Since near-infrared (NIR) light penetrates much farther into biological tissues than visible light, NIR fluorescence microscopy allows noninvasive imaging deep into tissues and even whole organisms. However, deep tissue imaging is currently hindered by a lack of small, bright, non-toxic biolabels that emit NIR light. This project will develop brightly fluorescent NIR biolabels by harnessing a class of promising tunable nanomaterials called DNA-templated silver clusters. Silver-cluster design and discovery will be carried out with novel machine-learning algorithms that learn from experimental materials and inform design. The optimized NIR biolabels will be employed to study endocrine hormones central to metabolic and cardiovascular disease and will also be broadly applicable for biomedical research in other areas, such as tumor formation and metastasis. Undergraduate and graduate student researchers participating in this project will receive multidisciplinary training at the unique intersection of biophotonics, nanomaterials, and data science, and research opportunities for undergraduates will focus on California community college students and transfer students.

In the second near-infrared window (NIR-II: 1,000-1,700 nm), biological tissues are transparent up to several centimeters depth, making this spectral window ideal for deep tissue imaging. However, most NIR-II fluorophores suffer from low fluorescence brightness, toxicity, or large physical size. This project investigates promising yet underexplored fluorescent DNA-templated silver clusters (Ag-DNAs) to develop small, stable, and modular NIR-II biolabels with broad applicability for deep tissue imaging. Ag-DNAs are composed of 10-30 silver atoms stabilized by short DNA oligonucleotides, with 500-1000 nm fluorescence colors selected by the DNA sequence. High throughput experimentation and custom multi-objective machine learning models will be developed to significantly extend the color palette of Ag-DNAs into the NIR-II and optimize Ag-DNAs as stable, biocompatible fluorophores. As a proof-of-principle, designed NIR-II-Ag-DNAs will be chemically attached to endocrine hormone proteins to track metabolic hormones in vivo. This project significantly advances the scientific framework for engineering metal clusters as novel fluorophores and, more broadly, for data-driven design of biopolymer-based biophotonic materials.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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University of California Irvine
United States
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