Bulk sets and single cell sets of TMT16-labeled GC-1 and GC-2 cells
ABSTRACT: We generated the raw sample sets of TMT16-labeled for the quantification of single-cell from two cultured murine cell lines, GC-1 spg (GC-1) and GC-2spd (GC-2), and the raw bulk sets of TMT16-labeled cells.
Project description:This paper describes data collected on 2 sets of 8 French red wines from two grape varieties: Pinot Noir (PN) and Cabernet Franc (CF). It provides, for the 16 wines, (i) sensory descriptive data obtained with a trained panel, (ii) volatile organic compounds (VOC) quantification data obtained by Headspace Solid Phase Micro-Extraction - Gas Chromatography - Mass Spectrometry (HS-SPME-GC-MS) and (iii) odor-active compounds identification by Headspace Solid Phase Micro-Extraction - Gas Chromatography - Mass Spectrometry - Olfactometry (HS-SPME-GC-MS-O). The raw data are hosted on an open-access research data repository .
Project description:We compared the performance of gas chromatography time-of-flight mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) for metabolite biomarker discovery. Metabolite extracts from 109 human serum samples were analyzed on both platforms with a pooled serum sample analyzed after every 9 biological samples for the purpose of quality control (QC). The experimental data derived from the pooled QC samples showed that the GC×GC-MS platform detected about three times as many peaks as the GC-MS platform at a signal-to-noise ratio SNR ? 50, and three times the number of metabolites were identified by mass spectrum matching with a spectral similarity score Rsim ? 600. Twenty-three metabolites had statistically significant abundance changes between the patient samples and the control samples in the GC-MS data set while 34 metabolites in the GC×GC-MS data set showed statistically significant differences. Among these two groups of metabolite biomarkers, nine metabolites were detected in both the GC-MS and GC×GC-MS data sets with the same direction and similar magnitude of abundance changes between the control and patient sample groups. Manual verification indicated that the difference in the number of the biomarkers discovered using these two platforms was mainly due to the limited resolution of chromatographic peaks by the GC-MS platform, which can result in severe peak overlap making subsequent spectrum deconvolution for metabolite identification and quantification difficult.
Project description:ADAP-GC is an automated computational pipeline for untargeted, GC/MS-based metabolomics studies. It takes raw mass spectrometry data as input and carries out a sequence of data processing steps including construction of extracted ion chromatograms, detection of chromatographic peak features, deconvolution of coeluting compounds, and alignment of compounds across samples. Despite the increased accuracy from the original version to version 2.0 in terms of extracting metabolite information for identification and quantitation, ADAP-GC 2.0 requires appropriate specification of a number of parameters and has difficulty in extracting information on compounds that are in low concentration. To overcome these two limitations, ADAP-GC 3.0 was developed to improve both the robustness and sensitivity of compound detection. In this paper, we report how these goals were achieved and compare ADAP-GC 3.0 against three other software tools including ChromaTOF, AnalyzerPro, and AMDIS that are widely used in the metabolomics community.
Project description:We have developed a novel technique of using fluorescent tRNA for translation monitoring (FtTM). FtTM enables the identification and monitoring of active protein synthesis sites within live cells at submicron resolution through quantitative microscopy of transfected bulk uncharged tRNA, fluorescently labeled in the D-loop (fl-tRNA). The localization of fl-tRNA to active translation sites was confirmed through its co-localization with cellular factors and its dynamic alterations upon inhibition of protein synthesis. Moreover, fluorescence resonance energy transfer (FRET) signals, generated when fl-tRNAs, separately labeled as a FRET pair occupy adjacent sites on the ribosome, quantitatively reflect levels of protein synthesis in defined cellular regions. In addition, FRET signals enable detection of intra-populational variability in protein synthesis activity. We demonstrate that FtTM allows quantitative comparison of protein synthesis between different cell types, monitoring effects of antibiotics and stress agents, and characterization of changes in spatial compartmentalization of protein synthesis upon viral infection.
Project description:In the vertebrate genomes studied to date the 5' end of many genes are associated with distinctive sequences known as CpG islands. CpG islands have three properties: they are non-methylated; the dinucleotide CpG occurs at the frequency predicted by base composition; and they are GC-rich. Unexpectedly we have found that CpG islands in certain fish only have the first two properties; that is, their GC-content is not elevated compared to bulk genomic DNA. Based on this finding, we speculate that the GC-richness of CpG islands in vertebrates other than fish is a passive consequence of a higher mutation rate in regions of open chromatin under conditions where the nucleotide precursor pools are biased.
Project description:Synthetic selective thyroid hormone (TH) receptor (TR) modulators (STRM) exhibit beneficial effects on dyslipidemias in animals and humans and reduce obesity, fatty liver, and insulin resistance in preclinical animal models. STRM differ from native TH in preferential binding to the TR? subtype vs. TR?, increased uptake into liver, and reduced uptake into other tissues. However, selective modulators of other nuclear receptors exhibit important gene-selective actions, which are attributed to differential effects on receptor conformation and dynamics and can have profound influences in animals and humans. Although there are suggestions that STRM may exhibit such gene-specific actions, the extent to which they are actually observed in vivo has not been explored. Here, we show that saturating concentrations of the main active form of TH, T(3), and the prototype STRM GC-1 induce identical gene sets in livers of euthyroid and hypothyroid mice and a human cultured hepatoma cell line that only expresses TR?, HepG2. We find one case in which GC-1 exhibits a modest gene-specific reduction in potency vs. T(3), at angiopoietin-like factor 4 in HepG2. Investigation of the latter effect confirms that GC-1 acts through TR? to directly induce this gene but this gene-selective activity is not related to unusual T(3)-response element sequence, unlike previously documented promoter-selective STRM actions. Our data suggest that T(3) and GC-1 exhibit almost identical gene regulation properties and that gene-selective actions of GC-1 and similar STRM will be subtle and rare.
Project description:BACKGROUND: Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS) makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. DESCRIPTION: Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP) server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.). Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP) their own data to the server for online processing via a novel raw data processing pipeline. CONCLUSIONS: MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to assess data quality and draw their own insights from published metabolomics datasets.
Project description:Protein turnover is an important aspect of the regulation of cellular processes for organisms when responding to developmental or environmental cues. The measurement of protein turnover in plants, in contrast to that of rapidly growing unicellular organismal cultures, is made more complicated by the high degree of amino acid recycling, resulting in significant transient isotope incorporation distributions that must be dealt with computationally for high throughput analysis to be practical. An algorithm in R, ProteinTurnover, was developed to calculate protein turnover with transient stable isotope incorporation distributions in a high throughput automated manner using high resolution MS and MS/MS proteomic analysis of stable isotopically labeled plant material. ProteinTurnover extracts isotopic distribution information from raw MS data for peptides identified by MS/MS from data sets of either isotopic label dilution or incorporation experiments. Variable isotopic incorporation distributions were modeled using binomial and beta-binomial distributions to deconvolute the natural abundance, newly synthesized/partial-labeled, and fully labeled peptide distributions. Maximum likelihood estimation was performed to calculate the distribution abundance proportion of old and newly synthesized peptides. The half-life or turnover rate of each peptide was calculated from changes in the distribution abundance proportions using nonlinear regression. We applied ProteinTurnover to obtain half-lives of proteins from enriched soluble and membrane fractions from Arabidopsis roots.
Project description:The development of improved mass spectrometers and supporting computational tools is expected to enable the rapid annotation of whole metabolomes. Essential for the progress is the identification of strengths and weaknesses of novel instrumentation in direct comparison to previous instruments. Orbitrap liquid chromatography (LC)-mass spectrometry (MS) technology is now widely in use, while Orbitrap gas chromatography (GC)-MS introduced in 2015 has remained fairly unexplored in its potential for metabolomics research. This study aims to evaluate the additional knowledge gained in a metabolomics experiment when using the high-resolution Orbitrap GC-MS in comparison to a commonly used unit-mass resolution single-quadrupole GC-MS. Samples from an osmotic stress treatment of a non-model organism, the microalga Skeletonema costatum, were investigated using comparative metabolomics with low- and high-resolution methods. Resulting datasets were compared on a statistical level and on the level of individual compound annotation. Both MS approaches resulted in successful classification of stressed vs. non-stressed microalgae but did so using different sets of significantly dysregulated metabolites. High-resolution data only slightly improved conventional library matching but enabled the correct annotation of an unknown. While computational support that utilizes high-resolution GC-MS data is still underdeveloped, clear benefits in terms of sensitivity, metabolic coverage, and support in structure elucidation of the Orbitrap GC-MS technology for metabolomics studies are shown here.
Project description:The transcription and transport of messenger RNA (mRNA) are critical steps in regulating the spatial and temporal components of gene expression, but it has not been possible to observe the dynamics of endogenous mRNA in primary mammalian tissues. We have developed a transgenic mouse in which all ?-actin mRNA is fluorescently labeled. We found that ?-actin mRNA in primary fibroblasts localizes predominantly by diffusion and trapping as single mRNAs. In cultured neurons and acute brain slices, we found that multiple ?-actin mRNAs can assemble together, travel by active transport, and disassemble upon depolarization by potassium chloride. Imaging of brain slices revealed immediate early induction of ?-actin transcription after depolarization. Studying endogenous mRNA in live mouse tissues provides insight into its dynamic regulation within the context of the cellular and tissue microenvironment.