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The Light Microscopy Module A Facility Overview-History and Science

We will share a brief history and provide a science overview of the many accomplishments of the Light Microscopy Module (LMM), a microscope that has been operating in the microgravity environment of the International Space Station (ISS) since 2010. It will be removed in October 2021. It was initially outfitted for the Constrained Vapor Bubble – Wickless Heat Pipe experiment. It was later reconfigured and upgraded many times to support a broad portfolio of Physical science and Biological experiments including: Complex Fluids, Colloids, Macro-Molecular Biophysics, Protein Crystals, and Plant Biology. The LMM has enabled many significant studies and discoveries and has seen its fair share of pleasant surprises. These include recording order arising out of disorder, e.g., systems of colloids that were glasses on Earth crystallizing to form large defect-free crystals, nematic ordering of elliptical colloids, and colloidal-polymer systems crystallizing. The LMM science teams have also seen how to improve product stabilizers once the effects of sedimentation on Earth were removed; they were able to see which tagged genes express in plants when gravity is removed, telling them which genes are essential for growing plants in space; they’ve tested protein crystal growth models; checked models for creating bijel electrodes that turn batteries into fast-charging supercapacitors; tested many forms of colloidal self-assembly: including those using depletion attraction, magnetic fields, and critical Casimir forces; they’ve observed explosive bubble nucleation in a wickless heat pipe, and much more. This work has been supported by the NASA Biological and Physical Sciences (BPS) Division and the ISS Program Office, Johnson Space Center Code OZ and Code OB, the Center for the Advancement of Science in Space (CASIS) / ISS National Lab, EPSCoR, and ISS international partners from ESA – the Netherlands and Italy, CSA, JAXA and S. Korea, and by Space Act Agreements with Procter and Gamble (P&G).

Colloids↗
DOE OSTI2022

Protein drift-diffusion dynamics and phase separation in curved cell membranes and dendritic spines: Hybrid discrete-continuum methods

We develop methods for investigating protein drift-diffusion dynamics in heterogeneous cell membranes and the roles played by geometry, diffusion, chemical kinetics, and phase separation. Our hybrid stochastic numerical methods combine discrete particle descriptions with continuum-level models for tracking the individual protein drift-diffusion dynamics when coupled to continuum fields. We show how our approaches can be used to investigate phenomena motivated by protein kinetics within dendritic spines. The spine geometry is hypothesized to play an important biological role regulating synaptic strength, protein kinetics, and self-assembly of clusters. We perform simulation studies for model spine geometries varying the neck size to investigate how phase-separation and protein organization is influenced by different shapes. We also show how our methods can be used to study the roles of geometry in reaction-diffusion systems including Turing instabilities. Furthermore, our methods provide general approaches for investigating protein kinetics and drift-diffusion dynamics within curved membrane structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Topographic Correction of Optical Remote Sensing Images in Mountainous Areas: A systematic review

Rugged terrain distorts optical remote sensing observations and subsequently impacts land cover classification and biophysical and biochemical parameter retrieval over mountainous areas. Therefore, topographic correction (TC) is a prerequisite for many remote sensing applications. Although various TC methods have been explored over the past four decades to mitigate topographic effects, a systematic and global review of these studies is still lacking. Using a multicomponent bibliometric approach, we extracted bibliometric metadata from 426 publications identified by searching titles, keywords, and abstracts for research on “topographic correction” and “topographic effects” in Scopus and Web of Science (WoS) from 1980 to 2022. Here this systematic review revealed a rapid growth in the number of TC studies since the 1980s, primarily driven by the availability of decametric-resolution remote sensing observations and digital elevation models (DEMs). Most of the research has focused on relatively low-elevation regions, with increasing attention beyond American and European regions, particularly in China. The seasonal distribution of satellite acquisition for TC showed considerable imbalance, mainly concentrated in months with favorable solar illumination conditions (e.g., May to October). Important themes emerged from the keyword analysis, including satellite sensors, DEMs, TC methods, evaluation criteria, and applications.

58 GEOSCIENCES↗
DOE OSTI2024

Ligand-Based Compound Activity Prediction via Few-Shot Learning

Predicting the activities of new compounds against biophysical or phenotypic assays based on the known activities of one or a few existing compounds is a common goal in early stage drug discovery. This problem can be cast as a “few-shot learning” challenge, and prior studies have developed few-shot learning methods to classify compounds as active versus inactive. However, the ability to go beyond classification and rank compounds by expected affinity is more valuable. We describe Few-Shot Compound Activity Prediction (FS-CAP), a novel neural architecture trained on a large bioactivity data set to predict compound activities against an assay outside the training set, based on only the activities of a few known compounds against the same assay. Our model aggregates encodings generated from the known compounds and their activities to capture assay information and uses a separate encoder for the new compound whose activity is to be predicted. The new method provides encouraging results relative to traditional chemical-similarity-based techniques as well as other state-of-the-art few-shot learning methods in tests on a variety of ligand-based drug discovery settings and data sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An atypical BRCT–BRCT interaction with the XRCC1 scaffold protein compacts human DNA Ligase IIIα within a flexible DNA repair complex

The XRCC1–DNA ligase IIIα complex (XL) is critical for DNA single-strand break repair, a key target for PARP inhibitors in cancer cells deficient in homologous recombination. Here, we combined biophysical approaches to gain insights into the shape and conformational flexibility of the XL as well as XRCC1 and DNA ligase IIIα (LigIIIα) alone. Structurally-guided mutational analyses based on the crystal structure of the human BRCT–BRCT heterodimer identified the network of salt bridges that together with the N-terminal extension of the XRCC1 C-terminal BRCT domain constitute the XL molecular interface. Coupling size exclusion chromatography with small angle X-ray scattering and multiangle light scattering (SEC-SAXS–MALS), we determined that the XL is more compact than either XRCC1 or LigIIIα, both of which form transient homodimers and are highly disordered. The reduced disorder and flexibility allowed us to build models of XL particles visualized by negative stain electron microscopy that predict close spatial organization between the LigIIIα catalytic core and both BRCT domains of XRCC1. Together our results identify an atypical BRCT–BRCT interaction as the stable nucleating core of the XL that links the flexible nick sensing and catalytic domains of LigIIIα to other protein partners of the flexible XRCC1 scaffold.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Widespread spring phenology effects on drought recovery of Northern Hemisphere ecosystems

The time required for an ecosystem to recover from severe drought is a key component of ecological resilience. The phenology effects on drought recovery are, however, poorly understood. These effects centre on how phenology variations impact biophysical feedbacks, vegetation growth and, ultimately, recovery itself. Using multiple remotely sensed datasets, we found that more than half of ecosystems in mid- and high-latitudinal Northern Hemisphere failed to recover from extreme droughts within a single growing season. Earlier spring phenology in the drought year slowed drought recovery when extreme droughts occurred in mid-growing season. Delayed spring phenology in the subsequent year slowed drought recovery for all vegetation types (with importance of spring phenology ranging from 46% to 58%). The phenology effects on drought recovery were comparable to or larger than other well-known postdrought climatic factors. These results strongly suggest that the interactions between vegetation phenology and drought must be incorporated into Earth system models to accurately quantify ecosystem resilience.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Surface-mediated spontaneous emulsification of the acylated peptide, semaglutide

Acylated peptides composed of glucagon-like peptide-1 receptor agonists modified with a fatty acid side chain are an important class of therapeutics for type 2 diabetes and obesity but are susceptible to an unusual physical instability in the presence of hydrophobic surfaces, i.e., spontaneous emulsification, also known as ouzo formation in practice. In this work, light scattering, small-angle X-ray scattering, and circular dichroism measurements are used to characterize the physical properties of the semaglutide colloidal phase, including size distribution, shape, secondary structure, internal structure, and internal composition, as a function of solution physico-chemical conditions. The existence and size of the colloids formed are successfully predicted by a classical Rayleigh model, which identifies the parameters controlling their size and formation. Colloid formation is found to be catalyzed by hydrophobic surfaces, and formation rates are modeled as an autocatalytic reaction, enabling the formation of a master curve for various surfaces that elucidates the mechanism. Surfaces differ due to differences in surface wettability, which can be correlated with Hansen solubility parameters. This work provides insights into this unusual colloidal phenomenon and guides the peptide synthesis process and drug product formulation in the pharmaceutical industry.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The genotype-phenotype landscape of an allosteric protein

Allostery is a fundamental biophysical mechanism that underlies cellular sensing, signaling, and metabolism. Yet a quantitative understanding of allosteric genotype-phenotype relationships remains elusive. Here, we report the large-scale measurement of the genotype-phenotype landscape for an allosteric protein: the lac repressor from Escherichia coli , LacI. Using a method that combines long-read and short-read DNA sequencing, we quantitatively measure the dose-response curves for nearly 10 5 variants of the LacI genetic sensor. The resulting data provide a quantitative map of the effect of amino acid substitutions on LacI allostery and reveal systematic sequence-structure-function relationships. We find that in many cases, allosteric phenotypes can be quantitatively predicted with additive or neural-network models, but unpredictable changes also occur. For example, we were surprised to discover a new band-stop phenotype that challenges conventional models of allostery and that emerges from combinations of nearly silent amino acid substitutions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Retrieval of biophysical parameters with AVIRIS and ISM: The Landes Forest, south west France

The first steps of an experiment for investigating the capability of airborne spectrometer data for retrieval of biophysical parameters of vegetation, especially water conditions are presented. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and ISM data were acquired in the frame of the 1991 NASA/JPL and CNES campaigns on the Landes, South west France, a large and flat forest area with mainly maritime pines. In-situ measurements were completed at that time; i.e. reflectance spectra, atmospheric profiles, sampling for further laboratory analyses of elements concentrations (lignin, water, cellulose, nitrogen,...). All information was integrated in an already existing data base (age, LAI, DBH, understory cover,...). A methodology was designed for (1) obtaining geometrically and atmospherically corrected reflectance data, (2) registering all available information, and (3) analyzing these multi-source informations. Our objective is to conduct comparative studies with simulation reflectance models, and to improve these models, especially in the MIR.

Zagolski, F.↗
DOE OSTI2021

Out of the Dark and Into the Light: A New View of Phytochrome Photobodies

Light is a critical environmental stimulus for plants, serving as an energy source via photosynthesis and a signal for developmental programming. Plants perceive light through various light-responsive proteins, termed photoreceptors. Phytochromes are red-light photoreceptors that are highly conserved across kingdoms. In the model plant Arabidopsis thaliana , phytochrome B serves as a light and thermal sensor, mediating physiological processes such as seedling germination and establishment, hypocotyl growth, chlorophyll biogenesis, and flowering. In response to red light, phytochromes convert to a biologically active form, translocating from the cytoplasm into the nucleus and further compartmentalizes into subnuclear compartments termed photobodies. PhyB photobodies regulate phytochrome-mediated signaling and physiological outputs. However, photobody function, composition, and biogenesis remain undefined since their discovery. Based on photobody cellular dynamics and the properties of internal components, photobodies have been suggested to undergo liquid-liquid phase separation, a process by which some membraneless compartments form. Here, we explore photobodies as environmental sensors, examine the role of their protein constituents, and outline the biophysical perspective that photobodies may be undergoing liquid-liquid phase separation. Understanding the molecular, cellular, and biophysical processes that shape how plants perceive light will help in engineering improved sunlight capture and fitness of important crops.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Soil Surface Runoff Scheme for Improving Land-Hydrology and Surface Fluxes in Simple SiB (SSiB)

Evapotranspiration on land is hard to measure and difficult to simulate. On the scale of a GCM grid, there is large subgrid-scale variability of orography, soil moisture, and vegetation. Our hope is to be able to tune the biophysical constants of vegetation and soil parameters to get the most realistic space-averaged diurnal cycle of evaporation and its climatology. Field experiments such as First ISLSCP Field Experiment (FIFE), Boreal Ecosystem-Atmosphere Study (BOREAS), and LBA help a great deal in improving our evapotranspiration schemes. However, these improvements have to be matched with, and coupled to, consistent improvement in land-hydrology; otherwise, the runoff problems will intrinsically reflect on the soil moisture and evapotranspiration errors. Indeed, a realistic runoff simulation also ensures a reasonable evapotranspiration simulation provided the precipitation forcing is reliable. We have been working on all of the above problems to improve the simulated hydrologic cycle. Through our participation in the evaluation and intercomparison of land-models under the behest of Global Soil Wetness Project (GSWP), we identified a few problems with Simple SiB (SSIB; Xue et al., 1991) hydrology in regions of significant snowmelt. Sud and Mocko (1999) show that inclusion of a separate snowpack model, with its own energy budget and fluxes with the atmosphere aloft and soil beneath, helps to ameliorate some of the deficiencies of delayed snowmelt and excessive spring season runoff. Thus, much more realistic timing of melt water generation was simulated with the new snowpack model in the subsequent GSWP re-evaluations using 2 years of ISLSCP Initiative I forcing data for 1987 and 1988. However, we noted an overcorrection of the low meltwater infiltration of SSiB. While the improvement in snowmelt timing was found everywhere, the snowmelt infiltration has became excessive in some regions, e.g., Lena river basin. This leads to much reduced runoff in many basins as compared to observations. We believe this is a consequence of neglect of the influence of subgrid-scale variations in orography that affects the production of surface runoff.

Sud, Y. C.↗
DOE OSTI2020

Where did the tumor start? An inverse solver with sparse localization for tumor growth models

In this work, we present a numerical scheme for solving an inverse problem for parameter estimation in tumor growth models for glioblastomas, a form of aggressive primary brain tumor. The growth model is a reaction–diffusion partial differential equation (PDE) for the tumor concentration. We use a PDE-constrained optimization formulation for the inverse problem. The unknown parameters are the reaction coefficient (proliferation), the diffusion coefficient (infiltration), and the initial condition field for the tumor PDE. Segmentation of magnetic resonance imaging (MRI) scans drive the inverse problem where segmented tumor regions serve as partial observations of the tumor concentration. Like most cases in clinical practice, we use data from a single time snapshot. Moreover, the precise time relative to the initiation of the tumor is unknown, which poses an additional difficulty for inversion. We perform a frozen-coefficient spectral analysis and show that the inverse problem is severely ill-posed. We introduce a biophysically motivated regularization on the structure and magnitude of the tumor initial condition. In particular, we assume that the tumor starts at a few locations (enforced with a sparsity constraint on the initial condition of the tumor) and that the initial condition magnitude in the maximum norm is equal to one. We solve the resulting optimization problem using an inexact quasi-Newton method combined with a compressive sampling algorithm for the sparsity constraint. Our implementation uses PETSc and AccFFT libraries. We conduct numerical experiments on synthetic and clinical images to highlight the improved performance of our solver over a previously existing solver that uses standard two-norm regularization for the calibration parameters. The existing solver is unable to localize the initial condition. Our new solver can localize the initial condition and recover infiltration and proliferation. In clinical datasets (for which the ground truth is unknown), our solver results in qualitatively different solutions compared to the two-norm regularized solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

On the variability of the Bering Sea Cold Pool and implications for the biophysical environment

The Bering Sea experiences a seasonal sea ice cover, which is important to the biophysical environment found there. A pool of cold bottom water (<2°C) is formed on the shelf each winter as a result of cooling and vertical mixing due to brine rejection during the predominately local sea ice growth. The extent and distribution of this Cold Pool (CP) is largely controlled by the winter extent of sea ice in the Bering Sea, which can vary considerably and recently has been much lower than average. The cold bottom water of the CP is important for food security because it delineates the boundary between arctic and subarctic demersal fish species. A northward retreat of the CP will likely be associated with migration of subarctic species toward the Chukchi Sea. We use the fully-coupled Regional Arctic System Model (RASM) to examine variability of the extent and distribution of the CP and its relation to change in the sea ice cover in the Bering Sea during the period 1980–2018. RASM results confirm the direct correlation between the extent of sea ice and the CP and show a smaller CP as a consequence of realistically simulated recent declines of the sea ice cover in the Bering Sea. In fact, the area of the CP was found to be only 31% of the long-term mean in July of 2018. In addition, we also find that a low ice year is followed by a later diatom bloom, while a heavy ice year is followed by an early diatom bloom. Finally, the RASM probabilistic intra-annual forecast capability is reviewed, based on 31-member ensembles for 2019–2021, for its potential use for prediction of the winter sea ice cover and the subsequent summer CP area in the Bering Sea.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Structure of an RNA G-quadruplex from the West Nile virus genome

Potential G-quadruplex sites have been identified in the genomes of DNA and RNA viruses and proposed as regulatory elements. The genus Orthoflavivirus contains arthropod-transmitted, positive-sense, single-stranded RNA viruses that cause significant human disease globally. Computational studies have identified multiple potential G-quadruplex sites that are conserved across members of this genus. Subsequent biophysical studies established that some G-quadruplexes predicted in Zika and tickborne encephalitis virus genomes can form and known quadruplex binders reduced viral yields from cells infected with these viruses. The susceptibility of RNA to degradation and the variability of loop regions have made structure determination challenging. Despite these difficulties, we report a high-resolution structure of the NS5-B quadruplex from the West Nile virus genome. Analysis reveals two stacked tetrads that are further stabilized by a stacked triad and transient noncanonical base pairing. This structure expands the landscape of solved RNA quadruplex structures and demonstrates the diversity and complexity of biological quadruplexes. We anticipate that the availability of this structure will assist in solving further viral RNA quadruplexes and provides a model for a conserved antiviral target in Orthoflavivirus genomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Wildfire Risk Evaluation Framework for Grid Operations and Planning

The United States (US) environmental protection agency's (EPA's) climate change indicators for wildfires show a long-term trend of increased annual wildfire activity, larger wildfire size, and more variable dynamics in wildfire behavior. This has caused more frequent preemptive public safety power shutoff (PSPS) events in the regions with recognized high wildfire risk. These preemptive power shutoffs attempt to prevent the ignition of a wildfire but it nonetheless renders the transmission line non-operational, which often sheds load of downstream communities. As wildfires and PSPS events become more frequent, it is crucial to find the communities most at risk of load shedding. To that end, this paper proposes the wildfire risk evaluation of the system (WiRES) framework, which is a performance-based framework that translates extreme weather-related and PSPS event probabilities into a cumulative probability of a non-operational transmission line. This study also provides a geospatial visualization tool that breaks down the entire western electrical coordinating council (WECC) region into 50 km grid cells which can be used to 1) filter out transmission lines with higher than a threshold outage probability, and 2) graphically discover the affected regions and their biophysical and socioeconomic metrics. %such as the social vulnerability index, population density, gross domestic product, etc. Lastly, an impact assessment study is conducted which connects the results of the proposed framework to python and powerworld-based contingency analysis to highlight the applicability of the framework.

Wildfire, Resilience, Extreme Events, Grid Reslien↗
DOE OSTI2021

OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The catalytic domains of Streptococcus mutans glucosyltransferases: a structural analysis

Streptococcus mutans, found in the human oral cavity, is a significant contributor to the pathogenesis of dental caries. This bacterium expresses three genetically distinct types of glucosyltransferases named GtfB (GTF-I), GtfC (GTF-SI) and GtfD (GTF-S) that play critical roles in the development of dental plaque. The catalytic domains of GtfB, GtfC and GtfD contain conserved active-site residues for the overall enzymatic activity that relate to hydrolytic glycosidic cleavage of sucrose to glucose and fructose, release of fructose and generation of a glycosyl-enzyme intermediate in the reducing end. In a subsequent transglycosylation step, the glucosyl moiety is transferred to the nonreducing end of an acceptor to form a growing glucan polymer chain made up of glucose molecules. It has been proposed that both sucrose breakdown and glucan synthesis occur in the same active site of the catalytic domain, although the active site does not appear to be large enough to accommodate both functions. These three enzymes belong to glycoside hydrolase family 70 (GH70), which shows homology to glycoside hydrolase family 13 (GH13). GtfC synthesizes both soluble and insoluble glucans (α-1,3 and α-1,6 glycosidic linkages), while GtfB and GtfD synthesize only insoluble or soluble glucans, respectively. Here, crystal structures of the catalytic domains of GtfB and GtfD are reported. These structures are compared with previously determined structures of the catalytic domain of GtfC. With this work, apo structures and inhibitor-complex structures with acarbose are now available for the catalytic domains of GtfC and GtfB. The structure of GtfC with maltose allows further identification and comparison of active-site residues. A model of sucrose binding to GtfB is also included. The new structure of the catalytic domain of GtfD affords a structural comparison of the three S. mutans glycosyltransferases. Unfortunately, the catalytic domain of GtfD is not complete since crystallization resulted in the structure of a truncated protein lacking approximately 200 N-terminal residues of domain IV.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Soil Carbon Saturation: What Do We Really Know?

Managing soils to increase organic carbon storage presents a potential opportunity to mitigate and adapt to global change challenges, while providing numerous co-benefits and ecosystem services. However, soils differ widely in their potential for carbon sequestration, and knowledge of biophysical limits to carbon accumulation may aid in informing priority regions. Consequently, there is great interest in assessing whether soils exhibit a maximum capacity for storing organic carbon, particularly within organo–mineral associations given the finite nature of reactive minerals in a soil. While the concept of soil carbon saturation has existed for over 25 years, recent studies have argued for and against its importance. Here, we summarize the conceptual understanding of soil carbon saturation at both micro- and macro-scales, define key terminology, and address common concerns and misconceptions. We review methods used to quantify soil carbon saturation, highlighting the theory and potential caveats of each approach. Critically, we explore the utility of the principles of soil carbon saturation for informing carbon accumulation, vulnerability to loss, and representations in process-based models. We highlight key knowledge gaps and propose next steps for furthering our mechanistic understanding of soil carbon saturation and its implications for soil management.

Environmental sciences↗