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3924 Publications

Showing 1-10 of 3924 results
07/04/24 | iTome Volumetric Serial Sectioning Apparatus for TEM
Peale DR, Hess H, Lee PR, Cardona A, Bock DD, Schneider-Mizell C, Fetter RD, Lee W, Robinson CG, Iyer N, Managan C
bioRxiv. 2024 Jul 07:. doi: 10.1101/2024.07.02.601671

An automated ultra-microtome capable of sectioning thousands of ultrathin sections onto standard TEM slot grids was developed and used to section: a complete Drosophila melanogaster first-instar larva, three sections per grid, into 4,866 34-nm-thick sections with a cutting and pickup success rate of 99.74%; 30 microns of mouse cortex measuring roughly 400 um x 2000 um at 40 nm per slice; and a full adult Drosophila brain and ventral nerve column into 9,300 sections with a pickup success rate of 99.95%. The apparatus uses optical interferometers to monitor a reference distance between the cutting knife and multiple sample blocks. Cut sections are picked up from the knife-boat water surface while they are still anchored to the cutting knife. Blocks without embedded tissue are used to displace tissue-containing sections away from the knife edge so that the tissue regions end up in the grid slot instead of on the grid rim.

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07/05/24 | LarvaTagger: Manual and automatic tagging of drosophila larval behaviour.
Laurent F, Blanc A, May L, Gándara L, Cocanougher BT, Jones BM, Hague P, Barre C, Vestergaard CL, Crocker J, Zlatic M, Jovanic T, Masson J
Bioinformatics. 2024 Jul 05:. doi: 10.1093/bioinformatics/btae441

MOTIVATION: As more behavioural assays are carried out in large-scale experiments on Drosophila larvae, the definitions of the archetypal actions of a larva are regularly refined. In addition, video recording and tracking technologies constantly evolve. Consequently, automatic tagging tools for Drosophila larval behaviour must be retrained to learn new representations from new data. However, existing tools cannot transfer knowledge from large amounts of previously accumulated data.We introduce LarvaTagger, a piece of software that combines a pre-trained deep neural network, providing a continuous latent representation of larva actions for stereotypical behaviour identification, with a graphical user interface to manually tag the behaviour and train new automatic taggers with the updated ground truth.

RESULTS: We reproduced results from an automatic tagger with high accuracy, and we demonstrated that pre-training on large databases accelerates the training of a new tagger, achieving similar prediction accuracy using less data.

AVAILABILITY: All the code is free and open source. Docker images are also available. See

SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.

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06/27/24 | Lattice light sheet microscopy reveals 4D force propagation dynamics and leading-edge behaviors in an embryonic epithelium in Drosophila.
Vanderleest TE, Xie Y, Budhathoki R, Linvill K, Hobson C, Heddleston J, Loerke D, Blankenship JT
Curr Biol. 2024 Jun 27:. doi: 10.1016/j.cub.2024.06.017

How pulsed contractile dynamics drive the remodeling of cell and tissue topologies in epithelial sheets has been a key question in development and disease. Due to constraints in imaging and analysis technologies, studies that have described the in vivo mechanisms underlying changes in cell and neighbor relationships have largely been confined to analyses of planar apical regions. Thus, how the volumetric nature of epithelial cells affects force propagation and remodeling of the cell surface in three dimensions, including especially the apical-basal axis, is unclear. Here, we perform lattice light sheet microscopy (LLSM)-based analysis to determine how far and fast forces propagate across different apical-basal layers, as well as where topological changes initiate from in a columnar epithelium. These datasets are highly time- and depth-resolved and reveal that topology-changing forces are spatially entangled, with contractile force generation occurring across the observed apical-basal axis in a pulsed fashion, while the conservation of cell volumes constrains instantaneous cell deformations. Leading layer behaviors occur opportunistically in response to favorable phasic conditions, with lagging layers "zippering" to catch up as new contractile pulses propel further changes in cell topologies. These results argue against specific zones of topological initiation and demonstrate the importance of systematic 4D-based analysis in understanding how forces and deformations in cell dimensions propagate in a three-dimensional environment.

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07/04/24 | CRISPR-array-mediated imaging of non-repetitive and multiplex genomic loci in living cells.
Yang L, Min Y, Liu Y, Gao B, Liu X, Huang Y, Wang H, Yang L, Liu ZJ, Chen L
Nat Methods. 2024 Jul 04:. doi: 10.1038/s41592-024-02333-3

Dynamic imaging of genomic loci is key for understanding gene regulation, but methods for imaging genomes, in particular non-repetitive DNAs, are limited. We developed CRISPRdelight, a DNA-labeling system based on endonuclease-deficient CRISPR-Cas12a (dCas12a), with an engineered CRISPR array to track DNA location and motion. CRISPRdelight enables robust imaging of all examined 12 non-repetitive genomic loci in different cell lines. We revealed the confined movement of the CCAT1 locus (chr8q24) at the nuclear periphery for repressed expression and active motion in the interior nucleus for transcription. We uncovered the selective repositioning of HSP gene loci to nuclear speckles, including a remarkable relocation of HSPH1 (chr13q12) for elevated transcription during stresses. Combining CRISPR-dCas12a and RNA aptamers allowed multiplex imaging of four types of satellite DNA loci with a single array, revealing their spatial proximity to the nucleolus-associated domain. CRISPRdelight is a user-friendly and robust system for imaging and tracking genomic dynamics and regulation.

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06/02/24 | Dynamic assemblies of parvalbumin interneurons in brain oscillations.
Huang Y, Chen H, Lin Y, Lin S, Zheng Q, Abdelfattah AS, Lavis LD, Schreiter ER, Lin B, Chen T
Neuron. 2024 Jun 02:. doi: 10.1016/j.neuron.2024.05.015

Brain oscillations are crucial for perception, memory, and behavior. Parvalbumin-expressing (PV) interneurons are critical for these oscillations, but their population dynamics remain unclear. Using voltage imaging, we simultaneously recorded membrane potentials in up to 26 PV interneurons in vivo during hippocampal ripple oscillations in mice. We found that PV cells generate ripple-frequency rhythms by forming highly dynamic cell assemblies. These assemblies exhibit rapid and significant changes from cycle to cycle, varying greatly in both size and membership. Importantly, this variability is not just random spiking failures of individual neurons. Rather, the activities of other PV cells contain significant information about whether a PV cell spikes or not in a given cycle. This coordination persists without network oscillations, and it exists in subthreshold potentials even when the cells are not spiking. Dynamic assemblies of interneurons may provide a new mechanism to modulate postsynaptic dynamics and impact cognitive functions flexibly and rapidly.

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06/28/24 | Exploration and exploitation are flexibly balanced during local search in flies
Goldschmidt D, Guo Y, Chitnis SS, Christoforou C, Turner-Evans D, Ribeiro C, Hermundstad AM, Jayaraman V, Haberkern H
bioRxiv. 2024 Jun 28:. doi: 10.1101/2024.06.26.600764

After finding food, a foraging animal must decide whether to continue feeding, or to explore the environment for potentially better options. One strategy to negotiate this tradeoff is to perform local searches around the food but repeatedly return to feed. We studied this behavior in flies and used genetic tools to uncover the underlying mechanisms. Over time, flies gradually expand their search, shifting from primarily exploiting food sources to exploring the environment, a change that is likely driven by increases in satiety. We found that flies’ search patterns preserve these dynamics even as the overall scale of the search is modulated by starvation-induced changes in metabolic state. In contrast, search induced by optogenetic activation of sugar sensing neurons does not show these dynamics. We asked what navigational strategies underlie local search. Using a generative model, we found that a change in locomotor pattern after food consumption could account for repeated returns to the food, but failed to capture relatively direct, long return trajectories. Alternative strategies, such as path integration or sensory taxis could allow flies to return from larger distances. We tested this by individually silencing the fly’s head direction system, olfaction and hygrosensation, and found that the only substantial effect was from perturbing hygrosensation, which reduced the number of long exploratory trips. Our study illustrates that local search is composed of multiple behavioral features that evolve over time based on both internal and external factors, providing a path towards uncovering the underlying neural mechanisms.

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06/01/24 | Resolution in super-resolution microscopy - definition, trade-offs and perspectives.
Prakash K, Baddeley D, Eggeling C, Fiolka R, Heintzmann R, Manley S, Radenovic A, Smith C, Shroff H, Schermelleh L
Nat Rev Mol Cell Biol. 2024 Jul 01:. doi: 10.1038/s41580-024-00755-7

Super-resolution microscopy (SRM) is gaining popularity in biosciences; however, claims about optical resolution are contested and often misleading. In this Viewpoint, experts share their views on resolution and common trade-offs, such as labelling and post-processing, aiming to clarify them for biologists and facilitate deeper understanding and best use of SRM.

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07/02/24 | Towards a simplified model of primary visual cortex
Du F, Núñez-Ochoa MA, Pachitariu M, Stringer C
bioRxiv. 2024 Jul 02:. doi: 10.1101/2024.06.30.601394

Artificial neural networks (ANNs) have been shown to predict neural responses in primary visual cortex (V1) better than classical models. However, this performance comes at the expense of simplicity because the ANN models typically have many hidden layers with many feature maps in each layer. Here we show that ANN models of V1 can be substantially simplified while retaining high predictive power. To demonstrate this, we first recorded a new dataset of over 29,000 neurons responding to up to 65,000 natural image presentations in mouse V1. We found that ANN models required only two convolutional layers for good performance, with a relatively small first layer. We further found that we could make the second layer small without loss of performance, by fitting a separate "minimodel" to each neuron. Similar simplifications applied for models of monkey V1 neurons. We show that these relatively simple models can nonetheless be useful for tasks such as object and visual texture recognition and we use the models to gain insight into how texture invariance arises in biological neurons.

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06/25/24 | Near-infrared nanosensors enable optical imaging of oxytocin with selectivity over vasopressin in acute mouse brain slices.
Mun J, Navarro N, Jeong S, Ouassil N, Leem E, Beyene AG, Landry MP
Proc Natl Acad Sci U S A. 2024 Jun 25;121(26):e2314795121. doi: 10.1073/pnas.2314795121

Oxytocin plays a critical role in regulating social behaviors, yet our understanding of its function in both neurological health and disease remains incomplete. Real-time oxytocin imaging probes with spatiotemporal resolution relevant to its endogenous signaling are required to fully elucidate oxytocin's role in the brain. Herein, we describe a near-infrared oxytocin nanosensor (nIROXT), a synthetic probe capable of imaging oxytocin in the brain without interference from its structural analogue, vasopressin. nIROXT leverages the inherent tissue-transparent fluorescence of single-walled carbon nanotubes (SWCNT) and the molecular recognition capacity of an oxytocin receptor peptide fragment to selectively and reversibly image oxytocin. We employ these nanosensors to monitor electrically stimulated oxytocin release in brain tissue, revealing oxytocin release sites with a median size of 3 µm in the paraventricular nucleus of C57BL/6 mice, which putatively represents the spatial diffusion of oxytocin from its point of release. These data demonstrate that covalent SWCNT constructs, such as nIROXT, are powerful optical tools that can be leveraged to measure neuropeptide release in brain tissue.

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06/20/24 | Neocortical inhibitory imbalance predicts successful sensory detection.
Deister CA, Moore AI, Voigts J, Bechek S, Lichtin R, Brown TC, Moore CI
Cell Rep. 2024 Jun 20;43(7):114233. doi: 10.1016/j.celrep.2024.114233

Perceptual success depends on fast-spiking, parvalbumin-positive interneurons (FS/PVs). However, competing theories of optimal rate and correlation in pyramidal (PYR) firing make opposing predictions regarding the underlying FS/PV dynamics. We addressed this with population calcium imaging of FS/PVs and putative PYR neurons during threshold detection. In primary somatosensory and visual neocortex, a distinct PYR subset shows increased rate and spike-count correlations on detected trials ("hits"), while most show no rate change and decreased correlations. A larger fraction of FS/PVs predicts hits with either rate increases or decreases. Using computational modeling, we found that inhibitory imbalance, created by excitatory "feedback" and interactions between FS/PV pools, can account for the data. Rate-decreasing FS/PVs increase rate and correlation in a PYR subset, while rate-increasing FS/PVs reduce correlations and offset enhanced excitation in PYR neurons. These findings indicate that selection of informative PYR ensembles, through transient inhibitory imbalance, is a common motif of optimal neocortical processing.

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