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An All-in-One Sustainable Smartphone Paper Biosensor for Water Toxicity Monitoring Combining Bioluminescence
Faisal Nazir1, Denise Gregucci1, Maria Maddalena Calabretta1
1Department of Chemistry "Giacomo Ciamician", University of Bologna, Via P. Gobetti 85, 40129 Bologna, Italy.
Analytical Chemistry
|August 12, 2025
Summary
This study presents a novel smartphone biosensor for water toxicity monitoring using bioluminescent bacteria. The integrated system, featuring an AI application, provides accurate, user-friendly quantitative results for environmental analysis.
Area of Science:
- Environmental Science
- Biosensor Technology
- Analytical Chemistry
Background:
- Existing biosensors for water toxicity lack integrated analytical and post-analytical steps for laboratory reporting.
- A sustainable, all-in-one paper biosensor is needed for efficient water toxicity monitoring.
Purpose of the Study:
- To develop a novel workflow for smartphone biosensor developers.
- To create a sustainable all-in-one toxicity paper biosensor using bioluminescent bacteria (Aliivibrio fischeri).
- To integrate bacteria immobilization, a calibration curve, and an AI application for quantitative analysis.
Main Methods:
- Implemented a novel procedure for a standard toxicity assay using Aliivibrio fischeri.
- Developed methods for bacteria immobilization and integration of an on-board calibration curve.
- Created a customized artificial intelligence (AI) application to convert smartphone images into quantitative data.
Main Results:
- Achieved a limit of detection of 0.23 ppb for the cyanotoxin microcystin-LR.
- Demonstrated accurate water toxicity analyses using an AI app and on-board calibration curve, regardless of smartphone camera resolution.
- First reported bioluminescence paper biosensor utilizing an AI algorithm for quantitative results via interpolation from an on-board calibration curve.
Conclusions:
- The developed biosensor offers a sustainable, all-in-one solution for water toxicity monitoring.
- The AI-driven approach enables accurate quantitative results from smartphone-captured images.
- This novel biosensor approach has broad potential for onsite analysis, citizen science, and other optical smartphone biosensor applications.
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