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Peter Schulz-Knappe

Publications and source records attributed to Peter Schulz-Knappe.

16 recordsLinked to original sources

Peptidomic analysis of human peripheral monocytes persistently infected by Chlamydia trachomatis.

Peptidomic analysis using Differential Peptide Display (DPD) of human peripheral blood mononuclear cells (PBMC) mock-infected or persistently infected by Chlamydia trachomatis (CT) revealed 10 peptides, expressed upon CT infection. Analysis of these 10 candidates by tandem mass spectrometry enabled the determination of seven candidates as fragments from the precursors (I) ferritin heavy chain subunit, (II) HLA class II histocompatibility antigen, (III) vimentin, (IV) indoleamine 2,3-dioxygenase, (V and VI) pre-B cell enhancing factor (PBEF), and (VII) Interleukin-8 (CXCL8). The identified candidates proved the presence of anti-bacterial and immunologically active monocytic proteins after CT infection.

Chlamydia trachomatis↗

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.

Biomarkers, Tumor↗

Correlation-associated peptide networks of human cerebrospinal fluid.

Profiling of peptides and small proteins from either human body fluids or tissues by chromatography and subsequent mass spectrometry reveals several thousand individual peptide signals per sample. Any peptide is an intermediate in the course of biosynthesis, post-translational modification (PTM), proteolytic processing and degradation. Changes in the concentration of one peptide often affects the concentration of the other, hence a challenge consists in the development of suitable tools to turn this large amount of data into biologically relevant information. Comprehensive statistical analysis of the peptide profiling data allows associating peptides, which are closely related in terms of peptide biochemistry. Here, the bioinformatic concept of peptide networks, correlation-associated peptide networks (CANs), is introduced. Peptides with statistical similarity of their concentrations are grouped in form of networks, and these networks are interpreted in terms of peptide biochemistry. The spectrum of functional relationships found in cerebrospinal fluid CAN covers PTM and proteolytic degradation of peptides, clearance processing in the complement cascade, common secretion of peptides by neuroendocrine cells as well as ubiquitin-mediated degradation. Our results indicate that CAN is a powerful bioinformatic tool for the systematic analysis and interpretation of large peptidomics and proteomics data and helps to discover novel bioactive and diagnostic peptides.

Chemical Fractionation↗

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.

Anticoagulants↗

HUPO Plasma Proteome Project specimen collection and handling: towards the standardization of parameters for plasma proteome samples.

There is a substantial list of pre-analytical variables that can alter the analysis of blood-derived samples. We have undertaken studies on some of these issues including choice of sample type, stability during storage, use of protease inhibitors, and clinical standardization. As there is a wide range of sample variables and a broad spectrum of analytical techniques in the HUPO PPP effort, it is not possible to define a single list of pre-analytical standards for samples or their processing. We present here a compendium of observations, drawing on actual results and sound clinical theories and practices. Based on our data, we find that (1) platelet-depleted plasma is preferable to serum for certain peptidomic studies; (2) samples should be aliquoted and stored preferably in liquid nitrogen; (3) the addition of protease inhibitors is recommended, but should be incorporated early and used judiciously, as some form non specific protein adducts and others interfere with peptide studies. Further, (4) the diligent tracking of pre-analytical variables and (5) the use of reference materials for quality control and quality assurance, are recommended. These findings help provide guidance on sample handling issues, with the overall suggestion being to be conscious of all possible pre-analytical variables as a prerequisite of any proteomic study.

Blood Platelets↗

A functional annotation of subproteomes in human plasma.

The data collected by Human Proteome Organization's Plasma Proteome Pilot project phase was analyzed by members of our working group. Accordingly, a functional annotation of the human plasma proteome was carried out. Here, we report the findings of our analyses. First, bioinformatic analyses were undertaken to determine the likely sources of plasma proteins and to develop a protein interaction network of proteins identified in this project. Second, annotation of these proteins was performed in the context of functional subproteomes involved in the coagulation pathway, the mononuclear phagocytic system, the inflammation pathway, the cardiovascular system, and the liver; as well as the subset of proteins associated with DNA binding activities. Our analyses contributed to the Plasma Proteome Database (http://www.plasmaproteomedatabase.org), an annotated database of plasma proteins identified by HPPP as well as from other published studies. In addition, we address several methodological considerations including the selective enrichment of post-translationally modified proteins by the use of multi-lectin chromatography as well as the use of peptidomic techniques to characterize the low molecular weight proteins in plasma. Furthermore, we have performed additional analyses of peptide identification data to annotate cleavage of signal peptides, sites of intra-membrane proteolysis and post-translational modifications. The HPPP-organized, multi-laboratory effort, as described herein, resulted in much synergy and was essential to the success of this project.

Blood Coagulation↗

Peptides in body fluids and tissues as markers of disease.

The general awareness of the importance of peptides in physiology and pathophysiology has increased strongly over the last few years. With worldwide progress in the analysis of whole genomes, the knowledge base in gene sequence and expression data useful for protein and peptide analysis has drastically increased. The medical need for relevant biomarkers is enormous. This is particularly true for the many types of cancer, but other diseases such as Type 2 diabetes also lack useful and adequate diagnostic markers with high specificity and sensitivity. Despite advances in imaging technologies for early detection of diseases, proteomic and peptidomic multiplex techniques have evolved in recent years. This review focuses on the application of peptidomics technologies to peptides in health and disease. Peptidomics technologies provide new opportunities for the detection of low-molecular-weight proteome biomarkers (peptides) by mass spectrometry. Improvements in peptidomics research are based on separation of peptides and/or proteins by their physicochemical properties in combination with mass spectrometric detection, identification and sophisticated bioinformatics tools for data analysis. Therefore, peptidomics technologies offer an opportunity to discover novel biomarkers for diagnosis and management of disease (e.g., prognosis, treatment decision and monitoring response to therapy).

Animals↗

High-throughput biomarker discovery and identification by mass spectrometry.

Native peptides and proteins are of increasing interest in biomedical research because they hold promise to represent a large number of useful diagnostic and therapeutic biomarkers. Discovery attempts from patient samples have to deal with the complexity of biology from a disease perspective as well as with a high individual variability. High throughput screening of samples is therefore the strategy of choice to detect relevant peptidic biomarkers, and requires a high order of automation particularly in the detection process. In this contribution, a novel technical approach employing a fully automated MALDI-TOF/TOF mass spectrometer is described. This approach combines high throughput biomarker discovery with the identification of corresponding endogenous peptides in one instrument and from the same set of samples. The degree of automation allows the analysis of thousands of chromatographic fractions corresponding to up to one hundred patient samples per day. The applied relative quantification via Differential Peptide Display((R)) is performed in a label-free way and shows a dynamic range of up to four orders of magnitude in the accessible peptide concentrations. The typical limit of detection is in the mid- to low-picomolar range for body fluids such as blood plasma, urine and cerebrospinal fluid. Sequence assignment via MALDI-TOF/TOF mass spectrometry is carried out either in an overview approach, characterizing rapidly the peptide composition e.g. of a novel sample, or in a directed approach, analyzing a list of biomarker candidates deduced from statistically significant abundance differences from the biomarker discovery process.

Biomarkers↗

The future of post-genomic biology at the proteomic level: an outlook.

Drug discovery and early-stage drugs and biomarkers development is a continuous adaptation and maturation process. The cycle of changes based on new findings is coupled with shifts in research priorities and make this part of pharmaceutical research a challenging endeavour. Over the last years, the emphasis on genomics has shifted to proteomics, the science of understanding how proteins translate gene information into function, and metabonomics, the science of small metabolites that are further apart from genomic projects. Proteomics describes the analysis of the protein complement of a biological sample with respect to temporal and spatial resolution. This technology is based on separation of complex protein mixtures by 2D gel-electrophoresis, in gel digest and mass spectrometric analysis of the protein fragments. Proteomics has been recently flanked by peptidomics, a new research direction aimed at the comprehensive analysis of small (1-20 kDa) polypeptides, thus covering the gap between proteomics and metabonomics. The refinement of peptidomics is based on an essential paradigm related to modularity and diversity. Peptides are a paramount example of how one single gene can release multiple functionalities. We can expect fast progress in understanding protein and peptide networks from a systems biology approach ending in the discovery of new peptide targets. However, the way from a complex sample to potential diagnostic and therapeutic targets will depend on technological developments and from the ability to discriminate true disease-related signals from false positive and negative signals, and the way from target discovery to target validation will not be short.

Aged↗

The peptidomics concept.

Peptides are a paramount example of how nature diversifies from one single gene to release multiple, regulated functionalities at the desired sites and time. To achieve this, peptides are sequentially generated by a complex network of more than 500 proteases, acting at intracellular sites, upon secretion, in extracellular environments, and, finally, serving (regulated) degradation. This cycle of maturation, activation, and degradation points out that the peptidome is mechanistically linked to the proteome: the distribution between both is regulated by proteases and counter-regulated by protease inhibitors. Given the high diversity of peptides in living systems and their involvement in key regulatory processes, a need for improved peptide discovery, ideally combining peptide sequence identification with peptide profiling, has emerged. Standard proteomic approaches are not suitable for a systematic peptide analysis, since they do not cover the low molecular mass window. The new direction in proteomic research to analyse this "terra incognita" is peptidomics. This novel concept aims at the comprehensive visualization and analysis of small polypeptides, thus covering the mass range between proteomics and metabonomics. The pacemakers for the development of peptidomics technologies are modern mass spectrometry and bioinformatics. They are ideally suited for sensitive and comprehensive peptide analysis, especially in combination with the massive information content of today's genomic and transcriptomic databases. Given the high diversity of native peptides in living systems, clinical chemistry and modern medicine are the prime application areas. The discovery of relevant peptide biomarkers and drug targets will strongly benefit from peptidomics.

Animals↗

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.

Adult↗

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.

Animals↗

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.

Adult↗

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.

Biomarkers, Tumor↗

Isolation and biochemical characterization of LEAP-2, a novel blood peptide expressed in the liver.

The human genome contains numerous genes whose protein products are unknown in terms of structure, interaction partner, expression, and function. To unravel the function of these orphan genes, it is of particular value to isolate native forms of protein and peptide products derived from these genes. From human blood ultrafiltrate, we characterized a novel gene-encoded, cysteine-rich, and cationic peptide that we termed liver-expressed antimicrobial peptide 2 (LEAP-2). We identified several circulating forms of LEAP-2 differing in their amino-terminal length, all containing a core structure with two disulfide bonds formed by cysteine residues in relative 1-3 and 2-4 positions. Molecular cloning of the cDNA showed that LEAP-2 is synthesized as a 77-residue precursor, which is predominantly expressed in the liver and highly conserved among mammals. This makes it a unique peptide that does not exhibit similarity with any known human peptide regarding its primary structure, disulfide motif, and expression. Analysis of the LEAP-2 gene resulted in the identification of an alternative promoter and at least four different splicing variants, with the two dominating transcripts being tissue-specifically expressed. The largest native LEAP-2 form of 40 amino acid residues is generated from the precursor at a putative cleavage site for a furin-like endoprotease. In contrast to smaller LEAP-2 variants, this peptide exhibited dose-dependent antimicrobial activity against selected microbial model organisms. LEAP-2 shares some characteristic properties with classic peptide hormones and it is expected that the isolation of this novel peptide will help to unravel its physiological role.

Alternative Splicing↗

High-resolution peptide mapping of cerebrospinal fluid: a novel concept for diagnosis and research in central nervous system diseases.

Peptides, such as many hormones, cytokines and growth factors play a central role in biological processes. Furthermore, as degradation products and processed forms of larger proteins they are part of the protein turnover. Thus, they can reflect disease-related changes in an organism's homeostasis in several ways. Since two-dimensional gel electrophoresis is restricted to analysis and display of proteins with relative molecular masses above 5000, we developed Differential Peptide Display (DPD), a new technology for analysis and visualization of peptides. Here we describe its application to cerebrospinal fluid of three subjects without a disease of the central nervous system (CNS) undergoing routine myelography and of two patients suffering from a primary CNS lymphoma. Peptides with a relative molecular mass below 20000 were extracted and analysed by a combination of chromatography and mass spectrometry. The peptide pattern of a sample was depicted as a multi-dimensional peptide mass fingerprint with each peptide's position being characterized by its molecular mass and chromatographic behaviour. Such a fingerprint of a CNS sample consists of more than 6000 different signals. Data analysis of peptide patterns from patients with CNS lymphoma compared to controls revealed obvious differences regarding the peptide content of the samples. By analysing peptides within a mass range of 750-20000, DPD extends 2D gel electrophoresis, thus offering the chance to investigate CNS diseases on the level of peptides. This represents a new approach for diagnosis and possible therapy.

Amino Acid Sequence↗