Petri net modelling of gene regulation of the Duchenne muscular dystrophy.

UNLABELLED: Searching for therapeutic strategies for Duchenne muscular dystrophy, it is of great interest to understand the responsible molecular pathways down-stream of dystrophin completely. For this reason we have performed real-time PCR experiments to compare mRNA expression levels of relevant genes in tissues of affected patients and controls. To bring experimental data in context with the underlying pathway theoretical models are needed. Modelling of biological processes in the cell at higher description levels is still an open problem in the field of systems biology. In this paper, a new application of Petri net theory is presented to model gene regulatory processes of Duchenne muscular dystrophy. We have developed a Petri net model, which is based mainly on own experimental and literature data. We distinguish between up- and down-regulated states of gene expression. The analysis of the model comprises the computation of structural and dynamic properties with focus on a thorough T-invariant analysis, including clustering techniques and the decomposition of the network into maximal common transition sets (MCT-sets), which can be interpreted as functionally related building blocks. All possible pathways, which reflect the complex net behaviour in dependence of different gene expression patterns, are discussed. We introduce Mauritius maps of T-invariants, which enable, for example, theoretical knockout analysis. The resulted model serves as basis for a better understanding of pathological processes, and thereby for planning next experimental steps in searching for new therapeutic possibilities. AVAILABILITY: Free availability of the Petri net editor and animator Snoopy and the clustering tool PInA via http://www-dssz.informatik.tu-cottbus.de/~ wwwdssz/. The Petri net models used can be accessed via http://www.tfh-berlin.de/bi/duchenne/.

Modularization of biochemical networks based on classification of Petri net t-invariants.

BACKGROUND: Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. METHODS: Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied. RESULTS: We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in Saccharomyces cerevisiae) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability. CONCLUSION: We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.

Antisense oligonucleotides and short interfering RNAs silencing the cyclin-dependent kinase inhibitor p21 improve proliferation of Duchenne muscular dystrophy patients' primary skeletal myoblasts.

Increased levels of the cyclin-dependent kinase inhibitor p21 associated with decreased myoblast proliferation may be involved in the dystrophic process in Duchenne muscular dystrophy (DMD). Therefore we are interested to improve the proliferation of primary myoblasts of DMD patients by a reduction in p21 using either antisense oligonucleotides (ASO) or short interfering RNAs (siRNA). After transient transfection of myoblasts in cell culture proliferation was analyzed using a 5-bromo-2'-deoxyuridine assay comparing specific transfected cells with untransfected cells and cells transfected with scrambled ASO and luciferase siRNA, respectively. Four of five Dystrophin-deficient (Dys(-)) cell culture samples revealed an increase in proliferation between 7% and 18% compared to untransfected cells and between 8% and 36% compared to cells transfected with scrambled ASO. Transfection with siRNA was performed for selected samples to determine whether siRNA is more effective in gene silencing than ASO. The increase in proliferation using luciferase siRNA as reference was comparable to or less than ASO data using scrambled ASO as reference. Using untransfected cells as reference, the increase in proliferation was higher for siRNA than ASO (20-47% vs. 7-18%), but the data must be carefully interpreted with respect to nonspecific effects on gene expression by siRNA. Our findings of transient p21 gene silencing represent a basis for viral vector-mediated drug-inducible p21 shRNA expression in Dys(-) myoblasts which might enhance, prolong and regulate the proliferation effect.

Identification of transcripts from a subtraction library which might be responsible for the mild phenotype in an intrafamilially variable course of Duchenne muscular dystrophy.

While frame-shift mutations are usually found in Duchenne muscular dystrophy (DMD), in-frame mutations are associated with the less severe phenotype of Becker's muscular dystrophy. Exceptions have been reported in both directions suggesting the existence of modifying genes, which might be helpful for innovation of new therapeutic strategies. We report on the very rare case of an intrafamilially different course of DMD, with the younger brother being far less affected than the older one when compared at the same age. In this context, we constructed a subtraction library enriched for transcripts over-expressed in the patient with the milder phenotype. Twelve random clones were sequenced, followed by database analysis. Six of them, casein kinase 1 alpha 1, RAP2B, dynactin 3 light chain, core binding factor beta, myosin light polypeptide 2 and one hypothetical gene, were further analysed by real-time RT-PCR. All these genes were over-expressed 3-20 times in the less affected patient compared with the more severely affected one. Casein kinase 1 and the hypothetical gene showed even a slightly higher expression than the control. Up-regulation of myosin light polypeptide 2, one of the most sensitive markers of muscle fibre regeneration, obviously reflects the milder phenotype. Casein kinase 1, dynactin and core binding factor are supposed to be involved in cell cycle pathways. RAP is a component of the signalling network which controls fundamental cellular processes such as proliferation and differentiation. All four might be interesting candidates for a therapeutic approach to diminish progression of dystrophy in DMD.

Transfection of normal primary human skeletal myoblasts with p21 and p57 antisense oligonucleotides to improve their proliferation: a first step towards an alternative molecular therapy approach of Duchenne muscular dystrophy.

Duchenne muscular dystrophy (DMD), caused by the absence of dystrophin, is associated with decreased muscle cell proliferation. An increased p21 mRNA level in DMD patients may be involved in the process. In this context we are interested to improve the proliferation of primary human skeletal muscle cells (SkMC) by a reduction in the cell cycle proteins p21 and p57 using the appropriate antisense oligonucleotides (ASO). Therefore a transfection procedure needs to be optimized in which the oligonucleotide enters the SkMC with a minimal loss of cell vitality and high efficiency. Three different formulations, Effectene, DAC40, and SuperFect, were compared. Proliferation was analyzed comparing cells transfected with p21 and/or p57 ASO vs. cells transfected with scrambled ASO using a bromodeoxyuridine assay. Under optimal conditions (a mixture of 0.25 microg ASO, 5 microl Effectene, 0.8 microl enhancer) SkMC transfected with p21 ASO reveal an average increase in cell proliferation of 32.5+/-11% after 24 h. p57 ASO shows the same effect, but concomitant transfection of p21 and p57 does not enhance it. A cell vitality of 78+/-14% after 24 h was determined by the MTT test. SkMC transfected with DAC40 reveal a maximal increase in proliferation of 38+/-7% after 48 h and show a vitality of 65+/-8%. In contrast to both these formulations, SuperFect was found to be highly toxic for SkMC, with more than 70% dead cells after 24 h. The increase in proliferation, the functional biological effect of p21 ASO, is well correlated with a decrease in p21 detected by western blot analysis of 31.6% for Effectene. Transfection efficiency was measured directly by FACS analysis using FITC-labeled ASO and data showing ASO internalization in 75.8+/-11.2% of the cell population for Effectene and 74.4+/-6.6% cells for DAC40. Taken together transient transfection of p21 or p57 ASO into primary human SkMC using Effectene significantly improves their proliferation compared to transfection with scrambled ASO without a major loss of cell vitality. This represents a basis for the transfer of this technique to dystrophin-deficient SkMC cultures and the introduction of the short interference-RNA technique which might enhance the effect on cell proliferation.