research articles Agilent Technologies 1100 series system was used to deliver a ﬂow of 1.5 µ L/min during desalting of the sample and 250 nL/ min during elution of the peptides into the mass spectrometer as described before.10 Each sample was loaded onto an online analytical fused silica needle column (Proxion Biosystems, Odense, Denmark) packed with 5-µ m Vydac C18 resin. Washing and desalting was done with 95% mobile phase A (H2O with 0.4% acetic acid and 0.005% heptaﬂuorobutyric (v/v)) and 5% mobile phase B (90% acetonitrile, 0.4% acetic acid, 0.005% heptaﬂuorobutyric acid in water). Samples were eluted from the analytical column by a linear gradient of 90% mobile phase A to 60% mobile phase A. A 34-min gradient was used for elution. A potential of 2.8 kV was applied to the emitter (Proxion Biosystems). The spectra were acquired on a quadrupole time- of-ﬂight mass spectrometer (Q-TOF US-API, Micromass, Manchester, U.K.) equipped with an ion source sample intro- duction system designed by Proxeon Biosystems (Odense, Denmark). Data were obtained in positive ion mode. Data- dependent acquisition was performed with a ion mass window to 2.5 Da. MS to MS/MS switch was set to a threshold of 10 counts/s, and MS/MS to MS was set to an intensity below a threshold of 2 counts/s. Charge state recognition was used to estimate the collision energy for the fragmented precursor. Scan time was set to 0.9 s, and interscan time was set to 0.1 s. The number of components (i.e., number of MS/MS per MS scan) was set to three resulting in a total cycle time (one MS and three MS/MS spectra) of 10 s. The acquisition of data was performed using MassLynx (version 4.0). The parameters used for generating peak lists from the raw data were the following: smooth window, 4.00; number of smooth, 2; smooth mode, Savitzky Golay; and percentage of peak height to calculate centroid spectra, 80% with no baseline subtraction. The gener- ated peak lists (pkl-ﬁle) were searched against the RefSeq human protein database (build 33, 29 572 sequences) (ww- w.ncbi.nlm.nih.gov./RefSeq/) using Mascot version 2.0, with a mass accuracy of 1.1 Da for the parent ion (MS) and 0.2 for the fragment ions (MS/MS), allowing a maximum of two missed cleavages. Carbamidomethylation of cysteines was considered as ﬁxed modiﬁcation, and oxidations of methionine residues, “medium” arginine (+6 Da), “heavy” arginine (+10 Da), and phosphorylation of tyrosine residue were considered as variable modiﬁcations. An initial protein list was generated using the following criteria. Only proteins containing at least one unique peptide (if the sequence has not been assigned to a different protein) with a Mascot score over 30 were considered in the data set. The sequence of higher scoring peptides was manually veriﬁed. Quantitation was performed on three to four peptides (wherever available) by comparing the extracted ion chromato- gram of the corresponding light and heavy peptides using MS- Quant.16 Reproducibility of measurements was performed by using two analysis of variance models as described earlier.17 The tandem mass spectra were manually veriﬁed to assign the sequence and phosphorylation sites for all peptides identiﬁed in this study (Supplementary Table 1). The phosphorylation sites were manually veriﬁed and assigned after conﬁrmation of a mass difference of 243 Da corresponding to phosphoty- rosine residue. Peptide Microarrays and Data Analysis. The WT (peptides containing a tyrosine residue in the center) and MUT (peptides where the central tyrosine residue was replaced by phenyla- lanine) peptides (Supplementary Table 2) were each spotted as triplicates on glass slides (Pepscan Systems, Lelystad, Netherlands) as described earlier.18 c-Src kinase assays were 3902 Journal of Proteome Research Vol. 7, No. 9, 2008 Amanchy et al. carried out using these custom peptide microarrays by incu- bating 50 ng of recombinant c-Src Kinase (Invitrogen, Carlsbad, CA) in kinase reaction buffer and 300 µ Ci/ml γ33P-labeled ATP (AH9968; GE Healthcare Biosciences Corp., Piscataway, NJ) at 25 °C for 1 h in a 120 µ L reaction volume supplemented with 200 µ M ATP. The reaction was stopped and the following washing steps were performed: 2 washes in 2 M sodium chloride containing 1% Triton X-100 followed by 3 washes in phosphate buffered saline containing Triton X-100 and 1 wash in distilled water. The glass slides were then air-dried and exposed to the phosphorimager screen for 12 h and scanned using Biorad Molecular Imager FX (Bio-Rad Laboratories, Inc., Hercules, CA). The image was processed using GenePix Pro 6.0 software (Molecular Devices Corporation, Sunnyvale, CA). Autoradiographs were obtained using a phosphorimager screen. The assay was performed in triplicate. The intensity values obtained were transformed to the log base 2 scale. Effects on intensity due to the position of the spot on the slide were estimated by performing a local regression analysis (loess) with respect to chip coordinates, and subtracted out.19 Normalized log 2 intensities for triplicate spots were averaged, and the mean log 2 MUT intensity was subtracted from the corre- sponding mean log 2 WT intensity for each peptide. The resulting background adjusted values were averaged over replicate arrays. The mean background adjusted log intensity for each peptide on the Y-axis, and the average of WT, and MUT log intensities on the X-axis were plotted to estimate the distribution of the intensity values arising from the phospho- rylated peptides. A key assumption for selection of positive (phosphorylated) peptides is that WT peptide intensity values are greater than MUT peptide intensities. It is also assumed that higher intensity peptides are more likely to be positive. We note that, consistent with this assumption, the WT intensity is consistently higher than MUT intensity for the high intensity peptides on the right side of the plot. Likewise, there is greater symmetry on the left side quadrant of the MvA plot, where we expect nonphosphorylated peptides to have WT intensities that are as likely to be lower than MUT values as higher. The classical False Positive Rate (expected error rate for a set of points) is derived by evaluating symmetry in the Y-axis. For each value of A, the classical FPR blue curve gives: (number of points below the X-axis to the right of A)/(number of points above the X-axis to the right of A), and describes the expected number of false positives in the upper right quadrant of the plot. Sometimes it is desirable to estimate the probability that a single given point is a false positive, allowing us to move the threshold to the left until the price of adding one more peptide is too high. This is described by the local false positive rate curve. The local FPR curve gives the probability of a positive peptide located at A being a false positive. We selected all peptides where the local false positive rate was lower than 0.15 and WT intensities were 2-fold greater compared to MUT. The resulting set has an overall FPR of 0.085. Results and Discussion Stable Isotope Labeling of Cellular Proteins for the Iden- tiﬁcation of c-Src Kinase Substrates. SILAC involves metabolic labeling of cellular proteomes by growing the cells in media containing amino acids labeled with stable isotopes. SILAC enables identiﬁcation of peptides labeled in vivo and relative quantitation of abundance of the peptides arising out of a mixture of labeled and unlabeled protein samples.15 This