Horst Rose

In vivo profiling of DPP4 inhibitors reveals alterations in collagen metabolism and accumulation of an amyloid peptide in rat plasma

Dipeptidyl peptidase 4 (DPP4) inhibitors represent a novel class of oral anti-hyperglycemic agents. The complete pharmacological profile of these protease inhibitors remains unclear. In order to gain deeper insight into the in vivo effects caused by DPP4 inhibition, two different DPP4 inhibitors (vildagliptin and AB192) were analyzed using differential peptide display. Wistar rats were treated with the DPP4 inhibitors (0.3mgkg(-1); 1mgkg(-1) or 3mgkg(-1) body weight) and DPP4 activity was measured before and at the end of the experiment. One hour after compound administration, blood plasma samples were collected to generate peptide displays and to subsequently identify differentially regulated peptides. A dose-dependent decrease in blood plasma DPP4 activity was measured for both inhibitors. DPP4 inhibition influenced collagen metabolism leading to depletion of collagen derived peptides (e.g. collagen alpha 1 (III) 521-554) and accumulation of related N-terminally extended collagen derived peptides (e.g. collagen alpha 1 (III) 519-554). Furthermore, the intact amyloid rat BRI (1-23) peptide was detected in plasma following in vivo DPP4 inhibition. DPP4 catalyzed cleavage kinetics of the BRI peptide were determined in vitro. The k(cat) and K(m) for cleavage by DPP4 were 5.2s(-1) and 14microM, respectively, resulting in a specificity constant k(cat)/K(m) of 0.36 x 10(6)s(-1)M(-1). Our results demonstrate that differential peptide analysis can be applied to monitor action of DPP4 inhibition in blood plasma. For the first time effects on basal collagen metabolism following DPP4 inhibition in vivo were demonstrated and the BRI amyloid peptide was identified as a novel DPP4 substrate.

Peptidomics Biomarker Discovery in Mouse Models of Obesity and Type 2 Diabetes

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.

Peptidomic analysis of blood plasma after in vivo treatment with protease inhibitors--a proof of concept study.

Native peptides can be regarded as surrogate markers for protease activity in biological samples. Analysis of peptides by peptidomics allows to monitor protease activity in vivo and to describe the influence of protease inhibition. To elucidate the potential of peptides as markers for in vivo protease inhibition we analyzed plasma samples from animals treated with either the indirect FXa inhibitor FONDAPARINUX or the dipeptidylpeptidase IV inhibitor AB192. Signals correlating with the treatment were subsequently identified and assessed with respect to protease-dependent consensus cleavage motifs and occurrence of downstream targets. It could be shown that regulated peptides were either substrates, products or downstream targets of the inhibited protease. The results from the present study demonstrate that the in vivo analysis of peptides by peptidomics has the potential to broaden the knowledge of inhibitor related effects in vivo and that this method may pave the way to develop predictive biomarkers.

The Concept of Functional Peptidomics for the Discovery of Bioactive Peptides in Cell Culture Models

Detection and purification of novel bioactive peptides from biological sources is a scientific task that led to a substantial number of important discoveries. One major laborious approach used is the repetitive stepwise separation of the test sample into several fractions followed by the determination of their bioactivity, until purity allows for sequence identification. We tested whether functional peptidomics, a combination of biological read-outs with differential peptide display (DPD) is a suitable strategy to isolate bioactive peptides at lower workload and with improved success. Additionally, we evaluated the use of DPD to monitor the processing status of proinsulin by inhibition of the insulin processing pathway. The rat insulinoma cell line INS-1 stimulated either with 2 mmol/l or 10 mmol/l glucose was used as model to generate differential peptide displays. In parallel, the bioactivity of the supernatants from the INS-1 cells was measured by glucose uptake and lipolysis assays using the adipocyte cell line 3T3-L1. We were able to quickly and elegantly trace the known activity of insulin to increase glucose uptake and inhibit lipolysis. Following re-chromatography of selected fractions, relevant peptides were identified by DPD and bioassays: the rat insulin-1 precursor and two different insulin peptides. We demonstrated in a semi-quantitative fashion that inhibition of proinsulin processing leads to accumulation of the insulin precursor, and reduced secretion of insulin-1. Thus, we conclude that DPD is an attractive support technology in peptide purification strategies aiming to identify bioactive compounds, and is superior to ELISA in discriminating between the processing status of insulin and its precursor.