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Published on: August 18, 2017
Improved spectra for MALDI MSI of peptides using ammonium phosphate monobasic in MALDI matrix
1School of Medicine, Department of Medical Biochemistry, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey.
Abstract:
MALDI mass spectrometry imaging (MSI) enables analysis of peptides along with histology. However, there are several critical steps in MALDI MSI of peptides, 1 of which is spectral quality. Suppression of MALDI matrix clusters by the aid of ammonium salts in MALDI experiments is well known. It is asserted that addition of ammonium salts dissociates potential matrix adducts and thereafter decreases matrix cluster formation. Consequently, MALDI MS sensitivity and mass accuracy increase. Up to our knowledge, a limited number of MALDI MSI studies used ammonium salts as matrix additives to suppress matrix clusters and enhance peptide signals. In this work, we investigated the effect of ammonium phosphate monobasic (AmP) as alpha-cyano-4-hydroxycinnamic acid (α-CHCA) matrix additive in MALDI MSI of peptides. Prior to MALDI MSI, the effect of varying concentrations of AmP in α-CHCA was assessed in bovine serum albumin tryptic digests and compared with the control (α-CHCA without AmP). Based on our data, the addition of AmP as matrix additive decreased matrix cluster formation regardless of its concentration, and specifically, 8 mM AmP and 10 mM AmP increased bovine serum albumin peptide signal intensities. In MALDI MSI of peptides, both 8 and 10 mM AmP in α-CHCA improved peptide signals especially in the mass range of m/z 2000 to 3000. In particular, 9 peptide signals were found to have differential intensities within the tissues deposited with AmP in α-CHCA (AUC > 0.60). To the best of our knowledge, this is the first MALDI MSI of peptides work investigating different concentrations of AmP as α-CHCA matrix additive to enhance peptide signals in formalin-fixed paraffin-embedded (FFPE) tissues. Further, AmP as part of α-CHCA matrix could enhance protein identifications and support MALDI MSI-based proteomic approaches.
Insights
Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) of peptides benefits from ammonium phosphate monobasic (AmP) as an alpha-cyano-4-hydroxycinnamic acid (α-CHCA) matrix additive. AmP enhances peptide signal intensity and reduces matrix clusters in formalin-fixed paraffin-embedded tissues.
Area of Science:
- Analytical Chemistry
- Biochemistry
- Proteomics
Background:
- MALDI mass spectrometry imaging (MSI) is crucial for analyzing peptides alongside histology.
- Spectral quality is a critical factor in MALDI MSI of peptides.
- Ammonium salts are known to suppress MALDI matrix clusters and improve sensitivity and mass accuracy.
Purpose of the Study:
- To investigate the effect of ammonium phosphate monobasic (AmP) as an alpha-cyano-4-hydroxycinnamic acid (α-CHCA) matrix additive in MALDI MSI of peptides.
- To assess the impact of varying AmP concentrations on peptide signal intensities and matrix cluster formation.
- To evaluate AmP's utility in enhancing peptide identification in formalin-fixed paraffin-embedded (FFPE) tissues.
Main Methods:
- MALDI MSI was performed on bovine serum albumin tryptic digests and FFPE tissues.
- Varying concentrations of AmP were added to the α-CHCA matrix.
- Spectra were analyzed to compare peptide signal intensities and matrix cluster formation with and without AmP.
Main Results:
- Addition of AmP to α-CHCA consistently decreased matrix cluster formation.
- 8 mM and 10 mM AmP significantly increased bovine serum albumin peptide signal intensities.
- In MALDI MSI of peptides, 8 mM and 10 mM AmP in α-CHCA improved peptide signals, particularly in the m/z 2000-3000 range.
- Differential peptide intensities (AUC > 0.60) were observed in tissues treated with AmP.
Conclusions:
- Ammonium phosphate monobasic (AmP) effectively suppresses matrix clusters in MALDI MSI of peptides.
- Optimized concentrations of AmP (8 mM and 10 mM) enhance peptide signal intensities in FFPE tissues.
- AmP as an α-CHCA matrix additive shows promise for improving protein identifications and advancing MALDI MSI-based proteomic approaches.
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