Improvement of performance in label-free quantitative proteome analysis with monolithic electrospray ionization emitter

Enhancing the performance of LC-MS for intact protein analysis by counteracting the signal suppression effects of trifluoroacetic acid during electrospray

We develop an acidic vapor assisted electrospray ionization strategy within an enclosed electrospray ionization source to counteract the ion suppression effects caused by trifluoroacetic acid.

A probabilistic framework for peptide and protein quantification from data-dependent and data-independent LC-MS proteomics experiments

A probability-based quantification framework is presented for the calculation of relative peptide and protein abundance in label-free and label-dependent LC-MS proteomics data. The results are accompanied by credible intervals and regulation probabilities. The algorithm takes into account data uncertainties via Poisson statistics modified by a noise contribution that is determined automatically during an initial normalization stage. Protein quantification relies on assignments of component peptides to the acquired data. These assignments are generally of variable reliability and may not be present across all of the experiments comprising an analysis. It is also possible for a peptide to be identified to more than one protein in a given mixture. For these reasons the algorithm accepts a prior probability of peptide assignment for each intensity measurement. The model is constructed in such a way that outliers of any type can be automatically reweighted. Two discrete normalization methods can be employed. The first method is based on a user-defined subset of peptides, while the second method relies on the presence of a dominant background of endogenous peptides for which the concentration is assumed to be unaffected. Normalization is performed using the same computational and statistical procedures employed by the main quantification algorithm. The performance of the algorithm will be illustrated on example data sets, and its utility demonstrated for typical proteomics applications. The quantification algorithm supports relative protein quantification based on precursor and product ion intensities acquired by means of data-dependent methods, originating from all common isotopically-labeled approaches, as well as label-free ion intensity-based data-independent methods.

Recent advances on multidimensional liquid chromatography-mass spectrometry for proteomics: from qualitative to quantitative analysis--a review

With the acceleration of proteome research, increasing attention has been paid to multidimensional liquid chromatography-mass spectrometry (MDLC-MS) due to its high peak capacity and separation efficiency. Recently, many efforts have been put to improve MDLC-based strategies including "top-down" and "bottom-up" to enable highly sensitive qualitative and quantitative analysis of proteins, as well as accelerate the whole analytical procedure. Integrated platforms with combination of sample pretreatment, multidimensional separations and identification were also developed to achieve high throughput and sensitive detection of proteomes, facilitating highly accurate and reproducible quantification. This review summarized the recent advances of such techniques and their applications in qualitative and quantitative analysis of proteomes.

Quantitative serum proteomics using dual stable isotope coding and nano LC-MS/MSMS

Stable isotope coding technique in combination with mass spectrometry has emerged as a powerful tool to accurately identify and differentially quantify proteins within complex protein mixtures. We present a novel methodology to increase the yield of quantified proteins while maintaining a high stable-isotopic labeling efficacy. With this approach, intact proteins in complex biological sample such as sera are labeled with the designated dual stable isotope coding (DSIC) systems. In brief, intact proteins are coded sequentially with acrylamide to label Cysteine residues (Cys) and with succinic anhydride to label Lysine residues (Lys). Protein samples coded with this dual stable isotope are subjected to an online 2D-HPLC fractionation. The resolved protein fractions are individually digested with trypsin and analyzed with nano LC-MS/MSMS. Our results show that the DSIC labeling efficiency is 100% for Cysteine (Cys) labeled with acrylamide and 98% for Lysine (Lys) labeled with succinic anhydride. A comparative analysis of DSIC labeling and single labeling of Cysteine residues was made. Analysis of an entire anion-exchange chromatography subfraction of sera yielded 165 identified proteins (criteria: error rate <5% and unique peptides >or=2), 104 of which were quantified using the single labeling method (i.e., Cysteine acrylamide labeling only). In contrast, using same criteria for identification, a total 185 proteins were identified and 174 proteins were quantified using the DSIC labeling technique.

"One-pot" process for fabrication of organic-silica hybrid monolithic capillary columns using organic monomer and alkoxysilane

A "one-pot" process for the preparation of organic-silica hybrid capillary monolithic columns by concurrently using organic monomers and alkoxysilanes was described. In this process, the hydrolyzed alkoxysilanes of tetramethoxysilane (TMOS) and vinyltrimethoxysilane (VTMS) as precursors for the synthesis of a silica-based monolith using the sol-gel method and the organic monomer (allyldimethyldodecylammonium bromide (ADDAB) or acrylamide (AA)) with vinyl groups for free radical polymerization along with the initiator of azobisisobutyronitrile (AIBN) were concurrently introduced into a pretreated capillary; after that, the polycondensation of alkoxysilanes and the copolymerization of organic monomers and as-precondensed siloxanes were subsequently carried out within the confines of a capillary at the proper reaction conditions. Two types of organic-silica hybrid capillary monolithic columns with hydrophobic and hydrophilic properties have been fabricated, respectively, by this "one-pot" process using two different organic monomers of ADDAB and AA. The morphologies of the synthesized organic-silica hybrid monolithic columns were characterized by scanning electron microscopy (SEM). The performances of these organic-silica monolithic columns were investigated by capillary electrochromatography (CEC). The retention behaviors of the neutral and polar compounds on the resulting hydrophobic and hydrophilic organic-silica hybrid monolithic columns confirmed the successful incorporation of organic monomers in the silica monolithic matrix. In addition, the ADDA-silica hybrid capillary monolithic column was also applied in the analysis of tryptic digests of bovine serum albumin (BSA) and mouse liver extract by microliquid chromatography-tandem mass spectrometry (microLC-MS/MS) for demonstrating its potential in proteome analysis.