LC MS configuration Nanoscale LC separation of the tryptic p

LC-MS configuration Nanoscale LC separation of the tryptic peptides was performed with a NanoAcquity system (Waters Corporation). Samples were loaded on to a Symmetry C18 5μm, 2cm×180μm trap column (Waters) at a flow rate of 5μl/min prior to separation on a Bridged Ethyl Hybrid C18 1.7μm, 25cm×75μm analytical reversed-phase column (Waters) by application of a 90min gradient from 1% ACN and 0.1% formic hexokinase inhibitor to 40% ACN and 0.1% formic acid at a column flow rate of 0.25μl/min. The column temperature was maintained at 35°C. Analysis of the eluted tryptic peptides was performed using a Synapt G2 Q-TOF (quadrupole time-of-flight) mass spectrometer (Waters Corporation) equipped with a nanolockspray source (Waters Corporation) fitted with a pico-tip emitter (New Objective) operated at a capillary voltage of approximately 3kV. For all measurements, the mass spectrometer was operated in v-mode with a typical resolution of at least 20,000 full width at half maximum. All analyses were performed in positive mode ESI. The time-of-flight analyzer of the mass spectrometer was externally calibrated with a NaI mixture from m/z 50 to 1990. The collision gas used was argon, maintained at a constant pressure of 2.0×10−3mbar in the collision cell. The lock mass, [Glu1]-fFibrinopeptide B, was delivered from the auxiliary pump of the NanoAcquity system with a concentration of 100fmol/μl at 0.5μl/min to the reference sprayer of the nanolockspray source. The data were post-acquisition lock-mass corrected using the monoisotopic mass of the doubly charged precursor of [Glu1]-Fibrinopeptide B, delivered through the reference sprayer, which was sampled every 120s. Accurate mass precursor and fragment ion LC-MS data were collected in data independent, alternate scanning (LC-MSE) mode of acquisition [2,3] LC-MS data processing and protein identification Continuum LC-MS data were processed and searched using ProteinLynx GlobalSERVER v2.5 (Waters Corporation). Protein identifications were obtained by searching databases of Rattus norvegicus databases (v15.12, 7449 entries) and Homo Sapiens release (2011_11, 20,335 entries). Sequence information of Alcohol dehydrogenase Saccharomyces cerevisiae was added to the databases to afford the ability to normalize the data sets and to estimate amounts and concentration and that of known contaminant proteins (e.g. serum albumin Bos taurus and trypsin Sus scrofa). A decoy was generated on the fly with every database search experiment conducted to estimate the protein false positive rate of identification. Data independent scanning protein identifications were accepted when more than three fragment ions per peptide, seven fragment ions per protein and more than 2 peptides per protein were identified, in at least one technical replicate per sample. Protein quantitation was only reported when the protein was detected in at least 2 out of 3 technical replicate of at least one biological replicate. Typical search criteria used for protein identification included automatic peptide and fragment ion tolerance settings (approximately 10 and 25 ppm, respectively), 1 allowed missed cleavage, fixed carbamidomethyl-cysteine modification and variable methionine oxidation. Raw data were expressed as ‘relative molar amount units’ calculated by dividing the determined molar amount for a given protein by the summed determined amount for all identified proteins as this accounts for both technical and biological variations [3,4,11]. To enable reuse of the continuum LC-MS data by other proteome search engines, MS1 and reconstructed MSn mass spectrometric data generated by PLGS were exported in mzML format. Geometric normalization between cell types and across species: to compare these relative molar amounts between cell types and across species, data were biologically interpreted after geometric normalization to a set of stable housekeeping proteins, as described in the associated 4 Pubmed-indexed studies thus far: analysis of the rat beta cell proteome [4], identification of doublecortin [5], protein phosphatase 1-inhibitor 1 [6] and ubiquitin thioesterase-L1 [8] as candidate real-time biomarkers for beta cell destruction (Table 2).