Description
Building an integrated view of cellular responses to environmental cues remains a fundamental challenge due to the complexity of intracellular networks in mammalian cells. Here we introduce an integrative biochemical and genetic framework to dissect signal transduction events using multiple data types, and in particular, to unify signaling and transcriptional networks. Using the Toll-like receptor (TLR) system as a model cellular response, we generate comprehensive datasets of physical, enzymatic, and functional interactions, and integrate these data to reveal biochemical paths that connect TLR4 signaling to transcription. We define the roles of proximal TLR4 kinases, identify and functionally test two dozen candidate regulators, and demonstrate a role for Ap1ar (encoding the Gadkin protein) and its binding partner Picalm, potentially linking vesicle transport with pro-inflammatory responses. Our study thus demonstrates how deciphering dynamic cellular responses by integrating datasets on various regulatory layers defines key components and higher-order logic underlying signaling-to-transcription pathways.
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: SILAC
Contact
Principal Investigators:
(in alphabetical order)
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Steven A. Carr, Broad Institute of MIT and Harvard, United States
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Submitting User: |
clauser
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Number of distinct conditions across all analyses (original submission and reanalyses)
associated with this dataset.
Distinct condition labels are counted across all files submitted in the "Metadata" category
having a "Condition" column in this dataset.
"N/A" means no results of this type were submitted.
Number of distinct biological replicates across all analyses (original submission and reanalyses)
associated with this dataset.
Distinct replicate labels are counted across all files submitted in the "Metadata" category
having a "BioReplicate" or "Replicate" column in this dataset.
"N/A" means no results of this type were submitted.
Number of distinct technical replicates across all analyses (original submission and reanalyses)
associated with this dataset.
The technical replicate count is defined as the maximum number of times any one distinct
combination of condition and biological replicate was analyzed across all files submitted in the
"Metadata" category. In the case of fractionated experiments, only the first fraction is
considered.
"N/A" means no results of this type were submitted.
Originally identified proteins that were automatically
remapped by MassIVE to proteins in the
SwissProt
human reference database.
"N/A" means no results of this type were submitted.
Number of distinct protein accessions reported across all analyses (original submission and
reanalyses) associated with this dataset.
"N/A" means no results of this type were submitted.
Number of distinct unmodified peptide sequences reported across all analyses (original
submission and reanalyses) associated with this dataset.
"N/A" means no results of this type were submitted.
Number of distinct peptide sequences (including modified variants or peptidoforms) reported
across all analyses (original submission and reanalyses) associated with this dataset.
"N/A" means no results of this type were submitted.
Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all
analyses (original submission and reanalyses) associated with this dataset.
"N/A" means no results of this type were submitted.
Number of distinct proteins quantified across all analyses (original submission and reanalyses)
associated with this dataset.
Distinct protein accessions are counted across all files submitted in the "Statistical Analysis
of Quantified Analytes" category having a "Protein" column in this dataset.
"N/A" means no results of this type were submitted.
Number of distinct proteins found to be differentially abundant in at least one comparison
across all analyses (original submission and reanalyses) associated with this dataset.
A protein is differentially abundant if its change in abundance across conditions is found
to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated
with statistical tests for differential abundance.
Distinct protein accessions are counted across all files submitted in the "Statistical Analysis
of Quantified Analytes" category having a "Protein" column in this dataset.
"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE.
It has been imported to MassIVE for reanalysis purposes, so its spectra data here may
consist solely of processed peak lists suitable for reanalysis with most software.