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132 Janelia Publications

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    12/23/20 | Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning.
    Unger EK, Keller JP, Altermatt M, Liang R, Matsui A, Dong C, Hon OJ, Yao Z, Sun J, Banala S, Flanigan ME, Jaffe DA, Hartanto S, Carlen J, Mizuno GO, Borden PM, Shivange AV, Cameron LP, Sinning S, Underhill SM, Olson DE, Amara SG, Temple Lang D, Rudnick G, Marvin JS, Lavis LD, Lester HA, Alvarez VA, Fisher AJ, Prescher JA, Kash TL, Yarov-Yarovoy V, Gradinaru V, Looger LL, Tian L
    Cell. 2020 Dec 23;183(7):1986-2002.e26. doi: 10.1016/j.cell.2020.11.040

    Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which has been hampered by our inability to monitor serotonin release and transport with high spatial and temporal resolution. We developed and applied a binding-pocket redesign strategy, guided by machine learning, to create a high-performance, soluble, fluorescent serotonin sensor (iSeroSnFR), enabling optical detection of millisecond-scale serotonin transients. We demonstrate that iSeroSnFR can be used to detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep/wake transitions. We also developed a robust assay of serotonin transporter function and modulation by drugs. We expect that both machine-learning-guided binding-pocket redesign and iSeroSnFR will have broad utility for the development of other sensors and in vitro and in vivo serotonin detection, respectively.

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    12/14/20 | Cis-regulatory variation in the shavenbaby gene underlies intraspecific phenotypic variation, mirroring interspecific divergence in the same trait.
    Soverna AF, Rodriguez NC, Korgaonkar A, Hasson E, Stern DL, Frankel N
    Evolution. 2020 Dec 14:. doi: 10.1111/evo.14142

    Despite considerable progress in recent decades in dissecting the genetic causes of natural morphological variation, there is limited understanding of how variation within species ultimately contributes to species differences. We have studied patterning of the non-sensory hairs, commonly known as "trichomes," on the dorsal cuticle of first-instar larvae of Drosophila. Most Drosophila species produce a dense lawn of dorsal trichomes, but a subset of these trichomes were lost in D. sechellia and D. ezoana due entirely to regulatory evolution of the shavenbaby (svb) gene. Here, we describe intraspecific variation in dorsal trichome patterns of first-instar larvae of D. virilis that is similar to the trichome pattern variation identified previously between species. We found that a single large effect QTL, which includes svb, explains most of the trichome number difference between two D. virilis strains and that svb expression correlates with the trichome difference between strains. This QTL does not explain the entire difference between strains, implying that additional loci contribute to variation in trichome numbers. Thus, the genetic architecture of intraspecific variation exhibits similarities and differences with interspecific variation that may reflect differences in long-term and short-term evolutionary processes.

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    12/14/20 | The connectome of the adult mushroom body provides insights into function.
    Li F, Lindsey JW, Marin EC, Otto N, Dreher M, Dempsey G, Stark I, Bates AS, Pleijzier MW, Schlegel P, Nern A, Takemura S, Eckstein N, Yang T, Francis A, Braun A, Parekh R, Costa M, Scheffer LK, Aso Y, Jefferis GS, Abbott LF, Litwin-Kumar A, Waddell S, Rubin GM
    eLife. 2020 Dec 14;9:. doi: 10.7554/eLife.62576

    Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory and activity regulation. Here we identify new components of the MB circuit in , including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.

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    12/01/20 | The structural basis of Rubisco phase separation in the pyrenoid.
    He S, Chou H, Matthies D, Wunder T, Meyer MT, Atkinson N, Martinez-Sanchez A, Jeffrey PD, Port SA, Patena W, He G, Chen VK, Hughson FM, McCormick AJ, Mueller-Cajar O, Engel BD, Yu Z, Jonikas MC
    Nature Plants. 2020 Dec 01;6(12):1480-1490. doi: 10.1038/s41477-020-00811-y

    Approximately one-third of global CO fixation occurs in a phase-separated algal organelle called the pyrenoid. The existing data suggest that the pyrenoid forms by the phase separation of the CO-fixing enzyme Rubisco with a linker protein; however, the molecular interactions underlying this phase separation remain unknown. Here we present the structural basis of the interactions between Rubisco and its intrinsically disordered linker protein Essential Pyrenoid Component 1 (EPYC1) in the model alga Chlamydomonas reinhardtii. We find that EPYC1 consists of five evenly spaced Rubisco-binding regions that share sequence similarity. Single-particle cryo-electron microscopy of these regions in complex with Rubisco indicates that each Rubisco holoenzyme has eight binding sites for EPYC1, one on each Rubisco small subunit. Interface mutations disrupt binding, phase separation and pyrenoid formation. Cryo-electron tomography supports a model in which EPYC1 and Rubisco form a codependent multivalent network of specific low-affinity bonds, giving the matrix liquid-like properties. Our results advance the structural and functional understanding of the phase separation underlying the pyrenoid, an organelle that plays a fundamental role in the global carbon cycle.

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    09/09/21 | A sequence-based method for predicting extant fold switchers that undergo α-helix ↔ β-strand transitions.
    Mishra S, Looger LL, Porter LL
    Biopolymers. 2021 Sep 09:e23471. doi: 10.1002/bip.23471

    Extant fold-switching proteins remodel their secondary structures and change their functions in response to cellular stimuli, regulating biological processes and affecting human health. Despite their biological importance, these proteins remain understudied. Predictive methods are needed to expedite the process of discovering and characterizing more of these shapeshifting proteins. Most previous approaches require a solved structure or all-atom simulations, greatly constraining their use. Here, we propose a high-throughput sequence-based method for predicting extant fold switchers that transition from α-helix in one conformation to β-strand in the other. This method leverages two previous observations: (a) α-helix ↔ β-strand prediction discrepancies from JPred4 are a robust predictor of fold switching, and (b) the fold-switching regions (FSRs) of some extant fold switchers have different secondary structure propensities when expressed by themselves (isolated FSRs) than when expressed within the context of their parent protein (contextualized FSRs). Combining these two observations, we ran JPred4 on 99-fold-switching proteins and found strong correspondence between predicted and experimentally observed α-helix ↔ β-strand discrepancies. To test the overall robustness of this finding, we randomly selected regions of proteins not expected to switch folds (single-fold proteins) and found significantly fewer predicted α-helix ↔ β-strand discrepancies. Combining these discrepancies with the overall percentage of predicted secondary structure, we developed a classifier to identify extant fold switchers (Matthews correlation coefficient of .71). Although this classifier had a high false-negative rate (7/17), its false-positive rate was very low (2/136), suggesting that it can be used to predict a subset of extant fold switchers from a multitude of available genomic sequences.

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    09/07/21 | Dissociable contributions of phasic dopamine activity to reward and prediction.
    Pan W, Coddington LT, Dudman JT
    Cell Reports. 2021 Sep 07;36(10):109684. doi: 10.1016/j.celrep.2021.109684

    Sensory cues that precede reward acquire predictive (expected value) and incentive (drive reward-seeking action) properties. Mesolimbic dopamine neurons' responses to sensory cues correlate with both expected value and reward-seeking action. This has led to the proposal that phasic dopamine responses may be sufficient to inform value-based decisions, elicit actions, and/or induce motivational states; however, causal tests are incomplete. Here, we show that direct dopamine neuron stimulation, both calibrated to physiological and greater intensities, at the time of reward can be sufficient to induce and maintain reward seeking (reinforcing) although replacement of a cue with stimulation is insufficient to induce reward seeking or act as an informative cue. Stimulation of descending cortical inputs, one synapse upstream, are sufficient for reinforcement and cues to future reward. Thus, physiological activation of mesolimbic dopamine neurons can be sufficient for reinforcing properties of reward without being sufficient for the predictive and incentive properties of cues.

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    09/02/21 | A framework for studying behavioral evolution by reconstructing ancestral repertoires.
    Hernández DG, Rivera C, Cande J, Zhou B, Stern D, Berman GJ
    eLife. 2021 Sep 02;10:. doi: 10.7554/eLife.61806

    Although different animal species often exhibit extensive variation in many behaviors, typically scientists examine one or a small number of behaviors in any single study. Here, we propose a new framework to simultaneously study the evolution of many behaviors. We measured the behavioral repertoire of individuals from six species of fruit flies using unsupervised techniques and identified all stereotyped movements exhibited by each species. We then fit a Generalized Linear Mixed Model to estimate the intra- and inter-species behavioral covariances, and, by using the known phylogenetic relationships among species, we estimated the (unobserved) behaviors exhibited by ancestral species. We found that much of intra-specific behavioral variation has a similar covariance structure to previously described long-time scale variation in an individual's behavior, suggesting that much of the measured variation between individuals of a single species in our assay reflects differences in the status of neural networks, rather than genetic or developmental differences between individuals. We then propose a method to identify groups of behaviors that appear to have evolved in a correlated manner, illustrating how sets of behaviors, rather than individual behaviors, likely evolved. Our approach provides a new framework for identifying co-evolving behaviors and may provide new opportunities to study the mechanistic basis of behavioral evolution.

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    09/02/21 | Classification and genetic targeting of cell types in the primary taste and premotor center of the adult brain.
    Sterne GR, Otsuna H, Dickson BJ, Scott K
    eLife. 2021 Sep 02;10:. doi: 10.7554/eLife.71679

    Neural circuits carry out complex computations that allow animals to evaluate food, select mates, move toward attractive stimuli, and move away from threats. In insects, the subesophageal zone (SEZ) is a brain region that receives gustatory, pheromonal, and mechanosensory inputs and contributes to the control of diverse behaviors, including feeding, grooming, and locomotion. Despite its importance in sensorimotor transformations, the study of SEZ circuits has been hindered by limited knowledge of the underlying diversity of SEZ neurons. Here, we generate a collection of split-GAL4 lines that provides precise genetic targeting of 138 different SEZ cell types in adult , comprising approximately one third of all SEZ neurons. We characterize the single cell anatomy of these neurons and find that they cluster by morphology into six supergroups that organize the SEZ into discrete anatomical domains. We find that the majority of local SEZ interneurons are not classically polarized, suggesting rich local processing, whereas SEZ projection neurons tend to be classically polarized, conveying information to a limited number of higher brain regions. This study provides insight into the anatomical organization of the SEZ and generates resources that will facilitate further study of SEZ neurons and their contributions to sensory processing and behavior.

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    09/02/21 | Electrode pooling can boost the yield of extracellular recordings with switchable silicon probes.
    Lee KH, Ni Y, Colonell J, Karsh B, Putzeys J, Pachitariu M, Harris TD, Meister M
    Nature Communications. 2021 Sep 02;12(1):5245. doi: 10.1038/s41467-021-25443-4

    State-of-the-art silicon probes for electrical recording from neurons have thousands of recording sites. However, due to volume limitations there are typically many fewer wires carrying signals off the probe, which restricts the number of channels that can be recorded simultaneously. To overcome this fundamental constraint, we propose a method called electrode pooling that uses a single wire to serve many recording sites through a set of controllable switches. Here we present the framework behind this method and an experimental strategy to support it. We then demonstrate its feasibility by implementing electrode pooling on the Neuropixels 1.0 electrode array and characterizing its effect on signal and noise. Finally we use simulations to explore the conditions under which electrode pooling saves wires without compromising the content of the recordings. We make recommendations on the design of future devices to take advantage of this strategy.

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    09/02/21 | Spatiotemporal coordination of transcription preinitiation complex assembly in live cells.
    Nguyen VQ, Ranjan A, Liu S, Tang X, Ling YH, Wisniewski J, Mizuguchi G, Li KY, Jou V, Zheng Q, Lavis LD, Lionnet T, Wu C
    Molecular Cell. 2021 Sep 02;81(17):3560-3575. doi: 10.1016/j.molcel.2021.07.022

    Transcription initiation by RNA polymerase II (RNA Pol II) requires preinitiation complex (PIC) assembly at gene promoters. In the dynamic nucleus, where thousands of promoters are broadly distributed in chromatin, it is unclear how multiple individual components converge on any target to establish the PIC. Here we use live-cell, single-molecule tracking in S. cerevisiae to visualize constrained exploration of the nucleoplasm by PIC components and Mediator's key role in guiding this process. On chromatin, TFIID/TATA-binding protein (TBP), Mediator, and RNA Pol II instruct assembly of a short-lived PIC, which occurs infrequently but efficiently within a few seconds on average. Moreover, PIC exclusion by nucleosome encroachment underscores regulated promoter accessibility by chromatin remodeling. Thus, coordinated nuclear exploration and recruitment to accessible targets underlies dynamic PIC establishment in yeast. Our study provides a global spatiotemporal model for transcription initiation in live cells.

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