Interfacing gene circuits with microelectronics through engineered population dynamics

Optimal network sizes for most robust Turing patterns

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

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

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

Unraveling biochemical spatial patterns: Machine learning approaches to the inverse problem of stationary Turing patterns

The diffusion-driven Turing instability is a potential mechanism for spatial pattern formation in numerous biological and chemical systems. However, engineering these patterns and demonstrating that they are produced by this mechanism is challenging. To address this, we aim to solve the inverse problem in artificial and experimental Turing patterns. This task is challenging since patterns are often corrupted by noise and slight changes in initial conditions can lead to different patterns. We used both least squares to explore the problem and physics-informed neural networks to build a noise-robust method. We elucidate the functionality of our network in scenarios mimicking biological noise levels and showcase its application using an experimentally obtained chemical pattern. The findings reveal the significant promise of machine learning in steering the creation of synthetic patterns in bioengineering, thereby advancing our grasp of morphological intricacies within biological systems while acknowledging existing limitations.

A hybrid transistor with transcriptionally controlled computation and plasticity

Organic electrochemical transistors (OECTs) are ideal devices for translating biological signals into electrical readouts and have applications in bioelectronics, biosensing, and neuromorphic computing. Despite their potential, developing programmable and modular methods for living systems to interface with OECTs has proven challenging. Here we describe hybrid OECTs containing the model electroactive bacterium Shewanella oneidensis that enable the transduction of biological computations to electrical responses. Specifically, we fabricated planar p-type OECTs and demonstrated that channel de-doping is driven by extracellular electron transfer (EET) from S. oneidensis. Leveraging this mechanistic understanding and our ability to control EET flux via transcriptional regulation, we used plasmid-based Boolean logic gates to translate biological computation into current changes within the OECT. Finally, we demonstrated EET-driven changes to OECT synaptic plasticity. This work enables fundamental EET studies and OECT-based biosensing and biocomputing systems with genetically controllable and modular design elements.

Design of synthetic bacterial biosensors

Novel whole-cell bacterial biosensor designs require an emphasis on moving toward field deployment. Many current sensors are characterized under specified laboratory conditions, which frequently do not represent actual deployment conditions. To this end, recent developments such as toolkits for probing new host chassis that are more robust to environments of interest, have paved the way for improved designs. Strategies for rational tuning of genetic components or tools such as genetic amplifiers or designs that allow post hoc tuning are essential in optimizing existing biosensors for practical application. Furthermore, recent work has seen a rise in directed evolution techniques, which can be immensely valuable in both tuning existing sensors and developing sensors for new analytes that lack characterized sensors. Combined with advancements in bioinformatics and capabilities in rewiring two-component systems, many new sensors can be established, broadening biosensor use cases. Last, recent work in CRISPR-based dynamic regulation and memory mechanisms, as well as kill-switches for biosafety and innovative output integration concepts, represents promising steps toward designing bacterial biosensors for deployment in dynamic and heterogeneous conditions.

Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability

Isogenic cell populations can cope with stress conditions by switching to alternative phenotypes. Even if it can lead to increased fitness in a natural context, this feature is typically unwanted for a range of applications (e.g., bioproduction, synthetic biology, and biomedicine) where it tends to make cellular response unpredictable. However, little is known about the diversification profiles that can be adopted by a cell population. Here, we characterize the diversification dynamics for various systems (bacteria and yeast) and for different phenotypes (utilization of alternative carbon sources, general stress response and more complex development patterns). Our results suggest that the diversification dynamics and the fitness cost associated with cell switching are coupled. To quantify the contribution of the switching cost on population dynamics, we design a stochastic model that let us reproduce the dynamics observed experimentally and identify three diversification regimes, i.e., constrained (at low switching cost), dispersed (at medium and high switching cost), and bursty (for very high switching cost). Furthermore, we use a cell-machine interface called Segregostat to demonstrate that different levels of control can be applied to these diversification regimes, enabling applications involving more precise cellular responses.

A Hybrid Transistor with Transcriptionally Controlled Computation and Plasticity

Organic electrochemical transistors (OECTs) are ideal devices for translating biological signals into electrical readouts and have applications in bioelectronics, biosensing, and neuromorphic computing. Despite their potential, developing programmable and modular methods for living systems to interface with OECTs has proven challenging. Here we describe hybrid OECTs containing the model electroactive bacterium Shewanella oneidensis that enable the transduction of biological computations to electrical responses. Specifically, we fabricated planar p-type OECTs and demonstrated that channel de-doping is driven by extracellular electron transfer (EET) from S. oneidensis. Leveraging this mechanistic understanding and our ability to control EET flux via transcriptional regulation, we used plasmid-based Boolean logic gates to translate biological computation into current changes within the OECT. Finally, we demonstrated EET-driven changes to OECT synaptic plasticity. This work enables fundamental EET studies and OECT-based biosensing and biocomputing systems with genetically controllable and modular design elements.

Sub-1.4 cm3 capsule for detecting labile inflammatory biomarkers in situ

Transient molecules in the gastrointestinal tract such as nitric oxide and hydrogen sulfide are key signals and mediators of inflammation. Owing to their highly reactive nature and extremely short lifetime in the body, these molecules are difficult to detect. Here we develop a miniaturized device that integrates genetically engineered probiotic biosensors with a custom-designed photodetector and readout chip to track these molecules in the gastrointestinal tract. Leveraging the molecular specificity of living sensors1, we genetically encoded bacteria to respond to inflammation-associated molecules by producing luminescence. Low-power electronic readout circuits2 integrated into the device convert the light emitted by the encapsulated bacteria to a wireless signal. We demonstrate in vivo biosensor monitoring in the gastrointestinal tract of small and large animal models and the integration of all components into a sub-1.4 cm3 form factor that is compatible with ingestion and capable of supporting wireless communication. With this device, diseases such as inflammatory bowel disease could be diagnosed earlier than is currently possible, and disease progression could be more accurately tracked. The wireless detection of short-lived, disease-associated molecules with our device could also support timely communication between patients and caregivers, as well as remote personalized care.

Bacterial metal(loid) resistance genes (MRGs) and their variation and application in environment: A review

Toxic metal(loid)s are widespread and permanent in the biosphere, and bacteria have evolved a wide variety of metal(loid) resistance genes (MRGs) to resist the stress of excess metal(loid)s. Via active efflux, permeability barriers, extracellular/intracellular sequestration, enzymatic detoxification and reduction in metal(loid)s sensitivity of cellular targets, the key components of bacterial cells are protected from toxic metal(loid)s to maintain their normal physiological functions. Exploiting bacterial metal(loid) resistance mechanisms, MRGs have been applied in many environmental fields. Based on the specific binding ability of MRGs-encoded regulators to metal(loid)s, MRGs-dependent biosensors for monitoring environmental metal(loid)s are developed. MRGs-related biotechnologies have been applied to environmental remediation of metal(loid)s by using the metal(loid) tolerance, biotransformation, and biopassivation abilities of MRGs-carrying microorganisms. In this work, we review the historical evolution, resistance mechanisms, environmental variation, and environmental applications of bacterial MRGs. The potential hazards, unresolved problems, and future research directions are also discussed.

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.

Fabrication, control, and modeling of robots inspired by flagella and cilia

Flagella and cilia are slender structures that serve important functionalities in the microscopic world through their locomotion induced by fluid and structure interaction. With recent developments in microscopy, fabrication, biology, and modeling capability, robots inspired by the locomotion of these organelles in low Reynolds number flow have been manufactured and tested on the micro-and macro-scale, ranging from medicalin vivomicrobots, microfluidics to macro prototypes. We present a collection of modeling theories, control principles, and fabrication methods for flagellated and ciliary robots.

Exploiting Information and Control Theory for Directing Gene Expression in Cell Populations

Microbial populations can adapt to adverse environmental conditions either by appropriately sensing and responding to the changes in their surroundings or by stochastically switching to an alternative phenotypic state. Recent data point out that these two strategies can be exhibited by the same cellular system, depending on the amplitude/frequency of the environmental perturbations and on the architecture of the genetic circuits involved in the adaptation process. Accordingly, several mitigation strategies have been designed for the effective control of microbial populations in different contexts, ranging from biomedicine to bioprocess engineering. Technically, such control strategies have been made possible by the advances made at the level of computational and synthetic biology combined with control theory. However, these control strategies have been applied mostly to synthetic gene circuits, impairing the applicability of the approach to natural circuits. In this review, we argue that it is possible to expand these control strategies to any cellular system and gene circuits based on a metric derived from this information theory, i.e., mutual information (MI). Indeed, based on this metric, it should be possible to characterize the natural frequency of any gene circuits and use it for controlling gene circuits within a population of cells.

Recent advances in biomedical, biosensor and clinical measurement devices for use in humans and the potential application of these technologies for the study of physiology and disease in wild animals

The goal of achieving enhanced diagnosis and continuous monitoring of human health has led to a vibrant, dynamic and well-funded field of research in medical sensing and biosensor technologies. The field has many sub-disciplines which focus on different aspects of sensor science; engaging engineers, chemists, biochemists and clinicians, often in interdisciplinary teams. The trends which dominate include the efforts to develop effective point of care tests and implantable/wearable technologies for early diagnosis and continuous monitoring. This review will outline the current state of the art in a number of relevant fields, including device engineering, chemistry, nanoscience and biomolecular detection, and suggest how these advances might be employed to develop effective systems for measuring physiology, detecting infection and monitoring biomarker status in wild animals. Special consideration is also given to the emerging threat of antimicrobial resistance and in the light of the current SARS-CoV-2 outbreak, zoonotic infections. Both of these areas involve significant crossover between animal and human health and are therefore well placed to seed technological developments with applicability to both human and animal health and, more generally, the reviewed technologies have significant potential to find use in the measurement of physiology in wild animals. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.

Electronic signals are electrogenetically relayed to control cell growth and co-culture composition

There is much to be gained by enabling electronic interrogation and control of biological function. While the benefits of bioelectronics that rely on potential-driven ionic flows are well known (electrocardiograms, defibrillators, neural prostheses, etc) there are relatively few advances targeting nonionic molecular networks, including genetic circuits. Redox activities combine connectivity to electronics with the potential for specific genetic control in cells. Here, electrode-generated hydrogen peroxide is used to actuate an electrogenetic "relay" cell population, which interprets the redox cue and synthesizes a bacterial signaling molecule (quorum sensing autoinducer AI-1) that, in turn, signals increased growth rate in a second population. The dramatically increased growth rate of the second population is enabled by expression of a phosphotransferase system protein, HPr, which is important for glucose transport. The potential to electronically modulate cell growth via direct genetic control will enable new opportunities in the treatment of disease and manufacture of biological therapeutics and other molecules.

Synthetic biology as driver for the biologization of materials sciences

Materials in nature have fascinating properties that serve as a continuous source of inspiration for materials scientists. Accordingly, bio-mimetic and bio-inspired approaches have yielded remarkable structural and functional materials for a plethora of applications. Despite these advances, many properties of natural materials remain challenging or yet impossible to incorporate into synthetic materials. Natural materials are produced by living cells, which sense and process environmental cues and conditions by means of signaling and genetic programs, thereby controlling the biosynthesis, remodeling, functionalization, or degradation of the natural material. In this context, synthetic biology offers unique opportunities in materials sciences by providing direct access to the rational engineering of how a cell senses and processes environmental information and translates them into the properties and functions of materials. Here, we identify and review two main directions by which synthetic biology can be harnessed to provide new impulses for the biologization of the materials sciences: first, the engineering of cells to produce precursors for the subsequent synthesis of materials. This includes materials that are otherwise produced from petrochemical resources, but also materials where the bio-produced substances contribute unique properties and functions not existing in traditional materials. Second, engineered living materials that are formed or assembled by cells or in which cells contribute specific functions while remaining an integral part of the living composite material. We finally provide a perspective of future scientific directions of this promising area of research and discuss science policy that would be required to support research and development in this field.

Applications, challenges, and needs for employing synthetic biology beyond the lab

Synthetic biology holds great promise for addressing global needs. However, most current developments are not immediately translatable to 'outside-the-lab' scenarios that differ from controlled laboratory settings. Challenges include enabling long-term storage stability as well as operating in resource-limited and off-the-grid scenarios using autonomous function. Here we analyze recent advances in developing synthetic biological platforms for outside-the-lab scenarios with a focus on three major application spaces: bioproduction, biosensing, and closed-loop therapeutic and probiotic delivery. Across the Perspective, we highlight recent advances, areas for further development, possibilities for future applications, and the needs for innovation at the interface of other disciplines.

Robust direct digital-to-biological data storage in living cells

DNA has been the predominant information storage medium for biology and holds great promise as a next-generation high-density data medium in the digital era. Currently, the vast majority of DNA-based data storage approaches rely on in vitro DNA synthesis. As such, there are limited methods to encode digital data into the chromosomes of living cells in a single step. Here, we describe a new electrogenetic framework for direct storage of digital data in living cells. Using an engineered redox-responsive CRISPR adaptation system, we encoded binary data in 3-bit units into CRISPR arrays of bacterial cells by electrical stimulation. We demonstrate multiplex data encoding into barcoded cell populations to yield meaningful information storage and capacity up to 72 bits, which can be maintained over many generations in natural open environments. This work establishes a direct digital-to-biological data storage framework and advances our capacity for information exchange between silicon- and carbon-based entities.

Emerging biofabrication approaches for gastrointestinal organoids towards patient specific cancer models

Tissue engineered organoids are simple biomodels that can emulate the structural and functional complexity of specific organs. Here, we review developments in three-dimensional (3D) artificial cell constructs to model gastrointestinal dynamics towards cancer diagnosis. We describe bottom-up approaches to fabricate close-packed cell aggregates, from the use of biochemical and physical cues to guide the self-assembly of organoids, to the use of engineering approaches, including 3D printing/additive manufacturing and external field-driven protocols. Finally, we outline the main challenges and possible risks regarding the potential translation of gastrointestinal organoids from laboratory settings to patient-specific models in clinical applications.

Medical Micro/Nanorobots in Precision Medicine

Advances in medical robots promise to improve modern medicine and the quality of life. Miniaturization of these robotic platforms has led to numerous applications that leverages precision medicine. In this review, the current trends of medical micro and nanorobotics for therapy, surgery, diagnosis, and medical imaging are discussed. The use of micro and nanorobots in precision medicine still faces technical, regulatory, and market challenges for their widespread use in clinical settings. Nevertheless, recent translations from proof of concept to in vivo studies demonstrate their potential toward precision medicine.