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Different Transcriptional Profiles of RAW264.7 Infected with Mycobacterium tuberculosis H37Rv and BCG Identified via Deep Sequencing
BACKGROUND: The Mycobacterium tuberculosis H37Rv and BCG effects on the host cell transcriptional profile consider a main research point. In the present study the transcriptome profiling analysis of RAW264.7 either infected with Mycobacterium tuberculosis H37Rv or BCG have been reported using Solexa...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3526534/ https://www.ncbi.nlm.nih.gov/pubmed/23284841 http://dx.doi.org/10.1371/journal.pone.0051988 |
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author | Pan, Fengguang Zhao, Yaya Zhu, Seng Sun, Changjiang Lei, Liancheng Feng, Xin Han, Wen yu |
author_facet | Pan, Fengguang Zhao, Yaya Zhu, Seng Sun, Changjiang Lei, Liancheng Feng, Xin Han, Wen yu |
author_sort | Pan, Fengguang |
collection | PubMed |
description | BACKGROUND: The Mycobacterium tuberculosis H37Rv and BCG effects on the host cell transcriptional profile consider a main research point. In the present study the transcriptome profiling analysis of RAW264.7 either infected with Mycobacterium tuberculosis H37Rv or BCG have been reported using Solexa/Illumina digital gene expression (DGE). RESULTS: The DGE analysis showed 1,917 different expressed genes between the BCG and H37Rv group. In addition, approximately 5% of the transcripts appeared to be predicted genes that have never been described before. KEGG Orthology (KO) annotations showed more than 71% of these transcripts are possibly involved in approximately 210 known metabolic or signaling pathways. The gene of the 28 pathways about pathogen recognition receptors and Mycobacterium tuberculosis interaction with macrophages were analyzed using the CLUSTER 3.0 available, the Tree View tool and Gene Orthology (GO). Some genes were randomly selected to confirm their altered expression levels by quantitative real-time PCR (qRT-PCR). CONCLUSION: The present study used DGE from pathogen recognition receptors and Mycobacterium tuberculosis interaction with macrophages to understand the interplay between Mycobacterium tuberculosis and RAW264.7. Meanwhile find some important host protein which was affected by Mycobacterium tuberculosis to provide evidence for the further improvement of the present efficacy of existing Mycobacterium tuberculosis therapy and vaccine. |
format | Online Article Text |
id | pubmed-3526534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-35265342013-01-02 Different Transcriptional Profiles of RAW264.7 Infected with Mycobacterium tuberculosis H37Rv and BCG Identified via Deep Sequencing Pan, Fengguang Zhao, Yaya Zhu, Seng Sun, Changjiang Lei, Liancheng Feng, Xin Han, Wen yu PLoS One Research Article BACKGROUND: The Mycobacterium tuberculosis H37Rv and BCG effects on the host cell transcriptional profile consider a main research point. In the present study the transcriptome profiling analysis of RAW264.7 either infected with Mycobacterium tuberculosis H37Rv or BCG have been reported using Solexa/Illumina digital gene expression (DGE). RESULTS: The DGE analysis showed 1,917 different expressed genes between the BCG and H37Rv group. In addition, approximately 5% of the transcripts appeared to be predicted genes that have never been described before. KEGG Orthology (KO) annotations showed more than 71% of these transcripts are possibly involved in approximately 210 known metabolic or signaling pathways. The gene of the 28 pathways about pathogen recognition receptors and Mycobacterium tuberculosis interaction with macrophages were analyzed using the CLUSTER 3.0 available, the Tree View tool and Gene Orthology (GO). Some genes were randomly selected to confirm their altered expression levels by quantitative real-time PCR (qRT-PCR). CONCLUSION: The present study used DGE from pathogen recognition receptors and Mycobacterium tuberculosis interaction with macrophages to understand the interplay between Mycobacterium tuberculosis and RAW264.7. Meanwhile find some important host protein which was affected by Mycobacterium tuberculosis to provide evidence for the further improvement of the present efficacy of existing Mycobacterium tuberculosis therapy and vaccine. Public Library of Science 2012-12-19 /pmc/articles/PMC3526534/ /pubmed/23284841 http://dx.doi.org/10.1371/journal.pone.0051988 Text en © 2012 Pan et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Pan, Fengguang Zhao, Yaya Zhu, Seng Sun, Changjiang Lei, Liancheng Feng, Xin Han, Wen yu Different Transcriptional Profiles of RAW264.7 Infected with Mycobacterium tuberculosis H37Rv and BCG Identified via Deep Sequencing |
title | Different Transcriptional Profiles of RAW264.7 Infected with Mycobacterium tuberculosis H37Rv and BCG Identified via Deep Sequencing |
title_full | Different Transcriptional Profiles of RAW264.7 Infected with Mycobacterium tuberculosis H37Rv and BCG Identified via Deep Sequencing |
title_fullStr | Different Transcriptional Profiles of RAW264.7 Infected with Mycobacterium tuberculosis H37Rv and BCG Identified via Deep Sequencing |
title_full_unstemmed | Different Transcriptional Profiles of RAW264.7 Infected with Mycobacterium tuberculosis H37Rv and BCG Identified via Deep Sequencing |
title_short | Different Transcriptional Profiles of RAW264.7 Infected with Mycobacterium tuberculosis H37Rv and BCG Identified via Deep Sequencing |
title_sort | different transcriptional profiles of raw264.7 infected with mycobacterium tuberculosis h37rv and bcg identified via deep sequencing |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3526534/ https://www.ncbi.nlm.nih.gov/pubmed/23284841 http://dx.doi.org/10.1371/journal.pone.0051988 |
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