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Analytical framework for peptidomics applied to large scale neuropeptide identification

ABSTRACT: Endogenous peptides are extracted and seperated with nLC with HCD fragmentation on a LTQ Orbitrap Velos. Data analysis was done with Mascot and MaxQuant

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Rattus Rattus (black Rat)

TISSUE(S): Brain

SUBMITTER: Christian Kelstrup

LAB HEAD: Jesper V. Olsen

PROVIDER: PXD002431 | Pride | 2016-05-03

REPOSITORIES: Pride

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			Action	DRS
	20100805_Velos3_AnSe_Batch12faste_hypot_S1.raw	Raw
	20100805_Velos3_AnSe_Batch12faste_hypot_S10.raw	Raw
	20100805_Velos3_AnSe_Batch12faste_hypot_S11.raw	Raw
	20100805_Velos3_AnSe_Batch12faste_hypot_S12.raw	Raw
	20100805_Velos3_AnSe_Batch12faste_hypot_S13.raw	Raw

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Analytic framework for peptidomics applied to large-scale neuropeptide identification.

Secher Anna A Kelstrup Christian D CD Conde-Frieboes Kilian W KW Pyke Charles C Raun Kirsten K Wulff Birgitte S BS Olsen Jesper V JV

Nature communications 20160504

Large-scale mass spectrometry-based peptidomics for drug discovery is relatively unexplored because of challenges in peptide degradation and identification following tissue extraction. Here we present a streamlined analytical pipeline for large-scale peptidomics. We developed an optimized sample preparation protocol to achieve fast, reproducible and effective extraction of endogenous peptides from sub-dissected organs such as the brain, while diminishing unspecific protease activity. Each peptid ...[more]

PMID: 27142507

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Analytical framework for peptidomics applied to large scale neuropeptide identification

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Analytic framework for peptidomics applied to large-scale neuropeptide identification.

Project description:Large-scale mass spectrometry-based peptidomics for drug discovery is relatively unexplored because of challenges in peptide degradation and identification following tissue extraction. Here we present a streamlined analytical pipeline for large-scale peptidomics. We developed an optimized sample preparation protocol to achieve fast, reproducible and effective extraction of endogenous peptides from sub-dissected organs such as the brain, while diminishing unspecific protease activity. Each peptidome sample was analysed by high-resolution tandem mass spectrometry and the resulting data set was integrated with publically available databases. We developed and applied an algorithm that reduces the peptide complexity for identification of biologically relevant peptides. The developed pipeline was applied to rat hypothalamus and identifies thousands of neuropeptides and their post-translational modifications, which is combined in a resource format for visualization, qualitative and quantitative analyses.

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