Viability Counts
Viability Counts - Related Videos
05:47
Counting and Determining the Viability of Cultured Cells
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Cited by 19 •
2008
Determining the number of cells in culture is important in standardization of culture conditions and in performing accurate quantitation experiments. In this video, we demonstrate how cells are counted using a hemacytometer.
10:19
Using a Hemacytometer to Count Cells
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2023
Many biomedical experiments require manipulation of a known quantity of cells, in order to achieve accurate, reproducible, and statistically-relevant data. Therefore, learning how to count cells is a particularly essential technique for any successful biomedical scientist. The most common way to count cells is by using a hemacytometer - an instrument that bears two laser-etched grids, which aid in the enumeration of an aliquot cells under a simple light microscope. This data can then be used to...
06:37
Counting Human Neural Stem Cells
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Cited by 14 •
2007
Knowledge of the exact number of viable cells is required for many tissue culture manipulations. This protocol describes how to differentiate between live and dead cells and quantify cells using a hemacytometer. Although it describes counting human neural stem/precursor cells (hNSPCs), it can be used for other cell types.
12:03
Viability Assays for Cells in Culture
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Cited by 39 •
2014
Therapeutic compounds are often first examined in vitro with viability assays. Blind cell counts by a human observer can be highly sensitive to small changes in cell number but do not assess function. Computerized viability assays, as described here, can assess both structure and function in an objective manner.
07:05
Viability of Bioprinted Cellular Constructs Using a Three Dispenser Cartesian Printer
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Cited by 6 •
2015
A Cartesian bioprinter was designed and fabricated to allow multi-material deposition in precise, reproducible geometries, while also allowing control of environmental factors. Utilizing the three-dimensional bioprinter, complex and viable constructs may be printed and easily reproduced.
FAQs
Serial dilution plating links a countable colony number to the viable population in the original sample. A sample is diluted stepwise, plated on suitable culture medium, and the colonies that develop are counted; the result is then converted to colony-forming units (CFU). This conversion makes samples with different starting concentrations quantitatively comparable.
Dye-exclusion assays provide a different readout by separating cells that retain viability from those showing damage. Rather than relying on colony development, the assay uses differential dye behavior to classify cells as living or damaged. This is useful when the experimental question centers on cell integrity or survival, especially in host-cell studies.
Culture conditions are central to the interpretation of a plating-based count. The selected medium must be suitable for the organisms being assessed, because colony formation is the event used for enumeration. Serial dilution also matters: it creates samples whose colony numbers can be counted and converted into CFU, enabling meaningful comparisons between conditions.
In infection research, a change in viability count can address several distinct questions: whether a pathogen replicated, whether host cells survived, whether a treatment reduced viable organisms, or whether immune activity caused killing. The same quantitative framework therefore connects microbiological growth measurements with outcomes in host-pathogen and immune-mediated infection models.
Begin with the sample, prepare serial dilutions, and plate those dilutions on suitable culture media. After colonies form, count them and convert the count to CFU for the original sample. The resulting value can then be compared across experimental conditions to evaluate survival, growth, or treatment effects.
They provide a common quantitative outcome for samples exposed to different treatments, infection settings, or immune conditions. Comparing the resulting CFU or dye-based viability classifications helps determine whether organisms persisted, host cells remained alive, or an intervention altered survival. This supports direct interpretation of growth and treatment effects.
A reduced count indicates fewer viable cells or microorganisms detected under the assay conditions, whereas an increased count supports greater survival or growth. In infection studies, researchers can use these differences to compare pathogen replication, host-cell survival, antimicrobial effects, or immune-mediated killing while keeping the measurement type consistent across conditions.