Driven by the inextricable complexity of proteomes, technical limits of MS instrumentation are constantly pushed, with the development of multiple ion sources, analyzers or detectors, the three main elements of mass spectrometers. Matrix-assisted laser desorption/ionization (MALDI) [202] and electrospray ionization (ESI) [203] are generally used in proteomics in combination with a variety of mass analyzers including time of flight (TOF), ion trap (IT), quadrupole (Q), Fourier transform ion cyclotron resonance (FTICR) or Orbitrap. Hybrid

mass spectrometers enable the determination of protein amino acid sequence, expression level and structural features (i.e., PTM sites) using multiple stage MS fragmentation (MSn). Ion fragmentation is generally done by collision induced dissociation (CID) but electron transfer dissociation Selleck Enzalutamide (ETD) may be more suited to

analyze PTMs [204]. The ESI linear trap quadrupole (LTQ)-Orbitrap is one of the most performant and recent instrument commercialized, combining the MSn capability of the LTQ with the high Gamma-secretase inhibitor resolution and mass accuracy of the Orbitrap [205], [206] and [207]. Several bioinformatics tools were developed to interpret MS data. These include tools for peptide/protein identification (i.e., Mascot [208], Phenyx [209]) or PTMs analysis (i.e., Quickmod [210]) based on sequence database search algorithms as well as tools for protein/peptide quantification (i.e., Isobar, Easyquant [211]). As protein/peptide identification is a probability based process, false discovery rates (FDR) are generally calculated to estimate the rates of mistakenly identified proteins and should generally be kept below 1% at the peptide or protein level [212]. When peptide or protein sequences are absent from databases, often resulting from unexpected PTMs, de novo peptide sequencing can aminophylline be performed manually

or using specific programs. Quantitative proteomic data are needed to determine the specific set of proteins exhibiting different expression levels in healthy versus pathological states. Relative quantification has traditionally been performed by 2-DE or DIGE, followed by staining and image analysis to identify differences in gel patterns (Fig. 2). Although providing access to a range of PTMs and protein isoforms, the procedure is not best-suited for the rapid analysis of complex samples, suffering principally from a lack of automatization and a limited dynamic range together with reproducibility, resolution and sensitivity issues. Alternatively, high throughput shotgun quantitative proteomic platforms coupled with multidimensional LC has been widely used to tackle complex mixtures, either relying on isotope labeling of proteins or peptides, or “label-free” with quantification based on spectral counting or ion peak intensity [213].While the latter could be more convenient for analyzing large number of samples (ex.