Abstract
A suite of bioactive peptides orchestrates a variety of cellular interactions in the mammalian brain. The bioanalytical strategy known as neuropeptidomics evolved from the quest to globally characterize these important cell–cell signaling peptides. The goal of a neuropeptidomics experiment is to characterize the peptides present in an intact brain, brain region, or even an individual neuron. A neuropeptidomics measurement needs to contend with the large dynamic range and low abundance of the neuropeptides that are present within a background of peptides resulting from the postmortem degradation of high-level ubiquitous proteins. The core components of a successful effort include effective tissue sampling and stabilization, sensitive and robust peptide characterization, and comprehensive data analysis and interpretation. Mass spectrometry (MS) has become the central analytical approach for high-throughput characterization of the brain peptidome because of its capability to detect, identify, and quantify known and unknown peptides with high confidence. Robust fractionation techniques, such as two-dimensional liquid chromatography (LC), are commonly used in conjunction with MS to enhance investigation of the peptidome. Identification and characterization of peptides is more complex when neuropeptide prohormone genes have not been annotated in an unbiased manner. This chapter outlines techniques and describes protocols for three different experimental designs that combine MS with LC, each aimed at high-throughput discovery of peptides in brain tissue. Further, we describe the currently available bioinformatics tools for automatic query of the experimental data against existing protein databases, manual retrieval of structural information from raw MS data, and label-free quantitation.
| Original language | English (US) |
|---|---|
| Title of host publication | Neuromethods |
| Publisher | Humana Press Inc. |
| Pages | 161-177 |
| Number of pages | 17 |
| DOIs | |
| State | Published - Jan 1 2019 |
Publication series
| Name | Neuromethods |
|---|---|
| Volume | 146 |
| ISSN (Print) | 0893-2336 |
| ISSN (Electronic) | 1940-6045 |
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Keywords
- Bioinformatics
- Hormone
- Liquid chromatography
- Mass spectrometry
- Neuropeptide
- Neuropeptidome
ASJC Scopus subject areas
- Neuroscience(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Pharmacology, Toxicology and Pharmaceutics(all)
- Psychiatry and Mental health
Cite this
Neuropeptidomics of the mammalian brain. / Xie, Fang; Anapindi, Krishna D.B.; Romanova, Elena Vikentievna; Sweedler, Jonathan V.
Neuromethods. Humana Press Inc., 2019. p. 161-177 (Neuromethods; Vol. 146).Research output: Chapter in Book/Report/Conference proceeding › Chapter
}
TY - CHAP
T1 - Neuropeptidomics of the mammalian brain
AU - Xie, Fang
AU - Anapindi, Krishna D.B.
AU - Romanova, Elena Vikentievna
AU - Sweedler, Jonathan V
PY - 2019/1/1
Y1 - 2019/1/1
N2 - A suite of bioactive peptides orchestrates a variety of cellular interactions in the mammalian brain. The bioanalytical strategy known as neuropeptidomics evolved from the quest to globally characterize these important cell–cell signaling peptides. The goal of a neuropeptidomics experiment is to characterize the peptides present in an intact brain, brain region, or even an individual neuron. A neuropeptidomics measurement needs to contend with the large dynamic range and low abundance of the neuropeptides that are present within a background of peptides resulting from the postmortem degradation of high-level ubiquitous proteins. The core components of a successful effort include effective tissue sampling and stabilization, sensitive and robust peptide characterization, and comprehensive data analysis and interpretation. Mass spectrometry (MS) has become the central analytical approach for high-throughput characterization of the brain peptidome because of its capability to detect, identify, and quantify known and unknown peptides with high confidence. Robust fractionation techniques, such as two-dimensional liquid chromatography (LC), are commonly used in conjunction with MS to enhance investigation of the peptidome. Identification and characterization of peptides is more complex when neuropeptide prohormone genes have not been annotated in an unbiased manner. This chapter outlines techniques and describes protocols for three different experimental designs that combine MS with LC, each aimed at high-throughput discovery of peptides in brain tissue. Further, we describe the currently available bioinformatics tools for automatic query of the experimental data against existing protein databases, manual retrieval of structural information from raw MS data, and label-free quantitation.
AB - A suite of bioactive peptides orchestrates a variety of cellular interactions in the mammalian brain. The bioanalytical strategy known as neuropeptidomics evolved from the quest to globally characterize these important cell–cell signaling peptides. The goal of a neuropeptidomics experiment is to characterize the peptides present in an intact brain, brain region, or even an individual neuron. A neuropeptidomics measurement needs to contend with the large dynamic range and low abundance of the neuropeptides that are present within a background of peptides resulting from the postmortem degradation of high-level ubiquitous proteins. The core components of a successful effort include effective tissue sampling and stabilization, sensitive and robust peptide characterization, and comprehensive data analysis and interpretation. Mass spectrometry (MS) has become the central analytical approach for high-throughput characterization of the brain peptidome because of its capability to detect, identify, and quantify known and unknown peptides with high confidence. Robust fractionation techniques, such as two-dimensional liquid chromatography (LC), are commonly used in conjunction with MS to enhance investigation of the peptidome. Identification and characterization of peptides is more complex when neuropeptide prohormone genes have not been annotated in an unbiased manner. This chapter outlines techniques and describes protocols for three different experimental designs that combine MS with LC, each aimed at high-throughput discovery of peptides in brain tissue. Further, we describe the currently available bioinformatics tools for automatic query of the experimental data against existing protein databases, manual retrieval of structural information from raw MS data, and label-free quantitation.
KW - Bioinformatics
KW - Hormone
KW - Liquid chromatography
KW - Mass spectrometry
KW - Neuropeptide
KW - Neuropeptidome
UR - http://www.scopus.com/inward/record.url?scp=85070549048&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85070549048&partnerID=8YFLogxK
U2 - 10.1007/978-1-4939-9662-9_14
DO - 10.1007/978-1-4939-9662-9_14
M3 - Chapter
AN - SCOPUS:85070549048
T3 - Neuromethods
SP - 161
EP - 177
BT - Neuromethods
PB - Humana Press Inc.
ER -