# Impact of antibacterial therapeutic agents on biofilm-tissue interactions in a 3D implant-tissue-oral-bacterial-biofilm model

**Authors:** Carina Mikolai, Kathrin Wöll, Muhammad Imran Rahim, Andreas Winkel, Christine S. Falk, Meike Stiesch

PMC · DOI: 10.1038/s41598-025-03855-2 · Scientific Reports · 2025-05-30

## TL;DR

This study uses a 3D model to test how antibacterial agents affect biofilm-tissue interactions around dental implants, showing their impact on bacterial viability and inflammation.

## Contribution

The study validates a 3D model for evaluating antibacterial efficacy and inflammation in peri-implant biofilm-tissue interactions.

## Key findings

- Antibacterial agents reduced bacterial viability but did not affect biofilm volume.
- All agents preserved epithelial integrity, while untreated biofilms caused epithelial damage.
- Different agents modulated pro-inflammatory responses by affecting specific cytokine levels.

## Abstract

Bacterial biofilms on dental implants can lead to peri-implant infections and demonstrate a remarkable ability to evade host immunity and resist antibiotics. Advanced in vitro models, such as the three-dimensional implant-tissue-oral-bacterial-biofilm model (INTERbACT), are essential to evaluate antibiofilm efficacy. The INTERbACT model, effectively reproduces the complex triangular interactions between an organotypic oral mucosa, an integrated implant and an oral multispecies biofilms, in the peri-implant situation. Here, we investigated the effect of antibacterial agents (chlorhexidine, amoxicillin, ciprofloxacin, doxycycline, and metronidazole) on biofilm-tissue interactions in the INTERbACT model. While the antibacterial interventions had no effect on biofilm volume, all agents decreased the proportion of viable bacteria, underscoring their effect on bacterial viability despite biofilm resilience. Biofilm exposure to untreated tissues caused epithelial damage, whereas all antibacterial agents preserved epithelial integrity. However, the modulation of pro-inflammatory response differed between the various agents. All antibacterial treatments reduced hBD-2 and TIMP-1 levels. While doxycycline decreased IL-1β and CCL20, chlorhexidine lowered TNF-α level. In conclusion, the INTERbACT model allowed the successful assessment of antibacterial efficacy, elucidation of biofilm resistance and characterization of inflammation during peri-implant tissue-biofilm interactions. This validation highlights the model’s potential as a platform for developing and evaluating new therapeutic strategies for peri-implant diseases.

## Linked entities

- **Chemicals:** chlorhexidine (PubChem CID 9552079), amoxicillin (PubChem CID 33613), ciprofloxacin (PubChem CID 2764), doxycycline (PubChem CID 54671203), metronidazole (PubChem CID 4173), hBD-2 (PubChem CID 163297647)

## Full-text entities

- **Genes:** DEFB4A (defensin beta 4A) [NCBI Gene 1673] {aka BD-2, DEFB-2, DEFB102, DEFB2, DEFB4, HBD-2}, TIMP1 (TIMP metallopeptidase inhibitor 1) [NCBI Gene 7076] {aka CLGI, EPA, EPO, HCI, TIMP, TIMP-1}, CCL20 (C-C motif chemokine ligand 20) [NCBI Gene 6364] {aka CKb4, Exodus, LARC, MIP-3-alpha, MIP-3a, MIP3A}, IL1A (interleukin 1 alpha) [NCBI Gene 3552] {aka IL-1 alpha, IL-1A, IL1, IL1-ALPHA, IL1F1}, TNF (tumor necrosis factor) [NCBI Gene 7124] {aka DIF, IMD127, TNF-alpha, TNFA, TNFSF2, TNLG1F}
- **Diseases:** peri (MESH:D057873), inflammation (MESH:D007249), infections (MESH:D007239)
- **Chemicals:** amoxicillin (MESH:D000658), doxycycline (MESH:D004318), chlorhexidine (MESH:D002710), metronidazole (MESH:D008795), ciprofloxacin (MESH:D002939)

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12125177/full.md

## References

7 references — full list in the complete paper: https://tomesphere.com/paper/PMC12125177/full.md

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Source: https://tomesphere.com/paper/PMC12125177