Synthetic Morphogenesis

Evolutionary Implications of Self-Assembling Cybernetic Materials with Collective Problem-Solving Intelligence at Multiple Scales

In recent years, the scientific community has increasingly recognized the complex multi-scale competency architecture (MCA) of biology, comprising nested layers of active homeostatic agents, each forming the self-orchestrated substrate for the layer above, and, in turn, relying on the structural and functional plasticity of the layer(s) below. The question of how natural selection could give rise to this MCA has been the focus of intense research. Here, we instead investigate the effects of such decision-making competencies of MCA agential components on the process of evolution itself, using in silico neuroevolution experiments of simulated, minimal developmental biology. We specifically model the process of morphogenesis with neural cellular automata (NCAs) and utilize an evolutionary algorithm to optimize the corresponding model parameters with the objective of collectively self-assembling a two-dimensional spatial target pattern (reliable morphogenesis). Furthermore, we systematically vary the accuracy with which the uni-cellular agents of an NCA can regulate their cell states (simulating stochastic processes and noise during development). This allows us to continuously scale the agents' competency levels from a direct encoding scheme (no competency) to an MCA (with perfect reliability in cell decision executions). We demonstrate that an evolutionary process proceeds much more rapidly when evolving the functional parameters of an MCA compared to evolving the target pattern directly. Moreover, the evolved MCAs generalize well toward system parameter changes and even modified objective functions of the evolutionary process. Thus, the adaptive problem-solving competencies of the agential parts in our NCA-based in silico morphogenesis model strongly affect the evolutionary process, suggesting significant functional implications of the near-ubiquitous competency seen in living matter.

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.

Motile Living Biobots Self-Construct from Adult Human Somatic Progenitor Seed Cells

Fundamental knowledge gaps exist about the plasticity of cells from adult soma and the potential diversity of body shape and behavior in living constructs derived from genetically wild-type cells. Here anthrobots are introduced, a spheroid-shaped multicellular biological robot (biobot) platform with diameters ranging from 30 to 500 microns and cilia-powered locomotive abilities. Each Anthrobot begins as a single cell, derived from the adult human lung, and self-constructs into a multicellular motile biobot after being cultured in extra cellular matrix for 2 weeks and transferred into a minimally viscous habitat. Anthrobots exhibit diverse behaviors with motility patterns ranging from tight loops to straight lines and speeds ranging from 5-50 microns s-1 . The anatomical investigations reveal that this behavioral diversity is significantly correlated with their morphological diversity. Anthrobots can assume morphologies with fully polarized or wholly ciliated bodies and spherical or ellipsoidal shapes, each related to a distinct movement type. Anthrobots are found to be capable of traversing, and inducing rapid repair of scratches in, cultured human neural cell sheets in vitro. By controlling microenvironmental cues in bulk, novel structures, with new and unexpected behavior and biomedically-relevant capabilities, can be discovered in morphogenetic processes without direct genetic editing or manual sculpting.

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.

Steering self-organisation through confinement

Self-organisation is the spontaneous emergence of spatio-temporal structures and patterns from the interaction of smaller individual units. Examples are found across many scales in very different systems and scientific disciplines, from physics, materials science and robotics to biology, geophysics and astronomy. Recent research has highlighted how self-organisation can be both mediated and controlled by confinement. Confinement is an action over a system that limits its units' translational and rotational degrees of freedom, thus also influencing the system's phase space probability density; it can function as either a catalyst or inhibitor of self-organisation. Confinement can then become a means to actively steer the emergence or suppression of collective phenomena in space and time. Here, to provide a common framework and perspective for future research, we examine the role of confinement in the self-organisation of soft-matter systems and identify overarching scientific challenges that need to be addressed to harness its full scientific and technological potential in soft matter and related fields. By drawing analogies with other disciplines, this framework will accelerate a common deeper understanding of self-organisation and trigger the development of innovative strategies to steer it using confinement, with impact on, e.g., the design of smarter materials, tissue engineering for biomedicine and in guiding active matter.

The rapid-tome, a 3D-printed microtome, and an updated hand-sectioning method for high-quality plant sectioning

BACKGROUND

Microscopic analysis of plant anatomy is a common procedure in biology to study structure and function that requires high-quality sections for accurate measurements. Hand sectioning of specimens is typically limited to moderately soft tissue while harder samples prohibit sectioning by hand and/or result in inconsistent thicknesses.

RESULTS

Here we present both a clearly described hand-sectioning method and a novel microtome design that together provide the means to section a variety of plant sample types. The described hand-sectioning method for herbaceous stems works well for softer subjects but is less suitable for samples with secondary growth (e.g., wood production). Instead, the "Rapid-Tome" is a novel tool for sectioning both soft and tougher high-aspect-ratio samples, such as stems and roots, with excellent sample control. The Rapid-Tome can be 3D-printed in approximately 18 h on a mid-quality printer common at university maker spaces. After printing and trimming, Rapid-Tome assembly takes a few minutes with five metal parts common at hardware stores. Users sectioned a variety of plant samples including the hollow internodes of switchgrass (Panicum virgatum), fibrous switchgrass roots containing aerenchyma, and woody branches of eastern red cedar (Juniperus virginiana) and American sycamore (Platanus occidentalis). A comparative analyses with Rapid-Tome-produced sections readily revealed a significant difference in seasonal growth of sycamore xylem vessel area in spring (49%) vs. summer (23%). Additionally, high school students with no prior experience produced sections with the Rapid-Tome adequate for comparative analyses of various plant samples in less than an hour.

CONCLUSIONS

The described hand-sectioning method is suitable for softer tissues, including hollow-stemmed grasses and similar samples. In addition, the Rapid-Tome provides capacity to safely produce high-quality sections of tougher plant materials at a fraction of the cost of traditional microtomes combined with excellent sample control. The Rapid-Tome features rapid sectioning, sample advancement, blade changes, and sample changes; it is highly portable and can be used easily with minimal training making production of thin sections accessible for classroom and outreach use, in addition to research.

Evidence of a possible multicellular life cycle in Escherichia coli

Biofilms are surface-attached multicellular microbial communities. Their genetics have been extensively studied, but the cell-scale morphogenetic events of their formation are largely unknown. Here, we recorded the entirety of morphogenesis in Escherichia coli, and discovered a previously unknown multicellular self-assembly process. Unattached, single-cells formed 4-cell rosettes which grew into constant-width chains. After ∼10 cell generations, these multicellular chains attached to surfaces and stopped growing. Chains remained clonal throughout morphogenesis. We showed that this process generates biofilms, which we found are composed of attached clonal chains, aligned in parallel. We investigated genetics of chain morphogenesis: Ag43 facilitates rosette formation and clonality; type-1 fimbriae and curli promote stability and configuration; and extracellular polysaccharide production facilitates attachment. Our study establishes that E. coli, a unicellular organism, can follow a multistage, clonal, genetically-regulated, rosette-initiated multicellular life cycle. These findings have implications for synthetic biology, multicellular development, and the treatment and prevention of bacterial diseases.

Synthetic gene circuits for cell state detection and protein tuning in human pluripotent stem cells

During development, cell state transitions are coordinated through changes in the identity of molecular regulators in a cell type‐ and dose‐specific manner. The ability to rationally engineer such transitions in human pluripotent stem cells (hPSC) will enable numerous applications in regenerative medicine. Herein, we report the generation of synthetic gene circuits that can detect a desired cell state using AND‐like logic integration of endogenous miRNAs (classifiers) and, upon detection, produce fine‐tuned levels of output proteins using an miRNA‐mediated output fine‐tuning technology (miSFITs). Specifically, we created an “hPSC ON” circuit using a model‐guided miRNA selection and circuit optimization approach. The circuit demonstrates robust PSC‐specific detection and graded output protein production. Next, we used an empirical approach to create an “hPSC‐Off” circuit. This circuit was applied to regulate the secretion of endogenous BMP4 in a state‐specific and fine‐tuned manner to control the composition of differentiating hPSCs. Our work provides a platform for customized cell state‐specific control of desired physiological factors in hPSC, laying the foundation for programming cell compositions in hPSC‐derived tissues and beyond.

Optogenetic control of apical constriction induces synthetic morphogenesis in mammalian tissues

The emerging field of synthetic developmental biology proposes bottom-up approaches to examine the contribution of each cellular process to complex morphogenesis. However, the shortage of tools to manipulate three-dimensional (3D) shapes of mammalian tissues hinders the progress of the field. Here we report the development of OptoShroom3, an optogenetic tool that achieves fast spatiotemporal control of apical constriction in mammalian epithelia. Activation of OptoShroom3 through illumination in an epithelial Madin-Darby Canine Kidney (MDCK) cell sheet reduces the apical surface of the stimulated cells and causes displacements in the adjacent regions. Light-induced apical constriction provokes the folding of epithelial cell colonies on soft gels. Its application to murine and human neural organoids leads to thickening of neuroepithelia, apical lumen reduction in optic vesicles, and flattening in neuroectodermal tissues. These results show that spatiotemporal control of apical constriction can trigger several types of 3D deformation depending on the initial tissue context.

Arrested coalescence of multicellular aggregates

Multicellular aggregates are known to exhibit liquid-like properties. The fusion process of two cell aggregates is commonly studied as the coalescence of two viscous drops. However, tissues are complex materials and can exhibit viscoelastic behaviour. It is known that elastic effects can prevent the complete fusion of two drops, a phenomenon known as arrested coalescence. Here we study this phenomenon in stem cell aggregates and provide a theoretical framework which agrees with the experiments. In addition, agent-based simulations show that active cell fluctuations can control a solid-to-fluid phase transition, revealing that arrested coalescence can be found in the vicinity of an unjamming transition. By analysing the dynamics of the fusion process and combining it with nanoindentation measurements, we obtain the effective viscosity, shear modulus and surface tension of the aggregates. More generally, our work provides a simple, fast and inexpensive method to characterize the mechanical properties of viscoelastic materials.

Synthetic Morphogenesis: introducing IEEE journal readers to programming living mammalian cells to make structures

Synthetic morphogenesis is a new engineering discipline, in which cells are genetically engineered to make designed shapes and structures. At least in this early phase of the field, devices tend to make use of natural shape-generating processes that operate in embryonic development, but invoke them artificially at times and in orders of a technologist's choosing. This requires construction of genetic control, sequencing and feedback systems that have close parallels to electronic design, which is one reason the field may be of interest to readers of IEEE journals. The other reason is that synthetic morphogenesis allows the construction of two-way interfaces, especially opto-genetic and opto-electronic, between the living and the electronic, allowing unprecedented information flow and control between the two types of 'machine'. This review introduces synthetic morphogenesis, illustrates what has been achieved, drawing parallels wherever possible between biology and electronics, and looks forward to likely next steps and challenges to be overcome.

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.

Synthetic mammalian signaling circuits for robust cell population control

In multicellular organisms, cells actively sense and control their own population density. Synthetic mammalian quorum-sensing circuits could provide insight into principles of population control and extend cell therapies. However, a key challenge is reducing their inherent sensitivity to "cheater" mutations that evade control. Here, we repurposed the plant hormone auxin to enable orthogonal mammalian cell-cell communication and quorum sensing. We designed a paradoxical population control circuit, termed "Paradaux," in which auxin stimulates and inhibits net cell growth at different concentrations. This circuit limited population size over extended timescales of up to 42 days of continuous culture. By contrast, when operating in a non-paradoxical regime, population control became more susceptible to mutational escape. These results establish auxin as a versatile "private" communication system and demonstrate that paradoxical circuit architectures can provide robust population control.

Mathematical Modelling in Plant Synthetic Biology

Mathematical modelling techniques are integral to current research in plant synthetic biology. Modelling approaches can provide mechanistic understanding of a system, allowing predictions of behaviour and thus providing a tool to help design and analyse biological circuits. In this chapter, we provide an overview of mathematical modelling methods and their significance for plant synthetic biology. Starting with the basics of dynamics, we describe the process of constructing a model over both temporal and spatial scales and highlight crucial approaches, such as stochastic modelling and model-based design. Next, we focus on the model parameters and the techniques required in parameter analysis. We then describe the process of selecting a model based on tests and criteria and proceed to methods that allow closer analysis of the system's behaviour. Finally, we highlight the importance of uncertainty in modelling approaches and how to deal with a lack of knowledge, noisy data, and biological variability; all aspects that play a crucial role in the cooperation between the experimental and modelling components. Overall, this chapter aims to illustrate the importance of mathematical modelling in plant synthetic biology, providing an introduction for those researchers who are working with or working on modelling techniques.

Mechanical oscillations orchestrate axial patterning through Wnt activation in Hydra

Mechanical input shapes cell fate decisions during development and regeneration in many systems, yet the mechanisms of this cross-talk are often unclear. In regenerating Hydra tissue spheroids, periodic osmotically driven inflation and deflation cycles generate mechanical stimuli in the form of tissue stretching. Here, we demonstrate that tissue stretching during inflation is important for the appearance of the head organizer—a group of cells that secrete the Wnt3 ligand. Exploiting time series RNA expression profiles, we identify the up-regulation of Wnt signaling as a key readout of the mechanical input. In this system, the levels of Wnt3 expression correspond to the levels of stretching, and Wnt3 overexpression alone enables successful regeneration in the absence of mechanical stimulation. Our findings enable the incorporation of mechanical signals in the framework of Hydra patterning and highlight the broad significance of mechanochemical feedback loops for patterning epithelial lumens.

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.

Ten future challenges for synthetic biology

After 2 decades of growth and success, synthetic biology has now become a mature field that is driving significant innovation in the bioeconomy and pushing the boundaries of the biomedical sciences and biotechnology. So what comes next? In this article, 10 technological advances are discussed that are expected and hoped to come from the next generation of research and investment in synthetic biology; from ambitious projects to make synthetic life, cell simulators and custom genomes, through to new methods of engineering biology that use automation, deep learning and control of evolution. The non-exhaustive list is meant to inspire those joining the field and looks forward to how synthetic biology may evolve over the coming decades.

Localized Proteolysis for the Construction of Intracellular Asymmetry in Escherichia coli

Protein-level regulations have gained importance in building synthetic circuits, as they offer a potential advantage in the speed of operation compared to gene regulation circuits. In nature, localized protein degradation is prevalent in polarizing cellular signaling. We, therefore, set out to systematically investigate whether localized proteolysis can be employed to construct intracellular asymmetry in Escherichia coli. We demonstrate that, by inserting a cognate cleavage site between the reporter and C-terminal degron, the unstable reporter can be stabilized in the presence of the tobacco etch virus protease. Furthermore, the split protease can be functionally reconstituted by the PopZ-based polarity system to exert localized proteolysis. Selective stabilization of the unstable reporter at the PopZ pole can lead to intracellular asymmetry in E. coli. Our study provides complementary evidence to support that localized proteolysis may be a strategy for polarization in developmental cell biology. Circuits designed in this study may also help to expand the synthetic biology repository for the engineering of synthetic morphogenesis, particularly for processes that require rapid control of local protein abundance.

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.

Signaling, Deconstructed: Using Optogenetics to Dissect and Direct Information Flow in Biological Systems

Cells receive enormous amounts of information from their environment. How they act on this information-by migrating, expressing genes, or relaying signals to other cells-comprises much of the regulatory and self-organizational complexity found across biology. The "parts list" involved in cell signaling is generally well established, but how do these parts work together to decode signals and produce appropriate responses? This fundamental question is increasingly being addressed with optogenetic tools: light-sensitive proteins that enable biologists to manipulate the interaction, localization, and activity state of proteins with high spatial and temporal precision. In this review, we summarize how optogenetics is being used in the pursuit of an answer to this question, outlining the current suite of optogenetic tools available to the researcher and calling attention to studies that increase our understanding of and improve our ability to engineer biology.

Context-aware synthetic biology by controller design: Engineering the mammalian cell

The rise of systems biology has ushered a new paradigm: the view of the cell as a system that processes environmental inputs to drive phenotypic outputs. Synthetic biology provides a complementary approach, allowing us to program cell behavior through the addition of synthetic genetic devices into the cellular processor. These devices, and the complex genetic circuits they compose, are engineered using a design-prototype-test cycle, allowing for predictable device performance to be achieved in a context-dependent manner. Within mammalian cells, context effects impact device performance at multiple scales, including the genetic, cellular, and extracellular levels. In order for synthetic genetic devices to achieve predictable behaviors, approaches to overcome context dependence are necessary. Here, we describe control systems approaches for achieving context-aware devices that are robust to context effects. We then consider cell fate programing as a case study to explore the potential impact of context-aware devices for regenerative medicine applications.

Synthetic living machines: A new window on life

Increased control of biological growth and form is an essential gateway to transformative medical advances. Repairing of birth defects, restoring lost or damaged organs, normalizing tumors, all depend on understanding how cells cooperate to make specific, functional large-scale structures. Despite advances in molecular genetics, significant gaps remain in our understanding of the meso-scale rules of morphogenesis. An engineering approach to this problem is the creation of novel synthetic living forms, greatly extending available model systems beyond evolved plant and animal lineages. Here, we review recent advances in the emerging field of synthetic morphogenesis, the bioengineering of novel multicellular living bodies. Emphasizing emergent self-organization, tissue-level guided self-assembly, and active functionality, this work is the essential next generation of synthetic biology. Aside from useful living machines for specific functions, the rational design and analysis of new, coherent anatomies will greatly increase our understanding of foundational questions in evolutionary developmental and cell biology.

Morphogenesis: Guiding Embryonic Development with Light

Embryonic development is controlled by dynamic signaling systems that are translated into patterns of gene expression. Optogenetics has now been used to rescue genetic loss of Drosophila terminal patterning, bringing us a step closer to reconstruct morphogenesis synthetically.

Liquid Crystal Elastomers for Biological Applications

The term liquid crystal elastomer (LCE) describes a class of materials that combine the elastic entropy behaviour associated with conventional elastomers with the stimuli responsive properties of anisotropic liquid crystals. LCEs consequently exhibit attributes of both elastomers and liquid crystals, but additionally have unique properties not found in either. Recent developments in LCE synthesis, as well as the understanding of the behaviour of liquid crystal elastomers—namely their mechanical, optical and responsive properties—is of significant relevance to biology and biomedicine. LCEs are abundant in nature, highlighting the potential use of LCEs in biomimetics. Their exceptional tensile properties and biocompatibility have led to research exploring their applications in artificial tissue, biological sensors and cell scaffolds by exploiting their actuation and shock absorption properties. There has also been significant recent interest in using LCEs as a model for morphogenesis. This review provides an overview of some aspects of LCEs which are of relevance in different branches of biology and biomedicine, as well as discussing how recent LCE advances could impact future applications.

Construction of intracellular asymmetry and asymmetric division in Escherichia coli

The design principle of establishing an intracellular protein gradient for asymmetric cell division is a long-standing fundamental question. While the major molecular players and their interactions have been elucidated via genetic approaches, the diversity and redundancy of natural systems complicate the extraction of critical underlying features. Here, we take a synthetic cell biology approach to construct intracellular asymmetry and asymmetric division in Escherichia coli, in which division is normally symmetric. We demonstrate that the oligomeric PopZ from Caulobacter crescentus can serve as a robust polarized scaffold to functionalize RNA polymerase. Furthermore, by using another oligomeric pole-targeting DivIVA from Bacillus subtilis, the newly synthesized protein can be constrained to further establish intracellular asymmetry, leading to asymmetric division and differentiation. Our findings suggest that the coupled oligomerization and restriction in diffusion may be a strategy for generating a spatial gradient for asymmetric cell division.

Plant Biosystems Design Research Roadmap 1.0

Human life intimately depends on plants for food, biomaterials, health, energy, and a sustainable environment. Various plants have been genetically improved mostly through breeding, along with limited modification via genetic engineering, yet they are still not able to meet the ever-increasing needs, in terms of both quantity and quality, resulting from the rapid increase in world population and expected standards of living. A step change that may address these challenges would be to expand the potential of plants using biosystems design approaches. This represents a shift in plant science research from relatively simple trial-and-error approaches to innovative strategies based on predictive models of biological systems. Plant biosystems design seeks to accelerate plant genetic improvement using genome editing and genetic circuit engineering or create novel plant systems through de novo synthesis of plant genomes. From this perspective, we present a comprehensive roadmap of plant biosystems design covering theories, principles, and technical methods, along with potential applications in basic and applied plant biology research. We highlight current challenges, future opportunities, and research priorities, along with a framework for international collaboration, towards rapid advancement of this emerging interdisciplinary area of research. Finally, we discuss the importance of social responsibility in utilizing plant biosystems design and suggest strategies for improving public perception, trust, and acceptance.

Reverse and Forward Engineering Multicellular Structures with Optogenetics

Understanding how cells self-organize into functional higher-order structures is of great interest, both towards deciphering animal development, as well as for our ability to predictably build custom tissues to meet research and therapeutic needs. The proper organization of cells across length-scales results from interconnected and dynamic networks of molecules and cells. Optogenetic probes provide dynamic and tunable control over molecular events within cells, and thus represent a powerful approach to both dissect and control collective cell behaviors. Here we emphasize the breadth of the optogenetic toolkit and discuss how these methods have already been used to reverse-engineer the design rules of developing organisms. We also offer our perspective on the rich potential for optogenetics to power forward-engineering of tissue assembly towards the generation of bespoke tissues with user-defined properties.

Reactivation of Atrium Genes Is a Primer for Heart Infarction or Regeneration

The inability of the adult heart to repair or regenerate is manifested in prevalent morbidity and mortality related to myocardial infarction and heart failure. However, the cue to the reactivation of cardiomyocyte proliferation in the adult remains largely unknown. In the present study, three independent datasets were explored using bioinformatics analysis methods to solve the problem. Our results revealed that atrium genes were upregulated in response to the injury, which indicates the possible cell type withdraw and reinitiation of proliferation capability. Our findings might provide an alternative viewpoint on the cardiomyocyte regeneration or myocardial infarction.

Cell-in-the-loop pattern formation with optogenetically emulated cell-to-cell signaling

Designing and implementing synthetic biological pattern formation remains challenging due to underlying theoretical complexity as well as the difficulty of engineering multicellular networks biochemically. Here, we introduce a cell-in-the-loop approach where living cells interact through in silico signaling, establishing a new testbed to interrogate theoretical principles when internal cell dynamics are incorporated rather than modeled. We present an easy-to-use theoretical test to predict the emergence of contrasting patterns in gene expression among laterally inhibiting cells. Guided by the theory, we experimentally demonstrate spontaneous checkerboard patterning in an optogenetic setup, where cell-to-cell signaling is emulated with light inputs calculated in silico from real-time gene expression measurements. The scheme successfully produces spontaneous, persistent checkerboard patterns for systems of sixteen patches, in quantitative agreement with theoretical predictions. Our research highlights how tools from dynamical systems theory may inform our understanding of patterning, and illustrates the potential of cell-in-the-loop for engineering synthetic multicellular systems.

Substrate composition directs slime molds behavior

Cells, including unicellulars, are highly sensitive to external constraints from their environment. Amoeboid cells change their cell shape during locomotion and in response to external stimuli. Physarum polycephalum is a large multinucleated amoeboid cell that extends and develops pseudopods. In this paper, changes in cell behavior and shape were measured during the exploration of homogenous and non-homogenous environments that presented neutral, and nutritive and/or adverse substances. In the first place, we developed a fully automated image analysis method to measure quantitatively changes in both migration and shape. Then we measured various metrics that describe the area covered, the exploration dynamics, the migration rate and the slime mold shape. Our results show that: (1) Not only the nature, but also the spatial distribution of chemical substances affect the exploration behavior of slime molds; (2) Nutritive and adverse substances both slow down the exploration and prevent the formation of pseudopods; and (3) Slime mold placed in an adverse environment preferentially occupies previously explored areas rather than unexplored areas using mucus secretion as a buffer. Our results also show that slime molds migrate at a rate governed by the substrate up until they get within a critical distance to chemical substances.

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

Synthetic biology is the discipline of engineering application-driven biological functionalities that were not evolved by nature. Early breakthroughs of cell engineering, which were based on ectopic (over)expression of single sets of transgenes, have already had a revolutionary impact on the biotechnology industry, regenerative medicine and blood transfusion therapies. Now, we require larger-scale, rationally assembled genetic circuits engineered to programme and control various human cell functions with high spatiotemporal precision in order to solve more complex problems in applied life sciences, biomedicine and environmental sciences. This will open new possibilities for employing synthetic biology to advance personalized medicine by converting cells into living therapeutics to combat hitherto intractable diseases.

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.

The Cognitive Lens: a primer on conceptual tools for analysing information processing in developmental and regenerative morphogenesis

Brains exhibit plasticity, multi-scale integration of information, computation and memory, having evolved by specialization of non-neural cells that already possessed many of the same molecular components and functions. The emerging field of basal cognition provides many examples of decision-making throughout a wide range of non-neural systems. How can biological information processing across scales of size and complexity be quantitatively characterized and exploited in biomedical settings? We use pattern regulation as a context in which to introduce the Cognitive Lens-a strategy using well-established concepts from cognitive and computer science to complement mechanistic investigation in biology. To facilitate the assimilation and application of these approaches across biology, we review tools from various quantitative disciplines, including dynamical systems, information theory and least-action principles. We propose that these tools can be extended beyond neural settings to predict and control systems-level outcomes, and to understand biological patterning as a form of primitive cognition. We hypothesize that a cognitive-level information-processing view of the functions of living systems can complement reductive perspectives, improving efficient top-down control of organism-level outcomes. Exploration of the deep parallels across diverse quantitative paradigms will drive integrative advances in evolutionary biology, regenerative medicine, synthetic bioengineering, cognitive neuroscience and artificial intelligence. This article is part of the theme issue 'Liquid brains, solid brains: How distributed cognitive architectures process information'.

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.

Cell competition during reprogramming gives rise to dominant clones

The ability to generate induced pluripotent stem cells from differentiated cell types has enabled researchers to engineer cell states. Although studies have identified molecular networks that reprogram cells to pluripotency, the cellular dynamics of these processes remain poorly understood. Here, by combining cellular barcoding, mathematical modeling, and lineage tracing approaches, we demonstrate that reprogramming dynamics in heterogeneous populations are driven by dominant “elite” clones. Clones arise a priori from a population of poised mouse embryonic fibroblasts derived from Wnt1-expressing cells that may represent a neural crest–derived population. This work highlights the importance of cellular dynamics in fate programming outcomes and uncovers cell competition as a mechanism by which cells with eliteness emerge to occupy and dominate the reprogramming niche.

Biological Engineered Living Materials: Growing Functional Materials with Genetically Programmable Properties

Natural biological materials exhibit remarkable properties: self-assembly from simple raw materials, precise control of morphology, diverse physical and chemical properties, self-repair, and the ability to sense-and-respond to environmental stimuli. Despite having found numerous uses in human industry and society, the utility of natural biological materials is limited. But, could it be possible to genetically program microbes to create entirely new and useful biological materials? At the intersection between microbiology, material science, and synthetic biology, the emerging field of biological engineered living materials (ELMs) aims to answer this question. Here we review recent efforts to program cells to produce living materials with novel functional properties, focusing on microbial systems that can be engineered to grow materials and on new genetic circuits for pattern formation that could be used to produce the more complex systems of 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.

A general framework dedicated to computational morphogenesis Part II - Knowledge representation and architecture

In our previous paper we introduced morphogenesis and post-embryonic life as arising from cells interacting via coupled chemical, electrical and mechanical processes occurring across multiple organization levels. We reviewed these processes from the perspectives of developmental biology and how they relate to physics-based constitutive equations that are well suited to model intercellular interactions' fields. In this paper we will describe a knowledge representation and architectural design strategy that can organize and encode the biochemical, biological and biophysical data necessary to represent and model the highly specialized and diversified cells that constitute living tissues. Since there are about 200 different types of cells in mammalian tissues, a huge amount of molecular, cellular and tissue data must be accounted for. This data cannot be incorporated in an ad hoc manner but, on the contrary, must be organized according to some sound principles. We give an overview of these principles and describe how they can be incorporated as proper features of a Knowledge Base System (KBS) dedicated to computational morphogenesis (CM).

A general framework dedicated to computational morphogenesis Part I - Constitutive equations

In order to understand living organisms, considerable experimental efforts and resources have been devoted to correlate genes and their expressions with cell, tissue, organ and whole organisms' phenotypes. This data driven approach to knowledge discovery has led to many breakthrough in our understanding of healthy and diseased states, and is paving the way to improve the diagnosis and treatment of diseases. Complementary to this data-driven approach, computational models of biological systems based on first principles have been developed in order to deepen our understanding of the multi-scale dynamics that drives normal and pathological biological functions. In this paper we describe the biological, physical and mathematical concepts that led to the design of a Computational Morphogenesis (CM) platform baptized Generic Modeling and Simulating Platform (GMSP). Its role is to generate realistic 3D multi-scale biological tissues from virtual stem cells and the intended target applications include in virtuo studies of normal and abnormal tissue (re)generation as well as the development of complex diseases such as carcinogenesis. At all space-scales of interest, biological agents interact with each other via biochemical, bioelectrical, and mechanical fields that operate in concert during embryogenesis, growth and adult life. The spatio-temporal dependencies of these fields can be modeled by physics-based constitutive equations that we propose to examine in relation to the landmark biological events that occur during embryogenesis.

Programming self-organizing multicellular structures with synthetic cell-cell signaling

A common theme in the self-organization of multicellular tissues is the use of cell-cell signaling networks to induce morphological changes. We used the modular synNotch juxtacrine signaling platform to engineer artificial genetic programs in which specific cell-cell contacts induced changes in cadherin cell adhesion. Despite their simplicity, these minimal intercellular programs were sufficient to yield assemblies with hallmarks of natural developmental systems: robust self-organization into multidomain structures, well-choreographed sequential assembly, cell type divergence, symmetry breaking, and the capacity for regeneration upon injury. The ability of these networks to drive complex structure formation illustrates the power of interlinking cell signaling with cell sorting: Signal-induced spatial reorganization alters the local signals received by each cell, resulting in iterative cycles of cell fate branching. These results provide insights into the evolution of multicellularity and demonstrate the potential to engineer customized self-organizing tissues or materials.

Guided morphogenesis through optogenetic activation of Rho signalling during early Drosophila embryogenesis

During organismal development, cells undergo complex changes in shape whose causal relationship to individual morphogenetic processes remains unclear. The modular nature of such processes suggests that it should be possible to isolate individual modules, determine the minimum set of requirements sufficient to drive tissue remodeling, and re-construct morphogenesis. Here we use optogenetics to reconstitute epithelial folding in embryonic Drosophila tissues that otherwise would not undergo invagination. We show that precise spatial and temporal activation of Rho signaling is sufficient to trigger apical constriction and tissue folding. Induced furrows can occur at any position along the dorsal–ventral or anterior–posterior embryo axis in response to the spatial pattern and level of optogenetic activation. Thus, epithelial folding is a direct function of the spatio-temporal organization and strength of Rho signaling that on its own is sufficient to drive tissue internalization independently of any pre-determined condition or differentiation program associated with endogenous invagination processes.

Optogenetics is opening the possibility to not only perturb morphogenesis, but also to guide it. Here, the authors use this technique to reconstruct epithelial folding in Drosophila embryos and study the relationship between strength of Rho activation, apical constrictions, and tissue invagination.

Engineered Living Materials: Prospects and Challenges for Using Biological Systems to Direct the Assembly of Smart Materials

Vast potential exists for the development of novel, engineered platforms that manipulate biology for the production of programmed advanced materials. Such systems would possess the autonomous, adaptive, and self-healing characteristics of living organisms, but would be engineered with the goal of assembling bulk materials with designer physicochemical or mechanical properties, across multiple length scales. Early efforts toward such engineered living materials (ELMs) are reviewed here, with an emphasis on engineered bacterial systems, living composite materials which integrate inorganic components, successful examples of large-scale implementation, and production methods. In addition, a conceptual exploration of the fundamental criteria of ELM technology and its future challenges is presented. Cradled within the rich intersection of synthetic biology and self-assembling materials, the development of ELM technologies allows the power of biology to be leveraged to grow complex structures and objects using a palette of bio-nanomaterials.

Programmed hierarchical patterning of bacterial populations

Modern genetic tools allow the dissection and emulation of fundamental mechanisms shaping morphogenesis in multicellular organisms. Several synthetic genetic circuits for control of multicellular patterning have been reported to date. However, hierarchical induction of gene expression domains has received little attention from synthetic biologists, despite its importance in biological self-organization. Here we report a synthetic genetic system implementing population-based AND-logic for programmed autonomous induction of bacterial gene expression domains. We develop a ratiometric assay for bacteriophage T7 RNA polymerase activity and use it to systematically characterize different intact and split enzyme variants. We then utilize the best-performing variant to build a three-color patterning system responsive to two different homoserine lactones. We validate the AND gate-like behavior of this system both in cell suspension and in surface culture. Finally, we use the synthetic circuit in a membrane-based spatial assay to demonstrate programmed hierarchical patterning of gene expression across bacterial populations.