We report the isolation and characterization of a novel human peptide with antimicrobial activity, termed LEAP-1 (liver-expressed antimicrobial peptide). Using a mass spectrometric assay detecting cysteine-rich peptides, a 25-residue peptide containing four disulfide bonds was identified in human blood ultrafiltrate. LEAP-1 expression was predominantly detected in the liver, and, to a much lower extent, in the heart. In radial diffusion assays, Gram-positive Bacillus megaterium, Bacillus subtilis, Micrococcus luteus, Staphylococcus carnosus, and Gram-negative Neisseria cinerea as well as the yeast Saccharomyces cerevisiae dose-dependently exhibited sensitivity upon treatment with synthetic LEAP-1. The discovery of LEAP-1 extends the known families of mammalian peptides with antimicrobial activity by its novel disulfide motif and distinct expression pattern. ß

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.

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.

Peptides with biological functions often contain disulfide bridges connecting two cysteine residues. In an attempt to screen biological fluids for peptides containing cysteine residues, we have developed a sensitive and specific method to label cysteines selectively and detect the resulting molecular mass shift by differential mass spectrometry. First, reduction of disulfide bridges and carboxyamidomethylation of free thiols is adjusted to quantitatively achieve cysteine alkylation for complex peptide extracts. In a second step, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) before and after chemical derivatization is performed, followed by differential analysis to determine shifted peaks; shifted peaks belong to cysteine-containing peptides, other peaks remain unchanged. The number of cysteines can then be determined by the resulting molecular mass shift. Free, reduced cysteines are shifted by 57 u, two oxidized cysteines involved in disulfide bridges (cystine) result in a shift to higher mass per disulfide bridge of 116 u. Disulfide bridges connecting different amino acid chains like insulin break up during reduction. In this case, two peaks with lower molecular masses result from a single one in the unmodified sample. With this technique, we were able to identify cysteine-containing peptides and short fragments of proteins present in human blood filtrate.

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.