Proteome discoverer software suite

Manufactured by Thermo Fisher Scientific

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Proteome Discoverer software suite is a bioinformatics platform designed for the analysis and interpretation of mass spectrometry-based proteomics data. The software provides a comprehensive solution for the identification, quantification, and characterization of proteins from complex biological samples.

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Lab products found in correlation

Mascot search engine, by Matrix Science (15 mentions) Ltq orbitrap xl mass spectrometer, by Thermo Fisher Scientific (2 mentions) Q exactive mass spectrometer, by Thermo Fisher Scientific (1 mentions) Orbitrap fusion lumos mass spectrometer, by Thermo Fisher Scientific (1 mentions) Nano lc system, by Thermo Fisher Scientific (1 mentions) Orbitrap fusion tribrid, by Thermo Fisher Scientific (1 mentions) Easylc, by Thermo Fisher Scientific (1 mentions) Mascot, by Matrix Science (1 mentions)

22 protocols using proteome discoverer software suite

Proteome Analysis of Leptospira interrogans

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The mass spectrometry-derived
data from all of the LC-MS/MS analyses were searched against L. interrogans serogroup Icterohaemorrhagiae serovar
copenhageni (strain Fiocruz L1-130) obtained from the NCBI (3667 protein
entries). The database was also added with sequences of commonly encountered
protein contaminants such as BSA, trypsin, and keratins (115 contaminant
entries). The MS data were analyzed using the SEQUEST-HT and Mascot
search algorithms in the Proteome Discoverer software suite, version
2.2 (Thermo Fischer Scientific, Bremen, Germany) with the following
search parameters: (a) trypsin as the proteolytic enzyme (with up
to one missed cleavage); (b) fragment mass tolerance of 0.05 Da; (c)
precursor mass tolerance of 10 ppm; (d) oxidation of methionine as
a dynamic modification, and (e) carbamidomethylation of cysteine as
a static modification. The peptide-to-spectrum match scoring function
was identified with 1% false discovery rate (FDR) at the peptide level.

Phukan H., Sarma A., Rex D.A., Rai A.B., Prasad T.S, & Madanan M.G. (2022). Unique Posttranslational Modification Sites of Acetylation, Citrullination, Glutarylation, and Phosphorylation Are Found to Be Specific to the Proteins Partitioned in the Triton X-114 Fractions of Leptospira. ACS Omega, 7(22), 18569-18576.

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Mass Spectrometry Analysis of Gpr54 Interactome

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For mass spectrometry (MS) analysis, anti-Gpr54 IP was performed with the whole-cell lysates derived from two 10-cm dishes of RAW264.7 cells with or without Kp-10 treatment for 20 min. The protein complexes after Co-IP were extensively washed with PBS, followed by on-bead digestion. Mass spectra were acquired on a Q-Exactive mass spectrometer (Thermo Scientific, Bremen, Germany). The raw mass spectrometry data were searched against the mouse IPI databases (version 3.86, released on June 28, 2012) using the Proteome Discoverer software suite (Thermo Scientific, San Jose, USA) utilizing a label-free quantification feature. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE^{52 (link)} partner repository with the dataset identifier PXD038433.

Li Z., Yang X., Fu R., Wu Z., Xu S., Jiao J., Qian M., Zhang L., Wu C., Xie T., Yao J., Wu Z., Li W., Ma G., You Y., Chen Y., Zhang H.K., Cheng Y., Tang X., Wu P., Lian G., Wei H., Zhao J., Xu J., Ai L., Siwko S., Wang Y., Ding J., Song G., Luo J., Liu M, & Xiao J. (2024). Kisspeptin-10 binding to Gpr54 in osteoclasts prevents bone loss by activating Dusp18-mediated dephosphorylation of Src. Nature Communications, 15, 1300.

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Comprehensive Proteomics Analysis Workflow

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Proteome Discoverer software suite (v2.2, Thermo Fisher Scientific) and Mascot search engine [v2.5, Matrix Science (2 (link))] were used for peptide identification and quantification. The data were searched against an in-house generated database containing all proteins corresponding to mouse in the SwissProt database plus a list of common contaminants and all the corresponding decoy entries (released, April 2018). A precursor ion mass tolerance of 7 ppm at the MS1 level was used, and up to three missed cleavages for trypsin were allowed. The fragment ion mass tolerance was set to 0.5 Da. Oxidation of methionine and protein acetylation at the protein N-terminus were defined as variable modification, whereas carbamidomethylation on cysteines was set as a fixed modification. Identified peptides were filtered using a 5% FDR. Protein abundance was estimated using the area under the chromatographic peak of the three most intense peptides per protein. Data were log-transformed, and fold changes, P values, and q values were calculated to assess protein relative quantification.

Aranda S., Alcaine-Colet A., Blanco E., Borràs E., Caillot C., Sabidó E, & Di Croce L. (2019). Chromatin capture links the metabolic enzyme AHCY to stem cell proliferation. Science Advances, 5(3), eaav2448.

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Quantitative Proteome Analysis Pipeline

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Proteome Discoverer software suite (Thermo Fisher Scientific) and Mascot search engine (Matrix Science) were used for peptide identification and quantitation. Data were searched against the Swiss-Prot human database. A precursor ion mass tolerance of 7 ppm at the MS1 level was used, and up to three miscleavages for trypsin were allowed. The fragment ion mass tolerance was set to 0.5 Da. Methionine oxidation and N-terminal protein acetylation were used as variable modifications, whereas carbamidomethylation on cysteines was set as a fixed modification. False discovery rate (FDR) in peptide identification was set to a maximum of 5%. Raw proteomics data are currently being deposited in the PRIDE repository and will be available in the revised version of the manuscript.

Gómez-Marín E., Posavec-Marjanović M., Zarzuela L., Basurto-Cayuela L., Guerrero-Martínez J.A., Arribas G., Yerbes R., Ceballos-Chávez M., Rodríguez-Paredes M., Tomé M., Durán R.V., Buschbeck M, & Reyes J.C. (2022). The high mobility group protein HMG20A cooperates with the histone reader PHF14 to modulate TGFβ and Hippo pathways. Nucleic Acids Research, 50(17), 9838-9857.

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Quantitative Proteomics Using SILAC

Cited 1 time

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SILAC was performed as previously described [25 (link)]. SILAC labeling was performed using SILAC-Lys8- Arg10-Kit media (Silantes). Peptide mixes were analyzed using an OrbitrapFusion Lumos mass spectrometer (Thermo Scientific, San Jose, CA, USA) coupled to an EasyLC (Thermo Scientific (Proxeon), Odense, Denmark). All data were acquired with Xcalibur software v3.0.63. Proteome Discoverer software suite (v2.0, Thermo Fisher Scientific) and the Mascot search engine (v2.5, Matrix Science (1)) were used for peptide identification and quantification. Samples were searched against a SwissProt database containing entries corresponding to Human (version of April 2016) a list of common contaminants and all the corresponding decoy entries. Resulting data files were filtered for FDR < 1%.

Janin M., Ortiz-Barahona V., de Moura M.C., Martínez-Cardús A., Llinàs-Arias P., Soler M., Nachmani D., Pelletier J., Schumann U., Calleja-Cervantes M.E., Moran S., Guil S., Bueno-Costa A., Piñeyro D., Perez-Salvia M., Rosselló-Tortella M., Piqué L., Bech-Serra J.J., De La Torre C., Vidal A., Martínez-Iniesta M., Martín-Tejera J.F., Villanueva A., Arias A., Cuartas I., Aransay A.M., La Madrid A.M., Carcaboso A.M., Santa-Maria V., Mora J., Fernandez A.F., Fraga M.F., Aldecoa I., Pedrosa L., Graus F., Vidal N., Martínez-Soler F., Tortosa A., Carrato C., Balañá C., Boudreau M.W., Hergenrother P.J., Kötter P., Entian K.D., Hench J., Frank S., Mansouri S., Zadeh G., Dans P.D., Orozco M., Thomas G., Blanco S., Seoane J., Preiss T., Pandolfi P.P, & Esteller M. (2019). Epigenetic loss of RNA-methyltransferase NSUN5 in glioma targets ribosomes to drive a stress adaptive translational program. Acta Neuropathologica, 138(6), 1053-1074.

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Proteome Discoverer Protein Identification

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Proteome Discoverer software suite (v2.0, Thermo Fisher Scientific) and the Mascot search engine (v2.5, Matrix Science) (Perkins et al., 1999 (link)) were used for peptide identification and quantification. Samples were searched against a M. pneumoniae database with a list of common contaminants and all the corresponding decoy entries (87,059 entries). Trypsin was chosen as the enzyme and a maximum of three miscleavages were allowed. Carbamidomethylation (cysteine) was set as a fixed modification, whereas oxidation (methionine), acetylation (N-terminal), and phosphorylation (serine, threonine and tyrosine) were used as variable modifications. Searches were performed using a peptide tolerance of 7 ppm, and a product ion tolerance of 0.5 Da. Resulting data files were filtered by an FDR < 5%.

Yus E., Lloréns-Rico V., Martínez S., Gallo C., Eilers H., Blötz C., Stülke J., Lluch-Senar M, & Serrano L. (2019). Determination of the Gene Regulatory Network of a Genome-Reduced Bacterium Highlights Alternative Regulation Independent of Transcription Factors. Cell Systems, 9(2), 143-158.e13.

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Phosphoproteome Quantification and Analysis

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Proteome Discoverer software suite (v2.2, Thermo Fisher Scientific) and the Mascot search engine (v2.5, Matrix Science; Bowne et al., 2002 (link)) were used for peptide identification and quantification (Perkins et al., 1999 (link)). Samples were searched against the Uniprot proteome database corresponding to Bos Taurus (UP000009136), and a list of common contaminants (total entries 24,097), plus all the corresponding decoy entries. Trypsin was chosen as enzyme and a maximum of three miscleavages were allowed. Carbamidomethylation (C) was set as a fixed modification, whereas oxidation (M), phosphorylation (STY) and acetylation (N-terminal) were used as variable modifications. Searches were performed using a peptide tolerance of 7 ppm and a product ion tolerance of 0.5 Da, and identified phosphopeptides were filtered for FDR < 5%. Phosphopeptides were quantified by extraction of their precursor areas using Skyline (version 4.2.0.19009). Light/dark fold change and p values were calculated for phosphopeptides present in two or more replicates of each condition.

Plana-Bonamaisó A., López-Begines S., Fernández-Justel D., Junza A., Soler-Tapia A., Andilla J., Loza-Alvarez P., Rosa J.L., Miralles E., Casals I., Yanes O., de la Villa P., Buey R.M, & Méndez A. (2020). Post-translational regulation of retinal IMPDH1 in vivo to adjust GTP synthesis to illumination conditions. eLife, 9, e56418.

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Quantitative Proteome Profiling Using Mascot

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We used the Proteome Discoverer software suite (PD version 2.0.0.802; Thermo Fisher Scientific) to search the raw files with the Mascot search engine (v2.5.1, Matrix Science), validate peptides with Percolator (v2.05), and provide MS1 quantification through PD’s Area Detector Module. We matched MS1 precursors in a 350–10,000 mass range against the tryptic RefProtDB database digest (2015-06-10 download) with Mascot permitting up to two missed cleavage sites (without cleavage before P), a precursor mass tolerance of 20 ppm, and a fragment mass tolerance of 0.5 Da. We allowed the following dynamic modifications: Acetyl (Protein N-term), Oxidation (M), Carbamidomethyl (C), DeStreak (C), and Deamidated (NQ). For the Percolator module, we set the target strict and relaxed FDRs for peptide spectral matches (PSMs) at 0.01 and 0.05 (1% and 5%), respectively. We used gpGrouper (v1.0.040) for gene product inference and label-free iBAQ quantification with shared peptide distribution. We then median-normalized iBAQ values by sample for further analysis.

Alcott C.E., Yalamanchili H.K., Ji P., van der Heijden M.E., Saltzman A., Elrod N., Lin A., Leng M., Bhatt B., Hao S., Wang Q., Saliba A., Tang J., Malovannaya A., Wagner E.J., Liu Z, & Zoghbi H.Y. (2020). Partial loss of CFIm25 causes learning deficits and aberrant neuronal alternative polyadenylation. eLife, 9, e50895.

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Peptide Identification and Quantification

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Proteome Discoverer software suite (v2.0, Thermo Fisher Scientific) and the Mascot search engine (v2.5, Matrix Science) were used for peptide identification and quantification (Perkins et al, 1999). Samples were searched against a customized database for each species as described in the corresponding section. Trypsin was chosen as the enzyme, and a maximum of three miscleavages were allowed. Carbamidomethylation (C) was set as a fixed modification, whereas oxidation (M) and acetylation (N‐terminal) were used as variable modifications. Searches were performed using a mass accuracy enforcement of 7 ppm, which goes accordingly with the accuracy of the Orbitrap mass analyzer, and a product ion tolerance of 0.5 Da. Resulting data files were filtered for FDR < 1.

Miravet‐Verde S., Ferrar T., Espadas‐García G., Mazzolini R., Gharrab A., Sabido E., Serrano L, & Lluch‐Senar M. (2019). Unraveling the hidden universe of small proteins in bacterial genomes. Molecular Systems Biology, 15(2), e8290.

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Proteomic Analysis of Lung Tissue in SD Rats

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The modeling and grouping methods of SD rats followed the same instructions as in bulletin 2.4. Samples of the left lung tissue were taken for proteomic screening, followed by splitting decomposition, centrifugation, protein extraction, detection of protein concentration, proteolysis, and peptide purification and quantification. The qualitative and quantitative analysis of protein was conducted using liquid chromatography-mass spectrometry (LCMS). The detailed procedure was listed in reference item 6. Protein data were retrieved from the database of the Proteome Discoverer software suite (Version 2.1, Thermo Fisher Scientific). The total protein (TP) was retrieved in 3 sample groups, and the relative amount of protein was determined in each group. Proteins with P value <0.05 and absolute value of fold change (FC)>0.1 were considered to be differential expression proteins (DEPs). Contrast detection analysis on inflammatory proteins TNFRSF1, LBP, and NOS2 was conducted.

Ma Y., Chen Y., Li Y., Liu Y., Kong Y., Zou Q., Guo Z., Li X., Chu Y, & Wang Q. (2022). A Probe into the Intervention Mechanism of Yiqi Huayu Jiedu Decoction on TLR4/NLRP3 Signal Pathway in Lipopolysaccharide-Induced Acute Respiratory Distress Syndrome (ARDS) Rats. Evidence-based Complementary and Alternative Medicine : eCAM, 2022, 3051797.

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