Ångström-resolution fluorescence microscopy

Abstract

Fluorescence microscopy, with its molecular specificity, is one of the major characterization methods used in the life sciences to understand complex biological systems. Super-resolution approaches1–6 can achieve resolution in cells in the range of 15 to 20 nm, but interactions between individual biomolecules occur at length scales below 10 nm and characterization of intramolecular structure requires Ångström resolution. State-of-the-art super-resolution implementations7–14 have demonstrated spatial resolutions down to 5 nm and localization precisions of 1 nm under certain in vitro conditions. However, such resolutions do not directly translate to experiments in cells, and Ångström resolution has not been demonstrated to date. Here we introdue a DNA-barcoding method, resolution enhancement by sequential imaging (RESI), that improves the resolution of fluorescence microscopy down to the Ångström scale using off-the-shelf fluorescence microscopy hardware and reagents. By sequentially imaging sparse target subsets at moderate spatial resolutions of >15 nm, we demonstrate that single-protein resolution can be achieved for biomolecules in whole intact cells. Furthermore, we experimentally resolve the DNA backbone distance of single bases in DNA origami with Ångström resolution. We use our method in a proof-of-principle demonstration to map the molecular arrangement of the immunotherapy target CD20 in situ in untreated and drug-treated cells, which opens possibilities for assessing the molecular mechanisms of targeted immunotherapy. These observations demonstrate that, by enabling intramolecular imaging under ambient conditions in whole intact cells, RESI closes the gap between super-resolution microscopy and structural biology studies and thus delivers information key to understanding complex biological systems.

Decoding the molecular interplay of endogenous CD20 and Rituximab with fast volumetric nanoscopy

“…For the first demonstration of TDI-DNA-PAINT, we selected a routinely used classical DNA-PAINT imager strand P3 (10 nucleotides) 1 and the speed optimized R4 (7 nt) 2 and labeled them with one or two ATTO Oxa14 dyes. In the remainder of the manuscript, we will refer to the dual-labeled and singlelabeled imagers as Ox2-(P3 or R4) and Ox1-(P3 or R4), respectively.…”

“…Hence, to realize the full potential of sub-nanometer localization precision methods such as MINFLUX 16 or MINSTED 17 , they have to use DNA-PAINT or photoactivatable fluorophores ensuring that two adjacent fluorophores are never present or photoactivated simultaneously. Since in DNA-PAINT, the achievable localization precision does not only scale with the number of detected photons per localization but also with the number of localizations acquired per target it can likewise achieve superior resolution 2 . Unfortunately, such high spatial resolutions come along with extremely long acquisition times impeding large field of view nanometer resolution imaging.…”

“…DNA-based points accumulation for imaging in nanoscale topography (DNA-PAINT) relies on transient binding of a fluorophore-tagged single-stranded short oligonucleotide probe (imager strand) to a complementary oligonucleotide (docking strand) attached at the target of interest 1 . Several key benefits of DNA-PAINT include the possibility to achieve sub-10 nm spatial resolution using a conventional widefield/TIRF microscope 2 , easy multiplexing via sequential imaging of targets of interest with different imager strands (exchange-PAINT) 3 , and resilience to photobleaching of fluorophores as they are constantly replenished by freely diffusing imager strands in solution. Nevertheless, a major issue remains to be the background signal originating from freely diffusing imager probes in solution.…”

Investigating Uncertainties in Single-Molecule Localization Microscopy Using Experimentally Informed Monte Carlo Simulation

“…We note that the MC model may also be used to investigate the uncertainties associated with different imaging or labeling techniques such as using a higher photon budget through DNA-PAINT or similar techniques, or using smaller-sized self-labeling protein tags (e.g., SNAP-Tag). Reducing localization uncertainties from 15 to 5 nm allows sufficient resolution of individual NUP133 and NUP210 proteins but not for NUP93 (Figure S4a–S4f).…”

“…The presence of a few smaller clusters (arrows in Figure 3b and 3d) is attributed to the low-efficiency labeling of NPCs, which has been previously observed. 36 Quantitative We note that the MC model may also be used to investigate the uncertainties associated with different imaging or labeling techniques such as using a higher photon budget through DNA-PAINT 36 or similar techniques, 39 or using smaller-sized self-labeling protein tags 40 We further demonstrated two applications on how the MC framework can help interpret SMLM data: (1) to optimize the parameters used for clustering individual NPCs from SMLM data and (2) to explore the effect of steric hindrance on the preferred labeling angle of the NUP93-and NUP133-primary antibodies.…”