Filter
Associated Lab
- Aguilera Castrejon Lab (16) Apply Aguilera Castrejon Lab filter
- Ahrens Lab (63) Apply Ahrens Lab filter
- Aso Lab (40) Apply Aso Lab filter
- Baker Lab (38) Apply Baker Lab filter
- Betzig Lab (112) Apply Betzig Lab filter
- Beyene Lab (13) Apply Beyene Lab filter
- Bock Lab (17) Apply Bock Lab filter
- Branson Lab (52) Apply Branson Lab filter
- Card Lab (41) Apply Card Lab filter
- Cardona Lab (63) Apply Cardona Lab filter
- Chklovskii Lab (13) Apply Chklovskii Lab filter
- Clapham Lab (14) Apply Clapham Lab filter
- Cui Lab (19) Apply Cui Lab filter
- Darshan Lab (12) Apply Darshan Lab filter
- Dennis Lab (1) Apply Dennis Lab filter
- Dickson Lab (46) Apply Dickson Lab filter
- Druckmann Lab (25) Apply Druckmann Lab filter
- Dudman Lab (50) Apply Dudman Lab filter
- Eddy/Rivas Lab (30) Apply Eddy/Rivas Lab filter
- Egnor Lab (11) Apply Egnor Lab filter
- Espinosa Medina Lab (19) Apply Espinosa Medina Lab filter
- Feliciano Lab (7) Apply Feliciano Lab filter
- Fetter Lab (41) Apply Fetter Lab filter
- Fitzgerald Lab (29) Apply Fitzgerald Lab filter
- Freeman Lab (15) Apply Freeman Lab filter
- Funke Lab (38) Apply Funke Lab filter
- Gonen Lab (91) Apply Gonen Lab filter
- Grigorieff Lab (62) Apply Grigorieff Lab filter
- Harris Lab (60) Apply Harris Lab filter
- Heberlein Lab (94) Apply Heberlein Lab filter
- Hermundstad Lab (26) Apply Hermundstad Lab filter
- Hess Lab (76) Apply Hess Lab filter
- Ilanges Lab (2) Apply Ilanges Lab filter
- Jayaraman Lab (46) Apply Jayaraman Lab filter
- Ji Lab (33) Apply Ji Lab filter
- Johnson Lab (6) Apply Johnson Lab filter
- Kainmueller Lab (19) Apply Kainmueller Lab filter
- Karpova Lab (14) Apply Karpova Lab filter
- Keleman Lab (13) Apply Keleman Lab filter
- Keller Lab (76) Apply Keller Lab filter
- Koay Lab (18) Apply Koay Lab filter
- Lavis Lab (148) Apply Lavis Lab filter
- Lee (Albert) Lab (34) Apply Lee (Albert) Lab filter
- Leonardo Lab (23) Apply Leonardo Lab filter
- Li Lab (28) Apply Li Lab filter
- Lippincott-Schwartz Lab (167) Apply Lippincott-Schwartz Lab filter
- Liu (Yin) Lab (6) Apply Liu (Yin) Lab filter
- Liu (Zhe) Lab (61) Apply Liu (Zhe) Lab filter
- Looger Lab (138) Apply Looger Lab filter
- Magee Lab (49) Apply Magee Lab filter
- Menon Lab (18) Apply Menon Lab filter
- Murphy Lab (13) Apply Murphy Lab filter
- O'Shea Lab (6) Apply O'Shea Lab filter
- Otopalik Lab (13) Apply Otopalik Lab filter
- Pachitariu Lab (47) Apply Pachitariu Lab filter
- Pastalkova Lab (18) Apply Pastalkova Lab filter
- Pavlopoulos Lab (19) Apply Pavlopoulos Lab filter
- Pedram Lab (15) Apply Pedram Lab filter
- Podgorski Lab (16) Apply Podgorski Lab filter
- Reiser Lab (51) Apply Reiser Lab filter
- Riddiford Lab (44) Apply Riddiford Lab filter
- Romani Lab (43) Apply Romani Lab filter
- Rubin Lab (143) Apply Rubin Lab filter
- Saalfeld Lab (63) Apply Saalfeld Lab filter
- Satou Lab (16) Apply Satou Lab filter
- Scheffer Lab (36) Apply Scheffer Lab filter
- Schreiter Lab (67) Apply Schreiter Lab filter
- Sgro Lab (21) Apply Sgro Lab filter
- Shroff Lab (30) Apply Shroff Lab filter
- Simpson Lab (23) Apply Simpson Lab filter
- Singer Lab (80) Apply Singer Lab filter
- Spruston Lab (93) Apply Spruston Lab filter
- Stern Lab (156) Apply Stern Lab filter
- Sternson Lab (54) Apply Sternson Lab filter
- Stringer Lab (34) Apply Stringer Lab filter
- Svoboda Lab (135) Apply Svoboda Lab filter
- Tebo Lab (33) Apply Tebo Lab filter
- Tervo Lab (9) Apply Tervo Lab filter
- Tillberg Lab (21) Apply Tillberg Lab filter
- Tjian Lab (64) Apply Tjian Lab filter
- Truman Lab (88) Apply Truman Lab filter
- Turaga Lab (50) Apply Turaga Lab filter
- Turner Lab (37) Apply Turner Lab filter
- Vale Lab (7) Apply Vale Lab filter
- Voigts Lab (3) Apply Voigts Lab filter
- Wang (Meng) Lab (18) Apply Wang (Meng) Lab filter
- Wang (Shaohe) Lab (25) Apply Wang (Shaohe) Lab filter
- Wu Lab (9) Apply Wu Lab filter
- Zlatic Lab (28) Apply Zlatic Lab filter
- Zuker Lab (25) Apply Zuker Lab filter
Associated Project Team
- CellMap (12) Apply CellMap filter
- COSEM (3) Apply COSEM filter
- FIB-SEM Technology (2) Apply FIB-SEM Technology filter
- Fly Descending Interneuron (10) Apply Fly Descending Interneuron filter
- Fly Functional Connectome (14) Apply Fly Functional Connectome filter
- Fly Olympiad (5) Apply Fly Olympiad filter
- FlyEM (53) Apply FlyEM filter
- FlyLight (49) Apply FlyLight filter
- GENIE (45) Apply GENIE filter
- Integrative Imaging (3) Apply Integrative Imaging filter
- Larval Olympiad (2) Apply Larval Olympiad filter
- MouseLight (18) Apply MouseLight filter
- NeuroSeq (1) Apply NeuroSeq filter
- ThalamoSeq (1) Apply ThalamoSeq filter
- Tool Translation Team (T3) (26) Apply Tool Translation Team (T3) filter
- Transcription Imaging (49) Apply Transcription Imaging filter
Publication Date
- 2025 (85) Apply 2025 filter
- 2024 (222) Apply 2024 filter
- 2023 (161) Apply 2023 filter
- 2022 (193) Apply 2022 filter
- 2021 (194) Apply 2021 filter
- 2020 (196) Apply 2020 filter
- 2019 (202) Apply 2019 filter
- 2018 (232) Apply 2018 filter
- 2017 (217) Apply 2017 filter
- 2016 (209) Apply 2016 filter
- 2015 (252) Apply 2015 filter
- 2014 (236) Apply 2014 filter
- 2013 (194) Apply 2013 filter
- 2012 (190) Apply 2012 filter
- 2011 (190) Apply 2011 filter
- 2010 (161) Apply 2010 filter
- 2009 (158) Apply 2009 filter
- 2008 (140) Apply 2008 filter
- 2007 (106) Apply 2007 filter
- 2006 (92) Apply 2006 filter
- 2005 (67) Apply 2005 filter
- 2004 (57) Apply 2004 filter
- 2003 (58) Apply 2003 filter
- 2002 (39) Apply 2002 filter
- 2001 (28) Apply 2001 filter
- 2000 (29) Apply 2000 filter
- 1999 (14) Apply 1999 filter
- 1998 (18) Apply 1998 filter
- 1997 (16) Apply 1997 filter
- 1996 (10) Apply 1996 filter
- 1995 (18) Apply 1995 filter
- 1994 (12) Apply 1994 filter
- 1993 (10) Apply 1993 filter
- 1992 (6) Apply 1992 filter
- 1991 (11) Apply 1991 filter
- 1990 (11) Apply 1990 filter
- 1989 (6) Apply 1989 filter
- 1988 (1) Apply 1988 filter
- 1987 (7) Apply 1987 filter
- 1986 (4) Apply 1986 filter
- 1985 (5) Apply 1985 filter
- 1984 (2) Apply 1984 filter
- 1983 (2) Apply 1983 filter
- 1982 (3) Apply 1982 filter
- 1981 (3) Apply 1981 filter
- 1980 (1) Apply 1980 filter
- 1979 (1) Apply 1979 filter
- 1976 (2) Apply 1976 filter
- 1973 (1) Apply 1973 filter
- 1970 (1) Apply 1970 filter
- 1967 (1) Apply 1967 filter
Type of Publication
4074 Publications
Showing 651-660 of 4074 resultsWe describe an approach to study the conformation of individual proteins during single particle tracking (SPT) in living cells. "Binder/tag" is based on incorporation of a 7-mer peptide (the tag) into a protein where its solvent exposure is controlled by protein conformation. Only upon exposure can the peptide specifically interact with a reporter protein (the binder). Thus, simple fluorescence localization reflects protein conformation. Through direct excitation of bright dyes, the trajectory and conformation of individual proteins can be followed. Simple protein engineering provides highly specific biosensors suitable for SPT and FRET. We describe tagSrc, tagFyn, tagSyk, tagFAK, and an orthogonal binder/tag pair. SPT showed slowly diffusing islands of activated Src within Src clusters and dynamics of activation in adhesions. Quantitative analysis and stochastic modeling revealed in vivo Src kinetics. The simplicity of binder/tag can provide access to diverse proteins.
The target for the "rapid" (<24 h) antidepressant effects of S-ketamine is unknown, vitiating programs to rationally develop more effective rapid antidepressants. To describe a drug's target, one must first understand the compartments entered by the drug, at all levels-the organ, the cell, and the organelle. We have, therefore, developed molecular tools to measure the subcellular, organellar pharmacokinetics of S-ketamine. The tools are genetically encoded intensity-based S-ketamine-sensing fluorescent reporters, iSKetSnFR1 and iSKetSnFR2. In solution, these biosensors respond to S-ketamine with a sensitivity, S-slope = delta(F/F)/(delta[S-ketamine]) of 0.23 and 1.9/μM, respectively. The iSKetSnFR2 construct allows measurements at <0.3 μM S-ketamine. The iSKetSnFR1 and iSKetSnFR2 biosensors display >100-fold selectivity over other ligands tested, including R-ketamine. We targeted each of the sensors to either the plasma membrane (PM) or the endoplasmic reticulum (ER). Measurements on these biosensors expressed in Neuro2a cells and in human dopaminergic neurons differentiated from induced pluripotent stem cells (iPSCs) show that S-ketamine enters the ER within a few seconds after appearing in the external solution near the PM, then leaves as rapidly after S-ketamine is removed from the extracellular solution. In cells, S-slopes for the ER and PM-targeted sensors differ by <2-fold, indicating that the ER [S-ketamine] is less than 2-fold different from the extracellular [S-ketamine]. Organelles represent potential compartments for the engagement of S-ketamine with its antidepressant target, and potential S-ketamine targets include organellar ion channels, receptors, and transporters.
Neurons derived from the same progenitor may acquire different fates according to their birth timing/order. To reveal temporally guided cell fates, we must determine neuron types as well as their lineage relationships and times of birth. Recent advances in genetic lineage analysis and fate mapping are facilitating such studies. For example, high-resolution lineage analysis can identify each sequentially derived neuron of a lineage and has revealed abrupt temporal identity changes in diverse Drosophila neuronal lineages. In addition, fate mapping of mouse neurons made from the same pool of precursors shows production of specific neuron types in specific temporal patterns. The tools used in these analyses are helping to further our understanding of the genetics of neuronal temporal identity.
The additive and synergistic therapeutic effects derived from combinations of chemotherapeutic drugs and radiation have established an indispensable paradigm: cancer must be attacked on multiple fronts. However, the increased antitumor efficacy of such combinational regimens is also associated with severe systemic toxicity, as these drugs cannot selectively target tumor cells. Monoclonal antibodies (mAbs), which have exquisite specificity for their antigens, are becoming an increasingly important class of antitumor agents, as they enhance the efficacy of various therapeutic regimens without significantly increasing systemic toxicity. Furthermore, preclinical and early clinical evidence indicate that combinations of antibody-based drugs provide even greater efficacy with minimal side effects. Unfortunately, the research, manufacturing and regulatory costs of mAb development pose a significant barrier to the use of antibody-based combination therapies. An emerging alternative is the use of dual-targeting bispecific antibodies (BsAbs). BsAbs are derived from the recombination of variable domains of two antibodies with different specificities; BsAbs are thus capable of binding both antigens of their parental antibodies. With the recent progress that has been made in antibody engineering technology, BsAbs that simultaneously target two tumor-associated molecules (eg, growth factor receptors) are being heralded for their potential to deliver two therapeutic moieties in a single molecule.
Characterizing the identity and types of neurons in the brain, as well as their associated function, requires a means of quantifying and comparing 3D neuron morphology. Presently, neuron comparison methods are based on statistics from neuronal morphology such as size and number of branches, which are not fully suitable for detecting local similarities and differences in the detailed structure. We developed BlastNeuron to compare neurons in terms of their global appearance, detailed arborization patterns, and topological similarity. BlastNeuron first compares and clusters 3D neuron reconstructions based on global morphology features and moment invariants, independent of their orientations, sizes, level of reconstruction and other variations. Subsequently, BlastNeuron performs local alignment between any pair of retrieved neurons via a tree-topology driven dynamic programming method. A 3D correspondence map can thus be generated at the resolution of single reconstruction nodes. We applied BlastNeuron to three datasets: (1) 10,000+ neuron reconstructions from a public morphology database, (2) 681 newly and manually reconstructed neurons, and (3) neurons reconstructions produced using several independent reconstruction methods. Our approach was able to accurately and efficiently retrieve morphologically and functionally similar neuron structures from large morphology database, identify the local common structures, and find clusters of neurons that share similarities in both morphology and molecular profiles.
Superresolution imaging techniques based on the precise localization of single molecules, such as photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), achieve high resolution by fitting images of single fluorescent molecules with a theoretical Gaussian to localize them with a precision on the order of tens of nanometers. PALM/STORM rely on photoactivated proteins or photoswitching dyes, respectively, which makes them technically challenging. We present a simple and practical way of producing point localization-based superresolution images 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. To detect single fluorophores, we simply acquire a stream of fluorescence images. Fluorophore bleach or blink-off events are detected 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 also show that BaLM works with a spectrum of fluorescent molecules in the same sample. Thus, BaLM extends single molecule-based superresolution localization to samples labeled with multiple conventional fluorescent probes.
Significance: Genetically encoded calcium ion (Ca2+) indicators (GECIs) are powerful tools for monitoring intracellular Ca2+ concentration changes in living cells and model organisms. In particular, GECIs have found particular utility for monitoring the transient increase of Ca2+concentration that is associated with the neuronal action potential. However, the palette of highly optimized GECIs for imaging of neuronal activity remains relatively limited. Expanding the selection of available GECIs to include new colors and distinct photophysical properties could create new opportunities for in vitro and in vivo fluorescence imaging of neuronal activity. In particular, blue-shifted variants of GECIs are expected to have enhanced two-photon brightness, which would facilitate multiphoton microscopy. Aim: We describe the development and applications of T-GECO1-a high-performance blue-shifted GECI based on the Clavularia sp.-derived mTFP1. Approach: We use protein engineering and extensive directed evolution to develop T-GECO1. We characterize the purified protein and assess its performance in vitro using one-photon excitation in cultured rat hippocampal neurons, in vivo using one-photon excitation fiber photometry in mice, and ex vivo using two-photon Ca2+ imaging in hippocampal slices. Results: The Ca2+-bound state of T-GECO1 has an excitation peak maximum of 468 nm, an emission peak maximum of 500 nm, an extinction coefficient of 49,300M−1cm−1, a quantum yield of 0.83, and two-photon brightness approximately double that of EGFP. The Ca2+-dependent fluorescence increase is 15-fold, and the apparent Kd for Ca2+ is 82 nM. With two-photon excitation conditions at 850 nm, T-GECO1 consistently enabled the detection of action potentials with higher signal-to-noise (SNR) than a late generation GCaMP variant. Conclusions: T-GECO1 is a high-performance blue-shifted GECI that, under two-photon excitation conditions, provides advantages relative to late generation GCaMP variants. Keywords: blue-shifted fluorescence; genetically encoded calcium ion indicator; neuronal activity imaging; protein engineering; two-photon excitation.
Insulin signaling controls organ growth and final body size in insects. Recent results have begun to clarify how insulin signaling drives organ growth to match nutrient levels, but have not yet elucidated how insulin signaling controls final body size.
Separate recent studies have revealed the physiological changes underlying the evolution of body size in an insect and advanced our understanding of the genetics of insect growth. These studies highlight the gulf between physiological and genetic studies of growth control and the exciting opportunities for unification of these fields.
Manipulation of hematopoietic stem/progenitor cells (HSPCs) ex vivo is of clinical importance for stem cell expansion and gene therapy applications. However, most cultured HSPCs are actively cycling, and show a homing and engraftment defect compared with the predominantly quiescent noncultured HSPCs. We previously showed that HSPCs make contact with osteoblasts in vitro via a polarized membrane domain enriched in adhesion molecules such as tetraspanins. Here we show that increased cell cycling during ex vivo culture of HSPCs resulted in disruption of this membrane domain, as evidenced by disruption of polarity of the tetraspanin CD82. Chemical disruption or antibody-mediated blocking of CD82 on noncultured HSPCs resulted in decreased stromal cell adhesion, homing, and engraftment in nonobese diabetic/severe combined immunodeficiency IL-2γ(null) (NSG) mice compared with HSPCs with an intact domain. Most leukemic blasts were actively cycling and correspondingly displayed a loss of domain polarity and decreased homing in NSG mice compared with normal HSPCs. We conclude that quiescent cells, unlike actively cycling cells, display a polarized membrane domain enriched in tetraspanins that mediates homing and engraftment, providing a mechanistic explanation for the homing/engraftment defect of cycling cells and a potential new therapeutic target to enhance engraftment.