institute of bioinformatics and systems biology / mips

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Proteomics

We currently have two Proteomics projects at the Institute for Bioinformatics (IBI). One is dedicated to the proteomic analysis of pathogenic bacteria while the other aims at process optimization and development of improved production logs for Proteomics of mammalian tissues. In both projects, the bioinformatics part is done in cooperation with Biomax Informatics AG.

1. Proteomics of Pathogenic Bacteria

This project is part of the 'BMBF Förderschwerpunkt':

Neue effiziente Methoden für die funktionelle Proteomanalyse (New Efficient Methods for the Functional Analysis of Proteomes)

Head:: Prof. Dr. Michael Hecker, Institut für Mikrobiologie, Universität Greifswald
Dr. Peter R. Jungblut, Max-Planck-Institut für Infektionsbiologie, Berlin
Prof. Dr. Jürgen Wehland, GBF, Braunschweig

1.1 Description

The main objective of this project is to optimize the efficiency of analyzing Proteomes of micro organisms. To reach this goal, we have partitioned the project in six highly interacting areas:

Increase the efficiency of Proteome analysis
Partitioning of a Proteome into sub-Proteomes and subsequent reconstruction of the complete Proteomes
Physiological approaches
Technology development for comparative Proteomics using surface and extracellular proteins as example
Sub-Proteomes and the development of protein-arrays based on antigen-antibody binding
Comparative Proteomics and bioinformatics

1.2 Bioinformatics

1.2.1 Staff at IBI

1.2.2 Objectives

The exploration of complete Proteomes of bacteria generates large and complex data sets. We aim to develop a protein information environment based on those experimentally generated data in combination with relevant genomic information.

After the collection of all parameters of the experiments, the primary goal is the analysis of the raw data from the measures (basic statistical analysis, interpretation of MS-spectra, spot detection on 2DE gels). These computations are usually performed by commercial software. However all this information has to be stored, maintained, and integrated.

Once we have such a list of protein id's and quantities, the questions are:

Of what kind are these proteins, what are there roles in the cell?
Are they involved in signal transduction pathways, in metabolic pathways?
What is there function?
Do they compose protein complexes?
...

To tackle this questions we work on three topics.

First, we try to collect as much information about cooperating genes as possible. In this context some genes are cooperating if for example there is a known protein interaction between them, or they are in a comon expression-cluster, or they share a conjoint matabolic rection path, ...
All these groups of cooporating genes are then collected in a database. Basicly, an entry in this database has a list of gene names/protein names, an organism name, the kind of data which was used (e.g. mRNA expression data, the MIPS functional catalog, a protein interaction database, ...), and some annotation under which circumstances we colected this group (experimental conditions, parameters, ...).
The second task is to develop algorithms how to use this data, e.g. for trans-genome predictions, experiment validation, function prediction, etc.
Thirdly, we must develop a graphical user interface, which is capable in displaying groups of genes/proteins in a intuitive way. Classical user interfaces found in the web have usually just simple tables but we need views that are capable to display those groups in the context of their occurence. That means we should display a metabolic path or protein complex as graph, we should show a functional catalog as a tree-structure, we should draw proteins meassured on a 2DE gel on a gel-like display ...

For this purpose, we develop PRIME - a protein information environment.

1.3 Project Structure

Part I

From sub-Proteomes to the complete Proteome in Bacillus subtilis - an analytical and physiological approach.
Head: M. Hecker (Greifswald)

Part II

Improving efficiency in analyzing Proteomes of clinically relevant bacteria
Head: P. R. Jungblut (Berlin)

Part III

Sub-Proteomes, pathogenicity factors and protein chips
Head: J. Wehland (Braunschweig) and M. Hecker (Greifswald)

Part IV

Bioinformatics
Head: H.-W. Mewes (Munich-Neuherberg)

Part V

Joint ventures with industrial partners

2. Proteomics of Mammalian Tissues

This project is part of the 'BMBF Förderschwerpunkt':

Neue effiziente Methoden für die funktionelle Proteomanalyse (New Efficient Methods for the Functional Analysis of Proteomes)

Head:: Dr. phil. Dr. med. habil. Friedrich Lottspeich (MPI), Max-Planck-Institut für Biochemie, Martinsried
: 2.1 Description

Set-up of a technology platform for the functional Proteome analysis of tissues. This project aims to improve the experimental conditions and the analyses and interpretation of Proteome data.

We will develop standardized procedures for the preparation of samples and the high-throughput processing necessary for the quantitative collection of Proteome data. Already existing procedures will be optimized. In order to achieve this the provision of powerful bioinformatics tools for the data analyses is indispensable. The project partners will analyze different tissues of the model organism mouse to improve the experimental design. One approach will be the comparative analysis of Proteome and Transcriptome data. The resulting methods will be applied to the project "human kidney carcinoma".

2.2 Bioinformatics

2.2.1 Staff at IBI

Yu Wang, yu.wang@helmholtz-muenchen.de

2.2.2 Objectives

Provision of an up to date annotation of protein sequences of mouse and human. Implementation of relevant computational analyses and development of new strategies in order to keep annotations in a current state.
Provision and integration of the MetaMIPS (part of GAMS) software. Further development of this program package with a special focus on the integration of public data sources on signal transduction, metabolic pathways and protein-protein interactions.
Provision and integration of MouseExpress.

2.3 Project Structure

Competence network I

The model organism mouse

J. Beckers, M. H. de Angelis
Comparing Proteomics and Transcriptomics in mouse
R. Wanke, E. Wolf
Analyzing the Proteome and Metabolome in mouse

Competence network II

Technology development

Toplab
Technology development for functional Proteomics
F. Lottspeich
Technology development for the analysis of membrane proteins
G. J. Arnold
Generation and evaluation of peptide-induced antibodies and antibody arrays
M. Meisterernst
Identification and isolation of signal dependent Proteomes
Definiens
Development of an image analysis tool for 2DE gels
Biomax, H.W. Mewes
Development of a bioinformatics system for Proteomics

Competence network III

Kidney carcinoma

Seliger, Wilex