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Elk1 affects katanin and spastin proteins via differential transcriptional and post-transcriptional regulations.

ABSTRACT: Microtubule severing, which is highly critical for the survival of both mitotic and post-mitotic cells, has to be precisely adjusted by regulating the expression levels of severing proteins, katanin and spastin. Even though severing mechanism is relatively well-studied, there are limited studies for the transcriptional regulation of microtubule severing proteins. In this study, we identified the main regulatory region of KATNA1 gene encoding katanin-p60 as 5' UTR, which has a key role for its expression, and showed Elk1 binding to KATNA1. Furthermore, we identified that Elk1 decreased katanin-p60 and spastin protein expressions, while mRNA levels were increased upon Elk1 overexpression. In addition, SUMOylation is a known post-translational modification regulating Elk1 activity. A previous study suggested that K230, K249, K254 amino acids in the R domain are the main SUMOylation sites; however, we identified that these amino acids are neither essential nor substantial for Elk1 SUMOylation. Also, we determined that KATNA1 methylation results in the reduction of Elk1 binding whereas SPG4 methylation does not. Together, our findings emphasizing the impacts of both transcriptional and post-transcriptional regulations of katanin-p60 and spastin suggest that Elk1 has a key role for differential expression patterns of microtubule severing proteins, thereby regulating cellular functions through alterations of microtubule organization.

SUBMITTER: Kelle D

PROVIDER: S-EPMC6383945 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Respiratory epithelial cells are the primary target of influenza virus infection in human. However, the molecular mechanisms of airway epithelial cell responses to viral infection are not fully understood. Revealing genome-wide transcriptional and post-transcriptional regulatory relationships can further advance our understanding of this problem, which motivates the development of novel and more efficient computational methods to simultaneously infer the transcriptional and post-transcriptional regulatory networks.Here we propose a novel framework named SITPR to investigate the interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes. Briefly, a background regulatory network on a genome-wide scale (~23,000 nodes and ~370,000 potential interactions) is constructed from curated knowledge and algorithm predictions, to which the identification of transcriptional and post-transcriptional regulatory relationships is anchored. To reduce the dimension of the associated computing problem down to an affordable size, several topological and data-based approaches are used. Furthermore, we propose the constrained LASSO formulation and combine it with the dynamic Bayesian network (DBN) model to identify the activated regulatory relationships from time-course expression data. Our simulation studies on networks of different sizes suggest that the proposed framework can effectively determine the genuine regulations among TFs, miRNAs and target genes; also, we compare SITPR with several selected state-of-the-art algorithms to further evaluate its performance. By applying the SITPR framework to mRNA and miRNA expression data generated from human lung epithelial A549 cells in response to A/Mexico/InDRE4487/2009 (H1N1) virus infection, we are able to detect the activated transcriptional and post-transcriptional regulatory relationships as well as the significant regulatory motifs.Compared with other representative state-of-the-art algorithms, the proposed SITPR framework can more effectively identify the activated transcriptional and post-transcriptional regulations simultaneously from a given background network. The idea of SITPR is generally applicable to the analysis of gene regulatory networks in human cells. The results obtained for human respiratory epithelial cells suggest the importance of the transcriptional, post-transcriptional regulations as well as their synergies in the innate immune responses against IAV infection.

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Elk1 affects katanin and spastin proteins via differential transcriptional and post-transcriptional regulations.

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