Combining Microscopy Assays of Bacteria-Surface Interactions To Better Evaluate Antimicrobial Polymer Coatings.
M K L N SikosanaA RulandC WernerLars David RennerPublished in: Applied and environmental microbiology (2022)
Validation of the antimicrobial performance of contact-killing polymer surfaces through the experimental determination of bacterial adhesion or viability, is essential for their targeted development and application. However, there is not yet a consensus on the single most appropriate evaluation method or procedure. Combining and benchmarking previously reported assays could reduce the significant variation and misinterpretation of efficacy data obtained from different methods. In this work, we systematically investigated the response of bacterial cells to antiadhesive and antiseptic polymer coatings by combining (i) bulk solution-based, (ii) thin-film spacer-based, and (iii) direct-contact assays. In addition, we evaluated the studied assays using a five-point scoring framework that highlights key areas for improvement. Our data suggest that combined microscopy assays provide a more comprehensive representation of antimicrobial performance, thereby helping to identify effective types of antibacterial polymer coatings. IMPORTANCE We present and evaluate a combination of methods for validating the efficacy of antimicrobial surfaces. Antimicrobial surfaces/coatings based on contact-killing components can be instrumental to functionalize a wide range of products. However, there is not yet a consensus on the single, most appropriate method to evaluate their performance. By combining three microscopy methods, we were able to discern contact-killing effects at the single-cell level that were not detectable by conventional bulk microbiological analyses. The developed approach is considered advantageous for the future targeted development of robust and sustainable antimicrobial surfaces.
Keyphrases
- high throughput
- staphylococcus aureus
- biofilm formation
- single cell
- high resolution
- optical coherence tomography
- rna seq
- cancer therapy
- electronic health record
- induced apoptosis
- machine learning
- cell proliferation
- pseudomonas aeruginosa
- label free
- escherichia coli
- deep learning
- endoplasmic reticulum stress
- molecularly imprinted