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EN
Non-homologous RNA recombination is a process enabling the exchange of genetic material between various (related or unrelated) RNA-based viruses. Despite extensive investigations its molecular mechanism remains unclear. Studies on genetic recombination in brome mosaic virus (BMV) have shown that local hybridization between genomic RNAs induces frequent non-homologous crossovers. A detailed analysis of recombinant structures suggested that local complementary regions might be involved in two types of non-homologous recombination in BMV: site-specific and heteroduplex-mediated. To verify the above hypothesis and better recognize the mechanism of the phenomenon studied we have tested how the putative types of recombination are affected by a specific mutation in the BMV polymerase gene or by changes in RNA structure. The experiments undertaken revealed substantial differences between site-specific and heteroduplex-mediated recombination, indicating that they occur according to different mechanisms. The former can be classified as homology-assisted, and the latter as homology-independent. In addition to local RNA/RNA hybridization, short regions of homology are required for site-specific crossovers to occur. They are most efficiently mediated if one homologous sequence is located at the beginning of and the second just before a double-stranded region. At present it is difficult to state what is the mechanism of heteroduplex-mediated recombination. Earlier it was postulated that strong RNA/RNA interaction enforces template switching by the viral replicase. There are, however, several observations questioning this model and indicating that some other factors, which are still unknown, may influence heteroduplex-mediated crossovers.
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Content available remote Computational methods in diagnostics of chronic hepatitis C
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EN
Despite the considerable progress that has recently been made in medicine, the treatment of viral infections is still a problem remaining to be solved. This especially concerns infections caused by newly emerging patogenes such as: human immunodeficiency virus, hepatitis C virus or SARS-coronavirus. There are several lines of evidence that the unusual genetic polymorphism of these viruses is responsible for the observed therapeutic difficulties. In order to determine whether some parameters describing a very complex and variable viral population can be used as prognostic factors during antiviral treatment computational methods were applied. To this end, the structure of the viral population and virus evolution in the organisms of two patients suffering from chronic hepatitis C were analyzed. Here we demonstrated that phylogenetic trees and Hamming distances best reflect the differences between virus populations present in the organisms of patients who responded positively and negatively to the applied therapy. Interestingly, the obtained results suggest that based on the elaborated method df virus population analysis one can predict the final outcome of the treatment even before it has started.
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