Abstract
Comprehensive knowledge of the intracellular protein interactions of cell-surface receptors will greatly advance our comprehension of the underlying trafficking mechanisms. Hence, development of effective and high-throughput approaches is highly desired. In this work, we presented a strategy aiming to tailor toward the analysis of intracellular protein interactome of cell-surface receptors. We used α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors subunit GluA1 as an example to illustrate the methodological application. To capture intracellular proteins that interact with GluA1, after surface biotinylation of the prepared hippocampal neurons and slices, the non-biotinylated protein components as intracellular protein-enriched fraction were unconventionally applied for the following co-immunoprecipitation. The co-immuno-precipitated proteins were then analyzed through mass spectrometry-based proteomics and bioinformatics platforms. The detailed localizations indicated that intracellular proteins accounted for up to 93.7 and 90.3% of the analyzed proteins in the neurons and slices, respectively, suggesting that our protein preparation was highly effective to characterize intracellular interactome of GluA1. Further, we systematically revealed the protein functional profile of GluA1 intracellular interactome, thereby providing complete overview and better comprehension of diverse intracellular biological processes correlated with the complex GluA1 trafficking. All experimental results demonstrated that our methodology would be applicable and useful for intracellular interaction proteomics of general cell-surface receptors.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The proteomics raw data can be found in the ProteomeXchange Consortium with the identifier PXD026268. The datasets supporting this article have been uploaded as part of the electronic supplementary materials.
References
Bissen D, Foss F, Acker-Palmer A (2019) AMPA receptors and their minions: auxiliary proteins in AMPA receptor trafficking. Cell Mol Life Sci 76(11):2133–2169. https://doi.org/10.1007/s00018-019-03068-7
Brechet A, Buchert R, Schwenk J, Boudkkazi S, Zolles G, Siquier-Pernet K, Schaber I, Bildl W, Saadi A, Bole-Feysot C, Nitschke P, Reis A, Sticht H, Al-Sanna’a N, Rolfs A, Kulik A, Schulte U, Colleaux L, Abou Jamra R, Fakler B (2017) AMPA-receptor specific biogenesis complexes control synaptic transmission and intellectual ability. Nat Commun 4(8):15910. https://doi.org/10.1038/ncomms15910
Chourbaji S, Vogt MA, Fumagalli F, Sohr R, Frasca A, Brandwein C, Hörtnagl H, Riva MA, Sprengel R, Gass P (2008) AMPA receptor subunit 1 (GluR-A) knockout mice model the glutamate hypothesis of depression. FASEB J 22(9):3129–3134. https://doi.org/10.1096/fj.08-106450
Crupi MJ, Richardson DS, Mulligan LM (2015) Cell surface biotinylation of receptor tyrosine kinases to investigate intracellular trafficking. Methods Mol Biol 1233:91–102. https://doi.org/10.1007/978-1-4939-1789-1_9
Di Fiore PP, von Zastrow M (2014) Endocytosis, signaling, and beyond. CSH PERSPECT BIOL 6(8):a016865–a016865. https://doi.org/10.1101/cshperspect.a016865
Eagle GL, Zhuang J, Jenkins RE, Till KJ, Jithesh PV, Lin K, Johnson GG, Oates M, Park K, Kitteringham NR, Pettitt AR (2015) Total proteome analysis identifies migration defects as a major pathogenetic factor in immunoglobulin heavy chain variable region (IGHV)-unmutated chronic lymphocytic leukemia. Mol Cell Proteom 14(4):933–945. https://doi.org/10.1074/mcp.M114.044479
Goh LK, Sorkin A (2013) Endocytosis of receptor tyrosine kinases. CSH PERSPECT BIOL 5(5):a017459–a017459. https://doi.org/10.1101/cshperspect.a017459
Gong W, Liao W, Fang C, Liu Y, Xie H, Yi F, Huang R, Wang L, Zhou J (2021) Analysis of chronic mild stress-induced hypothalamic proteome: identification of protein dysregulations associated with vulnerability and resiliency to depression or anxiety. Front Mol Neurosci 14:633398. https://doi.org/10.3389/fnmol.2021.633398
Greco TM, Miteva Y, Conlon FL, Cristea IM (2012) Complementary proteomic analysis of protein complexes. Methods Mol Biol 917:391–407. https://doi.org/10.1007/978-1-61779-992-1_22
Huang DW, Sherman BT, Lempicki RA (2008) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4(1):44–57. https://doi.org/10.1038/nprot.2008.211
Liu Z, Li S, Wang H, Tang M, Zhou M, Yu J, Bai S, Li P, Zhou J, Xie P (2017) Proteomic and network analysis of human serum albuminome by integrated use of quick crosslinking and two-step precipitation. Sci Rep 7(1):9856. https://doi.org/10.1038/s41598-017-09563-w
Liu YC, Tian FF, Li SM, Chen W, Gong WB, Xie H, Liu D, Huang RZ, Liao W, Yi FP, Zhou J (2021) Global effects of RAB3GAP1 dysexpression on the proteome of mouse cortical neurons. Amino Acids 53(9):1339–1350. https://doi.org/10.1007/s00726-021-03058-9
Ma J, Chen T, Wu S, Yang C, Bai M, Shu K, Li K, Zhang G, Jin Z, He F, Hermjakob H, Zhu Y (2019) iProX: an integrated proteome resource. Nucleic Acids Res 47(D1):D1211–D1217. https://doi.org/10.1093/nar/gky869
Maere S, Heymans K, Kuiper M (2005) BiNGO: a cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21(16):3448–3449. https://doi.org/10.1093/bioinformatics/bti551
McMahon HT, Boucrot E (2011) Molecular mechanism and physiological functions of clathrin-mediated endocytosis. Nat Rev Mol Cell Biol 12(8):517–533. https://doi.org/10.1038/nrm3151
Mi H, Ebert D, Muruganujan A, Mills C, Albou L-P, Mushayamaha T, Thomas PD (2021) PANTHER version 16: a revised family classification, tree-based classification tool, enhancer regions and extensive API. Nucleic Acids Res 49(D1):D394–D403. https://doi.org/10.1093/nar/gkaa1106
Mishra S, Knupp A, Szabo MP, Williams CA, Kinoshita C, Hailey DW, Wang Y, Andersen OM, Young JE (2022) The Alzheimer’s gene SORL1 is a regulator of endosomal traffic and recycling in human neurons. Cell Mol Life Sci 79(3):162. https://doi.org/10.1007/s00018-022-04182-9
Pischedda F, Szczurkowska J, Cirnaru MD, Giesert F, Vezzoli E, Ueffing M, Sala C, Francolini M, Hauck SM, Cancedda L, Piccoli G (2014) A cell surface biotinylation assay to reveal membrane-associated Neuronal Cues: Negr1 regulates dendritic arborization. Mol Cell Proteomics 13(3):733–748. https://doi.org/10.1074/mcp.M113.031716
Posner BI, Laporte SA (2010) Cellular signalling: peptide hormones and growth factors. Prog Brain Res 181:1–16. https://doi.org/10.1016/S0079-6123(08)81001-1
Qiao R, Li S, Zhou M, Chen P, Liu Z, Tang M, Zhou J (2017) In-depth analysis of the synaptic plasma membrane proteome of small hippocampal slices using an integrated approach. Neuroscience 353:119–132. https://doi.org/10.1016/j.neuroscience.2017.04.015
Raudvere U, Kolberg L, Kuzmin I, Arak T, Adler P, Peterson H, Vilo J (2019) g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update). Nucleic Acids Res 47(W1):W191–W198. https://doi.org/10.1093/nar/gkz369
Rowe C, Gerrard DT, Jenkins R, Berry A, Durkin K, Sundstrom L, Goldring CE, Park BK, Kitteringham NR, Hanley KP, Hanley NA (2013) Proteome-wide analyses of human hepatocytes during differentiation and dedifferentiation. Hepatology 58(2):799–809. https://doi.org/10.1002/hep.26414
Schwenk J, Boudkkazi S, Kocylowski MK, Brechet A, Zolles G, Bus T, Costa K, Kollewe A, Jordan J, Bank J, Bildl W, Sprengel R, Kulik A, Roeper J, Schulte U, Fakler B (2019) An ER assembly line of AMPA-receptors controls excitatory neurotransmission and its plasticity. Neuron 104(4):680–692. https://doi.org/10.1016/j.neuron.2019.08.033
Sigismund S, Confalonieri S, Ciliberto A, Polo S, Scita G, Di Fiore PP (2012) Endocytosis and signaling: cell logistics shape the eukaryotic cell plan. Physiol Rev 92(1):273–366. https://doi.org/10.1152/physrev.00005.2011
Smolders K, Lombaert N, Valkenborg D, Baggerman G, Arckens L (2015) An effective plasma membrane proteomics approach for small tissue samples. Sci Rep 5:10917. https://doi.org/10.1038/srep10917
Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P, Jensen LJ, Christian M, v, (2019) STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 47(D1):D607–D613. https://doi.org/10.1093/nar/gky1131
Tao Y-X, Conn PM (2014) Chaperoning G protein-coupled receptors: from cell biology to therapeutics. Endocr Rev 35(4):602–647. https://doi.org/10.1210/er.2013-1121
Thomas-Crusells J, Vieira A, Saarma M, Rivera C (2003) A novel method for monitoring surface membrane trafficking on hippocampal acute slice preparation. J Neurosci Methods 125(1–2):159–166. https://doi.org/10.1016/s0165-0270(03)00050-5
Varea O, Martin-de-Saavedra MD, Kopeikina KJ, Schürmann B, Fleming HJ, Fawcett-Patel JM, Bach A, Jang S, Peles E, Kim E, Penzes P (2015) Synaptic abnormalities and cytoplasmic glutamate receptor aggregates in contactin associated protein-like 2/Caspr2 knockout neurons. Proc Natl Acad Sci U S A 112(19):6176–6181. https://doi.org/10.1073/pnas.1423205112
Wang M, Pan W, Xu Y, Zhang J, Wan J, Jiang H (2022) A potential target for the treatment of cardiovascular diseases. J Inflamm Res 15:3083–3094. https://doi.org/10.2147/JIR.S350109
Wu QL, Gao Y, Li JT, Ma WY, Chen NH (2021) The role of AMPARs composition and trafficking in synaptic plasticity and diseases. Cell Mol Neurobiol 42(8):2489–2504. https://doi.org/10.1007/s10571-021-01141-z
Xie C, Mao X, Huang J, Ding Y, Wu J, Dong S, Kong L, Gao G, Li C-Y, Wei L (2011) KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res 39(Suppl_2):W316–W322. https://doi.org/10.1093/nar/gkr483
Yuan G, Yu TW (2021) GluA1-homomeric AMPA receptor in synaptic plasticity and neurological diseases. Neuropharmacology 1(197):108708. https://doi.org/10.1016/j.neuropharm.2021.108708
Zhang J, Li J, Yin Y, Li X, Jiang Y, Wang Y, Cha C, Guo G (2020) Collapsin response mediator protein 2 and endophilin2 coordinate regulation of AMPA receptor GluA1 subunit recycling. Front Mol Neurosci 13:128. https://doi.org/10.3389/fnmol.2020.00128
Zhou M, Liu Z, Yu J, Li S, Tang M, Zeng L, Wang H, Xie H, Peng L, Huang H, Zhou C, Xie P, Zhou J (2018a) Quantitative proteomic analysis reveals synaptic dysfunction in the amygdala of rats susceptible to chronic mild stress. Neuroscience 376:24–39. https://doi.org/10.1016/j.neuroscience.2018.02.010
Zhou M, Tang M, Li S, Peng L, Huang H, Fang Q, Liu Z, Xie P, Li G, Zhou J (2018b) Effective lock-in strategy for proteomic analysis of corona complexes bound to amino-free ligands of gold nanoparticles. Nanoscale 10(26):12413–12423. https://doi.org/10.1039/c8nr01077c
Zimmerman B, Beautrait A, Aguila B, Charles R, Escher E, Claing A, Bouvier M, Laporte SA (2012) Differential beta-arrestin-dependent conformational signaling and cellular responses revealed by angiotensin analogs. Sci Signal 5(221):ra33. https://doi.org/10.1126/scisignal.2002522
Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grant Nos. 31770890 and 31570826).
Author information
Authors and Affiliations
Contributions
YL, FY and JZ: designed the project. YL, MZ, ZL and SL: performed experiments. HL and RH: analyzed the data. YL, FY and JZ: prepared the manuscript. All authors read and approved the final manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Conflict of interest
The authors declare that they have no conflicts of interest.
Ethical approval
The experimental protocol was approved by the Ethical Committee of Chongqing Medical University. Animals were treated in accordance with the National Institutes of Health Guidelines for the use and care of laboratory animals.
Additional information
Handling editor: K. Wan Li.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
726_2022_3223_MOESM1_ESM.tif
Supplementary file1 Supplementary Fig. 1 Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) band pattern of the co-immunoprecipitation (co-IP) protein samples from the experimental (Exp) and control groups. Protein bands were excised to five gel slices per lane and subjected to gel-based tandem mass spectrometry (GeLC–MS/MS) analysis (TIF 7889 KB)
726_2022_3223_MOESM2_ESM.xlsx
Supplementary file2 Supplementary Table 1 All proteins identified from the hippocampal neurons and slices in the experimental (Exp) and control groups of the co-immuno-precipitation (co-IP) experiment. The two samples from independent experiments were prepared for each group. Each sample in duplicate was analyzed by solution-based tandem mass spectrometry (SoLC–MS/MS) and gel-based tandem mass spectrometry (GeLC–MS/MS). To eliminate non-specific bindings of Protein G agarose beads, the total proteins identified in the two control samples by the two proteomic approaches were excluded from the list of the experimental group (XLSX 487 KB)
726_2022_3223_MOESM3_ESM.xlsx
Supplementary file3 Supplementary Table 2 Mass spectrometry (MS)-based identification information of GluA1 in solution-based tandem mass spectrometry (SoLC–MS/MS) and gel-based tandem mass spectrometry (GeLC–MS/MS) analyses (XLSX 11 KB)
726_2022_3223_MOESM4_ESM.xlsx
Supplementary file4 Supplementary Table 3 Intracellular localizations of the potential GluA1-interacting proteins identified from the hippocampal neurons and slices. The analysis was conducted using seven bioinformatics tools: OmicsBean, g:Profiler, BINGO, STRING, PANTHER, DAVID and KOBAS (XLSX 78 KB)
726_2022_3223_MOESM5_ESM.xlsx
Supplementary file5 Supplementary Table 4 Enrichment results of gene ontology (GO) annotations in biological process and molecular function, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway terms of the identified potential GluA1-interacting proteins. The significantly enriched items were shown in yellow (XLSX 492 KB)
726_2022_3223_MOESM6_ESM.xlsx
Supplementary file6 Supplementary Table 5 Summary of the potential GluA1-interacting proteins identified in the present study (with literature evidence) (XLSX 30 KB)
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Liu, Y., Zhang, M., Liu, Z. et al. A strategy can be used to analyze intracellular interaction proteomics of cell-surface receptors. Amino Acids 55, 263–273 (2023). https://doi.org/10.1007/s00726-022-03223-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00726-022-03223-8