Automated Colony Counting
Automated Colony Counting - Related Videos
03:55
Counting Colony Forming Units (CFUs): Quantifying Bacteria from Fly Bodies
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2023
Drosophila microbiota impacts the animal's development, immunity and physiology. This video describes a method to quantify bacteria from flies by determining the colony forming units from whole body preparations. The featured protocol demonstrates the technique with flies, reared under gnotobiotic conditions using four bacterial species.
11:01
Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins
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Cited by 90 •
2016
This paper describes the quantification of hemocytometer and migration/invasion micrographs through two new open-source ImageJ plugins Cell Concentration Calculator and migration assay Counter. Furthermore, it describes image acquisition and calibration protocols as well as discusses in detail the input requirements of the plugins.
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...
13:16
Determination of Mammalian Cell Counts, Cell Size and Cell Health Using the Moxi Z Mini Automated Cell Counter
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Cited by 18 •
2012
The Moxi Z miniature automated cell counter is a novel instrument that combines the Coulter Principle with patented thin-film sensor technology and a proprietary software algorithm to perform sizing and counting of a broad size range of particles as well as to determine the overall health of monodisperse mammalian cell cultures. This protocol describes the use of this instrument for counting and assessing the health of cell cultures.
06:44
Keratinocyte Colony Formation Assay: An In Vitro Assay to Assess the Ability of Keratinocytes to Grow into Colonies
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2023
In this video, we perform a clonogenic assay of keratinocytes harvested from adult mice to determine the ability of individual cells to proliferate and form colonies. This keratinocyte harvesting technique is useful for studying other downstream aspects of cutaneous chemical carcinogenesis and tumor promotion.
FAQs
Segmentation thresholds determine which image features the system classifies as colonies rather than agar background. Contrast can separate visibly distinct growth, while color and size criteria help identify colonies with particular visual characteristics. Because these settings influence which features are counted, consistent analysis conditions are important when comparing microbial growth across treatments or time points.
Manual counting can introduce subjectivity when researchers decide whether faint, small, or visually similar features represent colonies. Digital analysis applies the selected image criteria consistently across plates, reducing variation associated with individual observers. This standardized approach supports more reproducible measurements and strengthens comparisons among experimental groups, repeated assays, and different observation time points.
A colony-forming unit, or CFU, is the reporting format often produced when counted colonies are used to quantify viable organisms. In infection research, CFU measurements help represent the amount of recoverable microbial growth in a sample or assay. The resulting values can support comparisons between treatments, organisms, and experimental time points.
The main distinction is how colony recognition and enumeration are performed. Manual workflows depend on a person visually inspecting and recording colonies, whereas the automated approach analyzes a captured plate image using defined contrast, color, or size criteria. This difference can reduce counting time and observer subjectivity while enabling larger numbers of plates to be processed in a standardized manner.
A typical workflow begins with capturing an image of a culture plate on solid medium. The system then separates colony features from the agar background according to selected visual thresholds, counts the detected colonies, and reports the result, often as colony-forming units. Applying the same image-analysis approach across samples supports consistent enumeration and comparison.
The method is useful for bacterial and fungal growth assays, antimicrobial susceptibility studies, and measurements of viable organisms in clinical or experimental samples. It can also support higher-throughput workflows, allowing researchers to compare microbial growth across treatments or time points more efficiently than manual enumeration alone.
By counting colonies after experimental treatment, researchers can compare the amount of microbial growth associated with different antimicrobial conditions. Reporting results consistently as colony counts or colony-forming units provides a quantitative basis for evaluating treatment-related differences. Automated analysis is particularly relevant when susceptibility experiments include many samples or require comparisons across multiple time points.