Source 1primary paper2021
Toolkit/pulsatile-signal filters and decoders
pulsatile-signal filters and decoders
Taxonomy: Mechanism Branch / Architecture. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
Pulsatile-signal filters and decoders are synthetic gene-network constructs generated by combining a demultiplexer with dCas9-based regulatory networks. They are designed to decode complex dynamic input patterns, including pulsatile signals, into differential gene-expression outputs.
Usefulness & Problems
Why this is useful
These constructs are useful for dynamic information processing in synthetic biology because they convert temporal signal features into distinct transcriptional responses. Source literature also reports their use in precise multidimensional regulation of a heterologous metabolic pathway, indicating biotechnological utility.
Source:
Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway.
Source:
show that this circuit can be employed to demultiplex dynamically encoded signals
Problem solved
They address the problem of decoding complex, time-varying input signals within synthetic gene circuits rather than responding only to static signal levels. The reported systems specifically target dynamic signal decoding and differential gene expression from pulsatile inputs.
Source:
Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway.
Taxonomy & Function
Primary hierarchy
Mechanism Branch
Architecture: A reusable architecture pattern for arranging parts into an engineered system.
Mechanisms
dynamic signal decodingkinetic filtering based on differing regulator response kineticstranscriptional regulation by dcas9-based gene networksTechniques
Computational DesignTarget processes
No target processes tagged yet.
Implementation Constraints
cofactor dependency: cofactor requirement unknownencoding mode: genetically encodedimplementation constraint: context specific validationoperating role: sensor
Implementation involved combining a demultiplexer architecture with dCas9-based gene networks to build the decoding circuits. The supplied evidence does not provide construct maps, guide RNA design rules, expression systems, delivery methods, or cofactor requirements.
The provided evidence does not specify quantitative performance metrics, host organism, target genes, response times, or decoding accuracy. Independent replication is not indicated in the supplied material, and validation appears to derive from a single 2021 study.
Validation
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
Supporting Sources
Ranked Claims
Dynamic multiplexing was used for precise multidimensional regulation of a heterologous metabolic pathway.
Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway.
Dynamic multiplexing was used for precise multidimensional regulation of a heterologous metabolic pathway.
Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway.
Dynamic multiplexing was used for precise multidimensional regulation of a heterologous metabolic pathway.
Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway.
Dynamic multiplexing was used for precise multidimensional regulation of a heterologous metabolic pathway.
Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway.
Dynamic multiplexing was used for precise multidimensional regulation of a heterologous metabolic pathway.
Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway.
Dynamic multiplexing was used for precise multidimensional regulation of a heterologous metabolic pathway.
Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway.
Dynamic multiplexing was used for precise multidimensional regulation of a heterologous metabolic pathway.
Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway.
The reported systems elucidate design principles of dynamic information processing and provide synthetic systems capable of decoding complex signals for biotechnological applications.
Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.
The reported systems elucidate design principles of dynamic information processing and provide synthetic systems capable of decoding complex signals for biotechnological applications.
Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.
The reported systems elucidate design principles of dynamic information processing and provide synthetic systems capable of decoding complex signals for biotechnological applications.
Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.
The reported systems elucidate design principles of dynamic information processing and provide synthetic systems capable of decoding complex signals for biotechnological applications.
Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.
The reported systems elucidate design principles of dynamic information processing and provide synthetic systems capable of decoding complex signals for biotechnological applications.
Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.
The reported systems elucidate design principles of dynamic information processing and provide synthetic systems capable of decoding complex signals for biotechnological applications.
Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.
The reported systems elucidate design principles of dynamic information processing and provide synthetic systems capable of decoding complex signals for biotechnological applications.
Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.
Combining the demultiplexer with dCas9-based gene networks enabled construction of pulsatile-signal filters and decoders.
We combine this demultiplexer with dCas9-based gene networks to construct pulsatile-signal filters and decoders.
Combining the demultiplexer with dCas9-based gene networks enabled construction of pulsatile-signal filters and decoders.
We combine this demultiplexer with dCas9-based gene networks to construct pulsatile-signal filters and decoders.
Combining the demultiplexer with dCas9-based gene networks enabled construction of pulsatile-signal filters and decoders.
We combine this demultiplexer with dCas9-based gene networks to construct pulsatile-signal filters and decoders.
Combining the demultiplexer with dCas9-based gene networks enabled construction of pulsatile-signal filters and decoders.
We combine this demultiplexer with dCas9-based gene networks to construct pulsatile-signal filters and decoders.
Combining the demultiplexer with dCas9-based gene networks enabled construction of pulsatile-signal filters and decoders.
We combine this demultiplexer with dCas9-based gene networks to construct pulsatile-signal filters and decoders.
Combining the demultiplexer with dCas9-based gene networks enabled construction of pulsatile-signal filters and decoders.
We combine this demultiplexer with dCas9-based gene networks to construct pulsatile-signal filters and decoders.
Combining the demultiplexer with dCas9-based gene networks enabled construction of pulsatile-signal filters and decoders.
We combine this demultiplexer with dCas9-based gene networks to construct pulsatile-signal filters and decoders.
Light-responsive transcriptional regulators with differing response kinetics were used to build a falling-edge pulse-detector.
Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling-edge pulse-detector
Light-responsive transcriptional regulators with differing response kinetics were used to build a falling-edge pulse-detector.
Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling-edge pulse-detector
Light-responsive transcriptional regulators with differing response kinetics were used to build a falling-edge pulse-detector.
Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling-edge pulse-detector
Light-responsive transcriptional regulators with differing response kinetics were used to build a falling-edge pulse-detector.
Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling-edge pulse-detector
Light-responsive transcriptional regulators with differing response kinetics were used to build a falling-edge pulse-detector.
Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling-edge pulse-detector
Light-responsive transcriptional regulators with differing response kinetics were used to build a falling-edge pulse-detector.
Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling-edge pulse-detector
Light-responsive transcriptional regulators with differing response kinetics were used to build a falling-edge pulse-detector.
Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling-edge pulse-detector
The falling-edge pulse-detector can be employed to demultiplex dynamically encoded signals.
show that this circuit can be employed to demultiplex dynamically encoded signals
The falling-edge pulse-detector can be employed to demultiplex dynamically encoded signals.
show that this circuit can be employed to demultiplex dynamically encoded signals
The falling-edge pulse-detector can be employed to demultiplex dynamically encoded signals.
show that this circuit can be employed to demultiplex dynamically encoded signals
The falling-edge pulse-detector can be employed to demultiplex dynamically encoded signals.
show that this circuit can be employed to demultiplex dynamically encoded signals
The falling-edge pulse-detector can be employed to demultiplex dynamically encoded signals.
show that this circuit can be employed to demultiplex dynamically encoded signals
The falling-edge pulse-detector can be employed to demultiplex dynamically encoded signals.
show that this circuit can be employed to demultiplex dynamically encoded signals
The falling-edge pulse-detector can be employed to demultiplex dynamically encoded signals.
show that this circuit can be employed to demultiplex dynamically encoded signals
Dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Approval Evidence
1 source2 linked approval claimsfirst-pass slug pulsatile-signal-filters-and-decoders
to construct pulsatile-signal filters and decoders
Source:
design principlesupports
The reported systems elucidate design principles of dynamic information processing and provide synthetic systems capable of decoding complex signals for biotechnological applications.
Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.
Source:
engineering resultsupports
Combining the demultiplexer with dCas9-based gene networks enabled construction of pulsatile-signal filters and decoders.
We combine this demultiplexer with dCas9-based gene networks to construct pulsatile-signal filters and decoders.
Source:
Comparisons
Source-backed strengths
The source literature states that combining a demultiplexer with dCas9-based gene networks enabled construction of pulsatile-signal filters and decoders. The same study reports application of dynamic multiplexing to precise multidimensional control of a heterologous metabolic pathway and presents these systems as exemplars of dynamic information-processing design principles.
Source:
We combine this demultiplexer with dCas9-based gene networks to construct pulsatile-signal filters and decoders.
Source:
Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling-edge pulse-detector
Source:
Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state.
Compared with dCas9-based gene networks
pulsatile-signal filters and decoders and dCas9-based gene networks address a similar problem space.
Shared frame: same top-level item type; shared mechanisms: dynamic signal decoding
Compared with demultiplexer for dynamically encoded signals
pulsatile-signal filters and decoders and demultiplexer for dynamically encoded signals address a similar problem space.
Shared frame: same top-level item type; shared mechanisms: dynamic signal decoding
Compared with falling-edge pulse-detector
pulsatile-signal filters and decoders and falling-edge pulse-detector address a similar problem space.
Shared frame: same top-level item type; shared mechanisms: dynamic signal decoding
Strengths here: looks easier to implement in practice.
Ranked Citations
- 1.