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Micorarray technologies

Working Group Stahl

In the TCI, a complete DNA-chipsystem (Affymetrix 417 Arrayer, Gesim Nanoplotter 2.1, Axon 4000B Scanner, Agilent Bioanalyser) as well as a multiplex-system (Biorad, Magpix) for qualitative and quantitative genome/proteome-analysis is available. DNA chiptechnology will be used for functional genomics and to check for changes in gene expression during long term culture of cells in advanced reactor systems developed in the institute (e.g. mist chamber bioreactor). The procedures will be used to identify those cell lines and cell line-bioreactor combinations which show the best retention of tissue-specific gene expression, e.g. in response to drugs, matrices and growth factors. The following chip formats are available in the institute: DNA, Protein, Aptamer, HSP90 and living cell microarrays. Many interactions with the scientific excellence clusters “Rebirth” and “Biofabrication for NIFE” as well as with the new Centre of Biomedical Drug Research (BMWZ) are established. Here, we developed a HSP90 protein microarray to investigate drug-target interactions and to identify drugs. For example protein microarrays hybridized with labelled inhibitors can be used to analyse ATP-binding proteins such as HSP90α or HtpG involved in many diseases such as cancer, Morbus Alzheimer or malaria. The analysis of such interactions can improve screening for active substrates in the pharmaceutical field. Functional protein microarrays are promising parallel screening platforms in modern drug discovery processes, talented for analysing huge numbers of drugs in a time, material and cost effective manner.

Statistical evalution of Microarray experiments

Working Group Lindner, Working Group Stahl

In the area of DNA-microarrays, our research is aimed towards analysis and quantification of systematic bias that occurs in chip generation and measurement and is difficult to monitor. Examples for such bias sources are spotting and scanning parameters as well as dye-dependent effects and photobleaching. Obtained information is used to develop and validate statistical methods as well as normalization algorithms. Besides the mathematical/statistical approach, our workgroup is developing biochemical solutions to overcome systematic bias. The overall goal being improvement of quality, reproducibility and therefore significance of microarray data as well as contributing to the development of standards for handling microarrays and their data.

Biotesting

Working Group Stahl

Nanotoxicological, nanotherapeutics and drug screening studies are still primarily based on two dimensional (2D) cell culture or, in the later stages, on complex animal in vivo models. Although 2D cell culture is a robust, well-established and reproducible technique of in vitro testing, the use of 2D cultures often yields results with large discrepancies relative to in vivo animal models. This is not surprising, since 2D cell culture represents an environment, remarkably distinct from the in vivo situation, where the majority of tissues are three-dimensional (3D). In this regard, in vitro studies in a 3D cell culture model seem to be more appropriate compared to 2D monolayer systems, since toxicity results can be more strongly influenced by the cell microenvironment. For our biotesting assays we use spheroids (cell aggregates) that represent a simple 3D system since no scaffold or supporting material is required for 3D cell growth. Furthermore, we can run our assays under static as well as under dynamic conditions. Additionally, we want to develop pH-responsive theranostic liposomes, which contain both quantum dots (QD) and new bioactive molecules for cell imaging and targeted therapy. Therefore, we have engineered liposome-quantum dot (L/QD) hybrid vesicles consisting of model anticancer drug into the liposomes. We developed complete control systems for an optimized growth, handling and testing of cell cultures under reproducible and standardized conditions. In parallel, the cellular systems are miniaturized by the development of living cell microarrays.