Designing cell function: assembly of synthetic gene circuits for cell biology applications

Synthetic genetic circuits for programmable biological functionalities

Living organisms evolve complex genetic networks to interact with the environment. Due to the rapid development of synthetic biology, various modularized genetic parts and units have been identified from these networks. They have been employed to construct synthetic genetic circuits, including toggle switches, oscillators, feedback loops and Boolean logic gates. Building on these circuits, complex genetic machines with capabilities in programmable decision-making could be created. Consequently, these accomplishments have led to novel applications, such as dynamic and autonomous modulation of metabolic networks, directed evolution of biological units, remote and targeted diagnostics and therapies, as well as biological containment methods to prevent release of engineered microorganisms and genetic materials. Herein, we outline the principles in genetic circuit design that have initiated a new chapter in transforming concepts to realistic applications. The features of modularized building blocks and circuit architecture that facilitate realization of circuits for a variety of novel applications are discussed. Furthermore, recent advances and challenges in employing genetic circuits to impart microorganisms with distinct and programmable functionalities are highlighted. We envision that this review gives new insights into the design of synthetic genetic circuits and offers a guideline for the implementation of different circuits in various aspects of biotechnology and bioengineering.

Systematic Evaluation of Site-Specific Recombinant Gene Expression for Programmable Mammalian Cell Engineering

Many branches of biology depend on stable and predictable recombinant gene expression, which has been achieved in recent years through targeted integration of the recombinant gene into defined integration sites. However, transcriptional levels of recombinant genes in characterized integration sites are controlled by multiple components of the integrated expression cassette. Lack of readily available tools has inhibited meaningful experimental investigation of the interplay between the integration site and the expression cassette components. Here we show in a systematic manner how multiple components contribute to final net expression of recombinant genes in a characterized integration site. We develop a CRISPR/Cas9-based toolbox for construction of mammalian cell lines with targeted integration of a landing pad, containing a recombinant gene under defined 5' proximal regulatory elements. Generated site-specific recombinant cell lines can be used in a streamlined recombinase-mediated cassette exchange for fast screening of different expression cassettes. Using the developed toolbox, we show that different 5' proximal regulatory elements generate distinct and robust recombinant gene expression patterns in defined integration sites of CHO cells with a wide range of transcriptional outputs. This approach facilitates the generation of user-defined and product-specific gene expression patterns for programmable mammalian cell engineering.

Optimal parameter identification of synthetic gene networks using harmony search algorithm

Computational modeling of engineered gene circuits is an important while challenged task in systems biology. In order to describe and predict the response behaviors of genetic circuits using reliable model parameters, this paper applies an optimal experimental design(OED) method to obtain input signals. In order to obtain informative observations, this study focuses on maximizing Fisher information matrix(FIM)-based optimal criteria and to provide optimal inputs. Furthermore, this paper designs a two-stage optimization with the modified E-optimal criteria and applies harmony search(HS)-based OED algorithm to minimize estimation errors. The proposed optimal identification methodology involves estimation errors and the sample size to pursue a trade-off between estimation accuracy and measurement cost in modeling gene networks. The designed cost function takes two major factors into account, in which experimental costs are proportional to the number of time points. Experiments select two types of synthetic genetic networks to validate the effectiveness of the proposed HS-OED approach. Identification outcomes and analysis indicate the proposed HS-OED method outperforms two candidate OED approaches, with reduced computational effort.

Biofunctionalized Materials Featuring Feedforward and Feedback Circuits Exemplified by the Detection of Botulinum Toxin A

Feedforward and feedback loops are key regulatory elements in cellular signaling and information processing. Synthetic biology exploits these elements for the design of molecular circuits that enable the reprogramming and control of specific cellular functions. These circuits serve as a basis for the engineering of complex cellular networks, opening the door for numerous medical and biotechnological applications. Here, a similar principle is applied. Feedforward and positive feedback circuits are incorporated into biohybrid polymer materials in order to develop signal-sensing and signal-processing devices. This concept is exemplified by the detection of the proteolytic activity of the botulinum neurotoxin A. To this aim, site-specific proteases are incorporated into receiver, transmitter, and output materials, and their release, diffusion, and/or activation are wired according to a feedforward or a positive feedback circuit. The development of a quantitative mathematical model enables analysis and comparison of the performance of both systems. The flexible design could be easily adapted to detect other toxins or molecules of interest. Furthermore, cellular signaling or gene regulatory pathways could provide additional blueprints for the development of novel biohybrid circuits. Such information-processing, material-embedded biological circuits hold great promise for a variety of analytical, medical, or biotechnological applications.

Programmable RNA-based systems for sensing and diagnostic applications

The emerging field of RNA nanotechnology harnesses the versatility of RNA molecules to generate nature-inspired systems with programmable structure and functionality. Such methodology has therefore gained appeal in the fields of biosensing and diagnostics, where specific molecular recognition and advanced input/output processing are demanded. The use of RNA modules and components allows for achieving diversity in structure and function, for processing information with molecular precision, and for programming dynamic operations on the grounds of predictable non-covalent interactions. When RNA nanotechnology meets bioanalytical chemistry, sensing of target molecules can be performed by harnessing programmable interactions of RNA modules, advanced field-ready biosensors can be manufactured by interfacing RNA-based devices with supporting portable platforms, and RNA sensors can be engineered to be genetically encoded allowing for real-time imaging of biomolecules in living cells. In this article, we report recent advances in RNA-based sensing technologies and discuss current trends in RNA nanotechnology-enabled biomedical diagnostics. In particular, we describe programmable sensors that leverage modular designs comprising dynamic aptamer-based units, synthetic RNA nanodevices able to perform target-responsive regulation of gene expression, and paper-based sensors incorporating artificial RNA networks. Graphical Abstract ᅟ.

More from less - bottom-up reconstitution of cell biology

The ultimate goal of bottom-up synthetic biology is recreating life in its simplest form. However, in its quest to find the minimal functional units of life, this field contributes more than its main aim by also offering a range of tools for asking, and experimentally approaching, biological questions. This Review focusses on how bottom-up reconstitution has furthered our understanding of cell biology. Studying cell biological processes in vitro has a long tradition, but only recent technological advances have enabled researchers to reconstitute increasingly complex biomolecular systems by controlling their multi-component composition and their spatiotemporal arrangements. We illustrate this progress using the example of cytoskeletal processes. Our understanding of these has been greatly enhanced by reconstitution experiments, from the first in vitro experiments 70 years ago to recent work on minimal cytoskeleton systems (including this Special Issue of Journal of Cell Science). Importantly, reconstitution approaches are not limited to the cytoskeleton field. Thus, we also discuss progress in other areas, such as the shaping of biomembranes and cellular signalling, and prompt the reader to add their subfield of cell biology to this list in the future.

Synthetic mammalian pattern formation driven by differential diffusivity of Nodal and Lefty

A synthetic mammalian reaction-diffusion pattern has yet to be created, and Nodal-Lefty signaling has been proposed to meet conditions for pattern formation: Nodal is a short-range activator whereas Lefty is a long-range inhibitor. However, this pattern forming possibility has never been directly tested, and the underlying mechanisms of differential diffusivity of Nodal and Lefty remain unclear. Here, through a combination of synthetic and theoretical approaches, we show that a reconstituted Nodal-Lefty network in mammalian cells spontaneously gives rise to a pattern. Surprisingly, extracellular Nodal is confined underneath the cells, resulting in a narrow distribution compared with Lefty. The short-range distribution requires the finger 1 domain of Nodal, and transplantation of the finger 1 domain into Lefty shortens the distribution of Lefty, successfully preventing pattern formation. These results indicate that the differences in localization and domain structures between Nodal and Lefty, combined with the activator-inhibitor topology, are sufficient for reaction-diffusion patterning.

Nodal-Lefty signaling combines a short-range activator and a long-range inhibitor for axis formation and left-right patterning. Here the authors reconstitute a synthetic biology activator-inhibitor circuit of Nodal-Lefty to drive pattern formation in mammalian cells.