Hartmut Selle

Identification of Novel Biomarker Candidates by Differential Peptidomics Analysis of Cerebrospinal Fluid in Alzheimers Disease

The objective of this work was the application of peptidomics technologies for the detection and identification of reliable and robust biomarkers for Alzheimers disease (AD) contributing to facilitate and further improve the diagnosis of AD. Using a new method for the comprehensive and comparative profiling of peptides, the differential peptide display (DPD), 312 cerebrospinal fluid (CSF) samples from AD patients, cognitively unimpaired subjects and from patients suffering from other primary dementia disorders were analysed as four independent analytical sets. By combination with a cross validation procedure, candidates were selected from a total of more than 6,000 different peptide signals based on their discriminating power. Twelve candidates were identified using mass-spectrometric techniques as fragments of the possibly neuroprotective neuroendocrine protein VGF and another one as the complement factor C3 descendent C3f. The combination of peptide profiling and cross validation resulted in the detection of novel potential biomarkers with remarkable robustness and a close relation to AD pathophysiology.

The process chain for peptidomic biomarker discovery

Over the last few years the interest in diagnostic markers for specific diseases has increased continuously. It is expected that they not only improve a patients medical treatment but also contribute to accelerating the process of drug development. This demand for new biomarkers is caused by a lack of specific and sensitive diagnosis in many diseases. Moreover, diseases usually occur in different types or stages which may need different diagnostic and therapeutic measures. Their differentiation has to be considered in clinical studies as well. Therefore, it is important to translate a macroscopic pathological or physiological finding into a microscopic view of molecular processes and vice versa, though it is a difficult and tedious task. Peptides play a central role in many physiological processes and are of importance in several areas of drug research. Exploration of endogenous peptides in biologically relevant sources may directly lead to new drug substances, serve as key information on a new target and can as well result in relevant biomarker candidates. A comprehensive analysis of peptides and small proteins of a biological system corresponding to the respective genomic information (peptidomics®methods) was a missing link in proteomics. A new peptidomic technology platform addressing peptides was recently presented, developed by adaptation of the striving proteomic technologies. Here, concepts of using peptidomics technologies for biomarker discovery are presented and illustrated with examples. It is discussed how the biological hypothesis and sample quality determine the result of the study. A detailed study design, appropriate choice and application of technology as well as thorough data interpretation can lead to significant results which have to be interpreted in the context of the underlying disease. The identified biomarker candidates will be characterised in validation studies before use. This approach for discovery of peptide biomarkes has potential for improving clinical studies.

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 organisms 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 peptides 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.

Datamining Methodology for LC-MALDI-MS Based Peptide Profiling

This report will provide a brief overview of the application of data mining in proteomic peptide profiling used for medical biomarker research. Mass spectrometry based profiling of peptides and proteins is frequently used to distinguish disease from non-disease groups and to monitor and predict drug effects. It has the promising potential to enter clinical laboratories as a general purpose diagnostic tool. Data mining methodologies support biomedical science to manage the vast data sets obtained from these instrumentations. Here we will review the typical workflow of peptide profiling, together with typical data mining methodology. Mass spectrometric experiments in peptidomics raise numerous questions in the fields of signal processing, statistics, experimental design and discriminant analysis.

Peptide Sequence Prediction Supported by Correlation-Associated Networks in Human Cerebrospinal Fluid

During the course of biosynthesis, processing and degradation of a peptide, many structurally related intermediate peptide products are generated. Human body fluids and tissues contain several thousand peptides that can be profiled by reversed-phase chromatography and subsequent MALDI-ToF-mass spectrometry. Correlation-Associated Peptide Networks (CAN) efficiently detect structural and biological relations of peptides, based on statistical analysis of peptide concentrations. We combined CAN with recognition of probable cleavage sites for peptidases and proteases in cerebrospinal fluid, resulting in a model able to predict the sequence of unknown peptides with high accuracy. On the basis of this approach, identification of peptide coordinates can be prioritized, and a rapid overview of the peptide content of a novel sample source can be obtained.

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.

Chapter 7 Clinical peptidomics: peptide-biomarker discovery in blood

Publisher Summary Peptides and proteins define the actual phenotype of an organism and thus reflect the current physiology as well as any pathogenic processes. Proteomics is regarded as a central technology in describing the transition from genotype to phenotype and, in more practical terms, from health to disease by describing the underlying mechanisms at a molecular level that is specific to time, quantity, and localization. This chapter focuses on a certain aspect of the proteome—the smaller native endogenous peptides. The research area and technologies addressing this field of endogenous peptides in general are referred to as “peptidomics.” Specifically, the field of clinical peptidomics, by analyzing blood samples from patients within clinical trials, is evolving rapidly. The prerequisites for this type of research are addressed in the chapter. It may be considered as a general principle that peptide precursors sometimes carry several distinct biological activities that are silent after protein biosynthesis. Only at certain times and in specific compartments are they activated by different proteolytic processes. This mechanistic way for the regulated release of biologically active compounds from inactive precursor molecules is probably a very safe way to assure the presence of the molecules at the desired concentration and conformation at the precise location and time when they are needed. In addition to the several modes of intracellular processing, extracellular processing of proteins is a frequently used way to tailor proteins and peptides. In a relevant number of instances, peptidases can liberate biologically active peptides.