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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A mutagenic analysis of NahE, a hydratase-aldolase in the naphthalene degradative pathway

NahE is a hydratase-aldolase that converts o-substituted trans-benzylidenepyruvates (H, OH, or CO 2 - ) to benzaldehyde, salicylaldehyde, or 2-carboxybenzaldehyde, respectively, and pyruvate. The enzyme is in a bacterial degradative pathway for naphthalene, which is a toxic and persistent environmental contaminant. Sequence, crystallographic, and mutagenic analysis identified the enzyme as a member of the N-acetylneuraminate lyase (NAL) subgroup in the aldolase superfamily. As such, it has a conserved lysine (Lys183) and tyrosine (Tyr155), for Schiff base formation, as well as a GXXGE motif for binding of the pyruvoyl carboxylate group. A crystal structure of the selenomethionine derivative of NahE shows these active site elements along with nearby residues that might be involved in the mechanism and/or specificity. Mutations of five active site amino acids (Thr65, Trp128, Tyr155, Asn157, and Asn281) were constructed and kinetic parameters measured in order to assess the effect(s) on catalysis. Here, the results show that the two Trp128 mutants (Phe and Tyr) have the least effect on catalysis, whereas amino acids with bulky side chains at Thr65 (Val) and Asn281 (Leu) have the greatest effect. Changing Tyr155 to Phe and Asn157 to Ala also hinders catalysis, and the effects fall in between these extremes. These observations are put into a structural context using a crystal structure of the Schiff base of the reaction intermediate. Trapping experiments with substrate, Na(CN)BH 3 , and wild type enzyme and selected mutants mostly paralleled the kinetic analysis, and identified two salicylaldehyde-modified lysines: the active site lysine (Lys183) and one outside the active site (Lys279). The latter could be responsible for the observed inhibition of NahE by salicylaldehyde. Together, the results provide new insights into the NahE-catalyzed reaction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Complete Genome Sequence of Sulfurospirillum Strain ACS TCE , a Tetrachloroethene-Respiring Anaerobe Isolated from Contaminated Soil

Here, we report the complete genome sequence of the tetrachloroethene-to-trichloroethene dechlorinator Sulfurospirillum sp. strain ACS TCE . The genome consists of a 38.05-kb circular plasmid and a 2.69-Mb circular chromosome, which encodes 3 identical reductive dehalogenases with 91.47% amino acid identity to the PceA of Sulfurospirillum multivorans strain DSM 12446.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Amplicon Sequencing Assessment to Measure Microbial Community Response from Heavy Metal Contaminated Soils in Savannah River site, Tims Branch watershed

Long-term presence of heavy metal contamination in soils is correlated with changes in microbial community structures and can lead to the reduction of indigenous species. Tolerance to soil heavy metal toxicity varies among different microbial communities. It remains unclear whether long term effects caused by metal perturbations are associated with soil microbial community dysregulation in Tims Branch watershed. Research Questions: Does heavy metal contamination in Tims Branch soils decrease microbial species diversity significantly compared to non-contaminated soils? Does the species richness decrease in contaminated samples? between samples? Is diversity in low, mid and high contamination soils significantly different compared to control samples? Hypothesis: The relative abundance and diversity of species are significantly altered in soils which are contaminated with heavy metals in the Tims Branch watershed. Objectives: Use amplicon sequencing technology along with bioinformatics to compare bacterial communities between four sites in Tims Branch watershed. Evaluate the percent relative abundance and diversity across the site. Conclusions: All bacterial communities exposed to different heavy metal concentrations were dominated by four major groups (Proteobacteria, Acidobacteria, Chloroflexi and Verrucomicrobia). The dominant phyla Proteobacteria, Acidobacteria and Chloroflexi accounted for 61 % of the relative abundance. Soil bacterial α-diversity, expressed as observed species richness metric and Shannon's diversity index, was the highest in sample location four (high contamination). The lowest observed was at the control location. Species richness increased when concentrations of heavy metals were localized, inferring that the metals can alter microbial community structure. PERMANOVA analysis between contaminated groups tested significant using the Adonis (F (4,29) =1.9712; p < 0.001). There is a 20 percent variation explained between groups (R2 = 0.214). This analysis proves to be beneficial in detecting microbial communities altered by contaminated soils. Moreover, certain concentrations of heavy metals can alter microbial community structures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Complete genome sequence of Cellulomonas sp., strain ES6, a chromate-reducing bacterium isolated from chromium-contaminated subsurface sediment

ABSTRACT Cellulomonas sp. strain ES6 is a chromate-reducing bacterium isolated from chromium contaminated subsurface sediment. Illumina MiSeq and Oxford Nanopore sequencing were used to assemble the genome sequence which consisted of a single circular chromosome of 4.13 Mb, contained 3,960 protein encoding genes and with an overall G + C content 75.38%.

Perea, Katheryn R.↗
DOE OSTI2024

Detection of anaerobic and aerobic bacteria from commercial tattoo and permanent makeup inks

ABSTRACT Tattooing and use of permanent makeup (PMU) have dramatically increased over the last decade, with a concomitant increase in ink-related infections. Studies have shown evidence that commercial tattoo and PMU inks are frequently contaminated with pathogenic microorganisms. Considering that tattoo inks are placed into the dermal layer of the skin where anaerobic bacteria can thrive and cause infections in low-oxygen environments, the prevalence of anaerobic and aerobic bacteria should be assessed in tattoo and PMU inks. In this study, we tested 75 tattoo and PMU inks using the analytical methods described in the FDA Bacteriological Analytical Manual Chapter 23 for the detection of both aerobic and anaerobic bacterial contamination, followed by 16S rRNA gene sequencing for microbial identification. Of 75 ink samples, we found 26 contaminated samples with 34 bacterial isolates taxonomically classified into 14 genera and 22 species. Among the 34 bacterial isolates, 19 were identified as possibly pathogenic bacterial strains. Two species, namelyCutibacterium acnes(four strains) andStaphylococcus epidermidis(two strains) were isolated under anaerobic conditions. Two possibly pathogenic bacterial strains,Staphylococcus saprophyticusandC. acnes, were isolated together from the same ink samples (n= 2), indicating that tattoo and PMU inks can contain both aerobic (S. saprophyticus) and anaerobic bacteria (C. acnes). No significant association was found between sterility claims on the ink label and the absence of bacterial contamination. The results indicate that tattoo and PMU inks can also contain anaerobic bacteria. IMPORTANCE The rising popularity of tattooing and permanent makeup (PMU) has led to increased reports of ink-related infections. This study is the first to investigate the presence of both aerobic and anaerobic bacteria in commercial tattoo and PMU inks under aerobic and anaerobic conditions. Our findings reveal that unopened and sealed tattoo inks can harbor anaerobic bacteria, known to thrive in low-oxygen environments, such as the dermal layer of the skin, alongside aerobic bacteria. This suggests that contaminated tattoo inks could be a source of infection from both types of bacteria. The results emphasize the importance of monitoring these products for both aerobic and anaerobic bacteria, including possibly pathogenic microorganisms.

Biotechnology & Applied Microbiology↗
DOE OSTI2021

Beyond the usual suspects: methanogenic communities in eastern North American peatlands are also influenced by nickel and copper concentrations

Peatlands both accumulate carbon and release methane, but their broad range in environmental conditions means that the diversity of microorganisms responsible for carbon cycling is still uncertain. Here, we describe a community analysis of methanogenic archaea responsible for methane production in 17 peatlands from 36 to 53 N latitude across the eastern half of North America, including three metal-contaminated sites. Methanogenic community structure was analysed through Illumina amplicon sequencing of the mcrA gene. Whether metal-contaminated sites were included or not, metal concentrations in peat were a primary driver of methanogenic community composition, particularly nickel, a trace element required in the F 430 cofactor in methyl-coenzyme M reductase that is also toxic at high concentrations. Copper was also a strong predictor, likely due to inhibition at toxic levels and/or to cooccurrence with nickel, since copper enzymes are not known to be present in anaerobic archaea. Here, the methanogenic groups Methanocellales and Methanosarcinales were prevalent in peatlands with low nickel concentrations, while Methanomicrobiales and Methanomassiliicoccales were abundant in peatlands with higher nickel concentrations. Results suggest that peat-associated trace metals are predictors of methanogenic communities in peatlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multiple Cases of Bacterial Sequence Erroneously Incorporated Into Publicly Available Chloroplast Genomes

Public sequencing databases are invaluable resources to biological researchers, but assessing data veracity as well as the curation and maintenance of such large collections of data can be challenging. Genomes of eukaryotic organelles, such as chloroplasts and other plastids, are particularly susceptible to assembly errors and misrepresentations in these databases due to their close evolutionary relationships with bacteria, which may co-occur within the same environment, as can be the case when sequencing plants. Here, based on sequence similarities with bacterial genomes, we identified several suspicious chloroplast assemblies present in the National Institutes of Health (NIH) Reference Sequence (RefSeq) collection. Investigations into these chloroplast assemblies reveal examples of erroneous integration of bacterial sequences into chloroplast ribosomal RNA (rRNA) loci, often within the rRNA genes, presumably due to the high similarity between plastid and bacterial rRNAs. The bacterial lineages identified within the examined chloroplasts as the most likely source of contamination are either known associates of plants, or co-occur in the same environmental niches as the examined plants. Modifications to the methods used to process untargeted ‘raw’ shotgun sequencing data from whole genome sequencing efforts, such as the identification and removal of bacterial reads prior to plastome assembly, could eliminate similar errors in the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

AlphaFold Protein Structure Database for Sequence-Independent Molecular Replacement

Crystallographic phasing recovers the phase information that is lost during a diffraction experiment. Molecular replacement is a commonly used phasing method for crystal structures in the protein data bank. In one form it uses a protein sequence to search a structure database to find suitable templates for phasing. However, sequence information is not always available, such as when proteins are crystallized with unknown binding partner proteins or when the crystal is of a contaminant. The recent development of AlphaFold published the predicted protein structures for every protein from twenty distinct species. In this work, we tested whether AlphaFold-predicted E. coli protein structures were accurate enough to enable sequence-independent phasing of diffraction data from two crystallization contaminants of unknown sequence. Using each of more than 4000 predicted structures as a search model, robust molecular replacement solutions were obtained, which allowed the identification and structure determination of YncE and YadF. Our results demonstrate the general utility of the AlphaFold-predicted structure database with respect to sequence-independent crystallographic phasing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Reaction pathways and Sb(III) minerals formation during the reduction of Sb(V) by Rhodoferax ferrireducens strain YZ-1

Antimony (Sb), a non-essential metalloid, can be released into the environment through various industrial ac-tivities. Sb(III) is considered more toxic than Sb(V), but Sb(III) can be immobilized through the precipitation of insoluble Sb 2 S 3 or Sb 2 O 3 . In the subsurface, Sb redox chemistry is largely controlled by microorganisms; how-ever, the exact mechanisms of Sb(V) reduction to Sb(III) are still unclear. Here, in this study, a new strain of Sb(V)-reducing bacterium, designated as strain YZ-1, that can respire Sb(V) as a terminal electron acceptor was iso-lated from Sb-contaminated soils. 16S-rRNA gene sequencing of YZ-1 revealed high similarity to a known Fe(III)-reducer, Rhodoferax ferrireducens. XRD and XAFS analyses revealed that bioreduction of Sb(V) to Sb(III) proceed through a transition from amorphous valentinite to crystalline senarmontite (allotropes of Sb 2 O 3 ). Genomic DNA sequencing found that YZ-1 possesses arsenic (As) metabolism genes, including As(V) reductase arsC. The qPCR analysis showed that arsC was highly expressed during Sb(V)-reduction by YZ-1, and thus is proposed as the potential Sb(V) reductase in YZ-1. This study provides new insight into the pathways and products of microbial Sb(V) reduction and demonstrates the potential of a newly isolated bacterium for Sb bioremediation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Distribution Development for Residual Inventory at the New York West Valley Site - 20400

The New York State Energy Research and Development Authority (NYSERDA) is the owner of the Western New York Nuclear Service Center (WNYNSC), a 1,351 ha site located approximately 48 km south of Buffalo, New York. In 1962, Nuclear Fuel Services, Inc. (NFS) entered into Agreements with the Atomic Energy Commission and New York State to construct the first commercial reprocessing plant of nuclear fuel in the United States. NFS, a private company, built and operated the spent fuel reprocessing plant and waste disposal facilities, processing 640 Mg of spent nuclear fuel from 1966 to 1972 under an Atomic Energy Commission license. Nuclear fuel reprocessing operations ended in 1972 and never reopened, leaving behind radioactive and chemical wastes. Operations led to contamination in a number of facilities and locations. Some of that contamination has migrated from waste disposal zones to other layers, formations, and features on and off the WNYNSC. Phase I decommissioning activities are ongoing and involve the removal of a number of areas and structures that have been associated with contamination. The purpose of this work is to outline the approach for characterizing contamination not associated with disposed wastes, contaminated structures, or specific releases. In this work, the term, residual radiological activity, is used to describe environmental contamination that exists subsequent to the completion of Phase I decommissioning activities, that is not associated with disposed wastes, contaminated structures, or specific releases. Contamination from the Site was quantified relative to data that characterize the concentrations of radionuclides that exist in background. Background concentrations are those present in the area but having no influence from Site related activities. The existence of residual radiological activity that is elevated relative to background has the potential to contribute to future risks to human health and the environment. As a consequence, the residual inventory information is used to inform the West Valley Probabilistic Performance Assessment (PPA) model to characterize potential future risks to human health and the environment. The centralized West Valley Data Management System (DMS) was the source of information for the data assembled in this analysis. The DMS is a fairly large compilation consisting of thousands of records from investigation studies, with sample dates ranging from 1990 to present. Samples from monitoring wells, boreholes, geoprobe studies, surface water, surface soils, storm water outfalls, ventilation stack filters, plant and animal tissues, and more are included in the DMS. Results are typically reported in units of activity per unit volume. For the purpose of the analyses presented here, all results were converted into consistent units of pCi per unit volume. Since 1990, data have been collected from various locations across the WNYNSC at different times with varying frequency over the course of several decades. As a consequence, a number of potential issues can arise with respect to the assembly of a dataset that is deemed adequate for the characterization of residual radiological activity. These issues were assessed and resolved to the extent possible through careful consideration of the properties of the distributions. The intent was to use data which characterize the current state of the Site. Radionuclides can be designated to one of several groups depending on their origin. In this work the groups considered were 1) Naturally Occurring Radioactive Material (NORM), 2) fallout, and 3) Other (including power plant, medical research, etc). This grouping is a useful construct with respect to the interpretation of fixed laboratory results. For example, NORM radionuclides that exist within a decay chain should have approximately equivalent distributions of concentrations if they are representative of background conditions. Insights such as these can be used as a check to identify sample results that need to be further investigated or omitted due to issues associated with reported results from fixed laboratory analyses. This type of analysis provided a foundation for the assessment of the adequacy of sample results for use in subsequent components of an assessment. The general process for the assessment of residual radiological contamination at the Site consists of a sequence of several steps. First, for each analyte, several statistical tests were performed to assess the weight of evidence against the null hypothesis that the mean of the distribution of concentrations was equal to zero. If the mean of the distribution of concentrations for a given radionuclide was not found to be greater than zero, then it was removed from consideration as a component of the residual radiological contamination. If there was significant evidence to reject the hypothesis of the mean being equal to zero, the second step was to compare the distribution of the data from the Site to that of the corresponding background. A suite of tests was used to compare the distributions of the site and background data. The results of these tests were collectively used to determine if site data are elevated relative to background. The third step was to develop distributions using a Bayesian framework to characterize the distribution of mean of the increment present above background for each of the radionuclides. The Bayesian model implemented allowed for the comparison of site-specific records to background concentrations to better approximate contamination attributed to the Site. A final screening step was employed for radionuclides that exceed background. This screening step compared 95% upper confidence limits (UCLs) from the increment distribution developed in the previous step to the risk screening levels. This approach yields a list of analytes that were determined to be elevated relative to background.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Reducing host DNA contamination in 16S rRNA gene surveys of anthozoan microbiomes using PNA clamps

Efforts to study the microbial communities associated with corals can be limited by inefficiencies in the sequencing process due to high levels of host amplification by universal bacterial 16S rRNA gene primers. Here, we develop an inexpensive peptide nucleic acid (PNA) clamp that binds to a target sequence of host DNA during PCR and blocks amplification. We then test the ability of this PNA clamp to mitigate host contamination and increase overall microbial sequence coverage on samples from three coral species: the gorgonians Eunicea flexuosa and Gorgonia ventalina, and the scleractinian Porites panamensis. The 20-bp PNA clamp was designed using DNA from E. flexuosa. Adding the PNA clamp during PCR increased the percentage of microbial reads in E. flexuosa samples more than 11-fold. Microbial community diversity was similar without- and with-PNA clamps, as were the relative frequencies of the ten most abundant ASVs (amplicon sequence variants), indicating that the clamps successfully blocked host DNA amplification while simultaneously increasing microbial DNA amplification proportionally across the most abundant taxa. The reduction of E. flexuosa DNA correlated with an increase in the abundance of rarer taxa. The clamp also increased the average percentage of microbial reads in another gorgonian, G. ventalina, by 8.6-fold without altering the microbial community beta diversity, and in a distantly related scleractinian coral, P. panamensis, by nearly double. The reduction of host contamination correlated with the number of nucleotide mismatches between the host amplicon and the PNA clamp. The PNA clamp costs as little as $0.48 per sample, making it an efficient and cost-effective solution to increase microbial sequence coverage for high-throughput sequencing of coral microbial communities.

16S rRNA gene sequencing↗
DOE OSTI2022

Enhancing the Phytoremediation of Heavy Metals by Combining Hyperaccumulator and Heavy Metal-Resistant Plant Growth-Promoting Bacteria

Heavy metals (HMs) have become a major environmental pollutant threatening ecosystems and human health. Although hyperaccumulators provide a viable alternative for the bioremediation of HMs, the potential of phytoremediation is often limited by the small biomass and slow growth rate of hyperaccumulators and HM toxicity to plants. Here, plant growth-promoting bacteria (PGPB)-assisted phytoremediation was used to enhance the phytoremediation of HM-contaminated soils. A PGPB with HM-tolerant (HMT-PGPB), Bacillus sp. PGP15 was isolated from the rhizosphere of a cadmium (Cd) hyperaccumulator, Solanum nigrum . Pot experiments demonstrated that inoculation with strain PGP15 could significantly increase the growth of S. nigrum . More importantly, strain PGP15 markedly improved Cd accumulation in S. nigrum while alleviating Cd-induced stress in S. nigrum . Specifically, PGP15 inoculation significantly decreased the contents of H 2 O 2 , MDA, and O 2 · − in S. nigrum , while the activities (per gram plant fresh weight) of SOD, APX, and CAT were significantly increased in the PGP15-inoculated plants compared with the control sample. These results suggested that the interactions between strain PGP15 and S. nigrum could overcome the limits of phytoremediation alone and highlighted the promising application potential of the PGPB-hyperaccumulator collaborative pattern in the bioremediation of HM-contaminated soils. Furthermore, the PGP15 genome was sequenced and compared with other strains to explore the mechanisms underlying plant growth promotion by HMT-PGPB. The results showed that core genes that define the fundamental metabolic capabilities of strain PGP15 might not be necessary for plant growth promotion. Meanwhile, PGP15-specific genes, including many transposable elements, played a crucial role in the adaptive evolution of HM resistance. Overall, our results improve the understanding of interactions between HMT-PGPB and plants and facilitate the application of HMT-PGPB in the phytoremediation of HM-contaminated soils.

Zhang, Yong↗
DOE OSTI2026

Data Mining of Groundwater to Identify MAGs with Methane, Propane and Toluene Monooxygenases

Whole genome sequencing datasets, involving more than 600 groundwater samples, from nine countries, were analyzed to identify metagenome assembled genomes (MAGs) containing full operons for propane monooxygenase, soluble methane monooxygease, toluene monooxygenase and particulate ammonia/methane monooxygenase. The enzymes encoded by these genes are a focus of interest because of their ability to degrade common groundwater contaminants. Due to the large amount of data, sequence analyses involved more than 80 individual KBase narratives. The approach followed the KBase tutorial called "Metagenome-Assembled Genome Extraction from a Compost Microbiome Enrichment" The generated MAGs were exported from each individual narrative into separate summary KBase narratives for each monooxygenase. Three KBase narratives were generated for particulate ammonia/methane monooxygenase, due to the large number of MAGs identified.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Automated Framework for Groundwater Monitoring Using DWT with LSTM and Transformers

Environmental monitoring is critical for safeguarding public health and ecological well-being. Traditional data structuring and workflow monitoring methods consume significant time and effort, hindering timely insights and effective decision-making. Our study addresses this challenge by presenting an AI framework that automates data cleaning, structuring, and modeling processes, specifically targeting applications in groundwater monitoring. By leveraging automation for data processing and model training, our framework establishes a novel and efficient paradigm for environmental monitoring, with its potential application to the vast network of over a hundred Department of Energy Environmental Management (DoE-EM) cleanup sites across the country. It analyzes data streams from a network of groundwater Internet-of-Things (IoT) sensors deployed at the Savannah River Site (SRS) for prediction modeling. This allows human experts to focus on analysis and decision-making, ultimately leading to better environmental outcomes.The framework employs multivariate time-series forecasting methods to study and model the behavior of varying chemical analytes. The continuous learning process is enabled by utilizing deep learning techniques. It allows the framework to become more nuanced in its analysis over time, adapting to the specific characteristics of the environmental site and the evolving nature of contaminant behavior. Deep learning models known for sequence modeling, LSTM, and Transformers are employed for time series forecasting. Data processing and structuring are essential components significantly impacting the final model's performance. This hypothesis was proven by presenting a comparative analysis of model performance with processed and unprocessed data. The feature engineering approach utilized was the Discrete Wavelet Transform, which works well with time series data.

Discrete Wavelet Transform (DWT)↗