Biomedical subjects

Christoph Schaab

Publications and source records attributed to Christoph Schaab.

3 recordsLinked to original sources

PubMed2004

Panel of Bacillus subtilis reporter strains indicative of various modes of action.

In a recent project, we collected the transcriptional profiles of Bacillus subtilis 168 after treatment with a large set of diverse antibacterial agents. One result of the data analysis was the identification of marker genes that are indicative of certain compounds or compound classes. We cloned these promoter regions in front of a luciferase reporter gene and reintroduced the constructs individually into the B. subtilis chromosome. Strains were analyzed for their responsiveness after treatment with a set of 37 antibacterials. Twelve functional reporter strains were generated that were selectively and significantly upregulated by the compounds. The selectivity of the reporter strains ranged from generic pathways like protein biosynthesis, cell wall biosynthesis, and fatty acid biosynthesis to compound classes (quinolones and glycopeptides) and individual compounds (rifampin, cycloserine, and clindamycin). Five of the strains are amenable for high-throughput applications, e.g., pathway-specific screening. In summary, we successfully generated B. subtilis reporter strains that are indicative of the mechanisms of action of various classes of antibacterials. The set of reporter strains presented herein can be used for mode-of-action analyses and for whole-cell screening of compound libraries in a mode-of-action-specific manner.

Anti-Infective Agents↗

PubMed2004

Prediction of mechanisms of action of antibacterial compounds by gene expression profiling.

We have generated a database of expression profiles carrying the transcriptional responses of the model organism Bacillus subtilis following treatment with 37 well-characterized antibacterial compounds of different classes. The database was used to build a predictor for the assignment of the mechanisms of action (MoAs) of antibacterial compounds by the use of support vector machines. This predictor was able to correctly classify the MoA class for most compounds tested. Furthermore, we provide evidence that the in vivo MoA of hexachlorophene does not match the MoA predicted from in vitro data, a situation frequently faced in drug discovery. A database of this kind may facilitate the prioritization of novel antibacterial entities in drug discovery programs. Potential applications and limitations are discussed.

Anti-Bacterial Agents↗

PubMed2002

Improving DNA array data quality by minimising 'neighbourhood' effects.

Gene expression studies using cDNA arrays require robust and sensitive detection methods. Being extremely sensitive, radioactive detection suffers from the influence of signals positioned in each other's vicinity, the 'neighbourhood' effect. This limits the gene density of arrays and the quality of the results obtained. We have investigated the quantitative influence of different parameters on the 'neighbourhood' effect. By using a model experimental system, we could show that the effect is linear and depends only on the intensity of the hybridisation signal. We identified a common factor that can describe the influence of the neighbour spots based on their intensities. This factor is <1%, but it has to be taken into account if a high dynamic range of gene expression is to be detected. We could also derive the factor, although with less precision, from comparison of duplicate spots on arrays of 4565 different clones and replication of the hybridisation experiments. The calculated coefficient applied to our actual experimental results not only revealed previously undetected tissue or cell-specific expression differences, but also increased the dynamic range of detection. It thus provides a relatively simple way of improving DNA array data quality with few experimental modifications.

Gene Expression Profiling↗