Comparison of Three Quantitative Phosphoproteomic Strategies to Study Receptor Tyrosine Kinase Signaling

There are three quantitative phosphoproteomic strategies most commonly used to study receptor tyrosine kinase (RTK) signaling. These strategies quantify changes in: (1) all three forms of phosphosites (phosphoserine, phosphothreonine and phosphotyrosine) following enrichment of phosphopeptides by titanium dioxide or immobilized metal affinity chromatography; (2) phosphotyrosine sites following anti- phosphotyrosine antibody enrichment of phosphotyrosine peptides; or (3) phosphotyrosine proteins and their binding partners following anti-phosphotyrosine protein immunoprecipitation. However, it is not clear from literature which strategy is more effective. In this study, we assessed the utility of these three phosphoproteomic strategies in RTK signaling studies by using EphB receptor signaling as an example. We used all three strategies with stable isotope labeling with amino acids in cell culture (SILAC) to compare changes in phosphoproteomes upon EphB receptor activation. We used bioinformatic analysis to compare results from the three analyses. Our results show that the three strategies provide complementary information about RTK pathways

In-Depth Quantitative Proteomic Analysis of de Novo Protein Synthesis Induced by Brain-Derived Neurotrophic Factor

Measuring the synthesis of new proteins in the context of a much greater number of pre-existing proteins can be difficult. To overcome this obstacle, bioorthogonal noncanonical amino acid tagging (BONCAT) can be combined with stable isotope labeling by amino acid in cell culture (SILAC) for comparative proteomic analysis of de novo protein synthesis (BONLAC). In the present study, we show that alkyne resin-based isolation of l-azidohomoalanine (AHA)-labeled proteins using azide/alkyne cycloaddition minimizes contamination from pre-existing proteins. Using this approach, we isolated and identified 7414 BONCAT-labeled proteins. The nascent proteome isolated by BONCAT was very similar to the steady-state proteome, although transcription factors were highly enriched by BONCAT. About 30% of the methionine residues were replaced by AHA in our BONCAT samples, which allowed for identification of methionine-containing peptides. There was no bias against low-methionine proteins by BONCAT at the proteome level. When we applied the BONLAC approach to screen for brain-derived neurotrophic factor (BDNF)-induced protein synthesis, 53 proteins were found to be significantly changed 2 h after BDNF stimulation. Our study demonstrated that the newly synthesized proteome, even after a short period of stimulation, can be efficiently isolated by BONCAT and analyzed to a depth that is similar to that of the steady-state proteome

In-Depth Quantitative Proteomic Analysis of de Novo Protein Synthesis Induced by Brain-Derived Neurotrophic Factor

Measuring the synthesis of new proteins in the context of a much greater number of pre-existing proteins can be difficult. To overcome this obstacle, bioorthogonal noncanonical amino acid tagging (BONCAT) can be combined with stable isotope labeling by amino acid in cell culture (SILAC) for comparative proteomic analysis of de novo protein synthesis (BONLAC). In the present study, we show that alkyne resin-based isolation of l-azidohomoalanine (AHA)-labeled proteins using azide/alkyne cycloaddition minimizes contamination from pre-existing proteins. Using this approach, we isolated and identified 7414 BONCAT-labeled proteins. The nascent proteome isolated by BONCAT was very similar to the steady-state proteome, although transcription factors were highly enriched by BONCAT. About 30% of the methionine residues were replaced by AHA in our BONCAT samples, which allowed for identification of methionine-containing peptides. There was no bias against low-methionine proteins by BONCAT at the proteome level. When we applied the BONLAC approach to screen for brain-derived neurotrophic factor (BDNF)-induced protein synthesis, 53 proteins were found to be significantly changed 2 h after BDNF stimulation. Our study demonstrated that the newly synthesized proteome, even after a short period of stimulation, can be efficiently isolated by BONCAT and analyzed to a depth that is similar to that of the steady-state proteome

Deep Coverage of Global Protein Expression and Phosphorylation in Breast Tumor Cell Lines Using TMT 10-plex Isobaric Labeling

Labeling peptides with isobaric tags is a popular strategy in quantitative bottom-up proteomics. In this study, we labeled six breast tumor cell lysates (1.34 mg proteins per channel) using 10-plex tandem mass tag reagents and analyzed the samples on a Q Exactive HF Quadrupole-Orbitrap mass spectrometer. We identified a total of 8,706 proteins and 28,186 phosphopeptides, including 7,394 proteins and 23,739 phosphosites common to all channels. The majority of technical replicates correlated with a <i>R</i>² ≥ 0.98, indicating minimum variability was introduced after labeling. Unsupervised hierarchical clustering of phosphopeptide data sets successfully classified the breast tumor samples into Her2 (epidermal growth factor receptor 2) positive and Her2 negative groups, whereas mRNA abundance did not. The tyrosine phosphorylation levels of receptor tyrosine kinases, phosphoinositide-3-kinase, protein kinase C delta, and Src homology 2, among others, were significantly higher in the Her2 positive than the Her2 negative group. Despite ratio compression in MS2-based experiments, we demonstrated the ratios calculated using an MS2 method are highly correlated (<i>R</i>² > 0.65) with ratios obtained using MS3-based quantitation (using a Thermo Orbitrap Fusion mass spectrometer) with reduced ratio suppression. Given the deep coverage of global and phosphoproteomes, our data show that MS2-based quantitation using TMT can be successfully used for large-scale multiplexed quantitative proteomics

ABRF Proteome Informatics Research Group (iPRG) 2015 Study: Detection of Differentially Abundant Proteins in Label-Free Quantitative LC–MS/MS Experiments

Detection of differentially abundant proteins in label-free quantitative shotgun liquid chromatography–tandem mass spectrometry (LC–MS/MS) experiments requires a series of computational steps that identify and quantify LC–MS features. It also requires statistical analyses that distinguish systematic changes in abundance between conditions from artifacts of biological and technical variation. The 2015 study of the Proteome Informatics Research Group (iPRG) of the Association of Biomolecular Resource Facilities (ABRF) aimed to evaluate the effects of the statistical analysis on the accuracy of the results. The study used LC–tandem mass spectra acquired from a controlled mixture, and made the data available to anonymous volunteer participants. The participants used methods of their choice to detect differentially abundant proteins, estimate the associated fold changes, and characterize the uncertainty of the results. The study found that multiple strategies (including the use of spectral counts versus peak intensities, and various software tools) could lead to accurate results, and that the performance was primarily determined by the analysts’ expertise. This manuscript summarizes the outcome of the study, and provides representative examples of good computational and statistical practice. The data set generated as part of this study is publicly available

Extracellular phosphorylation of a receptor tyrosine kinase controls synaptic localization of NMDA receptors and regulates pathological pain

<div><p>Extracellular phosphorylation of proteins was suggested in the late 1800s when it was demonstrated that casein contains phosphate. More recently, extracellular kinases that phosphorylate extracellular serine, threonine, and tyrosine residues of numerous proteins have been identified. However, the functional significance of extracellular phosphorylation of specific residues in the nervous system is poorly understood. Here we show that synaptic accumulation of GluN2B-containing N-methyl-D-aspartate receptors (NMDARs) and pathological pain are controlled by ephrin-B-induced extracellular phosphorylation of a single tyrosine (p*Y504) in a highly conserved region of the fibronectin type III (FN3) domain of the receptor tyrosine kinase EphB2. Ligand-dependent Y504 phosphorylation modulates the EphB-NMDAR interaction in cortical and spinal cord neurons. Furthermore, Y504 phosphorylation enhances NMDAR localization and injury-induced pain behavior. By mediating inducible extracellular interactions that are capable of modulating animal behavior, extracellular tyrosine phosphorylation of EphBs may represent a previously unknown class of mechanism mediating protein interaction and function.</p></div

ABRF Proteome Informatics Research Group (iPRG) 2015 Study: Detection of Differentially Abundant Proteins in Label-Free Quantitative LC–MS/MS Experiments

Detection of differentially abundant proteins in label-free quantitative shotgun liquid chromatography–tandem mass spectrometry (LC–MS/MS) experiments requires a series of computational steps that identify and quantify LC–MS features. It also requires statistical analyses that distinguish systematic changes in abundance between conditions from artifacts of biological and technical variation. The 2015 study of the Proteome Informatics Research Group (iPRG) of the Association of Biomolecular Resource Facilities (ABRF) aimed to evaluate the effects of the statistical analysis on the accuracy of the results. The study used LC–tandem mass spectra acquired from a controlled mixture, and made the data available to anonymous volunteer participants. The participants used methods of their choice to detect differentially abundant proteins, estimate the associated fold changes, and characterize the uncertainty of the results. The study found that multiple strategies (including the use of spectral counts versus peak intensities, and various software tools) could lead to accurate results, and that the performance was primarily determined by the analysts’ expertise. This manuscript summarizes the outcome of the study, and provides representative examples of good computational and statistical practice. The data set generated as part of this study is publicly available

ABRF Proteome Informatics Research Group (iPRG) 2015 Study: Detection of Differentially Abundant Proteins in Label-Free Quantitative LC–MS/MS Experiments

Detection of differentially abundant proteins in label-free quantitative shotgun liquid chromatography–tandem mass spectrometry (LC–MS/MS) experiments requires a series of computational steps that identify and quantify LC–MS features. It also requires statistical analyses that distinguish systematic changes in abundance between conditions from artifacts of biological and technical variation. The 2015 study of the Proteome Informatics Research Group (iPRG) of the Association of Biomolecular Resource Facilities (ABRF) aimed to evaluate the effects of the statistical analysis on the accuracy of the results. The study used LC–tandem mass spectra acquired from a controlled mixture, and made the data available to anonymous volunteer participants. The participants used methods of their choice to detect differentially abundant proteins, estimate the associated fold changes, and characterize the uncertainty of the results. The study found that multiple strategies (including the use of spectral counts versus peak intensities, and various software tools) could lead to accurate results, and that the performance was primarily determined by the analysts’ expertise. This manuscript summarizes the outcome of the study, and provides representative examples of good computational and statistical practice. The data set generated as part of this study is publicly available

ABRF Proteome Informatics Research Group (iPRG) 2015 Study: Detection of Differentially Abundant Proteins in Label-Free Quantitative LC–MS/MS Experiments

Detection of differentially abundant proteins in label-free quantitative shotgun liquid chromatography–tandem mass spectrometry (LC–MS/MS) experiments requires a series of computational steps that identify and quantify LC–MS features. It also requires statistical analyses that distinguish systematic changes in abundance between conditions from artifacts of biological and technical variation. The 2015 study of the Proteome Informatics Research Group (iPRG) of the Association of Biomolecular Resource Facilities (ABRF) aimed to evaluate the effects of the statistical analysis on the accuracy of the results. The study used LC–tandem mass spectra acquired from a controlled mixture, and made the data available to anonymous volunteer participants. The participants used methods of their choice to detect differentially abundant proteins, estimate the associated fold changes, and characterize the uncertainty of the results. The study found that multiple strategies (including the use of spectral counts versus peak intensities, and various software tools) could lead to accurate results, and that the performance was primarily determined by the analysts’ expertise. This manuscript summarizes the outcome of the study, and provides representative examples of good computational and statistical practice. The data set generated as part of this study is publicly available

Extracellular phosphorylation is induced by ephrin-B2 and mediates the EphB—N-methyl-D-aspartate receptor (NMDAR) interaction.

<p>(A) Untransfected cultured rat cortical neurons (day in vitro [DIV] 6–7) were treated with ephrin-B2 (+) or control reagents (-) for 45–60 minutes and either control (C) or K252b. Endogenous EphB2 was immunoprecipitated using α-EphB2 antibodies, and blots (listed top to bottom) were probed for GluN1, EphB2, EphB2 p*Y504, EphB2 p*Y662, and tubulin. Panels on the left show IP samples and right panels show lysates. (B–C) Quantification of the effects of ephrin-B2 treatment after blockade of extracellular kinase activity with K252b on the phosphorylation of Y504 (B) and the EphB—NMDAR interaction (C) in neurons (**<i>p <</i> 0.01, ****<i>p <</i> 0.001, ANOVA followed by Fisher’s exact test; <i>n</i> = 5 experiments for each condition). (D) Untransfected cultured rat spinal cord neurons (DIV 12–14) were treated with ephrin-B2 (+) or control reagents (-) for 45–60 minutes and either control (C) or K252b. Endogenous EphB2 was immunoprecipitated using α-EphB2 antibodies and blots (listed top to bottom) were probed for GluN1, EphB2, EphB2 p*Y504, EphB2 p*Y662, and tubulin. (E–F) Quantification of the effects of ephrin-B2 treatment after blockade of extracellular kinase activity with K252b (****<i>p <</i> 0.001, ANOVA followed by Fisher’s exact test; <i>n</i> = 5 experiments for each condition).</p