Methods to Estimate Confluency in Cell Culture?

Methods to Estimate Confluency in Cell Culture? Complete Guide!

Methods to Estimate Confluency in Cell Culture? Cell culture monitoring is crucial in cell therapy applications. Cell viability assays can provide valuable information on the quality of the cells used in these applications. Live population tracking can also be very beneficial in stem cell cultures. The results of such analyses can be quantified with the use of image analysis algorithms. Moreover, live population tracking allows scientists to monitor how the cells grow and develop.

Methods to Estimate Confluency in Cell Culture
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Table of Contents

Methods to Estimate Confluency in Cell Culture

Image-based method

A qualitative visual inspection of a cell culture can be useful for estimating confluency. However, an automated image-based method is the gold standard for reproducibility, accuracy, and reliability.

Image-based methods have several limitations. First, they are subject to high inter-individual variability. For example, a survey of researchers using cell culture revealed a variation of up to 11.7% in confluency. Hence, a consistent, accurate method to check confluency is essential.

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In this study, a cell culture of the McCoy cell line was used. The cells were seeded at a density of 2 x 104 cells per ml in 96-well plates. Four replicates were prepared. The cells were then placed in a CELENA(r) X Stage Top Incubator Pro, and photographed at 20-minute intervals for 48 hours. The images were analyzed using CELENA(r) X Cell Analyzer software.

Phase contrast microscopy

Another method for determining confluency in cell cultures is phase contrast microscopy. This technique is widely used in the laboratory setting to examine adherent cells. However, it has several limitations, including low contrast and bright halo artifacts surrounding cellular objects. Halo artifacts may falsely inflate cell area measurements and obscure cell contours. For this reason, segmentation of PCM images requires sophisticated algorithms.

Phenol red

Phenol red is a color-changing substance that is often used to check the confluency of cell cultures. This dye is non-toxic and can be seen without a microscope. If phenol red is present, there is a good chance that bacteria are causing contamination. Bacteria are very ubiquitous and have a high metabolic rate, which can affect pH and the color of phenol red. Bacteria are also very small, making them difficult to see under low microscope magnification, but can be seen as distinct shapes at higher magnification.

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The color of phenol red changes from yellow to red to fuchsia with increasing pH. It is used to test the confluency of cell cultures and is commonly included in tissue culture media. It has been described as a weak estrogen under some conditions, but is for the most part an inert compound. Its concentration varies according to the type of media used and ranges from five to fifteen milligrams/mL.

Cell Imaging

Cell cultures are monitored for pH with the Cytation(tm) 5 Cell Imaging Multi-Mode Reader. The Cytation(tm) 5 has the capability of taking measurements from phenol red in real time while microscopic imaging is performed using a 6-position objective turret and LED light cubes.

With this technology, the time required to image a 96-well culture is reduced to mere seconds. In addition, the Gen5 Microplate Reader Software allows for continuous real-time monitoring of long-term live cell cultures.

Phenol red is a bifunctional color indicator that shows how concentrated a solution of phenol red is. Its sensitivity increases with pH and increases when the media contains greater amounts of phenol red. The concentration of phenol red in culture medium is equal to the concentration of pH in the medium.

Visual inspection

Visual inspection of cell confluency is an essential part of successful cell culture applications. Using a microscopic approach, a researcher can estimate the level of confluence of the growing cells, determining when they are ready for assay or passage. Unfortunately, microscopic inspection has a high degree of error and has not been standardized. This can negatively affect downstream experiments.

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Confluency is usually expressed as a percentage, and refers to the proportion of culture dish or flask surface covered by adherent cells. For example, if a culture dish or flask is filled with HEK293 cells, 80% of the surface will be covered by the cells. While confluency can be difficult to measure, there are some simple guidelines to keep in mind. The area covered by cells should be equal to the area that is not covered by cells.

Compare the Images

Another method for estimating confluency is to compare images of cells at different stages of culture. To perform this task, an imaging software called PHANTAST is used. This software calculates the fraction of pixels in an image labeled as a cell. The precision of the method was found to be 2.7%, with good quality estimation across a wide range of confluencies. Moreover, the algorithm also has the advantage of being consistent, allowing for comparison across trials.

Cell Density

Another method of determining cell density is PCC. The resulting values of PCC and confluency should be correlated. In order to perform this calculation, the two metrics must be measured and analyzed. The result of a PCC-based method should be compared with the mean cell density for confluency.

Errors During Estimation of Confluency in Cell Culture

Finite Sampling Size

Estimation of error due to finite sampling size is a problem that arises when experiments are performed on a limited number of cells. The sample size is usually not large enough to permit accurate estimation of the parameter that controls the population. For example, a cell division rate can be unknown, and researchers need to make measurements to determine its variability. However, this method often fails to reveal the true variability of the sample.

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The issue of sample size is one of the most important issues in science. It impacts the hypothesis and the design of a study. Without a proper calculation of the sample size, the results may be inaccurate, cost the experimenter time and create ethical dilemmas. Hence, we must take the time to understand the concepts involved in calculating sample size.

Standard Error

Standard error is the difference between the mean value and the standard deviation of the sample. Its magnitude depends on the sample size and the natural variation of the sample. Higher resolution imaging software can measure a diameter with a lower error. Similarly, a larger sample size can increase the precision of the measurement.

As an effective cellular biologist, it is important to be aware of and use statistics. By following the seven steps of statistical hypothesis testing, cellular biologists can minimize the risk of making common mistakes. The Molecular Biology of the Cell website provides useful information on statistical tests and experimental design. It also provides consultants who can assist with specific problems.

Other Ways to Estimate Confluency in Cell Culture

There are several ways to test cell confluency. One method is to use bioorthogonal labeling. In this method, the cells must be at least 50-80% confluent. This level is considered appropriate for experiments using bioorthogonal labels. Cells at this confluency can be exposed to 100 mM menadione. The cells can then be grown to a desired confluency.

Another way is to use a live cell imaging technique. This allows researchers to view the cells without killing them. It can also be used to monitor the number of live cells in a culture. In contrast, endpoint assays are more invasive. Using live-cell imaging allows researchers to see the cells as they grow.

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LipImage(tm) 815 caused slight reductions in the viability of four cell lines. RAW 264.7 macrophages exhibited the least variation in viability, ranging from 94.4% +-5.2 mL at the lowest concentration. The most dramatic reduction was observed with NIH-3T3 fibroblasts when LipImage(tm) 815 was used at a concentration of 128 ug/mL.

The WST-8 assay is another method to check cell viability. It uses a lower cell count than LDH release cell death assay. It uses cells that are nearly confluent. The WST-8 assay also calculates the standard deviation (SD), which is a measure of variability among results.