Browsing by Subject "Super-resolution microscopy"

Now showing 1 - 4 of 4
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    Author Correction: Super-resolution microscopy compatible fluorescent probes reveal endogenous glucagon-like peptide-1 receptor distribution and dynamics
    (Nature Publishing Group, 2020-10-09) Ast, Julia; Arvaniti, Anastasia; Fine, Nicholas H. F.; Nasteska, Daniela; Ashford, Fiona B.; Stamataki, Zania; Koszegi, Zsombor; Bacon, Andrea; Jones, Ben J.; Lucey, Maria A.; Sasaki, Shugo; Brierley, Daniel I.; Hastoy, Benoit; Tomas, Alejandra; D’Agostino, Giuseppe; Reimann, Frank; Lynn, Francis C.; Reissaus, Christopher A.; Linnemann, Amelia K.; D’Este, Elisa; Calebiro, Davide; Trapp, Stefan; Johnsson, Kai; Podewin, Tom; Broichhagen, Johannes; Hodson, David J.; Pediatrics, School of Medicine
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    Deep learning-driven adaptive optics for single-molecule localization microscopy
    (Springer Nature, 2023) Zhang, Peiyi; Ma, Donghan; Cheng, Xi; Tsai, Andy P.; Tang, Yu; Gao, Hao-Cheng; Fang, Li; Bi, Cheng; Landreth, Gary E.; Chubykin, Alexander A.; Huang, Fang; Anatomy, Cell Biology and Physiology, School of Medicine
    The inhomogeneous refractive indices of biological tissues blur and distort single-molecule emission patterns generating image artifacts and decreasing the achievable resolution of single-molecule localization microscopy (SMLM). Conventional sensorless adaptive optics methods rely on iterative mirror changes and image-quality metrics. However, these metrics result in inconsistent metric responses and thus fundamentally limit their efficacy for aberration correction in tissues. To bypass iterative trial-then-evaluate processes, we developed deep learning-driven adaptive optics for SMLM to allow direct inference of wavefront distortion and near real-time compensation. Our trained deep neural network monitors the individual emission patterns from single-molecule experiments, infers their shared wavefront distortion, feeds the estimates through a dynamic filter and drives a deformable mirror to compensate sample-induced aberrations. We demonstrated that our method simultaneously estimates and compensates 28 wavefront deformation shapes and improves the resolution and fidelity of three-dimensional SMLM through >130-µm-thick brain tissue specimens.
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    Semi-automated single-molecule microscopy screening of fast-dissociating specific antibodies directly from hybridoma cultures
    (Elsevier, 2021-02-02) Miyoshi, Takushi; Zhang, Qianli; Miyake, Takafumi; Watanabe, Shin; Ohnishi, Hiroe; Chen, Jiji; Vishwasrao, Harshad D.; Chakraborty, Oisorjo; Belyantseva, Inna A.; Perrin, Benjamin J.; Shroff, Hari; Friedman, Thomas B.; Omori, Koichi; Watanabe, Naoki; Biology, School of Science
    Fast-dissociating, specific antibodies are single-molecule imaging probes that transiently interact with their targets and are used in biological applications including image reconstruction by integrating exchangeable single-molecule localization (IRIS), a multiplexable super-resolution microscopy technique. Here, we introduce a semi-automated screen based on single-molecule total internal reflection fluorescence (TIRF) microscopy of antibody-antigen binding, which allows for identification of fast-dissociating monoclonal antibodies directly from thousands of hybridoma cultures. We develop monoclonal antibodies against three epitope tags (FLAG-tag, S-tag, and V5-tag) and two F-actin crosslinking proteins (plastin and espin). Specific antibodies show fast dissociation with half-lives ranging from 0.98 to 2.2 s. Unexpectedly, fast-dissociating yet specific antibodies are not so rare. A combination of fluorescently labeled Fab probes synthesized from these antibodies and light-sheet microscopy, such as dual-view inverted selective plane illumination microscopy (diSPIM), reveal rapid turnover of espin within long-lived F-actin cores of inner-ear sensory hair cell stereocilia, demonstrating that fast-dissociating specific antibodies can identify novel biological phenomena.
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    Super-resolution microscopy compatible fluorescent probes reveal endogenous glucagon-like peptide-1 receptor distribution and dynamics
    (Nature Research, 2020-01-24) Ast, Julia; Arvaniti, Anastasia; Fine, Nicholas H. F.; Nasteska, Daniela; Ashford, Fiona B.; Stamataki, Zania; Zania, Zsombor; Bacon, Andrea; Jones, Ben J.; Lucey, Maria A.; Sasaki, Shugo; Brierley, Daniel I.; Hastoy, Benoit; Tomas, Alejandra; D’Agostino, Giuseppe; Reimann, Frank; Lynn, Francis C.; Reissaus, Christopher A.; Linnemann, Amelia K.; D’Este, Elisa; Calebiro, Davide; Trapp, Stefan; Johnsson, Kai; Podewin, Tom; Broichhagen, Johannes; Hodson, David J.; Pediatrics, School of Medicine
    The glucagon-like peptide-1 receptor (GLP1R) is a class B G protein-coupled receptor (GPCR) involved in metabolism. Presently, its visualization is limited to genetic manipulation, antibody detection or the use of probes that stimulate receptor activation. Herein, we present LUXendin645, a far-red fluorescent GLP1R antagonistic peptide label. LUXendin645 produces intense and specific membrane labeling throughout live and fixed tissue. GLP1R signaling can additionally be evoked when the receptor is allosterically modulated in the presence of LUXendin645. Using LUXendin645 and LUXendin651, we describe islet, brain and hESC-derived β-like cell GLP1R expression patterns, reveal higher-order GLP1R organization including membrane nanodomains, and track single receptor subpopulations. We furthermore show that the LUXendin backbone can be optimized for intravital two-photon imaging by installing a red fluorophore. Thus, our super-resolution compatible labeling probes allow visualization of endogenous GLP1R, and provide insight into class B GPCR distribution and dynamics both in vitro and in vivo.