Establishment of a 3D-Printed Tissue-on-a-Chip Model for Live Imaging of Bacterial Infections

Albert Fuglsang-Madsen1,2, Janus Anders Juul Haagensen1,2, Charlotte De Rudder1,2,3

  • 1Department of Clinical Microbiology, Rigshospitalet, Copenhagen, Denmark.

Insights

A new 3D-printed lung-on-a-chip model accurately simulates bacterial infections like Pseudomonas aeruginosa, offering a better way to study respiratory diseases and test new antibiotic treatments.

Area of Science:

  • Biomedical Engineering
  • Infectious Diseases
  • Microfluidics

Background:

  • Bacterial pathogens and antibiotic resistance pose significant global health threats, particularly in lower respiratory tract infections.
  • Existing in vivo models for diseases like cystic fibrosis have limitations in accurately replicating human respiratory infections.
  • Developing advanced models is crucial for understanding host-pathogen interactions and evaluating novel therapies.

Purpose of the Study:

  • To introduce a novel 3D-printed, cytocompatible microfluidic lung-on-a-chip device.
  • To simulate the human lung environment for studying infectious diseases.
  • To overcome limitations of current in vivo models for respiratory infections.

Main Methods:

  • A 3D-printed microfluidic device was developed to create a lung-on-a-chip model.
  • Fully differentiated lung epithelia were colonized with Pseudomonas aeruginosa at an air-liquid interface.
  • Dynamic flow was incorporated to simulate clearance of toxins and bacterial cells, mimicking acute and chronic infections.

Main Results:

  • The device successfully enabled colonization and infection with Pseudomonas aeruginosa.
  • Dynamic flow simulated clearance mechanisms, applicable to both acute and chronic infection models.
  • The platform allowed real-time monitoring of therapeutic interventions and analysis of bacterial load and cytokine secretion.

Conclusions:

  • The developed lung-on-a-chip device shows significant potential for advancing infectious disease research.
  • This model can optimize treatment strategies for bacterial infections.
  • The platform facilitates the development of novel therapeutic approaches against infections.