Discover the expert tips that will teach you how to calculate cell confluency with maximum precision. Embark on a journey through the world of cell confluency estimation together with us and equip yourself with the techniques and tools to achieve better results. From optimal experimental conditions to imaging methods and automated image analysis software, we’ve got you covered!
Why do cell confluency estimations matter in life science experiments?
In cellular differentiation experiments, achieving optimal cell confluency is an important step. The term “confluence” refers to the proportion of cell dish culture surface occupied by adherent cells. Researchers must make crucial decisions about their cell culture to ensure the presence of viable cells and to maintain a healthy and functional culture. (Chui et al., 2020)
Using cell culture, researchers grow cells in a controlled environment outside of their natural setting, typically in a laboratory dish or flask. As cells proliferate and divide, they spread across the available surface. Cell confluency becomes relevant in experimental settings where the density of cells can influence various cellular processes, including cell signaling, metabolism, and response to stimuli. (Zenan et al., 2021)
Low confluency (e.g. 20-30%) indicates that there is still enough space available for the cells to proliferate. High confluency (e.g. 80-100%) means that the cells have covered most of the available surface, and they may start to exhibit contact inhibition. This is a phenomenon where cells stop dividing when they come into contact with neighboring cells.
Cell confluency is also considered a very important parameter in cell culture, as it is used to determine when cells are ready to be subcultured, harvested, transfected, or used in any other experimental procedures. Therefore, accurately measuring cell confluency is a fundamental step in sustaining robust cell cultures and securing precise outcomes in experiments (Jaccard et al., 2014).
Did you know?
Contact inhibition in cell biology involves two closely related phenomena: contact inhibition of locomotion and contact inhibition of proliferation. For example, normal cells cease migration and adhere to each other upon contact with neighboring cells, forming an orderly cell array.
In contrast, tumor cells do not exhibit this inhibition, continuing to move and proliferate in a disordered manner even after contact with neighboring cells. Contact inhibition not only affects cell movement but also restricts the proliferation of normal cells, a sensitivity that cancer cells typically lack (Ribatti, 2017).
Must-have tools for precise cell confluence estimation
Obtaining precise cell confluence measurements relies on the use of specific tools and techniques. One essential component is the selection of appropriate vessels such as cell culture flasks and tissue culture dishes, including Petri dishes.
Did you know?
The choice of tissue culture medium or growth medium generally depends on the specific cell type and experimental requirements.
For example, the confluence of endothelial cells, epithelial cells, pluripotent stem cells, fibroblasts, HeLa cells, HUVEC cells, HEK cells, and others needs to be carefully monitored to maintain a healthy and functional culture. (Chui et al., 2020)
The table below showcases commonly used cells in cell culture, along with the recommended culture medium and flask coating. Depending on your specific experimental conditions, alternative combinations may be necessary.
| Cell Type | Use | Culture Medium and Flask Coating |
|---|---|---|
| Endothelial cells | cancer therapy, wound healing, also used in cell signaling and toxicology screening | Ham’s F-12K with 10% FBS (Foetal Bovine Serum) and 100µg/mL heparin Fibronectin-coated, 1% gelatine |
| Keratinocytes | diseases of the skin (e.g., skin cancer, psoriasis) | Keratinocyte Growth Medium 2 (serum-free) |
| Epithelial cells | cancer therapy, toxicology studies | MEM (Minimum Essential Medium) and 10-20% FBS (depending on tissue), McCoy’s 5A and 10% FBS, F-12K with 10% FBS |
| Melanocytes | wound healing, melanoma, other skin conditions, toxicity, derma response to UV radiation | MEM 1% gelatine |
| Fibroblasts | wound healing and regeneration (iPS-inducing pluripotent stem cells) | DMEM (Dulbecco’s Modified. Eagle Medium) and 10% FBS |
| Smooth muscle cells | fibrosis, cancer research | Smooth Muscle Growth Medium-2 |
| Immune cells | cell-based assays, differentiation studies | RPMI 1640 + 2mM Glutamine + 10-20% FBS |
| Stem cells | differentiation into different cell types and allow the study of disease states | Gibco media |
To promote even confluency distribution from the center to the periphery of a Petri dish, careful considerations about the experimental setting and equipment used should be taken. For example, the treatment of cell culture flasks plays a pivotal role in facilitating cell adherence.
The surface coating of culture flasks helps to enhance the adherence of cultured cells and can be a determining factor in whether your culture experiment performs successfully or not. Various techniques involve applying extracellular matrix proteins (e.g., collagen, fibrin, fibronectin, gelatin) or synthetic polymers to the flask surface. This treatment prepares the flask surface to support the adherence and growth of cultured cells. (Abraham et al., 2011)
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Explore tried-and-true methods for measuring cell confluency
If you’ve been looking for effective analysis methods on how to measure the confluency of cells, we have some tips for you.
Measuring cell confluency is a multistep process in cell culture experiments. The process of cell confluence analysis involves both quantitative analysis and visual estimation.
The visual method is a very straightforward approach. This means researchers visually inspect the cell culture under a microscope, assessing the extent to which the growth surface is covered by cells. This qualitative method provides an initial impression of the confluency level of your cell culture.
Moving beyond a visual inspection, quantitative methods are employed. For example, open-source image analysis software such as ImageJ or CellProfiler can be used for automated cell confluence analysis. With the help of these tools, the percentage of cell-covered area relative to the total area can be calculated. (Busschots et al., 2015)
Another approach is sequence analysis, which allows the analysis of sequential images of a cell culture over time (e.g., time-lapse microscopy, live-cell imaging). This method allows researchers to make timely decisions about the optimal time for experimental interventions.
Impedance-based systems, such as the Electric Cell-substrate Impedance Sensing (ECIS) are non-invasive and label-free methods to monitor changes in electrical impedance across cell culture surfaces as cells grow, providing real-time data on confluency. As cells grow to confluency the impedance current increases (Morgan et al., 2019).
The latest advancement in cell confluency tools involves integrating AI-based applications for the automated analysis of cell culture images. These tools are fast and provide accurate results because they are usually trained on comprehensive real-life datasets.
Measuring cell confluency often starts with a visual estimation and progresses to a quantitative method (if needed). Only an integration of various techniques ensures a comprehensive understanding of the underlying confluency dynamics.
Researchers frequently begin with visually assessing cell cultures under a microscope before deciding whether to employ quantitative methods. However, only quantitative measures allow for consistency and reproducibility. Tools such as image analysis software provide reliable insights into the confluence status of cell cultures.
Interpreting confluency measurements the right way
When it comes to estimating cell confluency, calculating the confluency percentage correctly is key.
Accurate interpretation of confluency measurements involves understanding the growth behavior of adherent cells, implementing strategies to increase confluency when necessary, and determining the optimal confluence rate for experimental interventions (e.g., transfection, etc.). The overall success and reliability of cell culture experiments rely on these considerations. (Nikcevic et al., 2003)
When cell confluency is too low, there are several strategies to increase it (Ammerman et al., 2008):
- Increase the number of seeded cells.
- Optimize culture conditions e.g. nutrient supply
However, the optimal confluence rate varies depending on the cell type and transfection method. Generally speaking, a confluence rate between 70-90% is considered optimal for most cell types.
What does 50% confluence mean?
In a cell culture, “50% confluence” means that approximately half of the growth surface in a culture vessel (e.g. petri dish, flask) is covered by adherent cells. It indicates that the cells have proliferated and spread to cover half of the available space. This measurement is often used to describe the early stages of growth, where there is still space for cells to further populate the culture vessel.
However, researchers use the term “half-confluent monolayer” to refer to a cell culture, where the cells have covered 50% of the available surface, but have not yet formed a completely closed or confluent monolayer. This means that the cells may still be in the process of actively proliferating (Nikcevic et al., 2003).
As soon as the cells exceed 50% confluency, it means that more than half of the growth surface is covered. When the entire available surface is covered a confluent monolayer is achieved (Nikcevic et al., 2003).
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What does 70% confluence mean?
“70% confluence” means that approximately 70% of the growth surface in the culture vessel is covered by adherent cells. At this level, the cells have spread to cover a substantial portion of the available surface. This state is often considered optimal for many procedures such as sub-culturing, plating, or experiments (Abo-Aziza et al., 2017).
High confluence levels result in abundantly populated images, meaning visually dense and well-covered surface areas. Typically, cultures at 70% have a high cell viability and proliferation rate. This indicates that the cells are viable and metabolically active. At this point, they are often considered optimal and ready for transfection. The cells are actively dividing, but have not yet reached a point where contact inhibition significantly hinders transfection efficiency (Nikcevic et al., 2003).
What does 100% confluence mean?
When the entire surface area is completely covered by cells, the cell culture is about to become over-confluent. This can lead to several issues that may impact experimental outcomes and the health of the cell population (Abo-Aziza et al., 2017). There are some common problems, that are associated with over-confluent cells:
- Increased metabolic stress
- Contact inhibition
- Nutrient depletion
- Altered cell behavior
- Reduced experimental precision
To minimize the risk of these issues, researchers try to maintain cells at an optimal confluence level, typically between 70-90% for many cell types. However, there are different strategies you can use to prevent over-confluence (see infographic below).
How AI software makes a difference in cell confluency measurement
For years, scientists relied on manual or semi-automated methods to estimate cell coverage, facing challenges in accurately quantifying cell monolayers. These methods were time-consuming and prone to human error, limiting the accuracy required for cell culture experiments.
The advent of AI-driven image analysis tools has restructured the way researchers assess cell confluency. This innovative technology, encompassing automated confluency measurements and density data analysis has significantly enhanced our ability to monitor cell growth and quantify crucial metrics in cell culture studies.
Cell segmentation is an important step for confluency measurement. In terms of confluence measurement, this involves accurately identifying and outlining individual cells as well as cell accumulations within microscopy images, distinctly separating them from the background. Software tools like the IKOSA Prisma Confluence App were specifically developed for the analysis of cell monolayers in a high-throughput manner, providing researchers with efficient and accurate measurements of cell confluence.
Advantages of AI software over traditional confluence measurement methods
| Traditional approach | AI-driven methods | |
|---|---|---|
| Measurement technique | Visual inspection typically involves manually assessing cell density using microscopy. | Image analysis utilizes machine learning models to analyze images automatically. |
| Accuracy and Precision | Subject to observer bias. Results may vary based on the individual interpretation of cell confluence data. | Higher accuracy and consistency. AI models can provide more objective and reproducible measurements. |
| Analysis speed | Time-consuming. It requires manual counting and assessment, which can be rather slow. | AI can process large datasets and provide confluence measurements quickly. |
| Scalability | Limited → manual methods may become impractical for high-throughput experiments. | High → AI can handle large datasets, making it suitable for high-throughput and automated workflows. |
| User training | Requires training. | User-friendly. |
| Adaptability to cell types | Variable, depending on cell types, manual methods may be more challenging for certain cell lines. | Versatile, AI solutions can be trained on diverse cell types. |
| Real-time monitoring | Challenging and impractical with manual methods. | AI solutions can analyze live images, enabling continuous monitoring. |
| Technical resources | Limited requirements (microscope and basic lab equipment). | Computational resources and access to computers are required. |
| Costs | Low initial costs, but labor-intensive. | Initial investment for setup and training. |
Looking for an efficient way to measure cell confluency? The IKOSA Confluence App has your needs covered.
Transform your analysis workflow with the IKOSA Confluence App
The IKOSA Prisma Confluence App embodies state-of-the-art cell confluency measurement. Its outstanding performance in cell confluency measurement is a result of extensive training based on real-life datasets. Trained on various cell types and imaging modalities, this App has been optimized for a high degree of generalizability in confluence detection across various cellular structures and microscopy techniques.
The App’s rigorous development process has ensured adaptability, allowing researchers to confidently utilize it across different experiments, knowing that it comprehensively recognizes and measures cell coverage irrespective of the specific cell type, microscopes, or imaging method used.
Like the entire Prisma Application portfolio, the Confluence Analysis App is integrated into our easy-to-use and browser-based IKOSA platform, removing barriers such as coding or expensive IT investments. Just open the platform in your web browser and start analyzing.
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References
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