Hans-Dieter Zucht

Casocidin-I: a casein-αs2 derived peptide exhibits antibacterial activity

Here we report the isolation and characterization of an antibacterial peptide from bovine milk inhibiting the growth of Escherichia coli, and Staphylococcus carnosus. The primary structure of the peptide was revealed as a 39‐amino‐acid‐containing fragment of bovine αs2‐casein (position 165–203) by means of Edman amino acid sequencing and mass spectrometry. Since human milk does not contain any casein‐αs2, these findings could explain the different influence of human and bovine milk on the gastrointestinal flora of the suckling.

Purification of novel peptide antibiotics from human milk

A strategy was established for the identification of novel antimicrobial peptides from human milk. For the generation of bioactive peptides human milk was acidified and proteolyzed with pepsin simulating the digest in infants stomachs. Separation of proteins and resulting fragments was performed by means of reversed-phase chromatography detecting the antimicrobial activity of each fraction using a sensitive radial diffusion assay. In order to avoid the purification of the known abundant antimicrobial milk protein lysozyme, it was identified in HPLC fractions by its enzymatic activity and by matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS). On condition that lysozyme was not detectable and antibacterial activity of HPLC fractions was caused by a peptide, which was confirmed by proteolytic cleavage leading to a loss of activity, further purification was performed by consecutive chromatographic steps guided by the antibacterial assay. Using this strategy, an as yet unknown casein fragment exhibiting antimicrobial activity was purified in addition to antimicrobial lactoferrin fragments. The new antimicrobial peptide resembles a proteolytic fragment of human casein-K (residues 63-117) and inhibits the growth of gram-positive, gram-negative bacteria, and yeasts. Our results confirm that antimicrobially-active peptides are liberated from human milk proteins during proteolytic hydrolysis and may play an important role in the host defense system of the newborn.

Towards Characterization of the Human Urinary Peptidome

Biomarker discovery in human urine has become an evolving and potentially valuable topic in relation to renal function and diseases of the urinary tract. In order to deliver on the promises and to facilitate the development of validated biomarkers or biomarker panels, protein and peptide profiling techniques need high sample throughput, speed of analysis, and reproducibility of results. Here, we outline the performance characteristics of the liquid chromatography/MALDI-TOF-MS based differential peptide display (DPD(1)) approach for separating, detecting, abundance profiling and identification of native peptides derived from human urine. The typical complexity of peptides in human urine (resolution of the technique with respect to detectable number of peptides), the reproducibility (coefficient of variation for abundance profiles of all peptides detected in biological samples) and dynamic range of the technique as well as the lower limit of detection were characterized. A substantial number of peptides present in normal human urine were identified and compared to findings in four published proteome studies. In an explorative approach, pathological urines from patients suffering from post-renal-filtration diseases were qualitatively compared to normal urine. In conclusion, the peptidomics technology as shown here has a great potential for high throughput and high resolution urine peptide profiling analyses. It is a promising tool to study not only renal physiology and pathophysiology and to determine new biomarkers of renal diseases; it also has the potential to study remotely localized or systemic aberrations within human biology.

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.

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.

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.

Peptidomics analysis of human blood specimens for biomarker discovery

This review addresses the concepts, limitations and perspectives for the application of peptidomics science and technologies to discover putative biomarkers in blood specimens. Peptidomics can be defined as the comprehensive multiplex analysis of endogenous peptides contained within a biological sample under defined conditions to describe the multitude of native peptides in a biological compartment. In addition to the discovery of disease associated biomarkers, an emerging field in peptidomics is the analysis of peptides to describe in vivo effects of protease inhibitors. The development and application of peptidomics technologies represent an arena of biomarker research that has the potential for adding significant clinical value.

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.

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 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.