This work was supported by a Grand Challenge grant to W.M.O. from the Linda Crnic Institute for Down syndrome and by a DARPA cooperative agreement 13-34-RTA-FP-007. We would like to thank Jesse Kurland and Kira Cozzolino for their contributions in reading and commenting on the manuscript.

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The authors have nothing to disclose.

The proteomics workflow outlined here provides an effective method for identifying high-confidence protein interactors for a protein of interest. This approach decreases the sample complexity through subcellular fraction and focuses on increasing the identification interaction partners through robust sample preparation, offline sample clean up, and stringent quality control of the LC-MS system. The downstream data analysis described here allows for a simple statistical evaluation of the proteins identified as copurifying with the bait. However, due to a high number of experimental variables (scale, cell line, antibody choice), each experiment requires different cutoffs and considerations regarding data visualization and enrichment.
The first design consideration in an IP-MS experiment is the selection of antibodies that will be used for copurification of the protein of interest along with its interacting partners. While the availability of commercial antibodies has expanded to cover larger portions of the human proteome over the past several decades, there are still many proteins for which reagents are limited. Furthermore, antibodies that have been validated for applications such as western blot detection may be incapable of selective enrichment of the target protein in an immunoprecipitation experiment. Prior to conducting a large-scale interaction proteomics experiment, it is suggested to complete an IP from a 90% confluent 10 cm dish, or equivalent cell number, and probe for the target protein of interest by western blotting. If more than a single antibody is available for immunoprecipitation, it is additionally suggested to select multiple antibodies recognizing epitopes within different portions of the protein. The binding of an antibody to a bait protein can occlude the necessary binding interface for putative interacting partners. Selection of a secondary epitope for the bait protein will increase the coverage of the interaction profile identified by a mass spectrometry-based experiment.
A second major consideration lies in the selection of the appropriate control for distinguishing high-confidence interactions from low-confidence or nonspecific interactions from those identified as copurifying with the bait. The most stringent control for an IP-MS experiment is to complete the immunoprecipitation from a CRISPR KO cell line of the bait. Such a control enables identification and filtering out of nonspecific proteins that bind directly to the antibody rather than the bait protein. In cases where generating a CRISPR KO cell line of each bait protein is not feasible, an IgG-bead control of the same isotype of the bait antibody can be used. In experiments employing a panel of antibodies representing multiple species, the use of a beads only control can be appropriate but will increase the rate of false positives identified as high-confidence interactors.
Selection of the cell line used in an IP-MS experiment is dependent on several key factors. Protein expression and localization are largely dependent on cell type. While RNA expression estimates can be found for most genes in many commonly used cell lines, protein expression is poorly correlated with RNA expression and must be determined experimentally25. Cell lines in which a bait protein is expressed in very low copy number should be avoided to circumvent problems associated with drastic increases in cell culture scale that may be required. It should be noted, however, that sample preparation can be optimized for the detection of very low abundance proteins. The filter aided sample prep (FASP) method, while robust, can cause a more than 50% loss of peptide in a sample. The Single-Pot Solid-Phase-enhanced Sample Preparation (SP3) is an efficient method of generating samples for mass spectrometry analysis that minimizes sample loss26. The increased recovery enabled by the SP3 method of sample preparation can be a useful alternative in this workflow for quantification of proteins that fall near the limit of detection.
This proteomics workflow has been applied across many nuclear baits, including kinases, E3 ubiquitin ligases, and scaffolding members of multisubunit complexes. Assuming proper validation of antibody reagents, successful execution of this workflow will result in detection of high-confidence protein nuclear interaction partners for a protein of interest.

The human proteome exhibits vast structural and biochemical diversity through the formation of stable multisubunit complexes and transient protein-protein interactions. Accordingly, the identification of interaction partners for a protein of interest is commonly required in investigations to unravel molecular mechanism. Recent advances in affinity purification protocols and the advent of high-resolution fast-scanning mass spectrometry instrumentation have enabled easy mapping of protein interaction landscapes in a single unbiased experiment.
Protein interaction protocols commonly employ ectopic expression systems with affinity-tagged fusion constructs to identify protein interactions without requiring high-quality antibodies recognizing a protein of interest1,2. However, epitope tag-based methods have several drawbacks. Physical interactions with the epitope may lead to the detection of nonspecific copurifying proteins3. Additionally, fusion of these epitope tags to the N- or C-terminal of a protein may block native protein-protein interactions, or disrupt protein folding to promote non-physiological conformations4. Furthermore, ectopic expression systems typically overexpress the bait protein at supraphysiological concentrations, which can result in the identification of artifactual protein interactions, particularly for dosage-sensitive genes5. To circumvent these issues, the endogenous bait protein can be immunoprecipitated along with associated interacting prey proteins, assuming availability of a high-quality antibody that recognizes the native protein.
Provided here is an interaction proteomics workflow for detecting the nuclear interactome of an endogenous protein using the CMGC protein kinase DYRK1A as an example. Disruption of DYRK1A copy number, activity level, or expression can cause severe intellectual disability in humans, and embryonic lethality in mice6,7,8,9. DYRK1A exhibits dynamic spatiotemporal regulation10, and compartmentalized protein interactions11,12, requiring approaches capable of detecting low abundance interaction partners specific to different subcellular compartments.
This protocol employs cellular fractionation of human HeLa cells into cytosol and nucleoplasm fractions, immunoprecipitation, sample preparation for mass spectrometry, and an overview of a bioinformatic pipeline for evaluating data quality and visualizing results, with R scripts provided for analysis and visualization (Figure 1). Proteomics software packages used in this workflow are all freely available for download or can be accessed through a web interface. For additional information on software and computational methods, in-depth tutorials and instruction are available at the links provided.

<table><tbody><tr><td>0.25% Trypsin, 0.1% EDTA</td><td>Thermo Fisher Scientific</td><td>25200056</td><td></td></tr><tr><td>1.5 ml low-rention microcentrifuge tubes</td><td>Fisher Scientific</td><td>02-681-320</td><td></td></tr><tr><td>4-20% Mini PROTEAN TGX Precast Protein Gels</td><td>Bio-Rad</td><td>4561096</td><td></td></tr><tr><td>acetone (HPLC)</td><td>Thermo Fisher Scientific</td><td>A949SK-4</td><td></td></tr><tr><td>Amicon Ultra 0.5 ml 30k filter column</td><td>Millipore Sigma</td><td>UFC503096</td><td></td></tr><tr><td>Benzamidine</td><td>Sigma-Aldrich</td><td>12072</td><td></td></tr><tr><td>benzonase</td><td>Sigma-Aldrich</td><td>E1014</td><td></td></tr><tr><td>Chloroacetamide</td><td>Sigma-Aldrich</td><td>C0267</td><td></td></tr><tr><td>Dialysis tubing closure</td><td>Caroline Biological Supply Company</td><td>684239</td><td></td></tr><tr><td>DTT</td><td>Sigma-Aldrich</td><td>10197777001</td><td></td></tr><tr><td>EDTA</td><td>Sigma-Aldrich</td><td>EDS</td><td></td></tr><tr><td>GAPDH antibody</td><td>Santa Cruz Biotechnology</td><td>Sc-47724</td><td></td></tr><tr><td>Glycerol</td><td>Fisher Scientific</td><td>887845</td><td></td></tr><tr><td>Glycine</td><td>Sigma-Aldrich</td><td>G8898</td><td></td></tr><tr><td>HeLa QC tryptic digest</td><td>Pierce</td><td>88329</td><td></td></tr><tr><td>HEPES</td><td>Fisher Scientific</td><td>AAJ1692630</td><td></td></tr><tr><td>insulin</td><td>Thermo Fisher Scientific</td><td>12585014</td><td></td></tr><tr><td>iodoacetamide</td><td>Sigma-Aldrich</td><td>I1149</td><td></td></tr><tr><td>KONTES Dounce homogenizer 7 ml</td><td>VWR</td><td>KT885300-0007</td><td></td></tr><tr><td>Large Clearance pestle 7ml</td><td>VWR</td><td>KT885301-0007</td><td></td></tr><tr><td>Lysyl endopeptidase C</td><td>VWR</td><td>125-05061</td><td></td></tr><tr><td>Magnesium Chloride</td><td>Sigma-Aldrich</td><td>208337</td><td></td></tr><tr><td>Microcystin</td><td>enzo life sciences</td><td>ALX-350-012-C100</td><td></td></tr><tr><td>Nonidet P 40 Substitute solution</td><td>Sigma-Aldrich</td><td>98379</td><td></td></tr><tr><td>p84 antibody</td><td>GeneTex</td><td>GTX70220</td><td></td></tr><tr><td>Phosphate Buffered Saline</td><td></td><td></td><td></td></tr><tr><td>Pierce BCA Protein Assay Kit</td><td>Thermo Fisher Scientific</td><td>23227</td><td></td></tr><tr><td>Pierce BSA Protein Digest, MS grade</td><td>Thermo Fisher Scientific</td><td>88341</td><td>LCMS QC</td></tr><tr><td>Pierce C18 spin columns</td><td>Thermo Fisher Scientific</td><td>PI-89873</td><td></td></tr><tr><td>Pierce Trypsin Protease, MS Grade</td><td>Thermo Fisher Scientific</td><td>90057</td><td>For mass spectrometry sample prep</td></tr><tr><td>PMSF</td><td>Sigma-Aldrich</td><td>P7626</td><td></td></tr><tr><td>Potassium Chloride</td><td>Sigma-Aldrich</td><td>P9541</td><td></td></tr><tr><td>Protein A Sepharose CL-4B</td><td>GE Healthcare Bio-Sciences</td><td>17-0780-01</td><td></td></tr><tr><td>Protein G Sepharose 4 Fast Flow</td><td>GE Healthcare Bio-Sciences</td><td>17-0618-01</td><td></td></tr><tr><td>SDS</td><td>Sigma-Aldrich</td><td>L3771</td><td></td></tr><tr><td>Silica emitter tip</td><td>Pico TIP</td><td>FS360-20-10</td><td></td></tr><tr><td>Small Clearance pestle 7ml</td><td>VWR</td><td>KT885302-0007</td><td></td></tr><tr><td>Sodium Chloride</td><td>Sigma-Aldrich</td><td>S3014</td><td></td></tr><tr><td>Sodium Fluoride</td><td>Sigma-Aldrich</td><td>201154</td><td></td></tr><tr><td>Sodium metabisulfite</td><td>Sigma-Aldrich</td><td>31448</td><td></td></tr><tr><td>Sodium orthovanadate</td><td>Sigma-Aldrich</td><td>S6508</td><td></td></tr><tr><td>Spectra/ Por 8 kDa 24 mm dialysis tubing</td><td>Thomas Scientific</td><td>3787K17</td><td></td></tr><tr><td>TC Dish 150, Standard</td><td>Sarstedt</td><td>83.3903</td><td>Tissue culture dish for adherent cells</td></tr><tr><td>TCA</td><td>Sigma-Aldrich</td><td>T9159</td><td></td></tr><tr><td>TCEP</td><td>Thermo Scientific</td><td>PG82080</td><td></td></tr><tr><td>TFA</td><td>Thermo Fisher Scientific</td><td>28904</td><td></td></tr><tr><td>Thermo Scientific Orbitrap Fusion MS</td><td>Thermo Fisher Scientific</td><td></td><td></td></tr><tr><td>Trizma Base</td><td>Sigma-Aldrich</td><td>T6066</td><td></td></tr><tr><td>Urea</td><td>Thermo Fisher Scientific</td><td>29700</td><td></td></tr><tr><td>Waters ACQUITY M-Class UPLC</td><td>Waters</td><td></td><td></td></tr><tr><td>Waters ACQUITY UPLC M-Class Column Reversed-Phase 1.7&amp;micro;m Spherical Hybrid (1.7 &amp;micro;m, 75 &amp;micro;m x 250 mm)</td><td>Waters</td><td>186007484</td><td>nanoflow C18 column</td></tr></tbody></table>

label-free immunoprecipitation mass spectrometry workflow for large-scale nuclear interactome profiling

Immunoaffinity purification mass spectrometry (IP-MS) has emerged as a robust quantitative method of identifying protein-protein interactions. This publication presents a complete interaction proteomics workflow designed for identifying low abundance protein-protein interactions from the nucleus that could also be applied to other subcellular compartments. This workflow includes subcellular fractionation, immunoprecipitation, sample preparation, offline cleanup, single-shot label-free mass spectrometry, and downstream computational analysis and data visualization. Our protocol is optimized for detecting compartmentalized, low abundance interactions that are difficult to identify from whole cell lysates (e.g., transcription factor interactions in the nucleus) by immunoprecipitation of endogenous proteins from fractionated subcellular compartments. The sample preparation pipeline outlined here provides detailed instructions for the preparation of HeLa cell nuclear extract, immunoaffinity purification of endogenous bait protein, and quantitative mass spectrometry analysis. We also discuss methodological considerations for performing large-scale immunoprecipitation in mass spectrometry-based interaction profiling experiments and provide guidelines for evaluating data quality to distinguish true positive protein interactions from nonspecific interactions. This approach is demonstrated here by investigating the nuclear interactome of the CMGC kinase, DYRK1A, a low abundance protein kinase with poorly defined interactions within the nucleus.

The majority of protein mass identified in an IP-MS experiment consists of nonspecific proteins. Thus, one of the key challenges of an IP-MS experiment is the interpretation of which proteins are high-confidence interactors vs. nonspecific interactors. To demonstrate the crucial parameters used in the evaluation of data quality the study analyzed triplicate immunoprecipitations from 5 mg of HeLa nuclear extract utilizing a bead only control. The first internal check to ensure that an IP-MS experiment is reliable is whether the bait protein ranks as one of the highest enriched proteins identified by both fold-change over control and SAINT probability. In this case, the bait DYRK1A ranked among the top three enriched proteins over the control (Figure 2A,B). In a nuclear interactome study of DYRK1A utilizing four independent antibodies, an FC-A cutoff of &gt;3.00 and SAINT probability cutoff &gt;0.7 provided a stringent cutoff for identification of both novel and previously validated interactors22. When applied to this experiment, a clear separation could be seen between the high-confidence interactors and &gt;95% of copurified proteins identified as nonspecific (Figure 2A,B). Applying both a fold change enrichment and probability threshold increases stringency by requiring a consistently high enrichment of protein IDs across biological replicates.
In addition to statistical scoring, the CRAPome analysis workflow also maps previously reported interactions onto bait-prey data23. While this mapping can be useful for thresholding high and low-confidence interactions, previously reported interactions can score poorly by FC-A and SAINT probabilities, potentially indicating that many known interactions of a given bait may exist only in specific cell types, contexts, or organelles. For the example DYRK1A dataset, iREF interactor FC-A values were as low as 0.45, representing a very low enrichment over control (Figure 2C). To avoid inflation of false positives, statistical thresholding should be performed in a manner that prioritizes stringency over reduction of false negatives. It should be noted that the detection of these interactions was independent of protein abundance (Figure 2C). Calculated absolute copy number of each iREF interaction within HeLa cells showed no correlation to the detection levels of an interaction partner by IP-MS24.
Cytoscape serves as an effective tool for visualizing multiple layers of interaction data19. In the DYRK1A immunoprecipitation experiment described here, the combined use of FC-A &gt; 3.0 and SAINT &gt; 0.9 reduced the list of high-confidence interactors to six proteins (Figure 2D). However, when applying an FC-A cutoff of &gt; 3.0 in isolation, eight additional proteins were added to the network. These additional protein interactors have high connectivity with the interactors already in the network, suggesting they are associated in similar complexes or functional roles. To this end, evidence from the STRING-DB of protein-protein interactions was integrated into this network as blue dashed lines20. While this single-bait, triplicate experiment provides a limited sample of the full DYRK1A interaction network, the use of additional baits, replicates, and integration of large public data sets can be used to expand the network of high-confidence interactions. The statistical cutoffs will thus be specific to each individual experiment and will need to be evaluated thoroughly.
<img alt="Nuclear extract generation, immunoprecipitation, mass spectrometry, computational analysis diagram." class="xfigimg" src="/files/ftp_upload/60432/60432fig01.jpg" data-altupdatedat="1747911167000" data-alt="Figure 1"> 
Figure 1: Representative proteomics workflow for subcellular IP-MS. Cells are grown in either 4 L round bottom flasks or 15 cm tissue culture dishes and harvested at the same time for subcellular fractionation. Cells are fractionated into a cytosolic, nuclear, and a nuclear pellet, and immunoprecipitations are done from 1−10 mg of nuclear lysate using one or multiple antibodies recognizing the same bait. Filter aided sample prep (FASP) and offline sample cleanup are performed prior to single shot mass spectrometry. A downstream computational pipeline is used to process data into interpretable interaction data. <a href="https://www.jove.com/files/ftp_upload/60432/60432fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Protein interaction analysis; SAINT probability vs FC-A scatter plot; protein abundance graph; DYRK1A network diagram." class="xfigimg" src="/files/ftp_upload/60432/60432fig02.jpg" data-altupdatedat="1747911167000" data-alt="Figure 2"> 
Figure 2: Representative data for a single-bait single-antibody IP-MS experiment. (A) FC-A and SAINT probability output from CRAPome analysis workflow for an optimal experiment using a single antibody for the kinase DYRK1A (n = 3). Beads-only controls were used for comparison. Red solid lines represent cutoffs set at FC-A &gt; 3.00 and SAINT &gt; 0.7. (B) MaxQuant protein abundance estimates (iBAQ) output vs. log2 ratio of protein abundance in DYRK1A IP to control, colored by the adjusted p value range from empirical Bayes analysis of the label-free intensities. (C) FC-A and estimated copy number of proteins listed as interacting proteins in the iRef database23,24. (D) Cytoscape network visualization of DYRK1A interactors. Blue nodes = FC-A &gt; 3.00, SAINT &gt; 0.7. Orange nodes = FC-A &gt; 3.00. Black edges = proteins identified as interactors in IPMS experiment. Blue dashed edge = SAINT interaction between prey protein (confidence &gt; .150). <a href="https://www.jove.com/files/ftp_upload/60432/60432fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="2">Protease inhibitor (PI) mixture</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Final Concentration</td>
		</tr>
		<tr>
			<td>Sodium Metabisulfite</td>
			<td>1 mM</td>
		</tr>
		<tr>
			<td>Benzamidine</td>
			<td>1 mM</td>
		</tr>
		<tr>
			<td>Dithiothreitol (DTT)</td>
			<td>1 mM</td>
		</tr>
		<tr>
			<td>Phenylmethanesulfonyl fluoride (PMSF)</td>
			<td>0.25 mM</td>
		</tr>
		<tr>
			<td colspan="2"></td>
		</tr>
		<tr>
			<td colspan="2">Phosphatase Inhibitor (PhI) mixture</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Final Concentration</td>
		</tr>
		<tr>
			<td>Microcystin LR</td>
			<td>1 µM</td>
		</tr>
		<tr>
			<td>Sodium Orthovanadate</td>
			<td>0.1 mM</td>
		</tr>
		<tr>
			<td>Sodium fluoride</td>
			<td>5 mM</td>
		</tr>
		<tr>
			<td colspan="2"></td>
		</tr>
		<tr>
			<td colspan="2">Subcellular fractionation Buffers:</td>
		</tr>
		<tr>
			<td colspan="2"></td>
		</tr>
		<tr>
			<td colspan="2">Buffer A pH 7.9</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Final Concentration</td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>10 mM</td>
		</tr>
		<tr>
			<td>MgCl2</td>
			<td>1.5 mM</td>
		</tr>
		<tr>
			<td>KCl</td>
			<td>10 mM</td>
		</tr>
		<tr>
			<td colspan="2"></td>
		</tr>
		<tr>
			<td colspan="2">Buffer B pH 7.9</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Final Concentration</td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>20 mM</td>
		</tr>
		<tr>
			<td>MgCl2</td>
			<td>1.5 mM</td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>420 mM</td>
		</tr>
		<tr>
			<td>Ethylenediaminetetraacetic acid (EDTA)</td>
			<td>0.4 mM</td>
		</tr>
		<tr>
			<td>Glycerol</td>
			<td>25% (v/v)</td>
		</tr>
		<tr>
			<td colspan="2"></td>
		</tr>
		<tr>
			<td colspan="2">Buffer C pH 7.9</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Final Concentration</td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>20 mM</td>
		</tr>
		<tr>
			<td>MgCl2</td>
			<td>2 mM</td>
		</tr>
		<tr>
			<td>KCl</td>
			<td>100 mM</td>
		</tr>
		<tr>
			<td>Ethylenediaminetetraacetic acid (EDTA)</td>
			<td>0.4 mM</td>
		</tr>
		<tr>
			<td>Glycerol</td>
			<td>20% (v/v)</td>
		</tr>
		<tr>
			<td colspan="2"></td>
		</tr>
		<tr>
			<td colspan="2">Immunoprecipitation Buffers:</td>
		</tr>
		<tr>
			<td colspan="2"></td>
		</tr>
		<tr>
			<td colspan="2">IP Buffer 1</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Final Concentration</td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>20 mM</td>
		</tr>
		<tr>
			<td>KCl</td>
			<td>150 mM</td>
		</tr>
		<tr>
			<td>EDTA</td>
			<td>0.1 mM</td>
		</tr>
		<tr>
			<td>NP-40</td>
			<td>0.1% (v/v)</td>
		</tr>
		<tr>
			<td>Glycerol</td>
			<td>10% (v/v)</td>
		</tr>
		<tr>
			<td colspan="2"></td>
		</tr>
		<tr>
			<td colspan="2">IP Buffer 2</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Final Concentration</td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>20 mM</td>
		</tr>
		<tr>
			<td>KCl</td>
			<td>500 mM</td>
		</tr>
		<tr>
			<td>EDTA</td>
			<td>0.1 mM</td>
		</tr>
		<tr>
			<td>NP-40</td>
			<td>0.1% (v/v)</td>
		</tr>
		<tr>
			<td>Glycerol</td>
			<td>10% (v/v)</td>
		</tr>
		<tr>
			<td colspan="2"></td>
		</tr>
		<tr>
			<td colspan="2">SDS Alkylation Buffer pH 8.5</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Final Concentration</td>
		</tr>
		<tr>
			<td>SDS</td>
			<td>4% (v/v)</td>
		</tr>
		<tr>
			<td>Chloroacetamide</td>
			<td>40 mM</td>
		</tr>
		<tr>
			<td>TCEP</td>
			<td>10 mM</td>
		</tr>
		<tr>
			<td>Tris</td>
			<td>100 mM</td>
		</tr>
		<tr>
			<td colspan="2"></td>
		</tr>
		<tr>
			<td colspan="2">UA pH 8.5</td>
		</tr>
		<tr>
			<td>Reagent</td>
			<td>Final Concentration</td>
		</tr>
		<tr>
			<td>Urea</td>
			<td>8 M</td>
		</tr>
		<tr>
			<td>Tris</td>
			<td>0.1 M</td>
		</tr>
		<tr>
			<td colspan="2">* use HPLC grade H2O</td>
		</tr>
	</tbody>
</table>
Table 1: Buffer compositions
Supplemental Coding Files. <a href="https://www.jove.com/files/ftp_upload/60432/Supplemental_Coding_Files.zip" target="_blank">Please click here to download this file.</a>

Watch this Scientific Journal Video about Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling at JoVE.com

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Described is a proteomics workflow for identifying protein interaction partners from a nuclear subcellular fraction using immunoaffinity enrichment of a given protein of interest and label-free mass spectrometry. The workflow includes subcellular fractionation, immunoprecipitation, filter aided sample preparation, offline cleanup, mass spectrometry, and a downstream bioinformatics pipeline.

Immunoaffinity purification mass spectrometry (IP-MS) has emerged as a robust quantitative method of identifying protein-protein interactions. This ...

label-free-immunoprecipitation-mass-spectrometry-workflow-for-large

Research

JoVE Journal

Biochemistry

16.0K Views.  University of Colorado. Deze proteomics workflow maakt het mogelijk om endogene eiwit-eiwitinteracties met subcellulaire resolutie te identificeren en in kaart te brengen. Deze techniek is bijzonder voordelig bij het onderzoeken van aas eiwitten die dosering gevoelig, lage overvloed, of hebben meerdere subcellulaire lokalisaties. Deze methode kan worden toegepast op het in kaart brengen van endogene eiwit interacties ervan uitgaande dat er een geschikte affiniteit reagens beschikbaar.Dit is vooral belangrijk ...

Video: Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

A Protein Preparation Method for the High-throughput Identification of Proteins Interacting with a Nuclear Cofactor Using LC-MS/MS Analysis

Transcriptional coregulators are vital to the efficient transcriptional regulation of nuclear chromatin structure. Coregulators play a variety of roles in regulating transcription. These include the direct interaction with transcription factors, the covalent modification of histones and other proteins, and the occasional chromatin conformation alteration. Accordingly, establishing relatively quick methods for identifying proteins that interact within this network is crucial to enhancing our understanding of the underlying regulatory mechanisms. LC-MS/MS-mediated protein binding partner identification is a validated technique used to analyze protein-protein interactions. By immunoprecipitating a previously-identified member of a protein complex with an antibody (occasionally with an antibody for a tagged protein), it is possible to identify its unknown protein interactions via mass spectrometry analysis. Here, we present a method of protein preparation for the LC-MS/MS-mediated high-throughput identification of protein interactions involving nuclear cofactors and their binding partners. This method allows for a better understanding of the transcriptional regulatory mechanisms of the targeted nuclear factors.

We have established a method for the purification of coregulatory interaction proteins using the LC-MS/MS system.

Transcriptional coregulators are vital to the efficient transcriptional regulation of nuclear chromatin structure. Coregulators play a variety of roles in ...

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Most proteins act in association with others; hence, it is crucial to characterize these functional units in order to fully understand biological processes. Affinity purification coupled to mass spectrometry (AP-MS) has become the method of choice for identifying protein-protein interactions. However, conventional AP-MS studies provide information on protein interactions, but the organizational information is lost. To address this issue, we developed a strategy to unravel the distinct functional assemblies a protein might be involved in, by resolving affinity-purified protein complexes prior to their characterization by mass spectrometry. Protein complexes isolated through affinity purification of a bait protein using an epitope tag and competitive elution are separated through blue native electrophoresis. Comparison of protein migration profiles through correlation profiling using quantitative mass spectrometry allows assignment of interacting proteins to distinct molecular entities. This method is able to resolve protein complexes of close molecular weights that might not be resolved by traditional chromatographic techniques such as gel filtration. With little more work than conventional AP-geLC-MS/MS, we demonstrate this strategy may in many cases be adequate for obtaining protein complex topological information concomitantly to identifying protein interactions.

Here we present protocols for affinity purification of protein complexes and their separation by blue native PAGE, followed by protein correlation profiling using label free quantitative mass spectrometry. This method is useful to resolve interactomes into distinct protein complexes.

Most proteins act in association with others; hence, it is crucial to characterize these functional units in order to fully understand biological ...

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) coupled to tandem mass spectrometry (LC-MS/MS) and isobaric labeling multiplexing capacity. Here, we introduce a deep-proteomics profiling protocol that combines 10-plex tandem mass tag (TMT) labeling with an extensive LC/LC-MS/MS platform, and post-MS computational interference correction to accurately quantitate whole proteomes. This protocol includes the following main steps: protein extraction and digestion, TMT labeling, 2-dimensional (2D) LC, high-resolution mass spectrometry, and computational data processing. Quality control steps are included for troubleshooting and evaluating experimental variation. More than 10,000 proteins in mammalian samples can be confidently quantitated with this protocol. This protocol can also be applied to the quantitation of post translational modifications with minor changes. This multiplexed, robust method provides a powerful tool for proteomic analysis in a variety of complex samples, including cell culture, animal tissues, and human clinical specimens.

We present a protocol to accurately quantitate proteins with isobaric labelling, extensive fractionation, bioinformatics tools, and quality control steps in combination with liquid chromatography interfaced to a high-resolution mass spectrometer.

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) ...

High-Resolution Complexome Profiling by Cryoslicing BN-MS Analysis

Proteins generally exert biological functions through interactions with other proteins, either in dynamic protein assemblies or as a part of stably formed complexes. The latter can be elegantly resolved according to molecular size using native polyacrylamide gel electrophoresis (BN-PAGE). Coupling of such separations to sensitive mass spectrometry (BN-MS) has been well-established and theoretically allows for exhaustive assessment of the extractable complexome in biological samples. However, this approach is rather laborious and provides limited complex size resolution and sensitivity. Also, its application has remained restricted to abundant mitochondrial and plastid proteins. Thus, for a majority of proteins, information regarding integration into stable protein complexes is still lacking. Presented here is an optimized approach for complexome profiling comprising preparative-scale BN-PAGE separation, sub-millimeter sampling of broad gel lanes by cryomicrotome slicing, and mass spectrometric analysis with label-free protein quantification. The procedures and tools for critical steps are described in detail. As an application, the report describes complexome analysis of a solubilized endosome-enriched membrane fraction from mouse kidneys, with 2,545 proteins profiled in total. The results demonstrate identification of uniform, low-abundance membrane proteins such as intracellular ion channels as well as high resolution, complex protein assembly patterns, including glycosylation isoforms. The results are in agreement with independent biochemical analyses. In summary, this methodology allows for comprehensive and unbiased identification of protein (super)complexes and their subunit composition, providing a basis for investigating stoichiometry, assembly, and interaction dynamics of protein complexes in any biological system.

A versatile cryoslicing BN-MS protocol using a microtome is presented for high-resolution complexome profiling.

Proteins generally exert biological functions through interactions with other proteins, either in dynamic protein assemblies or as a part of stably formed ...

Analyzing Large Protein Complexes by Structural Mass Spectrometry

Living cells control and regulate their biological processes through the coordinated action of a large number of proteins that assemble themselves into an array of dynamic, multi-protein complexes1. To gain a mechanistic understanding of the various cellular processes, it is crucial to determine the structure of such protein complexes, and reveal how their structural organization dictates their function. Many aspects of multi-protein complexes are, however, difficult to characterize, due to their heterogeneous nature, asymmetric structure, and dynamics. Therefore, new approaches are required for the study of the tertiary levels of protein organization.
One of the emerging structural biology tools for analyzing macromolecular complexes is mass spectrometry (MS)2-5. This method yields information on the complex protein composition, subunit stoichiometry, and structural topology. The power of MS derives from its high sensitivity and, as a consequence, low sample requirement, which enables examination of protein complexes expressed at endogenous levels. Another advantage is the speed of analysis, which allows monitoring of reactions in real time. Moreover, the technique can simultaneously measure the characteristics of separate populations co-existing in a mixture. 
Here, we describe a detailed protocol for the application of structural MS to the analysis of large protein assemblies. The procedure begins with the preparation of gold-coated capillaries for nanoflow electrospray ionization (nESI). It then continues with sample preparation, emphasizing the buffer conditions which should be compatible with nESI on the one hand, and enable to maintain complexes intact on the other. We then explain, step-by-step, how to optimize the experimental conditions for high mass measurements and acquire MS and tandem MS spectra. Finally, we chart the data processing and analyses that follow. Rather than attempting to characterize every aspect of protein assemblies, this protocol introduces basic MS procedures, enabling the performance of MS and MS/MS experiments on non-covalent complexes. Overall, our goal is to provide researchers unacquainted with the field of structural MS, with knowledge of the principal experimental tools.

Mass spectrometry has proven to be a valuable tool for analyzing large protein complexes. This method enables insights into the composition, stoichiometry and overall architecture of multi-subunit assemblies. Here, we describe, step-by-step, how to perform a structural mass spectrometry analysis, and characterize macromolecular structures.

Living cells control and regulate their biological processes through the coordinated action of a large number of proteins that assemble themselves into an ...

Biology

A Protocol for the Identification of Protein-protein Interactions Based on 15N Metabolic Labeling, Immunoprecipitation, Quantitative Mass Spectrometry and Affinity Modulation

Protein-protein interactions are fundamental for many biological processes in the cell. Therefore, their characterization plays an important role in current research and a plethora of methods for their investigation is available1. Protein-protein interactions often are highly dynamic and may depend on subcellular localization, post-translational modifications and the local protein environment2. Therefore, they should be investigated in their natural environment, for which co-immunoprecipitation approaches are the method of choice3. Co-precipitated interaction partners are identified either by immunoblotting in a targeted approach, or by mass spectrometry (LC-MS/MS) in an untargeted way. The latter strategy often is adversely affected by a large number of false positive discoveries, mainly derived from the high sensitivity of modern mass spectrometers that confidently detect traces of unspecifically precipitating proteins. A recent approach to overcome this problem is based on the idea that reduced amounts of specific interaction partners will co-precipitate with a given target protein whose cellular concentration is reduced by RNAi, while the amounts of unspecifically precipitating proteins should be unaffected. This approach, termed QUICK for QUantitative Immunoprecipitation Combined with Knockdown4, employs Stable Isotope Labeling of Amino acids in Cell culture (SILAC)5 and MS to quantify the amounts of proteins immunoprecipitated from wild-type and knock-down strains. Proteins found in a 1:1 ratio can be considered as contaminants, those enriched in precipitates from the wild type as specific interaction partners of the target protein. Although innovative, QUICK bears some limitations: first, SILAC is cost-intensive and limited to organisms that ideally are auxotrophic for arginine and/or lysine. Moreover, when heavy arginine is fed, arginine-to-proline interconversion results in additional mass shifts for each proline in a peptide and slightly dilutes heavy with light arginine, which makes quantification more tedious and less accurate5,6. Second, QUICK requires that antibodies are titrated such that they do not become saturated with target protein in extracts from knock-down mutants.
Here we introduce a modified QUICK protocol which overcomes the abovementioned limitations of QUICK by replacing SILAC for 15N metabolic labeling and by replacing RNAi-mediated knock-down for affinity modulation of protein-protein interactions. We demonstrate the applicability of this protocol using the unicellular green alga Chlamydomonas reinhardtii as model organism and the chloroplast HSP70B chaperone as target protein7 (Figure 1). HSP70s are known to interact with specific co-chaperones and substrates only in the ADP state8. We exploit this property as a means to verify the specific interaction of HSP70B with its nucleotide exchange factor CGE19.

A Protocol for the Identification of Protein-protein Interactions Based on 15N Metabolic Labeling, Immunoprecipitation, Quantitative Mass Spectrometry and Affinity Modulation

We present a variation of the QUICK (QUantitative Immunoprecipitation Combined with Knockdown) approach that was introduced previously to distinguish between true and false protein-protein interactions. Our approach is based on 15N metabolic labeling, the modulation of affinities of protein-protein interactions by the presence/absence of ATP, immunoprecipitation, and quantitative mass spectrometry.

Protein-protein interactions are fundamental for many biological processes in the cell. Therefore, their characterization plays an important role in ...

The ChroP Approach Combines ChIP and Mass Spectrometry to Dissect Locus-specific Proteomic Landscapes of Chromatin

Chromatin is a highly dynamic nucleoprotein complex made of DNA and proteins that controls various DNA-dependent processes. Chromatin structure and function at specific regions is regulated by the local enrichment of histone post-translational modifications (hPTMs) and variants, chromatin-binding proteins, including transcription factors, and DNA methylation. The proteomic characterization of chromatin composition at distinct functional regions has been so far hampered by the lack of efficient protocols to enrich such domains at the appropriate purity and amount for the subsequent in-depth analysis by Mass Spectrometry (MS). We describe here a newly designed chromatin proteomics strategy, named ChroP (Chromatin Proteomics), whereby a preparative chromatin immunoprecipitation is used to isolate distinct chromatin regions whose features, in terms of hPTMs, variants and co-associated non-histonic proteins, are analyzed by MS. We illustrate here the setting up of ChroP for the enrichment and analysis of transcriptionally silent heterochromatic regions, marked by the presence of tri-methylation of lysine 9 on histone H3. The results achieved demonstrate the potential of ChroP in thoroughly characterizing the heterochromatin proteome and prove it as a powerful analytical strategy for understanding how the distinct protein determinants of chromatin interact and synergize to establish locus-specific structural and functional configurations.

By combining native and crosslinking chromatin immunoprecipitation with high-resolution Mass Spectrometry, ChroP approach enables to dissect the composite proteomic architecture of histone modifications, variants and non-histonic proteins synergizing at functionally distinct chromatin domains.

Chromatin is a highly dynamic nucleoprotein complex made of DNA and proteins that controls various DNA-dependent processes. Chromatin structure and ...

Discovering Protein Interactions and Characterizing Protein Function Using HaloTag Technology

Research in proteomics has exploded in recent years with advances in mass spectrometry capabilities that have led to the characterization of numerous proteomes, including those from viruses, bacteria, and yeast.&#160; In comparison, analysis of the human proteome lags behind, partially due to the sheer number of proteins which must be studied, but also the complexity of networks and interactions these present. To specifically address the challenges of understanding the human proteome, we have developed HaloTag technology for protein isolation, particularly strong for isolation of multiprotein complexes and allowing more efficient capture of weak or transient interactions and/or proteins in low abundance. &#160;HaloTag is a genetically encoded protein fusion tag, designed for covalent, specific, and rapid immobilization or labelling of proteins with various ligands. Leveraging these properties, numerous applications for mammalian cells were developed to characterize protein function and here we present methodologies including: protein pull-downs used for discovery of novel interactions or functional assays, and cellular localization. We find significant advantages in the speed, specificity, and covalent capture of fusion proteins to surfaces for proteomic analysis as compared to other traditional non-covalent approaches. We demonstrate these and the broad utility of the technology using two important epigenetic proteins as examples, the human bromodomain protein BRD4, and histone deacetylase HDAC1.&#160; These examples demonstrate the power of this technology in enabling &#160;the discovery of novel interactions and characterizing cellular localization in eukaryotes, which will together further understanding of human functional proteomics. &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;

HaloTag technology is a multifunctional technology which has shown significant success in isolation of both small and large protein complexes from mammalian cells.&#160; Here we highlight the advantages of this technology compared to existing alternatives and demonstrate its utility to study numerous aspects of protein function inside eukaryotic cells.

Research in proteomics has exploded in recent years with advances in mass spectrometry capabilities that have led to the characterization of numerous ...

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics

Quantitative proteomics combined with immuno-affinity purification, SILAC immunoprecipitation, represent a powerful means for the discovery of novel protein:protein interactions. By allowing the accurate relative quantification of protein abundance in both control and test samples, true interactions may be easily distinguished from experimental contaminants. Low affinity interactions can be preserved through the use of less-stringent buffer conditions and remain readily identifiable. This protocol discusses the labeling of tissue culture cells with stable isotope labeled amino acids, transfection and immunoprecipitation of an affinity tagged protein of interest, followed by the preparation for submission to a mass spectrometry facility. This protocol then discusses how to analyze and interpret the data returned from the mass spectrometer in order to identify cellular partners interacting with a protein of interest. As an example this technique is applied to identify proteins binding to the eukaryotic translation initiation factors: eIF4AI and eIF4AII.

SILAC immunoprecipitation experiments represent a powerful means for discovering novel protein:protein interactions. By allowing the accurate relative quantification of protein abundance in both control and test samples, true interactions may be easily distinguished from experimental contaminants, and low affinity interactions preserved through use of less-stringent buffer conditions.

Quantitative proteomics combined with immuno-affinity purification, SILAC immunoprecipitation, represent a powerful means for the discovery of novel ...

Protein Interaction Analysis in HEK-293 Cells Using Co-Immunoprecipitation

Immunoprecipitation with an Anti-Epitope Tag Affinity Gel to Study Protein-Protein Interactions

Protein-protein interactions (PPIs) play a pivotal role in biological phenomena, such as cellular organization, intracellular signal transduction, and transcriptional regulation. Therefore, understanding PPIs is an important starting point for further investigation of the function of the target protein. In this study, we propose a simple method to determine the binding of two target proteins by introducing mammalian expression vectors into HEK-293 cells using the polyethylenimine method, lysing the cells in homemade protein lysis buffer, and pulling down the target proteins on an epitope tag affinity gel. In addition, the PPI between the various epitope tag fused proteins can be confirmed by using affinity antibodies against each tag instead of the epitope tag affinity gel. This protocol could also be used to verify various PPIs, including nuclear extracts, from other cell lines. Therefore, it can be used as a basic method in a variety of PPI experiments. Proteins degrade by extended time course and repeated freeze-thaw cycles. Therefore, cell lysis, immunoprecipitation, and immunoblotting should be performed as seamlessly as possible.

Author Spotlight: Unraveling the Molecular Mechanisms of Brown and Beige Adipocyte Regulation

Protein-protein interactions are important for elucidating the function of target proteins, and co-immunoprecipitation (co-IP) can easily confirm PPIs. We transiently transfected a plasmid encoding an epitope-tagged protein into HEK-293 cells and developed an immunoprecipitation method to easily confirm the binding of two target proteins.

Protein-protein interactions (PPIs) play a pivotal role in biological phenomena, such as cellular organization, intracellular signal transduction, and ...

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

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