期刊
ACS APPLIED MATERIALS & INTERFACES
卷 11, 期 8, 页码 7743-7754出版社
AMER CHEMICAL SOC
DOI: 10.1021/acsami.8b19977
关键词
plasmonics; bioimaging; gold nanostar; surface-enhanced Raman scattering; microRNA
资金
- US Department of Energy Offices of Science [DE-SC0014077]
- National Science Foundation Graduate Research Fellowship [1106401]
- DOE Office of Science [DE-AC02-06CH11357]
- DOE
- MRCAT/EnviroCAT member institutions
Monitoring gene expression within whole plants is critical for many applications ranging from plant biology to agricultural biotechnology and biofuel development; however, no method currently exists for in vivo monitoring of genomic targets in plant systems without requiring sample extraction. Herein, we report a unique multimodal method based on plasmonic nanoprobes capable of in vivo imaging and biosensing of microRNA biotargets within whole plant leaves by integrating three different and complementary techniques: surface-enhanced Raman scattering (SERS), X-ray fluorescence (XRF), and plasmonics-enhanced two-photon luminescence (TPL). The method developed uses plasmonic nanostars, which not only provide large Raman signal enhancement but also allow for localization and quantification by XRF and plasmonics-enhanced TPL, owing to gold content and high two-photon luminescence cross sections. Our method uses inverse molecular sentinel nanoprobes for SERS bioimaging of microRNA within Arabidopsis thaliana leaves to provide a dynamic SERS map of detected microRNA targets while also quantifying nanoprobe concentrations using XRF and TPL. The nanoprobes were observed to occupy the intercellular spaces upon infiltration into the leaf tissues. This report lays the foundation for the use of plasmonic nanoprobes for in vivo functional imaging of nucleic acid biotargets in whole plants, a tool that will revolutionize bioengineering research by allowing the study of these biotargets with previously unmet spatial and temporal resolution, 200 mu m and 30 min, respectively.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据