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2454 Janelia Publications

Showing 1-10 of 2454 results
04/18/24 | Connectome-driven neural inventory of a complete visual system
Aljoscha Nern , Frank Loesche , Shin-ya Takemura , Laura E Burnett , Marisa Dreher , Eyal Gruntman , Judith Hoeller , Gary B Huang , Michal Januszewski , Nathan C Klapoetke , Sanna Koskela , Kit D Longden , Zhiyuan Lu , Stephan Preibisch , Wei Qiu , Edward M Rogers , Pavithraa Seenivasan , Arthur Zhao , John Bogovic , Brandon S Canino , Jody Clements , Michael Cook , Samantha Finley-May , Miriam A Flynn , Imran Hameed , Kenneth J Hayworth , Gary Patrick Hopkins , Philip M Hubbard , William T Katz , Julie Kovalyak , Shirley A Lauchie , Meghan Leonard , Alanna Lohff , Charli A Maldonado , Caroline Mooney , Nneoma Okeoma , Donald J Olbris , Christopher Ordish , Tyler Paterson , Emily M Phillips , Tobias Pietzsch , Jennifer Rivas Salinas , Patricia K Rivlin , Ashley L Scott , Louis A Scuderi , Satoko Takemura , Iris Talebi , Alexander Thomson , Eric T Trautman , Lowell Umayam , Claire Walsh , John J Walsh , C Shan Xu , Emily A Yakal , Tansy Yang , Ting Zhao , Jan Funke , Reed George , Harald F Hess , Gregory S X E Jefferis , Christopher Knecht , Wyatt Korff , Stephen M Plaza , Sandro Romani , Stephan Saalfeld , Louis K Scheffer , Stuart Berg , Gerald M Rubin , Michael B Reiser
bioRxiv. 2024 Apr 18:. doi: 10.1101/2024.04.16.589741

Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brain’s volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the fly’s visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the 53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila, a foundation for a deeper understanding of sensory processing.

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03/25/24 | Amino acid transporter SLC7A5 regulates cell proliferation and secretary cell differentiation and distribution in the mouse intestine
Bao L, Fu L, Su Y, Chen Z, Peng Z, Sun L, Gonzalez FJ, Wu C, Zhang H, Shi B, Shi Y
Int J Biol Sci. 2024 Mar 25;20(6):2187-2201. doi: 10.7150/ijbs.94297

The intestine is critical for not only processing nutrients but also protecting the organism from the environment. These functions are mainly carried out by the epithelium, which is constantly being self-renewed. Many genes and pathways can influence intestinal epithelial cell proliferation. Among them is mTORC1, whose activation increases cell proliferation. Here, we report the first intestinal epithelial cell (IEC)-specific knockout () of an amino acid transporter capable of activating mTORC1. We show that the transporter, SLC7A5, is highly expressed in mouse intestinal crypt and reduces mTORC1 signaling. Surprisingly, adult intestinal crypts have increased cell proliferation but reduced mature Paneth cells. Goblet cells, the other major secretory cell type in the small intestine, are increased in the crypts but reduced in the villi. Analyses with scRNA-seq and electron microscopy have revealed dedifferentiation of Paneth cells in mice, leading to markedly reduced secretory granules with little effect on Paneth cell number. Thus, SLC7A5 likely regulates secretory cell differentiation to affect stem cell niche and indirectly regulate cell proliferation.

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04/12/24 | Leptin Activated Hypothalamic BNC2 Neurons Acutely Suppress Food Intake
Han L. Tan , Luping Yin , Yuqi Tan , Jessica Ivanov , Kaja Plucinska , Anoj Ilanges , Brian R. Herb , Putianqi Wang , Christin Kosse , Paul Cohen , Dayu Lin , Jeffrey M. Friedman
bioRxiv. 12 Apr 2024:. doi: 10.1101/2024.01.25.577315

Leptin is an adipose tissue hormone that maintains homeostatic control of adipose tissue mass by regulating the activity of specific neural populations controlling appetite and metabolism1. Leptin regulates food intake by inhibiting orexigenic agouti-related protein (AGRP) neurons and activating anorexigenic pro-opiomelanocortin (POMC) neurons2. However, while AGRP neurons regulate food intake on a rapid time scale, acute activation of POMC neurons has only a minimal effect3–5. This has raised the possibility that there is a heretofore unidentified leptin-regulated neural population that suppresses appetite on a rapid time scale. Here, we report the discovery of a novel population of leptin-target neurons expressing basonuclin 2 (Bnc2) that acutely suppress appetite by directly inhibiting AGRP neurons. Opposite to the effect of AGRP activation, BNC2 neuronal activation elicited a place preference indicative of positive valence in hungry but not fed mice. The activity of BNC2 neurons is finely tuned by leptin, sensory food cues, and nutritional status. Finally, deleting leptin receptors in BNC2 neurons caused marked hyperphagia and obesity, similar to that observed in a leptin receptor knockout in AGRP neurons. These data indicate that BNC2-expressing neurons are a key component of the neural circuit that maintains energy balance, thus filling an important gap in our understanding of the regulation of food intake and leptin action.

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04/17/24 | Prior Expectations in Visual Speed Perception Predict Encoding Characteristics of Neurons in Area MT
Zhang L, Stocker AA
The Journal of Neuroscience. Jun-04-2022;42(14):2951 - 2962. doi: 10.1523/JNEUROSCI.1920-21.2022
04/17/24 | Prior Expectations in Visual Speed Perception Predict Encoding Characteristics of Neurons in Area MT
Zhang L, Stocker AA
The Journal of Neuroscience. Jun-04-2022;42(14):2951 - 2962. doi: 10.1523/JNEUROSCI.1920-21.2022
04/11/24 | A blue-shifted genetically encoded Ca2+ indicator with enhanced two-photon absorption
Abhi Aggarwal , Smrithi Sunil , Imane Bendifallah , Michael Moon , Mikhail Drobizhev , Landon Zarowny , Jihong Zheng , Sheng-Yi Wu , Alexander W. Lohman , Alison G. Tebo , Valentina Emiliani , Kaspar Podgorski , Yi Shen , Robert E. Campbell
bioRxiv. 2024 Apr 11:. doi:

Significance: Genetically encoded calcium ion (Ca2+) indicators (GECIs) are powerful tools for monitoring intracellular Ca2+ concentration changes in living cells and model organisms. In particular, GECIs have found particular utility for monitoring the transient increase of Ca2+concentration that is associated with the neuronal action potential. However, the palette of highly optimized GECIs for imaging of neuronal activity remains relatively limited. Expanding the selection of available GECIs to include new colors and distinct photophysical properties could create new opportunities for in vitro and in vivo fluorescence imaging of neuronal activity. In particular, blue-shifted variants of GECIs are expected to have enhanced two-photon brightness, which would facilitate multiphoton microscopy.

Aim: We describe the development and applications of T-GECO1-a high-performance blue-shifted GECI based on the Clavularia sp.-derived mTFP1.

Approach: We use protein engineering and extensive directed evolution to develop T-GECO1. We characterize the purified protein and assess its performance in vitro using one-photon excitation in cultured rat hippocampal neurons, in vivo using one-photon excitation fiber photometry in mice, and ex vivo using two-photon Ca2+ imaging in hippocampal slices.

Results: The Ca2+-bound state of T-GECO1 has an excitation peak maximum of 468 nm, an emission peak maximum of 500 nm, an extinction coefficient of 49,300M−1cm−1, a quantum yield of 0.83, and two-photon brightness approximately double that of EGFP. The Ca2+-dependent fluorescence increase is 15-fold, and the apparent Kd for Ca2+ is 82 nM. With two-photon excitation conditions at 850 nm, T-GECO1 consistently enabled the detection of action potentials with higher signal-to-noise (SNR) than a late generation GCaMP variant.

Conclusions: T-GECO1 is a high-performance blue-shifted GECI that, under two-photon excitation conditions, provides advantages relative to late generation GCaMP variants.

Keywords: blue-shifted fluorescence; genetically encoded calcium ion indicator; neuronal activity imaging; protein engineering; two-photon excitation.

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04/06/24 | A tunable and versatile chemogenetic near infrared fluorescent reporter
Lina El Hajji , Benjamin Bunel , Octave Joliot , Chenge Li , Alison G. Tebo , Christine Rampon , Michel Volovitch , Evelyne Fischer , Nicolas Pietrancosta , Franck Perez , Xavier Morin , Sophie Vriz , Arnaud Gautier
bioRxiv. 2024 Apr 6:. doi: 10.1101/2024.04.05.588310

Near-infrared (NIR) fluorescent reporters provide additional colors for highly multiplexed imaging of cells and organisms, and enable imaging with less toxic light and higher contrast and depth. Here, we present the engineering of nirFAST, a small tunable chemogenetic NIR fluorescent reporter that is brighter than top-performing NIR fluorescent proteins in cultured mammalian cells. nirFAST is a small genetically encoded protein of 14 kDa that binds and stabilizes the fluorescent state of synthetic, highly cell-permeant, fluorogenic chromophores (so-called fluorogens) that are otherwise dark when free. Engineered to emit NIR light, nirFAST can also emit far-red or red lights through change of chromophore. nirFAST allows the imaging of proteins in live cultured mammalian cells, chicken embryo tissues and zebrafish larvae. Its near infrared fluorescence provides an additional color for high spectral multiplexing. We showed that nirFAST is well-suited for stimulated emission depletion (STED) nanoscopy, allowing the efficient imaging of proteins with subdiffraction resolution in live cells. nirFAST enabled the design of a chemogenetic green-NIR fluorescent ubiquitination-based cell cycle indicator (FUCCI) for the monitoring of the different phases of the cell cycle. Finally, bisection of nirFAST allowed the design of a fluorogenic chemically induced dimerization technology with NIR fluorescence readout, enabling the control and visualization of protein proximity.

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04/06/24 | Convolutional Neural Network Transformer (CNNT) for Fluorescence Microscopy image Denoising with Improved Generalization and Fast Adaptation
Azaan Rehman , Alexander Zhovmer , Ryo Sato , Yosuke Mukoyama , Jiji Chen , Alberto Rissone , Rosa Puertollano , Harshad Vishwasrao , Hari Shroff , Christian A. Combs , Hui Xue
arXiv. 2024 Apr 6:

Deep neural networks have been applied to improve the image quality of fluorescence microscopy imaging. Previous methods are based on convolutional neural networks (CNNs) which generally require more time-consuming training of separate models for each new imaging experiment, impairing the applicability and generalization. Once the model is trained (typically with tens to hundreds of image pairs) it can then be used to enhance new images that are like the training data. In this study, we proposed a novel imaging-transformer based model, Convolutional Neural Network Transformer (CNNT), to outperform the CNN networks for image denoising. In our scheme we have trained a single CNNT based backbone model from pairwise high-low SNR images for one type of fluorescence microscope (instance structured illumination, iSim). Fast adaption to new applications was achieved by fine-tuning the backbone on only 5-10 sample pairs per new experiment. Results show the CNNT backbone and fine-tuning scheme significantly reduces the training time and improves the image quality, outperformed training separate models using CNN approaches such as - RCAN and Noise2Fast. Here we show three examples of the efficacy of this approach on denoising wide-field, two-photon and confocal fluorescence data. In the confocal experiment, which is a 5 by 5 tiled acquisition, the fine-tuned CNNT model reduces the scan time form one hour to eight minutes, with improved quality.

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04/06/24 | COPII with ALG2 and ESCRTs control lysosome-dependent microautophagy of ER exit sites.
Liao Y, Pang S, Li W, Shtengel G, Choi H, Schaefer K, Xu CS, Lippincott-Schwartz J
Dev Cell. 2024 Apr 06:. doi: 10.1016/j.devcel.2024.03.027

Endoplasmic reticulum exit sites (ERESs) are tubular outgrowths of endoplasmic reticulum that serve as the earliest station for protein sorting and export into the secretory pathway. How these structures respond to different cellular conditions remains unclear. Here, we report that ERESs undergo lysosome-dependent microautophagy when Ca is released by lysosomes in response to nutrient stressors such as mTOR inhibition or amino acid starvation in mammalian cells. Targeting and uptake of ERESs into lysosomes were observed by super-resolution live-cell imaging and focus ion beam scanning electron microscopy (FIB-SEM). The mechanism was ESCRT dependent and required ubiquitinated SEC31, ALG2, and ALIX, with a knockout of ALG2 or function-blocking mutations of ALIX preventing engulfment of ERESs by lysosomes. In vitro, reconstitution of the pathway was possible using lysosomal lipid-mimicking giant unilamellar vesicles and purified recombinant components. Together, these findings demonstrate a pathway of lysosome-dependent ERES microautophagy mediated by COPII, ALG2, and ESCRTS induced by nutrient stress.

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04/08/24 | Spike sorting with Kilosort4
Pachitariu M, Sridhar S, Pennington J, Stringer C
Nat Methods. 2024 Apr 08:. doi: 10.1038/s41592-024-02232-7

Spike sorting is the computational process of extracting the firing times of single neurons from recordings of local electrical fields. This is an important but hard problem in neuroscience, made complicated by the nonstationarity of the recordings and the dense overlap in electrical fields between nearby neurons. To address the spike-sorting problem, we have been openly developing the Kilosort framework. Here we describe the various algorithmic steps introduced in different versions of Kilosort. We also report the development of Kilosort4, a version with substantially improved performance due to clustering algorithms inspired by graph-based approaches. To test the performance of Kilosort, we developed a realistic simulation framework that uses densely sampled electrical fields from real experiments to generate nonstationary spike waveforms and realistic noise. We found that nearly all versions of Kilosort outperformed other algorithms on a variety of simulated conditions and that Kilosort4 performed best in all cases, correctly identifying even neurons with low amplitudes and small spatial extents in high drift conditions.

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