Bioworks 3

Cell lysates from HCT-8 cells stably expressing either Flag or Aurora A-Flag were immunoprecipitated by using anti-Flag M2 agarose beads (Sigma), and separated via SDS-PAGE. Liquid chromatography tandem mass spectrometry was performed on a LTQ-Orbitrap instrument (Thermo Electron Corporation). The data were analyzed using the IPI databases for human version 3.35 with BioWorks 3.2 software (Thermo Electron Corporation).

Mass spectra were searched against a protein database using the SEQUEST [25 (link)] algorithm in Bioworks 3.3 (Thermo Fisher Scientific). At the time of analysis, the C. virginianus known proteome contained fewer than 100 proteins so the reference proteome (RefSeq) for Gallus gallus containing 18,768 entries was downloaded from NCBI on September 29, 2009. The protein database was in silico trypsin digested and cysteine carbamidomethylation and methionine oxidations (single and double) were included in the search criteria. Precursor and fragment ion tolerances were set at 1.5 Daltons. A randomized decoy database was also searched with mass spectra using the same search criteria as described above to estimate the probability of peptide identifications being false positives. We used a peptide probability filter of p ≤ 0.05 for protein identifications. Identified proteins were evaluated for differential expression using Monte Carlo re-sampling statistics [26 (link)] at a p-value of ≤ 0.05. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD001206.

Immunoprecipitated antigens were separated on 7% TA gels and subjected to in gel trypsin digest and subsequent liquid chromatography-tandem mass spectrometry as previously described31 (link). Proteins were identified using a publically available proteome for serotype M1 S. pyogenes (Uniprot, CP000017)32 33 (link); and correlation of the MS/MS peptide data with the in silico trypsin fragmentation patterns predicted using BioWorks 3.3 and the SEQUEST algorithm (Thermo Scientific). Peptides generating ions of 200–2000 amu, with a cross correlation score >1.5, 2.0, or 2.5 (where z = 1, 2 or 3 respectively) and a p < 0.01 were mapped onto the S. pyogenes proteome. Proteins that contained two or more of the identified peptides were selected for further analysis. The protein probability for each selected protein was calculated using the SEQUEST algorithm and reported as a range of up to 20 values derived independently from analysis of proteins from each of the strains examined.

For protein identification, MSⁿ data were searched against translated genomic database (Eichinger et al., 2005 (link); curated at dictybase.org) using SEQUEST (Bioworks 3.3, Thermo Fisher Scientific) with the following settings: 1000 ppm (10 ppm for data acquired using LTQ Orbitrap XL™) tolerance was set for precursor masses and 0.5 Da for fragment masses; trypsin was specified as the enzyme and only fully tryptic peptide identifications were retained; a maximum of three missed cleavage sites, three differential amino acids per modification, and three differential modifications per peptide were allowed; oxidization of methionine (+15.99 Da), carboxyamidomethylation of cysteine (+57.02 Da), phosphorylation of serine/threonine/tyrosine (+79.97 Da), and O-GlcNAc modification of serine/threonine (+203.08 Da) were set as differential modifications. All the raw spectra were searched against both normal (forward) and reverse databases under the same parameters. Peptides were filtered to 1% false-discovery rate and protein assignments were required to have a minimum of two independent peptides.

Acquired MS/MS spectra were searched against an international protein index “rat v. 3.78 FASTA-format decoy database” downloaded from European Bioinformatics Institute (EBI, http://www.ebi.ac.uk/). The SEQUEST algorithm [19 (link)] was used to find the best matching sequences from the database with BioWorks 3.3 (Thermo Fisher Scientific Inc., Rockford, IL, USA) for fully tryptic peptides. The mass of the amino acid cysteine was statically modified by +57 Da and the differential modification search was performed for oxidation (+16 Da on Met). Xcorr values were based on tryptic peptides and charge states following 1.8 for singly charged peptides, 2.5 for doubly charged peptides, 3.5 for triply charged peptides, and 0.08 for ΔCn (DTASelect v. 2.0.39). The analysis of protein fold-change was quantified by an overall spectral counting method comparison of label-free methods for quantifying human proteins [20 (link)].

MS/MS spectra were searched against E. coli using Sequest (version 27, rev 12), which is part of the BioWorks 3.3 data analysis package (Thermo Fisher, San Jose, CA). MS/MS spectra were searched with a maximum allowed deviation of 10 ppm for the precursor mass and 1 amu for fragment masses. Methionine oxidation and cysteine carboxamidomethylation were allowed as variable modifications, two missed cleavages were allowed and the minimum number of tryptic termini was 1. After the database search, the DTA and OUT files were imported into Scaffold (versions 1.07 and 2.01) (Proteomesoftware, Portland, OR). Scaffold was used to organize the data and to validate peptide identifications using the Peptide Prophet algorithm and only identifications with a probability >95% were retained. Subsequently, the Protein-Prophet algorithm was applied and protein identifications with a probability of >99% with 2 peptides in at least one of the samples were retained. Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped. For each protein identified, the number of spectral counts (the number of MS/MS associated with an identified protein) is listed in Supplemental Table S5.