Retention Time Prediction for Glycopeptides in Reversed-Phase Chromatography for Glycoproteomic Applications.

The sequence-specific retention calculator algorithm (SSRCalc) [ Krokhin , O. V. Anal. Chem. 2006 , 78 , 7785 ] was adapted for the prediction of retention times of N-glycopeptides separated by reversed-phase high performance liquid chromatography (RPLC). The retention time shifts (dHI = HIglyco - HIdeglyco, where HI is the hydrophobicity index, measured in percent acetonitrile units) used for modeling were measured for 602 glycopeptides versus 123 of their deglycosylated analogues. Our method used a tryptic digest of 12 purified glycoproteins, glycopeptide enrichment, deglycosylation with PNGaseF, and RPLC-MS/MS analysis of combined (deglycosylated and intact) peptide mixtures. On average, glycosylation yields a 0.79% acetonitrile unit decrease in retention, compared with the hydrophobicity indices of their deglycosylated analogues. These values, however, are drastically different for asialo (-1.37% acetonitrile units), monosialylated (-0.47% acetonitrile units), disialylated (+0.61% acetonitrile units), and trisialylated (+1.94% acetonitrile units) glycans. Peptide retention time shifts upon glycosylation (dHI) vary depending on the number of monosaccharide units, the presence or absence of sialic acid, peptide hydrophobicity, and the number of position-dependent features. These features are mostly driven by competing effects of acidic residues (aspartic acid and sialic acid) on ion-pair formation and by nearest-neighbor effects of hydrophilic glycans. The accuracy of the modified prediction model for glycopeptides approaches that of the prediction for nonmodified species (R2 = 0.97 vs 0.98). However, retention time prediction based on the experimental retention values of deglycosylated analogues (HIglyco = HIdeglyco + dHI, R2 = 0.995) is much more accurate, thus providing a solid support for glycopeptide identification in complex samples based on mass and retention time.

Sequence-Specific Model for Peptide Retention Time Prediction in Strong Cation Exchange Chromatography.

The development of a peptide retention prediction model for strong cation exchange (SCX) separation on a Polysulfoethyl A column is reported. Off-line 2D LC-MS/MS analysis (SCX-RPLC) of S. cerevisiae whole cell lysate was used to generate a retention dataset of ∼30 000 peptides, sufficient for identifying the major sequence-specific features of peptide retention mechanisms in SCX. In contrast to RPLC/hydrophilic interaction liquid chromatography (HILIC) separation modes, where retention is driven by hydrophobic/hydrophilic contributions of all individual residues, SCX interactions depend mainly on peptide charge (number of basic residues at acidic pH) and size. An additive model (incorporating the contributions of all 20 residues into the peptide retention) combined with a peptide length correction produces a 0.976 R2 value prediction accuracy, significantly higher than the additive models for either HILIC or RPLC. Position-dependent effects on peptide retention for different residues were driven by the spatial orientation of tryptic peptides upon interaction with the negatively charged surface functional groups. The positively charged N-termini serve as a primary point of interaction. For example, basic residues (Arg, His, Lys) increase peptide retention when located closer to the N-terminus. We also found that hydrophobic interactions, which could lead to a mixed-mode separation mechanism, are largely suppressed at 20-30% of acetonitrile in the eluent. The accuracy of the final Sequence-Specific Retention Calculator (SSRCalc) SCX model (∼0.99 R2 value) exceeds all previously reported predictors for peptide LC separations. This also provides a solid platform for method development in 2D LC-MS protocols in proteomics and peptide retention prediction filtering of false positive identifications.

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 MS(2) 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.

Retention time prediction for post-translationally modified peptides: Ser, Thr, Tyr-phosphorylation.

The development of a peptide retention prediction model for reversed-phase chromatography applications in proteomics is reported for peptides carrying phosphorylated Ser, Thr and Tyr-residues. The major retention features have been assessed using a collection of over 10,000 phosphorylated/non-phosphorylated peptide pairs identified in a series 1D and 2D LC-MS/MS acquisitions using formic acid as ion pairing modifier. Single modification event on average results in increased peptide retention for phosphorylation of Ser (+ 1.46), Thr (+1.33), Tyr (+0.93% acetonitrile, ACN) on gradient elution scale for Luna C18(2) stationary phase. We established several composition and sequence specific features, which drive deviations from these average values. Thus, single phosphorylation of serine results in retention shifts ranging from -2.4 to 5.5% ACN depending on position of the residue, nature of nearest neighbour residues, peptide length, hydrophobicity and pI value, and its propensity to form amphipathic helical structures. We established that the altered ion-pairing environment upon phosphorylation is detrimental for this variability. Hydrophobicity of ion-pairing modifier directly informs the magnitude of expected shifts: (most hydrophilic) 0.5 % acetic acid (larger positive shift upon phosphorylation) > 0.1 % formic acid (positive) > 0.1 % trifluoroacetic (negative) > 0.1 % heptafluorobutyric acid (larger negative shift). The effect of phosphorylation has been also evaluated for several separation conditions used in the first dimension of 2D LC applications: high pH reversed-phase (RP), hydrophilic interaction liquid chromatography (HILIC), strong cation- and strong anion exchange separations.