Differential Phosphoproteomics of Fibroblast Growth Factor Signaling: Identification of Src Family Kinase-Mediated Phosphorylation Events

Activation of signal transduction by the receptor tyrosine kinase, fibroblast growth factor receptor (FGFR), results in a cascade of protein−protein interactions that rely on the occurrence of specific tyrosine phosphorylation events. One such protein recruited to the activated receptor complex is the nonreceptor tyrosine kinase, Src, which is involved in both initiation and termination of further signaling events. To gain a further understanding of the tyrosine phosphorylation events that occur during FGF signaling, with a specific focus on those that are dependent on Src family kinase (SFK) activity, we have applied SILAC combined with chemical inhibition of SFK activity to search for phosphorylation events that are dependent on SFK activity in FGF stimulated cells. In addition, we used a more targeted approach to carry out high coverage phosphopeptide mapping of one Src substrate protein, the multifunctional adaptor Dok1, and to identify SFK-dependent Dok1 binding partners. From these analyses we identify 80 SFK-dependent phosphorylation events on 40 proteins. We further identify 18 SFK-dependent Dok1 interactions and 9 SFK-dependent Dok1 phosphorylation sites, 6 of which had not previously been known to be SFK-dependent

Differential Phosphoproteomics of Fibroblast Growth Factor Signaling: Identification of Src Family Kinase-Mediated Phosphorylation Events

Activation of signal transduction by the receptor tyrosine kinase, fibroblast growth factor receptor (FGFR), results in a cascade of protein−protein interactions that rely on the occurrence of specific tyrosine phosphorylation events. One such protein recruited to the activated receptor complex is the nonreceptor tyrosine kinase, Src, which is involved in both initiation and termination of further signaling events. To gain a further understanding of the tyrosine phosphorylation events that occur during FGF signaling, with a specific focus on those that are dependent on Src family kinase (SFK) activity, we have applied SILAC combined with chemical inhibition of SFK activity to search for phosphorylation events that are dependent on SFK activity in FGF stimulated cells. In addition, we used a more targeted approach to carry out high coverage phosphopeptide mapping of one Src substrate protein, the multifunctional adaptor Dok1, and to identify SFK-dependent Dok1 binding partners. From these analyses we identify 80 SFK-dependent phosphorylation events on 40 proteins. We further identify 18 SFK-dependent Dok1 interactions and 9 SFK-dependent Dok1 phosphorylation sites, 6 of which had not previously been known to be SFK-dependent

Differential Phosphoproteomics of Fibroblast Growth Factor Signaling: Identification of Src Family Kinase-Mediated Phosphorylation Events

Activation of signal transduction by the receptor tyrosine kinase, fibroblast growth factor receptor (FGFR), results in a cascade of protein−protein interactions that rely on the occurrence of specific tyrosine phosphorylation events. One such protein recruited to the activated receptor complex is the nonreceptor tyrosine kinase, Src, which is involved in both initiation and termination of further signaling events. To gain a further understanding of the tyrosine phosphorylation events that occur during FGF signaling, with a specific focus on those that are dependent on Src family kinase (SFK) activity, we have applied SILAC combined with chemical inhibition of SFK activity to search for phosphorylation events that are dependent on SFK activity in FGF stimulated cells. In addition, we used a more targeted approach to carry out high coverage phosphopeptide mapping of one Src substrate protein, the multifunctional adaptor Dok1, and to identify SFK-dependent Dok1 binding partners. From these analyses we identify 80 SFK-dependent phosphorylation events on 40 proteins. We further identify 18 SFK-dependent Dok1 interactions and 9 SFK-dependent Dok1 phosphorylation sites, 6 of which had not previously been known to be SFK-dependent

Differential Phosphoproteomics of Fibroblast Growth Factor Signaling: Identification of Src Family Kinase-Mediated Phosphorylation Events

Activation of signal transduction by the receptor tyrosine kinase, fibroblast growth factor receptor (FGFR), results in a cascade of protein−protein interactions that rely on the occurrence of specific tyrosine phosphorylation events. One such protein recruited to the activated receptor complex is the nonreceptor tyrosine kinase, Src, which is involved in both initiation and termination of further signaling events. To gain a further understanding of the tyrosine phosphorylation events that occur during FGF signaling, with a specific focus on those that are dependent on Src family kinase (SFK) activity, we have applied SILAC combined with chemical inhibition of SFK activity to search for phosphorylation events that are dependent on SFK activity in FGF stimulated cells. In addition, we used a more targeted approach to carry out high coverage phosphopeptide mapping of one Src substrate protein, the multifunctional adaptor Dok1, and to identify SFK-dependent Dok1 binding partners. From these analyses we identify 80 SFK-dependent phosphorylation events on 40 proteins. We further identify 18 SFK-dependent Dok1 interactions and 9 SFK-dependent Dok1 phosphorylation sites, 6 of which had not previously been known to be SFK-dependent

SLoMo: Automated Site Localization of Modifications from ETD/ECD Mass Spectra

Recently, software has become available to automate localization of phosphorylation sites from CID data and to assign associated confidence scores. We present an algorithm, SLoMo (Site Localization of Modifications), which extends this capability to ETD/ECD mass spectra. Furthermore, SLoMo caters for both high and low resolution data and allows for site-localization of any UniMod post-translational modification. SLoMo accepts input data from a variety of formats (e.g., Sequest, OMSSA). We validate SLoMo with high and low resolution ETD, ECD, and CID data

SLoMo: Automated Site Localization of Modifications from ETD/ECD Mass Spectra

Recently, software has become available to automate localization of phosphorylation sites from CID data and to assign associated confidence scores. We present an algorithm, SLoMo (Site Localization of Modifications), which extends this capability to ETD/ECD mass spectra. Furthermore, SLoMo caters for both high and low resolution data and allows for site-localization of any UniMod post-translational modification. SLoMo accepts input data from a variety of formats (e.g., Sequest, OMSSA). We validate SLoMo with high and low resolution ETD, ECD, and CID data

Database Search Strategies for Proteomic Data Sets Generated by Electron Capture Dissociation Mass Spectrometry

Large data sets of electron capture dissociation (ECD) mass spectra from proteomic experiments are rich in information; however, extracting that information in an optimal manner is not straightforward. Protein database search engines currently available are designed for low resolution CID data, from which Fourier transform ion cyclotron resonance (FT-ICR) ECD data differs significantly. ECD mass spectra contain both z-prime and z-dot fragment ions (and c-prime and c-dot); ECD mass spectra contain abundant peaks derived from neutral losses from charge-reduced precursor ions; FT-ICR ECD spectra are acquired with a larger precursor <i>m</i>/<i>z</i> isolation window than their low-resolution CID counterparts. Here, we consider three distinct stages of postacquisition analysis: (1) processing of ECD mass spectra prior to the database search; (2) the database search step itself and (3) postsearch processing of results. We demonstrate that each of these steps has an effect on the number of peptides identified, with the postsearch processing of results having the largest effect. We compare two commonly used search engines: Mascot and OMSSA. Using an ECD data set of modest size (3341 mass spectra) from a complex sample (mouse whole cell lysate), we demonstrate that search results can be improved from 630 identifications (19% identification success rate) to 1643 identifications (49% identification success rate). We focus in particular on improving identification rates for doubly charged precursors, which are typically low for ECD fragmentation. We compare our presearch processing algorithm with a similar algorithm recently developed for electron transfer dissociation (ETD) data

Database Search Strategies for Proteomic Data Sets Generated by Electron Capture Dissociation Mass Spectrometry

Large data sets of electron capture dissociation (ECD) mass spectra from proteomic experiments are rich in information; however, extracting that information in an optimal manner is not straightforward. Protein database search engines currently available are designed for low resolution CID data, from which Fourier transform ion cyclotron resonance (FT-ICR) ECD data differs significantly. ECD mass spectra contain both z-prime and z-dot fragment ions (and c-prime and c-dot); ECD mass spectra contain abundant peaks derived from neutral losses from charge-reduced precursor ions; FT-ICR ECD spectra are acquired with a larger precursor <i>m</i>/<i>z</i> isolation window than their low-resolution CID counterparts. Here, we consider three distinct stages of postacquisition analysis: (1) processing of ECD mass spectra prior to the database search; (2) the database search step itself and (3) postsearch processing of results. We demonstrate that each of these steps has an effect on the number of peptides identified, with the postsearch processing of results having the largest effect. We compare two commonly used search engines: Mascot and OMSSA. Using an ECD data set of modest size (3341 mass spectra) from a complex sample (mouse whole cell lysate), we demonstrate that search results can be improved from 630 identifications (19% identification success rate) to 1643 identifications (49% identification success rate). We focus in particular on improving identification rates for doubly charged precursors, which are typically low for ECD fragmentation. We compare our presearch processing algorithm with a similar algorithm recently developed for electron transfer dissociation (ETD) data

Differential regulation of tyrosine phosphorylation on Eps8.

<p>Heavy, medium and light SILAC labelled HEK 293T cells were treated with either 25 nM dasatinib, 20 µM SU5402, or no inhibitor, prior to FGF2 stimulation (20 ng/ml; 15 min). Myc-Eps8 was immunoprecipitated and the resulting sample was run on an SDS-PAGE gel and, following in-gel trypsin digestion and phophopeptide enrichment, analysed by mass spectrometry. Each graph represents specific residues on Eps8 as indicated. Each data point represents a single peptide identification. <i>P</i> values were calculated by an unpaired t-test (0.01–0.05 =  *; 0.001–0.01 =  **; <0.001 =  ***). +, the median of the ratios isMethod S1). A) Experiment was carried out in the absence of sodium pervanadate. B) Experiment was carried out in the presence of 2 mM sodium pervanvadate.</p

Targeted Online Liquid Chromatography Electron Capture Dissociation Mass Spectrometry for the Localization of Sites of in Vivo Phosphorylation in Human Sprouty2

We demonstrate a strategy employing collision-induced dissociation for phosphopeptide discovery, followed by targeted electron capture dissociation (ECD) for site localization. The high mass accuracy and low background noise of the ECD mass spectra allow facile sequencing of coeluting isobaric phosphopeptides, with up to two isobaric phosphopeptides sequenced from a single mass spectrum. In contrast to the previously described neutral loss dependent ECD method, targeted ECD allows analysis of both phosphotyrosine peptides and lower abundance phosphopeptides. The approach was applied to phosphorylation analysis of human Sprouty2, a regulator of receptor tyrosine kinase signaling. Fifteen sites of phosphorylation were identified, 11 of which are novel