Collaborative Research: New class of near-infrared fluorophores derived from DNA-templated silver clusters for deep tissue imaging

由于近红外（NIR）光比可见光更深入地穿透生物组织，因此NIR荧光显微镜允许深入组织甚至整个生物体的非侵入性成像。然而，深层组织成像目前受到缺乏发射NIR光的小的、明亮的、无毒的生物标记的阻碍。该项目将开发明亮的荧光近红外生物标记，利用一类有前途的可调纳米材料称为DNA模板银簇。银集群的设计和发现将使用新颖的机器学习算法进行，这些算法从实验材料中学习并为设计提供信息。优化的NIR生物标记将用于研究代谢和心血管疾病的内分泌激素，也将广泛适用于其他领域的生物医学研究，如肿瘤形成和转移。参与该项目的本科生和研究生研究人员将在生物光子学、纳米材料和数据科学的独特交叉点接受多学科培训，本科生的研究机会将集中在加州社区大学生和转学生。在第二个近红外窗口（NIR-II：1，000 - 1，700 nm）中，生物组织在几厘米的深度内都是透明的，这使得该光谱窗口成为深层组织成像的理想选择。然而，大多数NIR-II荧光团具有低荧光亮度、毒性或大的物理尺寸。本项目研究有前途但未充分探索的荧光DNA模板银簇（Ag-DNA），以开发小，稳定，模块化的近红外-II生物标记，具有广泛的适用性深组织成像。Ag-DNA由10-30个银原子组成，由短DNA寡核苷酸稳定，具有由DNA序列选择的500-1000 nm荧光颜色。将开发高通量实验和定制的多目标机器学习模型，以显着扩展Ag-DNA的调色板到NIR-II中，并将Ag-DNA优化为稳定的生物相容性荧光团。作为原理验证，设计的NIR-II-Ag-DNA将化学连接到内分泌激素蛋白质上，以跟踪体内代谢激素。该项目显著推进了工程金属簇作为新型荧光团的科学框架，更广泛地说，用于基于生物聚合物的生物光子材料的数据驱动设计。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.