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Construction and verification of the transcriptional regulatory response network of Streptococcus mutans upon treatment with the biofilm inhibitor carolacton.

Sudhakar P, Reck M, Wang W, He FQ, Wagner-Döbler I, Dobler IW, Zeng AP - BMC Genomics (2014)

Bottom Line: To unravel key regulators mediating these effects, the transcriptional regulatory response network of S. mutans biofilms upon carolacton treatment was constructed and analyzed.These sub-networks were significantly enriched with genes sharing common functions.Deletion of cysR, the node having the highest connectivity among the regulators chosen from the regulatory network, resulted in a mutant which was insensitive to carolacton thus demonstrating not only the essentiality of cysR for the response of S. mutans biofilms to carolacton but also the relevance of the predicted network.

View Article: PubMed Central - PubMed

Affiliation: Institute of Bioprocess and Biosystems Engineering, Hamburg University of Technology, 21073 Hamburg, Germany. iwd@helmholtz-hzi.de.

ABSTRACT

Background: Carolacton is a newly identified secondary metabolite causing altered cell morphology and death of Streptococcus mutans biofilm cells. To unravel key regulators mediating these effects, the transcriptional regulatory response network of S. mutans biofilms upon carolacton treatment was constructed and analyzed. A systems biological approach integrating time-resolved transcriptomic data, reverse engineering, transcription factor binding sites, and experimental validation was carried out.

Results: The co-expression response network constructed from transcriptomic data using the reverse engineering algorithm called the Trend Correlation method consisted of 8284 gene pairs. The regulatory response network inferred by superimposing transcription factor binding site information into the co-expression network comprised 329 putative transcriptional regulatory interactions and could be classified into 27 sub-networks each co-regulated by a transcription factor. These sub-networks were significantly enriched with genes sharing common functions. The regulatory response network displayed global hierarchy and network motifs as observed in model organisms. The sub-networks modulated by the pyrimidine biosynthesis regulator PyrR, the glutamine synthetase repressor GlnR, the cysteine metabolism regulator CysR, global regulators CcpA and CodY and the two component system response regulators VicR and MbrC among others could putatively be related to the physiological effect of carolacton. The predicted interactions from the regulatory network between MbrC, known to be involved in cell envelope stress response, and the murMN-SMU_718c genes encoding peptidoglycan biosynthetic enzymes were experimentally confirmed using Electro Mobility Shift Assays. Furthermore, gene deletion mutants of five predicted key regulators from the response networks were constructed and their sensitivities towards carolacton were investigated. Deletion of cysR, the node having the highest connectivity among the regulators chosen from the regulatory network, resulted in a mutant which was insensitive to carolacton thus demonstrating not only the essentiality of cysR for the response of S. mutans biofilms to carolacton but also the relevance of the predicted network.

Conclusion: The network approach used in this study revealed important regulators and interactions as part of the response mechanisms of S. mutans biofilm cells to carolacton. It also opens a door for further studies into novel drug targets against streptococci.

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Topological view of the transcriptional regulatory response network (TRRN) ofS. mutansbiofilms upon carolacton treatment. The TRRN was inferred by overlaying the regulator-target gene binding site map onto the co-expression network. It consisted of 27 co-regulated gene groups or subnetworks each under the control of a transcription factor and comprised 329 regulatory interactions involving 307 genes. Some of the co-regulated gene groups overlap with each other as a result of genes modulated by more than one transcription factor. The 27 regulators with outgoing connections (marked with red circles) along with 10 other regulators only with incoming connections (marked with black circles) found to be among target genes within the sub-networks are indicated as well as non-regulator target genes (indicated by green circles). If the upstream regulatory regions of the target genes or their corresponding operons harbored multiple putative binding sites of its predicted regulator(s), then they are indicated by orange circles). In addition, the regulators with outgoing connections are also marked with their gene names above their respective nodes. Blue arrows indicate a positive (activation) relationship whereas red arrows stand for a negative (repression) effect. Connections always flow from top to bottom. Spatial positions of transcription factor nodes are manipulated so as to pictorially depict the possible hierarchies. The carolacton context TRRN shown herein is observed to be organized as a double layered hierarchy. The network was visualized using Cytoscape.
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Fig2: Topological view of the transcriptional regulatory response network (TRRN) ofS. mutansbiofilms upon carolacton treatment. The TRRN was inferred by overlaying the regulator-target gene binding site map onto the co-expression network. It consisted of 27 co-regulated gene groups or subnetworks each under the control of a transcription factor and comprised 329 regulatory interactions involving 307 genes. Some of the co-regulated gene groups overlap with each other as a result of genes modulated by more than one transcription factor. The 27 regulators with outgoing connections (marked with red circles) along with 10 other regulators only with incoming connections (marked with black circles) found to be among target genes within the sub-networks are indicated as well as non-regulator target genes (indicated by green circles). If the upstream regulatory regions of the target genes or their corresponding operons harbored multiple putative binding sites of its predicted regulator(s), then they are indicated by orange circles). In addition, the regulators with outgoing connections are also marked with their gene names above their respective nodes. Blue arrows indicate a positive (activation) relationship whereas red arrows stand for a negative (repression) effect. Connections always flow from top to bottom. Spatial positions of transcription factor nodes are manipulated so as to pictorially depict the possible hierarchies. The carolacton context TRRN shown herein is observed to be organized as a double layered hierarchy. The network was visualized using Cytoscape.

Mentions: Combining inferred correlation relationships from the co-expression network and the regulator-binding site map resulted in 227 transcriptional regulatory relationships with predicted direct biological causality (see Additional file 5). After operon oriented adjustment (see Methods), the transcriptional response regulatory network (TRRN) (Figure 2) comprised 329 relationships among 307 genes, of which 37 were found to be transcription factors. Based on the predicted transcriptional regulatory connections, the TRRN genes could be organized into 27 co-regulated gene groups or sub-networks. A co-regulated gene group is defined as a set of genes which are putatively regulated by a common transcription factor. 10 of the 37 regulators were associated with predicted incoming connections only and were contained within the 27 sub-networks with different size distributions. The largest sub-network was that putatively modulated by CodY (which is a known global regulator [38]) and comprised 84 genes. The second largest sub-network consisted of 26 genes under the putative control of CysR (the cysteine metabolism regulatory protein encoded by SMU_852) followed by two sub-networks each containing 22 genes and predicted to be modulated by the essential TCS response regulator VicR and the global regulator CcpA, respectively.Figure 2


Construction and verification of the transcriptional regulatory response network of Streptococcus mutans upon treatment with the biofilm inhibitor carolacton.

Sudhakar P, Reck M, Wang W, He FQ, Wagner-Döbler I, Dobler IW, Zeng AP - BMC Genomics (2014)

Topological view of the transcriptional regulatory response network (TRRN) ofS. mutansbiofilms upon carolacton treatment. The TRRN was inferred by overlaying the regulator-target gene binding site map onto the co-expression network. It consisted of 27 co-regulated gene groups or subnetworks each under the control of a transcription factor and comprised 329 regulatory interactions involving 307 genes. Some of the co-regulated gene groups overlap with each other as a result of genes modulated by more than one transcription factor. The 27 regulators with outgoing connections (marked with red circles) along with 10 other regulators only with incoming connections (marked with black circles) found to be among target genes within the sub-networks are indicated as well as non-regulator target genes (indicated by green circles). If the upstream regulatory regions of the target genes or their corresponding operons harbored multiple putative binding sites of its predicted regulator(s), then they are indicated by orange circles). In addition, the regulators with outgoing connections are also marked with their gene names above their respective nodes. Blue arrows indicate a positive (activation) relationship whereas red arrows stand for a negative (repression) effect. Connections always flow from top to bottom. Spatial positions of transcription factor nodes are manipulated so as to pictorially depict the possible hierarchies. The carolacton context TRRN shown herein is observed to be organized as a double layered hierarchy. The network was visualized using Cytoscape.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4048456&req=5

Fig2: Topological view of the transcriptional regulatory response network (TRRN) ofS. mutansbiofilms upon carolacton treatment. The TRRN was inferred by overlaying the regulator-target gene binding site map onto the co-expression network. It consisted of 27 co-regulated gene groups or subnetworks each under the control of a transcription factor and comprised 329 regulatory interactions involving 307 genes. Some of the co-regulated gene groups overlap with each other as a result of genes modulated by more than one transcription factor. The 27 regulators with outgoing connections (marked with red circles) along with 10 other regulators only with incoming connections (marked with black circles) found to be among target genes within the sub-networks are indicated as well as non-regulator target genes (indicated by green circles). If the upstream regulatory regions of the target genes or their corresponding operons harbored multiple putative binding sites of its predicted regulator(s), then they are indicated by orange circles). In addition, the regulators with outgoing connections are also marked with their gene names above their respective nodes. Blue arrows indicate a positive (activation) relationship whereas red arrows stand for a negative (repression) effect. Connections always flow from top to bottom. Spatial positions of transcription factor nodes are manipulated so as to pictorially depict the possible hierarchies. The carolacton context TRRN shown herein is observed to be organized as a double layered hierarchy. The network was visualized using Cytoscape.
Mentions: Combining inferred correlation relationships from the co-expression network and the regulator-binding site map resulted in 227 transcriptional regulatory relationships with predicted direct biological causality (see Additional file 5). After operon oriented adjustment (see Methods), the transcriptional response regulatory network (TRRN) (Figure 2) comprised 329 relationships among 307 genes, of which 37 were found to be transcription factors. Based on the predicted transcriptional regulatory connections, the TRRN genes could be organized into 27 co-regulated gene groups or sub-networks. A co-regulated gene group is defined as a set of genes which are putatively regulated by a common transcription factor. 10 of the 37 regulators were associated with predicted incoming connections only and were contained within the 27 sub-networks with different size distributions. The largest sub-network was that putatively modulated by CodY (which is a known global regulator [38]) and comprised 84 genes. The second largest sub-network consisted of 26 genes under the putative control of CysR (the cysteine metabolism regulatory protein encoded by SMU_852) followed by two sub-networks each containing 22 genes and predicted to be modulated by the essential TCS response regulator VicR and the global regulator CcpA, respectively.Figure 2

Bottom Line: To unravel key regulators mediating these effects, the transcriptional regulatory response network of S. mutans biofilms upon carolacton treatment was constructed and analyzed.These sub-networks were significantly enriched with genes sharing common functions.Deletion of cysR, the node having the highest connectivity among the regulators chosen from the regulatory network, resulted in a mutant which was insensitive to carolacton thus demonstrating not only the essentiality of cysR for the response of S. mutans biofilms to carolacton but also the relevance of the predicted network.

View Article: PubMed Central - PubMed

Affiliation: Institute of Bioprocess and Biosystems Engineering, Hamburg University of Technology, 21073 Hamburg, Germany. iwd@helmholtz-hzi.de.

ABSTRACT

Background: Carolacton is a newly identified secondary metabolite causing altered cell morphology and death of Streptococcus mutans biofilm cells. To unravel key regulators mediating these effects, the transcriptional regulatory response network of S. mutans biofilms upon carolacton treatment was constructed and analyzed. A systems biological approach integrating time-resolved transcriptomic data, reverse engineering, transcription factor binding sites, and experimental validation was carried out.

Results: The co-expression response network constructed from transcriptomic data using the reverse engineering algorithm called the Trend Correlation method consisted of 8284 gene pairs. The regulatory response network inferred by superimposing transcription factor binding site information into the co-expression network comprised 329 putative transcriptional regulatory interactions and could be classified into 27 sub-networks each co-regulated by a transcription factor. These sub-networks were significantly enriched with genes sharing common functions. The regulatory response network displayed global hierarchy and network motifs as observed in model organisms. The sub-networks modulated by the pyrimidine biosynthesis regulator PyrR, the glutamine synthetase repressor GlnR, the cysteine metabolism regulator CysR, global regulators CcpA and CodY and the two component system response regulators VicR and MbrC among others could putatively be related to the physiological effect of carolacton. The predicted interactions from the regulatory network between MbrC, known to be involved in cell envelope stress response, and the murMN-SMU_718c genes encoding peptidoglycan biosynthetic enzymes were experimentally confirmed using Electro Mobility Shift Assays. Furthermore, gene deletion mutants of five predicted key regulators from the response networks were constructed and their sensitivities towards carolacton were investigated. Deletion of cysR, the node having the highest connectivity among the regulators chosen from the regulatory network, resulted in a mutant which was insensitive to carolacton thus demonstrating not only the essentiality of cysR for the response of S. mutans biofilms to carolacton but also the relevance of the predicted network.

Conclusion: The network approach used in this study revealed important regulators and interactions as part of the response mechanisms of S. mutans biofilm cells to carolacton. It also opens a door for further studies into novel drug targets against streptococci.

Show MeSH
Related in: MedlinePlus