algorithms between systems can vary drastically. The system software should be able to accurately assess the desired measurand, which may include many considerations for the usability of the software. Ultimately, the cell counting system chosen will be specific to the sample and desired result and should be made with consideration to long-term consistency, especially when considering manufacturing applications.
Questions to consider when selecting your cell counting system
What reagents can you use for the intended measurand?
- What is the availability of the reagents?
- What is the lead time or shipping duration?
- What is the cost of the reagent?
- What color/fluorescence are they?
- How bright is the signal?
What consumables are needed to measure the cells?
- What is the availability of different consumable offers, such as depth, for different size or spheroid sizes?
- What is the shelf-life of the consumables?
- What is the cost of the consumables?
- Do the consumables have auto-fluorescence?
- How clean are they? Are they reusable?
- How accurate are the dimensions?
What are the available cell identification algorithms?
- What imaging modes are available?
- Is the algorithm able to analyze both brightfield and fluorescent images separately and together?
- Can the software measure both total cells or viable cells and viability simultaneously from the same cell sample?
- Can the software provide cell counts, size, and morphology?
- How well can the algorithm de-cluster cells that are in close proximity?
- How many preset assays and cell types does the software contain?
- Can the software analyze cell population through visual gating strategies?
- Can the counting parameters be saved for future use?
- How easy is the software to use?
References:
- Chan GK, Kleinheinz TL, Peterson D, Moffat JG. A simple high-content cell cycle assay reveals frequent discrepancies between cell number and ATP and MTS proliferation assays. PLoS One. 2013;8(5):e63583
- Chan LL, Kuksin D, Laverty DJ, Saldi S, Qiu J. Morphological observation and analysis using automated image cytometry for the comparison of trypan blue and fluorescence-based viability detection method. Cytotechnology. 2015;67(3):461-473.
- Chan LL, Rice WL, Qiu J. Observation and quantification of the morphological effect of trypan blue rupturing dead or dying cells. PLoS One. 2020;15(1):e0227950. Published 2020 Jan 24. doi:10.1371/journal.pone.0227950
- Chan LL, Kuksin D, Laverty DJ, Saldi S, Qiu J. Morphological observation and analysis using automated image cytometry for the comparison of trypan blue and fluorescence-based viability detection method. Cytotechnology. 2015;67(3):461-473.
- Chan LL, Rice WL, Qiu J. Observation and quantification of the morphological effect of trypan blue rupturing dead or dying cells. PLoS One. 2020;15(1):e0227950. Published 2020 Jan 24. doi:10.1371/journal.pone.0227950
- Chan LL, Laverty DJ, Smith T, et al. Accurate measurement of peripheral blood mononuclear cell concentration using image cytometry to eliminate RBC-induced counting error. J Immunol Methods. 2013;388(1-2):25-32.
- Chan LL, Wilkinson AR, Paradis BD, Lai N. Rapid image-based cytometry for comparison of fluorescent viability staining methods. J Fluoresc. 2012;22(5):1301-1311
- Chan LL, McCulley KJ, Kessel SL. Assessment of Cell Viability with Single-, Dual-, and Multi-Staining Methods Using Image Cytometry. Methods Mol Biol. 2017;1601:27-41.
For research use only. Not for use in diagnostic procedures.