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At least 865 records · Page 48

The effect of shear strain and shear localization on fault healing

The seismic cycle of repeated earthquake failure requires that faults regain frictional strength during the interseismic phase, when the fault is locked or undergoing quasi-static creep. Fault healing plays a central role in determining earthquake stress drop, recurrence interval, elastic radiation frequency and other source parameters. In particular, the longer a fault remains quasi-stationary, the stronger it becomes and the larger the potential stress drop can be for the next event. Here, we address the role of shear strain and strain localization on fault healing and healing rate. We performed slide-hold-slide friction experiments on quartz gouge in the double-direct shear configuration for shear strain up to 25 and hold times from 10 to 1000 s. The results show that both healing and healing rate increase nonlinearly with increasing shear strain. Frictional healing scales with volumetric strain within the laboratory fault zone. Using the volumetric strain upon reshear as a proxy for strain localization, we demonstrate that the capacity of a fault to heal is directly proportional to shear bandwidth and degree of strain localization. The more the deformation is localized, the higher are the healing and healing rate, and thus, the fault strength. Our data provide a framework for understanding variations in fault strength over the seismic cycle and the role of brecciation and strain localization on spatiotemporal variations in fault strength.

58 GEOSCIENCES↗

LATTE: open-source, high-performance traveltime computation, tomography and source location in acoustic and elastic media

Traveltime-based tomography and source location are fundamental approaches for imaging subsurface structures and understanding the spatiotemporal distribution of seismicity from local to global scales. We present an open-source, high-performance framework integrating eikonal equation solvers and adjoint-state theory for traveltime computation, velocity tomography, source location and joint tomography-location in 2-D/3-D acoustic and elastic media. We introduce novel regularization schemes based on total generalized p-variation, structural similarity and multitask machine learning to enhance the fidelity and interpretability of inverted models and source locations. Key features of our implementation also include the ability to leverage both absolute-difference and double-difference traveltime misfits for high-fidelity velocity tomography and source parameter estimation; support for traveltime computation and inversion in diverse 2-D/3-D scenarios with arbitrary source and receiver distributions; and a perturbation-based optimal step-size estimation method to reduce computational costs. In addition, our implementation employs shared-memory and distributed-memory parallelization to provide an efficient solution for traveltime computation, tomography, and source location. In conclusion, we validate the efficacy and accuracy of our approach through multiple synthetic data examples.

58 GEOSCIENCES↗

Landscape analysis of environmental data sources for linkage with SEER cancer patients database

Abstract One of the challenges associated with understanding environmental impacts on cancer risk and outcomes is estimating potential exposures of individuals diagnosed with cancer to adverse environmental conditions over the life course. Historically, this has been partly due to the lack of reliable measures of cancer patients’ potential environmental exposures before a cancer diagnosis. The emerging sources of cancer-related spatiotemporal environmental data and residential history information, coupled with novel technologies for data extraction and linkage, present an opportunity to integrate these data into the existing cancer surveillance data infrastructure, thereby facilitating more comprehensive assessment of cancer risk and outcomes. In this paper, we performed a landscape analysis of the available environmental data sources that could be linked to historical residential address information of cancer patients’ records collected by the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program. The objective is to enable researchers to use these data to assess potential exposures at the time of cancer initiation through the time of diagnosis and even after diagnosis. The paper addresses the challenges associated with data collection and completeness at various spatial and temporal scales, as well as opportunities and directions for future research.

60 APPLIED LIFE SCIENCES↗

Expression of dehydroshikimate dehydratase in poplar induces transcriptional and metabolic changes in the phenylpropanoid pathway

Abstract Modification of lignin in feedstocks via genetic engineering aims to reduce biomass recalcitrance to facilitate efficient conversion processes. These improvements can be achieved by expressing exogenous enzymes that interfere with native biosynthetic pathways responsible for the production of the lignin precursors. In planta expression of a bacterial 3-dehydroshikimate dehydratase in poplar trees reduced lignin content and altered the monomer composition, which enabled higher yields of sugars after cell wall polysaccharide hydrolysis. Understanding how plants respond to such genetic modifications at the transcriptional and metabolic levels is needed to facilitate further improvement and field deployment. In this work, we acquired fundamental knowledge on lignin-modified poplar expressing 3-dehydroshikimate dehydratase using RNA-seq and metabolomics. The data clearly demonstrate that changes in gene expression and metabolite abundance can occur in a strict spatiotemporal fashion, revealing tissue-specific responses in the xylem, phloem, or periderm. In the poplar line that exhibited the strongest reduction in lignin, we found that 3% of the transcripts had altered expression levels and ~19% of the detected metabolites had differential abundance in the xylem from older stems. The changes affected predominantly the shikimate and phenylpropanoid pathways as well as secondary cell wall metabolism, and resulted in significant accumulation of hydroxybenzoates derived from protocatechuate and salicylate.

59 BASIC BIOLOGICAL SCIENCES↗

Magnetic frame-dragging correction to the electromagnetic solution of a compact neutron star

ABSTRACT Neutron stars are usually modelled as spherical, rotating perfect conductors with a predominant intrinsic dipolar magnetic field anchored to their stellar crust. Due to their compactness, General Relativity corrections must be accounted for in Maxwell’s equations, leading to modified interior and exterior electromagnetic solutions. We present analytical solutions for slowly rotating magnetized neutron stars, taking into account the magnetic frame-dragging correction. For typical compactness values, i.e. Rs ∼ 0.5 [R*], we show that the new terms lead to a per cent order correction in the magnetic field orientation and strength compared to the case, with no magnetic frame-dragging correction. Also, we obtain a self-consistent redistribution of the surface azimuthal current. We verify the validity of the derived solution through two-dimensional particle-in-cell simulations of an isolated neutron star. Defining the azimuthal electric and magnetic field amplitudes during the transient phase as observables, we prove that the magnetic frame-dragging correction reduces the transient wave amplitude, as expected from the analytical solution. We show that simulations are more accurate and stable, when we include all first-order terms. The increased accuracy at lower spatiotemporal resolutions translates into a reduction in simulation runtimes.

Torres, R. (ORCID:0000000291820228)↗

Footprints of Worldwide Adaptation in Structured Populations of Drosophila melanogaster Through the Expanded DEST 2.0 Genomic Resource

Abstract Large-scale genomic resources can place genetic variation into an ecologically informed context. To advance our understanding of the population genetics of the fruit fly Drosophila melanogaster, we present an expanded release of the community-generated population genomics resource Drosophila Evolution over Space and Time (DEST 2.0; https://dest.bio/). This release includes 530 high-quality pooled libraries from flies collected across six continents over more than a decade (2009 to 2021), most at multiple time points per year; 211 of these libraries are sequenced and shared here for the first time. We used this enhanced resource to elucidate several aspects of the species' demographic history and identify novel signs of adaptation across spatial and temporal dimensions. For example, we showed that the spatial genetic structure of populations is stable over time, but that drift due to seasonal contractions of population size causes populations to diverge over time. We identified signals of adaptation that vary between continents in genomic regions associated with xenobiotic resistance, consistent with independent adaptation to common pesticides. Moreover, by analyzing samples collected during spring and fall across Europe, we provide new evidence for seasonal adaptation related to loci associated with pathogen response. Furthermore, we have also released an updated version of the DEST genome browser. This is a useful tool for studying spatiotemporal patterns of genetic variation in this classic model system.

Biochemistry & Molecular Biology↗

Responses of the Plant Cell Wall to Sub-Zero Temperatures: A Brief Update

Our general understanding of plant responses to sub-zero temperatures focuses on mechanisms that mitigate stress to the plasma membrane. The plant cell wall receives comparatively less attention, and questions surrounding its role in mitigating freezing injury remain unresolved. Despite recent molecular discoveries that provide insight into acclimation responses, the goal of reducing freezing injury in herbaceous and woody crops remains elusive. This is likely due to the complexity associated with adaptations to low temperatures. Understanding how leaf cell walls of herbaceous annuals promote tissue tolerance to ice does not necessarily lead to understanding how meristematic tissues are protected from freezing by tissue-level barriers formed by cell walls in overwintering tree buds. In this mini-review, we provide an overview of biological ice nucleation and explain how plants control the spatiotemporal location of ice formation. We discuss how sugars and pectin side chains alleviate adhesive injury that develops at sub-zero temperatures between the matrix polysaccharides and ice. The importance of site-specific cell-wall elasticity to promote tissue expansion for ice accommodation and control of porosity to impede ice growth and promote supercooling will be presented. How specific cold-induced proteins modify plant cell walls to mitigate freezing injury will also be discussed. The opinions presented in this report emphasize the importance of a plant’s developmental physiology when characterizing mechanisms of freezing survival.

59 BASIC BIOLOGICAL SCIENCES↗

Leading the way out: how a plant myosin facilitates vesicle tethering during exocytosis

Exocytosis is a process by which molecules, such as lipids, proteins, and polysaccharides, are delivered to the plasma membrane (PM) and the extracellular space via vesicular transport. Precise orchestration of this process ensures the spatiotemporal specificity of cargo delivery and therefore plays a vital role in cell growth, function, and response to environmental cues (reviewed in Wu and Guo, 2015; Ravikumar et al., 2017). Lastly, while sophisticated mechanisms for exocytosis have been described in animal and yeast cells, the extent of conservation of these mechanisms in plant systems is far less clear.

59 BASIC BIOLOGICAL SCIENCES↗

Arabidopsis myosin XIK interacts with the exocyst complex to facilitate vesicle tethering during exocytosis

Myosin motors are essential players in secretory vesicle trafficking and exocytosis in yeast and mammalian cells; however, similar roles in plants remain a matter for debate, at least for diffusely growing cells. Here, we demonstrate that Arabidopsis (Arabidopsis thaliana) myosin XIK, via its globular tail domain (GTD), participates in the vesicle tethering step of exocytosis through direct interactions with the exocyst complex. Specifically, myosin XIK GTD bound directly to several exocyst subunits in vitro and functional fluorescently tagged XIK colocalized with multiple exocyst subunits at plasma membrane (PM)-associated stationary foci. Moreover, genetic and pharmacological inhibition of myosin XI activity reduced the rate of appearance and lifetime of stationary exocyst complexes at the PM. By tracking single exocytosis events of cellulose synthase (CESA) complexes with high spatiotemporal resolution imaging and pair-wise colocalization of myosin XIK, exocyst subunits, and CESA6, we demonstrated that XIK associates with secretory vesicles earlier than exocyst and is required for the efficient localization and normal dynamic behavior of exocyst complex at the PM tethering site. This study reveals an important functional role for myosin XI in secretion and provides insights about the dynamic regulation of exocytosis in plants.

59 BASIC BIOLOGICAL SCIENCES↗

A family of α/β hydrolases removes phytol from chlorophyll metabolites for tocopherol biosynthesis in Arabidopsis

Tocopherol synthesis requires phytyl diphosphate derived from phytol esterified to chlorophyll metabolites. The >600-member Arabidopsis thaliana α/β hydrolase (ABH) gene family contains 4 members that can release phytol from chlorophyll metabolites in vitro; however, only pheophytinase (PPH) affects tocopherol synthesis when mutated, reducing seed tocopherols by 5%. We report the biochemical analysis of 2 previously uncharacterized ABHs, chlorophyll dephytylase 2 (CLD2) and CLD3, and their respective mutants singly and in combinations with pph and cld1 alleles. While all CLDs localized to the thylakoid and could hydrolyze phytol from chlorophylls and Pheophytin a in vitro, CLD3 had the highest in vitro activity and the largest effect on tocopherol synthesis in vivo. The 3 CLDs acted cooperatively to provide phytol for 31% of tocopherols synthesized in light-grown leaf tissue. Dark-induced leaf senescence assays showed PPH is required for 18% of the tocopherols synthesized. Though the cld123 triple mutant had no impact on dark-induced tocopherol content, cld123 in the pph background reduced tocopherol levels by an additional 18%. In seeds, pph and cld123 each reduced tocopherol content by 5% and by 15% in the cld123pph quadruple mutant. VTE7 ( ViTamin E7 ) is an envelope-localized ABH that specifically affects chlorophyll biosynthetic intermediates in vivo and is required for 55% of seed tocopherol synthesis. The introduction of cld123pph into the vte7 background further reduced seed tocopherol levels to 23% of that of the wild type. Our findings demonstrate that phytol provision for tocopherol biosynthesis and homeostasis is a complex process involving the coordinated spatiotemporal expression of multiple ABH family members.

arabidopsis↗

Complete replacement of Arabidopsis oil-producing enzymes with heterologous diacylglycerol acyltransferases

Acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1) and phospholipid:diacylglycerol acyltransferase 1 (PDAT1) share responsibility for triacylglycerol (TAG) biosynthesis, and their selectivities control TAG fatty acid (FA) compositions. For rational metabolic engineering of seed oils, replacing endogenous TAG biosynthesis with exogenous enzymes containing different substrate FA selectivities is desirable; however, the dgat1-1/pdat1-2 double mutant is pollen lethal. Here, we evaluated the ability of 3 DGAT1s, from phylogenetically diverse plants with distinct TAG assembly processes, to completely replace endogenous TAG biosynthesis in Arabidopsis ( Arabidopsis thaliana ). We transformed dgat1-1 mutant plants with expression constructs for DGAT1 s from Camelina sativa , Physaria fendleri , and castor ( Ricinus communis ). Transgene expression was properly “contextualized” by using a previously determined minimum necessary expression unit containing the promoter/5′ UTR and first intron of native AtDGAT1 ; both of these DNA elements are essential for pollen expression. Next, we crossed homozygous lines with a DGAT1/DGAT1/PDAT1/pdat1-2 parent. C. sativa and P. fendleri DGAT1s restored the FA compositions and transcriptional differences of dgat1-1 to near wild-type and rescued the dgat1-1/pdat1-2 pollen lethality. R. communis DGAT1 was active in dgat1-1 seeds but produced unique oil profiles and alterations in the expression of lipid metabolic genes; it also failed to rescue dgat1-1/pdat1-2 lethality. This study confirms that the promoter and first intron of AtDGAT1 can modulate the expression of foreign DGAT1 genes to fit the correct spatiotemporal profile necessary for completely replacing endogenous TAG biosynthesis. Furthermore, it demonstrates an additional layer of unexpected enzyme incompatibility between oilseed lineages, which may complicate bioengineering approaches that seek to replace essential genes with orthologs.

McGuire, Sean T. [Washington State Univ., Pullman,↗

Genomics-enabled analysis of specialized metabolism in bioenergy crops: Current progress and challenges

Plants produce a staggering diversity of specialized small molecule metabolites that play vital roles in mediating environmental interactions and stress adaptation. This chemical diversity derives from dynamic biosynthetic pathway networks that are often species-specific and operate under tight spatiotemporal and environmental control. A growing divide between demand and environmental challenges in food and bioenergy crop production have intensified research on these complex metabolite networks and their contribution to crop fitness. High-throughput omics technologies provide access to ever-increasing data resources for investigating plant metabolism. However, the efficiency of using such system-wide data to decode the gene and enzyme functions controlling specialized metabolism has remained limited; due largely to the recalcitrance of many plants to genetic approaches and the lack of ‘user-friendly’ biochemical tools for studying the diverse enzyme classes involved in specialized metabolism. With emphasis on terpenoid metabolism in the bioenergy crop switchgrass as an example, this review aims to illustrate current advances and challenges in the application of DNA synthesis and synthetic biology tools for accelerating the functional discovery of genes, enzymes and pathways in plant specialized metabolism. These technologies have accelerated knowledge development on the biosynthesis and physiological roles of diverse metabolite networks across many ecologically and economically important plant species and can provide resources for application to precision breeding and natural product metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Development of an Experimental Approach to Achieve Spatially Resolved Plant Root-Associated Metaproteomics Using an Agar-Plate System

Plant–microbe interactions in the rhizosphere play a vital role in plant health and productivity. The composition and function of root-associated microbiomes is strongly influenced by their surrounding environment, which is often customized by their host. How microbiomes change with respect to space and time across plant roots remains poorly understood, and methodologies that facilitate spatiotemporal metaproteomic studies of root-associated microbiomes are yet to be realized. Here, we developed a method that provides spatially resolved metaproteome measurements along plant roots embedded in agar-plate culture systems, which have long been used to study plants. Spatially defined agar “plugs” of interest were excised and subsequently processed using a novel peptide extraction method prior to metaproteomics, which was used to infer both microbial community composition and function. As a proof-of-principle, a previously studied 10-member community constructed from a Populus root system was grown in an agar plate with a 3-week-old Populus trichocarpa plant. Metaproteomics was performed across two time points (24 and 48 h) for three distinct locations (root base, root tip, and a region distant from the root). The spatial resolution of these measurements provides evidence that microbiome composition and expression changes across the plant root interface. Interrogation of the individual microbial proteomes revealed functional profiles related to their behavioral associations with the plant root, in which chemotaxis and augmented metabolism likely supported predominance of the most abundant member. This study demonstrated a novel peptide extraction method for studying plant agar-plate culture systems, which was previously unsuitable for (meta)proteomic measurements.

59 BASIC BIOLOGICAL SCIENCES↗

Closed-Loop Control of Active Nematic Flows

Stabilizing and shaping autonomous flows of active fluids is a fundamental challenge and a prerequisite for applications. We embed a light-responsive microtubule-based nematic in a proportional-integral control loop that adjusts the applied light intensity in response to real-time measurements of the spatially averaged flow speed. The self-regulating hardware-software-wetware system maintains a target flow speed against external or internal perturbations, including protein aging and aggregation, sample-to-sample variability, and temperature variation. Varying the controller’s gains reveals antagonistic roles between feedback and intrinsic processes, leading to nontrivial dynamics observed in fluctuation spectra. In particular, oscillations emerge from the interplay between the controller, motor binding kinetics, and active hydrodynamic relaxation. Accounting for the underlying binding timescale, our coarse-grained model and nematohydrodynamics simulations corroborate these observations. This work provides insight into the coupled dynamics of controlled active matter, laying the foundation for spatiotemporal patterning of active stress to generate and stabilize new dynamical configurations.

Active nematics↗

Recurrent convolutional neural networks for modeling nonadiabatic dynamics of quantum-classical systems

Recurrent neural networks (RNNs) have recently been extensively applied to model the time evolution in fluid dynamics, weather predictions, and even chaotic systems due to their ability to capture temporal dependencies and sequential patterns in data. Here we present an RNN model based on convolutional neural networks for modeling the nonlinear nonadiabatic dynamics of hybrid quantum-classical systems. The dynamical evolution of the hybrid systems is governed by equations of motion for classical degrees of freedom and von Neumann equation for electrons. The Physics-Aware Recurrent Convolution (PARC) neural network structure incorporates a differentiator-integrator architecture that inductively models the spatiotemporal dynamics of generic physical systems. Here, we apply our RNN approach to learn the space-time evolution of a one-dimensional semiclassical Holstein model after an interaction quench. For shallow quenches (small changes in electron-lattice coupling), the deterministic dynamics can be accurately captured using a single-CNN-based recurrent network. In contrast, deep quenches induce chaotic evolution, making long-term trajectory prediction significantly more challenging. Nonetheless, we demonstrate that the PARC-CNN architecture can effectively learn the statistical climate of the Holstein model under deep-quench conditions.

Holstein model↗

String-Breaking Dynamics in Quantum Adiabatic and Diabatic Processes

Confinement prohibits isolation of color charges, e.g., quarks, in nature via a process called string breaking : the separation of two charges results in an increase in the energy of a color flux, visualized as a string, connecting those charges. Eventually, creating additional charges is energetically favored, hence breaking the string. Such a phenomenon can be probed in simpler models, including quantum spin chains, enabling enhanced understanding of string-breaking dynamics. A challenging task is to understand how string breaking occurs as time elapses, in an out-of-equilibrium setting. This work establishes the phenomenology of dynamical string breaking induced by a gradual increase of string tension over time. It, thus, goes beyond instantaneous quench processes and enables tracking the real-time evolution of strings in a more controlled setting. We focus on domain-wall confinement in a family of quantum Ising chains. Our results indicate that, for sufficiently short strings and slow evolution, string breaking can be described by the transition dynamics of a two-state quantum system akin to a Landau-Zener process. For longer strings, a more intricate spatiotemporal pattern emerges: the string breaks by forming a superposition of bubbles (domains of flipped spins of varying sizes), which involve highly excited states. We finally demonstrate that string breaking driven only by quantum fluctuations can be realized in the presence of sufficiently long-ranged interactions. This work holds immediate relevance for studying string breaking in quantum-simulation experiments.

Ising model↗

Sparse non-Markovian Noise Modeling of Transmon-Based Multi-Qubit Operations

The influence of noise on quantum dynamics is one of the main factors preventing current quantum processors from performing accurate quantum computations. Sufficient noise characterization and modeling can provide key insights into the effect of noise on quantum algorithms and inform the design of targeted error protection protocols. However, constructing effective noise models that are sparse in model parameters, yet predictive can be challenging. In this work, we present an approach for effective noise modeling of multi-qubit operations on transmon-based devices. Through a comprehensive characterization of seven devices offered by the IBM Quantum Platform, we show that the model can capture and predict a wide range of single- and two-qubit behaviors, including non-Markovian effects resulting from spatiotemporally correlated noise sources. The model’s predictive power is further highlighted through multi-qubit dynamical decoupling demonstrations and an implementation of the variational quantum eigensolver. As a training proxy for the hardware, we show that the model can predict expectation values within a relative error of 0.5%; this is a sevenfold improvement over default hardware noise models. Through these demonstrations, we highlight key error sources in superconducting qubits and illustrate the utility of reduced noise models for predicting hardware dynamics.

open quantum systems & decoherence↗

Intrinsic spatial chirp of subcycle terahertz pulsed beams

Here, we present an analysis of spatial chirp in subcycle pulsed beams corroborated by spatiotemporal electro-optic sampling measurements of terahertz radiation. Modeling the subcycle pulsed beam as a superposition of monochromatic Gaussian beams, free-space propagation is shown to directly lead to lateral spatial chirp with the spectrum on-axis substantially bluer than the overall energy spectrum. The two-transverse + one-temporal dimensional profile of terahertz subcycle pulsed beams from organic crystals DSTMS and OH1 are measured and compared with observed spatiospectral correlations consistent with the model.

43 PARTICLE ACCELERATORS↗