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Prediction of Bacterial microRNAs and possible targets in human cell transcriptome

Abstract

Recent studies have examined gene transfer from bacteria to humans that would result in vertical inheritance. Bacterial DNA appears to integrate into the human somatic genome through an RNA intermediate, and such integrations are detected more frequently in tumors than normal samples and in RNA than DNA samples. Also, vertebrate viruses encode products that interfere with the RNA silencing machinery, suggesting that RNA silencing may indeed be important for antiviral responses in vertebrates. RNA silencing in response to virus infection could be due to microRNAs encoded by either the virus or the host. We hypothesized that bacterial expression of RNA molecules with secondary structures is potentially able to generate miRNA molecules that can interact with the human host mRNA during bacterial infection. To test this hypothesis, we developed a pipelinebased bioinformatics approach to identify putative micro-RNAs derived from bacterial RNAs that may have the potential to regulate gene expression of the human host cell. Our results suggest that 68 bacterial RNAs predicted from 37 different bacterial genomes have predicted secondary structures potentially able to generate putative microRNAs that may interact with messenger RNAs of genes involved in 47 different human diseases. As an example, we examined the effect of transfecting three putative microRNAs into human embryonic kidney 293 (HEK293) cells. The results show that the bacterially derived microRNA sequence can significantly regulate the expression of the respective target human gene. We suggest that the study of these predicted microRNAs may yield important clues as to how the human host cell processes involved in human diseases like cancer, diabetes, rheumatoid arthritis, and others may respond to a particular bacterial environment.

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Correspondence to Amir Shmaryahu.

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Shmaryahu, A., Carrasco, M. & Valenzuela, P.D. Prediction of Bacterial microRNAs and possible targets in human cell transcriptome. J Microbiol. 52, 482–489 (2014). https://doi.org/10.1007/s12275-014-3658-3

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Keywords

  • bioinformatics
  • RNA structure
  • microRNA
  • bacterial RNA
  • human diseases