A portable micro-nanochannel bio-3D printed liver microtissue biosensor for DON detection

Area of Science:

• Biomedical Engineering
• Biosensor Technology
• Food Safety

Background:

• Mycotoxin contamination, particularly deoxynivalenol (DON), poses a significant threat to food safety and quality.
• Accurate and rapid detection methods for DON are crucial for post-production grain assessment.
• Existing detection methods can be time-consuming or require specialized laboratory equipment.

Purpose of the Study:

• To develop a portable micro-nanochannel biosensor utilizing 3D-printed liver microtissues for sensitive deoxynivalenol (DON) detection.
• To integrate bio-3D printing technology with electrochemical sensing for mycotoxin analysis.
• To provide a rapid and convenient tool for assessing mycotoxin hazards in grain.

Main Methods:

• Fabrication of a biosensor by modifying a screen-printed carbon electrode (SPCE) with nanoporous anodic aluminum oxide (AAO), gold nanoparticles (AuNPs), and cytochrome C oxidase (COx).
• Development of bio-ink using gelatin methacrylate hydrogel and hepatocellular carcinoma cells for 3D printing liver microtissues.
• Immobilization of 3D-printed liver microtissues onto the modified electrode to create the biosensor.
• Electrochemical detection of DON using cyclic voltammetry (CV).

Main Results:

• The developed biosensor demonstrated a positive correlation between peak current and DON concentration.
• A linear detection range of 2–40 μg/mL was established with a correlation coefficient R² of 0.99471.
• A low limit of detection (LOD) of 1.229 μg/mL was achieved, indicating high sensitivity.
• Successful construction of a portable micro-nanochannel bio-3D printed liver microtissue biosensor.

Conclusions:

• The study successfully developed a portable biosensor based on 3D-printed liver microtissues for rapid and sensitive DON detection.
• This innovative approach offers a promising tool for on-site mycotoxin hazard detection in grain production.
• The biosensor holds significant potential for predicting and assessing post-production quality changes in grain.