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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Data and scripts associated with a manuscript investigating dissolved organic matter and microbial community linkages across seven globally distributed rivers

This data package is associated with the publication “Meta-metabolome ecology reveals that geochemistry and microbial functional potential are linked to organic matter development across seven rivers” submitted to Science of the Total Environment. This data package includes the data necessary to replicate the analyses presented within the manuscript to investigate dissolved organic matter (DOM) development across broad spatial distances and within divergent biomes. Specifically, we included the Fourier transform ion cyclotron mass spectrometry (FTICR-MS) data, geochemistry data, annotated metagenomic data, and results from ecological null modeling analyses in this data package. Additionally, we included the scripts necessary to generate the figures from the manuscript. Complete metagenomic data associated with this data package can be found at the National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. This dataset consists of (1) four folders; (2) a file-level metadata (flmd) file; (3) a data dictionary (dd) file; (4) a factor sheet describing samples; and (5) a readme. The FTICR Data folder contains (1) the processed Fourier transform ion cyclotron mass spectrometry (FTICR-MS) data; (2) a transformation-weighted characteristics dendrogram generated from the FTICR-MS data; and (3) the script used to generate all FTICR-MS related figures. The Geochemical Data folder contains (1) the single geochemistry data file and (2) the R script responsible for generating associated figures. The Metagenomic Data folder contains (1) annotation information across different levels; (2) carbohydrate active enzyme (CAZyme) information from the dbCAN database (Yin et al., 2012); (3) phylogenetic tree data (FASTAs, alignments, and tree file); and (4) the scripts necessary to analyze all of these data and generate figures. The Null Modeling Data folder contains (1) data generated during null modeling for each river and all rivers combined and (2) the R scripts necessary to process the data. All files are .csv, .pdf, .tsv, .tre, .faa, .afa, .tree, or .R.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

First report of barley root-knot nematode, Meloidogyne naasi from turfgrass in Idaho, with multigene molecular characterization

Barley root-knot nematode, Meloidogyne naasi Franklin, 1965, is one of the most important pest nematodes infecting monocots (Franklin, 1965). Two-inch core soil samples collected from a golf course in Ada County, Idaho were submitted for identification in November of 2019. A high number of Meloidogyne sp. juveniles were recovered from both soil samples using sieving and decantation followed by the sugar centrifugal flotation method. They were examined by light microscopy, morphometric measurements, and multiple molecular markers, including the ribosomal 28S D2–D3 and intergenic spacer 2 (IGS-2) regions, mitochondrial markers cytochrome oxidase I (COI) and the interval from COII to 16S, and the protein-coding gene Hsp90. Morphometrics as well as BlastN comparisons with other root-knot nematode sequences from GenBank were consistent with identification as M. naasi. Phylogenetic trees inferred from 28S, IGS-2, COI, or Hsp90 alignments each separated the Idaho population into a strongly supported clade with other populations of M. naasi, while the COII-16S interval could not resolve M. naasi from M. minor. This report represents the first morphological and molecular characterization of Meloidogyne naasi from turfgrass in Idaho.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

First Report and Molecular Variability of Belonolaimus longicaudatus Associated with Turfgrass in Maryland

Abstract Turfgrass is a crop used extensively in athletic fields and golf courses in Maryland. A soil sample collected in July 2023 from an athletic field in Baltimore County, Maryland, part of a turfgrass nematode survey, containedBelonolaimus longicaudatus. In the southeastern United States,B. longicaudatusis an economically important pathogen of warm season turfgrass. The density was four individuals/100 cm 3 of soil, and no visual symptoms were observed in the bermudagrass field. Morphological features and morphometrics of males and females were consistent withB. longicaudatusand placed the Maryland population in a subclade that was geographically represented by populations from north and west Florida, Texas, and South Carolina. Sequencing of the internal transcribed spacer region ITS1 and ITS2 and 28S large ribosomal subunit D2-23 expansion region confirmed the species' identity. Phylogenetic trees and parsimony network analysis placed the Maryland isolate in a large grouping ofB. longicaudatuspopulations including those from Alabama, Delaware, Florida, Indiana, Mississippi, South Carolina, and Texas. To our knowledge, this is the first report ofB. longicaudatusin Maryland.

Zoology↗
DOE OSTI2022

GROWdb US River Systems - Samples

GROW Overview We developed the Genome Resolved Open Watersheds database (GROWdb), which aims to increase genomic sampling and understanding of global river microbiomes. An emphasis of GROWdb is to create a publicly available and ever-expanding microbial genome database that is focused on rivers while being interoperable with databases from other ecosystems. GROWdb is based on a network-of-networks approach to move beyond a small collection of well-studied rivers, towards a spatially distributed, global network of systematic observations. GROWdb represents the first microbial, river-focused resource parsed at various scales from genes to MAGs to community level including expression and potential based measurements that will be of interest to microbiologists, ecologists, geochemists, hydrologists, and modelers. Dataset Acknowledgement GROWdb contains data from various research campaigns, please acknowledge the following data generators, as appropriate: WHONDRS derived genomes or samples - include this statement in your acknowledgements: “This study used data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) under the River Corridor Science Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL) that was generated at the U.S. Department of Energy (DOE) Joint Genome Institute User Facility. PNNL is operated by Battelle Memorial Institute for the U.S. DOE under Contract No. DE-AC05-76RL01830. The SFA is supported by the U.S. DOE, Office of Biological and Environmental Research (BER), Environmental System Science (ESS) Program.” Total Samples loaded onto this Narrative: 178 Note: Not all GROW samples may be loaded into KBase Data Availability The data underlying GROWdb are accessible across various platforms to ensure all levels of data structure are widely available. First, all reads and MAGs are publicly hosted on National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. Second, all data related data presented here including MAG annotations, extended data tables, phylogenetic tree files, antibiotic resistance gene database files, and MAG abundance tables are available in Zenodo (link). Beyond the flat database files listed above, our aim for GROWdb was to maximize data use by making the data available in searchable and interactive platforms including the National Microbiome Data Collaborative (NMDC) data portal, the Department of Energy’s Systems Biology Knowledgebase (KBase), and a GROW specific user interface released here, GROWdb Explorer. Each platform provides different ways to interact with GROWdb: NMDC GROWdb formed a pilot project for the NMDC. Specifically, individual GROWdb datasets (metagenomes, metatranscriptomes, etc) are easily accessible and searchable through the NMDC data portal, where they are systematically connected to each other and to a rich suite of sample information and standard analysis results, following Findable, Accessible, Interoperable, and Reusable (FAIR) data practices. KBase GROWdb is publicly available within KBase, including samples (this Narrative), MAGs, and corresponding genome scale metabolic models. Access within KBase allows for immediate access and reuse of data, including comparison to private data using KBase’s 500+ analysis tools. Other linked narratives in KBase: GROW Metagenome Assembled Genomes (MAGs) GROW Metabolic Models GROWdb Explorer GROWdb data is also explorable through a graphical user interface built through the Colorado State University Geospatial Centroid (https://geocentroid.shinyapps.io/GROWdatabase/), allowing users to search and graph microbial and spatial data simultaneously. In summary, this microbial genome resource represents the first publicly available genome collection from rivers and offers data that can be leveraged across microbiome studies. GROWdb is an expanding repository to incorporate and unify global river multi-omic data for the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Genome collection processing for “Conserved upper thermal limits and small safety margins in soil copiotrophic bacteria”

We extracted the genomic DNA of 400 randomly selected isolates using a Quick-DNA Microprep Kit (Zymo Research D3020) according to the manufacturer’s protocol. We then submitted the extracted gDNA samples for short-read Illumina sequencing (200 Mbp) at SeqCoast Genomics (Portsmouth, NH, USA). After preprocessing the sequences using Trimmommatic (Bolger et al. 2014), we assembled the genomes using SPADES (Bankevich et al. 2012) and checked the quality of each assembly using QUAST (Gurevich et al. 2013). We processed the genome assemblies using a KBase (v1.4.0) pipeline (Allen et al. 2017; Arkin et al. 2018). Briefly, we used DRAM (v0.1.2) with default settings to annotate the genome assemblies. We then evaluated genome quality and possible contamination levels using CheckM (v1.0.18) (Parks et al. 2015) and retained genomes with completeness above 98% and contamination below 5% (n = 354), following the authors' guidelines. We then obtained taxonomic assignments for all remaining isolates using the Genome Taxonomy Database tool GTDB-Tk (v2.3.2, database version r214) (Chaumeil et al. 2019). We constructed a phylogenetic tree using the tool SpeciesTree (v2.2.0). We then trimmed the tree (using Trim SpeciesTree to GenomeSet- v1.4.0), retaining only tips within our collection with measured thermal performance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Case Study: Can you find Delftia?

Delftia is a genus of bacteria with a bunch of cool features! The best studied species, Delftia acidovorans can produce gold nanoparticles from gold ions in solution. This bacteria has been found living in biofolms with Cupriavidis metallidurans on gold nuggets. It is also found in soil, in sinks and in rhizospheres of different plants where it promotes their growth. Delftia acidovorans forms gold nuggets by producing a short nonribosomal peptide called delftibactin. The 16 genes responsible for the production of delftibactin are called the del cluster (delA-delP). These genes were originally discovered in Delftia acidovorans SPH-1, but our research shows that the del cluster appears to be present across the genus. We'll start with a number of raw reads, clean them up and do a little taxonomy to figure out what we might be able to assemble. Next, we'll assemble the reads using 4 different methods and pick out the best assembly. Then we'll take those reads and sort them by genome and assess the quality of those genomes. We'll select the high quality genomes to annotate and insert into phylogenetic trees to find relatives.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Sugar Relese Supplementary Text and Figures

Phylogenetic tree of GAUT Protein Family and gene model, RNAi construct, and relative transcript abundance of GAUT4 in switchgrass, rice and poplar knockdown (KD) lines.

bio engineered↗
DOE OSTI2022

Molecular evolution of human coronavirus-NL63, -229E, -HKU1 and -OC43 in hospitalized children in China

Human coronaviruses (HCoVs) HCoV-NL63, HCoV-229E, HCoV-HKU1 and HCoV-OC43 have been circulated in the human population worldwide, and they are associated with a broad range of respiratory diseases with varying severity. However, there are neither effective therapeutic drugs nor licensed vaccines available for the treatment and prevention of infections by the four HCoVs. In this study, we collected nasopharyngeal aspirates of children hospitalized for respiratory tract infection in China during 2014–2018 and conducted next-generation sequencing. Sequences of four HCoVs were then selected for an in-depth analysis. Genome sequences of 2 HCoV-NL63, 8 HCoV-229E, 2 HCoV-HKU1, and 6 HCoV-OC43 were obtained. Based on the full-length S gene, a strong temporal signal was found in HCoV-229E and the molecular evolutionary rate was 6 × 10 −4 substitutions/site/year. Based on the maximum-likelihood (ML) phylogenetic tree of complete S gene, we designated H78 as a new sub-genotype C2 of HCoV-HKU1, and the obtained P43 sequence was grouped into the reported novel genotype K of HCoV-OC43 circulating in Guangzhou, China. Based on the complete genome, potential recombination events were found to occur as two phenomena, namely intraspecies and interspecies. Moreover, we observed two amino acid substitutions in the S1 subunit of obtained HCoV-NL63 (G534V) and HCoV-HKU1 (H512R), while residues 534 and 512 are important for the binding of angiotensin-converting enzyme 2 and neutralizing antibodies, respectively. Our findings might provide a clue for the molecular evolution of the four HCoVs and help in the early diagnosis, treatment and prevention of broad-spectrum HCoV infection.

Shao, Nan↗
DOE OSTI2023

classLog: Logistic regression for the classification of genetic sequences

Introduction Sequencing and phylogenetic classification have become a common task in human and animal diagnostic laboratories. It is routine to sequence pathogens to identify genetic variations of diagnostic significance and to use these data in realtime genomic contact tracing and surveillance. Under this paradigm, unprecedented volumes of data are generated that require rapid analysis to provide meaningful inference. Methods We present a machine learning logistic regression pipeline that can assign classifications to genetic sequence data. The pipeline implements an intuitive and customizable approach to developing a trained prediction model that runs in linear time complexity, generating accurate output rapidly, even with incomplete data. Our approach was benchmarked against porcine respiratory and reproductive syndrome virus (PRRSv) and swine H1 influenza A virus (IAV) datasets. Trained classifiers were tested against sequences and simulated datasets that artificially degraded sequence quality at 0, 10, 20, 30, and 40%. Results When applied to a poor-quality sequence data, the classifier achieved between >85% to 95% accuracy for the PRRSv and the swine H1 IAV HA dataset and this increased to near perfect accuracy when using the full dataset. The model also identifies amino acid positions used to determine genetic clade identity through a feature selection ranking within the model. These positions can be mapped onto a maximum-likelihood phylogenetic tree, allowing for the inference of clade defining mutations. Discussion Our approach is implemented as a python package with code available at https://github.com/flu-crew/classLog .

Zeller, Michael A.↗
DOE OSTI2022

Transcriptome Sequencing of Agave angustifolia Reveals Conservation and Diversification in the Expression of Cinnamyl Alcohol Dehydrogenase Genes in Agave Species

Agave angustifolia is an important crassulacean acid metabolism plant species, with wide applications in beverage and sisal fiber production. In this study, we carried out a transcriptome analysis of A. angustifolia leaves, generating a total of 58,482,436 clean reads through Illumina paired-end sequencing. De novo transcriptome assembly generated 67,314 unigenes, with about half of them having homologs in four public databases. In the Nr database, Asparagus officinalis was shown to be most closely related to agave, and the early angiosperm Amborella trichopoda was selected as an outgroup species. We further identified five, two, seven, seven, seven, six and six CAD genes in asparagus, amborella, A. deserti, A. tequilana, A. americana, A. hybrid H11648 and A. angustifolia, respectively. The maximum likelihood phylogenetic tree revealed the species-specific expansion of CAD genes in arabidopsis, rice and agave. The expression analysis indicated the conservatively expressed CAD1/2/4/6, providing candidate targets for manipulation to improve lignin traits. The species-specific expression of CAD3/5/7 indicates the existence of different regulatory mechanisms controlling the expression of these genes in agave species. This study presents the first transcriptome dataset of A. angustifolia, facilitating future studies on lignin biosynthesis in agave.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Unveiling the Arsenal of Apple Bitter Rot Fungi: Comparative Genomics Identifies Candidate Effectors, CAZymes, and Biosynthetic Gene Clusters in Colletotrichum Species

The bitter rot of apple is caused by Colletotrichum spp. and is a serious pre-harvest disease that can manifest in postharvest losses on harvested fruit. In this study, we obtained genome sequences from four different species, C. chrysophilum, C. noveboracense, C. nupharicola, and C. fioriniae, that infect apple and cause diseases on other fruits, vegetables, and flowers. Our genomic data were obtained from isolates/species that have not yet been sequenced and represent geographic-specific regions. Genome sequencing allowed for the construction of phylogenetic trees, which corroborated the overall concordance observed in prior MLST studies. Bioinformatic pipelines were used to discover CAZyme, effector, and secondary metabolic (SM) gene clusters in all nine Colletotrichum isolates. We found redundancy and a high level of similarity across species regarding CAZyme classes and predicted cytoplastic and apoplastic effectors. SM gene clusters displayed the most diversity in type and the most common cluster was one that encodes genes involved in the production of alternapyrone. Our study provides a solid platform to identify targets for functional studies that underpin pathogenicity, virulence, and/or quiescence that can be targeted for the development of new control strategies. With these new genomics resources, exploration via omics-based technologies using these isolates will help ascertain the biological underpinnings of their widespread success and observed geographic dominance in specific areas throughout the country.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A Re-Evaluation of African Swine Fever Genotypes Based on p72 Sequences Reveals the Existence of Only Six Distinct p72 Groups

The African swine fever virus (ASFV) is currently causing a world-wide pandemic of a highly lethal disease in domestic swine and wild boar. Currently, recombinant ASF live-attenuated vaccines based on a genotype II virus strain are commercially available in Vietnam. With 25 reported ASFV genotypes in the literature, it is important to understand the molecular basis and usefulness of ASFV genotyping, as well as the true significance of genotypes in the epidemiology, transmission, evolution, control, and prevention of ASFV. Historically, genotyping of ASFV was used for the epidemiological tracking of the disease and was based on the analysis of small fragments that represent less than 1% of the viral genome. The predominant method for genotyping ASFV relies on the sequencing of a fragment within the gene encoding the structural p72 protein. Genotype assignment has been accomplished through automated phylogenetic trees or by comparing the target sequence to the most closely related genotyped p72 gene. To evaluate its appropriateness for the classification of genotypes by p72, we reanalyzed all available genomic data for ASFV. We conclude that the majority of p72-based genotypes, when initially created, were neither identified under any specific methodological criteria nor correctly compared with the already existing ASFV genotypes. Based on our analysis of the p72 protein sequences, we propose that the current twenty-five genotypes, created exclusively based on the p72 sequence, should be reduced to only six genotypes. To help differentiate between the new and old genotype classification systems, we propose that Arabic numerals (1, 2, 8, 9, 15, and 23) be used instead of the previously used Roman numerals. Furthermore, we discuss the usefulness of genotyping ASFV isolates based only on the p72 gene sequence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Small signaling peptides, phylogenetic analysis

ML Phylogenetic analysis of small signaling peptides in Arabidopsis, Sorghum bicolor, Rice, Wheat, Maize, and Brachypodium. Sorghum only phylogenetic trees were used to name genes. All trees but RALF tree are rooted at midpoint.

Kurtz, Evan [Department of Biochemistry and Biophy↗
NASA NTRS1971

Evolution of proteins.

The amino acid sequences of proteins from living organisms are dealt with. The structure of proteins is first discussed; the variation in this structure from one biological group to another is illustrated by the first halves of the sequences of cytochrome c, and a phylogenetic tree is derived from the cytochrome c data. The relative geological times associated with the events of this tree are discussed. Errors which occur in the duplication of cells during the evolutionary process are examined. Particular attention is given to evolution of mutant proteins, globins, ferredoxin, and transfer ribonucleic acids (tRNA's). Finally, a general outline of biological evolution is presented.

Dayhoff, M. O.↗
NASA NTRS1981

The evolution of blue-greens and the origins of chloroplasts

All of the available molecular data support the theory that the chloroplasts of eukaryote cells were originally free-living blue-greens. Of great interest is what the relationships are between contemporary types of blue-greens and eukaryote chloroplasts and whether the chloroplasts of the various eukaryotes are the result of one or more than one symbiosis. By combining information from phylogenetic trees based on cytochrome c6 and 2Fe-2S ferredoxin sequences, it is shown that the chloroplasts of a number of eukaryote algae as well as the protist Euglena are polyphyletic; the chloroplasts of green algae and the higher plants may be the result of a single symbiosis.

Schwartz, R. M.↗
NASA NTRS1982

Evolution of major metabolic innovations in the Precambrian

A combination of information on the metabolic capabilities of prokaryotes with a composite phylogenetic tree depicting an overview of prokaryote evolution based on the sequences of bacterial ferredoxin, 2Fe-2S ferredoxin, 5S ribosomal RNA, and c-type cytochromes shows three zones of major metabolic innovation in the Precambrian. The middle of these, which reflects the genesis of oxygen-releasing photosynthesis and aerobic respiration, links metabolic innovations of the anaerobic stem on the one hand and, on the other, proliferation of aerobic bacteria and the symbiotic associations leading to the eukaryotes. Those pathways where information on the structure of the enzymes is known are especially considered. Halobacterium and Thermoplasma (archaebacteria) do not belong to a totally independent line on the basis of the composite tree but branch from the eukaryote cytoplasmic line.

Barnabas, J.↗
NASA NTRS1984

Evolution of prokaryote and eukaryote lines inferred from sequence evidence

This paper describes the evolution of prokaryotes and early eukaryotes, including their symbiotic relationships, as inferred from phylogenetic trees of bacterial ferredoxin, 5S ribosomal RNA, ribulose-1,5-biphosphate carboxylase large chain, and mitochondrial cytochrome oxidase polypeptide II.

Hunt, L. T.↗
NASA NTRS1985

Insights into the phylogenetic positions of photosynthetic bacteria obtained from 5S rRNA and 16S rRNA sequence data

Comparisons of complete 16S ribosomal ribonucleic acid (rRNA) sequences established that the secondary structure of these molecules is highly conserved. Earlier work with 5S rRNA secondary structure revealed that when structural conservation exists the alignment of sequences is straightforward. The constancy of structure implies minimal functional change. Under these conditions a uniform evolutionary rate can be expected so that conditions are favorable for phylogenetic tree construction.

Fox, G. E.↗