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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Genome sequence of the model rice variety KitaakeX

Abstract Background The availability of thousands of complete rice genome sequences from diverse varieties and accessions has laid the foundation for in-depth exploration of the rice genome. One drawback to these collections is that most of these rice varieties have long life cycles, and/or low transformation efficiencies, which limits their usefulness as model organisms for functional genomics studies. In contrast, the rice variety Kitaake has a rapid life cycle (9 weeks seed to seed) and is easy to transform and propagate. For these reasons, Kitaake has emerged as a model for studies of diverse monocotyledonous species. Results Here, we report the de novo genome sequencing and analysis of Oryza sativa ssp. japonica variety KitaakeX, a Kitaake plant carrying the rice XA21 immune receptor. Our KitaakeX sequence assembly contains 377.6 Mb, consisting of 33 scaffolds (476 contigs) with a contig N50 of 1.4 Mb. Complementing the assembly are detailed gene annotations of 35,594 protein coding genes. We identified 331,335 genomic variations between KitaakeX and Nipponbare (ssp. japonica ), and 2,785,991 variations between KitaakeX and Zhenshan97 (ssp. indica ). We also compared Kitaake resequencing reads to the KitaakeX assembly and identified 219 small variations. The high-quality genome of the model rice plant KitaakeX will accelerate rice functional genomics. Conclusions The high quality, de novo assembly of the KitaakeX genome will serve as a useful reference genome for rice and will accelerate functional genomics studies of rice and other species.

Nipponbare↗
DOE OSTI2015

Transcriptome sequencing and differential gene expression analysis in Viola yedoensis Makino (Fam. Violaceae) responsive to cadmium (Cd) pollution

Viola yedoensis Makino is an important Chinese traditional medicine plant adapted to cadmium (Cd) pollution regions. Illumina sequencing technology was used to sequence the transcriptome of V. yedoensis Makino. We sequenced Cd-treated (VIYCd) and untreated (VIYCK) samples of V. yedoensis, and obtained 100,410,834 and 83,587,676 high quality reads, respectively. After de novo assembly and quantitative assessment, 109,800 unigenes were finally generated with an average length of 661 bp. We then obtained functional annotations by aligning unigenes with public protein databases including NR, NT, SwissProt, KEGG and COG. In addition, 892 differentially expressed genes (DEGs) were investigated between the two libraries of untreated (VIYCK) and Cd-treated (VIYCd) plants. Moreover, 15 randomly selected DEGs were further validated with qRT-PCR and the results were highly accordant with the Solexa analysis. This study firstly generated a successful global analysis of the V. yedoensis transcriptome and it will provide for further studies on gene expression, genomics, and functional genomics in Violaceae. - Highlights: • A de novo assembly generated 109,800 unigenes and 5,4479 of them were annotated. • 31,285 could be classified into 26 COG categories. • 263 biosynthesis pathways were predicted and classified into five categories. • 892 DEGs were detected and 15 of them were validated by qRT-PCR.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Listeria monocytogenes in Stone Fruits Linked to a Multistate Outbreak: Enumeration of Cells and Whole-Genome Sequencing

In 2014, the identification of stone fruits contaminated with led to the subsequent identification of a multistate outbreak. Simultaneous detection and enumeration of L. monocytogenes were performed on 105 fruits, each weighing 127 to 145 g, collected from 7 contaminated lots. The results showed that 53.3% of the fruits yielded L. monocytogenes (lower limit of detection, 5 CFU/fruit), and the levels ranged from 5 to 2,850 CFU/fruit, with a geometric mean of 11.3 CFU/fruit (0.1 CFU/g of fruit). Two serotypes, IVb-v1 and 1/2b, were identified by a combination of PCR- and antiserum-based serotyping among isolates from fruits and their packing environment; certain fruits contained a mixture of both serotypes. Single nucleotide polymorphism (SNP)-based whole-genome sequencing (WGS) analysis clustered isolates from two case-patients with the serotype IVb-v1 isolates and distinguished outbreak-associated isolates from pulsed-field gel electrophoresis (PFGE)-matched, but epidemiologically unrelated, clinical isolates. The outbreak-associated isolates differed by up to 42 SNPs. All but one serotype 1/2b isolate formed another WGS cluster and differed by up to 17 SNPs. Fully closed genomes of isolates from the stone fruits were used as references to maximize the resolution and to increase our confidence in prophage analysis. Putative prophages were conserved among isolates of each WGS cluster. All serotype IVb-v1 isolates belonged to singleton sequence type 382 (ST382); all but one serotype 1/2b isolate belonged to clonal complex 5.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Impact of Sequencing Radiation Therapy and Chemotherapy on Long-Term Local Toxicity for Early Breast Cancer: Results of a Randomized Study at 15-Year Follow-Up

Purpose: To compare long-term late local toxicity after either concomitant or sequential chemoradiation therapy after breast-conserving surgery. Methods and Materials: From 1997 to 2002, women aged 18 to 75 years who underwent breast-conserving surgery and axillary dissection for early breast cancer and in whom CMF (cyclophosphamide, methotrexate, and 5-fluorouracil) chemotherapy was planned were randomized between concomitant and sequential radiation therapy. Radiation therapy was delivered to the whole breast through tangential fields to 50 Gy in 20 fractions over a period of 4 weeks, followed by an electron boost. Surviving patients were tentatively contacted and examined between March and September 2014. Patients in whom progressive disease had developed or who had undergone further breast surgery were excluded. Local toxicity (fibrosis, telangiectasia, and breast atrophy or retraction) was scored blindly to the treatment received. A logistic regression was run to investigate the effect of treatment sequence after correction for several patient-, treatment-, and tumor-related covariates on selected endpoints. The median time to cross-sectional analysis was 15.7 years (range, 12.0-17.8 years). Results: Of 206 patients randomized, 154 (74.8%) were potentially eligible. Of these, 43 (27.9%) refused participation and 4 (2.6%) had been lost to follow-up, and for 5 (3.2%), we could not restore planning data; thus, the final number of analyzed patients was 102. No grade 4 toxicity had been observed, whereas the number of grade 3 toxicity events was low (<8%) for each item, allowing pooling of grade 2 and 3 events for further analysis. Treatment sequence (concomitant vs sequential) was an independent predictor of grade 2 or 3 fibrosis according to both the National Cancer Institute Common Terminology Criteria for Adverse Events (odds ratio [OR], 4.05; 95% confidence interval [CI], 1.34-12.2; P=.013) and the SOMA (Subjective, Objective, Management and Analytic) scale (OR, 3.75; 95% CI, 1.19-11.79; P=.018), as well as grade 2 or 3 breast atrophy or retraction (OR, 3.87; 95% CI, 1.42-10.56; P=.008). No effect on telangiectasia was detected. Conclusions: At long-term follow-up, concomitant chemoradiation therapy has a detrimental effect on both fibrosis and retraction with an approximately 4-fold increase in the odds of grade 2 or 3 toxicity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

A General Materials Data Science Framework for Quantitative 2D Analysis of Particle Growth from Image Sequences

Abstract Phase transformations are a challenging problem in materials science, which lead to changes in properties and may impact performance of material systems in various applications. We introduce a general framework for the analysis of particle growth kinetics by utilizing concepts from machine learning and graph theory. As a model system, we use image sequences of atomic force microscopy showing the crystallization of an amorphous fluoroelastomer film. To identify crystalline particles in an amorphous matrix and track the temporal evolution of the particle dispersion, we have developed quantitative methods of 2D analysis. 700 image sequences were analyzed using a neural network architecture, achieving 0.97 pixel-wise classification accuracy as a measure of the correctly classified pixels. The growth kinetics of isolated and impinged particles were tracked throughout time using these image sequences. The relationship between image sequences and spatiotemporal graph representations was explored to identify the proximity of crystallites from each other. The framework enables the analysis of all image sequences without the requirement of sampling for specific particles or timesteps for various materials systems.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Recruiting Human Microbiome Shotgun Data to Site-Specific Reference Genomes

The human body consists of innumerable multifaceted environments that predispose colonization by a number of distinct microbial communities, which play fundamental roles in human health and disease. In addition to community surveys and shotgun metagenomes that seek to explore the composition and diversity of these microbiomes, there are significant efforts to sequence reference microbial genomes from many body sites of healthy adults. To illustrate the utility of reference genomes when studying more complex metagenomes, we present a reference-based analysis of sequence reads generated from 55 shotgun metagenomes, selected from 5 major body sites, including 16 sub-sites. Interestingly, between 13% and 92% (62.3% average) of these shotgun reads were aligned to a then-complete list of 2780 reference genomes, including 1583 references for the human microbiome. However, no reference genome was universally found in all body sites. For any given metagenome, the body site-specific reference genomes, derived from the same body site as the sample, accounted for an average of 58.8% of the mapped reads. While different body sites did differ in abundant genera, proximal or symmetrical body sites were found to be most similar to one another. The extent of variation observed, both between individuals sampled within the same microenvironment, or at the same site within the same individual over time, calls into question comparative studies across individuals even if sampled at the same body site. This study illustrates the high utility of reference genomes and the need for further site-specific reference microbial genome sequencing, even within the already well-sampled human microbiome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

A Microfluidic DNA Library Preparation Platform for Next-Generation Sequencing

Next-generation sequencing (NGS) is emerging as a powerful tool for elucidating genetic information for a wide range of applications. Unfortunately, the surging popularity of NGS has not yet been accompanied by an improvement in automated techniques for preparing formatted sequencing libraries. To address this challenge, we have developed a prototype microfluidic system for preparing sequencer-ready DNA libraries for analysis by Illumina sequencing. Our system combines droplet-based digital microfluidic (DMF) sample handling with peripheral modules to create a fully-integrated, sample-in library-out platform. In this report, we use our automated system to prepare NGS libraries from samples of human and bacterial genomic DNA. E. coli libraries prepared on-device from 5 ng of total DNA yielded excellent sequence coverage over the entire bacterial genome, with .99% alignment to the reference genome, even genome coverage, and good quality scores. Furthermore, we produced a de novo assembly on a previously unsequenced multi-drug resistant Klebsiella pneumoniae strain BAA-2146 (KpnNDM). The new method described here is fast, robust, scalable, and automated. Our device for library preparation will assist in the integration of NGS technology into a wide variety of laboratories, including small research laboratories and clinical laboratories.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Cyote-attack Chain Estimator

Attack Chain Estimator (ACE) Application Overview The Attack Chain Estimator (ACE) Application is a sophisticated tool designed for the ingestion, classification, sequencing, and enrichment of cybersecurity threat reports. This application leverages advanced machine learning models and extensive historical data to provide comprehensive insights into cyber threats, specifically targeting Industrial Control Systems (ICS). Purpose The primary functions of the ACE Application include: Ingestion of Cybersecurity Threat Reporting: Capable of ingesting text-based threat reports in markdown or text file format. Supports ingestion of structured data from other sources in STIX/JSON format. Classification of Report’s Text-Based Events: Utilizes a DeBERTa classifier, specifically trained on cybersecurity data, to map the events to MITRE ATT&CK for ICS Tactics and Techniques. Classification is performed using multiple Jupyter notebooks and machine learning workflows hosted as FastAPI microservices: regex_data deberta_base_35_train_hft_classifier_mlflow.ipynb hft_regex_classifier_mlflow.ipynb param_train_hft_classifier_mlflow.ipynb regex_tactic_tech.ipynb Ordering of Tactics, Techniques, and Observable Events: Sequences the identified tactics, techniques, and events to form a coherent attack chain. Enrichment with Historical Attack Chain Details: Enhances the attack chain with details from historical attacks using a Markov model developed from CyOTE Precursor Analysis Report data. The Markov model is available as a FastAPI endpoint for seamless integration. Enrichment with Adversary Emulation Capabilities Data: Integrates adversary emulation capabilities data using MITRE Caldera for OT adversary abilities UUIDs. Export of Output Files: Provides options to export the enriched attack chain in JSON or CSV formats. Routing of Output to Other Applications: Facilitates routing of output to various platforms and applications, including: Threat Intelligence Platforms COREII Scout for Threat Intelligence Analysis COREII Modeling and Simulation for Adversary Emulation Technical Description The ACE Application is an advanced cybersecurity tool designed to provide detailed threat analysis and sequence generation. It is built on a robust architecture that integrates natural language processing, machine learning, and historical data modeling. Key Components: Data Ingestion Module: Handles the input of threat reports and data from various formats, ensuring flexibility in data sources. Classification Engine: Employs DeBERTa-based classifiers hosted as FastAPI microservices to analyze and classify threat report events in accordance with the MITRE ATT&CK framework for ICS. Sequence Generator: Orders the classified events into a logical attack chain, providing clear insight into the sequence of tactics and techniques used in the threat. Enrichment Engine: Integrates historical data and adversary emulation capabilities to enhance the attack chain with valuable context and additional details. The historical data enrichment is powered by a Markov model, which is available as a FastAPI endpoint. Export and Routing Module: Facilitates the export of the enriched attack chain in multiple formats and routes the output to designated applications for further analysis or emulation.

Paul, Tony [Idaho National Laboratory (INL), Idaho↗
DOE OSTI2025

Behavior of Single-Line-Ground Faults in Inverter-Based Resource Dominated Grids Explained

It has been observed by protection engineers that it is difficult for a protective relay to identify the faulted phase during a single-line-ground (SLG) fault in a power system with a high ingression of inverter-based resources (IBR) using currents (phase or sequence). Further studies using electromagnetic transient (EMT) simulation show that the initial operating conditions of the IBRs influence the response of phase currents during an SLG fault. In this letter, we conduct a quantitative analysis using sequence components. We find that the pre-fault condition determines the relative position of the current contributed by the grid versus that from the IBR, and further dictates which phase has the largest magnitude during an SLG condition. Finally, this finding is further verified by the EMT simulation results.

electromagnetic transient simulation↗
DOE OSTI2013

The structure of the SBP-Tag–streptavidin complex reveals a novel helical scaffold bridging binding pockets on separate subunits

The structure of the SBP-Tag–streptavidin complex reveals a novel mode of peptide recognition in which a single peptide binds simultaneously to biotin-binding pockets from adjacent subunits of streptavidin. The molecular details of peptide recognition suggest how the SBP-Tag can be further modified to become an even more useful tag for a wider range of biotechnological applications. The 38-residue SBP-Tag binds to streptavidin more tightly (K{sub d} ≃ 2.5–4.9 nM) than most if not all other known peptide sequences. Crystallographic analysis at 1.75 Å resolution shows that the SBP-Tag binds to streptavidin in an unprecedented manner by simultaneously interacting with biotin-binding pockets from two separate subunits. An N-terminal HVV peptide sequence (residues 12–14) and a C-terminal HPQ sequence (residues 31–33) form the bulk of the direct interactions between the SBP-Tag and the two biotin-binding pockets. Surprisingly, most of the peptide spanning these two sites (residues 17–28) adopts a regular α-helical structure that projects three leucine side chains into a groove formed at the interface between two streptavidin protomers. The crystal structure shows that residues 1–10 and 35–38 of the original SBP-Tag identified through in vitro selection and deletion analysis do not appear to contact streptavidin and thus may not be important for binding. A 25-residue peptide comprising residues 11–34 (SBP-Tag2) was synthesized and shown using surface plasmon resonance to bind streptavidin with very similar affinity and kinetics when compared with the SBP-Tag. The SBP-Tag2 was also added to the C-terminus of β-lactamase and was shown to be just as effective as the full-length SBP-Tag in affinity purification. These results validate the molecular structure of the SBP-Tag–streptavidin complex and establish a minimal bivalent streptavidin-binding tag from which further rational design and optimization can proceed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Genomes OnLine database (GOLD) v.7: updates and new features

The Genomes Online Database (GOLD) (https://gold.jgi.doe.gov) is an open online resource, which maintains an up-to-date catalog of genome and metagenome projects in the context of a comprehensive list of associated metadata. Information in GOLD is organized into four levels: Study, Biosample/Organism, Sequencing Project and Analysis Project. Currently GOLD hosts information on 33 415 Studies, 49 826 Biosamples, 313 324 Organisms, 215 881 Sequencing Projects and 174 454 Analysis Projects with a total of 541 metadata fields, of which 80 are based on controlled vocabulary (CV) terms. GOLD provides a user-friendly web interface to browse sequencing projects and launch advanced search tools across four classification levels. Users submit metadata on a wide range of Sequencing and Analysis Projects in GOLD before depositing sequence data to the Integrated Microbial Genomes (IMG) system for analysis. GOLD conforms with and supports the rules set by the Genomic Standards Consortium (GSC) Minimum Information standards. The current version of GOLD (v.7) has seen the number of projects and associated metadata increase exponentially over the years. This paper provides an update on the current status of GOLD and highlights the new features added over the last two years.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Consistent Feature Extraction From Vector Fields: Combinatorial Representations and Analysis Under Local Reference Frames

This dissertation presents research on addressing some of the contemporary challenges in the analysis of vector fields—an important type of scientific data useful for representing a multitude of physical phenomena, such as wind flow and ocean currents. In particular, new theories and computational frameworks to enable consistent feature extraction from vector fields are presented. One of the most fundamental challenges in the analysis of vector fields is that their features are defined with respect to reference frames. Unfortunately, there is no single “correct” reference frame for analysis, and an unsuitable frame may cause features of interest to remain undetected, thus creating serious physical consequences. This work develops new reference frames that enable extraction of localized features that other techniques and frames fail to detect. As a result, these reference frames objectify the notion of “correctness” of features for certain goals by revealing the phenomena of importance from the underlying data. An important consequence of using these local frames is that the analysis of unsteady (time-varying) vector fields can be reduced to the analysis of sequences of steady (timeindependent) vector fields, which can be performed using simpler and scalable techniques that allow better data management by accessing the data on a per-time-step basis. Nevertheless, the state-of-the-art analysis of steady vector fields is not robust, as most techniques are numerical in nature. The residing numerical errors can violate consistency with the underlying theory by breaching important fundamental laws, which may lead to serious physical consequences. This dissertation considers consistency as the most fundamental characteristic of computational analysis that must always be preserved, and presents a new discrete theory that uses combinatorial representations and algorithms to provide consistency guarantees during vector field analysis along with the uncertainty visualization of unavoidable discretization errors. Together, the two main contributions of this dissertation address two important concerns regarding feature extraction from scientific data: correctness and precision. The work presented here also opens new avenues for further research by exploring more-general reference frames and more-sophisticated domain discretizations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Data Analysis for DNA Stable Isotope Probing Experiments Using Multiple Window High-Resolution SIP

DNA stable isotope probing (DNA-SIP) allows for the identification of microbes that assimilate isotopically labeled substrates into DNA. Here we describe the analysis of sequencing data using the multiple window high-resolution DNA-SIP method (MW-HR-SIP). MW-HR-SIP has improved accuracy over other methods and is easily implemented on the statistical platform R. Here, we also discuss key experimental parameters to consider when designing DNA-SIP experiments and how these parameters affect accuracy of analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

IMG-ABC. A knowledge base to fuel discovery of biosynthetic gene clusters and novel secondary metabolites

In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG’s comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC’s focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in lphaproteobacteria . IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG’s extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

The DOE Joint Genome Institute Enabling Advances in Energy & Environmental Research (2016 Fact Sheet)

The U.S. Department of Energy (DOE) Joint Genome Institute (JGI) is the only federally-funded high-throughput genome sequencing and analysis facility dedicated to genomes of non-medical microbes, microbial communities, plants, fungi and other targets relevant to DOE missions in energy, climate, and environment. DOE JGI provides collaborators around the world with access to massive-scale DNA sequencing to underpin modern systems biology research and provide fundamental data on key genes that may link to biological functions, including microbial metabolic pathways and enzymes that are used to generate fuel molecules, affect plant biomass formation, degrade contaminants, or capture CO 2 . The information can then be used to optimize organisms for biofuels production and other DOE missions.

09 BIOMASS FUELS↗
DOE OSTI2018

Data Analyst - A Device for Continuous Repeating Real-Time Assay of HPGe, CZT, or Scintillation Gamma Spectra - 18574

There are many situations where a continuous repeating series of quantitative gamma spectral assays is desirable. These include measurements of fluid going through a pipe, of items on a conveyor passing under a detector, a detector aimed at the ground on a moving platform, or a detector in free air as a plume of radioactivity drifts by. While Canberra and many others have built and deployed many of these devices, they have all been custom built for that particular application, and rather expensive. The Data Analyst [DA] is a general purpose device that is designed to fulfill many of these applications without modification, but can be fairly-easily modified if needed. The DA is a small [12 x 18 x 5 cm], low-power [3 W] box that accepts the input from external MCAs, controls the acquisition cycle, analyzes the results, and transmits them to the outside world when needed. The detector-MCAs supported are HPGe with Lynx MCA, NaI or CeBr or LaBr with Osprey MCA, and CZT or CsI with internal MCAs. The DA internal software used for analysis is the full standard Genie analysis software, which is very widely used and well accepted in the industry. This allows exported spectral files to be reviewed and confirmed by Experts, and reanalyzed if needed. The DA hardware is totally autonomous. As soon as power is applied, it starts the pre-programmed sequences of acquisition and analysis. Multiple analysis sequences [called Workflows] can be in operation simultaneously, e.g. with different count times and different nuclide libraries. Only the detector with MCA, and the DA are required in the field. A PC can be connected to the DA locally or remotely via WiFi, USB, or Ethernet. The PC is needed to setup the DA, and to readout the results. The DA also supports [with application-specific programming] external Inputs/Outputs either for recording with the analysis results or for use in the computation of the result, e.g. temperature, flow rate, pressure, ... ]. The DA also has an internal GPS receiver with external antenna. Applications of the DA that are discussed include stack gas effluent activity where a portion of the effluent stream was extracted to flow through a shield with a HPGe detector and Lynx MCA, and measurement of reactor coolant activity where a shielded CZT detector and MCA were aimed at various sections of reactor primary coolant during a maintenance outage. Potential other applications are also described. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Manila clams from Hg polluted sediments of Marano and Grado lagoons (Italy) harbor detoxifying Hg resistant bacteria in soft tissues

A mechanism of mercury detoxification has been suggested by a previous study on Hg bioaccumulation in Manila clams (Ruditapes philippinarum) in the polluted Marano and Grado lagoons and in this study we demonstrate that this event could be partly related to the detoxifying activities of Hg-resistant bacteria (MRB) harbored in clam soft tissues. Therefore, natural clams were collected in six stations during two different periods (winter and spring) from Marano and Grado Lagoons. Siphons, gills and hepatopancreas from acclimatized clams were sterile dissected to isolate MRB. These anatomical parts were glass homogenized or used for whole, and they were lying on a solid medium containing 5 mg l{sup −1} HgCl{sub 2} and incubated at 30 °C. A total of fourteen bacterial strains were isolated and were identified by 16S rDNA sequencing and analysis, revealing that strains were representative of eight bacterial genera, four of which were Gram-positive (Enterococcus, Bacillus, Jeotgalicoccus and Staphylococcus) and other four were Gram-negative (Stenotrophomonas, Vibrio, Raoultella and Enterobacter). Plasmids and merA genes were found and their sequences determined. Fluorescence in situ hybridization (FISH) technique shows the presence of Firmicutes, Actinobacteria and Gammaproteobacteria by using different molecular probes in siphon and gills. Bacterial clumps inside clam flesh were observed and even a Gram-negative endosymbiont was disclosed by transmission electronic microscope inside clam cells. Bacteria harbored in cavities of soft tissue have mercury detoxifying activity. This feature was confirmed by the determination of mercuric reductase in glass-homogenized siphons and gills. -- Highlights: ► We isolated Gram-positive and Gram-negative Hg resistant strains from soft tissues of Ruditapes philippinarum. ► We identify 14 mercury resistant strains by 16S rRNA gene sequences. ► Bacteria in siphon and gill tissues of clams were observed by TEM and identified with different FISH probes. ► Hg-reductase (MerA) activity in glass homogenized clam tissues was also determined.

60 APPLIED LIFE SCIENCES↗