Reconstitution of an Ultradian Oscillator in Mammalian Cells by a Synthetic Biology Approach

Mathematical and In Silico Analysis of Synthetic Inhibitory Circuits That Program Self-Organizing Multicellular Structures

Bottom-up approaches are becoming increasingly popular for studying multicellular self-organization and development. In contrast to the classic top-down approach, where parts of the organization/developmental process are broken to understand the process, the goal is to build the process to understand it. For example, synthetic circuits have been built to understand how cell-cell communication and differential adhesion can drive multicellular development. The majority of current bottom-up efforts focus on using activatory circuits to engineer and understand development, but efforts with inhibitory circuits have been minimal. Yet, inhibitory circuits are ubiquitous and vital to native developmental processes. Thus, inhibitory circuits are a crucial yet poorly studied facet of bottom-up multicellular development. To demonstrate the potential of inhibitory circuits for building and developing multicellular structures, several synthetic inhibitory circuits that combine engineered cell-cell communication and differential adhesion were designed, and then examined for synthetic development capability using a previously validated in silico framework. These designed inhibitory circuits can build a variety of patterned, self-organized structures and even morphological oscillations. These results support that inhibitory circuits can be powerful tools for building, studying, and understanding developmental processes.

Mechanistic Model-Driven Biodesign in Mammalian Synthetic Biology

Mathematical modeling plays a vital role in mammalian synthetic biology by providing a framework to design and optimize design circuits and engineered bioprocesses, predict their behavior, and guide experimental design. Here, we review recent models used in the literature, considering mathematical frameworks at the molecular, cellular, and system levels. We report key challenges in the field and discuss opportunities for genome-scale models, machine learning, and cybergenetics to expand the capabilities of model-driven mammalian cell biodesign.

Timed Pulses in DNA Strand Displacement Reactions

Inspired by naturally occurring regulatory mechanisms that allow complex temporal pulse features with programmable delays, we demonstrate here a strategy to achieve temporally programmed pulse output signals in DNA-based strand displacement reactions (SDRs). To achieve this, we rationally designed input strands that, once bound to their target duplex, can be gradually degraded, resulting in a pulse output signal. We also designed blocker strands that suppress strand displacement and determine the time at which the pulse reaction is generated. We show that by controlling the degradation rate of blocker and input strands, we can finely control the delayed pulse output over a range of 10 h. We also prove that it is possible to orthogonally delay two different pulse reactions in the same solution by taking advantage of the specificity of the degradation reactions for the input and blocker strands. Finally, we show here two possible applications of such delayed pulse SDRs: the time-programmed pulse decoration of DNA nanostructures and the sequentially appearing and self-erasing formation of DNA-based patterns.

The Goodwin Oscillator and its Legacy

In the 1960's Brian Goodwin published a couple of mathematical models showing how feedback inhibition can lead to oscillations and discussed possible implications of this behaviour for the physiology of the cell. He also presented key ideas about the rich dynamics that may result from the coupling between such biochemical oscillators. Goodwin's work motivated a series of theoretical investigations aiming at identifying minimal mechanisms to generate limit cycle oscillations and deciphering design principles of biological oscillators. The three-variable Goodwin model (adapted by Griffith) can be seen as a core model for a large class of biological systems, ranging from ultradian to circadian clocks. We summarize here main ideas and results brought by Goodwin and review a couple of modeling works directly or indirectly inspired by Goodwin's findings.

Synthetic tissue engineering: Programming multicellular self-organization by designing customized cell-cell communication

Cells communicate with each other to organize multicellular collective systems and assemble complex, elaborate tissue structures by themselves during development. Despite intensive biological studies, what kind of cell-cell communication can sufficiently drive self-organization of specific tissue architectures remain unclear. Thanks to recent advances on genetic engineering technologies, synthetic biologists start to build customized cell-cell communication with user-defined signal input and gene expression output to program multicellular behaviors using mammalian systems. This review article introduces how we can design and engineer customized cell-cell communication to program synthetic self-organizing multicellular structures. Creating tissue formation processes with synthetic genetic programs will help understanding of fundamental principles of how genetic programs drive tissue self-organization and provide new capabilities on tissue engineering for cell-based regenerative therapy applications.

A tunable dual-input system for on-demand dynamic gene expression regulation

Cellular systems have evolved numerous mechanisms to adapt to environmental stimuli, underpinned by dynamic patterns of gene expression. In addition to gene transcription regulation, modulation of protein levels, dynamics and localization are essential checkpoints governing cell functions. The introduction of inducible promoters has allowed gene expression control using orthogonal molecules, facilitating its rapid and reversible manipulation to study gene function. However, differing protein stabilities hinder the generation of protein temporal profiles seen in vivo. Here, we improve the Tet-On system integrating conditional destabilising elements at the post-translational level and permitting simultaneous control of gene expression and protein stability. We show, in mammalian cells, that adding protein stability control allows faster response times, fully tunable and enhanced dynamic range, and improved in silico feedback control of gene expression. Finally, we highlight the effectiveness of our dual-input system to modulate levels of signalling pathway components in mouse Embryonic Stem Cells.

Synthetic development: building mammalian multicellular structures with artificial genetic programs

Synthetic biology efforts began in simple single-cell systems, which were relatively easy to manipulate genetically (Cameron et al., 2014). The field grew exponentially in the last two decades, and one of the latest frontiers are synthetic developmental programs for multicellular mammalian systems (Black et al., 2017; Wieland and Fussenegger, 2012) to genetically control features such as patterning or morphogenesis. These programs rely on engineered cell-cell communications, multicellular gene regulatory networks and effector genes. Here, we contextualize the first of these synthetic developmental programs, examine molecular and computational tools that can be used to generate next generation versions, and present the general logic that underpins these approaches. These advances are exciting as they represent a novel way to address both control and understanding in the field of developmental biology and tissue development (Elowitz and Lim, 2010; Velazquez et al., 2018; White et al., 2018; Morsut, 2017). This field is just at the beginning, and it promises to be of major interest in the upcoming years of biomedical research.

Synthetic developmental biology: build and control multicellular systems

Synthetic biology offers a bottom-up engineering approach that intends to understand complex systems via design-build-test cycles. Embryonic development comprises complex processes that originate at the level of gene regulatory networks in a cell and emerge into collective cellular behaviors with multicellular forms and functions. Here, we review synthetic biology approaches to development that involve building de novo developmental trajectories or engineering control in stem cell-derived multicellular systems. The field of synthetic developmental biology is rapidly growing with the help of recent advances in artificial gene circuits, self-organizing organoids, and controllable tissue microenvironments. The outcome will be a blueprint to decode principles of morphogenesis and to create programmable organoids with novel designs or improved functions.

Episodic Ultradian Events-Ultradian Rhythms

In the fast lane of chronobiology, ultradian events are short-term rhythms that have been observed since the beginning of modern biology and were quantified about a century ago. They are ubiquitous in all biological systems and found in all organisms, from unicellular organisms to mammals, and from single cells to complex biological functions in multicellular animals. Since these events are aperiodic and last for a few minutes to a few hours, they are better classified as episodic ultradian events (EUEs). Their origin is unclear. However, they could have a molecular basis and could be controlled by hormonal inputs-in vertebrates, they originate from the activity of the central nervous system. EUEs are receiving increasing attention but their aperiodic nature requires specific sampling and analytic tools. While longer scale rhythms are adaptations to predictable changes in the environment, in theory, EUEs could contribute to adaptation by preparing organisms and biological functions for unpredictability.

Regulation of Gene Expression and Signaling Pathway Activity in Mammalian Cells by Automated Microfluidics Feedback Control

Gene networks and signaling pathways display complex topologies and, as a result, complex nonlinear behaviors. Accumulating evidence shows that both static (concentration) and dynamical (rate-of-change) features of transcription factors, ligands and environmental stimuli control downstream processes and ultimately cellular functions. Currently, however, methods to generate stimuli with the desired features to probe cell response are still lacking. Here, combining tools from Control Engineering and Synthetic Biology (cybergenetics), we propose a simple and cost-effective microfluidics-based platform to precisely regulate gene expression and signaling pathway activity in mammalian cells by means of real-time feedback control. We show that this platform allows (i) to automatically regulate gene expression from inducible promoters in different cell types, including mouse embryonic stem cells; (ii) to precisely regulate the activity of the mTOR signaling pathway in single cells; (iii) to build a biohybrid oscillator in single embryonic stem cells by interfacing biological parts with virtual in silico counterparts. Ultimately, this platform can be used to probe gene networks and signaling pathways to understand how they process static and dynamic features of specific stimuli, as well as for the rapid prototyping of synthetic circuits for biotechnology and biomedical purposes.