David L. Richmond

Unilamellar vesicle formation and encapsulation by microfluidic jetting

Compartmentalization of biomolecules within lipid membranes is a fundamental requirement of living systems and an essential feature of many pharmaceutical therapies. However, applications of membrane-enclosed solutions of proteins, DNA, and other biologically active compounds have been limited by the difficulty of forming unilamellar vesicles with controlled contents in a repeatable manner. Here, we demonstrate a method for simultaneously creating and loading giant unilamellar vesicles (GUVs) using a pulsed microfluidic jet. Akin to blowing a bubble, the microfluidic jet deforms a planar lipid bilayer into a vesicle that is filled with solution from the jet and separates from the planar bilayer. In contrast with existing techniques, our method rapidly generates multiple monodisperse, unilamellar vesicles containing solutions of unrestricted composition and molecular weight. Using the microfluidic jetting technique, we demonstrate repeatable encapsulation of 500-nm particles into GUVs and show that functional pore proteins can be incorporated into the vesicle membrane to mediate transport. The ability of microfluidic jetting to controllably encapsulate solutions inside of GUVs creates new opportunities for the study and use of compartmentalized biomolecular systems in science, industry, and medicine.

Forming giant vesicles with controlled membrane composition, asymmetry, and contents

Growing knowledge of the key molecular components involved in biological processes such as endocytosis, exocytosis, and motility has enabled direct testing of proposed mechanistic models by reconstitution. However, current techniques for building increasingly complex cellular structures and functions from purified components are limited in their ability to create conditions that emulate the physical and biochemical constraints of real cells. Here we present an integrated method for forming giant unilamellar vesicles with simultaneous control over (i) lipid composition and asymmetry, (ii) oriented membrane protein incorporation, and (iii) internal contents. As an application of this method, we constructed a synthetic system in which membrane proteins were delivered to the outside of giant vesicles, mimicking aspects of exocytosis. Using confocal fluorescence microscopy, we visualized small encapsulated vesicles docking and mixing membrane components with the giant vesicle membrane, resulting in exposure of previously encapsulated membrane proteins to the external environment. This method for creating giant vesicles can be used to test models of biological processes that depend on confined volume and complex membrane composition, and it may be useful in constructing functional systems for therapeutic and biomaterials applications.

Death Receptors DR6 and TROY Regulate Brain Vascular Development

Signaling events that regulate central nervous system (CNS) angiogenesis and blood-brain barrier (BBB) formation are only beginning to be elucidated. By evaluating the gene expression profile of mouse vasculature, we identified DR6/TNFRSF21 and TROY/TNFRSF19 as regulators of CNS-specific angiogenesis in both zebrafish and mice. Furthermore, these two death receptors interact both genetically and physically and are required for vascular endothelial growth factor (VEGF)-mediated JNK activation and subsequent human brain endothelial sprouting in vitro. Increasing beta-catenin levels in brain endothelium upregulate DR6 and TROY, indicating that these death receptors are downstream target genes of Wnt/beta-catenin signaling, which has been shown to be required for BBB development. These findings define a role for death receptors DR6 and TROY in CNS-specific vascular development.

Inkjet formation of unilamellar lipid vesicles for cell-like encapsulation.

Encapsulation of macromolecules within lipid vesicles has the potential to drive biological discovery and enable development of novel, cell-like therapeutics and sensors. However, rapid and reliable production of large numbers of unilamellar vesicles loaded with unrestricted and precisely-controlled contents requires new technologies that overcome size, uniformity, and throughput limitations of existing approaches. Here we present a high-throughput microfluidic method for vesicle formation and encapsulation using an inkjet printer at rates up to 200 Hz. We show how multiple high-frequency pulses of the inkjets piezoelectric actuator create a microfluidic jet that deforms a bilayer lipid membrane, controlling formation of individual vesicles. Variations in pulse number, pulse voltage, and solution viscosity are used to control the vesicle size. As a first step toward cell-like reconstitution using this method, we encapsulate the cytoskeletal protein actin and use co-encapsulated microspheres to track its polymerization into a densely entangled cytoskeletal network upon vesicle formation.

A Doppler effect in embryonic pattern formation

Observing an embryonic Doppler effect The sound of an oncoming train changes as it passes you, a phenomenon termed the Doppler effect. Soroldoni et al. propose a similar event during the formation of vertebrate embryo body segments. It is generally thought that the internal timing of a genetic oscillator called the “segmentation clock” sets the rhythm of body segments called somites. However, time-lapse microscopy of the spatial waves of oscillations and the timing of body segment formation showed segments forming faster than spatial genetic oscillations. This “Doppler effect” occurs because the end of the oscillating tissue moves steadily into the oncoming waves. Thus, the rhythm of sequential body segmentation is a function of genetic oscillations, their changing wave pattern, and tissue shortening. Science, this issue p. 222 Genetic oscillations, their changing spatial pattern, and tissue shortening direct the rhythm of sequential body segmentation. During embryonic development, temporal and spatial cues are coordinated to generate a segmented body axis. In sequentially segmenting animals, the rhythm of segmentation is reported to be controlled by the time scale of genetic oscillations that periodically trigger new segment formation. However, we present real-time measurements of genetic oscillations in zebrafish embryos showing that their time scale is not sufficient to explain the temporal period of segmentation. A second time scale, the rate of tissue shortening, contributes to the period of segmentation through a Doppler effect. This contribution is modulated by a gradual change in the oscillation profile across the tissue. We conclude that the rhythm of segmentation is an emergent property controlled by the time scale of genetic oscillations, the change of oscillation profile, and tissue shortening.

Stratified Tidal Flow over a Bump

The interaction of a stratified flow with an isolated topographic feature can introduce numerous disturbances into the flow, including turbulent wakes, internal waves, and eddies. Measurements made near a “bump” east of Race Rocks, Vancouver Island, reveal a wide range of phenomena associated with the variable flow speeds and directions introduced by the local tides. Upstream and downstream flows were observed by placing two acoustic Doppler current profilers (ADCPs) on one flank of the bump. Simultaneous shipboard ADCP surveys corroborated some of the more striking features. Froude number conditions varied from subcritical to supercritical as the tidal velocities varied from 0.2 to 1.5 m s 1 . During the strong ebb, when the moored ADCPs were located on the lee side, a persistent full-water-depth lee wave was detected in one of the moored ADCPs and the shipboard ADCP. However, the placement of the moorings would suggest that, by the time it appears in the moored ADCP beams, the lee wave has been swept downstream or has separated from the bump. Raw ADCP beam velocities suggest enhanced turbulence during various phases of the tide. Many of the three-dimensional flow characteristics are in good agreement with laboratory studies, and some characteristics, such as shear in the bottom boundary layer, are not.

The segmentation clock: inherited trait or universal design principle?

Metamerism is a widespread feature of multicellular body plans; however, our understanding of the underlying mechanisms that generate these patterns is currently based on only a few model organisms. In particular, vertebrate embryos use a segmentation clock to rhythmically and sequentially add segments in concert with posterior elongation of their body. Recent evidence of a segmentation clock acting in arthropods indicates that this mechanism may be a widely used strategy for generating serial anatomy in animals. Whether this is due to homology or convergence is not yet known, but the recent discovery of an oscillatory process associated with the production of sequential root primordia in plants suggests that a segmentation clock is a fundamental patterning principle in growing tissues, independent of ancestry. In this review, we consider the principles of the segmentation clock that may be conserved across the animal and plant kingdoms, and discuss opportunities for cross-fertilization between these active fields of research.

Uncertainty-Driven Forest Predictors for Vertebra Localization and Segmentation

Accurate localization, identification and segmentation of vertebrae is an important task in medical and biological image analysis. The prevailing approach to solve such a task is to first generate pixelindependent features for each vertebra, e.g. via a random forest predictor, which are then fed into an MRF-based objective to infer the optimal MAP solution of a constellation model. We abandon this static, twostage approach and mix feature generation with model-based inference in a new, more flexible, way. We evaluate our method on two data sets with different objectives. The first is semantic segmentation of a 21-part body plan of zebrafish embryos in microscopy images, and the second is localization and identification of vertebrae in benchmark human CT.

Convexity Shape Constraints for Image Segmentation

Segmenting an image into multiple components is a central task in computer vision. In many practical scenarios, prior knowledge about plausible components is available. Incorporating such prior knowledge into models and algorithms for image segmentation is highly desirable, yet can be non-trivial. In this work, we introduce a new approach that allows, for the first time, to constrain some or all components of a segmentation to have convex shapes. Specifically, we extend the Minimum Cost Multicut Problem by a class of constraints that enforce convexity. To solve instances of this NP-hard integer linear program to optimality, we separate the proposed constraints in the branch-and-cut loop of a state-of-the-art ILP solver. Results on photographs and micrographs demonstrate the effectiveness of the approach as well as its advantages over the state-of-the-art heuristic.

Mapping Auto-context Decision Forests to Deep ConvNets for Semantic Segmentation.

We consider the task of pixel-wise semantic segmentation given a small set of labeled training images. Among two of the most popular techniques to address this task are Decision Forests (DF) and Neural Networks (NN). In this work, we explore the relationship between two special forms of these techniques: stacked DFs (namely Auto-context) and deep Convolutional Neural Networks (ConvNet). Our main contribution is to show that Auto-context can be mapped to a deep ConvNet with novel architecture, and thereby trained end-to-end. This mapping can be used as an initialization of a deep ConvNet, enabling training even in the face of very limited amounts of training data. We also demonstrate an approximate mapping back from the refined ConvNet to a second stacked DF, with improved performance over the original. We experimentally verify that these mappings outperform stacked DFs for two different applications in computer vision and biology: Kinect-based body part labeling from depth images, and somite segmentation in microscopy images of developing zebrafish. Finally, we revisit the core mapping from a Decision Tree (DT) to a NN, and show that it is also possible to map a fuzzy DT, with sigmoidal split decisions, to a NN. This addresses multiple limitations of the previous mapping, and yields new insights into the popular Rectified Linear Unit (ReLU), and more recently proposed concatenated ReLU (CReLU), activation functions.