Literature DB >> 35322335

Identification of the TF-miRNA-mRNA co-regulatory networks involved in sepsis.

Xiaoqian Luo1, Weina Lu1, Jianfeng Zhao2, Jun Hu1, Enjiang Chen1, Shi Fu2, Qinghui Fu3.   

Abstract

Sepsis is a life-threatening medical condition caused by a dysregulated host response to infection. Recent studies have found that the expression of miRNAs is associated with the pathogenesis of sepsis and septic shock. Our study aimed to reveal which miRNAs may be involved in the dysregulated immune response in sepsis and how these miRNAs interact with transcription factors (TFs) using a computational approach with in vitro validation studies. To determine the network of TFs, miRNAs, and target genes involved in sepsis, GEO datasets GSE94717 and GSE131761 were used to identify differentially expressed miRNAs and DEGs. TargetScan and miRWalk databases were used to predict biological targets that overlap with the identified DEGs of differentially expressed miRNAs. The TransmiR database was used to predict the differential miRNA TFs that overlap with the identified DEGs. The TF-miRNA-mRNA network was constructed and visualized. Finally, qRT-PCR was used to verify the expression of TFs and miRNA in HUVECs. Between the healthy and sepsis groups, there were 146 upregulated and 98 downregulated DEGs in the GSE131761 dataset, and there were 1 upregulated and 183 downregulated DEMs in the GSE94717 dataset. A regulatory network of the TF-miRna target genes was established. According to the experimental results, RUNX3 was found to be downregulated while MAPK14 was upregulated, which corroborates the result of the computational expression analysis. In a HUVECs model, miR-19b-1-5p and miR-5009-5p were found to be significantly downregulated. Other TFs and miRNAs did not correlate with our bioinformatics expression analysis. We constructed a TF-miRNA-target gene regulatory network and identified potential treatment targets RUNX3, MAPK14, miR-19b-1-5p, and miR-5009-5p. This information provides an initial basis for understanding the complex sepsis regulatory mechanisms.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Sepsis; Transcription factors; miRNA

Mesh:

Substances:

Year:  2022        PMID: 35322335     DOI: 10.1007/s10142-022-00843-x

Source DB:  PubMed          Journal:  Funct Integr Genomics        ISSN: 1438-793X            Impact factor:   3.674


  29 in total

1.  Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

Authors:  M Ashburner; C A Ball; J A Blake; D Botstein; H Butler; J M Cherry; A P Davis; K Dolinski; S S Dwight; J T Eppig; M A Harris; D P Hill; L Issel-Tarver; A Kasarskis; S Lewis; J C Matese; J E Richardson; M Ringwald; G M Rubin; G Sherlock
Journal:  Nat Genet       Date:  2000-05       Impact factor: 38.330

2.  Gene Expression Omnibus: NCBI gene expression and hybridization array data repository.

Authors:  Ron Edgar; Michael Domrachev; Alex E Lash
Journal:  Nucleic Acids Res       Date:  2002-01-01       Impact factor: 16.971

3.  Specificity of microRNA target selection in translational repression.

Authors:  John G Doench; Phillip A Sharp
Journal:  Genes Dev       Date:  2004-03-10       Impact factor: 11.361

4.  The lingering consequences of sepsis: a hidden public health disaster?

Authors:  Derek C Angus
Journal:  JAMA       Date:  2010-10-27       Impact factor: 56.272

5.  miR-128-3p enhances the protective effect of dexmedetomidine on acute lung injury in septic mice by targeted inhibition of MAPK14.

Authors:  Li Ding; Xiang Gao; Shenghui Yu; Liufang Sheng
Journal:  J Bioenerg Biomembr       Date:  2020-06-27       Impact factor: 2.945

Review 6.  Roles for microRNAs in conferring robustness to biological processes.

Authors:  Margaret S Ebert; Phillip A Sharp
Journal:  Cell       Date:  2012-04-27       Impact factor: 41.582

Review 7.  Sepsis and septic shock.

Authors:  Maurizio Cecconi; Laura Evans; Mitchell Levy; Andrew Rhodes
Journal:  Lancet       Date:  2018-06-21       Impact factor: 79.321

Review 8.  Inflammation-induced cancer: crosstalk between tumours, immune cells and microorganisms.

Authors:  Eran Elinav; Roni Nowarski; Christoph A Thaiss; Bo Hu; Chengcheng Jin; Richard A Flavell
Journal:  Nat Rev Cancer       Date:  2013-11       Impact factor: 69.800

9.  Transcriptional reprogramming of CD11b+Esam(hi) dendritic cell identity and function by loss of Runx3.

Authors:  Joseph Dicken; Alexander Mildner; Dena Leshkowitz; Ivo P Touw; Shay Hantisteanu; Steffen Jung; Yoram Groner
Journal:  PLoS One       Date:  2013-10-15       Impact factor: 3.240

10.  STRING v9.1: protein-protein interaction networks, with increased coverage and integration.

Authors:  Andrea Franceschini; Damian Szklarczyk; Sune Frankild; Michael Kuhn; Milan Simonovic; Alexander Roth; Jianyi Lin; Pablo Minguez; Peer Bork; Christian von Mering; Lars J Jensen
Journal:  Nucleic Acids Res       Date:  2012-11-29       Impact factor: 16.971

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