Stability of End-to-End Base Stacking Interactions in Highly Concentrated DNA Solutions
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Chemistry↗
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How Do Ionic Liquids “Fold” Ionenes? Computational and Experimental Analysis of Imidazolium Polymers Based on Ether and Alkyl Chain Variations Dissolved in an Ionic Liquid
Molecular dynamics (MD) simulations and complementary experiments are used here to understand the inter- and intramolecular structure and conformational properties of ionenes (i.e., cationic polymers formed from condensation reactions) dissolved in an ionic liquid (IL), 1-ethyl-3-methylimidazolium bistriflimide [C 2 mim + ][Tf 2 N - ]. The simulated structural properties are benchmarked against experimental analyses of these same polymers, mainly using dynamic light scattering (DLS) experiments. Four different imidazolium ionenes are considered, corresponding to variations in the chemistry and structure of the repeat units including: (1) poly (decylimidazolium) (PD 10 ); (2) poly (tetraethyleneglycolimidazolium) (PE 10 ); (3) alternating copolymer (P(ED) 5 ); and (4) a block copolymer (PE 5 D 5 ). Detailed computational analyses of the polymer structure and conformational properties were performed, including the radius of gyration, end-to-end distance, torsional distributions, and site-site and spatial distribution functions. Overall, there is a competition between intramolecular associations between the imidazolium groups and the ether sites in the polymers versus the intermolecular interactions of the polymer imidazolium groups with the surrounding anion molecules. The polymer with only ether linkages (PE 10 ) results in the most intramolecular interactions, leading to significant coiling behavior and chain contraction. These strong interactions reduce chain flexibility, but they also result in much more linear chain configurations and alignment of the imidazolium groups. The polymer structure is strongly affected as the concentration of alkyl groups is increased, and we find that the polymer architecture (alternating versus block copolymer) also has an important influence. Furthermore, these detailed observations are important for understanding the connection between the molecular design of imidazolium polymers and their emergent structural properties, which could lead to unique opportunities for creating polymer composites.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Overlap Concentration in Salt-Free Polyelectrolyte Solutions
For strongly charged polyelectrolytes in salt-free solutions, we use molecular dynamics simulations of a coarse-grained bead-spring model to calculate overlap concentrations c* and chain structure for polymers containing N = 10 to 1600 monomers. Over much of this range, we find that the end-to-end distance R* at c* increases faster than linearly with increasing N, as chains at the overlap concentration approach strongly extended conformations. This trend results in the overlap concentration c* decreasing as a stronger function of N than the classical prediction c* ~ N –2 . Finally, this stronger dependence can be fit either by a logarithmic correction to scaling or by an apparent scaling c* ~ N –m , with m > 2.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Control over Conformational Landscapes of Polypeptoids by Monomer Sequence Patterning
The ability to program chain conformation and structure through control over the monomer sequence of synthetic polymers has broad implications for next-generation material design. While related problems of protein-folding and de novo design have generated accurate predictions of 3D folded chain structures, generalization to synthetic polymers remains intractable due to the requirement of large structural databases and the intrinsically disordered nature of polymer building blocks. In this work, polypeptoids, a class of peptidomimetic synthetic polymers, are utilized to build a general workflow for the study of relationships between monomer sequence and dynamic 3D chain structure in solution. Furthermore, this work demonstrates how control over the monomer sequence can alter the conformational landscape of synthetic polymers to deviate dramatically from classical chain statistics. Specifically, the distribution of end-to-end distances, as measured by double electron-electron resonance spectroscopy in dilute solvent, is systematically skewed towards shorter distances with an increasing number of hydrophobes and further refined by hydrophobe arrangement in amphiphilic polypeptoid chains.
36 MATERIALS SCIENCE↗
Bottom-Up Simulation, Reconstruction, and Quantification of Macromolecule Sequences from Experimental Polymerizations
Motivated by the canonical sequence–structure–function paradigm, tools to characterize chemical patterning in natural biomacromolecules, from proteins to nucleic acids, have grown exponentially in recent years. However, analogous strategies for synthetic macromolecules remain in nascent stages, complicated by sequence polydispersity and analytical limitations. To address this, we have developed a comprehensive and open-source Python package, PRISM (polymer rate insights and sequence modeling), an end-to-end workflow that provides a path from experimental kinetics measurements to quantitative and qualitative metrics for describing chemical patterning in stochastic polymers. First, a numerical integration strategy was constructed to simulate and fit experimental data from reversible addition–fragmentation chain transfer (RAFT) polymerization kinetics, enabling the facile estimation of relevant reactivity ratios. These ratios were then used in a mechanism-specific stochastic kinetic simulation strategy to simulate sequence ensembles corresponding to model systems spanning experimental copolymers, classes of statistical polymers (e.g., alternating, block, and gradient), and multiblock copolymers. Lastly, inspired by sequence homology metrics from bioinformatics, we introduce visualization strategies and quantitative metrics to facilitate comparisons of different sequence ensembles. As the sequence–structure–function paradigm becomes increasingly central in de novo design of synthetic macromolecules, this toolkit provides a first step toward accurate and representative sequence description and featurization.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Noncanonical folding of peptoid oligomers: Formation of a closed conformation in nonpolar solvent
Peptoids provide a versatile platform for foldamer design, yet their conformational behavior in low-dielectric media remains poorly understood. The structural characteristics of N-1-phenylethylglycine (Nspe) homo-oligomers were inves-tigated in chloroform, a solvent that mimics the interior of lipid bilayers, using nuclear magnetic resonance (NMR) spec-troscopy and molecular dynamics (MD) simulations. Nspe7 populated two distinct compact conformations, while Nspe10 adopted a single homogeneous conformation related to the previously reported Nspe9 threaded-loop structure. Integrated experimental and computational analysis reveals that these structures are stabilized by cooperative end-to-end intramo-lecular hydrogen bonding, cis-trans backbone isomerism, and hydrophobic side-chain shielding. The resulting structures minimize exposed polar surface area, demonstrating a closed conformation in the low-dielectric environment. These find-ings establish specific chain-length requirements for achieving well-defined closed conformations. This work provides insights into peptoid folding in nonpolar media, enabling rational design strategies for solvent-directed conformational switching systems.
Oh, Jinyoung↗
Shear-Induced Conformations of Salt-Free Polyelectrolytes in Semidilute Solutions
Here, we present coarse-grained molecular dynamics simulations of salt-free polyelectrolyte chains in semidilute solutions under simple shear flow, with full hydrodynamic interactions and explicit dipolar solvent. At equilibrium, chain orientation statistics follow a pseudo-Voigt distribution, and the structural correlation length and chain end-to-end vector autocorrelation function exhibit scaling behavior consistent with theoretical predictions for polyelectrolytes. Under shear, chains transition from coiled to stretched states and the end-to-end vector autocorrelation function reveals oscillatory dynamics at high Weissenberg numbers. Analysis of the gyration tensor and shear strain distributions identified three distinct chain populations with directional alignment along and against the shear gradient. Compared with their neutral polymer counterparts, polyelectrolytes exhibit stronger shear thinning and enhanced chain alignment under the same Weissenberg number, which is attributed to electrostatic interactions and shear-induced counterion release. These findings provide molecular insight into the distinct flow response of charged polymers and have implications for tailoring the rheological properties of polyelectrolyte-based materials.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Compound Meta-Optics for Complete and Loss-Less Field Control
Optical metasurfaces offer a compact platform for manipulation of the amplitude, phase, and polarization state of light. Independent control over these properties, however, is hindered by the symmetric transmission matrix associated with single-layer metasurfaces. Here, we utilize multilayer birefringent meta-optics to realize high-efficiency, independent control over the amplitude, phase, and polarization state of light. In this work, high-efficiency control is enabled by redistributing the wavefront between cascaded metasurfaces, while end-to-end inverse design is used to realize independent complex-valued functions for orthogonal polarization states. Based on this platform, we demonstrate spatial mode division multiplexing, optical mode conversion, and universal vectorial holograms, all with diffraction efficiencies over 80%. This meta-optic platform expands the design space of flat optics and could lead to advances in optical communications, quantum entanglement, and information encryption.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Chirality Amplified: Long, Discrete Helicene Nanoribbons
Here we report the synthesis of two polyhelicene frameworks consisting, from end-to-end, of 18 and 24 fused benzene rings. The latter exhibits the largest electronic circular dichroism in the visible spectrum of any molecule. These shape-persistent helical nanoribbons incorporate multiple helicenes, a class of contorted polycyclic aromatic molecules consisting of ortho-annulated rings. These conjugated, chiral molecules have interesting chemical, biological, and chiroptical properties; however, there are very few helicenes with extraordinary chiroptical response over a broad range of the visible spectrum—a key criterion for applications such as chiral optoelectronics. In this report, we show that coupling the polyhelicene framework with multiple perylene-diimide subunits elicits a significant chiroptic response. Notably, the molar circular dichroism increases faster than the absorptivity of these molecules as their helical axis lengthens. Computational analysis reveals that the greatly amplified circular dichroism arises from exciton-like interactions between the perylene-diimide and the helicene moieties. As a result, we predict that even greater chiroptic enhancement will result from further axial elongation of these nanoribbons, which can be readily enabled via the iterative synthetic method presented herein.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Ethanol-Induced Condensation and Decondensation in DNA-Linked Nanoparticles: A Nucleosome-like Model for the Condensed State
Inspired by the conventional use of ethanol to induce DNA precipitation, ethanol condensation has been applied as a routine method to dynamically tune “bond” lengths (i.e., the surface-to-surface distances between adjacent nanoparticles that are linked by DNA) and thermal stabilities of colloidal crystals involving DNA-linked nanoparticles. However, the underlying mechanism of how the DNA bond that links gold nanoparticles changes in this class of colloidal crystals in response to ethanol remains unclear. Here, we conducted a series of all-atom molecular dynamic (MD) simulations to explore the free energy landscape for DNA condensation and decondensation. Our simulations confirm that DNA condensation is energetically much more favorable under 80% ethanol conditions than in pure water, as a result of ethanol’s role in enhancing electrostatic interactions between oppositely charged species. Moreover, the condensed DNA adopts B-form in pure water and A-form in 80% ethanol, which indicates that the higher-order transition does not affect DNA’s conformational preferences. We further propose a nucleosome-like supercoiled model for the DNA condensed state, and we show that the DNA end-to-end distance derived from this model matches the experimentally measured DNA bond length of about 3 nm in the fully condensed state for DNA where the measured length is 16 nm in water. Altogether, this study provides an atomistic understanding of the mechanism underlying ethanol-induced condensation and water-induced decondensation, while our proposed nucleosome-like model allows the design of new strategies for interpreting experimental studies of DNA condensation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Bayesian Model for HOPE Mass Spectrometers on Van Allen Probes
Space instruments rely heavily on modeling to predict and understand the instrument response, enabling a determination of the capabilities and resolution. The Bayesian approach provides a framework to incorporate prior knowledge and propagate uncertainty to predict the instrument response. We present an empirical Bayes model for the end-to-end performance of the Helium, Oxygen, Proton, and Electron mass spectrometers aboard the Van Allen Probes mission. In this model, we use a combination of external modeling, laboratory calibration, and expert opinion to construct the time-of-flight spectra and demonstrate good agreement with on-orbit data. The empirical Bayes model is applied to explore doubly charged ions and carbon, nitrogen, oxygen discrimination during the Van Allen Probes mission.
47 OTHER INSTRUMENTATION↗
An End-To-End Earthquake Detection Method for Joint Phase Picking and Association Using Deep Learning
Earthquake monitoring by seismic networks typically involves a workflow consisting of phase detection/picking, association, and location tasks. In recent years, the accuracy of these individual stages has been improved through the use of machine learning techniques. Here, in this study, we introduce a new end-to-end approach that improves overall earthquake detection accuracy by jointly optimizing each stage of the detection pipeline. We propose a neural network architecture for the task of multi-station processing of seismic waveforms recorded over a seismic network. This end-to-end architecture consists of three sub-networks: a backbone network that extracts features from raw waveforms, a phase picking sub-network that picks P- and S-wave arrivals based on these features, and an event detection sub-network that aggregates the features from multiple stations to associate and detect earthquakes across a seismic network. We use these sub-networks together with a shift-and-stack module based on back-projection that introduces kinematic constraints on arrival times, allowing the neural network model to generalize to different velocity models and to variable station geometry in seismic networks. We evaluate our proposed method on the STanford EArthquake Dataset (STEAD) and on the 2019 Ridgecrest, CA earthquake sequence. The results demonstrate that our end-to-end approach can effectively pick P- and S-wave arrivals and achieve earthquake detection accuracy rivaling that of other state-of-the-art approaches. Because our approach preserves information across tasks in the detection pipeline, it has the potential to outperform approaches that do not.
58 GEOSCIENCES↗
Improving the Quasi‐Biennial Oscillation via a Surrogate‐Accelerated Multi‐Objective Optimization
Accurate simulation of the quasi-biennial oscillation (QBO) is challenging due to uncertainties in representing convectively generated gravity waves. We develop an end-to-end uncertainty quantification workflow that calibrates these gravity wave processes in E3SM for a realistic QBO. Central to our approach is a domain knowledge-informed, compressed representation of high-dimensional spatio-temporal wind fields. By employing a parsimonious statistical model that learns the fundamental frequency from complex observations, we extract interpretable and physically meaningful quantities capturing key attributes. Building on this, we train a probabilistic surrogate model that approximates the fundamental characteristics of the QBO as functions of critical physics parameters governing gravity wave generation. Leveraging the Karhunen–Loève decomposition, our surrogate efficiently represents these characteristics as a set of orthogonal features, capturing cross-correlations among multiple physics quantities evaluated at different pressure levels and enabling rapid surrogate-based inference at a fraction of the computational cost of full-scale simulations. Finally, we analyze the inverse problem using a multi-objective approach. Our study reveals a tension between amplitude and period that constrains the QBO representation, precluding a single optimal solution. To navigate this, we quantify the bi-criteria trade-off and generate a set of Pareto optimal parameter values that balance the conflicting objectives. This integrated workflow improves the fidelity of QBO simulations and offers a versatile template for uncertainty quantification in complex geophysical models.
54 ENVIRONMENTAL SCIENCES↗
Correlator convolutional neural networks as an interpretable architecture for image-like quantum matter data
Image-like data from quantum systems promises to offer greater insight into the physics of correlated quantum matter. However, the traditional framework of condensed matter physics lacks principled approaches for analyzing such data. Machine learning models are a powerful theoretical tool for analyzing image-like data including many-body snapshots from quantum simulators. Recently, they have successfully distinguished between simulated snapshots that are indistinguishable from one and two point correlation functions. Thus far, the complexity of these models has inhibited new physical insights from such approaches. Here, we develop a set of nonlinearities for use in a neural network architecture that discovers features in the data which are directly interpretable in terms of physical observables. Applied to simulated snapshots produced by two candidate theories approximating the doped Fermi-Hubbard model, we uncover that the key distinguishing features are fourth-order spin-charge correlators. Our approach lends itself well to the construction of simple, versatile, end-to-end interpretable architectures, thus paving the way for new physical insights from machine learning studies of experimental and numerical data.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
PlasmidMaker is a versatile, automated, and high throughput end-to-end platform for plasmid construction
Abstract Plasmids are used extensively in basic and applied biology. However, design and construction of plasmids, specifically the ones carrying complex genetic information, remains one of the most time-consuming, labor-intensive, and rate-limiting steps in performing sophisticated biological experiments. Here, we report the development of a versatile, robust, automated end-to-end platform named PlasmidMaker that allows error-free construction of plasmids with virtually any sequences in a high throughput manner. This platform consists of a most versatile DNA assembly method using Pyrococcus furiosus Argonaute ( Pf Ago)-based artificial restriction enzymes, a user-friendly frontend for plasmid design, and a backend that streamlines the workflow and integration with a robotic system. As a proof of concept, we used this platform to generate 101 plasmids from six different species ranging from 5 to 18 kb in size from up to 11 DNA fragments. PlasmidMaker should greatly expand the potential of synthetic biology.
59 BASIC BIOLOGICAL SCIENCES↗
An end-to-end pipeline for succinic acid production at an industrially relevant scale using Issatchenkia orientalis
Abstract Microbial production of succinic acid (SA) at an industrially relevant scale has been hindered by high downstream processing costs arising from neutral pH fermentation for over three decades. Here, we metabolically engineer the acid-tolerant yeast Issatchenkia orientalis for SA production, attaining the highest titers in sugar-based media at low pH (pH 3) in fed-batch fermentations, i.e. 109.5 g/L in minimal medium and 104.6 g/L in sugarcane juice medium. We further perform batch fermentation using sugarcane juice medium in a pilot-scale fermenter (300×) and achieve 63.1 g/L of SA, which can be directly crystallized with a yield of 64.0%. Finally, we simulate an end-to-end low-pH SA production pipeline, and techno-economic analysis and life cycle assessment indicate our process is financially viable and can reduce greenhouse gas emissions by 34–90% relative to fossil-based production processes. We expect I. orientalis can serve as a general industrial platform for production of organic acids.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Conserved chromatin and repetitive patterns reveal slow genome evolution in frogs
Frogs are an ecologically diverse and phylogenetically ancient group of anuran amphibians that include important vertebrate cell and developmental model systems, notably the genus Xenopus. Here we report a high-quality reference genome sequence for the western clawed frog, Xenopus tropicalis, along with draft chromosome-scale sequences of three distantly related emerging model frog species, Eleutherodactylus coqui, Engystomops pustulosus, and Hymenochirus boettgeri. Frog chromosomes have remained remarkably stable since the Mesozoic Era, with limited Robertsonian (i.e., arm-preserving) translocations and end-to-end fusions found among the smaller chromosomes. Conservation of synteny includes conservation of centromere locations, marked by centromeric tandem repeats associated with Cenp-a binding surrounded by pericentromeric LINE/L1 elements. This work explores the structure of chromosomes across frogs, using a dense meiotic linkage map for X. tropicalis and chromatin conformation capture (Hi-C) data for all species. Abundant satellite repeats occupy the unusually long (~20 megabase) terminal regions of each chromosome that coincide with high rates of recombination. Both embryonic and differentiated cells show reproducible associations of centromeric chromatin and of telomeres, reflecting a Rabl-like configuration. Our comparative analyses reveal 13 conserved ancestral anuran chromosomes from which contemporary frog genomes were constructed.
59 BASIC BIOLOGICAL SCIENCES↗