Higher-order cellular information processing with synthetic RNA devices - PubMed (original) (raw)
Higher-order cellular information processing with synthetic RNA devices
Maung Nyan Win et al. Science. 2008.
Abstract
The engineering of biological systems is anticipated to provide effective solutions to challenges that include energy and food production, environmental quality, and health and medicine. Our ability to transmit information to and from living systems, and to process and act on information inside cells, is critical to advancing the scale and complexity at which we can engineer, manipulate, and probe biological systems. We developed a general approach for assembling RNA devices that can execute higher-order cellular information processing operations from standard components. The engineered devices can function as logic gates (AND, NOR, NAND, or OR gates) and signal filters, and exhibit cooperativity. RNA devices process and transmit molecular inputs to targeted protein outputs, linking computation to gene expression and thus the potential to control cellular function.
Figures
Fig. 1
Functional RNA device composition framework. The color scheme for all figures is as follows: brown, aptamer or sensor component; purple, catalytic core of the ribozyme or actuator component; blue, loop regions of the actuator component; green and red, strands within the transmitter component that participate in the competitive hybridization event. (A) A functional composition framework for assembling RNA devices from modular components. Information in the form of a molecular input is received by the sensor and transmitted by the transmitter to a regulated activity of the actuator, which in turn controls the translation of a target transcript as an output. (B) Three signal integration schemes represent different component assembly strategies to build higher-order RNA devices. The RNA device in SI 1 involves multiple actuator components controlled by single sensor-transmitter components, whereas those in SI 2 and 3 involve multiple sensor-transmitter components controlling a single actuator component.
Fig. 2
RNA devices based on signal integration within the 3′ UTR (SI 1). Single-input gates are indicated in dashed boxes, and triangles indicate relationships between associated gate inputs and outputs. (A) An RNA device composed of two Buffer gates responsive to the same input functions to shift the device response lower than that of the single-input gate. (B) The device output of RNA devices composed of two single-input gates and their single-input gate counterparts. (Left) Device response (bars) is reported as the difference between gene expression activities in the absence and presence of the appropriate inputs [10 mM theophylline (theo) or 1 mM tetracycline (tc)] (21). (Right) Device signal (arrows) is reported over the full transcriptional range of the promoter system used as a percentage of the expression activity relative to that of an inactive ribozyme control, where circles and arrowheads indicate device signals in the absence and presence of input, respectively. The negative sign indicates the down-regulation of target gene expression by the Inverter gates. (C) An RNA device that performs an AND operation by coupling two Buffer gates responsive to different inputs and the associated truth table. (D) The device response of an AND gate (L2bulge1 + L2bulge1tc). Device response under different input conditions [theo or tc (−), 0 mM; theo (+), 5 mM; tc (+), 0.25 mM] is reported as the difference between expression activity in the absence of both inputs and that at the indicated input conditions. (E) An RNA device that performs a NOR operation by coupling two Inverter gates responsive to different inputs and the associated truth table. (F) The device response of a NOR gate (L2bulgeOff1 + L2bulgeOff1tc). Device response under different input conditions [theo or tc (−), 0 mM; theo (+), 10 mM; tc (+), 0.5 mM] is reported as the difference between expression activity in the presence of both inputs and that at the indicated input conditions. Error bars represent the SD from at least three independent experiments.
Fig. 3
RNA devices based on signal integration at the ribozyme core (SI 2). Internal gates are indicated in dashed boxes, and triangles indicate relationships between associated internal gate inputs and outputs. (A) An RNA device that performs a NAND operation by coupling two internal Inverter gates responsive to different inputs to different ribozyme stems and the associated truth table. (B) The device response of a NAND gate (L1cm10 – L2bulgeOff3tc). Device response under different input conditions [theo or tc (−), 0 mM; theo (+), 10 mM; tc (+), 1 mM] is reported as in Fig. 2F. Error bars represent the SD from at least three independent experiments.
Fig. 4
RNA devices based on signal integration at a single ribozyme stem (SI 3). Internal gates (IG_n_) are indicated in dashed boxes, and triangles indicate relationships between associated internal gate inputs and the device output. (A) An RNA device that performs an AND operation by coupling internal Buffer (IG1) and Inverter (IG2) gates responsive to different inputs to a single ribozyme stem. (B) The device response of an AND gate (tc-theo-On1). Device response under different input conditions [theo or tc (−), 0 mM; theo (+), 2.5 mM; tc (+), 0.5 mM] is reported as in Fig. 2D. (C) An RNA device composed of internal Buffer (IG1) and Inverter (IG2) gates responsive to the same input coupled to a single ribozyme stem. (D) The device response of RNA devices composed of internal Buffer and Inverter gates and their single-internal gate device counterpart (L2bulge1). Device response is reported as in Fig. 2B. Theo-theo-On10, -On11, -On12, and -On13 exhibit varying degrees of cooperativity, as quantified by Hill coefficients (_n_H) greater than 1 (26). (E) The device output response of theo-theo-On13 shows a high degree of programmed cooperativity. The device response is normalized to the response at 10 mM theophylline (21). Error bars represent the SD from at least three independent experiments.
Comment in
- Cell biology. RNA computing in a living cell.
Shapiro E, Gil B. Shapiro E, et al. Science. 2008 Oct 17;322(5900):387-8. doi: 10.1126/science.1165665. Science. 2008. PMID: 18927381 No abstract available.
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References
- Guet CC, Elowitz MB, Hsing W, Leibler S. Science. 2002;296:1466. - PubMed
- Kramer BP, Fischer C, Fussenegger M. Biotechnol Bioeng. 2004;87:478. - PubMed
- Seelig G, Soloveichik D, Zhang DY, Winfree E. Science. 2006;314:1585. - PubMed
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