Literature DB >> 23982306

MitomiRs, chloromiRs and modelling of the microRNA inhibition.

J Demongeot1, H Hazgui, S Bandiera, O Cohen, A Henrion-Caude.   

Abstract

MicroRNAs are non-coding parts of nuclear and mitochondrial genomes, preventing the weakest part of the genetic regulatory networks from being expressed and preventing the appearance of a too many attractors in these networks. They have also a great influence on the chromatin clock, which ensures the updating of the genetic regulatory networks. The post-transcriptional inhibitory activity by the microRNAs, which is partly unspecific, is due firstly to their possibly direct negative action during translation by hybridizing tRNAs, especially those inside the mitochondrion, hence slowing mitochondrial respiration, and secondly to their action on a large number of putative m-RNA targets like those involved in immunetworks; We show that the circuits in the core of the interaction graphs are responsible for the small number of dedicated attractors that correspond to genetically controlled functions, partly due to a general filtering by the microRNAs. We analyze this influence as well as their impact on important functions like the control by the p53 network over the apoptosis/proliferation system and the homeostasis of the energy metabolism. In this last case, we show the role of two kinds of microRNAs, both involved in the control of the mitochondrial genome: (1) nuclear microRNAs, called mitoMirs, inhibiting mitochondrial genes and (2) putative mitochondrial microRNAs inhibiting the tRNAs functioning.

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Year:  2013        PMID: 23982306     DOI: 10.1007/s10441-013-9190-8

Source DB:  PubMed          Journal:  Acta Biotheor        ISSN: 0001-5342            Impact factor:   1.774


  3 in total

1.  A Model for the Lifespan Loss Due to a Viral Disease: Example of the COVID-19 Outbreak.

Authors:  Kayode Oshinubi; Cécile Fougère; Jacques Demongeot
Journal:  Infect Dis Rep       Date:  2022-04-25

Review 2.  Insights into the Regulatory Role of Non-coding RNAs in Cancer Metabolism.

Authors:  Fredy O Beltrán-Anaya; Alberto Cedro-Tanda; Alfredo Hidalgo-Miranda; Sandra L Romero-Cordoba
Journal:  Front Physiol       Date:  2016-08-08       Impact factor: 4.566

3.  SARS-CoV-2 and miRNA-like inhibition power.

Authors:  Jacques Demongeot; Hervé Seligmann
Journal:  Med Hypotheses       Date:  2020-09-04       Impact factor: 1.538

  3 in total

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