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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genomes and metagenome assemblies

Iron is a micronutrient for nearly all life on Earth. It can be used as an electron donor and electron acceptor by iron-oxidizing and iron-reducing microorganisms and is used in a variety of biological processes, including photosynthesis and respiration. While it is the fourth most abundant metal in the Earth’s crust, iron is often limiting for growth in oxic environments because it is readily oxidized and precipitated. Much of our understanding of how microorganisms compete for and utilize iron is based on laboratory experiments. However, the advent of next-generation sequencing and surge in publicly available sequence data has made it possible to probe the structure and function of microbial communities in the environment. To bridge the gap between our understanding of iron acquisition, iron redox cycling, iron storage, and magnetosome formation in model microorganisms and the plethora of sequence data available from environmental studies, we have created a comprehensive database of hidden Markov models (HMMs) based on genes related to iron acquisition, storage, and reduction/oxidation in Bacteria and Archaea. Along with this database, we present FeGenie, a bioinformatics tool that accepts genome and metagenome assemblies as input and uses our comprehensive HMM database to annotate provided datasets with respect to iron-related genes and gene neighborhood. An important contribution of this tool is the efficient identification of genes involved in iron oxidation and dissimilatory iron reduction, which have been largely overlooked by standard annotation pipelines. We validated FeGenie against a selected set of 28 isolate genomes and showcase its utility in exploring iron genes present in 27 metagenomes, 4 isolate genomes from human oral biofilms, and 17 genomes from candidate organisms, including members of the candidate phyla radiation. We show that FeGenie accurately identifies iron genes in isolates. Furthermore, analysis of metagenomes using FeGenie demonstrates that the iron gene repertoire and abundance of each environment is correlated with iron richness. While this tool will not replace the reliability of culture-dependent analyses of microbial physiology, it provides reliable predictions derived from the most up-to-date genetic markers. FeGenie’s database will be maintained and continually updated as new genes are discovered.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

RNA language models predict mutations that improve RNA function

Structured RNA lies at the heart of many central biological processes, from gene expression to catalysis. RNA structure prediction is not yet possible due to a lack of high-quality reference data associated with organismal phenotypes that could inform RNA function. We present GARNET (Gtdb Acquired RNa with Environmental Temperatures), a new database for RNA structural and functional analysis anchored to the Genome Taxonomy Database (GTDB). GARNET links RNA sequences to experimental and predicted optimal growth temperatures of GTDB reference organisms. Using GARNET, we develop sequence- and structure-aware RNA generative models, with overlapping triplet tokenization providing optimal encoding for a GPT-like model. Leveraging hyperthermophilic RNAs in GARNET and these RNA generative models, we identify mutations in ribosomal RNA that confer increased thermostability to the Escherichia coli ribosome. The GTDB-derived data and deep learning models presented here provide a foundation for understanding the connections between RNA sequence, structure, and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Engineering a new tripartite split-ccGFP system from Corynactis californica for detecting protein–protein interactions

Protein-protein interactions (PPIs) are critical to a range of biological processes and, consequently, aberrant interactions are implicated in many disorders. The study of the complex networks of PPIs promises to elucidate undiscovered roles in cellular processes and the mechanisms of disease. To accomplish this, tools to effectively sense PPIs are necessary. Effective PPI sensors must rapidly detect interactions in real-time with high sensitivity without perturbing the proteins of interest (POIs) under study. Split fluorescent proteins have previously been used to successfully monitor PPIs, in part due to the small size of the tags. Here, we developed an optimized tripartite split GFP system based on Corynactis californica GFP (ccGFP) to detect PPIs in vitro. In this sensor system, ccGFP fragments ccGFP10 and ccGFP11 are tagged to two POIs. PPIs can then be detected via fluorescence by complementation to the third fragment, ccGFP1-9, which reconstitutes functional ccGFP. The optimized ccGFP system shows improved detection kinetics and pH and temperature stability compared to a previous system. We then validated the sensor by monitoring PPIs in two model systems: attractive/repulsive coiled-coils and rapamycin-inducible FRB/FKBP heterodimerization. Finally, we developed an anti-tripartite ccGFP single-chain variable fragment (scFv), which could enable versatile detection of identified protein-protein complexes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

A parsimonious modular approach to building a mechanistic belowground carbon and nitrogen model

Abstract Soil decomposition models range from simple empirical functions to those that represent physical, chemical, and biological processes. Here we develop a parsimonious, modular C and N cycle model, the Dual Arrhenius Michaelis‐Menten‐Microbial Carbon and Nitrogen Phyisology (DAMM‐MCNiP), that generates testable hypotheses regarding the effect of temperature, moisture, and substrate supply on C and N cycling. We compared this model to DAMM alone and an empirical model of heterotrophic respiration based on Harvard Forest data. We show that while different model structures explain similar amounts of variation in respiration, they differ in their ability to infer processes that affect C flux. We applied DAMM‐MCNiP to explain an observed seasonal hysteresis in the relationship between respiration and temperature and show using an exudation simulation that the strength of the priming effect depended on the stoichiometry of the inputs. Low C:N inputs stimulated priming of soil organic matter decomposition, but high C:N inputs were preferentially utilized by microbes as a C source with limited priming. The simplicity of DAMM‐MCNiP's simultaneous representations of temperature, moisture, substrate supply, enzyme activity, and microbial growth processes is unique among microbial physiology models and is sufficiently parsimonious that it could be incorporated into larger‐scale models of C and N cycling.

Abramoff, Rose Z.↗
DOE OSTI2024

Unveiling the nanoscale architectures and dynamics of protein assembly with in situ atomic force microscopy

Proteins play a vital role in different biological processes by forming complexes through precise folding with exclusive inter- and intra-molecular interactions. Understanding the structural and regulatory mechanisms underlying protein complex formation provides insights into biophysical processes. Furthermore, the principle of protein assembly gives guidelines for new biomimetic materials with potential applications in medicine, energy, and nanotechnology. Atomic force microscopy (AFM) is a powerful tool for investigating protein assembly and interactions across spatial scales (single molecules to cells) and temporal scales (milliseconds to days). It has significantly contributed to understanding nanoscale architectures, inter- and intra-molecular interactions, and regulatory elements that determine protein structures, assemblies, and functions. This review describes recent advancements in elucidating protein assemblies with in situ AFM. We discuss the structures, diffusions, interactions, and assembly dynamics of proteins captured by conventional and high-speed AFM in near-native environments and recent AFM developments in the multimodal high-resolution imaging, bimodal imaging, live cell imaging, and machine-learning-enhanced data analysis. These approaches show the significance of broadening the horizons of AFM and enable unprecedented explorations of protein assembly for biomaterial design and biomedical research.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Conformational Change in a Four‐Tetrad DNA G‐Quadruplex upon Intercalation of a Small‐Molecule Ligand PyDH2

Abstract G‐quadruplexes (G4s) are non‐canonical DNA structures implicated in a number of biological processes. Small‐molecule ligands can alter stability and folding of G4s, which can potentially be exploited for therapeutic purposes. In this work, we investigate the interaction of telomeric DNA fragment fromTetrahymena thermophila(TET25, 5′‐G(TTGGGG) 4‐ 3′) with a G4 ligand PyDH2 belonging to the bisquinolinium family. When alone, TET25 adopts a mixture of three conformations, with the most abundant being a four‐tetrad hybrid G4. In the presence of PyDH2, surprisingly, TET25 folds into an antiparallel chair G4, with PyDH2 intercalated between G‐tetrads 2 and 3, according to our crystal structure. The structure represents the second example, and the first crystallographic evidence, of ligand intercalation into a G4. In solution, the interaction of PyDH2 and TET25 leads to a number of complexes differing by G4 topology and binding stoichiometry, strong stabilization of G4 (∆T m = 12.4 °C in the presence of one equiv. of PyDH2) and large hysteresis of ∼10 °C, suggesting that ligand binding and G4 folding processes are complex.

Chemistry↗
DOE OSTI2017

Ecophysiological variation of transpiration of pine forests: synthesis of new and published results

Canopy transpiration (E C ) is a large fraction of evapotranspiration, integrating physical and biological processes within the energy, water, and carbon cycles of forests. Quantifying E C is of both scientific and practical importance, providing information relevant to questions ranging from energy partitioning to ecosystem services, such as primary productivity and water yield. We estimated E C of four pine stands differing in age and growing on sandy soils. The stands consisted of two wide-ranging conifer species: Pinus taeda and Pinus sylvestris, in temperate and boreal zones, respectively. Combining results from these and published studies on all soil types, we derived an approach to estimate daily EC of pine forests, representing a wide range of conditions from 35° S to 64° N latitude. During the growing season and under moist soils, maximum daily E C (E Cm ) at day-length normalized vapor pressure deficit of 1 kPa (E Cm-ref ) increased by 0.55 ± 0.02 (mean ± SE) mm/d for each unit increase of leaf area index (L) up to L = ~5, showing no sign of saturation within this range of quickly rising mutual shading. The initial rise of E Cm with atmospheric demand was linearly related to E Cm -ref. Both relations were unaffected by soil type. Consistent with theoretical prediction, daily EC was sensitive to decreasing soil moisture at an earlier point of relative extractable water in loamy than sandy soils. Our finding facilitates the estimation of daily EC of wide-ranging pine forests using remotely sensed L and meteorological data. We advocate an assembly of worldwide sap flux database for further evaluation of this approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Comparing Trace Element Bioaccumulation and Depuration in Snails and Mayfly Nymphs at a Coal Ash–Contaminated Site

In this work, we examined the bioaccumulation of essential (Cu, Fe, Se, and Zn) and nonessential (As and Hg) trace elements in 2 aquatic invertebrate species (adult snails and mayfly nymphs) with different feeding habits at the site of a coal ash spill. Differences in food web pathway, exposure concentrations, and biological processing affected bioaccumulation patterns in these species. Mayflies had higher body burdens, but snails had higher retention of most elements studied.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2024

Improving the reliability of machine learned potentials for modeling inhomogeneous liquids

The atomic-scale response of inhomogeneous fluids at interfaces and surrounding solute particles plays a critical role in governing chemical, electrochemical, and biological processes. Classical molecular dynamics simulations have been applied extensively to simulate the response of fluids to inhomogeneities directly, but are limited by the accuracy of the underlying interatomic potentials. Here, we use neural network potentials (NNPs) trained to ab initio simulations to accurately predict the inhomogeneous responses of two distinct fluids: liquid water and molten NaCl. Although NNPs can be readily trained to model complex bulk systems across a range of state points, we show that to appropriately model a fluid's response at an interface, relevant inhomogeneous configurations must be included in the training data. In order to sufficiently sample appropriate configurations of such inhomogeneous fluids, we develop protocols based on molecular dynamics simulations in the presence of external potentials. We demonstrate that NNPs trained on inhomogeneous fluid configurations can more accurately predict several key properties of fluids—including the density response, surface tension and size-dependent cavitation free energies—for liquid water and molten NaCl, compared to both empirical interatomic potentials and NNPs that are not trained on such inhomogeneous configurations. This work therefore provides a first demonstration and framework to extract the response of inhomogeneous fluids from first principles for classical density-functional treatment of fluids free from empirical potentials.

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

Perimatrix of middle ear cholesteatoma: A granulation tissue with a specific transcriptomic signature

Objectives/Hypothesis: To establish comprehensive transcriptomic profiles of cholesteatoma perimatrix tissue and granulation tissue from chronic otitis media (COM) that did not develop cholesteatoma, which can indicate molecular pathways involved in the cholesteatoma perimatrix pathology and invasiveness. Study Design: Retrospective Case Series. Methods: Transcriptome data were obtained from cholesteatoma perimatrix tissue and COM granulation tissue by an Illumina iScan microarray. Differentially expressed genes (DEGs) were subsequently analyzed using both bioinformatical functional annotation and network analysis. Expression of candidate genes (MMP9 and LCN2) was validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) on a larger group of samples. Results: Analysis of the transcriptome led to the identification of 169 differentially expressed genes between investigated tissues. Bioinformatic analysis suggested that most significant biological processes involving DEGs were previously described in cholesteatoma pathology. Network analysis identified ERBB2, TFAP2A, and TP63 as major hubs of the DEGs molecular network. Furthermore, it was observed that the cellular component most significantly enriched in DEGs was extracellular space containing 47 DEGs. Using qRT-PCR, it was confirmed that mRNA levels of the major extracellular hub (MMP9) are increased, whereas its interacting molecule (LCN2) mRNA levels were decreased in cholesteatoma perimatrix tissue compared to COM granulation tissue. Conclusions: The current study approach offers an overall look at molecular mechanisms that describe the cholesteatoma entity by focusing exclusively on the perimatrix processes in comparison to COM granulation tissue. The observed differences in gene expression between cholesteatoma perimatrix and COM granulation tissue could suggest novel markers potentially influenced by the perimatrix–matrix molecular interplay, which is not present in COM without cholesteatoma. Level of Evidence: NA. Laryngoscope, 130:E220–E227, 2020. © 2019 The American Laryngological, Rhinological and Otological Society, Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Temporal dynamics of protein and post-translational modification abundances in Populus leaf across a diurnal period

Populus spp. are dedicated woody biomass feedstocks for advanced biofuels and bioproducts. Proper growth and fitness of poplar as a sustainable feedstock depends on timely perception and response to environmental signals (e.g., light, temperature, water). Poplar leaves, like other C3 photosynthesis plants, have evolved oscillating or circadian rhythms that play important roles in synchronizing biological processes with external cues. To characterize this phenomenon at a molecular level, we employed bottom-up proteomics using high-resolution mass spectrometry and de novo-assisted database searching to identify abundance changes in proteins and post-translational modifications in poplar leaf tissue sampled across a 12/12-hour light/dark diurnal period.

09 BIOMASS FUELS↗
DOE OSTI2019

Wood and water: How trees modify wood development to cope with drought

Societal Impact Statement Drought plays a conspicuous role in forest mortality, and is expected to become more severe in future climate scenarios. Recent surges in drought‐associated forest tree mortality have been documented worldwide. For example, recent droughts in California and Texas killed approximately 129 million and 300 million trees, respectively. Drought has also induced acute pine tree mortality across east‐central China, and across extensive areas in southwest China. Understanding the biological processes that enable trees to modify wood development to mitigate the adverse effects of drought will be crucial for the development of successful strategies for future forest management and conservation. Summary Drought is a recurrent stress to forests, causing periodic forest mortality with enormous economic and environmental costs. Wood is the water‐conducting tissue of tree stems, and trees modify wood development to create anatomical features and hydraulic properties that can mitigate drought stress. This modification of wood development can be seen in tree rings where not only the amount of wood but also the morphology of the water‐conducting cells are modified in response to environmental conditions. In this review, we provide an overview of how trees conduct water, and how trees modify wood development to affect water conduction properties in response to drought. We discuss key needs for new research, and how new knowledge of wood formation can play a role in the conservation of forests under threat by climate change.

Rodriguez‐Zaccaro, F. Daniela↗
DOE OSTI2017

Structure and catalytic activation of the TRIM23 RING E3 ubiquitin ligase: DAWIDZIAK et al.

Tripartite motif (TRIM) proteins comprise a large family of RING-type ubiquitin E3 ligases that regulate important biological processes. An emerging general model is that TRIMs form elongated antiparallel coiled-coil dimers that prevent interaction of the two attendant RING domains. The RING domains themselves bind E2 conjugating enzymes as dimers, implying that an active TRIM ligase requires higher-order oligomerization of the basal coiled-coil dimers. Here, we report crystal structures of the TRIM23 RING domain in isolation and in complex with an E2–ubiquitin conjugate. Our results indicate that TRIM23 enzymatic activity requires RING dimerization, consistent with the general model of TRIM activation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Autonomous Changes in Polymer Materials Driven by Chemical Fuels

Time-dependent properties in polymer materials can be achieved through coupling to out-of-equilibrium chemical fuel reactions that mimic biological processes. Through transient changes in bonding in polymers, transient gelation, changes in mechanical stiffness, swelling, self-healing, or self-assembly can be achieved. Recent advances in these categories are discussed. These out-of-equilibrium behaviors enable applications ranging from smart adhesives to actuators for soft robotics. However, challenges remain, including waste accumulation, bio-compatibility, and achieving functionally useful performance. Addressing these issues is essential for advancing the practical use of chemically driven polymer materials and unlocking their full potential for future technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Feature Design for Protein Interface Hotspots Using KFC2 and Rosetta

Protein–protein interactions regulate many essential biological processes and play an important role in health and disease. The process of experimentally characterizing protein residues that contribute the most to protein–protein interaction affinity and specificity is laborious. Thus, developing models that accurately characterize hotspots at protein–protein interfaces provides important information about how to inhibit therapeutically relevant protein–protein interactions. During the course of the ICERM WiSDM workshop 2017, we combined the KFC2a protein–protein interaction hotspot prediction features with Rosetta scoring function terms and interface filter metrics. A two-way and three-way forward selection strategy was employed to train support vector machine classifiers, as was a reverse feature elimination strategy. From these results, we identified subsets of KFC2a and Rosetta combined features that show improved performance over KFC2a features alone.

Seeger, Franziska↗
DOE OSTI2024

Beyond the Surface: Non-Invasive Low-Field NMR Analysis of Microbially-Induced Calcium Carbonate Precipitation in Shale Fractures

Microbially-induced calcium carbonate precipitation (MICP) is a biological process in which microbially-produced urease enzymes convert urea and calcium into solid calcium carbonate (CaCO 3 ) deposits. MICP has been demonstrated to reduce permeability in shale fractures under elevated pressures, raising the possibility of applying this technology to enhance shale reservoir storage safety. For this and other applications to become a reality, non-invasive tools are needed to determine how effectively MICP seals shale fractures at subsurface temperatures. In this study, two different MICP strategies were tested on 2.54 cm diameter and 5.08 cm long shale cores with a single fracture at 60 °C. Flow-through, pulsed-flow MICP-treatment was repeatedly applied to Marcellus shale fractures with and without sand (“proppant”) until reaching approximately four orders of magnitude reduction in apparent permeability, while a single application of polymer-based “immersion” MICP-treatment was applied to an Eagle Ford shale fracture with proppant. Low-field nuclear magnetic resonance (LF-NMR) and X-Ray computed microtomography (micro-CT) techniques were used to assess the degree of biomineralization. With the flow-through approach, these tools revealed that while CaCO 3 precipitation occurred throughout the fracture, there was preferential precipitation around proppant. Without proppant, the same approach led to premature sealing at the inlet side of the core. In contrast, immersion MICP-treatment sealed off the fracture edges and showed less mineral precipitation overall. This study highlights the use of LF-NMR relaxometry in characterizing fracture sealing and can help guide NMR logging tools in subsurface remediation efforts.

MICP↗
DOE OSTI2019

Long-term performance of a UASB reactor treating acid mine drainage: effects of sulfate loading rate, hydraulic retention time, and COD/SO42- ratio

Acid mine drainage (AMD) is among the most serious threats to water and the typical alkali-based treatment costs are high. This study's main objective was the establishment of a highly efficient biological process using an upflow anaerobic sludge blanket (UASB) reactor to treat AMD based on a shorter hydraulic retention time (HRT) and lower organic matter input. The process was evaluated for a long-term operation (739days) in terms of the influence of HRT (14-24h), metal addition, sulfate loading rate (0.5-2.6gSO(4)(2-)l(-1)d(-1)), and the COD/SO42- ratio (0.67-1.0) using ethanol as the only electron donor at a pH of 4.0. Neutral effluent pH was achieved throughout the time apart from operational modifications. The reduction in HRT from 24 to 16h and an increase in the sulfate loading rate (SLR) up to 2.25gSO(4)(2-)l(-1)d(-1) improved the sulfate removal to (92.1 +/- 1.8)% with 80% chemical oxygen demand (COD) removal. However, the sulfate reduction was less than 80% when the HRT and SLR was changed to 14h and 2.6gSO(4)(2-)l(-1)d(-1), respectively. The oxidation of organic matter by sulfate reduction was greater than 50% regardless of the conditions imposed but the use of ethanol to treat AMD was more efficient when either the HRT was 16h (1.5gSO(4)(2-)l(-1)d(-1)) in the presence of Fe, Zn, and Cu or the HRT was 14h (2.6gSO(4)(2-)l(-1)d(-1)) but the COD/SO42- ratio was reduced to 0.67. The fully optimized conditions of the UASB reactor were set at an HRT of 16h, SLR of 1.5gSO(4)(2-)l(-1)d(-1), and a COD/SO42- ratio of 1.0.

Acid mine drainage↗