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

由于近红外(NIR)光比可见光更能穿透生物组织，因此近红外荧光显微镜可以实现深入组织甚至整个生物体的非侵入性成像。然而，深层组织成像目前由于缺乏发射近红外光的小、明亮、无毒的生物标记而受到阻碍。该项目将通过利用一种名为DNA模板银团簇的有前途的可调纳米材料来开发明亮的近红外生物标记。银星团的设计和发现将使用从实验材料中学习并为设计提供信息的新型机器学习算法。优化的近红外生物标记将用于研究代谢和心血管疾病的核心内分泌激素，并将广泛应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学院学生和转校生。在第二个近红外窗口(NIR-II：1,000-1,700 nm)，生物组织是透明的，深度可达几厘米，使此光谱窗口成为深层组织成像的理想选择。然而，大多数NIR-II荧光团都存在荧光亮度低、毒性大或物理尺寸大等问题。该项目研究前景看好但未被开发的荧光DNA模板银团簇(Ag-DNA)，以开发小的、稳定的、模块化的NIR-II生物标记，具有广泛的深部组织成像应用。Ag-DNA由10-30个银原子组成，由短DNA寡核苷酸稳定，根据DNA序列选择500-1000 nm的荧光颜色。将开发高通量实验和定制的多目标机器学习模型，以显著将Ag-DNA的调色板扩展到NIR-II中，并将Ag-DNA优化为稳定的、生物兼容的荧光团。作为原理的证明，设计的NIR-II-Ag-DNA将以化学方式连接到内分泌激素蛋白上，以跟踪体内的代谢激素。该项目极大地推进了将金属簇设计为新型荧光团的科学框架，以及更广泛地说，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智力优势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.