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2224 Publications

Showing 41-50 of 2224 results
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    11/10/22 | Robotic Multi-Probe-Single-Actuator Inchworm Neural Microdrive
    Smith R, Kolb I, Tanaka S, Lee A, Harris T, Barbic M
    eLife. 2022 Nov 10:. doi: 10.7554/eLife.71876

    Electrophysiology is one of the major experimental techniques used in neuroscience. The favorable spatial and temporal resolution as well as the increasingly larger site counts of brain recording electrodes contribute to the popularity and importance of electrophysiology in neuroscience. Such electrodes are typically mechanically placed in the brain to perform acute or chronic freely moving animal measurements. The micro positioners currently used for such tasks employ a single translator per independent probe being placed into the targeted brain region, leading to significant size and weight restrictions. To overcome this limitation, we have developed a miniature robotic multi-probe neural microdrive that utilizes novel phase-change-material-filled resistive heater micro-grippers. The microscopic dimensions, gentle gripping action, independent electronic actuation control, and high packing density of the grippers allow for micrometer-precision independent positioning of multiple arbitrarily shaped parallel neural electrodes with only a single piezo actuator in an inchworm motor configuration. This multi-probe-single-actuator design allows for significant size and weight reduction, as well as remote control and potential automation of the microdrive. We demonstrate accurate placement of multiple independent recording electrodes into the CA1 region of the rat hippocampus in vivo in acute and chronic settings. Thus, our robotic neural microdrive technology is applicable towards basic neuroscience and clinical studies, as well as other multi-probe or multi-sensor micro-positioning applications.

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    11/08/22 | Robust cell identity specifications through transitions in the collective state of growing developmental systems
    Stanoev A, Koseska A
    Current Opinion in Systems Biology. 2022 Nov 08;31:100437. doi: 10.1016/j.coisb.2022.100437

    Mammalian development is characterized with transitions from homogeneous populations of precursor to heterogeneous population of specified cells. We review here the main dynamical mechanisms through which such transitions are conceptualized, and discuss that the differentiation timing, robust cell-type proportions and recovery upon perturbation are emergent property of proliferating and communicating cell populations. We argue that studying developmental systems using transitions in collective system states is necessary to describe observed experimental features, and propose additionally the basis of a novel analytical method to deduce the relationship between single-cell dynamics and the collective, symmetry-broken states in cellular populations.

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    11/07/22 | Cellpose 2.0: how to train your own model.
    Pachitariu M, Stringer C
    Nature Methods. 2022 Nov 07;19(12):1634-41. doi: 10.1038/s41592-022-01663-4

    Pretrained neural network models for biological segmentation can provide good out-of-the-box results for many image types. However, such models do not allow users to adapt the segmentation style to their specific needs and can perform suboptimally for test images that are very different from the training images. Here we introduce Cellpose 2.0, a new package that includes an ensemble of diverse pretrained models as well as a human-in-the-loop pipeline for rapid prototyping of new custom models. We show that models pretrained on the Cellpose dataset can be fine-tuned with only 500-1,000 user-annotated regions of interest (ROI) to perform nearly as well as models trained on entire datasets with up to 200,000 ROI. A human-in-the-loop approach further reduced the required user annotation to 100-200 ROI, while maintaining high-quality segmentations. We provide software tools such as an annotation graphical user interface, a model zoo and a human-in-the-loop pipeline to facilitate the adoption of Cellpose 2.0.

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    Looger Lab
    11/07/22 | Chemically stable fluorescent proteins for advanced microscopy.
    Campbell BC, Paez-Segala MG, Looger LL, Petsko GA, Liu CF
    Nature Methods. 2022 Nov 07:. doi: 10.1038/s41592-022-01660-7

    We report the rational engineering of a remarkably stable yellow fluorescent protein (YFP), 'hyperfolder YFP' (hfYFP), that withstands chaotropic conditions that denature most biological structures within seconds, including superfolder green fluorescent protein (GFP). hfYFP contains no cysteines, is chloride insensitive and tolerates aldehyde and osmium tetroxide fixation better than common fluorescent proteins, enabling its use in expansion and electron microscopies. We solved crystal structures of hfYFP (to 1.7-Å resolution), a monomeric variant, monomeric hyperfolder YFP (1.6 Å) and an mGreenLantern mutant (1.2 Å), and then rationally engineered highly stable 405-nm-excitable GFPs, large Stokes shift (LSS) monomeric GFP (LSSmGFP) and LSSA12 from these structures. Lastly, we directly exploited the chemical stability of hfYFP and LSSmGFP by devising a fluorescence-assisted protein purification strategy enabling all steps of denaturing affinity chromatography to be visualized using ultraviolet or blue light. hfYFP and LSSmGFP represent a new generation of robustly stable fluorescent proteins developed for advanced biotechnological applications.

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    11/04/22 | Facemap: a framework for modeling neural activity based on orofacial tracking
    Atika Syeda , Lin Zhong , Renee Tung , Will Long , Marius Pachitariu , Carsen Stringer
    bioRxiv. 2022 Nov 04:. doi: 10.1101/2022.11.03.515121

    Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand the nature and function of these signals, we need better computational models to characterize the behaviors and relate them to neural activity. Here we developed Facemap, a framework consisting of a keypoint tracking algorithm and a deep neural network encoder for predicting neural activity. We used the Facemap keypoints as input for the deep neural network to predict the activity of ∼50,000 simultaneously-recorded neurons and in visual cortex we doubled the amount of explained variance compared to previous methods. Our keypoint tracking algorithm was more accurate than existing pose estimation tools, while the inference speed was several times faster, making it a powerful tool for closed-loop behavioral experiments. The Facemap tracker was easy to adapt to data from new labs, requiring as few as 10 annotated frames for near-optimal performance. We used Facemap to find that the neuronal activity clusters which were highly driven by behaviors were more spatially spread-out across cortex. We also found that the deep keypoint features inferred by the model had time-asymmetrical state dynamics that were not apparent in the raw keypoint data. In summary, Facemap provides a stepping stone towards understanding the function of the brainwide neural signals and their relation to behavior.

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    11/02/22 | Cap-dependent translation initiation monitored in living cells.
    Gandin V, English BP, Freeman M, Leroux L, Preibisch S, Walpita D, Jaramillo M, Singer RH
    Nature Communications. 2022 Nov 02;13(1):6558. doi: 10.1038/s41467-022-34052-8

    mRNA translation is tightly regulated to preserve cellular homeostasis. Despite extensive biochemical, genetic, and structural studies, a detailed understanding of mRNA translation regulation is lacking. Imaging methodologies able to resolve the binding dynamics of translation factors at single-cell and single-mRNA resolution were necessary to fully elucidate regulation of this paramount process. Here live-cell spectroscopy and single-particle tracking were combined to interrogate the binding dynamics of endogenous initiation factors to the 5'cap. The diffusion of initiation factors (IFs) changed markedly upon their association with mRNA. Quantifying their diffusion characteristics revealed the sequence of IFs assembly and disassembly in cell lines and the clustering of translation in neurons. This approach revealed translation regulation at high spatial and temporal resolution that can be applied to the formation of any endogenous complex that results in a measurable shift in diffusion.

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    Sternson Lab
    11/02/22 | Characterization of Ultrapotent Chemogenetic Ligands for Research Applications in Nonhuman Primates.
    Raper J, Eldridge MA, Sternson SM, Shim JY, Fomani GP, Richmond BJ, Wichmann T, Galvan A
    ACS Chemical Neuroscience. 2022 Nov 02;13(21):3118-3125. doi: 10.1021/acschemneuro.2c00525

    Chemogenetics is a technique for obtaining selective pharmacological control over a cell population by expressing an engineered receptor that is selectively activated by an exogenously administered ligand. A promising approach for neuronal modulation involves the use of "Pharmacologically Selective Actuator Modules" (PSAMs); these chemogenetic receptors are selectively activated by ultrapotent "Pharmacologically Selective Effector Molecules" (uPSEMs). To extend the use of PSAM/PSEMs to studies in nonhuman primates, it is necessary to thoroughly characterize the efficacy and safety of these tools. We describe the time course and brain penetrance in rhesus monkeys of two compounds with promising binding specificity and efficacy profiles in studies, uPSEM792 and uPSEM817, after systemic administration. Rhesus monkeys received subcutaneous (s.c.) or intravenous (i.v.) administration of uPSEM817 (0.064 mg/kg) or uPSEM792 (0.87 mg/kg), and plasma and cerebrospinal fluid samples were collected over 48 h. Both compounds exhibited good brain penetrance, relatively slow washout, and negligible conversion to potential metabolites─varenicline or hydroxyvarenicline. In addition, we found that neither of these uPSEMs significantly altered the heart rate or sleep. Our results indicate that both compounds are suitable candidates for neuroscience studies using PSAMs in nonhuman primates.

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    10/28/22 | High-throughput automated methods for classical and operant conditioning of larvae.
    Croteau-Chonka EC, Clayton MS, Venkatasubramanian L, Harris SN, Jones BM, Narayan L, Winding M, Masson J, Zlatic M, Klein KT
    eLife. 2022 Oct 28;11:. doi: 10.7554/eLife.70015

    Learning which stimuli (classical conditioning) or which actions (operant conditioning) predict rewards or punishments can improve chances of survival. However, the circuit mechanisms that underlie distinct types of associative learning are still not fully understood. Automated, high-throughput paradigms for studying different types of associative learning, combined with manipulation of specific neurons in freely behaving animals, can help advance this field. The Drosophila melanogaster larva is a tractable model system for studying the circuit basis of behaviour, but many forms of associative learning have not yet been demonstrated in this animal. Here, we developed a high-throughput (i. e. multi-larva) training system that combines real-time behaviour detection of freely moving larvae with targeted opto- and thermogenetic stimulation of tracked animals. Both stimuli are controlled in either open- or closed-loop, and delivered with high temporal and spatial precision. Using this tracker, we show for the first time that Drosophila larvae can perform classical conditioning with no overlap between sensory stimuli (i. e. trace conditioning). We also demonstrate that larvae are capable of operant conditioning by inducing a bend direction preference through optogenetic activation of reward-encoding serotonergic neurons. Our results extend the known associative learning capacities of Drosophila larvae. Our automated training rig will facilitate the study of many different forms of associative learning and the identification of the neural circuits that underpin them.

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    10/27/22 | Spatial organization of the 3D genome encodes gene co-expression programs in single cells
    Peng Dong , Shu Zhang , Liangqi Xie , Lihua Wang , Andrew L. Lemire , Arthur D. Lander , Howard Y. Chang , Zhe J. Liu
    bioRxiv. 2022 Oct 27:. doi: 10.1101/2022.10.26.513917

    Deconstructing the mechanism by which the 3D genome encodes genetic information to generate diverse cell types during animal development is a major challenge in biology. The contrast between the elimination of chromatin loops and domains upon Cohesin loss and the lack of downstream gene expression changes at the cell population level instigates intense debates regarding the structure-function relationship between genome organization and gene regulation. Here, by analyzing single cells after acute Cohesin removal with sequencing and spatial genome imaging techniques, we discover that, instead of dictating population-wide gene expression levels, 3D genome topology mediated by Cohesin safeguards long-range gene co-expression correlations in single cells. Notably, Cohesin loss induces gene co-activation and chromatin co-opening between active domains in cis up to tens of megabase apart, far beyond the typical length scale of enhancer-promoter communication. In addition, Cohesin separates Mediator protein hubs, prevents active genes in cis from localizing into shared hubs and blocks intersegment transfer of diverse transcriptional regulators. Together, these results support that spatial organization of the 3D genome orchestrates dynamic long-range gene and chromatin co-regulation in single living cells.

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    10/26/22 | Muscles that move the retina augment compound eye vision in Drosophila.
    Fenk LM, Avritzer SC, Weisman JL, Nair A, Randt LD, Mohren TL, Siwanowicz I, Maimon G
    Nature. 2022 Oct 26:. doi: 10.1038/s41586-022-05317-5

    Most animals have compound eyes, with tens to thousands of lenses attached rigidly to the exoskeleton. A natural assumption is that all of these species must resort to moving either their head or their body to actively change their visual input. However, classic anatomy has revealed that flies have muscles poised to move their retinas under the stable lenses of each compound eye. Here we show that Drosophila use their retinal muscles to smoothly track visual motion, which helps to stabilize the retinal image, and also to perform small saccades when viewing a stationary scene. We show that when the retina moves, visual receptive fields shift accordingly, and that even the smallest retinal saccades activate visual neurons. Using a head-fixed behavioural paradigm, we find that Drosophila perform binocular, vergence movements of their retinas-which could enhance depth perception-when crossing gaps, and impairing the physiology of retinal motor neurons alters gap-crossing trajectories during free behaviour. That flies evolved an ability to actuate their retinas suggests that moving the eye independently of the head is broadly paramount for animals. The similarities of smooth and saccadic movements of the Drosophila retina and the vertebrate eye highlight a notable example of convergent evolution.

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