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DIRECT PEPTIDE PROFILING BY MASS-SPECTROMETRY OF SINGLE IDENTIFIED NEURONS REVEALS COMPLEX NEUROPEPTIDE-PROCESSING PATTERN

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UNSPECIFIED (1994) DIRECT PEPTIDE PROFILING BY MASS-SPECTROMETRY OF SINGLE IDENTIFIED NEURONS REVEALS COMPLEX NEUROPEPTIDE-PROCESSING PATTERN. JOURNAL OF BIOLOGICAL CHEMISTRY, 269 (48). pp. 30288-30292. ISSN 0021-9258

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Abstract

A novel strategy combining peptide fingerprinting of single neurons by matrix-assisted laser desorption ionization mass spectrometry, molecular cloning, peptide chemistry, and electrospray ionization mass spectrometry was used to study the intricate processing pattern of a preprohormone expressed in identified neurons, the neuroendocrine light yellow cells (LYCs) of the gastropod mollusc, Lymnaea stagnalis. The cDNA encoding the precursor, named prepro-LYCP (LYCPs, light yellow cell peptides), predicts a straightforward processing into three peptides, LYCP I, II, and III, at conventional dibasic processing sites flanking the peptide domains on the precursor. However, matrix-assisted laser desorption ionization mass spectrometry of single LYCs revealed trimmed variant peptides derived from LYCP I and II. The variants were much more abundant than the intact peptides, indicating that LYCP I and II serve as intermediates in a peptide-processing sequence. Using the molecular masses of the peptides as markers to guide their isolation by well established purification methods, the structural identities of the peptides could be confirmed by amino acid sequencing. Furthermore, matrix-assisted laser desorption ionization mass spectrometry could detect colocalization of a novel peptide with the LYCPs.

Item Type: Journal Article
Subjects: Q Science > QD Chemistry
Journal or Publication Title: JOURNAL OF BIOLOGICAL CHEMISTRY
Publisher: AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC
ISSN: 0021-9258
Date: 2 December 1994
Volume: 269
Number: 48
Number of Pages: 5
Page Range: pp. 30288-30292
Publication Status: Published
URI: http://wrap.warwick.ac.uk/id/eprint/20170

Data sourced from Thomson Reuters' Web of Knowledge

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