Filter
Associated Lab
- Aguilera Castrejon Lab (15) Apply Aguilera Castrejon Lab filter
- Ahrens Lab (56) Apply Ahrens Lab filter
- Aso Lab (39) Apply Aso Lab filter
- Baker Lab (38) Apply Baker Lab filter
- Betzig Lab (110) Apply Betzig Lab filter
- Beyene Lab (10) Apply Beyene Lab filter
- Bock Lab (17) Apply Bock Lab filter
- Branson Lab (48) Apply Branson Lab filter
- Card Lab (40) Apply Card Lab filter
- Cardona Lab (63) Apply Cardona Lab filter
- Chklovskii Lab (13) Apply Chklovskii Lab filter
- Clapham Lab (12) 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 (46) Apply Dudman Lab filter
- Eddy/Rivas Lab (30) Apply Eddy/Rivas Lab filter
- Egnor Lab (11) Apply Egnor Lab filter
- Espinosa Medina Lab (16) Apply Espinosa Medina Lab filter
- Feliciano Lab (6) Apply Feliciano Lab filter
- Fetter Lab (41) Apply Fetter Lab filter
- Fitzgerald Lab (28) Apply Fitzgerald Lab filter
- Freeman Lab (15) Apply Freeman Lab filter
- Funke Lab (34) Apply Funke Lab filter
- Gonen Lab (91) Apply Gonen Lab filter
- Grigorieff Lab (62) Apply Grigorieff Lab filter
- Harris Lab (58) Apply Harris Lab filter
- Heberlein Lab (94) Apply Heberlein Lab filter
- Hermundstad Lab (22) Apply Hermundstad Lab filter
- Hess Lab (71) Apply Hess Lab filter
- Ilanges Lab (1) Apply Ilanges Lab filter
- Jayaraman Lab (44) 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 (75) Apply Keller Lab filter
- Koay Lab (16) Apply Koay Lab filter
- Lavis Lab (136) Apply Lavis Lab filter
- Lee (Albert) Lab (34) Apply Lee (Albert) Lab filter
- Leonardo Lab (23) Apply Leonardo Lab filter
- Li Lab (25) Apply Li Lab filter
- Lippincott-Schwartz Lab (161) Apply Lippincott-Schwartz Lab filter
- Liu (Yin) Lab (5) Apply Liu (Yin) Lab filter
- Liu (Zhe) Lab (58) Apply Liu (Zhe) Lab filter
- Looger Lab (137) 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 (4) Apply O'Shea Lab filter
- Otopalik Lab (13) Apply Otopalik Lab filter
- Pachitariu Lab (41) Apply Pachitariu Lab filter
- Pastalkova Lab (18) Apply Pastalkova Lab filter
- Pavlopoulos Lab (19) Apply Pavlopoulos Lab filter
- Pedram Lab (14) Apply Pedram Lab filter
- Podgorski Lab (16) Apply Podgorski Lab filter
- Reiser Lab (49) Apply Reiser Lab filter
- Riddiford Lab (44) Apply Riddiford Lab filter
- Romani Lab (40) Apply Romani Lab filter
- Rubin Lab (139) Apply Rubin Lab filter
- Saalfeld Lab (60) Apply Saalfeld Lab filter
- Satou Lab (16) Apply Satou Lab filter
- Scheffer Lab (36) Apply Scheffer Lab filter
- Schreiter Lab (62) Apply Schreiter Lab filter
- Sgro Lab (20) Apply Sgro Lab filter
- Shroff Lab (23) Apply Shroff Lab filter
- Simpson Lab (23) Apply Simpson Lab filter
- Singer Lab (80) Apply Singer Lab filter
- Spruston Lab (91) Apply Spruston Lab filter
- Stern Lab (152) Apply Stern Lab filter
- Sternson Lab (54) Apply Sternson Lab filter
- Stringer Lab (29) Apply Stringer Lab filter
- Svoboda Lab (135) Apply Svoboda Lab filter
- Tebo Lab (31) Apply Tebo Lab filter
- Tervo Lab (9) Apply Tervo Lab filter
- Tillberg Lab (17) Apply Tillberg Lab filter
- Tjian Lab (64) Apply Tjian Lab filter
- Truman Lab (88) Apply Truman Lab filter
- Turaga Lab (46) Apply Turaga Lab filter
- Turner Lab (35) Apply Turner Lab filter
- Vale Lab (6) Apply Vale Lab filter
- Voigts Lab (2) Apply Voigts Lab filter
- Wang (Meng) Lab (9) Apply Wang (Meng) Lab filter
- Wang (Shaohe) Lab (24) 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 (5) Apply CellMap filter
- COSEM (3) Apply COSEM 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 (51) Apply FlyEM filter
- FlyLight (46) Apply FlyLight filter
- GENIE (40) Apply GENIE filter
- Integrative Imaging (1) Apply Integrative Imaging filter
- Larval Olympiad (2) Apply Larval Olympiad filter
- MouseLight (16) Apply MouseLight filter
- NeuroSeq (1) Apply NeuroSeq filter
- ThalamoSeq (1) Apply ThalamoSeq filter
- Tool Translation Team (T3) (24) Apply Tool Translation Team (T3) filter
- Transcription Imaging (49) Apply Transcription Imaging filter
Publication Date
- 2024 (141) Apply 2024 filter
- 2023 (175) Apply 2023 filter
- 2022 (192) Apply 2022 filter
- 2021 (193) 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
3920 Publications
Showing 1211-1220 of 3920 resultsLive imaging of transcription and RNA dynamics has been successful in cultured cells and tissues of vertebrates but is challenging to accomplish in vivo. The zebrafish offers important advantages to study these processes--optical transparency during embryogenesis, genetic tractability and rapid development. Therefore, to study transcription and RNA dynamics in an intact vertebrate organism, we have adapted the MS2 RNA-labeling system to zebrafish. By using this binary system to coexpress a fluorescent MS2 bacteriophage coat protein (MCP) and an RNA of interest tagged with multiple copies of the RNA hairpin MS2-binding site (MBS), live-cell imaging of RNA dynamics at single RNA molecule resolution has been achieved in other organisms. Here, using a Gateway-compatible MS2 labeling system, we generated stable transgenic zebrafish lines expressing MCP, validated the MBS-MCP interaction and applied the system to investigate zygotic genome activation (ZGA) and RNA localization in primordial germ cells (PGCs) in zebrafish. Although cleavage stage cells are initially transcriptionally silent, we detect transcription of MS2-tagged transcripts driven by the βactin promoter at ∼ 3-3.5 h post-fertilization, consistent with the previously reported ZGA. Furthermore, we show that MS2-tagged nanos3 3'UTR transcripts localize to PGCs, where they are diffusely cytoplasmic and within larger cytoplasmic accumulations reminiscent of those displayed by endogenous nanos3. These tools provide a new avenue for live-cell imaging of RNA molecules in an intact vertebrate. Together with new techniques for targeted genome editing, this system will be a valuable tool to tag and study the dynamics of endogenous RNAs during zebrafish developmental processes.
Behavioral strategies employed for chemotaxis have been described across phyla, but the sensorimotor basis of this phenomenon has seldom been studied in naturalistic contexts. Here, we examine how signals experienced during free olfactory behaviors are processed by first-order olfactory sensory neurons (OSNs) of the Drosophila larva. We find that OSNs can act as differentiators that transiently normalize stimulus intensity-a property potentially derived from a combination of integral feedback and feed-forward regulation of olfactory transduction. In olfactory virtual reality experiments, we report that high activity levels of the OSN suppress turning, whereas low activity levels facilitate turning. Using a generalized linear model, we explain how peripheral encoding of olfactory stimuli modulates the probability of switching from a run to a turn. Our work clarifies the link between computations carried out at the sensory periphery and action selection underlying navigation in odor gradients.
Neurons throughout the sensory pathway adapt their responses depending on the statistical structure of the sensory environment. Contrast gain control is a form of adaptation in the auditory cortex, but it is unclear whether the dynamics of gain control reflect efficient adaptation, and whether they shape behavioral perception. Here, we trained mice to detect a target presented in background noise shortly after a change in the contrast of the background. The observed changes in cortical gain and behavioral detection followed the dynamics of a normative model of efficient contrast gain control; specifically, target detection and sensitivity improved slowly in low contrast, but degraded rapidly in high contrast. Auditory cortex was required for this task, and cortical responses were not only similarly affected by contrast but predicted variability in behavioral performance. Combined, our results demonstrate that dynamic gain adaptation supports efficient coding in auditory cortex and predicts the perception of sounds in noise.
The RNA-guided CRISPR-associated protein Cas9 is used for genome editing, transcriptional modulation, and live-cell imaging. Cas9-guide RNA complexes recognize and cleave double-stranded DNA sequences on the basis of 20-nucleotide RNA-DNA complementarity, but the mechanism of target searching in mammalian cells is unknown. Here, we use single-particle tracking to visualize diffusion and chromatin binding of Cas9 in living cells. We show that three-dimensional diffusion dominates Cas9 searching in vivo, and off-target binding events are, on average, short-lived (<1 second). Searching is dependent on the local chromatin environment, with less sampling and slower movement within heterochromatin. These results reveal how the bacterial Cas9 protein interrogates mammalian genomes and navigates eukaryotic chromatin structure.
The final stage of cytokinesis is abscission, the cutting of the narrow membrane bridge connecting two daughter cells. The endosomal sorting complex required for transport (ESCRT) machinery is required for cytokinesis, and ESCRT-III has membrane scission activity in vitro, but the role of ESCRTs in abscission has been undefined. Here, we use structured illumination microscopy and time-lapse imaging to dissect the behavior of ESCRTs during abscission. Our data reveal that the ESCRT-I subunit tumor-susceptibility gene 101 (TSG101) and the ESCRT-III subunit charged multivesicular body protein 4b (CHMP4B) are sequentially recruited to the center of the intercellular bridge, forming a series of cortical rings. Late in cytokinesis, however, CHMP4B is acutely recruited to the narrow constriction site where abscission occurs. The ESCRT disassembly factor vacuolar protein sorting 4 (VPS4) follows CHMP4B to this site, and cell separation occurs immediately. That arrival of ESCRT-III and VPS4 correlates both spatially and temporally with the abscission event suggests a direct role for these proteins in cytokinetic membrane abscission.
We present a reconstruction of the dynamics of flight initiation from kinematic data extracted from high-speed video recordings of the fruit fly Drosophila melanogaster. The dichotomy observed in this insect’s flight initiation sequences, generated by the presence or absence of visual stimuli, clearly generates two contrasting sets of dynamics once the flies become airborne. By calculating reaction forces and moments using the unconstrained motion formulation for a rigid body, we assess the fly’s responses amidst these two dynamic patterns as a step towards refining our understanding of insect flight control.
Aphids are sap-feeding insects that host a range of bacterial endosymbionts including the obligate, nutritional mutualist Buchnera plus several bacteria that are not required for host survival. Among the latter, ’Candidatus Regiella insecticola’ and ’Candidatus Hamiltonella defensa’ are found in pea aphids and other hosts and have been shown to protect aphids from natural enemies. We have sequenced almost the entire genome of R. insecticola (2.07 Mbp) and compared it with the recently published genome of H. defensa (2.11 Mbp). Despite being sister species the two genomes are highly rearranged and the genomes only have \~{}55% of genes in common. The functions encoded by the shared genes imply that the bacteria have similar metabolic capabilities, including only two essential amino acid biosynthetic pathways and active uptake mechanisms for the remaining eight, and similar capacities for host cell toxicity and invasion (type 3 secretion systems and RTX toxins). These observations, combined with high sequence divergence of orthologues, strongly suggest an ancient divergence after establishment of a symbiotic lifestyle. The divergence in gene sets and in genome architecture implies a history of rampant recombination and gene inactivation and the ongoing integration of mobile DNA (insertion sequence elements, prophage and plasmids).
Cortical spreading depression is a slowly propagating wave of near-complete depolarization of brain cells followed by temporary suppression of neuronal activity. Accumulating evidence indicates that cortical spreading depression underlies the migraine aura and that similar waves promote tissue damage in stroke, trauma, and hemorrhage. Cortical spreading depression is characterized by neuronal swelling, profound elevation of extracellular potassium and glutamate, multiphasic blood flow changes, and drop in tissue oxygen tension. The slow speed of the cortical spreading depression wave implies that it is mediated by diffusion of a chemical substance, yet the identity of this substance and the pathway it follows are unknown. Intercellular spread between gap junction-coupled neurons or glial cells and interstitial diffusion of K(+) or glutamate have been proposed. Here we use extracellular direct current potential recordings, K(+)-sensitive microelectrodes, and 2-photon imaging with ultrasensitive Ca(2+) and glutamate fluorescent probes to elucidate the spatiotemporal dynamics of ionic shifts associated with the propagation of cortical spreading depression in the visual cortex of adult living mice. Our data argue against intercellular spread of Ca(2+) carrying the cortical spreading depression wavefront and are in favor of interstitial K(+) diffusion, rather than glutamate diffusion, as the leading event in cortical spreading depression.
The goal of our study was to examine whether the in vivo force-length behavior, work and elastic energy savings of distal muscle-tendon units in the legs of tammar wallabies (Macropus eugenii) change during level versus incline hopping. To address this question, we obtained measurements of muscle activation (via electromyography), fascicle strain (via sonomicrometry) and muscle-tendon force (via tendon buckles) from the lateral gastrocnemius (LG) and plantaris (PL) muscles of tammar wallabies trained to hop on a level and an inclined (10 degrees, 17.4% grade) treadmill at two speeds (3.3 m s(-1) and 4.2 m s(-1)). Similar patterns of muscle activation, force and fascicle strain were observed under both level and incline conditions. This also corresponded to similar patterns of limb timing and movement (duty factor, limb contact time and hopping frequency). During both level and incline hopping, the LG and PL exhibited patterns of fascicle stretch and shortening that yielded low levels of net fascicle strain [LG: level, -1.0+/-4.6% (mean +/- S.E.M.) vs incline, 0.6+/-4.5%; PL: level, 0.1+/-1.0% vs incline, 0.4+/-1.6%] and muscle work (LG: level, -8.4+/-8.4 J kg(-1) muscle vs incline, -6.8+/-7.5 J kg(-1) muscle; PL: level, -2.0+/-0.6 J kg(-1) muscle vs incline, -1.4+/-0.7 J kg(-1) muscle). Consequently, neither muscle significantly altered its contractile dynamics to do more work during incline hopping. Whereas electromyographic (EMG) phase, duration and intensity did not differ for the LG, the PL exhibited shorter but more intense periods of activation, together with reduced EMG phase (P<0.01), during incline versus level hopping. Our results indicate that design for spring-like tendon energy savings and economical muscle force generation is key for these two distal muscle-tendon units of the tammar wallaby, and the need to accommodate changes in work associated with level versus incline locomotion is achieved by more proximal muscles of the limb.
Spinal muscular atrophy (SMA) is a lethal neurodegenerative disease specifically affecting spinal motor neurons. SMA is caused by the homozygous deletion or mutation of the survival of motor neuron 1 (SMN1) gene. The SMN protein plays an essential role in the assembly of spliceosomal ribonucleoproteins. However, it is still unclear how low levels of the ubiquitously expressed SMN protein lead to the selective degeneration of motor neurons. An additional role for SMN in the regulation of the axonal transport of mRNA-binding proteins (mRBPs) and their target mRNAs has been proposed. Indeed, several mRBPs have been shown to interact with SMN, and the axonal levels of few mRNAs, such as the β-actin mRNA, are reduced in SMA motor neurons. In this study we have identified the β-actin mRNA-binding protein IMP1/ZBP1 as a novel SMN-interacting protein. Using a combination of biochemical assays and quantitative imaging techniques in primary motor neurons, we show that IMP1 associates with SMN in individual granules that are actively transported in motor neuron axons. Furthermore, we demonstrate that IMP1 axonal localization depends on SMN levels, and that SMN deficiency in SMA motor neurons leads to a dramatic reduction of IMP1 protein levels. In contrast, no difference in IMP1 protein levels was detected in whole brain lysates from SMA mice, further suggesting neuron specific roles of SMN in IMP1 expression and localization. Taken together, our data support a role for SMN in the regulation of mRNA localization and axonal transport through its interaction with mRBPs such as IMP1.