Don’t you love it when something works the first time? If you’re a scientific researcher, you know that first-time success, unfortunately, doesn’t happen all the time. A great example is when using antibiotics and cell selection agents.

Antibiotics and cell selection agents are critical cell culture reagents. While following existing protocols often allows you to use antibiotics in cell culture right away, sometimes things don’t work how you expected, and additional troubleshooting is needed to optimize your experiment.  

Some of the ways to troubleshoot antibiotic use in cell culture are to ensure you’re using the correct concentration of properly prepared antibiotics. Rule out contamination and check for side effects. If using multiple antibiotics, evaluate if there is an interaction between them.

This article covers ways to help troubleshoot antibiotic use in cell culture in case it didn’t work on your first, or second, or third … try.

 

In this article:

Untransformed or contaminating cells are still growing

Antibiotic concentration

Antibiotic interactions

Contamination

Improper preparation or storage of antibiotic stock solutions

Transformed cells aren’t growing

Slow growth or strange results

References

 

To help troubleshoot where the breakdown with antibiotic use may be occurring, let’s first discuss some of the observations you may be seeing. The most common signs pointing towards antibiotic issues are:

• Cells are growing that shouldn’t be (untransformed or contaminating cells)
• Cells that should be growing aren’t (transformed cells)
• Slow growth or strange results

Untransformed or contaminating cells are still growing

If you have cells that shouldn’t be growing, such as untransformed or contaminating cells, then there are a few issues that you’ll want to consider troubleshooting:

·         Antibiotic concentration

·         Antibiotic interaction

·         Contamination

·         Improper preparation or storage of antibiotic stock solutions

Antibiotic concentration

Using the proper concentration of antibiotics is really important. If the concentration is too dilute, then the antibiotics will be ineffective at killing untransformed and contaminating cells.

Different antibiotics are used at different concentrations. For example, different concentrations of puromycin, blasticidin, and hygromycin are used with HEK 293T cells (Table 1).

 

Table 1. Suggested concentration for cell selection agents (VectorBuilder, 2026).

Selection Agent	Cell line	Recommended concentration
Puromycin	293T	1-2 ug/mL
Blasticidin	293T	5-15 ug/mL
Hygromycin	293T	100-200 ug/mL

 

What is less appreciated is that even for a single antibiotic, its potency will vary between different cell lines (Delrue et al, 2018). So, let’s suppose you’re working with blasticidin. If you’re using HEK 293T cells, it would be reasonable to try a concentration recommended in Table 1 and see how your experiment goes.

If you’re instead working with a different cell line, without a recommended concentration, then you will definitely want to run a kill curve to establish the ideal working concentration for blasticidin with your cell line of interest.

Here’s where the troubleshooting comes in. Let’s say you’re using a recommended concentration of antibiotic with your cell line, and the experiment isn’t working quite right. If you have too many untransformed cells growing, that may indicate you’re using too little antibiotic (Table 2).

 

Table 2. Troubleshooting antibiotic concentration.

Observation	Antibiotic concentration is:
Untransformed and contaminating cells are growing rampantly	Too dilute
Transformed cells survive, untransformed and contaminating cells die	Just right
Transformed cells die or have very slow growth	Too concentrated

 

While it’s reasonable to start with recommended concentrations, if you’re seeing untransformed cells proliferate then you’ll want to run a kill curve to determine the ideal antibiotic concentration for your experimental setup.

Antibiotic interactions

There are certain experimental setups, in both mammalian and bacterial cell culture, that call for the use of multiple antibiotics. Typically, you will want to adjust the concentration of each antibiotic when using more than one. But how much you adjust their concentration will depend on if and how the antibiotics are influencing each other’s potency.

If you’re using multiple antibiotics in your experimental setup, then one reason untransformed cells could be growing is because there is an antagonistic interaction between the antibiotics. To explain what that means, let’s go over the different types of interactions that combined antibiotics can have.

Antibiotics that combine as you would expect – that is, they neither increase nor decrease each other’s potency – are considered additive. When an interaction is additive, you will usually want to use about half of the concentration of what you would use them at as single agents to account for using both.

If antibiotics have a synergistic interaction, then this means that they are more potent at killing cells together than alone as individual agents. In this case you can reduce the concentration of antibiotics you’re using, which may help avoid any complicating side effects.

Lastly, if antibiotics are antagonistic, then they will be less potent at killing cells in combination compared to when they’re used as single agents. So, you’ll need to increase the concentration of antibiotics.

If untransformed cells are growing in your setup, then an antagonistic interaction between antibiotics may be the cause.

How antibiotics interact is, cell-type specific (Brochado et al, 2018). What this means is that a pair of antibiotics could be additive in one type of cell, synergistic in another type of cell, and antagonistic in a third cell type.

If you’re using multiple antibiotics for your experiment, and seeing unusual results, then it is probably worth determining if there is an interaction between the antibiotics you’re using in that specific cell type.

By the way, antibiotic interactions are analyzed by running a “checkerboard” assay. Check out this article if you want to learn about this assay and how it is used to determine additive, synergistic, and antagonistic relationships between antibiotics (Figure 1).

Figure 1. Using a checkerboard assay to assess if two antibiotics are additive (left), synergistic (middle), or antagonistic (right).

 

Contamination

So far, we’ve been focusing on untransformed cells. But another form of cells that shouldn’t be growing in your culture are contaminating cells. These are commonly bacteria, yeast, and other microorganisms sourced from the local environment (your skin, hair, clothes, lab coat, lab surfaces, etc.) that, if unchecked, can thrive in your culture.

Contamination is prevalent in cell culture, with the most troublesome contaminant being Mycoplasma. These unwelcome and hard-to-spot invaders can complicate biological readings, influence the cells that you’re trying to study, and provide a false readout for what you’re trying to look at.

If you find that your cells are contaminated and you’re working with a routine cell line that you have plenty more uncontaminated aliquots of, then it is often the cleanest solution (pun intended) to responsibly discard your current culture and start fresh with a new one.

However, if you’re working with a rare, expensive, or tough-to-source cell line, then you may be properly motivated to try to save your contaminated culture.

Not all antibiotics work against Mycoplasma. Those that target the cell wall, such as ampicillin, carbenicillin, and vancomycin, are ineffective against Mycoplasma which lack this exterior barrier. Other antibiotics like gentamicin and kanamycin can have activity against Mycoplasma, although susceptibility varies and effective concentrations may exceed those typically used in cell culture.

Do your best to avoid contamination by using proper aseptic technique and testing early and often for Mycoplasma. And if you’re seeing unusual results in your experiments, you may want to test for contamination again. 

 

Improper preparation or storage of antibiotic stock solutions

Proper preparation and storage of antibiotic stock solutions and aliquots is really simple. However, doing these steps wrong is a surprisingly common mistake for cell culture and related experiments.

Some of the frequent ways this step gets messed up include:

1. Miscalculating the concentration
2. Using the wrong solvent
3. Not filter sterilizing the antibiotic stock solution
4. Storing the solution at room temperature or 4 °C for too long
5. Adding antibiotics to the growth media while it’s still hot.

Note that only water-based antibiotic stock solutions necessitate filter sterilization. Contaminants won’t grow in organic solvents such as ethanol or DMSO, so no filtering is necessary for stocks solubilized with these solvents. 

If you’re unsure if your antibiotics are still good, then the easiest way to check is to test them. By making sure that your stock is killing sensitive cells, and not killing resistant cells, you can be confident that your stock solutions are working as expected.

 

Transformed cells aren’t growing

This scenario is basically the opposite of what we just described, and you will want to look at some of the same parameters, but just from the other side.

Did you use too high of a concentration of antibiotics? Running a kill curve with your cells of interest would help you determine that. Remember, one source of too concentrated antibiotics could be an improperly calculated stock solution.

If using multiple antibiotics, do they have a synergistic interaction? The checkerboard assay would reveal if this is your issue (Figure 1).

These are the first things to try if you’re observing no cell growth in your culture. Additionally, though this isn’t really antibiotic related, you would want to make sure that the growth issue isn’t inherent to the cells that you’re using.

 

Slow growth or strange results

The previous two observations are pretty obvious to spot. This last one is a bit more subtle. Your desired cells are growing, and undesired cells are not. It’s just that you detect something is a little off. For example, your cells are growing too slowly, or you’re not getting the same results you used to get with this cell line. These observations may indicate that the antibiotics themselves are causing side effects.

In cell culture we’re using antibiotics to select for the cells of interest, while killing (or stalling the growth of) untransformed and contaminating cells. However, antibiotics can cause side effects in the surviving cells of interest, such as by changing their gene expression, metabolism, and differentiation (Table 3).

 

Table 3. Examples of cell culture side effects caused by antibiotics

Side effect	References
Changes in gene expression	Ryu et al, 2017
Changes in metabolism	Elliot and Jiang, 2019
Defective differentiation	Cohen et al, 2006; Nygaard et al, 2015; Varghese et al, 2017

 

Given the extensive side effects that antibiotics can have on mammalian cell culture, it is important to have a control when you’re assaying cell cultures to make sure that the signal that you’re observing is not just a cellular stress response to antibiotic exposure. See this article for more details about these controls and why they’re critical for proper interpretation of your experimental results. 

Antibiotics are not always required in mammalian cell culture, and given their side effects it is often beneficial to remove them before your assay or to avoid them altogether. It’s important to know when to skip antibiotics and only use them if they’re really necessary for your particular experiment.

If antibiotics are necessary for your experiment, then minimizing the side effects is another important reason for optimizing antibiotic concentration in your experimental setup. You could run an experiment that is similar to a kill curve where you’re titrating antibiotic concentration. But this time instead of reading out the viability of resistant cells, you would be measuring any changes on the phenotype that you’re interested in, such as gene expression, metabolism, or differentiation. Then you can pick the maximum concentration of antibiotics that doesn’t have an impact on that experimental readout.

Another reason for strange results or slow growth is contamination, which we discussed previously in this article. Check your culture to rule out contamination being the culprit that might be influencing your cells of interest and causing experimental errors. 

 

Troubleshooting is a core part of our experience as researchers, and cell culture work and antibiotics are no exception. Using high-quality antibiotics is a great way to minimize the amount of time you spend optimizing your cell culture work. Follow these steps to minimize the amount of troubleshooting you’re doing, and maximizing your time discovering new science!

 

References

Brochado, A. R., Telzerow, A., Bobonis, J., Banzhaf, M., Mateus, A., Selkrig, J., Huth, E., Bassler, S., Zamarreño Beas, J., Zietek, M., Ng, N., Foerster, S., Ezraty, B., Py, B., Barras, F., Savitski, M. M., Bork, P., Göttig, S., & Typas, A. (2018). Species-specific activity of antibacterial drug combinations. Nature, 559(7713), 259–263. https://doi.org/10.1038/s41586-018-0278-9

Delrue, I., Pan, Q., Baczmanska, A. K., Callens, B. W., & Verdoodt, L. L. M. (2018). Determination of the Selection Capacity of Antibiotics for Gene Selection. Biotechnology journal, 13(8), e1700747. https://doi.org/10.1002/biot.201700747

Elliott, R. L., & Jiang, X. P. (2019). The adverse effect of gentamicin on cell metabolism in three cultured mammary cell lines: "Are cell culture data skewed?". PloS one, 14(4), e0214586. https://doi.org/10.1371/journal.pone.0214586

Gautier-Bouchardon A. V. (2018). Antimicrobial Resistance in Mycoplasmaspp. Microbiology spectrum, 6(4), 10.1128/microbiolspec.arba-0030-2018. https://doi.org/10.1128/microbiolspec.ARBA-0030-2018

Nygaard, U. H., Niehues, H., Rikken, G., Rodijk-Olthuis, D., Schalkwijk, J., & van den Bogaard, E. H. (2015). Antibiotics in cell culture: friend or foe? Suppression of keratinocyte growth and differentiation in monolayer cultures and 3D skin models. Experimental dermatology, 24(12), 964–965. https://doi.org/10.1111/exd.12834

Olarerin-George, A. O., & Hogenesch, J. B. (2015). Assessing the prevalence of mycoplasma contamination in cell culture via a survey of NCBI's RNA-seq archive. Nucleic acids research, 43(5), 2535–2542. https://doi.org/10.1093/nar/gkv136

Ryu, A. H., Eckalbar, W. L., Kreimer, A., Yosef, N., & Ahituv, N. (2017). Use antibiotics in cell culture with caution: genome-wide identification of antibiotic-induced changes in gene expression and regulation. Scientific reports, 7(1), 7533. https://doi.org/10.1038/s41598-017-07757-w

UNC Lineberger Comprehensive Cancer Center. (2019, March 1). Mycoplasma. https://unclineberger.org/tissueculture/contaminant/mycoplasmacontam/

Varghese, D. S., Parween, S., Ardah, M. T., Emerald, B. S., & Ansari, S. A. (2017). Effects of Aminoglycoside Antibiotics on Human Embryonic Stem Cell Viability during Differentiation In Vitro. Stem cells international, 2017, 2451927. https://doi.org/10.1155/2017/2451927

VectorBuilder. (2026, May 22). Which drug-selection marker should I use? VectorBuilder Inc. https://en.vectorbuilder.com/resources/faq/optimize-drug-selection-markers.html

 

 

 

 

 

 

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antibiotics bacterial cell culture cell culture Simon Currie

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