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Peptidomics

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Cover of 'Peptidomics'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Origins, Technological Development, and Applications of Peptidomics
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    Chapter 2 Brain Tissue Sample Stabilization and Extraction Strategies for Neuropeptidomics
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    Chapter 3 Isolation of Endogenous Peptides from Cultured Cell Conditioned Media for Mass Spectrometry
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    Chapter 4 Mass Spectrometric Identification of Endogenous Peptides
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    Chapter 5 Bioinformatics for Prohormone and Neuropeptide Discovery
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    Chapter 6 Substrate Capture Assay Using Inactive Oligopeptidases to Identify Novel Peptides
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    Chapter 7 Non-targeted Identification of d-Amino Acid-Containing Peptides Through Enzymatic Screening, Chiral Amino Acid Analysis, and LC-MS
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    Chapter 8 Quantitative Peptidomics: General Considerations
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    Chapter 9 Quantitative Peptidomics with Isotopic and Isobaric Tags
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    Chapter 10 Quantitative Peptidomics Using Reductive Methylation of Amines
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    Chapter 11 Metabolic Labeling to Quantify Drosophila Neuropeptides and Peptide Hormones
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    Chapter 12 Data Preprocessing, Visualization, and Statistical Analyses of Nontargeted Peptidomics Data from MALDI-MS
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    Chapter 13 Affinity Purification of Neuropeptide Precursors from Mice Lacking Carboxypeptidase E Activity
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    Chapter 14 Mass Spectrometry Based Immunopeptidomics for the Discovery of Cancer Neoantigens
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    Chapter 15 Milk Peptidomics to Identify Functional Peptides and for Quality Control of Dairy Products
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    Chapter 16 Neuropeptidomic Analysis of Zebrafish Brain
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    Chapter 17 Identification, Quantitation, and Imaging of the Crustacean Peptidome
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    Chapter 18 Identification of Endogenous Neuropeptides in the Nematode C. elegans Using Mass Spectrometry
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    Chapter 19 EndoProteoFASP as a Tool to Unveil the Peptidome-Protease Profile: Application to Salivary Diagnostics
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    Chapter 20 Methodology for Urine Peptidome Analysis Based on Nano-HPLC Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry
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    Chapter 21 Identification of Components in Frog Skin Secretions with Therapeutic Potential as Antidiabetic Agents
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    Chapter 22 High-Accuracy Mass Spectrometry Based Screening Method for the Discovery of Cysteine Containing Peptides in Animal Venoms and Toxins
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    Chapter 23 Analysis of the Snake Venom Peptidome
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    Chapter 24 Identification of Peptides in Spider Venom Using Mass Spectrometry
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    Chapter 25 Single Cell Peptidomics: Approach for Peptide Identification by N-Terminal Peptide Derivatization
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    Chapter 26 Peptidomic Identification of Cysteine-Rich Peptides from Plants
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    Chapter 27 Analysis of Endogenous Peptide Pools of Physcomitrella patens Moss
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    Chapter 28 The Bright Future of Peptidomics
Attention for Chapter 11: Metabolic Labeling to Quantify Drosophila Neuropeptides and Peptide Hormones
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Chapter title
Metabolic Labeling to Quantify Drosophila Neuropeptides and Peptide Hormones
Chapter number 11
Book title
Peptidomics
Published by
Springer New York, February 2018
DOI 10.1007/978-1-4939-7537-2_11
Pubmed ID
Book ISBNs
978-1-4939-7536-5, 978-1-4939-7537-2
Authors

Thomas Otto Kunz, Jiangtian Chen, Megha, Christian Wegener

Abstract

Neuropeptides and peptide hormones are involved in the regulation of most if not all body functions, ranging from physiology to neuronal processing and the control of behavior. To assess their functions, it is often vital to determine when and in which quantities they are produced, stored, and released. The latter is especially difficult to assess in small insects, such as the genetically amenable fruit fly Drosophila melanogaster, and cannot be achieved merely by quantifying mRNA transcripts. We have adapted and optimized methods to quantify neuropeptides and peptide hormones by metabolic labeling followed by LC-MS. In this chapter, we describe the labeling protocols used in our laboratory and discuss problems and pitfalls that we encountered.

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The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 29%
Student > Bachelor 1 14%
Student > Postgraduate 1 14%
Student > Master 1 14%
Unknown 2 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 43%
Neuroscience 1 14%
Unknown 3 43%