Research Projects

Bacterial infections, especially those from multidrug-resistant organisms, pose a serious global health threat. Diagnostic delays, centralized labs, and empirical antibiotic use worsen antimicrobial resistance (AMR). Culture-based tests are slow and labor-intensive; molecular diagnostics are faster but costly and limited. Bacterial metabolic activities can trigger colorimetric changes with chromogenic substrates, while smartphone and IoT technologies enable decentralized, automated diagnostics. Our group developed a TRL-3 wound dressing that detects infections and provides antibiotic-free protection using E. coli as a model. This proposal aims to advance it to TRL-6 by improving hydrogel stability, expanding detection to 20+ strains with species-level chromogenic indicators (e.g., S. aureus, P. aeruginosa), and validating with clinical specimens. We hypothesize that a chromogenic hydrogel patch with smartphone-enabled, cloud-based analysis can serve as a robust, amplification-free sensor for broad-spectrum detection and point-of-care clinical diagnosis. (I) Specific Aims: • Fabricate a biochemically responsive hydrogel patch with chromogenic agents sensitive to bacterial enzymatic/metabolic activities. • Profile colorimetric responses across 20+ strains, including MDR subspecies, under varied loads and time points to define diagnostic thresholds and kinetics. • Implement an IoT-enabled interface for automated interpretation, resistance recognition, and cloud data management. • Validate using clinical specimens (blood, urine, wound swabs) to assess accuracy, specificity, sensitivity, and usability in POC and low-resource settings. (II) Novelty: Unlike single-target molecular tests, this platform uses broad-spectrum metabolic sensing to detect diverse species and subspecies. Key features: • Amplification-Free, Label-Free Detection: No nucleic acid amplification or antibody tagging, reducing cost and complexity. • Smartphone Integration: Consumer smartphones for hue detection with custom algorithms and cloud analytics. • IoT Connectivity: Automated interpretation with cloud storage and remote access supports scalability and surveillance. • Custom Hydrogel Matrix: Electrospun or structured hydrogels offer high surface area and tunable porosity for rapid analyte interaction. (III) Anticipated Impact: • Rapid Diagnosis: Reduces time-to-result from days to hours for early, targeted treatment. • Decentralized Testing: Easy to use with minimal infrastructure, ideal for rural and low-resource settings. • AMR Surveillance: Remote data collection supports national and global monitoring. • Affordable and Scalable: Low-cost disposable patches with smartphones offer a cost-effective alternative with IoT and AI/ML compatibility. • Clinical Translation: Compact hardware, broad sampling (blood, urine, swabs, saliva), and automated readouts suit commercial translation and regulatory approval. This proposal bridges TRL-3 to TRL-6 by validating technical performance and user operability in clinically relevant settings.