Manual cell counting V.S. Automated cell counting

How can automated cell counters overcome the 4 major problems with manual cell counting?

Manual cell counting is still the golden standard method of cell counting in many labs. But, as presented in this article, there are several issues with the results obtained by manually counting cells with trypan blue and hemocytometer.

Cell counting with image cytometry and the automated cell counters provides a solution to all of these problems.

Furthermore, methods for counting adherent and aggregated cells are also developed for the NucleoCounter^® system, allowing for fast and specific measurements of cells that are normally challenging to estimate specific cell concentrations of. This provides an immense advance in precision and reproducibility for mammalian cell culturing.

Automated cell counter - NucleoCounter NC-200

Request a Quote
Request a Demo
Contact us

Request a Quote

Request a Demo

Challenges in manual cell counting of mammalian cells

The time at the microscope counting cells is both laborious and time-consuming. As mammalian cells are delicate systems, they require high reproducibility of setup during culturing. It is vital to know the specific cell concentration and viability of a cell sample to obtain reproducibility in subculturing, monitoring growth rates or for cryopreservation^1,2. But manual cell counting of the cell concentration can give rise to large errors in cell concentration and viability.

The 4 biggest problems with manual cell counting:

Human perception of definition of cell
Volume, dilution and pipetting errors
Trypan blue exclusion for viability determination
Counting enough events

1. Human perception and definition of cells

The manual recognition of when a cell is a cell or when it is cell debris or other particles can be challenging even for the trained eye. Each person performing the manual cell count has a certain set of criteria that defines a cell and the threshold of brightness of the stain in order to count it as viable or dead. These interpersonal differences in manual cell recognition can be crucial for the experimental setup. If multiple users count the same sample it is not uncommon to see a variance significantly higher than the mean of a Poisson distribution³.

Figure 1. Cell samples with cell debris are very challenging to count correctly manually. In comparison, fluorescent events are clearly visible.

2. Volume, dilution and pipetting errors with manual cell counting

The preparation and loading of the cell sample in the hemocytometer can give rise to errors. Though the hemocytometer contains a given volume, the space between the counting chamber and the cover glass might be slightly increased when the chamber is filled with liquid (Fig. 2). This can give rise to errors based on wrong estimation of the volume. Volumetric errors can also arise from pipetting or from serial dilutions.

Figure 2. Side view of a hemocytometer when empty (left) and filled (right). Loading of the hemocytometer can result in an increase in the volume of the chamber. This results in an underestimation of the sample volume giving rise to too high estimation of cell concentrations.

3. Viability determinations: Trypan blue or DAPI?

When estimating the cell viability manually, trypan blue is used as a marker for dead cells. Trypan blue stains dead cells with a permeable cell membrane whereas viable cells are not stained. But as trypan blue is also toxic to the cells, viable cells are eventually stained within a timeframe of 5 to 30 minutes. Trypan blue is known to underestimate the viability of cell populations and caution must be taken when interpreting trypan blue-based vitality⁵. Therefore, selecting a membrane impermeable DNA-binding dye as DAPI for definition of dead cells will increase the precision in viability determinations.

4. Counting enough cells

Although manual cell counting in the improved Neubauer hemocytometer is standardized to ten chambers corresponding to 1 µL total counted¹, the procedure for manual cell count is, in many cases, to count 100 cells or a specific volume as 0.4 µL regardless of the concentration of cells. Such a low volume and cell count increases the effect of stochastic variables. If only 100 cells are counted, the variation from pure statistics will be 10 %, assuming the variation follows the Poisson distribution according to which the expected standard deviation is equivalent to the square root of the number of counted events, even without human-introduced variations.

Avoid human interference using the Via1-cassette™

The Via1- Cassette™ (Fig. 3) is designed to overcome all human interference in cell counting:

No human bias will influence the result – the definition of cells are performed with the software based on acridine orange signal, and will be the same in every analysis.
No user or pipetting errors interfere with data generation – the cassettes have a pre-calibrated volume of the measurement chamber giving a precise and reproducible result.
The cassettes are loaded with immobilized acridine orange and DAPI for definition of total cell and dead cell population, respectively.
The instrument will tell you if you have too few or too many cells in the sample.

The cassettes are disposable plastic units that contain the fluorescent dye used for analysis. A cell sample is easily loaded into the cassette by submerging the inbuilt pipette into the cell suspension and pressing the piston.

Figure 3: The Via1-Cassette™ designed for fast and efficient one-step viability and cell concentration count. Acridine orange stains the total population of cells with and dead cells are stained with DAPI. Learn more…

Automated cell counters for higher precision and reproducibility

One of the most precise and easy-to-use systems is the NucleoCounter^® developed by ChemoMetec A/S⁴. The NucleoCounter^® instruments are image cytometers based on fluorescence microscopy with fluorophores for detection of cell populations (Fig. 4). The light sources are LEDs, which have a persistent lifetime and stability. Light is filtered through a suitable set of excitation filters matching the dyes in the cassette. The sample is semi-automatically loaded and stained with appropriate dyes within the cassette, and the cassette is inserted into the light path in the instrument. The resulting emitted light is focused and filtered, and an image is captured onto a digital camera. Image cytometry with the NucleoCounter^® system provides not only a platform for obtaining high-quality data, but also allows for visual inspection of data, as images captured can be viewed with accompanying software.

Figure 4. Image cytometry and the fluorescence microscope within the NucleoCounter^® family. The light sources are LEDs, which are filtered though the excitation filter. When passing through the sample in the cassette (yellow), the fluorophores bound to cells will emit light, which is focused and passed though an emission filter to remove light with unspecific wavelengths. The focused emitted light is captured by a charge-coupled device (CCD) camera.

Fluorophores for cell counting

Automated cell counting with the Via1-Cassette™ (for NucleoCounter® NC-200™ and NC-3000™) is based upon two spectrally and biologically different dyes defining total cells and unviable cells, that is AO (acridine orange) and DAPI (4′,6-diamidino-2-phenylindole). Acridine orange is cell permeable and binds to cellular material with green fluorescence and is an efficient dye for total cell count⁶.

The NucleoCounter^® system detects the interaction between DNA and AO with excitation at 500 nm and emission at 555/35 nm. DAPI is an efficient stain for dead cells as living cells are impermeable for low concentrations of DAPI (a few µg per mL). DAPI fluoresces blue upon binding to AT-rich clusters in the minor groove of double stranded DNA⁷.

Author:

Merethe Mørch Frøsig, PhD, MSc
Field Application Scientist, ChemoMetec A/S

Literature

Phelan, M.C., Basic techniques in mammalian cell tissue culture. Curr Protoc Cell Biol, 2007. Chapter 1: p. Unit 1.1.
Freshney, R.I., Basic Principles of Cell Culture. 2006: p. 1–22.
Nielson, L., G. Smyth, and P. Greenfield, Hemacytometer Cell Count Distributions: Implications of Non-Poisson Behavior. Biotechnology Progress, 1991. 7(6): p. 560-563.
Shah, D., et al., NucleoCounter-An efficient technique for the determination of cell number and viability in animal cell culture processes. Cytotechnology, 2006. 51(1): p. 39-44.
Tennant, J.R., Evaluation of the Trypan Blue Technique for Determination of Cell Viability. Transplantation, 1964. 2: p. 685-94. PMID: 14224649.
Robbins, E. and P.I. Marcus, Dynamics of Acridine Orange-Cell Interaction. I. Interrelationships of acridine orange particles and cytoplasmic reddening. J Cell Biol, 1963. 18: p. 237-50. PMID: 14079487.
Kubista, M., B. Akerman, and B. Nordén, Characterization of interaction between DNA and 4′,6-diamidino-2-phenylindole by optical spectroscopy. Biochemistry, 1987. 26(14): p. 4545-53. PMID: 3663606.

Manual cell counting V.S. Automated cell counting

How can automated cell counters overcome the 4 major problems with manual cell counting?