Friday, April 4, 2025
4/4/2025
DNA nanotechnology and synthetic biology for AI-supported detection and precision therapeutics - DNA nanotechnology and synthetic biology for AI-supported detection and precision therapeutics Project Summary: Overview and Goals: In this MIRA application, we propose to develop a transdisciplinary research program centered around AI-supported biosensing and precision therapeutics using DNA nanotechnology and synthetic biology. My lab at the State University of New York, University at Albany (UAlbany) is a bioanalytical and biophysical chemistry lab focused on technology development. During my independent career, my lab has integrated chemistry, nanotechnology, biology, and advanced computational methodologies for biomedical investigations, i.e., (1) Highly sensitive point-of-care detection of whole and/or fragmented genomes, (2) DNA nano-receptors for AI-enabled biomarker-free detection, (3) Controllable RNA, and small molecule nano- therapeutics. In this MIRA proposal, we propose to build upon the expertise and discoveries accumulated throughout my career at UAlbany to develop a robust research program. Research Track Ia. Synthetic biology cascade reaction for paper-based pathogen detection. We propose to develop a synthetic biology cascade reaction using an isothermal amplification reaction, CRISPR-Cas12a, a toehold RNA switch, and in vitro translation. In this direction, we will employ the proposed cascade reaction to detect a pathogen of interest through a color change on a paper substrate. To demonstrate our technology against various pathogens (bacteria and viruses) and genomes (RNA and DNA), we will use circular double- stranded DNA genomes from Salmonella and wild-type Escherichia coli and single-stranded RNA genomes from West Nile, Zika, and Dengue viruses as model systems. Because there is more than one amplification step in the proposed cascade reaction, the sensitivity is greater than that of conventional single-step amplification reactions. The specificity is enhanced due to several checkpoints in the cascade reaction. The entire reaction is complete under 6-hrs, making it highly useful for point-of-care detection of low-copy pathogens. Research Track Ib. DL-assisted image analysis and mobile-app-driven data transmission. The visual data obtained in Part Ia will be analyzed through deep-learning (DL) assisted image analysis in collaboration with 'AI in Complex Systems Lab' at UAlbany. A mobile app will be developed to capture data images and analyze them through a DL engine in a cloud database with wireless transmission capabilities. This step will facilitate the translation of our findings into practical use for public health. Research Track II. ML-supported DNA nano-receptor array technology for biomarker-free analysis. My lab has been investigating the interactions between two-dimensional nanoparticles and single-stranded DNAs through theoretical and experimental studies. Using the insightful knowledge learned through these studies, we have formulated DNA-nanoparticle assemblies (termed ‘DNA nano-receptors’), which are the building blocks of our proposed DNA nano-receptor array platform. The DNA nano-receptor array generates fingerprint fluorescence data when it encounters a biosystem of interest. Enabled by machine learning (ML), the fingerprint data is used to make predictions to identify individual targets. We have demonstrated the detection of specific cell types, RNAs, proteins, and even complex mixtures (i.e., adulterants in fruit juices) using this platform without requiring a specific biomarker. In this MIRA application, we will advance our technological platform beyond its initial phase and challenge it against complex systems such as antibiotic resistance in bacteria, pathogen contamination in consumable products, and subtypes in breast cancer cell lines. This innovative direction in our efforts will result in a simple and bias-free detection setup that utilizes predictions/decisions made by ML. Research Track III. Genome-triggered encapsulated payload release from DNA hydrogels. In this track, we
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