Engineering a novel self-powering electrochemical biosensor

Synthetic biology and biomimetic chemistry as converging technologies fostering a new generation of smart biosensors

Biosensors are powerful tunable systems able to switch between an ON/OFF status in response to an external stimulus. This extraordinary property could be engineered by adopting synthetic biology or biomimetic chemistry to obtain tailor-made biosensors having the desired requirements of robustness, sensitivity and detection range. Recent advances in both disciplines, in fact, allow to re-design the configuration of the sensing elements - either by modifying toggle switches and gene networks, or by producing synthetic entities mimicking key properties of natural molecules. The present review considered the role of synthetic biology in sustaining biosensor technology, reporting examples from the literature and reflecting on the features that make it a useful tool for designing and constructing engineered biological systems for sensing application. Besides, a section dedicated to bioinspired synthetic molecules as powerful tools to enhance biosensor potential is reported, and treated as an extension of the concept of biomimetic chemistry, where organic synthesis is used to generate artificial molecules that mimic natural molecules. Thus, the design of synthetic molecules, such as aptamers, biomimetics, molecular imprinting polymers, peptide nucleic acids, and ribozymes were encompassed as "products" of biomimetic chemistry.

Towards light-mediated sensing of bacterial comfort

Bacterial comfort is central to biotechnological applications. Here, we report the characterization of different sensoring systems, the first step within a broader synthetic biology-inspired light-mediated strategy to determine Escherichia coli perception of environmental factors critical to bacterial performance. We did so by directly 'asking' bacterial cultures with light-encoded questions corresponding to the excitation wavelength of fluorescent proteins placed under the control of environment-sensitive promoters. We built four genetic constructions with fluorescent proteins responding to glucose, temperature, oxygen and nitrogen; and a fifth construction allowing UV-induced expression of heterologous genes. Our engineered strains proved able to give feedback in response to key environmental factors and to express heterologous proteins upon light induction. This light-based dialoguing strategy reported here is the first effort towards developing a human-bacteria interphase with both fundamental and applied implications.

SIGNIFICANCE AND IMPACT OF THE STUDY

The results we present here are at the core of a larger synthetic biology research effort aiming at establishing a dialogue with bacteria. The framework is to convert the human voice into electric pulses, these into light pulses exciting bacterial fluorescent proteins, and convert light-emission back into electric pulses, which will be finally transformed into synthetic voice messages. We report here the first results of the project, in the form of light-based determination of key parameters for bacterial comfort. The ultimate goal of this strategy is to combine different engineered populations to have a combined feedback from the pool.

Modular design of artificial tissue homeostasis: robust control through synthetic cellular heterogeneity

Synthetic biology efforts have largely focused on small engineered gene networks, yet understanding how to integrate multiple synthetic modules and interface them with endogenous pathways remains a challenge. Here we present the design, system integration, and analysis of several large scale synthetic gene circuits for artificial tissue homeostasis. Diabetes therapy represents a possible application for engineered homeostasis, where genetically programmed stem cells maintain a steady population of β-cells despite continuous turnover. We develop a new iterative process that incorporates modular design principles with hierarchical performance optimization targeted for environments with uncertainty and incomplete information. We employ theoretical analysis and computational simulations of multicellular reaction/diffusion models to design and understand system behavior, and find that certain features often associated with robustness (e.g., multicellular synchronization and noise attenuation) are actually detrimental for tissue homeostasis. We overcome these problems by engineering a new class of genetic modules for ‘synthetic cellular heterogeneity’ that function to generate beneficial population diversity. We design two such modules (an asynchronous genetic oscillator and a signaling throttle mechanism), demonstrate their capacity for enhancing robust control, and provide guidance for experimental implementation with various computational techniques. We found that designing modules for synthetic heterogeneity can be complex, and in general requires a framework for non-linear and multifactorial analysis. Consequently, we adapt a ‘phenotypic sensitivity analysis’ method to determine how functional module behaviors combine to achieve optimal system performance. We ultimately combine this analysis with Bayesian network inference to extract critical, causal relationships between a module's biochemical rate-constants, its high level functional behavior in isolation, and its impact on overall system performance once integrated.

Over the last decade several relatively small synthetic gene networks have been successfully implemented and characterized, including oscillators, toggle switches, and intercellular communication systems. However, the ability to engineer large-scale synthetic gene networks for controlling multicellular systems with predictable and robust behavior remains a challenge. Here we present a novel combination of computational methods to aid the iterative design and optimization of such synthetic biological systems. We apply these methods to the design and analysis of an artificial tissue homeostasis system that exhibits coordinated control of cellular proliferation, differentiation, and cell-death. Achieving artificial tissue homeostasis would be therapeutically relevant for diseases such as Type I diabetes, for instance by transplanting genetically engineered stem cells that stably maintain populations of insulin-producing beta-cells despite normal cell death and autoimmune attacks. To manage complexity in the design process, we employ principles of logic abstraction and modularity and investigate their limits in biological networks. In this work, we find factors often associated with robustness (e.g., multicellular synchronization and noise attenuation) to be actually detrimental, and overcome these problems by engineering genetic modules that generate beneficial population heterogeneity. A combination of computational methods elucidates how these modules function to enhance robust control, and provides guidance for experimental implementation.