Peptide retention time prediction for immobilized artificial membrane phosphatidylcholine stationary phase: method development and preliminary observations

Development of the first peptide retention prediction model for immobilized artificial membrane phosphatidylcholine (IAM.PC) stationary phase is reported. 2D liquid chromatography coupled to tandem mass spectrometry (2D LC-MS/MS) analysis of a whole cell lysate of S. cerevisiae yielded a retention dataset of ~29,500 tryptic peptides; sufficient for confident assignment of retention coefficients which determine the contribution of individual amino acids in peptide retention. Retention data from the first dimension was used for the modelling: an IAM.PC.DD2 column, with pH 7.4 ammonium bicarbonate, and a water/acetonitrile gradient. Peptide separation using the IAM.PC.DD2 phase was compared to a standard C18 phase (Luna C18(2)). There was a significant reduction in peptide retention (~14 % acetonitrile on average), indicating that the phosphatidylcholine stationary phase is significantly more hydrophilic. In comparison to the C18 phase, a substantial increase was found in the relative retention contribution for the positively charged Arg and Lys, and the aromatic Tyr, Trp and His residues. A decrease in retention contribution was observed for the negatively charged Asp and Glu. This indicates an involvement of electrostatic interactions with the glycerophosphate functional groups, and possibly, delocalization effects from hydrogen bonds between the phosphate group and the aromatic side chains in the separation mechanism

Characterization of Whole and Fragmented Wild-Type Porcine IgG

Glycoproteomic analyses of tryptic (glyco)peptides from wild-type (WT) porcine IgG were performed. In a first protocol, intact antibody was digested with trypsin, followed by glycopeptide enrichment and liquid chromatography-tandem MS (HPLC–MS/MS). This procedure allowed to detect N-glycopeptides observed previously (Lopez, P. G. et al., Glycoconj. J. 2016, 33 (1), 79), plus other non-reported N-glycopeptides. The method provided useful information but did not allow to discern between Fab (antigen-binding region) and Fc (constant region, fragment crystallizable) peptides/glycopeptides. In a second scheme, glycoproteomic analysis was attempted for Fab and Fc fragments obtained by papain and Fabulous™ hydrolysis. Usually employed for milligram amounts of antibodies, the papain and Fabulous™ protocols were adapted to 200 μg of WT IgG. Fab and Fc fragments were separated by size-exclusion (SEC) HPLC. Fractions collected were reanalyzed by gel electrophoresis (SDS-PAGE). Bands were excised, and fragments digested in-gel, followed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS and HPLC/MS–MS. In the protocol no glycopeptide enrichment was involved, that is, whole tryptic digests were analyzed. Fc N-glycopeptides were identified, and greater numbers of non-glycosylated peptides were tabulated. Very few peptides overlapped between Fc and Fab, as most peptides were clearly from Fc or Fab. HPLC-MS/MS detected more sialylated glycoforms than MALDI-TOF-MS. Sections of Fab and Fc were assigned de novo, through a database search or manually

3D HPLC-MS with Reversed-Phase Separation Functionality in All Three Dimensions for Large-Scale Bottom-Up Proteomics and Peptide Retention Data Collection

The growing complexity of proteomics samples and the desire for deeper analysis drive the development of both better MS instrument and advanced multidimensional separation schemes. We applied 1D, 2D, and 3D LC-MS/MS separation protocols (all of reversed-phase C18 functionality) to a tryptic digest of whole Jurkat cell lysate to estimate the depth of proteome coverage and to collect high-quality peptide retention information. We varied pH of the eluent and hydrophobicity of ion-pairing modifier to achieve good separation orthogonality (utilization of MS instrument time). All separation modes employed identical LC settings with formic-acid-based eluents in the last dimension. The 2D protocol used a high pH–low pH scheme with 21 concatenated fractions. In the 3D protocol, six concatenated fractions from the first dimension (C18, heptafluorobutyric acid) were analyzed using the identical 2D LC-MS procedure. This approach permitted a detailed evaluation of the analysis output consuming 21× and 126× the analysis time and sample load compared to 1D. Acquisition over 189 h of instrument time in 3D mode resulted in the identification of ∼14 000 proteins and ∼250 000 unique peptides. We estimated the dynamic range via peak intensity at the MS² level as approximately 10^4.2, 10^5.6, and 10^6.2 for the 1D, 2D, and 3D protocols, respectively. The uniform distribution of the number of acquired MS/MS, protein, and peptide identifications across all 126 fractions and through the chromatographic time scale in the last LC-MS stage indicates good separation orthogonality. The protocol is scalable and is amenable to the use of peptide retention prediction in all dimensions. All these features make it a very good candidate for large-scale bottom-up proteomic runs, which target both protein identification as well as the collection of peptide retention data sets for targeted quantitative applications