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Computational prediction of non-enzymatic RNA degradation patterns

100%

Rybarczyk A., Jackowiak P., Figlerowicz M., Blazewicz J.

Acta Biochimica Polonica

2016

vol. 63

issue 4

745-751

Since the beginning of the 21st century, an increasing interest in the research of ribonucleic acids has been observed in response to a surprising discovery of the role that RNA molecules play in the biological systems. It was demonstrated that they do not only take part in the protein synthesis (mRNA, rRNA, tRNA) but also are involved in the regulation of gene expression. Several classes of small regulatory RNAs have been discovered (e.g. microRNA, small interfering RNA, piwiRNA). Most of them are excised from specific double-stranded RNA precursors by enzymes that belong to the RNaseIII family (Drosha, Dicer or Dicer-like proteins). More recently, it has been shown that small regulatory RNAs are also generated as stable intermediates of RNA degradation (the so called RNA fragments originating from tRNA, snRNA, snoRNA etc.). Unfortunately, the mechanisms underlying biogenesis of the RNA fragments remain unclear. It is thought that several factors may be involved in the formation of the RNA fragments. The most important are the specific RNases, RNA-protein interactions and RNA structure. In this work, we focus on the RNA primary and secondary structures as factors influencing the RNA stability and consequently the pattern of RNA fragmentation. Earlier, we identified the major structural factors affecting non-enzymatic RNA degradation. Now, based on these data, we developed a new branch-and-cut algorithm that is able to predict the products of large RNA molecules' hydrolysis in vitro. We also present the experimental data that verify the results generated using this algorithm.

RNA-Seq-based analysis of differential gene expression associated with hepatitis C virus infection in a cell culture

64%

Hojka-Osinska A., Budzko L., Zmienko A., Rybarczyk A., Maillard P., Budkowska A., Figlerowicz M., Jackowiak P.

Acta Biochimica Polonica

2016

vol. 63

issue 4

789-798

Hepatitis C virus (HCV) infection is one of the major causes of chronic liver diseases. Unfortunately, the mechanisms of HCV infection-induced liver injury and host-virus interactions are still not well recognized. To better understand these processes we determined the changes in the host gene expression that occur during HCV infection of Huh-7.5 cells. As a result, we identified genes that may contribute to the immune and metabolic cellular responses to infection. Pathway enrichment analysis indicated that HCV induced an increased expression of genes involved in mitogen-activated protein kinases signaling, adipocytokine signaling, cell cycle and nitrogen metabolism. In addition, the enrichment analyses of processes and molecular functions revealed that the up-regulated genes were mainly implicated in the negative regulation of phosphorylation. Construction of the pathway-gene-process network enabled exploration of a much more complex landscape of molecular interactions. Consequently, several essential processes altered by HCV infection were identified: negative regulation of cell cycle, response to endoplasmic reticulum stress, response to reactive oxygen species, toll-like receptor signaling and pattern recognition receptor signaling. The analyses of genes whose expression was decreased upon HCV infection showed that the latter were engaged in the metabolism of lipids and amino acids. Moreover, we observed disturbance in the cellular antiviral defense. Altogether, our results demonstrated that HCV infection elicits host response that includes a very wide range of cellular mechanisms. Our findings significantly broaden the understanding of complex processes that accompany HCV infection. Consequently, they may be used for developing new host-oriented therapeutic strategies.

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2 Acta Biochimica Polonica

2 2016

2 Figlerowicz M.

2 Jackowiak P.

2 Rybarczyk A.

1 Blazewicz J.

1 Budkowska A.

1 Budzko L.

1 Hojka-Osinska A.

1 Maillard P.

1 Zmienko A.

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Computational prediction of non-enzymatic RNA degradation patterns

RNA-Seq-based analysis of differential gene expression associated with hepatitis C virus infection in a cell culture