Abstract
To decipher the molecular mechanisms of biological function, it is critical to map the molecular composition of individual cells or even more importantly tissue samples in the context of their biological environment in situ. Immunofluorescence (IF) provides specific labeling for molecular profiling. However, conventional IF methods have finite multiplexing capabilities due to spectral overlap of the fluorophores. Various sequential imaging methods have been developed to circumvent this spectral limit but are not widely adopted due to the common limitation of requiring multirounds of slow (typically over 2 h at room temperature to overnight at 4 degrees C in practice) immunostaining. We present here a practical and robust method, which we call DNA Exchange Imaging (DEI), for rapid in situ spectrally unlimited multiplexing. This technique overcomes speed restrictions by allowing for single-round immunostaining with DNA-barcoded antibodies, followed by rapid (less than 10 min) buffer exchange of fluorophore-bearing DNA imager strands. The programmability of DEI allows us to apply it to diverse microscopy platforms (with Exchange Confocal, Exchange-SIK Exchange-STED, and Exchange-PAINT demonstrated here) at multiple desired resolution scales (from similar to 300 nm down to sub-20 nm). We optimized and validated the use of DEI in complex biological samples, including primary neuron cultures and tissue sections. These results collectively suggest DNA exchange as a versatile, practical platform for rapid, highly multiplexed in situ imaging, potentially enabling new applications ranging from basic science, to drug discovery, and to clinical pathology.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Physik |
Fakultätsübergreifende Einrichtungen: | Center for NanoScience (CENS) |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 530 Physik
500 Naturwissenschaften und Mathematik > 500 Naturwissenschaften |
ISSN: | 1530-6984 |
Sprache: | Englisch |
Dokumenten ID: | 53528 |
Datum der Veröffentlichung auf Open Access LMU: | 14. Jun. 2018, 09:53 |
Letzte Änderungen: | 04. Nov. 2020, 13:32 |