Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Base Sequence”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Microbial Dark Matter: Unusual intervening sequences in 16S rRNA genes of candidate phyla from the deep subsurface

The Microbial Dark Matter project has sequenced genomes from over 200 single cells from candidate phyla, greatly expanding our knowledge of the ecology, inferred metabolism, and evolution of these widely distributed, yet poorly understood lineages. The second phase of this project aims to sequence an additional 800 single cells from known as well as potentially novel candidate phyla derived from a variety of environments. In order to identify whole genome amplified single cells, screening based on phylogenetic placement of 16S rRNA gene sequences is being conducted. Briefly, derived 16S rRNA gene sequences are aligned to a custom version of the Greengenes reference database and added to a reference tree in ARB using parsimony. In multiple samples from deep subsurface habitats but not from other habitats, a large number of sequences proved difficult to align and therefore to place in the tree. Based on comparisons to reference sequences and structural alignments using SSU-ALIGN, many of these ?difficult? sequences appear to originate from candidate phyla, and contain intervening sequences (IVSs) within the 16S rRNA genes. These IVSs are short (39 - 79 nt) and do not appear to be self-splicing or to contain open reading frames. IVSs were found in the loop regions of stem-loop structures in several different taxonomic groups. Phylogenetic placement of sequences is strongly affected by IVSs; two out of three groups investigated were classified as different phyla after their removal. Based on data from samples screened in this project, IVSs appear to be more common in microbes occurring in deep subsurface habitats, although the reasons for this remain elusive.

09 BIOMASS FUELS↗
DOE OSTI2017

basecRAWller v0.1

This software implements the first base caller for nanopore data that calls bases directly from raw data. The basecRAWller algorithm has two major advantages over current nanopore base calling software: (1) streaming base calling and (2) base calling from information rich raw signal. The ability to perform truly streaming base calling as signal is received from the sequencer can be very powerful as this is one of the major advantages of this technology as compared to other sequencing technologies. As such enabling as much streaming potential as possible will be incredibly important as this technology continues to become more widely applied in biosciences. All other base callers currently employ the Viterbi algorithm which requires the whole sequence to employ the complete base calling procedure and thus precludes a natural streaming base calling procedure. The other major advantage of the basecRAWller algorithm is the prediction of bases from raw signal which contains much richer information than the segmented chunks that current algorithms employ. This leads to the potential for much more accurate base calls which would make this technology much more valuable to all of the growing user base for this technology.

Brown, JamesB↗
DOE OSTI2015

ProDeGe: A computational protocol for fully automated decontamination of genomes

Single amplified genomes and genomes assembled from metagenomes have enabled the exploration of uncultured microorganisms at an unprecedented scale. However, both these types of products are plagued by contamination. Since these genomes are now being generated in a high-throughput manner and sequences from them are propagating into public databases to drive novel scientific discoveries, rigorous quality controls and decontamination protocols are urgently needed. Here, we present ProDeGe (Protocol for fully automated Decontamination of Genomes), the first computational protocol for fully automated decontamination of draft genomes. ProDeGe classifies sequences into two classes—clean and contaminant—using a combination of homology and feature-based methodologies. On average, 84% of sequence from the non-target organism is removed from the data set (specificity) and 84% of the sequence from the target organism is retained (sensitivity). Lastly, the procedure operates successfully at a rate of ~0.30 CPU core hours per megabase of sequence and can be applied to any type of genome sequence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Multiple Lines of Evidences Reveal Mechanisms Underpinning Mercury Resistance and Volatilization by Stenotrophomonas sp. MA5 Isolated from the Savannah River Site (SRS), USA

A largely understudied microbially mediated mercury (Hg) bioremediative pathway includes the volatilization of Hg 2+ to Hg 0 . Therefore, studies on Hg resistant bacteria (HgR), isolated from historically long-term contaminated environments, can serve as models to understand mechanisms underpinning Hg cycling. Towards this end, a mercury resistant bacterial strain, identified as Stenotrophomonas sp., strain MA5, was isolated from Mill Branch on the Savannah River Site (SRS); an Hg-impacted ecosystem. Minimum inhibitory concentration (MIC) analysis showed Hg resistance of up to 20 µg/mL by MA5 with 95% of cells retaining viability. Microcosm studies showed that the strain depleted more than 90% of spiked Hg 2+ within the first 24 h of growth and the detection of volatilized mercury indicated that the strain was able to reduce Hg 2+ to Hg 0 . To understand molecular mechanisms of Hg volatilization, a draft whole genome sequence was obtained, annotated and analyzed, which revealed the presence of a transposon-derived mer operon (merRTPADE) in MA5, known to transport and reduce Hg 2+ into Hg 0 . Based on the whole genome sequence of strain MA5, qRT-PCR assays were designed on merRTPADE, we found a ~40-fold higher transcription of mer T, P, A, D and E when cells were exposed to 5 µg/mL Hg 2+ . Interestingly, strain MA5 increased cellular size as a function of increasing Hg concentrations, which is likely an evolutionary response mechanism to cope with Hg stress. Moreover, metal contaminated environments are shown to co-select for antibiotic resistance. When MA5 was screened for antibiotic resistance, broad resistance against penicillin, streptomycin, tetracycline, ampicillin, rifampicin, and erythromycin was found; this correlated with the presence of multiple gene determinants for antibiotic resistance within the whole genome sequence of MA5. Overall, this study provides an in-depth understanding of the underpinnings of Stenotrophomonas-mercury interactions that facilitate cellular survival in a contaminated soil habitat.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Novel Grid-forming Voltage Control Strategy for Supplying Unbalanced Microgrid Loads Using Inverter-based Resources

This paper presents a novel grid-forming voltage control strategy for a battery energy storage system to maintain balanced three-phase output voltages when serving unbalanced loads. A stationary reference frame (αβ) based control scheme is proposed to regulate positive-sequence and negative-sequence voltages. Compared with the conventional rotating reference frame (dq) based control scheme, the proposed scheme shows better dynamic performance. Then, we analyze the system zero-sequence network and propose adding a grounding transformer to the Y/Yg connected output transformer to further reduce the voltage unbalance at the point of common coupling. The simulation results demonstrate the effective performance of the proposed voltage control scheme. Based on the results, the power-voltage unbalance curve is derived for different output transformer configurations to establish the relationship between the power unbalance limit and the voltage unbalance limit for microgrid power scheduling.

Xu, Bei↗
DOE OSTI2017

Anomaly Detection in Moving-Camera Video Sequences Using Principal Subspace Analysis

This study presents a family of algorithms based on sparse decompositions that detect anomalies in video sequences obtained from slow moving cameras. These algorithms start by computing the union of subspaces that best represents all the frames from a reference (anomaly free) video as a low-rank projection plus a sparse residue. Then, they perform a low-rank representation of a target (possibly anomalous) video by taking advantage of both the union of subspaces and the sparse residue computed from the reference video. Such algorithms provide good detection results while at the same time obviating the need for previous video synchronization. However, this is obtained at the cost of a large computational complexity, which hinders their applicability. Another contribution of this paper approaches this problem by using intrinsic properties of the obtained data representation in order to restrict the search space to the most relevant subspaces, providing computational complexity gains of up to two orders of magnitude. The developed algorithms are shown to cope well with videos acquired in challenging scenarios, as verified by the analysis of 59 videos from the VDAO database that comprises videos with abandoned objects in a cluttered industrial scenario.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Tuning the Cavity Size and Chirality of Self-Assembling 3D DNA Crystals

The foundational goal of structural DNA nanotechnology—the field that uses oligonucleotides as a molecular building block for the programmable self-assembly of nanostructured systems—was to use DNA to construct three-dimensional (3D) lattices for solving macromolecular structures. The programmable nature of DNA makes it an ideal system for rationally constructing self-assembled crystals and immobilizing guest molecules in a repeating 3D array through their specific stereospatial interactions with the scaffold. In this work, we have extended a previously described motif (4 × 5) by expanding the structure to a system that links four double-helical layers; we use a central weaving oligonucleotide containing a sequence of four six-base repeats (4 × 6), forming a matrix of layers that are organized and dictated by a series of Holliday junctions. In addition, we have assembled mirror image crystals (l-DNA) with the identical sequence that are completely resistant to nucleases. Bromine and selenium derivatives were obtained for the l- and d-DNA forms, respectively, allowing phase determination for both forms and solution of the resulting structures to 3.0 and 3.05 Å resolution. Both right- and left-handed forms crystallized in the trigonal space groups with mirror image 3-fold helical screw axes P32 and P31 for each motif, respectively. The structures reveal a highly organized array of discrete and well-defined cavities that are suitable for hosting guest molecules and allow us to dictate a priori the assembly of guest–DNA conjugates with a specified crystalline hand.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Interplay between spin-orbit coupling and strong correlation effects: Comparison of the three osmate double perovskites Ba 2 AOsO 6 (A=Na, Ca, Y)

High formal valence Os-based double perovskites are a focus of current interest because they display strong interplay of large spin-orbit coupling and strong electronic correlation. Here we present the electronic and magnetic characteristics of a sequence of three cubic Os based double perovskites Ba 2 AOsO 6 (A=Na, Ca, Y), with formal valences of Os +7 (d 1 ),Os +6 (d 2 ), and Os +5 (d 3 ). For these first principles based calculations we apply an “exact exchange for correlated electrons” functional, with exact exchange applied in a hybrid fashion solely to the Os (5d) states. While Ba 2 NaOsO 6 is a reported ferromagnetic Dirac-Mott insulator studied previously, the other two show antiferromagnetic ordering while all retain the undistorted cubic structure. For comparison purposes we have investigated only the ferromagnetic ordered phase. A metal-insulator transition is predicted to occur upon rotating the direction of magnetization in all three materials, reflecting the central role of spin-orbit coupling in these small gap osmates. Surprises arising from comparing formal charge states with the radial charge densities are discussed. Chemical shielding factors and orbital susceptibilities are provided for comparison with future nuclear magnetic resonance data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Preliminary Economics for Hydrocarbon Fuel Production from Cellulosic Sugars

Biorefinery process and economic models built in CHEMCAD and a preliminary, genome-scale metabolic model for the oleaginous yeast Lipomyces starkeyi were used to simulate the bioconversion of corn stover to lipids, and the upgrading of these hydrocarbon precursors to diesel and jet fuel. The metabolic model was based on the recently released genome sequence for L. starkeyi and on metabolic pathway information from the literature. The process model was based on bioconversion, lipid extraction, and lipid oil upgrading data found in literature, on new laboratory experimental data, and on yield predictions from the preliminary L. starkeyi metabolic model. The current plant gate production cost for a distillate-range hydrocarbon fuel was estimated by the process model Base Case to be $\$9.5$ /gallon ($\$9.0$ /gallon of gasoline equivalent) with assumptions of 2011 $\$US$, 10% internal return on investment, and 2205 ton/day dry feed rate. Opportunities for reducing the cost to below $\$5.0$ /gallon, such as improving bioconversion lipid yield and hydrogenation catalyst selectivity, are presented in a Target Case. The process and economic models developed for this work will be updated in 2014 with new experimental data and predictions from a refined metabolic network model for L. starkeyi. Attaining a production cost of $\$3.0$ /gallon will require finding higher value uses for lignin other than power generation, such as conversion to additional fuel or to a co-product.

Collett, James R.↗
DOE OSTI2022

Classification of bacterial plasmid and chromosome derived sequences using machine learning

Plasmids are important genetic elements that facilitate horizonal gene transfer between bacteria and contribute to the spread of virulence and antimicrobial resistance. Most bacterial genome sequences in the public archives exist in draft form with many contigs, making it difficult to determine if a contig is of chromosomal or plasmid origin. Using a training set of contigs comprising 10,584 chromosomes and 10,654 plasmids from the PATRIC database, we evaluated several machine learning models including random forest, logistic regression, XGBoost, and a neural network for their ability to classify chromosomal and plasmid sequences using nucleotide k-mers as features. Based on the methods tested, a neural network model that used nucleotide 6-mers as features that was trained on randomly selected chromosomal and plasmid subsequences 5kb in length achieved the best performance, outperforming existing out-of-the-box methods, with an average accuracy of 89.38% ± 2.16% over a 10-fold cross validation. The model accuracy can be improved to 92.08% by using a voting strategy when classifying holdout sequences. In both plasmids and chromosomes, subsequences encoding functions involved in horizontal gene transfer—including hypothetical proteins, transporters, phage, mobile elements, and CRISPR elements—were most likely to be misclassified by the model. This study provides a straightforward approach for identifying plasmid-encoding sequences in short read assemblies without the need for sequence alignment-based tools.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera

This research was initiated as a part of the Advanced Sensor and Imaging System Technology (ASSIST) program at NASA Langley Research Center. The primary goal of this research is the development of image analysis algorithms for the detection of runways and other objects using an on-board camera. Initial effort was concentrated on images acquired using a passive millimeter wave (PMMW) sensor. The images obtained using PMMW sensors under poor visibility conditions due to atmospheric fog are characterized by very low spatial resolution but good image contrast compared to those images obtained using sensors operating in the visible spectrum. Algorithms developed for analyzing these images using a model of the runway and other objects are described in Part 1 of this report. Experimental verification of these algorithms was limited to a sequence of images simulated from a single frame of PMMW image. Subsequent development and evaluation of algorithms was done using video image sequences. These images have better spatial and temporal resolution compared to PMMW images. Algorithms for reliable recognition of runways and accurate estimation of spatial position of stationary objects on the ground have been developed and evaluated using several image sequences. These algorithms are described in Part 2 of this report. A list of all publications resulting from this work is also included.

Kasturi, Rangachar↗
DOE OSTI2019

Can MR elastography be used to measure liver stiffness in patients with iron overload?

Untreated hepatic iron overload causes hepatic fibrosis and cirrhosis and can predispose to hepatocellular carcinoma. MR elastography (MRE) provides a non-invasive means to measure liver stiffness, which correlates with liver fibrosis but standard gradient recalled echo (GRE)-based MRE techniques fail in patients with high iron due to very low hepatic signal. Short echo time (TE) 2D spin echo echoplanar imaging (SE-EPI)-based MRE may allow measurement of stiffness in the iron loaded liver. The purpose of this study was to describe the use of such an MRE sequence in patients undergoing liver iron quantification by MRI. In our preliminary study of 43 patients with mean LIC of 9.3 mg/g (range 1.8–21.5 mg/g), liver stiffness measurements could be made in 77% (33/43) of patients with a short TE, SE-EPI based MRE sequence. On average, mean LIC in patients with failed MRE was higher than in those with successful MRE (15.9 mg/g dry weight vs. 7.3 mg/g), but a cut-off value for successful MRE could not be established. Seven patients (21% of those with successful MRE) had liver stiffness values suggestive of the presence of significant fibrosis (> 2.49 kPa). A short TE, SE-EPI based MR elastography sequence allows successful measurement of liver stiffness in a majority of patients with liver iron loading, potentially allowing non-invasive screening for fibrosis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

EVOLUTIONARY TRACKS FOR BETELGEUSE

We have constructed a series of nonrotating quasi-hydrostatic evolutionary models for the M2 Iab supergiant Betelgeuse (α Orionis). Our models are constrained by multiple observed values for the temperature, luminosity, surface composition, and mass loss for this star, along with the parallax distance and high-resolution imagery that determines its radius. We have then applied our best-fit models to analyze the observed variations in surface luminosity and the size of detected surface bright spots as the result of up-flowing convective material from regions of high temperature in the surface convective zone. We also attempt to explain the intermittently observed periodic variability in a simple radial linear adiabatic pulsation model. Based on the best fit to all observed data, we suggest a best progenitor mass estimate of 20{sub −3}{sup +5} M{sub ⊙} and a current age from the start of the zero-age main sequence of 8.0–8.5 Myr based on the observed ejected mass while on the giant branch.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Genomic analysis of 1710 surveillance-based Neisseria gonorrhoeae isolates from the USA in 2019 identifies predominant strain types and chromosomal antimicrobial-resistance determinants

This study characterized high-quality whole-genome sequences of a sentinel, surveillance-based collection of 1710 Neisseria gonorrhoeae (GC) isolates from 2019 collected in the USA as part of the Gonococcal Isolate Surveillance Project (GISP). It aims to provide a detailed report of strain diversity, phylogenetic relationships and resistance determinant profiles associated with reduced susceptibilities to antibiotics of concern. The 1710 isolates represented 164 multilocus sequence types and 21 predominant phylogenetic clades. Common genomic determinants defined most strains’ phenotypic, reduced susceptibility to current and historic antibiotics (e.g. bla TEM plasmid for penicillin, tetM plasmid for tetracycline, gyrA for ciprofloxacin, 23S rRNA and/or mosaic mtr operon for azithromycin, and mosaic penA for cefixime and ceftriaxone). The most predominant phylogenetic clade accounted for 21 % of the isolates, included a majority of the isolates with low-level elevated MICs to azithromycin (2.0 µg ml –1 ), carried a mosaic mtr operon and variants in PorB, and showed expansion with respect to data previously reported from 2018. The second largest clade predominantly carried the GyrA S91F variant, was largely ciprofloxacin resistant (MIC ≥1.0 µg ml –1 ), and showed significant expansion with respect to 2018. Overall, a low proportion of isolates had medium- to high-level elevated MIC to azithromycin ((≥4.0 µg ml –1 ), based on C2611T or A2059G 23S rRNA variants). One isolate carried the penA 60.001 allele resulting in elevated MICs to cefixime and ceftriaxone of 1.0 µg ml –1 . This high-resolution snapshot of genetic profiles of 1710 GC sequences, through a comparison with 2018 data (1479 GC sequences) within the sentinel system, highlights change in proportions and expansion of select GC strains and the associated genetic mechanisms of resistance. The knowledge gained through molecular surveillance may support rapid identification of outbreaks of concern. Continued monitoring may inform public health responses to limit the development and spread of antibiotic-resistant gonorrhoea.

(3-6) antimicrobial resistance↗
DOE OSTI2015

The Release 6 reference sequence of the Drosophila melanogaster genome

Drosophila melanogaster plays an important role in molecular, genetic, and genomic studies of heredity, development, metabolism, behavior, and human disease. The initial reference genome sequence reported more than a decade ago had a profound impact on progress in Drosophila research, and improving the accuracy and completeness of this sequence continues to be important to further progress. We previously described improvement of the 117-Mb sequence in the euchromatic portion of the genome and 21 Mb in the heterochromatic portion, using a whole-genome shotgun assembly, BAC physical mapping, and clone-based finishing. Here, we report an improved reference sequence of the single-copy and middle-repetitive regions of the genome, produced using cytogenetic mapping to mitotic and polytene chromosomes, clone-based finishing and BAC fingerprint verification, ordering of scaffolds by alignment to cDNA sequences, incorporation of other map and sequence data, and validation by whole-genome optical restriction mapping. These data substantially improve the accuracy and completeness of the reference sequence and the order and orientation of sequence scaffolds into chromosome arm assemblies. Representation of the Y chromosome and other heterochromatic regions is particularly improved. The new 143.9-Mb reference sequence, designated Release 6, effectively exhausts clone-based technologies for mapping and sequencing. Highly repeat-rich regions, including large satellite blocks and functional elements such as the ribosomal RNA genes and the centromeres, are largely inaccessible to current sequencing and assembly methods and remain poorly represented. In conclusion, further significant improvements will require sequencing technologies that do not depend on molecular cloning and that produce very long reads.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

Circulating Mirna Spaceflight Signature Reveals Targets to Mitigate Associated Health Risks

We have identified and validated a spaceflight-associated microRNA (miRNA) signature that is shared by rodents and humans in response to simulated, short-duration, and long-duration spaceflight and regulates vascular damage caused by simulated deep space radiation. In previous studies, we had identified miRNAs that are predicted to regulate rodent responses to spaceflight in low-Earth orbit. Here we have confirmed the expression of these proposed spaceflight associated miRNAs in rodents reacting to simulated spaceflight conditions (exposure to ionizing radiation combined with simulated microgravity) and in astronaut samples from the NASA Twins Study via direct quantification of miRNAs, miRNA sequencing, and inferring miRNA target levels based on single-cell RNA (scRNA-seq) and single-cell chromatin (scATAC-seq) sequencing data. To demonstrate the physiological relevance of key spaceflight associated miRNAs, we utilized antagomirs to inhibit their expression and successfully rescue simulated deep space radiation-mediated damage in human 3D vascular constructs.

Sherina Malkani↗
DOE OSTI2021

Surrogate Model of Flexible Research Platform EnergyPlus Models to Enable Sensitivity Analysis

This letter report describes the surrogate models developed from the EnergyPlus model of Oak Ridge National Laboratory’s Flexible Research Platform. Two data-driven black-box models were developed, and the outputs of the surrogate models were compared with the EnergyPlus model. The two models developed are a multilayer perceptron deep learning model, and a long short-term memory (LSTM) neural network model. The three factors for selecting the black-box models are scalability, computation time, and accuracy. A total of 107 input variables were the dominant variables in determining the outputs of building energy consumptions and thermal comfort. A total of 54 output variables were identified as the prediction targets, including the system- and zone-level outputs. The large set of the simulation cases were generated by integrating sensor errors into an emulator based on EnergyPlus and Python EMS, which includes advanced control sequences from ASHRAE Guideline 36-2018: High-Performance Sequences of Operation. The surrogate models were developed based on a set of large-scale simulation runs (i.e., 4,000 runs) on a cloud platform. The comparison analysis shows that the two black-box models had good accuracy for predicting new outputs for sensitivity analysis using the root mean square error metric. As a next step, the developed surrogate models will be used to perform sensitivity analysis for different sensor impacts (e.g., sensor types, sensor locations).

42 ENGINEERING↗
DOE OSTI2016

S2M: A Stochastic Simulation Model of Poliovirus Genetic State Transition

Modeling the molecular mechanisms that govern genetic variation can be useful in understanding the dynamics that drive genetic state transition in quasispecies viruses. For example, there is considerable interest in understanding how the relatively benign vaccine strains of poliovirus eventually revert to forms that confer neurovirulence and cause disease (ie, vaccine-derived poliovirus). This report describes a stochastic simulation model, S2M, which can be used to generate hypothetical outcomes based on known mechanisms of genetic diversity. S2M begins with predefined genotypes based on the Sabin-1 and Mahoney wild-type sequences, constructs a set of independent cell-based populations, and performs in-cell replication and cell-to-cell infection cycles while quantifying genetic changes that track the transition from Sabin-1 toward Mahoney. Realism is incorporated into the model by assigning defaults for variables that constrain mechanisms of genetic variability based roughly on metrics reported in the literature, yet these values can be modified at the command line in order to generate hypothetical outcomes driven by these parameters. To demonstrate the utility of S2M, simulations were performed to examine the effects of the rates of replication error and recombination and the presence or absence of defective interfering particles, upon reaching the end states of Mahoney resemblance (semblance of a vaccine-derived state), neurovirulence, genome fitness, and cloud diversity. Simulations provide insight into how modeled biological features may drive hypothetical outcomes, independently or in combination, in ways that are not always intuitively obvious.

59 BASIC BIOLOGICAL SCIENCES↗