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The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes.

Fu LM, Fu-Liu CS - BMC Microbiol. (2007)

Bottom Line: Its control and management have been complicated by multi-drug resistance and latent infection, which prompts scientists to find new and more effective drugs.To date, it is only possible to assign a function to 52% of proteins predicted in the genome.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Pacific Tuberculosis and Cancer Research Organization, Irvine, California, USA. lifu@patcar.org

ABSTRACT

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.

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Related in: MedlinePlus

The gene expression map of genes involved in the log-phase growth of Mycobacterium tuberculosis. The map was generated by Eisen's cluster-analysis program called CLUSTER and viewed by the TREEVIEW program. Several clusters representing aggregations of functionally related genes are visible in the dendrogram (on the left of the image) showing how genes are grouped. The detailed image is available at our web site [see Additional file 2] annotated with gene names alongside of the image strip [see Additional file 3].
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Figure 1: The gene expression map of genes involved in the log-phase growth of Mycobacterium tuberculosis. The map was generated by Eisen's cluster-analysis program called CLUSTER and viewed by the TREEVIEW program. Several clusters representing aggregations of functionally related genes are visible in the dendrogram (on the left of the image) showing how genes are grouped. The detailed image is available at our web site [see Additional file 2] annotated with gene names alongside of the image strip [see Additional file 3].

Mentions: The microarray data of those genes involved in the in vitro growth of M. tuberculosis during log phase were analyzed through the hierarchical clustering algorithm of Eisen's Cluster program [12]. This cluster-analysis program allowed us to explore the internal structure of the data and derive useful information concerning the coordination and collaboration among the genes. A measure fundamental to clustering is that of similarity. We define similarity between genes by their correlation in terms of gene expression patterns across multiple samples. The dendrogram generated by the algorithm (Figure 1) was organized according to this measure and displayed in a way to optimize the similarity of adjacent elements (genes). In the dendrogram, more related genes were joined earlier, and several highly dense clusters with peaks spreading along were visible.


The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes.

Fu LM, Fu-Liu CS - BMC Microbiol. (2007)

The gene expression map of genes involved in the log-phase growth of Mycobacterium tuberculosis. The map was generated by Eisen's cluster-analysis program called CLUSTER and viewed by the TREEVIEW program. Several clusters representing aggregations of functionally related genes are visible in the dendrogram (on the left of the image) showing how genes are grouped. The detailed image is available at our web site [see Additional file 2] annotated with gene names alongside of the image strip [see Additional file 3].
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1884158&req=5

Figure 1: The gene expression map of genes involved in the log-phase growth of Mycobacterium tuberculosis. The map was generated by Eisen's cluster-analysis program called CLUSTER and viewed by the TREEVIEW program. Several clusters representing aggregations of functionally related genes are visible in the dendrogram (on the left of the image) showing how genes are grouped. The detailed image is available at our web site [see Additional file 2] annotated with gene names alongside of the image strip [see Additional file 3].
Mentions: The microarray data of those genes involved in the in vitro growth of M. tuberculosis during log phase were analyzed through the hierarchical clustering algorithm of Eisen's Cluster program [12]. This cluster-analysis program allowed us to explore the internal structure of the data and derive useful information concerning the coordination and collaboration among the genes. A measure fundamental to clustering is that of similarity. We define similarity between genes by their correlation in terms of gene expression patterns across multiple samples. The dendrogram generated by the algorithm (Figure 1) was organized according to this measure and displayed in a way to optimize the similarity of adjacent elements (genes). In the dendrogram, more related genes were joined earlier, and several highly dense clusters with peaks spreading along were visible.

Bottom Line: Its control and management have been complicated by multi-drug resistance and latent infection, which prompts scientists to find new and more effective drugs.To date, it is only possible to assign a function to 52% of proteins predicted in the genome.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Pacific Tuberculosis and Cancer Research Organization, Irvine, California, USA. lifu@patcar.org

ABSTRACT

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.

Show MeSH
Related in: MedlinePlus