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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 145 records · Page 8

The dynamic Atg13-free conformation of the Atg1 EAT domain is required for phagophore expansion

Yeast macroautophagy begins with the de novo formation of a double-membrane phagophore at the preautophagosomal structure/phagophore assembly site (PAS), followed by its expansion into the autophagosome responsible for cargo engulfment. The kinase Atg1 is recruited to the PAS by Atg13 through interactions between the EAT domain of the former and the tMIM motif of the latter. Mass-spectrometry data have shown that, in the absence of Atg13, the EAT domain structure is strikingly dynamic, but the function of this Atg13-free dynamic state has been unclear. We used structure-based mutational analysis and quantitative and superresolution microscopy to show that Atg1 is present on autophagic puncta at, on average, twice the stoichiometry of Atg13. Moreover, Atg1 colocalizes with the expanding autophagosome in a manner dependent on Atg8 but not Atg13. We used isothermal titration calorimetry and crystal structure information to design an EAT domain mutant allele ATG1 DD that selectively perturbs the function of the Atg13-free state. Atg1 DD shows reduced PAS formation and does not support phagophore expansion, showing that the EAT domain has an essential function that is separate from its Atg13-dependent role in autophagy initiation.

59 BASIC BIOLOGICAL SCIENCES↗

MapReduce Implementation of a Hybrid Spectral Library-Database Search Method for Large-Scale Peptide Identification

A MapReduce-based implementation called MR- MSPolygraph for parallelizing peptide identification from mass spectrometry data is presented. The underlying serial method, MSPolygraph, uses a novel hybrid approach to match an experimental spectrum against a combination of a protein sequence database and a spectral library. Our MapReduce implementation can run on any Hadoop cluster environment. Experimental results demonstrate that, relative to the serial version, MR-MSPolygraph reduces the time to solution from weeks to hours, for processing tens of thousands of experimental spectra. Speedup and other related performance studies are also reported on a 400-core Hadoop cluster using spectral datasets from environmental microbial communities as inputs.

59 BASIC BIOLOGICAL SCIENCES↗

PGP: parallel prokaryotic proteogenomics pipeline for MPI clusters, high-throughput batch clusters and multicore workstations

Summary: We present the first public release of our proteogenomic annotation pipeline. We have previously used our original unreleased implementation to improve the annotation of 46 diverse prokaryotic genomes by discovering novel genes, post-translational modifications and correcting the erroneous annotations by analyzing proteomic mass-spectrometry data. This public version has been redesigned to run in a wide range of parallel Linux computing environments and provided with the automated configuration, build and testing facilities for easy deployment and portability.

59 BASIC BIOLOGICAL SCIENCES↗

The survivability of phyllosilicates and carbonates impacting Stardust Al foils: Facilitating the search for cometary water

Abstract Comet 81P/Wild 2 samples returned by NASA's Stardust mission provide an unequalled opportunity to study the contents of, and hence conditions and processes operating on, comets. They can potentially validate contentious interpretations of cometary infrared spectra and in situ mass spectrometry data: specifically the identification of phyllosilicates and carbonates. However, Wild 2 dust was collected via impact into capture media at ~6 km s −1 , leading to uncertainty as to whether these minerals were captured intact, and, if subjected to alteration, whether they remain recognizable. We simulated Stardust Al foil capture conditions using a two‐stage light‐gas gun, and directly compared transmission electron microscope analyses of pre‐ and postimpact samples to investigate survivability of lizardite and cronstedtite (phyllosilicates) and calcite (carbonate). We find the phyllosilicates do not survive impact as intact crystalline materials but as moderately to highly vesiculated amorphous residues lining resultant impact craters, whose bulk cation to Si ratios remain close to that of the impacting grain. Closer inspection reveals variation in these elements on a submicron scale, where impact‐induced melting accompanied by reducing conditions (due to the production of oxygen scavenging molten Al from the target foils) has resulted in the production of native silicon and Fe‐ and Fe‐Si‐rich phases. In contrast, large areas of crystalline calcite are preserved within the calcite residue, with smaller regions of vesiculated, Al‐bearing calcic glass. Unambiguous identification of calcite impactors on Stardust Al foil is therefore possible, while phyllosilicate impactors may be inferred from vesiculated residues with appropriate bulk cation to Si ratios. Finally, we demonstrate that the characteristic textures and elemental distributions identifying phyllosilicates and carbonates by transmission electron microscopy can also be observed by state‐of‐the‐art scanning electron microscopy providing rapid, nondestructive initial mineral identifications in Stardust residues.

79 ASTRONOMY AND ASTROPHYSICS↗

Multiscale Simulations of ALD in Cross Flow Reactors

In this study, we have developed a multiscale simulation code that allows us to study the impact of surface chemistry on the coating of large area substrates with high surface area/high aspect-ratio features. Our code, based on open-source libraries, takes advantage of the ALD surface chemistry to achieve an extremely efficient two-way coupling between reactor and feature length scales, and it can provide simulated quartz crystal microbalance and mass spectrometry data at any point of the reactor. By combining experimental surface characterization with simple analysis of growth profiles in a tubular cross flow reactor, we are able to extract a minimal set of reactions to effectively model the surface chemistry, including the presence of spurious CVD, to evaluate the impact of surface chemistry on the coating of large, high surface area substrates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

glmnetLRC f/k/a lrc package: Logistic Regression Classification

Methods for fitting and predicting logistic regression classifiers (LRC) with an arbitrary loss function using elastic net or best subsets. This package adds additional model fitting features to the existing glmnet and bestglm R packages. This package was created to perform the analyses described in Amidan BG, Orton DJ, LaMarche BL, et al. 2014. Signatures for Mass Spectrometry Data Quality. Journal of Proteome Research. 13(4), 2215-2222. It makes the model fitting available in the glmnet and bestglm packages more general by identifying optimal model parameters via cross validation with an customizable loss function. It also identifies the optimal threshold for binary classification.

Source record↗

Atreyu

Ion mobility mass spectrometry data viewer and extractor, targeted toward PNNL's UIMF files

Degan, Michael↗

DeconEngineV2

The DeconEngine includes routines for deconvoluting (deisotoping) observed isotopic signatures in mass spectrometry data to detect features.

Monroe, Matthew↗

Informed Proteomics

The Informed Proteomics project includes algorithms for proteomic mass spectrometry data analysis. Although the back-end data access and some of the scoring routines are general purpose, this repository is currently maintained for top down MS/MS datasets.

Fujimoto, Grant↗

MsDataFileReader

A VB.NET DLL that can read mass spectrometry data from four file formats: mzXML, mzData, concatenated .dta files (_dta.txt), and Mascot Generic Format files (.mgf)

Gibbons, Bryson↗

LC-IMS-MS Feature Finder

LC-IMS-MS Feature Finder is a command line software application which searches for possible molecular ion signatures in multidimensional liquid chromatography, ion mobility spectrometry, and mass spectrometry data by clustering deisotoped peaks with similar monoisotopic mass values, charge states, elution times, and drift times. The software application includes an algorithm for detecting multiple conformations and co-eluting species in the ion mobility dimension. LC-IMS-MS Feature Finder is designed to create an output file with detected features that includes associated information about the detected features.

Crowell, KevinL.↗

MetISIS

The software enables identifying small molecules based on mass spectrometry data.

Kangas, Lars↗

Random forest models accurately classify synthetic opioids using high-dimensionality mass spectrometry datasets

Detection of novel threat agents presents several challenges, a principle one being the development of untargeted methods to screen an increasing number of threat chemicals whose exact structures are unknown. With the use of Machine Learning (ML) tools, we can guide the development of analytical methods for broad-spectrum detection of unbounded threat chemical families in complex mixtures. Toward this goal, we used nominal mass and high-resolution mass spectrometry data for hundreds of synthetic opioids and non-opioid compounds. We tested two ML techniques, logistic regression and random forest, to develop models towards a practical, implementable method for opioid detection. We found that of these tested ML methods, random forest models resulted in the highest validation accuracy (95+%) for both nominal mass and high-resolution classification of opioids versus non-opioids, with low false positive and false negative rates. The RF models were then used to successfully predict the classification of 10 compounds—five opioids and five non-opioids not part of the training and validation analysis. This application of ML is a critical step towards the development of field-deployable nominal mass spectrometers with ML-driven analyses for classification of emergent threats.

Arasteh, Kourosh [Lawrence Livermore National Labo↗

On the Zwitterionic Nature of Gas-Phase Peptides and Protein Ions

Determining the total number of charged residues corresponding to a given value of net charge for peptides and proteins in gas phase is crucial for the interpretation of mass-spectrometry data, yet it is far from being understood. Here we show that a novel computational protocol based on force field and massive density functional calculations is able to reproduce the experimental facets of well investigated systems, such as angiotensin II, bradykinin, and tryptophan-cage. The protocol takes into account all of the possible protomers compatible with a given charge state. Our calculations predict that the low charge states are zwitterions, because the stabilization due to intramolecular hydrogen bonding and salt-bridges can compensate for the thermodynamic penalty deriving from deprotonation of acid residues. In contrast, high charge states may or may not be zwitterions because internal solvation might not compensate for the energy cost of charge separation.

59 BASIC BIOLOGICAL SCIENCES↗

Impacts of phase state and water content on secondary organic aerosol formation and partitioning (Final Technical Report)

Secondary organic aerosols (SOA) account for a major fraction of particulate matter in the atmosphere, affecting climate, air quality, and public health. SOA formation and evolution are highly complex processes involving both chemical reactions and transport of molecules in air, at particle surfaces, and within particles. The state of the matter, or “phase state,” comprising SOA can vary from a liquid, over an amorphous semi-solid, to a glassy solid, depending on chemical composition, water content, relative humidity (RH), and temperature. The occurrence of glassy and amorphous semi-solid states can pose limitations on the rate of transport of molecules, affecting gas-particle interactions and challenging the treatment of SOA in atmospheric models. The objective of this project was to improve fundamental understanding of the interplay of the phase state of particles and water content on the evolution of SOA formation. We have developed a method to estimate the glass transition temperature (T g ) of organic compounds to predict the phase state and viscosity of SOA. This method has been applied to high resolution mass spectrometry data of various types of SOA, achieving a good agreement with viscosity measurements. In addition, the viscosity estimation method was implemented into a regional model CMAQ to simulate diel and seasonal variations of SOA phase state over the U.S. Applying kinetic multilayer modeling, we analyzed laboratory experiments and ARM field measurements (e.g., HI-SCALE) on kinetic limitations of amine uptake. We have also conducted numerical simulations to estimate equilibration timescales of SOA partitioning. Overall, we have evaluated the impacts of phase state and water content on SOA lifecycle that should contribute to reducing the uncertainty of SOA representation in regional climate and air quality predictions. The project has yielded 17 publications, in which DE-SC0018349 is explicitly acknowledged. Please see the list of publications as below, followed by summary of research activities.

54 ENVIRONMENTAL SCIENCES↗

Analysis of metabolomics datasets with high-performance computing and metabolite atlases

Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged for future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. Furthermore, by using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models.

59 BASIC BIOLOGICAL SCIENCES↗

Stratospheric nitric oxide and ozone measurements using photoionization mass spectrometry and UV absorption

Nitric oxide has been measured in situ between 38.4 and 29.8 km by a new technique, photoionization mass spectrometry. Data indicate a peak mixing ratio of 5.7 plus or minus 0.35 ppbv at 37.5 km and only 0.2 plus or minus 0.2 ppbv at 32.8 km with a sharp gradient in concentration between 33 and 34 km. Simultaneous in-situ measurements of the ozone concentration show no significant feature at that altitude. The rapid decrease in mixing ratio is not predicted by current theory.

Maier, E. J.↗