Cedars-Sinai Van Eyk Lab - PINE

Cedars-Sinai Van Eyk Lab - PINE
PINE: An Automation Tool to Extract & Visualize Functionally Enriched Networks from Mass Spectrometry-Based Proteomics Datasets
Data License: CC BY 4.0 | ProteomeXchange: PXD017324
  • Organism: Mus musculus
  • Instrument: Orbitrap Fusion Lumos
  • SpikeIn: No
  • Keywords: Proteomics, data visualization, enriched networks, automated bioinformatics tool, post-translational modifications
  • Lab head: Jennifer Van Eyk Submitter: Vidya Venkatraman
Abstract
Recent surges in mass spectrometry-based proteomics studies demands a concurrent rise in speedy and optimized data processing tools and pipelines. While several stand-alone databases exist that store gene interaction and annotation information, we developed Protein Interaction Network Extractor (PINE) as a fully-automated, user-friendly, graphical interface-based bioinformatics tool that has an easily adoptable framework suitable for study of all proteins and post-translational modifications (PTMs) sites enabling simple, quick and robust visualization of differentially expressed proteins or PTMs and their interaction or functionally enriched networks. PINE tool can be applied not only to better understand protein functional interaction networks but also to analyze PTMs involved and their effect. To illustrate the relevance of the tool, we explore the total proteome and its PTM -associated relationships in two different nonalcoholic steatohepatitis (NASH) mouse models to show different context-specific use cases. The strength of this tool relies in its ability to (1) perform accurate protein identifier mapping to resolve any ambiguity, (2) retrieve interaction data from multiple publicly available protein-protein interaction databases, (3) assimilate these complex networks into meaningful functionally enriched pathways. Ultimately this tool can be used as an extremely powerful approach for novel hypothesis generation towards understanding disease mechanisms and potential therapeutics.
Experiment Description
Titanium Dioxide (TiO2) phospho enrichment was performed as previously described [43]. Briefly, 400ug of sample were digested as described above and individually de‐salted on Oasis HLB cartridges (Water, 10 mg) and eluted in 300 μL of 80% ACN, 5% TFA, 1 m glycolic acid. Each sample was then incubated in 50 μL titanium dioxide (TiO2) slurry (30 mg/mL, Glygen Corp, Columbia, MD) at room temperature on a shaker overnight. Then the TiO2 beads were washed twice with 200 μL of 80% ACN, 5% TFA, once with 200 μL of 80% ACN, 0.1% TFA, and eluted in 180 μL of 30% ACN/ 1% NH4OH and neutralized with 200 μL of 10% FA. Samples were then desalted on Oasis HLB μ‐elution plates (Waters) and eluted in 80% ACN, 0.1% FA, dried in speedvac, then resuspended in 0.1% FA for LC–MS/MS analysis. MS data were acquired on Orbitrap Fusion Lumos (Thermo) mass spectrometer connected to an Ultimate 3000 nano LC system (Thermo Scientific) with a 60-minute gradient operating in DDA‐MS mode as described in Robinson et al. 2019. DDA files were converted to mzXML and searched through the Trans Proteomic Pipeline (TPP) using 3 algorithms, (1) Comet [49], (2) X!tandem! Native scoring [50] and (3) X!tandem! K‐scoring [51] against a reviewed, mouse canonical protein sequence database, downloaded from the Uniprot database on January 24th, 2019, containing 17,002 target proteins and 17,002 randomized decoy proteins. Target-decoy modeling of peptide spectral matches was performed with peptide prophet [52] and peptides with a probability score of > 95% from the entire experimental dataset were imported into Skyline software [53] for quantification of precursor extracted ion intensities (XICs). Precursor XICs from each experimental file were extracted against the Skyline library, and peptide XICs with isotope dot product scores>0.8 were filtered for final statistical analysis of proteomic differences [54]. Raw peptide intensities were used to calculate pairwise comparisons between experimental groups using the linear mixed effects model built into the open sources MSSTATs (v3.2.2) software suite [55]. Peptide abundance differences with a nominal p-value < 0.05 were considered significantly different.
Sample Description
Livers were obtained from three-month old Gnmt -/- mice in a C57Bl/6 background with hepatic lipid accumulation with age matched WT littermates. Frozen mouse livers were ground while frozen in a liquid N2 cooled cryohomoginizer (Retsch). Samples were denatured in 8M urea and 100mM TRIS-HCL, pH 8.0 and ultrasonicated (QSonica) at 4 ºC for 10 min in 10 second repeating on/off intervals of 10 seconds and centrifuged at 16,000 x g for 10min at 4 ºC. The soluble fraction was reduced with DTT (15mM) for 1h at 37 ºC, alkylated with iodoacetamide (30mM) for 30min at room temperature in the dark, diluted to a final concentration of 2M Urea with 100mM TRIS-HCL, pH 8.0 and digested for 16 hours on a shaker at 37 ºC with a 1:40 ratio of Trypsin/Lys-C mix (Promega). Each sample was de-salted using HLB plates (Oasis HLB 30µm, 5mg sorbent, Waters).Titanium Dioxide (TiO2) phospho enrichment was performed as previously described [43]. Briefly, 400ug of sample were digested as described above and individually de‐salted on Oasis HLB cartridges (Water, 10 mg) and eluted in 300 μL of 80% ACN, 5% TFA, 1 m glycolic acid. Each sample was then incubated in 50 μL titanium dioxide (TiO2) slurry (30 mg/mL, Glygen Corp, Columbia, MD) at room temperature on a shaker overnight. Then the TiO2 beads were washed twice with 200 μL of 80% ACN, 5% TFA, once with 200 μL of 80% ACN, 0.1% TFA, and eluted in 180 μL of 30% ACN/ 1% NH4OH and neutralized with 200 μL of 10% FA. Samples were then desalted on Oasis HLB μ‐elution plates (Waters) and eluted in 80% ACN, 0.1% FA, dried in speedvac, then resuspended in 0.1% FA for LC–MS/MS analysis.
Created on 1/29/20, 2:08 PM
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