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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Hypermut 3: identifying specific mutational patterns in a defined nucleotide context that allows multistate characters

Abstract Motivation The detection of APOBEC3F- and APOBEC3G-induced mutations in virus sequences is useful for identifying hypermutated sequences. These sequences are not representative of viral evolution and can therefore alter the results of downstream sequence analyses if included. We previously published the software Hypermut, which detects hypermutation events in sequences relative to a reference. Two versions of this method are available as a webtool. Neither of these methods consider multistate characters or gaps in the sequence alignment. Results Here, we present an updated, user-friendly web and command-line version of Hypermut with functionality to handle multistate characters and gaps in the sequence alignment. This tool allows for straightforward integration of hypermutation detection into sequence analysis pipelines. As with the previous tool, while the main purpose is to identify G to A hypermutation events, any mutational pattern and context can be specified. Availability and implementation Hypermut 3 is written in Python 3. It is available as a command-line tool at https://github.com/MolEvolEpid/hypermut3 and as a webtool at https://www.hiv.lanl.gov/content/sequence/HYPERMUT/hypermutv3.html.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

EcoPLOT: dynamic analysis of biogeochemical data

Motivation: We have created EcoPLOT (parameterized linkage of omics-driven technologies), a web-app for the dynamic, interactive analysis of biogeochemical datasets that combines state-of-the-art analysis tools to statistically and graphically explore environmental, geochemical and microbiome datasets. Using the iterative random forest, a machine learning algorithm, EcoPLOT allows for the de novo discovery of drivers which exhibit significant impact on plant, microbial or soil dynamics. Availability and implementation: EcoPLOT is built entirely within the R language. It can be accessed through any system where R is installed, including Windows, Mac and most Linux systems. EcoPLOT is free to use and can be accessed at https://github.com/cdsanchez18/EcoPLOT.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Genomic Characterization of Newly Completed Genomes of Botulinum Neurotoxin-Producing Species from Argentina, Australia, and Africa

Botulinum neurotoxin-producing clostridia are diverse in the types of toxins they produce as well as in their overall genomic composition. They are globally distributed, with prevalent species and toxin types found within distinct geographic regions, but related strains containing the same toxin types may also be located on distinct continents. The mechanisms behind the spread of these bacteria and the independent movements of their bont genes may be understood through examination of their genetic backgrounds. The generation of 15 complete genomic sequences from bacteria isolated in Argentina, Australia, and Africa allows for a thorough examination of genome features, including overall relationships, bont gene cluster locations and arrangements, and plasmid comparisons, in bacteria isolated from various areas in the southern hemisphere. Insights gained from these examinations provide an understanding of the mechanisms behind the independent movements of these elements among distinct species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Worldwide Population Genomics Reveal Long-Term Stability of the Mitochondrial Genome Architecture in a Keystone Marine Plant

Mitochondrial genomes (mitogenomes) of flowering plants are composed of multiple chromosomes. Recombination within and between the mitochondrial chromosomes may generate diverse DNA molecules termed isoforms. The isoform copy number and composition can be dynamic within and among individual plants due to uneven replication and homologous recombination. Nonetheless, despite their functional importance, the level of mitogenome conservation within species remains understudied. Whether the ontogenetic variation translates to evolution of mitogenome composition over generations is currently unknown. Here we show that the mitogenome composition of the seagrass Zostera marina is conserved among worldwide populations that diverged ca. 350,000 years ago. Using long-read sequencing, we characterized the Z. marina mitochondrial genome and inferred the repertoire of recombination-induced configurations. To characterize the mitochondrial genome architecture worldwide and study its evolution, we examined the mitogenome in Z. marina meristematic region sampled in 16 populations from the Pacific and Atlantic oceans. Our results reveal a striking similarity in the isoform relative copy number, indicating a high conservation of the mitogenome composition among distantly related populations and within the plant germline, despite a notable variability during individual ontogenesis. Our study supplies a link between observations of dynamic mitogenomes at the level of plant individuals and long-term mitochondrial evolution.

(sub)stoichiometric shifting↗
DOE OSTI2024

Combining compositional data sets introduces error in covariance network reconstruction

Microbial communities are diverse biological systems that include taxa from across multiple kingdoms of life. Notably, interactions between bacteria and fungi play a significant role in determining community structure. However, these statistical associations across kingdoms are more difficult to infer than intra-kingdom associations due to the nature of the data involved using standard network inference techniques. We quantify the challenges of cross-kingdom network inference from both theoretical and practical points of view using synthetic and real-world microbiome data. We detail the theoretical issue presented by combining compositional data sets drawn from the same environment, e.g. 16S and ITS sequencing of a single set of samples, and we survey common network inference techniques for their ability to handle this error. We then test these techniques for the accuracy and usefulness of their intra- and inter-kingdom associations by inferring networks from a set of simulated samples for which a ground-truth set of associations is known. We show that while the two methods mitigate the error of cross-kingdom inference, there is little difference between techniques for key practical applications including identification of strong correlations and identification of possible keystone taxa (i.e. hub nodes in the network). Furthermore, we identify a signature of the error caused by transkingdom network inference and demonstrate that it appears in networks constructed using real-world environmental microbiome data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Corn stover variability drives differences in bisabolene production by engineered Rhodotorula toruloides

Microbial conversion of lignocellulosic biomass represents an alternative route for production of biofuels and bioproducts. While researchers have mostly focused on engineering strains such as Rhodotorula toruloides for better bisabolene production as a sustainable aviation fuel, less is known about the impact of the feedstock heterogeneity on bisabolene production. Critical material attributes like feedstock composition, nutritional content, and inhibitory compounds can all influence bioconversion. Further, the given feedstocks can have a marked influence on selection of suitable pretreatment and hydrolysis technologies, optimizing the fermentation conditions, and possibly even modifying the microorganism's metabolic pathways, to better utilize the available feedstock. Here, this work aimed to examine and understand how variations in corn stover batches, anatomical fractions, and storage conditions impact the efficiency of bisabolene production by R. toruloides. All of these represent different facets of feedstock heterogeneity. Deacetylation, mechanical refining, and enzymatic hydrolysis of these variable feedstocks served as the basis of this research. The resulting hydrolysates were converted to bisabolene via fermentation, a sustainable aviation fuel precursor, using an engineered R. toruloides strain. This study showed that different sources of feedstock heterogeneity can influence microbial growth and product titer in counterintuitive ways, as revealed through global analysis of protein expression. The maximum bisabolene produced by R. toruloides was on the stalk fraction of corn stover hydrolysate (8.89 ± 0.47 g/L). Further, proteomics analysis comparing the protein expression between the anatomic fractions showed that proteins relating to carbohydrate metabolism, energy production, and conversion as well as inorganic ion transport metabolism were either significantly upregulated or downregulated. Specifically, downregulation of proteins related to the iron–sulfur cluster in stalk fraction suggests a coordinated response by R. toruloides to maintain overall metabolic balance, and this was corroborated by the concentration of iron in the feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2022

Functional characterization of diverse type I-F CRISPR-associated transposons

CRISPR-Cas systems generally provide adaptive immunity in prokaryotes through RNA-guided degradation of foreign genetic elements like bacteriophages and plasmids. Recently, however, transposon-encoded and nuclease-deficient CRISPR-Cas systems were characterized and shown to be co-opted by Tn7-like transposons for CRISPR RNA-guided DNA transposition. As a genome engineering tool, these CRISPR-Cas systems and their associated transposon proteins can be deployed for programmable, site-specific integration of sizable cargo DNA, circumventing the need for DNA cleavage and homology-directed repair involving endogenous repair machinery. Here, we selected a diverse set of type I-F3 CRISPR-associated transposon systems derived from Gammaproteobacteria, predicted all components essential for transposition activity, and deployed them for functionality testing within Escherichia coli. Our results demonstrate that these systems possess a significant range of integration efficiencies with regards to temperature, transposon size, and flexible PAM requirements. Additionally, our findings support the categorization of these systems into functional compatibility groups for efficient and orthogonal RNA-guided DNA integration. This work expands the CRISPR-based toolbox with new CRISPR RNA-guided DNA integrases that can be applied to complex and extensive genome engineering efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structural basis for the tRNA-dependent activation of the terminal complex of selenocysteine synthesis in humans

Abstract O-Phosphoseryl-tRNASec selenium transferase (SepSecS) catalyzes the terminal step of selenocysteine (Sec) synthesis in archaea and eukaryotes. How the Sec synthetic machinery recognizes and discriminates tRNASec from the tRNA pool is essential to the integrity of the selenoproteome. Previously, we suggested that SepSecS adopts a competent conformation that is pre-ordered for catalysis. Herein, using high-resolution X-ray crystallography, we visualized tRNA-dependent conformational changes in human SepSecS that may be a prerequisite for achieving catalytic competency. We show that tRNASec binding organizes the active sites of the catalytic protomer, while stabilizing the N- and C-termini of the non-catalytic protomer. Binding of large anions to the catalytic groove may further optimize the catalytic site for substrate binding and catalysis. Our biochemical and mutational analyses demonstrate that productive SepSecS•tRNASec complex formation is enthalpically driven and primarily governed by electrostatic interactions between the acceptor-, TΨC-, and variable arms of tRNASec and helices α1 and α14 of SepSecS. The detailed visualization of the tRNA-dependent activation of SepSecS provides a structural basis for a revised model of the terminal reaction of Sec formation in archaea and eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Heinz-resistant tomato cultivars exhibit a lignin-based resistance to field dodder ( Cuscuta campestris ) parasitism

Cuscuta species (dodders) are agriculturally destructive, parasitic angiosperms. These parasitic plants use haustoria as physiological bridges to extract nutrients and water from hosts. Cuscuta campestris has a broad host range and wide geographical distribution. While some wild tomato relatives are resistant, cultivated tomatoes are generally susceptible to C. campestris infestations. However, some specific Heinz tomato (Solanum lycopersicum) hybrid cultivars exhibit resistance to dodders in the field, but their defense mechanism was previously unknown. Here, we discovered that the stem cortex in these resistant lines responds with local lignification upon C. campestris attachment, preventing parasite entry into the host. Lignin Induction Factor 1 (LIF1, an AP2-like transcription factor), SlMYB55, and Cuscuta R-gene for Lignin-based Resistance 1, a CC-NBS-LRR (CuRLR1) are identified as factors that confer host resistance by regulating lignification. SlWRKY16 is upregulated upon C. campestris infestation and potentially negatively regulates LIF1 function. Intriguingly, CuRLR1 may play a role in signaling or function as an intracellular receptor for receiving Cuscuta signals or effectors, thereby regulating lignification-based resistance. In summary, these four regulators control the lignin-based resistance response in specific Heinz tomato cultivars, preventing C. campestris from parasitizing resistant tomatoes. This discovery provides a foundation for investigating multilayer resistance against Cuscuta species and has potential for application in other essential crops attacked by parasitic plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs

Fungal specialized metabolites are a major source of beneficial compounds that are routinely isolated, characterized, and manufactured as pharmaceuticals, agrochemical agents, and industrial chemicals. The production of these metabolites is encoded by biosynthetic gene clusters that are often silent under standard growth conditions. There are limited resources for characterizing the direct link between abiotic stimuli and metabolite production. Herein, we introduce a network analysis-based, data-driven algorithm comprising two routes to characterize the production of specialized fungal metabolites triggered by different exogenous compounds: the direct route and the auxiliary route. Both routes elucidate the influence of treatments on the production of specialized metabolites from experimental data. The direct route determines known and putative metabolites induced by treatments and provides additional insight over traditional comparison methods. The auxiliary route is specific for discovering unknown analytes, and further identification can be curated through online bioinformatic resources. We validated our algorithm by applying chitooligosaccharides and lipids at two different temperatures to the fungal pathogen Aspergillus fumigatus. After liquid chromatography–mass spectrometry quantification of significantly produced analytes, we used network centrality measures to rank the treatments’ ability to elucidate these analytes and confirmed their identity through fragmentation patterns or in silico spiking with commercially available standards. Later, we examined the transcriptional regulation of these metabolites through real-time quantitative polymerase chain reaction. Our data-driven techniques can complement existing metabolomic network analysis by providing an approach to track the influence of any exogenous stimuli on metabolite production. Our experimental-based algorithm can overcome the bottlenecks in elucidating novel fungal compounds used in drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Characterizing Machine Learning I/O Workloads on Leadership Scale HPC Systems

High performance computing (HPC) is no longer solely limited to traditional workloads such as simulation and modeling. With the increase in the popularity of machine learning (ML) and deep learning (DL) technologies, we are observing that an increasing number of HPC users are incorporating ML methods into their workflow and scientific discovery processes, across a wide spectrum of science domains such as biology, earth science, and physics. This gives rise to a diverse set of I/O patterns than the traditional checkpoint/restart-based HPC I/O behavior. The details of the I/O characteristics of such ML I/O workloads have not been studied extensively for large-scale leadership HPC systems. This paper aims to fill that gap by providing an in-depth analysis to gain an understanding of the I/O behavior of ML I/O workloads using darshan - an I/O characterization tool designed for lightweight tracing and profiling. We study the darshan logs of more than 23, 000 HPC ML I/O jobs over a time period of one year running on Summit - the second-fastest supercomputer in the world. This paper provides a systematic I/O characterization of ML I/O jobs running on a leadership scale supercomputer to understand how the I/O behavior differs across science domains and the scale of workloads, and analyze the usage of parallel file system and burst buffer by ML I/O workloads.

Paul, Arnab↗
DOE OSTI2023

Intermittent supplementation with fisetin improves arterial function in old mice by decreasing cellular senescence

Cellular senescence and the senescence-associated secretory phenotype (SASP) contribute to age-related arterial dysfunction, in part, by promoting oxidative stress and inflammation, which reduce the bioavailability of the vasodilatory molecule nitric oxide (NO). In the present study, we assessed the efficacy of fisetin, a natural compound, as a senolytic to reduce vascular cell senescence and SASP factors and improve arterial function in old mice. We found that fisetin decreased cellular senescence in human endothelial cell culture. In old mice, vascular cell senescence and SASP-related inflammation were lower 1 week after the final dose of oral intermittent (1 week on—2 weeks off—1 weeks on dosing) fisetin supplementation. Old fisetin-supplemented mice had higher endothelial function. Leveraging old p16-3MR mice, a transgenic model allowing genetic clearance of p16 INK4A -positive senescent cells, we found that ex vivo removal of senescent cells from arteries isolated from vehicle- but not fisetin-treated mice increased endothelium-dependent dilation, demonstrating that fisetin improved endothelial function through senolysis. Enhanced endothelial function with fisetin was mediated by increased NO bioavailability and reduced cellular- and mitochondrial-related oxidative stress. Arterial stiffness was lower in fisetin-treated mice. Ex vivo genetic senolysis in aorta rings from p16-3MR mice did not further reduce mechanical wall stiffness in fisetin-treated mice, demonstrating lower arterial stiffness after fisetin was due to senolysis. Lower arterial stiffness with fisetin was accompanied by favorable arterial wall remodeling. The findings from this study identify fisetin as promising therapy for clinical translation to target excess cell senescence to treat age-related arterial dysfunction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The air mycobiome is decoupled from the soil mycobiome in the California San Joaquin Valley

Abstract Dispersal is a key force in the assembly of fungal communities and the air is the dominant route of dispersal for most fungi. Understanding the dynamics of airborne fungi is important for determining their source and for helping to prevent fungal disease. This understanding is important in the San Joaquin Valley of California, which is home to 4.2 million people and where the airborne fungus Coccidioides is responsible for the most important fungal disease of otherwise healthy humans, coccidioidomycosis. The San Joaquin Valley is the most productive agricultural region in the United States, with the principal crops grown therein susceptible to fungal pathogens. Here, we characterize the fungal community in soil and air on undeveloped and agricultural land in the San Joaquin Valley using metabarcoding of the internal transcribed spacer 2 variable region of fungal rDNA. Using 1,002 individual samples, we report one of the most extensive studies of fungi sampled simultaneously from air and soil using modern sequencing techniques. We find that the air mycobiome in the San Joaquin Valley is distinct from the soil mycobiome, and that the assemblages of airborne fungi from sites as far apart as 160 km are far more similar to one another than to the fungal communities in nearby soils. Additionally, we present evidence that airborne fungi in the San Joaquin Valley are subject to dispersal limitation and cyclical intra‐annual patterns of community composition. Our findings are broadly applicable to understanding the dispersal of airborne fungi and the taxonomic structure of airborne fungal assemblages.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Imaging beyond the surface region: Probing hidden materials via atomic force microscopy

Probing material properties at surfaces down to the single-particle scale of atoms and molecules has been achieved, but high-resolution subsurface imaging remains a nanometrology challenge due to electromagnetic and acoustic dispersion and diffraction. The atomically sharp probe used in scanning probe microscopy (SPM) has broken these limits at surfaces. Subsurface imaging is possible under certain physical, chemical, electrical, and thermal gradients present in the material. Of all the SPM techniques, atomic force microscopy has entertained unique opportunities for nondestructive and label-free measurements. Here, we explore the physics of the subsurface imaging problem and the emerging solutions that offer exceptional potential for visualization. We discuss materials science, electronics, biology, polymer and composite sciences, and emerging quantum sensing and quantum bio-imaging applications. The perspectives and prospects of subsurface techniques are presented to stimulate further work toward enabling noninvasive high spatial and spectral resolution investigation of materials including meta- and quantum materials.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Methylotrophy in the Mire: direct and indirect routes for methane production in thawing permafrost

While wetlands are major sources of biogenic methane (CH 4 ), our understanding of resident microbial metabolism is incomplete, which compromises the prediction of CH 4 emissions under ongoing climate change. Here, we employed genome-resolved multi-omics to expand our understanding of methanogenesis in the thawing permafrost peatland of Stordalen Mire in Arctic Sweden. In quadrupling the genomic representation of the site’s methanogens and examining their encoded metabolism, we revealed that nearly 20% of the metagenome-assembled genomes (MAGs) encoded the potential for methylotrophic methanogenesis. Further, 27% of the transcriptionally active methanogens expressed methylotrophic genes; for Methanosarcinales and Methanobacteriales MAGs, these data indicated the use of methylated oxygen compounds (e.g., methanol), while for Methanomassiliicoccales, they primarily implicated methyl sulfides and methylamines. In addition to methanogenic methylotrophy, >1,700 bacterial MAGs across 19 phyla encoded anaerobic methylotrophic potential, with expression across 12 phyla. Metabolomic analyses revealed the presence of diverse methylated compounds in the Mire, including some known methylotrophic substrates. Active methylotrophy was observed across all stages of a permafrost thaw gradient in Stordalen, with the most frozen non-methanogenic palsa found to host bacterial methylotrophy and the partially thawed bog and fully thawed fen seen to house both methanogenic and bacterial methylotrophic activities. Methanogenesis across increasing permafrost thaw is thus revised from the sole dominance of hydrogenotrophic production and the appearance of acetoclastic at full thaw to consider the co-occurrence of methylotrophy throughout. Collectively, these findings indicate that methanogenic and bacterial methylotrophy may be an important and previously underappreciated component of carbon cycling and emissions in these rapidly changing wetland habitats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Refinement of the “ Candidatus Accumulibacter” genus based on metagenomic analysis of biological nutrient removal (BNR) pilot-scale plants operated with reduced aeration

Members of the “Candidatus Accumulibacter” genus are widely studied as key polyphosphate-accumulating organisms (PAOs) in biological nutrient removal (BNR) facilities performing enhanced biological phosphorus removal (EBPR). This diverse lineage includes 18 “Ca. Accumulibacter” species, which have been proposed based on the phylogenetic divergence of the polyphosphate kinase 1 (ppk1) gene and genome-scale comparisons of metagenome-assembled genomes (MAGs). Phylogenetic classification based on the 16S rRNA genetic marker has been difficult to attain because most “Ca. Accumulibacter” MAGs are incomplete and often do not include the rRNA operon. Here, we investigate the “Ca. Accumulibacter” diversity in pilot-scale treatment trains performing BNR under low dissolved oxygen (DO) conditions using genome-resolved metagenomics. Using long-read sequencing, we recovered medium- and high-quality MAGs for 5 of the 18 “Ca. Accumulibacter” species, all with rRNA operons assembled, which allowed a reassessment of the 16S rRNA-based phylogeny of this genus and an analysis of phylogeny based on the 23S rRNA gene.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Improved recovery of cell-cycle gene expression in Saccharomyces cerevisiae from regulatory interactions in multiple omics data

Gene expression is regulated by DNA-binding transcription factors (TFs). Together with their target genes, these factors and their interactions collectively form a gene regulatory network (GRN), which is responsible for producing patterns of transcription, including cyclical processes such as genome replication and cell division. However, identifying how this network regulates the timing of these patterns, including important interactions and regulatory motifs, remains a challenging task. Results We employed four in vivo and in vitro regulatory data sets to investigate the regulatory basis of expression timing and phase-specific patterns cell-cycle expression in Saccharomyces cerevisiae . Specifically, we considered interactions based on direct binding between TF and target gene, indirect effects of TF deletion on gene expression, and computational inference. We found that the source of regulatory information significantly impacts the accuracy and completeness of recovering known cell-cycle expressed genes. The best approach involved combining TF-target and TF-TF interactions features from multiple datasets in a single model. In addition, TFs important to multiple phases of cell-cycle expression also have the greatest impact on individual phases. Important TFs regulating a cell-cycle phase also tend to form modules in the GRN, including two sub-modules composed entirely of unannotated cell-cycle regulators ( STE12-TEC1 and RAP1-HAP1-MSN4 ). Conclusion Our findings illustrate the importance of integrating both multiple omics data and regulatory motifs in order to understand the significance regulatory interactions involved in timing gene expression. This integrated approached allowed us to recover both known cell-cycles interactions and the overall pattern of phase-specific expression across the cell-cycle better than any single data set. Likewise, by looking at regulatory motifs in the form of TF-TF interactions, we identified sets of TFs whose co-regulation of target genes was important for cell-cycle expression, even when regulation by individual TFs was not. Overall, this demonstrates the power of integrating multiple data sets and models of interaction in order to understand the regulatory basis of established biological processes and their associated gene regulatory networks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Ozonized biochar filtrate effects on the growth of Pseudomonas putida and cyanobacteria Synechococcus elongatus PCC 7942

Background: Biochar ozonization was previously shown to dramatically increase its cation exchange capacity, thus improving its nutrient retention capacity. The potential soil application of ozonized biochar warrants the need for a toxicity study that investigates its effects on microorganisms. Results: In the study presented here, we found that the filtrates collected from ozonized pine 400 biochar and ozonized rogue biochar did not have any inhibitory effects on the soil environmental bacteria Pseudomonas putida, even at high dissolved organic carbon (DOC) concentrations of 300 ppm. However, the growth of Synechococcus elongatus PCC 7942 was inhibited by the ozonized biochar filtrates at DOC concentrations greater than 75 ppm. Further tests showed the presence of some potential inhibitory compounds (terephthalic acid and p-toluic acid) in the filtrate of non-ozonized pine 400 biochar; these compounds were greatly reduced upon wet-ozonization of the biochar material. Nutrient detection tests also showed that dry-ozonization of rogue biochar enhanced the availability of nitrate and phosphate in its filtrate, a property that may be desirable for soil application. Conclusion: Ozonized biochar substances can support soil environmental bacterium Pseudomonas putida growth, since ozonization detoxifies the potential inhibitory aromatic molecules.

59 BASIC BIOLOGICAL SCIENCES↗