Abstract
Rat, mouse and human liver microsomes and S9 fractions were analyzed using an optimized method combining ion exchange fractionation of digested peptides, and ultra-high performance liquid chromatography (UHPLC) coupled to high resolution tandem mass spectrometry (HR-MS/MS). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository (Vizcaíno et al., 2013 [1]) with the dataset identifiers PXD000717, PXD000720, PXD000721, PXD000731, PXD000733 and PXD000734. Data related to the peptides (trypsin digests only) were also uploaded to Peptide Atlas (Farrah et al., 2013 [2]) and are available with the dataset identifiers PASS00407, PASS00409, PASS00411, PASS00412, PASS00413 and PASS00414. The present dataset is associated with a research article published in EuPA Open Proteomics [3].
Specifications table
| Subject area | Chemistry, biology |
|---|---|
| More specific subject area | Proteomic analysis |
| Type of data |
|
| How data was acquired | 2D-LC–MS/MS using Agilent 1200 HPLC, Shimadzu Nexera UHPLC, and AB Sciex TripleTOF 5600 mass spectrometer |
| Data format | .wiff,.wiff.scan (raw files) |
| .group,.xml (search files) | |
| .mgf (peak files) | |
| .xlsx (false-discovery rate analysis and processed results) | |
| Experimental factors | No sample pretreatment applied |
| Experimental features | Liver microsomes/S9 fractions were solubilized, denatured, and subjected to a trypsin/pepsin parallel dual-digestion. Digested peptides were fractionated using strong cation exchange (SCX) chromatography prior to UHPLC–MS/MS with subsequent data-mining and bioinformatics analysis. |
| Data source location | Université du Québec à Montréal (UQÀM), Chemistry Department, Montréal, Que., Canada |
| Data accessibility | The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository [1] with the dataset identifiers PXD000717, PXD000720, PXD000721, PXD000731, PXD000733 and PXD000734. Data related to the peptides (trypsin digests only) were also uploaded to Peptide Atlas [2] and are available with the dataset identifiers PASS00407, PASS00409, PASS00411, PASS00412, PASS00413 and PASS00414. |
Value of the data
-
•
Liver proteins identified in microsomal and S9 fractions with high sequence coverage.
-
•
Comprehensive list of proteotypic peptides reported for each identified protein enables more targeted analyses.
-
•
Cross-species analysis of rat, mouse and human liver microsomes and S9 fractions.
-
•
Multiple-sequence alignment (MSA) analysis possible between proteins exclusively found in each species.
1. Experimental design, materials and methods
Rat, mouse, and human liver microsomes or S9 fractions (0.6 mg protein, n=2) were solubilized in 2% SDS solution (1:1 v/v ratio) and then diluted with 0.1 M ammonium bicarbonate (pH 8.5) prior to reductive alkylation with dithiothreitol (2.5 mM) and iodoacetamide (5 mM). Additional ammonium bicarbonate (for trypsin), or 0.2% trifluoroacetic acid in 20% methanol (for pepsin), was added for an overnight digestion at a 1:50 (w/w) enzyme/protein ratio. Digests were neutralized, diluted with water, and subjected to solid-phase extraction (SPE) on a 1 cm3 (30 mg) OASIS HLB cartridge (Waters, Milford, MA), eluting with 100% methanol (1 ml). Eluates were evaporated to dryness under vacuum, reconstituted in SCX buffer A (see below), and injected (100 μl, 0.5 mg protein) onto a Zorbax 300-SCX 150×2.1 mm column with 5 μm (300 Å) particles (Agilent Technologies, Palo Alto, CA) using an Agilent 1200 series HPLC equipped with a binary pump, degasser, diode array detector and fraction collector. SCX fractionation was performed (250 μl/min) with a gradient of 0–50% B in 15 min, up to 100% B at 25 min, then held for an additional 5 min at 100% B, where buffers A and B were 10 mM potassium dihydrogen phosphate in 25% acetonitrile (pH 2.75), and 1 M potassium chloride in buffer A (pH 2.75), respectively. UV absorbance was monitored at 220 and 280 nm. For trypsin samples, 3 min (0.75 ml) fractions were aliquoted into 1.5 ml tubes between 1.5 and 19.5 min, while for pepsin, 4 min (1.0 ml) fractions were collected between 1.5 and 25.5 min. Fractions were evaporated to dryness under vacuum and kept at −30 °C.
Dried fractions were reconstituted in 10% acetonitrile (100 μl) and injected (20 μl) onto an Aeris PEPTIDE XB-C18 100×2.1 mm column, with solid core 1.7 μm particles (100 Å) (Phenomenex, Torrance, CA). RP-LC was performed (300 μl/min, 40 °C) on a Nexera UHPLC system (Shimadzu, Columbia, MD) with water (A) and acetonitrile (B), both containing 0.1% formic acid with a gradient of 5% B held for 2 min, increased linearly to reach 30% B at 24 min, to 50% B at 26 min, then to 85% B at 26.5 min and held for 2 min. MS and MS/MS spectra were collected on a high-resolution hybrid quadrupole-time-of-flight (QqTOF) TripleTOF 5600 mass spectrometer (AB Sciex, Concord, Ont.) equipped with a DuoSpray ion source in positive ion mode. The instrument performed a survey TOF-MS acquisition from m/z 140–1250 (250 ms accumulation time), followed by MS/MS on the 15 most intense precursor ions from m/z 250−1250 (precursors excluded for 20 s after two occurrences) using information-dependent acquisition (IDA) with dynamic background subtraction (DBS). Each MS/MS acquisition (m/z 80–1500) had an accumulation time of 50 ms and collision energy of 30±10 V. The total cycle time was 1.05 s.
MS/MS files were combined and searched against the UniProt protein database (www.uniprot.org, release date 26/06/2013) by ProteinPilot software (version 4.1) using Paragon algorithm [4] using a thorough ID search with no specified enzyme and carbamoylation as a fixed cysteine modification. The search was performed for +2 to +4 charge states and MS tolerance was 0.05 Da on precursor ions and 0.1 Da on fragment ions. All duplicates were first processed alone, then together and finally tryptic and peptic digest for each sample were co-processed to obtain the total number of proteins and peptides. Proteins were identified with a 1% global false discovery rate (FDR) using a target-decoy database search algorithm [5] in ProteinPilot Descriptive Statistics Template (version 3.001p) (www.absciex.com/PDST). ProteinPilot Protein Alignment Template (version 2.000p) was also used for replicate analysis. The list of UniProt accession numbers from identified proteins was uploaded to NCBI Batch Entrez (www.ncbi.nlm.nih.gov/sites/batchentrez) to obtain the batch FASTA file, which was subsequently submitted to ExPASy (www.expasy.org) for determination of isoelectric point and monoisotopic molecular weight, to Phobius (phobius.sbc.su.se) [6] for prediction of integral membrane proteins, and to GRAVY Calculator (www.gravy-calculator.de) to compute grand average of hydropathy (GRAVY) scores. Processed lists of the identified proteins in rat, mouse, and human liver microsomes and S9 fractions, as well as the corresponding proteotypic peptides can be found in Supplemental Tables S1 and S2 (see Tables 1 and 2 for details).
Table 1.
Processed data from proteomic analysis of rat, mouse, and human liver microsomes and S9 fractions.
| Spices | Sample | ID | Protein data location | Peptide data location |
|---|---|---|---|---|
| Rattus norvegicus | Liver microsomes | RLM | Supplemental Table S1-1 | Supplemental Table S2-1 |
| Liver S9 fraction | RLS | Supplemental Table S1-2 | Supplemental Table S2-2 | |
| Mus musculus | Liver microsomes | MLM | Supplemental Table S1-3 | Supplemental Table S2-3 |
| Liver S9 fraction | MLS | Supplemental Table S1-4 | Supplemental Table S2-4 | |
| Homo sapiens | Liver microsomes | HLM | Supplemental Table S1-5 | Supplemental Table S2-5 |
| Liver S9 fraction | HLS | Supplemental Table S1-6 | Supplemental Table S2-6 |
Table 2.
Dataset identifiers of the mass spectrometry data obtained from the analysis of rat, mouse, and human liver microsomes and S9 fractions on the public proteomics repositories.
| Spices | Sample | ID | Protein dataset identifier (PRIDE) | Peptide dataset identifier (PeptideAtlas) |
|---|---|---|---|---|
| Rattus norvegicus | Liver microsomes | RLM | PXD000720 | PASS00407 |
| Liver S9 fraction | RLS | PXD000717 | PASS00409 | |
| Mus musculus | Liver microsomes | MLM | PXD000731 | PASS00411 |
| Liver S9 fraction | MLS | PXD000733 | PASS00412 | |
| Homo sapiens | Liver microsomes | HLM | PXD000721 | PASS00413 |
| Liver S9 fraction | HLS | PXD000734 | PASS00414 |
Funding sources
Financial support for this study was provided by the Natural Sciences and Engineering Research Council of Canada (Discovery Grant no. 355933-2011).
Acknowledgments
Authors would also like to thank Dr. Sean Seymour (AB Sciex), Dr. Eric Deutsch (Institute for System Biology/PeptideAtlas) and the PRIDE team for their kind and timely support.
Footnotes
Supplementary data associated with this article can be found in the online version at doi:10.1016/j.dib.2015.02.007.
Supporting information
Supporting Information. Table S1. Final list of the proteins identified in rat, mouse and human liver microsomes/S9 fractions at 1% FDR; Table S2. Final list of the prototypic peptides identified in rat, mouse and human liver microsomes/S9 fractions at 1% FDR.
References
- 1.Vizcaíno J.A., Côté R.G., Csordas A., Dianes J.A., Fabregat A., Foster J.M., Griss J., Alpi E., Birim M., Contell J., O’Kelly G., Schoenegger A., Ovelleiro D., Pérez-Riverol Y., Reisinger F., Ríos D., Wang R., Hermjakob H. The PRoteomics IDEntifications (PRIDE) database and associated tools: status in 2013. Nucleic Acids Res. 2013;41:D1063–D1069. doi: 10.1093/nar/gks1262. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Farrah T., Deutsch E.W., Hoopmann M.R., Hallows J.L., Sun Z., Huang C.-Y., Moritz R.L. The state of the human proteome in 2012 as viewed through PeptideAtlas. J. Proteome Res. 2013;12:162–171. doi: 10.1021/pr301012j. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.M. Golizeh, C. Schneider, L. Ohlund, L. Sleno, Multidimensional LC–MS/MS analysis of liver proteins in rat, mouse and human microsomal and S9 fractions. EuPA Open Proteomics 6 (2015) 16-27, 10.1016/j.euprot.2015.01.003.
- 4.Shilov I.V., Seymour S.L., Patel A.A., Loboda A., Tang W.H., Keating S.P., Hunter C.L., Nuwaysir L.M., Schaeffer D.A. The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra. Mol. Cell. Proteomics. 2007;6:1638–1655. doi: 10.1074/mcp.T600050-MCP200. [DOI] [PubMed] [Google Scholar]
- 5.Tang W.H., Shilov I.V., Seymour S.L. Nonlinear fitting method for determining local false discovery rates from decoy database searches. J. Proteome Res. 2008;7:3661–3667. doi: 10.1021/pr070492f. [DOI] [PubMed] [Google Scholar]
- 6.Krogh A., Sonnhammer E.L.L., Käll L. Advantages of combined transmembrane topology and signal peptide prediction — the Phobius web server. Nucleic Acids Res. 2007;35:429–432. doi: 10.1093/nar/gkm256. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supporting Information. Table S1. Final list of the proteins identified in rat, mouse and human liver microsomes/S9 fractions at 1% FDR; Table S2. Final list of the prototypic peptides identified in rat, mouse and human liver microsomes/S9 fractions at 1% FDR.
