Jennifer Van Eyk (Presenter)
Cedars Sinai Medical Center
Bio: Dr. Van Eyk is a Professor of Medicine at Cedars-Sinai Medical Center, Director of the Basic Science Research in the Barbra Streisand Woman"s Hearth Center and Director of the Advance Clinical Biosystems Institute. Dr. Van Eyk"s lab specializes in developing robust technological pipelines to precisely quantify proteins, isoform and their post-translational modifications (PTM) in disease pathways. This includes understanding interplay between competing PTMs like O-GlcNAc and phosphorylation and multiple oxidative modifications. Her group uses automation in sample preparation to allow for high-throughput and robust MS analysis, which includes discovery and the novel approach, SWATH (DIA) that allows complete and reproducible analysis of 1000s of proteins in 100s of samples. As well, absolute quantification of key targets can be quickly and cost effectively via ultra sensitive ELISA platf
Authorship: Qin Fu1*#, Eric Grote2#, Vidya, Venkatraman, Jie Zhu2, Christine Jelinek2, Anna Köttgen3,4, Josef Coresh3, Jennifer E. Van Eyk1,2
1. Advanced Clinical Biosystems Research Institute, The Heart Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048
| Short Abstract There are many proposed avenues for a seamless transition between biomarker discovery data and selected reaction monitoring (SRM) assays for biomarker validation. Unfortunately, studies with the abundant urinary protein uromodulin and albumin showed that these methods do not converge on a consistent set of surrogate peptides for targeted MS.As an alternative, we present an empirical peptide selection workflow for robust protein quantitation. Comparing the apparent abundance of a plurality of peptides derived from the same target protein makes it possible to select signature peptides that are unaffected by the unpredictable confounding factors that are inevitably present in biological samples. We are developing an algorism to select correlated and quantitive peptides for SRM/MRM analysis. |
Long Abstract
There are many proposed avenues for a seamless transition between biomarker discovery data and selected reaction monitoring (SRM) assays for biomarker validation. Unfortunately, studies with the abundant urinary protein uromodulin showed that these methods do not converge on a consistent set of surrogate peptides for targeted MS. As an alternative, we present an empirical peptide selection workflow for robust protein quantitation. The relative SRM signal intensity of 12 uromodulin-derived peptides was compared between tryptic digests of 9 urine specimens. Pairwise coefficients of variation between the 12 peptides ranged from 0.19 to 0.99. A correlation matrix was utilized to identify peptides that reproducibly track the amount of uromodulin protein. Four peptides with robust and highly-correlated SRM signals were selected. Absolute quantitation was performed using stable-isotope labeled versions of these peptides as internal standards and a standard curve prepared from a tryptic digest of purified uromodulin.
Absolute quantification of uromodulin in 40 clinical urine specimens yielded inter-peptide correlations of ≥0.984 and correlations of ≥0.912 with ELISA data. The SRM assays were linear over >3 orders of magnitude and had typical inter-digest CV"s of <10%, inter-injection CV"s of <7%, and inter-transition CV"s of <7%. Comparing the apparent abundance of a plurality of peptides derived from the same target protein makes it possible to select signature peptides that are unaffected by the unpredictable confounding factors that are inevitably present in biological samples. We are developing an algorism to select correlated and quantitive peptides for SRM/MRM analysis.
References & Acknowledgements:
References
1. Anderson L, Hunter CL. Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins. Molecular & Cellular Proteomics 2006;5:573-88.
2. Grote E, Fu Q, Ji W, Liu X, Van Eyk JE. Using pure protein to build a multiple reaction monitoring mass spectrometry assay for targeted detection and quantitation. Methods in molecular biology 2013;1005:199-213.
3. Liu X, Jin Z, O'Brien R, Bathon J, Dietz HC, Grote E, Van Eyk JE. Constrained selected reaction monitoring: Quantification of selected post-translational modifications and protein isoforms. Methods 2013;61:304-12.
4. Grant RP, Hoofnagle AN. From lost in translation to paradise found: Enabling protein biomarker method transfer by mass spectrometry. Clin Chem 2014;60:941-4.
Acknowledgements:
This work was supported by NHLBI Johns Hopkins Proteomic Innovation Center in Heart Failure¡ªHHSN268201000032C (JVE) and partially supported by the Chronic Kidney Disease Biomarker Consortium funded by NIDDK U01- U01DK085689. The authors would like to thank Zongming Fu and Ronald Holewinski for running samples on the Orbitrap ELITE and Triple-TOF 5600 LC MS/MS instruments.
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