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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

The effects of photosynthetic rate on respiration in light, starch/sucrose partitioning, and other metabolic fluxes within photosynthesis

In the future, plants may encounter increased light and elevated CO 2 levels. How consequent alterations in photosynthetic rates will impact fluxes in photosynthetic carbon metabolism remains uncertain. Respiration in light ( R L ) is pivotal in plant carbon balance and a key parameter in photosynthesis models. Understanding the dynamics of photosynthetic metabolism and R L under varying environmental conditions is essential for optimizing plant growth and agricultural productivity. However, measuring R L under high light and high CO 2 (HLHC) conditions poses challenges using traditional gas exchange methods. In this study, we employed isotopically nonstationary metabolic flux analysis (INST-MFA) to estimate RL and investigate photosynthetic carbon flux, unveiling nuanced adjustments in Camelina sativa under HLHC. Despite numerous flux alterations in HLHC, RL remained stable. HLHC affects several factors influencing RL, such as starch and sucrose partitioning, v o /v c ratio, triose phosphate partitioning, and hexose kinase activity. Analysis of A/C i curve operational points reveals that HLHC’s major changes primarily stem from CO 2 suppressing photorespiration. Integration of these fluxes into a simplified model predicts changes in CBC labeling under HLHC. This study extends our prior discovery that incomplete CBC labeling is due to unlabeled carbon reimported during R L , offering insights into manipulating labeling through adjustments in photosynthetic rates.

Elevated CO2↗

Federated User Account Management

Abstract. BNL SDCC (Scientific Data and Computing Center) recently deployed a centralized identity management solution to support Single Sign On (SSO) authentication across multiple IT systems. The system supports federated login access via CILogon and InCommon and multi-factor authentication (MFA) to meet security standards for various application and services such as Jupyterhub / Invenio that are provided to the SDCC user community. CoManage (Cloud) and FreeIPA / Keycloak (local) are utilized to provided complex authorization for authenticated users. This talk will focus on technical overviews and strategies to tackle the challenges/obstacles in our facility.

42 ENGINEERING↗

Accurate flux predictions using tissue-specific gene expression in plant metabolic modeling

The accurate prediction of complex phenotypes such as metabolic fluxes in living systems is a grand challenge for systems biology and central to efficiently identifying biotechnological interventions that can address pressing industrial needs. The application of gene expression data to improve the accuracy of metabolic flux predictions using mechanistic modeling methods such as flux balance analysis (FBA) has not been previously demonstrated in multi-tissue systems, despite their biotechnological importance. We hypothesized that a method for generating metabolic flux predictions informed by relative expression levels between tissues would improve prediction accuracy. Relative gene expression levels derived from multiple transcriptomic and proteomic datasets were integrated into FBA predictions of a multi-tissue, diel model of Arabidopsis thaliana’s central metabolism. This integration dramatically improved the agreement of flux predictions with experimentally based flux maps from 13 C metabolic flux analysis compared with a standard parsimonious FBA approach. Disagreement between FBA predictions and MFA flux maps was measured using weighted averaged percent error values, and for parsimonious FBA this was 169%–180% for high light conditions and 94%–103% for low light conditions, depending on the gene expression dataset used. This fell to 10%-13% and 9%-11% upon incorporating expression data into the modeling process, which also substantially altered the predicted carbon and energy economy of the plant.

59 BASIC BIOLOGICAL SCIENCES↗

BayFlux v1.0

This is an open source software library for performing Bayesian genome scale 13C Metabolic Flux Analysis (Bayesian 13C MFA). This is a new type of metabolic modeling that quantifies flux in a probabilistic manner at the genome scale.

Garcia Martin, Hector↗

A Method to Constrain Genome-Scale Models with 13 C Labeling Data

Current limitations in quantitatively predicting biological behavior hinder our efforts to engineer biological systems to produce biofuels and other desired chemicals. Here, we present a new method for calculating metabolic fluxes, key targets in metabolic engineering, that incorporates data from 13C labeling experiments and genome-scale models. The data from 13 C labeling experiments provide strong flux constraints that eliminate the need to assume an evolutionary optimization principle such as the growth rate optimization assumption used in Flux Balance Analysis (FBA). This effective constraining is achieved by making the simple but biologically relevant assumption that flux flows from core to peripheral metabolism and does not flow back. The new method is significantly more robust than FBA with respect to errors in genome-scale model reconstruction. Furthermore, it can provide a comprehensive picture of metabolite balancing and predictions for unmeasured extracellular fluxes as constrained by 13 C labeling data. A comparison shows that the results of this new method are similar to those found through 13 C Metabolic Flux Analysis ( 13 C MFA) for central carbon metabolism but, additionally, it provides flux estimates for peripheral metabolism. The extra validation gained by matching 48 relative labeling measurements is used to identify where and why several existing COnstraint Based Reconstruction and Analysis (COBRA) flux prediction algorithms fail. We demonstrate how to use this knowledge to refine these methods and improve their predictive capabilities. This method provides a reliable base upon which to improve the design of biological systems.

59 BASIC BIOLOGICAL SCIENCES↗

Development of a Knowledgebase (MetRxn) of Metabolites, Reactions and Atom Mappings to Accelerate Discovery and Redesign

With advances in DNA sequencing and genome annotation techniques, the breadth of metabolic knowledge across all kingdoms of life is increasing. The construction of genome-scale models (GSMs) facilitates this distillation of knowledge by systematically accounting for reaction stoichiometry and directionality, gene to protein to reaction relationships, reaction localization among cellular organelles, metabolite transport costs and routes, transcriptional regulation, and biomass composition. Genome-scale reconstructions available now span across all kingdoms of life, from microbes to whole-plant models, and have become indispensable for driving informed metabolic designs and interventions. A key barrier to the pace of this development is our inability to utilize metabolite/reaction information from databases such as BRENDA [1], KEGG [2], MetaCyc [3], etc. due to incompatibilities of representation, duplications, and errors. Duplicate entries constitute a major impediment, where the same metabolite is found with multiple names across databases and models, which significantly slows downs the collating of information from multiple data sources. This can also lead to serious modeling errors such as charge/mass imbalances [4,5] which can thwart model predictive abilities such as identifying synthetic lethal gene pairs and quantifying metabolic flows. Hence, we created the MetRxn database [6] that takes the next step in integrating data from multiple sources and formats to automatically create a standardized knowledgebase. We subsequently deployed this resource to bring about new paradigms in genome-scale metabolic model reconstruction, metabolic flux elucidation through MFA, modeling of microbial communities, and pathway prospecting. This research has enabled the PI’s group to continue building upon research milestones and reach new ones (see list of MetRxn-related publications below).

59 BASIC BIOLOGICAL SCIENCES↗

The Design and Evaluation of Zero Trust Architecture for Electric Vehicle Charging Infrastructure: EVs @ Scale Series on EV Charging Station Cybersecurity

Implementing a zero trust architecture can significantly bolster the security of electric vehicle (EV) charging infrastructure. EV charging infrastructure includes numerous networked interfaces, each of which can present potential vulnerabilities. When these vulnerabilities are exploited, they can compromise the entire system, leading to severe operational and security risks. Zero trust is a security model that operates on the principle of "never trust, always verify," which helps manage the attack surface and limit the scope of any potential compromises. Fundamentally, this model ensures that no entity, whether inside or outside the network, is trusted by default. The design principles of zero trust include continuous verification, strict deny-by-default access controls, and micro-segmentation. Continuous verification ensures that every request is thoroughly checked, regardless of its origin. Strict access controls enforce the principle of least privilege, allowing users and devices only the minimum necessary access to perform their functions. Micro-segmentation involves dividing the network into smaller, isolated segments to prevent lateral movement in case of a breach. In the context of EV charging infrastructure, zero trust can be implemented through various strategies. For example, multi-factor authentication (MFA) can be required for engineers to access the management interfaces and control systems of charging stations. Real-time monitoring and analysis of network traffic can help detect and respond to anomalies. Systems that do not need to communicate with each other can be micro-segmented to enhance security. All communications should adhere to predefined policies to be permitted. Additionally, encrypting communications can protect sensitive information exchanged between chargers and management systems. This paper presents a zero trust architecture specifically designed for EV charging infrastructure. Implementing zero trust not only mitigates risks but also builds a resilient infrastructure capable of withstanding and quickly recovering from cyber threats. The architecture addresses six defined security objectives. A comprehensive test plan is developed to assess the architecture against these objectives, and the results of the evaluation are reported. This approach is essential for maintaining the reliability and integrity of EV charging services in an increasingly interconnected and vulnerable digital landscape. This is the first in a planned series of papers exploring the implementation of zero trust in EV charging infrastructure. Each paper will delve into different aspects and applications of zero trust, highlighting how various work processes and requirements can lead to distinct architectural designs. These architectures will be tailored to address specific security challenges and operational needs within the EV charging ecosystem, ensuring a robust and adaptable security framework.

33 ADVANCED PROPULSION SYSTEMS↗

Transcript abundance on its own cannot be used to infer fluxes in central metabolism

An attempt has been made to define the extent to which metabolic flux in central plant metabolism is reflected by changes in the transcriptome and metabolome, based on an analysis of in vitro cultured immature embryos of two oilseed rape (Brassica napus) accessions which contrast for seed lipid accumulation. Metabolic flux analysis (MFA) was used to constrain a flux balance metabolic model which included 671 biochemical and transport reactions within the central metabolism. This highly confident flux information was eventually used for comparative analysis of flux vs. transcript (metabolite). Metabolite profiling succeeded in identifying 79 intermediates within the central metabolism, some of which differed quantitatively between the two accessions and displayed a significant shift corresponding to flux. An RNA-Seq based transcriptome analysis revealed a large number of genes which were differentially transcribed in the two accessions, including some enzymes/proteins active in major metabolic pathways. With a few exceptions, differential activity in the major pathways (glycolysis, TCA cycle, amino acid, and fatty acid synthesis) was not reflected in contrasting abundances of the relevant transcripts. The conclusion was that transcript abundance on its own cannot be used to infer metabolic activity/fluxes in central plant metabolism. Lastly, this limitation needs to be borne in mind in evaluating transcriptome data and designing metabolic engineering experiments.

13C-metabolic flux analysis↗

Spacelab system analysis: The modified free access protocol: An access protocol for communication systems with periodic and Poisson traffic

The protocol definition and terminal hardware for the modified free access protocol, a communications protocol similar to Ethernet, are developed. A MFA protocol simulator and a CSMA/CD math model are also developed. The protocol is tailored to communication systems where the total traffic may be divided into scheduled traffic and Poisson traffic. The scheduled traffic should occur on a periodic basis but may occur after a given event such as a request for data from a large number of stations. The Poisson traffic will include alarms and other random traffic. The purpose of the protocol is to guarantee that scheduled packets will be delivered without collision. This is required in many control and data collection systems. The protocol uses standard Ethernet hardware and software requiring minimum modifications to an existing system. The modification to the protocol only affects the Ethernet transmission privileges and does not effect the Ethernet receiver.

Ingels, Frank↗

Space Magnets Attracting Interest on Earth: Applications of Physical and Biological Techniques In the Study of Gravisensing and Response System of Plants

The BioTube/Magnetic Field Apparatus (MFA) research is designed to provide insight into the organization and operation of the gravity sensing systems of plants and other small organisms. This experiment on STS-107 uses magnetic fields to manipulate sensory cells in plant roots, thus using magnetic fields as a tool to study gravity-related phenomena. The experiment will be located in the SPACEHAB module and is about the size of a household microwave oven. The goal of the experiment is to improve our understanding of the basic phenomenon of how plants respond to gravity. The BioTube/MFA experiment specifically examines how gravitational forces serve as a directional signal for growth in the low-gravity environment of space. As with all basic research, this study will contribute to an improved understanding of how plants grow and will have important implications for improving plant growth and productivity on Earth. In BioTube/MFA, magnetic fields will be used to determine whether the distribution of subcellular starch grains, called amyloplasts, within plant cells predicts the direction in which roots will grow and curve in microgravity.

Karl H Hasenstein↗

Integrating Interactive Jupyter Notebooks at the BNL SDCC

At the SDCC we are deploying a Jupyterhub infrastructure to enable scientists from multiple disciplines to access our diverse compute and storage resources. One major design goal was to avoid rolling out yet another compute backend, but rather to leverage our pre-existing resources via our batch systems (HTCondor and Slurm). Challenges faced include creating a frontend that allows users to choose what HPC resources they have access to as well as selecting containers or environments, delegating authentication to a MFA-enabled proxy, and automating deployment of multiple hub instances. This paper covers the design and features of our Jupyterhub service.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

13 C-Fingerprinting and Metabolic Flux Analysis of Bacterial Metabolisms

13 C-assisted metabolism analysis provides rigorous calculations of the intracellular reaction rates (i.e., fluxes) within the central metabolism of microbial hosts. This mapping of the intracellular network within microbes has proven to be essential for understanding the cell physiology. The approach is also a key to identifying central metabolic nodes, probing the rigidity of a metabolic network, revealing cofactor balances, and delineating hidden pathways. Here we present the methodology of using stable isotopic carbon substrates for both qualitative ( 13 C-fingerprinting of functional pathways) and quantitative (Metabolic Flux Analysis) metabolism studies on bacterial species. In this methodology, we include step-by-step instructions to use the open source WUflux software for the steady-state flux calculations based on labeling information of amino acids or free metabolites.

13C-MFA, Metabolites, Flux ratio, Metabolism, Prot↗

Microfibril orientation and compositional heterogeneity in fiber and vessel cell walls of poplar xylem studied by AFM-IR and SFG spectroscopy

Understanding the structural organization of cellulose microfibrils (CMFs) within individual plant cell walls is essential for connecting cell wall architecture to its mechanical and physiological functions. However, due to the complex hierarchical structure and nanoscale heterogeneity of cell walls, it remains technically challenging to resolve detailed compositional and orientational information at subcellular levels of individual cell walls. This study investigates the internal 3D structure, chemical composition, and sublayer organization of fiber and vessel cell walls in the xylem tissue of a two-year-old field-grown hybrid poplar tree (Populus alba × P. glandulosa) using photothermal atomic force microscopy coupled with infrared spectroscopy (AFM-IR) and sum frequency generation (SFG) hyperspectral microscopy. AFM-IR provided nanoscale chemical imaging, revealing localized compositional heterogeneity, including variations between adjacent cell walls and transitional layers beyond the traditional S1, S2, and S3 sublayers. SFG microscopy revealed that CMFs in fiber walls are highly aligned along the stem axis, consistent with their role in mechanical support, while vessel cell walls exhibited slightly tilted CMFs, reflecting their function in hydraulic transport. Together, these results offer new insights into cell-type-specific CMF organization and compositional gradients in hybrid poplar xylem. These findings highlight the structural and chemical complexity of secondary cell walls in woody plants and demonstrate the value of AFM-IR and SFG spectroscopy in elucidating plant cell wall architecture.

60 APPLIED LIFE SCIENCES↗

Decoding how a soil bacterium extracts building blocks and metabolic energy from ligninolysis provides road map for lignin valorization

Significance Lignin is the only renewable and abundant polymer on the earth with aromatic units as its building blocks; however, it remains as an untapped resource. The current approach to making the biofuel industry cost competitive with the petroleum industry is to derive more value from the lignin. In this study we combined the unique approaches of both chemical engineering and biology to gain a deeper understanding of the metabolism of a soil bacterium, Sphingobium sp. SYK-6, that enables it to survive on lignin-derived monomers and oligomers. Understanding the central metabolism of SYK-6 will enable researchers to redesign the metabolic pathways of Sphingobium sp. SYK-6 more effectively to provide a renewable route for the production of products currently sourced from petrochemicals.

09 BIOMASS FUELS↗

Quantitative Multilevel Analysis of Central Metabolism in Developing Oilseeds of Oilseed Rape During In Vitro Culture

Seeds provide the basis for many food, feed, and fuel products. Continued increases in seed yield, composition, and quality require an improved understanding of how the developing seed converts carbon and nitrogen supplies into storage. Current knowledge of this process is often based on the premise that transcriptional regulation directly translates via enzyme concentration into flux. In an attempt to highlight metabolic control, we explore genotypic differences in carbon partitioning for in vitro cultured developing embryos of oilseed rape (Brassica napus). We determined biomass composition as well as 79 net fluxes, the levels of 77 metabolites, and 26 enzyme activities with specific focus on central metabolism in nine selected germplasm accessions. We observed a tradeoff between the biomass component fractions of lipid and starch. With increasing lipid content over the spectrum of genotypes, plastidic fatty acid synthesis and glycolytic flux increased concomitantly, while glycolytic intermediates decreased. The lipid/starch tradeoff was not reflected at the proteome level, pointing to the significance of (posttranslational) metabolic control. Enzyme activity/flux and metabolite/flux correlations suggest that plastidic pyruvate kinase exerts flux control and that the lipid/starch tradeoff is most likely mediated by allosteric feedback regulation of phosphofructokinase and ADP-glucose pyrophosphorylase. Also, quantitative data were used to calculate in vivo mass action ratios, reaction equilibria, and metabolite turnover times. Compounds like cyclic 3',5'-AMP and sucrose-6-phosphate were identified to potentially be involved in so far unknown mechanisms of metabolic control. This study provides a rich source of quantitative data for those studying central metabolism..

13C-MFA flux analysis↗

In Vivo Thermodynamic Analysis of Glycolysis in Clostridium thermocellum and Thermoanaerobacterium saccharolyticum Using 13 C and 2 H Tracers

Clostridium thermocellum and Thermoanaerobacterium saccharolyticum are thermophilic anaerobic bacteria with complementary metabolic capabilities that utilize distinct glycolytic pathways for the conversion of cellulosic sugars to biofuels. We integrated quantitative metabolomics with 2 H and 13 C metabolic flux analysis to investigate the in vivo reversibility and thermodynamics of the central metabolic networks of these two microbes. We found that the glycolytic pathway in C. thermocellum operates remarkably close to thermodynamic equilibrium, with an overall drop in Gibbs free energy 5-fold lower than that of T. saccharolyticum or anaerobically grown Escherichia coli . The limited thermodynamic driving force of glycolysis in C. thermocellum could be attributed in large part to the small free energy of the phosphofructokinase reaction producing fructose bisphosphate. The ethanol fermentation pathway was also substantially more reversible in C. thermocellummthan in T. saccharolyticum. These observations help explain the comparatively low ethanol titers of C. thermocellum and suggest engineering interventions that can be used to increase its ethanol productivity and glycolytic rate. In addition to thermodynamic analysis, we used our isotope tracer data to reconstruct the T. saccharolyticum central metabolic network, revealing exclusive use of the Embden-Meyerhof-Parnas (EMP) pathway for glycolysis, a bifurcated tricarboxylic acid (TCA) cycle, and a sedoheptulose bisphosphate bypass active within the pentose phosphate pathway. Thermodynamics constitutes a key determinant of flux and enzyme efficiency in metabolic networks. Here, we provide new insights into the divergent thermodynamics of the glycolytic pathways of C. thermocellum and T. saccharolyticum, two industrially relevant thermophilic bacteria whose metabolism still is not well understood. We report that while the glycolytic pathway in T. saccharolyticum is as thermodynamically favorable as that found in model organisms, such as E. coli or Saccharomyces cerevisiae , the glycolytic pathway of C. thermocellum operates near equilibrium. The use of a near-equilibrium glycolytic pathway, with potentially increased ATP yield, by this cellulolytic microbe may represent an evolutionary adaptation to growth on cellulose, but it has the drawback of being highly susceptible to product feedback inhibition. The results of this study will facilitate future engineering of high-performance strains capable of transforming cellulosic biomass to biofuels at high yields and titers.

59 BASIC BIOLOGICAL SCIENCES↗

PIV Logon Configuration Guidance

This document details the configurations and enhancements implemented to support the usage of federal Personal Identity Verification (PIV) Card for logon on unclassified networks. The guidance is a reference implementation of the configurations and enhancements deployed at the Los Alamos National Laboratory (LANL) by Network and Infrastructure Engineering – Core Services (NIE-CS).

97 MATHEMATICS AND COMPUTING↗