Martin Blüggel

Genetic analysis of the mouse brain proteome

Proteome analysis is a fundamental step in systematic functional genomics. Here we have resolved 8,767 proteins from the mouse brain proteome by large-gel two-dimensional electrophoresis. We detected 1,324 polymorphic proteins from the European collaborative interspecific backcross. Of these, we mapped 665 proteins genetically and identified 466 proteins by mass spectrometry. Qualitatively polymorphic proteins, to 96%, reflect changes in conformation and/or mass. Quantitatively polymorphic proteins show a high frequency (73%) of allele-specific transmission in codominant heterozygotes. Variations in protein isoforms and protein quantity often mapped to chromosomal positions different from that of the structural gene, indicating that single proteins may act as polygenic traits. Genetic analysis of proteomes may detect the types of polymorphism that are most relevant in disease-association studies.

Identification of vaccine candidate antigens of Staphylococcus aureus by serological proteome analysis

In this study we applied serological proteome analysis (Klade, C. S. et al. Proteomics 2001, 1, 890–898) for identification of bacterial vaccine candidate antigens. First, approximately one hundred sera from healthy individuals and patients suffering from Staphylococcus aureus infections were screened for antibodies against staphylococcal lysates and recombinant proteins representing surface antigens. Two pools (healthy donors, patients) each consisting of five sera with the highest antiproteinaceous IgG reactivity were selected. Second, S. aureus COL was grown under different conditions and the number of antigens expressed was monitored by Western blot analysis. Third, surface proteins were enriched by digesting the bacterial cell wall under isotonic conditions and subsequent removal of protoplasts. These protein preparations were resolved by two‐dimensional electrophoresis (2‐DE) (pI 4–7). 2‐DE immunoblotting using the preselected serum pools at 1:10 000–1:100 000 dilutions revealed a number of highly immunogenic staphylococcal proteins. Twenty‐one spots were isolated by preparative 2‐DE, and analysed by matrix‐assisted laser desorption/ionization mass spectrometry and tandem mass spectrometry sequencing of tryptic peptides. This led to the identification of 15 proteins including known and novel vaccine candidates. Seroreactivity of several antigens including serine‐aspartate repeat containing protein D, immuno‐dominant staphylococcal antigen and a novel 309 amino acid lipoprotein was independently confirmed by enzyme‐linked immunosorbent assay and Western blot analysis of purified recombinant proteins. In conclusion, serological proteome analysis proved to be a powerful tool for the identification of novel staphylococcal antigens, which provide a basis for rational vaccine design.

The hprK gene of Enterococcus faecalis encodes a novel bifunctional enzyme: the HPr kinase/phosphatase

The HPr kinase of Gram‐positive bacteria is an ATP‐dependent serine protein kinase, which phosphorylates the HPr protein of the bacterial phosphotransferase system (PTS) and is involved in the regulation of carbohydrate metabolism. The hprK gene from Enterococcus faecalis was cloned via polymerase chain reaction (PCR) and sequenced. The deduced amino acid sequence was confirmed by microscale Edman degradation and mass spectrometry combined with collision‐induced dissociation of tryptic peptides derived from the HPr kinase of E. faecalis. The gene was overexpressed in Escherichia coli, which does not contain any ATP‐dependent HPr kinase or phosphatase activity. The homogeneous recombinant protein exhibits the expected HPr kinase activity as well as a P‐Ser‐HPr phosphatase activity, which was assumed to be a separate enzyme activity. The bifunctional HPr kinase/phosphatase acts preferentially as a kinase at high ATP levels of 2 mM occurring in glucose‐metabolizing Streptococci. At low ATP levels, the enzyme hydrolyses P‐Ser‐HPr. In addition, high concentrations of phosphate present under starvation conditions inhibit the HPr kinase activity. Thus, a putative function of the enzyme may be to adjust the ratio of HPr and P‐Ser‐HPr according to the metabolic state of the cell; P‐Ser‐HPr is involved in carbon catabolite repression and regulates sugar uptake via the phosphotransferase system (PTS). Reinvestigation of the previously described Bacillus subtilis HPr kinase revealed that it also possesses P‐Ser‐HPr phosphatase activity. However, contrary to the E. faecalis enzyme, ATP alone was not sufficient to switch the phosphatase activity of the B. subtilis enzyme to the kinase activity. A change in activity of the B. subtilis HPr kinase was only observed when fructose‐1,6‐bisphosphate was also present.

An easy-to-use Decoy Database Builder software tool, implementing different decoy strategies for false discovery rate calculation in automated MS/MS protein identifications.

One of the major challenges for large scale proteomics research is the quality evaluation of results. Protein identification from complex biological samples or experimental setups is often a manual and subjective task which lacks profound statistical evaluation. This is not feasible for high‐throughput proteomic experiments which result in large datasets of thousands of peptides and proteins and their corresponding mass spectra. To improve the quality, reliability and comparability of scientific results, an estimation of the rate of erroneously identified proteins is advisable. Moreover, scientific journals increasingly stipulate that articles containing considerable MS data should be subject to stringent statistical evaluation. We present a newly developed easy‐to‐use software tool enabling quality evaluation by generating composite target‐decoy databases usable with all relevant protein search engines. This tool, when used in conjunction with relevant statistical quality criteria, enables to reliably determine peptides and proteins of high quality, even for nonexperienced users (e.g. laboratory staff, researchers without programming knowledge). Different strategies for building decoy databases are implemented and the resulting databases are characterized and compared. The quality of protein identification in high‐throughput proteomics is usually measured by the false positive rate (FPR), but it is shown that the false discovery rate (FDR) delivers a more meaningful, robust and comparable value.

Investigation of charge variants of rViscumin by two‐dimensional gel electrophoresis and mass spectrometry

A method for the analysis of the rViscumin heterodimer (recombinant mistletoe lectin) based on two‐dimensional (2‐D) polyacrylamide gel electrophoresis and mass spectrometry was developed and used for quality control concerning purity and homogeneity of the recombinant protein processed under Good Manufacturing Practice (GMP) conditions. A series of spots with different pI‐values in the pH‐gradient of both rViscumin A‐ and B‐chain were observed independently from the experimental conditions like urea concentration, heat treatment or the use of cysteine alkylating agents. Comparative studies of the major spots using matrix assisted laser desorption/ionization‐mass spectrometry (MALDI‐MS), liquid chromatography‐electrospray ionization (LC‐ESI)‐MS and LC‐ESI‐tandem MS (MS/MS) after tryptic in‐gel digestion resulted in a sequence coverage of 92% for the A‐chain and 95% for the B‐chain. No molecular differences like common chemical or post‐translational modifications or nonenzymatic deamidation were found to cause the different charge values of the separated spots. Therefore, these protein spots were extracted from the 2‐D gel and separated again by 2‐D gel electrophoresis (termed Re‐2‐DE). Each of the single spots tested in the Re‐2‐DE experiment split up in the same heterogeneous pattern concerning the pI‐values. We suggest that the observed charge variants of rViscumin are the result of conformational protein variants, existing in an equilibrium during sample preparation and/or isoelectric focusing and are not caused from microheterogeneity in the primary structure of rViscumin.

Ligand motif of the autoimmune disease-associated mouse MHC class II molecule H2-As

The MHC class II molecule H2‐As, expressed in the SJL mouse strain, is the principle restriction element of autoreactive CD4+ T cells mediating experimental autoimmune encephalomyelitis, an animal model of multiple sclerosis. We deduced the H2‐As ligand motif from the analysis of naturally processed self peptides and from peptide binding studies. Major anchor residues were identified using various sets of substituted and truncated peptides, derived from natural peptide ligands and known H2‐As binders like myelin basic protein 81 – 99. The nine‐residue H2‐As core binding motif comprises an arrangement of anchors in relative positions P1, P4, P6, P7, and P9. The P1 pocket is relatively unspecific and the P6 pocket favors hydrophobic‐aliphatic side chains. The P1 pocket contributes little to peptide binding. Primary anchors were identified in P4, P7, and in particular in P9. The preferred anchor residues are Lys (P4), His / Arg (P7), and Pro (P9), respectively. Ala‐polysubstituted peptides containing only one of these dominant anchor residues still retain the capacity to bind to H2‐As. Thus, the presence of only one suitable anchor side chain in P4, P7, or P9 is sufficient for high‐affinity peptide binding, at least in the absence of negatively charged side chains nearby. The identified ligand motif facilitates the analysis of immunogenic peptides interacting with H2‐As and will allow a better prediction of pathogenetically relevant peptide antigens in the autoimmune mouse model.

Getting a grip on proteomics data: Proteomics Data Collection (ProDaC)

In proteomics, rapid developments in instrumentation led to the acquisition of increasingly large data sets. Correspondingly, ProDaC was founded in 2006 as a Coordination Action project within the 6th European Union Framework Programme to support data sharing and community‐wide data collection. The objectives of ProDaC were the development of documentation and storage standards, setup of a standardized data submission pipeline and collection of data. Ending in March 2009, ProDaC has delivered a comprehensive toolbox of standards and computer programs to achieve these goals.

Identification of major histocompatibility complex class II-associated peptides derived from freshly prepared rat Langerhans cells using MALDI-PSD and Edman degradation

The isolation and identification is described of MHC class II-bound peptides derived from Langerhans cells. A combination of preparative micro-HPLC, MALDI-MS, Edman degradation was used for determining the amino acid sequence of MHC-associated peptides. Sample handling was crucial because fractions containing trace amounts of material require immediate storage at -80 degrees C to prevent peptide losses.

In-Depth Protein Characterization by Mass Spectrometry

Within this chapter, various techniques and instructions for characterizing primary structure of proteins are presented, whereas the focus lies on obtaining as much complete sequence information of single proteins as possible. Especially, in the area of protein production, mass spectrometry-based detailed protein characterization plays an increasing important role for quality control. In comparison to typical proteomics applications, wherein it is mostly sufficient to identify proteins by few peptides, several complementary techniques have to be applied to maximize primary structure information and analysis steps have to be specifically adopted. Starting from sample preparation down to mass spectrometry analysis and finally to data analysis, some of the techniques typically applied are outlined here in a summarizing and introductory manner.

Hochdurchsatz Analyse in den Biowissenschaften durch die Nutzung von Service Oriented Clustering (Proliferating High Throughput Analysis in Life Science by using Service Oriented Clustering)

Zusammenfassung Obwohl man Cluster erfolgreich für Aufgaben wie Protein Identifikation und multiple alignment einsetzt, sind sie dennoch selten Teil des Laboralltags. Hauptgrund ist die schlechte Integrationsfähigkeit aktueller Lösungen in den Arbeitsablauf. Das Konzept Dienste Orientierter Cluster soll dieses Problem beheben.