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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Antimicrobial resistance prediction in PATRIC and RAST

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.org/), we have been collecting bacterial genomes with AMR metadata for several years. In order to advance phenotype prediction and the identification of genomic regions relating to AMR, we have updated the PATRIC FTP server to enable access to genomes that are binned by their AMR phenotypes, as well as metadata including minimum inhibitory concentrations. Using this infrastructure, we custom built AdaBoost (adaptive boosting) machine learning classifiers for identifying carbapenem resistance in Acinetobacter baumannii , methicillin resistance in Staphylococcus aureus , and beta-lactam and co-trimoxazole resistance in Streptococcus pneumoniae with accuracies ranging from 88–99%. We also did this for isoniazid, kanamycin, ofloxacin, rifampicin, and streptomycin resistance in Mycobacterium tuberculosis , achieving accuracies ranging from 71–88%. Lastly, this set of classifiers has been used to provide an initial framework for species-specific AMR phenotype and genomic feature prediction in the RAST and PATRIC annotation services.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Disease Diagnostics Research at Los Alamos National Laboratory

Human evolution and persistent diseases have existed side-by-side. A recent concern is the re-emergence of tuberculosis, one of the oldest and most challenging diseases known to man. Effective diagnosis can save lives and prevent its spread. This talk will cover how our immune system discriminates between itself and foreign entities and how a new laboratory and nature inspired strategy can detect tuberculosis equally well in human and animal populations. The approach is being extended to other applications such as the identification of strep throat and respiratory infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Boxwood blight: an ongoing threat to ornamental and native boxwood

Boxwood blight is an emerging disease of ornamental and native boxwood plants in the family Buxaceae . First documented in the 1990s at a single location in England, the disease is now reported throughout Europe, Asia, New Zealand, and North America. To address the growing concern over boxwood blight, ongoing research focuses on multiple biological and genetic aspects of the causal pathogens and susceptible host plants. Characterization of genetic variation among the Calonectri a fungi that cause boxwood blight shows that two unique sister species with different geographic distributions incite the disease. Studies of the pathogen life cycle show the formation of long-lived survival structures and that host infection is dependent on inoculum density, temperature, and humidity. Host range investigations detail high levels of susceptibility among boxwood as well as the potential for asymptomatic boxwood infection and for other plants in the family Buxaceae to serve as additional hosts. Multiple DNA-based diagnostic assays are available, ranging from probe-based quantitative PCR assays to the use of comparative genomics to develop robust diagnostic markers or provide whole genome-scale identifications. Though many questions remain, the research that continues to address boxwood blight demonstrates the importance of applying a multidisciplinary approach to understand and control emerging plant diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Identification of a Latin American-specific BabA adhesin variant through whole genome sequencing of Helicobacter pylori patient isolates from Nicaragua

In this study, Helicobacter pylori (H. pylori) is one of the most common bacterial infections in humans and this infection can lead to gastric ulcers and gastric cancer. H. pylori is one of the most genetically variable human pathogens and the ability of the bacterium to bind to the host epithelium as well as the presence of different virulence factors and genetic variants within these genes have been associated with disease severity. Nicaragua has particularly high gastric cancer incidence and we therefore studied Nicaraguan clinical H. pylori isolates for factors that could contribute to cancer risk. The complete genomes of fifty-two Nicaraguan H. pylori i isolates were sequenced and assembled de novo, and phylogenetic and virulence factor analyses were performed. The Nicaraguan isolates showed phylogenetic relationship with West African isolates in whole-genome sequence comparisons and with Western and urban South-and Central American isolates using MLSA (Multi-locus sequence analysis). A majority, 77 % of the isolates carried the cancer-associated virulence gene cagA and also the s1/i1/m1 vacuolating cytotoxin, vacA allele combination, which is linked to increased severity of disease. Specifically, we also found that Nicaraguan isolates have a blood group-binding adhesin (BabA) variant highly similar to previously reported BabA sequences from Latin America, including from isolates belonging to other phylogenetic groups. These BabA sequences were found to be under positive selection at several amino acid positions that differed from the global collection of isolates. In conclusion, the discovery of a Latin American BabA variant, independent of overall phylogenetic background, suggests hitherto unknown host or environmental factors within the Latin American population giving H. pylori isolates carrying this adhesin variant a selective advantage, which could affect pathogenesis and risk for sequelae through specific adherence properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

High-quality Acinetobacter genomes recovered from combat wounds via metagenomic sequencing resemble cultured isolate genomes

The ability to accurately characterize wound pathogens is critical to informing clinical decisions for wound infections with complex treatment requirements. Acinetobacter baumannii is an impactful nosocomial pathogen in combat wounds and civilian hospital-acquired infections. An informed understanding of the phylogenetics and epidemiology of A. baumannii infections in military and civilian environments could guide approaches that improve antibiotic treatment regimens for both military and civilian patients. Whole-genome data for bacterial strains can be difficult to obtain due to challenges in culturing isolates from preserved military specimens. Metagenomic sequencing and assembly create opportunities for genomic analysis of pathogens directly from clinical specimens. The ability to perform comparative analyses between metagenome-derived genomes and culture-derived genomes would support a range of comparative bacterial genomic studies. Wound tissue biopsy and effluent samples from combat injuries were subjected to metagenomic sequencing and assembly. In total, 42 microbial metagenome-assembled genomes (MAGs) were obtained directly from metagenomic sequence data, 36 of which were designated “high” quality. Thirty of these genomes corresponded to Acinetobacter, with 29 mapping specifically to A. baumannii. Other observed genera included Bordetella, Citrobacter, Escherichia, and Pseudomonas. Single-copy and multi-copy orthologs were identified across Acinetobacter MAGs and publicly available isolate genomes derived from military and civilian sources. Both MAG and military isolate genomes were annotated with antimicrobial resistance data, and MAG genomes were statistically comparable to genomes obtained from isolates. Our results highlight the potential of de novo metagenome assembly for enabling high-resolution characterization directly from clinical specimens, thereby improving diagnostic precision, guiding antimicrobial stewardship, and enhancing understanding of pathogen evolution across diverse healthcare and battlefield environments.

Acinetobacter baumannii↗
DOE OSTI2020

CasCollect: targeted assembly of CRISPR-associated operons from high-throughput sequencing data

Abstract CRISPR arrays and CRISPR-associated (Cas) proteins comprise a widespread adaptive immune system in bacteria and archaea. These systems function as a defense against exogenous parasitic mobile genetic elements that include bacteriophages, plasmids and foreign nucleic acids. With the continuous spread of antibiotic resistance, knowledge of pathogen susceptibility to bacteriophage therapy is becoming more critical. Additionally, gene-editing applications would benefit from the discovery of new cas genes with favorable properties. While next-generation sequencing has produced staggering quantities of data, transitioning from raw sequencing reads to the identification of CRISPR/Cas systems has remained challenging. This is especially true for metagenomic data, which has the highest potential for identifying novel cas genes. We report a comprehensive computational pipeline, CasCollect, for the targeted assembly and annotation of cas genes and CRISPR arrays—even isolated arrays—from raw sequencing reads. Benchmarking our targeted assembly pipeline demonstrates significantly improved timing by almost two orders of magnitude compared with conventional assembly and annotation, while retaining the ability to detect CRISPR arrays and cas genes. CasCollect is a highly versatile pipeline and can be used for targeted assembly of any specialty gene set, reconfigurable for user provided Hidden Markov Models and/or reference nucleotide sequences.

Podlevsky, Joshua D.↗
DOE OSTI2013

Identification of widespread adenosine nucleotide binding in Mycobacterium tuberculosis

The annotation of protein function is almost completely performed by in silico approaches. However, computational prediction of protein function is frequently incomplete and error prone. In Mycobacterium tuberculosis (Mtb), ~25% of all genes have no predicted function and are annotated as hypothetical proteins. This lack of functional information severely limits our understanding of Mtb pathogenicity. Current tools for experimental functional annotation are limited and often do not scale to entire protein families. Here, we report a generally applicable chemical biology platform to functionally annotate bacterial proteins by combining activity-based protein profiling (ABPP) and quantitative LC-MS-based proteomics. As an example of this approach for high-throughput protein functional validation and discovery, we experimentally annotate the families of ATP-binding proteins in Mtb. Our data experimentally validate prior in silico predictions of >250 ATPases and adenosine nucleotide-binding proteins, and reveal 73 hypothetical proteins as novel ATP-binding proteins. We identify adenosine cofactor interactions with many hypothetical proteins containing a diversity of unrelated sequences, providing a new and expanded view of adenosine nucleotide binding in Mtb. Furthermore, many of these hypothetical proteins are both unique to Mycobacteria and essential for infection, suggesting specialized functions in mycobacterial physiology and pathogenicity. Thus, we provide a generally applicable approach for high throughput protein function discovery and validation, and highlight several ways in which application of activity-based proteomics data can improve the quality of functional annotations to facilitate novel biological insights.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2024

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

ABSTRACT There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (“functional modules”), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida . Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

09 BIOMASS FUELS↗
DOE OSTI2020

A Gene Cluster That Encodes Histone Deacetylase Inhibitors Contributes to Bacterial Persistence and Antibiotic Tolerance in Burkholderia thailandensis

Persister cells are genetically identical variants in a bacterial population that have phenotypically modified their physiology to survive environmental stress. In bacterial pathogens, persisters are able to survive antibiotic treatment and reinfect patients in a frustrating cycle of chronic infection. To better define core persistence mechanisms for therapeutics development, we performed transcriptomics analyses of Burkholderia thailandensis populations enriched for persisters via three methods: flow sorting for low proton motive force, meropenem treatment, and culture aging. Although the three persister-enriched populations generally displayed divergent gene expression profiles that reflect the multimechanistic nature of stress adaptations, there were several common gene pathways activated in two or all three populations. These include polyketide and nonribosomal peptide synthesis, Clp proteases, mobile elements, enzymes involved in lipid metabolism, and ATP binding cassette (ABC) transporter systems. In particular, identification of genes that encode polyketide synthases (PKSs) and fatty acid catabolism factors indicates that generation of secondary metabolites, natural products, and complex lipids could be part of the metabolic program that governs the persistence state. We also found that loss-of-function mutations in the PKS-encoding gene locus BTH_I2366, which plays a role in biosynthesis of histone deacetylase (HDAC) inhibitors, resulted in increased sensitivity to antibiotics targeting DNA replication. Furthermore, treatment of multiple bacterial pathogens with a fatty acid synthesis inhibitor, CP-640186, potentiated the efficacy of meropenem against the persister populations. Altogether, our results suggest that bacterial persisters may exhibit an outwardly dormant physiology but maintain active metabolic processes that are required to maintain persistence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Staphylococcus pseudintermedius 5'-nucleotidase suppresses canine phagocytic activity

Staphylococcus pseudintermedius is a major opportunistic bacterial pathogen and the leading cause of pyoderma in dogs. In canines it is also often associated with infections of the urinary system and wounds and occasionally infects people. Widespread antimicrobial resistance has made the development of alternative treatments a high priority. The development of a staphylococcal vaccine, however, has proven challenging. Identification of virulence factors that inhibit phagocytosis and avoid innate immunity may play a significant role in preventing or treating infection with S. pseudintermedius. In this study, we identified a putative 5'-nucleotidase provisionally named SpAdsA, a S. pseudintermedius cell- wall protein encoded by SpAdsA. SpAdsA shares approximately 52% identity with the orthologous protein of Staphylococcus aureus and 14.8% identity with that of Streptococcus suis type2. It catalyzes the dephosphorylation of adenosine triphosphate and attenuation of this enzyme with critical amino acid substitutions nearly eliminated its hydrolytic activity. Furthermore, exogenous adenosine inhibited phagocytosis of S. pseudintermedius by canine neutrophils and monocytes. Conversely, the addition of SpAdsA inhibitor or A2A adenosine receptor antagonist impaired the capacity of S. pseudintermedius to escape from killing by phagocytic cells. The neutralizing ability of canine antibody produced against SpAdsA-M was determined. Taken together, these results suggest that SpAdsA likely plays an important role in S. pseudintermedius virulence and that attenuated SpAdsA may be a good candidate for inclusion in a vaccine against S. pseudintermedius.

5'-nucleotidase↗
DOE OSTI2024

Cacao pod transcriptome profiling of seven genotypes identifies features associated with post-penetration resistance to Phytophthora palmivora

Abstract The oomycete Phytophthora palmivora infects the fruit of cacao trees ( Theobroma cacao ) causing black pod rot and reducing yields. Cacao genotypes vary in their resistance levels to P. palmivora , yet our understanding of how cacao fruit respond to the pathogen at the molecular level during disease establishment is limited. To address this issue, disease development and RNA-Seq studies were conducted on pods of seven cacao genotypes (ICS1, WFT, Gu133, Spa9, CCN51, Sca6 and Pound7) to better understand their reactions to the post-penetration stage of P. palmivora infection. The pod tissue- P. palmivora pathogen assay resulted in the genotypes being classified as susceptible (ICS1, WFT, Gu133 and Spa9) or resistant (CCN51, Sca6 and Pound7). The number of differentially expressed genes (DEGs) ranged from 1625 to 6957 depending on genotype. A custom gene correlation approach identified 34 correlation groups. De novo motif analysis was conducted on upstream promoter sequences of differentially expressed genes, identifying 76 novel motifs, 31 of which were over-represented in the upstream sequences of correlation groups and associated with gene ontology terms related to oxidative stress response, defense against fungal pathogens, general metabolism and cell function. Genes in one correlation group (Group 6) were strongly induced in all genotypes and enriched in genes annotated with defense-responsive terms. Expression pattern profiling revealed that genes in Group 6 were induced to higher levels in the resistant genotypes. An additional analysis allowed the identification of 17 candidate cis -regulatory modules likely to be involved in cacao defense against P. palmivora . This study is a comprehensive exploration of the cacao pod transcriptional response to P. palmivora spread after infection. We identified cacao genes, promoter motifs, and promoter motif combinations associated with post-penetration resistance to P. palmivora in cacao pods and provide this information as a resource to support future and ongoing efforts to breed P. palmivora -resistant cacao.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Disease insights through cross-species phenotype comparisons

New sequencing technologies have ushered in a new era for diagnosis and discovery of new causative mutations for rare diseases. However, the sheer numbers of candidate variants that require interpretation in an exome or genomic analysis are still a challenging prospect. A powerful approach is the comparison of the patient’s set of phenotypes (phenotypic profile) to known phenotypic profiles caused by mutations in orthologous genes associated with these variants. The most abundant source of relevant data for this task is available through the efforts of the Mouse Genome Informatics group and the International Mouse Phenotyping Consortium. In this review, we highlight the challenges in comparing human clinical phenotypes with mouse phenotypes and some of the solutions that have been developed by members of the Monarch Initiative. These tools allow the identification of mouse models for known disease-gene associations that may otherwise have been overlooked as well as candidate genes may be prioritized for novel associations. The culmination of these efforts is the Exomiser software package that allows clinical researchers to analyse patient exomes in the context of variant frequency and predicted pathogenicity as well the phenotypic similarity of the patient to any given candidate orthologous gene.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Multi-omics Characterization of the Host Response to COVID-19

This project is a multi-disciplinary collaboration between investigators at PNNL with expertise in mass spectrometry (MS)-based omics technology development, omics measurement methods development and application, statistics, machine learning and integration of disparate datasets for a systems-level understanding, and expertise in pathogenic coronaviruses, and investigators at the University of Wisconsin-Madison (UW-Madison) with expertise in pathogenic respiratory viruses (e.g. influenza). The goal of this project is to obtain a comprehensive picture of the human host factors critical for the outcome of SARS-CoV-2 infection. We will generate broad untargeted multi-omics profiles using both state-of-the-art and novel instrumentation and approaches to enable the identification of the molecular mechanisms and host response pathways that impact human COVID-19 outcomes. We anticipate these results will lead to the generation of biomarker panels that are predictive of disease outcomes and mechanistic hypotheses that can be further interrogated in future studies and will provide the basis for vaccine or therapeutic development. To do so, we are obtaining and analyzing blood samples from COVID-19 patients with a range of disease outcomes that were treated at the Center Hospital of the National Center for Global Health and Medicine in Tokyo, Japan and other collaborating hospitals in our network. Specifically, this project will fund proteomics and metabolomics analyses of clinical COVID samples, machine learning-based integration of the data, and pathway-based interpretation of the data. This project was funded in June 2020. In the time span of June to September 2020, the project team developed an analytically and statistically robust analysis plan and made various preparations to facilitate sample receipt from our UW-Madison collaborators. This included blocking and randomization of sample prep orders, ordering of reagents and reference materials, and shipping of materials needed for preparation of the samples under BSL3 conditions to our collaborators at UW-Madison. As of FY21, this project has been picked up via a sponsor, the Naval Medical Research Center, which will cover the remainder of the proposed scope of work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

A funnel approach to enable analyses of epitope-specific human CD4 T cells specific for influenza and SARS-CoV-2

Protection against pathogens relies heavily on the adaptive immune response, whose key regulators are CD4 T cells. CD4 T cells, notable for their complex repertoire and functional potential, can most easily be dissected by identifying, quantifying, characterizing, and isolating epitope-specific cells. In the study reported here, we present a systematic and unbiased strategy that has enabled the identification of highly immunogenic peptide epitopes derived from influenza virus and SARS-CoV-2, presented by human HLA-DR proteins. Coupling the use of HLA-DR transgenic mice with infection and vaccination and highly sensitive epitope-specific cytokine ELISpot assays, we have narrowed the potential epitopes from 450 to 600 peptides to 5–15 peptides for each allele by an iterative process of elimination and selection, which we have termed a funnel approach. These epitopes have been validated in HLA-DR-typed human CD4 T cells directly ex vivo and enabled the derivation and implementation of HLA-DR peptide tetramers. Tetramer staining of human PBMCs enriched for CD4 T memory populations from healthy adult subjects, highlighted this approach as a sensitive and specific method for identifying novel epitopes, and subsequent CD4 T-cell responses to human viral infections.

CD4 T cell↗
DOE OSTI2021

Enabling generalized phage therapy to treat secondary infections in COVID-19 (CRADA Final Report)

COVID-19 is a global health threat, with 32 millions infected and more than 500,000 deaths in the U.S. alone. A key aspect of COVID-19 deaths is bacterial secondary infections, with Staphylococcus aureus, Acinetobacter baumannii, and Pseudomonas aeruginosa identified as some of the major causative pathogens. Phage therapy, i.e., the administration of bacteriophages (viruses infecting these bacterial pathogens) to patients offers a complementary solution to antibiotics with multiple key advantages. Felix Biotechnology’s is developing a high-throughput platform to identify phages that not only kill pathogens, but also drive targeted trade-off of pathogenic phenotypes such as reduced virulence and antibiotic resistance, at a fraction of the time and R&D cost of any competitor. In this project, collaboration with scientists from the Lawrence Berkeley National Laboratory enabled Felix Biotechnology to establish robust analysis pipeline to investigate phage-host interactions in complex samples. These should enable a quick and robust identification of promising phages and key genetic determinants for therapy applications, paving the way towards a streamlined and safe use of phages in the clinic.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Genetic Control of Plant Root Colonization by the Biocontrol agent, Pseudomonas fluorescens

Plant growth promoting rhizobacteria (PGPR) are a critical component of plant root ecosystems. PGPR promote plant growth by solubilizing inaccessible minerals, suppressing pathogenic microorganisms in the soil, and directly stimulating growth through hormone synthesis. Pseudomonas fluorescens is a well-established PGPR isolated from wheat roots that can also colonize the root system of the model plant, Arabidopsis thaliana. We have created barcoded transposon insertion mutant libraries suitable for genome-wide transposon-mediated mutagenesis followed by sequencing (TnSeq). These libraries consist of over 105 independent insertions, collectively providing loss-of-function mutants for nearly all genes in the P.fluorescens genome. Each insertion mutant can be unambiguously identified by a randomized 20 nucleotide sequence (barcode) engineered into the transposon sequence. We used these libraries in a gnotobiotic assay to examine the colonization ability of P.fluorescens on A.thaliana roots. Taking advantage of the ability to distinguish individual colonization events using barcode sequences, we assessed the timing and microbial concentration dependence of colonization of the rhizoplane niche. These data provide direct insight into the dynamics of plant root colonization in an in vivo system and define baseline parameters for the systematic identification of the bacterial genes and molecular pathways using TnSeq assays. Having determined parameters that facilitate potential colonization of roots by thousands of independent insertion mutants in a single assay, we are currently establishing a genome-wide functional map of genes required for root colonization in P.fluorescens. Importantly, the approach developed and optimized here for P.fluorescens>A.thaliana colonization will be applicable to a wide range of plant-microbe interactions, including biofuel feedstock plants and microbes known or hypothesized to impact on biofuel-relevant traits including biomass productivity and pathogen resistance.

Cole, Benjamin J.↗
DOE OSTI2016

Morphological and molecular characterization of fungal pathogen, Magnaphorthe oryzae

Rice is arguably the most crucial food crops supplying quarter of calories intake. Fungal pathogen, Magnaphorthe oryzae promotes blast disease unconditionally to gramineous host including rice species. This disease spurred an outbreaks and constant threat to cereal production. Global rice yield declining almost 10-30% including Malaysia. As Magnaphorthe oryzae and its host is model in disease plant study, the rice blast pathosystem has been the subject of intense interest to overcome the importance of the disease to world agriculture. Therefore, in this study, our prime objective was to isolate samples of Magnaphorthe oryzae from diseased leaf obtained from MARDI Seberang Perai, Penang, Malaysia. Molecular identification was performed by sequences analysis from internal transcribed spacer (ITS) region of nuclear ribosomal RNA genes. Phylogenetic affiliation of the isolated samples were analyzed by comparing the ITS sequences with those deposited in the GenBank database. The sequence of the isolate demonstrated at least 99% nucleotide identity with the corresponding sequence in GenBank for Magnaphorthe oryzae. Morphological observed under microscope demonstrated that the structure of conidia followed similar characteristic as M. oryzae. Finding in this study provide useful information for breeding programs, epidemiology studies and improved disease management.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2005

Microbial Surveillance of Potable Water Sources of the International Space Station

To mitigate risk to the crew, the microbial surveillance of the quality of potable water sources of the International Space Station (ISS) has been ongoing since before the arrival of the first permanent crew. These water sources have included stored ground-supplied water, water produced by the shuttle fuel cells during flight, and ISS humidity condensate that is reclaimed and processed. Monitoring was accomplished using a self-contained filter designed to allow bacterial growth and enumeration during flight. Upon return to earth, microbial isolates were identified using 16S ribosomal gene sequencing. While the predominant isolates were common Gramnegative bacteria including Ralstonia eutropha, Methylobacterium fujisawaense, and Spingomonas paucimobilis, opportunistic pathogens such as Stenotrophomonas maltophilia and Pseudomonas aeruginosa were also isolated. Results of in-flight enumeration have indicated a fluctuation of bacterial counts above system design specifications. Additional in-flight monitoring capability for the specific detection of coliforms was added in 2004; no coliforms have been detected from any potable water source. Neither the bacterial concentrations nor the identification of the isolates recovered from these samples has suggested a threat to crew health.

Bruce, Rebekah J.↗