Literature DB >> 16464164

Peptidomics biomarker discovery in mouse models of obesity and type 2 diabetes.

Petra Budde1, Imke Schulte, Annette Appel, Susanne Neitz, Markus Kellmann, Harald Tammen, Rüdiger Hess, Horst Rose.   

Abstract

Type 2 diabetes mellitus (T2DM) is caused by the failure of the pancreatic beta-cell to secrete sufficient insulin to compensate a decreased response of peripheral tissues to insulin action. The pathological events causing beta-cell dysfunctions are only poorly understood and early markers that would predict islet function are missing. In contrast to immunoassays, unbiased proteomic technologies provide the opportunity to screen for novel marker protein and peptides of T2DM. An important subset of the proteome, peptides and peptide hormones secreted by the pancreas are deregulated in T2DM. The mass range of peptides and small proteins (1-20 kDa) is only sufficiently targeted by peptidomics, a combination of liquid chromatographic and mass spectrometric (MS) peptide analysis. Here, we describe the application of isotope label-free quantitative peptidomics to display and quantify relevant changes in the level of pancreatic peptides and peptide hormones in a preclinical model of T2DM, the Lep(ob)/Lep(ob) mouse. The amino acid sequence of statistical relevant top candidates was determined by MS/MS fragmentation or Edman degradation. The comparison of lean versus obese mice revealed increased levels of islet-specific peptides that can be divided into the following categories 1) the major islet peptide hormones insulin, amylin and glucagon; 2) proinsulin and C-peptide and 3) novel processing products of secretogranin, glucagon and amylin. Furthermore, we found increased levels of proteins and peptides implicated in zymogen granule maturation (syncollin) and nutritional digestion. In summary, our findings demonstrate that peptidomics is a valid approach to screen for novel peptide biomarkers.

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Year:  2005        PMID: 16464164     DOI: 10.2174/138620705774962535

Source DB:  PubMed          Journal:  Comb Chem High Throughput Screen        ISSN: 1386-2073            Impact factor:   1.339


  3 in total

1.  Changing perspectives in diabetes: their impact on its classification.

Authors:  T J Wilkin
Journal:  Diabetologia       Date:  2007-04-25       Impact factor: 10.122

Review 2.  A proteomic approach to obesity and type 2 diabetes.

Authors:  Elena López-Villar; Gabriel Á Martos-Moreno; Julie A Chowen; Shigeru Okada; John J Kopchick; Jesús Argente
Journal:  J Cell Mol Med       Date:  2015-05-09       Impact factor: 5.310

3.  Combination Effects of Metformin and a Mixture of Lemon Balm and Dandelion on High-Fat Diet-Induced Metabolic Alterations in Mice.

Authors:  Jae Young Choi; Tae-Woo Jang; Phil Hyun Song; Seong Hoon Choi; Sae-Kwang Ku; Chang-Hyun Song
Journal:  Antioxidants (Basel)       Date:  2022-03-18
  3 in total

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