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Global analysis of impact of Atg5 mutation on steady-state protein levels

ABSTRACT: This experiment analyzes the global impact of Atg5-/- mutation on steady-state protein levels by a standard SILAC experiment. WT+vector cells were grown in isotopically labeled media for multiple passages in order to fully label the proteome. Unlabeled Atg5-/- cells and labeled WT+vector cells were grown to confluency and protein extracts from quiescent cultures were combined at a 1:1 ratio and analyzed by LC-MS/MS. In this experiment, ratios of labeled to unlabeled spectra report on changes in steady-state expression levels of proteins induced by impairment of autophagy. Table of files Cells Fractionation Raw Data Filenames Wildtype & Atg5-/- Yes SILAC_(1-8).raw (8 fractions)

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Sina Ghaemmaghami

PROVIDER: MSV000080752 | MassIVE | Wed Mar 29 06:20:00 BST 2017

SECONDARY ACCESSION(S): PXD003558

REPOSITORIES: MassIVE

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Publications

Global Analysis of Cellular Protein Flux Quantifies the Selectivity of Basal Autophagy.

Zhang Tian T Shen Shichen S Qu Jun J Ghaemmaghami Sina S

Cell reports 20160303 10

In eukaryotic cells, macroautophagy is a catabolic pathway implicated in the degradation of long-lived proteins and damaged organelles. Although it has been demonstrated that macroautophagy can selectively degrade specific targets, its contribution to the basal turnover of cellular proteins has not been quantified on proteome-wide scales. In this study, we created autophagy-deficient primary human fibroblasts and quantified the resulting changes in basal degradative flux by dynamic proteomics. O ...[more]

PMID: 26947064

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Global analysis of impact of Atg5 mutation on steady-state protein levels

Project description:This experiment analyzes the global impact of Atg5-/- mutation on steady-state protein levels by a standard SILAC experiment. WT+vector cells were grown in isotopically labeled media for multiple passages in order to fully label the proteome. Unlabeled Atg5-/- cells and labeled WT+vector cells were grown to confluency and protein extracts from quiescent cultures were combined at a 1:1 ratio and analyzed by LC-MS/MS. In this experiment, ratios of labeled to unlabeled spectra report on changes in steady-state expression levels of proteins induced by impairment of autophagy. Table of files Cells Fractionation Raw Data Filenames Wildtype & Atg5-/- Yes SILAC_(1-8).raw (8 fractions)

2016-06-14 | PXD003558 | Pride

Wild type versus delta vts1

Project description:The experiment was designed to look for genes up/downregulated in the absense of Vts1p compared to wild-type cells grown in steady state conditions. Keywords: VTS1

2006-02-15 | GSE3859 | GEO

Metabolic labeling of Hek293 cells using 4-thiouracil

Project description:Hek293 cells were metabolically labelled using 4-thiouracil as described in (Schwalb et al, Science. 2016 Jun 3;352(6290):1225-8) but without fragmentation, and then bulk RNA was prepared for sequencing using the STRT method (Islam et al, Genome Res. 2011 Jul;21(7):1160-7). Samples were incubated in duplicate for 5, 15 and 30 minutes and included an unlabeled control representing the steady-state expression state.

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Streptococcus mutans UA159 vs. fabM mutant strain (UR117), pH7 vs. pH5/5.5

Project description:Transcriptional analysis of glucose shock vs. steady-state growth in the parent strain and an acid sensitive mutant strain of S. mutans RNA was extracted from 4 replicate samples of S. mutans UA159 and UR117 (fabM mutant strain) grown in continuous culture to a steady-state pH value of 7. The cultures were exposed to a glucose shock (200mM) and samples were collected upon achieving culture pH value of 5.5. pH control was re-established and cultures were allowed to grow to a steady-state pH value of 5 (for UA159) and 5.5 (for fabM mutant). RNA was labeled with Cy3. For each replicate, labeled RNA was hybridized to slides along with Cy5-labeled reference RNA, extracted from S. mutans UA159 cultures grown to mid-log.

2015-02-15 | E-GEOD-64236 | biostudies-arrayexpress

Mesenchymal stem cell labelings with ferritin

Project description:Mesenchymal stem cells (MSC) omplexed to different transfection agents (R60, R200, DOSPER, jetPei, Pulsin). Two MSC populations (h21 and h24) and two passages (P2 and P4) were tested with different labelings. In a direct design experiment each sample was compared to its unlabeled control sample. Keywords: Human gene expression study Reference design with unlabeled cells in the Cy3 reference channel, and labeled cells in the Cy5 channel.

2010-05-16 | E-GEOD-11470 | biostudies-arrayexpress

Mixing of Escherichia coli cells labeled with 13C glucose with unlabeled E. coli cells for benchmarking of protein-based stable isotope probing proteomics (Protein-SIP)

Project description:This dataset is part of a study aimed at developing algorithms for the quantification of stable isotope content in microorganisms after labeling them with stable isotope-labeled substrates. In this dataset Escherichia coli cultures were labeled with different percentages (1% or 10%) of either single-carbon 13C glucose (13C2) or fully-labeled 13C glucose (13C1-6). Labeled cells were subsequently mixed with unlabeled E. coli cells in fixed ratios (50%, 90%, 95%, 99%). Cultures of E. coli were grown in M9 minimal medium in which a percentage of the glucose was replaced with 13C2 or 13C1-6 glucose for >10 generations to achieve close to complete labeling of cells. Triplicate cultures were grown for each percentage. Please note that the unlabeled glucose that was used of course had a natural content of 13C of around 1.1%, thus the 0% added label samples have an actual 13C content of 1.1% and all added label is on top of this value. We included a tab delimited table with this submission providing details on all raw files.

2022-12-30 | PXD024287 | Pride

geoRge: A Computational Tool To Detect the Presence of Stable Isotope Labeling in LC/MS-Based Untargeted Metabolomics

Project description:Studying the flow of chemical moieties through the complex set of metabolic reactions that happen in the cell is essential to understanding the alterations in homeostasis that occur in disease. Recently, LC/MS-based untargeted metabolomics and isotopically labeled metabolites have been used to facilitate the unbiased mapping of labeled moieties through metabolic pathways. However, due to the complexity of the resulting experimental data sets few computational tools are available for data analysis. Here we introduce geoRge, a novel computational approach capable of analyzing untargeted LC/MS data from stable isotope-labeling experiments. geoRge is written in the open language R and runs on the output structure of the XCMS package, which is in widespread use. As opposed to the few existing tools, which use labeled samples to track stable isotopes by iterating over all MS signals using the theoretical mass difference between the light and heavy isotopes, geoRge uses unlabeled and labeled biologically equivalent samples to compare isotopic distributions in the mass spectra. Isotopically enriched compounds change their isotopic distribution as compared to unlabeled compounds. This is directly reflected in a number of new m/z peaks and higher intensity peaks in the mass spectra of labeled samples relative to the unlabeled equivalents. The automated untargeted isotope annotation and relative quantification capabilities of geoRge are demonstrated by the analysis of LC/MS data from a human retinal pigment epithelium cell line (ARPE-19) grown on normal and high glucose concentrations mimicking diabetic retinopathy conditions in vitro. In addition, we compared the results of geoRge with the outcome of X(13)CMS, since both approaches rely entirely on XCMS parameters for feature selection, namely m/z and retention time values. geoRge is available as an R script at https://github.com/jcapelladesto/geoRge.

2015-09-15 | MTBLS213 | MetaboLights

Chromatin based modeling of transcription rates identifies the contribution of different regulatory layers to steady-state mRNA levels

Project description:Messenger RNA levels in eukaryotes are balanced by two consecutive regulatory layers. Primary, transcriptional regulation at the level of chromatin and secondary, post-transcriptional regulation of the initial transcript in the cytoplasm. Each layer is individually studied in mechanistic detail, while integration of both processes is required to quantify the individual contribution to steady-state RNA levels. Here we show that chromatin features are sufficient to model transcription rate but with different sensitivities in dividing versus post mitotic cells. In both cases chromatin derived transcript levels explains over 80% of variance in measured RNA level enabling to separate transcription from different post-transcriptional processes. By further inclusion of measurements of mRNA half-life and micro RNA expression data we identify a low quantitative contribution of RNA decay by either micro RNA or general differential turnover to final mRNA levels. Together this establishes a chromatin based quantitative model for the contribution of transcriptional and posttranscriptional processes to steady-state levels of messenger RNA. H3K36me3 ChIP followed by deep sequencing // time-series of mRNA measurement on Affymetrix microarray platform following actinomycinD treatment. MmES Samples: mRNA measurement on Affymetrix microarray platform following thioU labeling and separation of fractions according to labeled (newly synthetised) and unlabeled (pre-existing) RNA.

2012-07-23 | E-GEOD-33252 | biostudies-arrayexpress

Mock microbial community with spike-ins of 13C-labeled Escherichia coli cells for benchmarking of protein-based stable isotope probing proteomics (Protein-SIP)

Project description:This dataset is part of a study aimed at developing algorithms for the quantification of stable isotope content in microorganisms in microbial communities after labeling them with stable isotope-labeled substrates. For this dataset Escherichia coli cultures were labeled with different percentages (1, 5 and 10%) of fully labeled 13C glucose (13C1-6) and spiked-in into a mock microbial community consisting of 32 species of bacteria, archaea, eukaryote and bacteriophages (UNEVEN Community described in Kleiner et al. 2017 Nat Communications 8(1):1558). The community also contained unlabeled E. coli cells and labeled/unlabeled E. coli cells in the spike-in sample were at a 1:1 ratio. Cultures of E. coli were grown in M9 minimal medium in which a percentage of the glucose was replaced with 13C1-6 glucose for >10 generations to achieve close to complete labeling of cells. The following percentages of 13C1-6 glucose were added 1, 5 and 10%. Triplicate cultures were grown for each percentage. Please note that the unlabeled glucose that was used of course had a natural content of 13C of around 1.1%, thus the 0% added label samples have an actual 13C content of 1.1% and all added label is on top of this value. We included a tab delimited table with this submission providing details on all raw files.

2022-12-30 | PXD024174 | Pride

D vulgaris WT-IPFG07 chemostat comparison

Project description:Parallel chemostats of Desulfovibrio vulgaris Hildenborough WT and IPFG07 (DsrC low-expression) mutant were sampled over 5 turnovers at steady-state. Extracted proteins were digested with trypsin and peptides were isotopically labeled for quantification using the diDO-IPTL methodology (Waldbauer et al. 2017 Analytical Chemistry).

2018-11-26 | MSV000083165 | MassIVE

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