| Autor: |
Hebert, Nicole, McKay, Matthew, Yang, Mark, Van Soest, Remco, Settineri, Tina, Molloy, Mark P., Krisp, Christoph |
| Jazyk: |
angličtina |
| Rok vydání: |
2014 |
| Předmět: |
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| Popis: |
Strong cation exchange (SCX) chromatography of tryptic peptides is commonly applied in the proteomic field to overcome limitations in mass spectrometry (MS) based peptide detection due to high sample complexity. One of the most well-established approaches is to use multi-dimensional Protein Identification Technology (MudPIT), which couples SCX with reverse phase (RP) chromatography in an online workflow. Our current research aims to develop a MudPIT-based chip trapping system that would be appropriate for plasma-based biomarker detection. The MudPIT trap chip consists of two C18 RP phases and one SCX phase. The first RP phase is used for sample desalting. This phase is followed by the SCX phase for charge-based separation of the peptides. The second RP phase is used to retain peptides elution from the SCX phase. Each sample or salt elution step was followed by an acetonitrile gradient to transfer peptides either from the first RP phase to the SCX resin or elute peptides from the second RP phase for analytical separation on a 15 cm, 75 μm iD C18 RP chip column and SRM-MS on a 4000 QTrap mass spectrometer. The use of the MudPIT peptide trapping strategy reduces the complexity in each elution fraction which benefits peptide ionization and reduces ion suppression. This will enable precise and multiplexed detection of less abundant biomarker proteins that will be of interest for clinical applications. MudCHiP column applicability to discovery applications was assessed using a 5600 TripleTOF mass spectrometer. We tested up to 10 μg loads of tryptic peptides from cell lysates and plasma samples and achieved 4-fold increases in peptide spectra identification and a more than 2-fold increase in protein identification compared with conventional methods. Thus, the MudCHiP columns demonstrate applicability to both targeted and discovery proteomics with great advantages over conventionally used strategies. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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