Yirui Zhang*, Kai Chang, Babatunde Ogunlade, Liam Herndon, Loza F. Tadesse, Amanda R. Kirane* and Jennifer A. Dionne*,
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引用次数: 0
Abstract
Raman spectroscopy has made significant progress in biosensing and clinical research. Here, we describe how surface-enhanced Raman spectroscopy (SERS) assisted with machine learning (ML) can expand its capabilities to enable interpretable insights into the transcriptome, proteome, and metabolome at the single-cell level. We first review how advances in nanophotonics–including plasmonics, metamaterials, and metasurfaces–enhance Raman scattering for rapid, strong label-free spectroscopy. We then discuss ML approaches for precise and interpretable spectral analysis, including neural networks, perturbation and gradient algorithms, and transfer learning. We provide illustrative examples of single-cell Raman phenotyping using nanophotonics and ML, including bacterial antibiotic susceptibility predictions, stem cell expression profiles, cancer diagnostics, and immunotherapy efficacy and toxicity predictions. Lastly, we discuss exciting prospects for the future of single-cell Raman spectroscopy, including Raman instrumentation, self-driving laboratories, Raman data banks, and machine learning for uncovering biological insights.
拉曼光谱在生物传感和临床研究方面取得了重大进展。在此,我们将介绍表面增强拉曼光谱(SERS)如何在机器学习(ML)的辅助下扩展其功能,从而在单细胞水平上对转录组、蛋白质组和代谢组进行可解释的深入研究。我们首先回顾了纳米光子学的进步--包括等离子体、超材料和超表面--是如何增强拉曼散射以实现快速、强大的无标记光谱学的。然后,我们讨论了用于精确和可解释光谱分析的 ML 方法,包括神经网络、扰动和梯度算法以及迁移学习。我们提供了利用纳米光子学和 ML 进行单细胞拉曼表型分析的示例,包括细菌抗生素敏感性预测、干细胞表达谱、癌症诊断以及免疫疗法疗效和毒性预测。最后,我们讨论了单细胞拉曼光谱学令人兴奋的未来前景,包括拉曼仪器、自动驾驶实验室、拉曼数据库以及用于揭示生物学见解的机器学习。
期刊介绍:
ACS Nano, published monthly, serves as an international forum for comprehensive articles on nanoscience and nanotechnology research at the intersections of chemistry, biology, materials science, physics, and engineering. The journal fosters communication among scientists in these communities, facilitating collaboration, new research opportunities, and advancements through discoveries. ACS Nano covers synthesis, assembly, characterization, theory, and simulation of nanostructures, nanobiotechnology, nanofabrication, methods and tools for nanoscience and nanotechnology, and self- and directed-assembly. Alongside original research articles, it offers thorough reviews, perspectives on cutting-edge research, and discussions envisioning the future of nanoscience and nanotechnology.