PMID: PMC4184449-1-2

 

    Legend: Gene, Sites

Title : Oxonium Ion Distributions

Abstract :
  1. In order to confirm the ioncom positions from the MS data, we used data-dependent LC–tandemmass spectrometry
  2. Collisional dissociation of glycopeptides leadsto formation of oxonium ions that are useful as features for identifyingglycopeptides in LC–MS/MS chromatograms
  3. We therefore used the absence of oxonium ions to disqualifya precursor ion as glycopeptide
  4. On the basis of this rationale, wecompared the abundances of oxonium ions in extracted ion chromatograms(EICs) of glycopeptides observed using C18-MS/MS versus HILIC-C18-MS/MSdata
  5. Figure 1 compares the HexNAc oxoniumion (m/z 204) EIC with the BPC (basepeak chromatogram) for hemagglutinin
  6. Oxonium ion profiles for therest of the proteins analyzed are presented in Supporting Information Figure S-1
  7. When using HILIC-C18, weobserved that the abundances of the HexNAc (m/z 204) oxonium ion profile were similar to those of theBPC, consistent with the fact that most of the detected ions correspondedto glycopeptides
  8. For the C18 LC–MS experiments, the abundancesof HexNAc oxonium ion were 10-fold lower than the BPC, indicatingthat most of the detected ions corresponded to unglycosylated peptides
  9. Using C18-MS, unmodified peptides were the most abundant ions selectedby the acquisition software for tandem MS based on abundance
  10. By contrast,for HILIC-C18 data, glycopeptides were the most abundant ions presentand were selected automatically for tandem MS. The oxonium ion distributionswere consistent with the results obtained from the LC–MS data,shown in Table 1, indicating the contributionof glycopeptides to total ion abundances in C18 and HILIC-C18 runs
  11. Oxonium ions detectedearly in the chromatogram using HILIC-C18-MSresulted from a small fraction of the enriched glycopeptides fromthe HILIC trapping column getting washed away with the dead volumecontaining high organic mobile phase
  12. This was a fixed and unbiasedloss that accounted for less that 2% of the total sample abundanceand did not affect the relative abundances of the compounds beingretained on the C18 analytical columns
  13. Figure 2 shows the percent of precursorions identified as glycopeptides based on formation of oxonium ionsin data-dependent LC–MS/MS runs using HILIC-C18-MS versus C18-MS
  14. We concluded that use of HILIC-C18-MS resulted in significant increasein the ability to analyze glycopeptides using data-dependent LC–MS/MS
  15. These data demonstrate that the HILIC-C18-MS increased abundancesof glycopeptides relative to unglycosylated peptides and thus thequality of data-dependent LC–tandem MS data
  16. The improved dataquality increased confidence in assignments and decreased false identifications
  17. Two AGP glycopeptides (ENGTISR/ENGTVSRand NEEYNK) were detectedonly using HILIC-C18-MS
  18. This was due to the fact that tryptic cleavageof AGP produces glycopeptides that are only 5–7 amino acidslong and are not retained during the trapping step when using C18-MS
  19. These glycopeptides were trapped on the HILIC enrichment column whenusing HILIC-C18-MS and eluted soon after the solvent front on theanalytical chromatogram, as seen in SupportingInformation Figure S-1(b), which allowed them to undergo MSand MS/MS analysis
  20. The C18 trapping step can be eliminated to retainany shorter glycopeptides in a sample
  21. However, in our experience,an online trapping step is a useful means to eliminate salts and othercontaminants while minimizing manual manipulation
Output (sent_index, trigger, protein, sugar, site):
  • 10. glycopeptides, , -, -, glycopeptides
  • 11. glycopeptides, , -, -, glycopeptides
  • 13. glycopeptides, , -, -, glycopeptides
  • 14. glycopeptides, , -, -, glycopeptides
  • 15. glycopeptides, , -, -, glycopeptides
  • 15. unglycosylated, , -, -, peptides
  • 17. glycopeptides, , -, -, glycopeptides
  • 18. glycopeptides, , -, -, glycopeptides
  • 19. glycopeptides, , -, -, glycopeptides
  • 2. glycopeptides, , -, -, glycopeptides
  • 2. identifyingglycopeptides, , -, -, identifyingglycopeptides
  • 20. glycopeptides, , -, -, glycopeptides
  • 3. glycopeptide, , -, -, glycopeptide
  • 4. glycopeptides, , -, -, glycopeptides
  • 7. glycopeptides, , -, -, glycopeptides
  • 8. unglycosylated, , -, -, peptides
Output(Part-Of) (sent_index, protein, site):
*Output_Site_Fusion* (sent_index, protein, sugar, site):

 

 

Protein NCBI ID SENTENCE INDEX