What is a bacterial biofilm?

A biofilm is a community of microorganisms associated with an extracellular matrix. Biofilms often develop on surfaces, although suspended microbial aggregates can also display biofilm-like characteristics. The matrix can contain polysaccharides, proteins, extracellular DNA and other materials. Its composition depends on the organisms and their environment. Biofilms develop in many familiar places, including dental plaque, water distribution systems, soil particles, industrial equipment and some infected tissues or medical devices.

Their structure is not uniform. Cells near the outside may have better access to oxygen and nutrients than cells located deeper within the community. These differences create small-scale environmental gradients. Consequently, cells within one biofilm may differ in growth rate, metabolism and response to antimicrobial exposure. The important point is that biofilm formation changes more than the physical arrangement of cells. It can also change their physiology.

What does the minimum inhibitory concentration measure?

The minimum inhibitory concentration is the lowest tested concentration of an antimicrobial agent that prevents visible microbial growth under a specified test procedure. In a conventional broth microdilution assay, an antibiotic is prepared at a series of concentrations. A standardized bacterial inoculum is added, and the test is incubated under controlled conditions. After incubation, the laboratory determines which concentrations inhibit visible growth.

For example, suppose a hypothetical bacterium is tested against an antibiotic at concentrations of 0.25, 0.5, 1, 2, 4 and 8 mg/L. If visible growth occurs at 0.25 and 0.5 mg/L but not at 1 mg/L or above, the observed MIC is 1 mg/L. This value applies to the organism, antimicrobial agent and test conditions used. It should not be interpreted as a fixed property independent of experimental conditions. Importantly, MIC measures growth inhibition, not necessarily bacterial killing.

Some bacteria may remain viable even when visible growth is prevented. A separate bactericidal endpoint, such as the minimum bactericidal concentration (MBC), can assess killing under a specified protocol. The MBC is conventionally based on a defined reduction in viable counts, not proof that every cell is dead. Clinical laboratories interpret MIC values using validated organism–drug-specific criteria, where available. An MIC number alone does not establish whether an antibiotic is clinically suitable.

Why does biofilm growth change antimicrobial susceptibility?

Several biological processes can contribute to reduced antimicrobial susceptibility in biofilms.

Extracellular matrix and antibiotic exposure

The extracellular matrix may influence the movement, binding or local availability of antimicrobial compounds. For example, some matrix components can interact with particular antibiotics, reducing the amount that reaches certain bacterial cells. However, it would be incorrect to describe every biofilm as an impermeable barrier. Some antibiotics penetrate particular biofilms relatively well. Even when penetration occurs, reduced bacterial killing may result from physiological conditions inside the community.

The effect depends on the antibiotic, bacterial species, matrix composition and experimental environment.

Slow growth and metabolic differences

Many antibiotics are especially effective against bacteria carrying out particular growth-related processes. Beta-lactam antibiotics, for example, interfere with bacterial cell-wall synthesis. Cells that are actively growing and dividing may respond differently from cells with greatly reduced growth activity. Biofilms frequently contain regions with limited nutrients or oxygen. Cells in these regions may grow slowly or enter physiological states associated with reduced susceptibility.

This does not mean that every biofilm cell is dormant. A biofilm can contain metabolically active, slowly growing and relatively inactive populations simultaneously.

Persister cells and phenotypic tolerance

Some bacterial populations contain cells that survive antimicrobial exposure without necessarily carrying inherited resistance mechanisms. These cells may display phenotypic tolerance, meaning they survive conditions that kill other members of the population. Persister cells are one example. When favourable conditions return, surviving cells may resume growth. Their descendants can remain susceptible to the same antibiotic in conventional testing.

This distinction matters because antibiotic tolerance and genetically inherited resistance are different biological phenomena.

Genetic resistance can also occur

Biofilms can provide environments in which genetic variation, selection and microbial interactions occur. Resistance genes or mutations may influence antimicrobial responses within a biofilm, just as they can in planktonic populations. Nevertheless, biofilm-associated reduced susceptibility should not automatically be described as genetic antibiotic resistance. A researcher must distinguish inherited resistance from reversible physiological tolerance and other environmental effects.

MIC, BPC, MBIC and MBEC: Different laboratory questions

Although the abbreviations appear similar, they describe different experimental endpoints.

The proposed distinctions above follow Coenye’s 2023 review. In published experiments, BPC, MBIC and MBEC are not uniformly defined or standardized. Some studies use MBIC to describe inhibition of initial biofilm formation, so the method and exact endpoint must be read before comparing results. This is especially important when comparing studies. One laboratory may assess regrowth after treatment, while another may measure culturable cells recovered from a treated biofilm.

Consequently, a reported MBEC should always be interpreted alongside the method used to determine it.

How is MBEC measured?

A widely used experimental approach involves growing biofilms on small pegs attached to a microplate lid. This general arrangement is associated with the Calgary Biofilm Device and related peg-based methods. First, bacteria are allowed to establish biofilms on the pegs. The biofilms are then exposed to different concentrations of an antimicrobial agent. After treatment, the biofilm-associated cells are assessed for survival or regrowth using the specified assay procedure.

In a regrowth-based test, a concentration may meet the study’s MBEC endpoint when no growth is detectable in the recovery medium after the specified treatment and recovery period. However, no detectable growth is not identical to proof that every bacterial cell has been killed. The result depends on the sensitivity of the recovery method and whether injured cells can resume growth under the conditions provided. Some protocols instead determine viable counts or use other biological readouts.

The choice of method therefore affects what the reported MBEC means.

Why is MBEC often higher than MIC?

Consider a hypothetical laboratory experiment involving one bacterial isolate and one antibiotic. The conventional planktonic MIC is measured as 1 mg/L. An established biofilm is then exposed to the same antibiotic, and the experimental MBEC is determined as 64 mg/L using a clearly specified regrowth-based assay. The ratio is:

MBEC ÷ MIC = 64 mg/L ÷ 1 mg/L = 64 (illustrative ratio).

This is a 64-fold ratio between two different experimental endpoints; it is not a standardized clinical susceptibility category. These numbers are illustrative, not results from a published study. The difference may reflect altered metabolism, heterogeneous cell populations, extracellular matrix interactions or other biofilm-associated processes. It does not mean that a clinician should prescribe 64 times the normal antibiotic dose.

Laboratory concentrations cannot be translated directly into treatment recommendations. Drug exposure at the infection site, toxicity, host responses and other clinical factors must be considered. Furthermore, MBEC is not necessarily higher than MIC for every organism–antibiotic combination and every assay. Experimental conditions and endpoint definitions matter.

What does recent research show?

A 2025 systematic review challenges a common assumption

A systematic review by Madduri, Vanommeslaeghe and Coenye examined whether larger or denser biofilms are necessarily less susceptible to antibiotics. The authors screened 328 studies and included 35 that met their criteria for detailed analysis. The results were heterogeneous. Some studies found associations between greater biofilm formation and reduced antimicrobial susceptibility. Others reported weak associations or no convincing relationship.

Differences depended on bacterial species, strains, antibiotics and experimental methods. The review therefore challenged the simple assumption that a larger biofilm must always be more difficult to eradicate. This is important because researchers frequently use crystal violet staining to classify isolates as weak or strong biofilm producers. Such measurements do not necessarily predict the antibiotic susceptibility of an established biofilm.

The review was based on published studies rather than a new randomized clinical experiment. Its conclusions concern the available experimental literature, not a universal clinical prediction rule.

A 2026 study compared MIC and MBEC in Pseudomonas aeruginosa

Güngördü Dalar and Gönüllü reported an experimental study of Pseudomonas aeruginosa isolates obtained from patients with cystic fibrosis. The published abstract reports a comparison of conventional MIC and biofilm-associated MBEC values. Detailed protocol and isolate-level information require examination of the full paper. According to the publisher’s abstract and highlights, MBEC values were higher than corresponding MIC values for the antimicrobials tested in this isolate collection. This finding concerns the tested strains, drugs and laboratory model.

The abstract reports a statistically significant difference; the precise comparison and statistical analysis should be checked in the full paper before quoting a numerical p value. The study provides a specific example of how biofilm-associated susceptibility can differ from conventional planktonic testing. However, the accessible abstract does not establish the exact isolate count or all experimental details needed for a complete independent assessment. Those details must be checked in the full paper before adding numerical isolate-level claims.

The findings also should not be generalized automatically to other bacterial species, infection sites or antibiotic combinations.

Does more biofilm always mean more antibiotic resistance?

No. Biofilm biomass and antimicrobial susceptibility are related but distinct properties. A crystal violet biofilm assay estimates retained, stainable attached biomass under the chosen washing and extraction conditions. This can include bacterial cells, extracellular matrix and material associated with dead cells. It does not directly measure the number of living bacteria. A thicker or more strongly stained biofilm may contain more material, but this does not necessarily establish greater antibiotic tolerance.

For example, two bacterial isolates could produce similar crystal violet measurements but differ in their metabolic activity, matrix composition or antimicrobial susceptibility. Conversely, isolates with different biofilm biomass may have similar susceptibility under a particular assay. The 2025 systematic review demonstrates why these relationships need to be measured rather than assumed. It examined heterogeneous studies, so it does not provide a universal predictive equation for individual isolates.

How should researchers design a biofilm antimicrobial experiment?

A useful experiment begins with a clear biological question. If the aim is to determine whether an antibiotic prevents bacterial growth, conventional MIC testing may be appropriate. If the aim is to determine whether an antibiotic prevents biofilm formation, a biofilm-prevention assay may be more relevant. If the question concerns treatment of an already established biofilm, researchers should use an assay designed to measure survival or eradication after biofilm development.

The experimental design should specify the organism and strain, growth medium, biofilm-development period, surface or model system, antibiotic exposure, treatment duration and recovery conditions. Untreated biofilm controls establish baseline recovery, while sterile controls help detect contamination or background signal. Independent biological replicates, a defined inoculum and a specified detection limit are important for interpreting the results.

Researchers should report the detection limit and explain how they define an endpoint such as MBEC. Where possible, complementary measurements can strengthen the interpretation. For example, crystal violet staining can provide information about retained biomass, while CFU counts or validated viability assays address different aspects of bacterial survival. A reduction in biomass should not be described automatically as bacterial killing.

Similarly, a reduction in CFU does not prove that the extracellular matrix has disappeared. These distinctions are essential when evaluating antibiotics, disinfectants, bacteriophages or experimental antibiofilm interventions.

Can MBEC replace conventional MIC testing?

At present, MBEC should not be treated as a universal replacement for conventional clinical antimicrobial susceptibility testing. MIC-based testing has established standardized procedures and interpretive frameworks for many organism–drug combinations. Biofilm susceptibility testing remains less standardized. Laboratories use different biofilm models, treatment conditions and endpoints. There are also important gaps between in-vitro biofilm measurements and clinical outcomes.

An antibiotic that performs well in a laboratory biofilm model may not necessarily produce the best outcome in a patient. Conversely, laboratory models may not reproduce all the conditions present at an infection site. The 2023 review by Coenye emphasized the need for standardized methods and clinical validation before biofilm susceptibility testing can become a routine basis for treatment selection. For researchers, biofilm testing remains valuable because it can answer biological questions that conventional MIC testing was not designed to address.

Conclusion

MIC and MBEC are not competing measurements of the same biological property. MIC describes growth inhibition under defined conventional test conditions. MBEC addresses the eradication of an established biofilm according to a specified experimental endpoint. The difference between these measurements reflects the importance of bacterial growth state, community structure and environmental conditions. Recent research also shows that biofilm biomass alone is an unreliable universal predictor of antimicrobial susceptibility.

The central laboratory lesson is to choose the assay according to the biological question, report exactly what was measured, and avoid interpreting a single antimicrobial susceptibility value beyond the conditions in which it was obtained.

Related reading

For a broader introduction to bacterial structure, growth and biofilms, see Bacteria: Their Characteristics, Diversity and Roles in Nature.

References

1. Coenye, T. (2023). Biofilm antimicrobial susceptibility testing: Where are we and where could we be going? Clinical Microbiology Reviews, 36(4), e00024-23. https://doi.org/10.1128/cmr.00024-23
2. Güngördü Dalar, Z., & Gönüllü, N. (2026). Biofilm-associated reduced antimicrobial susceptibility in Pseudomonas aeruginosa isolates from cystic fibrosis patients: MIC–MBEC discordance. Diagnostic Microbiology and Infectious Disease, 116(3), Article 117577. https://doi.org/10.1016/j.diagmicrobio.2026.117577
3. Liu, H. Y., Prentice, E. L., & Webber, M. A. (2024). Mechanisms of antimicrobial resistance in biofilms. npj Antimicrobials and Resistance, 2, Article 27. https://doi.org/10.1038/s44259-024-00046-3
4. Macià, M. D., Rojo-Molinero, E., & Oliver, A. (2014). Antimicrobial susceptibility testing in biofilm-growing bacteria. Clinical Microbiology and Infection, 20(10), 981–990. https://doi.org/10.1111/1469-0691.12651
5. Madduri, A., Vanommeslaeghe, L., & Coenye, T. (2025). Is increased biofilm formation associated with decreased antimicrobial susceptibility? A systematic literature review. Microorganisms, 13(10), Article 2292. https://doi.org/10.3390/microorganisms13102292