Designer cell signal processing circuits for biotechnology

Thermal Input/Concentration Output Systems Processed by Chemical Reactions of Helicene Oligomers

This article describes thermal input/concentration output systems processed by chemical reactions. Various sophisticated thermal inputs can be converted into concentration outputs through the double-helix formation of helicene oligomers exhibiting thermal hysteresis. The inputs include high or low temperature, cooling or heating state, slow or fast cooling state, heating state, and cooling history. The chemical basis for the properties of the chemical reactions includes the reversibility out of chemical equilibrium, sigmoidal relationship and kinetics, bistability involving metastable states, positive feedback by self-catalytic chemical reactions, competitive chemical reactions, and fine tunability for parallel processing. The interfacing of concentration outputs in other systems is considered, and biological cells are considered to have been utilizing such input/output systems processed by chemical reactions.

Biological Parts for Engineering Abiotic Stress Tolerance in Plants

It is vital to ramp up crop production dramatically by 2050 due to the increasing global population and demand for food. However, with the climate change projections showing that droughts and heatwaves becoming common in much of the globe, there is a severe threat of a sharp decline in crop yields. Thus, developing crop varieties with inbuilt genetic tolerance to environmental stresses is urgently needed. Selective breeding based on genetic diversity is not keeping up with the growing demand for food and feed. However, the emergence of contemporary plant genetic engineering, genome-editing, and synthetic biology offer precise tools for developing crops that can sustain productivity under stress conditions. Here, we summarize the systems biology-level understanding of regulatory pathways involved in perception, signalling, and protective processes activated in response to unfavourable environmental conditions. The potential role of noncoding RNAs in the regulation of abiotic stress responses has also been highlighted. Further, examples of imparting abiotic stress tolerance by genetic engineering are discussed. Additionally, we provide perspectives on the rational design of abiotic stress tolerance through synthetic biology and list various bioparts that can be used to design synthetic gene circuits whose stress-protective functions can be switched on/off in response to environmental cues.

Programming living sensors for environment, health and biomanufacturing

Synthetic biology offers new tools and capabilities of engineering cells with desired functions for example as new biosensing platforms leveraging engineered microbes. In the last two decades, bacterial cells have been programmed to sense and respond to various input cues for versatile purposes including environmental monitoring, disease diagnosis and adaptive biomanufacturing. Despite demonstrated proof-of-concept success in the laboratory, the real-world applications of microbial sensors have been restricted due to certain technical and societal limitations. Yet, most limitations can be addressed by new technological developments in synthetic biology such as circuit design, biocontainment and machine learning. Here, we summarize the latest advances in synthetic biology and discuss how they could accelerate the development, enhance the performance and address the present limitations of microbial sensors to facilitate their use in the field. We view that programmable living sensors are promising sensing platforms to achieve sustainable, affordable and easy-to-use on-site detection in diverse settings.

Synthetic biology approaches to copper remediation: bioleaching, accumulation and recycling

One of the current aims of synthetic biology is the development of novel microorganisms that can mine economically important elements from the environment or remediate toxic waste compounds. Copper, in particular, is a high-priority target for bioremediation owing to its extensive use in the food, metal and electronic industries and its resulting common presence as an environmental pollutant. Even though microbe-aided copper biomining is a mature technology, its application to waste treatment and remediation of contaminated sites still requires further research and development. Crucially, any engineered copper-remediating chassis must survive in copper-rich environments and adapt to copper toxicity; they also require bespoke adaptations to specifically extract copper and safely accumulate it as a human-recoverable deposit to enable biorecycling. Here, we review current strategies in copper bioremediation, biomining and biorecycling, as well as strategies that extant bacteria use to enhance copper tolerance, accumulation and mineralization in the native environment. By describing the existing toolbox of copper homeostasis proteins from naturally occurring bacteria, we show how these modular systems can be exploited through synthetic biology to enhance the properties of engineered microbes for biotechnological copper recovery applications.

Genomic Intelligence as Über Bio-Cybersecurity: The Gödel Sentence in Immuno-Cognitive Systems

This paper gives formal foundations and evidence from gene science in the post Barbara McClintock era that the Gödel Sentence, far from being an esoteric construction in mathematical logic, is ubiquitous in genomic intelligence that evolved with multi-cellular life. Conditions uniquely found in the Adaptive Immune System (AIS) and Mirror Neuron System (MNS), termed the genomic immuno-cognitive system, coincide with three building blocks in computation theory of Gödel, Turing and Post (G-T-P). (i) Biotic elements have unique digital identifiers with gene codes executing 3D self-assembly for morphology and regulation of the organism using the recursive operation of Self-Ref (Self-Reference) with the other being a self-referential projection of self. (ii) A parallel offline simulation meta/mirror environment in 1–1 relation to online machine executions of self-codes gives G-T-P Self-Rep (Self-Representation). (iii) This permits a digital biotic entity to self-report that it is under attack by a biotic malware or non-self antigen in the format of the Gödel sentence, resulting in the “smarts” for contextual novelty production. The proposed unitary G-T-P recursive machinery in AIS and in MNS for social cognition yields a new explanation that the Interferon Gamma factor, known for friend-foe identification in AIS, is also integral to social behaviors. New G-T-P bio-informatics of AIS and novel anti-body production is given with interesting testable implications for COVID-19 pathology.

Nucleobase Pair-Metal Dimer/Dinuclear Metal Cation Interaction: A Theoretical Study

Nucleobase pair-metal dimer/dinuclear metal cation interactions play an important role in biological applications because of their highly symmetrical structures and high stabilities. In this work, we have selected five adenine-adenine hydrogen bonding, adenine-thymine (AT), adenine-uracil, adenine-adenine stacking pairs, and Watson-Crick AT stacking pairs and studied their interaction with the coinage metal dimer M2 and M2 2+ metal cations, where M = Ag, Au, and Cu. Quantum chemical calculations have been carried out with density functional theory (DFT) and time-dependent DFT (TDDFT) methods. Electronic structures were analyzed by the partial density of states method. During interactions, we find that M-M distances are shorter than the sum of van der Waals radii of the corresponding two homocoinage metal atoms, which show the existence of significant metallophilic interactions. Results indicated that nucleobase-M2 2+ complexes are stronger as compared to nucleobase-M2 complexes. Also, the replacement of the hydrogen bond by the dinuclear metal cation-coordinated bond forms more stable alternative metallo-DNA sequences in AAST base pairs. TDDFT calculations reveal that nucleobase-Cu2 complexes and nucleobase-Ag2 2+/Au2 2+ complexes can be used for fluorescent markers and logic gate applications. Atom-in-molecules analysis predicted the noncovalent interaction in these complexes.

Engineering Synthetic Signaling in Plants

Synthetic signaling is a branch of synthetic biology that aims to understand native genetic regulatory mechanisms and to use these insights to engineer interventions and devices that achieve specified design parameters. Applying synthetic signaling approaches to plants offers the promise of mitigating the worst effects of climate change and providing a means to engineer crops for entirely novel environments, such as those in space travel. The ability to engineer new traits using synthetic signaling methods will require standardized libraries of biological parts and methods to assemble them; the decoupling of complex processes into simpler subsystems; and mathematical models that can accelerate the design-build-test-learn cycle. The field of plant synthetic signaling is relatively new, but it is poised for rapid advancement. Translation from the laboratory to the field is likely to be slowed, however, by the lack of constructive dialogue between researchers and other stakeholders.

A Novel Eukaryote-Like CRISPR Activation Tool in Bacteria: Features and Capabilities

CRISPR (clustered regularly interspaced short palindromic repeats) activation (CRISPRa) in bacteria is an attractive method for programmable gene activation. Recently, a eukaryote-like, σ⁵⁴ -dependent CRISPRa system has been reported. It exhibits high dynamic ranges and permits flexible target site selection. Here, an overview of the existing strategies of CRISPRa in bacteria is presented, and the characteristics and design principles of the CRISPRa system are introduced. Possible scenarios for applying the eukaryote-like CRISPRa system is discussed with corresponding suggestions for performance optimization and future functional expansion. The authors envision the new eukaryote-like CRISPRa system enabling novel designs in multiplexed gene regulation and promoting research in the σ⁵⁴ -dependent gene regulatory networks among a variety of biotechnology relevant or disease-associated bacterial species.

Synthetic Biology Enables Programmable Cell-Based Biosensors

Cell-based biosensors offer cheap, portable and simple methods of detecting molecules of interest but have yet to be truly adopted commercially. Issues with their performance and specificity initially slowed the development of cell-based biosensors. With the development of rational approaches to tune response curves, the performance of biosensors has rapidly improved and there are now many biosensors capable of sensing with the required performance. This has stimulated an increased interest in biosensors and their commercial potential. However the reliability, long term stability and biosecurity of these sensors are still barriers to commercial application and public acceptance. Research into overcoming these issues remains active. Here we present the state-of-the-art tools offered by synthetic biology to allow construction of cell-based biosensors with customisable performance to meet the real world requirements in terms of sensitivity and dynamic range and discuss the research progress to overcome the challenges in terms of the sensor stability and biosecurity fears.

CyanoGate: A Modular Cloning Suite for Engineering Cyanobacteria Based on the Plant MoClo Syntax

Recent advances in synthetic biology research have been underpinned by an exponential increase in available genomic information and a proliferation of advanced DNA assembly tools. The adoption of plasmid vector assembly standards and parts libraries has greatly enhanced the reproducibility of research and the exchange of parts between different labs and biological systems. However, a standardized modular cloning (MoClo) system is not yet available for cyanobacteria, which lag behind other prokaryotes in synthetic biology despite their huge potential regarding biotechnological applications. By building on the assembly library and syntax of the Plant Golden Gate MoClo kit, we have developed a versatile system called CyanoGate that unites cyanobacteria with plant and algal systems. Here, we describe the generation of a suite of parts and acceptor vectors for making (1) marked/unmarked knock-outs or integrations using an integrative acceptor vector, and (2) transient multigene expression and repression systems using known and previously undescribed replicative vectors. We tested and compared the CyanoGate system in the established model cyanobacterium Synechocystis sp. PCC 6803 and the more recently described fast-growing strain Synechococcus elongatus UTEX 2973. The UTEX 2973 fast-growth phenotype was only evident under specific growth conditions; however, UTEX 2973 accumulated high levels of proteins with strong native or synthetic promoters. The system is publicly available and can be readily expanded to accommodate other standardized MoClo parts to accelerate the development of reliable synthetic biology tools for the cyanobacterial community.

Synthetic genetic circuits for programmable biological functionalities

Living organisms evolve complex genetic networks to interact with the environment. Due to the rapid development of synthetic biology, various modularized genetic parts and units have been identified from these networks. They have been employed to construct synthetic genetic circuits, including toggle switches, oscillators, feedback loops and Boolean logic gates. Building on these circuits, complex genetic machines with capabilities in programmable decision-making could be created. Consequently, these accomplishments have led to novel applications, such as dynamic and autonomous modulation of metabolic networks, directed evolution of biological units, remote and targeted diagnostics and therapies, as well as biological containment methods to prevent release of engineered microorganisms and genetic materials. Herein, we outline the principles in genetic circuit design that have initiated a new chapter in transforming concepts to realistic applications. The features of modularized building blocks and circuit architecture that facilitate realization of circuits for a variety of novel applications are discussed. Furthermore, recent advances and challenges in employing genetic circuits to impart microorganisms with distinct and programmable functionalities are highlighted. We envision that this review gives new insights into the design of synthetic genetic circuits and offers a guideline for the implementation of different circuits in various aspects of biotechnology and bioengineering.

A Uniform Molecular Low-Density Parity Check Decoder

Error correction codes, such as low-density parity check (LDPC) codes, are required to be larger scale to meet the increasing demands for reliable and massive data transmission. However, the construction of such a large-scale decoder will result in high complexity and hinder its silicon implementation. Thanks to the advantages of natural computing in high parallelism and low power, we propose a method to synthesize a uniform molecular LDPC decoder by implementing the belief-propagation algorithm with chemical reaction networks (CRNs). This method enables us to flexibly design the LDPC decoder with arbitrary code length, code rate, and node degrees. Compared with existing methods, our proposal reduces the number of reactions to update the variable nodes by 42.86% and the check nodes by 47.37%. Numerical results are presented to show the feasibility and validity of our proposal.

Scaling up genetic circuit design for cellular computing: advances and prospects

Synthetic biology aims to engineer and redesign biological systems for useful real-world applications in biomanufacturing, biosensing and biotherapy following a typical design-build-test cycle. Inspired from computer science and electronics, synthetic gene circuits have been designed to exhibit control over the flow of information in biological systems. Two types are Boolean logic inspired TRUE or FALSE digital logic and graded analog computation. Key principles for gene circuit engineering include modularity, orthogonality, predictability and reliability. Initial circuits in the field were small and hampered by a lack of modular and orthogonal components, however in recent years the library of available parts has increased vastly. New tools for high throughput DNA assembly and characterization have been developed enabling rapid prototyping, systematic in situ characterization, as well as automated design and assembly of circuits. Recently implemented computing paradigms in circuit memory and distributed computing using cell consortia will also be discussed. Finally, we will examine existing challenges in building predictable large-scale circuits including modularity, context dependency and metabolic burden as well as tools and methods used to resolve them. These new trends and techniques have the potential to accelerate design of larger gene circuits and result in an increase in our basic understanding of circuit and host behaviour.

Orthogonality and Burdens of Heterologous AND Gate Gene Circuits in E. coli

Synthetic biology approaches commonly introduce heterologous gene networks into a host to predictably program cells, with the expectation of the synthetic network being orthogonal to the host background. However, introduced circuits may interfere with the host’s physiology, either indirectly by posing a metabolic burden and/or through unintended direct interactions between parts of the circuit with those of the host, affecting functionality. Here we used RNA-Seq transcriptome analysis to quantify the interactions between a representative heterologous AND gate circuit and the host Escherichia coli under various conditions including circuit designs and plasmid copy numbers. We show that the circuit plasmid copy number outweighs circuit composition for their effect on host gene expression with medium-copy number plasmid showing more prominent interference than its low-copy number counterpart. In contrast, the circuits have a stronger influence on the host growth with a metabolic load increasing with the copy number of the circuits. Notably, we show that variation of copy number, an increase from low to medium copy, caused different types of change observed in the behavior of components in the AND gate circuit leading to the unbalance of the two gate-inputs and thus counterintuitive output attenuation. The study demonstrates the circuit plasmid copy number is a key factor that can dramatically affect the orthogonality, burden and functionality of the heterologous circuits in the host chassis. The results provide important guidance for future efforts to design orthogonal and robust gene circuits with minimal unwanted interaction and burden to their host.

Synthetic Cell-Based Sensors with Programmed Selectivity and Sensitivity

Bacteria live in an ever changing environment and, to adapt their physiology, they have to sense the changes. Our current understanding of the mechanisms and elements involved in the detection and processing of these environmental signals grant us access to an array of genetic components able to process such information. As engineers can use different electronic components to build a circuit, we can rewire the cellular components to create digital logic and analogue gene circuits that will program cell behaviour in a designed manner in response to a specific stimulus. Here we present the methods and protocols for designing and implementing synthetic cell-based biosensors that use engineered genetic logic and analogue amplifying circuits to significantly increase selectivity and sensitivity, for example, for heavy metal ions in an aqueous environment. The approach is modular and can be readily applied to improving the sensing limit and performance of a range of microbial cell-based sensors to meet their real world detection requirement.