Browse
Submit Data
Databases
API
Help

Dataset Information

370 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

MetaProSIP protein-SIP data - MetaProSIP: automated inference of stable isotope incorporation rates in proteins for functional metaproteomics

ABSTRACT: MetaProSIP offers an automated high-throughput solution for 13C or 15N protein-SIP experiments. Labeled peptides are identified based on their unlabeled isotopologues. It calculates incorporation of heavy isotopes (RIA), the labeling ratio (LR) between proteins as well as additional shape properties of the isotopic distribution. FeatureXML files have been created using OpenMS 1.10 using the FeatureFinderCentroided tool. Unlabeled peptides have been identified by OMSSA 2.1.9 (precursor mass tolerance 10 ppm, fragment mass tolerance 0.5 Da, FDR filtering at 2%) and mapped to the feature data using the IDMapper tool.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Uncultured Bacterium

SUBMITTER: Timo Sachsenberg

PROVIDER: PXD000382 | Pride | 2014-11-27

REPOSITORIES: Pride

ACCESS DATA

Json Xml

Publications

MetaProSIP: automated inference of stable isotope incorporation rates in proteins for functional metaproteomics.

Sachsenberg Timo T Herbst Florian-Alexander FA Taubert Martin M Kermer René R Jehmlich Nico N von Bergen Martin M Seifert Jana J Kohlbacher Oliver O

Journal of proteome research 20141201 2

We propose a joint experimental and theoretical approach to the automated reconstruction of elemental fluxes in microbial communities. While stable isotope probing of proteins (protein-SIP) has been successfully applied to study interactions and elemental carbon and nitrogen fluxes, the volume and complexity of mass spectrometric data in protein-SIP experiments pose new challenges for data analysis. Together with a flexible experimental setup, the novel bioinformatics tool MetaProSIP offers an a ...[more]

PMID: 25412983

Similar Datasets

Tracing incorporation of heavy water into proteins for species-specific metabolic activity in complex communities using protein-based stable isotope probing proteomics (Protein-SIP)

Project description:This dataset was obtained from the authors of Starke et al. (2020, Journal of Proteomics 222: 103791, https://doi.org/10.1016/j.jprot.2020.103791). Sample labels: 1 - High fiber diet inoculum 2 - High protein diet inoculum 3,4,5 - High fiber + unlabeled water 6,7,8 - High protein + unlabeled water 9,10,11 - High fiber + 25% of 99.9 atom% D2O 12,13,14 - High protein + 25% of 99.9 atom% D2O 15,16,17 - High fiber + 25% of 99.0 atom% H218O 18,19,20 - High protein + 25% of 99.0 atom% H218O Direct quote from the original article describing the dataset. “…the impact of specific diets on a defined microbial community derived from a human fecal sample was to be determined. The defined community was chosen to provide a stable in vitro setup that could be useful for future microbiome research. Briefly, the microbial community was grown in a heavy fiber and a heavy protein diet in addition to 25% heavy water, either as D2O or H218O. A dosage of 25% isotopically labeled water was chosen by trial-and-error to yield sufficient incorporation into protein but avoid the reduction of activity of individual organisms. A difference in growth medium formulation, representing a high-fiber diet and a high-protein diet, was utilized to evaluate shifts in microbial activity. We chose to assess these diets because high-protein, low-carbohydrate interventions represent a popular weight-loss strategy and because we expected a strong effect on the synthesis of amino acids by this comparison. After an incubation time of 12 h, the proteins were analyzed for label-free quantitation (metaproteomics) and incorporation of isotopes (protein-SIP), each in triplicates….”

2022-12-30 | PXD024291 | Pride

pyQms - partial labeled proteome gold standard

Project description:" The novel mass spectrometry quantitation tool pyQms can calculate isotope patterns for molecules that have any isotope enrichment or combinations of, e.g. 13C or 15N and allows partially labeled molecules to be quantified as well, as observed in pulse or pulse-chase experiments where enrichment levels change dynamically. In order to test how pyQms performs on such a task, we created a gold standard (GS) data set of partially labeled proteomes, which allows evaluation of algorithms detecting partial labeld isotopologues against the ground truth against 5 mixed samples. Cultures of Chlamydomonas reinhardtii were grown on medium containing 20, 40, 60, 80 and 100% 15N. Since partially labeled peptides will not produce interpretable fragmentation spectra, each of the partially labeled proteomes were mixed with an unlabeled (14N) or fully labeled (15N) proteome, yielding 5 mixed samples (0|100, 20|100, 40|100, 0|60 and 0|80). " (Modified from manuscript)

2017-08-10 | PXD003236 | Pride

SIP Identifies a Network of Dosage Compensation Condensin I Loops

Project description:Chromatin loops are a major componant of 3D nuclear organization that appear as intense point-to-point interactions in Hi-C maps. Identification of these loops is an important part of Hi-C analysis. We present SIP, Significant Interaction Peak caller, a platform independent program to identify these loops in a time and memory efficient manner and which is resistant to noise and sequencing depth. We also present a companion tool, SIPMeta, to create more visually accurate average plots of Hi-C and HiChIP data. We then demonstrate that use of SIP and SIPMeta can lead to biological insight through characterizing the contribution of several transcription factors to CTCF loops in human cells. We then use SIP and SIPMeta to discover loops associated with condensin IDCC in C. elegans and confirm these loops by HiChIP. These loops form a network of interactions and likely explain the partial condensation of dosage compensated X chromosomes in hermaphrodites.

2020-02-04 | GSE132640 | GEO

Perinatal paroxetine exposure in Selcetively-bred Low Responder rats

Project description:Selective serotonin reuptake inhibitor (SSRI) antidepressants are the mainstay treatment for the 10-20% of pregnant and postpartum women who suffer major depression, but the effects of SSRIs on their children’s developing brain and later emotional health are poorly understood. SSRI use during pregnancy can elicit antidepressant withdrawal in newborns and increase toddlers’ anxiety and social avoidance. In rodents, perinatal SSRI exposure increases adult depression- and anxiety-like behavior, although certain individuals are more vulnerable to these effects than others. Our study establishes a rodent model of individual differences in susceptibility to perinatal SSRI exposure, utilizing selectively-bred Low Responder (LR) and High Responder (HR) rats that were previously bred for high versus low behavioral response to novelty. Pregnant HR/LR females were chronically treated with the SSRI paroxetine (10 mg/kg/day p.o.) to examine its effects on offspring’s emotional behavior and gene expression in the developing brain. Paroxetine treatment had minimal effect on HR/LR dams’ pregnancy outcomes or maternal behavior. We found that LR offspring, naturally prone to an inhibited/anxious temperament, were susceptible to behavioral abnormalities associated with perinatal SSRI exposure (which exacerbated their Forced Swim Test immobility), while high risk-taking HR offspring were resistant. Microarray studies revealed robust perinatal SSRI-induced gene expression changes in the developing LR hippocampus and amygdala (postnatal days 7-21), including transcripts involved in neurogenesis, synaptic vesicle components, and energy metabolism. These results highlight the LR/HR model as a useful tool to explore the neurobiology of individual differences in susceptibility to perinatal SSRI exposure.

2018-03-03 | GSE111362 | GEO

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

Incorporation of fluoritnated tryptophan into RV1187

Project description:Targeted assays were created to monitor the incorporation of fluorinated tryptophan into Rv1187. Assay development was performed on a mixture of labeled and unlabeled Rv1187.

2021-03-09 | PXD010703 | panorama

Validation of the Global Polypectomy Assessment Tool (GPAT)

Project description:Colorectal polypectomy is offten incompletely performed with high variability between endoscopists, resulting in interval cancer or repeated procedures. Current available scoring systems for polypectomy technique are lacking in different areas so the investigators developed the Global Polypectomy Assessment Tool (GPAT) which is an online video-based assessment tool for any colorectal polypectomy. The goal of the study is to assess the validity of GPAT through demonstrating the inter-rater agreement (Fleiss Kappa (κ)). GPAT has 20 items, contains evidence-based statements to aid interpretation, calculates an overall quality score and a complexity score.

| 61454 | ecrin-mdr-crc

Effect of cellular and viral miRNAs on target RNA half-life in three human B-cell lines

Project description:Total, nascent and unlabeled RNA were prepared following 1h of labeling with 100 µM 4-thiouridine and 3 replicates analyzed by Affymetrix Gene ST 1.0 arrays Transcript half-lives were determined in DG75-eGFP, DG75-10/12 and BCBL-1 based on nascent/total RNA ratios; unlabeled RNA was analyzed in addition

2010-11-04 | E-GEOD-18882 | 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

Transcriptional and Behavioral Responses of Zebrafish Larvae to Microcystin-LR Exposure

Project description:Microcystin-LR (MC-LR), the most toxic member of microcystin family, inhibits protein phosphatase PP2A, triggers oxidative stress and induces hepatotoxicity. Gene expression profiling of MC-LR treated larvae using DNA microarray analysis revealed effects in the retinal visual cycle and pigmentation synthesis pathways that have not been previously associated with MC-LR. Liver-related genes were also differentially expressed. The microarray data were confirmed by quantitative real-time PCR. Our findings provide new evidence that microcystin-LR exposure of zebrafish larvae modulates the retinal visual cycle and pigmentation synthesis pathways and ultimately alter larval zebrafish behavior

2017-02-16 | GSE73739 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data