Expression levels of mRNA change under the influence of external factors and cell processes. miRNA and RISC complex play a major role in the regulation of expression. miRNA-regulated genes participate in cellular signaling cascades responsible for the proper functioning of crucial processes including cell cycle regulation, stress responses and carcinogenesis, and many miRNAs may function as either oncogenes or tumor suppressors under certain conditions. An increasing number of studies have identified miRNAs as potential biomarkers for human cancer and other diseases diagnosis, prognosis and therapeutic targets High-throughput techniques used in biological research and medicine allow determining global changes of mRNA and miRNA in the course of normal and disease processes, but even full knowledge of all miRNA and mRNA level changes does not provide an answer to question which miRNAs are important for mRNA levels characterizing a pathological situation in a particular patient, as most mRNAs are targeted by many miRNAs and changes of some of these may not reflect changes in their targets. In our previous work, combining mathematical modeling with high throughput experiments, we developed a method which allows extracting from many miRNA those which play the most important role in global change of transcript level (Mura et al., BMC Genomics, 2019). We used an unconventional approach in which the model was not used for prediction of transcript levels but the results obtained by the model compared to results of experiment served for estimation of miRNA significance in induction of transcript changes. This model allowed establishing a ranking list of miRNA having highest impact on mRNA change after irradiation. It is important to notice that in the previous studies, we have included data at one time point and we have not determined whether the miRNA impact on mRNA level change result from RNA modifications such as oxidation under the influence of radiation, or from changes in the level of some miRNAs. The objectives of the current project are a logical extension of the previous project results. First of all, we are planning to include longer-term dynamics and, combining experimentation with modeling to determine whether the weight of individual miRNAs in changes in mRNA levels at different times and conditions is characteristic of the type of cells or of the type of stimulus acting on cell. This can be accomplished by performing microarray and deep sequencing experiments in which the mRNA and miRNA levels will be determined for cell lines at several times after exposure to ionizing radiation. Model parameters will be determined using the Approximate Bayesian Computation techniques. Second, we consider the fact that miRNA interference with mRNA is highly variable with time. Accordingly, we plan to examine the biological mechanisms that control changes in model parameters over time, depending also on cell type and type of stimulus. This includes a relationship between the rank of different miRNAs and their nucleotide sequence and the sequence of their pre-miRNAs determining their binding to specific proteins. We also plan to perform premiRNA sequence analysis and analyze features important for high-rank miRNA in various cell types and stimuli. Finally, we plan to run a series of experiments with reporter genes with various combinations of miRNA target sequences. Third, we plan to extend our modeling effort to include determining the effect of miRNAs of high significance for transcriptome changes on the translation process and protein production. This plan is also based on a series of preliminary findings involving the organization of the translation process involving ribosomes, polysomes and other factors. There are specific points in this process where interference of miRNA is important. Based on preliminary research, we propose to devise a mathematical model that allows predicting the role of miRNA in changes of translation efficiency over time in forced situations, including specific changes caused by cancer therapies. The results obtained in our previous study and recent preliminary experiments with polysome profiles of translation are promising and we are convinced that development of this model and its experimental verification which we plan in this project will create the solid basis for a new medical tool with which much more precise estimation of pathological processes of individual patient could be accomplished.

Project manager

Marek Kimmel

Contractors