Sequential Establishment of Stripe Patterns in an Expanding Cell Population

Synthetic microbial ecology: engineering habitats for modular consortia

Microbiomes, the complex networks of micro-organisms and the molecules through which they interact, play a crucial role in health and ecology. Over at least the past two decades, engineering biology has made significant progress, impacting the bio-based industry, health, and environmental sectors; but has only recently begun to explore the engineering of microbial ecosystems. The creation of synthetic microbial communities presents opportunities to help us understand the dynamics of wild ecosystems, learn how to manipulate and interact with existing microbiomes for therapeutic and other purposes, and to create entirely new microbial communities capable of undertaking tasks for industrial biology. Here, we describe how synthetic ecosystems can be constructed and controlled, focusing on how the available methods and interaction mechanisms facilitate the regulation of community composition and output. While experimental decisions are dictated by intended applications, the vast number of tools available suggests great opportunity for researchers to develop a diverse array of novel microbial ecosystems.

Light Control in Microbial Systems

Light is a key environmental component influencing many biological processes, particularly in prokaryotes such as archaea and bacteria. Light control techniques have revolutionized precise manipulation at molecular and cellular levels in recent years. Bacteria, with adaptability and genetic tractability, are promising candidates for light control studies. This review investigates the mechanisms underlying light activation in bacteria and discusses recent advancements focusing on light control methods and techniques for controlling bacteria. We delve into the mechanisms by which bacteria sense and transduce light signals, including engineered photoreceptors and light-sensitive actuators, and various strategies employed to modulate gene expression, protein function, and bacterial motility. Furthermore, we highlight recent developments in light-integrated methods of controlling microbial responses, such as upconversion nanoparticles and optical tweezers, which can enhance the spatial and temporal control of bacteria and open new horizons for biomedical applications.

Automatic design of gene regulatory mechanisms for spatial pattern formation

Gene regulatory mechanisms (GRMs) control the formation of spatial and temporal expression patterns that can serve as regulatory signals for the development of complex shapes. Synthetic developmental biology aims to engineer such genetic circuits for understanding and producing desired multicellular spatial patterns. However, designing synthetic GRMs for complex, multi-dimensional spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a methodology to automatically design GRMs that can produce any given two-dimensional spatial pattern. The proposed approach uses two orthogonal morphogen gradients acting as positional information signals in a multicellular tissue area or culture, which constitutes a continuous field of engineered cells implementing the same designed GRM. To efficiently design both the circuit network and the interaction mechanisms-including the number of genes necessary for the formation of the target spatial pattern-we developed an automated algorithm based on high-performance evolutionary computation. The tolerance of the algorithm can be configured to design GRMs that are either simple to produce approximate patterns or complex to produce precise patterns. We demonstrate the approach by automatically designing GRMs that can produce a diverse set of synthetic spatial expression patterns by interpreting just two orthogonal morphogen gradients. The proposed framework offers a versatile approach to systematically design and discover complex genetic circuits producing spatial patterns.

Viral infection dynamics with immune chemokines and CTL mobility modulated by the infected cell density

We study a viral infection model incorporating both cell-to-cell infection and immune chemokines. Based on experimental results in the literature, we make a standing assumption that the cytotoxic T lymphocytes (CTL) will move toward the location with more infected cells, while the diffusion rate of CTL is a decreasing function of the density of infected cells. We first establish the global existence and ultimate boundedness of the solution via a priori energy estimates. We then define the basic reproduction number of viral infection R 0 and prove (by the uniform persistence theory, Lyapunov function technique and LaSalle invariance principle) that the infection-free steady state E 0 is globally asymptotically stable ifR 0 < 1 . WhenR 0 > 1 , then E 0 becomes unstable, and another basic reproduction number of CTL response R 1 becomes the dynamic threshold in the sense that ifR 1 < 1 , then the CTL-inactivated steady state E 1 is globally asymptotically stable; and ifR 1 > 1 , then the immune response is uniform persistent and, under an additional technical condition the CTL-activated steady state E 2 is globally asymptotically stable. To establish the global stability results, we need to prove point dissipativity, obtain uniform persistence, construct suitable Lyapunov functions, and apply the LaSalle invariance principle.

Self-enhanced mobility enables vortex pattern formation in living matter

Ranging from subcellular organelle biogenesis to embryo development, the formation of self-organized structures is a hallmark of living systems. Whereas the emergence of ordered spatial patterns in biology is often driven by intricate chemical signalling that coordinates cellular behaviour and differentiation1-4, purely physical interactions can drive the formation of regular biological patterns such as crystalline vortex arrays in suspensions of spermatozoa5 and bacteria6. Here we discovered a new route to self-organized pattern formation driven by physical interactions, which creates large-scale regular spatial structures with multiscale ordering. Specifically we found that dense bacterial living matter spontaneously developed a lattice of mesoscale, fast-spinning vortices; these vortices each consisted of around 104-105 motile bacterial cells and were arranged in space at greater than centimetre scale and with apparent hexagonal order, whereas individual cells in the vortices moved in coordinated directions with strong polar and vortical order. Single-cell tracking and numerical simulations suggest that the phenomenon is enabled by self-enhanced mobility in the system-that is, the speed of individual cells increasing with cell-generated collective stresses at a given cell density. Stress-induced mobility enhancement and fluidization is prevalent in dense living matter at various scales of length7-9. Our findings demonstrate that self-enhanced mobility offers a simple physical mechanism for pattern formation in living systems and, more generally, in other active matter systems10 near the boundary of fluid- and solid-like behaviours11-17.

Quorum sensing-induced transition from colloidal waves to Turing-like patterns in chemorepulsive active colloids

The study of active systems, especially in the presence of a chemical background field, is garnering significant attention. Traditionally, the self-propelled velocity of active colloids was assumed to be constant, independent of the local density of colloids. In this work, we introduce a chemotactic active system that features quorum sensing (QS), wherein particles act as chemorepellents. Interestingly, these particles lose their activity in regions of high local particle density. Our findings reveal that QS leads to a transition from an oscillatory colloidal wave to a Turing-like pattern, with the observation of an intermediate state. With the variation of the sensing threshold, both the mean oscillation frequency of the system and the number of clusters exhibit non-monotonic dependence. Furthermore, the QS-induced pattern differs markedly from systems without QS, primarily due to the competitive interplay between diffusion and chemotaxis. The dynamics of this phenomenon are explained using a coarse-grained mean field model.

Colloidal Self-Assembly: From Passive to Active Systems

Self-assembly fundamentally implies the organization of small sub-units into large structures or patterns without the intervention of specific local interactions. This process is commonly observed in nature, occurring at various scales ranging from atomic/molecular assembly to the formation of complex biological structures. Colloidal particles may serve as micrometer-scale surrogates for studying assembly, particularly for the poorly understood kinetic and dynamic processes at the atomic scale. Recent advances in colloidal self-assembly have enabled the programmable creation of novel materials with tailored properties. We here provide an overview and comparison of both passive and active colloidal self-assembly, with a discussion on the energy landscape and interactions governing both types. In the realm of passive colloidal assembly, many impressive and important structures have been realized, including colloidal molecules, one-dimensional chains, two-dimensional lattices, and three-dimensional crystals. In contrast, active colloidal self-assembly, driven by optical, electric, chemical, or other fields, involves more intricate dynamic processes, offering more flexibility and potential new applications. A comparative analysis underscores the critical distinctions between passive and active colloidal assemblies, highlighting the unique collective behaviors emerging in active systems. These behaviors encompass collective motion, motility-induced phase segregation, and exotic properties arising from out-of-equilibrium thermodynamics. Through this comparison, we aim to identify the future opportunities in active assembly research, which may suggest new application domains.

The role of filamentous matrix molecules in shaping the architecture and emergent properties of bacterial biofilms

Numerous bacteria naturally occur within spatially organised, multicellular communities called biofilms. Moreover, most bacterial infections proceed with biofilm formation, posing major challenges to human health. Within biofilms, bacterial cells are embedded in a primarily self-produced extracellular matrix, which is a defining feature of all biofilms. The biofilm matrix is a complex, viscous mixture primarily composed of polymeric substances such as polysaccharides, filamentous protein fibres, and extracellular DNA. The structured arrangement of the matrix bestows bacteria with beneficial emergent properties that are not displayed by planktonic cells, conferring protection against physical and chemical stresses, including antibiotic treatment. However, a lack of multi-scale information at the molecular level has prevented a better understanding of this matrix and its properties. Here, we review recent progress on the molecular characterisation of filamentous biofilm matrix components and their three-dimensional spatial organisation within biofilms.

Characterization and Control of the Run-and-Tumble Dynamics of Escherichia Coli

We characterize the full spatiotemporal gait of populations of swimming Escherichia coli using renewal processes to analyze the measurements of intermediate scattering functions. This allows us to demonstrate quantitatively how the persistence length of an engineered strain can be controlled by a chemical inducer and to report a controlled transition from perpetual tumbling to smooth swimming. For wild-type E. coli, we measure simultaneously the microscopic motility parameters and the large-scale effective diffusivity, hence quantitatively bridging for the first time small-scale directed swimming and macroscopic diffusion.

Synthetic Homoserine Lactone Sensors for Gram-Positive Bacillus subtilis Using LuxR-Type Regulators

A universal biochemical signal for bacterial cell-cell communication could facilitate programming dynamic responses in diverse bacterial consortia. However, the classical quorum sensing paradigm is that Gram-negative and Gram-positive bacteria generally communicate via homoserine lactones (HSLs) or oligopeptide molecular signals, respectively, to elicit population responses. Here, we create synthetic HSL sensors for Gram-positive Bacillus subtilis 168 using allosteric LuxR-type regulators (RpaR, LuxR, RhlR, and CinR) and synthetic promoters. Promoters were combinatorially designed from different sequence elements (-35, -16, -10, and transcriptional start regions). We quantified the effects of these combinatorial promoters on sensor activity and determined how regulator expression affects its activation, achieving up to 293-fold activation. Using the statistical design of experiments, we identified significant effects of promoter regions and pairwise interactions on sensor activity, which helped to understand the sequence-function relationships for synthetic promoter design. We present the first known set of functional HSL sensors (≥20-fold dynamic range) in B. subtilis for four different HSL chemical signals: p-coumaroyl-HSL, 3-oxohexanoyl-HSL, n-butyryl-HSL, and n-(3-hydroxytetradecanoyl)-HSL. This set of synthetic HSL sensors for a Gram-positive bacterium can pave the way for designable interspecies communication within microbial consortia.

Quantitative characterization of run-and-tumble statistics in bulk bacterial suspensions

We introduce a numerical method to extract the parameters of run-and-tumble dynamics from experimental measurements of the intermediate scattering function. We show that proceeding in Laplace space is unpractical and employ instead renewal processes to work directly in real time. We first validate our approach against data produced using agent-based simulations. This allows us to identify the length and time scales required for an accurate measurement of the motility parameters, including tumbling frequency and swim speed. We compare different models for the run-and-tumble dynamics by accounting for speed variability at the single-cell and population level, respectively. Finally, we apply our approach to experimental data on wild-type Escherichia coli obtained using differential dynamic microscopy.

Motility-Induced Phase Separation Mediated by Bacterial Quorum Sensing

We study motility-induced phase separation (MIPS) in living active matter, in which cells interact through chemical signaling, or quorum sensing. In contrast to previous theories of MIPS, our multiscale continuum model accounts explicitly for genetic regulation of signal production and motility. Through analysis and simulations, we derive a new criterion for the onset of MIPS that depends on features of the genetic network. Furthermore, we identify and characterize a new type of oscillatory instability that occurs when gene regulation inside cells promotes motility in higher signal concentrations.

Non-reciprocity across scales in active mixtures

In active matter, particles typically experience mediated interactions, which are not constrained by Newton's third law and are therefore generically non-reciprocal. Non-reciprocity leads to a rich set of emerging behaviors that are hard to account for starting from the microscopic scale, due to the absence of a generic theoretical framework out of equilibrium. Here we consider bacterial mixtures that interact via mediated, non-reciprocal interactions (NRI) like quorum-sensing and chemotaxis. By explicitly relating microscopic and macroscopic dynamics, we show that, under conditions that we derive explicitly, non-reciprocity may fade upon coarse-graining, leading to large-scale equilibrium descriptions. In turn, this allows us to account quantitatively, and without fitting parameters, for the rich behaviors observed in microscopic simulations including phase separation, demixing, and multi-phase coexistence. We also derive the condition under which non-reciprocity survives coarse-graining, leading to a wealth of dynamical patterns. Again, our analytical approach allows us to predict the phase diagram of the system starting from its microscopic description. All in all, our work demonstrates that the fate of non-reciprocity across scales is a subtle and important question.

Interplay of cell motility and self-secreted extracellular polymeric substance induced depletion effects on spatial patterning in a growing microbial colony

Reproducing bacteria self-organize to develop patterned biofilms in various conditions. Various factors contribute to the shaping of a multicellular bacterial organization. Here we investigate how motility force and self-secreted extracellular polymeric substances (EPS) influence bacterial cell aggregation, leading to phase-separated colonies using a particle-based/individual-based model. Our findings highlight the critical role of the interplay between motility force and depletion effects in regulating phase separation within a growing colony under far-from-equilibrium conditions. We observe that increased motility force hinders depletion-induced cell aggregation and phase segregation, necessitating a higher depletion effect for highly motile bacteria to undergo phase separation within a growing biofilm. We present a phase diagram illustrating the systematic variation of motility force and repulsive mechanical force, shedding light on the combined contributions of these two factors: self-propulsive motion and aggregation due to the depletion effect, resulting in the presence of small to large bacterial aggregates. Furthermore, our study reveals the dynamic nature of clustering, marked by changes in cluster size over time. Additionally, our findings suggest that differential dispersion among the components can lead to the localization of EPS at the periphery of a growing colony. Our study enhances the understanding of the collective dynamics of motile bacterial cells within a growing colony, particularly in the presence of a self-secreted polymer-driven depletion effect.

Density-dependent within-patch movement behavior of two competing species

Movement behavior is central to understanding species distributions, population dynamics and coexistence with other species. Although the relationship between conspecific density and emigration has been well studied, little attention has been paid to how interspecific competitor density affects another species' movement behavior. We conducted releases of two species of competing Tribolium flour beetles at different densities, alone and together in homogeneous microcosms, and tested whether their recaptures-with-distance were well described by a random-diffusion model. We also determined whether mean displacement distances varied with the release density of conspecific and heterospecific beetles. A diffusion model provided a good fit to the redistribution of T. castaneum and T. confusum at all release densities, explaining an average of >60% of the variation in recaptures. For both species, mean displacement (directly proportional to the diffusion rate) exhibited a humped-shaped relationship with conspecific density. Finally, we found that both species of beetle impacted the within-patch movement rates of the other species, but the effect depended on density. For T. castaneum in the highest density treatment, the addition of equal numbers of T. castaneum or T. confusum had the same effect, with mean displacements reduced by approximately one half. The same result occurred for T. confusum released at an intermediate density. In both cases, it was total beetle abundance, not species identity that mattered to mean displacement. We suggest that displacement or diffusion rates that exhibit a nonlinear relationship with density or depend on the presence or abundance of interacting species should be considered when attempting to predict the spatial spread of populations or scaling up to heterogeneous landscapes.

Cooperation in bioluminescence: understanding the role of autoinducers by a stochastic random resistor model

Quorum sensing is a communication mechanism adopted by different bacterial strains for the regulation of gene transcription. It takes place through the exchange of molecules called autoinducers. Bioluminescence is an emergent threshold phenomenon shown by some bacteria strains. Its precise relationship to quorum sensing is a debated topic, particularly regarding the role of the different autoinducers used by bacteria. In this paper, assuming a direct relationship between bioluminescence and quorum sensing, we investigate the role of multiple autoinducers in the bioluminescence response of Vibrio harveyi, considered as a model bioluminescent strain, due to its quorum sensing circuitry involving an array of three different autoinducers. Experiments on mutants of this bacterium, obtained by suppression of one or more autoinducers, reveal their relative non-trivial relevance and cooperative interaction patterns. The proposed analysis is implemented on a regular lattice, whose nodes represent microbial entities equipped with charges, which represent the ability to up/down regulate the gene expression. Quorum sensing results from a Coulomb-type field, produced by the charges. In analogy with random resistor network models, the lattice is permeated by an effective current which accounts for the amount and distribution of the charges. We propose that the presence of different autoinducers correspond to a different up/down regulation of gene expression, i.e., to a different way to account for the charges. Then, by introducing a modulation of the charge dependence into the current flowing within the network, we show that it is able to describe the bioluminescence exhibited by V. harveyi mutants. Furthermore, modulation of the charge dependence allows the interactions between the different autoinducers to be taken into account, providing a prediction regarding the data obtainable under specific growth conditions.

Dynamical Pattern Formation without Self-Attraction in Quorum-Sensing Active Matter: The Interplay between Nonreciprocity and Motility

We study a minimal model involving two species of particles interacting via quorum-sensing rules. Combining simulations of the microscopic model and linear stability analysis of the associated coarse-grained field theory, we identify a mechanism for dynamical pattern formation that does not rely on the standard route of intraspecies effective attractive interactions. Instead, our results reveal a highly dynamical phase of chasing bands induced only by the combined effects of self-propulsion and nonreciprocity in the interspecies couplings. Turning on self-attraction, we find that the system may phase separate into a macroscopic domain of such chaotic chasing bands coexisting with a dilute gas. We show that the chaotic dynamics of bands at the interfaces of this phase-separated phase results in anomalously slow coarsening.

Pattern formation by bacteria-phage interactions

The interactions between bacteria and phages-viruses that infect bacteria-play critical roles in agriculture, ecology, and medicine; however, how these interactions influence the spatial organization of both bacteria and phages remain largely unexplored. Here, we address this gap in knowledge by developing a theoretical model of motile, proliferating bacteria that aggregate via motility-induced phase separation (MIPS) and encounter phage that infect and lyse the cells. We find that the non-reciprocal predator-prey interactions between phage and bacteria strongly alter spatial organization, in some cases giving rise to a rich array of finite-scale stationary and dynamic patterns in which bacteria and phage coexist. We establish principles describing the onset and characteristics of these diverse behaviors, thereby helping to provide a biophysical basis for understanding pattern formation in bacteria-phage systems, as well as in a broader range of active and living systems with similar predator-prey or other non-reciprocal interactions.

Automatic design of gene regulatory mechanisms for spatial pattern formation

Synthetic developmental biology aims to engineer gene regulatory mechanisms (GRMs) for understanding and producing desired multicellular patterns and shapes. However, designing GRMs for spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a methodology to automatically design GRMs that can produce any given spatial pattern. The proposed approach uses two orthogonal morphogen gradients acting as positional information signals in a multicellular tissue area or culture, which constitutes a continuous field of engineered cells implementing the same designed GRM. To efficiently design both the circuit network and the interaction mechanisms-including the number of genes necessary for the formation of the target pattern-we developed an automated algorithm based on high-performance evolutionary computation. The tolerance of the algorithm can be configured to design GRMs that are either simple to produce approximate patterns or complex to produce precise patterns. We demonstrate the approach by automatically designing GRMs that can produce a diverse set of synthetic spatial expression patterns by interpreting just two orthogonal morphogen gradients. The proposed framework offers a versatile approach to systematically design and discover pattern-producing genetic circuits.

Enabling technology and core theory of synthetic biology

Synthetic biology provides a new paradigm for life science research ("build to learn") and opens the future journey of biotechnology ("build to use"). Here, we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology, including synthesis and assembly of a genome, DNA storage, gene editing, molecular evolution and de novo design of function proteins, cell and gene circuit engineering, cell-free synthetic biology, artificial intelligence (AI)-aided synthetic biology, as well as biofoundries. We also introduce the concept of quantitative synthetic biology, which is guiding synthetic biology towards increased accuracy and predictability or the real rational design. We conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.

A programmable oral bacterial hydrogel for controllable production and release of nanovaccine for tumor immunotherapy

Oral protein vaccines are mainly used to prevent the infection of intestinal pathogens in clinic due to their high safety and strong compliance. However, it is necessary to design the efficient delivery systems to overcome the harsh gastrointestinal environment in the application process. Here we established a programmable oral bacterial hydrogel system for spatiotemporally controllable production and release of nanovaccines. The system was divided into three parts: (1) Engineered bacteria were encapsulated in chitosan-sodium alginate microcapsules, which offered protection against the extreme acid conditions in the stomach. (2) Microcapsules were dissolved, and then engineered bacteria were released and colonized in the intestine. (3) The release of nanovaccines was controlled periodically by a synchronous lysis genetic circuit for tumor immunotherapy. Compared to control groups, tumor volume of subcutaneous tumor-bearing mice treated with bacterial microgels releasing optimized nanovaccine was almost inhibited by 75% and T cell response was activated at least 2-fold. We believe that this programmable bacterial hydrogel will offer a promising way for the application of oral nanovaccines.

Engineered bacterial swarm patterns as spatial records of environmental inputs

A diverse array of bacteria species naturally self-organize into durable macroscale patterns on solid surfaces via swarming motility-a highly coordinated and rapid movement of bacteria powered by flagella. Engineering swarming is an untapped opportunity to increase the scale and robustness of coordinated synthetic microbial systems. Here we engineer Proteus mirabilis, which natively forms centimeter-scale bullseye swarm patterns, to 'write' external inputs into visible spatial records. Specifically, we engineer tunable expression of swarming-related genes that modify pattern features, and we develop quantitative approaches to decoding. Next, we develop a dual-input system that modulates two swarming-related genes simultaneously, and we separately show that growing colonies can record dynamic environmental changes. We decode the resulting multicondition patterns with deep classification and segmentation models. Finally, we engineer a strain that records the presence of aqueous copper. This work creates an approach for building macroscale bacterial recorders, expanding the framework for engineering emergent microbial behaviors.

Engineered Living Materials For Sustainability

Recent advances in synthetic biology and materials science have given rise to a new form of materials, namely engineered living materials (ELMs), which are composed of living matter or cell communities embedded in self-regenerating matrices of their own or artificial scaffolds. Like natural materials such as bone, wood, and skin, ELMs, which possess the functional capabilities of living organisms, can grow, self-organize, and self-repair when needed. They also spontaneously perform programmed biological functions upon sensing external cues. Currently, ELMs show promise for green energy production, bioremediation, disease treatment, and fabricating advanced smart materials. This review first introduces the dynamic features of natural living systems and their potential for developing novel materials. We then summarize the recent research progress on living materials and emerging design strategies from both synthetic biology and materials science perspectives. Finally, we discuss the positive impacts of living materials on promoting sustainability and key future research directions.

Microphase separation of living cells

Self-organization of cells is central to a variety of biological systems and physical concepts of condensed matter have proven instrumental in deciphering some of their properties. Here we show that microphase separation, long studied in polymeric materials and other inert systems, has a natural counterpart in living cells. When placed below a millimetric film of liquid nutritive medium, a quasi two-dimensional, high-density population of Dictyostelium discoideum cells spontaneously assembles into compact domains. Their typical size of 100 μm is governed by a balance between competing interactions: an adhesion acting as a short-range attraction and promoting aggregation, and an effective long-range repulsion stemming from aerotaxis in near anoxic condition. Experimental data, a simple model and cell-based simulations all support this scenario. Our findings establish a generic mechanism for self-organization of living cells and highlight oxygen regulation as an emergent organizing principle for biological matter.

Population dynamics with resource-dependent dispersal: single- and two-species models

In this paper, we consider the population models with resource-dependent dispersal for single-species and two-species with competition. For the single-species model, it is well-known that the total population supported by the environment is always greater than the environmental carrying capacity if the dispersal is simply random diffusion. However, we find that the total population supported can be equal or smaller than the environmental carrying capacity when the dispersal depends on the resource distribution. This analytical finding not only well agrees with the yeast experiment observation of Zhang et al. (Ecol Lett 20(9):1118-1128, 2017), but also indicates that resource-dependent dispersal may produce different outcomes compared to the random dispersal. For the two-species competition model, when two competing species use the same dispersal strategy up to a multiplicative constant (i.e. their dispersal strategies are proportional) or both diffusion coefficients are large, we give a classification of global dynamics. We also show, along with numerical simulations, that if the dispersal strategies are resource-dependent, even one species has slower diffusion, coexistence is possible though competitive exclusion may occur under different conditions. This is distinct from the prominent result that with random dispersal the slower diffuser always wipes out its fast competitor. Our analytical results, supported by the numerical simulations, show that the resource-dependent dispersal strategy has profound impact on the population dynamics and evolutionary processes.

Global dynamics and pattern formation for predator-prey system with density-dependent motion

In this paper, we concern with the predator-prey system with generalist predator and density-dependent prey-taxis in two-dimensional bounded domains. We derive the existence of classical solutions with uniform-in-time bound and global stability for steady states under suitable conditions through the Lyapunov functionals. In addition, by linear instability analysis and numerical simulations, we conclude that the prey density-dependent motility function can trigger the periodic pattern formation when it is monotone increasing.

The present and future of Turing models in developmental biology

The Turing model (or reaction-diffusion model), first published in 1952, is a mathematical model that can account for autonomy in the morphogenesis of organisms. Although initially controversial, the model has gradually gained wider acceptance among experimental embryologists due to the accumulation of experimental data to support it. More recently, this model and others based on it have been used not only to explain biological phenomena conceptually but also as working hypotheses for molecular-level experiments and as internal components of more-complex 3D models. In this Spotlight, I will provide a personal perspective from an experimental biologist on some of the recent developments of the Turing model.

On a two-species competitive predator-prey system with density-dependent diffusion

This paper deals with a two-species competitive predator-prey system with density-dependent diffusion, i.e., \begin{eqnarray*}\label{1a} \left\{ \begin{split}{}&u_t=\Delta (d_{1}(w)u)+\gamma_{1}uF_{1}(w)-uh_{1}(u)-\beta_{1}uv,&(x,t)\in \Omega\times (0,\infty),\\&v_t=\Delta (d_{2}(w)v)+\gamma_{2}vF_{2}(w)-vh_{2}(v)-\beta_{2}uv,&(x,t)\in \Omega\times (0,\infty),\\&w_t=D\Delta w-uF_{1}(w)-vF_{2}(w)+f(w),&(x,t)\in \Omega\times (0,\infty), \end{split} \right. \end{eqnarray*} under homogeneous Neumann boundary conditions in a smooth bounded domain $\Omega\subset \mathbb{R}^{2}$, with the nonnegative initial data $\left( {u_{0}, v_{0}, w_{0}} \right) \in (W^{1,p}(\Omega))^{3}$ with $p>2$, where the parameters $D,\gamma_{1},\gamma_{2},\beta_{1},\beta_{2}>0$, $d_{1}(w)$ and $d_{2}(w)$ are density-dependent diffusion functions, $F_{1}(w)$ and $F_{2}(w)$ are commonly called the functional response functions accounting for the intake rate of predators as the functions of prey density, $h_{1}(u)$ and $h_{2}(v)$ represent the mortality rates of predators, and $f(w)$ stands for the growth function of the prey. First, we rigorously prove the global boundedness of classical solutions for the above general model provided that the parameters satisfy some suitable conditions by means of $L^{p}$-estimate techniques. Moreover, in some particular cases, we establish the asymptotic stabilization and precise convergence rates of globally bounded solutions under different conditions on the parameters by constructing some appropriate Lyapunov functionals. Our results not only extend the previous ones, but also involve some new conclusions.

Predator-prey systems with defense switching and density-suppressed dispersal strategy

In this paper, we consider the following predator-prey system with defense switching mechanism and density-suppressed dispersal strategy $ \begin{equation*} \begin{cases} u_t = \Delta(d_1(w)u)+\frac{\beta_1 uvw}{u+v}-\alpha_1 u, & x\in \Omega, \; \; t>0, \\ v_t = \Delta(d_2(w)v)+\frac{\beta_2 uvw}{u+v}-\alpha_2 v, & x\in \Omega, \; \; t>0, \\ w_t = \Delta w-\frac{\beta_3 uvw}{u+v}+\sigma w\left(1-\frac{w}{K}\right), & x\in \Omega, \; \; t>0, \\ \frac{\partial u}{\partial \nu} = \frac{\partial v}{\partial \nu} = \frac{\partial w}{\partial \nu} = 0, & x\in\partial\Omega, \; \; t>0, \\ (u, v, w)(x, 0) = (u_0, v_0, w_0)(x), & x\in\Omega, \ \end{cases} \end{equation*} $ where $ \Omega\subset{\mathbb{R}}^2 $ is a bounded domain with smooth boundary. Based on the method of energy estimates and Moser iteration, we establish the existence of global classical solutions with uniform-in-time boundedness. We further prove the global stability of co-existence equilibrium by using the Lyapunov functionals and LaSalle's invariant principle. Finally we conduct linear stability analysis and perform numerical simulations to illustrate that the density-suppressed dispersal may trigger the pattern formation.

4-bit adhesion logic enables universal multicellular interface patterning

Multicellular systems, from bacterial biofilms to human organs, form interfaces (or boundaries) between different cell collectives to spatially organize versatile functions^1,2. The evolution of sufficiently descriptive genetic toolkits probably triggered the explosion of complex multicellular life and patterning^3,4. Synthetic biology aims to engineer multicellular systems for practical applications and to serve as a build-to-understand methodology for natural systems^5–8. However, our ability to engineer multicellular interface patterns^2,9 is still very limited, as synthetic cell–cell adhesion toolkits and suitable patterning algorithms are underdeveloped^5,7,10–13. Here we introduce a synthetic cell–cell adhesin logic with swarming bacteria and establish the precise engineering, predictive modelling and algorithmic programming of multicellular interface patterns. We demonstrate interface generation through a swarming adhesion mechanism, quantitative control over interface geometry and adhesion-mediated analogues of developmental organizers and morphogen fields. Using tiling and four-colour-mapping concepts, we identify algorithms for creating universal target patterns. This synthetic 4-bit adhesion logic advances practical applications such as human-readable molecular diagnostics, spatial fluid control on biological surfaces and programmable self-growing materials^5–8,14. Notably, a minimal set of just four adhesins represents 4 bits of information that suffice to program universal tessellation patterns, implying a low critical threshold for the evolution and engineering of complex multicellular systems^3,5.

A synthetic cell-cell adhesion logic using swarming E. coli with 4 bits of information is introduced, enabling the programming of interfaces that combine to form universal tessellation patterns over a large scale.

Engineered Living Hydrogels

Living biological systems, ranging from single cells to whole organisms, can sense, process information, and actuate in response to changing environmental conditions. Inspired by living biological systems, engineered living cells and nonliving matrices are brought together, which gives rise to the technology of engineered living materials. By designing the functionalities of living cells and the structures of nonliving matrices, engineered living materials can be created to detect variability in the surrounding environment and to adjust their functions accordingly, thereby enabling applications in health monitoring, disease treatment, and environmental remediation. Hydrogels, a class of soft, wet, and biocompatible materials, have been widely used as matrices for engineered living cells, leading to the nascent field of engineered living hydrogels. Here, the interactions between hydrogel matrices and engineered living cells are described, focusing on how hydrogels influence cell behaviors and how cells affect hydrogel properties. The interactions between engineered living hydrogels and their environments, and how these interactions enable versatile applications, are also discussed. Finally, current challenges facing the field of engineered living hydrogels for their applications in clinical and environmental settings are highlighted.

Spatial patterns in ecological systems: from microbial colonies to landscapes

Self-organized spatial patterns are ubiquitous in ecological systems and allow populations to adopt non-trivial spatial distributions starting from disordered configurations. These patterns form due to diverse nonlinear interactions among organisms and between organisms and their environment, and lead to the emergence of new (eco)system-level properties unique to self-organized systems. Such pattern consequences include higher resilience and resistance to environmental changes, abrupt ecosystem collapse, hysteresis loops, and reversal of competitive exclusion. Here, we review ecological systems exhibiting self-organized patterns. We establish two broad pattern categories depending on whether the self-organizing process is primarily driven by nonlinear density-dependent demographic rates or by nonlinear density-dependent movement. Using this organization, we examine a wide range of observational scales, from microbial colonies to whole ecosystems, and discuss the mechanisms hypothesized to underlie observed patterns and their system-level consequences. For each example, we review both the empirical evidence and the existing theoretical frameworks developed to identify the causes and consequences of patterning. Finally, we trace qualitative similarities across systems and propose possible ways of developing a more quantitative understanding of how self-organization operates across systems and observational scales in ecology.

Analytical approach to chiral active systems: suppressed phase separation of interacting Brownian circle swimmers

We consider chirality in active systems by exemplarily studying the phase behavior of planar systems of interacting Brownian circle swimmers with a spherical shape. For this purpose, we derive a predictive field theory that is able to describe the collective dynamics of circle swimmers. The theory yields a mapping between circle swimmers and noncircling active Brownian particles and predicts that the angular propulsion of the particles leads to a suppression of their motility-induced phase separation, being in line with recent simulation results. In addition, the theory provides analytical expressions for the spinodal corresponding to the onset of motility-induced phase separation and the associated critical point as well as for their dependence on the angular propulsion of the circle swimmers. We confirm our findings by Brownian dynamics simulations. The agreement between results from theory and simulations is found to be good.

Dynamics of Bacteria Scanning a Porous Environment

It has recently been reported that bacteria, such as Escherichia coli Bhattacharjee and Datta, Nat. Commun. 10, 2075 (2019).NCAOBW2041-172310.1038/s41467-019-10115-1 and Pseudomonas putida Alirezaeizanjani et al., Sci. Adv. 6, eaaz6153 (2020).SACDAF2375-254810.1126/sciadv.aaz6153, perform distinct modes of motion when placed in porous media as compared to dilute regions or free space. This has led us to suggest an efficient strategy for active particles in a disordered environment: reorientations are suppressed in locally dilute regions and intensified in locally dense ones. Thereby the local geometry determines the optimal path of the active agent and substantially accelerates the dynamics for up to 2 orders of magnitude. We observe a nonmonotonic behavior of the diffusion coefficient in dependence on the tumbling rate and identify a localization transition, either by increasing the density of obstacles or by decreasing the reorientation rate.

Principles for the design of multicellular engineered living systems

Remarkable progress in bioengineering over the past two decades has enabled the formulation of fundamental design principles for a variety of medical and non-medical applications. These advancements have laid the foundation for building multicellular engineered living systems (M-CELS) from biological parts, forming functional modules integrated into living machines. These cognizant design principles for living systems encompass novel genetic circuit manipulation, self-assembly, cell-cell/matrix communication, and artificial tissues/organs enabled through systems biology, bioinformatics, computational biology, genetic engineering, and microfluidics. Here, we introduce design principles and a blueprint for forward production of robust and standardized M-CELS, which may undergo variable reiterations through the classic design-build-test-debug cycle. This Review provides practical and theoretical frameworks to forward-design, control, and optimize novel M-CELS. Potential applications include biopharmaceuticals, bioreactor factories, biofuels, environmental bioremediation, cellular computing, biohybrid digital technology, and experimental investigations into mechanisms of multicellular organisms normally hidden inside the "black box" of living cells.

Interactions in active colloids

The past two decades have seen a remarkable progress in the development of synthetic colloidal agents which are capable of creating directed motion in an unbiased environment at the microscale. These self-propelling particles are often praised for their enormous potential to self-organize into dynamic nonequilibrium structures such as living clusters, synchronized super-rotor structures or self-propelling molecules featuring a complexity which is rarely found outside of the living world. However, the precise mechanisms underlying the formation and dynamics of many of these structures are still barely understood, which is likely to hinge on the gaps in our understanding of how active colloids interact. In particular, besides showing comparatively short-ranged interactions which are well known from passive colloids (Van der Waals, electrostatic etc), active colloids show novel hydrodynamic interactions as well as phoretic and substrate-mediated 'osmotic' cross-interactions which hinge on the action of the phoretic field gradients which are induced by the colloids on other colloids in the system. The present article discusses the complexity and the intriguing properties of these interactions which in general are long-ranged, non-instantaneous, non-pairwise and non-reciprocal and which may serve as key ingredients for the design of future nonequilibrium colloidal materials. Besides providing a brief overview on the state of the art of our understanding of these interactions a key aim of this review is to emphasize open key questions and corresponding open challenges.

A Predictive Reaction-diffusion Based Model of E.coli Colony Growth Control

Bacterial colony formations exhibit diverse morphologies and dynamics. A mechanistic understanding of this process has broad implications to ecology and medicine. However, many control factors and their impacts on colony formation remain underexplored. Here we propose a reaction-diffusion based dynamic model to quantitatively describe cell division and colony expansion, where control factors of colony spreading take the form of nonlinear density-dependent function and the intercellular impacts take the form of density-dependent hill function. We validate the model using experimental E. coli colony growth data and our results show that the model is capable of predicting the whole colony expansion process in both time and space under different conditions. Furthermore, the nonlinear control factors can predict colony morphology at both center and edge of the colony.

CRISPR-Based Genetic Switches and Other Complex Circuits: Research and Application

CRISPR-based enzymes have offered a unique capability to the design of genetic switches, with advantages in designability, modularity and orthogonality. CRISPR-based genetic switches operate on multiple levels of life, including transcription and translation. In both prokaryotic and eukaryotic cells, deactivated CRISPR endonuclease and endoribonuclease have served in genetic switches for activating or repressing gene expression, at both transcriptional and translational levels. With these genetic switches, more complex circuits have been assembled to achieve sophisticated functions including inducible switches, non-linear response and logical biocomputation. As more CRISPR enzymes continue to be excavated, CRISPR-based genetic switches will be used in a much wider range of applications.

Spatial modulation of individual behaviors enables an ordered structure of diverse phenotypes during bacterial group migration

Coordination of diverse individuals often requires sophisticated communications and high-order computational abilities. Microbial populations can exhibit diverse individualistic behaviors, and yet can engage in collective migratory patterns with a spatially sorted arrangement of phenotypes. However, it is unclear how such spatially sorted patterns emerge from diverse individuals without complex computational abilities. Here, by investigating the single-cell trajectories during group migration, we discovered that, despite the constant migrating speed of a group, the drift velocities of individual bacteria decrease from the back to the front. With a Langevin-type modeling framework, we showed that this decreasing profile of drift velocities implies the spatial modulation of individual run-and-tumble random motions, and enables the bacterial population to migrate as a pushed wave front. Theoretical analysis and stochastic simulations further predicted that the pushed wave front can help a diverse population to stay in a tight group, while diverse individuals perform the same type of mean reverting processes around centers orderly aligned by their chemotactic abilities. This mechanism about the emergence of orderly collective migration from diverse individuals is experimentally demonstrated by titration of bacterial chemoreceptor abundance. These results reveal a simple computational principle for emergent ordered behaviors from heterogeneous individuals.

Organisms living in large groups often have to move together in order to navigate, forage for food, and increase their roaming range. Such groups are often made up of distinct individuals that must integrate their different behaviors in order to migrate in the same direction at a similar pace. For instance, for the bacteria Escherichia coli to travel as a condensed group, they must coordinate their response to a set of chemical signals called chemoattractants that tell them where to go.

The chemoattractants surrounding the bacteria are unequally distributed so that there is more of them at the front than the back of the group. During migration, each bacterium moves towards this concentration gradient in a distinct way, spontaneously rotating its direction in a ‘run-and-tumble’ motion that guides it towards areas where there are high levels of these chemical signals. In addition to this variability, how well individual bacteria are able to swim up the gradient also differs within the population. Bacteria that are better at sensing the chemoattractant gradient are placed at the front of the group, while those that are worst are shifted towards the back. This spatial arrangement is thought to help the bacteria migrate together. But how E. coli organize themselves in to this pattern is unclear, especially as they cannot communicate directly with one another and display such diverse, randomized behaviors.

To help answer this question, Bai, He et al. discovered a general principle that describes how single bacterial cells move within a group. The results showed that E. coli alter their run-and-tumble motion depending on where they reside within the population: individuals at the rear drift faster so they can catch up with the group, while those leading the group drift slower to draw themselves back. This ‘reversion behavior’ allows the migrating bacteria to travel at a constant speed around a mean position relative to the group.

A cell’s drifting speed is determined by how well it moves towards the chemoattractant and its response to the concentration gradient. As a result, the mean position around which the bacterium accelerates or deaccelerates will vary depending on how sensitive it is to the chemoattractant gradient. The E. coli therefore spatially arrange themselves so that the more sensitive bacteria are located at the front of the group where the gradient is shallower; and cells that are less sensitive are located towards the back where the gradient is steeper.

These findings suggest a general principle for how bacteria form ordered patterns whilst migrating as a collective group. This behavior could also apply to other populations of distinct individuals, such as ants following a trail or flocks of birds migrating in between seasons.

Effects of internal dynamics on chemotactic aggregation of bacteria

The effects of internal adaptation dynamics on the self-organized aggregation of chemotactic bacteria are investigated by Monte Carlo (MC) simulations based on a two-stream kinetic transport equation coupled with a reaction-diffusion equation of the chemoattractant that bacteria produce. A remarkable finding is a nonmonotonic behavior of the peak aggregation density with respect to the adaptation time; more specifically, aggregation is the most enhanced when the adaptation time is comparable to or moderately larger than the mean run time of bacteria. Another curious observation is the formation of a trapezoidal aggregation profile occurring at a very large adaptation time, where the biased motion of individual cells is rather hindered at the plateau regimes due to the boundedness of the tumbling frequency modulation. Asymptotic analysis of the kinetic transport system is also carried out, and a novel asymptotic equation is obtained at the large adaptation-time regime while the Keller-Segel type equations are obtained when the adaptation time is moderate. Numerical comparison of the asymptotic equations with MC results clarifies that trapezoidal aggregation is well described by the novel asymptotic equation, and the nonmonotonic behavior of the peak aggregation density is interpreted as the transient of the asymptotic solutions between different adaptation time regimes.

The spatial organization of microbial communities during range expansion

Microbes in nature often live in dense and diverse communities exhibiting a variety of spatial structures. Microbial range expansion is a universal ecological process that enables populations to form spatial patterns. It can be driven by both passive and active processes, for example, mechanical forces from cell growth and bacterial motility. In this review, we provide a taste of recent creative and sophisticated efforts being made to address basic questions in spatial ecology and pattern formation during range expansion. We especially highlight the role of motility to shape community structures, and discuss the research challenges and future directions.

Directed Evolution: Methodologies and Applications

Directed evolution aims to expedite the natural evolution process of biological molecules and systems in a test tube through iterative rounds of gene diversifications and library screening/selection. It has become one of the most powerful and widespread tools for engineering improved or novel functions in proteins, metabolic pathways, and even whole genomes. This review describes the commonly used gene diversification strategies, screening/selection methods, and recently developed continuous evolution strategies for directed evolution. Moreover, we highlight some representative applications of directed evolution in engineering nucleic acids, proteins, pathways, genetic circuits, viruses, and whole cells. Finally, we discuss the challenges and future perspectives in directed evolution.

Engineered probiotics for local tumor delivery of checkpoint blockade nanobodies

Checkpoint inhibitors have revolutionized cancer therapy but only work in a subset of patients and can lead to a multitude of toxicities, suggesting the need for more targeted delivery systems. Because of their preferential colonization of tumors, microbes are a natural platform for the local delivery of cancer therapeutics. Here, we engineer a probiotic bacteria system for the controlled production and intratumoral release of nanobodies targeting programmed cell death-ligand 1 (PD-L1) and cytotoxic T lymphocyte-associated protein-4 (CTLA-4) using a stabilized lysing release mechanism. We used computational modeling coupled with experimental validation of lysis circuit dynamics to determine the optimal genetic circuit parameters for maximal therapeutic efficacy. A single injection of this engineered system demonstrated an enhanced therapeutic response compared to analogous clinically relevant antibodies, resulting in tumor regression in syngeneic mouse models. Supporting the potentiation of a systemic immune response, we observed a relative increase in activated T cells, an abscopal effect, and corresponding increases in systemic T cell memory populations in mice treated with probiotically delivered checkpoint inhibitors. Last, we leveraged the modularity of our platform to achieve enhanced therapeutic efficacy in a poorly immunogenic syngeneic mouse model through effective combinations with a probiotically produced cytokine, granulocyte-macrophage colony-stimulating factor (GM-CSF). Together, these results demonstrate that our engineered probiotic system bridges synthetic biology and immunology to improve upon checkpoint blockade delivery.

Short-range quorum sensing controls horizontal gene transfer at micron scale in bacterial communities

In bacterial communities, cells often communicate by the release and detection of small diffusible molecules, a process termed quorum-sensing. Signal molecules are thought to broadly diffuse in space; however, they often regulate traits such as conjugative transfer that strictly depend on the local community composition. This raises the question how nearby cells within the community can be detected. Here, we compare the range of communication of different quorum-sensing systems. While some systems support long-range communication, we show that others support a form of highly localized communication. In these systems, signal molecules propagate no more than a few microns away from signaling cells, due to the irreversible uptake of the signal molecules from the environment. This enables cells to accurately detect micron scale changes in the community composition. Several mobile genetic elements, including conjugative elements and phages, employ short-range communication to assess the fraction of susceptible host cells in their vicinity and adaptively trigger horizontal gene transfer in response. Our results underscore the complex spatial biology of bacteria, which can communicate and interact at widely different spatial scales.

Collective colony growth is optimized by branching pattern formation in Pseudomonas aeruginosa

Branching pattern formation is common in many microbes. Extensive studies have focused on addressing how such patterns emerge from local cell-cell and cell-environment interactions. However, little is known about whether and to what extent these patterns play a physiological role. Here, we consider the colonization of bacteria as an optimization problem to find the colony patterns that maximize colony growth efficiency under different environmental conditions. We demonstrate that Pseudomonas aeruginosa colonies develop branching patterns with characteristics comparable to the prediction of modeling; for example, colonies form thin branches in a nutrient-poor environment. Hence, the formation of branching patterns represents an optimal strategy for the growth of Pseudomonas aeruginosa colonies. The quantitative relationship between colony patterns and growth conditions enables us to develop a coarse-grained model to predict diverse colony patterns under more complex conditions, which we validated experimentally. Our results offer new insights into branching pattern formation as a problem-solving social behavior in microbes and enable fast and accurate predictions of complex spatial patterns in branching colonies.

Reversible thermal regulation for bifunctional dynamic control of gene expression in Escherichia coli

Genetically programmed circuits allowing bifunctional dynamic regulation of enzyme expression have far-reaching significances for various bio-manufactural purposes. However, building a bio-switch with a post log-phase response and reversibility during scale-up bioprocesses is still a challenge in metabolic engineering due to the lack of robustness. Here, we report a robust thermosensitive bio-switch that enables stringent bidirectional control of gene expression over time and levels in living cells. Based on the bio-switch, we obtain tree ring-like colonies with spatially distributed patterns and transformer cells shifting among spherical-, rod- and fiber-shapes of the engineered Escherichia coli. Moreover, fed-batch fermentations of recombinant E. coli are conducted to obtain ordered assembly of tailor-made biopolymers polyhydroxyalkanoates including diblock- and random-copolymer, composed of 3-hydroxybutyrate and 4-hydroxybutyrate with controllable monomer molar fraction. This study demonstrates the possibility of well-organized, chemosynthesis-like block polymerization on a molecular scale by reprogrammed microbes, exemplifying the versatility of thermo-response control for various practical uses.

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.

Transfer of printed electronic structures using graphene oxide and gelatin enables reversible and biocompatible interface with living cells

We present a low-cost, easy-to-implement platform for printing materials and interfacing them with eukaryotic cells. We show that thermal or chemical reduction of a graphene oxide thin film allows water-assisted delamination of the film from glass or plastic. The chemical and physical properties and permeability of the resulting film are dependent on the method of reduction and deposition of the graphene oxide, with thermal reduction removing more oxidized carbon functionality than chemical reduction. We also developed a method to attach the films onto cell surfaces using a thin layer of gelatin as an adhesive. In general, the films are highly impermeable to nutrients and we observed a significant amount of cell death when gelatin was not used; gelatin enables diffusion of nutrients for sustained cell viability. The combination of nanoscale membranes with a low melting point biopolymer allows us to reversibly interface cells with cargo transferred by graphene oxide while maintaining cell viability. To demonstrate delivery of electronic structures, we modified a commercial off-the-shelf printer to print a silver-based ink directly onto the reduced graphene oxide films which we then transferred to the surface of the cells.

Synthetic protein-binding DNA sponge as a tool to tune gene expression and mitigate protein toxicity

Versatile tools for gene expression regulation are vital for engineering gene networks of increasing scales and complexity with bespoke responses. Here, we investigate and repurpose a ubiquitous, indirect gene regulation mechanism from nature, which uses decoy protein-binding DNA sites, named DNA sponge, to modulate target gene expression in Escherichia coli. We show that synthetic DNA sponges can be designed to reshape the response profiles of gene circuits, lending multifaceted tuning capacities including reducing basal leakage by >20-fold, increasing system output amplitude by >130-fold and dynamic range by >70-fold, and mitigating host growth inhibition by >20%. Further, multi-layer DNA sponges for decoying multiple regulatory proteins provide an additive tuning effect on the responses of layered circuits compared to single-layer sponges. Our work shows synthetic DNA sponges offer a simple yet generalizable route to systematically engineer the performance of synthetic gene circuits, expanding the current toolkit for gene regulation with broad potential applications.

Decoy binding sites are natural regulators of gene expression. Here the authors design synthetic DNA sponges that fine tune the performance of synthetic gene circuits in a simple yet systematic manner, expanding the synthetic biology toolkit for gene regulation.