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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Aerodynamic Sensitivities over Separable Shape Tensors

Here, we present a comprehensive aerodynamic sensitivity analysis of airfoil parameterization informed by separable shape tensors. This parameterization approach uniquely benefits the design process by isolating various well-studied shape characteristics, such as airfoil thickness, and providing a well-regulated low-dimensional parameter domain for aerodynamic designs. Exploring the aerodynamic sensitivities of this novel parameterization can provide valuable insights for more robust designs and future manufacturing efforts. We construct a data-driven parameter space of airfoils using principal geodesic analysis of separable shape tensors informed by a curated database containing almost 20,000 suitable engineering airfoils. Analyzing the shape reconstruction error and the maximum mean discrepancy between joint distributions of aerodynamic quantities, we study the dimensionality of the learned parameter space. This simple numerical experiment demonstrates a dramatic dimension reduction that retains design effectiveness and promotes regularity of the shape representations. Finally, we generate new airfoils and use the HAM2D Reynolds-averaged Navier–Stokes solver to predict lift, drag, and moment coefficients. We compute multiple sensitivity metrics to quantify and assert the consistency of parameter influence on the aerodynamic quantities. We also explore low-dimensional polynomial ridge approximations to motivate physical intuitions and offer explanations of the approximated sensitivities.

17 WIND ENERGY↗
DOE OSTI2022

Multi-Species Complex and Standard Metabolomic Samples with Verified Truth Annotations Dataset

This dataset contains 4523251 (~6.35 GB) metabolite-spectra matches following identification with CoreMS. Data were manually curated as true positives, true negatives, or unknowns. Calculations for spectral similarity scores were carried out with two methods for a total of ~12.7 GB (6.35 * 2) of data. They are all .tsv files, though can easily be changed to .txt. The file types are: * human cerebrospinal fluid (CSF), human blood plasma human urine: already published here https://www.nature.com/articles/s41597-021-00894-y, • purchased FAMES standards • fungi species (A. niger, A. nidulans, T. reesei) • soil crust

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Modeling and simulation to investigate the electrification potential of medium- and heavy-duty vehicle fleets

This project involves developing and integrating new modeling tools to simulate the dynamics of electric medium- and heavy-duty fleet vehicle adoption. A technical and economic modeling tool, combining a data-driven hardware cost model with a cost-optimal charging strategy microsimulation, enables tailored analysis of the costs and benefits of electrifying individual fleets. Next, a novel text synthesis process, applied to a curated corpus of literature, quantifies trade-offs between technical, economic, and other factors in the fleet vehicle procurement decision. The outcomes of these tasks combine with knowledge from recent literature on fleet decision processes to specify the vehicle procurement model used by fleets in an agent-based model of the medium- and heavy-duty electric vehicle market. This model embodies an especially disaggregated approach to adoption modeling, internalizing factors and dynamics that conventional adoption models externalize. In particular, explicitly modeling the formation and diffusion of opinions among agents enables experiments that conventional models cannot support. Demonstrations show, for example, that increasing the extent of interactions between populations with different proclivities to electric vehicles has an asymmetrical outcome. High-proclivity electric vehicle adoption is generally unaffected as interactions increase, but low-proclivity adoption is accelerated. By representing individual fleets' requirements and costs at a high level of detail, incorporating an adoption decision model informed by a wide body of empirical research, and broadening the array of variables and dynamics available for experimentation, this integrated model offers a new way to understand the urgent challenge of eliminating emissions from the most emissions-intensive transportation sectors.

Trinko, David A.↗
DOE OSTI2022

Root image collection from a genotype by environment (GxE) root architecture study of the bioenergy species, Populus trichocarpa

Here we present a curated dataset; raw images of fresh roots collected from a genotype by environment (growth matrix) greenhouse root architecture study of the bioenergy species, Populus trichocarpa. Five separate experiments were performed to generate the dataset. Biological replicates (ramets, vegetative propagants) of Populus trichocarpa genotypes BESC 24 and BESC 375 were used for all experiments. The first two experiments were an eight-week and a six-week pot experiment where plants with grown in 4" X 14" sized pots were filled with Farfard 3B potting soil (Fafard Sungro #3B), and watered twice daily. Average greenhouse humidity and growth temperature were around 50-60% and 23°C, respectively. Ramets of P. trichocarpa genotypes BESC 24 and BESC 375 were used in various experiments. The source of this material was dormant field cuttings grown in greenhouse. The second experiment was a Microcosm root architecture experiment. This was done in a microcosm built with double-decker tissue culture Magenta box. Tissue culture plants with new root initials were transferred to microcosm with pro choice rapid dry growth matrix with 1x Hoagland’s solution pH5.7 and grown for six weeks until harvest. Temperature was held at ~22°C. The closed container trapped moisture. The source material was tissue culture stock plants established from shoot tips of greenhouse stock plants (obtained from same set of dormant field cuttings as rest of the study). For the remaining two experiments, greenwood stem cuttings from greenhouse grown plants were grown in six-week rhizotron and two-week hydroponics experiments in the greenhouse. For rhizotron experiments, plants were grown in 2-D rhizotron with black panels on both sides (31cm H x 30cm L x 1.2cm W) and watered daily. For hydroponics experiment, plants were grown in a 15ml falcon tube with distilled water and covered in foil and shaken a few times a day. Greenhouse temperature was held at ~ 23°C and humidity was between 50-60%. Stems were cut off and the root system was separated, gently washed to rid of matrix, immersed in a water tray and scanned for obtaining raw root images reported here. All scans of roots floating in a water tray were performed using an Epson Perfection V850 Pro Photo Scanner. Additional meta data is embedded in the raw image files.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Two-dimensional heteronuclear single quantum coherence (HSQC) NMR spectra of lignin isolated from Populus trichocarpa residues after CELF pretreatment and CBP fermentation

Here we present a curated dataset of a series of two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra of lignin isolated from a woody energy crop (Populus trichocarpa) residues after co-solvent enhanced lignocellulosic fractionation (CELF) pretreatment and consolidated bioprocessing (CBP) process. The natural poplar variant GW-9947 from the Center for Bioenergy Innovation (CBI) was used. The poplar was knife milled and passed through a 1 mm sieve. The CELF pretreatment was performed in a Parr autoclave reactor with 7.5 wt % solids loading, 0.5 wt% H2SO4 as catalyst at 150°C with 15, 25 and 30 minutes, respectively. Tetrahydrofuran was added in a 1:1 mass ratio with water as the pretreatment solvent. The residues from CELF pretreatment were then subjected to CBP using the bacterium C. thermocellum DSM 1313. CBP fermentations were performed at 60 °C in a shaker at 50 grams/L solids loadings. Lignin was isolated from the pretreated samples after ball-milling in a porcelain jar with ceramic balls via Retsch PM 200 at 580 rpm for 2.5 h followed by enzymatic hydrolysis in acetate buffer (pH 4.8, 50 °C) for 48 h. The lignin samples were characterized using 13C–1H HSQC experiments which were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus. A standard Bruker pulse sequence was used on a Prodigy platform cryoprobe. The dry lignin samples were dissolved in deuterated dimethylsulfoxide for HSQC experiments. The spectra were acquired under the following acquisition conditions: 210 ppm spectral width in F1 (13C) dimension with 256 data points and 11 ppm spectral width in F2 (1H) dimension with 1024 data points, a 90° pulse, a one bond C–H coupling constant of 145 Hz, a 1.0 s pulse delay, and 64 scans. All the data was processed using the TopSpin 3.6 software (Bruker BioSpin). The NMR spectra provides structural characteristics information about lignin remaining in solids after CELF (150 °C with 15, 25 and 30 minutes) process and C. thermocellum CBP.

Lignin structure, HSQC, poplar, CELF, CBP, CBI↗
DOE OSTI2024

Two-dimensional heteronuclear single quantum coherence (HSQC) NMR spectra of lignin isolated from field grown transgenic poplar

Here we present a curated dataset of a series of two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra of lignin isolated from a field grown transgenic poplar engineered with a monolignol 4-O-methyltransferase (MOMT4). The poplar was collected from a 2-year-old rotation trees within a three-year field trial experiment. The poplar was Soxhlet-extracted with toluene/ethanol and the extractives-free poplar was then ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h (in 5 min on and 5 min off cycles to avoid excessive sample heating). The ball-milled materials were then subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was extracted twice with 96:4 (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover the lignin. The dry lignin samples were dissolved in deuterated dimethyl sulfoxide for NMR experiments. 13C–1H HSQC experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence (hsqcetgpsisp2.2) on a Prodigy platform cryoprobe. The NMR spectra were acquired under the following acquisition conditions: 220 ppm spectral width in F1 (13C) dimension with 256 data points and 12 ppm spectral width in F2 (1H) dimension with 1024 data points, a 90° pulse, a one bond C–H coupling constant of 145 Hz, a 1.0 s pulse delay, and 64 scans. All the data was processed using the Bruker’s TopSpin 3.6 software. The NMR spectra provides structural characteristics information about lignin in field grown transgenic MOMT4 poplar. Additional meta data is embedded in the raw spectra figures.

Lignin structure, HSQC, poplar, field trial, MOMT4↗
DOE OSTI2024

Carbon-13 NMR spectra of lignin isolated from field grown transgenic poplar

Here we present a curated dataset of a series of 13C nuclear magnetic resonance (NMR) spectra of lignin isolated from transgenic monolignol 4-O-methyltransferase (MOMT4) engineered poplar. The transgenic poplar was collected from a 3-year field trial experiment. The poplar was Soxhlet-extracted with toluene/ethanol and the extractives-free poplar was then ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h. The ball-milled materials were then subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was extracted twice with 96:4 (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover the lignin. The dry lignin samples were dissolved in deuterated dimethyl sulfoxide for NMR characterization. 13C experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence (zgpg) on a Prodigy platform cryoprobe. The NMR spectra were acquired under the following conditions: spectra width 229 ppm, 64k data points, 1s pulse delay, and 6k scans. All the data was processed using the Bruker’s TopSpin 3.6 software. Additional meta data is embedded in the raw spectra files.

13C NMR, lignin, poplar, field trial, MOMT4, CBI↗
DOE OSTI2024

Cellulose crystallinity index (CrI) of switchgrass measured by solid-state NMR

Here we present a curated dataset of switchgrass cellulose crystallinity index (CrI) measured using solid state nuclear magnetic resonance (NMR) spectroscopy. Seventy-two topline switchgrass lines grown in greenhouse were collected and ground to -20/+80 mesh. The switchgrass was then Soxhlet-extracted with toluene/ethanol for 24 h to remove extractives. The extractives-free switchgrass was holopulped by using peracetic acid at 5 g loading per g biomass and the solution consistency was adjusted to 5% with DI water. Holopulping was conducted at room temperature for 24 h with stirring. The obtained holocellulose was washed excessively with DI water and air-dried at room temperature for 24 h. The dried holocellulose was treated with hydrochloric acid (2.5 M) for 2 h to remove hemicellulose. The isolated cellulose was collected by filtration, rinsed with DI water, and used to analyze cellulose crystallinity by solid-state NMR. The NMR samples were prepared by packing the moisturized cellulose into 4-mm cylindrical Zirconia MAS rotors. Cross polarization/magic angle spinning (CP/MAS) NMR analysis of cellulose was carried out on a Bruker Avance III 400-MHz spectrometer operating at 100.59 MHz for 13C in a Bruker double-resonance MAS probe head at spinning speeds of 8 kHz. The CP/MAS experiments utilized a 5 ms (90°) proton pulse, 1.5 ms contact pulse, 4 s recycle delay and 4000 scans. The cellulose crystallinity index was determined from the areas of the cellulose crystalline C4 signal (δ 86-92 ppm) over the entire C4 regions (δ 79-92 ppm) in the NMR spectra.

Cellulose, crystallinity index, switchgrass, solid↗
DOE OSTI2024

Proton NMR spectra of lignin isolated from field grown transgenic poplar

Here we present a curated dataset of a series of 1H nuclear magnetic resonance (NMR) spectra of lignin isolated from transgenic monolignol 4-O-methyltransferase (MOMT4) engineered poplar. The transgenic poplar was collected from a 2-year-old rotation trees within a three-year field trial experiment. Two replicates were collected for each transgenic poplar for the 1H NMR analysis. The poplar samples were Soxhlet-extracted with toluene/ethanol to remove the extractives and the extractives-free poplar was then ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h. The ball-milled materials were subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was extracted twice with 96:4 (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover lignin. The dry lignin samples were dissolved in deuterated dimethyl sulfoxide and transferred into a 5 mm NMR tube. 1H NMR experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence (zg) on a Prodigy platform cryoprobe. The NMR spectra were acquired with 16 ppm spectra width, 32k data points, 3s pulse delay, and 16 scans. All the data was processed using the Bruker’s TopSpin 3.6 software. Additional meta data is embedded in the raw spectra files.

1H NMR, lignin, poplar, field trial, MOMT4, CBI↗
DOE OSTI2024

Heteronuclear single quantum coherence (HSQC) NMR spectra of lignin isolated from switchgrass residues after fermentation with milling

Here we present a curated dataset of two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra of lignin isolated from a herbaceous energy crop (Panicum virgatum L.). The lowland variant “Timber” switchgrass from Ernst seeds was used. The switchgrass was knife milled and passed through a 2 mm sieve prior to consolidated bioprocessing (CBP) process. Switchgrass was suspended in Milli-Q water and autoclaved for 90 min on liquid cycles. The residues after autoclaving were then subjected to CBP using coculture of Clostridium thermocellum (C. thermocellum DSM 1313 (LL1004)) and Thermoanaerobacterium thermosaccarolyticum ( T. thermosaccharolyticum HG-8 ATCC 31960 (LL1244)). Once-fermented and twice-fermented (FF) switchgrass were subjected to ball and disc milling in bioreactors at 55 °C and 60, 48 grams/L solids loadings for primary and secondary fermentation respectively. When fermentations were completed, the residual solids were rinsed with milli-Q water. Lignin was isolated from the pretreated residues after ball-milling in a porcelain jar with ceramic balls via Retsch PM 200 at 600 rpm for 2 h followed by enzymatic hydrolysis in acetate buffer (pH 4.8, 50 °C) for 48 h. The dry lignin samples were dissolved in deuterated dimethyl sulfoxide (d6) and characterized using 13C–1H HSQC in a Bruker Avance III HD 500-MHz NMR spectrometer. A standard Bruker pulse sequence (hsqcetgpsisp.2) was used on a Prodigy platform cryoprobe. The spectra were acquired with the following acquisition conditions: 230 ppm spectral width in F1 (13C) dimension with 256 data points and 12 ppm spectral width in F2 (1H) dimension with 2048 data points, a 90° pulse, with a C–H coupling constant of 145 Hz, a 1.0 s pulse delay, and 64 scans. Spectra were processed using the Bruker TopSpin 3.6 software.

Lignin, HSQC, Switchgrass, CBP , Ball mill, Disc m↗
DOE OSTI2024

HSQC spectra of lignin isolated from poplar stems

Here we present a curated dataset of two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra of lignin isolated from stems of genetically engineered poplar through auxin signaling gene modification. The plants were grown in greenhouse with temperatures between 21 and 23 °C. Plants were harvested and the aboveground stems were cut off an approximately five-inch-long segment from the bottom end of the plant stem, debarked and air-dried for three weeks. The dried stem samples were Wiley milled (mesh size 20), Soxhlet-extracted with toluene/ethanol for 24 h to remove extractives. The extracted biomass was ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h (in 5 min on and 5 min off cycles to avoid excessive sample heating). The ball-milled materials were then subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was freeze-dried to recover the lignin. The dry stem lignin samples were dissolved in deuterated dimethyl sulfoxide (d6) and transferred into a 5 mm tube. 13C–1H HSQC experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence on a Prodigy platform cryoprobe. The NMR spectra were acquired under the following acquisition conditions: 230 ppm spectral width in F1 (13C) dimension with 256 data points and 12 ppm spectral width in F2 (1H) dimension with 2048 data points, a 90° pulse, a one bond C–H coupling constant of 145 Hz, a 1.0 s pulse delay, and 64 scans. Spectra were processed using the Bruker TopSpin 3.6 software. Additional meta data is embedded in the raw spectra figures.

HSQC, lignin, poplar, stems, CBI↗
DOE OSTI2024

HSQC spectra of lignin isolated from poplar roots

Here we present a curated dataset of two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra of lignin isolated from roots of a greenhouse grown natural population of an energy crop poplar (Populus trichocarpa). Dormant cuttings of field-grown poplar were grown in 6-liter pots in a peat-based media containing bark, perlite, vermiculite, dolomite lime and a wetting agent in an environmentally controlled greenhouse. Temperatures were between 21 and 23 °C, with supplemental lighting to support a 16-h day length using 1000-watt high-pressure sodium lights in greenhouse. Once established, all plants were cut-back, allowed to regrow and harvested at the same time following an eight-month long growth period. Plants were harvested and the belowground roots were washed off soils, blotted, dried in an oven at 70 °C for 3 days, and Wiley milled (mesh size 20). The roots were Soxhlet-extracted with toluene/ethanol for 24 h to remove extractives. The extracted roots were ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h (in 5 min on and 5 min off cycles to avoid excessive sample heating). The ball-milled materials were then subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was extracted twice with 96% (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover lignin. The dry lignin samples were dissolved in deuterated dimethyl sulfoxide (d6) and transferred into a 5 mm tube. 13C–1H HSQC experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence on a Prodigy platform cryoprobe. The NMR spectra were acquired under the following acquisition conditions: 220 ppm spectral width in F1 (13C) dimension with 256 data points and 12 ppm spectral width in F2 (1H) dimension with 1024 data points, a 90° pulse, a one bond C–H coupling constant of 145 Hz, a 1.0 s pulse delay, and 64 scans. Spectra were processed using the Bruker TopSpin software. Additional meta data is embedded in the raw spectra figures.

HSQC, lignin, poplar, roots, CBI↗
DOE OSTI2026

Hyaloscypha finlandica Metabolome Repository

This repository provides the curated data tables, manuscript figure and table exports, dependency records, and workflow scripts supporting an integrated comparative genomics and untargeted LC-MS/MS metabolomics analysis of Hyaloscypha finlandica strain PMI 746, a root-associated dark septate endophyte of poplar. The repository includes genome-mining summaries from antiSMASH, FunBGCeX, BGC-Prophet, and BiG-SCAPE; processed metabolomics inputs; metabolite annotation evidence; statistical outputs; and publication-facing figures and tables. Raw LC-MS/MS spectra, full genome/protein downloads, and large generated tool outputs are referenced through public archive/accession records and are not stored in Git.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Multi-scale models of whole cells: progress and challenges

Whole-cell modeling is “the ultimate goal” of computational systems biology and “a grand challenge for 21st century”. These complex, highly detailed models account for the activity of every molecule in a cell and serve as comprehensive knowledgebases for the modeled system. Their scope and utility far surpass those of other systems models. In fact, whole-cell models (WCMs) are an amalgam of several types of “system” models. The models are simulated using a hybrid modeling method where the appropriate mathematical methods for each biological process are used to simulate their behavior. Given the complexity of the models, the process of developing and curating these models is labor-intensive and to date only a handful of these models have been developed. While whole-cell models provide valuable and novel biological insights, and to date have identified some novel biological phenomena, their most important contribution has been to highlight the discrepancy between available data and observations that are used for the parametrization and validation of complex biological models. Another realization has been that current whole-cell modeling simulators are slow and to run models that mimic more complex (e.g., multi-cellular) biosystems, those need to be executed in an accelerated fashion on high-performance computing platforms. In this manuscript, we review the progress of whole-cell modeling to date and discuss some of the ways that they can be improved.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Multiple Cases of Bacterial Sequence Erroneously Incorporated Into Publicly Available Chloroplast Genomes

Public sequencing databases are invaluable resources to biological researchers, but assessing data veracity as well as the curation and maintenance of such large collections of data can be challenging. Genomes of eukaryotic organelles, such as chloroplasts and other plastids, are particularly susceptible to assembly errors and misrepresentations in these databases due to their close evolutionary relationships with bacteria, which may co-occur within the same environment, as can be the case when sequencing plants. Here, based on sequence similarities with bacterial genomes, we identified several suspicious chloroplast assemblies present in the National Institutes of Health (NIH) Reference Sequence (RefSeq) collection. Investigations into these chloroplast assemblies reveal examples of erroneous integration of bacterial sequences into chloroplast ribosomal RNA (rRNA) loci, often within the rRNA genes, presumably due to the high similarity between plastid and bacterial rRNAs. The bacterial lineages identified within the examined chloroplasts as the most likely source of contamination are either known associates of plants, or co-occur in the same environmental niches as the examined plants. Modifications to the methods used to process untargeted ‘raw’ shotgun sequencing data from whole genome sequencing efforts, such as the identification and removal of bacterial reads prior to plastome assembly, could eliminate similar errors in the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗
DOE OSTI2022

A Path-Based Analysis of Infected Cell Line and COVID-19 Patient Transcriptome Reveals Novel Potential Targets and Drugs Against SARS-CoV-2

Most transcriptomic studies of SARS-CoV-2 infection have focused on differentially expressed genes, which do not necessarily reveal the genes mediating the transcriptomic changes. In contrast, exploiting curated biological network, our PathExt tool identifies central genes from the differentially active paths mediating global transcriptomic response. Here we apply PathExt to multiple cell line infection models of SARS-CoV-2 and other viruses, as well as to COVID-19 patient-derived PBMCs. The central genes mediating SARS-CoV-2 response in cell lines were uniquely enriched for ATP metabolic process, G1/S transition, leukocyte activation and migration. In contrast, PBMC response reveals dysregulated cell-cycle processes. In PBMC, the most frequently central genes are associated with COVID-19 severity. Importantly, relative to differential genes, PathExt-identified genes show greater concordance with several benchmark anti-COVID-19 target gene sets. We propose six novel anti-SARS-CoV-2 targets ADCY2, ADSL, OCRL, TIAM1, PBK, and BUB1, and potential drugs targeting these genes, such as Bemcentinib, Phthalocyanine, and Conivaptan.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions

The development of effective vaccines is crucial for combating current and emerging pathogens. Despite significant advances in the field of vaccine development there remain numerous challenges including the lack of standardized data reporting and curation practices, making it difficult to determine correlates of protection from experimental and clinical studies. Significant gaps in data and knowledge integration can hinder vaccine development which relies on a comprehensive understanding of the interplay between pathogens and the host immune system. In this review, we explore the current landscape of vaccine development, highlighting the computational challenges, limitations, and opportunities associated with integrating diverse data types for leveraging artificial intelligence (AI) and machine learning (ML) techniques in vaccine design. We discuss the role of natural language processing, semantic integration, and causal inference in extracting valuable insights from published literature and unstructured data sources, as well as the computational modeling of immune responses. Furthermore, we highlight specific challenges associated with uncertainty quantification in vaccine development and emphasize the importance of establishing standardized data formats and ontologies to facilitate the integration and analysis of heterogeneous data. Through data harmonization and integration, the development of safe and effective vaccines can be accelerated to improve public health outcomes. Looking to the future, we highlight the need for collaborative efforts among researchers, data scientists, and public health experts to realize the full potential of AI-assisted vaccine design and streamline the vaccine development process.

60 APPLIED LIFE SCIENCES↗