Anisotropic particle multiphase equilibria in nonuniform fields.

We report a method to predict equilibrium concentration profiles of hard ellipses in nonuniform fields, including multiphase equilibria of fluid, nematic, and crystal phases. Our model is based on a balance of osmotic pressure and field mediated forces by employing the local density approximation. Implementation of this model requires development of accurate equations of state for each phase as a function of hard ellipse aspect ratio in the range k = 1-9. The predicted density profiles display overall good agreement with Monte Carlo simulations for hard ellipse aspect ratios k = 2, 4, and 6 in gravitational and electric fields with fluid-nematic, fluid-crystal, and fluid-nematic-crystal multiphase equilibria. The profiles of local order parameters for positional and orientational order display good agreement with values expected for bulk homogeneous hard ellipses in the same density ranges. Small discrepancies between predictions and simulations are observed at crystal-nematic and crystal-fluid interfaces due to limitations of the local density approximation, finite system sizes, and uniform periodic boundary conditions. The ability of the model to capture multiphase equilibria of hard ellipses in nonuniform fields as a function of particle aspect ratio provides a basis to control anisotropic particle microstructure on interfacial energy landscapes in diverse materials and applications.

Multistate Dynamic Pathways for Anisotropic Colloidal Assembly and Reconfiguration.

We report the controlled interfacial assembly and reconfiguration of rectangular prism colloidal particles between microstructures of varying positional and orientational order including stable, metastable, and transient states. Structurally diverse states are realized by programming time dependent electric fields that mediate dipolar interactions determining particle position, orientation, compression, and chaining. We identify an order parameter set that defines each state as a combination of the positional and orientational order. These metrics are employed as reaction coordinates to capture the microstructure evolution between initial and final states upon field changes. Assembly trajectory manifolds between states in the low-dimensional reaction coordinate space reveal a dynamic pathway map including information about pathway accessibility, reversibility, and kinetics. By navigating the dynamic pathway map, we demonstrate reconfiguration between states on minute time scales, which is practically useful for particle-based materials processing and device responses. Our findings demonstrate a conceptually general approach to discover dynamic pathways as a basis to control assembly and reconfiguration of self-organizing building blocks that respond to global external stimuli.

Colloidal Deposition by Polymer-Surfactant Complexes with Dilution and Shear.

Deposition of silica microparticles on glass substrates was measured as a function of cationic polymer-anionic surfactant composition and shear rate. Particles were initially deposited in quiescent conditions in different polymer-surfactant compositions, which were chosen based on prior measurements of composition-dependent polymer-surfactant interactions and deposition behavior (up to 0.5 wt % polymer and 12 wt % surfactant). Programmed shear and dilution profiles in a flow cell together with optical microscopy observation were used to continuously track particle deposition, detachment, and redeposition. Knowledge of the shear-dependent torque on each particle provides information on adhesive torque mediated by polymer-surfactant complexes. Detachment of colloids initially deposited by depletion interactions occurs at low shear rates (∼100 s-1) due to lack of tangential forces or an adhesive torque. Further dilution produced redeposition of particles that resisted detachment (up to ∼2000 s-1) as the result of strong cationic polymer bridge formation, presumably due to preferential surfactant removal. Dilution from different initial compositions indicates a pathway dependence of polymer-surfactant de-complexation into shear-resistant cationic bridges. These findings demonstrate the ability to program deposition behavior via the informed design of initial polymer-surfactant compositions and shear profiles. The particle trajectory analysis developed in this work provides an assay to screen composition-dependent colloidal deposition in diverse materials and applications.

The integrated LIM-peptidase domain of the CSA1-CHS3/DAR4 paired immune receptor detects changes in DA1 peptidase inhibitors in Arabidopsis.

White blister rust, caused by the oomycete Albugo candida, is a widespread disease of Brassica crops. The Brassica relative Arabidopsis thaliana uses the paired immune receptor complex CSA1-CHS3/DAR4 to resist Albugo infection. The CHS3/DAR4 sensor NLR, which functions together with its partner, the helper NLR CSA1, carries an integrated domain (ID) with homology to DA1 peptidases. Using domain swaps with several DA1 homologs, we show that the LIM-peptidase domain of the family member CHS3/DAR4 functions as an integrated decoy for the family member DAR3, which interacts with and inhibits the peptidase activities of the three closely related peptidases DA1, DAR1, and DAR2. Albugo infection rapidly lowers DAR3 levels and activates DA1 peptidase activity, thereby promoting endoreduplication of host tissues to support pathogen growth. We propose that the paired immune receptor CSA1-CHS3/DAR4 detects the actions of a putative Albugo effector that reduces DAR3 levels, resulting in defense activation.

Energy landscapes on polymerized liquid crystal interfaces.

We measure and model monolayers of concentrated diffusing colloidal probes interacting with polymerized liquid crystal (PLC) planar surfaces. At topological defects in local nematic director profiles at PLC surfaces, we observe time-averaged two-dimensional particle density profiles of diffusing colloidal probes that closely correlate with spatial variations in PLC optical properties. An inverse Monte Carlo analysis of particle concentration profiles yields two-dimensional PLC interfacial energy landscapes on the kT-scale, which is the inherent scale of many interfacial phenomena (e.g., self-assembly, adsorption, diffusion). Energy landscapes are modelled as the superposition of macromolecular repulsion and van der Waals attraction based on an anisotropic dielectric function obtained from the liquid crystal birefringence. Modelled van der Waals landscapes capture most net energy landscape variations and correlate well with experimental PLC director profiles around defects. Some energy landscape variations near PLC defects indicate either additional local repulsive interactions or possibly the need for more rigorous van der Waals models with complete spectral data. These findings demonstrate direct, sensitive measurements of kT-scale van der Waals energy landscapes at PLC interfacial defects and suggest the ability to design interfacial anisotropic materials and van der Waals energy landscapes for colloidal assembly.

Blood Protein Exclusion from Polymer Brushes.

We report interactions between adsorbed copolymers of poly(ethylene glycol) (PEG) in the presence of two abundant blood proteins, serum albumin and an immunoglobulin G, up to physiological blood concentrations. We directly and nonintrusively measure interactions between PEG triblock copolymers (PEG-PPO-PEG) adsorbed to hydrophobic colloids and surfaces using Total Internal Reflection Microscopy, which provides kT- and nanometer-scale resolution of interaction potentials (energy vs separation). In the absence of protein, adsorbed PEG copolymer repulsion is consistent with dimensions and architectures of PEG brushes on both colloids and surfaces. In the presence of proteins, we observe concentration dependent depletion attraction and no change to brush repulsion, indicating protein exclusion from PEG brushes. Because positive and negative protein adsorption are mutually exclusive, our observations of concentration dependent depletion attraction with no change to brush repulsion unambiguously indicate the absence of protein coronas at physiological protein concentrations. These findings demonstrate a direct sensitive approach to determine interactions between proteins and particle/surface coatings important to diverse biotechnology applications.

Design rules for 2D field mediated assembly of different shaped colloids into diverse microstructures.

Assembling different shaped particles into ordered microstructures is an open challenge in creating multifunctional particle-based materials and devices. Here, we report the two-dimensional (2D) AC electric field mediated assembly of different shaped colloidal particles into amorphous, liquid crystalline, and crystalline microstructures. Particle shapes investigated include disks, ellipses, squares, and rectangles, which show how systematic variations in anisotropy and corner curvature determine the number and type of resulting microstructures. AC electric fields induce dipolar interactions to control particle positional and orientational order. Microstructural states are determined via particle tracking to compute order parameters, which agree with computer simulations and show how particle packing and dipolar interactions together produce each structure. Results demonstrate how choice of particle shape and field conditions enable kinetically viable routes to assemble nematic, tetratic, and smectic liquid crystal structures as well as crystals with stretched 4- and 6-fold symmetry. Results show it is possible to assemble all corresponding hard particle phases, but also show how dipolar interactions influence and produce additional microstructures. Our findings provide design rules for the assembly of diverse microstructures of different shaped particles in AC electric fields, which could enable scalable and reconfigurable particle-based materials, displays, and printing technologies.

Modulation of receptor-like transmembrane kinase 1 nuclear localization by DA1 peptidases in Arabidopsis.

The cleavage of intracellular domains of receptor-like kinases (RLKs) has an important functional role in the transduction of signals from the cell surface to the nucleus in many organisms. However, the peptidases that catalyze protein cleavage during signal transduction remain poorly understood despite their crucial roles in diverse signaling processes. Here, we report in the flowering plant Arabidopsis thaliana that members of the DA1 family of ubiquitin-regulated Zn metallopeptidases cleave the cytoplasmic kinase domain of transmembrane kinase 1 (TMK1), releasing it for nuclear localization where it represses auxin-responsive cell growth during apical hook formation by phosphorylation and stabilization of the transcriptional repressors IAA32 and IAA34. Mutations in DA1 family members exhibited reduced apical hook formation, and DA1 family-mediated cleavage of TMK1 was promoted by auxin treatment. Expression of the DA1 family-generated intracellular kinase domain of TMK1 by an auxin-responsive promoter fully restored apical hook formation in a tmk1 mutant, establishing the function of DA1 family peptidase activities in TMK1-mediated differential cell growth and apical hook formation. DA1 family peptidase activity therefore modulates TMK1 kinase activity between a membrane location where it stimulates acid cell growth and initiates an auxin-dependent kinase cascade controlling cell proliferation in lateral roots and a nuclear localization where it represses auxin-mediated gene expression and growth.

Surface Morphology-Enhanced Delivery of Bioinspired Eco-Friendly Microcapsules.

We report the development of novel mineralized protein microcapsules to address critical challenges in the environmental impact and performance of consumer, pharmaceutical, agrochemical, cosmetic, and paint products. We designed environment-friendly capsules composed of proteins and biominerals as an alternative to solid microplastic particles or core-shell capsules made of nonbiodegradable synthetic polymeric resins. We synthesized mineralized capsule surface morphologies to mimic the features of natural pollens, which dramatically improved the deposition of high value-added fragrance chemicals on target substrates in realistic application conditions. A mechanistic model accurately captures the observed enhanced deposition behavior and shows how surface features generate an adhesive torque that resists shear detachment. Mineralized protein capsule performance is shown to depend both on material selection that determines van der Waals attraction and on capsule-substrate energy landscapes as parameterized by a geometric taxonomy for surface morphologies. These findings have broad implications for engineering multifunctional environmentally friendly delivery systems.

Hard superellipse phases: particle shape anisotropy & curvature.

We report computer simulations of two-dimensional convex hard superellipse particle phases vs. particle shape parameters including aspect ratio, corner curvature, and sidewall curvature. Shapes investigated include disks, ellipses, squares, rectangles, and rhombuses, as well as shapes with non-uniform curvature including rounded squares, rounded rectangles, and rounded rhombuses. Using measures of orientational order, order parameters, and a novel stretched bond orientational order parameter, we systematically identify particle shape properties that determine liquid crystal and crystalline phases including their coarse boundaries and symmetry. We observe phases including isotropic, nematic, tetratic, plastic crystals, square crystals, and hexagonal crystals (including stretched variants). Our results catalog known benchmark shapes, but include new shapes that also interpolate between known shapes. Our results indicate design rules for particle shapes that determine two-dimensional liquid, liquid crystalline, and crystalline microstructures that can be realized via particle assembly.

Anisotropic colloidal interactions & assembly in AC electric fields.

We match experimental and simulated configurations of anisotropic epoxy colloidal particles in high frequency AC electric fields by identifying analytical potentials for dipole-field and dipole-dipole interactions. We report an inverse Monte Carlo simulation algorithm to determine optimal fits of analytical potentials by matching simulated and experimental distribution functions for non-uniform liquid, liquid crystal, and crystal microstructures in varying amplitude electric fields. Two potentials that include accurate particle volume and dimensions along with a concentration dependent prefactor quantitatively capture experimental observations. At low concentrations, an effective ellipsoidal point dipole potential works well, whereas a novel stretched point dipole potential is found to be suitable at all concentrations, field amplitudes, and degrees of ordering. The simplicity, accuracy, and adjustability of the stretched point dipole potential suggest it can be applied to model field mediated microstructures and assembly of systematically varying anisotropic particle shapes.

Fast-forward breeding for a food-secure world.

Crop production systems need to expand their outputs sustainably to feed a burgeoning human population. Advances in genome sequencing technologies combined with efficient trait mapping procedures accelerate the availability of beneficial alleles for breeding and research. Enhanced interoperability between different omics and phenotyping platforms, leveraged by evolving machine learning tools, will help provide mechanistic explanations for complex plant traits. Targeted and rapid assembly of beneficial alleles using optimized breeding strategies and precise genome editing techniques could deliver ideal crops for the future. Realizing desired productivity gains in the field is imperative for securing an adequate future food supply for 10 billion people.

Droplet Formation and Growth Mechanisms in Reaction-Induced Spontaneous Emulsification of 3-(Trimethoxysilyl) Propyl Methacrylate.

Spontaneous emulsification of 3-(trimethoxysilyl) propyl methacrylate (TPM) can produce complex and active colloids, nanoparticles, or monodisperse Pickering emulsions. Despite the applicability of TPM in particle synthesis, the nucleation and growth mechanisms of TPM emulsions are still poorly understood. We investigate droplet formation and growth of TPM in aqueous solutions under quiescent conditions. Our results show that in the absence of stirring the mechanisms of diffusion and stranding likely drive the spontaneous emulsification of TPM through the formation of co-soluble species during hydrolysis. In addition, turbidity and dynamic light scattering experiments show that the pH modulates the growth mechanism. At pH 10.1, the droplets grow via Ostwald ripening, while at pH 11.5, the droplets grow via monomer addition. Adding surfactants [Tween, sodium dodecyl sulfate (SDS), or cetyltrimethylammonium bromide] leads to <100 nm droplets that are kinetically stable. The growth of Tween droplets occurs through addition of TPM species while the number density of droplets is kept constant. In addition, in the presence of the ionic surfactant SDS, electrostatic repulsion between the solubilized TPM species and SDS leads to a significant increase in the number density of droplets as well as additional nucleation events. Finally, imaging of the solubilization of TPM in capillaries shows that in the absence of a surfactant, TPM hydrolysis is likely the rate-limiting step for emulsification, whereas the presence of silica particles in the aqueous phase likely acts as a catalyst of TPM hydrolysis. Our experiments highlight the importance of diffusion and solubilization of TPM species in the aqueous phase in the nucleation and growth of droplets.

Controlling colloidal crystals via morphing energy landscapes and reinforcement learning.

We report a feedback control method to remove grain boundaries and produce circular shaped colloidal crystals using morphing energy landscapes and reinforcement learning-based policies. We demonstrate this approach in optical microscopy and computer simulation experiments for colloidal particles in ac electric fields. First, we discover how tunable energy landscape shapes and orientations enhance grain boundary motion and crystal morphology relaxation. Next, reinforcement learning is used to develop an optimized control policy to actuate morphing energy landscapes to produce defect-free crystals orders of magnitude faster than natural relaxation times. Morphing energy landscapes mechanistically enable rapid crystal repair via anisotropic stresses to control defect and shape relaxation without melting. This method is scalable for up to at least N = 103 particles with mean process times scaling as N 0.5 Further scalability is possible by controlling parallel local energy landscapes (e.g., periodic landscapes) to generate large-scale global defect-free hierarchical structures.

Multiple wheat genomes reveal global variation in modern breeding.

Advances in genomics have expedited the improvement of several agriculturally important crops but similar efforts in wheat (Triticum spp.) have been more challenging. This is largely owing to the size and complexity of the wheat genome1, and the lack of genome-assembly data for multiple wheat lines2,3. Here we generated ten chromosome pseudomolecule and five scaffold assemblies of hexaploid wheat to explore the genomic diversity among wheat lines from global breeding programs. Comparative analysis revealed extensive structural rearrangements, introgressions from wild relatives and differences in gene content resulting from complex breeding histories aimed at improving adaptation to diverse environments, grain yield and quality, and resistance to stresses4,5. We provide examples outlining the utility of these genomes, including a detailed multi-genome-derived nucleotide-binding leucine-rich repeat protein repertoire involved in disease resistance and the characterization of Sm16, a gene associated with insect resistance. These genome assemblies will provide a basis for functional gene discovery and breeding to deliver the next generation of modern wheat cultivars.

Variation in the expression of a transmembrane protein influences cell growth in Arabidopsis thaliana petals by altering auxin responses.

BACKGROUND: The same species of plant can exhibit very diverse sizes and shapes of organs that are genetically determined. Characterising genetic variation underlying this morphological diversity is an important objective in evolutionary studies and it also helps identify the functions of genes influencing plant growth and development. Extensive screens of mutagenised Arabidopsis populations have identified multiple genes and mechanisms affecting organ size and shape, but relatively few studies have exploited the rich diversity of natural populations to identify genes involved in growth control. RESULTS: We screened a relatively well characterised collection of Arabidopsis thaliana accessions for variation in petal size. Association analyses identified sequence and gene expression variation on chromosome 4 that made a substantial contribution to differences in petal area. Variation in the expression of a previously uncharacterised gene At4g16850 (named as KSK) had a substantial role on variation in organ size by influencing cell size. Over-expression of KSK led to larger petals with larger cells and promoted the formation of stamenoid features. The expression of auxin-responsive genes known to limit cell growth was reduced in response to KSK over-expression. ANT expression was also reduced in KSK over-expression lines, consistent with altered floral identities. Auxin responses were reduced in KSK over-expressing cells, consistent with changes in auxin-responsive gene expression. KSK may therefore influence auxin responses during petal development. CONCLUSIONS: Understanding how genetic variation influences plant growth is important for both evolutionary and mechanistic studies. We used natural populations of Arabidopsis thaliana to identify sequence variation in a promoter region of Arabidopsis accessions that mediated differences in the expression of a previously uncharacterised membrane protein. This variation contributed to altered auxin responses and cell size during petal growth.

Reduced chromatin accessibility underlies gene expression differences in homologous chromosome arms of diploid Aegilops tauschii and hexaploid wheat.

BACKGROUND: Polyploidy is centrally important in the evolution and domestication of plants because it leads to major genomic changes, such as altered patterns of gene expression, which are thought to underlie the emergence of new traits. Despite the common occurrence of these globally altered patterns of gene expression in polyploids, the mechanisms involved are not well understood. RESULTS: Using a precisely defined framework of highly conserved syntenic genes on hexaploid wheat chromosome 3DL and its progenitor 3 L chromosome arm of diploid Aegilops tauschii, we show that 70% of these gene pairs exhibited proportionately reduced gene expression, in which expression in the hexaploid context of the 3DL genes was ∼40% of the levels observed in diploid Ae tauschii. Several genes showed elevated expression during the later stages of grain development in wheat compared with Ae tauschii. Gene sequence and methylation differences probably accounted for only a few cases of differences in gene expression. In contrast, chromosome-wide patterns of reduced chromatin accessibility of genes in the hexaploid chromosome arm compared with its diploid progenitor were correlated with both reduced gene expression and the imposition of new patterns of gene expression. CONCLUSIONS: Our pilot-scale analyses show that chromatin compaction may orchestrate reduced gene expression levels in the hexaploid chromosome arm of wheat compared to its diploid progenitor chromosome arm.

Synergistic Polymer-Surfactant-Complex Mediated Colloidal Interactions and Deposition.

Total internal reflection microscopy (TIRM) is used to directly, sensitively, and simultaneously measure colloidal interactions, dynamics, and deposition for a broad range of polymer-surfactant compositions. A deposition state diagram containing comprehensive information about particle interactions, trajectories, and deposition behavior is obtained for polymer-surfactant compositions covering four decades in both polymer and surfactant concentrations. Bulk polymer-surfactant phase behavior and surface properties are characterized to provide additional information to interpret mechanisms. Materials investigated include cationic acrylamide-acrylamidopropyltrimonium copolymer (AAC), sodium lauryl ether sulfate (SLES) surfactant, silica colloids, and glass microscope slides. Measured colloid-substrate interaction potentials and deposition behavior show nonmonotonic trends vs polymer-surfactant composition and appear to be synergistic in the sense that they are not easily explained as the superposition of single-component-mediated interactions. Broad findings show that at some compositions polymer-surfactant complexes mediate bridging and depletion attractions that promote colloidal deposition, whereas other compositions produce electrosteric repulsion that deters colloidal deposition. These findings illustrate mechanisms underlying colloid-surface interactions in polymer-surfactant mixtures, which are important to controlling selective colloidal deposition in multicomponent formulation applications.

Spatially varying colloidal phase behavior on multi-dimensional energy landscapes.

A method is reported to determine equilibrium concentration profiles and local phase behavior of colloids on multi-dimensional energy landscapes. A general expression is derived based on local particle concentration and osmotic pressure differences that are balanced by forces on colloids due to energy landscape gradients. This analysis is applied to colloidal particles in high frequency AC electric fields within octupolar electrodes, where the energy landscape can be shaped in two dimensions. These results are also directly applicable to any particles having induced dipoles in spatially non-uniform electromagnetic fields. Predictions based on modeling colloids with an effective hard disk equation of state indicate inhomogeneous solid and fluid states coexisting on different shaped energy landscapes including multiple minima. Model predictions show excellent agreement with time-averaged Brownian dynamic simulations at equilibrium. Findings demonstrate a general approach to understand colloidal phase behavior on energy landscapes due to external fields, which could enable control of colloidal microstructures on morphing energy landscapes and the inverse design of fields to assemble hierarchically structured colloidal materials.