Search NASA⌕ Search

SEARCH · Search NASA

Results for “Biophysical Processes”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24

Automating crystallographic structure solution and refinement of protein–ligand complexes

A software system for automated protein–ligand crystallography has been implemented in the Phenix suite. This significantly reduces the manual effort required in high-throughput crystallographic studies. High-throughput drug-discovery and mechanistic studies often require the determination of multiple related crystal structures that only differ in the bound ligands, point mutations in the protein sequence and minor conformational changes. If performed manually, solution and refinement requires extensive repetition of the same tasks for each structure. To accelerate this process and minimize manual effort, a pipeline encompassing all stages of ligand building and refinement, starting from integrated and scaled diffraction intensities, has been implemented in Phenix. The resulting system is able to successfully solve and refine large collections of structures in parallel without extensive user intervention prior to the final stages of model completion and validation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Forest reorganisation effects on fuel moisture content can exceed changes due to climate warming in wet temperate forests

Abstract The distributions of vegetation and fire activity are changing rapidly in response to climate warming. In many regions, climate effects on dead fuel moisture content (FMC) are expected to increase future wildfire activity. However, forest FMC is largely driven by microclimate conditions, which are moderated from open weather by vegetation canopies. As shifts in vegetation increase under climate warming, the extent to which future fire activity will be driven by climate directly or associated vegetation shifts remains unresolved. Here, we present a study aimed at quantifying the relative magnitudes of (i) direct climate warming, and (ii) vegetation change, on FMC. Field sites to evaluate these effects were established in a natural laboratory of altered forest states to mature wet temperate forest in south‐eastern Australia. FMC was estimated using a process‐based model and 48 years of reconstructed climate data. Canopy effects on microclimate were captured by transferring inputs from climate to microclimate using models parameterised with field observations. To evaluate the relative magnitude of climate and vegetation effects, we calculated the maximum difference in mean annual FMC across annual climate replicates and compared this to FMC differences across reorganising forest sites. Our results show vegetation effects on FMC can exceed those related to expected climate change. Changes to forest structure and composition increased (+15.7%) and decreased (−12.3%) mean annual FMC, with a larger negative effect when forest cover was completely removed (−18.5%). In contrast, the largest climate effect on FMC was −6.6% across 48‐years of data. Our study demonstrates that the magnitude of vegetation effects on FMC can exceed expected climate change effects. Models of future fire activity that do not account for changing vegetation effects on microclimate are omitting a key biophysical control on FMC and therefore may not be accurately predicting future fire activity.

Brown, Tegan P.↗

Engineered synthetic antibodies as probes to quantify the energetic contributions of ligand binding to conformational changes in proteins

Conformational changes in proteins due to ligand binding are ubiquitous in biological processes and are integral to many biological systems. However, it is often challenging to link ligand-induced conformational changes to a resulting biological function because it is difficult to distinguish between the energetic components associated with ligand binding and those due to structural rearrangements. Consequently, here, we used a unique approach exploiting conformation-specific and regio-specific synthetic antibodies (sABs) to probe the energetic contributions of ligand binding to conformation changes. Using maltose-binding protein (MBP) as a model system, customized phage-display selections were performed to generate sABs that stabilize MBP in different conformational states, modulating ligand-binding affinity in competitive, allosteric, or peristeric manners. We determined that the binding of a closed conformation–specific sAB (sAB-11M) to MBP in the absence of maltose is entropically driven, providing new insight into designing antibody-stabilized protein interactions. Crystal structures of sABs bound to MBP, together with biophysical data, delineate the basis of free energy differences between different conformational states and confirm the use of the sABs as energy probes for dissecting enthalpic and entropic contributions to conformational transitions. Our work provides a foundation for investigating the energetic contributions of distinct conformational dynamics to specific biological outputs. We anticipate that our approach also may be valuable for analyzing the energy landscapes of regulatory proteins controlling biological responses to environmental changes.

59 BASIC BIOLOGICAL SCIENCES↗

Hotspots of uncertainty in land-use and land-cover change projections: A global-scale model comparison

Model-based global projections of future land use and land cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socio-economic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g. boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process as well as improving the allocation mechanisms of LULC change models remain important challenges. Furthermore, current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.

54 ENVIRONMENTAL SCIENCES↗

Response to 'Comment on 'Elastic incoherent neutron scattering operating by varying instrumental energy resolution: Principle, simulations, and experiments of the resolution elastic neutron scattering (RENS)'' [Rev. Sci. Instrum. 83, 107101 (2012)]

Recently [S. Magazu et al., Rev. Sci. Instrum. 82, 105115 (2011)] we have proposed a new method for characterizing, by neutron scattering, the dynamical properties of complex material systems, such as, the ones of interest in the biophysical field. This approach called Resolution Elastic Neutron Scattering, in short RENS, is based on the detection of the elastically scattered neutron intensity as a function of the instrumental energy resolution. By experimental, theoretical, and numerical findings, we have pointed out that an inflection point occurs in the elastic intensity when the system relaxation time approaches the instrumental energy resolution time. This approach, differently from quasi-elastic neutron scattering (QENS), gives the chance to evaluate the system relaxation times without using pre-defined models that can be wrong and/or misleading. Here, we reply to a Comment on the above-mentioned main paper in which Wuttke proposes a different approach to evaluate the above-mentioned inflection point; on this regard, it should be noticed that the existence of the inflection point, which is the main topic of our work, is not questioned and that the approach proposed by Wuttke in the Comment, although valid for a class of dynamical processes, is not applicable when different and distinct processes occur simultaneously at different time scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Ensuring thermodynamic consistency with invertible coarse-graining

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insights by isolating the essential degrees of freedom that dictate the thermodynamic properties of a complex, condensed-phase system. The reduced complexity of the model typically leads to lower computational costs and more efficient sampling compared with atomistic models. Designing “good” coarse-grained models is an art. Generally, the mapping from fine-grained configurations to coarse-grained configurations itself is not optimized in any way; instead, the energy function associated with the mapped configurations is. In this work, we explore the consequences of optimizing the coarse-grained representation alongside its potential energy function. We use a graph machine learning framework to embed atomic configurations into a low-dimensional space to produce efficient representations of the original molecular system. Because the representation we obtain is no longer directly interpretable as a real-space representation of the atomic coordinates, we also introduce an inversion process and an associated thermodynamic consistency relation that allows us to rigorously sample fine-grained configurations conditioned on the coarse-grained sampling. We illustrate that this technique is robust, recovering the first two moments of the distribution of several observables in proteins such as chignolin and alanine dipeptide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Driving terrestrial ecosystem models from space

Regional air pollution, land-use conversion, and projected climate change all affect ecosystem processes at large scales. Changes in vegetation cover and growth dynamics can impact the functioning of ecosystems, carbon fluxes, and climate. As a result, there is a need to assess and monitor vegetation structure and function comprehensively at regional to global scales. To provide a test of our present understanding of how ecosystems operate at large scales we can compare model predictions of CO2, O2, and methane exchange with the atmosphere against regional measurements of interannual variation in the atmospheric concentration of these gases. Recent advances in remote sensing of the Earth's surface are beginning to provide methods for estimating important ecosystem variables at large scales. Ecologists attempting to generalize across landscapes have made extensive use of models and remote sensing technology. The success of such ventures is dependent on merging insights and expertise from two distinct fields. Ecologists must provide the understanding of how well models emulate important biological variables and their interactions; experts in remote sensing must provide the biophysical interpretation of complex optical reflectance and radar backscatter data.

Waring, R. H.↗

Selenocyanate derived Se-incorporation into the nitrogenase Fe protein cluster

The nitrogenase Fe protein mediates ATP-dependent electron transfer to the nitrogenase MoFe protein during nitrogen fixation, in addition to catalyzing MoFe protein-independent substrate (CO 2 ) reduction and facilitating MoFe protein metallocluster biosynthesis. The precise role(s) of the Fe protein Fe 4 S 4 cluster in some of these processes remains ill-defined. Herein, we report crystallographic data demonstrating ATP-dependent chalcogenide exchange at the Fe 4 S 4 cluster of the nitrogenase Fe protein when potassium selenocyanate is used as the selenium source, an unexpected result as the Fe protein cluster is not traditionally perceived as a site of substrate binding within nitrogenase. The observed chalcogenide exchange illustrates that this Fe 4 S 4 cluster is capable of core substitution reactions under certain conditions, adding to the Fe protein’s repertoire of unique properties.

59 BASIC BIOLOGICAL SCIENCES↗

Electron microscopy holdings of the Protein Data Bank: the impact of the resolution revolution, new validation tools, and implications for the future

Abstract As a discipline, structural biology has been transformed by the three-dimensional electron microscopy (3DEM) “Resolution Revolution” made possible by convergence of robust cryo-preservation of vitrified biological materials, sample handling systems, and measurement stages operating a liquid nitrogen temperature, improvements in electron optics that preserve phase information at the atomic level, direct electron detectors (DEDs), high-speed computing with graphics processing units, and rapid advances in data acquisition and processing software. 3DEM structure information (atomic coordinates and related metadata) are archived in the open-access Protein Data Bank (PDB), which currently holds more than 11,000 3DEM structures of proteins and nucleic acids, and their complexes with one another and small-molecule ligands (~ 6% of the archive). Underlying experimental data (3DEM density maps and related metadata) are stored in the Electron Microscopy Data Bank (EMDB), which currently holds more than 21,000 3DEM density maps. After describing the history of the PDB and the Worldwide Protein Data Bank (wwPDB) partnership, which jointly manages both the PDB and EMDB archives, this review examines the origins of the resolution revolution and analyzes its impact on structural biology viewed through the lens of PDB holdings. Six areas of focus exemplifying the impact of 3DEM across the biosciences are discussed in detail (icosahedral viruses, ribosomes, integral membrane proteins, SARS-CoV-2 spike proteins, cryogenic electron tomography, and integrative structure determination combining 3DEM with complementary biophysical measurement techniques), followed by a review of 3DEM structure validation by the wwPDB that underscores the importance of community engagement.

Burley, Stephen K. (ORCID:0000000224879713)↗

TDP-43 α-helical structure tunes liquid–liquid phase separation and function

Liquid–liquid phase separation (LLPS) is involved in the formation of membraneless organelles (MLOs) associated with RNA processing. The RNA-binding protein TDP-43 is present in several MLOs, undergoes LLPS, and has been linked to the pathogenesis of amyotrophic lateral sclerosis (ALS). While some ALS-associated mutations in TDP-43 disrupt self-interaction and function, here we show that designed single mutations can enhance TDP-43 assembly and function via modulating helical structure. Using molecular simulation and NMR spectroscopy, we observe large structural changes upon dimerization of TDP-43. Two conserved glycine residues (G335 and G338) are potent inhibitors of helical extension and helix–helix interaction, which are removed in part by variants at these positions, including the ALS-associated G335D. Substitution to helix-enhancing alanine at either of these positions dramatically enhances phase separation in vitro and decreases fluidity of phase-separated TDP-43 reporter compartments in cells. Furthermore, G335A increases TDP-43 splicing function in a minigene assay. Therefore, the TDP-43 helical region serves as a short but uniquely tunable module where application of biophysical principles can precisely control assembly and function in cellular and synthetic biology applications of LLPS.

60 APPLIED LIFE SCIENCES↗

Hydropower Operations in the Colorado River Basin: Institutional Analysis of Opportunities and Constraints

The Colorado River Basin is facing an unprecedented drought. In ongoing drought management efforts, limited attention has been paid to hydropower generation. While some studies do exist on hydropower, they are quantitative in nature and focus on calculating the reduction in megawatts generated at dams in the Basin with declining water availability. These studies simplify the complex process of hydropower generation; water availability is but one factor that impacts hydropower generation. At a more fundamental level, formal institutional arrangements, that is, laws, policies, and rules create the framework within which dams are operated and hydropower is generated. This paper conducts a comparative institutional analysis of water, environment, and energy laws and policies and changes therein to understand the constraints and opportunities faced by hydropower generation in the Colorado River Basin. To tease out the nuances in how institutional arrangements affect dam operations and hydropower generation, the comparative analysis focuses on the two largest and strategically important dams in the Basin: Hoover and Glen Canyon. This paper uses Elinor Ostrom’s Institutional Analysis and Development Framework to analyze laws and policies at three levels: constitutional-choice, collective-choice, and operational levels. Constitutional-choice level laws and policies apply to the entire Basin, whereas collective-choice level and operational level laws and policies are dam specific. Hoover and Glen Canyon Dams face similar biophysical challenges by the virtue of their location in the same river basin. Yet, despite the similarity in the biophysical setting, the analysis in this study finds that the differences in the applicability of constitutional-choice level laws along with the differences in dam specific collective-choice and operational level institutional arrangements produce a distinct set of constraints for hydropower generation at Hoover and Glen Canyon Dams. Even without a drought, water and environmental laws at both the constitutionalchoice and collective-choice levels as well as power contracts constrain hydropower generation and limit the flexibility with which Glen Canyon Dam can be operated. Water and environmental laws also impose specific water release requirements that, at times, require off-peak power generation at Glen Canyon Dam. On the other hand, even with a drought, Hoover Dam faces limited hydropower generation constraints and can operate flexibly. This is because constitutional-choice level laws and dam-specific collective-choice and operational level laws pose limited constraints for flexible daily operations at Hoover. The result is that Hoover Dam can generate hydropower at the same level as it did three decades ago and operate flexibly to provide ancillary services and peaking generation. While water and environmental laws and policies pose constraints for hydropower generation, the analysis in this study further finds that specific historic provisions within energyrelated institutional arrangements and recent changes within power contracts have maintained and even enhanced the value of hydropower to power customers. Historic institutional provisions ensure that hydropower is sold ‘at cost’ making this resource economically competitive with wholesale electricity market rates. Recent power contract modifications have resulted in the amendment of an older resale prohibition clause to expand the flexibility available to power customers in using their capacity and/or energy allocation in RTOs, ISOs, and bulk power markets. This amendment has opened up an opportunity for customers, especially Hoover power customers, to use flexible generation and ancillary services in a market environment. In addition, the extension of power contract duration to the legally maximum term has enhanced the reliability and stability of this resource for customers. In the Colorado River Basin, despite the enduring economic responsibility of power customers—where laws require customers to pay for a large portion of construction and O&M costs whether or not they actually receive hydropower— the persistent threat of a drought-induced water shortage, and constraints imposed by water and environmental laws and policies, power customers continue to invest in this resource as energy-related institutional arrangements and power contract provisions protect the reasons why they value hydropower. Lastly, the analysis in this study finds that the consequences of changes in hydropower generation for energy users, irrigators, and environmental programs in the Basin depend on how specific institutional arrangements tie electricity revenues to irrigation aid and environmental programs, and how the power contracts themselves are set up. Collective-choice level institutional arrangements create a higher level of financial dependency of irrigation aid and environmental programs on electricity revenues in the Upper Basin—the legal subdivision of Colorado River where Glen Canyon Dam is located—compared to the Lower Basin—the legal subdivision of Colorado River where Hoover Dam is located. Therefore, changes in hydropower generation or the way its revenue is collected and used will have far reacting detrimental consequences for the Upper Basin. Likewise, differences in the nature of power contracts for Glen Canyon and Hoover Dams also creates differences in the financial impact incurred by energy users when there is a reduction in hydropower generation. While this study identifies the types of impacts on resource users as a result of specific institutional arrangements, the calculation of extent of impact warrants further attention. Hydropower in the United States is in a unique position today. The strategic importance of this resource for the nation’s electricity sector is rapidly growing even as its contribution to overall electricity generation remains fairly small. This strategic importance, however, is built hydropower’s ability to operate flexibly in order to support the integration of intermittent renewable generating sources and the expansion of electricity markets. As this study shows, such flexibility may not be available at certain plants not due to the lack of water availability but because of institutional constraints. Institutional arrangements may also require dam operators to first consider high priority water uses (such as irrigation or environmental needs), which in turn may limit the ability to generate hydropower when it is most valuable or useful. Engineering and quantitative models, such as production cost models, recognize policy constraints for hydropower operations but often inadequately capture or assume away such constraints in the models. A failure to account for policy constraints in these models runs the risk of inaccurate representation of the operational flexibility and capacity available at specific hydropower plants, which can result in over/underestimation of hydropower’s ability to support the integration of variable renewable resources and address grid reliability concerns. Against this background, this paper and the analysis herein serves as an example of how we can systematically identify institutional constraints (and opportunities) that influence the flexibility in not only generating electricity at specific dams but also using this hydropower once it is generated.

13 HYDRO ENERGY↗

Hybrid biophysical systems for atmospheric CO 2 capture

Negative emissions technologies will be essential for limiting anthropogenic global temperature increases to 2 °C in the later years of the 21st century. Carbonic anhydrase (CA) metalloenzymes catalyze the otherwise slow conversion of CO 2 into carbonic acid (H 2 CO 3 ), suggesting their utility in the rapid hydration and downstream capture of dissolved CO 2 in aqueous media for a variety of CO 2 capture methods, such as thermal and pH swings and mineralization. The possibility of driving the rapid capture of CO 2 by catalyzing the CO 2 hydration bottleneck carries real potential for realizing efficient direct air capture (DAC) and direct ocean capture (DOC) systems. However, scaled application of CAs will be dependent on some way of economically sourcing the enzymes at volumes relevant to scaled DAC/DOC operations. In this perspective, we consider the prospect of catalyzing CO 2 hydration using a CA that is bound to the outer membrane of a cyanobacterial host, engineered constructs we call CyCAMs. Coupling extracellular CA expression to a marine, photosynthetic cyanobacterial host results in a CO 2 hydration catalyst that is continuously refreshed during the bacterial growth cycle, without the need for enzyme purification or harvesting steps. In the case of marine cyanobacteria, sunlight and the solutes native to seawater provide the respective energy, nutrients and sources of inorganic carbon essential to maintaining the bacterial population. We consider the potential impact of CA-mediated CO 2 hydration on a variety of DAC processes, with CO 2 mineralization explored as a primary use case.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Let's Exploit Available Knowledge on Vegetation Fluorescence

The potential to measure vegetation fluorescence from space (1) and to derive from it direct information on the gross primary productivity (GPP) of terrestrial ecosystems is probably the most thrilling development in remote sensing and global ecology of recent years, as it moves Earth observation techniques from the detection of canopy biophysics (e.g., fraction of absorbed radiation) and biochemistry (chlorophyll and nitrogen content) to the realm of ecosystem function. The existence of a functional relationship between fluorescence and photosynthesis has been elucidated over the last decade by several laboratories, notably as part of the preliminary studies of the European Space Agency Fluorescence Explorer (FLEX) Earth Explorer Mission. The empirical observation presented by Guanter et al. (2) of a linear relationship between fluorescence radiance and GPP, however, provides the first experimental confirmation of the feasibility of the approach— already thoroughly tested at leaf level—at the desired scale, despite the confounding effects associated with the satellite detection of such a faint signal. A word of clarification is needed here. The use of fluorescence as a probe of leaf photochemistry has been a staple of plant ecophysiology for decades, rooted in a sound understanding of photosynthetic energy dissipation. However, most past studies had to rely for the interpretation of results on active (pulse-saturated) techniques, making them unsuitable for remote-sensing applications. Over recent years, however, novel process based models have been developed for the interpretation of steady-state, solar-induced fluorescence at the leaf to canopy scale (3). We are therefore in a position to move beyond the mere empirical observation of an association between GPP and fluorescence radiance. In particular, Guanter et al. (2) base their analysis on the assumption of a constant ratio between photosynthetic and fluorescence light use efficiencies (equation 3 in ref. 2).We know, however, that the ratio is not constant, but changes widely in response to light, CO2, stomatal limitations, and extreme stress (4, 5). What’s more, we can make sense of such changes, thus extracting valuable information from the very scatter that is apparent in their data. However, this process will require the availability of more tailored instruments, such as the one planned for the FLEX mission. As already stressed by Guanter et al. (2), the spatial resolution of the Global Ozone Monitoring Experiment-2 sensor (40 × 80 km) makes it difficult to compare meaningfully the fluorescence signal with ground measurements, when only 60–70% of the footprint consists of the desired land-cover type (table S1 in ref. 2), suggesting that this could be largely responsible for the low signals observed in European grasslands. Moreover, the overpass time of the MetOp-A satellite (9:30 AM) implies that fluorescence is generally measured under light-limiting conditions, when fluorescence is only marginally affected by stomatal closure even under stress conditions. This result could explain the seasonal mismatch with daily GPP observed in natural ecosystems in the absence of irrigation (figure 4 in ref. 2). We hope, therefore, that this welcome contribution to this fast-advancing field will help demonstrate the potential of the new technique, and pave the way for more refined studies under both a technological and scientific point of view.

Space↗

Structural basis for the allosteric modulation of rhodopsin by nanobody binding to its extracellular domain

Rhodopsin is a prototypical G protein-coupled receptor (GPCR) critical for vertebrate vision. Research on GPCR signaling states has been facilitated using llama-derived nanobodies (Nbs), some of which bind to the intracellular surface to allosterically modulate the receptor. Extracellularly binding allosteric nanobodies have also been investigated, but the structural basis for their activity has not been resolved to date. Here, we report a library of Nbs that bind to the extracellular surface of rhodopsin and allosterically modulate the thermodynamics of its activation process. Crystal structures of Nb2 in complex with native rhodopsin reveal a mechanism of allosteric modulation involving extracellular loop 2 and native glycans. Nb2 binding suppresses Schiff base deprotonation and hydrolysis and prevents intracellular outward movement of helices five and six – a universal activation event for GPCRs. Nb2 also mitigates protein misfolding in a disease-associated mutant rhodopsin. Our data show the power of nanobodies to modulate the photoactivation of rhodopsin and potentially serve as therapeutic agents for disease-associated rhodopsin misfolding.

59 BASIC BIOLOGICAL SCIENCES↗

Molecular dynamics of combustion reactions in supercritical carbon dioxide. Part 4: boxed MD study of formyl radical dissociation and recombination

Fossil fuel oxy-combustion is an emergent technology where habitual nitrogen diluent is replaced by high pressure (supercritical) carbon dioxide. The supercritical state of CO2 increases the efficiency of the energy conversion and the absence of nitrogen from the reaction mixture reduces pollution by NOx. However, the effects of a supercritical environment on elementary reactions kinetics are not well understood at present. We used boxed molecular dynamics simulations at the QM/MM theory level to predict the kinetics of dissociation/recombination reaction HCO• + [M] ↔ H• + CO + [M], an important elementary step in many combustion processes. A wide range of temperatures (400–1600 K) and pressures (0.3–1000 atm) were studied. Potentials of mean force were plotted and used to predict activation free energies and rate constants. Based on the data obtained, extended Arrhenius equation parameters were fitted and tabulated. The apparent activation energy for the recombination reaction becomes negative above 30 atm. As the temperature increased, the pressure effect on the rate constant decreased. While at 400 K the pressure increase from 0.3 atm to 300 atm accelerated the dissociation reaction by a factor of 250, at 1600 K the same pressure increase accelerated this reaction by a factor of 100.

Biochemistry & Molecular Biology↗

Parameterization-Induced Uncertainties and Impacts of Crop Management Harmonization in a Global Gridded Crop Model Ensemble

Global gridded crop models (GGCMs) combine agronomic or plant growth models with gridded spatial input data to estimate spatially explicit crop yields and agricultural externalities at the global scale. Differences in GGCM outputs arise from the use of different biophysical models, setups, and input data. GGCM ensembles are frequently employed to bracket uncertainties in impact studies without investigating the causes of divergence in outputs. This study explores differences in maize yield estimates from five GGCMs based on the public domain field-scale model Environmental Policy Integrated Climate (EPIC) that participate in the AgMIP Global Gridded Crop Model Intercomparison initiative. Albeit using the same crop model, the GGCMs differ in model version, input data, management assumptions, parameterization, and selection of subroutines affecting crop yield estimates via cultivar distributions, soil attributes, and hydrology among others. The analyses reveal inter-annual yield variability and absolute yield levels in the EPIC-based GGCMs to be highly sensitive to soil parameterization and crop management. All GGCMs show an intermediate performance in reproducing reported yields with a higher skill if a static soil profile is assumed or sufficient plant nutrients are supplied. An in-depth comparison of setup domains for two EPIC-based GGCMs shows that GGCM performance and plant stress responses depend substantially on soil parameters and soil process parameterization, i.e. hydrology and nutrient turnover, indicating that these often neglected domains deserve more scrutiny. For agricultural impact assessments, employing a GGCM ensemble with its widely varying assumptions in setups appears the best solution for coping with uncertainties from lack of comprehensive global data on crop management, cultivar distributions and coefficients for agro-environmental processes. However, the underlying assumptions require systematic specifications to cover representative agricultural systems and environmental conditions. Furthermore, the interlinkage of parameter sensitivity from various domains such as soil parameters, nutrient turnover coefficients, and cultivar specifications highlights that global sensitivity analyses and calibration need to be performed in an integrated manner to avoid bias resulting from disregarded core model domains. Finally, relating evaluations of the EPIC-based GGCMs to a wider ensemble based on individual core models shows that structural differences outweigh in general differences in configurations of GGCMs based on the same model, and that the ensemble mean gains higher skill from the inclusion of structurally different GGCMs. Although the members of the wider ensemble herein do not consider crop-soil-management interactions, their sensitivity to nutrient supply indicates that findings for the EPIC-based sub-ensemble will likely become relevant for other GGCMs with the progressing inclusion of such processes.

Folberth, Christian↗

Substrate binding-induced conformational transitions in the omega-3 fatty acid transporter MFSD2A

Major Facilitator Superfamily Domain containing 2 A (MFSD2A) is a transporter that is highly enriched at the blood-brain and blood-retinal barriers, where it mediates Na + -dependent uptake of ω-3 fatty acids in the form of lysolipids into the brain and eyes, respectively. Despite recent structural insights, it remains unclear how this process is initiated, and driven by Na + . Here, we perform Molecular Dynamics simulations which demonstrate that substrates enter outward facing MFSD2A from the outer leaflet of the membrane via lateral openings between transmembrane helices 5/8 and 2/11. The substrate headgroup enters first and engages in Na + -bridged interactions with a conserved glutamic acid, while the tail is surrounded by hydrophobic residues. This binding mode is consistent with a “trap-and-flip” mechanism and triggers transition to an occluded conformation. Furthermore, using machine learning analysis, we identify key elements that enable these transitions. These results advance our molecular understanding of the MFSD2A transport cycle.

59 BASIC BIOLOGICAL SCIENCES↗

A comprehensive simulation framework for imaging single particles and biomolecules at the European X-ray Free-Electron Laser

The advent of newer, brighter, and more coherent X-ray sources, such as X-ray Free-Electron Lasers (XFELs), represents a tremendous growth in the potential to apply coherent X-rays to determine the structure of materials from the micron-scale down to the Angstrom-scale. There is a significant need for a multi-physics simulation framework to perform source-to-detector simulations for a single particle imaging experiment, including (i) the multidimensional simulation of the X-ray source; (ii) simulation of the wave-optics propagation of the coherent XFEL beams; (iii) atomistic modelling of photon-material interactions; (iv) simulation of the time-dependent diffraction process, including incoherent scattering; (v) assembling noisy and incomplete diffraction intensities into a three-dimensional data set using the Expansion-Maximisation-Compression (EMC) algorithm and (vi) phase retrieval to obtain structural information. Furthermore, we demonstrate the framework by simulating a single-particle experiment for a nitrogenase iron protein using parameters of the SPB/SFX instrument of the European XFEL. This exercise demonstrably yields interpretable consequences for structure determination that are crucial yet currently unavailable for experiment design.

42 ENGINEERING↗