Identification of mouse organ endogenous peptides by high throughput mass spectrometry
Author:
Affiliation:

Clc Number:

Fund Project:

National Key R&D Program of China (Nos. 2017YFA0505702, 2016YFA0501302), National Natural Science Foundation of China (No. 21675006).

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Endogenous peptides, in the form of cytokines, growth hormones and hormone peptides, play an important role in human hormones, nerves, cell growth and reproduction. Neuropeptide is a kind of endogenous peptide, which is related to the physiological activities of pain, sleep, emotion, learning and memory. Neuropeptides exist not only in the nerve cells of the brain, but also in other body fluids and organs. At present, there is still a lack of research on endogenous peptides, especially on neuropeptides. In this study, high-throughput liquid chromatography tandem mass spectrometry was used to identify the distribution of endogenous peptides in the pancreas, heart, liver and kidney as well as the types of neuropeptides. The results showed that the number of endogenous peptides and neuropeptides in the liver was the highest while that of the pancreas was the lowest. The identified endogenous peptides were organ-specific and presented different dynamic distribution in four kinds of organs. The number of LPV (Longest peptide variant) of neuropeptide in the four organs varies greatly, and the distribution of gene family is also different. For example, neuropeptide in pancreas belongs to Glucagon family, while neuropeptide in heart belongs to ACBD7, Granins, PEBP and other families. The identification results will provide reference value for the mechanism study of diseases and the research and development of therapeutic drugs.

    Reference
    Related
    Cited by
Get Citation

张佩,邵先锋,王振山,贾辰熙. 高通量质谱法用于小鼠器官内源性肽的鉴定[J]. Chinese Journal of Biotechnology, 2019, 35(4): 697-706

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:September 13,2018
  • Revised:
  • Adopted:
  • Online: April 18,2019
  • Published:
Article QR Code