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Multilevel systems biology analysis of lung transcriptomics data identifies key miRNAs and potential miRNA target genes for SARS-CoV-2 infection

BACKGROUND: The spread of a novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) has affected both the public health and the global economy. The current study was aimed at analysing the genetic sequence of this highly contagious corona virus from an evolutionary perspective, comparing...

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Autores principales: Banaganapalli, Babajan, Al-Rayes, Nuha, Awan, Zuhier Ahmed, Alsulaimany, Faten A., Alamri, Abdulhakeem S., Elango, Ramu, Malik, Md Zubbair, Shaik, Noor A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197616/
https://www.ncbi.nlm.nih.gov/pubmed/34157472
http://dx.doi.org/10.1016/j.compbiomed.2021.104570
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author Banaganapalli, Babajan
Al-Rayes, Nuha
Awan, Zuhier Ahmed
Alsulaimany, Faten A.
Alamri, Abdulhakeem S.
Elango, Ramu
Malik, Md Zubbair
Shaik, Noor A.
author_facet Banaganapalli, Babajan
Al-Rayes, Nuha
Awan, Zuhier Ahmed
Alsulaimany, Faten A.
Alamri, Abdulhakeem S.
Elango, Ramu
Malik, Md Zubbair
Shaik, Noor A.
author_sort Banaganapalli, Babajan
collection PubMed
description BACKGROUND: The spread of a novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) has affected both the public health and the global economy. The current study was aimed at analysing the genetic sequence of this highly contagious corona virus from an evolutionary perspective, comparing the genetic variation features of different geographic strains, and identifying the key miRNAs as well as their gene targets from the transcriptome data of infected lung tissues. METHODS: A multilevel robust computational analysis was undertaken for viral genetic sequence alignment, phylogram construction, genome-wide transcriptome data interpretation of virus-infected lung tissues, miRNA mapping, and functional biology networking. RESULTS: Our findings show both genetic similarities as well as notable differences in the S protein length among SARS-CoV-1, SARS-CoV-2 and MERS viruses. All SARS-CoV-2 strains showed a high genetic similarity with the parent Wuhan strain, but Saudi Arabian, South African, USA, Russia and New Zealand strains carry 3 additional genetic variations like P333L (RNA -dependant RNA polymerase), D614G (spike), and P4715L (ORF1ab). The infected lung tissues demonstrated the upregulation of 282 (56.51%) antiviral defensive response pathway genes and downregulation of 217 (43.48%) genes involved in autophagy and lung repair pathways. By miRNA mapping, 4 key miRNAs (hsa-miR-342-5p, hsa-miR-432-5p, hsa-miR-98-5p and hsa-miR-17-5p), targeting multiple host genes (MYC, IL6, ICAM1 and VEGFA) as well as SARS-CoV2 gene (ORF1ab) were identified. CONCLUSION: Systems biology methods offer a new perspective in understanding the molecular basis for the faster spread of SARS-CoV-2 infection. The antiviral miRNAs identified in this study may aid in the ongoing search for novel personalized therapeutic avenues for COVID patients.
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spelling pubmed-81976162021-06-15 Multilevel systems biology analysis of lung transcriptomics data identifies key miRNAs and potential miRNA target genes for SARS-CoV-2 infection Banaganapalli, Babajan Al-Rayes, Nuha Awan, Zuhier Ahmed Alsulaimany, Faten A. Alamri, Abdulhakeem S. Elango, Ramu Malik, Md Zubbair Shaik, Noor A. Comput Biol Med Article BACKGROUND: The spread of a novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) has affected both the public health and the global economy. The current study was aimed at analysing the genetic sequence of this highly contagious corona virus from an evolutionary perspective, comparing the genetic variation features of different geographic strains, and identifying the key miRNAs as well as their gene targets from the transcriptome data of infected lung tissues. METHODS: A multilevel robust computational analysis was undertaken for viral genetic sequence alignment, phylogram construction, genome-wide transcriptome data interpretation of virus-infected lung tissues, miRNA mapping, and functional biology networking. RESULTS: Our findings show both genetic similarities as well as notable differences in the S protein length among SARS-CoV-1, SARS-CoV-2 and MERS viruses. All SARS-CoV-2 strains showed a high genetic similarity with the parent Wuhan strain, but Saudi Arabian, South African, USA, Russia and New Zealand strains carry 3 additional genetic variations like P333L (RNA -dependant RNA polymerase), D614G (spike), and P4715L (ORF1ab). The infected lung tissues demonstrated the upregulation of 282 (56.51%) antiviral defensive response pathway genes and downregulation of 217 (43.48%) genes involved in autophagy and lung repair pathways. By miRNA mapping, 4 key miRNAs (hsa-miR-342-5p, hsa-miR-432-5p, hsa-miR-98-5p and hsa-miR-17-5p), targeting multiple host genes (MYC, IL6, ICAM1 and VEGFA) as well as SARS-CoV2 gene (ORF1ab) were identified. CONCLUSION: Systems biology methods offer a new perspective in understanding the molecular basis for the faster spread of SARS-CoV-2 infection. The antiviral miRNAs identified in this study may aid in the ongoing search for novel personalized therapeutic avenues for COVID patients. Elsevier Ltd. 2021-08 2021-06-12 /pmc/articles/PMC8197616/ /pubmed/34157472 http://dx.doi.org/10.1016/j.compbiomed.2021.104570 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Banaganapalli, Babajan
Al-Rayes, Nuha
Awan, Zuhier Ahmed
Alsulaimany, Faten A.
Alamri, Abdulhakeem S.
Elango, Ramu
Malik, Md Zubbair
Shaik, Noor A.
Multilevel systems biology analysis of lung transcriptomics data identifies key miRNAs and potential miRNA target genes for SARS-CoV-2 infection
title Multilevel systems biology analysis of lung transcriptomics data identifies key miRNAs and potential miRNA target genes for SARS-CoV-2 infection
title_full Multilevel systems biology analysis of lung transcriptomics data identifies key miRNAs and potential miRNA target genes for SARS-CoV-2 infection
title_fullStr Multilevel systems biology analysis of lung transcriptomics data identifies key miRNAs and potential miRNA target genes for SARS-CoV-2 infection
title_full_unstemmed Multilevel systems biology analysis of lung transcriptomics data identifies key miRNAs and potential miRNA target genes for SARS-CoV-2 infection
title_short Multilevel systems biology analysis of lung transcriptomics data identifies key miRNAs and potential miRNA target genes for SARS-CoV-2 infection
title_sort multilevel systems biology analysis of lung transcriptomics data identifies key mirnas and potential mirna target genes for sars-cov-2 infection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8197616/
https://www.ncbi.nlm.nih.gov/pubmed/34157472
http://dx.doi.org/10.1016/j.compbiomed.2021.104570
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