From Hemocytometers to Advanced Tech: The Evolution of Cell Counting

Cell counting is a fundamental step in any experiment that requires knowledge of cell density and viability. Traditionally, it has been performed manually, using a hemocytometer and a microscope to evaluate samples by eye. However, this approach has several limitations that have led to automated cell counters being more widely adopted. This article covers the basic principles of hemocytometer-based cell counting and highlights the advantages of automated platforms. It also explores how cell counting technology is evolving to support the growing use of 3D cell models.

Principles of hemocytometer-based cell counting

A standard hemocytometer consists of two main parts: a specialized glass slide with a grid etched into the surface, and a thick glass coverslip. When the coverslip is placed on top of the slide, it creates chambers that can each hold a specific volume of liquid. To perform a cell count, the cell suspension is stained with a viability dye, such as Trypan blue, and a small volume of the sample (~10 µL) is introduced to the counting chamber. The cells are then counted manually with the aid of a microscope, and the concentration and viability are calculated. For improved counting accuracy, it is common practice to average the number of cells in several squares, and to only include cells touching the top and right edges of each grid area.

Limitations of hemocytometers

While hemocytometers are inexpensive, reusable, and require only small amounts of sample, their benefits are offset by several drawbacks. First, manual counting is both labor-intensive and time-consuming, which can be especially problematic when handling large numbers of samples. Second, counting accuracy and reproducibility can be affected by device misuse, as well as by subjectivity among users. A common mistake is to leave the cells in Trypan blue for an extended period, which can cause cytotoxicity or cell death, leading to unreliable viability measurements. Other limitations of hemocytometer-based cell counting are that it lacks statistical robustness at low sample concentrations and may not always provide the depth of information required by modern research applications.

The introduction of automated cell counters

Automated cell counting dates back to the 1950s, when Wallace H. Coulter introduced the first Coulter counter. Designed to measure changes in electrical resistance as cells passed through a small aperture, the Coulter counter enabled researchers to quickly and easily determine the number and size distribution of cells in a suspension sample. However, despite being widely used for counting blood cells, the Coulter counter has seen more limited uptake for routine cell biology applications. One reason for this is the Coulter counter’s inability to accurately distinguish cell clusters. Another is that it does not provide cell viability metrics. To address these issues, other types of automated cell counters have been developed, including instruments with imaging capabilities and the capacity to measure fluorescence.

Advantages of automated cell counting

One of the main advantages of automated cell counting is that it delivers more rapid results than manual counting methods, which can be especially beneficial for high-throughput laboratories. Automated cell counting also offers superior counting accuracy and reproducibility by eliminating human error and subjectivity from the counting process. Other advantages of automated cell counting are that it requires only minimal training and, depending on the type of instrument being used, can often provide additional information beyond cell numbers and viability data.

Types of fluorescence-based cell counting

Fluorescence-based cell counting is a popular alternative to bright field analysis that offers greater flexibility in method selection. One of the best known approaches combines acridine orange (AO) with propidium iodide (PI), whereby AO can enter all cells and emits green fluorescence when bound to DNA, while PI can only enter dead or dying cells and emits red fluorescence upon DNA binding. Because PI absorbs AO fluorescence through Förster resonance energy transfer (FRET), live cells fluoresce green and dead cells fluoresce red, allowing for accurate determination of the total cell number and viability. Another common method pairs DNA staining with detection of metabolic activity, such as through the combination of PI and Calcein AM, a membrane permeant reagent that fluoresces green when cleaved by intracellular esterases. In this scenario, the number of viable cells (i.e., green cells) is calculated as a percentage of the total cell number (i.e., red cells plus green cells).

The changing landscape of automated cell counting

The increased use of 3D cell models for scientific research is driving change within the field of automated cell counting. Complex 3D populations such as spheroids and organoids are known to vary in size and morphology depending on countless environmental factors or protocols, which inevitably makes obtaining accurate counts more challenging. This problem is being resolved with the development of sophisticated machine learning algorithms, including software that is trained to differentiate individual spherical objects within clusters, as well as algorithms that engulf the individual outer membranes within the field of view to calculate accurate surface area and organoids per mL data. The need to adopt greener working practices is contributing to further developments, with automated cell counting technology becoming more sustainable by moving away from the use of disposable counting slides. For example, the Corning^® Cell Counter works with a standard reusable glass hemocytometer, meaning no consumables are required—an approach that is both environmentally friendly and more cost-effective.