ABSTRACT: MudPIT Analysis
Four biological replicates of FLAG-Hoxa1, and corresponding negative controls, and FLAG-Hoxb1, and corresponding negative controls, were prepared from a chromatin enriched fraction isolated from mouse KH2ES cells and subjected to FLAG affinity purification. The eluted proteins were TCA-precipitated and analyzed by MudPIT. TCA-precipitated proteins were urea-denatured, reduced, alkylated and digested with endoproteinase Lys-C (Roche) followed by modified trypsin (Promega). Peptide mixtures were loaded onto 250 um fused silica microcapillary columns packed with strong cation exchange resin (Luna, Phenomenex) and 5-um C18 reverse phase (Aqua, Phenomenex), and then connected to a 100 um fused silica microcapillary column packed with 5-um C18 reverse phase (Aqua, Phenomenex). Loaded microcapillary columns were placed in-line with a Quaternary Agilent 1100 series HPLC pump and a LTQ linear ion trap mass spectrometer equipped with a nano-LC electrospray ionization source (ThermoScientific, San Jose, CA). Fully automated 10-step MudPIT runs were carried out on the electrosprayed peptides. Tandem mass (MS/MS) spectra were interpreted using ProluCID (v. 1.3.3) against a database consisting of 78014 nonredundant Mus musculus proteins (NCBI, 2016-06-23 release), 193 usual contaminants (human keratins, IgGs, and proteolytic enzymes). To estimate false discovery rates (FDR)s, the amino acid sequence of each non-redundant protein entry was randomized to generate a virtual library. This resulted in a total library of 116008 non-redundant sequences against which the spectra were matched. All cysteines were considered as fully carboxamidomethylated (+57 Da statically added), while methionine oxidation was searched as a differential modification. DTASelect (v. 1.9) and swallow, an in-house developed software, were used to filter ProLuCID search results at given FDRs at the spectrum, peptide, and protein levels. Here all controlled FDRs were less than 5%. All 16 data sets were contrasted against their merged data set, respectively, using Contrast v 1.9 and in house developed sandmartin v0.0.1. Our in-house developed software, NSAF7 v0.0.1, was used to generate spectral count-based label free quantitation results.