Mining logic gates in prokaryotic transcriptional regulation networks

Governing principles of transcriptional logic out of equilibrium

To survive, adapt, and develop, cells respond to external and internal stimuli by tightly regulating transcription. Transcriptional regulation involves the combinatorial binding of a repertoire of transcription factors to DNA, which often results in switch-like binary outputs akin to Boolean logic gates. Recent experimental studies have demonstrated that in eukaryotes, transcription factor binding to DNA often involves energy expenditure, thereby driving the system out of equilibrium. The governing principles of transcriptional logic operations out of equilibrium remain unexplored. Here, we employ a simple two-input, single-locus model of transcription that can accommodate both equilibrium and nonequilibrium mechanisms. Using this model, we find that nonequilibrium regimes can give rise to all the logic operations accessible in equilibrium. Strikingly, energy expenditure alters the regulatory function of the two transcription factors in a mutually exclusive manner. This allows for the emergence of new logic operations that are inaccessible in equilibrium. Overall, our results show that energy expenditure can expand the range of cellular decision-making without the need for more complex promoter architectures.

A versatile regulatory toolkit of arabinose-inducible artificial transcription factors for Enterobacteriaceae

The Gram-negative bacteria Salmonella enterica and Escherichia coli are important model organisms, powerful prokaryotic expression platforms for biotechnological applications, and pathogenic strains constitute major public health threats. To facilitate new approaches for research and biotechnological applications, we here develop a set of arabinose-inducible artificial transcription factors (ATFs) using CRISPR/dCas9 and Arabidopsis-derived DNA-binding proteins to control gene expression in E. coli and Salmonella over a wide inducer concentration range. The transcriptional output of the different ATFs, in particular when expressed in Salmonella rewired for arabinose catabolism, varies over a wide spectrum (up to 35-fold gene activation). As a proof-of-concept, we use the developed ATFs to engineer a Salmonella two-input biosensor strain, SALSOR 0.2 (SALmonella biosenSOR 0.2), which detects and quantifies alkaloid drugs through a measurable fluorescent output. Moreover, we use plant-derived ATFs to regulate β-carotene biosynthesis in E. coli, resulting in ~2.1-fold higher β-carotene production compared to expression of the biosynthesis pathway using a strong constitutive promoter.

A logical way to reprogram plants

Living cells constantly monitor their external and internal environments for changing conditions, stresses or developmental cues. Networks of genetically encoded components sense and process these signals following pre-defined rules in such a way that specific combinations of the presence or absence of certain signals activate suitable responses. Many biological signal integration mechanisms approximate Boolean logic operations, whereby presence or absence of signals are computed as variables with values described as either true or false, respectively. Boolean logic gates are commonly used in algebra and in computer sciences, and have long been recognized as useful information processing devices in electronic circuits. In these circuits, logic gates integrate multiple input values and produce an output signal according to pre-defined Boolean logic operations. Recent implementation of these logic operations using genetic components to process information in living cells has allowed genetic circuits to enable novel traits with decision-making capabilities. Although several literature reports describe the design and use of these logic gates to introduce new functions in bacterial, yeast and mammalian cells, similar approaches in plants remain scarce, likely due to challenges posed by the complexity of plants and the lack of some technological advances, e.g., species-independent genetic transformation. In this mini review, we have surveyed recent reports describing synthetic genetic Boolean logic operators in plants and the different gate architectures used. We also briefly discuss the potential of deploying these genetic devices in plants to bring to fruition a new generation of resilient crops and improved biomanufacturing platforms.

Engineering transcriptional regulation in Escherichia coli using an archaeal TetR-family transcription factor

Synthetic biology requires well-characterized biological parts that can be combined into functional modules. One type of biological parts are transcriptional regulators and their cognate operator elements, which enable to either generate an input-specific response or are used as actuator modules. A range of regulators has already been characterized and used for orthogonal gene expression engineering, however, previous efforts have mostly focused on bacterial regulators. This work aims to design and explore the use of an archaeal TetR family regulator, FadR_Sa from Sulfolobus acidocaldarius, in a bacterial system, namely Escherichia coli. This is a challenging objective given the fundamental difference between the bacterial and archaeal transcription machinery and the lack of a native TetR-like FadR regulatory system in E. coli. The synthetic σ⁷⁰-dependent bacterial promoter proD was used as a starting point to design hybrid bacterial/archaeal promoter/operator regions, in combination with the mKate2 fluorescent reporter enabling a readout. Four variations of proD containing FadR_Sa binding sites were constructed and characterized. While expressional activity of the modified promoter proD was found to be severely diminished for two of the constructs, constructs in which the binding site was introduced adjacent to the -35 promoter element still displayed sufficient basal transcriptional activity and showed up to 7-fold repression upon expression of FadR_Sa. Addition of acyl-CoA has been shown to disrupt FadR_Sa binding to the DNA in vitro. However, extracellular concentrations of up to 2 mM dodecanoate, subsequently converted to acyl-CoA by the cell, did not have a significant effect on repression in the bacterial system. This work demonstrates that archaeal transcription regulators can be used to generate actuator elements for use in E. coli, although the lack of ligand response underscores the challenge of maintaining biological function when transferring parts to a phylogenetically divergent host.

Cis-Regulatory Logic Produces Gene-Expression Noise Describing Phenotypic Heterogeneity in Bacteria

Gene transcriptional process is random. It occurs in bursts and follows single-molecular kinetics. Intermittent bursts are measured based on their frequency and size. They influence temporal fluctuations in the abundance of total mRNA and proteins by generating distinct transcriptional variations referred to as “noise”. Noisy expression induces uncertainty because the association between transcriptional variation and the extent of gene expression fluctuation is ambiguous. The promoter architecture and remote interference of different cis-regulatory elements are the crucial determinants of noise, which is reflected in phenotypic heterogeneity. An alternative perspective considers that cellular parameters dictating genome-wide transcriptional kinetics follow a universal pattern. Research on noise and systematic perturbations of promoter sequences reinforces that both gene-specific and genome-wide regulation occur across species ranging from bacteria and yeast to animal cells. Thus, deciphering gene-expression noise is essential across different genomics applications. Amidst the mounting conflict, it is imperative to reconsider the scope, progression, and rational construction of diversified viewpoints underlying the origin of the noise. Here, we have established an indication connecting noise, gene expression variations, and bacterial phenotypic variability. This review will enhance the understanding of gene-expression noise in various scientific contexts and applications.

Picking the right metaphors for addressing microbial systems: economic theory helps understanding biological complexity

Any descriptive language is necessarily metaphoric and interpretative. Two somewhat overlapping-but not identical-languages have been thoroughly employed in the last decade to address the issue of regulatory complexity in biological systems: the terminology of network theory and the jargon of electric circuitry. These approaches have found many formal equivalences between the layout of extant genetic circuits and the architecture of man-made counterparts. However, these languages still fail to describe accurately key features of biological objects, in particular the diversity of signal-transfer molecules and the diffusion that is inherent to any biochemical system. Furthermore, current formalisms associated with networks and circuits can hardly face the problem of multi-scale regulatory complexity-from single molecules to entire ecosystems. We argue that the language of economic theory might be instrumental not only to portray accurately many features of regulatory networks, but also to unveil aspects of the biological complexity problem that remain opaque to other types of analyses. The main perspective opened by the economic metaphor when applied to control of microbiological activities is a focus on metabolism, not gene selfishness, as the necessary background to make sense of regulatory phenomena. As an example, we analyse and reinterpret the widespread phenomenon of catabolite repression with the formal frame of the consumer's choice theory.

Whole-Cell Microbial Bioreporter for Soil Contaminants Detection

Anthropogenic activities have released various contaminants into soil that pose a serious threat to the ecosystem and human well-being. Compared to conventional analytical methodologies, microbial cell-based bioreporters are offering a flexible, rapid, and cost-effective strategy to assess the environmental risks. This review aims to summarize the recent progress in the application of bioreporters in soil contamination detection and provide insight into the challenges and current strategies. The biosensing principles and genetic circuit engineering are introduced. Developments of bioreporters to detect and quantify heavy metal and organic contaminants in soil are reviewed. Moreover, future opportunities of whole-cell bioreporters for soil contamination monitoring are discussed.

A guide to the design of synthetic gene networks in mammalian cells

Synthetic biology aims to harness natural and synthetic biological parts and engineering them in new combinations and systems, producing novel therapies, diagnostics, bioproduction systems, and providing information on the mechanism of function of biological systems. Engineering cell function requires the rewiring or de novo construction of cell information processing networks. Using natural and synthetic signal processing elements, researchers have demonstrated a wide array of signal sensing, processing and propagation modules, using transcription, translation, or post-translational modification to program new function. The toolbox for synthetic network design is ever-advancing and has still ample room to grow. Here, we review the diversity of synthetic gene networks, types of building modules, techniques of regulation, and their applications.

Unstructured kinetic models to simulate an arabinose switch that decouples cell growth from metabolite production

Modeling synthetic gene circuits to implement dynamic flux balancing is crucial in teaching and exploring metabolic engineering strategies to repartition metabolic precursors and construct efficient microbial cell factories. Microbial fitness and production rates are often complex phenotypes that are governed by highly non-linear, multivariable functions which are intrinsically linked through carbon metabolism. The solution of such dynamic system can be difficult for synthetic biologists to visualize or conceptualize. Recently, researchers (Santala et al., Metab. Eng. Comm., 2018) have implemented an arabinose based genetic switch to dynamically partition the central carbon flux between cell growth and product formation. The autonomous switch allowed dynamic shift from arabinose-associated cell growth to acetate-associated product (wax ester) formation. This system clearly demonstrates the effectiveness of using a genetic switch to decouple cell growth from product formation in a one-pot bioreactor to minimize operational cost. Coupled with Michaelis-Menten kinetics, and Luedeking-Piret equations, we were able to reconstruct and analyze this metabolic switch in silica and achieved graphical solutions that qualitatively match with the experimental data. By assessing physiologically-accessible parameter space, we observed a wide range of dynamic behavior and examined the different limiting cases. Graphical solutions for this dynamic system can be viewed simultaneously and resolved in real time via buttons on the graphical user interface (GUI). Metabolic bottlenecks in the system can be accurately predicted by varying the respective rate constants. The GUI serves as a diagnosis toolkit to troubleshoot genetic circuits design constraints and as an interactive workflow of using this arabinose based genetic switch to dynamically control carbon flux, which may provide a valuable computational toolbox for metabolic engineers and synthetic biologists to simulate and understand complex genetic-metabolic system.

Application of combinatorial optimization strategies in synthetic biology

In the first wave of synthetic biology, genetic elements, combined into simple circuits, are used to control individual cellular functions. In the second wave of synthetic biology, the simple circuits, combined into complex circuits, form systems-level functions. However, efforts to construct complex circuits are often impeded by our limited knowledge of the optimal combination of individual circuits. For example, a fundamental question in most metabolic engineering projects is the optimal level of enzymes for maximizing the output. To address this point, combinatorial optimization approaches have been established, allowing automatic optimization without prior knowledge of the best combination of expression levels of individual genes. This review focuses on current combinatorial optimization methods and emerging technologies facilitating their applications.

Regulation of bistability in the std fimbrial operon of Salmonella enterica by DNA adenine methylation and transcription factors HdfR, StdE and StdF

Bistable expression of the Salmonella enterica std operon is controlled by an AND logic gate involving three transcriptional activators: the LysR-type factor HdfR and the StdE and StdF regulators encoded by the std operon itself. StdE activates transcription of the hdfR gene, and StdF activates std transcription together with HdfR. Binding of HdfR upstream of the std promoter is hindered by methylation of GATC sites located within the upstream activating sequence (UAS). Epigenetic control by Dam methylation thus antagonizes formation of the StdE-StdF-HdfR loop and tilts the std switch toward the StdOFF state. In turn, HdfR binding hinders methylation of the UAS, permitting activation of the StdE-StdF-HdfR loop and concomitant formation of StdON cells. Bistability is thus the outcome of competition between DNA adenine methylation and the StdE-StdF-HdfR activator loop.

ParAlleL: A Novel Population-Based Approach to Biological Logic Gates

In vivo logic gates have proven difficult to combine into larger devices. Our cell-based logic system, ParAlleL, decomposes a large circuit into a collection of small subcircuits working in parallel, each subcircuit responding to a different combination of inputs. A final global output is then generated by a combination of the responses. Using ParAlleL, for the first time a completely functional 3-bit full adder and full subtractor were generated using Escherichia coli cells, as well as a calculator-style display that shows a numeric result, from 0 to 7, when the proper 3 bit binary inputs are introduced into the system. ParAlleL demonstrates the use of a parallel approach for the design of cell-based logic gates that facilitates the generation and analysis of complex processes, without the need for complex genetic engineering.

Interplay of synergy and redundancy in diamond motif

The formalism of partial information decomposition provides a number of independent components which altogether constitute the total information provided by the source variable(s) about the target variable(s). These non-overlapping terms are recognized as unique information, synergistic information, and redundant information. The metric of net synergy conceived as the difference between synergistic and redundant information is capable of detecting effective synergy, effective redundancy, and information independence among stochastic variables. The net synergy can be quantified using appropriate combinations of different Shannon mutual information terms. The utilization of the net synergy in network motifs with the nodes representing different biochemical species, involved in information sharing, uncovers rich store for exciting results. In the current study, we use this formalism to obtain a comprehensive understanding of the relative information processing mechanism in a diamond motif and two of its sub-motifs, namely, bifurcation and integration motif embedded within the diamond motif. The emerging patterns of effective synergy and effective redundancy and their contribution toward ensuring high fidelity information transmission are duly compared in the sub-motifs. Investigation on the metric of net synergy in independent bifurcation and integration motifs are also executed. In all of these computations, the crucial roles played by various systemic time scales, activation coefficients, and signal integration mechanisms at the output of the network topologies are especially emphasized. Following this plan of action, we become confident that the origin of effective synergy and effective redundancy can be architecturally justified by decomposing a diamond motif into bifurcation and integration motif. According to our conjecture, the presence of a common source of fluctuations creates effective redundancy. Our calculations reveal that effective redundancy empowers signal fidelity. Moreover, to achieve this, input signaling species avoids strong interaction with downstream intermediates. This strategy is capable of making the diamond motif noise-tolerant. Apart from the topological features, our study also puts forward the active contribution of additive and multiplicative signal integration mechanisms to nurture effective redundancy and effective synergy.

Synthesis of control unit for future biocomputer

Background

Synthesis of a variety of biological circuits for specific functional purposes has made a tremendous progress in recent years. The ultimate goal of combining molecular biology and engineering is to realize a functional biocomputer. To address this challenge, all previous efforts work toward building up the bio-computer as the ultimate goal. To this aim, there should be a key module, named control unit (CU), to direct a serious of logic or arithmetic operations within the processor.

Methods

This research task develops a bio-CU to work with a bio-ALU, which is realized from the combination of previously developed genetic logic gates to fulfill the kernel function of CPU as those done in the silicon computer.

Results

A possible framework of the bio-CPU has demonstrated how to connect a bio-CU with a bio-ALU to conduct a fetch-decode-execute cycle of a macro instruction. It presents not only capability of 4-bit full adder but coordination of related modules in biocomputer.

Conclusions

We have demonstrated computer simulation for applications of the genetic circuits in biocomputer construction. It’s expected to inspire follow-up study to synthesize potential configurations of the future biocomputer.

Evolutionary tinkering vs. rational engineering in the times of synthetic biology

Synthetic biology is not only a contemporary reformulation of the recombinant DNA technologies of the last 30 years, combined with descriptive language imported from electrical and industrial engineering. It is also a new way to interpret living systems and a statement of intent for the use and reprogramming of biological objects for human benefit. In this context, the notion of designer biology is often presented as opposed to natural selection following the powerful rationale formulated by François Jacob on evolution-as-tinkering. The onset of synthetic biology opens a different perspective by leaving aside the question about the evolutionary origin of biological phenomena and focusing instead on the relational logic and the material properties of the corresponding components that make biological system work as they do. Once a functional challenge arises, the solution space for the problem is not homogeneous but it has attractors that can be accessed either through random exploration (as evolution does) or rational design (as engineers do). Although these two paths (i.e. evolution and engineering) are essentially different, they can lead to solutions to specific mechanistic bottlenecks that frequently coincide or converge-and one can easily help to understand and improve the other. Alas, productive discussions on these matters are often contaminated by ideological preconceptions that prevent adoption of the engineering metaphor to understand and ultimately reshape living systems-as ambitioned by synthetic biology. Yet, some possible ways to overcome the impasse are feasible. In parallel to Monod's evolutionary paradox of teleo-logy (finality/purpose) vs. teleo-nomy (appearance of finality/purpose), a mechanistic paradox could be entertained between techno-logy (rational engineering) vs techno-nomy (appearance of rational engineering), all for the sake of understanding the relational logic that enables live systems to function as physico-chemical entities in time and space. This article thus proposes a radical vision of synthetic biology through the lens of the engineering metaphor.

Mining Novel Constitutive Promoter Elements in Soil Metagenomic Libraries in Escherichia coli

Although functional metagenomics has been widely employed for the discovery of genes relevant to biotechnology and biomedicine, its potential for assessing the diversity of transcriptional regulatory elements of microbial communities has remained poorly explored. Here, we experimentally mined novel constitutive promoter sequences in metagenomic libraries by combining a bi-directional reporter vector, high-throughput fluorescence assays and predictive computational methods. Through the expression profiling of fluorescent clones from two independent soil sample libraries, we have analyzed the regulatory dynamics of 260 clones with candidate promoters as a set of active metagenomic promoters in the host Escherichia coli. Through an in-depth analysis of selected clones, we were able to further explore the architecture of metagenomic fragments and to report the presence of multiple promoters per fragment with a dominant promoter driving the expression profile. These approaches resulted in the identification of 33 novel active promoters from metagenomic DNA originated from very diverse phylogenetic groups. The in silico and in vivo analysis of these individual promoters allowed the generation of a constitutive promoter consensus for exogenous sequences recognizable by E. coli in metagenomic studies. The results presented here demonstrates the potential of functional metagenomics for exploring environmental bacterial communities as a source of novel regulatory genetic parts to expand the toolbox for microbial engineering.

Toward theoretical synthesis of biocomputer

Increasing applications of fundamental biological gates have been successfully built during this decade. Proceeding to the current development, this study presents a genetic arithmetic and logical unit (ALU) design based on a series of genetic logic gates. The system level's architecture consists of three parts: temp register, ALU and accumulator register. Using the concept of the ALU on the digital computer, the authors present the fundamental function of the genetic ALU via full adder register and also build the bio-storage devices to store data generated from the genetic ALU. The system in this study shows the capability of computing and storage on the biocomputer.

Design specifications for cellular regulation

A critical feature of all cellular processes is the ability to control the rate of gene or protein expression and metabolic flux in changing environments through regulatory feedback. We review the many ways that regulation is represented through causal, logical, and dynamical components. Formalizing the nature of these components promotes effective comparison among distinct regulatory networks and provides a common framework for the potential design and control of regulatory systems in synthetic biology.

Data Integration and Mining for Synthetic Biology Design

One aim of synthetic biologists is to create novel and predictable biological systems from simpler modular parts. This approach is currently hampered by a lack of well-defined and characterized parts and devices. However, there is a wealth of existing biological information, which can be used to identify and characterize biological parts, and their design constraints in the literature and numerous biological databases. However, this information is spread among these databases in many different formats. New computational approaches are required to make this information available in an integrated format that is more amenable to data mining. A tried and tested approach to this problem is to map disparate data sources into a single data set, with common syntax and semantics, to produce a data warehouse or knowledge base. Ontologies have been used extensively in the life sciences, providing this common syntax and semantics as a model for a given biological domain, in a fashion that is amenable to computational analysis and reasoning. Here, we present an ontology for applications in synthetic biology design, SyBiOnt, which facilitates the modeling of information about biological parts and their relationships. SyBiOnt was used to create the SyBiOntKB knowledge base, incorporating and building upon existing life sciences ontologies and standards. The reasoning capabilities of ontologies were then applied to automate the mining of biological parts from this knowledge base. We propose that this approach will be useful to speed up synthetic biology design and ultimately help facilitate the automation of the biological engineering life cycle.

RNA aptamers as genetic control devices: the potential of riboswitches as synthetic elements for regulating gene expression

RNA utilizes many different mechanisms to control gene expression. Among the regulatory elements that respond to external stimuli, riboswitches are a prominent and elegant example. They consist solely of RNA and couple binding of a small molecule ligand to the so-called "aptamer domain" with a conformational change in the downstream "expression platform" which then determines system output. The modular organization of riboswitches and the relative ease with which ligand-binding RNA aptamers can be selected in vitro against almost any molecule have led to the rapid and widespread adoption of engineered riboswitches as artificial genetic control devices in biotechnology and synthetic biology over the past decade. This review highlights proof-of-principle applications to demonstrate the versatility and robustness of engineered riboswitches in regulating gene expression in pro- and eukaryotes. It then focuses on strategies and parameters to identify aptamers that can be integrated into synthetic riboswitches that are functional in vivo, before finishing with a reflection on how to improve the regulatory properties of engineered riboswitches, so that we can not only further expand riboswitch applicability, but also finally fully exploit their potential as control elements in regulating gene expression.

Loregic: a method to characterize the cooperative logic of regulatory factors

The topology of the gene-regulatory network has been extensively analyzed. Now, given the large amount of available functional genomic data, it is possible to go beyond this and systematically study regulatory circuits in terms of logic elements. To this end, we present Loregic, a computational method integrating gene expression and regulatory network data, to characterize the cooperativity of regulatory factors. Loregic uses all 16 possible two-input-one-output logic gates (e.g. AND or XOR) to describe triplets of two factors regulating a common target. We attempt to find the gate that best matches each triplet’s observed gene expression pattern across many conditions. We make Loregic available as a general-purpose tool (github.com/gersteinlab/loregic). We validate it with known yeast transcription-factor knockout experiments. Next, using human ENCODE ChIP-Seq and TCGA RNA-Seq data, we are able to demonstrate how Loregic characterizes complex circuits involving both proximally and distally regulating transcription factors (TFs) and also miRNAs. Furthermore, we show that MYC, a well-known oncogenic driving TF, can be modeled as acting independently from other TFs (e.g., using OR gates) but antagonistically with repressing miRNAs. Finally, we inter-relate Loregic’s gate logic with other aspects of regulation, such as indirect binding via protein-protein interactions, feed-forward loop motifs and global regulatory hierarchy.

Gene expression is controlled by various gene regulatory factors. Those factors work cooperatively forming a complex regulatory circuit genome wide. Corruptions of regulatory cooperativity may lead to abnormal gene expression activity such as cancer. Traditional experimental methods, however, can only identify small-scale regulatory activity. Thus, to systematically understand the cooperativity between and among different types of regulatory factors, we need the efficient and systematic computational methods. Regulatory circuits have been suggested to behave analogously to the electronic circuits in which a wide variety of electronic elements work coordinately to function correctly. Recently, an increasing amount of next generation sequencing data provides a great resource to study regulatory activity. Thus, we developed a general-purpose computational method using logic-circuit models from electronics and applied it to a human leukemia dataset, identifying the genome-wide cooperativity of transcription factors and microRNAs.

Expanding the logic of bacterial promoters using engineered overlapping operators for global regulators

The understanding of how the architecture of cis-regulatory elements at bacterial promoters determines their final output is of central interest in modern biology. In this work, we attempt to gain insight into this process by analyzing complex promoter architectures in the model organism Escherichia coli. By focusing on the relationship between different TFs at the genomic scale in terms of their binding site arrangement and their effect on the target promoters, we found no strong constraint limiting the combinatorial assembly of TF pairs in E. coli. More strikingly, overlapping binding sites were found equally associated with both equivalent (both TFs have the same effect on the promoter) and opposite (one TF activates while the other repress the promoter) effects on gene expression. With this information on hand, we set an in silico approach to design overlapping sites for three global regulators (GRs) of E. coli, specifically CRP, Fis, and IHF. Using random sequence assembly and an evolutionary algorithm, we were able to identify potential overlapping operators for all TF pairs. In order to validate our prediction, we constructed two lac promoter variants containing overlapping sites for CRP and IHF designed in silico. By assaying the synthetic promoters using a GFP reporter system, we demonstrated that these variants were functional and activated by CRP and IHF in vivo. Taken together, presented results add new information on the mechanisms of signal integration in bacterial promoters and provide new strategies for the engineering of synthetic regulatory circuits in bacteria.

A Novel Synthesizing Genetic Logic Circuit: Frequency Multiplier

This paper presents a novel synthesizing genetic logic circuit design based on an existing synthetic genetic oscillator, which provides a function of frequency multiplier to synthesize a clock signal whose frequency is a multiple of that of the genetic oscillator. In the renowned literature, the synthetic genetic oscillator, known as a repressilator, has been successfully built in Escherichia coli to generate a periodic oscillating phenomenon through three repressive genes repress each other in a chain. On the basis of this fact, our proposed genetic frequency multiplier circuit utilizes genetic Buffers in series with a waveform-shaping circuit to reshape the genetic oscillation signal into a crisp logic clock signal. By regulating different threshold levels in the Buffer, the time length of logic high/low levels in a fundamental sinusoidal wave can be engineered to pulse-width-modulated (PWM) signals with various duty cycles. Integrating some of genetic logic XOR gates and PWM signals from the output of the Buffers, a genetic frequency multiplier circuit can be created and the clock signal with the integer-fold of frequency of the genetic oscillator is generated. The synthesized signal can be used in triggering the downstream digital genetic logic circuits. Simulation results show the applicability of the proposed idea.

Synthesizing genetic sequential logic circuit with clock pulse generator

Background

Rhythmic clock widely occurs in biological systems which controls several aspects of cell physiology. For the different cell types, it is supplied with various rhythmic frequencies. How to synthesize a specific clock signal is a preliminary but a necessary step to further development of a biological computer in the future.

Results

This paper presents a genetic sequential logic circuit with a clock pulse generator based on a synthesized genetic oscillator, which generates a consecutive clock signal whose frequency is an inverse integer multiple to that of the genetic oscillator. An analogous electronic waveform-shaping circuit is constructed by a series of genetic buffers to shape logic high/low levels of an oscillation input in a basic sinusoidal cycle and generate a pulse-width-modulated (PWM) output with various duty cycles. By controlling the threshold level of the genetic buffer, a genetic clock pulse signal with its frequency consistent to the genetic oscillator is synthesized. A synchronous genetic counter circuit based on the topology of the digital sequential logic circuit is triggered by the clock pulse to synthesize the clock signal with an inverse multiple frequency to the genetic oscillator. The function acts like a frequency divider in electronic circuits which plays a key role in the sequential logic circuit with specific operational frequency.

Conclusions

A cascaded genetic logic circuit generating clock pulse signals is proposed. Based on analogous implement of digital sequential logic circuits, genetic sequential logic circuits can be constructed by the proposed approach to generate various clock signals from an oscillation signal.

Engineering multicellular logic in bacteria with metabolic wires

Aromatic biodegradation pathways of environmental bacteria are vast sources of matching trios of enzymes, substrates and regulators that can be refactored to run logic operations through cell-to-cell communication. As a proof of concept, the connection between two Pseudomonas putida strains using benzoic acid as the wiring molecule is presented. In this system, a sender strain harboring the TOL pathway for biodegradation of aromatics processed toluene as input and generated benzoate as the output signal. Diffusion of such metabolic intermediate to the medium was then sensed by a second strain (the receiver) that used benzoate as input for a new logic gate producing a visual output (i.e., light emission). The setup was functional irrespective of whether sender and receiver cells were in direct contact or in liquid culture. These results highlight the potential of environmental metabolic pathways as sources of building blocks for the engineering of multicellular logic in prokaryotic systems.

In silico design and in vivo implementation of yeast gene Boolean gates

In our previous computational work, we showed that gene digital circuits can be automatically designed in an electronic fashion. This demands, first, a conversion of the truth table into Boolean formulas with the Karnaugh map method and, then, the translation of the Boolean formulas into circuit schemes organized into layers of Boolean gates and Pools of signal carriers. In our framework, gene digital circuits that take up to three different input signals (chemicals) arise from the composition of three kinds of basic Boolean gates, namely YES, NOT, and AND. Here we present a library of YES, NOT, and AND gates realized via plasmidic DNA integration into the yeast genome. Boolean behavior is reproduced via the transcriptional control of a synthetic bipartite promoter that contains sequences of the yeast VPH1 and minimal CYC1 promoters together with operator binding sites for bacterial (i.e. orthogonal) repressor proteins. Moreover, model-driven considerations permitted us to pinpoint a strategy for re-designing gates when a better digital performance is required. Our library of well-characterized Boolean gates is the basis for the assembly of more complex gene digital circuits. As a proof of concepts, we engineered two 2-input OR gates, designed by our software, by combining YES and NOT gates present in our library.

Expanding the boolean logic of the prokaryotic transcription factor XylR by functionalization of permissive sites with a protease-target sequence

The σ54-dependent prokaryotic regulator XylR implements a one-input/one-output actuator that transduces the presence of the aromatic effector m-xylene into transcriptional activation of the cognate promoter Pu. Such a signal conversion involves the effector-mediated release of the intramolecular repression of the N-terminal A domain on the central C module of XylR. On this background, we set out to endow this regulator with additional signal-sensing capabilities by inserting a target site of the viral protease NIa in permissive protein locations that once cleaved in vivo could either terminate XylR activity or generate an effector-independent, constitutive transcription factor. To find optimal protein positions to this end, we saturated the xylR gene DNA with a synthetic transposable element designed for randomly delivering in-frame polypeptides throughout the sequence of any given protein. This Tn5-based system supplies the target gene with insertions of a selectable marker that can later be excised, leaving behind the desired (poly) peptides grafted into the protein structure. Implementation of such knock-in-leave-behind (KILB) method to XylR was instrumental to produce a number of variants of this transcription factor (TF) that could compute in vivo two inputs (m-xylene and protease) into a single output following a logic that was dependent on the site of the insertion of the NIa target sequence in the TF. Such NIa-sensitive XylR specimens afforded the design of novel regulatory nodes that entered protease expression as one of the signals recognized in vivo for controlling Pu. This approach is bound to facilitate the functionalization of TFs and other proteins with new traits, especially when their forward engineering is made difficult by, for example, the absence of structural data.

A visual dual-aptamer logic gate for sensitive discrimination of prion diseases-associated isoform with reusable magnetic microparticles and fluorescence quantum dots

Molecular logic gates, which have attracted increasing research interest and are crucial for the development of molecular-scale computers, simplify the results of measurements and detections, leaving the diagnosis of disease either "yes" or "no". Prion diseases are a group of fatal neurodegenerative disorders that happen in human and animals. The main problem with a diagnosis of prion diseases is how to sensitively and selectively discriminate and detection of the minute amount of PrP(Res) in biological samples. Our previous work had demonstrated that dual-aptamer strategy could achieve highly sensitive and selective discrimination and detection of prion protein (cellular prion protein, PrP(C), and the diseases associated isoform, PrP(Res)) in serum and brain. Inspired by the advantages of molecular logic gate, we further conceived a new concept for dual-aptamer logic gate that responds to two chemical input signals (PrP(C) or PrP(Res) and Gdn-HCl) and generates a change in fluorescence intensity as the output signal. It was found that PrP(Res) performs the "OR" logic operation while PrP(C) performs "XOR" logic operation when they get through the gate consisted of aptamer modified reusable magnetic microparticles (MMPs-Apt1) and quantum dots (QDs-Apt2). The dual-aptamer logic gate simplifies the discrimination results of PrP(Res), leaving the detection of PrP(Res) either "yes" or "no". The development of OR logic gate based on dual-aptamer strategy and two chemical input signals (PrP(Res) and Gdn-HCl) is an important step toward the design of prion diseases diagnosis and therapy systems.

Engineered riboswitches: Expanding researchers' toolbox with synthetic RNA regulators

Riboswitches are natural RNA-based genetic switches that sense small-molecule metabolites and regulate in response the expression of the corresponding metabolic genes. Within the last years, several engineered riboswitches have been developed that act on various stages of gene expression. These switches can be engineered to respond to any ligand of choice and are therefore of great interest for synthetic biology. In this review, we present an overview of engineered riboswitches and discuss their application in conditional gene expression systems. We will provide structural and mechanistic insights and point out problems and recent trends in the development of engineered riboswitches.

Functionalization of whole-cell bacterial reporters with magnetic nanoparticle

We developed a biocompatible and highly efficient approach for functionalization of bacterial cell wall with magnetic nanoparticles (MNPs). Three Acinetobacter baylyi ADP1 chromosomally based bioreporters, which were genetically engineered to express bioluminescence in response to salicylate, toluene/xylene and alkanes, were functionalized with 18 ± 3 nm iron oxide MNPs to acquire magnetic function. The efficiency of MNPs functionalization of Acinetobacter bioreporters was 99.96 ± 0.01%. The MNPs‐functionalized bioreporters (MFBs) can be remotely controlled and collected by an external magnetic field. The MFBs were all viable and functional as good as the native cells in terms of sensitivity, specificity and quantitative response. More importantly, we demonstrated that salicylate sensing MFBs can be applied to sediments and garden soils, and semi‐quantitatively detect salicylate in those samples by discriminably recovering MFBs with a permanent magnet. The magnetically functionalized cells are especially useful to complex environments in which the indigenous cells, particles and impurities may interfere with direct measurement of bioreporter cells and conventional filtration is not applicable to distinguish and harvest bioreporters. The approach described here provides a powerful tool to remotely control and selectively manipulate MNPs‐functionalized cells in water and soils. It would have a potential in the application of environmental microbiology, such as bioremediation enhancement and environment monitoring and assessment.

Implementing conventional logic unconventionally: photochromic molecular populations as registers and logic gates

In this paper we detail experimental methods to implement registers, logic gates and logic circuits using populations of photochromic molecules exposed to sequences of light pulses. Photochromic molecules are molecules with two or more stable states that can be switched reversibly between states by illuminating with appropriate wavelengths of radiation. Registers are implemented by using the concentration of molecules in each state in a given sample to represent an integer value. The register's value can then be read using the intensity of a fluorescence signal from the sample. Logic gates have been implemented using a register with inputs in the form of light pulses to implement 1-input/1-output and 2-input/1-output logic gates. A proof of concept logic circuit is also demonstrated; coupled with the software workflow describe the transition from a circuit design to the corresponding sequence of light pulses.

Competition for catalytic resources alters biological network dynamics

Genetic regulation networks orchestrate many complex cellular behaviors. Dynamic operations that take place within cells are thus dependent on the gene expression machinery, enabled by powerful enzymes such as polymerases, ribosomes, or nucleases. These generalist enzymes typically process many different substrates, potentially leading to competitive situations: by saturating the common enzyme, one substrate may down-regulate its competitors. However, most theoretical or experimental models simply omit these effects, focusing on the pattern of genetic regulatory interactions as the main determinant of network function. We show here that competition effects have important outcomes, which can be spotted within the global dynamics of experimental systems. Further we demonstrate that enzyme saturation creates a layer of cross couplings that may foster, but also hamper, the expected behavior of synthetic biology constructs.

Implementing an OR-NOT (ORN) logic gate with components of the SOS regulatory network of Escherichia coli

Whether biological or electronic, man-engineered computation is based on logic circuits assembled with binary gates that are interconnected to perform Boolean operations. We report here the rewiring of the SOS system of Escherichia in a fashion that makes the output of both the recA and lexA promoters to faithfully follow the pattern of a binary composite OR-NOT gate (ORN) in which the inputs are DNA damage (e.g. nalidixic acid addition) and IPTG as an exogenous signal. Unlike other non-natural gates whose implementation requires changes in genes and promoters of the genome of the host cells, this ORN was brought about by the sole addition of wild-type bacteria with a plasmid encoding a module for LacI(q)-dependent expression of lexA. Specifically, we demonstrate that the interplay between native, chromosomally-encoded components of the SOS system and the extra parts engineered in such a plasmid made the desired performance to happen without any modification of the core DNA-damage response network. It is thus possible to artificially interface autonomous cell networks with a predetermined logic by means of Boolean gates built with regulatory elements already functioning in the recipient organism.

The logicome of environmental bacteria: merging catabolic and regulatory events with Boolean formalisms

The regulatory and metabolic networks that rule biodegradation of pollutants by environmental bacteria are wired to the rest of the cellular physiology through both transcriptional factors and intermediary signal molecules. In this review, we examine some formalisms for describing catalytic/regulatory circuits of this sort and advocate the adoption of Boolean logic for combining transcriptional and enzymatic occurrences in the same biological system. As an example, we show how known regulatory and metabolic actions that bring about biodegradation of m-xylene by Pseudomonas putida mt-2 can be represented as clusters of binary operations and then reconstructed as a digital network. Despite the many simplifications, Boolean tools still capture the gross behaviour of the system even in the absence of kinetic constants determined experimentally. On this basis, we argue that still with a limited volume of data binary formalisms allow us to penetrate the raison d'être of extant regulatory and metabolic architectures.

Automatic design of digital synthetic gene circuits

De novo computational design of synthetic gene circuits that achieve well-defined target functions is a hard task. Existing, brute-force approaches run optimization algorithms on the structure and on the kinetic parameter values of the network. However, more direct rational methods for automatic circuit design are lacking. Focusing on digital synthetic gene circuits, we developed a methodology and a corresponding tool for in silico automatic design. For a given truth table that specifies a circuit's input–output relations, our algorithm generates and ranks several possible circuit schemes without the need for any optimization. Logic behavior is reproduced by the action of regulatory factors and chemicals on the promoters and on the ribosome binding sites of biological Boolean gates. Simulations of circuits with up to four inputs show a faithful and unequivocal truth table representation, even under parametric perturbations and stochastic noise. A comparison with already implemented circuits, in addition, reveals the potential for simpler designs with the same function. Therefore, we expect the method to help both in devising new circuits and in simplifying existing solutions.

Synthetic Biology is a novel discipline that aims at the construction of new biological systems able to perform specific tasks. Following the example of electrical engineering, most of the synthetic systems so far realized look like circuits where smaller DNA-encoded components are interconnected by the exchange of different kinds of molecules. According to this modular approach, we developed, in a previous work, a tool for the visual design of new genetic circuits whose components are displayed on the computer screen and connected through hypothetical wires where molecules flow. Here, we present an extension of this tool that automatically computes the structure of a digital gene circuit–where the inputs and the output take only 0/1 values–by applying procedures commonly used in electrical engineering to biology. In this way, our method generalizes and simplifies the design of genetic circuits far more complex than the ones so far realized. Moreover, different from other currently used methods, our approach limits the use of optimization procedures and drastically reduces the computational time necessary to derive the circuit structure. Future improvements can be achieved by exploiting some more biological mechanisms able to mimic Boolean behavior, without a substantial growth of the algorithmic complexity.

Design and connection of robust genetic circuits

Phenotypic robustness is a highly sought after goal for synthetic biology. There are many well-studied examples of robust systems in biology, and for the advancement of synthetic biology, particularly in performance-critical applications, fundamental understanding of how robustness is both achieved and maintained is very important. A synthetic circuit may fail to behave as expected for a multitude of reasons, and since many of these failures are difficult to predict a priori, a better understanding of a circuit's behavior as well as its possible failures are needed. In this chapter, we outline work that has been done in developing design principles for robust synthetic circuits, as well as sharing our experiences designing and constructing gene circuits.

Regulatory exaptation of the catabolite repression protein (Crp)-cAMP system in Pseudomonas putida

The genome of the soil bacterium Pseudomonas putida KT2440 encodes singular orthologues of genes crp (encoding the catabolite repression protein, Crp) and cyaA (adenylate cyclase) of Escherichia coli. The levels of cAMP formed by P. putida cells were below detection with a Dictyostelium biosensor in vivo. The cyaA(P. putida) gene was transcribed in vivo but failed to complement the lack of maltose consumption of a cyaA mutant of E. coli, thereby indicating that cyaA(P. putida) was poorly translated or rendered non-functional in the heterologous host. Yet, generation of cAMP by CyaA(P. putida) could be verified by expressing the cyaA(P. putida) gene in a hypersensitive E. coli strain. On the other hand, the crp(P. putida) gene restored the metabolic capacities of an equivalent crp mutant of E. coli, but not in a double crp/cyaA strain, suggesting that the ability to regulate such functions required cAMP. In order to clarify the breadth of the Crp/cAMP system in P. putida, crp and cyaA mutants were generated and passed through a battery of phenotypic tests for recognition of gross metabolic properties and stress-endurance abilities. These assays revealed that the loss of each gene led in most (but not all) cases to the same phenotypic behaviour, indicating a concerted functionality. Unexpectedly, none of the mutations affected the panel of carbon compounds that can be used by P. putida as growth substrates, the mutants being impaired only in the use of various dipeptides as N sources. Furthermore, the lack of crp or cyaA had little influence on the gross growth fingerprinting of the cells. The poor physiological profile of the Crp-cAMP system of P. putida when compared with E. coli exposes a case of regulatory exaptation, i.e. the process through which a property evolved for a particular function is co-opted for a new use.

Mechanisms and evolution of control logic in prokaryotic transcriptional regulation

A major part of organismal complexity and versatility of prokaryotes resides in their ability to fine-tune gene expression to adequately respond to internal and external stimuli. Evolution has been very innovative in creating intricate mechanisms by which different regulatory signals operate and interact at promoters to drive gene expression. The regulation of target gene expression by transcription factors (TFs) is governed by control logic brought about by the interaction of regulators with TF binding sites (TFBSs) in cis-regulatory regions. A factor that in large part determines the strength of the response of a target to a given TF is motif stringency, the extent to which the TFBS fits the optimal TFBS sequence for a given TF. Advances in high-throughput technologies and computational genomics allow reconstruction of transcriptional regulatory networks in silico. To optimize the prediction of transcriptional regulatory networks, i.e., to separate direct regulation from indirect regulation, a thorough understanding of the control logic underlying the regulation of gene expression is required. This review summarizes the state of the art of the elements that determine the functionality of TFBSs by focusing on the molecular biological mechanisms and evolutionary origins of cis-regulatory regions.