Using synthetic biology to explore principles of development

Colony pattern multistability emerges from a bistable switch

Microbial colony development hinges upon a myriad of factors, including mechanical, biochemical, and environmental niches, which collectively shape spatial patterns governed by intricate gene regulatory networks. The inherent complexity of this phenomenon necessitates innovative approaches to comprehend and compare the mechanisms driving pattern formation. Here, we unveil the multistability of bacterial colony patterns, where bacterial colony patterns can stabilize into multiple distinct types including ring-like patterns and sector-like patterns on hard agar, orchestrated by a simple synthetic bistable switch. Utilizing quantitative imaging and spatially resolved transcriptome approaches, we explore the deterministic process of a ring-like colony pattern formation from a single cell. This process is primarily driven by bifurcation events programmed by the gene regulatory network and microenvironmental cues. Additionally, we observe a noise-induced process amplified by the founder effect, leading to patterns of symmetry-break during range expansion. The degrees of asymmetry are profoundly influenced by the initial conditions of single progenitor cells during the nascent stages of colony development. These findings underscore how the process of range expansion enables individual cells, exposed to a uniform growth-promoting environment, to exhibit inherent capabilities in generating emergent, self-organized behavior.

Optimal network sizes for most robust Turing patterns

Many cellular patterns exhibit a reaction-diffusion component, suggesting that Turing instability may contribute to pattern formation. However, biological gene-regulatory pathways are more complex than simple Turing activator-inhibitor models and generally do not require fine-tuning of parameters as dictated by the Turing conditions. To address these issues, we employ random matrix theory to analyze the Jacobian matrices of larger networks with robust statistical properties. Our analysis reveals that Turing patterns are more likely to occur by chance than previously thought and that the most robust Turing networks have an optimal size, consisting of only a handful of molecular species, thus significantly increasing their identifiability in biological systems. Broadly speaking, this optimal size emerges from a trade-off between the highest stability in small networks and the greatest instability with diffusion in large networks. Furthermore, we find that with multiple immobile nodes, differential diffusion ceases to be important for Turing patterns. Our findings may inform future synthetic biology approaches and provide insights into bridging the gap to complex developmental pathways.

A three-node Turing gene circuit forms periodic spatial patterns in bacteria

Turing patterns are self-organizing systems that can form spots, stripes, or labyrinths. Proposed examples in tissue organization include zebrafish pigmentation, digit spacing, and many others. The theory of Turing patterns in biology has been debated because of their stringent fine-tuning requirements, where patterns only occur within a small subset of parameters. This has complicated the engineering of synthetic Turing gene circuits from first principles, although natural genetic Turing networks have been identified. Here, we engineered a synthetic genetic reaction-diffusion system where three nodes interact according to a non-classical Turing network with improved parametric robustness. The system reproducibly generated stationary, periodic, concentric stripe patterns in growing E. coli colonies. A partial differential equation model reproduced the patterns, with a Turing parameter regime obtained by fitting to experimental data. Our synthetic Turing system can contribute to nanotechnologies, such as patterned biomaterial deposition, and provide insights into developmental patterning programs. A record of this paper's transparent peer review process is included in the supplemental information.

Programming the elongation of mammalian cell aggregates with synthetic gene circuits

A key goal of synthetic morphogenesis is the identification and implementation of methods to control morphogenesis. One line of research is the use of synthetic genetic circuits guiding the self-organization of cell ensembles. This approach has led to several recent successes, including control of cellular rearrangements in 3D via control of cell-cell adhesion by user-designed artificial genetic circuits. However, the methods employed to reach such achievements can still be optimized along three lines: identification of circuits happens by hand, 3D structures are spherical, and effectors are limited to cell-cell adhesion. Here we show the identification, in a computational framework, of genetic circuits for volumetric axial elongation via control of proliferation, tissue fluidity, and cell-cell signaling. We then seek to implement this design in mammalian cell aggregates in vitro. We start by identifying effectors to control tissue growth and fluidity in vitro. We then combine these new modules to construct complete circuits that control cell behaviors of interest in space and time, resulting in measurable tissue deformation along an axis that depends on the engineered signaling modules. Finally, we contextualize in vitro and in silico implementations within a unified morphospace to suggest further elaboration of this initial family of circuits towards more robust programmed axial elongation. These results and integrated in vitro/in silico pipeline demonstrate a promising method for designing, screening, and implementing synthetic genetic circuits of morphogenesis, opening the way to the programming of various user-defined tissue shapes.

Image-guided optogenetic spatiotemporal tissue patterning using μPatternScope

In the field of tissue engineering, achieving precise spatiotemporal control over engineered cells is critical for sculpting functional 2D cell cultures into intricate morphological shapes. In this study, we engineer light-responsive mammalian cells and target them with dynamic light patterns to realize 2D cell culture patterning control. To achieve this, we developed μPatternScope (μPS), a modular framework for software-controlled projection of high-resolution light patterns onto microscope samples. μPS comprises hardware and software suite governing pattern projection and microscope maneuvers. Together with a 2D culture of the engineered cells, we utilize μPS for controlled spatiotemporal induction of apoptosis to generate desired 2D shapes. Furthermore, we introduce interactive closed-loop patterning, enabling a dynamic feedback mechanism between the measured cell culture patterns and the light illumination profiles to achieve the desired target patterning trends. Our work offers innovative tools for advanced tissue engineering applications through seamless fusion of optogenetics, optical engineering, and cybernetics.

Control of spatio-temporal patterning via cell growth in a multicellular synthetic gene circuit

A major goal in synthetic development is to build gene regulatory circuits that control patterning. In natural development, an interplay between mechanical and chemical communication shapes the dynamics of multicellular gene regulatory circuits. For synthetic circuits, how non-genetic properties of the growth environment impact circuit behavior remains poorly explored. Here, we first describe an occurrence of mechano-chemical coupling in synthetic Notch (synNotch) patterning circuits: high cell density decreases synNotch-gated gene expression in different cellular systems in vitro. We then construct, both in vitro and in silico, a synNotch-based signal propagation circuit whose outcome can be regulated by cell density. Spatial and temporal patterning outcomes of this circuit can be predicted and controlled via modulation of cell proliferation, initial cell density, and/or spatial distribution of cell density. Our work demonstrates that synthetic patterning circuit outcome can be controlled via cellular growth, providing a means for programming multicellular circuit patterning outcomes.

Robust tissue pattern formation by coupling morphogen signal and cell adhesion

Morphogens, locally produced signaling molecules, form a concentration gradient to guide tissue patterning. Tissue patterns emerge as a collaboration between morphogen diffusion and responsive cell behaviors, but the mechanisms through which diffusing morphogens define precise spatial patterns amidst biological fluctuations remain unclear. To investigate how cells respond to diffusing proteins to generate tissue patterns, we develop SYMPLE3D, a 3D culture platform. By engineering gene expression responsive to artificial morphogens, we observe that coupling morphogen signals with cadherin-based adhesion is sufficient to convert a morphogen gradient into distinct tissue domains. Morphogen-induced cadherins gather activated cells into a single domain, removing ectopically activated cells. In addition, we reveal a switch-like induction of cadherin-mediated compaction and cell mixing, homogenizing activated cells within the morphogen gradient to form a uniformly activated domain with a sharp boundary. These findings highlight the cooperation between morphogen gradients and cell adhesion in robust tissue patterning and introduce a novel method for tissue engineering to develop new tissue domains in organoids.

Development of Leptolyngbya sp. BL0902 into a model organism for synthetic biological research in filamentous cyanobacteria

Cyanobacteria have great potential in CO2-based bio-manufacturing and synthetic biological studies. The filamentous cyanobacterium, Leptolyngbya sp. strain BL0902, is comparable to Arthrospira (Spirulina) platensis in commercial-scale cultivation while proving to be more genetically tractable. Here, we report the analyses of the whole genome sequence, gene inactivation/overexpression in the chromosome and deletion of non-essential chromosomal regions in this strain. The genetic manipulations were performed via homologous double recombination using either an antibiotic resistance marker or the CRISPR/Cpf1 editing system for positive selection. A desD-overexpressing strain produced γ-linolenic acid in an open raceway photobioreactor with the productivity of 0.36 g·m-2·d-1. Deletion mutants of predicted patX and hetR, two genes with opposite effects on cell differentiation in heterocyst-forming species, were used to demonstrate an analysis of the relationship between regulatory genes in the non-heterocystous species. Furthermore, a 50.8-kb chromosomal region was successfully deleted in BL0902 with the Cpf1 system. These results supported that BL0902 can be developed into a stable photosynthetic cell factory for synthesizing high value-added products, or used as a model strain for investigating the functions of genes that are unique to filamentous cyanobacteria, and could be systematically modified into a genome-streamlined chassis for synthetic biological purposes.

Engineering Tunable, Low Latency Spatial Computation with Dual Input Quorum Sensing Promoters

Quorum sensing signals have evolved for population-level signaling in bacterial communities and are versatile tools for engineering cell-cell signaling in synthetic biology projects. Here, we characterize the spatial diffusion of a palette of quorum sensing signals and find that their diffusion in agar can be predicted from their molecular weight with a simple power law. We also engineer novel dual- and multi-input promoters that respond to quorum-sensing diffusive signals for use in engineered genetic systems. We engineer a promoter scaffold that can be adapted for activation and repression by multiple diffusers simultaneously. Lastly, we combine the knowledge on diffusion dynamics with the novel genetic components to build a new generation of spatial, stripe-forming systems with a simplified design, improved robustness, tuneability, and response time.

Contact area and tissue growth dynamics shape synthetic juxtacrine signaling patterns

Cell-cell communication through direct contact, or juxtacrine signaling, is important in development, disease, and many areas of physiology. Synthetic forms of juxtacrine signaling can be precisely controlled and operate orthogonally to native processes, making them a powerful reductionist tool with which to address fundamental questions in cell-cell communication in vivo. Here we investigate how cell-cell contact length and tissue growth dynamics affect juxtacrine signal responses through implementing a custom synthetic gene circuit in Drosophila wing imaginal discs alongside mathematical modeling to determine synthetic Notch (synNotch) activation patterns. We find that the area of contact between cells largely determines the extent of synNotch activation, leading to the prediction that the shape of the interface between signal-sending and signal-receiving cells will impact the magnitude of the synNotch response. Notably, synNotch outputs form a graded spatial profile that extends several cell diameters from the signal source, providing evidence that the response to juxtacrine signals can persist in cells as they proliferate away from source cells, or that cells remain able to communicate directly over several cell diameters. Our model suggests the former mechanism may be sufficient, since it predicts graded outputs without diffusion or long-range cell-cell communication. Overall, we identify that cell-cell contact area together with output synthesis and decay rates likely govern the pattern of synNotch outputs in both space and time during tissue growth, insights that may have broader implications for juxtacrine signaling in general.

Understanding and manipulating extracellular behaviors of Wnt ligands

Wnt, a family of secreted signaling proteins, serves diverse functions in embryogenesis, organogenesis, cancer, and stem cell functions. In the context of development, Wnt has been considered a representative morphogen, forming concentration gradients to give positional information to cells or tissues. However, although gradients are often illustrated in schemata, the reality of concentration gradients, or in other words, actual spatial distribution of Wnt ligands, and their behaviors in the extracellular space still remain poorly known. To understand extracellular behavior of Wnt ligands, quantitative analyses such as fluorescence correlation spectroscopy (FCS) and fluorescence recovery after photobleaching (FRAP) are highly informative because Wnt dispersal involves physical and biochemical processes, such as diffusion and binding to or dissociation from cell surface molecules, including heparan sulfate proteoglycans (HSPGs). Here, I briefly discuss representative methods to quantify morphogen dynamics. In addition, I discuss molecular manipulations of morphogens, mainly focusing on use of protein binders, and synthetic biology of morphogens as indicators of current and future directions in this field.

Programming Juxtacrine-Based Synthetic Signaling Networks in a Cellular Potts Framework

Synthetic development is a synthetic biology subfield aiming to reprogram higher-order eukaryotic cells for tissue formation and morphogenesis. Reprogramming efforts commonly rely upon implementing custom signaling networks into these cells, but the efficient design of these signaling networks is a substantial challenge. It is difficult to predict the tissue/morphogenic outcome of these networks, and in vitro testing of many networks is both costly and time-consuming. We therefore developed a computational framework with an in silico cell line (ISCL) that sports basic but modifiable features such as adhesion, motility, growth, and division. More importantly, ISCL can be quickly engineered with custom genetic circuits to test, improve, and explore different signaling network designs. We implemented this framework in a free cellular Potts modeling software CompuCell3D. In this chapter, we briefly discuss how to start with CompuCell3D and then go through the steps of how to make and modify ISCL. We then go through the steps of programming custom genetic circuits into ISCL to generate an example signaling network.

Enabling neighbour labelling: using synthetic biology to explore how cells influence their neighbours

Cell-cell interactions are central to development, but exploring how a change in any given cell relates to changes in the neighbour of that cell can be technically challenging. Here, we review recent developments in synthetic biology and image analysis that are helping overcome this problem. We highlight the opportunities presented by these advances and discuss opportunities and limitations in applying them to developmental model systems.

Carotenoid ornaments and the spandrels of physiology: a critique of theory to explain condition dependency

Even as numerous studies have documented that the red and yellow coloration resulting from the deposition of carotenoids serves as an honest signal of condition, the evolution of condition dependency is contentious. The resource trade-off hypothesis proposes that condition-dependent honest signalling relies on a trade-off of resources between ornamental display and body maintenance. By this model, condition dependency can evolve through selection for a re-allocation of resources to promote ornament expression. By contrast, the index hypothesis proposes that selection focuses mate choice on carotenoid coloration that is inherently condition dependent because production of such coloration is inexorably tied to vital cellular processes. These hypotheses for the origins of condition dependency make strongly contrasting and testable predictions about ornamental traits. To assess these two models, we review the mechanisms of production of carotenoids, patterns of condition dependency involving different classes of carotenoids, and patterns of behavioural responses to carotenoid coloration. We review evidence that traits can be condition dependent without the influence of sexual selection and that novel traits can show condition-dependent expression as soon as they appear in a population, without the possibility of sexual selection. We conclude by highlighting new opportunities for studying condition-dependent signalling made possible by genetic manipulation and expression of ornamental traits in synthetic biological systems.

Synthetic symmetry breaking and programmable multicellular structure formation

During development, cells undergo symmetry breaking into differentiated subpopulations that self-organize into complex structures.1,2,3,4,5 However, few tools exist to recapitulate these behaviors in a controllable and coupled manner.6,7,8,9 Here, we engineer a stochastic recombinase genetic switch tunable by small molecules to induce programmable symmetry breaking, commitment to downstream cell fates, and morphological self-organization. Inducers determine commitment probabilities, generating tunable subpopulations as a function of inducer dosage. We use this switch to control the cell-cell adhesion properties of cells committed to each fate.10,11 We generate a wide variety of 3D morphologies from a monoclonal population and develop a computational model showing high concordance with experimental results, yielding new quantitative insights into the relationship between cell-cell adhesion strengths and downstream morphologies. We expect that programmable symmetry breaking, generating precise and tunable subpopulation ratios and coupled to structure formation, will serve as an integral component of the toolbox for complex tissue and organoid engineering.

Spatial biology of Ising-like synthetic genetic networks

BACKGROUND

Understanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial correlations (and anti-correlations) from interacting gene networks could serve to uncover generic scaling properties of these ubiquitous phenomena.

RESULTS

Here, we combine synthetic biology, statistical mechanics models, and computational simulations to study the spatial behavior of synthetic gene networks (SGNs) in Escherichia coli quasi-2D colonies growing on hard agar surfaces. Guided by the combined mechanisms of the contact process lattice simulation and two-dimensional Ising model (CPIM), we describe the spatial behavior of bi-stable and chemically coupled SGNs that self-organize into patterns of long-range correlations with power-law scaling or short-range anti-correlations. These patterns, resembling ferromagnetic and anti-ferromagnetic configurations of the Ising model near critical points, maintain their scaling properties upon changes in growth rate and cell shape.

CONCLUSIONS

Our findings shed light on the spatial biology of coupled and bistable gene networks in growing cell populations. This emergent spatial behavior could provide insights into the study and engineering of self-organizing gene patterns in eukaryotic tissues and bacterial consortia.

Microbial models of development: Inspiration for engineering self-assembled synthetic multicellularity

While the field of synthetic developmental biology has traditionally focused on the study of the rich developmental processes seen in metazoan systems, an attractive alternate source of inspiration comes from microbial developmental models. Microbes face unique lifestyle challenges when forming emergent multicellular collectives. As a result, the solutions they employ can inspire the design of novel multicellular systems. In this review, we dissect the strategies employed in multicellular development by two model microbial systems: the cellular slime mold Dictyostelium discoideum and the biofilm-forming bacterium Bacillus subtilis. Both microbes face similar challenges but often have different solutions, both from metazoan systems and from each other, to create emergent multicellularity. These challenges include assembling and sustaining a critical mass of participating individuals to support development, regulating entry into development, and assigning cell fates. The mechanisms these microbial systems exploit to robustly coordinate development under a wide range of conditions offer inspiration for a new toolbox of solutions to the synthetic development community. Additionally, recreating these phenomena synthetically offers a pathway to understanding the key principles underlying how these behaviors are coordinated naturally.

Self-organized collective cell behaviors as design principles for synthetic developmental biology

Over the past two decades, molecular cell biology has graduated from a mostly analytic science to one with substantial synthetic capability. This success is built on a deep understanding of the structure and function of biomolecules and molecular mechanisms. For synthetic biology to achieve similar success at the scale of tissues and organs, an equally deep understanding of the principles of development is required. Here, we review some of the central concepts and recent progress in tissue patterning, morphogenesis and collective cell migration and discuss their value for synthetic developmental biology, emphasizing in particular the power of (guided) self-organization and the role of theoretical advances in making developmental insights applicable in synthesis.

The emerging era of cell engineering: Harnessing the modularity of cells to program complex biological function

A new era of biological engineering is emerging in which living cells are used as building blocks to address therapeutic challenges. These efforts are distinct from traditional molecular engineering—their focus is not on optimizing individual genes and proteins as therapeutics, but rather on using molecular components as modules to reprogram how cells make decisions and communicate to achieve higher-order physiological functions in vivo. This cell-centric approach is enabled by a growing tool kit of components that can synthetically control core cell-level functional outputs, such as where in the body a cell should go, what other cells it should interact with, and what messages it should transmit or receive. The power of cell engineering has been clinically validated by the development of immune cells designed to kill cancer. This same tool kit for rewiring cell connectivity is beginning to be used to engineer cell therapies for a host of other diseases and to program the self-organization of tissues and organs. By forcing the conceptual distillation of complex biological functions into a finite set of instructions that operate at the cell level, these efforts also shed light on the fundamental hierarchical logic that links molecular components to higher-order physiological function.

Exploring standards for multicellular mammalian synthetic biology

Synthetic biology is moving towards bioengineering multicellular mammalian systems that are poised to advance tissue engineering, biomedicine, and the food industry. Despite progress, the field lacks a framework of standards that could greatly accelerate further development. Here, we explore the landscape of standards for multicellular mammalian synthetic biology. We discuss the limits of current technical standards and categorise unaddressed parameters into an abstraction hierarchy. We then define the concept of a 'synthetic multicellular mammalian system' and apply our standard hierarchy framework to illustrate how it could aid bioengineering endeavours. We conclude with promising areas that could shape the future of the field, flagging the need for a critical and holistic consideration of standards that requires cross-disciplinary dialogue.

Bacterial degrons in synthetic circuits

Bacterial proteases are a promising post-translational regulation strategy in synthetic circuits because they recognize specific amino acid degradation tags (degrons) that can be fine-tuned to modulate the degradation levels of tagged proteins. For this reason, recent efforts have been made in the search for new degrons. Here we review the up-to-date applications of degradation tags for circuit engineering in bacteria. In particular, we pay special attention to the effects of degradation bottlenecks in synthetic oscillators and introduce mathematical approaches to study queueing that enable the quantitative modelling of proteolytic queues.

SyNPL: Synthetic Notch pluripotent cell lines to monitor and manipulate cell interactions in vitro and in vivo

Cell-cell interactions govern differentiation and cell competition in pluripotent cells during early development, but the investigation of such processes is hindered by a lack of efficient analysis tools. Here, we introduce SyNPL: clonal pluripotent stem cell lines that employ optimised Synthetic Notch (SynNotch) technology to report cell-cell interactions between engineered ‘sender’ and ‘receiver’ cells in cultured pluripotent cells and chimaeric mouse embryos. A modular design makes it straightforward to adapt the system for programming differentiation decisions non-cell-autonomously in receiver cells in response to direct contact with sender cells. We demonstrate the utility of this system by enforcing neuronal differentiation at the boundary between two cell populations. In summary, we provide a new adaptation of SynNotch technology that could be used to identify cell interactions and to profile changes in gene or protein expression that result from direct cell-cell contact with defined cell populations in culture and in early embryos, and that can be customised to generate synthetic patterning of cell fate decisions.

Summary: Optimised Synthetic Notch circuitry in mouse pluripotent stem cells provides a modular tool with which to monitor cell-cell interactions and program synthetic patterning of cell fates in culture and in embryos.

Synthetic spatial patterning in bacteria: advances based on novel diffusible signals

Engineering multicellular patterning may help in the understanding of some fundamental laws of pattern formation and thus may contribute to the field of developmental biology. Furthermore, advanced spatial control over gene expression may revolutionize fields such as medicine, through organoid or tissue engineering. To date, foundational advances in spatial synthetic biology have often been made in prokaryotes, using artificial gene circuits. In this review, engineered patterns are classified into four levels of increasing complexity, ranging from spatial systems with no diffusible signals to systems with complex multi-diffusor interactions. This classification highlights how the field was held back by a lack of diffusible components. Consequently, we provide a summary of both previously characterized and some new potential candidate small-molecule signals that can regulate gene expression in Escherichia coli. These diffusive signals will help synthetic biologists to successfully engineer increasingly intricate, robust and tuneable spatial structures.

Hysteresis in PHYTOCHROME-INTERACTING FACTOR 4 and EARLY-FLOWERING 3 dynamics dominates warm daytime memory in Arabidopsis

Despite the identification of temperature sensors and downstream components involved in promoting stem growth by warm temperatures, when and how previous temperatures affect current plant growth remain unclear. Here we show that hypocotyl growth in Arabidopsis thaliana during the night responds not only to the current temperature but also to preceding daytime temperatures, revealing a short-term memory of previous conditions. Daytime temperature affected the levels of PHYTOCHROME-INTERACTING FACTOR 4 (PIF4) and LONG HYPOCOTYL 5 (HY5) in the nucleus during the next night. These factors jointly accounted for the observed growth kinetics, whereas nighttime memory of prior daytime temperature was impaired in pif4 and hy5 mutants. PIF4 promoter activity largely accounted for the temperature-dependent changes in PIF4 protein levels. Notably, the decrease in PIF4 promoter activity triggered by cooling required a stronger temperature shift than the increase caused by warming, representing a typical hysteretic effect; this hysteretic pattern required EARLY-FLOWERING 3 (ELF3). Warm temperatures promoted the formation of nuclear condensates of ELF3 in hypocotyl cells during the afternoon but not in the morning. These nuclear speckles showed poor sensitivity to subsequent cooling. We conclude that ELF3 achieves hysteresis and drives the PIF4 promoter into the same behavior, enabling a short-term memory of daytime temperature conditions.

Parameterized Computational Framework for the Description and Design of Genetic Circuits of Morphogenesis Based on Contact-Dependent Signaling and Changes in Cell-Cell Adhesion

Synthetic development is a nascent field of research that uses the tools of synthetic biology to design genetic programs directing cellular patterning and morphogenesis in higher eukaryotic cells, such as mammalian cells. One specific example of such synthetic genetic programs was based on cell-cell contact-dependent signaling using synthetic Notch pathways and was shown to drive the formation of multilayered spheroids by modulating cell-cell adhesion via differential expression of cadherin family proteins in a mouse fibroblast cell line (L929). The design method for these genetic programs relied on trial and error, which limited the number of possible circuits and parameter ranges that could be explored. Here, we build a parameterized computational framework that, given a cell-cell communication network driving changes in cell adhesion and initial conditions as inputs, predicts developmental trajectories. We first built a general computational framework where contact-dependent cell-cell signaling networks and changes in cell-cell adhesion could be designed in a modular fashion. We then used a set of available in vitro results (that we call the "training set" in analogy to similar pipelines in the machine learning field) to parameterize the computational model with values for adhesion and signaling. We then show that this parameterized model can qualitatively predict experimental results from a "testing set" of available in vitro data that varied the genetic network in terms of adhesion combinations, initial number of cells, and even changes to the network architecture. Finally, this parameterized model is used to recommend novel network implementation for the formation of a four-layered structure that has not been reported previously. The framework that we develop here could function as a testing ground to identify the reachable space of morphologies that can be obtained by controlling contact-dependent cell-cell communications and adhesion with these molecular tools and in this cellular system. Additionally, we discuss how the model could be expanded to include other forms of communication or effectors for the computational design of the next generation of synthetic developmental trajectories.

Sculpting with stem cells: how models of embryo development take shape

During embryogenesis, organisms acquire their shape given boundary conditions that impose geometrical, mechanical and biochemical constraints. A detailed integrative understanding how these morphogenetic information modules pattern and shape the mammalian embryo is still lacking, mostly owing to the inaccessibility of the embryo in vivo for direct observation and manipulation. These impediments are circumvented by the developmental engineering of embryo-like structures (stembryos) from pluripotent stem cells that are easy to access, track, manipulate and scale. Here, we explain how unlocking distinct levels of embryo-like architecture through controlled modulations of the cellular environment enables the identification of minimal sets of mechanical and biochemical inputs necessary to pattern and shape the mammalian embryo. We detail how this can be complemented with precise measurements and manipulations of tissue biochemistry, mechanics and geometry across spatial and temporal scales to provide insights into the mechanochemical feedback loops governing embryo morphogenesis. Finally, we discuss how, even in the absence of active manipulations, stembryos display intrinsic phenotypic variability that can be leveraged to define the constraints that ensure reproducible morphogenesis in vivo.

Programming cell growth into different cluster shapes using diffusible signals

Advances in genetic engineering technologies have allowed the construction of artificial genetic circuits, which have been used to generate spatial patterns of differential gene expression. However, the question of how cells can be programmed, and how complex the rules need to be, to achieve a desired tissue morphology has received less attention. Here, we address these questions by developing a mathematical model to study how cells can collectively grow into clusters with different structural morphologies by secreting diffusible signals that can influence cellular growth rates. We formulate how growth regulators can be used to control the formation of cellular protrusions and how the range of achievable structures scales with the number of distinct signals. We show that a single growth inhibitor is insufficient for the formation of multiple protrusions but may be achieved with multiple growth inhibitors, and that other types of signals can regulate the shape of protrusion tips. These examples illustrate how our approach could potentially be used to guide the design of regulatory circuits for achieving a desired target structure.

Rapid prototyping and design of cybergenetic single-cell controllers

The design and implementation of synthetic circuits that operate robustly in the cellular context is fundamental for the advancement of synthetic biology. However, their practical implementation presents challenges due to low predictability of synthetic circuit design and time-intensive troubleshooting. Here, we present the Cyberloop, a testing framework to accelerate the design process and implementation of biomolecular controllers. Cellular fluorescence measurements are sent in real-time to a computer simulating candidate stochastic controllers, which in turn compute the control inputs and feed them back to the controlled cells via light stimulation. Applying this framework to yeast cells engineered with optogenetic tools, we examine and characterize different biomolecular controllers, test the impact of non-ideal circuit behaviors such as dilution on their operation, and qualitatively demonstrate improvements in controller function with certain network modifications. From this analysis, we derive conditions for desirable biomolecular controller performance, thereby avoiding pitfalls during its biological implementation.

Quantitative developmental biology in vitro using micropatterning

Micropatterning encompasses a set of methods aimed at precisely controlling the spatial distribution of molecules onto the surface of materials. Biologists have borrowed the idea and adapted these methods, originally developed for electronics, to impose physical constraints on biological systems with the aim of addressing fundamental questions across biological scales from molecules to multicellular systems. Here, I approach this topic from a developmental biologist's perspective focusing specifically on how and why micropatterning has gained in popularity within the developmental biology community in recent years. Overall, this Primer provides a concise overview of how micropatterns are used to study developmental processes and emphasises how micropatterns are a useful addition to the developmental biologist's toolbox.

A review of regulated self-organizing approaches for tissue regeneration

Tissue and organ regeneration is the dynamic process by which a population of cells rearranges into a specific form with specific functions. Traditional tissue regeneration utilizes tissue grafting, cell implantation, and structured scaffolds to achieve clinical efficacy. However, tissue grafting methods face a shortage of donor tissue, while cell implantation may involve leakage of the implanted cells without a supportive 3D matrix. Cell migration, proliferation, and differentiation in structured scaffolds may disorganize and frustrate the artificially pre-designed structures, and sometimes involve immunogenic reactions. To overcome this limitation, the self-organizing properties and innate regenerative capability of tissue/organism formation in the absence of guidance by structured scaffolds has been investigated. This review emphasizes the growing subfield of the regulated self-organizing approach for neotissue formation and describes advances in the subfield using diverse, cutting-edge, inter-disciplinarity technologies. We cohesively summarize the directed self-organization of cells in the micro-engineered cell-ECM system and 3D/4D cell printing. Mathematical modeling of cellular self-organization is also discussed for providing rational guidance to intractable problems in tissue regeneration. It is envisioned that future self-organization approaches integrating biomathematics, micro-nano engineering, and gene circuits developed from synthetic biology will continue to work in concert with self-organizing morphogenesis to enhance rational control during self-organizing in tissue and organ regeneration.

Returning to kidney development to deliver synthetic kidneys

There is no doubt that the development of transplantable synthetic kidneys could improve the outcome for the many millions of people worldwide suffering from chronic kidney disease. Substantial progress has been made in the last 6 years in the generation of kidney tissue from stem cells. However, the limited scale, incomplete cellular complexity and functional immaturity of such structures suggests we are some way from this goal. While developmental biology has successfully guided advances to date, these human kidney models are limited in their capacity for ongoing nephrogenesis and lack corticomedullary definition, a unified vasculature and a coordinated exit path for urinary filtrate. This review will reassess our developmental understanding of how the mammalian embryo manages to create kidneys, how this has informed our progress to date and how both engineering and developmental biology can continue to guide us towards a synthetic kidney.

Annual Research Review: Anterior Modifiers in the Emergence of Neurodevelopmental Disorders (AMEND)-a systems neuroscience approach to common developmental disorders

We present the Anterior Modifiers in the Emergence of Neurodevelopmental Disorders (AMEND) framework, designed to reframe the field of prospective studies of neurodevelopmental disorders. In AMEND we propose conceptual, statistical and methodological approaches to separating markers of early-stage perturbations from later developmental modifiers. We describe the evidence for, and features of, these interacting components before outlining analytical approaches to studying how different profiles of early perturbations and later modifiers interact to produce phenotypic outcomes. We suggest this approach could both advance our theoretical understanding and clinical approach to the emergence of developmental psychopathology in early childhood.

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.

Synthetic Developmental Biology: Understanding Through Reconstitution

Reconstitution is an experimental strategy that seeks to recapitulate biological events outside their natural contexts using a reduced set of components. Classically, biochemical reconstitution has been extensively applied to identify the minimal set of molecules sufficient for recreating the basic chemistry of life. By analogy, reconstitution approaches to developmental biology recapitulate aspects of developmental events outside an embryo, with the goal of revealing the basic genetic circuits or physical cues sufficient for recreating developmental decisions. The rapidly growing repertoire of genetic, molecular, microscopic, and bioengineering tools is expanding the complexity and precision of reconstitution experiments. We review the emerging field of synthetic developmental biology, with a focus on the ways in which reconstitution strategies and new biological tools have enhanced our modern understanding of fundamental questions in developmental biology.

Predicting pattern formation in embryonic stem cells using a minimalist, agent-based probabilistic model

The mechanisms of pattern formation during embryonic development remain poorly understood. Embryonic stem cells in culture self-organise to form spatial patterns of gene expression upon geometrical confinement indicating that patterning is an emergent phenomenon that results from the many interactions between the cells. Here, we applied an agent-based modelling approach in order to identify plausible biological rules acting at the meso-scale within stem cell collectives that may explain spontaneous patterning. We tested different models involving differential motile behaviours with or without biases due to neighbour interactions. We introduced a new metric, termed stem cell aggregate pattern distance (SCAPD) to probabilistically assess the fitness of our models with empirical data. The best of our models improves fitness by 70% and 77% over the random models for a discoidal or an ellipsoidal stem cell confinement respectively. Collectively, our findings show that a parsimonious mechanism that involves differential motility is sufficient to explain the spontaneous patterning of the cells upon confinement. Our work also defines a region of the parameter space that is compatible with patterning. We hope that our approach will be applicable to many biological systems and will contribute towards facilitating progress by reducing the need for extensive and costly experiments.

Controlling spatiotemporal pattern formation in a concentration gradient with a synthetic toggle switch

The formation of spatiotemporal patterns of gene expression is frequently guided by gradients of diffusible signaling molecules. The toggle switch subnetwork, composed of two cross-repressing transcription factors, is a common component of gene regulatory networks in charge of patterning, converting the continuous information provided by the gradient into discrete abutting stripes of gene expression. We present a synthetic biology framework to understand and characterize the spatiotemporal patterning properties of the toggle switch. To this end, we built a synthetic toggle switch controllable by diffusible molecules in Escherichia coli. We analyzed the patterning capabilities of the circuit by combining quantitative measurements with a mathematical reconstruction of the underlying dynamical system. The toggle switch can produce robust patterns with sharp boundaries, governed by bistability and hysteresis. We further demonstrate how the hysteresis, position, timing, and precision of the boundary can be controlled, highlighting the dynamical flexibility of the circuit.

Using optogenetics to tackle systems-level questions of multicellular morphogenesis

Morphogenesis of multicellular systems is governed by precise spatiotemporal regulation of biochemical reactions and mechanical forces which together with environmental conditions determine the development of complex organisms. Current efforts in the field aim at decoding the system-level principles underlying the regulation of developmental processes. Toward this goal, optogenetics, the science of regulation of protein function with light, is emerging as a powerful new tool to quantitatively perturb protein function in vivo with unprecedented precision in space and time. In this review, we provide an overview of how optogenetics is helping to address system-level questions of multicellular morphogenesis and discuss future directions.

[George Lucas: prophet of transhumanism?]

Star Wars, a "general public" film saga, raises questions about human nature and transhumanism. It features different characters who are neither "real" humans nor robots; there are creatures that can be likened to advanced humans (cyborgs, chimeras or genetically-modified humans). Based on the "Star Wars" movie, we will approach some ways of modifying the human person both in his body and in his consciousness and we will wonder about the man of tomorrow by asking ourselves if George Lucas (director of the first film released) might have not been a visionary of the men of tomorrow.

Pattern formation mechanisms of self-organizing reaction-diffusion systems

Embryonic development is a largely self-organizing process, in which the adult body plan arises from a ball of cells with initially nearly equal potency. The reaction-diffusion theory first proposed by Alan Turing states that the initial symmetry in embryos can be broken by the interplay between two diffusible molecules, whose interactions lead to the formation of patterns. The reaction-diffusion theory provides a valuable framework for self-organized pattern formation, but it has been difficult to relate simple two-component models to real biological systems with multiple interacting molecular species. Recent studies have addressed this shortcoming and extended the reaction-diffusion theory to realistic multi-component networks. These efforts have challenged the generality of previous central tenets derived from the analysis of simplified systems and guide the way to a new understanding of self-organizing processes. Here, we discuss the challenges in modeling multi-component reaction-diffusion systems and how these have recently been addressed. We present a synthesis of new pattern formation mechanisms derived from these analyses, and we highlight the significance of reaction-diffusion principles for developmental and synthetic pattern formation.

Are the biomedical sciences ready for synthetic biology?

The ability to construct a functional system from its individual components is foundational to understanding how it works. Synthetic biology is a broad field that draws from principles of engineering and computer science to create new biological systems or parts with novel function. While this has drawn well-deserved acclaim within the biotechnology community, application of synthetic biology methodologies to study biological systems has potential to fundamentally change how biomedical research is conducted by providing researchers with improved experimental control. While the concepts behind synthetic biology are not new, we present evidence supporting why the current research environment is conducive for integration of synthetic biology approaches within biomedical research. In this perspective we explore the idea of synthetic biology as a discovery science research tool and provide examples of both top-down and bottom-up approaches that have already been used to answer important physiology questions at both the organismal and molecular level.

High-throughput micropatterning platform reveals Nodal-dependent bisection of peri-gastrulation-associated versus preneurulation-associated fate patterning

In vitro models of postimplantation human development are valuable to the fields of regenerative medicine and developmental biology. Here, we report characterization of a robust in vitro platform that enabled high-content screening of multiple human pluripotent stem cell (hPSC) lines for their ability to undergo peri-gastrulation-like fate patterning upon bone morphogenetic protein 4 (BMP4) treatment of geometrically confined colonies and observed significant heterogeneity in their differentiation propensities along a gastrulation associable and neuralization associable axis. This cell line-associated heterogeneity was found to be attributable to endogenous Nodal expression, with up-regulation of Nodal correlated with expression of a gastrulation-associated gene profile, and Nodal down-regulation correlated with a preneurulation-associated gene profile expression. We harness this knowledge to establish a platform of preneurulation-like fate patterning in geometrically confined hPSC colonies in which fates arise because of a BMPs signalling gradient conveying positional information. Our work identifies a Nodal signalling-dependent switch in peri-gastrulation versus preneurulation-associated fate patterning in hPSC cells, provides a technology to robustly assay hPSC differentiation outcomes, and suggests conserved mechanisms of organized fate specification in differentiating epiblast and ectodermal tissues.

Understanding the Mechanobiology of Early Mammalian Development through Bioengineered Models

Research in developmental biology has been recently enriched by a multitude of in vitro models recapitulating key milestones of mammalian embryogenesis. These models obviate the challenge posed by the inaccessibility of implanted embryos, multiply experimental opportunities, and favor approaches traditionally associated with organoids and tissue engineering. Here, we provide a perspective on how these models can be applied to study the mechano-geometrical contributions to early mammalian development, which still escape direct verification in species that develop in utero. We thus outline new avenues for robust and scalable perturbation of geometry and mechanics in ways traditionally limited to non-implanting developmental models.

Stem cell bioengineering: building from stem cell biology

New fundamental discoveries in stem cell biology have yielded potentially transformative regenerative therapeutics. However, widespread implementation of stem-cell-derived therapeutics remains sporadic. Barriers that impede the development of these therapeutics can be linked to our incomplete understanding of how the regulatory networks that encode stem cell fate govern the development of the complex tissues and organs that are ultimately required for restorative function. Bioengineering tools, strategies and design principles represent core components of the stem cell bioengineering toolbox. Applied to the different layers of complexity present in stem-cell-derived systems - from gene regulatory networks in single stem cells to the systemic interactions of stem-cell-derived organs and tissues - stem cell bioengineering can address existing challenges and advance regenerative medicine and cellular therapies.

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.

Adapting machine-learning algorithms to design gene circuits

BACKGROUND

Gene circuits are important in many aspects of biology, and perform a wide variety of different functions. For example, some circuits oscillate (e.g. the cell cycle), some are bistable (e.g. as cells differentiate), some respond sharply to environmental signals (e.g. ultrasensitivity), and some pattern multicellular tissues (e.g. Turing's model). Often, one starts from a given circuit, and using simulations, asks what functions it can perform. Here we want to do the opposite: starting from a prescribed function, can we find a circuit that executes this function? Whilst simple in principle, this task is challenging from a computational perspective, since gene circuit models are complex systems with many parameters. In this work, we adapted machine-learning algorithms to significantly accelerate gene circuit discovery.

RESULTS

We use gradient-descent optimization algorithms from machine learning to rapidly screen and design gene circuits. With this approach, we found that we could rapidly design circuits capable of executing a range of different functions, including those that: (1) recapitulate important in vivo phenomena, such as oscillators, and (2) perform complex tasks for synthetic biology, such as counting noisy biological events.

CONCLUSIONS

Our computational pipeline will facilitate the systematic study of natural circuits in a range of contexts, and allow the automatic design of circuits for synthetic biology. Our method can be readily applied to biological networks of any type and size, and is provided as an open-source and easy-to-use python module, GeneNet.

Microfluidics on the fly: Inexpensive rapid fabrication of thermally laminated microfluidic devices for live imaging and multimodal perturbations of multicellular systems

Microfluidic devices provide a platform for analyzing both natural and synthetic multicellular systems. Currently, substantial capital investment and expertise are required for creating microfluidic devices using standard soft-lithography. These requirements present barriers to entry for many nontraditional users of microfluidics, including developmental biology laboratories. Therefore, fabrication methodologies that enable rapid device iteration and work "out-of-the-box" can accelerate the integration of microfluidics with developmental biology. Here, we have created and characterized low-cost hybrid polyethylene terephthalate laminate (PETL) microfluidic devices that are suitable for cell and micro-organ culture assays. These devices were validated with mammalian cell lines and the Drosophila wing imaginal disc as a model micro-organ. First, we developed and tested PETLs that are compatible with both long-term cultures and high-resolution imaging of cells and organs. Further, we achieved spatiotemporal control of chemical gradients across the wing discs with a multilayered microfluidic device. Finally, we created a multilayered device that enables controllable mechanical loading of micro-organs. This mechanical actuation assay was used to characterize the response of larval wing discs at different developmental stages. Interestingly, increased deformation of the older wing discs for the same mechanical loading suggests that the compliance of the organ is increased in preparation for subsequent morphogenesis. Together, these results demonstrate the applicability of hybrid PETL devices for biochemical and mechanobiology studies on micro-organs and provide new insights into the mechanics of organ development.

Real-World Synthetic Biology: Is It Founded on an Engineering Approach, and Should It Be?

Authors often assert that a key feature of 21st-century synthetic biology is its use of an 'engineering approach'; design using predictive models, modular architecture, construction using well-characterized standard parts, and rigorous testing using standard metrics. This article examines whether this is, or even should be, the case. A brief survey of synthetic biology projects that have reached, or are near to, commercial application outside laboratories shows that they showed very few of these attributes. Instead, they featured much trial and error, and the use of specialized, custom components and assays. What is more, consideration of the special features of living systems suggest that a conventional engineering approach will often not be helpful. The article concludes that the engineering approach may be useful in some projects, but it should not be used to define or constrain synthetic biological endeavour, and that in fact the conventional engineering has more to gain by expanding and embracing more biological ways of working.