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Control and signal processing by transcriptional interference.

Buetti-Dinh A, Ungricht R, Kelemen JZ, Shetty C, Ratna P, Becskei A - Mol. Syst. Biol. (2009)

Bottom Line: When gene expression is induced weakly, the antagonistic activator can have a positive effect and can even trigger paradoxical activation.Indeed, a synthetic circuit generates a bell-shaped response, so that the induction of expression is limited to a narrow range of the input signal.The identification of conserved regulatory principles of interference will help to predict the transcriptional response of genes in their genomic context.

View Article: PubMed Central - PubMed

Affiliation: Institute of Molecular Biology, University of Zurich, Zurich, Switzerland.

ABSTRACT
A transcriptional activator can suppress gene expression by interfering with transcription initiated by another activator. Transcriptional interference has been increasingly recognized as a regulatory mechanism of gene expression. The signals received by the two antagonistically acting activators are combined by the polymerase trafficking along the DNA. We have designed a dual-control genetic system in yeast to explore this antagonism systematically. Antagonism by an upstream activator bears the hallmarks of competitive inhibition, whereas a downstream activator inhibits gene expression non-competitively. When gene expression is induced weakly, the antagonistic activator can have a positive effect and can even trigger paradoxical activation. Equilibrium and non-equilibrium models of transcription shed light on the mechanism by which interference converts signals, and reveals that self-antagonism of activators imitates the behavior of feed-forward loops. Indeed, a synthetic circuit generates a bell-shaped response, so that the induction of expression is limited to a narrow range of the input signal. The identification of conserved regulatory principles of interference will help to predict the transcriptional response of genes in their genomic context.

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Downstream antagonism. The TATA box is denoted by a checkered diamond in the genetic constructs. Error bars represent s.d. values calculated from three experiments, unless otherwise specified. (A) Expression driven by PGALUAS-TATA-tetO2 (RUY20) in the presence of different fixed concentrations of doxycycline. The curves were obtained by fitting equation (2) (Box 1): KDA=0.067, α=3.2. f(R)=0.31 and 1.05 for respective doxycycline concentrations (B) Scheme of non-competitive inhibition. When the AUAS and ADI activators bind to the promoter simultaneously, no transcription is initiated. (C) Expression driven by PGALUAS-TATA-FUS1UAS (YABH42.1) in the presence of different fixed concentrations of α-factor. The FUS1UAS contains three binding sites for the endogenous Ste12p transcriptional activator. Expression was adjusted using the PGALUAS-TATA-MutFUS1UAS construct (YABH43.2) to account for the nonspecific effects of α-factor on expression (see Materials and methods section). The curves are fits to the non-equilibrium model of the downstream antagonism (see Supplementary Information, SEq2) with pUAS=0.01 nM−1 min−1, pDI=0.005 nM−1 min−1, α=32.8, m1=0.07 min−1, m2=0.1 min−1, p3=1 min−1, m3=0.2 min−1 and k=0.2 min−1, Atot=500 nM, Kind=2161 nM, vmax=619; [ADI]=0, 0.89, 2.79 and 4.46 for the respective α-factor concentrations. (D, E) Contour plots represent expression levels as a function of ADI and AUAS using the parameter values as in (C), except for pDI=0.01 nM−1 min−1, and the cooperativity of binding, α was varied: α=1 (D) and α=20 (E). (F) Expression driven by the PtetO7-TATA-tetO2 (RUY65) and PtetO7-CYC1TATA (RUY67.13) constructs. LacZ was used to detect gene expression with higher sensitivity. Expression of the PTATA-tetO2 construct (RUY69), which lacks an upstream activation sequence, is below the detection limit. The value for s.d. is calculated from two experiments. The bell-shaped curve was obtained by fitting SEq. 4 (w=470, n=m=1.2, N=0.46 and M=0.79). Source data is available for this figure at www.nature.com/msb
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f3: Downstream antagonism. The TATA box is denoted by a checkered diamond in the genetic constructs. Error bars represent s.d. values calculated from three experiments, unless otherwise specified. (A) Expression driven by PGALUAS-TATA-tetO2 (RUY20) in the presence of different fixed concentrations of doxycycline. The curves were obtained by fitting equation (2) (Box 1): KDA=0.067, α=3.2. f(R)=0.31 and 1.05 for respective doxycycline concentrations (B) Scheme of non-competitive inhibition. When the AUAS and ADI activators bind to the promoter simultaneously, no transcription is initiated. (C) Expression driven by PGALUAS-TATA-FUS1UAS (YABH42.1) in the presence of different fixed concentrations of α-factor. The FUS1UAS contains three binding sites for the endogenous Ste12p transcriptional activator. Expression was adjusted using the PGALUAS-TATA-MutFUS1UAS construct (YABH43.2) to account for the nonspecific effects of α-factor on expression (see Materials and methods section). The curves are fits to the non-equilibrium model of the downstream antagonism (see Supplementary Information, SEq2) with pUAS=0.01 nM−1 min−1, pDI=0.005 nM−1 min−1, α=32.8, m1=0.07 min−1, m2=0.1 min−1, p3=1 min−1, m3=0.2 min−1 and k=0.2 min−1, Atot=500 nM, Kind=2161 nM, vmax=619; [ADI]=0, 0.89, 2.79 and 4.46 for the respective α-factor concentrations. (D, E) Contour plots represent expression levels as a function of ADI and AUAS using the parameter values as in (C), except for pDI=0.01 nM−1 min−1, and the cooperativity of binding, α was varied: α=1 (D) and α=20 (E). (F) Expression driven by the PtetO7-TATA-tetO2 (RUY65) and PtetO7-CYC1TATA (RUY67.13) constructs. LacZ was used to detect gene expression with higher sensitivity. Expression of the PTATA-tetO2 construct (RUY69), which lacks an upstream activation sequence, is below the detection limit. The value for s.d. is calculated from two experiments. The bell-shaped curve was obtained by fitting SEq. 4 (w=470, n=m=1.2, N=0.46 and M=0.79). Source data is available for this figure at www.nature.com/msb

Mentions: To study antagonism by downstream activators, activator-binding sites were inserted downstream of the TATA box in the promoter–GFP constructs. Binding of GEV to the upstream site, GALUAS, drove the expression of GFP (Figure 3A). The binding of rtTA to tet operators downstream of a TATA box inhibited GFP expression (Figure 3A). This indicates that in addition to DNA-binding protein domains alone (Brent and Ptashne, 1984; Murphy et al, 2007), full-length transcriptional activators can interfere with the transcriptional activation. Expression data at different strengths of downstream antagonism were in excellent agreement with an equilibrium model for non-competitive inhibition that incorporates the cooperative binding of GEV and rtTA (Box 1, Figure 3A and B) (Cornish-Bowden, 2004). Cooperative binding of rtTA to promoters has been observed (Becskei et al, 2005). The cooperative interaction between the upstream and downstream sites could account for the observation that at a low estradiol concentration, inhibition is weaker than predicted by a model of pure non-competitive inhibition.


Control and signal processing by transcriptional interference.

Buetti-Dinh A, Ungricht R, Kelemen JZ, Shetty C, Ratna P, Becskei A - Mol. Syst. Biol. (2009)

Downstream antagonism. The TATA box is denoted by a checkered diamond in the genetic constructs. Error bars represent s.d. values calculated from three experiments, unless otherwise specified. (A) Expression driven by PGALUAS-TATA-tetO2 (RUY20) in the presence of different fixed concentrations of doxycycline. The curves were obtained by fitting equation (2) (Box 1): KDA=0.067, α=3.2. f(R)=0.31 and 1.05 for respective doxycycline concentrations (B) Scheme of non-competitive inhibition. When the AUAS and ADI activators bind to the promoter simultaneously, no transcription is initiated. (C) Expression driven by PGALUAS-TATA-FUS1UAS (YABH42.1) in the presence of different fixed concentrations of α-factor. The FUS1UAS contains three binding sites for the endogenous Ste12p transcriptional activator. Expression was adjusted using the PGALUAS-TATA-MutFUS1UAS construct (YABH43.2) to account for the nonspecific effects of α-factor on expression (see Materials and methods section). The curves are fits to the non-equilibrium model of the downstream antagonism (see Supplementary Information, SEq2) with pUAS=0.01 nM−1 min−1, pDI=0.005 nM−1 min−1, α=32.8, m1=0.07 min−1, m2=0.1 min−1, p3=1 min−1, m3=0.2 min−1 and k=0.2 min−1, Atot=500 nM, Kind=2161 nM, vmax=619; [ADI]=0, 0.89, 2.79 and 4.46 for the respective α-factor concentrations. (D, E) Contour plots represent expression levels as a function of ADI and AUAS using the parameter values as in (C), except for pDI=0.01 nM−1 min−1, and the cooperativity of binding, α was varied: α=1 (D) and α=20 (E). (F) Expression driven by the PtetO7-TATA-tetO2 (RUY65) and PtetO7-CYC1TATA (RUY67.13) constructs. LacZ was used to detect gene expression with higher sensitivity. Expression of the PTATA-tetO2 construct (RUY69), which lacks an upstream activation sequence, is below the detection limit. The value for s.d. is calculated from two experiments. The bell-shaped curve was obtained by fitting SEq. 4 (w=470, n=m=1.2, N=0.46 and M=0.79). Source data is available for this figure at www.nature.com/msb
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2736658&req=5

f3: Downstream antagonism. The TATA box is denoted by a checkered diamond in the genetic constructs. Error bars represent s.d. values calculated from three experiments, unless otherwise specified. (A) Expression driven by PGALUAS-TATA-tetO2 (RUY20) in the presence of different fixed concentrations of doxycycline. The curves were obtained by fitting equation (2) (Box 1): KDA=0.067, α=3.2. f(R)=0.31 and 1.05 for respective doxycycline concentrations (B) Scheme of non-competitive inhibition. When the AUAS and ADI activators bind to the promoter simultaneously, no transcription is initiated. (C) Expression driven by PGALUAS-TATA-FUS1UAS (YABH42.1) in the presence of different fixed concentrations of α-factor. The FUS1UAS contains three binding sites for the endogenous Ste12p transcriptional activator. Expression was adjusted using the PGALUAS-TATA-MutFUS1UAS construct (YABH43.2) to account for the nonspecific effects of α-factor on expression (see Materials and methods section). The curves are fits to the non-equilibrium model of the downstream antagonism (see Supplementary Information, SEq2) with pUAS=0.01 nM−1 min−1, pDI=0.005 nM−1 min−1, α=32.8, m1=0.07 min−1, m2=0.1 min−1, p3=1 min−1, m3=0.2 min−1 and k=0.2 min−1, Atot=500 nM, Kind=2161 nM, vmax=619; [ADI]=0, 0.89, 2.79 and 4.46 for the respective α-factor concentrations. (D, E) Contour plots represent expression levels as a function of ADI and AUAS using the parameter values as in (C), except for pDI=0.01 nM−1 min−1, and the cooperativity of binding, α was varied: α=1 (D) and α=20 (E). (F) Expression driven by the PtetO7-TATA-tetO2 (RUY65) and PtetO7-CYC1TATA (RUY67.13) constructs. LacZ was used to detect gene expression with higher sensitivity. Expression of the PTATA-tetO2 construct (RUY69), which lacks an upstream activation sequence, is below the detection limit. The value for s.d. is calculated from two experiments. The bell-shaped curve was obtained by fitting SEq. 4 (w=470, n=m=1.2, N=0.46 and M=0.79). Source data is available for this figure at www.nature.com/msb
Mentions: To study antagonism by downstream activators, activator-binding sites were inserted downstream of the TATA box in the promoter–GFP constructs. Binding of GEV to the upstream site, GALUAS, drove the expression of GFP (Figure 3A). The binding of rtTA to tet operators downstream of a TATA box inhibited GFP expression (Figure 3A). This indicates that in addition to DNA-binding protein domains alone (Brent and Ptashne, 1984; Murphy et al, 2007), full-length transcriptional activators can interfere with the transcriptional activation. Expression data at different strengths of downstream antagonism were in excellent agreement with an equilibrium model for non-competitive inhibition that incorporates the cooperative binding of GEV and rtTA (Box 1, Figure 3A and B) (Cornish-Bowden, 2004). Cooperative binding of rtTA to promoters has been observed (Becskei et al, 2005). The cooperative interaction between the upstream and downstream sites could account for the observation that at a low estradiol concentration, inhibition is weaker than predicted by a model of pure non-competitive inhibition.

Bottom Line: When gene expression is induced weakly, the antagonistic activator can have a positive effect and can even trigger paradoxical activation.Indeed, a synthetic circuit generates a bell-shaped response, so that the induction of expression is limited to a narrow range of the input signal.The identification of conserved regulatory principles of interference will help to predict the transcriptional response of genes in their genomic context.

View Article: PubMed Central - PubMed

Affiliation: Institute of Molecular Biology, University of Zurich, Zurich, Switzerland.

ABSTRACT
A transcriptional activator can suppress gene expression by interfering with transcription initiated by another activator. Transcriptional interference has been increasingly recognized as a regulatory mechanism of gene expression. The signals received by the two antagonistically acting activators are combined by the polymerase trafficking along the DNA. We have designed a dual-control genetic system in yeast to explore this antagonism systematically. Antagonism by an upstream activator bears the hallmarks of competitive inhibition, whereas a downstream activator inhibits gene expression non-competitively. When gene expression is induced weakly, the antagonistic activator can have a positive effect and can even trigger paradoxical activation. Equilibrium and non-equilibrium models of transcription shed light on the mechanism by which interference converts signals, and reveals that self-antagonism of activators imitates the behavior of feed-forward loops. Indeed, a synthetic circuit generates a bell-shaped response, so that the induction of expression is limited to a narrow range of the input signal. The identification of conserved regulatory principles of interference will help to predict the transcriptional response of genes in their genomic context.

Show MeSH
Related in: MedlinePlus