Zone of Inhibition explained

Overview

Zone of inhibition (ZOI), also known as a zone of clearing or a halo assay, refers to the clear zone surrounding an antimicrobial agent. These ZOIs result from a complete absence of bacteria on, or within a confluent bacterial lawn (red arrow, figure 1a).

The antimicrobial activity of the agent is screened against a test organism which is used to create a confluent lawn of bacterial growth on an agar plate (blue rectangle, figure 1a).

ZOIs can be screened in a number of ways including: 

  • Spot-on-the-lawn assay (Van Reenen et al., 1998) – the ZOI is produced directly by the microorganism within the ZOI (figure 1b)
  • Disk diffusion test (Matuschek et al., 2014) – the ZOI is produced by the slow release of a purified antimicrobial agent from a paper disk soaked in the antimicrobial agent (figure 1a) 

Figure 1: (a) Zones of inhibition resulting from a disk diffusion test whereby a paper disk was soaked in an antimicrobial agent against an Escherichia coli lawn (Reller et al., 2009).
(b) Zone of inhibition resulting from the spot-on-the-lawn method testing lactic acid bacteria against a Salmonella Heidelberg lawn (Sabo et al., 2020).

What are Zones of Inhibition used for?

There are many applications of ZOI, all of which aim to evaluate the effectiveness of antimicrobials.  

In clinical microbiology, ZOI assays are used by scientists to test the effectiveness of antibiotics in treating bacterial infections, while also allowing them to monitor the development of antibiotic resistance (Reller et al., 2009). 

  • Antimicrobial Susceptibility testing (AST) – can be used to deduce if the confluent bacterial lawn is susceptible to a particular antimicrobial (Matuschek et al., 2014). If susceptible, then zones of inhibition will form due to the absence of the confluent bacterial lawn (Figure 2a, gentamicin).  Partial zones may also occur whereby some of the confluent lawn is absent but not fully (Figure 2a, 2%/5% acetic acid). 
  • Minimum inhibitory concentration (MIC) – ZOI can be used to determine the lowest concentration of an antibiotic required to inhibit the growth of bacteria (also referred to as a breakpoint). The ZOIs must be clear and not partial zones to determine the MIC (Reller et al., 2009).

Figure 1: (a) Antimicrobial Susceptibility testing (AST) of varying acetic acid concentrations and gentamicin against a confluent lawn of Escherichia coli (Kaur Monga et al.,1970). (b) Minimum inhibitory concentration (MIC) tests of vancomycin, daptomycin, and linezolid against Staphylococcus aureus using the Etest gradient diffusion method (Reller et al., 2009).

As bacteria become increasingly resistant to the current generation of antimicrobials, the need for new antimicrobial agents is becoming more urgent. In drug discovery, ZOI is a vital tool that helps scientists discover and create these novel antimicrobial agents. Zone of inhibition assays can help scientists screen the antimicrobial activity of natural products (essential oils for example) or antimicrobial-producing microorganisms through a variety of methods (Rossiter et al., 2017), (Balouiri et al., 2016).

Why antimicrobial resistance is a global concern

The prevalence of antibiotic resistance is growing globally. It is estimated that in 2019 almost 5 million deaths were associated with antimicrobial resistance, with respiratory infections being the most troublesome. The peak of antimicrobial resistance was found to occur in western sub-Saharan Africa where every 27·3 deaths per 100 000 were attributed to antimicrobial resistance. Surprisingly, Escherichia coli (E. coli), a common bacteria, was one of the big six leading pathogens that resulted in deaths in 2019 (figure 3) (Murray et al., 2022).

Figure 3: 2019 modelled estimates by country of the percentage of E. coli isolates that are resistant to the third-generation antimicrobial cephalosporin (Murray et al., 2022). If left unaddressed, reports commissioned by the UK government predict antimicrobial resistance could lead to the deaths of 10 million people per year globally by 2050 (O’Neill, 2019).

What causes zones of inhibition? 

ZOIs arise on a confluent lawn of bacteria due to an absence of bacteria; this absence is caused by two different antimicrobial mechanisms. When the growth of the bacterial lawn is prevented by the antimicrobial agent, this is referred to as bacteriostatic activity. In contrast, when the antimicrobial agent has killed the bacterial lawn, this is known as bactericidal activity (Pankey & Sabath, 2004).

Figure 4: Zone of inhibition measurements via various methods. (a) ZOI was measured via callipers. (b) ZOI is measured via a ruler (Petersen & McLaughlin, 2016). (c) ZOI is measured automatically via Singer instruments PIXL software, learn more here.

For reliable measurements and to prevent the formation of overlapping zones, it is recommended that a maximum of 6 disks be used on a 90mm Petri dish and 12 disks on a 150mm Petri dish (Matuschek et al., 2014).

What does a bigger zone of inhibition mean?

ZOI is used to determine if the test organism is susceptible (ZOI produced), intermediate (small ZOI produced), or resistant (no ZOI produced) to the antimicrobial agent (Tenover, 2019).  

  • Larger zones of inhibition – indicate the test organism (confluent bacterial lawn) is susceptible to the antimicrobial tested (Figure 4, blue circle)
  • Small or partial zones of inhibition – suggest the confluent lawn is resistant to the test antimicrobial or a higher concentration of the antimicrobial is required (Figure 4, yellow circle)
  • No ZOI present on the confluent lawn – indicates the test organism is resistant to the antimicrobial tested and the antimicrobial agent does not elicit any antimicrobial activity against the test organism (Figure 4, red circle)

Figure 4: Different sizes of zones of inhibition used to determine the susceptibility of Staphylococcus aureus to ampicillin (Tenover, 2019).

Variables that impact zone size:

  • the confluent lawn may appear resistant until the concentration is increased
  • Central disk/colony size – the size of what is producing the antimicrobial agent impacts the bioavailability of the antimicrobial
    • Colonies spotted onto the agar – larger colony spots will have more cells to produce the antimicrobial and therefore result in larger ZOI than smaller colony spots (Balouiri et al., 2016)
    • Antimicrobial-soaked disks – larger disks allow for more loading of the antimicrobial and therefore distribute more antimicrobial into the confluent lawn (Gould, 1998). 
  • Inoculum size and temperature – both affect the growth rate of the confluent lawn and can therefore impact the ZOI. Temperature can also affect the rate of antimicrobial uptake
  • Time of incubation – longer incubation times allow for higher antimicrobial uptakes and therefore larger ZOIs

To standardise ZOI measurements and to minimise the impact of variables, Bauer et al. established the Kirby–Bauer method in the 1960s (Bauer et al., 1966). Since then, improvements to this standard operating procedure have been established by scientists including the European Union Committee for Antimicrobial Susceptibility Testing (EUCAST). The latest standardised operating procedure (2023) from EUCAST can be found here with clinical breakpoints here.

Many challenges remain in the fight against antimicrobial resistance; however, increasing knowledge and investing in scientific research provides humanity’s best chance at wrangling the beast now, and for future generations.

Sign up to our mailing list

Sign up to our newsletter and a few times a year you’ll get the latest achievements
from our amazing Singer community straight to your inbox.

Sign up

References

1. Andrews, J. M. (2001). Determination of minimum inhibitory concentrations. Journal of Antimicrobial Chemotherapy, 48(SUPPL. 1). https://doi.org/10.1093/jac/48.suppl_1.5

2. Balouiri, M., Sadiki, M., & Ibnsouda, S. K. (2016). Methods for in vitro evaluating antimicrobial activity: A review. In Journal of Pharmaceutical Analysis (Vol. 6, Issue 2). https://doi.org/10.1016/j.jpha.2015.11.005

3. Gould, I. M. (1998). Determinants of response to antibiotic therapy. In Journal of Chemotherapy (Vol. 10, Issue 5). https://doi.org/10.1179/joc.1998.10.5.347

4. Kaur Monga, G., Ghosal, A., Shebitz, D., & Ramanathan, D. (1970). Determination of antibacterial activity in rhizome of plant Aechmea magdalenae (andre) andre ex baker. Journal of Medicinal Herbs and Ethnomedicine, 3. https://doi.org/10.25081/jmhe.2017.v3.3297

5. Matuschek, E., Brown, D. F. J., & Kahlmeter, G. (2014). Development of the EUCAST disk diffusion antimicrobial susceptibility testing method and its implementation in routine microbiology laboratories. Clinical Microbiology and Infection, 20(4). https://doi.org/10.1111/1469-0691.12373

5. Murray, C. J., Ikuta, K. S., Sharara, F., Swetschinski, L., Robles Aguilar, G., Gray, A., Han, C., Bisignano, C., Rao, P., Wool, E., Johnson, S. C., Browne, A. J., Chipeta, M. G., Fell, F., Hackett, S., Haines-Woodhouse, G., Kashef Hamadani, B. H., Kumaran, E. A. P., McManigal, B., … Naghavi, M. (2022). Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. The Lancet, 399(10325). https://doi.org/10.1016/S0140-6736(21)02724-0

6. O’Neill, J. (2019). Tackling drug-resistant infections globally: final report and recommendations: the review on antimicrobial resistance; 2016 [Available from: https://amr-review. org. Publications. Html, May.

7. Pankey, G. A., & Sabath, L. D. (2004). Clinical relevance of bacteriostatic versus bactericidal mechanisms of action in the treatment of gram-positive bacterial infections. In Clinical Infectious Diseases (Vol. 38, Issue 6). https://doi.org/10.1086/381972

8. Petersen, J., & McLaughlin, S. (2016). Laboratory Exercises in Microbiology: Discovering the Unseen World through Hands-On Investigation. CUNY Academic Works, October 2016.

9. Reller, B. L., Weinstein, Melvin., Jorgensen, J. H., & Ferraro, M. J. (2009). Antimicrobial susceptibility testing: A review of general principles and contemporary practices. In Clinical Infectious Diseases (Vol. 49, Issue 11). https://doi.org/10.1086/647952

10. Rossiter, S. E., Fletcher, M. H., & Wuest, W. M. (2017). Natural Products as Platforms to Overcome Antibiotic Resistance. In Chemical Reviews (Vol. 117, Issue 19). https://doi.org/10.1021/acs.chemrev.7b00283

11. Sabo, S. da S., Mendes, M. A., Araújo, E. da S., Muradian, L. B. de A., Makiyama, E. N., LeBlanc, J. G., Borelli, P., Fock, R. A., Knöbl, T., & Oliveira, R. P. de S. (2020). Bioprospecting of probiotics with antimicrobial activities against Salmonella Heidelberg and that produce B-complex vitamins as potential supplements in poultry nutrition. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-64038-9

12. Tenover, F. C. (2019). Antimicrobial susceptibility testing. In Encyclopedia of Microbiology. https://doi.org/10.1016/B978-0-12-801238-3.02486-7

13. Van Reenen, C. A., Dicks, L. M. T., & Chikindas, M. L. (1998). Isolation, purification and partial characterization of plantaricin 423, a bacteriocin produced by Lactobacillus plantarum. Journal of Applied Microbiology, 84(6). https://doi.org/10.1046/j.1365-2672.1998.00451.x

© 2024

Back to top