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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Grassmannian Shape Representations for Aerodynamic Applications: Preprint

Airfoil shape design is a classical problem in engineering, science, and manufacturing. Our motivation is to combine principled physics-based considerations for the shape design problem with modern computational techniques informed by a data-driven approach. Traditional analyses of airfoil shapes emphasize a flow-based sensitivity to deformations which can be represented generally by affine transformations (rotation, scaling, shearing, shifting). We present a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data, (ii) improved low-dimensional parameter domain for inferential statistics, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes.

blade representation↗

DOE OSTI2022

Grassmannian Shape Representations for Aerodynamic Applications

blade representation↗

DOE OSTI2024

MjCyc: Rediscovering the pathway-genome landscape of the first sequenced archaeon, Methanocaldococcus (Methanococcus) jannaschii

The genome of Methanocaldococcus (Methanococcus) jannaschii DSM 2661 was the first Archaeal genome to be sequenced in 1996. Subsequent sequence-based annotation cycles led to its first metabolic reconstruction in 2005. Leveraging new experimental results and function assignments, we have now re-annotated M. jannaschii, creating an updated resource with novel information and testable predictions in a pathway-genome database available at BioCyc.org. This reannotation effort has resulted in 652 function assignments with enzyme roles, accounting for a third of the total protein-coding entries for this genome. The updated resource includes 883 reactions, 540 enzymes, and 142 individual pathways. Despite notable progress in computational genomics, more than a third of the genome remains functionally uncharacterized. The publicly available MjCyc pathway-genome database holds great potential for the wider community to conduct research on the biology of methanogenic Archaea.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Fox Trails

1. This software utilizes python pandas to pull data from P6 databases or XER files. The software transforms the datasets into multiple main tables by joining, filtering, iteratively flattening hierarchical structured data, and pivoting datasets to give simple flat output tables. The activity table includes all of the information related to an activity including activity codes, global, EPS, and project codes, UDFs, and WBS information as separate columns. This includes the code id, code value and sequence number for all levels in hierarchical codes. The resource table is similar to the activity table and includes all of the information related to resources on activities including UPFs and resource codes. The resource time phased table takes the resource information and time phases it for the budget, forecast, late, and actual dates/units/costs that closely matches P6's user interface's values as it implements the resource curve and calendars. The wbs table contains the WBS structure broken out by levels and includes UDFs, codes, and notebook topics. The final P6 data table is the relationships table which simply contains the relationships. 2. When a user updates the tool with data (via giving it P6 project names with database username/password information or XER files) the system creates the data in #1, then creates a networkx graph with the activity data imbedded in the node data and the relationships added as edges. Each edge also has it's float calculated (working time distance between the predecessor and successor) and attached to the edge. Activities are also tagged as a potential start of a path based on their constraints, constraint dates, remaining start date, and activity status. When a user enters an activity ID into the UI, it runs a shortest path calculation on the network graph between each node tagged as potential start to the entered activity id based on the float tagged on the edge. Each path returned by the algorithm contains all of the nodes on the path in order, as well as the total float of the edges that make the path. This data is then collected and returned to the user in the form of a gantt chart with groupings for each path that includes the total float for each group. 3. Similar to 2, if the user passes through a reference dataset each activity set in the path is checked to see if it had a path in the reference dataset, if that path was the primary path between the start and end activities, and what has changed regarding logic and durations. These changes are color coded and summarized before sent to the user to be displayed by the UI for simple discovery. 4. Utilizing the data from #1, the user can submit desired grouping code(s) and filters to the system. The system will then pull the activities, resources, and relationships and create a gantt chart based on the groupings sent and filtered based on the filters sent. 5. The system will produce a gantt chart in a similar method to #4, but allows interactivity with the data. As the user interacts with the gantt chart, the software captures the changes and stores it with the user making the change so that project controls and implement those changes in P6.

Fox, Ben↗

DOE OSTI2021

INTEGRATE - Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design technology can capture complex non-linear aerodynamic effects while being 100 times faster than design approaches based on computational fluid dynamics. This project enables innovation in wind turbine design by accelerating time to market through higher-accuracy early design iterations to reduce the levelized cost of energy. INVERTIBLE NEURAL NETWORKS Researchers are leveraging a specialized invertible neural network (INN) architecture along with the novel dimension-reduction methods and airfoil/blade shape representations developed by collaborators at the National Institute of Standards and Technology (NIST) learns complex relationships between airfoil or blade shapes and their associated aerodynamic and structural properties. This INN architecture will accelerate designs by providing a cost-effective alternative to current industrial aerodynamic design processes, including: - Blade element momentum (BEM) theory models: limited effectiveness for design of offshore rotors with large, flexible blades where nonlinear aerodynamic effects dominate - Direct design using computational fluid dynamics (CFD): cost-prohibitive - Inverse-design models based on deep neural networks (DNNs): attractive alternative to CFD for 2D design problems, but quickly overwhelmed by the increased number of design variables in 3D problems AUTOMATED COMPUTATIONAL FLUID DYNAMICS FOR TRAINING DATA GENERATION - MERCURY FRAMEWORK The INN is trained on data obtained using the University of Marylands (UMD) Mercury Framework, which has with robust automated mesh generation capabilities and advanced turbulence and transition models validated for wind energy applications. Mercury is a multi-mesh paradigm, heterogeneous CPU-GPU framework. The framework incorporates three flow solvers at UMD, 1) OverTURNS, a structured solver on CPUs, 2) HAMSTR, a line based unstructured solver on CPUs, and 3) GARFIELD, a structured solver on GPUs. The framework is based on Python, that is often used to wrap C or Fortran codes for interoperability with other solvers. Communication between multiple solvers is accomplished with a Topology Independent Overset Grid Assembler (TIOGA). NOVEL AIRFOIL SHAPE REPRESENTATIONS USING GRASSMAN SPACES We developed a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation as an analytic generative model, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data , (ii) improved low-dimensional parameter domain for inferential statistics informing design/manufacturing, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes. TECHNOLOGY TRANSFER DEMONSTRATION - COUPLING WITH NREL WISDEM Researchers have integrated the inverse-design tool for 2D airfoils (INN-Airfoil) into WISDEM (Wind Plant Integrated Systems Design and Engineering Model), a multidisciplinary design and optimization framework for assessing the cost of energy, as part of tech-transfer demonstration. The integration of INN-Airfoil into WISDEM allows for the design of airfoils along with the blades that meet the dynamic design constraints on cost of energy, annual energy production, and the capital costs. Through preliminary studies, researchers have shown that the coupled INN-Airfoil + WISDEM approach reduces the cost of energy by around 1% compared to the conventional design approach. This page will serve as a place to easily access all the publications from this work and the repositories for the software developed and released through this pr...

aerodynamics↗

NASA NTRS2009

An Analysis of Rocket Propulsion Testing Costs

The primary mission at NASA Stennis Space Center (SSC) is rocket propulsion testing. Such testing is generally performed within two arenas: (1) Production testing for certification and acceptance, and (2) Developmental testing for prototype or experimental purposes. The customer base consists of NASA programs, DOD programs, and commercial programs. Resources in place to perform on-site testing include both civil servants and contractor personnel, hardware and software including data acquisition and control, and 6 test stands with a total of 14 test positions/cells. For several business reasons there is the need to augment understanding of the test costs for all the various types of test campaigns. Historical propulsion test data was evaluated and analyzed in many different ways with the intent to find any correlation or statistics that could help produce more reliable and accurate cost estimates and projections. The analytical efforts included timeline trends, statistical curve fitting, average cost per test, cost per test second, test cost timeline, and test cost envelopes. Further, the analytical effort includes examining the test cost from the perspective of thrust level and test article characteristics. Some of the analytical approaches did not produce evidence strong enough for further analysis. Some other analytical approaches yield promising results and are candidates for further development and focused study. Information was organized for into its elements: a Project Profile, Test Cost Timeline, and Cost Envelope. The Project Profile is a snap shot of the project life cycle on a timeline fashion, which includes various statistical analyses. The Test Cost Timeline shows the cumulative average test cost, for each project, at each month where there was test activity. The Test Cost Envelope shows a range of cost for a given number of test(s). The supporting information upon which this study was performed came from diverse sources and thus it was necessary to build several intermediate databases in order to understand, validate, and manipulate data. These intermediate databases (validated historical account of schedule, test activity, and cost) by themselves are of great value and utility. For example, for the Project Profile, we were able to merged schedule, cost, and test activity. This kind of historical account conveys important information about sequence of events, lead time, and opportunities for improvement in future propulsion test projects. The Product Requirement Document (PRD) file is a collection of data extracted from each project PRD (technical characteristics, test requirements, and projection of cost, schedule, and test activity). This information could help expedite the development of future PRD (or equivalent document) on similar projects, and could also, when compared to the actual results, help improve projections around cost and schedule. Also, this file can be sorted by the parameter of interest to perform a visual review of potential common themes or trends. The process of searching, collecting, and validating propulsion test data encountered a lot of difficulties which then led to a set of recommendations for improvement in order to facilitate future data gathering and analysis.

Ramirez-Pagan, Carmen P.↗

DOE OSTI2023

Automated methods for scalable, parallelized enzymatic biopolymer synthesis and modification using microfluidic devices

Methods for the automated template-free synthesis of user-defined sequence controlled biopolymers using microfluidic devices are described. The methods facilitate simultaneous synthesis of up to thousands of uniquely addressed biopolymers from the controlled movement and combination of regents as fluid droplets using microfluidic and EWOD-based systems. In some forms, biopolymers including nucleic acids, peptides, carbohydrates, and lipids are synthesized from step-wise assembly of building blocks based on a user-defined sequence of droplet movements. In some forms, the methods synthesize uniquely addressed nucleic acids of up to 1,000 nucleotides in length. Methods for adding, removing and changing barcodes on biopolymers are also provided. Biopolymers synthesized according to the methods, and libraries and databases thereof are also described. Modified biopolymers, including chemically modified nucleotides and biopolymers conjugated to other molecules are described.

Banal, James↗

DOE OSTI2020

A Viable New Strategy for the Discovery of Peptide Proteolytic Cleavage Products in Plant-Microbe Interactions

Small peptides that are proteolytic cleavage products (PCPs) of less than 100 amino acids are emerging as key signaling molecules that mediate cell-to-cell communication and biological processes that occur between and within plants, fungi, and bacteria. Yet, the discovery and characterization of these molecules is largely overlooked. Today, selective enrichment and subsequent characterization by mass spectrometry–based sequencing offers the greatest potential for their comprehensive characterization, however qualitative and quantitative performance metrics are rarely captured. Herein, we addressed this need by benchmarking the performance of an enrichment strategy, optimized specifically for small PCPs, using state-of-the-art de novo–assisted peptide sequencing. As a case study, we implemented this approach to identify PCPs from different root and foliar tissues of the hybrid poplar Populus × canescens 717-1B4 in interaction with the ectomycorrhizal basidiomycete Laccaria bicolor . In total, we identified 1,660 and 2,870 Populus and L. bicolor unique PCPs, respectively. Qualitative results supported the identification of well-known PCPs, like the mature form of the photosystem II complex 5-kDa protein (approximately 3 kDa). A total of 157 PCPs were determined to be significantly more abundant in root tips with established ectomycorrhiza when compared with root tips without established ectomycorrhiza and extramatrical mycelium of L. bicolor . These PCPs mapped to 64 Populus proteins and 69 L. bicolor proteins in our database, with several of them previously implicated in biologically relevant associations between plant and fungus.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Separable shape tensors for aerodynamic design

Airfoil shape design is a classical problem in engineering and manufacturing. In this work, we combine principled physics-based considerations for the shape design problem with modern computational techniques using a data-driven approach. Modern and traditional analyses of two-dimensional (2D) and three-dimensional (3D) aerodynamic shapes reveal a flow-based sensitivity to specific deformations that can be represented generally by affine transformations (rotation, scaling, shearing, and translation). We present a novel representation of shapes that decouples affine-style deformations over a submanifold and a product submanifold principally of the Grassmannian. As an analytic generative model, the separable representation, informed by a database of physically relevant airfoils, offers: (i) a rich set of novel 2D airfoil deformations not previously captured in the data, (ii) an improved low-dimensional parameter domain for inferential statistics informing design/manufacturing, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal 2D shapes.

42 ENGINEERING↗

DOE OSTI2024

Geophysical methods reveal the soil architecture and subsurface stratigraphic heterogeneities across land-lake interfaces along Lake Erie

Abstract Purpose The land-lake interface is a unique zone where terrestrial and aquatic ecosystems meet, forming part of the Earth’s most geochemically and biologically active zones. The unique characteristics of this interface are yet to be properly understood due to the inherently high spatiotemporal variability of subsurface properties, which are difficult to capture with the traditional soil sampling methods. Geophysical methods offer non-invasive techniques to capture variabilities in soil properties at a high resolution across various spatiotemporal scales. Methods We combined electromagnetic induction (EMI), electrical resistivity tomography (ERT), and ground penetrating radar (GPR) with data from soil cores and in situ sensors to investigate hydrostratigraphic heterogeneities across land-lake interfaces along the western basin of Lake Erie. Results EMI revealed high spatial heterogeneities in ECa distribution across the land-lake interfaces, with higher values in the wetland and transition zones compared to the upland zone. Soil ECa maps matched soil maps from a public database with the hydric soil units delineated as high conductivity zones (ECa > 40 mS/m). ERT and GPR showed vertical variation in soil properties with clear stratigraphic boundaries, and correlation of ERT profiles with lithologs from piezometers revealed the stratigraphic units of silt–clay and till sequence down to 3.5 m depth which are consistent with the surficial geology of the study area. Conclusions These results validate the use of multiple geophysical methods for extrapolating soil properties and mapping stratigraphic structures at land-lake interfaces, thereby providing the missing information required to improve the earth system model (ESM) of coastal interfaces.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

P finder: genomic and metagenomic annotation of RNase P RNA gene (rnpB)

Abstract Background The rnpB gene encodes for an essential catalytic RNA (RNase P). Like other essential RNAs, RNase P’s sequence is highly variable. However, unlike other essential RNAs (i.e. tRNA, 16 S, 6 S,...) its structure is also variable with at least 5 distinct structure types observed in prokaryotes. This structural variability makes it labor intensive and challenging to create and maintain covariance models for the detection of RNase P RNA in genomic and metagenomic sequences. The lack of a facile and rapid annotation algorithm has led to the rnpB gene being the most grossly under annotated essential gene in completed prokaryotic genomes with only a 24% annotation rate. Here we describe the coupling of the largest RNase P RNA database with the local alignment scoring algorithm to create the most sensitive and rapid prokaryote rnpB gene identification and annotation algorithm to date. Results Of the 2772 completed microbial genomes downloaded from GenBank only 665 genomes had an annotated rnpB gene. We applied P Finder to these genomes and were able to identify 2733 or nearly 99% of the 2772 microbial genomes examined. From these results four new rnpB genes that encode the minimal T-type P RNase P RNAs were identified computationally for the first time. In addition, only the second C-type RNase P RNA was identified in Sphaerobacter thermophilus . Of special note, no RNase P RNAs were detected in several obligate endosymbionts of sap sucking insects suggesting a novel evolutionary adaptation. Conclusions The coupling of the largest RNase P RNA database and associated structure class identification with the P Finder algorithm is both sensitive and rapid, yielding high quality results to aid researchers annotating either genomic or metagenomic data. It is the only algorithm to date that can identify challenging RNAse P classes such as C-type and the minimal T-type RNase P RNAs. P Finder is written in C# and has a user-friendly GUI that can run on multiple 64-bit windows platforms (Windows Vista/7/8/10). P Finder is free available for download at https://github.com/JChristopherEllis/P-Finder as well as a small sample RNase P RNA file for testing.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1990

Space Station Freedom Data Assessment Study

The SSF Data Assessment Study was initiated to identify payload and operations data requirements to be supported in the Space Station era. To initiate the study payload requirements from the projected SSF user community were obtained utilizing an electronic questionnaire. The results of the questionnaire were incorporated in a personal computer compatible database used for mission scheduling and end-to-end communications analyses. This paper discusses data flow paths and associated latencies, communications bottlenecks, resource needs versus availability, payload scheduling 'warning flags' and payload data loading requirements for each major milestone in the Space Station buildup sequence. This paper also presents the statistical and analytical assessments produced using the data base, an experiment scheduling program, and a Space Station unique end-to-end simulation model. The modeling concepts and simulation methodologies presented in this paper provide a foundation for forecasting communication requirements and identifying modeling tools to be used in the SSF Tactical Operations Planning (TOP) process.

Johnson, Anngienetta R.↗

NASA NTRS2000

A calmodulin binding protein from Arabidopsis is induced by ethylene and contains a DNA-binding motif

Calmodulin (CaM), a key calcium sensor in all eukaryotes, regulates diverse cellular processes by interacting with other proteins. To isolate CaM binding proteins involved in ethylene signal transduction, we screened an expression library prepared from ethylene-treated Arabidopsis seedlings with 35S-labeled CaM. A cDNA clone, EICBP (Ethylene-Induced CaM Binding Protein), encoding a protein that interacts with activated CaM was isolated in this screening. The CaM binding domain in EICBP was mapped to the C-terminus of the protein. These results indicate that calcium, through CaM, could regulate the activity of EICBP. The EICBP is expressed in different tissues and its expression in seedlings is induced by ethylene. The EICBP contains, in addition to a CaM binding domain, several features that are typical of transcription factors. These include a DNA-binding domain at the N terminus, an acidic region at the C terminus, and nuclear localization signals. In database searches a partial cDNA (CG-1) encoding a DNA-binding motif from parsley and an ethylene up-regulated partial cDNA from tomato (ER66) showed significant similarity to EICBP. In addition, five hypothetical proteins in the Arabidopsis genome also showed a very high sequence similarity with EICBP, indicating that there are several EICBP-related proteins in Arabidopsis. The structural features of EICBP are conserved in all EICBP-related proteins in Arabidopsis, suggesting that they may constitute a new family of DNA binding proteins and are likely to be involved in modulating gene expression in the presence of ethylene.

Non-NASA Center↗

NASA NTRS2012

Highlights from a Mach 4 Experimental Demonstration of Inlet Mode Transition for Turbine-Based Combined Cycle Hypersonic Propulsion

NASA is focused on technologies for combined cycle, air-breathing propulsion systems to enable reusable launch systems for access to space. Turbine Based Combined Cycle (TBCC) propulsion systems offer specific impulse (Isp) improvements over rocket-based propulsion systems in the subsonic takeoff and return mission segments along with improved safety. Among the most critical TBCC enabling technologies are: 1) mode transition from the low speed propulsion system to the high speed propulsion system, 2) high Mach turbine engine development and 3) innovative turbine based combined cycle integration. To address these challenges, NASA initiated an experimental mode transition task including analytical methods to assess the state-of-the-art of propulsion system performance and design codes. One effort has been the Combined-Cycle Engine Large Scale Inlet Mode Transition Experiment (CCE-LIMX) which is a fully integrated TBCC propulsion system with flowpath sizing consistent with previous NASA and DoD proposed Hypersonic experimental flight test plans. This experiment was tested in the NASA GRC 10 by 10-Foot Supersonic Wind Tunnel (SWT) Facility. The goal of this activity is to address key hypersonic combined-cycle engine issues including: (1) dual integrated inlet operability and performance issues-unstart constraints, distortion constraints, bleed requirements, and controls, (2) mode-transition sequence elements caused by switching between the turbine and the ramjet/scramjet flowpaths (imposed variable geometry requirements), and (3) turbine engine transients (and associated time scales) during transition. Testing of the initial inlet and dynamic characterization phases were completed and smooth mode transition was demonstrated. A database focused on a Mach 4 transition speed with limited off-design elements was developed and will serve to guide future TBCC system studies and to validate higher level analyses.

Foster, Lancert E.↗

DOE OSTI2023

Exposing new taxonomic variation with inflammation — a murine model-specific genome database for gut microbiome researchers

The murine CBA/J mouse model widely supports immunology and enteric pathogen research. This model has illuminated Salmonella interactions with the gut microbiome since pathogen proliferation does not require disruptive pretreatment of the native microbiota, nor does it become systemic, thereby representing an analog to gastroenteritis disease progression in humans. Despite the value to broad research communities, microbiota in CBA/J mice are not represented in current murine microbiome genome catalogs. Here we present the first microbial and viral genomic catalog of the CBA/J murine gut microbiome. Using fecal microbial communities from untreated and Salmonella-infected, highly inflamed mice, we performed genomic reconstruction to determine the impacts on gut microbiome membership and functional potential. From high depth whole community sequencing (~ 42.4 Gbps/sample), we reconstructed 2281 bacterial and 4516 viral draft genomes. Salmonella challenge significantly altered gut membership in CBA/J mice, revealing 30 genera and 98 species that were conditionally rare and unsampled in non-inflamed mice. Additionally, inflamed communities were depleted in microbial genes that modulate host anti-inflammatory pathways and enriched in genes for respiratory energy generation. Our findings suggest decreases in butyrate concentrations during Salmonella infection corresponded to reductions in the relative abundance in members of the Alistipes. Strain-level comparison of CBA/J microbial genomes to prominent murine gut microbiome databases identified newly sampled lineages in this resource, while comparisons to human gut microbiomes extended the host relevance of dominant CBA/J inflammation-resistant strains. This CBA/J microbiome database provides the first genomic sampling of relevant, uncultivated microorganisms within the gut from this widely used laboratory model. Using this resource, we curated a functional, strain-resolved view on how Salmonella remodels intact murine gut communities, advancing pathobiome understanding beyond inferences from prior amplicon-based approaches. Salmonella-induced inflammation suppressed Alistipes and other dominant members, while rarer commensals like Lactobacillus and Enterococcus endure. The rare and novel species sampled across this inflammation gradient advance the utility of this microbiome resource to benefit the broad research needs of the CBA/J scientific community, and those using murine models for understanding the impact of inflammation on the gut microbiome more generally.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Genome-wide identification and functional prediction of silicon (Si) transporters in poplar (Populus trichocarpa)

Abstract Silicon (Si) enhances plant tolerance to various biotic and abiotic stressors such as salinity, drought, and heat. In addition, Si can be biomineralized within plants to form organic carbon-containing phytoliths that can have ecosystem-level consequences by contributing to long-term carbon sequestration. Si is taken up and transported in plants via different transporter proteins such as influx transporters (e.g., Lsi1, Lsi6) and efflux transporters (e.g., Lsi2). Additionally, the imported Si can be deposited in plant leaves via silicification process using the Siliplant 1 (e.g., Slp1) protein. Functional homologs of these proteins have been reported in different food crops. Here, we performed a genome-wide analysis to identify different Si transporters and Slp1 homologs in the bioenergy crop poplar ( Populus trichocarpa Torr. and A. Gray ex W. Hook). We identified one channel-type Si influx transporter (PtLsi1; Potri.017G083300), one Si efflux transporter (PtLsi2; Potri.012G144000) and two proteins like Slp1 (PtSlp1a; Potri.004G168600 and PtSlp1b; Potri.009G129900 ) in the P. trichocarpa genome. We found a unique sequence (KPKPPVFKPPPVPI) in PtSlp1a which is repeated six times. Repeated presence of this sequence in PtSlp1a indicates that this protein might be important for silicification processes in P. trichocarpa. The mutation profiles of different Si transporters in a P. trichocarpa genome-wide association study population identified significant and impactful mutations in Potri.004G168600 and Potri.009G129900 . Using a publically accessible database ( http://bar.utoronto.ca/eplant_poplar/ ), digital expression analysis of the putative Si transporters in P. trichocarpa found low to moderate expression in the anticipated tissues, such as roots and leaves. Subcellular localization analysis found that PtLsi1/PtLsi2 are localized in the plasma membrane, whereas PtSlp1a/PtSlp1b are found in the extracellular spaces. Protein–Protein interaction analysis of PtLsi1/PtLsi2 identified Delta-1-pyrroline-5-carboxylate synthase (P5CS) as one of the main interacting partners of PtLsi2, which plays a key role in proline biosynthesis. Proline is a well-known participant in biotic and abiotic stress tolerance in plants. These findings will reinforce future efforts to modify Si accumulation for enhancing plant stress tolerance and carbon sequestration in poplar.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

IMG/VR v4: an expanded database of uncultivated virus genomes within a framework of extensive functional, taxonomic, and ecological metadata

Viruses are widely recognized as critical members of all microbiomes. Metagenomics enables large-scale exploration of the global virosphere, progressively revealing the extensive genomic diversity of viruses on Earth and highlighting the myriad of ways by which viruses impact biological processes. IMG/VR provides access to the largest collection of viral sequences obtained from (meta)genomes, along with functional annotation and rich metadata. A web interface enables users to efficiently browse and search viruses based on genome features and/or sequence similarity. Here, for this work, we present the fourth version of IMG/VR, composed of >15 million virus genomes and genome fragments, a ≈6-fold increase in size compared to the previous version. These clustered into 8.7 million viral operational taxonomic units, including 231 408 with at least one high-quality representative. Viral sequences in IMG/VR are now systematically identified from genomes, metagenomes, and metatranscriptomes using a new detection approach (geNomad), and IMG standard annotation are complemented with genome quality estimation using CheckV, taxonomic classification reflecting the latest taxonomic standards, and microbial host taxonomy prediction. IMG/VR v4 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG_VR.

59 BASIC BIOLOGICAL SCIENCES↗