SEARCH · Search NASA

Results for “Biochemical networks”

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.

SourceResearch connectionFrom yearThrough year

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

140 records · Page 8

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Applying the core-satellite species concept: Characteristics of rare and common riverine dissolved organic matter

Introduction: Dissolved organic matter (DOM) composition varies over space and time, with a multitude of factors driving the presence or absence of each compound found in the complex DOM mixture. Compounds ubiquitously present across a wide range of river systems (hereafter termed core compounds) may differ in chemical composition and reactivity from compounds present in only a few settings (hereafter termed satellite compounds). Here, we investigated the spatial patterns in DOM molecular formulae presence (occupancy) in surface water and sediments across 97 river corridors at a continental scale using the “Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems—WHONDRS” research consortium. Methods: We used a novel data-driven approach to identify core and satellite compounds and compared their molecular properties identified with Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Results: In this work, we found that core compounds clustered around intermediate hydrogen/carbon and oxygen/carbon ratios across both sediment and surface water samples, whereas the satellite compounds varied widely in their elemental composition. Within surface water samples, core compounds were dominated by lignin-like formulae, whereas protein-like formulae dominated the core pool in sediment samples. In contrast, satellite molecular formulae were more evenly distributed between compound classes in both sediment and water molecules. Core compounds found in both sediment and water exhibited lower molecular mass, lower oxidation state, and a higher degree of aromaticity, and were inferred to be more persistent than global satellite compounds. Higher putative biochemical transformations were found in core than satellite compounds, suggesting that the core pool was more processed. Discussion: The observed differences in chemical properties of core and satellite compounds point to potential differences in their sources and contribution to DOM processing in river corridors. Overall, our work points to the potential of data-driven approaches separating rare and common compounds to reduce some of the complexity inherent in studying riverine DOM.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Fungal organic acid uptake of mineral-derived K is dependent on distance from carbon hotspot

Fungal mineral weathering regulates the bioavailability of inorganic nutrients from mineral surfaces to organic matter and increase the bioavailable fraction of nutrients. Such weathering strategies are classified as biomechanical or biochemical. In the case of fungal uptake of mineral nutrients through biochemical weathering, it is widely hypothesized that uptake of inorganic nutrients occurs through organic acid chelation, but such processes have not been directly visualized. This is in part due to challenges in probing the complex and heterogeneous soil environment. Here, using an epoxy-based, mineral-doped soil micromodel platform, which emulates soil mineralogy and porosity, we visualize the molecular mechanisms of mineral weathering. Mass spectrometry imaging revealed differences in the distribution of fungal exudates, citric acid, and tartaric acid on the soil micromodels in presence of minerals. Citric acid was detected closer to the nutrient-rich inoculation point, whereas tartaric acid was highly abundant away from inoculation point. This suggested that the organic acid exuded by the fungi depended on the proximity from the carbon-rich organic substrate at the point of inoculation. Using a combination of X-ray fluorescence and X-ray near edge structure analysis, we identified citric acid- and tartaric acid-bound K within fungal hyphae networks grown in the presence of minerals. Combined, our results provide direct evidence that fungi uptake and transport mineral derived nutrient organic acid chelation. The results of this study provided unprecedented visualization of fungal uptake and transport of K + , while resolving the indirect weathering mechanism of fungal K uptake from mineral interfaces.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

The Legionella Effector SdjA Is a Bifunctional Enzyme That Distinctly Regulates Phosphoribosyl Ubiquitination

Legionella pneumophila promotes its survival and replication in phagocytes by actively modulating cellular processes using effectors injected into host cells by its Dot/Icm type IV secretion system. Many of these effectors function to manipulate the ubiquitin network of infected cells, thus contributing to the biogenesis of the Legionella-containing vacuole (LCV), which is permissive for bacterial replication. Among these, members of the SidE effector family (SidEs) catalyze ubiquitination of functionally diverse host proteins by a mechanism that is chemically distinct from the canonical three-enzyme cascade. The activity of SidEs is regulated by two mechanisms: reversal of the phosphoribosyl ubiquitination by DupA and DupB and direct inactivation by SidJ, which is a calmodulin-dependent glutamylase. In many L. pneumophila strains, SidJ belongs to a two-member protein family. Its homolog SdjA appears to function differently from SidJ despite the high-level similarity in their primary sequences. Here, we found that SdjA is a bifunctional enzyme that exhibits distinct activities toward members of the SidE family. It inhibits the activity of SdeB and SdeC by glutamylation. Unexpectedly, it also functions as a deglutamylase that reverses SidJ-induced glutamylation on SdeA. Our results reveal that an enzyme can catalyze two completely opposite biochemical reactions, which highlights the distinct regulation of phosphoribosyl ubiquitination by the SidJ effector family.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Quantum-enhanced photoprotection in neuroprotein architectures emerges from collective light-matter interactions

Background Superradiance is the phenomenon of many identical quantum systems absorbing and/or emitting photons collectively at a higher rate than any one system can individually. This phenomenon has been studied analytically in idealized distributions of electronic two-level systems (TLSs), each with a ground and excited state, as well as numerically in realistic photosynthetic nanotubes and cytoskeletal architectures. Methods Superradiant effects are studied here in idealized toy model systems and realistic biological mega-networks of tryptophan (Trp) molecules, which are strongly fluorescent amino acids found in many proteins. Each Trp molecule acts as a chromophore absorbing in the ultraviolet spectrum and can be treated approximately as a TLS, with its 1 L a excited singlet state; thus, organized Trp networks can exhibit superradiance. Such networks are found, for example, in microtubules, actin filaments, and amyloid fibrils. Microtubules and actin filaments are spiral-cylindrical protein polymers that play significant biological roles as primary constituents of the eukaryotic cytoskeleton, while amyloid fibrils have been targeted in a variety of neurodegenerative diseases. We treat these proteinaceous Trp networks as open quantum systems, using a non-Hermitian Hamiltonian to describe interactions of the chromophore network with the electromagnetic field. We numerically diagonalize the Hamiltonian to obtain its complex eigenvalues, where the real part is the energy and the imaginary part is its associated enhancement rate. We also consider multiple realizations of increasing static disorder in either the site energies or the decay rates. Results We obtained the energies and enhancement rates for realistic microtubules, actin filament bundles, and amyloid fibrils of differing lengths, and we use these values to calculate the quantum yield, which is the ratio of the number of photons emitted to the number of photons absorbed. We find that all three of these structures exhibit highly superradiant states near the low-energy portion of the spectrum, which enhances the magnitude and robustness of the quantum yield to static disorder and thermal noise. Conclusion The high quantum yield and stable superradiant states in these biological architectures may play a photoprotective rolein vivo, downconverting energetic ultraviolet photons—absorbed from those emitted by reactive free radical species—to longer, safer wavelengths and thereby mitigating biochemical stress and photophysical damage. Contrary to conventional assumptions that quantum effects cannot survive in large biosystems at high temperatures, our results suggest that macropolymeric collectives of TLSs in microtubules, actin filaments, and amyloid fibrils exhibit increasingly observable and robust effects with increasing length, up to the micron scale, due to quantum coherent interactions in the single-photon limit. Superradiant enhancement and high quantum yield exhibited in neuroprotein polymers could thus play a crucial role in information processing in the brain, the development of neurodegenerative diseases such as Alzheimer’s and related dementias, and a wide array of other pathologies characterized by anomalous protein aggregates.

Physics↗

DOE OSTI2024

Network of epistatic interactions in an enzyme active site revealed by large-scale deep mutational scanning

Cooperative interactions between amino acids are critical for protein function. A genetic reflection of cooperativity is epistasis, which is when a change in the amino acid at one position changes the sequence requirements at another position. To assess epistasis within an enzyme active site, we utilized CTX-M β-lactamase as a model system. CTX-M hydrolyzes β-lactam antibiotics to provide antibiotic resistance, allowing a simple functional selection for rapid sorting of modified enzymes. We created all pairwise mutations across 17 active site positions in the β-lactamase enzyme and quantitated the function of variants against two β-lactam antibiotics using next-generation sequencing. Context-dependent sequence requirements were determined by comparing the antibiotic resistance function of double mutations across the CTX-M active site to their predicted function based on the constituent single mutations, revealing both positive epistasis (synergistic interactions) and negative epistasis (antagonistic interactions) between amino acid substitutions. The resulting trends demonstrate that positive epistasis is present throughout the active site, that epistasis between residues is mediated through substrate interactions, and that residues more tolerant to substitutions serve as generic compensators which are responsible for many cases of positive epistasis. Additionally, we show that a key catalytic residue (Glu166) is amenable to compensatory mutations, and we characterize one such double mutant (E166Y/N170G) that acts by an altered catalytic mechanism. These findings shed light on the unique biochemical factors that drive epistasis within an enzyme active site and will inform enzyme engineering efforts by bridging the gap between amino acid sequence and catalytic function.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Data and scripts associated with “Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds” (v2)

This data package is associated with the publication “Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds” submitted to Biogeochemistry by Ryan et al., 2024 (DOI: https://doi.org/10.1007/s10533-024-01169-5). This study aims to investigate fundamental and transferable drivers of dissolved organic matter (DOM) diversity across five nested watersheds within the contiguous United States. DOM diversity was explored using ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The samples and the unprocessed FTICR-MS data used in this study are publicly available on the Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) data repository (see DOIs below). The data for the Willamette, Gunnison, Connecticut, and Deschutes basins were collected as part of a collaboration between the Watershed Rules of Life (WROL) project and Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS). The data for the Yakima River basin (YRB) was collected by the PNNL River Corridor SFA. The raw, unprocessed FTICR-MS data with additional (meta)data can be found at doi:10.15485/1895159 for WROL samples and doi:10.15485/1898912 for YRB samples. This data package contains the processed data used in the associated manuscript. This package also contains ancillary geospatial, hydrological, and geochemical information that supports the interpretation of the FTICR-MS data within Ryan et al., 2024. This data package is associated with the GitHub repository found at https://github.com/WHONDRS-Hub/rcsfa-RC4-WROL-YRB_DOM_Diversity. This data package was originally published August 2024. It was updated January 2025 (modified files). See the change history in the readme more details. At the directory level, the data package is comprised of three folders: (1) data, (2) output, and (3) src; and five additional files including the data dictionary (file ending in "_dd.csv”) and file-level metadata (file ending in “_flmd.csv”). The “src” folder contains the scripts used to process the FTICR data, conduct the analyses, and produce the manuscript figures. The inputs for these scripts are in the “data” folder and the returned outputs in the “output” folder. Inputs include temporal and spatial metadata associated with the sampling efforts, processed FTICR data, and total and normalized putative biochemical transformations per sample. Outputs include cleaned and combined data presented as tables, descriptive statistics, and plots. The file-level metadata file lists all files contained in this data package and descriptions for each. The data dictionary describes the units and definitions for each tabular data column or row header.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Statistical Classification of Biosignature Information using Multiple Instrument Observations

The accurate identification of biosignatures (indications of life) from data taken from remote or in situ planetary exploration is one of the most important challenges in astrobiology, the interdisciplinary field examining habitability and the potential for extraterrestrial life. This study employs machine learning algorithms to optimize the identification of biosignatures, with an emphasis on those which are agnostic to a specific biochemical basis. We exploit the wealth of terrestrial data available from biogenic and abiogenic systems to enhance efficient feature prioritization. Our dataset, pulled from public databases and laboratory recorded measurements, includes elemental abundance, isotopic fractionation, and VNIR/Raman spectra The data curation process included standardization for detection limits and ranges. Subsequent feature extraction yielded detailed inputs for machine learning, including combinations of elemental content, isotopic ratios, and parameters of spectral peaks and troughs. Feature significance was evaluated across diverse machine learning methodologies, such as k-nearest neighbors, logistic regression, Random Forest, support vector machines, and Gaussian Naïve Bayes, along with a combined voting classifier. We utilized Receiver Operating Characteristic Area Under the Curve (ROC AUC) across 2,000 50% test-train splits as a robust metric of model performance. Results revealed a promising ROC AUC of 0.853 for the combined voting classifier. Removing elemental abundance data notably reduced model accuracy (13% decrease in AUC), highlighting its critical role in biosignature detection. Several other individual data features exhibited significance within their respective data types, offering additional granularity. This research fortifies the relevance of machine learning to astrobiology, potentially enhancing life detection missions by allowing algorithmic prioritization of high-interest samples for further investigation. Future work will refine data standardization, expand the dataset to include more terrestrial systems, and incorporate convolutional neural networks for spectral feature extraction. The potential for public data sharing is also under exploration, reinforcing our commitment to collective scientific advancement.

Statistical↗

DOE OSTI2021

The CopA2-Type P 1B -Type ATPase CcoI Serves as Central Hub for cbb 3 -Type Cytochrome Oxidase Biogenesis

Copper (Cu)-transporting P 1B -type ATPases are ubiquitous metal transporters and crucial for maintaining Cu homeostasis in all domains of life. In bacteria, the P 1B -type ATPase CopA is required for Cu-detoxification and exports excess Cu(I) in an ATP-dependent reaction from the cytosol into the periplasm. CopA is a member of the CopA1-type ATPase family and has been biochemically and structurally characterized in detail. In contrast, less is known about members of the CopA2-type ATPase family, which are predicted to transport Cu(I) into the periplasm for cuproprotein maturation. One example is CcoI, which is required for the maturation of cbb 3 -type cytochrome oxidase (cbb 3 -Cox) in different species. Here, we reconstituted purified CcoI of Rhodobacter capsulatus into liposomes and determined Cu transport using solid-supported membrane electrophysiology. The data demonstrate ATP-dependent Cu(I) translocation by CcoI, while no transport is observed in the presence of a non-hydrolysable ATP analog. CcoI contains two cytosolically exposed N-terminal metal binding sites (N-MBSs), which are both important, but not essential for Cu delivery to cbb 3 -Cox. CcoI and cbb 3 -Cox activity assays in the presence of different Cu concentrations suggest that the glutaredoxin-like N-MBS1 is primarily involved in regulating the ATPase activity of CcoI, while the CopZ-like N-MBS2 is involved in Cu(I) acquisition. The interaction of CcoI with periplasmic Cu chaperones was analyzed by genetically fusing CcoI to the chaperone SenC. The CcoI-SenC fusion protein was fully functional in vivo and sufficient to provide Cu for cbb 3 -Cox maturation. In summary, our data demonstrate that CcoI provides the link between the cytosolic and periplasmic Cu chaperone networks during cbb 3 -Cox assembly.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

A model of spatio-temporal regulation within biomaterials using DNA reaction–diffusion waveguides

In multi-cellular organisms, cells and tissues coordinate biochemical signal propagation across length scales spanning micrometres to metres. Designing synthetic materials with similar capacities for coordinated signal propagation could allow these systems to adaptively regulate themselves across space and over time. Here, we combine ideas from cell signalling and electronic circuitry to propose a biochemical waveguide that transmits information in the form of a concentration of a DNA species on a directed path. The waveguide could be seamlessly integrated into a soft material because there is virtually no difference between the chemical or physical properties of the waveguide and the material it is embedded within. We propose the design of DNA strand displacement reactions to construct the system and, using reaction–diffusion models, identify kinetic and diffusive parameters that enable super-diffusive transport of DNA species via autocatalysis. Finally, to support experimental waveguide implementation, we propose a sink reaction and spatially inhomogeneous DNA concentrations that could mitigate the spurious amplification of an autocatalyst within the waveguide, allowing for controlled waveguide triggering. Chemical waveguides could facilitate the design of synthetic biomaterials with distributed sensing machinery integrated throughout their structure and enable coordinated self-regulating programmes triggered by changing environmental conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Microbial processing of plant remains is co-limited by multiple nutrients in global grasslands

Microbial processing of aggregate-unprotected organic matter inputs is key for soil fertility, long-term ecosystem carbon and nutrient sequestration and sustainable agriculture. In this work, we investigated the effects of adding multiple nutrients (nitrogen, phosphorus and potassium plus nine essential macro- and micro-nutrients) on decomposition and biochemical transformation of standard plant materials buried in 21 grasslands from four continents. Addition of multiple nutrients weakly but consistently increased decomposition and biochemical transformation of plant remains during the peak-season, concurrent with changes in microbial exoenzymatic activity. Higher mean annual precipitation and lower mean annual temperature were the main climatic drivers of higher decomposition rates, while biochemical transformation of plant remains was negatively related to temperature of the wettest quarter. Nutrients enhanced decomposition most at cool, high rainfall sites, indicating that in a warmer and drier future fertilized grassland soils will have an even more limited potential for microbial processing of plant remains.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2003

Non-Genomic Origins of Proteins and Metabolism

It is proposed that evolution of inanimate matter to cells endowed with a nucleic acid- based coding of genetic information was preceded by an evolutionary phase, in which peptides not coded by nucleic acids were able to self-organize into networks capable of evolution towards increasing metabolic complexity. Recent findings that truly different, simple peptides (Keefe and Szostak, 2001) can perform the same function (such as ATP binding) provide experimental support for this mechanism of early protobiological evolution. The central concept underlying this mechanism is that the reproduction of cellular functions alone was sufficient for self-maintenance of protocells, and that self- replication of macromolecules was not required at this stage of evolution. The precise transfer of information between successive generations of the earliest protocells was unnecessary and, possibly, undesirable. The key requirement in the initial stage of protocellular evolution was an ability to rapidly explore a large number of protein sequences in order to discover a set of molecules capable of supporting self- maintenance and growth of protocells. Undoubtedly, the essential protocellular functions were carried out by molecules not nearly as efficient or as specific as contemporary proteins. Many, potentially unrelated sequences could have performed each of these functions at an evolutionarily acceptable level. As evolution progressed, however proteins must have performed their functions with increasing efficiency and specificity. This, in turn, put additional constraints on protein sequences and the fraction of proteins capable of performing their functions at the required level decreased. At some point, the likelihood of generating a sufficiently efficient set of proteins through a non-coded synthesis was so small that further evolution was not possible without storing information about the sequences of these proteins. Beyond this point, further evolution required coupling between proteins and informational polymers that is characteristic to all known forms of life. The emergence of such coupling must be postulated in any scenario of the origin of life, no matter whether it starts with RNA or proteins. To examine the evolutionary potential of non-genomic systems, a simple, computationally tractable model, which is still capable of capturing the essential features of the real system, has been studied computationally. Both constructive and destructive processes have been introduced into the model in a stochastic manner. Instead of assuming random reaction sets, only a suite of protobiologically plausible reactions has been considered. Peptides have been explicitly considered as protoenzymes and their catalytic efficiencies have been assigned on the basis of biochemical principles and experimental estimates. Simulations have been carried out using a novel approach (The Next Reaction Method) that is appropriate even for very low concentrations of reactants. Studies have focused on global autocatalytic processes and their diversity.

Pohorille, Andrew↗

DOE OSTI2021

Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth

Sustaining a robust metabolic network requires a balanced and fully functioning proteome. In addition to amino acids, many enzymes require cofactors (coenzymes and engrafted prosthetic groups) to function properly. Extensively validated resource allocation models, such as genome-scale models of metabolism and gene expression (ME-models), have the ability to compute an optimal proteome composition underlying a metabolic phenotype, including the provision of all required cofactors. Here we apply the ME-model for Escherichia coli K-12 MG1655 to computationally examine how environmental conditions change the proteome and its accompanying cofactor usage. We found that: (1) The cofactor requirements computed by the ME-model mostly agree with the standard biomass objective function used in models of metabolism alone (M-models); (2) ME-model computations reveal non-intuitive variability in cofactor use under different growth conditions; (3) An analysis of ME-model predicted protein use in aerobic and anaerobic conditions suggests an enrichment in the use of peroxyl scavenging acids in the proteins used to sustain aerobic growth; (4) The ME-model could describe how limitation in key protein components affect the metabolic state of E . coli . Genome-scale models have thus reached a level of sophistication where they reveal intricate properties of functional proteomes and how they support different E . coli lifestyles.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2003

Developmental gene regulatory network architecture across 500 million years of echinoderm evolution

Evolutionary change in morphological features must depend on architectural reorganization of developmental gene regulatory networks (GRNs), just as true conservation of morphological features must imply retention of ancestral developmental GRN features. Key elements of the provisional GRN for embryonic endomesoderm development in the sea urchin are here compared with those operating in embryos of a distantly related echinoderm, a starfish. These animals diverged from their common ancestor 520-480 million years ago. Their endomesodermal fate maps are similar, except that sea urchins generate a skeletogenic cell lineage that produces a prominent skeleton lacking entirely in starfish larvae. A relevant set of regulatory genes was isolated from the starfish Asterina miniata, their expression patterns determined, and effects on the other genes of perturbing the expression of each were demonstrated. A three-gene feedback loop that is a fundamental feature of the sea urchin GRN for endoderm specification is found in almost identical form in the starfish: a detailed element of GRN architecture has been retained since the Cambrian Period in both echinoderm lineages. The significance of this retention is highlighted by the observation of numerous specific differences in the GRN connections as well. A regulatory gene used to drive skeletogenesis in the sea urchin is used entirely differently in the starfish, where it responds to endomesodermal inputs that do not affect it in the sea urchin embryo. Evolutionary changes in the GRNs since divergence are limited sharply to certain cis-regulatory elements, whereas others have persisted unaltered.

NASA Program Fundamental Space Biology↗

DOE OSTI2025

Mechanical separations of corn stover anatomical fractions in an integrated feedstock preprocessing system: An experimental and data-driven modeling study

High variabilities of material attributes in lignocellulosic biomass present risks for biofuel and biochemical productions and must be mitigated via preprocessing. Since almost no mechanical device is originally designed for processing biomass, how to operate existing apparatuses with efficient performance has not been investigated extensively. This work presents a study on an integrated screening and air classification to separate cobs and stalks from husks and leaves in corn stover. Prototype machine learning models were developed to assess the feasibility of predicting the process outcome based on the measurable parameters. The models trained upon limited experimental data rendered decent predictive accuracy of yield and purity. The experimental data and modeling results collectively suggest decreasing throughput leads to a higher purity. To the contrary, if throughput increases, a lower purity is likely. A possible trade-off between yield and purity of the separated streams indicates the need for optimal combinations of feedstock size, moisture, and throughput to achieve optimized separations. The results of this study also suggest the need to further improve model predictability by developing more accurate formulations for physics governing the integrated unit operations. To accomplish this, additional experimental data needs to be generated for model training.

09 - BIOMASS FUELS↗