Linagliptin treatment is associated with altered cobalamin (VitB12) homeostasis in mice and humans.

Linagliptin is a dipeptidyl peptidase-4 (DPP-4) inhibitor used for the treatment of type 2 diabetes, with additional beneficial effects for the kidney. Treatment of mice with linagliptin revealed increased storage of cobalamin (Cbl, Vitamin B12) in organs if a standard Cbl diet (30 µg Cbl/kg chow) is given. In order to translate these findings to humans, we determined methylmalonic acid (MMA), a surrogate marker of functional Cbl homeostasis, in human plasma and urine samples (n = 1092) from baseline and end of trial (6 months after baseline) of the previously completed MARLINA-T2D clinical trial. We found that individuals with medium Cbl levels (MMA between 50 and 270 nmol/L for plasma, 0.4 and 3.5 µmol/mmol creatinine for urine, at baseline and end of trial) exhibited higher MMA values at the end of study in placebo compared with linagliptin. Linagliptin might inhibit the N-terminal degradation of the transcobalamin receptor CD320, which is necessary for uptake of Cbl into endothelial cells. Because we demonstrate that linagliptin led to increased organ levels of Cbl in mice, sustained constant medium MMA levels in humans, and inhibited CD320 processing by DPP-4 in-vitro, we speculate that linagliptin promotes intra-cellular uptake of Cbl by prolonging half-life of CD320.

Data Preprocessing, Visualization, and Statistical Analyses of Nontargeted Peptidomics Data from MALDI-MS.

Mass spectrometric (MS) comparative analysis of peptides in biological specimens (nontargeted peptidomics) can result in large amounts of data due to chromatographic separation of a multitude of samples and subsequent MS analysis of numerous chromatographic fractions. Efficient yet effective strategies are needed to obtain relevant information. Combining visual and numerical data analysis offers a suitable approach to retrieve information and to filter data for significant differences as targets for succeeding MS/MS identifications.Visual analysis allows assessing features within a spatial context. Specific patterns are easily recognizable by the human eye. For example, derivatives representing modified forms of signals present are easily identifiable due to an apparent shift in mass and chromatographic retention times. On the other hand numerical data analysis offers the possibility to optimize spectra and to perform high-throughput calculations. A useful tool for such calculations is R, a freely available language and environment for statistical computing. R can be extended via packages to enable functionalities like mzML (open mass spectrometric data format) import and processing. R is capable of parallel processing enabling faster computation using the power of multicore systems.The combination and interplay of both approaches allows evaluating the data in a holistic way, thus helping the researcher to better understand data and experimental outcomes.

Collection and handling of blood specimens for peptidomics.

Pre-analytical variables can alter the analysis of blood-derived samples. In particular sample collection and specimen preparation can alter the validity of results obtained by modern multiplex assays (e.g., LC-MS). Low-molecular-weight proteins (peptides) as products of proteolytic cleavage events exhibit a close connection to protease activity. Increased or altered activity of proteases during sample collection, specimen generation, sample storage, and processing is mirrored by alterations in abundance of specific peptides. Awareness of clinical practices in medical laboratories and the current knowledge allow for identification of specific variables that affect the results of a peptidomic study. Knowledge of pre-analytical variables is a prerequisite to understand and control their impact.

Collection and handling of blood specimens for peptidomics.

Pre-analytical variables can alter the analysis of blood-derived samples. In particular, sample collection and specimen preparation can alter the validity of results obtained by modern multiplex assays (e.g., LC-MS). Low-molecular weight proteins (peptides) as products of proteolytic cleavage events exhibit a close connection to protease activity and function. Altered proteolytic activity during sample collection, preparation, handling, and storage is mirrored by alterations in abundance of specific peptides. Awareness of clinical practices in medical laboratories allows for the identification of specific variables that may affect the results of a peptidomic study. Knowledge of pre-analytical variables is a prerequisite to understand and control their impact.

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.

Peptidomic analysis of breast cancer reveals a putative surrogate marker for estrogen receptor-negative carcinomas.

Estrogen-receptor status provides a major biomarker in breast cancer classification and has an important impact on prognosis and treatment options. The aim of this study was to investigate peptide profiles of invasive breast cancer with positive (n=39) and negative receptor status (n=41). Peptide profiles were generated by 'Differential Peptide Display', which is an offline-coupled combination of reversed-phase-HPLC and MALDI mass spectrometry. Mass spectrometric data were correlated with the immunohistochemically determined receptor state. Identification of peptides of interest was carried out by additional mass spectrometric methods (eg MALDI-TOF-TOF-MS-MS). Approximately 3000-7000 signals were detected per sample and thymosin alpha-1, an asparaginyl endopeptidase generated cleavage product of the ubiquitous acidic protein prothymosin-alpha, was found to differentiate the tumor samples according to their receptor status with the highest specificity. The concentration of Thymosin alpha-1 was found to be upregulated (n=37) in estrogen-negative cancer samples and downregulated (n=32) in estrogen-positive breast cancer samples. The expression of the precursor protein (Prothymosin-alpha) has been discussed previously as a prognostic factor in breast cancer. It is involved in the ER signal transduction pathway as an anti-coactivator-inhibitor. From our findings we conclude that Thymosin alpha-1 could serve as a surrogate marker in breast cancers and may indicate ER functionality.

Peptidomic analysis of human blood specimens: comparison between plasma specimens and serum by differential peptide display.

The human Plasma Proteome Project pilot phase aims to analyze serum and plasma specimens to elucidate specimen characteristics by various proteomic techniques to ensure sufficient sample quality for the HUPO main phase. We used our proprietary peptidomics technologies to analyze the samples distributed by HUPO. Peptidomics summarizes technologies for visualization, quantitation, and identification of the low-molecular-weight proteome (<15 kDa), the "peptidome." We analyzed all four HUPO specimens (EDTA plasma, citrate plasma, heparin plasma, and serum) from African- and Asian-American donors and compared them to in-house collected Caucasian specimens. One main finding focuses on the most suitable method of plasma specimen collection. Gentle platelet removal from plasma samples is beneficial for improved specificity. Platelet contamination or activation of platelets by low temperature prior to their removal leads to distinct and multiple peptide signals in plasma samples. Two different specimen collection protocols for platelet-poor plasma are recommended. Further emphasis is placed on the differences between plasma and serum on a peptidomic level. A large number of peptides, many of them in rather high abundance, are only present in serum and not detectable in plasma. This ex vivo generation of multiple peptides hampers discovery efforts and is caused by a variety of factors: the release of platelet-derived peptides, other peptides derived from cellular components or the clot, enzymatic activities of coagulation cascades, and other proteases. We conclude that specimen collection is a crucial step for successful peptide biomarker discovery in human blood samples. For analysis of the low-molecular-weight proteome, we recommend the use of platelet-depleted EDTA or citrate plasma.

Prerequisites for peptidomic analysis of blood samples: I. Evaluation of blood specimen qualities and determination of technical performance characteristics.

Proteomics studies aiming at a detailed analysis of proteins, and peptidomics, aiming at the analysis of the low molecular weight proteome (peptidome) offer a promising approach to discover novel biomarkers valuable for different crucial steps in detection, prevention and treatment of disease. Much emphasis has been given to the analysis of blood, since this source would by far offer the largest number of meaningful biomarker applications. Blood is a complex liquid tissue that comprises cells and extra-cellular fluid. The choice of suitable specimen collection is crucial to minimize artificial occurring processes during specimen collection and preparation (e.g. cell lysis, proteolysis). After specimen collection, sample preparation for peptidomics is carried out by physical methods (filtration, gel-chromatography, precipitation) which allow for separation based on molecular size, with and without immunodepletion of major abundant proteins. Differential Peptide Display (DPD) is an offline-coupled combination of Reversed-Phase-HPLC and MALDI mass spectrometry in combination with in-house developed data display and analysis tools. Identifications of peptides are carried out by additional mass spectrometric methods (e.g. online LC-ESI-MS/MS). In the work presented here, insights into semi-quantitative mass spectrometric profiling of plasma peptides by DPD are given. This includes proper specimen selection (plasma vs. serum), sample preparation, especially peptide extraction, the determination of sensitivity (i.e. by establishing detection limits of exogenously spiked peptides), the reproducibility for individual as well as for all peptides (Coefficient of Variation calculations) and quantification (correlation between signal intensity and concentration). Finally, the implications for clinical peptidomics are discussed.

Prerequisites for peptidomic analysis of blood samples: II. Analysis of human plasma after oral glucose challenge -- a proof of concept.

Mass spectrometric plasma analysis for biomarker discovery has become an exploratory focus in proteomic research: the challenges of analyzing plasma samples by mass spectrometry have become apparent not only since the human proteome organization (HUPO) has put much emphasis on the human plasma proteome. This work demonstrates fundamental proteomic research to reveal sensitivity and quantification capabilities of our Peptidomics technologies by detecting distinct changes in plasma peptide composition in samples after challenging healthy volunteers with orally administered glucose. Differential Peptide Display (DPD) is a technique for peptidomics studies to compare peptides from distinct biological samples. Mass spectrometry (MS) is used as a qualitative and quantitative analysis tool without previous trypsin digestion or labeling of the samples. Circulating peptides (< 15 kDa) were extracted from 1.3 mL plasma samples and the extracts separated by liquid chromatography into 96 fractions. Each fraction was subjected to MALDI MS, and mass spectra of all fractions were combined resulting in a 2D-display of > 2,000 peptides from each sample. Endogenous peptides that responded to oral glucose challenge were detected by DPD of pre-and post-challenge plasma samples from 16 healthy volunteers and subsequently identified by nESI-qTOF MS. Two of the 15 MS peaks that were significantly modulated by glucose challenge were subsequently identified as insulin and C-peptide. These results were validated by using immunoassays for insulin and C-peptide. This paper serves as a proof of principle for proteomic biomarker discovery down to the pM concentration range by using small amounts of human plasma.

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.

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.

Identification of Peptide tumor markers in a tumor graft model in immunodeficient mice.

The medical demand for useful biomarkers is large and still increasing. This is especially true for cancer, because for this disease adequate diagnostic markers with high specificity and sensitivity are still lacking. Despite advances in imaging technologies for early detection of cancer, peptidomic multiplex techniques evolved in recent years will provide new opportunities for detection of low molecular weight (LMW) proteome biomarker (peptides) by mass spectrometry. Improvements in peptidomics research were made based on separation of peptides and/or proteins by their physico-chemical properties in combination with mass spectrometric detection, respectively identification, and sophisticated bioinformatic tools for data analysis. To evaluate the potential of serological tumor marker detection by differential peptide display (DPD) we analyzed plasma samples from a tumor graft model. After subcutaneous injection of HCT-116 cells in immunodeficient mice and their growth to a palpable tumor, plasma samples were analyzed by DPD. The comparison of obtained mass spectrometric data allows discovery of tumor specific peptides which fit well into the biological context of cancer pathogenesis and show a strong correlation to tumor growth. The identified peptides indicate events associated with hyper-proliferation and dedifferentiation of cells from an epithelial origin, which are typical characteristics of human carcinomas. We conclude that these findings are a "proof of principle" to detect differentially expressed, tumor-related peptides in plasma of tumor-bearing mice.

Mass spectrometric phenotyping of Val34Leu polymorphism of blood coagulation factor XIII by differential peptide display.

BACKGROUND: The Val34Leu mutation in the activation peptide of factor XIII (FXIIIA) correlates with a lower incidence of myocardial infarction and ischemic stroke but an increased risk for hemorrhagic stroke. We describe mass spectrometric detection of the activation peptide variants in human serum. METHODS: We used differential peptide display (DPD) to compare comprehensive peptide maps from pairs of serum samples from healthy volunteers. Peptides were separated by liquid chromatography, and fractions were subjected to mass spectrometry. Mass spectra of all fractions were combined, giving a peptide map representing a two-dimensional display of peptide masses. After comparison of peptide mass maps, peptides that differentiated FXIIIA phenotypes were identified by mass spectrometry. RESULTS: Val34Leu polymorphisms of the activation peptide of FXIIIA were identified in 20 serum samples from 10 volunteers by DPD, and their sequences were confirmed by nanoelectrospray-ionization quadrupole time-of-flight mass spectrometry. Analysis of three (V34V, V34L, and L34L) phenotypes was confirmed by allele-specific genotypic analysis in all (n = 10) volunteers. CONCLUSION: DPD provides a simple and easy-to-use phenotype assay with advantages over PCR-based assays in being faster and directly analyzing the compound of interest.

Expression profiling of breast cancer cells by differential peptide display.

Expression profiling of RNAs or proteins has become a promising means to investigate the heterogeneity of histopathologically defined classes of cancer. Peptides, representing degradation as well as processing products of proteins offer an even closer insight into cell physiology. Peptides are related to the turnover of cellular proteins and are capable to reflect disease-related changes in homoeostasis of the human body. Furthermore, peptides derived from tumor cells are potentially useful markers in the early detection of cancer. In this study, we introduced a method called differential peptide display (DPD) for separating, detecting, and identifying native peptides derived from whole cell extracts. This method is a highly standardized procedure, combining the power of reversed-phase chromatography with mass spectrometry. This technology is suitable to analyze cell lines, various tissue types and human body fluids. Peptide-based profiling of normal human mammary epithelial cells (HMEC) and the breast cancer cell line MCF-7 revealed complex peptide patterns comprising of up to 2300 peptides. Most of these peptides were common to both cell lines whereas about 8% differed in their abundance. Several of the differentially expressed peptides were identified as fragments of known proteins such as intermediate filament proteins, thymosins or Cathepsin D. Comparing cell lines with native tumors, overlapping peptide patterns were found between HMEC and a phylloides tumor (CP) on the one hand and MCF-7 cells and tissue from a invasive ductal carcinoma (DC) on the other hand.

Detection of low-molecular-mass plasma peptides in the cavernous and systemic blood of healthy men during penile flaccidity and rigidity--an experimental approach using the novel differential peptide display technology.

OBJECTIVES: To use Differential Peptide Display (DPD) technology to evaluate the patterns of low-molecular-mass peptides and small proteins in the systemic and cavernous blood taken from healthy adult male volunteers during the penile stages of flaccidity and rigidity. Results from basic research implicate a role of various peptides in the control of mammalian penile erectile tissue. Nevertheless, it is not yet known which particular peptides are essential in the regulation of penile flaccidity, tumescence, rigidity, and detumescence. METHODS: Five healthy male subjects were exposed to visual and tactile erotic stimuli to elicit penile erection. Whole blood was simultaneously aspirated from the corpus cavernosum and cubital vein during penile flaccidity and rigidity. Plasma aliquots were subjected to DPD analysis by means of matrix-assisted-laser-desorption-ionization mass mapping and electrospray-ionization quadrupole--time-of-flight mass spectrometry. RESULTS: High-resolution two-dimensional peptide mass mapping revealed differences in the systemic and cavernous plasma samples related to penile flaccidity and rigidity. Distinct signals were recognized in the cavernous but not in the systemic plasma obtained during flaccidity. These signals were not registered in the plasma samples obtained from the corpus cavernosum during rigid erection. Although one signal was identified as the blood coagulation-activating peptide XIIIa, the remaining two signals could not be related to any known peptide. These signals may represent unknown local peptidergic factors that might be involved in the regulation of penile flaccidity. CONCLUSIONS: Our study demonstrates that DPD is a feasible method for detecting differences in the cavernous and systemic blood in relation to the different functional conditions of the penile erectile tissue. Additional studies using DPD should include the analysis of blood samples taken from the cavernous meshwork of healthy subjects during penile tumescence and detumescence to establish DPD as a valuable tool in contemporary corpus cavernosum basic research.