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Cells contain hundreds of organelles and macromolecular assemblies. Obtaining a complete understanding of their intricate organization requires the nanometre-level, three-dimensional reconstruction of whole cells, which is only feasible with robust and scalable automatic methods. Here, to support the development of such methods, we annotated up to 35 different cellular organelle classes—ranging from endoplasmic reticulum to microtubules to ribosomes—in diverse sample volumes from multiple cell types imaged at a near-isotropic resolution of 4 nm per voxel with focused ion beam scanning electron microscopy (FIB-SEM)1. We trained deep learning architectures to segment these structures in 4 nm and 8 nm per voxel FIB-SEM volumes, validated their performance and showed that automatic reconstructions can be used to directly quantify previously inaccessible metrics including spatial interactions between cellular components. We also show that such reconstructions can be used to automatically register light and electron microscopy images for correlative studies. We have created an open data and open-source web repository, ‘OpenOrganelle’, to share the data, computer code and trained models, which will enable scientists everywhere to query and further improve automatic reconstruction of these datasets. Focused ion beam scanning electron microscopy (FIB-SEM) combined with deep-learning-based segmentation is used to produce three-dimensional reconstructions of complete cells and tissues, in which up to 35 different organelle classes are annotated.

Cells contain hundreds of different organelle and macromolecular assemblies intricately organized relative to each other to meet any cellular demands. Obtaining a complete understanding of their organization is challenging and requires nanometer-level, threedimensional reconstruction of whole cells. Even then, the immense size of datasets and large number of structures to be characterized requires generalizable, automatic methods. To meet this challenge, we developed an analysis pipeline for comprehensively reconstructing and analyzing the cellular organelles in entire cells imaged by focused ion beam scanning electron microscopy (FIB-SEM) at a near-isotropic size of 4 or 8 nm per voxel. The pipeline involved deep learning architectures trained on diverse samples for automatic reconstruction of 35 different cellular organelle classes - ranging from endoplasmic reticulum to microtubules to ribosomes - from multiple cell types.Automatic reconstructions were used to directly quantify various previously inaccessible metrics about these structures, including their spatial interactions. We show that automatic organelle reconstructions can also be used to automatically register light and electron microscopy images for correlative studies. We created an open data and open source web repository, OpenOrganelle, to share the data, computer code, and trained models, enabling scientists everywhere to query and further reconstruct the datasets.

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 Drosophila melanogaster. 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’s brain., eLife digest Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons – compared to some 86 billion in humans – the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map – or connectome – the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

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 Drosophila melanogaster. 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’s brain.

The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses, and proofread such large data sets; new methods that define cell types based on connectivity in addition to morphology; and new methods to simplify access to a large and evolving data set. From the resulting data we derive a better definition of computational compartments and their connections; an exhaustive atlas of cell examples and types, many of them novel; detailed circuits for most of the central brain; and exploration of the statistics and structure of different brain compartments, and the brain as a whole. We make the data public, with a web site and resources specifically designed to make it easy to explore, for all levels of expertise from the expert to the merely curious. The public availability of these data, and the simplified means to access it, dramatically reduces the effort needed to answer typical circuit questions, such as the identity of upstream and downstream neural partners, the circuitry of brain regions, and to link the neurons defined by our analysis with genetic reagents that can be used to study their functions.Note: In the next few weeks, we will release a series of papers with more involved discussions. One paper will detail the hemibrain reconstruction with more extensive analysis and interpretation made possible by this dense connectome. Another paper will explore the central complex, a brain region involved in navigation, motor control, and sleep. A final paper will present insights from the mushroom body, a center of multimodal associative learning in the fly brain.

SummaryNeuronal cell types are the nodes of neural circuits that determine the flow of information within the brain. Neuronal morphology, especially the shape of the axonal arbor, provides an essential descriptor of cell type and reveals how individual neurons route their output across the brain. Despite the importance of morphology, few projection neurons in the mouse brain have been reconstructed in their entirety. Here we present a robust and efficient platform for imaging and reconstructing complete neuronal morphologies, including axonal arbors that span substantial portions of the brain. We used this platform to reconstruct more than 1,000 projection neurons in the motor cortex, thalamus, subiculum, and hypothalamus. Together, the reconstructed neurons comprise more than 75 meters of axonal length and are available in a searchable online database. Axonal shapes revealed previously unknown subtypes of projection neurons and suggest organizational principles of long-range connectivity.

We used coarse-grained molecular dynamics simulations to examine the effects of transmembrane α-helical WALP peptides on the behavior of four-component lipid mixtures. These mixtures contain a high-melting temperature (high-Tm) lipid, a nanodomain-inducing low-Tm lipid, a macrodomain-inducing low-Tm lipid and cholesterol to model the outer leaflet of cell plasma membranes. In a series of simulations, we incrementally replace the nanodomain-inducing low-Tm lipid by the macrodomain-inducing low-Tm lipid and measure how lipid and phase properties are altered by the addition of WALPs of different length. Regardless of the ratio of the two low-Tm lipids, shorter WALPs increase domain size and all WALPs increase domain alignment between the two leaflets. These effects are smallest for the longest WALP tested, and increase with increasing WALP concentration. Thus, our simulations explain the experimental observation that WALPs induce macroscopic domains in otherwise nanodomain-forming lipid-only mixtures (unpublished). Since the cell plasma membrane contains a large fraction of transmembrane proteins, these findings link the behavior of lipid-only model membranes in vitro to phase behavior in vivo.

In the present chapter we discuss the complex mixing behaviour of plasma membrane lipids. To do so, we first introduce the plasma membrane and membrane mixtures often used to model its complexity. We then discuss the nature of lipid phase behaviour in bilayers and the distinction between these phases and other manifestations of non-random mixing found in one-phase mixtures, such as clusters, micelles and microemulsions. Finally, we demonstrate the applicability of Gibbs phase diagrams to the study of increasingly complex model membrane systems, with a focus on phase coexistence, morphology and their implications for the cell plasma membrane.

A number of highly curved membranes in vivo, such as epithelial cell microvilli, have the relatively high sphingolipid content associated with "raft-like" composition. Given the much lower bending energy measured for bilayers with "nonraft" low sphingomyelin and low cholesterol content, observing high curvature for presumably more rigid compositions seems counterintuitive. To understand this behavior, we measured membrane rigidity by fluctuation analysis of giant unilamellar vesicles. We found that including a transmembrane helical GWALP peptide increases the membrane bending modulus of the liquid-disordered (Ld) phase. We observed this increase at both low-cholesterol fraction and higher, more physiological cholesterol fraction. We find that simplified, commonly used Ld and liquid-ordered (Lo) phases are not representative of those that coexist. When Ld and Lo phases coexist, GWALP peptide favors the Ld phase with a partition coefficient of 3–10 depending on mixture composition. In model membranes at high cholesterol fractions, Ld phases with GWALP have greater bending moduli than the Lo phase that would coexist.

Simplified lipid mixtures are often used to model the complex behavior of the cell plasma membrane. Indeed, as few as four components — a high-melting lipid, a nandomain-inducing low-melting lipid, a macrodomain-inducing low-melting lipid and cholesterol (chol) — can give rise to a wide range of domain sizes and patterns that are highly sensitive to lipid compositions. Though these systems are studied extensively with experiments, the molecular-level details governing their phase behavior are not yet known. We address this issue by using molecular dynamics simulations to analyze how phase separation evolves in a four-component system as it transitions from small domains to large domains. To do so, we fix concentrations of the high-melting lipid 16:0,16:0-phosphatidylcholine (DPPC) and chol, and incrementally replace the nanodomain-inducing low-melting lipid 16:0,18:2-PC (PUPC) by the macrodomain-inducing low-melting lipid 18:2,18:2-PC (DUPC). Coarse-grained simulations of this four-component system reveal that lipid demixing increases as the amount of DUPC increases. Additionally, we find that domain size and interleaflet alignment change sharply over a narrow range of replacement of PUPC by DUPC, indicating that intraleaflet and interleaflet behaviors are coupled. Corresponding united atom simulations show that only lipids within ~ 2 nm of the phase interface are significantly perturbed regardless of domain composition or size. Thus, whereas the fraction of interface-perturbed lipids is negligible for large domains, it is significant for smaller ones. Together, these results reveal characteristic traits of bilayer thermodynamic behavior in four-component mixtures, and provide a baseline for investigation of the effects of proteins and other lipids on membrane phase properties.

To better understand animal cell plasma membranes, we studied simplified models, namely four-component lipid bilayer mixtures. Here we describe the domain size transition in the region of coexisting liquid-disordered (Ld) + liquid-ordered (Lo) phases. This transition occurs abruptly in composition space with domains increasing in size by two orders of magnitude, from tens of nanometers to microns. We measured the line tension between coexisting Ld and Lo domains close to the domain size transition for a variety of lipid mixtures, finding that in every case the transition occurs at a line tension of ∼0.3 pN. A computational model incorporating line tension and dipole repulsion indicated that even small changes in line tension can result in domains growing in size by several orders of magnitude, consistent with experimental observations. We find that other properties of the coexisting Ld and Lo phases do not change significantly in the vicinity of the abrupt domain size transition.

Ternary mixtures of high-melting lipid, low-melting lipid, and cholesterol exhibit a region of liquid-ordered + liquid-disordered phase coexistence analogous to raft + non-raft behavior in cells. These coexisting phases manifest domain sizes that range from a few nanometers to many microns, depending strongly on the nature of the low-melting lipid. When POPC, which gives rise to nanodomains, is replaced by DOPC, which yields macrodomains, an intermediate region is observed of patterned, or modulated phases. This domain morphology can be explained as a competition between line tension and bending energies with patterns occurring when the two are nearly balanced. Necessary for testing this model are measurements of line tension, and bending moduli for both phases. Here we report the bending moduli of coexisting Lo and Ld phases from mixtures that produce domains ranging in size from nanoscopic to macroscopic. Measurements were made by shape analysis of giant unilamellar vesicles with both fluorescence and phase contrast microscopy. Vesicles of a single phase were made by the gentle hydration method to obtain a more narrow distribution of vesicle tensions than is obtained by electroformation. A transmembrane helical peptide, WALP23, strongly partitions to the liquid disordered phase, and changes the size of coexisting Lo + Ld domains. We are currently investigating the effects of WALP23 on membrane mechanical properties and line tension.

Cells must be able to maintain and change membrane shape. This membrane curvature can be influenced by any lateral phase heterogeneity. Ternary mixtures of high-melting lipid, low-melting lipid, and cholesterol exhibit a region of liquid-ordered (Lo)+ liquid-disordered (Ld) phase coexistence analogous to raft + non-raft behavior in cells. Although curvature can induce separation and sorting in vitro, a number of highly-curved membranes in vivo have raft-like composition, which is puzzling since the raft-like compositions have greater rigidity in lipid model mixtures. We find that including transmembrane helical WALP peptides as a component of the model mixtures greatly changes their bending behavior. Measurements were made by shape analysis of giant unilamellar vesicles with both fluorescence and phase contrast microscopy. Vesicles of a single phase were made by the gentle hydration method to obtain a more narrow distribution of vesicle tensions than is obtained by electroformation. We find that a WALP peptide component rigidifies the liquid-disordered phase whereas the liquid-ordered phase is unaffected. This rigidifying effect might be related to the monolayers sliding relative to each other. Further, we have investigated the effects of peptides of different lengths and results suggest a role for hydrophobic mismatch of the peptide component relative to the bilayer thickness.

The presence and the properties of lipid bilayer nanometer-scale domains might be important for understanding the membranes of living cells. We used molecular dynamics (MD) simulations to investigate perturbations of a small patch of fluid-phase DPPC bilayer upon incorporation of fluorescent indocarbocyanine lipid probes commonly used to study membranes (DiI-C12:0, DiI-C18:0, or DiI-C18:2). In simulations containing 1 probe per 64 total lipids in each leaflet, an 8 - 12% decrease in chain order is observed for DPPC molecules in the solvation shell closest to the probe, relative to a pure DPPC bilayer. A ~5% increase in chain order is seen in the next three shells, resulting in a small overall increase in average DPPC chain order. In simulations with 1 probe per 256 total lipids in each leaflet, average DPPC chain order is unaffected by the probe. Thus, these DiI probes cause an oscillatory perturbation of their local environment but do not strongly influence the average properties of even "nanoscopic" lipid phase domains., 30 pages, 12 figures

Quaternary lipid mixtures containing a high-melting lipid, a nanodomain-inducing low-melting lipid, a macrodomain-inducing low-melting lipid and cholesterol reveal behaviors not observed in ternary mixtures. Through fixing the amounts of high-melting lipid, total low-melting lipid and cholesterol and altering only the relative amounts of the two low-melting lipids, domain size in quaternary mixtures can be finely tuned from nanoscopic to macroscopic, with an intermediate patterned phase morphology. We have previously used extensive coarse grain and atomistic molecular dynamics simulations to study one such quaternary lipid mixture, containing the high-melting lipid DPPC (16:0,16:0-PC), the low-melting lipids PUPC (16:0,18:2-PC) and DUPC (18:2,18:2-PC), and cholesterol. In particular, we quantified the effect of the two low-melting lipids on domain size, alignment, lipid order and lipid tilt. Using those simulations as a control, we are currently evaluating how adding WALP peptides to the quaternary mixture affects the sizes, alignment and properties of coexisting phases using coarse grained molecular dynamics. We examine how these properties are affected by both the length of the WALP peptide as well as their concentration. A main focus of our work is analyzing the extent to which the WALPs alter the onset of large-scale phase separation and domain alignment. The addition of WALP to the quaternary systems makes these simulations some of the most complex and biologically relevant membranes studied to date with molecular dynamics.

Giant Unilamelar Vesicles (GUVs) appear uniform for the brain-SM/POPC/Chol bilayer mixture, whereas GUVs exhibit macroscopic domains of coexisting liquid-disordered + liquid-ordered phases for the brain-SM/DOPC/Chol mixture. We can travel through composition space in order to study this transition from nanodomains with POPC to macrodomains with DOPC. Using ρ defined as the ratio [DOPC]/[DOPC]+[POPC], the domain morphology undergoes a transition regime where “modulated phases” appear as a function of ρ. The formation of these different morphologies on a GUV can be understood as a competition between line tension, which favors large domains, and bending energy, which favors small domains (Amazon et al). We measured the ρ values where modulated phases appear for different 4-component mixtures, using brain-SM, or egg-SM, or palmitoyl-SM as the high-melting lipid, and DOPC/POPC or DOPC/SOPC as the low melting lipids, for a total of six different 4-component mixtures. We then measured the line tension of the macroscopic domains vs ρ, and found the same line tension at ρ values at the transition between modulated phases and macroscopic phases. This finding implies that line tension has major control over domain morphology. We are currently studying how the transmembrane peptide, GWALP-23, changes the morphology by changing the values of the competing interactions.

The cell plasma membrane is often modeled using three-component mixtures containing a high melting lipid, a low melting lipid and cholesterol. These ternary mixtures exhibit either nanoscopoic or macroscopic liquid-liquid phase coexistence. An additional patterned phase morphology can exist in four component systems which combine a high melting lipid, cholesterol, a nanodomain-inducing low melting lipid and a macrodomain-inducing low melting lipid. The molecular-level details governing these different phase morphologies are not yet known. Here, we utilize molecular dynamics simulations to analyze how phase separation evolves in a four component mixture. We present data for 11 mixtures at a fixed composition of (16:0,16:0)-pc/(18:2,18:2)-pc/(16:0,18:2)-pc/Cholesterol (DPPC/DLiPC/PLiPC/Chol), where PLiPC is incrementally replaced by DLiPC from one simulation to the next. Each simulation was run to equilibrium over 25 μs using the Martini coarse grained forcefield and was then converted to united atom and run for a further 100 ns. We investigate trends in domain size, composition, interleaflet coupling and properties of the domain interface as a function of replacement of PLiPC by DLiPC.

Fluorescent lipid analogs are a valuable tool for studying membranes, and in recent years a wide variety of fluorescence techniques have contributed significantly to our understanding of lateral heterogeneity in both model and cell membranes. Despite their usefulness, it is often overlooked that these fluorescent molecules are extrinsic to the system of interest, and a meaningful interpretation of data, e.g. properties of nanoscopic domains, local motion and order of the probe environment, or Forster resonance energy transfer, can benefit from understanding probe location within the bilayer, and how the probe itself affects the native membrane state. We have conducted molecular dynamics simulations to investigate perturbations in a DPPC membrane of a family of commonly-used fluorescent lipids: the indocarbocyanine chromophore DiI attached to two alkyl chains, which vary in length and degree of unsaturation. In particular, we report on the order and dynamics of DPPC as a function of distance from the probe molecule, as well as the influence of probe acyl chains on the location and dynamics of the DiI chromophore.