Project description:Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.
Project description:The NIEHS data set (endpoint C) was provided by the National Institute of Environmental Health Sciences (NIEHS) of the National Institutes of Health (Research Triangle Park, NC, USA). The study objective was to use microarray gene expression data acquired from the liver of rats exposed to hepatotoxicants to build classifiers for prediction of liver necrosis. The gene expression compendium data set was collected from 418 rats exposed to one of eight compounds (1,2-dichlorobenzene, 1,4-dichlorobenzene, bromobenzene, monocrotaline, N-nitrosomorpholine, thioacetamide, galactosamine, and diquat dibromide). All eight compounds were studied using standardized procedures, i.e. a common array platform (Affymetrix Rat 230 2.0 microarray), experimental procedures and data retrieving and analysis processes.
Project description:Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.
Project description:To understand the ecophysiology of Sulfurihydrogenibium spp. in situ, integrated metagenomic, metatranscriptomic and metaproteomic analyses were conducted on a microbial community from Narrow Gauge at Mammoth Hot Springs, Yellowstone National Park.
2020-05-26 | PXD004323 | Pride
Project description:Streptomyces sp. isolated from wetlands sediments
Project description:We sequenced total RNA from whole blood samples of 27 wild gray wolves from Yellowstone National Park. Gene expression level analysis of both male and female wolves, ranging from ages 0.8-8.8 years.
Project description:In this study, we describe the isolation and identification of Streptomyces isolates collected from traditional medicinal plants’ rhizosphere during a campaign in Hamedan Province, Iran. Traditional medicinal plants represent a rich and unique source for the isolation of Streptomyces and new antimicrobial compounds. This strain was isolated from the rhizosphere of Helichrysum rubicundum
Project description:28 Streptomyces strains isolated from common scab lesions of potato tubers from a wide geographic range in Norway, were selected for microarray analysis. The selected strains were subjected to species identification by microarray, 16S phylogenetic analysis and PCR; and microarray-based comparative genome analysis. To our knowledge, this is the first report of S. turgidiscabies and S. europaeiscabiei in Norway.