2016 •
Basic Concepts in Mass Spectrometry and Protein Quantitation
Authors:
Jake Cosme, Irina Tchernyshyov, Anthony O. Gramolini, Anthony O. Gramolini
Abstract:
Mass spectrometry (MS) has provided some paradigm-shifting technology to the field of cardiac biology. Recent advances in MS have made protein identification into a high throughput analytic tool and improved accuracy and sensitivity of protein quantitation. Many of the tools available to scientists trying to answer fundamental questions of basic heart function and mechanisms of disease are quite robust and versatile. MS-based cardiac proteomic approaches have developed to such an extent that a researcher can design experiments to answer clear h (...)
Mass spectrometry (MS) has provided some paradigm-shifting technology to the field of cardiac biology. Recent advances in MS have made protein identification into a high throughput analytic tool and improved accuracy and sensitivity of protein quantitation. Many of the tools available to scientists trying to answer fundamental questions of basic heart function and mechanisms of disease are quite robust and versatile. MS-based cardiac proteomic approaches have developed to such an extent that a researcher can design experiments to answer clear hypotheses, but also studies can also be ‘hypothesis-generating’, ultimately leading to deeper analyses and considerations. Here, we will outline the basic concepts of MS in an effort to explain the potential of this technology in investigating cardiac based research questions. Principles of how current instrumentation functions and how data is acquired will be introduced. Protein quantitation in MS is available in many varieties and applications; this chapter will outline current available technologies in protein quantitation such as isotope-labeled and label-free approaches. With the introductory knowledge of MS and protein quantitation, we will examine some key cardiac proteomics studies and discuss how these principles have been applied to answer specific research questions. (Read More)
Jake Cosme, Irina Tchernyshyov, Anthony O. Gramolini
N/A ·
2016
Data science |
Computational biology |
Biochemical engineering |
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