Hello Everyone,
I’m exploring the feasibility of a mobile application that assists in identifying contamination in microbial cell cultures. The concept involves the following steps:
- Take a droplet from a flask containing the culture.
- Place the droplet on a single-use microscope slide.
- Capture an image of the droplet under a light microscope.
- Upload the image to the app.
The application, using deep learning algorithms, would analyze the shape and color of cells to detect patterns indicating contamination. Users would need to provide specific details such as:
- Buffer conditions
- Type of microorganism being cultured
- Hypothesis regarding potential contaminants
I would appreciate your insights on the following aspects:
- Existing Solutions: Are there already existing tools or applications that execute a similar function? If so, what are their strengths and weaknesses?
- Technical Feasibility: Given your expertise, do you see any technical challenges or limitations that might need special consideration from the biological perspective?
- Specific Biological Markers: What specific biological markers or patterns should we prioritize when identifying contamination in cell cultures?
- Practical Utility: How beneficial do you think such an application would be for researchers in the greater biological community in day-to-day lab activities?
Thank you very much for your valuable feedback and time!
I think a lot of cell biologists could look at their cells under a microscope and immediately tell if their cell culture was contaminated, although they might not be able to identify which type of contamination. Trying to distinguish which type of contamination could be difficult. Personally, I don't think that microbiologists would be interested in the application. There might be more interest from biologists who study non bacterial eukaryotic cell types like HEK293, Hela, cancer cells, and other types of mammalian cells.
Size of prokaryotic cells is about 1 - 5 microns and size of eukaryotic cells is at least 10 microns and larger. On the basis of size at least by eye, it is easy to separate eukaryotic cells from prokaryotic bacterial cells.
Bacterial cells can be groups by size and morphology. They can be spheres, rods, curved rods, etc. and grow in isolate, chains, or clusters. That to some degree tells you if you are looking at Escherichia coli, vibrio cholera, staphylococcus aureus, etc, although false positives are possible because some bacterial cell types have the same morphology and growth pattern.
A lot of mammalian cell culture biologists complain about Mycoplasma contamination because the size of the mycoplasma bacteria is smaller than 1 micron so it can seep through filters and so biologists might be interested in a application that could identify mycoplasma contamination. But cell biologists would probably look under the microscope immediately see the mycoplasma contamination because it is such a problem.
ImageJ is pretty standard for analyzing biological images. It is very powerful and you can write scripts for it, but it is kind of easy, but I don't think it is already automated for tasks like this.
When microbiologists complain about contamination, it is viral contamination of bacteriophages that they are complaining about. Bacteriophages are like nanometers in size so they can't be seen with a microscope but evidence of contamination is detected by lack of microbe cell growth due to lysis and the lysis of bacteria cells I believe you could detect from the images. Maybe microbiologists would be interested in an application that could detect lysed bacteria cells.
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