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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 37 records · Page 2

Improved Microbial Community Characterization of 16S rRNA via Metagenome Hybridization Capture Enrichment

Environmental microbial diversity is often investigated from a molecular perspective using 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics. While amplicon methods are fast, low-cost, and have curated reference databases, they can suffer from amplification bias and are limited in genomic scope. In contrast, shotgun metagenomic methods sample more genomic regions with fewer sequence acquisition biases, but are much more expensive (even with moderate sequencing depth) and computationally challenging. Here, we develop a set of 16S rRNA sequence capture baits that offer a potential middle ground with the advantages from both approaches for investigating microbial communities. These baits cover the diversity of all 16S rRNA sequences available in the Greengenes (v. 13.5) database, with no sequence having <78% sequence identity to at least one bait for all segments of 16S. The use of our baits provide comparable results to 16S amplicon libraries and shotgun metagenomic libraries when assigning taxonomic units from 16S sequences within the metagenomic reads. We demonstrate that 16S rRNA capture baits can be used on a range of microbial samples (i.e., mock communities and rodent fecal samples) to increase the proportion of 16S rRNA sequences (average > 400-fold) and decrease analysis time to obtain consistent community assessments. Furthermore, our study reveals that bioinformatic methods used to analyze sequencing data may have a greater influence on estimates of community composition than library preparation method used, likely due in part to the extent and curation of the reference databases considered. Thus, enriching existing aliquots of shotgun metagenomic libraries and obtaining modest numbers of reads from them offers an efficient orthogonal method for assessment of bacterial community composition.

59 BASIC BIOLOGICAL SCIENCES↗

Bidirectional titration of yeast gene expression using a pooled CRISPR guide RNA approach

Most classic genetic approaches utilize binary modifications that preclude the identification of key knockdowns for essential genes or other targets that only require moderate modulation. As a complementary approach to these classic genetic methods, we describe a plasmid-based library methodology that affords bidirectional, graded modulation of gene expression enabled by tiling the promoter regions of all 969 genes that comprise the ito977 model of Saccharomyces cerevisiae’s metabolic network. When coupled with a CRISPR-dCas9–based modulation and next-generation sequencing, this method affords a library-based, bidirection titration of gene expression across all major metabolic genes. We utilized this approach in two case studies: growth enrichment on alternative sugars, glycerol and galactose, and chemical overproduction of betaxanthins, leading to the identification of unique gene targets. In particular, we identify essential genes and other targets that were missed by classic genetic approaches.

59 BASIC BIOLOGICAL SCIENCES↗

Transforming Science Through Software: Improving While Delivering 100×

The U.S. Department of Energy (DOE) Exascale Computing Project (ECP) funded the development of new (and the transformation of important existing) applications, libraries, and tools that realized improvement in performance and capabilities of often 100 times or more on emerging exascale computers. This exceptional gain inspired the title of this special issue: Transforming Science through Software: Improving while delivering 100X. The term 100X refers to advancing capabilities in modeling, simulation, and analysis by a factor of 100 or more using some combination of new algorithms, optimization techniques, software libraries, and programming models, coupled with the next generation of hardware for high-performance computing (HPC). The papers in this issue share experiences with the practice and science of scientific software development, with an emphasis on developing a coherent, portable, and sustainable HPC software ecosystem for next-generation computational science. Finally, we hope to foster expanded community efforts related to the fundamental role of sustainable scientific software ecosystems in advancing the computing sciences.

97 MATHEMATICS AND COMPUTING↗

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↗

NASA Vision

Contents include the following: Administrator O'Keefe addresses NASA's return to flight. New independent engineering and safety center. Around the centers. NASA and your library: local libraries making room for space. Robonaut: the next generation. Inspiring the next generation ... of Hispanics. NASA and teachers focus on parks. GSFC director gives keynote address. Agency honor awards. Summer interns join the NASA team. Catching a comet's tail in Earth's atmosphere.

Fenton, Mary↗

A universal implementation of radiative effects in neutrino event generators

Due to the similarities between electron-nucleus (eA) and neutrino-nucleus scattering (νA), eA data can contribute key information to improve cross-section modeling in eA and hence in νA event generators. However, to compare data and generated events, either the data must be radiatively corrected or radiative effects need to be included in the event generators. We implemented a universal radiative corrections program that can be used with all reaction mechanisms and any eA event generator. Our program includes real photon radiation by the incident and scattered electrons, and virtual photon exchange and photon vacuum polarization diagrams. It uses the “extended peaking” approximation for electron radiation and neglects charged hadron radiation. This method, validated with GENIE, can also be extended to simulate νA radiative effects. This work facilitates data-event-generator comparisons used to improve νA event generators for the next-generation of neutrino experiments. Program Title: emMCRadCorr CPC Library link to program files:https://doi.org/10.17632/hmsxg82vnf.1 Developer's repository link:https://github.com/e4nu/emMCRadCorr Licensing provisions: AGPLv3 Programming language:C++ Nature of problem: Radiative effects can significantly modify the event kinematics and the resulting cross-sections. Such effects must be accounted for when comparing event generators to eA data. Existing radiative correction codes are tailored to specific processes and topologies, and are limited to a restricted phase space defined by the spectrometer acceptance. Therefore, a more general approach is required to apply radiative corrections to semi-inclusive and exclusive eA measurements. Solution method: Our program incorporates real photon radiation from both the incident and scattered electrons, as well as virtual photon exchange and photon vacuum polarization effects. It employs the “extended peaking” approximation for electron radiation while neglecting contributions from charged hadron radiation. The code is fully decoupled from event generator codes and can be used for all event generators in the market.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Virtual Test Bed (VTB) repository: a library of multiphysics reference reactor models using NEAMS tools

With the next generation of nuclear reactors under development, modeling and simulation (MS) tools are being developed by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in order to support their design, licensing, and future operation. Mirroring the physical test beds currently under construction (i.e., EBR-II and ZPPR), the Virtual Test Bed (VTB) was launched by the National Reactor Innovation Center (NRIC) in collaboration with NEAMS to support the advanced reactor community. This collaborative effort, which involves multiple teams at both Idaho National Laboratory and Argonne National Laboratory aims to use NEAMS tools to model a wide range of reactor designs. Those models are automatically tested to ensure their continued functionality as the tools are further developed. Examples are extensively documented, each acting as a tutorial for applying the relevant NEAMS tools to that reactor design. Currently, five advanced reactor types (with a total of eight specific design variants) are simulated by a variety of different models. These models range from steady-state, core multiphysics simulations to integrated plant analysis during loss-of flow transients. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

The Virtual Test Bed (VTB) Repository: A Library of Multiphysics Reference Reactor Models using NEAMS Tools

With the next generation of nuclear reactors under development, modeling and simulation (M&S) tools are being developed by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program in order to support their design, licensing, and future operation. Mirroring the physical test beds currently under construction (i.e., EBR-II and ZPPR), the Virtual Test Bed (VTB) was launched by the National Reactor Innovation Center (NRIC) in collaboration with NEAMS to support the advanced reactor community. This collaborative effort, which involves multiple teams at both Idaho National Laboratory and Argonne National Laboratory aims to use NEAMS tools to model a wide range of reactor designs. Those models are automatically tested to ensure their continued functionality as the tools are further developed. Examples are extensively documented, each acting as a tutorial for applying the relevant NEAMS tools to that reactor design. Currently, five advanced reactor types (with a total of eight specific design variants) are simulated by a variety of different models. These models range from steady-state, core multiphysics simulations to integrated plant analysis during loss-of-flow transients.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Standardized Sky Partitioning for the Next Generation Astronomy and Space Science Archives

The Johns Hopkins University and Space Telescope Science Institute are working together on this project to develop a library of standard software for data archives that will benefit the wider astronomical community. The ultimate goal was to develop and distribute a software library aimed at providing a common system for partitioning and indexing the sky in manageable sized regions and provide complex queries on the objects stored in this system. Whilst ongoing maintenance work will continue the primary goal has been completed. Most of the next generation sky surveys in the different wavelengths like 2MASS, GALEX, SDSS, GSC-II, DPOSS and FIRST have agreed on this common set of utilities. In this final report, we summarize work on the work elements assigned to the STScI project team.

Lal, Nand↗

Auralization Architectures for NASA?s Next Generation Aircraft Noise Prediction Program

Aircraft community noise is a significant concern due to continued growth in air traffic, increasingly stringent environmental goals, and operational limitations imposed by airport authorities. The assessment of human response to noise from future aircraft can only be afforded through laboratory testing using simulated flyover noise. Recent work by the authors demonstrated the ability to auralize predicted flyover noise for a state-of-the-art reference aircraft and a future hybrid wing body aircraft concept. This auralization used source noise predictions from NASA's Aircraft NOise Prediction Program (ANOPP) as input. The results from this process demonstrated that auralization based upon system noise predictions is consistent with, and complementary to, system noise predictions alone. To further develop and validate the auralization process, improvements to the interfaces between the synthesis capability and the system noise tools are required. This paper describes the key elements required for accurate noise synthesis and introduces auralization architectures for use with the next-generation ANOPP (ANOPP2). The architectures are built around a new auralization library and its associated Application Programming Interface (API) that utilize ANOPP2 APIs to access data required for auralization. The architectures are designed to make the process of auralizing flyover noise a common element of system noise prediction.

Rizzi, Stephen A.↗

Optimizing Single Nuclei Sequencing of Brain Samples From Space Flown Mice Across Age and Strain

The NASA GeneLab Sample Processing Laboratory offers high-throughput sequencing services to NASA-funded space biology researchers. Space biology studies have specific challenges such as low sample numbers, introducing susceptibility to batch effects from sample handling. These issues are compounded by complex protocols such as single-nuclei isolation and sequencing, which has recently become an attractive methodology for assessing the cellular diversity within spaceflight samples. High quality single-nuclei sequencing requires reproducible protocols to dissociate tissue and generate clean suspension of intact single nuclei. Producing single-nuclei suspension from brain tissue is particularly challenging due to cell type heterogeneity and the myelin sheath that carries over into the nuclei suspension as debris. Current procedures tend to be time consuming and sometimes include steps that can alter gene expression and create cell-type bias. Commercially available nuclei isolation kits, such as the 10X Genomics nuclei isolation kit, offers a streamlined way to process samples for nuclei isolation, thereby minimizing batch effects and enabling reproducibility. In this study, we report on the performance of the 10X Genomics nuclei isolation kit and Chromium Next GEM Single Cell Multiome ATAC + Gene Expression kit to generate sequencing libraries from space-flown mouse brain samples. Single nuclei sequencing was performed on frozen mouse brain tissue from two spaceflight missions, Rodent Research-10 (RR-10) and RR Reference Mission-2 (RRRM-2). RR-10 mice were female B6129SF2/J, euthanized at 18-19 weeks whereas RRRM-2 mice were female C57BL/6NTac, euthanized at 20 or 37 weeks. Sequencing data was processed using standard GeneLab data processing pipelines. We report evaluation of the performance of the 10X Genomics nuclei isolation kit for spaceflight samples from mouse brain, and evaluation of reproducibility across different mouse strains and age groups. We also report preliminary scientific results including cell type inference, cell clustering, and differentially expressed genes and pathways between spaceflight and ground control samples.

RR-10↗

Discovery of photosynthesis genes through whole-genome sequencing of acetate-requiring mutants of Chlamydomonas reinhardtii

Large-scale mutant libraries have been indispensable for genetic studies, and the development of next-generation genome sequencing technologies has greatly advanced efforts to analyze mutants. In this work, we sequenced the genomes of 660 Chlamydomonas reinhardtii acetate-requiring mutants, part of a larger photosynthesis mutant collection previously generated by insertional mutagenesis with a linearized plasmid. We identified 554 insertion events from 509 mutants by mapping the plasmid insertion sites through paired-end sequences, in which one end aligned to the plasmid and the other to a chromosomal location. Nearly all (96%) of the events were associated with deletions, duplications, or more complex rearrangements of genomic DNA at the sites of plasmid insertion, and together with deletions that were unassociated with a plasmid insertion, 1470 genes were identified to be affected. Functional annotations of these genes were enriched in those related to photosynthesis, signaling, and tetrapyrrole synthesis as would be expected from a library enriched for photosynthesis mutants. Systematic manual analysis of the disrupted genes for each mutant generated a list of 253 higher-confidence candidate photosynthesis genes, and we experimentally validated two genes that are essential for photoautotrophic growth, CrLPA3 and CrPSBP4 . The inventory of candidate genes includes 53 genes from a phylogenomically defined set of conserved genes in green algae and plants. Altogether, 70 candidate genes encode proteins with previously characterized functions in photosynthesis in Chlamydomonas , land plants, and/or cyanobacteria; 14 genes encode proteins previously shown to have functions unrelated to photosynthesis. Among the remaining 169 uncharacterized genes, 38 genes encode proteins without any functional annotation, signifying that our results connect a function related to photosynthesis to these previously unknown proteins. This mutant library, with genome sequences that reveal the molecular extent of the chromosomal lesions and resulting higher-confidence candidate genes, will aid in advancing gene discovery and protein functional analysis in photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗

Next-generation sequencing dataset of genome-scale CRISPRi in Synechococcus sp. PCC 7002 across seven conditions

A 33,298-member sgRNA library developed for Synechococus sp. PCC 7002 was screened with two replicates across seven growth conditions and sequenced with Illumina NextSeq (paired end, 2x150 bp) for a total of ~700M reads. The original plasmid library and the library after transformation into a dCas9-containing and dCas9-absent strain were also sequenced as a reference for initial sgRNA abundance.

genome- wide screens environmental acclimation spe↗

acCRISPR: an activity-correction method for improving the accuracy of CRISPR screens

Abstract High throughput CRISPR screens are revolutionizing the way scientists unravel the genetic underpinnings of engineered and evolved phenotypes. One of the critical challenges in accurately assessing screening outcomes is accounting for the variability in sgRNA cutting efficiency. Poorly active guides targeting genes essential to screening conditions obscure the growth defects that are expected from disrupting them. Here, we develop acCRISPR, an end-to-end pipeline that identifies essential genes in pooled CRISPR screens using sgRNA read counts obtained from next-generation sequencing. acCRISPR uses experimentally determined cutting efficiencies for each guide in the library to provide an activity correction to the screening outcomes via calculation of an optimization metric, thus determining the fitness effect of disrupted genes. CRISPR-Cas9 and -Cas12a screens were carried out in the non-conventional oleaginous yeast Yarrowia lipolytica and acCRISPR was used to determine a high-confidence set of essential genes for growth under glucose, a common carbon source used for the industrial production of oleochemicals. acCRISPR was also used in screens quantifying relative cellular fitness under high salt conditions to identify genes that were related to salt tolerance. Collectively, this work presents an experimental-computational framework for CRISPR-based functional genomics studies that may be expanded to other non-conventional organisms of interest.

59 BASIC BIOLOGICAL SCIENCES↗

Large Format Multifunction 2-Terabyte Optical Disk Storage System

The Kodak Digital Science OD System 2000E automated disk library (ADL) base module and write-once drive are being developed as the next generation commercial product to the currently available System 2000 ADL. Under government sponsorship with the Air Force's Rome Laboratory, Kodak is developing magneto-optic (M-O) subsystems compatible with the Kodak Digital Science ODW25 drive architecture, which will result in a multifunction (MF) drive capable of reading and writing 25 gigabyte (GB) WORM media and 15 GB erasable media. In an OD system 2000 E ADL configuration with 4 MF drives and 100 total disks with a 50% ration of WORM and M-O media, 2.0 terabytes (TB) of versatile near line mass storage is available.

Kaiser, David R.↗

A high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations

The development of next-generation sequencing (NGS) enabled a shift from array-based genotyping to directly sequencing genomic libraries for high-throughput genotyping. Even though whole-genome sequencing was initially too costly for routine analysis in large populations such as breeding or genetic studies, continued advancements in genome sequencing and bioinformatics have provided the opportunity to capitalize on whole-genome information. As new sequencing platforms can routinely provide high-quality sequencing data for sufficient genome coverage to genotype various breeding populations, a limitation comes in the time and cost of library construction when multiplexing a large number of samples. Here we describe a high-throughput whole-genome skim-sequencing (skim-seq) approach that can be utilized for a broad range of genotyping and genomic characterization. Using optimized low-volume Illumina Nextera chemistry, we developed a skim-seq method and combined up to 960 samples in one multiplex library using dual index barcoding. With the dual-index barcoding, the number of samples for multiplexing can be adjusted depending on the amount of data required, and could be extended to 3,072 samples or more. Panels of doubled haploid wheat lines ( Triticum aestivum , CDC Stanley x CDC Landmark), wheat-barley ( T . aestivum x Hordeum vulgare ) and wheat-wheatgrass ( Triticum durum x Thinopyrum intermedium ) introgression lines as well as known monosomic wheat stocks were genotyped using the skim-seq approach. Bioinformatics pipelines were developed for various applications where sequencing coverage ranged from 1 × down to 0.01 × per sample. Using reference genomes, we detected chromosome dosage, identified aneuploidy, and karyotyped introgression lines from the skim-seq data. Leveraging the recent advancements in genome sequencing, skim-seq provides an effective and low-cost tool for routine genotyping and genetic analysis, which can track and identify introgressions and genomic regions of interest in genetics research and applied breeding programs.

60 APPLIED LIFE SCIENCES↗

Non-target RNA depletion strategy to improve sensitivity of next-generation sequencing for the detection of RNA viruses in poultry

PCR-based assays have become the benchmark for detecting pathogens of poultry and other livestock; however, these techniques are limited in their ability to detect multiple infecting agents, provide limited genetic information on the pathogen, and, for RNA viruses, must be reviewed frequently to assure high sensitivity and specificity. In contrast, untargeted, high-throughput sequencing can rapidly detect all infecting agents in a sample while providing genomic sequence information to allow more in-depth characterization of viruses. Although next-generation sequencing (NGS) offers many advantages, one of its primary limitations is low sensitivity to pathogens given the abundance of host and other non-target sequences in sequencing libraries. We explored methods for improving the sensitivity of NGS to detect respiratory and enteric viruses in poultry from RNA extracts of swab samples. We employed commercial and custom-designed negative enrichment strategies to selectively deplete the most abundant rRNA reads from the host and non-target bacteria; host RNA was diminished from up to 40% of total reads to as low as 3%, and the total number of reads assigned to abundant bacterial classes were reduced greatly. Our treatment resulted in up to a 700-fold increase in the number of viral reads, detection of a greater number of viral agents, and higher average genome coverage for pathogens. Depletion assays added only 2 h to the NGS library preparation workflow. Custom depletion probe design offered significant cost savings (US$7–12 per sample) compared to commercial kits (US$30–50 per sample).

Parris, D. Joshua↗

The IDAES process modeling framework and model library—Flexibility for process simulation and optimization

Abstract Energy systems and manufacturing processes of the 21st century are becoming increasingly dynamic and interconnected, which require new capabilities to effectively model and optimize their design and operations. Such next generation computational tools must leverage state‐of‐the‐art techniques in optimization and be able to rapidly incorporate new advances. To address these requirements, we have developed the Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform, which builds on the strengths of both process simulators (model libraries) and algebraic modeling languages (advanced solvers). This paper specifically presents the IDAES Core Modeling Framework (IDAES‐CMF), along with a case study demonstrating the application of the framework to solve process optimization problems. Capabilities provided by this framework include a flexible, modifiable, open‐source platform for optimization of process flowsheets utilizing state‐of‐the‐art solvers and solution techniques, fully open and extensible libraries of dynamic unit operations models and thermophysical property models, and integrated support for superstructure‐based conceptual design and optimization under uncertainty.

42 ENGINEERING↗