Abstract
Intracellular molecular pathways (IMPs) involve multiple gene products implicated in certain biological functions. The best-known IMPs are metabolic pathways, signaling pathways, DNA repair pathways, and cytoskeleton reorganization pathways. The pathway-level of analysis in molecular biology provides a number of advantages compared to the analysis of single genes. First of all, IMPs are more stable biomarkers. This can be explained by the fact that most frequently several or even many individual gene products are involved in a single elementary biological process. For example, the members of RAF family or regulatory protein kinases can be all involved in the same biological process of signal transduction, by acting in an interchangeable way as the MAP kinase kinase kinases downstream to the RAS proteins. The RAS family, in turn, consists of many proteins that may exert basically the same functions, and so on. A variation in the expression of a single family member is hard to interpret, whereas the pathway level of analysis enables obtaining an integral figure for all the nodes and family members. Secondly, the pathway level of data analysis makes it possible to significantly reduce the experimental error of measuring gene expression. This allows to reduce or even eliminate the batch effects and to compare the data obtained using different experimental platforms. Several analytic approaches have been published to digest the mRNA or proteomic data at the level of IMPs, but an approach crosslinking the changes in microRNA (miR) profiles with the activation of molecular pathways was missing. Recently, we proposed a bioinformatic method termed MiRImpact, which enables to link the high-throughput miR expression data with the estimated outcome on the regulation of molecular pathways. MiRImpact was used to establish interactomic signatures for hundreds of molecular pathways, specific to stem cell differentiation, cancer progression, and cytomegalovirus infection. Of note, the impact of miRs appeared orthogonal to pathway regulation at the mRNA level, which stresses the importance of combining all available levels of gene regulation for building more objective models of intracellular molecular processes.
Keywords
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Abbreviations
- AI:
-
Cells after infection
- BC:
-
Bladder cancer
- HS:
-
Cells highly sensitive to HCMV infection
- IMP:
-
Intracellular molecular pathway
- LS:
-
Cells low sensitive to HCMV infection
- miPAS:
-
Pathway activation strength, calculated using microRNA expression data
- NGS:
-
Next-generation sequencing
- PAS:
-
Pathway activation strength, calculated using mRNA or protein expression data
- riboPAS:
-
Pathway activation strength, calculated using ribosome profiling gene expression data
- WI:
-
Cells without infection
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Buzdin, A.A., Borisov, N.M. (2019). MiRImpact as a Methodological Tool for the Analysis of MicroRNA at the Level of Molecular Pathways. In: Patel, V., Preedy, V. (eds) Handbook of Nutrition, Diet, and Epigenetics. Springer, Cham. https://doi.org/10.1007/978-3-319-55530-0_91
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