Point-localization superresolution techniques such as photoactivated localization microscopy (PALM) enable the imaging of fluorescent protein chimeras to reveal the organization of genetically-expressed proteins on the nanoscale with a density of molecules high enough to provide structural context. In PALM, serial photoactivation and subsequent bleaching of numerous sparse subsets of photoactivated fluorescent protein molecules is performed. Individual molecules are then localized at near molecular resolution by determining their centers of fluorescent emission via a statistical fit of their point-spread-function. The aggregate position information from all subsets is then assembled into a super-resolution image, in which individual fluorescent molecules are isolated at high molecular densities (up to 10,000 molecules/micron squared). While PALM is a powerful approach for investigating protein organization, tools for quantitative, spatial analysis of PALM datasets are largely missing. We developed a pair-correlation analysis method with PALM (PC-PALM) that enables complex patterns of protein organization across the plasma membrane to be analyzed. The approach uses an algorithm to distinguish a single protein with multiple appearances from clusters of proteins. This enables quantification of different parameters of spatial organization, including the presence of protein clusters, their size, density and abundance in the plasma membrane. Using this method, we demonstrated distinct nanoscale organization of plasma-membrane proteins with different membrane anchoring and lipid partitioning characteristics in COS-7 cells, and showed dramatic changes in glycosylphosphatidylinositol (GPI)-anchored protein arrangement under varying perturbations. Our results revealed that PC-PALM is an effective tool with broad applicability for analysis of protein heterogeneity and function, adaptable to other single-molecule strategies. We developed a new way of localizing fluorescent molecules for superresolution imaging that does not require photoactivatable or photoswitching probes. Called bleaching/blinking assisted localization microscopy (BaLM), the technique relies on the intrinsic bleaching and blinking behaviors characteristic of all commonly used fluorescent probes. Single fluorophores are detected by acquiring a stream of fluorescence images. Fluorophore bleach or blink-off events are then recorded by subtracting from each image of the series the subsequent image. Similarly, blink-on events are detected by subtracting from each frame the previous one. After image subtractions, fluorescence emission signals from single fluorophores are identified and the localizations are determined by fitting the fluorescence intensity distribution with a theoretical Gaussian. We found that BaLM works with all commonly used synthetic fluorescent dyes and genetically expressed fluorescent proteins. We further showed that BaLM can be used in multicolor superresolution experiments, deciphering the molecular distribution of up to four different proteins in a sample. These characteristics indicated that BaLM is a practical and versatile approach for obtaining superresolution images that can either stand alone or be used in conjunction with other superresolution approaches. Receptor-regulated cellular signaling often is mediated by formation of transient, heterogeneous protein complexes of undefined structure. To obtain greater insight into this process, we used single and two-color PALM to study complexes downstream of the T cell antigen receptor (TCR) at the plasma membrane of intact T cells. In resting and activated cells, several TCR associated signaling molecules, including LAT, ZAP-70 and TCRzeta chain were found to reside in nanoscale clusters whose formation depended on protein-protein and protein-lipid interactions. The adaptor SLP-76 localized to the periphery of these clusters. This nanoscale structure depended on polymerized actin and its disruption affected TCR-dependent cell function. We contributed to a new localization microscopy analysis method (called 3B analysis) that is able to greatly improve the resolution of live cell fluorescent images using standard fluorescent proteins and xenon arc lamp illumination. The technique employs Bayesian analysis to improve resolution by modeling the blinking and bleaching behavior of molecules from an entire dataset being generated by a number of fluorophores that may or may not be emitting light at any given time. The high resolution performance of this technique revealed the nanoscale dynamics of podosome formation and dissociation within a live cell with a resolution of 50 nm on a 4-s timescale.

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Lippincott-Schwartz, Jennifer (2015) Profile of Eric Betzig, Stefan Hell, and W. E. Moerner, 2014 Nobel Laureates in Chemistry. Proc Natl Acad Sci U S A 112:2630-2
Shcherbakova, Daria M; Sengupta, Prabuddha; Lippincott-Schwartz, Jennifer et al. (2014) Photocontrollable fluorescent proteins for superresolution imaging. Annu Rev Biophys 43:303-29
Sengupta, Prabuddha; van Engelenburg, Schuyler B; Lippincott-Schwartz, Jennifer (2014) Superresolution imaging of biological systems using photoactivated localization microscopy. Chem Rev 114:3189-202
Lippincott-Schwartz, Jennifer (2014) Foreword. Histochem Cell Biol 142:1-2
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Alivisatos, A Paul; Andrews, Anne M; Boyden, Edward S et al. (2013) Nanotools for neuroscience and brain activity mapping. ACS Nano 7:1850-66
Hu, Ying S; Nan, Xiaolin; Sengupta, Prabuddha et al. (2013) Accelerating 3B single-molecule super-resolution microscopy with cloud computing. Nat Methods 10:96-7
Millis, Bryan A; Burnette, Dylan T; Lippincott-Schwartz, Jennifer et al. (2013) Superresolution imaging with standard fluorescent probes. Curr Protoc Cell Biol 60:Unit 21.8.
Sengupta, Prabuddha; Lippincott-Schwartz, Jennifer (2013) Photohighlighting approaches to access membrane dynamics of the Golgi apparatus. Methods Cell Biol 118:217-34
Sengupta, Prabuddha; Jovanovic-Talisman, Tijana; Lippincott-Schwartz, Jennifer (2013) Quantifying spatial organization in point-localization superresolution images using pair correlation analysis. Nat Protoc 8:345-54

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