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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 OSTI2021

Generation of Pseudomonas putida KT2440 Strains with Efficient Utilization of Xylose and Galactose via Adaptive Laboratory Evolution

While Pseudomonas putida KT2440 has great potential for biomass-converting processes, its inability to utilize the biomass abundant sugars xylose and galactose has limited its applications. Here, in this study, we utilized Adaptive Laboratory Evolution (ALE) to optimize engineered KT2440 with heterologous expression of xylD encoding xylonate dehydratase from Caulobacter crescentus and galETKM encoding UDP-glucose 4-epimerase, galactose-1-phosphate uridylyltransferase, galactokinase, and galactose-1-epimerase from Escherichia coli K-12 MG1655. Poor starting strain growth (<0.1 h –1 or none) was evolutionarily optimized to rates of up to 0.25 h –1 on xylose and 0.52 h –1 on galactose. Whole-genome sequencing, transcriptomic analysis, and growth screens revealed significant roles of kguT encoding a 2-ketogluconate operon repressor and 2-ketogluconate transporter, and gtsABCD encoding an ATP-binding cassette (ABC) sugar transporting system in xylose and galactose growth conditions, respectively. Finally, we expressed the heterologous indigoidine production pathway in the evolved and unevolved engineered strains and successfully produced 3.2 g/L and 2.2 g/L from 10 g/L of either xylose or galactose in the evolved strains whereas the unevolved strains did not produce any detectable product. Thus, the generated KT2440 strains have the potential for broad application as optimized platform chassis to develop efficient microorganism-based biomass-utilizing bioprocesses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

p190RhoGAP proteins contain pseudoGTPase domains

The two p190RhoGAP proteins, p190RhoGAP-A and -B, are key regulators of Rho GTPase signaling and are essential for actin cytoskeletal structure and contractility. Here we report the discovery of two evolutionarily conserved GTPase-like domains located in the ‘middle domain’, previously thought to be unstructured. Deletion of these domains reduces RhoGAP activity. Crystal structures, MANT-GTPγS binding, thermal denaturation, biochemical assays and sequence homology analysis all strongly support defects in nucleotide-binding activity. Analysis of p190RhoGAP proteins therefore indicates the presence of two previously unidentified domains which represent an emerging group of pseudoenzymes, the pseudoGTPases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Structural underpinnings of Ric8A function as a G-protein α-subunit chaperone and guanine-nucleotide exchange factor

Resistance to inhibitors of cholinesterase 8A (Ric8A) is an essential regulator of G protein α-subunits (Gα), acting as a guanine nucleotide exchange factor and a chaperone. We report two crystal structures of Ric8A, one in the apo form and the other in complex with a tagged C-terminal fragment of Gα. These structures reveal two principal domains of Ric8A: an armadillo-fold core and a flexible C-terminal tail. Additionally, they show that the Gα C-terminus binds to a highly-conserved patch on the concave surface of the Ric8A armadillo-domain, with selectivity determinants residing in the Gα sequence. Biochemical analysis shows that the Ric8A C-terminal tail is critical for its stability and function. A model of the Ric8A/Gα complex derived from crosslinking mass spectrometry and molecular dynamics simulations suggests that the Ric8A C-terminal tail helps organize the GTP-binding site of Gα. This study lays the groundwork for understanding Ric8A function at the molecular level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Cut site preference allows influenza A virus PA-X to discriminate between host and viral mRNAs

Many viruses block host gene expression to take over the infected cell. This process, termed host shutoff, is thought to promote viral replication by preventing antiviral responses and redirecting cellular resources to viral processes. Several viruses from divergent families accomplish host shutoff through RNA degradation by endoribonucleases. However, viruses also need to ensure expression of their own genes. The influenza A virus endoribonuclease PA-X solves this problem by sparing viral mRNAs and some host RNAs necessary for viral replication. Here, to understand how PA-X distinguishes between RNAs, we characterized PA-X cut sites transcriptome-wide using 5' rapid amplification of complementary DNA ends coupled to high-throughput sequencing. This analysis, along with RNA structure predictions and validation experiments using reporters, shows that PA-Xs from multiple influenza strains preferentially cleave RNAs at GCUG tetramers in hairpin loops. Importantly, GCUG tetramers are enriched in the human but not the influenza transcriptome. Moreover, optimal PA-X cut sites inserted in the influenza A virus genome are quickly selected against during viral replication in cells. This finding suggests that PA-X evolved these cleavage characteristics to preferentially target host over viral mRNAs in a manner reminiscent of cellular self versus non-self discrimination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Naturally ornate RNA-only complexes revealed by cryo-EM

The structures of natural RNAs remain poorly characterized and may hold numerous surprises. Here we report three-dimensional structures of three large ornate bacterial RNAs using cryo-electron microscopy (cryo-EM). GOLLD (Giant, Ornate, Lake- and Lactobacillales-Derived), ROOL (Rumen-Originating, Ornate, Large) and OLE (Ornate Large Extremophilic) RNAs form homo-oligomeric complexes whose stoichiometries are retained at lower concentrations than measured in cells. OLE RNA forms a dimeric complex with long co-axial pipes spanning two monomers. Both GOLLD and ROOL form distinct RNA-only multimeric nanocages with diameters larger than the ribosome, each empty except for a disordered loop. Extensive intramolecular and intermolecular A-minor interactions, kissing loops, an unusual A–A helix and other interactions stabilize the three complexes. Sequence covariation analysis of these large RNAs reveals evolutionary conservation of intermolecular interactions, supporting the biological importance of large, ornate RNA quaternary structures that can assemble without any involvement of proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Dynamics of Intact MexAB-OprM Efflux Pump: Focusing on the MexA-OprM Interface

Antibiotic efflux is one of the most critical mechanisms leading to bacterial multidrug resistance. Antibiotics are effluxed out of the bacterial cell by a tripartite efflux pump, a complex machinery comprised of outer membrane, periplasmic adaptor, and inner membrane protein components. Understanding the mechanism of efflux pump assembly and its dynamics could facilitate discovery of novel approaches to counteract antibiotic resistance in bacteria. We built here an intact atomistic model of the Pseudomonas aeruginosa MexAB-OprM pump in a Gram-negative membrane model that contained both inner and outer membranes separated by a periplasmic space. All-atom molecular dynamics (MD) simulations confirm that the fully assembled pump is stable in the microsecond timescale. Using a combination of all-atom and coarse-grained MD simulations and sequence covariation analysis, we characterized the interface between MexA and OprM in the context of the entire efflux pump. These analyses suggest a plausible mechanism by which OprM is activated via opening of its periplasmic aperture through a concerted interaction with MexA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Development of a high-productivity, halophilic, thermotolerant microalga Picochlorum renovo

Abstract Microalgae are promising biocatalysts for applications in sustainable fuel, food, and chemical production. Here, we describe culture collection screening, down-selection, and development of a high-productivity, halophilic, thermotolerant microalga, Picochlorum renovo . This microalga displays a rapid growth rate and high diel biomass productivity (34 g m −2 day −1 ), with a composition well-suited for downstream processing. P. renovo exhibits broad salinity tolerance (growth at 107.5 g L −1 salinity) and thermotolerance (growth up to 40 °C), beneficial traits for outdoor cultivation. We report complete genome sequencing and analysis, and genetic tool development suitable for expression of transgenes inserted into the nuclear or chloroplast genomes. We further evaluate mechanisms of halotolerance via comparative transcriptomics, identifying novel genes differentially regulated in response to high salinity cultivation. These findings will enable basic science inquiries into control mechanisms governing Picochlorum biology and lay the foundation for development of a microalga with industrially relevant traits as a model photobiology platform.

09 BIOMASS FUELS↗
DOE OSTI2017

The crystal structure of pseudokinase PEAK1 (Sugen kinase 269) reveals an unusual catalytic cleft and a novel mode of kinase fold dimerization

The pseudokinase group encompasses some 10% of protein kinases, but pseudokinases diverge from canonical kinases in key motifs. The two members of the small new kinase family 3 (NKF3) group are considered pseudokinases. These proteins, pseudopodium-enriched atypical kinase 1 (PEAK1, Sugen kinase 269, or SgK269) and pragmin (Sugen kinase 223 or SgK223), act as scaffolds in growth factor signaling pathways, and both contain a kinase fold with degraded kinase motifs at their C termini. These kinases may harbor regions that mediate oligomerization or control other aspects of signal transduction, but a lack of structural information has precluded detailed investigations into their functional roles. In this study reported herein, we determined the X-ray crystal structure of the PEAK1 pseudokinase domain to 2.3 Å resolution. The structure revealed that the PEAK1 kinase-like domain contains a closed nucleotide-binding cleft that in this conformation may deleteriously affect nucleotide binding. Moreover, we found that N- and C-terminal extensions create a highly unusual all α-helical split-dimerization region, termed here the split helical dimerization (SHED) region. Sequence conservation analysis suggested that this region facilitates a dimerization mode that is conserved between PEAK1 and pragmin. Finally, we observed structural similarities between the PEAK1 SHED region and the C-terminal extension of the Parkinson's disease-associated kinase PINK1. In summary, PEAK1's kinase cleft is occluded, and its newly identified SHED region may promote an unexpected dimerization mode. Similarities of PEAK1 with the active kinase PINK1 may reclassify the latter as a member of the new kinase family 3 group.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Partitioning of Ca to metastable precipitates in a Mg-rare earth alloy

The potential effect of the element Ca on the precipitation behavior was investigated in an Mg-rare earth alloy. A combination of metastable β''' and β' precipitates was observed for the peak aging condition at 200°C. Ca addition was found to have no significant effect on the precipitating phases and evolution sequence. Composition analysis showed that the Ca partitioned to both β''' and β' precipitate phases. First-principles calculations indicated that Ca partitions to the rare-earth sublattice in the precipitate phase. This finding suggests the potential of Ca to partially replace costly rare-earth elements in precipitation-hardened Mg-rare earth alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Snekmer: a scalable pipeline for protein sequence fingerprinting based on amino acid recoding

Abstract Motivation The vast expansion of sequence data generated from single organisms and microbiomes has precipitated the need for faster and more sensitive methods to assess evolutionary and functional relationships between proteins. Representing proteins as sets of short peptide sequences (kmers) has been used for rapid, accurate classification of proteins into functional categories; however, this approach employs an exact-match methodology and thus may be limited in terms of sensitivity and coverage. We have previously used similarity groupings, based on the chemical properties of amino acids, to form reduced character sets and recode proteins. This amino acid recoding (AAR) approach simplifies the construction of protein representations in the form of kmer vectors, which can link sequences with distant sequence similarity and provide accurate classification of problematic protein families. Results Here, we describe Snekmer, a software tool for recoding proteins into AAR kmer vectors and performing either (i) construction of supervised classification models trained on input protein families or (ii) clustering for de novo determination of protein families. We provide examples of the operation of the tool against a set of nitrogen cycling families originally collected using both standard hidden Markov models and a larger set of proteins from Uniprot and demonstrate that our method accurately differentiates these sequences in both operation modes. Availability and implementation Snekmer is written in Python using Snakemake. Code and data used in this article, along with tutorial notebooks, are available at http://github.com/PNNL-CompBio/Snekmer under an open-source BSD-3 license. Supplementary information Supplementary data are available at Bioinformatics Advances online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Energy metric prediction for double insertion mutants via the RoseNet deep learning framework

Studying the structural and functional implications of protein mutations is an important task in computational biology and bioinformatics. We leverage our previously proposed RoseNet neural network architecture to predict energy metrics of proteins with double amino acid insertions or deletions (InDels). We train models on previously generated benchmark datasets containing the exhaustive double InDel mutations for three proteins, as well as an additional three proteins for which ∼145k random mutants, each with two InDels, have been generated. We expand on our previous work by evaluating three additional proteins and analyzing domain features that impact the prediction capabilities of RoseNet. These features include InDels into secondary structures and the solvent accessible surface area (SASA) scores of the residues. We uncover further evidence to support that RoseNet has a higher proficiency of generalizing to unseen residue combinations than unseen insertion positions. We also observe that RoseNet produces higher-quality predictions when inserting into a β-sheet over an α-helix. Additionally, when the insertions fall in an area of high SASA, RoseNet often displays better performance than inserting into areas of low SASA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

EC-Bench: A Benchmark for Enzyme Commission Number Prediction

Enzymes are proteins that catalyze specific biochemical reactions in cells. Enzyme Commission (EC) numbers are used to annotate enzymes in a four-level hierarchy that classifies enzymes based on the specific chemical reactions they catalyze. Accurate EC number prediction is essential for understanding enzyme functions. Despite the availability of numerous methods for predicting EC numbers from protein sequences, there is no unified framework for evaluating and studying such methods systematically. This gap limits the ability of the community to identify the most effective approaches for enzyme annotation. We introduce EC-Bench, a benchmark for EC number prediction, consisting of 1) an initial representative set of existing methods (including homology-based, deep learning, contrastive learning, and language model methods), 2) existing and novel accuracy and efficiency performance metrics, and 3) selected datasets to allow for comprehensive comparative study. EC-Bench is open-source and provides a framework for researchers to not only compare among existing methods objectively under uniform conditions, but also to introduce and effectively evaluate performance of new methods in a comparative framework. To demonstrate the utility of EC-Bench, we perform extensive experimentation to compare the existing EC number prediction methods and establish their advantages and disadvantages in a variety of prediction tasks, namely “exact EC number prediction”, “EC number completion” and (partial or additional) “EC number recommendation”. We find wide variation in the performance of different methods, but also subtle but potentially useful differences in the performance of different methods across tasks and for different parts of the EC hierarchy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

SpaRC: scalable sequence clustering using Apache Spark

MOTIVATION: Whole genome shotgun based next-generation transcriptomics and metagenomics studies often generate 100-1000 GB sequence data derived from tens of thousands of different genes or microbial species. Assembly of these data sets requires tradeoffs between scalability and accuracy. Current assembly methods optimized for scalability often sacrifice accuracy and vice versa. An ideal solution would both scale and produce optimal accuracy for individual genes or genomes. RESULTS: In this work we describe an Apache Spark-based scalable sequence clustering application, SparkReadClust (SpaRC), that partitions reads based on their molecule of origin to enable downstream assembly optimization. SpaRC produces high clustering performance on transcriptomes and metagenomes from both short and long read sequencing technologies. It reaches near-linear scalability with input data size and number of compute nodes. SpaRC can run on both cloud computing and HPC environments without modification while delivering similar performance. Our findings demonstrate that SpaRC provides a scalable solution for clustering billions of reads from next-generation sequencing experiments, and Apache Spark represents a cost-effective solution with rapid development/deployment cycles for similar large-scale sequence data analysis problems. AVAILABILITY AND IMPLEMENTATION: https://bitbucket.org/berkeleylab/jgi-sparc.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Homologous Recombination and Transposon Propagation Shape the Population Structure of an Organism from the Deep Subsurface with Minimal Metabolism

DPANN archaea are primarily known based on genomes from metagenomes and single cells. We reconstructed a complete population genome for Candidatus "Forterrea," a Diapherotrite with a predicted symbiotic lifestyle probably centered around nucleotide metabolism and RuBisCO. Genome-wide analysis of sequence variation provided insights into the processes that shape its population structure in the deep subsurface. The genome contains many transposons, yet reconstruction of a complete genome from a short-read insert data set was possible because most occurred only in some individuals. Accuracy of the final reconstruction could be verified because the genome displays the pattern of cumulative GC skew known for some archaea but more typically associated with bacteria. Sequence variation is highly localized, and most pronounced around transposons and relatively close to the origin of replication. Patterns of variation are best explained by homologous recombination, a process previously not described for DPANN archaea.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Time Sequence Machine Learning-Based Data Intrusion Detection for Smart Voltage Source Converter-Enabled Power Grid

Smart inverters of distributed energy resources can enable cloud computing, condition monitoring, result visualization, remote control, and peer-to-peer energy trading in advanced power systems. However, the advent of data injection attacks in the communication architecture can alter measurement characteristics of power grids and have devastating consequences. In this article, we propose a time sequence machine learning-based anomaly detection methodology for detecting cyber intrusion into control signal setpoints and dc voltage signal measurement bias of the voltage source converter (VSC) in wind generators. We first investigated the effects of four types of denial of service, tampering signal, and stealthy-type data intrusion attacks on smart VSCs and overall wind farms. We then proposed a novel time sequence machine learning-based intrusion detection framework that can be implemented to detect different cyberattacks in the VSCs. The performance of the proposed framework has been compared with that of autoencoder and clustering-based intrusion detection framework. The proposed framework was validated by using the IEEE 39 bus power system in the presence of four wind farms in different locations. Using several metrics for intrusion detection performance, we validated the effectiveness of the proposed framework.

42 ENGINEERING↗
DOE OSTI2021

Correction for Thompson et al., “Fatty Acid and Alcohol Metabolism in Pseudomonas putida : Functional Analysis Using Random Barcode Transposon Sequencing”

Volume 86, no. 21, 2020, e01665-20, https://doi.org/10.1128/AEM.01665-20. Readers should note that when the authors created the deletion mutant of PP_2675, they deleted the entire region between the gene’s start and stop codons. However, this also deleted the DNA that codes for the first 14 amino acids of the overlapping ORF PP_2676. Additionally, the originally published URL for the JBEI public strain repository was incorrect. The correct link to all strains and plasmids in this study is https://public-registry.jbei .org/folders/641.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Nitrate-Utilizing Microorganisms Resistant to Multiple Metals from the Heavily Contaminated Oak Ridge Reservation.

Contamination of environments with nitrate generated by industrial processes and the use of nitrogen-containing fertilizers is a growing problem worldwide. While nitrate can be removed from contaminated areas by microbial denitrification, nitrate frequently occurs with other contaminants, such as heavy metals, that have the potential to impede the process. In this work, nitrate-reducing microorganisms were enriched and isolated from both groundwater and sediments at the Oak Ridge Reservation (ORR) using concentrations of nitrate and metals (Al, Mn, Fe, Co, Ni, Cu, Cd, and U) similar to those observed in a contaminated environment at ORR. Seven new metal-resistant, nitrate-reducing strains were characterized, and their distribution across both noncontaminated and contaminated areas at ORR was examined. Additionally, while the seven strains have various pH ranges for growth, carbon source preferences, and degrees of resistance to individual and combinations of metals, all were able to reduce nitrate at similar rates both in the presence and absence of the mixture of metals found in the contaminated ORR environment. Four strains were identified in groundwater samples at different ORR locations by exact 16S RNA sequence variant analysis, and all four were found in both noncontaminated and contaminated areas. By using environmentally relevant metal concentrations, we successfully isolated multiple organisms from both ORR noncontaminated and contaminated environments that are capable of reducing nitrate in the presence of extreme mixed-metal contamination.IMPORTANCE Nitrate contamination is a global issue that affects groundwater quality. In some cases, cocontamination of groundwater with nitrate and mixtures of heavy metals could decrease microbially mediated nitrate removal, thereby increasing the duration of nitrate contamination. In this study, we used metal and nitrate concentrations that are present in a contaminated site at the Oak Ridge Reservation to isolate seven metal-resistant strains. All were able to reduce nitrate in the presence of high concentrations of a mixture of heavy metals. Four of seven strains were located in pristine as well as contaminated sites at the Oak Ridge Reservation. Further study of these nitrate-reducing strains will uncover mechanisms of resistance to multiple metals that will increase our understanding of the effect of nitrate and metal contamination on groundwater microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Fatty Acid and Alcohol Metabolism in Pseudomonas putida: Functional Analysis Using Random Barcode Transposon Sequencing.

With its ability to catabolize a wide variety of carbon sources and a growing engineering toolkit, Pseudomonas putida KT2440 is emerging as an important chassis organism for metabolic engineering. Despite advances in our understanding of the organism, many gaps remain in our knowledge of the genetic basis of its metabolic capabilities. The gaps are particularly noticeable in our understanding of both fatty acid and alcohol catabolism, where many paralogs putatively coding for similar enzymes coexist, making biochemical assignment via sequence homology difficult. To rapidly assign function to the enzymes responsible for these metabolisms, we leveraged random barcode transposon sequencing (RB-Tn-Seq). Global fitness analyses of transposon libraries grown on 13 fatty acids and 10 alcohols produced strong phenotypes for hundreds of genes. Fitness data from mutant pools grown on fatty acids of varying chain lengths indicated specific enzyme substrate preferences and enabled us to hypothesize that DUF1302/DUF1329 family proteins potentially function as esterases. From the data, we also postulate catabolic routes for the two biogasoline molecules isoprenol and isopentanol, which are catabolized via leucine metabolism after initial oxidation and activation with coenzyme A (CoA). Because fatty acids and alcohols may serve as both feedstocks and final products of metabolic-engineering efforts, the fitness data presented here will help guide future genomic modifications toward higher titers, rates, and yields. IMPORTANCE To engineer novel metabolic pathways into P. putida , a comprehensive understanding of the genetic basis of its versatile metabolism is essential. Here, we provide functional evidence for the putative roles of hundreds of genes involved in the fatty acid and alcohol metabolism of the bacterium. These data provide a framework facilitating precise genetic changes to prevent product degradation and to channel the flux of specific pathway intermediates as desired.

59 BASIC BIOLOGICAL SCIENCES↗