Low-cost arabinose induced genetic circuit for protein production: Modeling.

A low-cost reagent-producing genetic circuit was designed during this work. Its functioning is based on a positive feedback loop induced by a small amount of arabinose, allowing users to obtain reactants in a safe, constant, and controlled manner. The design-only approach to the project allows us to work in different kinds of computational models, thus, an ODE-based model was thoroughly developed and a cellular automata-based one was experimented with. Working on the ODE model, equilibrium states and system stability were studied. Circuit properties were also focused on one of which was a high concentration of interest protein produced by low inductor inputs. As a result, a mathematical expression capable of describing the quantity of produced reagent was obtained. In addition, the cellular automata model offers a new perspective, given its differences from the ODE model e.g. this type of model is a stochastic analysis and describes each cell individually instead of describing the whole cellular population.

Light-induced Patterning of Electroactive Bacterial Biofilms

Electroactive bacterial biofilms can function as living biomaterials that merge the functionality of living cells with electronic components. However, the development of such advanced living electronics has been challenged by the inability to control the geometry of electroactive biofilms relative to solid-state electrodes. Here, we developed a lithographic strategy to pattern conductive biofilms of Shewanella oneidensis by controlling aggregation protein CdrAB expression with a blue light-induced genetic circuit. This controlled deposition enabled S. oneidensis biofilm patterning on transparent electrode surfaces and measurements demonstrated tunable biofilm conduction dependent on pattern size. Controlling biofilm geometry also enabled us, for the first time, to quantify the intrinsic conductivity of living S. oneidensis biofilms and experimentally confirm predictions based on simulations of a recently proposed collision-exchange electron transport mechanism. Overall, we developed a facile technique for controlling electroactive biofilm formation on electrodes, with implications for both studying and harnessing bioelectronics.

Transcription factor competition facilitates self-sustained oscillations in single gene genetic circuits

Genetic feedback loops can be used by cells as a means to regulate internal processes or keep track of time. It is often thought that, for a genetic circuit to display self-sustained oscillations, a degree of cooperativity is needed in the binding and unbinding of actor species. This cooperativity is usually modeled using a Hill function, regardless of the actual promoter architecture. Moreover, genetic circuits do not operate in isolation and often transcription factors are shared between different promoters. In this work we show how mathematical modelling of genetic feedback loops can be facilitated with a mechanistic fold-change function that takes into account the titration effect caused by competing binding sites for transcription factors. The model shows how the titration effect aids self-sustained oscillations in a minimal genetic feedback loop: a gene that produces its own repressor directly — without cooperative transcription factor binding. The use of delay- differential equations leads to a stability contour that predicts whether a genetic feedback loop will show self-sustained oscillations, even when taking the bursty nature of transcription into account.

SYMBIOSIS: Synthetic Manipulable Biobricks via Orthogonal Serine Integrase Systems

Serine integrases are emerging as one of the most powerful biological tools for synthetic biology. They have been widely used across genome engineering and genetic circuit design. However, developing serine integrase-based tools for directly/precisely manipulating synthetic biobricks is still missing. Here, we report SYMBIOSIS, a versatile method that can robustly manipulate DNA parts in vivo and in vitro. First, we proposed a "Keys match Locks" model to demonstrate that three orthogonal serine integrases are able to irreversibly and stably switch on seven synthetic biobricks with high accuracy in vivo. Then, we demonstrated that purified integrases can facilitate the assembly of "Donor" and "Acceptor" plasmids in vitro to construct composite plasmids. Finally, we used SYMBIOSIS to assemble different chromoprotein genes and create novel colored Escherichia coli. We anticipate that our SYMBIOSIS strategy will accelerate synthetic biobricks manipulation, genetic circuit design, and multiple plasmids assembly for synthetic biology with broad potential applications.

Golden Gate Assembly of Aerobic and Anaerobic Microbial Bioreporters

Microbial bioreporters provide direct insight into cellular processes by producing a quantifiable signal dictated by reporter gene expression. The core of a bioreporter is a genetic circuit in which a reporter gene (or operon) is fused to promoter and regulatory sequences that govern its expression. In this study, we develop a system for constructing novel Escherichia coli bioreporters based on Golden Gate assembly, a synthetic biology approach for the rapid and seamless fusion of DNA fragments. Gene circuits are generated by fusing promoter and reporter sequences encoding yellow fluorescent protein, mCherry, bacterial luciferase, and an anaerobically active flavin-based fluorescent protein. We address a barrier to the implementation of Golden Gate assembly by designing a series of compatible destination vectors that can accommodate the assemblies. We validate the approach by measuring the activity of constitutive bioreporters and mercury and arsenic biosensors in quantitative exposure assays. We also demonstrate anaerobic quantification of mercury and arsenic in biosensors that produce flavin-based fluorescent protein, highlighting the expanding range of redox conditions that can be examined by microbial bioreporters. IMPORTANCE Microbial bioreporters are versatile genetic tools with wide-ranging applications, particularly in the field of environmental toxicology. For example, biosensors that produce a signal output in the presence of a specific analyte offer less costly alternatives to analytical methods for the detection of environmental toxins such as mercury and arsenic. Biosensors of specific toxins can also be used to test hypotheses regarding mechanisms of uptake, toxicity, and biotransformation. In this study, we develop an assembly platform that uses a synthetic biology technique to streamline construction of novel Escherichia coli bioreporters that produce fluorescent or luminescent signals either constitutively or in response to mercury and arsenic exposure. Beyond the synthesis of novel biosensors, our assembly platform can be adapted for numerous applications, including labelling bacteria for fluorescent microscopy, developing gene expression systems, and modifying bacterial genomes.

Root Patterning: Tuning SHORT ROOT Function Creates Diversity in Form

Roots have a fundamental role in plant growth and adaptation to different environments. Diversity in root morphology and architecture enables plants to acquire water and nutrients in contrasting substrate conditions, resist biotic and abiotic stress, and develop symbiotic associations. At its most fundamental level, morphology is determined by discrete changes in tissue patterning. Differences in the number and arrangement of the cell layers in the root can change tissue structure, as well as root length and girth, affecting important productivity traits. Therefore, understanding the molecular mechanisms controlling variation in developmental patterning is an important goal in biology. The ground tissue (GT) system is an ideal model to study the genetic basis of morphological diversity because it displays great interspecific variability in cell layer number. In addition, the genetic circuit controlling GT patterning in Arabidopsis thaliana has been well described, although little is known about species with more complex root anatomies. In this review, we will describe the Arabidopsis model for root radial patterning and present recent progress in elucidating the genetic circuitry controlling GT patterning in monocots and the legume Medicago truncatula (Mt), species that develop roots with more complex anatomies and multilayered cortex.

Transcriptional interference in toehold switch-based RNA circuits

Gene regulation based on regulatory RNA is an important mechanism in cells and is increasingly used for regulatory circuits in synthetic biology. Toehold switches are rationally designed post-transcriptional riboregulators placed in the 5' untranslated region of mRNA molecules. In the inactive state of a toehold switch, the ribosome-binding site is inaccessible for the ribosome. In the presence of a trigger RNA molecule protein production is turned on. Using antisense RNA against trigger molecules (anti-trigger RNA), gene expression can also be switched off again. We here study the utility and regulatory effect of antisense transcription in this context, which enables a particularly compact circuit design. Our circuits utilize two inducible promoters that separately regulate trigger and anti-trigger transcription, whereas their cognate toehold switch, regulating expression of a reporter protein, is transcribed from a constitutive promoter. We explore various design options for the arrangement of the promoters and demonstrate that the resulting dynamic behavior is strongly influenced by transcriptional interference (TI) effects, leading to more than four-fold differences in expression levels. Our experimental results are consistent with previous findings that enhanced local RNA polymerase concentrations due to active promoters in close proximity lead to an increase in transcriptional activity of the strongest promoter in the circuits. Based on this insight, we selected optimum promoter designs and arrangements for the realization of a genetic circuit comprised of two toehold switches, two triggers and two anti-triggers that function as a post-transcriptional RNA regulatory exclusive OR (XOR) gate.

Data-driven network models for genetic circuits from time-series data with incomplete measurements

Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro , due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements of state dynamics. We develop a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a previously reported in vitro genetic circuit and a new E. coli -based transcriptional event detector.