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A Method for Label-Free, Differential Top-Down Proteomics

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Quantitative Proteomics by Mass Spectrometry

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1410))

Abstract

Biomarker discovery in the translational research has heavily relied on labeled and label-free quantitative bottom-up proteomics. Here, we describe a new approach to biomarker studies that utilizes high-throughput top-down proteomics and is the first to offer whole protein characterization and relative quantitation within the same experiment. Using yeast as a model, we report procedures for a label-free approach to quantify the relative abundance of intact proteins ranging from 0 to 30 kDa in two different states. In this chapter, we describe the integrated methodology for the large-scale profiling and quantitation of the intact proteome by liquid chromatography-mass spectrometry (LC-MS) without the need for metabolic or chemical labeling. This recent advance for quantitative top-down proteomics is best implemented with a robust and highly controlled sample preparation workflow before data acquisition on a high-resolution mass spectrometer, and the application of a hierarchical linear statistical model to account for the multiple levels of variance contained in quantitative proteomic comparisons of samples for basic and clinical research.

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Acknowledgement

The methods used in this article were developed with partial support from the National Institute of General Medical Sciences P41GM108569 for the National Resource for Translational and Developmental Proteomics (NRTDP) based at Northwestern University

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Correspondence to Neil L. Kelleher .

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Ntai, I., Toby, T.K., LeDuc, R.D., Kelleher, N.L. (2016). A Method for Label-Free, Differential Top-Down Proteomics. In: Sechi, S. (eds) Quantitative Proteomics by Mass Spectrometry. Methods in Molecular Biology, vol 1410. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3524-6_8

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  • DOI: https://doi.org/10.1007/978-1-4939-3524-6_8

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3522-2

  • Online ISBN: 978-1-4939-3524-6

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