Filter
Associated Lab
- Ahrens Lab (36) Apply Ahrens Lab filter
- Aso Lab (30) Apply Aso Lab filter
- Baker Lab (19) Apply Baker Lab filter
- Betzig Lab (91) Apply Betzig Lab filter
- Beyene Lab (3) Apply Beyene Lab filter
- Bock Lab (14) Apply Bock Lab filter
- Branson Lab (40) Apply Branson Lab filter
- Card Lab (24) Apply Card Lab filter
- Cardona Lab (44) Apply Cardona Lab filter
- Chklovskii Lab (10) Apply Chklovskii Lab filter
- Clapham Lab (9) Apply Clapham Lab filter
- Cui Lab (19) Apply Cui Lab filter
- Darshan Lab (3) Apply Darshan Lab filter
- Dickson Lab (27) Apply Dickson Lab filter
- Druckmann Lab (21) Apply Druckmann Lab filter
- Dudman Lab (29) Apply Dudman Lab filter
- Eddy/Rivas Lab (30) Apply Eddy/Rivas Lab filter
- Egnor Lab (4) Apply Egnor Lab filter
- Fetter Lab (31) Apply Fetter Lab filter
- Fitzgerald Lab (9) Apply Fitzgerald Lab filter
- Freeman Lab (15) Apply Freeman Lab filter
- Funke Lab (18) Apply Funke Lab filter
- Gonen Lab (59) Apply Gonen Lab filter
- Grigorieff Lab (34) Apply Grigorieff Lab filter
- Hantman Lab (27) Apply Hantman Lab filter
- Harris Lab (39) Apply Harris Lab filter
- Heberlein Lab (13) Apply Heberlein Lab filter
- Hermundstad Lab (8) Apply Hermundstad Lab filter
- Hess Lab (55) Apply Hess Lab filter
- Huston Lab (4) Apply Huston Lab filter
- Jayaraman Lab (34) Apply Jayaraman Lab filter
- Ji Lab (32) Apply Ji Lab filter
- Johnson Lab (1) Apply Johnson Lab filter
- Karpova Lab (11) Apply Karpova Lab filter
- Keleman Lab (8) Apply Keleman Lab filter
- Keller Lab (57) Apply Keller Lab filter
- Koyama Lab (22) Apply Koyama Lab filter
- Lavis Lab (98) Apply Lavis Lab filter
- Lee (Albert) Lab (24) Apply Lee (Albert) Lab filter
- Lee (Tzumin) Lab (51) Apply Lee (Tzumin) Lab filter
- Leonardo Lab (19) Apply Leonardo Lab filter
- Lippincott-Schwartz Lab (64) Apply Lippincott-Schwartz Lab filter
- Liu Lab (41) Apply Liu Lab filter
- Looger Lab (127) Apply Looger Lab filter
- Magee Lab (31) Apply Magee Lab filter
- Menon Lab (12) Apply Menon Lab filter
- Murphy Lab (6) Apply Murphy Lab filter
- O'Shea Lab (2) Apply O'Shea Lab filter
- Pachitariu Lab (18) Apply Pachitariu Lab filter
- Pastalkova Lab (5) Apply Pastalkova Lab filter
- Pavlopoulos Lab (7) Apply Pavlopoulos Lab filter
- Podgorski Lab (14) Apply Podgorski Lab filter
- Reiser Lab (32) Apply Reiser Lab filter
- Riddiford Lab (20) Apply Riddiford Lab filter
- Romani Lab (23) Apply Romani Lab filter
- Rubin Lab (92) Apply Rubin Lab filter
- Saalfeld Lab (30) Apply Saalfeld Lab filter
- Scheffer Lab (33) Apply Scheffer Lab filter
- Schreiter Lab (37) Apply Schreiter Lab filter
- Simpson Lab (18) Apply Simpson Lab filter
- Singer Lab (35) Apply Singer Lab filter
- Spruston Lab (52) Apply Spruston Lab filter
- Stern Lab (55) Apply Stern Lab filter
- Sternson Lab (43) Apply Sternson Lab filter
- Stringer Lab (10) Apply Stringer Lab filter
- Svoboda Lab (122) Apply Svoboda Lab filter
- Tebo Lab (2) Apply Tebo Lab filter
- Tervo Lab (8) Apply Tervo Lab filter
- Tillberg Lab (9) Apply Tillberg Lab filter
- Tjian Lab (17) Apply Tjian Lab filter
- Truman Lab (56) Apply Truman Lab filter
- Turaga Lab (29) Apply Turaga Lab filter
- Turner Lab (12) Apply Turner Lab filter
- Vale Lab (1) Apply Vale Lab filter
- Wu Lab (8) Apply Wu Lab filter
- Zlatic Lab (27) Apply Zlatic Lab filter
- Zuker Lab (5) Apply Zuker Lab filter
Associated Project Team
- COSEM (1) Apply COSEM filter
- Fly Descending Interneuron (7) Apply Fly Descending Interneuron filter
- Fly Functional Connectome (11) Apply Fly Functional Connectome filter
- Fly Olympiad (4) Apply Fly Olympiad filter
- FlyEM (52) Apply FlyEM filter
- FlyLight (29) Apply FlyLight filter
- GENIE (32) Apply GENIE filter
- Larval Olympiad (2) Apply Larval Olympiad filter
- MouseLight (14) Apply MouseLight filter
- NeuroSeq (1) Apply NeuroSeq filter
- ThalamoSeq (1) Apply ThalamoSeq filter
- Tool Translation Team (T3) (11) Apply Tool Translation Team (T3) filter
- Transcription Imaging (45) Apply Transcription Imaging filter
Associated Support Team
- Anatomy and Histology (14) Apply Anatomy and Histology filter
- Annotation & Analytics (3) Apply Annotation & Analytics filter
- Cell and Tissue Culture (11) Apply Cell and Tissue Culture filter
- Cryo-Electron Microscopy (26) Apply Cryo-Electron Microscopy filter
- Drosophila Resources (24) Apply Drosophila Resources filter
- Electron Microscopy (10) Apply Electron Microscopy filter
- Gene Targeting and Transgenics (9) Apply Gene Targeting and Transgenics filter
- Janelia Experimental Technology (29) Apply Janelia Experimental Technology filter
- Light Microscopy (7) Apply Light Microscopy filter
- Management Team (1) Apply Management Team filter
- Molecular Biology (12) Apply Molecular Biology filter
- Project Technical Resources (14) Apply Project Technical Resources filter
- Quantitative Genomics (17) Apply Quantitative Genomics filter
- Scientific Computing Software (50) Apply Scientific Computing Software filter
- Scientific Computing Systems (4) Apply Scientific Computing Systems filter
- Viral Tools (8) Apply Viral Tools filter
- Vivarium (6) Apply Vivarium filter
Publication Date
- 2022 (75) Apply 2022 filter
- 2021 (179) Apply 2021 filter
- 2020 (178) Apply 2020 filter
- 2019 (177) Apply 2019 filter
- 2018 (206) Apply 2018 filter
- 2017 (187) Apply 2017 filter
- 2016 (191) Apply 2016 filter
- 2015 (196) Apply 2015 filter
- 2014 (191) Apply 2014 filter
- 2013 (136) Apply 2013 filter
- 2012 (112) Apply 2012 filter
- 2011 (98) Apply 2011 filter
- 2010 (62) Apply 2010 filter
- 2009 (56) Apply 2009 filter
- 2008 (40) Apply 2008 filter
- 2007 (21) Apply 2007 filter
- 2006 (3) Apply 2006 filter
2108 Janelia Publications
Showing 1991-2000 of 2108 resultsThe microtubule cytoskeleton has proven to be an effective target for cancer therapeutics. One class of drugs, known as microtubule stabilizing agents (MSAs), binds to microtubule polymers and stabilizes them against depolymerization. The prototype of this group of drugs, Taxol, is an effective chemotherapeutic agent used extensively in the treatment of human ovarian, breast, and lung carcinomas. Although electron crystallography and photoaffinity labeling experiments determined that the binding site for Taxol is in a hydrophobic pocket in beta-tubulin, little was known about the effects of this drug on the conformation of the entire microtubule. A recent study from our laboratory utilizing hydrogen-deuterium exchange (HDX) in concert with various mass spectrometry (MS) techniques has provided new information on the structure of microtubules upon Taxol binding. In the current study we apply this technique to determine the binding mode and the conformational effects on chicken erythrocyte tubulin (CET) of another MSA, discodermolide, whose synthetic analogues may have potential use in the clinic. We confirmed that, like Taxol, discodermolide binds to the taxane binding pocket in beta-tubulin. However, as opposed to Taxol, which has major interactions with the M-loop, discodermolide orients itself away from this loop and toward the N-terminal H1-S2 loop. Additionally, discodermolide stabilizes microtubules mainly via its effects on interdimer contacts, specifically on the alpha-tubulin side, and to a lesser extent on interprotofilament contacts between adjacent beta-tubulin subunits. Also, our results indicate complementary stabilizing effects of Taxol and discodermolide on the microtubules, which may explain the synergy observed between the two drugs in vivo.
The excitability of individual dendritic branches is a plastic property of neurons. We found that experience in an enriched environment increased propagation of dendritic Na(+) spikes in a subset of individual dendritic branches in rat hippocampal CA1 pyramidal neurons and that this effect was mainly mediated by localized downregulation of A-type K(+) channel function. Thus, dendritic plasticity might be used to store recent experience in individual branches of the dendritic arbor.
Genetically encoded calcium indicators (GECIs) can be used to image activity in defined neuronal populations. However, current GECIs produce inferior signals compared to synthetic indicators and recording electrodes, precluding detection of low firing rates. We developed a single-wavelength GCaMP2-based GECI (GCaMP3), with increased baseline fluorescence (3-fold), increased dynamic range (3-fold) and higher affinity for calcium (1.3-fold). We detected GCaMP3 fluorescence changes triggered by single action potentials in pyramidal cell dendrites, with signal-to-noise ratio and photostability substantially better than those of GCaMP2, D3cpVenus and TN-XXL. In Caenorhabditis elegans chemosensory neurons and the Drosophila melanogaster antennal lobe, sensory stimulation-evoked fluorescence responses were significantly enhanced with GCaMP3 (4-6-fold). In somatosensory and motor cortical neurons in the intact mouse, GCaMP3 detected calcium transients with amplitudes linearly dependent on action potential number. Long-term imaging in the motor cortex of behaving mice revealed large fluorescence changes in imaged neurons over months.
During the development of the central nervous system (CNS) of Drosophila, neuronal stem cells, the neuroblasts (NBs), first generate a set of highly diverse neurons, the primary neurons that mature to control larval behavior, and then more homogeneous sets of neurons that show delayed maturation and are primarily used in the adult. These latter, ’secondary’ neurons show a complex pattern of expression of broad, which encodes a transcription factor usually associated with metamorphosis, where it acts as a key regulator in the transitions from larva and pupa.
Wnt signaling through Frizzled proteins guides posterior cells and axons in C. elegans into different spatial domains. Here we demonstrate an essential role for Wnt signaling through Ror tyrosine kinase homologs in the most prominent anterior neuropil, the nerve ring. A genetic screen uncovered cwn-2, the C. elegans homolog of Wnt5, as a regulator of nerve ring placement. In cwn-2 mutants, all neuronal structures in and around the nerve ring are shifted to an abnormal anterior position. cwn-2 is required at the time of nerve ring formation; it is expressed by cells posterior of the nerve ring, but its precise site of expression is not critical for its function. In nerve ring development, cwn-2 acts primarily through the Wnt receptor CAM-1 (Ror), together with the Frizzled protein MIG-1, with parallel roles for the Frizzled protein CFZ-2. The identification of CAM-1 as a CWN-2 receptor contrasts with CAM-1 action as a non-receptor in other C. elegans Wnt pathways. Cell-specific rescue of cam-1 and cell ablation experiments reveal a crucial role for the SIA and SIB neurons in positioning the nerve ring, linking Wnt signaling to specific cells that organize the anterior nervous system.
The C. elegans cell lineage provides a unique opportunity to look at how cell lineage affects patterns of gene expression. We developed an automatic cell lineage analyzer that converts high-resolution images of worms into a data table showing fluorescence expression with single-cell resolution. We generated expression profiles of 93 genes in 363 specific cells from L1 stage larvae and found that cells with identical fates can be formed by different gene regulatory pathways. Molecular signatures identified repeating cell fate modules within the cell lineage and enabled the generation of a molecular differentiation map that reveals points in the cell lineage when developmental fates of daughter cells begin to diverge. These results demonstrate insights that become possible using computational approaches to analyze quantitative expression from many genes in parallel using a digital gene expression atlas.
Forkhead transcription factors play critical roles in leukocyte homeostasis. To study further the immunological functions of Foxo1, we generated mice that selectively lack Foxo1 in T cells (Foxo1(flox/flox) Lck.cre(+)conditional knockout mice (cKO)). Although thymocyte development appeared relatively normal, Foxo1 cKO mice harbored significantly increased percentages of mature single positive T cells in the thymus as compared with WT mice, yet possessed smaller lymph nodes and spleens that contained fewer T cells. Foxo1 cKO T cells were not more prone to apoptosis, but instead were characterized by a CD62L(lo) CCR7(lo) CD44(hi) surface phenotype, a poorly populated lymphoid compartment in the periphery, and were relatively refractory to TCR stimulation, all of which were associated with reduced expression of Sell, Klf2, Ccr7, and S1pr1. Thus, Foxo1 is critical for naïve T cells to populate the peripheral lymphoid organs by coordinating a molecular program that maintains homeostasis and regulates trafficking.
Cortical information processing is under state-dependent control of subcortical neuromodulatory systems. Although this modulatory effect is thought to be mediated mainly by slow nonsynaptic metabotropic receptors, other mechanisms, such as direct synaptic transmission, are possible. Yet, it is currently unknown if any such form of subcortical control exists. Here, we present direct evidence of a strong, spatiotemporally precise excitatory input from an ascending neuromodulatory center. Selective stimulation of serotonergic median raphe neurons produced a rapid activation of hippocampal interneurons. At the network level, this subcortical drive was manifested as a pattern of effective disynaptic GABAergic inhibition that spread throughout the circuit. This form of subcortical network regulation should be incorporated into current concepts of normal and pathological cortical function.
Behaviour is governed by activity in highly structured neural circuits. Genetically targeted sensors and switches facilitate measurement and manipulation of activity in vivo, linking activity in defined nodes of neural circuits to behaviour. Because of access to specific cell types, these molecular tools will have the largest impact in genetic model systems such as the mouse. Emerging assays of mouse behaviour are beginning to rival those of behaving monkeys in terms of stimulus and behavioural control. We predict that the confluence of new behavioural and molecular tools in the mouse will reveal the logic of complex mammalian circuits.
Many theoretical advances have been made in applying probabilistic inference methods to improve the power of sequence homology searches, yet the BLAST suite of programs is still the workhorse for most of the field. The main reason for this is practical: BLAST’s programs are about 100-fold faster than the fastest competing implementations of probabilistic inference methods. I describe recent work on the HMMER software suite for protein sequence analysis, which implements probabilistic inference using profile hidden Markov models. Our aim in HMMER3 is to achieve BLAST’s speed while further improving the power of probabilistic inference based methods. HMMER3 implements a new probabilistic model of local sequence alignment and a new heuristic acceleration algorithm. Combined with efficient vector-parallel implementations on modern processors, these improvements synergize. HMMER3 uses more powerful log-odds likelihood scores (scores summed over alignment uncertainty, rather than scoring a single optimal alignment); it calculates accurate expectation values (E-values) for those scores without simulation using a generalization of Karlin/Altschul theory; it computes posterior distributions over the ensemble of possible alignments and returns posterior probabilities (confidences) in each aligned residue; and it does all this at an overall speed comparable to BLAST. The HMMER project aims to usher in a new generation of more powerful homology search tools based on probabilistic inference methods.