Artificial Symmetry-Breaking for Morphogenetic Engineering Bacterial Colonies

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.

Quantifying the fractal complexity of nutrient transport channels in Escherichia coli biofilms under varying cell shape and growth environment

Recent mesoscopic characterization of nutrient-transporting channels in Escherichia coli has allowed the identification and measurement of individual channels in whole mature colony biofilms. However, their complexity under different physiological and environmental conditions remains unknown. Analysis of confocal micrographs of colony biofilms formed by cell shape mutants of E. coli shows that channels have high fractal complexity, regardless of cell phenotype or growth medium. In particular, colony biofilms formed by the mutant strain ΔompR, which has a wide-cell phenotype, have a higher fractal dimension when grown on rich medium than when grown on minimal medium, with channel complexity affected by glucose and agar concentrations in the medium. Osmotic stress leads to a dramatic reduction in the ΔompR cell size but has a limited effect on channel morphology. This work shows that fractal image analysis is a powerful tool to quantify the effect of phenotypic mutations and growth environment on the morphological complexity of internal E. coli biofilm structures. If applied to a wider range of mutant strains, this approach could help elucidate the genetic determinants of channel formation in E. coli colony biofilms.

WebCM: A Web-Based Platform for Multiuser Individual-Based Modeling of Multicellular Microbial Populations and Communities

WebCM is a web platform that enables users to create, edit, run, and view individual-based simulations of multicellular microbial populations and communities on a remote compute server. WebCM builds upon the simulation software CellModeller in the back end and provides users with a web-browser-based modeling interface including model editing, execution, and playback. Multiple users can run and manage multiple simulations simultaneously, sharing the host hardware. Since it is based on CellModeller, it can utilize both GPU and CPU parallelization. The user interface provides real-time interactive 3D graphical representations for inspection of simulations at all time points, and the results can be downloaded for detailed offline analysis. It can be run on cloud computing services or on a local server, allowing collaboration within and between laboratories.

Phenotypic Patterning through Copy Number Adaptation to Environmental Gradients

We recently described a paradigm for engineering bacterial adaptation using plasmids coupled to the same origin of replication. In this study, we use plasmid coupling to generate spatially separated and phenotypically distinct populations in response to heterogeneous environments. Using a custom microfluidic device, we continuously tracked engineered populations along induced gradients, enabling an in-depth analysis of the spatiotemporal dynamics of plasmid coupling. Our observations reveal a pronounced phenotypic separation within 4 h exposure to an opposing gradient of AHL and arabinose. Additionally, by modulating the burden strength balance between coupled plasmids, we demonstrate the inherent limitations and tunability of this system. Intriguingly, phenotypic separation persists for an extended time, hinting at a biophysical spatial retention mechanism reminiscent of natural speciation processes. Complementing our experimental data, mathematical models provide invaluable insights into the underlying mechanisms and guide optimization of plasmid coupling for prospective applications of environmental copy number adaptation engineering across separated domains.

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.

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.

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.

High rates of plasmid cotransformation in E. coli overturn the clonality myth and reveal colony development

The concept of DNA transfer between bacteria was put forth by Griffith in 1928. During the dawn of molecular cloning of DNA in the 1980s, Hanahan described how the transformation of DNA plasmids into bacteria would allow for cloning of DNA fragments. Through this foundational work, it is widely taught that a typical transformation produces clonal bacterial colonies. Using low concentrations of several plasmids that encode different fluorescent proteins, under the same selective antibiotic, we show that E. coli bacteria readily accept multiple plasmids, resulting in widespread aclonality and reveal a complex pattern of colony development. Cotransformation of plasmids occurs by either CaCl2 or by electroporation methods. A bacterium rod transformed with three plasmids-each expressing a high level of a unique fluorescent protein-and replated on agar, appears to reassign a random number of the three fluorescent plasmids to its daughter cell during cell division. The potential to simultaneously follow multiple lineages of clonally related bacteria in a bacteria colony would allow for mosaic analysis of gene function. We show that clonally related bacterium rods self-organize in a fractal growth pattern and can remain linked during colony development revealing a potential target against microbiota growth.

Bacterial Growth, Communication, and Guided Chemotaxis in 3D-Bioprinted Hydrogel Environments

Bioprinting of engineered bacteria is of great interest for applications of synthetic biology in the context of living biomaterials, but so far, only a few viable approaches are available for the printing of gels hosting live Escherichia coli bacteria. Here, we develop a gentle extrusion-based bioprinting method based on an inexpensive alginate/agarose ink mixture that enables printing of E. coli into three-dimensional hydrogel structures up to 10 mm in height. We first characterize the rheological properties of the gel ink and then study the growth of the bacteria inside printed structures. We show that the maturation of fluorescent proteins deep within the printed structures can be facilitated by the addition of a calcium peroxide-based oxygen generation system. We then utilize the bioprinter to control different types of interactions between bacteria that depend on their spatial position. We next show quorum-sensing-based chemical communication between the engineered sender and receiver bacteria placed at different positions inside the bioprinted structure and finally demonstrate the fabrication of barrier structures defined by nonmotile bacteria that can guide the movement of chemotactic bacteria inside a gel. We anticipate that a combination of 3D bioprinting and synthetic biological approaches will lead to the development of living biomaterials containing engineered bacteria as dynamic functional units.

Decentralizing Cell-Free RNA Sensing With the Use of Low-Cost Cell Extracts

Cell-free gene expression systems have emerged as a promising platform for field-deployed biosensing and diagnostics. When combined with programmable toehold switch-based RNA sensors, these systems can be used to detect arbitrary RNAs and freeze-dried for room temperature transport to the point-of-need. These sensors, however, have been mainly implemented using reconstituted PURE cell-free protein expression systems that are difficult to source in the Global South due to their high commercial cost and cold-chain shipping requirements. Based on preliminary demonstrations of toehold sensors working on lysates, we describe the fast prototyping of RNA toehold switch-based sensors that can be produced locally and reduce the cost of sensors by two orders of magnitude. We demonstrate that these in-house cell lysates provide sensor performance comparable to commercial PURE cell-free systems. We further optimize these lysates with a CRISPRi strategy to enhance the stability of linear DNAs by knocking-down genes responsible for linear DNA degradation. This enables the direct use of PCR products for fast screening of new designs. As a proof-of-concept, we develop novel toehold sensors for the plant pathogen Potato Virus Y (PVY), which dramatically reduces the yield of this important staple crop. The local implementation of low-cost cell-free toehold sensors could enable biosensing capacity at the regional level and lead to more decentralized models for global surveillance of infectious disease.

Synthetic Lateral Inhibition in Periodic Pattern Forming Microbial Colonies

Multicellular entities are characterized by intricate spatial patterns, intimately related to the functions they perform. These patterns are often created from isotropic embryonic structures, without external information cues guiding the symmetry breaking process. Mature biological structures also display characteristic scales with repeating distributions of signals or chemical species across space. Many candidate patterning modules have been used to explain processes during development and typically include a set of interacting and diffusing chemicals or agents known as morphogens. Great effort has been put forward to better understand the conditions in which pattern-forming processes can occur in the biological domain. However, evidence and practical knowledge allowing us to engineer symmetry-breaking is still lacking. Here we follow a different approach by designing a synthetic gene circuit in E. coli that implements a local activation long-range inhibition mechanism. The synthetic gene network implements an artificial differentiation process that changes the physicochemical properties of the agents. Using both experimental results and modeling, we show that the proposed system is capable of symmetry-breaking leading to regular spatial patterns during colony growth. Studying how these patterns emerge is fundamental to further our understanding of the evolution of biocomplexity and the role played by self-organization. The artificial system studied here and the engineering perspective on embryogenic processes can help validate developmental theories and identify universal properties underpinning biological pattern formation, with special interest for the area of synthetic developmental biology.

Intra-colony channels in E. coli function as a nutrient uptake system

The ability of microorganisms to grow as aggregated assemblages has been known for many years, however their structure has remained largely unexplored across multiple spatial scales. The development of the Mesolens, an optical system which uniquely allows simultaneous imaging of individual bacteria over a 36 mm2 field of view, has enabled the study of mature Escherichia coli macro-colony biofilm architecture like never before. The Mesolens enabled the discovery of intra-colony channels on the order of 10 μm in diameter, that are integral to E. coli macro-colony biofilms and form as an emergent property of biofilm growth. These channels have a characteristic structure and re-form after total mechanical disaggregation of the colony. We demonstrate that the channels are able to transport particles and play a role in the acquisition of and distribution of nutrients through the biofilm. These channels potentially offer a new route for the delivery of dispersal agents for antimicrobial drugs to biofilms, ultimately lowering their impact on public health and industry.

Novel Tunable Spatio-Temporal Patterns From a Simple Genetic Oscillator Circuit

Multicellularity, the coordinated collective behavior of cell populations, gives rise to the emergence of self-organized phenomena at many different spatio-temporal scales. At the genetic scale, oscillators are ubiquitous in regulation of multicellular systems, including during their development and regeneration. Synthetic biologists have successfully created simple synthetic genetic circuits that produce oscillations in single cells. Studying and engineering synthetic oscillators in a multicellular chassis can therefore give us valuable insights into how simple genetic circuits can encode complex multicellular behaviors at different scales. Here we develop a study of the coupling between the repressilator synthetic genetic ring oscillator and constraints on cell growth in colonies. We show in silico how mechanical constraints generate characteristic patterns of growth rate inhomogeneity in growing cell colonies. Next, we develop a simple one-dimensional model which predicts that coupling the repressilator to this pattern of growth rate via protein dilution generates traveling waves of gene expression. We show that the dynamics of these spatio-temporal patterns are determined by two parameters; the protein degradation and maximum expression rates of the repressors. We derive simple relations between these parameters and the key characteristics of the traveling wave patterns: firstly, wave speed is determined by protein degradation and secondly, wavelength is determined by maximum gene expression rate. Our analytical predictions and numerical results were in close quantitative agreement with detailed individual based simulations of growing cell colonies. Confirming published experimental results we also found that static ring patterns occur when protein stability is high. Our results show that this pattern can be induced simply by growth rate dilution and does not require transition to stationary phase as previously suggested. Our method generalizes easily to other genetic circuit architectures thus providing a framework for multi-scale rational design of spatio-temporal patterns from genetic circuits. We use this method to generate testable predictions for the synthetic biology design-build-test-learn cycle.

From Microbial Communities to Distributed Computing Systems

A distributed biological system can be defined as a system whose components are located in different subpopulations, which communicate and coordinate their actions through interpopulation messages and interactions. We see that distributed systems are pervasive in nature, performing computation across all scales, from microbial communities to a flock of birds. We often observe that information processing within communities exhibits a complexity far greater than any single organism. Synthetic biology is an area of research which aims to design and build synthetic biological machines from biological parts to perform a defined function, in a manner similar to the engineering disciplines. However, the field has reached a bottleneck in the complexity of the genetic networks that we can implement using monocultures, facing constraints from metabolic burden and genetic interference. This makes building distributed biological systems an attractive prospect for synthetic biology that would alleviate these constraints and allow us to expand the applications of our systems into areas including complex biosensing and diagnostic tools, bioprocess control and the monitoring of industrial processes. In this review we will discuss the fundamental limitations we face when engineering functionality with a monoculture, and the key areas where distributed systems can provide an advantage. We cite evidence from natural systems that support arguments in favor of distributed systems to overcome the limitations of monocultures. Following this we conduct a comprehensive overview of the synthetic communities that have been built to date, and the components that have been used. The potential computational capabilities of communities are discussed, along with some of the applications that these will be useful for. We discuss some of the challenges with building co-cultures, including the problem of competitive exclusion and maintenance of desired community composition. Finally, we assess computational frameworks currently available to aide in the design of microbial communities and identify areas where we lack the necessary tools.

A synthetic system for asymmetric cell division in Escherichia coli

We describe a synthetic genetic circuit for controlling asymmetric cell division in E. coli in which a progenitor cell creates a differentiated daughter cell while retaining its original phenotype. Specifically, we engineered an inducible system that can bind and segregate plasmid DNA to a single position in the cell. Upon cell division, co-localized plasmids are kept by one and only one of the daughter cells. The other daughter cell receives no plasmid DNA and is hence irreversibly differentiated from its sibling. In this way, we achieved asymmetric cell division through asymmetric plasmid partitioning. We then used this system to achieve physical separation of genetically distinct cells by tying motility to differentiation. Finally, we characterized an orthogonal inducible circuit that enables the simultaneous asymmetric partitioning of two plasmid species, resulting in cells that have four distinct differentiated states. These results point the way towards engineering multicellular systems from prokaryotic hosts.

Hierarchical composition of reliable recombinase logic devices

A major goal of synthetic biology is to reprogram living organisms to solve pressing challenges in manufacturing, environmental remediation, and healthcare. Recombinase devices can efficiently encode complex logic in many species, yet current designs are performed on a case-by-case basis, limiting their scalability and requiring time-consuming optimization. Here we provide a systematic framework for engineering reliable recombinase logic devices by hierarchical composition of well-characterized, optimized recombinase switches. We apply this framework to build a recombinase logic device family supporting up to 4-input Boolean logic within a multicellular system. This work enables straightforward implementation of multicellular recombinase logic and will support the predictable engineering of several classes of recombinase devices to reliably control cellular behavior.

Genetic logic devices allow the host cell to incorporate multiple inputs to determine output behaviour. Here the authors provide a framework for engineering reliable recombinase-based devices and demonstrate 4-input logic in a multicellular system.

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.

Intercellular adhesion promotes clonal mixing in growing bacterial populations

Dense bacterial communities, known as biofilms, can have functional spatial organization driven by self-organizing chemical and physical interactions between cells, and their environment. In this work, we investigated intercellular adhesion, a pervasive property of bacteria in biofilms, to identify effects on the internal structure of bacterial colonies. We expressed the self-recognizing ag43 adhesin protein in Escherichia coli to generate adhesion between cells, which caused aggregation in liquid culture and altered microcolony morphology on solid media. We combined the adhesive phenotype with an artificial colony patterning system based on plasmid segregation, which marked clonal lineage domains in colonies grown from single cells. Engineered E. coli were grown to colonies containing domains with varying adhesive properties, and investigated with microscopy, image processing and computational modelling techniques. We found that intercellular adhesion elongated the fractal-like boundary between cell lineages only when both domains within the colony were adhesive, by increasing the rotational motion during colony growth. Our work demonstrates that adhesive intercellular interactions can have significant effects on the spatial organization of bacterial populations, which can be exploited for biofilm engineering. Furthermore, our approach provides a robust platform to study the influence of intercellular interactions on spatial structure in bacterial populations.

Role of growth rate on the orientational alignment of Escherichia coli in a slit

We present experimental data on the nematic alignment of Escherichia coli bacteria confined in a slit, with an emphasis on the effect of growth rate and corresponding changes in cell aspect ratio. Global alignment with the channel walls arises from the combination of local nematic ordering of nearby cells, induced by cell division and the elongated shape of the cells, and the preferential orientation of cells proximate to the side walls of the slit. Decreasing the growth rate leads to a decrease in alignment with the walls, which is attributed primarily to effects of changing cell aspect ratio rather than changes in the variance in cell area. Decreasing confinement also reduces the degree of alignment by a similar amount as a decrease in the growth rate, but the distribution of the degree of alignment differs. The onset of alignment with the channel walls is coincident with the slits reaching their steady-state occupancy and connected to the re-orientation of locally aligned regions with respect to the walls during density fluctuations.