A semi-solid in vitro biofilm model for evaluating antimicrobial potency and biofilm-specific activity

Abstract

Biofilms play a critical role in chronic bacterial infections, and new potent antimicrobials are urgently needed to address the escalating problem of antimicrobial resistance to existing therapies. To support the development of such therapeutics, there is a pressing need for biofilm models that better recapitulate the microenvironment of in vivo conditions. Existing in vitro assays, such as the widely used minimum biofilm eradication concentration (MBEC) assay, rely on liquid cultures that poorly reflect the structural and physiological characteristics of tissue-associated biofilms.

To address these limitations, we developed the Modified Crone's Model (MCM), a reproducible, semi-solid biofilm model that embeds bacteria in soft-tissue-like agar-based matrices. We established the MCM as a platform for evaluating the antimicrobial and specific anti-biofilm activity of novel and existing compounds. Biofilms grown in the MCM displayed consistent growth, in vivo-like morphology, and reduced variability compared to liquid-culture systems. Notably, antimicrobial susceptibility rankings in the MCM differed substantially from traditional assays, emphasizing that model-specific conditions can markedly affect the evaluation of antimicrobial potency and should be considered when selecting biofilm test systems.

Using the MCM, we screened a panel of therapeutic agents and identified two unsaturated fatty acids – cis-2-decenoic acid and cis-11-methyl-2-dodecenoic acid – as potent antibiotic potentiators with intrinsic anti-biofilm activity, undetectable in microbroth dilution assays. We further demonstrated the MCM's adaptability by replicating susceptibility profiles in biofilms grown on porcine bone tissue and implant surfaces, with no significant differences from agar-based biofilms.

The MCM offers a simple and reproducible platform for preclinical antimicrobial screening under semi-solid growth conditions that better reflect the spatial and diffusional constraints of biofilm-associated infections.