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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Observing fish interactions with marine energy turbines using acoustic cameras

Abstract Marine current energy converters such as tidal and riverine turbines have the potential to provide reliable, clean power. The risk of collision of fishes with marine energy turbines is not yet well understood, in part due to the challenges associated with observing fish at turbine sites. Turbidity and light availability can limit the effectiveness of optical sensors like video cameras, motivating the use of acoustic cameras for this task. However, challenges persist in collecting and interpreting data acquired from acoustic cameras. Given the limited number of turbine deployments to date, it is prudent to draw on the application of acoustic cameras to monitor fish in other scenarios. This article synthesizes their use for other fisheries applications to inform best practices and set realistic expectations for the results of acoustic camera monitoring at turbine sites. We discuss six key tasks performed with acoustic cameras: detecting objects, identifying objects as fish, counting fish, measuring fish, classifying fish taxonomically and analysing fish behavior. Specific challenges to monitoring fish at turbine sites are discussed. This article is intended to serve as a reference for researchers, regulators and marine energy developers on effective use of acoustic cameras to monitor fish at turbine sites. The studies detailed in this article provide evidence that, in some scenarios, acoustic cameras can be used to inform the risk of fish collision with marine energy turbines but doing so requires careful study design and data processing.

Cotter, Emma↗
DOE OSTI2022

Emerging wild virus of native grass bioenergy feedstock is well–established in the Midwestern USA and associated with premature stand senescence

The North American native prairie grass Panicum virgatum (switchgrass) is a primary bioenergy feedstock candidate. Its widespread distribution and genetic diversity enable the possibility of developing this perennial grass for high production in a variety of conditions, including on marginal lands. A critical concern in feedstock development and deployment is the risk of novel pathogen emergence. Here we investigate the landscape-scale prevalence and epidemiology of a little-studied North American virus first detected in switchgrass and other grasses in bioenergy trials in the US Midwest. Switchgrass mosaic virus (SwMV, Genus Marafivirus, Family Tymoviridae) is transmitted by leafhoppers and phylogenetically sister to Maize rayado fino virus, a significant pathogen of maize in parts of the Americas. Our goal was to determine whether SwMV is uniquely limited to specific bioenergy trials or well-established and circulating more broadly. We used molecular diagnostics to quantify naturally occurring SwMV infection in leafhoppers and switchgrass in naturalistic stands throughout a large Midwestern landscape, and quantified leafhopper abundances and stand performance. Our analysis revealed that this apparently wild virus is well-established and widespread. Infection was present at nearly all sites, across diverse landscape contexts, with prevalences ranging as high as 33%–60%. Infection appeared to accumulate and persist in stands over time. It was associated with increases in premature stand senescence but not with reductions in stand height. Although wild viruses are believed to evolve benign relationships with their natural hosts, these data suggest that SwMV has potential to impact yield components. Viruses are frequently overlooked in crop development efforts, but represent the majority of emerging plant pathogens. For SwMV, it is imperative to quantify its impact on host performance, to identify the extent of any host resistance, and to assess any risks of virus spillover to agricultural plantings of other Poaceae species, including maize and sorghum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Nanoscale imaging of He-ion irradiation effects on amorphous TaO x toward electroforming-free neuromorphic functions

Resistive switching in thin films has been widely studied in a broad range of materials. Yet, the mechanisms behind electroresistive switching have been persistently difficult to decipher and control, in part due to their non-equilibrium nature. Here, we demonstrate new experimental approaches that can probe resistive switching phenomena, utilizing amorphous TaO x as a model material system. Specifically, we applied scanning microwave impedance microscopy and cathodoluminescence (CL) microscopy as direct probes of conductance and electronic structure, respectively. These methods provide direct evidence of the electronic state of TaO x despite its amorphous nature. For example, CL identifies characteristic impurity levels in TaO x , in agreement with first principles calculations. We applied these methods to investigate He-ion-beam irradiation as a path to activate conductivity of materials and enable electroforming-free control over resistive switching. However, we find that even though He-ions begin to modify the nature of bonds even at the lowest doses, the films' conductive properties exhibit remarkable stability with large displacement damage and they are driven to metallic states only at the limit of structural decomposition. Finally, we show that electroforming in a nanoscale junction can be carried out with a dissipated power of <20 nW, a much smaller value compared to earlier studies and one that minimizes irreversible structural modifications of the films. Importantly, the multimodal approach described here provides a new framework toward the theory/experiment guided design and optimization of electroresistive materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution

Abstract Only a handful of somatic alterations have been linked to endocrine therapy resistance in hormone-dependent breast cancer, potentially explaining ∼40% of relapses. If other mechanisms underlie the evolution of hormone-dependent breast cancer under adjuvant therapy is currently unknown. In this work, we employ functional genomics to dissect the contribution of cis-regulatory elements (CRE) to cancer evolution by focusing on 12 megabases of noncoding DNA, including clonal enhancers, gene promoters, and boundaries of topologically associating domains. Parallel epigenetic perturbation (CRISPRi) in vitro reveals context-dependent roles for many of these CREs, with a specific impact on dormancy entrance and endocrine therapy resistance. Profiling of CRE somatic alterations in a unique, longitudinal cohort of patients treated with endocrine therapies identifies a limited set of noncoding changes potentially involved in therapy resistance. Overall, our data uncover how endocrine therapies trigger the emergence of transient features which could ultimately be exploited to hinder the adaptive process. Significance: This study shows that cells adapting to endocrine therapies undergo changes in the usage or regulatory regions. Dormant cells are less vulnerable to regulatory perturbation but gain transient dependencies which can be exploited to decrease the formation of dormant persisters.

Oncology↗
DOE OSTI2021

Repetitive diacetyl vapor exposure promotes ubiquitin proteasome stress and precedes bronchiolitis obliterans pathology

Bronchiolitis obliterans (BO) is a devastating lung disease seen commonly after lung transplant but also seen following severe respiratory tract infection or chemical inhalation exposure. Diacetyl (DA; 2,3-butanedione), highly reactive alpha-diketone is known to cause BO when inhaled, however, the mechanisms of how inhalation exposure leads to BO development remains poorly understood. In the current work, we combined two clinically relevant models for studying the pathogenesis of DA-induced BO: (1) an in vivo rat model of repetitive DA vapor exposures with recovery and (2) an in vitro model of primary human airway epithelial cells exposed to pure DA vapors. Rats exposed to 5 consecutive days 200 parts-per-million DA 6 hrs per day had worsening survival, persistent hypoxemia, poor weight gain, and histologic evidence of BO 14 days after DA exposure cessation. At the end of exposure, increased expression of the ubiquitin stress protein, ubiquitin-C, accumulated within DA-exposed rat lung homogenates, localized primarily to the airway epithelium, the primary site of BO development, and did not occur in air-exposed controls. Lung proteasome activity increased concurrently after DA exposure. In primary human airway cultures, global proteomics analysis identified 519 significantly modified proteins in DA-exposed samples relative to controls with the ubiquitin proteasome system, endosomal reticulum transport, and the response to unfolded protein pathways being upregulated while cell-cell adhesion and oxidation-reduction pathways being downregulated in DA-exposed samples. Altogether, repetitive DA vapor exposure resulted in abundant protein damage, accumulation of polyubiquinated proteins, and ubiquitin proteasome stress prior to the development of chemical-induced BO pathology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A qualitative study of marginalized students’ academic, physical, and social self-efficacy in a multiweek geoscience field program

Undergraduate summer field programs are valuable experiences that can foster or reduce students’ self-efficacy, an important factor in students’ success and retention in geoscience. Growing research findings show that science field experiences can be hostile and unwelcoming to students with marginalized identities, which may negatively impact their self-efficacy in geoscience, a discipline with a dearth of students from underrepresented, marginalized identities. We conducted an interpretive qualitative study examining how summer geoscience field programs affected two undergraduate, marginalized students’ self-efficacy. Adding to existing theoretical explanations of self-efficacy, we identified three types of self-efficacy impacted positively and negatively by geoscience field experiences: academic, physical, and social self-efficacy. We developed a nuanced understanding of the specific field experiences that influenced the ‘ups and downs’ of students’ self-efficacy and, ultimately, their intent in continuing to pursue a geoscience education or career. Despite negative experiences, including gender discrimination, crude sexual jokes, and a lack of belonging, the students described their intent to persist in geoscience. Here, our findings can assist geoscience educators (and others in field-based sciences) to consider experiences that support and hinder marginalized students’ self-efficacy. Also, our findings can guide efforts to improve geoscience field programs to create more inclusive environments.

case study↗
DOE OSTI2023

An Investigation on the Pollen-Induced Soiling Losses in Utility-Scale PV Plants

Here in this study, the impact of pollen as a PV soiling agent is investigated. The performance data of five utility-scale PV plants in North Carolina, USA, was collected and analyzed using two soiling extraction methods. Satellite and environmental data, including pollen counts, cropland, and vegetation, was also collected and analyzed to identify impacts to soiling losses. During the spring peak pollen season, performance losses of >15% were observed at all five sites. Partial performance recoveries following the pollen season were slow, with lack of correlation with rainfall. This means that the statistical soiling estimation methods that assume abrupt performance recovery from rain are not appropriate for pollen-impacted solar sites. When manual cleanings were performed on site the performance recovery ranged from 5% to 11% indicating persistent soiling impacts are present in this region. The results of this work provide new insights into the phenomenon of pollen deposition on PV systems, demonstrating that 1) soiling can also affect systems located in rainy locations and 2) that its effects cannot be determined using the current estimation methodologies.

14 SOLAR ENERGY↗
DOE OSTI2023

Application of electron beam technology to decompose persistent emerging drinking water contaminants: poly- and perfluoroalkyl substances (PFAS) and 1,4 dioxane.

Fermi Research Alliance, LLC (FRA) operates Fermilab under contract with the U.S. Department of Energy and has patents on technologies and applications of a novel mobile electron beam accelerator. A high-power version of this mobile accelerator based on FRA-developed SRF technology is under development at Illinois Accelerator Research Center (IARC) and can enable several new applications that have significant commercial potential. One such application is the e-beam treatment of persistent emerging contaminants in drinking water. The contaminants of concern are poly- and perfluoroalklyl substances (PFAS) and 1,4-dioxine. Both PFAS and 1,4-D are highly resistant to degradation and are not effectively removed by conventional drinking water treatment systems. Existing technologies, such as granular activated carbon (GAC) filters and reverse osmosis (RO) systems do not decompose. The Center for Clean Water Technology (CCWT) at Stony Brook University (SBU) is in the process of identifying and testing effective technologies to remove PFAS and/or 1,4-D from drinking waters. se PFAS, but rather concentrate them either by adsorption (GAC) or membrane rejection (RO). The Center for Clean Water Technology (CCWT) at Stony Brook University (SBU) is in the process of identifying and testing effective technologies to remove PFAS and/or 1,4-D from drinking waters to demonstrate the full-scale application of novel water treatment technologies and is experienced in conducting research to understand treatment performance with a particular focus on 1,4-D and PFAS contamination.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Seeding Advanced Treated Wastewater for Purposes of Direct Potable Reuse

Direct potable reuse (DPR) is a promising solution to address water scarcity. However, a better understanding of how introducing advanced treated water (ATW) affects microbial communities present in distribution systems is needed. Here, in this study, we measured changes to the microbial water quality in simulated distribution systems that were conditioned using treated, unimpaired surface water (SW) and then transitioned to ATW. In addition, we investigated whether adding a biological filtration step would seed the microbial community of the ATW and whether the influence would persist in the simulated distribution systems. We found that the bulk water in the ATW-fed distribution systems had lower cell counts and ATP concentrations and a distinct microbial community (based on 16S amplicon sequencing) compared to the SW-fed or the seeded ATW-fed systems. However, biofilm community composition and biomass remained consistent regardless of the feedwater. Increased microbial biomass and diversity were present in the seeded ATW, with several amplicon sequence variants identified as being introduced by the biological filter. Our results suggest that directly introducing ATW to distribution systems could disturb the existing microbial community. Preparing ATW for distribution via biological filtration may deliver more predictable and stable microbial water quality than introducing unseeded ATW.

16S↗
DOE OSTI2025

Catalyst Deactivation Modes of PdO/γ-Al 2 O 3 Catalysts for Lean Methane Oxidation

PdO/γ-Al 2 O 3 catalysts are one of the most active catalytic components for the complete oxidation of methane. Under reaction conditions, especially in a wet feed, the catalysts suffer severe performance degradation. This study establishes a series of testing protocols to systematically investigate the causes of catalyst deactivation under methane oxidation reaction conditions. Four distinct catalyst deactivation modes are identified. Two of the deactivation modes are directly related to H 2 O, either from the feed gas or as a part of the reaction products, with one (Mode 2) being attributed to the formation of surface hydroxyl groups and the other (Mode 3) to the competitive adsorption of H 2 O on the catalysts. The impact of the two deactivation modes is acute and severe but reversible. In contrast, the other two deactivation modes are gradual and persistent but irreversible. Both modes are induced by CH 4 oxidation reaction, with the impact of a wet feed (Mode 4) being substantially more severe than that of a dry feed (Mode 1). The major cause of the irreversible catalyst deactivation is attributed to surface reconstruction of PdO nanoparticles, which behaves as a passivation layer lowering the number of coordinately unsaturated Pd sites for CH 4 activation. Although the passivation layer is relatively stable against thermal or hydrothermal treatment, it is not completely inert. Formation and partial regeneration of the passivation layer is a highly dynamic process and heavily depends on the reaction temperature: a lower reaction temperature (≤ 450 ℃) can lead to quicker catalyst deactivation; but a higher reaction temperature (between 500 – 550 ℃) can result in a greater extent of catalyst deactivation.

PdO/γ-Al2O3↗
DOE OSTI2024

Improved Characterization of Soil Organic Matter by Integrating FT-ICR MS, Liquid Chromatography Tandem Mass Spectrometry, and Molecular Networking: A Case Study of Root Litter Decay under Drought Conditions

Understanding of how soil organic matter (SOM) chemistry is altered in a changing climate has advanced considerably; however, most SOM components remain unidentified, impeding the ability to characterize a major fraction of organic matter and predict what types of molecules, and from which sources, will persist in soil. Here we present a novel approach to better characterize SOM extracts by integrating information from three types of analyses, and we deploy this method to characterize decaying root-detritus soil microcosms subjected to either drought or normal conditions. To observe broad differences in composition, we employed direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). We complemented this with liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify components by library matching. Since libraries contain only a small fraction of SOM components, we also used fragment spectral cosine similarity scores to relate unknowns and library matches through molecular networks. This integrated approach allowed us to corroborate DI-FT-ICR MS molecular formulas using library matches, which included fungal metabolites and related polyphenolic compounds. We also inferred structures of unknowns from molecular networks and improved LC-MS/MS annotation rates from ~5 to 35% by considering DI-FT-ICR MS molecular formula assignments. Under drought conditions, we found greater relative amounts of lignin-like vs condensed aromatic polyphenol formulas and lower average nominal oxidation state of carbon, suggesting reduced decomposition of SOM and/or microbes under stress. Our integrated approach provides a framework for enhanced annotation of SOM components that is more comprehensive than performing individual data analyses in parallel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Understanding cold electron impact on parallel-propagating whistler chorus waves via moment-based quasilinear theory

Earth's magnetosphere hosts a wide range of collisionless particle populations that interact through various wave-particle processes. Among these, cold electrons, with energies below 100 eV, often dominate the plasma density but remain poorly characterized due to measurement challenges such as spacecraft charging and photoelectron contamination. Understanding the contribution of these cold populations to wave–particle interaction is of significant interest. Recent kinetic simulations identified a secondary drift-driven instability, in which parallel-propagating whistler-mode chorus waves excite oblique electrostatic whistler waves near the resonance cone and Bernstein-mode turbulence. These secondary modes enable a new channel of energy transfer from the parallel-propagating whistler wave to the cold electrons. In this work, we develop a moment-based quasilinear theory of the secondary instabilities to quantify such energy exchange. Our results show that these secondary instabilities persist for a wide range of parameters and, in many cases, lead to nearly complete damping of the primary wave. Such secondary instability might limit the amplitude of parallel-propagating whistler waves in Earth's magnetosphere and might explain why high-amplitude oblique whistler or electron Bernstein waves are rarely observed simultaneously with high-amplitude field-aligned whistler waves in the inner magnetosphere.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to national security, public health, and the economy. Development of new vaccines and antibodies for emerging viral threats requires substantial resources and time, and traditional development platforms for vaccines and antibodies are often too slow to combat continuously evolving immunological escape variants, reducing their efficacy over time. Previously, we designed a next-generation synthetic humanized nanobody (Nb) phage display library and demonstrated that this library could be used to rapidly identify highly specific and potent neutralizing heavy chain-only antibodies (HCAbs) with prophylactic and therapeutic efficacy in vivo against the original SARS-CoV-2. In this study, we used a combination of high throughput screening and machine learning (ML) models to identify HCAbs with potent efficacy against SARS-CoV-2 viral variants of interest (VOIs) and concern (VOCs). To start, we screened our highly diverse Nb phage display library against several pre-Omicron VOI and VOC receptor binding domains (RBDs) to identify panels of cross-reactive HCAbs. Using HCAb affinity for SARS-CoV-2 VOI and VOCs (pre-Omicron variants) and model features from other published data, we were able to develop a ML model that successfully identified HCAbs with efficacy against Omicron variants, independent of our experimental biopanning workflow. This biopanning informed ML approach reduced the experimental screening burden by 78% to 90% for the Omicron BA.5 and Omicron BA.1 variants, respectively. The combined approach can be applied to other emerging viruses with pandemic potential to rapidly identify effective therapeutic antibodies against emerging variants.

Antibodies↗
DOE OSTI2019

Solar soft cost ontology: a review of solar soft costs

The continued deployment of renewable energy is critical to the energy transition necessary for climate change mitigation. Since cost is one of the primary drivers of solar adoption, we must continue to reduce the cost of solar to hasten the transition to clean energy. Currently, solar soft costs account for 52%–70% of the cost of an installed residential solar photovoltaic (PV) system in the U.S. These costs are persistent and an increasing share of the costs, since hardware costs continue to decline. The consensus on a definition of soft costs is 'non-hardware costs', but defining something by what it is not does not tell us what it is, which makes it difficult to study and understand. To this end, we developed the solar soft cost ontology (SSCO) to provide a comprehensive view of the complex and variable knowledge domain of solar soft costs. In this work, we identify the main categories of solar soft costs, how they relate to each other, how that knowledge is created, shared, and acquired, and the relevant actors in the solar soft cost knowledge ecosystem. Developed by coding a corpus of nearly 130 academic articles, the resulting ontology in web ontology language (OWL) includes 136 classes and 87 properties. The SSCO can facilitate and enhance knowledge transfer of research findings and best practices within and between stakeholder communities, including researchers, practitioners, and policy makers, that seek to address solar soft costs. We conclude with a discussion of potential applications and use cases for the SSCO among this diverse stakeholder community.

14 SOLAR ENERGY↗
DOE OSTI2023

Improving an Acoustic Vehicle Detector Using an Iterative Self-Supervision Procedure

In many non-canonical data science scenarios, obtaining, detecting, attributing, and annotating enough high-quality training data is the primary barrier to developing highly effective models. Moreover, in many problems that are not sufficiently defined or constrained, manually developing a training dataset can often overlook interesting phenomena that should be included. To this end, we have developed and demonstrated an iterative self-supervised learning procedure, whereby models are successfully trained and applied to new data to extract new training examples that are added to the corpus of training data. Successive generations of classifiers are then trained on this augmented corpus. Using low-frequency acoustic data collected by a network of infrasound sensors deployed around the High Flux Isotope Reactor and Radiochemical Engineering Development Center at Oak Ridge National Laboratory, we test the viability of our proposed approach to develop a powerful classifier with the goal of identifying vehicles from continuously streamed data and differentiating these from other sources of noise such as tools, people, airplanes, and wind. Using a small collection of exhaustively manually labeled data, we test several implementation details of the procedure and demonstrate its success regardless of the fidelity of the initial model used to seed the iterative procedure. Finally, we demonstrate the method’s ability to update a model to accommodate changes in the data-generating distribution encountered during long-term persistent data collection.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Modeling the U.S. Western Electric Interconnection to Understand the Consequences of Hydrometeorological Extremes and Options for Risk Mitigation

Electricity grid operators around the world face a dual challenge; withstanding increasingly severe weather and the longer term impacts of climate change, while simultaneously decarbonizing. Extreme weather events such as heat waves and droughts are rising in both severity and frequency, which is threatening the reliability of electricity grids through increased demand, generation capacity losses, and equipment failures. Consequently, incorporating hydrometeorological stressors into computational power systems analysis is becoming an even more critical tool in long term planning and short term operations. However, there is a general lack of open-source customizable grid simulation software capable of exhaustively stress testing the grid under hydrometeorological uncertainty, and/or examining potential risk mitigation pathways. A related, persistent challenge for power system modelers is striking an appropriate balance between model fidelity (e.g. spatial scale and time resolution) and computational tractability (wall clock run-time). In this study, we are proposing a solution to this problem with open-source software that allows users to seamlessly customize the scale and track the accuracy of grid operations models. Our approach allows users to search over numerous model parameters (network topology, mathematical formulation, economic hurdle rates, and transmission line scaling) to identify model instantiations that accommodate experimental design. Further, we use this approach to demonstrate the importance of including extreme weather events in model validation and model selection. Focusing on the occurrence of heatwaves and droughts in the U.S. Western Interconnection, we examine role of extreme events in balancing tradeoffs between model fidelity and run-time at the model design stage.

Economics↗
DOE OSTI2025

GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics

Data package for Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon This data is published under a CC0 license. The authors encourage data reuse and request attribution by referencing the below citations for the data packages and associated manuscript. Please cite as: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics. [Data Set] PNNL DataHub. doi: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. MSV000097435: GLBRC soil yearlong incubation 13C-SIP-Lipidomics [Data Set] MassIVE. doi:10.25345/C57659T3K Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon. In Prep This data package consists of compound-specific 13C SIP-lipidomics data from a yearlong tracer incubation experiment designed to investigate microbial lipid persistence in switchgrass bioenergy crop soils. In order to explore how lipid structure may modulate the persistence of C in soil lipids, we leveraged soils from two sites (Michigan - sandy texture, Wisconsin - silty texture) operated by the U.S. Department of Energy-funded Great Lakes Bioenergy Research Center (GLBRC). These sites had comparable climates, identical management practices, but contrasting soil textures, allowing us to assess the variability of lipid accrual or degradation in soils as well as provide insight regarding the degree to which edaphic properties may regulate the retention of soil lipids. Untargeted lipidomics analyses were performed to identify 13C-labeled lipids in the soil microbiome after long-term incubation. Soils were supplemented with 100 micrograms glucose per gram dry soil (99 atom % 13C or natural abundance for paired control) and incubated; samples were collected two months and one year after glucose addition. Lipid extracts (MPLEx) were analyzed by LC-MS/MS and identified using LIQUID. Calculation of isotopic enrichment of lipids was performed by targeted approach using TarMet to quantify lipid isotopologues and IsoCorrectoR to correct for natural abundance isotopes. Contents: Data package contents reported here are the first version and contain downstream analysis files for the raw LC-MS mass spectrometry files (.mzXML) deposited at the MassIVE database repository under accession MSV000097435 (80 experimental runs; 5.85 GB) | MassIVE DOI: 10.25345/C57659T3K. Support files include the additional data download 'Read Me' file containing data descriptor information. Reported data download contents are structured for compliance with project data sharing guidelines, community standards initiatives, and sponsor stakeholder policies supporting FAIR data principles. Data processing software, analysis tools, and data workflows are listed below corresponding to the host repository long-term location. Available Data Downloads (0.3 GB): "GLBRC soil yearlong incubation 13C-SIP-Lipidomics_readme.txt" - 'Read Me' data package content file (txt) "GLBRC_DataPackage_analysis files" - Data processing files (Rmd) and saved intermediate data processing outputs (rds, csv, xlsx) "GLBRC_13C_lipidomics_dataset.xlsx" - processed data in tabular format (xlsx) Linked Software: LIQUID LC-MS Analysis Software | 10.5281/zenodo.6459462 Lipid Mini-On Software Tools | 10.5281/zenodo.1492803 pmartR Omics Statistical Software | 10.5281/zenodo.6108667 xcms (v4.3.3) TarMet (v1.1.1) IsoCorrectoR (1.24.0) Funding Acknowledgments: This research was supported by an Early Career Research Program award funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (OBER) Genomic Science program under FWP 68292, FWP 07880 and EMSL Exploratory Research Project 51095. A portion of this work was performed in the William R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by OBER and located at Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated by Battelle for the DOE under Contract DE-AC05-76RLO1830.

Rempfert, Kaitlin R [Pacific Northwest National La↗
DOE OSTI2021

Persistence and plasticity in bacterial gene regulation

Organisms orchestrate cellular functions through transcription factor (TF) interactions with their target genes, although these regulatory relationships are largely unknown in most species. Here we report a high-throughput approach for characterizing TF-target gene interactions across species and its application to 354 TFs across 48 bacteria, generating 17,000 genome-wide binding maps. This dataset revealed themes of ancient conservation and rapid evolution of regulatory modules. We observed rewiring, where the TF sensing and regulatory role is maintained while the arrangement and identity of target genes diverges, in some cases encoding entirely new functions. We further integrated phenotypic information to define new functional regulatory modules and pathways. So, we identified 242 new TF DNA binding motifs, including a 70% increase of known Escherichia coli motifs and the first annotation in Pseudomonas simiae, revealing deep conservation in bacterial promoter architecture. Our method provides a versatile tool for functional characterization of genetic pathways in prokaryotes and eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗