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The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes
BACKGROUND: Tuberculosis remains a leading infectious disease with global public health threat. Its control and management have been complicated by multi-drug resistance and latent infection, which prompts scientists to find new and more effective drugs. With the completion of the genome sequence of...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1884158/ https://www.ncbi.nlm.nih.gov/pubmed/17501996 http://dx.doi.org/10.1186/1471-2180-7-37 |
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author | Fu, Li M Fu-Liu, Casey S |
author_facet | Fu, Li M Fu-Liu, Casey S |
author_sort | Fu, Li M |
collection | PubMed |
description | BACKGROUND: Tuberculosis remains a leading infectious disease with global public health threat. Its control and management have been complicated by multi-drug resistance and latent infection, which prompts scientists to find new and more effective drugs. With the completion of the genome sequence of the etiologic bacterium, Mycobacterium tuberculosis, it is now feasible to search for new drug targets by sieving through a large number of gene products and conduct genome-scale experiments based on microarray technology. However, the full potential of genome-wide microarray analysis in configuring interrelationships among all genes in M. tuberculosis has yet to be realized. To date, it is only possible to assign a function to 52% of proteins predicted in the genome. RESULTS: We conducted a functional-genomics study using the high-resolution Affymetrix oligonucleotide GeneChip. Approximately one-half of the genes were found to be always expressed, including more than 100 predicted conserved hypotheticals, in the genome of M. tuberculosis during the log phase of in vitro growth. The gene expression profiles were analyzed and visualized through cluster analysis to epitomize the full details of genomic behavior. Broad patterns derived from genome-wide expression experiments in this study have provided insight into the interrelationships among genes in the basic cellular processes of M. tuberculosis. CONCLUSION: Our results have confirmed several known gene clusters in energy production, information pathways, and lipid metabolism, and also hinted at potential roles of hypothetical and regulatory proteins. |
format | Text |
id | pubmed-1884158 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18841582007-05-30 The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes Fu, Li M Fu-Liu, Casey S BMC Microbiol Research Article BACKGROUND: Tuberculosis remains a leading infectious disease with global public health threat. Its control and management have been complicated by multi-drug resistance and latent infection, which prompts scientists to find new and more effective drugs. With the completion of the genome sequence of the etiologic bacterium, Mycobacterium tuberculosis, it is now feasible to search for new drug targets by sieving through a large number of gene products and conduct genome-scale experiments based on microarray technology. However, the full potential of genome-wide microarray analysis in configuring interrelationships among all genes in M. tuberculosis has yet to be realized. To date, it is only possible to assign a function to 52% of proteins predicted in the genome. RESULTS: We conducted a functional-genomics study using the high-resolution Affymetrix oligonucleotide GeneChip. Approximately one-half of the genes were found to be always expressed, including more than 100 predicted conserved hypotheticals, in the genome of M. tuberculosis during the log phase of in vitro growth. The gene expression profiles were analyzed and visualized through cluster analysis to epitomize the full details of genomic behavior. Broad patterns derived from genome-wide expression experiments in this study have provided insight into the interrelationships among genes in the basic cellular processes of M. tuberculosis. CONCLUSION: Our results have confirmed several known gene clusters in energy production, information pathways, and lipid metabolism, and also hinted at potential roles of hypothetical and regulatory proteins. BioMed Central 2007-05-14 /pmc/articles/PMC1884158/ /pubmed/17501996 http://dx.doi.org/10.1186/1471-2180-7-37 Text en Copyright © 2007 Fu and Fu-Liu; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Fu, Li M Fu-Liu, Casey S The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes |
title | The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes |
title_full | The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes |
title_fullStr | The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes |
title_full_unstemmed | The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes |
title_short | The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes |
title_sort | gene expression data of mycobacterium tuberculosis based on affymetrix gene chips provide insight into regulatory and hypothetical genes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1884158/ https://www.ncbi.nlm.nih.gov/pubmed/17501996 http://dx.doi.org/10.1186/1471-2180-7-37 |
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