In vitro regulatory models for systems biology

Cascaded dissipative DNAzyme-driven layered networks guide transient replication of coded-strands as gene models

Dynamic, transient, out-of-equilibrium networks guide cellular genetic, metabolic or signaling processes. Designing synthetic networks emulating natural processes imposes important challenges including the ordered connectivity of transient reaction modules, engineering of the appropriate balance between production and depletion of reaction constituents, and coupling of the reaction modules with emerging chemical functions dictated by the networks. Here we introduce the assembly of three coupled reaction modules executing a cascaded dynamic process leading to the transient formation and depletion of three different Mg²⁺-ion-dependent DNAzymes. The transient operation of the DNAzyme in one layer triggers the dynamic activation of the DNAzyme in the subsequent layer, leading to a three-layer transient catalytic cascade. The kinetics of the transient cascade is computationally simulated. The cascaded network is coupled to a polymerization/nicking DNA machinery guiding transient synthesis of three coded strands acting as “gene models”, and to the rolling circle polymerization machinery leading to the transient synthesis of fluorescent Zn(II)-PPIX/G-quadruplex chains or hemin/G-quadruplex catalytic wires.

A reaction network executing a cascaded transient formation and depletion of three different catalytic strands is introduced. The system is coupled to the secondary temporal synthesis of different coded strands as gene models.

A small-molecule chemical interface for molecular programs

In vitro molecular circuits, based on DNA-programmable chemistries, can perform an increasing range of high-level functions, such as molecular level computation, image or chemical pattern recognition and pattern generation. Most reported demonstrations, however, can only accept nucleic acids as input signals. Real-world applications of these programmable chemistries critically depend on strategies to interface them with a variety of non-DNA inputs, in particular small biologically relevant chemicals. We introduce here a general strategy to interface DNA-based circuits with non-DNA signals, based on input-translating modules. These translating modules contain a DNA response part and an allosteric protein sensing part, and use a simple design that renders them fully tunable and modular. They can be repurposed to either transmit or invert the response associated with the presence of a given input. By combining these translating-modules with robust and leak-free amplification motifs, we build sensing circuits that provide a fluorescent quantitative time-response to the concentration of their small-molecule input, with good specificity and sensitivity. The programmability of the DNA layer can be leveraged to perform DNA based signal processing operations, which we demonstrate here with logical inversion, signal modulation and a classification task on two inputs. The DNA circuits are also compatible with standard biochemical conditions, and we show the one-pot detection of an enzyme through its native metabolic activity. We anticipate that this sensitive small-molecule-to-DNA conversion strategy will play a critical role in the future applications of molecular-level circuitry.

Boosting functionality of synthetic DNA circuits with tailored deactivation

Molecular programming takes advantage of synthetic nucleic acid biochemistry to assemble networks of reactions, in vitro, with the double goal of better understanding cellular regulation and providing information-processing capabilities to man-made chemical systems. The function of molecular circuits is deeply related to their topological structure, but dynamical features (rate laws) also play a critical role. Here we introduce a mechanism to tune the nonlinearities associated with individual nodes of a synthetic network. This mechanism is based on programming deactivation laws using dedicated saturable pathways. We demonstrate this approach through the conversion of a single-node homoeostatic network into a bistable and reversible switch. Furthermore, we prove its generality by adding new functions to the library of reported man-made molecular devices: a system with three addressable bits of memory, and the first DNA-encoded excitable circuit. Specific saturable deactivation pathways thus greatly enrich the functional capability of a given circuit topology.

Nonlinearity in synthetic molecular circuits is usually achieved by manipulation of network topology or of production kinetics. Here, the authors achieve bistability and other nonlinear behaviours by manipulating the individual degradation rate laws of circuit components using saturable pathways.

Rapid cell-free forward engineering of novel genetic ring oscillators

While complex dynamic biological networks control gene expression in all living organisms, the forward engineering of comparable synthetic networks remains challenging. The current paradigm of characterizing synthetic networks in cells results in lengthy design-build-test cycles, minimal data collection, and poor quantitative characterization. Cell-free systems are appealing alternative environments, but it remains questionable whether biological networks behave similarly in cell-free systems and in cells. We characterized in a cell-free system the ‘repressilator’, a three-node synthetic oscillator. We then engineered novel three, four, and five-gene ring architectures, from characterization of circuit components to rapid analysis of complete networks. When implemented in cells, our novel 3-node networks produced population-wide oscillations and 95% of 5-node oscillator cells oscillated for up to 72 hr. Oscillation periods in cells matched the cell-free system results for all networks tested. An alternate forward engineering paradigm using cell-free systems can thus accurately capture cellular behavior.

DOI:http://dx.doi.org/10.7554/eLife.09771.001

Engineers often use simplified models to test their ideas. For example, engineers test small-scale models of new airplane designs in wind tunnels to see how easily air flows by them. This saves the engineers the time and expense of building a full-sized aircraft only to learn it has serious design flaws.

The interactions of genes and proteins within living cells can be incredibly complex, and working out how a particular network works can take months or years in living cells. To try to speed up and simplify the process, scientists are developing models that do not involve cells. These models replicate the chemistry inside of the cells and allow scientists to observe complex interactions between genes, proteins and other cellular components. Some scientists have recreated complex patterns of gene expression in these cell-free models, but these systems still take a long time to make. It is also not yet clear whether these models accurately depict what happens in living cells.

Now, Niederholtmeyer, Sun et al. have created a cell-free system that allows the interactions of a large network of genes to be examined in a single day – a process that would previously have taken weeks or months. To test the model, Niederholtmeyer, Sun et al. recreated how networks of genes in the bacterium Escherichia coli interact to form “oscillations”, which produce a regular rhythm of gene expression. When the cell-free oscillator networks were inserted into live E. coli cells, the oscillators continued to produce the same patterns of gene expression as they did outside the cells.

Overall, the experiments show that cell-free models can accurately reproduce, or emulate, the behavior of cellular networks. This work now opens the door for engineering ever more complex genetic networks in a cell-free system, which in turn will enable rapid prototyping and detailed characterization of complex biological reaction networks.

DOI:http://dx.doi.org/10.7554/eLife.09771.002

Computational design of nucleic acid feedback control circuits

The design of synthetic circuits for controlling molecular-scale processes is an important goal of synthetic biology, with potential applications in future in vitro and in vivo biotechnology. In this paper, we present a computational approach for designing feedback control circuits constructed from nucleic acids. Our approach relies on an existing methodology for expressing signal processing and control circuits as biomolecular reactions. We first extend the methodology so that circuits can be expressed using just two classes of reactions: catalysis and annihilation. We then propose implementations of these reactions in three distinct classes of nucleic acid circuits, which rely on DNA strand displacement, DNA enzyme and RNA enzyme mechanisms, respectively. We use these implementations to design a Proportional Integral controller, capable of regulating the output of a system according to a given reference signal, and discuss the trade-offs between the different approaches. As a proof of principle, we implement our methodology as an extension to a DNA strand displacement software tool, thus allowing a broad range of nucleic acid circuits to be designed and analyzed within a common modeling framework.

Emergent properties of dense DNA phases toward artificial biosystems on a surface

CONSPECTUS: The expression of genes in a cell in response to external signals or internal programs occurs within an environment that is compartmentalized and dense. Reconstituting gene expression in man-made systems is relevant for the basic understanding of gene regulation, as well as for the development of applications in bio- and nanotechnology. DNA polymer brushes assembled on a surface emulate a dense cellular environment. In a regime of significant chain overlap, the highly charged nature of DNA, its entropic degrees of freedom, and its interaction with transcription/translation machinery lead to emergent collective biophysical and biochemical properties, which are summarized in this Account. First, we describe a single-step photolithographic biochip on which biomolecules can be immobilized. Then, we present the assembly of localized DNA brushes, a few kilo-base pairs long, with spatially varying density, reaching a DNA concentration of ∼10(7) base pairs/μm(3), which is comparable to the value in E. coli. We then summarize the response of brush height to changes in density and mono- and divalent ionic strength. The balance between entropic elasticity and swelling forces leads to a rich phase behavior. At no added salt, polymers are completely stretched due to the osmotic pressure of ions, and at high salt they assume a relaxed coil conformation. Midrange, the brush height scales with ratio of density and ionic strength to the third power, in agreement with the general theory of polyelectrolyte brushes. In response to trivalent cations, DNA brushes collapse into macroscopic dendritic condensates with hysteresis, coexistence, and a hierarchy of condensation with brush density. We next present an investigation of RNA transcription in the DNA brush. In general, the brush density entropically excludes macromolecules, depleting RNA polymerase concentration in the brush compared to the bulk, therefore reducing transcription rate. The orientation of transcription promoters with respect to the surface also affects the rate with a lower value for outward compared to inward transcription, likely due to local changes of RNA polymerase concentrations. We hypothesize that equalizing the macromolecular osmotic pressure between bulk and brush with the addition of inert macromolecules would overcome the entropic exclusion of DNA associated proteins, and lead to enhanced biochemical activity. Finally, we present protein synthesis cascades in DNA brushes patterned at close proximity, as a step toward biochemical signaling between brushes. Examining the synthesis of proteins polymerizing into crystalline tubes suggests that on-chip molecular traps serve as nucleation sites for protein assembly, thereby opening possibilities for reconstituting nanoscale protein assembly pathways.

The emerging age of cell-free synthetic biology

The engineering of and mastery over biological parts has catalyzed the emergence of synthetic biology. This field has grown exponentially in the past decade. As increasingly more applications of synthetic biology are pursued, more challenges are encountered, such as delivering genetic material into cells and optimizing genetic circuits in vivo. An in vitro or cell-free approach to synthetic biology simplifies and avoids many of the pitfalls of in vivo synthetic biology. In this review, we describe some of the innate features that make cell-free systems compelling platforms for synthetic biology and discuss emerging improvements of cell-free technologies. We also select and highlight recent and emerging applications of cell-free synthetic biology.