Dataset Information

MDCK cell line adaptation to suspension growth

ABSTRACT: Dataset submission for journal publication: Label-free quantification was performed using the software Progenesis LC-MS 3.0 (Nonlinear Dynamics, Germany). LC-MS runs were aligned to an automatically selected reference run. After peak picking, a list of the features was exported and analyzed using SearchGUI (Vaudel et al. 2011). Therefore, the list was divided 15 times and analyzed using the OMSSA and X!tandem search algorithm through the Uniprot/Trembel database (2013/07) of Canis familiaris entries. Established search parameters: tryptic digest with a maximum of one missed cleavage; fixed modification: carbamidomethylation of cysteine, variable modification: oxidation of methionine; peptide charge 2plus to 4plus; monoisotopic peptide masses; peptide tolerance of 0.3 Da; MS/MS tolerance of 0.5 Da. Data were imported into Peptide-Shaker (Version 0.22.5) and corrected with a false discovery rate of 0.05 (Barsnes et al. 2011; Vaudel et al. 2011). Afterwards, result files were imported to Progenesis and protein lists with calculated protein quantities were exported to Excel. For statistical analysis of the data a Students t-Test with a p-value less then 0.05 was performed with R (Team 2008).

INSTRUMENT(S): Q-Exactive

ORGANISM(S): Canis Lupus Familiaris (ncbitaxon:9615)

SUBMITTER: Sabine Pech

PROVIDER: MSV000086277 | MassIVE | Tue Oct 13 12:54:00 BST 2020

REPOSITORIES: MassIVE

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Project description:SUMO modification of proteins (sumoylation) is essential for mitotic progression from yeast to humans, but only a limited number of sumoylated proteins with functions in mitosis have been discovered. Vertebrates express three SUMO paralogs, SUMO-1, SUMO-2 and SUMO-3, but only SUMO-2 and -3 are chromosome-associated in mitosis. In this study, we used chromosome spreads to more precisely define the localization of endogenous SUMO-2 and -3 to the centromere as well as the chromosome protein scaffold. Furthermore, we developed methodologies for the immunopurification of endogenous SUMO-2 and -3 modified proteins from cell extracts. Using LC-MS/MS, we analyzed proteins immunopurified from mitotic chromosome fractions and G0 nuclear fractions. We identified 296 putative sumoylated proteins, with 138 being modified specifically in mitosis. We identified proteins known to localize to the centromere and kinetochore and the chromosome protein scaffold, consistent with SUMO-2/3 localization. Furthermore, we demonstrate that utilizing cell synchronization and fractionation allowed for the discovery of low abundance sumoylated proteins that are not detected in large asynchronous analyses. Our results provide a foundation for further characterization of the roles of sumoylation in regulating diverse aspects of chromosome segregation in mitosis. Thermo .raw files were uploaded to the ProHits (Liu et al, 2010) analytical suite and converted to .mzXML format using ReAdW software. Data were searched using X!Tandem (Craig & Beavis, 2004) against human ORFs (RefSeq v45). Search parameters specified a parent MS tolerance of +/- 15ppm, and an MS/MS tolerance of 0.4 Da, with up to two missed cleavages for trypsin. Oxidation of methionine and tryptophan, ubiquitylation of lysine, and alkylation of cysteine (by NEM) were allowed as variable modifications. Statistical validation of the results was performed using Peptide Prophet and Protein Prophet (Keller et al, 2002; Nesvizhskii et al, 2003) as part of the trans-proteomic pipeline. For each search, the Protein Prophet probability at a 1% false discovery rate was used as a cutoff value to generate SAINT-compatible input files. SAINT parameters were as follows: 5000 iterations, low mode Off (0), minFold 1 and normalization (1) (Choi et al, 2011). SAINT cutoff values of 0.75 were used to generate a high-confidence list of protein identifications.

Project description:One sub-project within the global Chromosome 19 Consortium, part of the Chromosome-Centric Human Proteome Project, is to define chromosome 19 gene and protein expression in glioma-derived cancer stem cells (GSCs). Chromosome 19 is notoriously linked to glioma by 1p/19q co-deletions and clinical tests are established to detect that specific aberration. GSCs are tumor-initiating cells and are hypothesized to provide a repository of cells in tumors that can self-replicate and be refractory to radiation and chemotherapeutic agents developed for the treatment of tumors. In this pilot study, we performed RNA-Seq, label-free quantitative protein measurements in six GSC lines, and targeted transcriptomic analysis using a chromosome 19 specific microarray in an additional 6 GSC lines. Here, we present insights into differences in GSC gene and protein expression, including the identification of proteins listed as having no or low evidence at the protein level (such as small nuclear ribonucleoprotein G-like protein, RUXGL_HUMAN), as correlated to chromosome 19 and GSC subtype. Furthermore, the upregulation of proteins downstream of adenovirus-associated viral integration site 1 (AAVS1) in GSC11 in response to oncolytic adenovirus treatment was demonstrated. Taken together, our results may indicate new roles for chromosome 19, beyond the 1p/19q co-deletion, in the future of personalized medicine for glioma patients. Data analysis: MS files (.raw) were imported into Progenesis LC-MS (version 18.214.1528, Nonlinear Dynamics) for m/z and retention time alignment. The top 5 spectra for each feature were exported (charge deconvolution, top 1000 peaks) as a combined .mgf file for database searching in PEAKS (version 6, Bioinformatics Solutions Inc., Waterloo, ON) against the UniprotKB/Swissprot-Human database (July 2013 version, 20,264 proteins), appended with the cRAP contaminant database. PEAKS DB and Mascot (version 2.3.02, Matrix Science) searches were performed with a parent ion tolerance of 10 ppm, fragment ion tolerance of 0.025 Da, fixed carbamidomethyl cysteine, and variable modifications of oxidation (M), phosphorylation (STY), and deamidation (NQ). Trypsin was specified as the enzyme, allowing for 2 missed cleavages and a maximum of 3 PTMs per peptide. An additional search for unexpected modifications was performed with the entire Unimod database. Finally, homology searching was performed using the SPIDER algorithm to identify peptides resulting from nonspecific cleavages or amino acid substitutions. Mascot and PEAKS SPIDER searches were combined (inChorus), using a 1% false discovery rate cutoff for both search engines. The resulting peptide-spectrum matches (95% peptide probability) were imported into Progenesis LC-MS. Conflict resolution was performed manually to ensure that a single peptide sequence was assigned to each feature by removing lower scoring peptides. The resulting normalized peptide intensity data were exported, and the peptide list was filtered to remove non-unique peptides, methionine-containing peptides, and all modified peptides except cysteine carbamidomethylation. For quantification, the filtered list of peptide intensities was imported into DanteR (version 0.1.1), and intensities for peptides of the same sequence were combined to form a single entry. The resulting peptide intensities were log2 transformed and combined to protein abundances (RRollup) using the default settings, excluding one-hit wonders (50% minimum presence of at least one peptide, minimum dataset presence 3, p-value cutoff of 0.05 for Grubbs’ test, minimum of 5 peptides for Grubbs’ test). The resulting proteins were quantified by 1-way ANOVA relative to M37; p-value adjustment for multiple testing was performed according to Benjamini and Hochberg.

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MDCK cell line adaptation to suspension growth

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