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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.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Computational Modeling and Evolutionary Implications of Biochemical Reactions in Bacterial Microcompartments

Bacterial microcompartments (BMCs) are protein-encapsulated compartments found across at least 23 bacterial phyla. BMCs contain a variety of metabolic processes that share the commonality of toxic or volatile intermediates, oxygen-sensitive enzymes and cofactors, or increased substrate concentration for magnified reaction rates. These compartmentalized reactions have been computationally modeled to explore the encapsulated dynamics, ask evolutionary-based questions, and develop a more systematic understanding required for the engineering of novel BMCs. Many crucial aspects of these systems remain unknown or unmeasured, such as substrate permeabilities across the protein shell, feasibility of pH gradients, and transport rates of associated substrates into the cell. This review explores existing BMC models, dominated in the literature by cyanobacterial carboxysomes, and highlights potentially important areas for exploration.

bacterial microcompartments↗
DOE OSTI2021

Injection data analysis using material balance time for CO 2 storage capacity estimation in deep closed saline aquifers

Estimating the ultimate storage capacity of deep saline aquifers is important to address the formation potential to store the envisioned large volumes of CO 2 . Injection data (i.e. injection rate, bottomhole pressure, and cumulative injected volume of CO 2 ) are routinely recorded during storage operations. These data contain valuable information on the subsurface (e.g. the reservoir pore volume and the formation storage capacity) that can be extracted. In this paper, we present a two-step graphical technique to infer the pore volume and the ultimate storage capacity of closed saline aquifers by analyzing the available injection data. First, the pore volume is inferred through adapting the concept of the material balance time. Material balance time is an approximate superposition time function developed to interpret production data from oil and gas wells operating at variable pressure/rate conditions during the boundary-dominated flow period. Using material balance techniques, the ultimate storage capacity is then estimated through linear extrapolation of the average pressure trend to the maximum allowable pressure the formation can withstand. The average pressure is not available in practice, but is can be obtained from the injection data. Two approaches are presented in this study to calculate the average pressure; namely the rigorous and the approximate approaches. Unlike the rigorous approach, the approximate approach does not require a prior knowledge of some reservoir properties (e.g. relative permeability, absolute permeability, formation porosity and thickness) to calculate the average pressure. To investigate its potential and reliability in analyzing CO 2 injection data, the proposed technique is applied to four synthetic cases representing different well operating conditions. Results indicate that the approximate approach consistently overestimates the actual (simulated) storage capacity as compared to the rigorous approach. The agreement - between the inferred and the simulated reservoir pore volume, and between the analytical and numerical estimates of storage capacity - validates the potential application of the technique to CO 2 storage in closed saline aquifers. The technique is further substantiated through application to a field data set utilized from a commercial-scale geological storage (CGS) project. Finally, field data interpretation shows that the proposed technique can be utilized to identify the degree of hydraulic continuity and reservoir compartmentalization within a target formation by interpreting the corresponding pressure and rate responses.

02 PETROLEUM↗
DOE OSTI2025

Bayesian learning with Gaussian processes for low-dimensional representations of time-dependent nonlinear systems

This work presents a data-driven method for learning low-dimensional time-dependent physics-based surrogate models whose predictions are endowed with uncertainty estimates. We use the operator inference approach to model reduction that poses the problem of learning low-dimensional model terms as a regression of state space data and corresponding time derivatives by minimizing the residual of reduced system equations. Standard operator inference models perform well with accurate training data that are dense in time, but producing stable and accurate models when the state data are noisy and/or sparse in time remains a challenge. Another challenge is the lack of uncertainty estimation for the predictions from the operator inference models. Our approach addresses these challenges by incorporating Gaussian process surrogates into the operator inference framework to (1) probabilistically describe uncertainties in the state predictions and (2) procure analytical time derivative estimates with quantified uncertainties. The formulation leads to a generalized least-squares regression and, ultimately, reduced-order models that are described probabilistically with a closed-form expression for the posterior distribution of the operators. The resulting probabilistic surrogate model propagates uncertainties from the observed state data to reduced-order predictions. Furthermore, we demonstrate the method is effective for constructing low-dimensional models of two nonlinear partial differential equations representing a compressible flow and a nonlinear diffusion–reaction process, as well as for estimating the parameters of a low-dimensional system of nonlinear ordinary differential equations representing compartmental models in epidemiology.

Data-driven model reduction↗
DOE OSTI2023

Benzo[$\mathcal{a}$]pyrene toxicokinetics in humans following dietary supplementation with 3,3'-diindolylmethane (DIM) or Brussels sprouts

Utilizing the atto-zeptomole sensitivity of UPLC-accelerator mass spectrometry (UPLC-AMS), we previously demonstrated significant first-pass metabolism following escalating (25–250 ng) oral micro-dosing in humans of [ 14 C]-benzo[a]pyrene ([ 14 C]-BaP). The present study examines the potential for supplementation with Brussels sprouts (BS) or 3,3' -diindolylmethane (DIM) to alter plasma levels of [ 14 C]-BaP and metabolites over a 48-h period following micro-dosing with 50 ng (5.4 nCi) [ 14 C]-BaP. Volunteers were dosed with [ 14 C]-BaP following fourteen days on a cruciferous vegetable restricted diet, or the same diet supplemented for seven days with 50 g of BS or 300 mg of BR-DIM ® prior to dosing. BS or DIM reduced total [ 14 C] recovered from plasma by 56–67% relative to nonintervention. Dietary supplementation with DIM markedly increased T max and reduced C max for [ 14 C]-BaP indicative of slower absorption. Further, both dietary treatments significantly reduced C max values of four downstream BaP metabolites, consistent with delaying BaP absorption. Dietary treatments also appeared to reduce the T 1/2 and the plasma AUC( 0,$\infty$ ) for Unknown Metabolite C, indicating some effect in accelerating clearance of this metabolite. Toxicokinetic constants for other metabolites followed the pattern for [ 14 C]-BaP (metabolite profiles remained relatively consistent) and non-compartmental analysis did not indicate other significant alterations. Significant amounts of metabolites in plasma were at the bay region of [ 14 C]-BaP irrespective of treatment. Although the number of subjects and large interindividual variation are limitations of this study, it represents the first human trial showing dietary intervention altering toxicokinetics of a defined dose of a known human carcinogen.

3,3'-diindolylmethane↗
DOE OSTI2024

Effects of Normal and Lateral Electric Fields on Membrane Mechanical Properties

As a core component of biological and synthetic membranes, lipid bilayers are key to compartmentalizing chemical processes. Bilayer morphology and mechanical properties are heavily influenced by electric fields such as those caused by biological ion concentration gradients. We present atomistic simulations exploring the effects of electric fields applied normally and laterally to lipid bilayers. We find that normal fields decrease membrane tension, while lateral fields increase it. Free energy perturbation calculations indicate the importance of dipole-dipole interactions to these tension changes, especially for lateral fields. We additionally show that membrane area compressibilities can be related to their cohesive energies, allowing us to estimate changes in membrane bending rigidity under applied fields. We find that normal fields decrease bending rigidity, while lateral fields increase it. Furthermore, these results point to the use of directed electric fields to locally control membrane stiffness, thereby modulating associated cellular processes.

Chemistry↗
DOE OSTI2023

Motility of Synthetic Cells from Engineered Lipids

Synthetic cells are artificial systems that resemble natural cells. Significant efforts have been made over the years to construct synthetic protocells that can mimic biological mechanisms and perform various complex processes. These include compartmentalization, metabolism, energy supply, communication, and gene reproduction. Cell motility is also of great importance, as nature uses elegant mechanisms for intracellular trafficking, immune response, and embryogenesis. In this review, we discuss the motility of synthetic cells made from lipid vesicles and relevant molecular mechanisms. Synthetic cell motion may be classified into surface-based or solution-based depending on whether it involves interactions with surfaces or movement in fluids. Collective migration behaviors have also been demonstrated. The swarm motion requires additional mechanisms for intercellular signaling and directional motility that enable communication and coordination among the synthetic vesicles. In addition, intracellular trafficking for molecular transport has been reconstituted in minimal cells with the help of DNA nanotechnology. These efforts demonstrate synthetic cells that can move, detect, respond, and interact. Finally, we envision that new developments in protocell motility will enhance our understanding of biological processes and be instrumental in bioengineering and therapeutic applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A catalog of the diversity and ubiquity of bacterial microcompartments

Abstract Bacterial microcompartments (BMCs) are organelles that segregate segments of metabolic pathways which are incompatible with surrounding metabolism. BMCs consist of a selectively permeable shell, composed of three types of structurally conserved proteins, together with sequestered enzymes that vary among functionally distinct BMCs. Genes encoding shell proteins are typically clustered with those for the encapsulated enzymes. Here, we report that the number of identifiable BMC loci has increased twenty-fold since the last comprehensive census of 2014, and the number of distinct BMC types has doubled. The new BMC types expand the range of compartmentalized catalysis and suggest that there is more BMC biochemistry yet to be discovered. Our comprehensive catalog of BMCs provides a framework for their identification, correlation with bacterial niche adaptation, experimental characterization, and development of BMC-based nanoarchitectures for biomedical and bioengineering applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A multi-step nucleation process determines the kinetics of prion-like domain phase separation

Compartmentalization by liquid-liquid phase separation (LLPS) has emerged as a ubiquitous mechanism underlying the organization of biomolecules in space and time. Here, we combine rapid-mixing time-resolved small-angle X-ray scattering (SAXS) approaches to characterize the assembly kinetics of a prototypical prion-like domain with equilibrium techniques that characterize its phase boundaries and the size distribution of clusters prior to phase separation. We find two kinetic regimes on the micro- to millisecond timescale that are distinguished by the size distribution of clusters. At the nanoscale, small complexes are formed with low affinity. After initial unfavorable complex assembly, additional monomers are added with higher affinity. At the mesoscale, assembly resembles classical homogeneous nucleation. Careful multi-pronged characterization is required for the understanding of condensate assembly mechanisms and will promote understanding of how the kinetics of biological phase separation is encoded in biomolecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Reconfigurable droplet networks

Droplet networks stabilized by lipid interfacial bilayers or colloidal particles have been extensively investigated in recent years and are of great interest for compartmentalized reactions and biological functions. However, current design strategies are disadvantaged by complex preparations and limited droplet size. Here, by using the assembly and jamming of cucurbit[8]uril surfactants at the oil-water interface, we show a novel means of preparing droplet networks that are multi-responsive, reconfigurable, and internally connected over macroscopic distances. Openings between the droplets enable the exchange of matter, affording a platform for chemical reactions and material synthesis. Our work requires only a manual compression to construct complex patterns of droplet networks, underscoring the simplicity of this strategy and the range of potential applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Task-oriented machine learning surrogates for tipping points of agent-based models

We present a machine learning framework bridging manifold learning, neural networks, Gaussian processes, and Equation-Free multiscale approach, for the construction of different types of effective reduced order models from detailed agent-based simulators and the systematic multiscale numerical analysis of their emergent dynamics. The specific tasks of interest here include the detection of tipping points, and the uncertainty quantification of rare events near them. Our illustrative examples are an event-driven, stochastic financial market model describing the mimetic behavior of traders, and a compartmental stochastic epidemic model on an Erdös-Rényi network. We contrast the pros and cons of the different types of surrogate models and the effort involved in learning them. Importantly, the proposed framework reveals that, around the tipping points, the emergent dynamics of both benchmark examples can be effectively described by a one-dimensional stochastic differential equation, thus revealing the intrinsic dimensionality of the normal form of the specific type of the tipping point. This allows a significant reduction in the computational cost of the tasks of interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Dense, continuous membrane labeling and expansion microscopy visualization of ultrastructure in tissues

Abstract Lipid membranes are key to the nanoscale compartmentalization of biological systems, but fluorescent visualization of them in intact tissues, with nanoscale precision, is challenging to do with high labeling density. Here, we report ultrastructural membrane expansion microscopy (umExM), which combines an innovative membrane label and optimized expansion microscopy protocol, to support dense labeling of membranes in tissues for nanoscale visualization. We validate the high signal-to-background ratio, and uniformity and continuity, of umExM membrane labeling in brain slices, which supports the imaging of membranes and proteins at a resolution of ~60 nm on a confocal microscope. We demonstrate the utility of umExM for the segmentation and tracing of neuronal processes, such as axons, in mouse brain tissue. Combining umExM with optical fluctuation imaging, or iterating the expansion process, yields ~35 nm resolution imaging, pointing towards the potential for electron microscopy resolution visualization of brain membranes on ordinary light microscopes.

Science & Technology - Other Topics↗
DOE OSTI2025

Design of diverse, functional mitochondrial targeting sequences across eukaryotic organisms using variational autoencoder

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Decompartmentalization of the yeast mitochondrial metabolism to improve chemical production in Issatchenkia orientalis

Microbial production of chemicals may suffer from inadequate cofactor provision, a challenge further exacerbated in yeasts due to compartmentalized cofactor metabolism. Here, we perform cofactor engineering through the decompartmentalization of mitochondrial metabolism to improve succinic acid (SA) production in Issatchenkia orientalis. We localize the reducing equivalents of mitochondrial NADH to the cytosol through cytosolic expression of its pyruvate dehydrogenase (PDH) complex and couple a reductive tricarboxylic acid pathway with a glyoxylate shunt, partially bypassing an NADH-dependent malate dehydrogenase to conserve NADH. Cytosolic SA production reaches a titer of 104 g/L and a yield of 0.85 g/g glucose, surpassing the yield of 0.66 g/g glucose constrained by cytosolic NADH availability. Additionally, expressing cytosolic PDH, we expand our I. orientalis platform to enhance acetyl-CoA-derived citramalic acid and triacetic acid lactone production by 1.22- and 4.35-fold, respectively. Our work establishes I. orientalis as a versatile platform to produce markedly reduced and acetyl-CoA-derived chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Complete biosynthesis of QS-21 in engineered yeast

QS-21 is a potent vaccine adjuvant and remains the only saponin-based adjuvant that has been clinically approved for use in humans. However, owing to the complex structure of QS-21, its availability is limited. Today, the supply depends on laborious extraction from the Chilean soapbark tree or on low-yielding total chemical synthesis. Here we demonstrate the complete biosynthesis of QS-21 and its precursors, as well as structural derivatives, in engineered yeast strains. The successful biosynthesis in yeast requires fine-tuning of the host’s native pathway fluxes, as well as the functional and balanced expression of 38 heterologous enzymes. The required biosynthetic pathway spans seven enzyme families—a terpene synthase, P450s, nucleotide sugar synthases, glycosyltransferases, a coenzyme A ligase, acyl transferases and polyketide synthases—from six organisms, and mimics in yeast the subcellular compartmentalization of plants from the endoplasmic reticulum membrane to the cytosol. Finally, by taking advantage of the promiscuity of certain pathway enzymes, we produced structural analogues of QS-21 using this biosynthetic platform. This microbial production scheme will allow for the future establishment of a structure–activity relationship, and will thus enable the rational design of potent vaccine adjuvants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Precise transcript targeting by CRISPR-Csm complexes

Robust and precise transcript targeting in mammalian cells remains a difficult challenge using existing approaches due to inefficiency, imprecision and subcellular compartmentalization. Here we show that the clustered regularly interspaced short palindromic repeats (CRISPR)-Csm complex, a multiprotein effector from type III CRISPR immune systems in prokaryotes, provides surgical RNA ablation of both nuclear and cytoplasmic transcripts. As part of the most widely occurring CRISPR adaptive immune pathway, CRISPR-Csm uses a programmable RNA-guided mechanism to find and degrade target RNA molecules without inducing indiscriminate trans-cleavage of cellular RNAs, giving it an important advantage over the CRISPR-Cas13 family of enzymes. Using single-vector delivery of the Streptococcus thermophilus Csm complex, we observe high-efficiency RNA knockdown (90–99%) and minimal off-target effects in human cells, outperforming existing technologies including short hairpin RNA- and Cas13-mediated knockdown. We also find that catalytically inactivated Csm achieves specific and durable RNA binding, a property we harness for live-cell RNA imaging. These results establish the feasibility and efficacy of multiprotein CRISPR-Cas effector complexes as RNA-targeting tools in eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The encapsulin from Thermotoga maritima is a flavoprotein with a symmetry matched ferritin-like cargo protein

Abstract Bacterial nanocompartments, also known as encapsulins, are an emerging class of protein-based ‘organelles’ found in bacteria and archaea. Encapsulins are virus-like icosahedral particles comprising a ~ 25–50 nm shell surrounding a specific cargo enzyme. Compartmentalization is thought to create a unique chemical environment to facilitate catalysis and isolate toxic intermediates. Many questions regarding nanocompartment structure–function remain unanswered, including how shell symmetry dictates cargo loading and to what extent the shell facilitates enzymatic activity. Here, we explore these questions using the model Thermotoga maritima nanocompartment known to encapsulate a redox-active ferritin-like protein. Biochemical analysis revealed the encapsulin shell to possess a flavin binding site located at the interface between capsomere subunits, suggesting the shell may play a direct and active role in the function of the encapsulated cargo. Furthermore, we used cryo-EM to show that cargo proteins use a form of symmetry-matching to facilitate encapsulation and define stoichiometry. In the case of the Thermotoga maritima encapsulin, the decameric cargo protein with fivefold symmetry preferentially binds to the pentameric-axis of the icosahedral shell. Taken together, these observations suggest the shell is not simply a passive barrier—it also plays a significant role in the structure and function of the cargo enzyme.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Multi-omics analysis reveals the dynamic interplay between Vero host chromatin structure and function during vaccinia virus infection

The genome folds into complex configurations and structures thought to profoundly impact its function. The intricacies of this dynamic structure-function relationship are not well understood particularly in the context of viral infection. To unravel this interplay, here we provide a comprehensive investigation of simultaneous host chromatin structural (via Hi-C and ATAC-seq) and functional changes (via RNA-seq) in response to vaccinia virus infection. Over time, infection significantly impacts global and local chromatin structure by increasing long-range intra-chromosomal interactions and B compartmentalization and by decreasing chromatin accessibility and inter-chromosomal interactions. Local accessibility changes are independent of broad-scale chromatin compartment exchange (~12% of the genome), underscoring potential independent mechanisms for global and local chromatin reorganization. While infection structurally condenses the host genome, there is nearly equal bidirectional differential gene expression. Despite global weakening of intra-TAD interactions, functional changes including downregulated immunity genes are associated with alterations in local accessibility and loop domain restructuring. Therefore, chromatin accessibility and local structure profiling provide impactful predictions for host responses and may improve development of efficacious anti-viral counter measures including the optimization of vaccine design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Insights from designing an artificial cascade catalysis system using principles from substrate channeling in enzymes

Generalizing the key requirements of highly-selective, multi-step chemical conversions involving spatially separated reaction centers remains one of the grand challenges of chemistry. Much work towards this effort has focused on decomposing multi-step conversions into their constituent reactions, whose intermediates are successively upgraded in a chemical cascade via diffusion from center to center. This approach for synthesizing more complex molecules takes its cues from biochemical networks, where near-unit conversion of even complex carbohydrates is achieved by upgrading chemical precursors via enzymatic cascades. In this computational study we examine a simple cascade involving coupled Ag and Cu catalysts that sequentially converts CO2 to CO and then CO2 and CO to reduced products, generically named CO2Product and COProduct. The system architecture is inspired by the phenomenon of biological substrate channeling, and components are examined to evaluate their effects on conversion efficiency in the cascade. Aside from a substrate channel linking two reaction centers, we find efficient cascades must also incorporate directional substrate diffusion, compartmentalization of the reaction centers, and proper timing of substrate arrival at the active center. We make explicit linkages between these requirements and chemical conversion in known biological systems, revealing additional control elements that could be incorporated.

CO 2 reduction↗