How to Perform and Analyze a Colony Formation Assay

The Colony Formation Assay (CFA), also known as the clonogenic assay, is a fundamental technique in cell biology used to evaluate the long-term reproductive capacity of cells. Developed in the 1950s by Theodore Puck and Philip Marcus, the assay provides a reliable measure of a cell’s ability to survive and proliferate indefinitely. It is a precise way to assess how a single cell responds to external factors like drugs or radiation over an extended period. By focusing on the formation of large cell populations, the CFA offers insights into cell survival that short-term viability tests cannot provide.

The Biological Basis of Clonogenicity

The core concept measured by the assay is clonogenicity: the ability of a single cell to multiply and form a large, genetically identical population called a colony. A cell is considered clonogenic if it can undergo sustained proliferation, typically resulting in a colony of 50 or more cells. This threshold of 50 cells, established by Puck and Marcus, indicates the cell has successfully completed at least five to six division cycles, proving its reproductive integrity.

This long-term measure differs significantly from simple viability assays, such as trypan blue exclusion, which only measure the immediate structural integrity of the cell membrane. A cell might appear viable in a short-term test but still lack the capability to divide successfully, a phenomenon known as reproductive cell death. The CFA is a superior indicator of a cell’s long-term health and its capacity to overcome cellular damage or stress.

Cells must be seeded at a low density to ensure that each resulting colony originates from a single, isolated progenitor cell, preventing overlap. For certain cell types, such as hematopoietic stem cells or transformed cells, the assay may be performed in specialized culture conditions using viscous media like soft agar or methylcellulose. These conditions prevent cell attachment and measure anchorage-independent growth, a hallmark of many cancer cells.

Performing the Assay: Key Procedural Steps

Preparation and Seeding

The CFA begins with preparing a single-cell suspension, often using trypsin to detach adherent cells. A precise count of viable cells must be determined using a hemocytometer or automated counter, as this number forms the basis for all subsequent calculations. Serial dilutions are performed to achieve the appropriate seeding density, ensuring individual cells are far enough apart to form distinct colonies.

Incubation and Counting

Cells are seeded into culture plates, with the untreated control group typically targeting 20 to 150 colonies per well. The number of cells seeded for treated groups must be adjusted based on expected cell death. Following treatment application, the cells are incubated for an extended period, typically ranging from one to three weeks, depending on the cell line’s doubling time.

Fixing and Staining

During incubation, cells that retained their clonogenic potential multiply until they reach the 50-cell threshold. Once the colonies are large enough, the medium is removed, and the colonies are preserved by fixing them, often using methanol or paraformaldehyde. The plates are then stained with a dye, such as crystal violet or Giemsa, which binds to cellular components, making the colonies visible.

The final step involves counting the stained colonies. Counting is traditionally done manually, though automated imaging systems are increasingly used to increase throughput and reduce human error.

Quantifying Results: Plating Efficiency and Survival Fraction

The raw count of colonies is converted into meaningful scientific data using two calculated metrics: Plating Efficiency (PE) and Survival Fraction (SF). PE is calculated first, representing the percentage of cells seeded in the untreated control group that successfully formed colonies. This metric measures the inherent health and growth conditions of the cell line.

Plating Efficiency (PE)

The formula for PE is the number of colonies counted divided by the number of cells seeded, multiplied by 100. For example, if 100 control cells are seeded and 50 colonies are counted, the PE is 50%. This indicates that half of the cells possessed clonogenic ability under those conditions.

Survival Fraction (SF)

The Survival Fraction (SF) quantifies the effect of the applied treatment, such as a drug or radiation, by normalizing the treated results against the control PE. The SF is calculated by dividing the number of colonies counted after treatment by the number of cells seeded, and then dividing this result by the Plating Efficiency of the untreated control group.

This normalization step accounts for the fact that only the clonogenic fraction of the initial population is capable of forming colonies. The resulting SF value provides a precise, relative measure of how many clonogenic cells survived the treatment, allowing for accurate comparison between different experimental conditions.

Primary Uses in Cancer and Drug Screening

The calculated Survival Fraction data is indispensable in medical research, particularly in oncology and radiation biology. The CFA is frequently regarded as the most accurate method for determining the effectiveness of various cytotoxic agents against cancer cell lines. Researchers use the SF values, often plotted against increasing drug concentrations, to determine the potency of novel chemotherapy agents or targeted therapies.

The assay provides a quantitative measure of a drug’s chemotoxicity by showing the reduction in colony formation as the drug dose increases. This allows for the calculation of an inhibitory concentration value (IC50), which is the concentration required to reduce colony formation by 50%.

In radiation biology, the CFA remains the established standard for evaluating the radiosensitivity of cells after exposure to ionizing radiation. Plotting the SF against the radiation dose generates a cell survival curve, which helps researchers understand reproductive cell death mechanisms. The data derived from these curves inform the design of radiation therapy protocols and the identification of compounds that can sensitize tumor cells to radiation. While the traditional CFA is low-throughput, its reliability makes it the standard benchmark against which newer screening methods are compared.