@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 {49177, title = {Joint deformable registration of large EM image volumes: a matrix solver approach.}, journal = {arXiv}, year = {2018}, month = {2018 Apr 26}, abstract = {

Large electron microscopy image datasets for connectomics are typically composed of thousands to millions of partially overlapping two-dimensional images (tiles), which must be registered into a coherent volume prior to further analysis. A common registration strategy is to find matching features between neighboring and overlapping image pairs, followed by a numerical estimation of optimal image deformation using a so-called solver program.\ 
Existing solvers are inadequate for large data volumes, and inefficient for small-scale image registration.\ 
In this work, an efficient and accurate matrix-based solver method is presented. A linear system is constructed that combines minimization of feature-pair square distances with explicit constraints in a regularization term. In absence of reliable priors for regularization, we show how to construct a rigid-model approximation to use as prior. The linear system is solved using available computer programs, whose performance on typical registration tasks we briefly compare, and to which future scale-up is delegated. Our method is applied to the joint alignment of 2.67 million images, with more than 200 million point-pairs and has been used for successfully aligning the first full adult fruit fly brain.

}, url = {https://arxiv.org/abs/1804.10019}, author = {Khairy, Khaled and Denisov, Gennady and Saalfeld, Stephan} } @article {49012, title = {A preferred curvature-based continuum mechanics framework for modeling embryogenesis.}, journal = {Biophysical Journal}, volume = {114}, year = {2018}, month = {2018 Jan 23}, pages = {267-77}, abstract = {

Mechanics plays a key role in the development of higher organisms. However, understanding this relationship is complicated by the difficulty of modeling the link between local forces generated at the subcellular level and deformations observed at the tissue and whole-embryo levels. Here we propose an approach first developed for lipid bilayers and cell membranes, in which force-generation by cytoskeletal elements enters a continuum mechanics formulation for the full system in the form of local changes in preferred curvature. This allows us to express and solve the system using only tissue strains. Locations of preferred curvature are simply related to products of gene expression. A solution, in that context, means relaxing the system{\textquoteright}s mechanical energy to yield global morphogenetic predictions that accommodate a tendency toward the local preferred curvature, without a need to explicitly model force-generation mechanisms at the molecular level. Our computational framework, which we call SPHARM-MECH, extends a 3D spherical harmonics parameterization known as SPHARM to combine this level of abstraction with a sparse shape representation. The integration of these two principles allows computer simulations to be performed in three dimensions on highly complex shapes, gene expression patterns, and mechanical constraints. We demonstrate our approach by modeling mesoderm invagination in the fruit-fly embryo, where local forces generated by the acto-myosin meshwork in the region of the future mesoderm lead to formation of a ventral tissue fold. The process is accompanied by substantial changes in cell shape and long-range cell movements. Applying SPHARM-MECH to whole-embryo live imaging data acquired with light-sheet microscopy reveals significant correlation between calculated and observed tissue movements. Our analysis predicts the observed cell shape anisotropy on the ventral side of the embryo and suggests an active mechanical role of mesoderm invagination in supporting the onset of germ-band extension.

}, doi = {10.1016/j.bpj.2017.11.015}, author = {Khairy, Khaled and Lemon, William C and Amat, Fernando and Keller, Philipp J} } @article {45457, title = {Light sheet-based imaging and analysis of early embryogenesis in the fruit fly.}, journal = {Methods in Molecular Biology}, volume = {1189}, year = {2015}, month = {2015}, pages = {79-97}, abstract = {

The fruit fly is an excellent model system for investigating the sequence of epithelial tissue invaginations constituting the process of gastrulation. By combining recent advancements in light sheet fluorescence microscopy (LSFM) and image processing, the three-dimensional fly embryo morphology and relevant gene expression patterns can be accurately recorded throughout the entire process of embryogenesis. LSFM provides exceptionally high imaging speed, high signal-to-noise ratio, low level of photoinduced damage, and good optical penetration depth. This powerful combination of capabilities makes LSFM particularly suitable for live imaging of the fly embryo.The resulting high-information-content image data are subsequently processed to obtain the outlines of cells and cell nuclei, as well as the geometry of the whole embryo tissue by image segmentation. Furthermore, morphodynamics information is extracted by computationally tracking objects in the image. Towards that goal we describe the successful implementation of a fast fitting strategy of Gaussian mixture models.The data obtained by image processing is well-suited for hypothesis testing of the detailed biomechanics of the gastrulating embryo. Typically this involves constructing computational mechanics models that consist of an objective function providing an estimate of strain energy for a given morphological configuration of the tissue, and a numerical minimization mechanism of this energy, achieved by varying morphological parameters.In this chapter, we provide an overview of in vivo imaging of fruit fly embryos using LSFM, computational tools suitable for processing the resulting images, and examples of computational biomechanical simulations of fly embryo gastrulation.

}, issn = {1940-6029}, doi = {10.1007/978-1-4939-1164-6_6}, author = {Khairy, Khaled and Lemon, William C and Amat, Fernando and Keller, Philipp J} } @article {5346, title = {Light sheet microscopy in cell biology.}, journal = {Methods in Molecular Biology}, volume = {931}, year = {2013}, month = {2013}, pages = {123-37}, abstract = {

Light sheet-based fluorescence microscopy (LSFM) is emerging as a powerful imaging technique for the life sciences. LSFM provides an exceptionally high imaging speed, high signal-to-noise ratio, low level of photo-bleaching, and good optical penetration depth. This unique combination of capabilities makes light sheet-based microscopes highly suitable for live imaging applications. Here, we provide an overview of light sheet-based microscopy assays for in vitro and in vivo imaging of biological samples, including cell extracts, soft gels, and large multicellular organisms. We furthermore describe computational tools for basic image processing and data inspection.

}, issn = {1940-6029}, doi = {10.1007/978-1-62703-056-4_7}, author = {Tomer, Raju and Khairy, Khaled and Keller, Philipp J} } @article {4898, title = {Quantitative high-speed imaging of entire developing embryos with simultaneous multiview light-sheet microscopy.}, journal = {Nature Methods}, volume = {9}, year = {2012}, month = {2012 Jun 3}, pages = {755-63}, abstract = {

Live imaging of large biological specimens is fundamentally limited by the short optical penetration depth of light microscopes. To maximize physical coverage, we developed the SiMView technology framework for high-speed in vivo imaging, which records multiple views of the specimen simultaneously. SiMView consists of a light-sheet microscope with four synchronized optical arms, real-time electronics for long-term sCMOS-based image acquisition at 175 million voxels per second, and computational modules for high-throughput image registration, segmentation, tracking and real-time management of the terabytes of multiview data recorded per specimen. We developed one-photon and multiphoton SiMView implementations and recorded cellular dynamics in entire Drosophila melanogaster embryos with 30-s temporal resolution throughout development. We furthermore performed high-resolution long-term imaging of the developing nervous system and followed neuroblast cell lineages in vivo. SiMView data sets provide quantitative morphological information even for fast global processes and enable accurate automated cell tracking in the entire early embryo.

High-resolution movies in the Digital Embryo repository
Nature News: "Fruitfly development, cell by cell" by Lauren Gravitz
Nature Methods Technology Feature: "Faster frames, clearer pictures" by Monya Baker
Andor Insight Awards: Life Sciences Winner

}, issn = {1548-7105}, doi = {10.1038/nmeth.2062}, author = {Tomer, Raju and Khairy, Khaled and Amat, Fernando and Keller, Philipp J} } @article {5381, title = {Minimum-energy vesicle and cell shapes calculated using spherical harmonics parameterization.}, journal = {Soft Matter}, volume = {7}, year = {2011}, month = {2011 Jan 21}, pages = {2138-43}, abstract = {

An important open question in biophysics is to understand how mechanical forces shape membrane-bounded cells and their organelles. A general solution to this problem is to calculate the bending energy of an arbitrarily shaped membrane surface, which can include both lipids and cytoskeletal proteins, and minimize the energy subject to all mechanical constraints. However, the calculations are difficult to perform, especially for shapes that do not possess axial symmetry. We show that the spherical harmonics parameterization (SHP) provides an analytic description of shape that can be used to quickly and reliably calculate minimum energy shapes of both symmetric and asymmetric surfaces. Using this method, we probe the entire set of shapes predicted by the bilayer couple model, unifying work based on different computational approaches, and providing additional details of the transitions between different shape classes. In addition, we present new minimum-energy morphologies based on non-linear models of membrane skeletal elasticity that closely mimic extreme shapes of red blood cells. The SHP thus provides a versatile shape description that can be used to investigate forces that shape cells.

}, doi = {10.1039/c0sm01193b}, author = {Khairy, Khaled and Howard, Jonathon} } @article {1680, title = {Reconstructing embryonic development.}, journal = {Genesis}, volume = {49}, year = {2011}, month = {2010 Dec 7}, pages = {488-513}, abstract = {

Novel approaches to bio-imaging and automated computational image processing allow the design of truly quantitative studies in developmental biology. Cell behavior, cell fate decisions, cell interactions during tissue morphogenesis, and gene expression dynamics can be analyzed in vivo for entire complex organisms and throughout embryonic development. We review state-of-the-art technology for live imaging, focusing on fluorescence light microscopy techniques for system-level investigations of animal development and discuss computational approaches to image segmentation, cell tracking, automated data annotation, and biophysical modeling. We argue that the substantial increase in data complexity and size requires sophisticated new strategies to data analysis to exploit the enormous potential of these new resources.

}, issn = {1526-968X}, doi = {10.1002/dvg.20698}, author = {Khairy, Khaled and Keller, Philipp J} } @article {3684, title = {Shedding light on the system: studying embryonic development with light sheet microscopy.}, journal = {Current Opinion in Genetics and Development}, volume = {21}, year = {2011}, month = {2011 Aug}, pages = {558-65}, abstract = {

Light sheet-based fluorescence microscopy (LSFM) is emerging as a powerful imaging technique for the life sciences. LSFM provides an exceptionally high imaging speed, high signal-to-noise ratio, low level of photo-bleaching and good optical penetration depth. This unique combination of capabilities makes light sheet-based microscopes highly suitable for live imaging applications. There is an outstanding potential in applying this technology to the quantitative study of embryonic development. Here, we provide an overview of the different basic implementations of LSFM, review recent technical advances in the field and highlight applications in the context of embryonic development. We conclude with a discussion of promising future directions.

}, issn = {1879-0380}, doi = {10.1016/j.gde.2011.07.003}, author = {Tomer, Raju and Khairy, Khaled and Keller, Philipp J} } @article {2027, title = {Fast, high-contrast imaging of animal development with scanned light sheet-based structured-illumination microscopy.}, journal = {Nature Methods}, volume = {7}, year = {2010}, month = {08/2010}, pages = {637-42}, abstract = {

Recording light-microscopy images of large, nontransparent specimens, such as developing multicellular organisms, is complicated by decreased contrast resulting from light scattering. Early zebrafish development can be captured by standard light-sheet microscopy, but new imaging strategies are required to obtain high-quality data of late development or of less transparent organisms. We combined digital scanned laser light-sheet fluorescence microscopy with incoherent structured-illumination microscopy (DSLM-SI) and created structured-illumination patterns with continuously adjustable frequencies. Our method discriminates the specimen-related scattered background from signal fluorescence, thereby removing out-of-focus light and optimizing the contrast of in-focus structures. DSLM-SI provides rapid control of the illumination pattern, exceptional imaging quality, and high imaging speeds. We performed long-term imaging of zebrafish development for 58 h and fast multiple-view imaging of early Drosophila melanogaster development. We reconstructed cell positions over time from the Drosophila DSLM-SI data and created a fly digital embryo.

}, keywords = {Animals, Drosophila melanogaster, Embryo, Microscopy, Nonmammalian, Zebrafish}, issn = {1548-7105}, doi = {10.1038/nmeth.1476}, author = {Keller, Philipp J and Schmidt, Annette D and Santella, Anthony and Khairy, Khaled and Zhirong Bao and Wittbrodt, Joachim and Stelzer, Ernst H K} }