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At least 1,081 records · Page 60

De Novo Design of High‐Affinity Miniprotein Binders Targeting Francisella Tularensis Virulence Factor

Abstract Francisella tularensis poses considerable public health risk due to its high infectivity and potential for bioterrorism. Francisella‐like lipoprotein (Flpp3), a key virulence factor unique to Francisella, plays critical roles in infection and immune evasion, making it a promising target for therapeutic development. However, the lack of well‐defined binding pockets and structural information on native interactions has hindered structure‐guided ligand discovery against Flpp3. Here, we used a combination of physics‐based and deep‐learning methods to design high‐affinity miniprotein binders targeting two distinct sites on Flpp3. We identified four binders for site I with binding affinities ranging between 24–110 nM. For the second site, an initial binder showed a dissociation constant ( K D ) of 81 nM, and subsequent site saturation mutagenesis yielded variants with sub‐nanomolar affinities. Circular dichroism confirmed the topology of designed miniproteins. The X‐ray crystal structure of Flpp3 in complex with a site I binder is nearly identical to the design model (Cα root‐mean‐square deviation (RMSD): 0.9 Å). These designed miniproteins provide research tools to explore the roles of Flpp3 in tularemia and should enable the development of new therapeutic candidates.

Gokce‐Alpkilic, Gizem [Molecular Engineering and S↗

Protective effects of non–catalytic proteins on endoglucanase activity at air and lignin interfaces

The manner in which added non-catalytic proteins during enzymatic hydrolysis of lignocellulosic substrates enhances hydrolysis mechanisms is not completely understood. Prior research has indicated that a reduction in the non-specific adsorption of enzymes on lignin, and deactivation of enzymes exposed to air–liquid interface provide rationale. This work investigated root causes including effects of the air–liquid interface on non-catalytic proteins, and effects of lignin on endoglucanase. Three different experimental designs and three variables (air–liquid interfacial area, the types of lignin (acid or enzymatic lignin), and the presence of non-enzymatic protein (bovine serum albumin [BSA] or soy proteins ) were used. The results showed that acid isolated lignin adsorbed almost all endoglucanase activity initially present in supernatant, independent of air interface conditions (25 or 250 ml flasks) with the presence of BSA preventing this effect. Endoglucanase lost 30%–50% of its activity due to an air–liquid interface in the presence of lignin while addition of non-enzymatic protein helped to preserve this enzyme's activity. Langmuir and Freundlich models applied to experimental data indicated that the adsorption increases with increasing temperature for both endoglucanase and BSA. Adsorption of the enzyme and protein were endothermic with an increase in entropy. Finally, these results, combined, show that hydrophobicity plays a strong role in the adsorption of both endoglucanase and BSA on lignin.

59 BASIC BIOLOGICAL SCIENCES↗

h5bench: A unified benchmark suite for evaluating HDF5 I/O performance on pre‐exascale platforms

Summary Parallel I/O is a critical technique for moving data between compute and storage subsystems of supercomputers. With massive amounts of data produced or consumed by compute nodes, high‐performant parallel I/O is essential. I/O benchmarks play an important role in this process; however, there is a scarcity of I/O benchmarks representative of current workloads on HPC systems. Toward creating representative I/O kernels from real‐world applications, we have created h5bench , a set of I/O kernels that exercise hierarchical data format version 5 (HDF5) I/O on parallel file systems in numerous dimensions. Our focus on HDF5 is due to the parallel I/O library's heavy usage in various scientific applications running on supercomputing systems. The various tests benchmarked in the h5bench suite include I/O operations (read and write), data locality (arrays of basic data types and arrays of structures), array dimensionality (one‐dimensional arrays, two‐dimensional meshes, three‐dimensional cubes), I/O modes (synchronous and asynchronous). In this paper, we present the observed performance of h5bench executed along several of these dimensions on existing supercomputers (Cori and Summit) and pre‐exascale platforms (Perlmutter, Theta, and Polaris). h5bench measurements can be used to identify performance bottlenecks and their root causes and evaluate I/O optimizations. As the I/O patterns of h5bench are diverse and capture the I/O behaviors of various HPC applications, this study will be helpful to the broader supercomputing and I/O community.

97 MATHEMATICS AND COMPUTING↗

Cell-Type-Specific Proteomics Analysis of a Small Number of Plant Cells by Integrating Laser Capture Microdissection with a Nanodroplet Sample Processing Platform

Plant organs and tissues contain multiple cell types, which are well organized in 3-dimensional structure to efficiently perform physiological functions such as homeostasis, response to environmental perturbation, pathogen infection. It is critically important to perform molecular measurements at the cell-type-specific level to discover mechanisms and unique features of cell populations that govern differentiation and respond to external perturbations. Although mass spectrometry-based proteomics has been demonstrated as an enabling discovery tool to study plant physiology, conventional approaches require millions of cells to generate robust biological conclusions. Such requirements mask the cell-to-cell heterogeneities and limit the comprehensive profiling of plant proteins at spatially resolved and cell-type-specific resolutions. This protocol describes a recently-developed proteomics workflow for studying a small number of plant cells by integrating laser capture microdissection, microfluidic nanodroplet-based sample preparation, with ultrasensitive liquid chromatography-mass spectrometry. Using poplar as a model tree species, we provide detailed protocols, including plant tissue harvest, tissue preparation, cryosectioning, laser microdissection, protein digestion, mass spectrometry measurement, and data analysis. We show the workflow enables the precise identification and quantification of thousands of proteins from hundreds of isolated plant root and leaf cells.

59 BASIC BIOLOGICAL SCIENCES↗

Beyond carbon flux partitioning: Carbon allocation and nonstructural carbon dynamics inferred from continuous fluxes

Carbon (C) allocation and nonstructural carbon (NSC) dynamics play essential roles in plant growth and survival under stress and disturbance. However, quantitative understanding of these processes remains limited. Here, in this work, we propose a framework where we connect commonly measured carbon cycle components (eddy covariance fluxes of canopy CO 2 exchange, soil CO 2 efflux, and allometry-based biomass and net primary production) by a simple mass balance model to derive ecosystem-level NSC dynamics (NSC i ), C translocation (dC i ), and the biomass production efficiency (BPE i ) in above- and belowground plant (i = agp and bgp) compartments. We applied this framework to two long-term monitored loblolly pine (Pinus taeda) plantations of different ages in North Carolina and characterized the variations of NSC and allocation in years under normal and drought conditions. The results indicated that the young stand did not have net NSC flux at the annual scale, whereas the mature stand stored a near-constant proportion of new assimilates as NSC every year under normal conditions, which was comparable in magnitude to new structural growth. Roots consumed NSC in drought and stored a significant amount of NSC post drought. The above- and belowground dC i and BPE i varied more from year to year in the young stand and approached a relatively stable pattern in the mature stand. The belowground BPE bgp differed the most between the young and mature stands and was most responsive to drought. With the internal C dynamics quantified, this framework may also improve biomass production estimation, which reveals the variations resulting from droughts. Overall, these quantified ecosystem-scale dynamics were consistent with existing evidence from tree-based manipulative experiments and measurements and demonstrated that combining the continuous fluxes as proposed here can provide additional information about plant internal C dynamics. Given that it is based on broadly available flux data, the proposed framework is promising to improve the allocation algorithms in ecosystem C cycle models and offers new insights into observed variability in soil–plant–climate interactions.

54 ENVIRONMENTAL SCIENCES↗

Plant functional types broadly describe water use strategies in the Caatinga, a seasonally dry tropical forest in northeast Brazil

In seasonally dry tropical forests, plant functional type can be classified as deciduous low wood density, deciduous high wood density, or evergreen high wood density species. While deciduousness is often associated with drought-avoidance and low wood density is often associated with tissue water storage, the degree to which these functional types may correspond to diverging and unique water use strategies has not been extensively tested. We examined (a) tolerance to water stress, measured by predawn and mid-day leaf water potential; (b) water use efficiency, measured via foliar δ 13 C; and (c) access to soil water, measured via stem water δ 18 O. We found that deciduous low wood density species maintain high leaf water potential and low water use efficiency. Deciduous high wood density species have lower leaf water potential and variable water use efficiency. Both groups rely on shallow soil water. Evergreen high wood density species have low leaf water potential, higher water use efficiency, and access alternative water sources. These findings indicate that deciduous low wood density species are drought avoiders, with a specialized strategy for storing root and stem water. Deciduous high wood density species are moderately drought tolerant, and evergreen high wood density species are the most drought tolerant group. Our results broadly support the plant functional type framework as a way to understand water use strategies, but also highlight species-level differences.

54 ENVIRONMENTAL SCIENCES↗

Hydraulic redistribution supplies a major water subsidy and improves water status of understory species in a longleaf pine ecosystem

Hydraulic redistribution (HR) is a common phenomenon in water-limited ecosystems; however, it remains unclear how the volume of water transported via HR compares to other components of the hydrologic budget and how HR influences water availability for understory plant communities. In this study, we investigate the absolute and relative magnitude of HR on a forest water budget and identify potential impacts of this water subsidy to understory plant communities. We scaled tree-level estimates of transpiration and HR of three common tree species naturally occurring in a longleaf pine woodland with plot-level measurements of basal area to determine their magnitude at the stand scale. We trenched plots containing understory vegetation but devoid of mature trees and their connected roots to exclude HR subsidies to understory plant species. We analysed soil water isotopes and assessed leaf water potential (Ψ L ) in trenched and control plots to determine if HR results in mixing of water among soil strata and improves understory plant moisture status. Water inputs from HR were equivalent to >30% of total rainfall for the site during the observation period and ~40% of total tree water uptake, depending on species. A stable isotope mixing model confirmed that soil water within HR-exposed plots was more similar to groundwater, whereas soil water within trenched plots was more similar to precipitation. Exclusion of HR via trenching decreased soil moisture and pre-dawn Ψ L for all understory species. These three lines of evidence suggest that HR from overstory trees redistributes a sizable portion of water from deeper to shallower soil profiles and that this water subsidy enhances understory plant water status.

54 ENVIRONMENTAL SCIENCES↗

In silico evaluation of plant nitrification suppression effects on agroecosystem nitrogen loss

Abstract Nitrification regulates the potential for nitrogen (N) loss from ecosystems because it converts ammonium to nitrate, which is susceptible to leaching and gaseous emissions. Crops can suppress the microbes that perform nitrification by exuding nitrification‐inhibiting compounds from their roots and taking up available ammonium. However, the effect of nitrification suppression on agroecosystem N losses remains poorly characterized, and a lack of temporal synchrony between nitrification, N losses, and nitrification suppression by plants could limit the effect of nitrification suppression. We used the DayCent‐CABBI model to evaluate the effectiveness of the suppression of nitrification by sorghum to reduce N 2 O emissions and nitrate leaching in an energy sorghum/soybean rotation at the Energy Farm in Urbana‐Champaign, IL. We simulated nitrification suppression at the measured levels (MeasNS) and at the maximum measured level applied to the entire growing season (MaxNS), and we also explored ways to better utilize nitrification suppression by altering the timing of urea–ammonium–nitrate fertilizer applications. Model experiments showed that most nitrification occurred immediately after fertilizer was applied, whereas nitrification suppression began to ramp up more than a month after planting. On an annual basis, MeasNS experiments showed a 1%–2% reduction in annual N 2 O emissions relative to no nitrification suppression (NoNS), and MaxNS experiments showed a 4%–9% reduction in annual N 2 O emissions relative to NoNS. Both nitrification suppression levels showed <1% reduction in nitrate leaching. Altering the timing of fertilizer applications to better synchronize nitrification suppression with high soil ammonium levels had mixed effects on annual N 2 O emissions and nitrate leaching and sometimes resulted in increased N losses. The timing of simulated N 2 O emissions shifted with the timing of fertilization, and N 2 O emissions from denitrification increased when N 2 O emissions from nitrification decreased. Increasing N retention during the non‐growing season may be more effective than growing‐season nitrification suppression for reducing annual N losses in the rainfed Midwest.

60 APPLIED LIFE SCIENCES↗

Using phenology to unravel differential soil water use and productivity in a semiarid savanna

Savannas are water-limited ecosystems characterized by two dominant plant types: trees and an understory primarily made up grass. Different phenology and root structures of these plant types complicate how savanna primary productivity responds to changes in water availability. We tested the hypothesis that productivity in savannas is controlled by the temporal and vertical distribution of soil water content (SWC) and differences in growing season length of understory and tree plant functional types. To quantify the relationship between tree, understory, and savanna-wide phenology and productivity, we used PhenoCam and satellite observations surrounding an eddy covariance tower at a semiarid savanna site in Arizona, USA. We distinguished between SWC across two different depth intervals (shallow, <0–30 cm and deep, >30–100 cm). We found that tree greenness increased with SWC at both depths, while understory greenness was only sensitive to the shallower SWC measurements. Onset of ecosystem dormancy, estimated from satellite observations close to the eddy covariance tower, explained more variability in annual gross primary productivity (GPP) than in other phenometrics. Higher SWC led to an extended growing season, caused by delayed dormancy in trees, but the understory showed no evidence of delayed dormancy in wetter periods. We infer that the timing of ecosystem scale dormancy, driven by trees, is important in understanding changes in a savanna's GPP. These findings highlight the important effects of rainfall during the winter. These findings suggest that savanna GPP is conditional on different responses to moisture availability in each of the dominant vegetation components.

54 ENVIRONMENTAL SCIENCES↗

Morphophysiological Plant Phenotyping for the Development of Plant Breeding Under Drought and Heat Conditions: A Practical Approach

ABSTRACT Currently, the breeding programs focus their efforts on identifying and developing tolerant genotypes to adverse conditions, such as drought and high temperatures. In this context, the physiological approach, which involves phenotyping several traits, is useful for breeding programs. Leaf photosynthetic traits have become one of the main objectives to be evaluated for breeders due to their relationship with improving grain yield and biomass production. Gas exchange ( Ge ) and chlorophyll “a” fluorescence ( Chf ) are the main tools to characterize the photosynthetic activity in real time at the leaf level. Consequently, several association studies using proximal and nonproximal sensing (e.g., RGB, thermography) have been developed. However, for the correct application of this breeding approach, it is essential to have a basic knowledge of both the physiological principles involved in the readings and the limitations of phenotyping due to the characteristics of the devices available on the market. This revision also covers other traits, such as the morphological and anatomical characteristics of leaves and roots, and the use of isotopes complementing Ge and Chf measurements.

Estrada, Félix [Instituto de Investigaciones Agrop↗

Soil water percolation and nutrient fluxes as a function of topographical, seasonal and soil texture variation in Central Amazonia, Brazil

Abstract Understanding soil water dynamics and transport of nutrients is challenging in tropical rainforests due to the uniqueness of several properties related to soils, vegetation and seasonality that make relating patterns found in temperate environments to tropical sites difficult. We address the need for better edaphic characterization in tropical environments by investigating soil water percolation rates and chemistry across topographic, soil texture and seasonal gradients in a mature tropical rainforest in Central Amazonia, Brazil. We utilized a passive wick flux meter (e.g., drainage lysimeter) to directly measure real‐time percolation fluxes at 60‐cm depth, and to sample a suite of chemical species across plateau, slope and valley topographic positions. We found percolation flux volume and chemical exports generally increase with decreasing elevation and clay content, which was lowest in the valley. Daily percolation flux was observed to be 2.39 ± 0.44 in plateau, 3.01 ± 0.50 in slope and 6.16 ± 0.83 mm in valley. Most solutes were present in small amounts of <1 mg L −1 , such as PO₄ 3− , Fe 2+ /Fe 3+ and Mn 2+ ; however, NO 3 − concentrations were >20 mg L −1 , even exceeding 100 mg L −1 in the valley. Based on additional isotopic analysis, we speculate high NO 3 − concentrations are partially an artefact of root decomposition following installation of the flux meters. The empirical relationships we show among percolation volume and nutrient exports under varying topographies and soil textures can improve Earth System Model performance by better constraining ecohydrological relationships to nutrient fluxes, which can in‐turn better illuminate the important factors that govern their behaviour.

54 ENVIRONMENTAL SCIENCES↗

Phosphorus budgets of intensively managed row crops at a long–term agroecosystem research site in the upper US Midwest

Phosphorus (P) budgets for cropping systems provide insights for keeping soil P at optimal levels for crops while avoiding excess inputs. We quantified 12 years of P inputs (fertilizer and atmospheric deposition) and outputs (harvest and leaching losses) for replicated maize (Zea mays L.)—soybean (Glycine max L.)—wheat (Triticum aestivum) crop rotations under conventional, no-till, reduced input, and biologically based (organic without compost or manure) management systems at the Kellogg Biological Station LTAR site in southwest Michigan. Conventional, no-till, and reduced input systems were fertilized between 13 and 50 kg P ha –1 depending on year. Soil test phosphorus (STP) was measured at 0- to 25-cm depth every autumn. Leached P was measured as dissolved P in the soil solution sampled beneath the rooting depth and combined with modeled percolation. Fertilization and harvest were the predominant P fluxes in the fertilized systems, whereas only harvest dominated P flux in the unfertilized organic system. Leaching losses were minor terms in the budgets, but leachate concentrations were nevertheless close to the range of concern for downstream eutrophication. Over the 12-year study period, the organic system exhibited a negative P balance (–82.0 kg P ha –1 ), coinciding with suboptimal STP levels, suggesting a need for P supplementation. In contrast, the fertilized systems showed positive P balances (mean: 70.1 kg P ha –1 ) with STP levels well above agronomic optima. Results underscore the importance of tailored P management strategies to sustain crop productivity while mitigating environmental impacts.

60 APPLIED LIFE SCIENCES↗

Sensitivity of Fine‐Resolution Urban Heat Island Simulations to Soil Moisture Parameterization

ABSTRACT Urban areas experience the impact of natural disasters, such as heatwaves and flash floods, disparately in different neighbourhoods across a city. The demand for precise urban hydrometeorological and hydroclimatological modelling to examine this disparity, and the interacting challenges posed by climate change and urbanisation, has thus surged. The Weather Research and Forecasting (WRF) model has served such operational and research purposes for decades. Recent advancements in WRF, including enhanced numerical schemes and sophisticated urban atmospheric‐hydrological parameterizations, have empowered the simulation of urban geophysical processes at high resolution (~1 km), but even this resolution misses significant urban microclimate variability. This study applies the large‐eddy simulations (LES) mode within WRF, coupled with single‐layer urban canopy models (SLUCM), to enable even finer‐scale modelling (150 m) of the Urban Heat Island (UHI) effect in the Baltimore metropolitan area. We run nine scenarios to evaluate various methods of initializing soil moisture and various spinup lead times, and to assess the impact of WRF's Mosaic approach in depicting subgrid‐scale processes. We evaluate the scenarios by comparing the WRF simulated land surface temperature (LST) against Landsat LST and the WRF simulated hourly 2‐m air temperatures (AT) with observations from eight weather stations across the domain. Results underscore the paramount influence of the lead spinup time on the spatiotemporal distribution of simulated soil moisture, consequently shaping WRF's efficacy in predicting the UHI. Furthermore, interpolating soil moisture‐related parameters from the parent for child domain initialization yields a notable reduction in mean and root‐mean‐squared errors. This improvement was particularly evident in simulations with the longest spinup time, affirming the importance of carefully designing the initialization of soil moisture for improved urban temperature predictions.

Talebpour, Mahdad↗

Predictive links between microbial communities and biological oxygen utilization in the Arctic Ocean

Microbial metabolism influences rates of net community production (NCP), exerting a direct biological control on marine oxygen and carbon fluxes. In the Arctic, it is increasingly important to understand and quantify this process, as ecological and oceanographic conditions shift due to changing climate. Here, we describe potential ecological links between pelagic microbial diversity and an NCP precursor, biological oxygen utilization, using machine learning and paired observations of community structure and metabolic activity from a seasonally and spatially variable transect of the Arctic Ocean (2019–2020 MOSAiC Expedition). Community structure was determined using 16S (prokaryotic) and 18S (eukaryotic) rRNA gene amplicon sequencing, and metabolic activity was derived from ΔO 2 /Ar. Using self-organizing maps, we identified clear successional patterns in observed microbial community structure that were seasonally driven in the upper ocean and vertically stratified with depth. Metabolic activity was also stratified, with a primarily net heterotrophic water column (median −1.5% biological oxygen saturation), excepting periodic oxygen supersaturation (maximum: 13.6%) within the mixed layer. Using DNA sequences as predictor variables, we then constructed a random forest regression model that reliably reconstructed biological oxygen concentrations (root mean squared error = 4.14 μmol kg −1 ). Top predictors from this model were from heterotrophic (bacteria) or potentially mixotrophic (dinoflagellate) taxa. These analyses highlight biologically driven diagnostic tools that can be used to expand biogeochemical datasets and improve the microbial perspectives and metabolisms represented in ecological models of net productivity and carbon flux in a changing Arctic Ocean.

Chamberlain, Emelia J. [Univ. of San Diego, San Di↗

Observation of Quadratic (Charge-2) Weyl Point Splitting in Near-Infrared Photonic Crystals

Weyl points are point degeneracies that occur in momentum space of 3D periodic materials and are associated with a quantized topological charge. Here, the splitting of a quadratic (charge-2) Weyl point into two linear (charge-1) Weyl points in a 3D micro-printed photonic crystal is observed experimentally via Fourier-transform infrared spectroscopy. Using a theoretical analysis rooted in symmetry arguments, it is shown that this splitting occurs along high-symmetry directions in the Brillouin zone. This micro-scale observation and control of Weyl points is important for realizing robust topological devices in the near-infrared.

47 OTHER INSTRUMENTATION↗

Ionic Liquid Facilitated Solvent‐Phase Polymerization of Ultrasmooth Coatings of Polycatecholamines

Mussel-inspired polycatecholamine coatings and films have proven to be versatile materials for surface modification. However, the progress of chemically modified coatings with tailored properties has been slow due to the lack of definitive evidence of their polymeric structure. Polycatecholamines form aggregates during polymerization, and their formation mechanism has been a subject of debate owing to their insolubility in traditional molecular solvents. Exploiting the capability of ionic liquids (ILs) to exhibit strong electrostatic interactions, herein, the first solution-phase polymerization approach is reported to achieve polymerization of four catecholamines – dopamine (DA), norepinephrine (NE), L-3,4-dihydroxyphenylalanine (L-DOPA), and adrenaline (AD). Kinetic control over the polymerization process in the solution phase enabled it to follow the process with 1 H NMR spectroscopy, revealing the formation of structural features of resulting complex heterogeneous and soluble polymers. The polymers are both covalent and associative in nature. Solution phase polymerization prevented the formation of large aggregates in the solution, thus facilitating the formation of coatings that are ultra-smooth and have root mean square roughness of the order of sub-nm to nm scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Speed vs Accuracy: Effect on Ligand Pose Accuracy of Varying Box Size and Exhaustiveness in AutoDock Vina

Abstract Structure‐based virtual high‐throughput screening involves docking chemical libraries to targets of interest. A parameter pertinent to the accuracy of the resulting pose is the root mean square deviation (RMSD) from a known crystallographic structure, i. e., the ‘docking power’. Here, using a popular algorithm, Autodock Vina, as a model program, we evaluate the effects of varying two common docking parameters: the box size (the size of docking search space) and the exhaustiveness of the global search (the number of independent runs starting from random ligand conformations) on the RMSD from the PDBbind v2017 refined dataset of experimental protein‐ligand complexes. Although it is clear that exhaustiveness is an important parameter, there is wide variation in the values used, with variation between 1 and >100. We, therefore, evaluated a combination of cubic boxes of different sizes and five exhaustiveness values (1, 8, 25, 50, 75, 100) within the range of those commonly adopted. The results show that the default exhaustiveness value of 8 performs well overall for most box sizes. In contrast, for all box sizes, but particularly for large boxes, an exhaustiveness value of 1 led to significantly higher median RMSD (mRMSD) values. The docking power was slightly improved with an exhaustiveness of 25, but the mRMSD changes little with values higher than 25. Therefore, although low exhaustiveness is computationally faster, the results are more likely to be far from reality, and, conversely, values >25 led to little improvement at the expense of computational resources. Overall, we recommend users to use at least the default exhaustiveness value of 8 for virtual screening calculations.

Agarwal, Rupesh↗