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At least 145 records · Page 8

Plant-specific features of respiratory supercomplex I + III2 from Vigna radiata

Abstract The last steps of cellular respiration—an essential metabolic process in plants—are carried out by mitochondrial oxidative phosphorylation. This process involves a chain of multi-subunit membrane protein complexes (complexes I–V) that form higher-order assemblies called supercomplexes. Although supercomplexes are the most physiologically relevant form of the oxidative phosphorylation complexes, their functions and structures remain mostly unknown. Here we present the cryogenic electron microscopy structure of the supercomplex I + III 2 from Vigna radiata (mung bean). The structure contains the full subunit complement of complex I, including a newly assigned, plant-specific subunit. It also shows differences in the mitochondrial processing peptidase domain of complex III 2 relative to a previously determined supercomplex with complex IV. The supercomplex interface, while reminiscent of that in other organisms, is plant specific, with a major interface involving complex III 2 ’s mitochondrial processing peptidase domain and no participation of complex I’s bridge domain. The complex I structure suggests that the bridge domain sets the angle between the enzyme’s two arms, limiting large-scale conformational changes. Moreover, complex I’s catalytic loops and its response in active-to-deactive assays suggest that, in V. radiata , the resting complex adopts a non-canonical state and can sample deactive- or open-like conformations even in the presence of substrate. This study widens our understanding of the possible conformations and behaviour of complex I and supercomplex I + III 2 . Further studies of complex I and its supercomplexes in diverse organisms are needed to determine the universal and clade-specific mechanisms of respiration.

59 BASIC BIOLOGICAL SCIENCES↗

Machine-learning enabled thermodynamic model for the design of new rare-earth compounds

We employ a descriptor based machine-learning approach to assess the effect of chemical alloying on formation-enthalpy of rare-earth intermetallics. Application of machine-learning approaches in rare-earth intermetallic design have been sparse due to limited availability of reliable datasets. In this work, we developed an ‘in-house’ rare-earth database with more than 600 + compounds, each entry was populated with formation enthalpy and related atomic features using high-throughput density-functional theory (DFT). The SISSO (sure independence screening and sparsifying operator) based machine-learning method with meaningful atomic features was used for training and testing the formation enthalpies of rare earth compounds. The complex lattice function coupled with the machine-learning model was used to explore the effect of transition metal alloying on the energy stability of Ce based cubic Laves phases (MgCu 2 type). The SISSO predictions show good agreement with high-fidelity DFT calculations and X-ray powder diffraction measurements. Our study provides quantitative guidance for compositional considerations within a machine-learning model and discovering new metastable materials. The electronic-structure of Ce-Fe-Cu based compound was also analyzed to get an in-depth understanding of the electronic origin of phase stability. The interpretable analytical models in combination with density-functional theory and experiments provide a fast and reliable design guide for discovering technologically useful materials.

36 MATERIALS SCIENCE↗

Corrosion-resistant polyurethane coatings from structure-homogenized biorefinery lignin through fractionation and oxypropylation

Using lignin for polyurethane (PU) synthesis is challenging because of its heterogeneous structure, i.e., broad molecule weight (MW) distribution and diverse hydroxyl (OH) functionality. This complexity influences the crosslinking reaction between lignin and isocyanate and affects the quality of PU products. Here, we propose a two-step strategy for lignin structure homogenization by lowering its MW and uniforming OH functionality (step 2). Step 1 involves a bioethanol fractionation process, yielding fractionated lignin with one order lower MW than the raw lignin while exhibiting better processability for the subsequent process. Step 2 is performed by an oxyalkylation process using fractionated lignin that converts phenolic and carboxylic OHs to aliphatic OHs. As a result, we obtained structure-homogenized lignin with good compatibility and crosslinking with hexamethylene diisocyanate for PU coating synthesis. Moreover, PU coatings prepared from structure-homogenized lignin display a defect-free microscopic structure and show better corrosion resistance than coatings fabricated from its raw lignin alternative. Overall, the structure homogenization process is a beneficial way of using lignin as biopolyol in PU synthesis toward the application-oriented design of corrosion-resistant lignin-based PU coatings.

36 MATERIALS SCIENCE↗

Universal signal scaling in microwave impedance microscopy

Microwave impedance microscopy (MIM) is an emerging scanning probe technique that measures the local complex dielectric function using near-field microwave. Although it has made significant impacts in diverse fields, a systematic, quantitative understanding of the signal's dependence on various important design parameters is lacking. Here, we show that for a wide range of MIM implementations, given a complex tip-sample admittance change ΔΥ, the MIM signal—the amplified change in the reflected microwave amplitude—is –G · ΔΥ/2Υ 0 · η 2 · V in , where η is the ratio of the microwave voltage at the probe to the incident microwave amplitude, Y o is the system admittance, and G is the total voltage gain. For linear circuits, η is determined by the circuit design and does not depend on V in . We show that the maximum achievable signal for different designs scales with η 2 or η when limited by input power or sample perturbation, respectively. Furthermore, this universal scaling provides guidance on diverse design goals, including maximizing narrow-band signal for imaging and balancing bandwidth and signal strength for spectroscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Isolation of Ce( IV ) centered polyoxoalkoxide sandwich-type complexes allows comparison of metal–oxygen bond covalency

The new Ce III centered sandwich-type complex (TBA) 3 [Ce{W 4 O 13 (OMe) 4 MoNO} 2 ] is reported. The redox properties of this molecule, and its all-molybdenum analogue, (TBA) 3 [Ce{Mo 5 O 13 (OMe) 4 NO} 2 ], were investigated using cyclic voltammetry. The data reveals the presence of reversible Ce IV /Ce III redox couples at modest potentials. One electron oxidation of the complexes provides facile access to the corresponding Ce IV derivatives, which were fully characterized. 17 O NMR spectroscopy reveals that the chemical shifts of the oxygen nuclei directly bound to Ce IV are much higher than the corresponding signals in isostructural, diamagnetic, Zr IV , Hf IV , or Th IV centered complexes. Density functional theory (DFT) calculations indicate that the increase in chemical shift correlates with an increase in the covalency of the M IV –O bonds, illustrating that 17 O NMR spectroscopy is a powerful experimental tool for interrogating the nature of metal oxygen bonding in diamagnetic complexes.

Shiels, Dominic [Univ. of Rochester, NY (United St↗

Design of Efficient Molecular Electrocatalysts for Water and Carbon Dioxide Reduction Using Predictive Models of Thermodynamic Properties

Objectives: 1) To design and synthesize water soluble transition metal complexes that function as electrocatalysts for the reduction of water to hydrogen or carbon dioxide to formate 2) To experimentally measure thermochemical properties, such as hydride donor ability, and use these quantities to optimize catalyst performance in solutions of varying pH 3) To incorporate results from detailed mechanistic and kinetic studies to direct improvements in catalyst design 4) To use thermochemical data from objective 2 to generate predictive models for the properties of new complexes to apply to the development of catalysts for other reductive reactions, with an emphasis on carbon dioxide reduction to methanol Description: Wide-spread implementation of renewable but intermittent energy sources, such as solar, requires the development of efficient methods for energy storage. The high energy density of chemical bonds makes chemical fuels an ideal solution for energy storage. Hydrogen and reduced carbon compounds have been proposed as ideal candidates for chemical fuels. However, the generation of chemical fuels from electricity requires competent electrocatalysts. The proposed research focuses on developing electrocatalysts for the reduction of water to hydrogen, and carbon dioxide to formate. Both products can be used directly as an energy carrier in fuel cells, or as a reductant for more saturated chemical fuels. Hydrogen is the most common fuel used in current commercial fuel cells. Additionally, there is interest in formic acid as a liquid carrier for hydrogen because of its increased storage density and ease of dehydrogenation. Formate is also an intermediate in the sequential reduction of CO 2 to methanol, another potential chemical fuel with high energy storage density. Despite the utility of formate as a chemical fuel or precursor, there are very few examples of electrocatalysts for its production from CO 2 , and even fewer demonstrate high product selectivity. In heterogeneous catalysis, the Sabatier principle is used to generate volcano curves that describe optimal thermochemical properties for key intermediates that result in peak catalytic activity. In most cases, such as hydrogen production and oxidation, the most favorable metals (Pt, Re, Rh, and Ir) are rare and expensive. Molecular inorganic complexes provide an opportunity to use electronic and steric ligand effects to tune the critical thermodynamic parameters of abundant metals to values comparable to key surface intermediates on precious metals. This principle will be applied to the design of aqueous homogeneous catalysts for the reduction of H 2 O and CO 2 optimized to function at specific pH ranges. The critical intermediate in both of these reactions is a metal hydride. The strength of this bond, or hydricity (ΔGH - ) dictates the overall thermodynamics of the reduction of H + to H 2 and the sequential reduction of C1 substrates, such as CO 2 , CO, and H 2 CO (the latter to CH 3 OH). ΔGH - will be systematically measured for a series of first row metal complexes to form predictive models for metal and ligand electronic effects. Benefits and Outcomes: This approach addresses thermodynamic requirements essential for energy-efficient catalyst design and transition state barrier considerations for faster catalysis. The advancements made from this research will include the discovery of efficient, stable, and fast catalysts for hydrogen and formate generation from electricity. The ability to store energy efficiently is critical to the widespread use of renewable energy schemes. This provides a viable solution to produce high energy density fuels for stationary and mobile energy applications. The fundamental research conducted is also directly applicable to the design of catalysts for the generation of further reduced products such as methanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Biosynthesis of Minimal C-Phycocyanin Chromophore Assemblies in E. coli Provides a Platform to Dissect Protein-Mediated Tuning of Exciton Transfer

Cyanobacteria are arguably among the most evolutionarily successful organisms on Earth, inhabiting a wide range of ocean, freshwater, soil, and even desert environments on every continent. The cyanobacterial phycobilisome consists of stacks of disk-like light-collecting moieties, allophycocyanin (APC) and phycocyanin (CPC), with covalently bound phycocyanobilin (PCB) pigments. The ways in which the energies of the specific chromophores in these complexes are tuned by the protein to achieve its highly efficient and directional energy transfer are not fully understood, as complex combinations of decay pathways are occurring simultaneously and competitively through this elaborate light-harvesting system. This makes it difficult to extract information about isolated protein-pigment interactions. We provide herein a description of a useful new experimental platform in which we have recombinantly expressed a fully functioning CPC complex and selectively created minimal chromophore sets to study their individual contributions to the overall CPC spectra. Structural and computational analysis of this protein system have provided a greater understanding of how the protein environment serves to alter the photophysics of each of these chromophores. Introduction of a quencher into various positions within CPC confirmed the ability of the protein environment to tune the directionality of energy transport in this assembly. Further mutational analysis suggested the roles of key amino acids surrounding the chromophores, showcasing the utility of heterologous expression techniques for understanding the effects of structure on EET mechanisms in the phycobilisome.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis of Novel Hybrid Nanostructures Employing Advanced Structural Characterization Techniques

This proposal was for carrying out research on creating novel hybrid nanostructures with novel and interesting functional properties with the help of advanced structural on adding 0.001, 0.01 and 0.02 mg of Au nanoparticles. From the reflectivity measurements, and the intensities of the various order diffraction peaks from the multilayers, we were able to reconstruct the electron density profiles of the films normal to their surfaces. characterization techniques. There were 3 components to the research: (1) seeing if new hybrid nanostructures could be synthesized from Au nanoparticles and lipid multilayers (2) making artificial cells from Galactopyranose-Derived Single-Chain Amphiphiles and sponge phases of lipid/amphiphile mixtures, and (3) characterizing the pair distribution function for complex nanoparticles of melanin to understand/predict the structural colors seen in aggregates of such nanoparticles.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Near-Infrared Emission from Sulfur Heteroatom Defects in Single-Walled Carbon Nanotubes

Quantum defects introduced into single-walled carbon nanotubes (SWCNTs) that support near-infrared emission are promising candidates for many applications. Here, we present a type of quantum defect in which sulfur atoms are incorporated into the crystal lattice of SWCNTs through their reactions with a mild reducing agent, sodium dithionite. When radical anions generated by sodium dithionites react with (6,5)-SWCNTs, two new emission features emerge at 1120 and 1250 nm. Comparing these spectral features with density functional theory calculation results, we attribute them to defects with episulfide or thioether structures. Here, by investigating the influences of reaction conditions including reactant concentration, light irradiation, and solvent type, we identify the reaction mechanism between SWCNTs and sodium dithionite and achieve good control over defect densities. Due to the intrinsic reactivity of sulfur species, the sulfur-containing quantum defects discovered here may facilitate the introduction of more complex and functionally diverse moieties into SWCNTs.

Anions↗

Meta-omics-aided isolation of an elusive anaerobic arsenic-methylating soil bacterium

Soil microbiomes harbour unparalleled functional and phylogenetic diversity. However, extracting isolates with a targeted function from complex microbiomes is not straightforward, particularly if the associated phenotype does not lend itself to high-throughput screening. Here, we tackle the methylation of arsenic (As) in anoxic soils. As methylation was proposed to be catalysed by sulfate-reducing bacteria. However, to date, there are no available anaerobic isolates capable of As methylation, whether sulfate-reducing or otherwise. The isolation of such a microorganism has been thwarted by the fact that the anaerobic bacteria harbouring a functional arsenite S-adenosylmethionine methyltransferase (ArsM) tested to date did not methylate As in pure culture. Additionally, fortuitous As methylation can result from the release of non-specific methyltransferases upon lysis. Thus, we combined metagenomics, metatranscriptomics, and metaproteomics to identify the microorganisms actively methylating As in anoxic soil-derived microbial cultures. Based on the metagenome-assembled genomes of microorganisms expressing ArsM, we isolated Paraclostridium sp. strain EML, which was confirmed to actively methylate As anaerobically. This work is an example of the application of meta-omics to the isolation of elusive microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗

Optimizing the Design of Diatom Biosilica-Targeted Fusion Proteins in Biosensor Construction for Bacillus anthracis Detection

In vivo functionalization of diatom biosilica frustules by genetic manipulation requires careful consideration of the overall structure and function of complex fusion proteins. Although we previously had transformed Thalassiosira pseudonana with constructs containing a single domain antibody (sdAb) raised against the Bacillus anthracis Sterne strain, which detected an epitope of the surface layer protein EA1 accessible in lysed spores, we initially were unsuccessful with constructs encoding a similar sdAb that detected an epitope of EA1 accessible in intact spores and vegetative cells. This discrepancy limited the usefulness of the system as an environmental biosensor for B. anthracis. We surmised that to create functional biosilica-localized biosensors with certain constructs, the biosilica targeting and protein trafficking functions of the biosilica-targeting peptide Sil3T8 had to be uncoupled. We found that retaining the ER trafficking sequence at the N-terminus and relocating the Sil3T8 targeting peptide to the C-terminus of the fusion protein resulted in successful detection of EA1 with both sdAbs. Homology modeling of antigen binding by the two sdAbs supported the hypothesis that the rescue of antigen binding in the previously dysfunctional sdAb was due to removal of steric hindrances between the antigen binding loops and the diatom biosilica for that particular sdAb.

59 BASIC BIOLOGICAL SCIENCES↗

Controlling Protein Enrichment in Lipid Sponge Phase Droplets using SNAP–Tag Bioconjugation

All cells use organized lipid compartments to facilitate specific biological functions. Membrane-bound organelles create defined spatial environments that favor unique chemical reactions while isolating incompatible biological processes. Despite the fundamental role of cellular organelles, there is a scarcity of methods for preparing functional artificial lipid-based compartments. In this work, we demonstrate a robust bioconjugation system for sequestering proteins into zwitterionic lipid sponge phase droplets. Incorporation of benzylguanine (BG)-modified phospholipids that form stable covalent linkages with an O 6 -methylguanine DNA methyltransferase (SNAP-tag) fusion protein enables programmable control of protein capture. We show that this methodology can be used to anchor hydrophilic proteins at the lipid-aqueous interface, concentrating them within an accessible but protected chemical environment. SNAP-tag technology enables the integration of proteins that regulate complex biological functions in lipid sponge phase droplets, and should facilitate the development of advanced lipid-based artificial organelles.

59 BASIC BIOLOGICAL SCIENCES↗

Background optimization of powder electron diffraction for implementation of the e-PDF technique and study of the local structure of iron oxide nanocrystals

The local structural characterization of iron oxide nanoparticles is explored using a total scattering analysis method known as pair distribution function (PDF) (also known as reduced density function) analysis. The PDF profiles are derived from background-corrected powder electron diffraction patterns (the e-PDF technique). Due to the strong Coulombic interaction between the electron beam and the sample, electron diffraction generally leads to multiple scattering, causing redistribution of intensities towards higher scattering angles and an increased background in the diffraction profile. In addition to this, the electron–specimen interaction gives rise to an undesirable inelastic scattering signal that contributes primarily to the background. The present work demonstrates the efficacy of a pre-treatment of the underlying complex background function, which is a combination of both incoherent multiple and inelastic scatterings that cannot be identical for different electron beam energies. Therefore, two different background subtraction approaches are proposed for the electron diffraction patterns acquired at 80 kV and 300 kV beam energies. From the least-square refinement (small-box modelling), both approaches are found to be very promising, leading to a successful implementation of the e-PDF technique to study the local structure of the considered nanomaterial.

36 MATERIALS SCIENCE↗

Deep Learning without Global Optimization by Random Fourier Neural Networks

Here we introduce a new training algorithm for deep neural networks that utilize random complex exponential activation functions. Our approach employs a Markov chain Monte Carlo sampling procedure to iteratively train network layers, avoiding global and gradient-based optimization while maintaining error control. It consistently attains the theoretical approximation rate for residual networks with complex exponential activation functions, determined by network complexity. Additionally, it enables efficient learning of multiscale and high-frequency features, producing interpretable parameter distributions. Despite using sinusoidal basis functions, we do not observe Gibbs phenomena in approximating discontinuous target functions.

97 MATHEMATICS AND COMPUTING↗

Medial packing and elastic asymmetry stabilize the double-gyroid in block copolymers

Triply-periodic networks are among the most complex and functionally valuable self-assembled morphologies, yet they form in nearly every class of biological and synthetic soft matter building blocks. In contrast to simpler assembly motifs – spheres, cylinders, layers – networks require molecules to occupy variable local environments, confounding attempts to understand their formation. Here, we examine the double-gyroid network phase by using a geometric formulation of the strong stretching theory of block copolymer melts, a prototypical soft self-assembly system. The theory establishes the direct link between molecular packing, assembly thermodynamics and the medial map, a generic measure of the geometric center of complex shapes. We show that “medial packing” is essential for stability of double-gyroid in strongly-segregated melts, reconciling a long-standing contradiction between infinite- and finite-segregation theories. Additionally, we find a previously unrecognized non-monotonic dependence of network stability on the relative entropic elastic stiffness of matrix-forming to tubular-network forming blocks. The composition window of stable double-gyroid widens for both large and small elastic asymmetry, contradicting intuitive notions that packing frustration is localized to the tubular domains. This study demonstrates the utility of optimized medial tessellations for understanding soft-molecular assembly and packing frustration via an approach that is readily generalizable far beyond gyroids in neat block copolymers.

36 MATERIALS SCIENCE↗

Impact of wet-dry cycling on the phase behavior and compartmentalization properties of complex coacervates

Abstract Wet-dry cycling on the early Earth is thought to have facilitated production of molecular building blocks of life, but its impact on self-assembly and compartmentalization remains largely unexplored. Here, we investigate dehydration/rehydration of complex coacervates, which are membraneless compartments formed by phase separation of polyelectrolyte solutions. Solution compositions are identified for which tenfold water loss results in maintenance, disappearance, or appearance of coacervate droplets. Systems maintaining coacervates throughout the dehydration process are further evaluated to understand how their compartmentalization properties change with drying. Although added total RNA concentrations increase tenfold, RNA concentration within coacervates remains steady. Exterior RNA concentrations rise, and exchange rates for encapsulated versus free RNAs increase with dehydration. We explain these results in light of the phase diagram, with dehydration-driven ionic strength increase being particularly important in determining coacervate properties. This work shows that wet-dry cycling can alter the phase behavior and protocell-relevant functions of complex coacervates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Validity of Machine Learning in the Quantitative Analysis of Complex Scanning Near-Field Optical Microscopy Signals Using Simulated Data

Scattering-type scanning near-field optical microscope (s-SNOM) is a modern technique for subdiffractional optical imaging and spectroscopy. Over the past two decades, tremendous efforts have been devoted to modeling complex tip-sample interactions in s-SNOM, aimed at understanding the electrodynamics of materials at the nanoscale. However, due to complexities in analytical methods and the limited computation power for fully numerical simulations, compromises must be made to facilitate the modeling of tip-sample interaction, such as using quasistatic approximation or unrealistic tip geometries. Here, we apply a variety of widely utilized machine-learning methods, including k nearest neighbor and feedforward neural network etc. to study the phase-resolved spectroscopic near-field response. With only a small set of training data, which is simulated using the finite-dipole model, we demonstrate that the relation between the experimental near-field signal and sample optical constant can be one to one mapped without the need for tip modeling: for a given material with a moderate dielectric function, its complex near-field spectrum can be accurately determined within the mid-IR spectral range, and vice versa. Our preliminary study sets the stage for future exploration using real experimental data. Our method is beneficial for processing the increasing amount of data accumulated across many research groups and especially useful for user facilities such as synchrotron-based national laboratories where a large amount of data is generated on a daily basis.

36 MATERIALS SCIENCE↗

Conformational spread drives the evolution of the calcium–calmodulin protein kinase II

The calcium calmodulin (Ca 2+ /CaM) dependent protein kinase II (CaMKII) decodes Ca 2+ frequency oscillations. The CaMKIIα isoform is predominantly expressed in the brain and has a central role in learning. I matched residue and organismal evolution with collective motions deduced from the atomic structure of the human CaMKIIα holoenzyme to learn how its ring architecture abets function. Protein dynamic simulations showed its peripheral kinase domains (KDs) are conformationally coupled via lateral spread along the central hub. The underlying β-sheet motions in the hub or association domain (AD) were deconvolved into dynamic couplings based on mutual information. They mapped onto a coevolved residue network to partition the AD into two distinct sectors. A second, energetically stressed sector was added to ancient bacterial enzyme dimers for assembly of the ringed hub. The continued evolution of the holoenzyme after AD–KD fusion targeted the sector’s ring contacts coupled to the KD. Among isoforms, the α isoform emerged last and, it alone, mutated rapidly after the poikilotherm–homeotherm jump to match the evolution of memory. The correlation between dynamics and evolution of the CaMKII AD argues single residue substitutions fine-tune hub conformational spread. The fine-tuning could increase CaMKIIα Ca 2+ frequency response range for complex learning functions.

59 BASIC BIOLOGICAL SCIENCES↗