A Mass Spectrometry-Based Approach for Mapping Protein Subcellular Localization Reveals the Spatial Proteome of Mouse Primary Neurons

Cell Reports

Volumn 20, Issue 11, 2017, Pages 2706-2718

  Itzhak, Daniel N ^a   Davies, Colin ^b   Tyanova, Stefka ^a   Mishra, Archana ^c   Williamson, James ^b   Antrobus, Robin ^b   Cox, Jürgen ^a   Weekes, Michael P ^b   Borner, Georg H H ^a  

^a MAX PLANCK INSTITUTE OF BIOCHEMISTRY   (Germany)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^c MAX PLANCK INSTITUTE OF NEUROBIOLOGY   (Germany)

Author keywords

EGF signaling; label free quantification; LFQ; neurons; organellar proteomics; primary cells; quantitative mass spectrometry; spatial proteomics; tandem mass tagging; TMT

Indexed keywords

PROTEOME; BIOLOGICAL MARKER;

ANALYTIC METHOD; ANIMAL EXPERIMENT; ANIMAL TISSUE; ARTICLE; CHEMICAL LABELING; CONTROLLED STUDY; EMBRYO; HIGH THROUGHPUT SCREENING; LABEL FREE QUANTIFICATION; LIMIT OF QUANTITATION; MASS SPECTROMETRY; MEASUREMENT ACCURACY; MEASUREMENT PRECISION; MOUSE; NERVE CELL; NONHUMAN; PRIORITY JOURNAL; PROTEIN LOCALIZATION; TANDEM MASS TAGGING; ANIMAL; CELL CULTURE; CELL FRACTIONATION; CELL ORGANELLE; HELA CELL LINE; HUMAN; ISOTOPE LABELING; METABOLISM; PROCEDURES; PROTEIN TRANSPORT; PROTEOMICS; STAINING; TANDEM MASS SPECTROMETRY;

ANIMALS; BIOMARKERS; CELL FRACTIONATION; CELLS, CULTURED; HELA CELLS; HUMANS; ISOTOPE LABELING; MICE; NEURONS; ORGANELLES; PROTEIN TRANSPORT; PROTEOME; PROTEOMICS; STAINING AND LABELING; SUBCELLULAR FRACTIONS; TANDEM MASS SPECTROMETRY;

EID: 85029363057     PISSN: None     EISSN: 22111247     Source Type: Journal    
DOI: 10.1016/j.celrep.2017.08.063     Document Type: Article

References (27)

1. Aebersold, R., Mann, M., Mass-spectrometric exploration of proteome structure and function. Nature 537 (2016), 347–355.
2. Boisvert, F.M., Ahmad, Y., Gierlinski, M., Charriere, F., Lamont, D., Scott, M., Barton, G., Lamond, A.I., A quantitative spatial proteomics analysis of proteome turnover in human cells. Mol. Cell. Proteomics, 11, 2012 M111.011429.
3. Christoforou, A., Mulvey, C.M., Breckels, L.M., Geladaki, A., Hurrell, T., Hayward, P.C., Naake, T., Gatto, L., Viner, R., Martinez Arias, A., Lilley, K.S., A draft map of the mouse pluripotent stem cell spatial proteome. Nat. Commun., 7, 2016, 8992.
4. Cox, J., Mann, M., MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26 (2008), 1367–1372.
5. Cox, J., Hein, M.Y., Luber, C.A., Paron, I., Nagaraj, N., Mann, M., Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol. Cell. Proteomics 13 (2014), 2513–2526.
6. Drissi, R., Dubois, M.L., Boisvert, F.M., Proteomics methods for subcellular proteome analysis. FEBS J. 280 (2013), 5626–5634.
7. Foster, L.J., de Hoog, C.L., Zhang, Y., Zhang, Y., Xie, X., Mootha, V.K., Mann, M., A mammalian organelle map by protein correlation profiling. Cell 125 (2006), 187–199.
8. Hesketh, G.G., Youn, J.Y., Samavarchi-Tehrani, P., Raught, B., Gingras, A.C., Parallel Exploration of Interaction Space by BioID and Affinity Purification Coupled to Mass Spectrometry. Methods Mol. Biol. 1550 (2017), 115–136.
9. Itzhak, D.N., Tyanova, S., Cox, J., Borner, G.H., Global, quantitative and dynamic mapping of protein subcellular localization. eLife, 5, 2016.
10. Jadot, M., Boonen, M., Thirion, J., Wang, N., Xing, J., Zhao, C., Tannous, A., Qian, M., Zheng, H., Everett, J.K., et al. Accounting for Protein Subcellular Localization: A Compartmental Map of the Rat Liver Proteome. Mol. Cell. Proteomics 16 (2017), 194–212.
11. Jean Beltran, P.M., Mathias, R.A., Cristea, I.M., A portrait of the human organelle proteome in space and time during cytomegalovirus infection. Cell Syst. 3 (2016), 361–373.e6.
12. Jean Beltran, P.M., Federspiel, J.D., Sheng, X., Cristea, I.M., Proteomics and integrative omic approaches for understanding host-pathogen interactions and infectious diseases. Mol. Syst. Biol., 13, 2017, 922.
13. Larance, M., Lamond, A.I., Multidimensional proteomics for cell biology. Nat. Rev. Mol. Cell Biol. 16 (2015), 269–280.
14. Mardakheh, F.K., Sailem, H.Z., Kümper, S., Tape, C.J., McCully, R.R., Paul, A., Anjomani-Virmouni, S., Jørgensen, C., Poulogiannis, G., Marshall, C.J., Bakal, C., Proteomics profiling of interactome dynamics by colocalisation analysis (COLA). Mol. Biosyst. 13 (2016), 92–105.
15. McAlister, G.C., Huttlin, E.L., Haas, W., Ting, L., Jedrychowski, M.P., Rogers, J.C., Kuhn, K., Pike, I., Grothe, R.A., Blethrow, J.D., Gygi, S.P., Increasing the multiplexing capacity of TMTs using reporter ion isotopologues with isobaric masses. Anal. Chem. 84 (2012), 7469–7478.
16. McAlister, G.C., Nusinow, D.P., Jedrychowski, M.P., Wühr, M., Huttlin, E.L., Erickson, B.K., Rad, R., Haas, W., Gygi, S.P., MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal. Chem. 86 (2014), 7150–7158.
17. Meberg, P.J., Miller, M.W., Culturing hippocampal and cortical neurons. Methods Cell Biol. 71 (2003), 111–127.
18. Ong, S.E., Blagoev, B., Kratchmarova, I., Kristensen, D.B., Steen, H., Pandey, A., Mann, M., Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics 1 (2002), 376–386.
19. Qian, X., Shen, Q., Goderie, S.K., He, W., Capela, A., Davis, A.A., Temple, S., Timing of CNS cell generation: a programmed sequence of neuron and glial cell production from isolated murine cortical stem cells. Neuron 28 (2000), 69–80.
20. Rhee, H.W., Zou, P., Udeshi, N.D., Martell, J.D., Mootha, V.K., Carr, S.A., Ting, A.Y., Proteomic mapping of mitochondria in living cells via spatially restricted enzymatic tagging. Science 339 (2013), 1328–1331.
21. Sciarretta, C., Minichiello, L., The preparation of primary cortical neuron cultures and a practical application using immunofluorescent cytochemistry. Methods Mol. Biol. 633 (2010), 221–231.
22. Sharma, K., Schmitt, S., Bergner, C.G., Tyanova, S., Kannaiyan, N., Manrique-Hoyos, N., Kongi, K., Cantuti, L., Hanisch, U.K., Philips, M.A., et al. Cell type- and brain region-resolved mouse brain proteome. Nat. Neurosci. 18 (2015), 1819–1831.
23. Tyanova, S., Temu, T., Cox, J., The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat. Protoc. 11 (2016), 2301–2319.
24. Tyanova, S., Temu, T., Sinitcyn, P., Carlson, A., Hein, M.Y., Geiger, T., Mann, M., Cox, J., The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13 (2016), 731–740.
25. Weekes, M.P., Tomasec, P., Huttlin, E.L., Fielding, C.A., Nusinow, D., Stanton, R.J., Wang, E.C., Aicheler, R., Murrell, I., Wilkinson, G.W., et al. Quantitative temporal viromics: an approach to investigate host-pathogen interaction. Cell 157 (2014), 1460–1472.
26. Wiśniewski, J.R., Hein, M.Y., Cox, J., Mann, M., A “proteomic ruler” for protein copy number and concentration estimation without spike-in standards. Mol. Cell. Proteomics 13 (2014), 3497–3506.
27. Xu, S.Y., Wu, Y.M., Ji, Z., Gao, X.Y., Pan, S.Y., A modified technique for culturing primary fetal rat cortical neurons. J. Biomed. Biotechnol., 2012, 2012, 803930.