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An Approach to Spatiotemporally Resolve Protein Interaction Networks in Living Cells.

ABSTRACT: Cells operate through protein interaction networks organized in space and time. Here, we describe an approach to resolve both dimensions simultaneously by using proximity labeling mediated by engineered ascorbic acid peroxidase (APEX). APEX has been used to capture entire organelle proteomes with high temporal resolution, but its breadth of labeling is generally thought to preclude the higher spatial resolution necessary to interrogate specific protein networks. We provide a solution to this problem by combining quantitative proteomics with a system of spatial references. As proof of principle, we apply this approach to interrogate proteins engaged by G-protein-coupled receptors as they dynamically signal and traffic in response to ligand-induced activation. The method resolves known binding partners, as well as previously unidentified network components. Validating its utility as a discovery pipeline, we establish that two of these proteins promote ubiquitin-linked receptor downregulation after prolonged activation.

SUBMITTER: Lobingier BT

PROVIDER: S-EPMC5616215 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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An Approach to Spatiotemporally Resolve Protein Interaction Networks in Living Cells.

Lobingier Braden T BT Hüttenhain Ruth R Eichel Kelsie K Miller Kenneth B KB Ting Alice Y AY von Zastrow Mark M Krogan Nevan J NJ

Cell 20170401 2

Cells operate through protein interaction networks organized in space and time. Here, we describe an approach to resolve both dimensions simultaneously by using proximity labeling mediated by engineered ascorbic acid peroxidase (APEX). APEX has been used to capture entire organelle proteomes with high temporal resolution, but its breadth of labeling is generally thought to preclude the higher spatial resolution necessary to interrogate specific protein networks. We provide a solution to this pro ...[more]

PMID: 28388416

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Project description:SRM assays were generated for selected interactors of B2AR and DOR(MSV000084857), as well as for localization controls and ribosomal proteins (RPL18A, RPL28, RPL3, RPL35A, RPL6) as internal controls for normalization (Table S5 in publication). SRM assay generation was performed using Skyline. For all targeted proteins, proteotypic peptides and optimal transitions for identification and quantification were selected based on a spectral library generated from the shotgun MS experiments. The Skyline spectral library was used to extract optimal coordinates for the SRM assays, e.g., peptide fragments and peptide retention times. For each protein 1-4 peptides were selected based on intensity, peptide length as well as chromatographic performance. For each peptide the 4 best SRM transitions were selected based on intensity and peak shape. Digested peptide mixtures were analyzed by LC-SRM on a Thermo Scientific TSQ Quantiva MS system equipped with a Proxeon Easy nLC 1200 ultra high-pressure liquid chromatography and autosampler system. Samples were injected onto a C18 column (25 cm x 75 mm I.D. packed with ReproSil Pur C18 AQ 1.9 mm particles) in 0.1% formic acid and then separated with an 80 min gradient from 5% to 40% Buffer B (90% ACN/10% water/0.1% formic acid) at a flow rate of 300 nl/min. SRM acquisition was performed operating Q1 and Q3 at 0.7 unit mass resolution. For each peptide the best 4 transitions were monitored in a scheduled fashion with a retention time window of 4 min and a cycle time fixed to 2s. Argon was used as the collision gas at a nominal pressure of 1.5 mTorr. Collision energies were calculated by, CE = 0.0348 * (m/z) + 0.4551 and CE = 0.0271 * (m/z) + 1.5910 (CE, collision en- ergy and m/z, mass to charge ratio) for doubly and triply charged precursor ions, respectively. RF lens voltages were calculated by, RF= 0.1088 * (m/z) + 21.029 and RF= 0.1157 * (m/z) + 0.1157 (RF, RF lens voltage andm/z, mass to charge ratio) for doubly and triply charged precursor ions, respectively. SRM data were processed using Skyline. Protein significance analysis for the different time points was performed using MSstats. Normalization across samples was conducted based on selected global standard proteins (RPL18A, RPL28, RPL3, RPL35A, RPL6). Each protein was tested for abundance differences comparing DOR-APEX2 time points to the spatial references, PM-APEX2 and ENDO-APEX2. Proteins with an adjusted p-value < 0.05 were considered significant.

Project description:SRM assays were generated for selected interactors of B2AR and DOR (MSV000084857), as well as for localization controls and ribosomal proteins (RPL18A, RPL28, RPL3, RPL35A, RPL6) as internal controls for normalization (Table S5 in publication). We selected localization markers for different cellular compartments and monitored them across the time points for B2AR and the spatial references (ENDO, CYTO, PM). The main goal of this experiment was to demonstrate that we can use the proximity labeling data to determine the localization of the receptor over the time course after receptor activation. SRM assay generation was performed using Skyline. For all targeted proteins, proteotypic peptides and optimal transitions for identification and quantification were selected based on a spectral library generated from the shotgun MS experiments. The Skyline spectral library was used to extract optimal coordinates for the SRM assays, e.g., peptide fragments and peptide retention times. For each protein 1-4 peptides were selected based on intensity, peptide length as well as chromatographic performance. For each peptide the 4 best SRM transitions were selected based on intensity and peak shape. Digested peptide mixtures were analyzed by LC-SRM on a Thermo Scientific TSQ Quantiva MS system equipped with a Proxeon Easy nLC 1200 ultra high-pressure liquid chromatography and autosampler system. Samples were injected onto a C18 column (25 cm x 75 mm I.D. packed with ReproSil Pur C18 AQ 1.9 mm particles) in 0.1% formic acid and then separated with an 80 min gradient from 5% to 40% Buffer B (90% ACN/10% water/0.1% formic acid) at a flow rate of 300 nl/min. SRM acquisition was performed operating Q1 and Q3 at 0.7 unit mass resolution. For each peptide the best 4 transitions were monitored in a scheduled fashion with a retention time window of 4 min and a cycle time fixed to 2s. Argon was used as the collision gas at a nominal pressure of 1.5 mTorr. Collision energies were calculated by, CE = 0.0348 * (m/z) + 0.4551 and CE = 0.0271 * (m/z) + 1.5910 (CE, collision energy and m/z, mass to charge ratio) for doubly and triply charged precursor ions, respectively. RF lens voltages were calculated by, RF= 0.1088 * (m/z) + 21.029 and RF= 0.1157 * (m/z) + 0.1157 (RF, RF lens voltage and m/z, mass to charge ratio) for doubly and triply charged precursor ions, respectively. SRM data were processed using Skyline. Protein significance analysis was performed using MSstats. Normalization across samples was conducted based on selected global standard proteins (RPL18A, RPL28, RPL3, RPL35A, RPL6). Each protein was tested for abundance differences comparing DOR-APEX2 time points to the spatial references, PM-APEX2 and ENDO-APEX2. Proteins with an adjusted p-value < 0.05 were considered significant.

Dataset Information

An Approach to Spatiotemporally Resolve Protein Interaction Networks in Living Cells.

Publications

An Approach to Spatiotemporally Resolve Protein Interaction Networks in Living Cells.

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