Improved Titanium Dioxide Enrichment of Phosphopeptides from HeLa Cells and High Confident Phosphopeptide Identification by Cross-Validation of MS/MS and MS/MS/MS Spectra

Enrichment is essential for phosphoproteome analysis because phosphorylated proteins are usually present in cells in low abundance. Recently, titanium dioxide (TiO2) has been demonstrated to enrich phosphopeptides from simple peptide mixtures with high specificity; however, the technology has not been optimized. In the present study, significant non-specific bindings were observed when proteome samples were applied to TiO2 columns. Column wash with an NH4Glu solution after loading peptide mixtures significantly increased the efficiency of TiO2 phosphopeptide enrichment with a recovery of up to 84%. Also, for proteome samples, more than a 2-fold increase in unique phosphopeptide identifications has been achieved. The use of NH4Glu for a TiO2 column wash does not significantly reduce the phosphopeptide recovery. A total of 858 phosphopeptides corresponding to 1034 distinct phosphosites has been identified from HeLa cells using the improved TiO2 enrichment procedure in combination with data-dependent neutral loss nano-RPLC-MS2-MS3 analysis. While 41 and 35% of the phosphopeptides were identified only by MS2 and MS3, respectively, 24% was identified by both MS2 and MS3. Cross-validation of the phosphopeptide assignment by MS2 and MS3 scans resulted in the highest confidence in identification (99.5%). Many phosphosites identified in this study appear to be novel, including sites from antigen Ki-67, nucleolar phosphoprotein p130, and Treacle protein. The study also indicates that evaluation of confidence levels for phosphopeptide identification via the reversed sequence database searching strategy might underestimate the false positive rate. Keywords: Phosphoproteomics • titanium dioxide • phosphopeptide enrichment • HeLa cells • tandem mass spectrometry • neutral loss sca

Improved Titanium Dioxide Enrichment of Phosphopeptides from HeLa Cells and High Confident Phosphopeptide Identification by Cross-Validation of MS/MS and MS/MS/MS Spectra

Enrichment is essential for phosphoproteome analysis because phosphorylated proteins are usually present in cells in low abundance. Recently, titanium dioxide (TiO2) has been demonstrated to enrich phosphopeptides from simple peptide mixtures with high specificity; however, the technology has not been optimized. In the present study, significant non-specific bindings were observed when proteome samples were applied to TiO2 columns. Column wash with an NH4Glu solution after loading peptide mixtures significantly increased the efficiency of TiO2 phosphopeptide enrichment with a recovery of up to 84%. Also, for proteome samples, more than a 2-fold increase in unique phosphopeptide identifications has been achieved. The use of NH4Glu for a TiO2 column wash does not significantly reduce the phosphopeptide recovery. A total of 858 phosphopeptides corresponding to 1034 distinct phosphosites has been identified from HeLa cells using the improved TiO2 enrichment procedure in combination with data-dependent neutral loss nano-RPLC-MS2-MS3 analysis. While 41 and 35% of the phosphopeptides were identified only by MS2 and MS3, respectively, 24% was identified by both MS2 and MS3. Cross-validation of the phosphopeptide assignment by MS2 and MS3 scans resulted in the highest confidence in identification (99.5%). Many phosphosites identified in this study appear to be novel, including sites from antigen Ki-67, nucleolar phosphoprotein p130, and Treacle protein. The study also indicates that evaluation of confidence levels for phosphopeptide identification via the reversed sequence database searching strategy might underestimate the false positive rate. Keywords: Phosphoproteomics • titanium dioxide • phosphopeptide enrichment • HeLa cells • tandem mass spectrometry • neutral loss sca

Improved Titanium Dioxide Enrichment of Phosphopeptides from HeLa Cells and High Confident Phosphopeptide Identification by Cross-Validation of MS/MS and MS/MS/MS Spectra

Enrichment is essential for phosphoproteome analysis because phosphorylated proteins are usually present in cells in low abundance. Recently, titanium dioxide (TiO2) has been demonstrated to enrich phosphopeptides from simple peptide mixtures with high specificity; however, the technology has not been optimized. In the present study, significant non-specific bindings were observed when proteome samples were applied to TiO2 columns. Column wash with an NH4Glu solution after loading peptide mixtures significantly increased the efficiency of TiO2 phosphopeptide enrichment with a recovery of up to 84%. Also, for proteome samples, more than a 2-fold increase in unique phosphopeptide identifications has been achieved. The use of NH4Glu for a TiO2 column wash does not significantly reduce the phosphopeptide recovery. A total of 858 phosphopeptides corresponding to 1034 distinct phosphosites has been identified from HeLa cells using the improved TiO2 enrichment procedure in combination with data-dependent neutral loss nano-RPLC-MS2-MS3 analysis. While 41 and 35% of the phosphopeptides were identified only by MS2 and MS3, respectively, 24% was identified by both MS2 and MS3. Cross-validation of the phosphopeptide assignment by MS2 and MS3 scans resulted in the highest confidence in identification (99.5%). Many phosphosites identified in this study appear to be novel, including sites from antigen Ki-67, nucleolar phosphoprotein p130, and Treacle protein. The study also indicates that evaluation of confidence levels for phosphopeptide identification via the reversed sequence database searching strategy might underestimate the false positive rate. Keywords: Phosphoproteomics • titanium dioxide • phosphopeptide enrichment • HeLa cells • tandem mass spectrometry • neutral loss sca

Identification of the SELDI ProteinChip Human Serum Retentate by Microcapillary Liquid Chromatography-Tandem Mass Spectrometry

Surface-enhanced laser desorption/ionization (SELDI) time-of-flight (TOF) mass spectrometry (MS) has been widely applied for conducting biomarker research with the goal of discovering patterns of proteins and/or peptides from biological samples that reflect disease status. Many diseases, ranging from cancers of the colon, breast, and prostate to Alzheimer's disease, have been studied through serum protein profiling using SELDI-based methods. Although the results from SELDI-based diagnostic studies have generated a great deal of excitement and skepticism alike, the basis of the molecular identities of the features that underpin the diagnostic potential of the mass spectra is still largely unexplored. A detailed investigation has been undertaken to identify the compliment of serum proteins that bind to the commonly used weak cation exchange (WCX-2) SELDI protein chip. Following incubation and washing of a standard serum sample on the WCX-2 sorbent, proteins were harvested, digested with trypsin, fractionated by strong cation exchange liquid chromatography (LC), and subsequently analyzed by microcapillary reversed-phase LC coupled online with an ion-trap mass spectrometer. This analysis resulted in the identification of 383 unique proteins in the WCX-2 serum retentate. Among the proteins identified, 50 (13%) are documented clinical biomarkers with 36 of these (72%) identified from multiple peptides. Keywords: SELDI • biomarker • serum proteomics • multidimensional fractionation • mass spectrometr

Identification of the SELDI ProteinChip Human Serum Retentate by Microcapillary Liquid Chromatography-Tandem Mass Spectrometry

Surface-enhanced laser desorption/ionization (SELDI) time-of-flight (TOF) mass spectrometry (MS) has been widely applied for conducting biomarker research with the goal of discovering patterns of proteins and/or peptides from biological samples that reflect disease status. Many diseases, ranging from cancers of the colon, breast, and prostate to Alzheimer's disease, have been studied through serum protein profiling using SELDI-based methods. Although the results from SELDI-based diagnostic studies have generated a great deal of excitement and skepticism alike, the basis of the molecular identities of the features that underpin the diagnostic potential of the mass spectra is still largely unexplored. A detailed investigation has been undertaken to identify the compliment of serum proteins that bind to the commonly used weak cation exchange (WCX-2) SELDI protein chip. Following incubation and washing of a standard serum sample on the WCX-2 sorbent, proteins were harvested, digested with trypsin, fractionated by strong cation exchange liquid chromatography (LC), and subsequently analyzed by microcapillary reversed-phase LC coupled online with an ion-trap mass spectrometer. This analysis resulted in the identification of 383 unique proteins in the WCX-2 serum retentate. Among the proteins identified, 50 (13%) are documented clinical biomarkers with 36 of these (72%) identified from multiple peptides. Keywords: SELDI • biomarker • serum proteomics • multidimensional fractionation • mass spectrometr

Investigation of the Mouse Serum Proteome

With the rapid assimilation of genomic information and the equally impressive developments in the field of proteomics, there is an unprecedented interest in biomarker discovery. Although human biofluids represent increasingly attractive samples from which new and more accurate disease biomarkers may be found, the intrinsic person-to-person variability in these samples complicates their discovery. One of the most extensively used animal models for studying human disease is mouse because, unlike humans, they represent a highly controllable experimental model system. Unfortunately, very little is known about the proteomic composition of mouse serum. In this study, a multidimensional fractionation approach on both the protein and the peptide level that does not require depletion of highly abundant serum proteins was combined with tandem mass spectrometry to characterize proteins within mouse serum. Over 12 300 unique peptides that originate from 4567 unique proteinsapproximately 16% of all known mouse proteinswere identified. The results presented here represent the broadest proteome coverage in mouse serum and provide a foundation from which quantitative comparisons can be made in this important animal model. Keywords: mouse • serum proteomics • multidimensional fractionation • tandem mass spectrometr

Optimized Method for Computing ¹⁸O/¹⁶O Ratios of Differentially Stable-Isotope Labeled Peptides in the Context of Postdigestion ¹⁸O Exchange/Labeling

Differential 18O/16O stable isotope labeling of peptides that relies on enzyme-catalyzed oxygen exchange at their carboxyl termini in the presence of H218O has been widely used for relative quantitation of peptides/proteins. The role of tryptic proteolysis in bottom-up shotgun proteomics and low reagent costs have made trypsin-catalyzed 18O postdigestion exchange a convenient and affordable stable isotope labeling approach. However, it is known that trypsin-catalyzed 18O exchange at the carboxyl terminus is in many instances inhomogeneous/incomplete. The extent of the 18O exchange/incorporation fluctuates from peptide to peptide mostly due to variable enzyme−substrate affinity. Thus, accurate calculation and interpretation of peptide ratios are analytically complicated and in some regard deficient. Therefore, a computational approach capable of improved measurement of actual 18O incorporation for each differentially labeled peptide pair is needed. In this regard, we have developed an algorithmic method that relies on the trapezoidal rule to integrate peak intensities of all detected isotopic species across a particular peptide ion over the retention time, which fits the isotopic manifold to Poisson distributions. Optimal values for manifold fitting were calculated and then 18O/16O ratios derived via evolutionary programming. The algorithm is tested using trypsin-catalyzed 18O postdigestion exchange to differentially label bovine serum albumin (BSA) at a priori determined ratios. Both accuracy and precision are improved utilizing this rigorous mathematical approach. We further demonstrate the effectiveness of this method to accurately calculate 18O/16O ratios in a large scale proteomic quantitation of detergent resistant membrane microdomains (DRMMs) isolated from cells expressing wild-type HIV-1 Gag and its nonmyristylated mutant

Optimized Method for Computing ¹⁸O/¹⁶O Ratios of Differentially Stable-Isotope Labeled Peptides in the Context of Postdigestion ¹⁸O Exchange/Labeling

Differential 18O/16O stable isotope labeling of peptides that relies on enzyme-catalyzed oxygen exchange at their carboxyl termini in the presence of H218O has been widely used for relative quantitation of peptides/proteins. The role of tryptic proteolysis in bottom-up shotgun proteomics and low reagent costs have made trypsin-catalyzed 18O postdigestion exchange a convenient and affordable stable isotope labeling approach. However, it is known that trypsin-catalyzed 18O exchange at the carboxyl terminus is in many instances inhomogeneous/incomplete. The extent of the 18O exchange/incorporation fluctuates from peptide to peptide mostly due to variable enzyme−substrate affinity. Thus, accurate calculation and interpretation of peptide ratios are analytically complicated and in some regard deficient. Therefore, a computational approach capable of improved measurement of actual 18O incorporation for each differentially labeled peptide pair is needed. In this regard, we have developed an algorithmic method that relies on the trapezoidal rule to integrate peak intensities of all detected isotopic species across a particular peptide ion over the retention time, which fits the isotopic manifold to Poisson distributions. Optimal values for manifold fitting were calculated and then 18O/16O ratios derived via evolutionary programming. The algorithm is tested using trypsin-catalyzed 18O postdigestion exchange to differentially label bovine serum albumin (BSA) at a priori determined ratios. Both accuracy and precision are improved utilizing this rigorous mathematical approach. We further demonstrate the effectiveness of this method to accurately calculate 18O/16O ratios in a large scale proteomic quantitation of detergent resistant membrane microdomains (DRMMs) isolated from cells expressing wild-type HIV-1 Gag and its nonmyristylated mutant

Optimized Method for Computing ¹⁸O/¹⁶O Ratios of Differentially Stable-Isotope Labeled Peptides in the Context of Postdigestion ¹⁸O Exchange/Labeling

Differential 18O/16O stable isotope labeling of peptides that relies on enzyme-catalyzed oxygen exchange at their carboxyl termini in the presence of H218O has been widely used for relative quantitation of peptides/proteins. The role of tryptic proteolysis in bottom-up shotgun proteomics and low reagent costs have made trypsin-catalyzed 18O postdigestion exchange a convenient and affordable stable isotope labeling approach. However, it is known that trypsin-catalyzed 18O exchange at the carboxyl terminus is in many instances inhomogeneous/incomplete. The extent of the 18O exchange/incorporation fluctuates from peptide to peptide mostly due to variable enzyme−substrate affinity. Thus, accurate calculation and interpretation of peptide ratios are analytically complicated and in some regard deficient. Therefore, a computational approach capable of improved measurement of actual 18O incorporation for each differentially labeled peptide pair is needed. In this regard, we have developed an algorithmic method that relies on the trapezoidal rule to integrate peak intensities of all detected isotopic species across a particular peptide ion over the retention time, which fits the isotopic manifold to Poisson distributions. Optimal values for manifold fitting were calculated and then 18O/16O ratios derived via evolutionary programming. The algorithm is tested using trypsin-catalyzed 18O postdigestion exchange to differentially label bovine serum albumin (BSA) at a priori determined ratios. Both accuracy and precision are improved utilizing this rigorous mathematical approach. We further demonstrate the effectiveness of this method to accurately calculate 18O/16O ratios in a large scale proteomic quantitation of detergent resistant membrane microdomains (DRMMs) isolated from cells expressing wild-type HIV-1 Gag and its nonmyristylated mutant

Investigation of the Mouse Serum Proteome

With the rapid assimilation of genomic information and the equally impressive developments in the field of proteomics, there is an unprecedented interest in biomarker discovery. Although human biofluids represent increasingly attractive samples from which new and more accurate disease biomarkers may be found, the intrinsic person-to-person variability in these samples complicates their discovery. One of the most extensively used animal models for studying human disease is mouse because, unlike humans, they represent a highly controllable experimental model system. Unfortunately, very little is known about the proteomic composition of mouse serum. In this study, a multidimensional fractionation approach on both the protein and the peptide level that does not require depletion of highly abundant serum proteins was combined with tandem mass spectrometry to characterize proteins within mouse serum. Over 12 300 unique peptides that originate from 4567 unique proteinsapproximately 16% of all known mouse proteinswere identified. The results presented here represent the broadest proteome coverage in mouse serum and provide a foundation from which quantitative comparisons can be made in this important animal model. Keywords: mouse • serum proteomics • multidimensional fractionation • tandem mass spectrometr