Automation of dimethylation after guanidination labeling chemistry and its compatibility with common buffers and surfactants for mass spectrometry-based shotgun quantitative proteome analysis

Recent advances in robotic protein sample preparation for clinical analysis and other biomedical applications

Discovery of new protein biomarker candidates has become a major research goal in the areas of clinical chemistry, analytical chemistry, and biomedicine. These important species constitute the molecular target when it comes to diagnosis, prognosis, and further monitoring of disease. However, their analysis requires powerful, selective and high-throughput sample preparation and product (analyte) characterisation approaches. In general, manual sample processing is tedious, complex and time-consuming, especially when large numbers of samples have to be processed (e.g., in clinical studies). Automation via microtiter-plate platforms involving robotics has brought improvements in high-throughput performance while comparable or even better precisions and repeatability (intra-day, inter-day) were achieved. At the same time, waste production and exposure of laboratory personnel to hazards were reduced. In comprehensive protein analysis workflows (e.g., liquid chromatography-tandem mass spectrometry analysis), sample preparation is an unavoidable step. This review surveys the recent achievements in automation of bottom-up and top-down protein and/or proteomics approaches. Emphasis is put on high-end multi-well plate robotic platforms developed for clinical analysis and other biomedical applications. The literature from 2013 to date has been covered.

An integrated sample pretreatment platform for quantitative N-glycoproteome analysis with combination of on-line glycopeptide enrichment, deglycosylation and dimethyl labeling

Relative quantification of N-glycoproteomes shows great promise for the discovery of candidate biomarkers and therapeutic targets. The traditional protocol for quantitative analysis of glycoproteomes is usually off-line performed, and suffers from long sample preparation time, and the risk of sample loss or contamination due to manual manipulation. In this study, a novel integrated sample preparation platform for quantitative N-glycoproteome analysis was established, with combination of online N-glycopeptide capture by a HILIC column, sample buffer exchange by a N2-assisted HILIC-RPLC interface, deglycosylation by a hydrophilic PNGase F immobilized enzymatic reactor (hIMER) and solid dimethyl labeling on a C18 precolumn. To evaluate the performance of such a platform, two equal aliquots of immunoglobulin G (IgG) digests were sequentially pretreated, followed by MALDI-TOF MS analysis. The signal intensity ratio of heavy/light (H/L) labeled deglycosylated peptides with the equal aliquots was 1.00 (RSD=6.2%, n=3), much better than those obtained by the offline protocol, with H/L ratio as 0.76 (RSD=11.6%, n=3). Additionally, the total on-line sample preparation time was greatly shortened to 160 min, much faster than that of offline approach (24h). Furthermore, such an integrated pretreatment platform was successfully applied to analyze the two kinds of hepatocarcinoma ascites syngeneic cell lines with high (Hca-F) and low (Hca-P) lymph node metastasis rates. For H/L labeled Hca-P lysates with the equal aliquots, 99.6% of log2 ratios (H/L) of quantified glycopeptides ranged from -1 to 1, demonstrating high accuracy of the developed sample preparation strategy. By triplicated analysis of glycopeptides and non-glycopeptides of Hca-F and Hca-P lysates, 43 up-regulated and 30 down-regulated (Hca-F/P) N-glycosylation sites, and 11 significantly changed N-glycoproteins were successfully quantified, and most of them were related to tumorigenesis and tumor metastasis. All these results demonstrate the developed integrated N-glycoprotein pretreatment platform is of great power for the accurate, precise and high-throughput analysis of N-glycoproteomes.

Comparative proteomic and metabolomic analysis of Staphylococcus warneri SG1 cultured in the presence and absence of butanol

The complete genome of the solvent tolerant Staphylococcus warneri SG1 was recently published. This Gram-positive bacterium is tolerant to a large spectrum of organic solvents including short-chain alcohols, alkanes, esters and cyclic aromatic compounds. In this study, we applied a two-dimensional liquid chromatography (2D-LC) mass spectrometry (MS) shotgun approach, in combination with quantitative 2-MEGA (dimethylation after guanidination) isotopic labeling, to compare the proteomes of SG1 grown under butanol-free and butanol-challenged conditions. In total, 1585 unique proteins (representing 65% of the predicted open reading frames) were identified, covering all major metabolic pathways. Of the 967 quantifiable proteins by 2-MEGA labeling, 260 were differentially expressed by at least 1.5-fold. These proteins are involved in energy metabolism, oxidative stress response, lipid and cell envelope biogenesis, or have chaperone functions. We also applied differential isotope labeling LC-MS to probe metabolite changes in key metabolic pathways upon butanol stress. This is the first comprehensive proteomic and metabolomic study of S. warneri SG1 and presents an important step toward understanding its physiology and mechanism of solvent tolerance.