assays/2_7-ProteomeAcquisition-MassSpectrometry/protocols/ProteomeAcquisition-MassSpectrometry.md

+# 2.7 Proteome acquisition via mass spectrometry analysis
+
+Total proteins and the enriched membrane proteins of the organellar fractions (F1-4) isolated from Ricinus endosperm tissue were analyzed by mass spectrometry (MS). Therefore, protein samples were loaded on an SDS-polyacrylamide gel, concentrated in the stacking gel, silver stained according to MS-compatible protocol, reduced, alkylated, and digested with trypsin. Peptides were extracted from the gel with 0.1% trifluoroacetic acid and subjected to liquid chromatography. For peptide separation an Ultimate 3000 Rapid Separation liquid chromatography system (Dionex; ThermoFisher Scientific) equipped with an Acclaim PepMap 100 C18 column (75 mm inner diameter x 50 cm length x 2 mm particle size from ThermoFisher Scientific) was used with a 140-minute LC- gradient. Mass spectrometry was carried out on an Obitrap Elite high- resolution instrument (ThermoFisher Scientific) operated in positive mode and equipped with a Nano electrospray ionization source. Capillary temperature was set to 275°C and source voltage to 1.5 kV. Survey scans were conducted in the orbitrap analyzer at a mass to charge (m/z) ranging from 350-1700 and a resolution of 60,000 (at 400 m/z). The target value for the automatic gain control was 1,000,000 and the maximum fill time 200 ms. The 20 most intense doubly and triply charged peptide ions (minimal signal intensity 500) were isolated, transferred to the linear ion trap (LTQ) part of the instrument and fragmented using collision induced dissociation (CID). Peptide fragments were analyzed using a maximal fill time of 200 ms and automatic gain control target value of 100,000. The available mass range was 200- 2000 m/z at a resolution of 5400 (at 400 m/z). Two fragment spectra were summed up and already fragmented ions excluded from fragmentation for 45 seconds.
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assays/2_8-Computational-MS-DataAnalysis/README.md

+
+Source: https://www.frontiersin.org/articles/10.3389/fpls.2023.1182105/full#supplementary-material
+
+## Table 1
+
+SUPPLEMENTARY TABLE 1
+List of proteins isolated from endosperm tissue of etiolated castor bean seedlings, which were identified and quantified in the density-gradient fractions containing the total proteins (T1 to T4) and membrane proteins (M1 to M4). Three biological replicates were subjected to proteome analysis. Only proteins contained at least two unique peptides and a minimum of three valid values in at least one fraction (total or membrane) were classified as “identified”. Values represent the absolute abundance of the proteins calculated by the sum of the peptide signal intensities.
+
+## Table 2
+
+SUPPLEMENTARY TABLE 2
+List of castor bean proteins that have been defined as specific to peroxisomes, plastids, mitochondria, cytosol, vacuole, ER, Golgi, and nucleus based on (1) in silico prediction tools for their subcellular localization within the cell and (2) experimental data from GFP and/or MS assays of their corresponding Arabidopsis homologue using SUBA 5.0.
+
+
+
+SUPPLEMENTARY FIGURE 1
+Classification of the identified castor bean endosperm proteins from a soluble and membrane fraction enriched with peroxisomes (A), mitochondria (B), and plastids (C). The classification is based on UniProt database. Numbers in percent refer to the number of proteins that have been assigned to a certain metabolic pathway relative to the total proteins of all metabolic pathways of the respective organelle.
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assays/2_8-Computational-MS-DataAnalysis/protocols/Computational-MS-DataAnalysis.md

+
+# 2.8 Computational MS data analysis
+
+For peptide and protein identification the acquired MS spectra were analyzed using the MaxQuant version 1.3.0.5 (MPI for Biochemistry, Planegg, Germany) with default parameters (Cox and Mann, 2008). Quantification was performed using the unlabeled quantification option of MaxQuant. The identified spectra were matched against the Ricinus proteome using the peptide search engine Andromeda (Cox et al., 2011). Only proteins containing at least two unique peptides and a minimum of three valid values in at least one group were quantified. A full list of all identified peptides from the proteome experiment is presented in Supplemental Table S1.
+All identified Ricinus proteins were analyzed by bidirectional BLAST against the Arabidopsis proteome (Altschul et al., 1990). Organelle distribution within the collected fractions was assayed using a set of marker proteins. Proteins were assigned as organelle markers if the experimental localization of their Arabidopsis homologues in the SUBA 5.0 database (Hooper et al., 2017; Hooper et al., 2022) corresponded with their sequence-based localization prediction in Ricinus. We predicted protein localization to peroxisomes, mitochondria, and plastids manually and using the publicly available tools PPero, PredPlantPTS1, and TargetP (Emanuelsson et al., 2000; Reumann et al., 2012; Wang et al., 2015).
+
+- Cox, J., and Mann, M. (2008). MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372. doi: 10.1038/nbt.1511
+- Cox, J., Neuhauser, N., Michalski, A., Scheltema, R. A., Olsen, J. V., and Mann, M. (2011). Andromeda: A peptide search engine integrated into the maxQuant environment. J. Proteome Res. 10, 1794–1805. doi: 10.1021/pr101065j
+- Altschul, S. F., Gish, W., Miller, W., Myers, E. W., and Lipman, D. J. (1990). Basic local alignment search tool. J. Mol. Biol. 215, 403–410. doi: 10.1016/S0022-2836(05) 80360-2
+- Hooper, C. M., Castleden, I. R., Tanz, S. K., Aryamanseh, N., and Millar, A. H. (2017). SUBA4: the interactive data analysis centre for Arabidopsis subcellular protein locations. Nucleic Acids Res. 45, D1064–D1074. doi: 10.1093/nar/gkw1041
+- Hooper, C. M., Castleden, I., Tanz, S. K., Grasso, S. V., Aryamanesh, N., and Millar, A. H. (2022). Subcellular Localisation database for Arabidopsis proteins version 5 (The University of Western Australia). doi: 10.26182/8dht-4017
+- Emanuelsson, O., Nielsen, H., Brunak, S., and von Heijne, G. (2000). Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J. Mol. Biol. 300, 1005–1016. doi: 10.1006/jmbi.2000.3903
+- Reumann, S., Buchwald, D., and Lingner, T. (2012). PredPlantPTS1: A web server for the prediction of plant peroxisomal proteins. Front. Plant Sci. 3. doi: 10.3389/ fpls.2012.00194
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