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 (72) 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 (59) 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 (145) 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
3924 Publications
Showing 3571-3580 of 3924 resultsGlucose is a primary source of energy for human cells. Glucose transporters form specialized membrane channels for the transport of sugars into and out of cells. Galactose permease (GalP) is the closest bacterial homolog of human facilitated glucose transporters. Here, we report the functional reconstitution and 2D crystallization of GalP. Single particle electron microscopy analysis of purified GalP shows that the protein assembles as an oligomer with three distinct densities. Reconstitution assays yield 2D GalP crystals that exhibit a hexagonal array having p3 symmetry. The projection structure of GalP at 18 A resolution shows that the protein is trimeric. Each monomer in the trimer forms its own channel, but an additional cavity (10 approximately 15 A in diameter) is apparent at the 3-fold axis of the oligomer. We show that the crystalline GalP is able to selectively bind substrate, suggesting that the trimeric form is biologically active.
A key regulatory gene in metamorphosing (holometabolous) insect life histories is the transcription factor broad (br), which specifies pupal development. To determine the role of br in a direct-developing (hemimetabolous) insect that lacks a pupal stage, we cloned br from the milkweed bug, Oncopeltus fasciatus (Of’br). We find that, unlike metamorphosing insects, in which br expression is restricted to the larval-pupal transition, Of’br mRNA is expressed during embryonic development and is maintained at each nymphal molt but then disappears at the molt to the adult. Induction of a supernumerary nymphal stage with a juvenile hormone (JH) mimic prevented the disappearance of br mRNA. In contrast, induction of a precocious adult molt by application of precocene II to third-stage nymphs caused a loss of br mRNA at the precocious adult molt. Thus, JH is necessary to maintain br expression during the nymphal stages. Injection of Of’br dsRNA into either early third- or fourth-stage nymphs caused a repetition of stage-specific pigmentation patterns and prevented the normal anisometric growth of the wing pads without affecting isometric growth or molting. Therefore, br is necessary for the mutable (heteromorphic) changes that occur during hemimetabolous development. Our results suggest that metamorphosis in insects arose as expression of br, which conveys competence for change, became restricted to one postembryonic instar. After this shift in br expression, the progressive changes that occur within the nymphal series in basal insects became compressed to the one short period of morphogenesis seen in the larva-to-pupa transition of holometabolous insects.
The PV2 (Celio 1990), a cluster of parvalbumin-positive neurons located in the ventromedial region of the distal periaqueductal gray (PAG) has not been previously described as its own entity, leading us to study its extent, connections, and gene expression. It is an oval, bilateral, elongated cluster composed of approximately 475 parvalbumin-expressing neurons in a single mouse hemisphere. In its anterior portion it impinges upon the paratrochlear nucleus (Par4) and in its distal portion it is harbored in the posterodorsal raphe nucleus (PDR). It is known to receive inputs from the orbitofrontal cortex and from the parvafox nucleus in the ventrolateral hypothalamus. Using anterograde tracing methods in parvalbumin-Cre mice, the main projections of the PV2 cluster innervate the supraoculomotor periaqueductal gray (Su3) of the PAG, the parvafox nucleus of the lateral hypothalamus, the gemini nuclei of the posterior hypothalamus, the septal regions, and the diagonal band in the forebrain, as well as various nuclei within the reticular formation in the midbrain and brainstem. Within the brainstem, projections were discrete, but involved areas implicated in autonomic control. The PV2 cluster expressed various peptides and receptors, including the receptor for Adcyap1, a peptide secreted by one of its main afferences, namely, the parvafox nucleus. The expression of GAD1 and GAD2 in the region of the PV2, the presence of Vgat-1 in a subpopulation of PV2-neurons as well as the coexistence of GAD67 immunoreactivity with parvalbumin in terminal endings indicates the inhibitory nature of a subpopulation of PV2-neurons. The PV2 cluster may be part of a feedback controlling the activity of the hypothalamic parvafox and the Su3 nuclei in the periaqueductal gray.
Rational protein design is an emerging approach for testing general theories of structure and function. The ability to manipulate function rationally also offers the possibility of creating new proteins of biotechnological value. Here we use the design approach to test the current understanding of the structural principles of allosteric interactions in proteins and demonstrate how a simple allosteric system can form the basis for the construction of a generic biosensor molecular engineering system. We have identified regions in Escherichia coli maltose-binding protein that are predicted to be allosterically linked to its maltose-binding site. Environmentally sensitive fluorophores were covalently attached to unique thiols introduced by cysteine mutations at specific sites within these regions. The fluorescence of such conjugates changes cooperatively with respect to maltose binding, as predicted. Spatial separation of the binding site and reporter groups allows the intrinsic properties of each to be manipulated independently. Provided allosteric linkage is maintained, ligand binding can therefore be altered without affecting transduction of the binding event by fluorescence. To demonstrate applicability to biosensor technology, we have introduced a series of point mutations in the maltose-binding site that lower the affinity of the protein for its ligand. These mutant proteins have been combined in a composite biosensor capable of measuring substrate concentration within 5% accuracy over a concentration range spanning five orders of magnitude.
The emerging picture of taste coding at the periphery is one of elegant simplicity. Contrary to what was generally believed, it is now clear that distinct cell types expressing unique receptors are tuned to detect each of the five basic tastes: sweet, sour, bitter, salty and umami. Importantly, receptor cells for each taste quality function as dedicated sensors wired to elicit stereotypic responses.
The sense of taste provides animals with valuable information about the nature and quality of food. Bitter taste detection functions as an important sensory input to warn against the ingestion of toxic and noxious substances. T2Rs are a family of approximately 30 highly divergent G-protein-coupled receptors (GPCRs) that are selectively expressed in the tongue and palate epithelium and are implicated in bitter taste sensing. Here we demonstrate, using a combination of genetic, behavioural and physiological studies, that T2R receptors are necessary and sufficient for the detection and perception of bitter compounds, and show that differences in T2Rs between species (human and mouse) can determine the selectivity of bitter taste responses. In addition, we show that mice engineered to express a bitter taste receptor in ’sweet cells’ become strongly attracted to its cognate bitter tastants, whereas expression of the same receptor (or even a novel GPCR) in T2R-expressing cells resulted in mice that are averse to the respective compounds. Together these results illustrate the fundamental principle of bitter taste coding at the periphery: dedicated cells act as broadly tuned bitter sensors that are wired to mediate behavioural aversion.
Sweet and umami (the taste of monosodium glutamate) are the main attractive taste modalities in humans. T1Rs are candidate mammalian taste receptors that combine to assemble two heteromeric G-protein-coupled receptor complexes: T1R1+3, an umami sensor, and T1R2+3, a sweet receptor. We now report the behavioral and physiological characterization of T1R1, T1R2, and T1R3 knockout mice. We demonstrate that sweet and umami taste are strictly dependent on T1R-receptors, and show that selective elimination of T1R-subunits differentially abolishes detection and perception of these two taste modalities. To examine the basis of sweet tastant recognition and coding, we engineered animals expressing either the human T1R2-receptor (hT1R2), or a modified opioid-receptor (RASSL) in sweet cells. Expression of hT1R2 in mice generates animals with humanized sweet taste preferences, while expression of RASSL drives strong attraction to a synthetic opiate, demonstrating that sweet cells trigger dedicated behavioral outputs, but their tastant selectivity is determined by the nature of the receptors.
In Drosophila, dosage compensation occurs by increasing the transcription of the single male X chromosome. Four trans-acting factors encoded by the male-specific lethal genes are required for this process. Dosage compensation is restricted to males by the splicing regulator Sex-lethal, which functions to prevent the production of the MSL-2 protein in females by an unknown mechanism. In this report, we provide evidence that Sex-lethal acts synergistically through sequences in both the 5' and 3' untranslated regions of MSL-2 to mediate repression. We also provide evidence that the repression of MSL-2 is directly regulated by Sex-lethal at the level of translation.
The expression of GABA is restricted to the progeny of only six of the 24 identified postembryonic lineages in the thoracic ganglia of the tobacco hornworm, Manduca sexta (Witten and Truman, 1991). It is colocalized with a peptide similar to molluscan small cardioactive peptide B (SCPB) in some of the neurons in two of the six lineages. By combining chemical ablation of the neuroblasts at specific larval stages with birth dating of the progeny, we tested whether the expression of GABA and the SCPB-like peptide was determined strictly by cell lineage or involved cellular interactions among the members of individual clonal groups. Chemical ablation of the six specific neuroblasts that produced the GABA-positive neurons (E, K, M, N, T, and X) or of the two that produced the GABA + SCPB-like-immunoreactive neurons (K, M) prior to the generation of their lineages resulted in the loss of these immunoreactivities. These results suggest that regulation between lineages did not occur. Ablation of the K and M neuroblasts after they had produced a small portion of their lineages had no effect on the expression of GABA, but did affect the pattern of the SCPB-like immunoreactivity. Combining birth-dating techniques with transmitter immunocytochemistry revealed that it was the position in the birth order and not interactions among the clonally related neurons that influenced the peptidergic phenotype. These results suggest that cell lineage is involved in establishing the GABAergic phenotype and that both cell lineage and birth order influence the determination of the peptidergic phenotype.(ABSTRACT TRUNCATED AT 250 WORDS)
Drosophila melanogaster plays an important role in molecular, genetic, and genomic studies of heredity, development, metabolism, behavior, and human disease. The initial reference genome sequence reported more than a decade ago had a profound impact on progress in Drosophila research, and improving the accuracy and completeness of this sequence continues to be important to further progress. We previously described improvement of the 117-Mb sequence in the euchromatic portion of the genome and 21 Mb in the heterochromatic portion, using a whole-genome shotgun assembly, BAC physical mapping, and clone-based finishing. Here, we report an improved reference sequence of the single-copy and middle-repetitive regions of the genome, produced using cytogenetic mapping to mitotic and polytene chromosomes, clone-based finishing and BAC fingerprint verification, ordering of scaffolds by alignment to cDNA sequences, incorporation of other map and sequence data, and validation by whole-genome optical restriction mapping. These data substantially improve the accuracy and completeness of the reference sequence and the order and orientation of sequence scaffolds into chromosome arm assemblies. Representation of the Y chromosome and other heterochromatic regions is particularly improved. The new 143.9-Mb reference sequence, designated Release 6, effectively exhausts clone-based technologies for mapping and sequencing. Highly repeat-rich regions, including large satellite blocks and functional elements such as the ribosomal RNA genes and the centromeres, are largely inaccessible to current sequencing and assembly methods and remain poorly represented. Further significant improvements will require sequencing technologies that do not depend on molecular cloning and that produce very long reads.