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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Single-Genome Sequencing of Hepatitis C Virus in Donor-Recipient Pairs Distinguishes Modes and Models of Virus Transmission and Early Diversification

Despite the recent development of highly effective anti-hepatitis C virus (HCV) drugs, the global burden of this pathogen remains immense. Control or eradication of HCV will likely require the broad application of antiviral drugs and development of an effective vaccine. A precise molecular identification of transmitted/founder (T/F) HCV genomes that lead to productive clinical infection could play a critical role in vaccine research, as it has for HIV-1. However, the replication schema of these two RNA viruses differ substantially, as do viral responses to innate and adaptive host defenses. These differences raise questions as to the certainty of T/F HCV genome inferences, particularly in cases where multiple closely related sequence lineages have been observed. To clarify these issues and distinguish between competing models of early HCV diversification, we examined seven cases of acute HCV infection in humans and chimpanzees, including three examples of virus transmission between linked donors and recipients. Using single-genome sequencing (SGS) of plasma vRNA, we found that inferred T/F sequences in recipients were identical to viral sequences in their respective donors. Early in infection, HCV genomes generally evolved according to a simple model of random evolution where the coalescent corresponded to the T/F sequence. Closely related sequence lineages could be explained by high multiplicity infection from a donor whose viral sequences had undergone a pretransmission bottleneck due to treatment, immune selection, or recent infection. These findings validate SGS, together with mathematical modeling and phylogenetic analysis, as a novel strategy to infer T/F HCV genome sequences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods

Early and accurate diagnosis of respiratory pathogens and associated outbreaks can allow for the control of spread, epidemiological modeling, targeted treatment, and decision making–as is evident with the current COVID-19 pandemic. Many respiratory infections share common symptoms, making them difficult to diagnose using only syndromic presentation. Yet, with delays in getting reference laboratory tests and limited availability and poor sensitivity of point-of-care tests, syndromic diagnosis is the most-relied upon method in clinical practice today. Here, we examine the variability in diagnostic identification of respiratory infections during the annual infection cycle in northern New Mexico, by comparing syndromic diagnostics with polymerase chain reaction (PCR) and sequencing-based methods, with the goal of assessing gaps in our current ability to identify respiratory pathogens. Of 97 individuals that presented with symptoms of respiratory infection, only 23 were positive for at least one RNA virus, as confirmed by sequencing. Whereas influenza virus (n = 7) was expected during this infection cycle, we also observed coronavirus (n = 7), respiratory syncytial virus (n = 8), parainfluenza virus (n = 4), and human metapneumovirus (n = 1) in individuals with respiratory infection symptoms. Four patients were coinfected with two viruses. In 21 individuals that tested positive using PCR, RNA sequencing completely matched in only 12 (57%) of these individuals. Few individuals (37.1%) were diagnosed to have an upper respiratory tract infection or viral syndrome by syndromic diagnostics, and the type of virus could only be distinguished in one patient. Thus, current syndromic diagnostic approaches fail to accurately identify respiratory pathogens associated with infection and are not suited to capture emerging threats in an accurate fashion. We conclude there is a critical and urgent need for layered agnostic diagnostics to track known and unknown pathogens at the point of care to control future outbreaks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Quantitative Dissection of Agrobacterium Virulence to Generate a Synthetic Ti Plasmid

Agrobacterium is not only a costly plant pathogen but is also an essential tool for plant transformation. Though Agrobacterium-mediated transformation (AMT) has been heavily studied, its polygenic nature and complex transcriptional regulation make identification of the genetic basis of transformational efficiency difficult through traditional genetic and bioinformatic approaches. Here, we use a bottom-up synthetic approach to systematically engineer the tumor-inducing plasmid (pTi), wherein the majority of virulence machinery is encoded. Using a validated toolkit to control Agrobacterium gene expression in planta, we perform a quantitative dissection of AMT to investigate the contributions of critical vir-genes at different expression levels. We construct a synthetic pTi capable of transient plant and stable fungal transformation and characterize bottlenecks and solutions for complex polygenic synthetic pTi designs. Our reductionist approach demonstrates how bottom-up engineering can be used to dissect and elucidate the genetic underpinnings of complex biological traits, laying the foundation for future engineering to establish full synthetic control over the critical process of AMT.

Agrobacterium-mediated transformation↗
DOE OSTI2014

Identification of a novel multiple kinase inhibitor with potent antiviral activity against influenza virus by reducing viral polymerase activity

Highlights: • Screening of 50,000 compounds and subsequent lead optimization identified WV970. • WV970 has antiviral effects against influenza A, B and highly pathogenic viral strains. • WV970 inhibits viral genome replication and transcription. • A target database search suggests that WV970 may bind to a number of kinases. • KINOMEscan screening revealed that WV970 has inhibitory effects on 15 kinases. - Abstract: Neuraminidase inhibitors are the only currently available influenza treatment, although resistant viruses to these drugs have already been reported. Thus, new antiviral drugs with novel mechanisms of action are urgently required. In this study, we identified a novel antiviral compound, WV970, through cell-based screening of a 50,000 compound library and subsequent lead optimization. This compound exhibited potent antiviral activity with nanomolar IC{sub 50} values against both influenza A and B viruses but not non-influenza RNA viruses. Time-of-addition and indirect immunofluorescence assays indicated that WV970 acted at an early stage of the influenza life cycle, but likely after nuclear entry of viral ribonucleoprotein (vRNP). Further analyses of viral RNA expression and viral polymerase activity indicated that WV970 inhibited vRNP-mediated viral genome replication and transcription. Finally, structure-based virtual screening and comprehensive human kinome screening were used to demonstrate that WV970 acts as a multiple kinase inhibitor, many of which are associated with influenza virus replication. Collectively, these results strongly suggest that WV970 is a promising anti-influenza drug candidate and that several kinases associated with viral replication are promising drug targets.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Quantifying leaf symptoms of sorghum charcoal rot in images of field‐grown plants using deep neural networks

Abstract Charcoal rot of sorghum (CRS) is a significant disease affecting sorghum crops, with limited genetic resistance available. The causative agent, Macrophomina phaseolina (Tassi) Goid, is a highly destructive fungal pathogen that targets over 500 plant species globally, including essential staple crops. Utilizing field image data for precise detection and quantification of CRS could greatly assist in the prompt identification and management of affected fields and thereby reduce yield losses. The objective of this work was to implement various machine learning algorithms to evaluate their ability to accurately detect and quantify CRS in red‐green‐blue images of sorghum plants exhibiting symptoms of infection. EfficientNet‐B3 and a fully convolutional network emerged as the top‐performing models for image classification and segmentation tasks, respectively. Among the classification models evaluated, EfficientNet‐B3 demonstrated superior performance, achieving an accuracy of 86.97%, a recall rate of 0.71, and an F1 score of 0.73. Of the segmentation models tested, FCN proved to be the most effective, exhibiting a validation accuracy of 97.76%, a recall rate of 0.68, and an F1 score of 0.66. As the size of the image patches increased, both models’ validation scores increased linearly, and their inference time decreased exponentially. This trend could be attributed to larger patches containing more information, improving model performance, and fewer patches reducing the computational load, thus decreasing inference time. The models, in addition to being immediately useful for breeders and growers of sorghum, advance the domain of automated plant phenotyping and may serve as a foundation for drone‐based or other automated field phenotyping efforts. Additionally, the models presented herein can be accessed through a web‐based application where users can easily analyze their own images.

Gonzalez, Emmanuel M.↗
DOE OSTI2026

Discovering novel therapeutic V H Hs for emerging viruses: perspectives from VEEV selection strategies

Introduction: Evolution or emergence of a new viral variant is a significant public health concern. Alphaviruses, such as Venezuelan equine encephalitis virus (VEEV), are mosquito-borne viruses which are becoming more prevalent due to expansion of vector habitats. Despite this, there are currently no antiviral therapies or FDA-approved vaccines available to treat or prevent VEEV infection. The increased prevalence of such viruses provides opportunities for novel variants to evolve. Key therapeutic molecules that could be developed against viral pathogens are recombinant antibodies or antibody fragments, such as the variable heavy domain of heavy chain antibodies (V H Hs). Methods: In vitro selections offer a promising pathway for identification of therapeutic antibodies, here we explored isolation of V H Hs using phage and yeast display methodology with three antigen formats 1) recombinant E2, 2) linear peptides of E2, selected based on molecular dynamics analysis, and 3) UV inactivated virus. Results: Here we report four novel “human” V H Hs which bind to the VEEV E2 protein selected using different strategies that include both computational and biochemical design of suitable antigens and whole virus selections. These V H Hs have distinct complementarity-determining regions (CDRs). Multiple VHHs bind to the VEEV viral particles in ELISAs, and we report the peptide epitope recognized by these V H Hs. Discussion: Though non-neutralizing, these V H Hs bind to and sequester VEEV viral particles preventing infection, demonstrating the potential of these V H Hs to perform viral “sponging” which represents a novel therapeutic approach. The selection strategies we report may have applications to further antibody developments against other viruses.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1977

Microbe Detector

The AutoMicrobic System (AMS) represents years of intensive research and development by McDonnell Douglas Corp. that originated with a NASA study aimed at development of a fully automated microbial detection and identification system for spacecraft use. A urine specimen is placed into the system, where it is subjected to different freeze-dried microbe nutrients for the nine most common pathogens. An electro-optical scanner studies each specimen once an hour through a 4-to-13 hour cycle, operating automatically. Changes in cell growths on each culture are monitored by computer. The presence of pathogens is indicated when growth reaches a predetermined level. The system also enumerates the pathogens and specifies the type. Developed initially to handle urine testing, AMS soon is expected to allow analyses of blood, spinal fluid, and other body fluids. An additional capability under development is "susceptibility testing," or the determination of which microbe-killing agents-such as penicillin or other antibiotics-would be most effective in eliminating the pathogens. The whole process of detecting, identifying, and enumerating the pathogens and determining susceptibility is accomplished in less half the time required for the manual procedure. The AMS minimizes human error, reduces technician time , and increases laboratory output.

Source record↗
DOE OSTI2016

Pond Crash Forensics: Presumptive identification of pond crash agents by next generation sequencing in replicate raceway mass cultures of Nannochloropsis salina

Productivity of algal mass culture can be severely reduced by contaminating organisms. It is, therefore, important to identify contaminants, determine their effect on productivity and, ultimately, develop countermeasures against such contamination. In this paper, we utilized microbiome analysis by second-generation sequencing of small subunit rRNA genes to characterize the predator and pathogen burden of open raceway cultures of Nannochloropsis salina. Samples were analyzed from replicate raceways before and after crashes. In one culture cycle, we identified two algivorous species, the rotifer Brachionus and gastrotrich Chaetonotus, the presence of which may have contributed to the loss of algal biomass. In the second culture cycle, the raceways were treated with hypochlorite in an unsuccessful attempt to interdict the crash. Finally, our analyses were shown to be an effective strategy for the identification of the biological contaminants and the characterization of intervention strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

PKC-η-MARCKS Signaling Promotes Intracellular Survival of Unopsonized Burkholderia thailandensis

Pathogenic Burkholderia rely on host factors for efficient intracellular replication and are highly refractory to antibiotic treatment. To identify host genes that are required by Burkholderia spp. during infection, we performed a RNA interference (RNAi) screen of the human kinome and identified 35 host kinases that facilitated Burkholderia thailandensis intracellular survival in human monocytic THP-1 cells. We validated a selection of host kinases using imaging flow cytometry to assess efficiency of B. thailandensis survival in the host upon siRNA-mediated knockdown. We focused on the role of the novel protein kinase C isoform, PKC-η, in Burkholderia infection and characterized PKC-η/MARCKS signaling as a key event that promotes the survival of unopsonized B. thailandensis CDC2721121 within host cells. While infection of lung epithelial cells with unopsonized Gram-negative bacteria stimulated phosphorylation of Ser175/160 in the MARCKS effector domain, siRNA-mediated knockdown of PKC-η expression reduced the levels of phosphorylated MARCKS by >3-fold in response to infection with Bt CDC2721121. We compared the effect of the conventional PKC-α and novel PKC-η isoforms on the growth of B. thailandensis CDC2721121 within monocytic THP-1 cells and found that ≥75% knock-down of PRKCH transcript levels reduced intracellular bacterial load 100% more efficiently when compared to growth in cells siRNA-depleted of the classical PKC-α, suggesting that the PKC-η isoform can specifically mediate Burkholderia intracellular survival. Based on imaging studies of intracellular B. thailandensis , we found that PKC-η function stimulates phagocytic pathways that promote B. thailandensis escape into the cytoplasm leading to activation of autophagosome flux. As a result, identification of host kinases that are targeted by Burkholderia during infection provides valuable molecular insights in understanding Burkholderia pathogenesis, and ultimately, in designing effective host-targeted therapies against infectious disease caused by intracellular pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Identification and Classification of Fungal GPCR Gene Families

G protein-coupled receptors (GPCRs) are transmembrane proteins crucial for signal transduction in eukaryotes, responding to diverse extracellular signals. Researchers have found and systematically summarized 14 distinct types of GPCRs in fungi but their distribution among numerous fungal species remained largely unexamined. Additionally, three families of mammalian homologs (Rhodopsin, Glutamate, and Frizzled) have been found in previous studies, but they are not included in the systematic classification of fungal GPCRs. Our study establishes a unified classification of 17 GPCR classes in fungi, combining 14 fungal and 3 mammalian previously recognized groups, and classifies 28,294 GPCRs across 1357 fungal species, significantly expanding the scale of GPCRs in fungi and demonstrating their broader distribution. We found that mammalian homologs are notably more prevalent in Early Diverging Fungi (EDF), whereas the previous 14 classes are predominantly found in Ascomycota and Basidiomycota. The most abundant class detected in fungi was Pth11-like GPCRs, exclusively found in Pezizomycotina and involved in fungal pathogenicity. Our analysis suggested that Pezizomycotina ancestor possessed an extensive array of Pth11-like GPCRs, but over time, some species underwent considerable reductions in these GPCRs in conjunction with genome contractions. Utilizing a custom-built convolutional neural network (CNN) for the identification of fungal GPCRs, we identified several putative novel fungal GPCRs. Predicted interactions between these prospective new GPCRs and G-alpha proteins, as simulated by AlphaFold Multimer, provided additional support for their functional relevance. In conclusion, our work defines the first large-scale, unified classification of fungal GPCRs, reveals lineage-specific expansions and contractions, and uncovers previously unrecognized GPCR candidates with potential functional roles in fungal signaling.

G protein-coupled receptors↗
DOE OSTI2021

A k-mer based approach for classifying viruses without taxonomy identifies viral associations in human autism and plant microbiomes

Viruses are an underrepresented taxa in the study and identification of microbiome constituents; however, they play an essential role in health, microbiome regulation, and transfer of genetic material. Only a few thousand viruses have been isolated, sequenced, and assigned a taxonomy, which limits the ability to identify and quantify viruses in the microbiome. Additionally, the vast diversity of viruses represents a challenge for classification, not only in constructing a viral taxonomy, but also in identifying similarities between a virus’ genotype and its phenotype. However, the diversity of viral sequences can be leveraged to classify their sequences in metagenomic and metatranscriptomic samples, even if they do not have a taxonomy. To identify and quantify viruses in transcriptomic and genomic samples, we developed a dynamic programming algorithm for creating a classification tree out of 715,672 metagenome viruses. To create the classification tree, we clustered proportional similarity scores generated from the k-mer profiles of each of the metagenome viruses to create a database of metagenomic viruses. The resulting Kraken2 database of the metagenomic viruses can be found here: https://www.osti.gov/biblio/1615774 and is compatible with Kraken2. We then integrated the viral classification database with databases created with genomes from NCBI for use with ParaKraken (a parallelized version of Kraken provided in Supplemental Zip 1), a metagenomic/transcriptomic classifier. To illustrate the breadth of our utility for classifying metagenome viruses, we analyzed data from a plant metagenome study identifying genotypic and compartment specific differences between two Populus genotypes in three different compartments. We also identified a significant increase in abundance of eight viral sequences in post mortem brains in a human metatranscriptome study comparing Autism Spectrum Disorder patients and controls. We also show the potential accuracy for classifying viruses by utilizing both the JGI and NCBI viral databases to identify the uniqueness of viral sequences. Finally, we validate the accuracy of viral classification with NCBI databases containing viruses with taxonomy to identify pathogenic viruses in known COVID-19 and cassava brown streak virus infection samples. Our method represents the compulsory first step in better understanding the role of viruses in the microbiome by allowing for a more complete identification of sequences without taxonomy. Better classification of viruses will improve identifying associations between viruses and their hosts as well as viruses and other microbiome members. Despite the lack of taxonomy, this database of metagenomic viruses can be used with any tool that utilizes a taxonomy, such as Kraken, for accurate classification of viruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Stenotrophomonas maltophilia differential gene expression in synthetic cystic fibrosis sputum reveals shared and cystic fibrosis strain-specific responses to the sputum environment.

Stenotrophomonas maltophilia is a Gram-negative opportunistic pathogen that can infect the lungs of people with cystic fibrosis (CF). The highly viscous mucus in the CF lung, expectorated as sputum, serves as the primary nutrient source for microbes colonizing this site and induces virulence-associated phenotypes and gene expression in several CF pathogens. Here, we characterized the transcriptional responses of three S. maltophilia strains during exposure to synthetic CF sputum media (SCFM2) to gain insight into how this organism interacts with the host in the CF lung. These efforts led to the identification of 881 transcripts differentially expressed by all three strains, many of which reflect the metabolic pathways used by S. maltophilia in sputum, as well as altered stress responses. The latter correlated with increased resistance to peroxide exposure after pre-growth in SCFM2 for two of the strains. We also compared the SCFM2 transcriptomes of two S. maltophilia CF isolates to that of the acute infection strain, S. maltophilia K279a, allowing us to identify CF isolate-specific signatures in differential gene expression. Expression of genes from the accessory genomes was also differentially altered in response to SCFM2. Finally, a number of biofilm-associated genes were differentially induced in SCFM2, particularly in K279a, which corresponded to increased aggregation and biofilm formation in this strain relative to both CF strains. Collectively, this work details the response of S. maltophilia to an environment that mimics important aspects of the CF lung, identifying potential survival strategies and metabolic pathways used by S. maltophilia during infections. Importance Stenotrophomonas maltophilia is an important infecting bacterium in the airways of people with cystic fibrosis (CF). However, compared to the other CF pathogens, S. maltophilia has been relatively understudied. The significance of our research is to provide insight into the global transcriptomic changes of S. maltophilia in response to a medium that was designed to mimic important aspects of the CF lung. This work allows us to understand the overall metabolic changes that occur when S. maltophilia encounters the CF lung, and generates a roadmap of candidate genes to test using in vitro and in vivo models of CF.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The essential effector SCRE1 in Ustilaginoidea virens suppresses rice immunity via a small peptide region

Summary The biotrophic fungal pathogen Ustilaginoidea virens causes rice false smut, a newly emerging plant disease that has become epidemic worldwide in recent years. The U. virens genome encodes many putative effector proteins that, based on the study of other pathosystems, could play an essential role in fungal virulence. However, few studies have been reported on virulence functions of individual U. virens effectors. Here, we report our identification and characterization of the secreted cysteine‐rich protein SCRE1, which is an essential virulence effector in U. virens . When SCRE1 was heterologously expressed in Magnaporthe oryzae , the protein was secreted and translocated into plant cells during infection. SCRE1 suppresses the immunity‐associated hypersensitive response in the nonhost plant Nicotiana benthamiana . Induced expression of SCRE1 in rice also inhibits pattern‐triggered immunity and enhances disease susceptibility to rice bacterial and fungal pathogens. The immunosuppressive activity is localized to a small peptide region that contains an important ‘cysteine‐proline‐alanine‐arginine‐serine’ motif. Furthermore, the scre1 knockout mutant generated using the CRISPR/Cas9 system is attenuated in U. virens virulence to rice, which is greatly complemented by the full‐length SCRE1 gene. Collectively, this study indicates that the effector SCRE1 is able to inhibit host immunity and is required for full virulence of U. virens .

Zhang, Nan↗
DOE OSTI2018

Impacts of environmental exposure on thermal and mycological characteristics of insulation wools

Highlights: • Insulation materials (IM) suffer expositions to weather on energy efficient buildings. • Induced exposure to weather of IM reveals differences in ATR-FTIR spectra. • Mycological analysis shows a significant effect of exposure condition on IM. • Mold species detected may induce human health risk and degradation of IM. • Thermal conductivity of IM according humidity of air may impact energy performance. - Abstract: Fieldwork was conducted on 138 energy efficient buildings, to check if building site practices induced exposure to weather of thermal insulation. In nearly 80% of cases, insulation was exposed to weather due to insufficient protection. Therefore insulating wools were exposed, divided into three parts (control, exposure under shelter, exposure to weather). After the exposure period these samples were submitted to thermal conductivity measurements and infrared spectroscopy. A numerical study was carried out to evaluate the influence of weather conditions on thermal performance. Identifications of molds were realized by direct cultures of each sample. Mycological analyses provided the most significant results, showing a significant effect of exposure condition, with possible consequences in human health (toxinogenic, allergenic or pathogenic species) and material properties (cellulolytic species). Infrared spectrometry also showed some changes in sensitivity to water. These results show the interest to study in more detail the variations in the sensitivity, to moisture and mold, of insulation material throughout its ageing on site, and the interactions with the practices of the building process.

36 MATERIALS SCIENCE↗
NASA NTRS2009

Human System Risk Management - Tools of our Trade

The risk of infectious disease to select individuals has historically been difficult to predict in either spaceflight or on Earth with health care efforts relying on broad-based prevention and post-infection treatment. Over the past 10 years, quantitative microbial risk assessment evaluations have evolved to formalize the assessment process and quantify the risk. This process of hazard identification, exposure assessment, dose-response assessment, and risk characterization has been applied by the water and food safety industries to address the public health impacts associated with the occurrence of and human exposure to pathogens in water and food for the development of preventive strategies for microbial disease. NASA is currently investigating the feasibility of using these techniques to better understand the risks to astronauts and refine their microbiological requirements. To assess these techniques, NASA began an evaluation of the potable water system on the International Space Station to determine how the microbial risk from water consumption during flight differed from terrestrial sources, such as municipal water systems. The ultimate goal of this work is to optimize microbial requirements which would minimize unnecessary cargo and use of crew time, while still protecting the health of the crew. Successful demonstration of this risk assessment framework with the water system holds the potential to maximize the use of available resources during spaceflight missions and facilitate investigations into the evaluation of other routes of infection, such as through the spaceflight foods system.

Ott, C. Mark↗
DOE OSTI2014

Proteome-wide identification of predominant subcellular protein localizations in a bacterial model organism

Proteomics data provide unique insights into biological systems, including the predominant subcellular localization (SCL) of proteins, which can reveal important clues about their functions. Here we analyzed data of a complete prokaryotic proteome expressed under two conditions mimicking interaction of the emerging pathogen Bartonella henselae with its mammalian host. Normalized spectral count data from cytoplasmic, total membrane, inner and outer membrane fractions allowed us to identify the predominant SCL for 82% of the identified proteins. The spectral count proportion of total membrane versus cytoplasmic fractions indicated the propensity of cytoplasmic proteins to co-fractionate with the inner membrane, and enabled us to distinguish cytoplasmic, peripheral innermembrane and bona fide inner membrane proteins. Principal component analysis and k-nearest neighbor classification training on selected marker proteins or predominantly localized proteins, allowed us to determine an extensive catalog of at least 74 expressed outer membrane proteins, and to extend the SCL assignment to 94% of the identified proteins, including 18% where in silico methods gave no prediction. Suitable experimental proteomics data combined with straightforward computational approaches can thus identify the predominant SCL on a proteome-wide scale. Finally, we present a conceptual approach to identify proteins potentially changing their SCL in a condition-dependent fashion.

59 BASIC BIOLOGICAL SCIENCES↗
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↗