@article {68301,
	title = {Molecular cartography: charting the sea of molecular organization in live synapses with nanoscale precision},
	journal = {Biophysical Journal},
	volume = {121},
	year = {2022},
	month = {2022 Feb 01},
	pages = {302a},
	abstract = {<p>Understanding live-cell behavior in part requires high precision mapping of molecular species in 3-D dynamic environments. Approaches like single-molecule localization microscopy (SMLM) offer high promise for challenges posed by molecular cartography. Effectively, the precision of these approaches is dependent on the how many photons / second a fluorescent marker is capable of emitting. For this reason, many SRLM experiments are typically done using fluorescent organic dyes (such as Alexa Fluors) in reducing chemical environments which cause some organic dyes to stochastically cycle through dark states, allowing single-molecule localization (e.g. (d)STORM). The need to couple these dyes to antibodies and the harsh reducing conditions makes their application to live cell work problematic. To overcome these limitations, we made use of modifications to Janelia Fluor-based dyes which make them spontaneously cycle through dark states (blink) under physiological imaging conditions. The dyes are spectrally compatible with photo-activatable fluorescent proteins such as mEos and allow for simultaneous 2-color superresolution microscopy. When conjugated to a HaloTag, these artificial dyes can bind genetically encodable targets in live samples, allowing subsequent measurement in a live-cell environment. To correct for nanoscale chromatic aberrations we developed a new machine-learning based approach with reconstruction errors below achievable localization precisions. We show that these methods allow the reconstruction of live synapse surfaces and a variety of the associated molecular machineries with up to 50 nm accuracy in 3 dimensions.</p>
},
	issn = {00063495},
	doi = {10.1016/j.bpj.2021.11.1246},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0006349521022219},
	author = {Nelson, Andrew J. and Zheng, Qinsi and Lavis, Luke D. and Ryan, Timothy A.}
}
