@article {69139, title = {Petascale pipeline for precise alignment of images from serial section electron microscopy.}, journal = {Nature Communications}, volume = {15}, year = {2024}, month = {2024 Jan 04}, pages = {289}, abstract = {

The reconstruction of neural circuits from serial section electron microscopy (ssEM) images is being accelerated by automatic image segmentation methods. Segmentation accuracy is often limited by the preceding step of aligning 2D section images to create a 3D image stack. Precise and robust alignment in the presence of image artifacts is challenging, especially as datasets are attaining the petascale. We present a computational pipeline for aligning ssEM images with several key elements. Self-supervised convolutional nets are trained via metric learning to encode and align image pairs, and they are used to initialize iterative fine-tuning of alignment. A procedure called vector voting increases robustness to image artifacts or missing image data. For speedup the series is divided into blocks that are distributed to computational workers for alignment. The blocks are aligned to each other by composing transformations with decay, which achieves a global alignment without resorting to a time-consuming global optimization. We apply our pipeline to a whole fly brain dataset, and show improved accuracy relative to prior state of the art. We also demonstrate that our pipeline scales to a cubic millimeter of mouse visual cortex. Our pipeline is publicly available through two open source Python packages.

}, keywords = {Animals, Brain, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Mice, Microscopy, Electron}, issn = {2041-1723}, doi = {10.1038/s41467-023-44354-0}, author = {Popovych, Sergiy and Macrina, Thomas and Kemnitz, Nico and Castro, Manuel and Nehoran, Barak and Jia, Zhen and Bae, J Alexander and Mitchell, Eric and Mu, Shang and Trautman, Eric T and Saalfeld, Stephan and Li, Kai and Seung, H Sebastian} } @article {68807, title = {Architecture and dynamics of a desmosome-endoplasmic reticulum complex.}, journal = {Nature Cell Biology}, volume = {25}, year = {2023}, month = {2023 Jun 16}, pages = {823-835}, abstract = {

The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signalling and lipid transfer. Here, using high-resolution volume electron microscopy, we find that the ER forms a previously unknown association with keratin intermediate filaments and desmosomal cell-cell junctions. Peripheral ER assembles into mirror image-like arrangements at desmosomes and exhibits nanometre proximity to keratin filaments and the desmosome cytoplasmic plaque. ER tubules exhibit stable associations with desmosomes, and perturbation of desmosomes or keratin filaments alters ER organization, mobility and expression of ER stress transcripts. These findings indicate that desmosomes and the keratin cytoskeleton regulate the distribution, function and dynamics of the ER network. Overall, this study reveals a previously unknown subcellular architecture defined by the structural integration of ER tubules with an epithelial intercellular junction.

}, keywords = {Cytoskeleton, Desmosomes, Endoplasmic Reticulum, Intermediate Filaments, Keratins}, issn = {1476-4679}, doi = {10.1038/s41556-023-01154-4}, author = {Bharathan, Navaneetha Krishnan and Giang, William and Hoffman, Coryn L and Aaron, Jesse S and Khuon, Satya and Chew, Teng-Leong and Preibisch, Stephan and Trautman, Eric T and Heinrich, Larissa and Bogovic, John and Bennett, Davis and Ackerman, David and Park, Woohyun and Petruncio, Alyson and Weigel, Aubrey V and Saalfeld, Stephan and Wayne Vogl, A and Stahley, Sara N and Kowalczyk, Andrew P} } @article {68251, title = {A scalable and modular automated pipeline for stitching of large electron microscopy datasets.}, journal = {eLife}, volume = {11}, year = {2022}, month = {2022 Jul 26}, abstract = {

Serial-section electronmicroscopy (ssEM) is themethod of choice for studyingmacroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so called connectomes. In order to use this data, consisting of up to 10 individual EM images, it must be assembled into a volume, requiring seamless 2D stitching from each physical section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipeline ASAP (Assembly Stitching and Alignment Pipeline) that is scalable to datasets containing petabytes of data and parallelized to work in a distributed computational environment. The pipeline is built on top of the Render (27) services used in the volume assembly of the brain of adult Drosophilamelanogaster (30). It achieves high throughput by operating on themeta-data and transformations of each image stored in a database, thus eliminating the need to render intermediate output. ASAP ismodular, allowing for easy incorporation of new algorithms without significant changes in the workflow. The entire software pipeline includes a complete set of tools for stitching, automated quality control, 3D section alignment, and final rendering of the assembled volume to disk. ASAP has been deployed for continuous stitching of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex (28; 8) at speeds that exceed imaging. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.

}, issn = {2050-084X}, doi = {10.7554/eLife.76534}, author = {Mahalingam, Gayathri and Torres, Russel and Kapner, Daniel and Trautman, Eric T and Fliss, Tim and Seshamani, Shamishtaa and Perlman, Eric and Young, Rob and Kinn, Samuel and Buchanan, JoAnn and Takeno, Marc M and Yin, Wenjing and Bumbarger, Daniel J and Gwinn, Ryder P and Nyhus, Julie and Lein, Ed and Smith, Steven J and Reid, R Clay and Khairy, Khaled A and Saalfeld, Stephan and Collman, Forrest and Macarico da Costa, Nuno} } @article {68507, title = {A connectome and analysis of the adult Drosophila central brain.}, journal = {Elife}, volume = {9}, year = {2020}, month = {2020 Sep 07}, abstract = {

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly . Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly{\textquoteright}s brain.

}, keywords = {Animals, Brain, Connectome, Drosophila melanogaster, Female, Male, Neurons, Synapses}, issn = {2050-084X}, doi = {10.7554/eLife.57443}, author = {Scheffer, Louis K and Xu, C Shan and Januszewski, Michal and Lu, Zhiyuan and Takemura, Shin-ya and Hayworth, Kenneth J and Huang, Gary B and Shinomiya, Kazunori and Maitlin-Shepard, Jeremy and Berg, Stuart and Clements, Jody and Hubbard, Philip M and Katz, William T and Umayam, Lowell and Zhao, Ting and Ackerman, David and Blakely, Tim and Bogovic, John and Dolafi, Tom and Kainmueller, Dagmar and Kawase, Takashi and Khairy, Khaled A and Leavitt, Laramie and Li, Peter H and Lindsey, Larry and Neubarth, Nicole and Olbris, Donald J and Otsuna, Hideo and Trautman, Eric T and Ito, Masayoshi and Bates, Alexander S and Goldammer, Jens and Wolff, Tanya and Svirskas, Robert and Schlegel, Philipp and Neace, Erika and Knecht, Christopher J and Alvarado, Chelsea X and Bailey, Dennis A and Ballinger, Samantha and Borycz, Jolanta A and Canino, Brandon S and Cheatham, Natasha and Cook, Michael and Dreher, Marisa and Duclos, Octave and Eubanks, Bryon and Fairbanks, Kelli and Finley, Samantha and Forknall, Nora and Francis, Audrey and Hopkins, Gary Patrick and Joyce, Emily M and Kim, SungJin and Kirk, Nicole A and Kovalyak, Julie and Lauchie, Shirley A and Lohff, Alanna and Maldonado, Charli and Manley, Emily A and McLin, Sari and Mooney, Caroline and Ndama, Miatta and Ogundeyi, Omotara and Okeoma, Nneoma and Ordish, Christopher and Padilla, Nicholas and Patrick, Christopher M and Paterson, Tyler and Phillips, Elliott E and Phillips, Emily M and Rampally, Neha and Ribeiro, Caitlin and Robertson, Madelaine K and Rymer, Jon Thomson and Ryan, Sean M and Sammons, Megan and Scott, Anne K and Scott, Ashley L and Shinomiya, Aya and Smith, Claire and Smith, Kelsey and Smith, Natalie L and Sobeski, Margaret A and Suleiman, Alia and Swift, Jackie and Takemura, Satoko and Talebi, Iris and Tarnogorska, Dorota and Tenshaw, Emily and Tokhi, Temour and Walsh, John J and Yang, Tansy and Horne, Jane Anne and Li, Feng and Parekh, Ruchi and Rivlin, Patricia K and Jayaraman, Vivek and Costa, Marta and Jefferis, Gregory Sxe and Ito, Kei and Saalfeld, Stephan and George, Reed and Meinertzhagen, Ian A and Rubin, Gerald M and Hess, Harald F and Jain, Viren and Plaza, Stephen M} } @article {49149, title = {A community-developed Open-Source computational ecosystem for big neuro data.}, journal = {Nature Methods}, volume = {15}, year = {2018}, month = {2018 Nov}, pages = {846-7}, abstract = {

Big imaging data is becoming more prominent in brain sciences across spatiotemporal scales and phylogenies. We have developed a computational ecosystem that enables storage, visualization, and analysis of these data in the cloud, thusfar spanning 20+ publications and 100+ terabytes including nanoscale ultrastructure, microscale synaptogenetic diversity, and mesoscale whole brain connectivity, making NeuroData the largest and most diverse open repository of brain data.

}, doi = {10.1038/s41592-018-0181-1}, author = {Vogelstein, Joshua T and Perlman, Eric and Falk, Benjamin and Baden, Alex and Roncal, William Gray and Chandrashekhar, Vikram and Collman, Forrest and Seshamani, Sharmishtaa and Patsolic, Jesse and Lillaney, Kunal and Kazhdan, Michael and Hider Jr., Robert and Pryor, Derek and Matelsky, Jordan and Gion, Timothy and Manavalan, Priya and Wester, Brock and Chevillet, Mark and Trautman, Eric T and Khairy, Khaled} } @article {48620, title = {A complete electron microscopy volume of the brain of adult Drosophila melanogaster.}, journal = {Cell}, volume = {174}, year = {2018}, month = {2018 Jul 12}, pages = {730-43}, abstract = {

Drosophila melanogaster has a rich repertoire of innate and learned behaviors. Its 100,000-neuron brain is a large but tractable target for comprehensive neural circuit mapping. Only electron microscopy (EM) enables complete, unbiased mapping of synaptic connectivity; however, the fly brain is too large for conventional EM. We developed a custom high-throughput EM platform and imaged the entire brain of an adult female fly at synaptic resolution. To validate the dataset, we traced brain-spanning circuitry involving the mushroom body (MB), which has been extensively studied for its role in learning. All inputs to Kenyon cells (KCs), the intrinsic neurons of the MB, were mapped, revealing a previously unknown cell type, postsynaptic partners of KC dendrites, and unexpected clustering of olfactory projection neurons. These reconstructions show that this freely available EM volume supports mapping of brain-spanning circuits, which will significantly accelerate Drosophila neuroscience..

}, doi = {10.1016/j.cell.2018.06.019}, author = {Zheng, Zhihao and Lauritzen, J Scott and Perlman, Eric and Robinson, Camenzind G and Nichols, Matthew and Milkie, Daniel E and Torrens, Omar and Price, John and Fisher, Corey B and Sharifi, Nadiya and Calle-Schuler, Steven A and Kmecova, Lucia and Ali, Iqbal J and Karsh, Bill and Trautman, Eric T and Bogovic, John A and Hanslovsky, Philipp and Jefferis, Gregory S X E and Kazhdan, Michael and Khairy, Khaled} } @article {46835, title = {Dynamical feature extraction at the sensory periphery guides chemotaxis.}, journal = {eLife}, volume = {4}, year = {2015}, month = {2015 Jun 16}, abstract = {

Behavioral strategies employed for chemotaxis have been described across phyla, but the sensorimotor basis of this phenomenon has seldom been studied in naturalistic contexts. Here, we examine how signals experienced during free olfactory behaviors are processed by first-order olfactory sensory neurons (OSNs) of the Drosophila larva. We find that OSNs can act as differentiators that transiently normalize stimulus intensity-a property potentially derived from a combination of integral feedback and feed-forward regulation of olfactory transduction. In olfactory virtual reality experiments, we report that high activity levels of the OSN suppress turning, whereas low activity levels facilitate turning. Using a generalized linear model, we explain how peripheral encoding of olfactory stimuli modulates the probability of switching from a run to a turn. Our work clarifies the link between computations carried out at the sensory periphery and action selection underlying navigation in odor gradients.

}, issn = {2050-084X}, doi = {10.7554/eLife.06694}, author = {Schulze, Aljoscha and Gomez-Marin, Alex and Rajendran, Vani G and Lott, Gus and Musy, Marco and Ahammad, Parvez and Deogade, Ajinkya and Sharpe, James and Riedl, Julia and Jarriault, David and Trautman, Eric T and Werner, Christopher and Venkadesan, Madhusudhan and Druckmann, Shaul and Jayaraman, Vivek and Louis, Matthieu} } @article {5423, title = {A GAL4-driver line resource for Drosophila neurobiology.}, journal = {Cell Reports}, volume = {2}, year = {2012}, month = {2012 Oct 25}, pages = {991-1001}, abstract = {

We established a collection of 7,000 transgenic lines of Drosophila melanogaster. Expression of GAL4 in each line is controlled by a different, defined fragment of genomic DNA that serves as a transcriptional enhancer. We used confocal microscopy of dissected nervous systems to determine the expression patterns driven by each fragment in the adult brain and ventral nerve cord. We present image data on 6,650 lines. Using both manual and machine-assisted annotation, we describe the expression patterns in the most useful lines. We illustrate the utility of these data for identifying novel neuronal cell types, revealing brain asymmetry, and describing the nature and extent of neuronal shape stereotypy. The GAL4 lines allow expression of exogenous genes in distinct, small subsets of the adult nervous system. The set of DNA fragments, each driving a documented expression pattern, will facilitate the generation of additional constructs for manipulating neuronal function. synapse was substantially elevated, at the endocytic zone there was no enhanced polymerization activity. We conclude that actin subserves spatially diverse, independently regulated processes throughout spines. Perisynaptic actin forms a uniquely dynamic structure well suited for direct, active regulation of the synapse.

For the overall strategy and methods used to produce the GAL4 lines:
Pfeiffer, B.D., Jenett, A., Hammonds, A.S., Ngo, T.T., Misra, S., Murphy, C., Scully, A., Carlson, J.W., Wan, K.H., Laverty, T.R., Mungall, C., Svirskas, R., Kadonaga, J.T., Doe, C.Q., Eisen, M.B., Celniker, S.E., Rubin, G.M. (2008). Tools for neuroanatomy and neurogenetics in Drosophila. Proc. Natl. Acad. Sci. USA 105, 9715-9720. http://www.pnas.org/content/105/28/9715.full.pdf+html synapse was substantially elevated, at the endocytic zone there was no enhanced polymerization activity. We conclude that actin subserves spatially diverse, independently regulated processes throughout spines. Perisynaptic actin forms a uniquely dynamic structure well suited for direct, active regulation of the synapse.

For data on expression in the embryo:
Manning, L., Purice, M.D., Roberts, J., Pollard, J.L., Bennett, A.L., Kroll, J.R., Dyukareva, A.V., Doan, P.N., Lupton, J.R., Strader, M.E., Tanner, S., Bauer, D., Wilbur, A., Tran, K.D., Laverty, T.R., Pearson, J.C., Crews, S.T., Rubin, G.M., and Doe, C.Q. (2012) Annotated embryonic CNS expression patterns of 5000 GMR GAL4 lines: a resource for manipulating gene expression and analyzing cis-regulatory motifs. Cell Reports (2012) Doi: 10.1016/j.celrep.2012.09.009 http://www.cell.com/cell-reports/fulltext/S2211-1247(12)00290-2 synapse was substantially elevated, at the endocytic zone there was no enhanced polymerization activity. We conclude that actin subserves spatially diverse, independently regulated processes throughout spines. Perisynaptic actin forms a uniquely dynamic structure well suited for direct, active regulation of the synapse.

For data on expression in imaginal discs:
Jory, A., Estella, C., Giorgianni, M.W., Slattery, M., Laverty, T.R., Rubin, G.M., and Mann, R.S. (2012) A survey of 6300 genomic fragments for cis-regulatory activity in the imaginal discs of Drosophila melanogaster. Cell Reports (2012) Doi: 10.1016/j.celrep.2012.09.010 http://www.cell.com/cell-reports/fulltext/S2211-1247(12)00291-4 synapse was substantially elevated, at the endocytic zone there was no enhanced polymerization activity. We conclude that actin subserves spatially diverse, independently regulated processes throughout spines. Perisynaptic actin forms a uniquely dynamic structure well suited for direct, active regulation of the synapse.

For data on expression in the larval nervous system:
Li, H.-H., Kroll, J.R., Lennox, S., Ogundeyi, O., Jeter, J., Depasquale, G., and Truman, J.W. (2013) A GAL4 driver resource for developmental and behavioral studies on the larval CNS of Drosophila. Cell Reports (submitted).

}, issn = {2211-1247}, doi = {10.1016/j.celrep.2012.09.011}, author = {Jenett, Arnim and Rubin, Gerald M and Ngo, Teri-T B and Shepherd, David and Murphy, Christine and Dionne, Heather and Pfeiffer, Barret D and Cavallaro, Amanda and Hall, Donald and Jeter, Jennifer and Iyer, Nirmala and Fetter, Dona and Hausenfluck, Joanna H and Peng, Hanchuan and Trautman, Eric T and Svirskas, Robert R and Myers, Eugene W and Iwinski, Zbigniew R and Aso, Yoshinori and Depasquale, Gina M and Enos, Adrianne and Hulamm, Phuson and Lam, Shing Chun Benny and Li, Hsing-Hsi and Laverty, Todd R and Long, Fuhui and Qu, Lei and Murphy, Sean D and Rokicki, Konrad and Safford, Todd and Shaw, Kshiti and Simpson, Julie H and Sowell, Allison and Tae, Susana and Yu, Yang and Zugates, Christopher T} }