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Chapter 2 : Architecture and Dynamics of Transcriptional Networks

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Abstract:

This chapter discusses the progress of the last few years in our understanding of the architecture of bacterial transcriptional networks (TRNs) and the functions provided by this architecture. The rest of this chapter concerns such local structural analysis, focusing on elementary circuits that make up the network. Other sections of the chapter are devoted to network motifs in the TRN of , their structure and function, aiming to covey the notion that each motif can carry out specific information processing functions. The analysis of the TRN revealed four main recurring patterns: (i) autoregulation, (ii) feedforward loop (FFL), (iii) single input module (SIM), and (iv) dense overlapping regulon (DOR). NAR of a TRN linearizes gene response and increases the input dynamic range of its downstream genes. The dynamical functions as well as other properties of the two common FFLs: the coherent type-1 FFL and the incoherent type-1 FFL are discussed. As described in the chapter, different functions are assigned to network motifs based on theory and experiments, with new functions continuously emerging. It is likely that additional studies on other systems in both , as well as other bacteria, will result in the identification of additional functions of network motifs in isolation and in the context of the entire network. A future challenge is to view network motif behavior within the global dynamics of gene networks, and assign certain functions of the network based on network architecture.

Citation: Bren A, Alon U. 2011. Architecture and Dynamics of Transcriptional Networks, p 17-30. In Storz G, Hengge R (ed), Bacterial Stress Responses, Second Edition. ASM Press, Washington, DC. doi: 10.1128/9781555816841.ch2

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Figures

Image of Figure 1.
Figure 1.

Graphic representation of part (~20%) of the TRN. Each gene (either a TF or target operon) is represented by a node, and transcriptional interactions between TFs and their target genes are represented by arrows. Reprinted from Alon, , with permission from the publisher.

Citation: Bren A, Alon U. 2011. Architecture and Dynamics of Transcriptional Networks, p 17-30. In Storz G, Hengge R (ed), Bacterial Stress Responses, Second Edition. ASM Press, Washington, DC. doi: 10.1128/9781555816841.ch2
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Image of Figure 2.
Figure 2.

Network motif structures. (a) Negative autoregulation. (b) Positive autoregulation. (c) Coherent type-1 feed-forward loop (C1-FFL). (d) Incoherent type-1 feed-forward loop (I1-FFL). (e) Single input module (SIM). (f) Dense overlapping regulon (DOR).

Citation: Bren A, Alon U. 2011. Architecture and Dynamics of Transcriptional Networks, p 17-30. In Storz G, Hengge R (ed), Bacterial Stress Responses, Second Edition. ASM Press, Washington, DC. doi: 10.1128/9781555816841.ch2
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Image of Figure 3.
Figure 3.

Functional properties of the C1-FFL motif. (a) C1-FFL with an AND gate input function as a sign-sensitive delay element and a persistence detector. Z is activated with a delay because it starts to accumulate only when Y crosses its activation threshold for Z. Short pulses of S are filtered out because they do not give Y enough time to accumulate and do not lead to Z expression (Shen-Orr et al., ). (b) The arabinose utilization system of is wired in a C1-FFL connectivity with an AND gate input function, compared to the lactose system which is wired by a simple regulation. (c) An experimental study using fluorescence reporter strains shows that, after addition of the input signal, cAMP (S) activation of the reporter is delayed compared to the reporter. No delay is observed after signal removal. Shown is GFP level divided by the optical density (OD) and normalized to the maximal level of each reporter strain grown on glucose minimal medium (Reprinted from Mangan, S., A. Zaslaver, and U. Alon. . The coherent feed-forward loop serves as a sign-sensitive delay element in transcription networks. . 197–204, with permission from the publisher.)

Citation: Bren A, Alon U. 2011. Architecture and Dynamics of Transcriptional Networks, p 17-30. In Storz G, Hengge R (ed), Bacterial Stress Responses, Second Edition. ASM Press, Washington, DC. doi: 10.1128/9781555816841.ch2
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Image of Figure 4.
Figure 4.

Dynamic and steady-state properties of the I1-FFL motif. (a) Theory predicts that the dynamic response of an I1-FFL is faster compared to simple regulation and it can generate a pulse in Z expression (time-dependent biphasic behavior). (b) The galactose utilization system of is wired in an I1-FFL connectivity. (c) The response of the promoter to cAMP is nonmonotonic. In this study reporter strains for (designated in the figure as ) and promoters were utilized. At low cAMP levels promoter activity of the reporter increases but, at high cAMP level, in correlation with a significant increase in expression, promoter activity of is decreased, generating a nonmonotonic response to cAMP levels. In a strain deleted for the gene, the promoter activity of the reporter continuously increases with cAMP levels. Shown is the promoter activity normalized to its maximal level. (Reprinted from Kaplan, S., A. Bren, A. Zaslaver, E. Dekel, and U. Alon. . The incoherent feed-forward loop can generate non-monotonic input functions for genes. . 203, with permission from the publisher.)

Citation: Bren A, Alon U. 2011. Architecture and Dynamics of Transcriptional Networks, p 17-30. In Storz G, Hengge R (ed), Bacterial Stress Responses, Second Edition. ASM Press, Washington, DC. doi: 10.1128/9781555816841.ch2
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Image of Figure 5.
Figure 5.

Diverse computations can be carried out by the DOR network motif. (a) The sugar utilization genes form a DOR network motif. (b) Input functions of different sugar genes. Each column represents a certain sugar utilization system. Input functions are defined as the promoter activity at 96 different combinations of the two input signals, cAMP (S) and the cognate sugar (S). The x-and y-axes correspond to sugar and cAMP concentrations, respectively. The same cAMP levels are used in all input functions, and the same sugar levels are used in each column. The figure shows promoter activity normalized to its maximal value for each promoter. (Reprinted from Kaplan, S., A. Bren, A. Zaslaver, E. Dekel, and U. Alon. . Diverse two-dimensional input functions control bacterial sugar genes. 786–792, with permission from the publisher.)

Citation: Bren A, Alon U. 2011. Architecture and Dynamics of Transcriptional Networks, p 17-30. In Storz G, Hengge R (ed), Bacterial Stress Responses, Second Edition. ASM Press, Washington, DC. doi: 10.1128/9781555816841.ch2
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