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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2010

NBC: the Naive Bayes Classification tool webserver for taxonomic classification of metagenomic reads

Motivation: Datasets from high-throughput sequencing technologies have yielded a vast amount of data about organisms in environmental samples. Yet, it is still a challenge to assess the exact organism content in these samples because the task of taxonomic classification is too computationally complex to annotate all reads in a dataset. An easy-to-use webserver is needed to process these reads. While many methods exist, only a few are publicly available on webservers, and out of those, most do not annotate all reads. Results: We introduce a webserver that implements the naïve Bayes classifier (NBC) to classify all metagenomic reads to their best taxonomic match. Results indicate that NBC can assign nextgeneration sequencing reads to their taxonomic classification and can find significant populations of genera that other classifiers may miss. Availability: Publicly available at: http://nbc.ece.drexel.edu.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Omega: an Overlap-graph de novo Assembler for Meta-genomics

Motivation: Metagenomic sequencing allows reconstruction of mi-crobial genomes directly from environmental samples. Omega (overlap-graph metagenome assembler) was developed here for assembling and scaffolding Illumina sequencing data of microbial communities. Results: Omega found overlaps between reads using a prefix/suffix hash table. The overlap graph of reads was simplified by removing transitive edges and trimming small branches. Unitigs were generat-ed based on minimum cost flow analysis of the overlap graph. Obtained unitigs were merged to contigs and scaffolds using mate-pair information. Omega was compared with two de Bruijn graph assemblers, SOAPdenovo and IDBA-UD, using a publically-available Illumina sequencing dataset of a 64-genome mock com-munity. The assembly results were verified by their alignment with reference genomes. The overall performances of the three assem-blers were comparable and each assembler provided best results for a subset of genomes.

Haider, Bahlul↗
DOE OSTI2015

MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets

The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here, we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments. Availability and implementation: MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license. Supplementary information: Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Advancements in the application of NanoSIMS and Raman microspectroscopy to investigate the activity of microbial cells in soils

The combined approach of incubating environmental samples with stable isotope-labeled substrates followed by single-cell analyses through high-resolution secondary ion mass spectrometry (NanoSIMS) or Raman microspectroscopy provides insights into the in situ function of microorganisms. This approach has found limited application in soils presumably due to the dispersal of microbial cells in a large background of particles. We developed a pipeline for the efficient preparation of cell extracts from soils for subsequent single-cell methods by combining cell detachment with separation of cells and soil particles followed by cell concentration. The procedure was evaluated by examining its influence on cell recoveries and microbial community composition across two soils. This approach generated a cell fraction with considerably reduced soil particle load and of sufficient small size to allow single-cell analysis by NanoSIMS, as shown when detecting active N2-fixing and cellulose-responsive microorganisms via 15 N2 and 13 C-UL-cellulose incubations, respectively. The same procedure was also applicable for Raman microspectroscopic analyses of soil microorganisms, assessed via microcosm incubations with a 13 C-labeled carbon source and deuterium oxide (D2O, a general activity marker). Lastly, the described sample preparation procedure enables single-cell analysis of soil microorganisms using NanoSIMS and Raman microspectroscopy, but should also facilitate single-cell sorting and sequencing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Metagenomic investigation of African dust events in the Caribbean

ABSTRACT African dust from the Sahara and Sahel regions of Northern Africa is blown intercontinental distances and is the highest portion of atmospheric dust generated each year. During the Northern Hemisphere summer months (boreal summer), these dust events travel into the Caribbean and southern United States. While viability assays, microscopy and bacterial amplicon analyses have shown that dust-associated microbes may be diverse, the specific microbial taxa that are transported intercontinental distances with these dust events remain poorly characterized. To provide new insights into these issues, five metagenomes of Saharan dust events occurring in the Caribbean, collected in the summer months of 2002 and 2008, were analyzed. The data revealed that similar microbial composition existed between three out of the five of the distinct dust events and that fungi were a prominent feature of the metagenomes compared to other environmental samples. These results have implications for better understanding of microbial transport through the atmosphere and may implicate that the dust-associated microbial load transiting the Atlantic with Saharan dust is similar from year to year.

Waters, Samantha Marie↗
DOE OSTI2023

Synchrotron X-rays reveal the modes of Fe binding and trace metal storage in the brown algae Laminaria digitata and Ectocarpus siliculosus

Abstract Iron is accumulated symplastically in kelp in a non-ferritin core that seems to be a general feature of brown algae. Microprobe studies show that Fe binding depends on tissue type. The sea is generally an iron-poor environment and brown algae were recognized in recent years for having a unique, ferritin-free iron storage system. Kelp (Laminaria digitata) and the filamentous brown alga Ectocarpus siliculosus were investigated using X-ray microprobe imaging and nanoprobe X-ray fluorescence tomography to explore the localization of iron, arsenic, strontium, and zinc, and micro-X-ray absorption near-edge structure (μXANES) to study Fe binding. Fe distribution in frozen hydrated environmental samples of both algae shows higher accumulation in the cortex with symplastic subcellular localization. This should be seen in the context of recent ultrastructural insight by cryofixation–freeze substitution that found a new type of cisternae that may have a storage function but differs from the apoplastic Fe accumulation found by conventional chemical fixation. Zn distribution co-localizes with Fe in E. siliculosus, whereas it is chiefly located in the L. digitata medulla, which is similar to As and Sr. Both As and Sr are mostly found at the cell wall of both algae. XANES spectra indicate that Fe in L. digitata is stored in a mineral non-ferritin core, due to the lack of ferritin-encoding genes. We show that the L. digitata cortex contains mostly a ferritin-like mineral, while the meristoderm may include an additional component.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Genomes OnLine Database (GOLD) v.6: data updates and feature enhancements

The Genomes Online Database (GOLD) (https://gold.jgi.doe.gov) is a manually curated data management system that catalogs sequencing projects with associated metadata from around the world. In the current version of GOLD (v.6), all projects are organized based on a four level classification system in the form of a Study, Organism (for isolates) or Biosample (for environmental samples), Sequencing Project and Analysis Project. Currently, GOLD provides information for 26 117 Studies, 239 100 Organisms, 15 887 Biosamples, 97 212 Sequencing Projects and 78 579 Analysis Projects. These are integrated with over 312 metadata fields from which 58 are controlled vocabularies with 2067 terms. The web interface facilitates submission of a diverse range of Sequencing Projects (such as isolate genome, singlecell genome, metagenome, metatranscriptome) and complex Analysis Projects (such as genome from metagenome, or combined assembly from multiple Sequencing Projects). GOLD provides a seamless interface with the Integrated Microbial Genomes (IMG) system and supports and promotes the Genomic Standards Consortium (GSC) Minimum Information standards. Here, this paper describes the data updates and additional features added during the last two years.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Improved precision in As speciation analysis with HERFD-XANES at the As K -edge: the case of As speciation in mine waste

High-energy-resolution fluorescence-detected (HERFD) X-ray absorption near-edge spectroscopy (XANES) is a spectroscopic method that allows for increased spectral feature resolution, and greater selectivity to decrease complex matrix effects compared with conventional XANES. XANES is an ideal tool for speciation of elements in solid-phase environmental samples. Accurate speciation of As in mine waste materials is important for understanding the mobility and toxicity of As in near-surface environments. In this study, linear combination fitting (LCF) was performed on synthetic spectra generated from mixtures of eight measured reference compounds for both HERFD-XANES and transmission-detected XANES to evaluate the improvement in quantitative speciation with HERFD-XANES spectra. The reference compounds arsenolite (As 2 O 3 ), orpiment (As 2 S 3 ), getchellite (AsSbS 3 ), arsenopyrite (FeAsS), kaňkite (FeAsO 4 ·3.5H 2 O), scorodite (FeAsO 4 ·2H 2 O), sodium arsenate (Na 3 AsO 4 ), and realgar (As 4 S 4 ) were selected for their importance in mine waste systems. Statistical methods of principal component analysis and target transformation were employed to determine whether HERFD improves identification of the components in a dataset of mixtures of reference compounds. LCF was performed on HERFD- and total fluorescence yield (TFY)-XANES spectra collected from mine waste samples. Arsenopyrite, arsenolite, orpiment, and sodium arsenate were more accurately identified in the synthetic HERFD-XANES spectra compared with the transmission-XANES spectra. In mine waste samples containing arsenopyrite and either scorodite or kaňkite, LCF with HERFD-XANES measurements resulted in fits with smaller R -factors than concurrently collected TFY measurements. The improved accuracy of HERFD-XANES analysis may provide enhanced delineation of As phases controlling biogeochemical reactions in mine wastes, contaminated soils, and remediation systems.

58 GEOSCIENCES↗
DOE OSTI2019

Wetland Sediments Host Diverse Microbial Taxa Capable of Cycling Alcohols

Alcohols are commonly derived from the degradation of organic matter and yet are rarely measured in environmental samples. Wetlands in the Prairie Pothole Region (PPR) support extremely high methane emissions and the highest sulfate reduction rates reported to date, likely contributing to a significant proportion of organic matter mineralization in this system. Here, while ethanol and isopropanol concentrations up to 4 to 5 mM in PPR wetland pore fluids have been implicated in sustaining these high rates of microbial activity, the mechanisms that support alcohol cycling in this ecosystem are poorly understood. We leveraged metagenomic and transcriptomic tools to identify genes, pathways, and microorganisms potentially accounting for alcohol cycling in PPR wetlands. Phylogenetic analyses revealed diverse alcohol dehydrogenases and putative substrates. Alcohol dehydrogenase and aldehyde dehydrogenase genes were included in 62 metagenome-assembled genomes (MAGs) affiliated with 16 phyla.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Environmental Selection, Dispersal, and Organism Interactions Shape Community Assembly in High-Throughput Enrichment Culturing

A central goal of microbial ecology is to identify and quantify the forces that lead to observed population distributions and dynamics. However, these forces, which include environmental selection, dispersal, and organism interactions, are often difficult to assess in natural environments. Here in this paper, we present a method that links microbial community structures with selective and stochastic forces through highly replicated subsampling and enrichment of a single environmental inoculum. Specifically, groundwater from a well-studied natural aquifer was serially diluted and inoculated into nearly 1,000 aerobic and anaerobic nitrate-reducing cultures, and the final community structures were evaluated with 16S rRNA gene amplicon sequencing. We analyzed the frequency and abundance of individual operational taxonomic units (OTUs) to understand how probabilistic immigration, relative fitness differences, environmental factors, and organismal interactions contributed to divergent distributions of community structures. We further used a most probable number (MPN) method to estimate the natural condition-dependent cultivable abundance of each of the nearly 400 OTU cultivated in our study and infer the relative fitness of each. Additionally, we infer condition-specific organism interactions and discuss how this high-replicate culturing approach is essential in dissecting the interplay between overlapping ecological forces and taxon-specific attributes that underpin microbial community assembly. IMPORTANCE Through highly replicated culturing, in which inocula are subsampled from a single environmental sample, we empirically determine how selective forces, interspecific interactions, relative fitness, and probabilistic dispersal shape bacterial communities. These methods offer a novel approach to untangle not only interspecific interactions but also taxon-specific fitness differences that manifest across different cultivation conditions and lead to the selection and enrichment of specific organisms. Additionally, we provide a method for estimating the number of cultivable units of each OTU in the original sample through the MPN approach.

16S RNA↗
DOE OSTI2020

Whole-Genome Sequence of Brevibacillus borstelensis SDM, Isolated from a Sorghum-Adapted Microbial Community

The isolation of novel microbes from environmental samples continues to be a key strategy for the discovery of new metabolic capacities for the degradation and transformation of lignocellulose. We report the draft genome sequence of a new strain of Brevibacillus borstelensis isolated from a sorghum-adapted microbial community derived from a compost sample.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Discovering the Molecular Determinants of Phaeobacter inhibens Susceptibility to Phaeobacter Phage MD18

Bacteriophages are useful nonantibiotic therapeutics for bacterial infections as well as threats to industries utilizing bacterial agents. This study identified Phaeobacter virus MD18 , a phage antagonist of Phaeobacter inhibens , a bacterium with promising use as a probiotic for aquatic farming industries. Genomic analysis suggested that Phaeobacter phage MD18 has evolved to enhance its replication in P. inhibens by adopting favorable tRNA genes as well as through genomic sequence adaptation to resemble host codon usage. Lastly, a high-throughput analysis of P. inhibens transposon insertion mutants identified genes that modulate host susceptibility to phage MD18 and implicated the type IV pilus as the likely receptor recognized for adsorption. This study marks the first characterization of the relationship between P. inhibens and an environmentally sampled phage, which informs our understanding of natural threats to the bacterium and may promote the development of novel phage technologies for genetic manipulation of this host.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Advantages and Limits of Metagenomic Assembly and Binning of a Giant Virus

ABSTRACT Giant viruses have large genomes, often within the size range of cellular organisms. This distinguishes them from most other viruses and demands additional effort for the successful recovery of their genomes from environmental sequence data. Here, we tested the performance of genome-resolved metagenomics on a recently isolated giant virus, Fadolivirus, by spiking it into an environmental sample from which two other giant viruses were isolated. At high spike-in levels, metagenome assembly and binning led to the successful genomic recovery of Fadolivirus from the sample. A complementary survey of the major capsid protein indicated the presence of other giant viruses in the sample matrix but did not detect the two isolated from this sample. Our results indicate that genome-resolved metagenomics is a valid approach for the recovery of near-complete giant virus genomes given that sufficient clonal particles are present. However, our data also underline that a vast majority of giant viruses remain currently undetected, even in an era of terabase-scale metagenomics. IMPORTANCE The discovery of large and giant nucleocytoplasmic large DNA viruses (NCLDV) with genomes in the megabase range and equipped with a wide variety of features typically associated with cellular organisms was one of the most unexpected, intriguing, and spectacular breakthroughs in virology. Recent studies suggest that these viruses are highly abundant in the oceans, freshwater, and soil, impact the biology and ecology of their eukaryotic hosts, and ultimately affect global nutrient cycles. Genome-resolved metagenomics is becoming an increasingly popular tool to assess the diversity and coding potential of giant viruses, but this approach is currently lacking validation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Accelerating large scale de novo metagenome assembly using GPUs

Metagenomic workflows involve studying uncultured microorganisms directly from the environment. These environmental samples when processed by modern sequencing machines yield large and complex datasets that exceed the capabilities of metagenomic software. The increasing sizes and complexities of datasets make a strong case for exascale-capable metagenome assemblers. However, the underlying algorithmic motifs are not well suited for GPUs. This poses a challenge since the majority of next-generation supercomputers will rely primarily on GPUs for computation. In this paper we present the first of its kind GPU-Accelerated implementation of the local assembly approach that is an integral part of a widely used large-scale metagenome assembler, MetaHipMer. Local assembly uses algorithms that induce random memory accesses and non-deterministic workloads, which make GPU offloading a challenging task. Our GPU implementation outperforms the CPU version by about 7x and boosts the performance of MetaHipMer by 42% when running on 64 Summit nodes.

Awan, Muaaz Gul↗
DOE OSTI2011

Discovering the Unknown: Improving Detection of Novel Species and Genera from Short Reads

High-throughput sequencing technologies enable metagenome profiling, simultaneous sequencing of multiple microbial species present within an environmental sample. Since metagenomic data includes sequence fragments (“reads”) from organisms that are absent from any database, new algorithms must be developed for the identification and annotation of novel sequence fragments. Homology-based techniques have been modified to detect novel species and genera, but, composition-based methods, have not been adapted. We develop a detection technique that can discriminate between “known” and “unknown” taxa, which can be used with composition-based methods, as well as a hybrid method. Unlike previous studies, we rigorously evaluate all algorithms for their ability to detect novel taxa. First, we show that the integration of a detector with a composition-based method performs significantly better than homology-based methods for the detection of novel species and genera, with best performance at finer taxonomic resolutions. Most importantly, we evaluate all the algorithms by introducing an “unknown” class and show that the modified version of PhymmBL has similar or better overall classification performance than the other modified algorithms, especially for the species-level and ultrashort reads. Finally, we evaluate theperformance of several algorithms on a real acid mine drainage dataset.

Rosen, Gail L.↗
DOE OSTI2025

genomeocean: a pretrained microbial genome foundational model (genomeoceanLLM) v1.0

We present Genomeocean, a foundational genome language model that represents the microbial genome sequences from complex environmental samples. By training on a large, diverse metagenomic dataset, Genomeocean learns species-specific sequence composition and can generate long, realistic open reading frames (ORFs). Our model employs a Byte-pair-encoding (BPE) tokenization strategy, allowing it to efficiently process large genomic datasets and generate long sequences up to 50kb. We demonstrate that fine-tuning Genomeocean can generate novel gene clusters encoding biosynthetic pathways, showcasing its ability to model both fundamental and complex biological processes. Our work establishes Genomeocean as a powerful tool for understanding microbial genome biology and paves the way for its application in a range of fields, from synthetic biology to microbiome research.

Wang, Zhong [Lawrence Berkeley National Laboratory↗
DOE OSTI2011

Functional analysis of metagenomes and metatranscriptomes using SEED and KEGG

Background: Metagenomics is the study of microbial organisms using sequencing applied directly to environmental samples. Technological advances in next-generation sequencing methods are fueling a rapid increase in the number and scope of metagenome projects. While metagenomics provides information on the gene content, metatranscriptomics aims at understanding gene expression patterns in microbial communities. The initial computational analysis of a metagenome or metatranscriptome addresses three questions: (1) Who is out there? (2) What are they doing? and (3) How do different datasets compare? There is a need for new computational tools to answer these questions. In 2007, the program MEGAN (MEtaGenome ANalyzer) was released, as a standalone interactive tool for analyzing the taxonomic content of a single metagenome dataset. The program has subsequently been extended to support comparative analyses of multiple datasets. Results: The focus of this paper is to report on new features of MEGAN that allow the functional analysis of multiple metagenomes (and metatranscriptomes) based on the SEED hierarchy and KEGG pathways. We have compared our results with the MG-RAST service for different datasets. Conclusions: The MEGAN program now allows the interactive analysis and comparison of the taxonomical and functional content of multiple datasets. As a stand-alone tool, MEGAN provides an alternative to web portals for scientists that have concerns about uploading their unpublished data to a website.

59 BASIC BIOLOGICAL SCIENCES↗