A mathematical model as a tool to identify microRNAs with highest impact on transcriptome changes.


Journal

BMC genomics
ISSN: 1471-2164
Titre abrégé: BMC Genomics
Pays: England
ID NLM: 100965258

Informations de publication

Date de publication:
06 Feb 2019
Historique:
received: 23 07 2018
accepted: 21 01 2019
entrez: 8 2 2019
pubmed: 8 2 2019
medline: 21 5 2019
Statut: epublish

Résumé

Rapid changes in the expression of many messenger RNA (mRNA) species follow exposure of cells to ionizing radiation. One of the hypothetical mechanisms of this response may include microRNA (miRNA) regulation, since the amounts of miRNAs in cells also vary upon irradiation. To address this possibility, we designed experiments using cancer-derived cell lines transfected with luciferase reporter gene containing sequences targeted by different miRNA species in its 3'- untranslated region. We focus on the early time-course response (1 h past irradiation) to eliminate secondary mRNA expression waves. Experiments revealed that the irradiation-induced changes in the mRNA expression depend on the miRNAs which interact with mRNA. To identify the strongest interactions, we propose a mathematical model which predicts the mRNA fold expression changes, caused by perturbation of microRNA-mRNA interactions. Model was applied to experimental data including various cell lines, irradiation doses and observation times, both ours and literature-based. Comparison of modelled and experimental mRNA expression levels given miRNA level changes allows estimating how many and which miRNAs play a significant role in transcriptome response to stress conditions in different cell types. As an example, in the human melanoma cell line the comparison suggests that, globally, a major part of the irradiation-induced changes of mRNA expression can be explained by perturbed miRNA-mRNA interactions. A subset of about 30 out of a few hundred miRNAs expressed in these cells appears to account for the changes. These miRNAs play crucial roles in regulatory mechanisms observed after irradiation. In addition, these miRNAs have a higher average content of GC and a higher number of targeted transcripts, and many have been reported to play a role in the development of cancer. Our proposed mathematical modeling approach may be used to identify miRNAs which participate in responses of cells to ionizing radiation, and other stress factors such as extremes of temperature, exposure to toxins, and drugs.

Sections du résumé

BACKGROUND BACKGROUND
Rapid changes in the expression of many messenger RNA (mRNA) species follow exposure of cells to ionizing radiation. One of the hypothetical mechanisms of this response may include microRNA (miRNA) regulation, since the amounts of miRNAs in cells also vary upon irradiation. To address this possibility, we designed experiments using cancer-derived cell lines transfected with luciferase reporter gene containing sequences targeted by different miRNA species in its 3'- untranslated region. We focus on the early time-course response (1 h past irradiation) to eliminate secondary mRNA expression waves.
RESULTS RESULTS
Experiments revealed that the irradiation-induced changes in the mRNA expression depend on the miRNAs which interact with mRNA. To identify the strongest interactions, we propose a mathematical model which predicts the mRNA fold expression changes, caused by perturbation of microRNA-mRNA interactions. Model was applied to experimental data including various cell lines, irradiation doses and observation times, both ours and literature-based. Comparison of modelled and experimental mRNA expression levels given miRNA level changes allows estimating how many and which miRNAs play a significant role in transcriptome response to stress conditions in different cell types. As an example, in the human melanoma cell line the comparison suggests that, globally, a major part of the irradiation-induced changes of mRNA expression can be explained by perturbed miRNA-mRNA interactions. A subset of about 30 out of a few hundred miRNAs expressed in these cells appears to account for the changes. These miRNAs play crucial roles in regulatory mechanisms observed after irradiation. In addition, these miRNAs have a higher average content of GC and a higher number of targeted transcripts, and many have been reported to play a role in the development of cancer.
CONCLUSIONS CONCLUSIONS
Our proposed mathematical modeling approach may be used to identify miRNAs which participate in responses of cells to ionizing radiation, and other stress factors such as extremes of temperature, exposure to toxins, and drugs.

Identifiants

pubmed: 30727966
doi: 10.1186/s12864-019-5464-0
pii: 10.1186/s12864-019-5464-0
pmc: PMC6366035
doi:

Substances chimiques

MicroRNAs 0
RNA, Messenger 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

114

Subventions

Organisme : Narodowe Centrum Nauki
ID : UMO-2015/19/B/ST7/02984

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Auteurs

Marzena Mura (M)

Department of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland. marzena.mura@polsl.pl.
, Ardigen S.A., ul. Bobrzyńskiego 14, 30-348, Cracow, Poland. marzena.mura@polsl.pl.

Roman Jaksik (R)

Department of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland.
Centre of Biotechnology, Silesian University of Technology, ul. Bolesława Krzywoustego 8, 44-100, Gliwice, Poland.

Anna Lalik (A)

Department of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland.
Centre of Biotechnology, Silesian University of Technology, ul. Bolesława Krzywoustego 8, 44-100, Gliwice, Poland.

Krzysztof Biernacki (K)

Department of Medical and Molecular Biology, School of Medicine with the Division of Dentistry in Zabrze, Medical University of Silesia in Katowice, Katowice, USA.

Marek Kimmel (M)

Department of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland.
Departments of Statistics and Bioengineering, Rice University, MS 138, 6100 Main, Houston, TX, 77005, USA.

Joanna Rzeszowska-Wolny (J)

Department of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland. joanna.rzeszowska@polsl.pl.
Centre of Biotechnology, Silesian University of Technology, ul. Bolesława Krzywoustego 8, 44-100, Gliwice, Poland. joanna.rzeszowska@polsl.pl.

Krzysztof Fujarewicz (K)

Department of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland.

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