Bacterial variability in the mammalian gut captured by a single-cell synthetic oscillator

Dextran sodium sulfate-induced colitis alters the proportion and composition of replicating gut bacteria

The bacteria living in the human gut are essential for host health. Though the composition and metabolism of these bacteria are well described in both healthy hosts and those with intestinal disease, less is known about the metabolic activity of the gut bacteria prior to, and during, disease development-especially regarding gut bacterial replication. Here, we use a recently developed single-cell technique alongside existing metagenomics-based tools to identify, track, and quantify replicating gut bacteria both ex vivo and in situ in the dextran sodium sulfate (DSS) mouse model of colitis. We show that the proportion of replicating gut bacteria decreases when mice have the highest levels of inflammation and returns to baseline levels as mice begin recovering. In addition, we report significant alterations in the composition of the replicating gut bacterial community ex vivo during colitis development. On the taxa level, we observe significant changes in the abundance of taxa such as the mucus-degrading Akkermansia and the poorly described Erysipelatoclostridium genus. We further demonstrate that many taxa exhibit variable replication rates in situ during colitis, including Akkermansia muciniphila. Lastly, we show that colitis development is positively correlated with increases in the presence and abundance of bacteria in situ which are predicted to be fast replicators. This could suggest that taxa with the potential to replicate quickly may have an advantage during intestinal inflammation. These data support the need for additional research using activity-based approaches to further characterize the gut bacterial response to intestinal inflammation and its consequences for both the host and the gut microbial community.IMPORTANCEIt is well known that the bacteria living inside the gut are important for human health. Indeed, the type of bacteria that are present and their metabolism are different in healthy people versus those with intestinal disease. However, less is known about how these gut bacteria are replicating, especially as someone begins to develop intestinal disease. This is particularly important as it is thought that metabolically active gut bacteria may be more relevant to health. Here, we begin to address this gap using several complementary approaches to characterize the replicating gut bacteria in a mouse model of intestinal inflammation. We reveal which gut bacteria are replicating, and how quickly, as mice develop and recover from inflammation. This work can serve as a model for future research to identify how actively growing gut bacteria may be impacting health, or why these particular bacteria tend to thrive during intestinal inflammation.

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

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

Light-driven synchronization of optogenetic clocks

Synthetic genetic oscillators can serve as internal clocks within engineered cells to program periodic expression. However, cell-to-cell variability introduces a dispersion in the characteristics of these clocks that drives the population to complete desynchronization. Here, we introduce the optorepressilator, an optically controllable genetic clock that combines the repressilator, a three-node synthetic network in E. coli, with an optogenetic module enabling to reset, delay, or advance its phase using optical inputs. We demonstrate that a population of optorepressilators can be synchronized by transient green light exposure or entrained to oscillate indefinitely by a train of short pulses, through a mechanism reminiscent of natural circadian clocks. Furthermore, we investigate the system's response to detuned external stimuli observing multiple regimes of global synchronization. Integrating experiments and mathematical modeling, we show that the entrainment mechanism is robust and can be understood quantitatively from single cell to population level.

Pattern Formation and Bistability in a Synthetic Intercellular Genetic Toggle

Differentiation within multicellular organisms is a complex process that helps to establish spatial patterning and tissue formation within the body. Often, the differentiation of cells is governed by morphogens and intercellular signaling molecules that guide the fate of each cell, frequently using toggle-like regulatory components. Synthetic biologists have long sought to recapitulate patterned differentiation with engineered cellular communities, and various methods for differentiating bacteria have been invented. Here, we couple a synthetic corepressive toggle switch with intercellular signaling pathways to create a "quorum-sensing toggle". We show that this circuit not only exhibits population-wide bistability in a well-mixed liquid environment but also generates patterns of differentiation in colonies grown on agar containing an externally supplied morphogen. If coupled to other metabolic processes, circuits such as the one described here would allow for the engineering of spatially patterned, differentiated bacteria for use in biomaterials and bioelectronics.

From resonance to chaos by modulating spatiotemporal patterns through a synthetic optogenetic oscillator

Oscillations are a recurrent phenomenon in biological systems across scales, but deciphering their fundamental principles is very challenging. Here, we tackle this challenge by redesigning the wellcharacterised synthetic oscillator known as "repressilator" in Escherichia coli and controlling it using optogenetics, creating the "optoscillator". Bacterial colonies manifest oscillations as spatial ring patterns. When we apply periodic light pulses, the optoscillator behaves as a forced oscillator and we systematically investigate the properties of the rings under various light conditions. Combining experiments with mathematical modeling, we demonstrate that this simple oscillatory circuit can generate complex dynamics that are transformed into distinct spatial patterns. We report the observation of synchronisation, resonance, subharmonic resonance and period doubling. Furthermore, we present evidence of a chaotic regime. This work highlights the intricate spatiotemporal patterns accessible by synthetic oscillators and underscores the potential of our approach in revealing fundamental principles of biological oscillations.

The gut microbiota and its biogeography

Biogeography is the study of species distribution and diversity within an ecosystem and is at the core of how we understand ecosystem dynamics and interactions at the macroscale. In gut microbial communities, a historical reliance on bulk sequencing to probe community composition and dynamics has overlooked critical processes whereby microscale interactions affect systems-level microbiota function and the relationship with the host. In recent years, higher-resolution sequencing and novel single-cell level data have uncovered an incredible heterogeneity in microbial composition and have enabled a more nuanced spatial understanding of the gut microbiota. In an era when spatial transcriptomics and single-cell imaging and analysis have become key tools in mammalian cell and tissue biology, many of these techniques are now being applied to the microbiota. This fresh approach to intestinal biogeography has given important insights that span temporal and spatial scales, from the discovery of mucus encapsulation of the microbiota to the quantification of bacterial species throughout the gut. In this Review, we highlight emerging knowledge surrounding gut biogeography enabled by the observation and quantification of heterogeneity across multiple scales.

From microbiome composition to functional engineering, one step at a time

SUMMARYCommunities of microorganisms (microbiota) are present in all habitats on Earth and are relevant for agriculture, health, and climate. Deciphering the mechanisms that determine microbiota dynamics and functioning within the context of their respective environments or hosts (the microbiomes) is crucially important. However, the sheer taxonomic, metabolic, functional, and spatial complexity of most microbiomes poses substantial challenges to advancing our knowledge of these mechanisms. While nucleic acid sequencing technologies can chart microbiota composition with high precision, we mostly lack information about the functional roles and interactions of each strain present in a given microbiome. This limits our ability to predict microbiome function in natural habitats and, in the case of dysfunction or dysbiosis, to redirect microbiomes onto stable paths. Here, we will discuss a systematic approach (dubbed the N+1/N-1 concept) to enable step-by-step dissection of microbiome assembly and functioning, as well as intervention procedures to introduce or eliminate one particular microbial strain at a time. The N+1/N-1 concept is informed by natural invasion events and selects culturable, genetically accessible microbes with well-annotated genomes to chart their proliferation or decline within defined synthetic and/or complex natural microbiota. This approach enables harnessing classical microbiological and diversity approaches, as well as omics tools and mathematical modeling to decipher the mechanisms underlying N+1/N-1 microbiota outcomes. Application of this concept further provides stepping stones and benchmarks for microbiome structure and function analyses and more complex microbiome intervention strategies.

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.

A synthetic population-level oscillator in non-microfluidic environments

Synthetic oscillators have become a research hotspot because of their complexity and importance. The construction and stable operation of oscillators in large-scale environments are important and challenging. Here, we introduce a synthetic population-level oscillator in Escherichia coli that operates stably during continuous culture in non-microfluidic environments without the addition of inducers or frequent dilution. Specifically, quorum-sensing components and protease regulating elements are employed, which form delayed negative feedback to trigger oscillation and accomplish the reset of signals through transcriptional and post-translational regulation. We test the circuit in devices with 1 mL, 50 mL, 400 mL of medium, and demonstrate that the circuit could maintain stable population-level oscillations. Finally, we explore potential applications of the circuit in regulating cellular morphology and metabolism. Our work contributes to the design and testing of synthetic biological clocks that function in large populations.

Actively replicating gut bacteria identified by 5-ethynyl-2'-deoxyuridine (EdU) click chemistry and cell sorting

The composition of the intestinal bacterial community is well described, but recent research suggests that the metabolism of these bacteria plays a larger role in health than which species are present. One fundamental aspect of gut bacterial metabolism that remains understudied is bacterial replication. Indeed, there exist few techniques which can identify actively replicating gut bacteria. In this study, we aimed to address this gap by adapting 5-ethynyl-2'-deoxyuridine (EdU) click chemistry (EdU-click), a metabolic labeling method, coupled with fluorescence-activated cell sorting and sequencing (FACS-Seq) to characterize replicating gut bacteria. We first used EdU-click with human gut bacterial isolates and show that many of them are amenable to this technique. We then optimized EdU-click and FACS-Seq for murine fecal bacteria and reveal that Prevotella UCG-001 and Ileibacterium are enriched in the replicating fraction. Finally, we labeled the actively replicating murine gut bacteria during exposure to cell wall-specific antibiotics in vitro. We show that regardless of the antibiotic used, the actively replicating bacteria largely consist of Ileibacterium, suggesting the resistance of this taxon to perturbations. Overall, we demonstrate how combining EdU-click and FACSeq can identify the actively replicating gut bacteria and their link with the composition of the whole community in both homeostatic and perturbed conditions. This technique will be instrumental in elucidating in situ bacterial replication dynamics in a variety of other ecological states, including colonization and species invasion, as well as for investigating the relationship between the replication and abundance of bacteria in complex communities.

Computational characterization of recombinase circuits for periodic behaviors

Recombinases are site-specific proteins found in nature that are capable of rearranging DNA. This function has made them promising gene editing tools in synthetic biology, as well as key elements in complex artificial gene circuits implementing Boolean logic. However, since DNA rearrangement is irreversible, it is still unclear how to use recombinases to build dynamic circuits like oscillators. In addition, this goal is challenging because a few molecules of recombinase are enough for promoter inversion, generating inherent stochasticity at low copy number. Here, we propose six different circuit designs for recombinase-based oscillators operating at a single copy number. We model them in a stochastic setting, leveraging the Gillespie algorithm for extensive simulations, and show that they can yield coherent periodic behaviors. Our results support the experimental realization of recombinase-based oscillators and, more generally, the use of recombinases to generate dynamic behaviors in synthetic biology.

The context matrix: Navigating biological complexity for advanced biodesign

Synthetic biology offers many solutions in healthcare, production, sensing and agriculture. However, the ability to rationally engineer synthetic biosystems with predictable and robust functionality remains a challenge. A major reason is the complex interplay between the synthetic genetic construct, its host, and the environment. Each of these contexts contains a number of input factors which together can create unpredictable behaviours in the engineered biosystem. It has become apparent that for the accurate assessment of these contextual effects a more holistic approach to design and characterisation is required. In this perspective article, we present the context matrix, a conceptual framework to categorise and explore these contexts and their net effect on the designed synthetic biosystem. We propose the use and community-development of the context matrix as an aid for experimental design that simplifies navigation through the complex design space in synthetic biology.

Bacterial degrons in synthetic circuits

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

Emergent evolutionary forces in spatial models of luminal growth and their application to the human gut microbiota

The genetic composition of the gut microbiota is constantly reshaped by ecological and evolutionary forces. These strain-level dynamics are challenging to understand because they depend on complex spatial growth processes that take place within a host. Here we introduce a population genetic framework to predict how stochastic evolutionary forces emerge from simple models of microbial growth in spatially extended environments like the intestinal lumen. Our framework shows how fluid flow and longitudinal variation in growth rate combine to shape the frequencies of genetic variants in simulated fecal samples, yielding analytical expressions for the effective generation times, selection coefficients, and rates of genetic drift. We find that over longer timescales, the emergent evolutionary dynamics can often be captured by well-mixed models that lack explicit spatial structure, even when there is substantial spatial variation in species-level composition. By applying these results to the human colon, we find that continuous fluid flow and simple forms of wall growth alone are unlikely to create sufficient bottlenecks to allow large fluctuations in mutant frequencies within a host. We also find that the effective generation times may be significantly shorter than expected from traditional average growth rate estimates. Our results provide a starting point for quantifying genetic turnover in spatially extended settings like the gut microbiota and may be relevant for other microbial ecosystems where unidirectional fluid flow plays an important role.

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

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

Complex dynamics in a synchronized cell-free genetic clock

Complex dynamics such as period doubling and chaos occur in a wide variety of non-linear dynamical systems. In the context of biological circadian clocks, such phenomena have been previously found in computational models, but their experimental study in biological systems has been challenging. Here, we present experimental evidence of period doubling in a forced cell-free genetic oscillator operated in a microfluidic reactor, where the system is periodically perturbed by modulating the concentration of one of the oscillator components. When the external driving matches the intrinsic period, we experimentally find period doubling and quadrupling in the oscillator dynamics. Our results closely match the predictions of a theoretical model, which also suggests conditions under which our system would display chaotic dynamics. We show that detuning of the external and intrinsic period leads to more stable entrainment, suggesting a simple design principle for synchronized synthetic and natural genetic clocks.

Theranostic cells: emerging clinical applications of synthetic biology

Synthetic biology seeks to redesign biological systems to perform novel functions in a predictable manner. Recent advances in bacterial and mammalian cell engineering include the development of cells that function in biological samples or within the body as minimally invasive diagnostics or theranostics for the real-time regulation of complex diseased states. Ex vivo and in vivo cell-based biosensors and therapeutics have been developed to target a wide range of diseases including cancer, microbiome dysbiosis and autoimmune and metabolic diseases. While probiotic therapies have advanced to clinical trials, chimeric antigen receptor (CAR) T cell therapies have received regulatory approval, exemplifying the clinical potential of cellular therapies. This Review discusses preclinical and clinical applications of bacterial and mammalian sensing and drug delivery platforms as well as the underlying biological designs that could enable new classes of cell diagnostics and therapeutics. Additionally, we describe challenges that must be overcome for more rapid and safer clinical use of engineered systems.

Single-Cell Technologies to Study Phenotypic Heterogeneity and Bacterial Persisters

Antibiotic persistence is a phenomenon in which rare cells of a clonal bacterial population can survive antibiotic doses that kill their kin, even though the entire population is genetically susceptible. With antibiotic treatment failure on the rise, there is growing interest in understanding the molecular mechanisms underlying bacterial phenotypic heterogeneity and antibiotic persistence. However, elucidating these rare cell states can be technically challenging. The advent of single-cell techniques has enabled us to observe and quantitatively investigate individual cells in complex, phenotypically heterogeneous populations. In this review, we will discuss current technologies for studying persister phenotypes, including fluorescent tags and biosensors used to elucidate cellular processes; advances in flow cytometry, mass spectrometry, Raman spectroscopy, and microfluidics that contribute high-throughput and high-content information; and next-generation sequencing for powerful insights into genetic and transcriptomic programs. We will further discuss existing knowledge gaps, cutting-edge technologies that can address them, and how advances in single-cell microbiology can potentially improve infectious disease treatment outcomes.

Rational Design and Characterization of Nitric Oxide Biosensors in E. coli Nissle 1917 and Mini SimCells

Nitric oxide (NO) is an important disease biomarker found in many chronic inflammatory diseases and cancers. A well-characterized nitric sensing system is useful to aid the rapid development of bacteria therapy and synthetic biology. In this work, we engineered a set of NO-responsive biosensors based on the P_norV promoter and its NorR regulator in the norRVW operon; the circuits were characterized and optimized in probiotic Escherichia coli Nissle 1917 and mini SimCells (minicells containing designed gene circuits for specific tasks). Interestingly, the expression level of NorR displayed an inverse correlation to the P_norV promoter activation, as a strong expression of the NorR regulator resulted in a low amplitude of NO-inducible gene expression. This could be explained by a competitive binding mechanism where the activated and inactivated NorR competitively bind to the same site on the P_norV promoter. To overcome such issues, the NO induction performance was further improved by making a positive feedback loop that fine-tuned the level of NorR. In addition, by examining two integration host factor (IHF) binding sites of the P_norV promoter, we demonstrated that the deletion of the second IHF site increased the maximum signal output by 25% (500 μM DETA/NO) with no notable increase in the basal expression level. The optimized NO-sensing gene circuit in anucleate mini SimCells exhibited increased robustness against external fluctuation in medium composition. The NO detection limit of the optimized gene circuit pPnorVβ was also improved from 25.6 to 1.3 nM in mini SimCells. Moreover, lyophilized mini SimCells can maintain function for over 2 months. Hence, SimCell-based NO biosensors could be used as safe sensor chassis for synthetic biology.

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.

Transcription-Factor-based Biosensor Engineering for Applications in Synthetic Biology

Transcription-factor-based biosensors (TFBs) are often used for metabolite detection, adaptive evolution, and metabolic flux control. However, designing TFBs with superior performance for applications in synthetic biology remains challenging. Specifically, natural TFBs often do not meet real-time detection requirements owing to their slow response times and inappropriate dynamic ranges, detection ranges, sensitivity, and selectivity. Furthermore, designing and optimizing complex dynamic regulation networks is time-consuming and labor-intensive. This Review highlights TFB-based applications and recent engineering strategies ranging from traditional trial-and-error approaches to novel computer-model-based rational design approaches. The limitations of the applications and these engineering strategies are additionally reviewed.

Pulses and delays, anticipation and memory: seeing bacterial stress responses from a single-cell perspective

Stress responses are crucial for bacteria to survive harmful conditions that they encounter in the environment. Although gene regulatory mechanisms underlying stress responses in bacteria have been thoroughly characterised for decades, recent advances in imaging technologies helped to uncover previously hidden dynamics and heterogeneity that become visible at the single-cell level. Despite the diversity of stress response mechanisms, certain dynamic regulatory features are frequently seen in single cells, such as pulses, delays, stress anticipation and memory effects. Often, these dynamics are highly variable across cells. While any individual cell may not achieve an optimal stress response, phenotypic diversity can provide a benefit at the population level. In this review, we highlight microscopy studies that offer novel insights into how bacteria sense stress, regulate protective mechanisms, cope with response delays and prepare for future environmental challenges. These studies showcase developments in the single-cell imaging toolbox including gene expression reporters, FRET, super-resolution microscopy and single-molecule tracking, as well as microfluidic techniques to manipulate cells and create defined stress conditions.

The role of gut microbiota in tumorigenesis and treatment

A large number of microbial communities exist in normal human intestinal tracts, which maintain a relatively stable dynamic balance under certain conditions. Gut microbiota are closely connected with human health and the occurrence of tumors. The colonization of certain intestinal bacteria on specific sites, gut microbiota disturbance and intestinal immune disorders can induce the occurrence of tumors. Meanwhile, gut microbiota can also play a role in tumor therapy by participating in immune regulation, influencing the efficacy of anti-tumor drugs, targeted therapy of engineered probiotics and fecal microbiota transplantation. This article reviews the role of gut microbiota in the occurrence, development, diagnosis and treatment of tumors. A better understanding of how gut microbiota affect tumors will help us find more therapies to treat the disease.

Plasmid Vectors for in Vivo Selection-Free Use with the Probiotic E. coli Nissle 1917

Escherichia coli Nissle 1917 (EcN) is a probiotic bacterium, commonly employed to treat certain gastrointestinal disorders. It is fast emerging as an important target for the development of therapeutic engineered bacteria, benefiting from the wealth of knowledge of E. coli biology and ease of manipulation. Bacterial synthetic biology projects commonly utilize engineered plasmid vectors, which are simple to engineer and can reliably achieve high levels of protein expression. However, plasmids typically require antibiotics for maintenance, and the administration of an antibiotic is often incompatible with in vivo experimentation or treatment. EcN natively contains plasmids pMUT1 and pMUT2, which have no known function but are stable within the bacteria. Here, we describe the development of the pMUT plasmids into a robust platform for engineering EcN for in vivo experimentation, alongside a CRISPR-Cas9 system to remove the native plasmids. We systematically engineered both pMUT plasmids to contain selection markers, fluorescent markers, temperature sensitive expression, and curli secretion systems to export a customizable functional material into the extracellular space. We then demonstrate that the engineered plasmids were maintained in bacteria as the engineered bacteria pass through the mouse GI tract without selection, and that the secretion system remains functional, exporting functionalized curli proteins into the gut. Our plasmid system presents a platform for the rapid development of therapeutic EcN bacteria.

Single Cell Characterization of a Synthetic Bacterial Clock with a Hybrid Feedback Loop Containing dCas9-sgRNA

Genetic networks that generate oscillations in gene expression activity are found in a wide range of organisms throughout all kingdoms of life. Oscillatory dynamics facilitates the temporal orchestration of metabolic and growth processes inside cells and organisms, as well as the synchronization of such processes with periodically occurring changes in the environment. Synthetic oscillator gene circuits such as the "repressilator" can perform similar functions in bacteria. Until recently, such circuits were mainly based on a relatively small set of well-characterized transcriptional repressors and activators. A promising, sequence-programmable alternative for gene regulation is given by CRISPR interference (CRISPRi), which enables transcriptional repression of nearly arbitrary gene targets directed by short guide RNA molecules. In order to demonstrate the use of CRISPRi in the context of dynamic gene circuits, we here replaced one of the nodes of a repressilator circuit by the RNA-guided dCas9 protein. Using single cell experiments in microfluidic reactors we show that this system displays robust relaxation oscillations over multiple periods and over several days. With a period of ≈14 bacterial generations, our oscillator is similar in speed as previously reported oscillators. Using an information-theoretic approach for the analysis of the single cell data, the potential of the circuit to act as a synthetic pacemaker for cellular processes is evaluated. We also observe that the oscillator appears to affect cellular growth, leading to variations in growth rate with the oscillator's frequency.

Engineering microbial diagnostics and therapeutics with smart control

Microbes have become an increasingly powerful chassis for developing diagnostic and therapeutic technologies. While many of the earlier engineering efforts used microbes that expressed relevant proteins constitutively, more microbes are being engineered to express them with region-selectivity and disease-responsiveness through biosensors. Such 'smart' microbes have been developed to diagnose and treat a wide range of disorders and diseases, including bacterial infections, cancers, inflammatory disorders, and metabolic disorders. In this review, we discuss synthetic biology technologies that have been applied to engineer microbes for biomedical applications, focusing on recent reports that demonstrate microbial sensing by using animal models or clinical samples. Advances in synthetic biology will enable engineered microbes to significantly improve the medical field.

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.

Toward a translationally independent RNA-based synthetic oscillator using deactivated CRISPR-Cas

In synthetic circuits, CRISPR-Cas systems have been used effectively for endpoint changes from an initial state to a final state, such as in logic gates. Here, we use deactivated Cas9 (dCas9) and deactivated Cas12a (dCas12a) to construct dynamic RNA ring oscillators that cycle continuously between states over time in bacterial cells. While our dCas9 circuits using 103-nt guide RNAs showed irregular fluctuations with a wide distribution of peak-to-peak period lengths averaging approximately nine generations, a dCas12a oscillator design with 40-nt CRISPR RNAs performed much better, having a strongly repressed off-state, distinct autocorrelation function peaks, and an average peak-to-peak period length of ∼7.5 generations. Along with free-running oscillator circuits, we measure repression response times in open-loop systems with inducible RNA steps to compare with oscillator period times. We track thousands of cells for 24+ h at the single-cell level using a microfluidic device. In creating a circuit with nearly translationally independent behavior, as the RNAs control each others' transcription, we present the possibility for a synthetic oscillator generalizable across many organisms and readily linkable for transcriptional control.

Genetic circuit design automation for the gut resident species Bacteroides thetaiotaomicron

Bacteroides thetaiotaomicron is a human-associated bacterium that holds promise for delivery of therapies in the gut microbiome1. Therapeutic bacteria would benefit from the ability to turn on different programs of gene expression in response to conditions inside and outside of the gut; however, the availability of regulatory parts, and methods to combine them, have been limited in B. thetaiotaomicron2-5. We report implementation of Cello circuit design automation software6 for this species. First, we characterize a set of genome-integrated NOT/NOR gates based on single guide RNAs (CRISPR-dCas9) to inform a Bt user constraint file (UCF) for Cello. Then, logic circuits are designed to integrate sensors that respond to bile acid and anhydrotetracycline (aTc), including one created to distinguish between environments associated with bioproduction, the human gut, and after release. This circuit was found to be stable under laboratory conditions for at least 12 days and to function in bacteria associated with a primary colonic epithelial monolayer in an in vitro human gut model system.

Counting Replication Origins to Measure Growth of Pathogens

For the past several decades, the success of bacterial strains in infecting their host has been essentially ascribed to the presence of canonical virulence genes. While it is unclear how much growth rate impacts the outcome of an infection, it is long known that the efficacy of the most commonly used antibiotics is correlated to growth. This applies especially to β-lactams, whose efficacy is nearly abolished when cells grow very slowly. It is therefore reasonable to assume that a niche or genetic dependent change in growth rate could contribute to the variability in the outcome of antibiotic therapy. However, little is known about the growth rate of pathogens or their pathotypes in their host.

Synthetic Biology Speeds Up Drug Target Discovery

As a rising emerging field, synthetic biology intends to realize precise regulations of cellular network by constructing artificial synthetic circuits, and it brings great opportunities to treat diseases and discover novel drug targets. Depending on the combination mode of different logic gates, various synthetic circuits are created to carry out multilevel regulations. In given synthetic circuits, drugs often act as inputs to drive circuits operation. It is becoming available to construct drug-responsive gene circuits for experimentally treating various disease models, including metabolic disease, immunity disease, cancer and bacterial infection. Synthetic biology works well in association with the CRISPR system for drug target functional screening. Remarkably, more and more well-designed circuits are developed to discover novel drug targets and precisely regulate drug therapy for diseases.

Isolating live cells after high-throughput, long-term, time-lapse microscopy

Single-cell genetic screens can be incredibly powerful, but current high-throughput platforms do not track dynamic processes, and even for non-dynamic properties they struggle to separate mutants of interest from phenotypic outliers of the wild-type population. Here we introduce SIFT, single-cell isolation following time-lapse imaging, to address these limitations. After imaging and tracking individual bacteria for tens of consecutive generations under tightly controlled growth conditions, cells of interest are isolated and propagated for downstream analysis, free of contamination and without genetic or physiological perturbations. This platform can characterize tens of thousands of cell lineages per day, making it possible to accurately screen complex phenotypes without the need for barcoding or genetic modifications. We applied SIFT to identify a set of ultraprecise synthetic gene oscillators, with circuit variants spanning a 30-fold range of average periods. This revealed novel design principles in synthetic biology and demonstrated the power of SIFT to reliably screen diverse dynamic phenotypes.