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Autophagosomes are crucial components of the cellular recycling machinery that form at endoplasmic reticulum (ER)-associated sites. As the autophagosome membrane is largely devoid of transmembrane proteins, autophagosome biogenesis is thought to be largely regulated by lipid transfer and lipid modifications, as well as membrane-associated proteins. While the membrane origin of autophagosomes and their lipid composition are still incompletely understood, previous studies have found the autophagosome membrane to be enriched in unsaturated fatty acids and have little cholesterol, suggesting that cholesterol removal is an integral step during autophagosome biogenesis. In our study, we demonstrate that short term cholesterol depletion leads to a rapid induction of autophagy and identify the ER-localized cholesterol transport protein GRAMD1C as a negative regulator of starvation-induced macroautophagy/autophagy. Abbreviations: ATG: autophagy related; ccRCC: clear cell renal cell carcinoma; ER: endoplasmic reticulum; GRAM: glucosyltransferases, RAB-like GTPase activators and myotubularins; GRAMD: GRAM domain containing; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MCBD: methyl-cyclodextrin; MTOR: mechanistic target of rapamycin kinase; VASt: VAD1 analog of StAR-related lipid transfer.

Connectomics is fundamental in propelling our understanding of the nervous system's organization, unearthing cells and wiring diagrams reconstructed from volume electron microscopy (EM) datasets. Such reconstructions, on the one hand, have benefited from ever more precise automatic segmentation methods, which leverage sophisticated deep learning architectures and advanced machine learning algorithms. On the other hand, the field of neuroscience at large, and of image processing in particular, has manifested a need for user-friendly and open source tools which enable the community to carry out advanced analyses. In line with this second vein, here we propose mEMbrain, an interactive MATLAB-based software which wraps algorithms and functions that enable labeling and segmentation of electron microscopy datasets in a user-friendly user interface compatible with Linux and Windows. Through its integration as an API to the volume annotation and segmentation tool VAST, mEMbrain encompasses functions for ground truth generation, image preprocessing, training of deep neural networks, and on-the-fly predictions for proofreading and evaluation. The final goals of our tool are to expedite manual labeling efforts and to harness MATLAB users with an array of semi-automatic approaches for instance segmentation. We tested our tool on a variety of datasets that span different species at various scales, regions of the nervous system and developmental stages. To further expedite research in connectomics, we provide an EM resource of ground truth annotation from four different animals and five datasets, amounting to around 180 h of expert annotations, yielding more than 1.2 GB of annotated EM images. In addition, we provide a set of four pre-trained networks for said datasets. All tools are available from https://lichtman.rc.fas.harvard.edu/mEMbrain/. With our software, our hope is to provide a solution for lab-based neural reconstructions which does not require coding by the user, thus paving the way to affordable connectomics., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Pavarino, Yang, Dhanyasi, Wang, Bidel, Lu, Yang, Francisco Park, Bangalore Renuka, Drescher, Samuel, Hochner, Katz, Zhen, Lichtman and Meirovitch.)

Population sizes of many birds are declining alarmingly and methods for estimating fluctuations in species' abundances at a large spatial scale are needed. The possibility to derive indicators from the tendency of specific species to co-occur with others has been overlooked. Here, we tested whether the abundance of resident titmice can act as a general ecological indicator of forest bird density in European forests. Titmice species are easily identifiable and have a wide distribution, which makes them potentially useful ecological indicators. Migratory birds often use information on the density of resident birds, such as titmice, as a cue for habitat selection. Thus, the density of residents may potentially affect community dynamics. We examined spatio-temporal variation in titmouse abundance and total bird abundance, each measured as biomass, by using long-term citizen science data on breeding forest birds in Finland and France. We analyzed the variation in observed forest bird density (excluding titmice) in relation to titmouse abundance. In Finland, forest bird density linearly increased with titmouse abundance. In France, forest bird density nonlinearly increased with titmouse abundance, the association weakening toward high titmouse abundance. We then analyzed whether the abundance (measured as biomass) of random species sets could predict forest bird density better than titmouse abundance. Random species sets outperformed titmice as an indicator of forest bird density only in 4.4% and 24.2% of the random draws, in Finland and France, respectively. Overall, the results suggest that titmice could act as an indicator of bird density in Northern European forest bird communities, encouraging the use of titmice observations by even less-experienced observers in citizen science monitoring of general forest bird density., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Synapses are particularly vulnerable in many neurodegenerative diseases and often the first to degenerate, for example in the motor neuron disease spinal muscular atrophy (SMA). Compounds that can counteract synaptic destabilisation are rare. Here, we describe an automated screening paradigm in zebrafish for small-molecule compounds that stabilize the neuromuscular synapse in vivo. We make use of a mutant for the axonal C-type lectin chondrolectin (chodl), one of the main genes dysregulated in SMA. In chodl-/- mutants, neuromuscular synapses that are formed at the first synaptic site by growing axons are not fully mature, causing axons to stall, thereby impeding further axon growth beyond that synaptic site. This makes axon length a convenient read-out for synapse stability. We screened 982 small-molecule compounds in chodl chodl-/- mutants and found four that strongly rescued motor axon length. Aberrant presynaptic neuromuscular synapse morphology was also corrected. The most-effective compound, the adenosine uptake inhibitor drug dipyridamole, also rescued axon growth defects in the UBA1-dependent zebrafish model of SMA. Hence, we describe an automated screening pipeline that can detect compounds with relevance to SMA. This versatile platform can be used for drug and genetic screens, with wider relevance to synapse formation and stabilisation., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2021. Published by The Company of Biologists Ltd.)

In recent years, zebrafish have become commonly used as a model for studying human traits and disorders. Their small size, high fecundity, and rapid development allow for more high-throughput experiments compared to other vertebrate models. Given that zebrafish share >70% gene homologs with humans and their genomes can be readily edited using highly efficient CRISPR methods, we are now able to rapidly generate mutations impacting practically any gene of interest. Unfortunately, our ability to phenotype mutant larvae has not kept pace. To address this challenge, we have developed a protocol that obtains multiple phenotypic measurements from individual zebrafish larvae in an automated and parallel fashion, including morphological features (i.e., body length, eye area, and head size) and movement/behavior. By assaying wild-type zebrafish in a variety of conditions, we determined optimal parameters that avoid significant developmental defects or physical damage; these include morphological imaging of larvae at two time points [3 days post fertilization (dpf) and 5 dpf] coupled with motion tracking of behavior at 5 dpf. As a proof-of-principle, we tested our approach on two novel CRISPR-generated mutant zebrafish lines carrying predicted null-alleles of syngap1b and slc7a5 , orthologs to two human genes implicated in autism-spectrum disorder, intellectual disability, and epilepsy. Using our optimized high-throughput phenotyping protocol, we recapitulated previously published results from mouse and zebrafish models of these candidate genes. In summary, we describe a rapid parallel pipeline to characterize morphological and behavioral features of individual larvae in a robust and consistent fashion, thereby improving our ability to better identify genes important in human traits and disorders., (Copyright © 2020 Colón-Rodríguez, Uribe-Salazar, Weyenberg, Sriram, Quezada, Kaya, Jao, Radke, Lein and Dennis.)

Myelinating oligodendrocytes are essential for central nervous system (CNS) formation and function. Their disruption is implicated in numerous neurodevelopmental, neuropsychiatric and neurodegenerative disorders. However, recent studies have indicated that oligodendrocytes may be tractable for treatment of disease. In recent years, zebrafish have become well established for the study of myelinating oligodendrocyte biology and drug discovery in vivo. Here, by automating the delivery of zebrafish larvae to a spinning disk confocal microscope, we were able to automate high-resolution imaging of myelinating oligodendrocytes in vivo. From there, we developed an image analysis pipeline that facilitated a screen of compounds with epigenetic and post-translational targets for their effects on regulating myelinating oligodendrocyte number. This screen identified novel compounds that strongly promote myelinating oligodendrocyte formation in vivo. Our imaging platform and analysis pipeline is flexible and can be employed for high-resolution imaging-based screens of broad interest using zebrafish., Competing Interests: JE, MS, DL No competing interests declared, KC funded by a collaborative grant from Biogen for part of the period of this project, JW Jill M Williamson: funded by a collaborative grant from Biogen for part of the period of this project, HK was employed by Biogen at the time of the study, MM Marc Muskavitch: was employed by Biogen at the time of the study, (© 2018, Early et al.)

"Vast" is a word often applied to environmental terrain that is perceived to have large spatial extent. This judgment is made even at viewing distances where traditional metric depth cues are not useful. This paper explores the perceptual basis of vast experience, including reliability and visual precursors. Experiment 1 demonstrated strong agreement in ratings of the spatial extent of two-dimensional (2D) scene images by participants in two countries under very different viewing conditions. Image categories labeled "vast" often exemplified scene attributes of ruggedness and openness (Oliva & Torralba, 2001). Experiment 2 quantitatively assessed whether these properties predict vastness. High vastness ratings were associated with highly open, or moderately open but rugged, scenes. Experiment 3 provided evidence, consistent with theory, that metric distance perception does not directly mediate the observed vastness ratings. The question remains as to how people perceive vast space when information about environmental scale is unavailable from metric depth cues or associated scene properties. We consider possible answers, including contribution from strong cues to relative depth.