Biomedical subjects

Michael Dondrup

Publications and source records attributed to Michael Dondrup.

6 recordsLinked to original sources

PubMed2006

Development of bioinformatic tools to support EST-sequencing, in silico- and microarray-based transcriptome profiling in mycorrhizal symbioses.

The great majority of terrestrial plants enters a beneficial arbuscular mycorrhiza (AM) or ectomycorrhiza (ECM) symbiosis with soil fungi. In the SPP 1084 "MolMyk: Molecular Basics of Mycorrhizal Symbioses", high-throughput EST-sequencing was performed to obtain snapshots of the plant and fungal transcriptome in mycorrhizal roots and in extraradical hyphae. To focus activities, the interactions between Medicago truncatula and Glomus intraradices as well as Populus tremula and Amanita muscaria were selected as models for AM and ECM symbioses, respectively. Together, almost, 20.000 expressed sequence tags (ESTs) were generated from different random and suppressive subtractive hybridization (SSH) cDNA libraries, providing a comprehensive overview of the mycorrhizal transcriptome. To automatically cluster and annotate EST-sequences, the BioMake and SAMS software tools were developed. In connection with the eNorthern software SteN, plant genes with a predicted mycorrhiza-induced expression were identified. To support experimental transcriptome profiling, macro- and microarray tools have been constructed for the two model mycorrhizae, based either on PCR-amplified cDNAs or 70mer oligonucleotides. These arrays were used to profile the transcriptome of AM and ECM roots under different conditions, and the data obtained were uploaded to the ArrayLIMS and EMMA databases that are designed to store and evaluate expression profiles from DNA arrays. Together, the EST- and transcriptome databases can be mined to identify candidate genes for targeted functional studies.

Computational Biology↗

PubMed2004

Construction and validation of cDNA-based Mt6k-RIT macro- and microarrays to explore root endosymbioses in the model legume Medicago truncatula.

To construct macro- and microarray tools suitable for expression profiling in root endosymbioses of the model legume Medicago truncatula, we PCR-amplified a total of 6048 cDNA probes representing genes expressed in uninfected roots, mycorrhizal roots and young root nodules [Nucleic Acids Res. 30 (2002) 5579]. Including additional probes for either tissue-specific or constitutively expressed control genes, 5651 successfully amplified gene-specific probes were used to grid macro- and to spot microarrays designated Mt6k-RIT (M. truncatula 6k root interaction transcriptome). Subsequent to a technical validation of microarray printing, we performed two pilot expression profiling experiments using Cy-labeled targets from Sinorhizobium meliloti-induced root nodules and Glomus intraradices-colonized arbuscular mycorrhizal roots. These targets detected marker genes for nodule and arbuscular mycorrhiza development, amongst them different nodule-specific leghemoglobin and nodulin genes as well as a mycorrhiza-specific phosphate transporter gene. In addition, we identified several dozens of genes that have so far not been reported to be differentially expressed in nodules or arbuscular mycorrhiza thus demonstrating that Mt6k-RIT arrays serve as useful tools for an identification of genes relevant for legume root endosymbioses. A comprehensive profiling of such candidate genes will be very helpful to the development of breeding strategies and for the improvement of cultivation management targeted at increasing legume use in sustainable agricultural systems.

Equipment Design↗

PubMed2003

Development of a Corynebacterium glutamicum DNA microarray and validation by genome-wide expression profiling during growth with propionate as carbon source.

A DNA microarray was developed to analyse global gene expression of the amino acid-producing bacterium Corynebacterium glutamicum. PCR products representing 93.4% of the predicted C. glutamicum genes were prepared and spotted in quadruplicate onto 3-aminopropyltrimethoxysilane-coated glass slides. The applicability of the C. glutamicum DNA microarray was demonstrated by co-hybridisation with fluorescently labelled cDNA probes. Analysis of the technical variance revealed that C. glutamicum genes detected with different intensities resulting in ratios greater than 1.52 or smaller than -1.52 can be regarded as differentially expressed with a confidence level of greater than 95%. In a validation example, we measured changes of the mRNA levels during growth of C. glutamicum with acetate and propionate as carbon sources. Acetate-grown C. glutamicum cultures were used as reference. At the 95% confidence interval, 117 genes revealed increased transcript levels in the presence of propionate, while 43 genes showed a decreased expression compared with the acetate-grown culture. Global expression profiling confirmed the induction of the prpD2B2C2 gene cluster already known to be essential for propionate degradation via the 2-methylcitrate cycle. Besides many genes of unknown function, the paralogous prpD1B1C1 gene cluster as well as fasI-B (encoding fatty-acid synthase IB), dtsR1 and dtsR2 (components of acyl-CoA carboxylases), gluABCD (glutamate transport system), putP (proline transport system), and pyc (pyruvate carboxylase) showed significantly increased expression levels. Differential expression of these genes was confirmed by real-time reverse transcription (RT) PCR assays.

Carbon↗

PubMed2003

Building a BRIDGE for the integration of heterogeneous data from functional genomics into a platform for systems biology.

The flood of data acquired from the increasing number of publicly available genomes has led to new demands for bioinformatics software. With the growing amount of information resulting from high throughput experiments new questions arise that often focus on the comparison of genes, genomes, and their expression profiles. Inferring new knowledge by combining different kinds of "post-genomics" data obviously necessitates the development of new approaches that allow the integration of variable data sources into a flexible framework. In this paper, we describe our concept for the integration of heterogeneous data into a platform for systems biology. We have implemented a Bioinformatics Resource for the Integration of heterogeneous Data from Genomic Explorations (BRIDGE) and illustrate the usability of our approach as a platform for systems biology for two sample applications.

Algorithms↗

PubMed2003

Bioinformatics support for high-throughput proteomics.

In the "post-genome" era, mass spectrometry (MS) has become an important method for the analysis of proteome data. The rapid advancement of this technique in combination with other methods used in proteomics results in an increasing number of high-throughput projects. This leads to an increasing amount of data that needs to be archived and analyzed. To cope with the need for automated data conversion, storage, and analysis in the field of proteomics, the open source system ProDB was developed. The system handles data conversion from different mass spectrometer software, automates data analysis, and allows the annotation of MS spectra (e.g. assign gene names, store data on protein modifications). The system is based on an extensible relational database to store the mass spectra together with the experimental setup. It also provides a graphical user interface (GUI) for managing the experimental steps which led to the MS data. Furthermore, it allows the integration of genome and proteome data. Data from an ongoing experiment was used to compare manual and automated analysis. First tests showed that the automation resulted in a significant saving of time. Furthermore, the quality and interpretability of the results was improved in all cases.

Algorithms↗

PubMed2003

EMMA: a platform for consistent storage and efficient analysis of microarray data.

As a high throughput technique, microarray experiments produce large data sets, consisting of measured data, laboratory protocols, and experimental settings. We have implemented the open source platform EMMA to store and analyze these data. The system provides automated pipelines for data processing and has a modular architecture that can be easily extended. EMMA features detailed reports about spots and their corresponding measurements. In addition to routine data analysis algorithms, the system can be integrated with other components that contain additional data sources (e.g. genome annotation systems).

Algorithms↗