Construction of Two-Input Logic Gates Using Transcriptional Interference

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.

When push comes to shove - RNA polymerase and DNA-bound protein roadblocks

In recent years, transcriptional roadblocking has emerged as a crucial regulatory mechanism in gene expression, whereby other DNA-bound obstacles can block the progression of transcribing RNA polymerase (RNAP), leading to RNAP pausing and ultimately dissociation from the DNA template. In this review, we discuss the mechanisms by which transcriptional roadblocks can impede RNAP progression, as well as how RNAP can overcome these obstacles to continue transcription. We examine different DNA-binding proteins involved in transcriptional roadblocking and their biophysical properties that determine their effectiveness in blocking RNAP progression. The catalytically dead CRISPR-Cas (dCas) protein is used as an example of an engineered programmable roadblock, and the current literature in understanding the polarity of dCas roadblocking is also discussed. Finally, we delve into a stochastic model of transcriptional roadblocking and highlight the importance of transcription factor binding kinetics and its resistance to dislodgement by an elongating RNAP in determining the strength of a roadblock.

A blueprint for a synthetic genetic feedback optimizer

Biomolecular control enables leveraging cells as biomanufacturing factories. Despite recent advancements, we currently lack genetically encoded modules that can be deployed to dynamically fine-tune and optimize cellular performance. Here, we address this shortcoming by presenting the blueprint of a genetic feedback module to optimize a broadly defined performance metric by adjusting the production and decay rate of a (set of) regulator species. We demonstrate that the optimizer can be implemented by combining available synthetic biology parts and components, and that it can be readily integrated with existing pathways and genetically encoded biosensors to ensure its successful deployment in a variety of settings. We further illustrate that the optimizer successfully locates and tracks the optimum in diverse contexts when relying on mass action kinetics-based dynamics and parameter values typical in Escherichia coli.

Transcription factor-based biosensors for screening and dynamic regulation

Advances in synthetic biology and genetic engineering are bringing into the spotlight a wide range of bio-based applications that demand better sensing and control of biological behaviours. Transcription factor (TF)-based biosensors are promising tools that can be used to detect several types of chemical compounds and elicit a response according to the desired application. However, the wider use of this type of device is still hindered by several challenges, which can be addressed by increasing the current metabolite-activated transcription factor knowledge base, developing better methods to identify new transcription factors, and improving the overall workflow for the design of novel biosensor circuits. These improvements are particularly important in the bioproduction field, where researchers need better biosensor-based approaches for screening production-strains and precise dynamic regulation strategies. In this work, we summarize what is currently known about transcription factor-based biosensors, discuss recent experimental and computational approaches targeted at their modification and improvement, and suggest possible future research directions based on two applications: bioproduction screening and dynamic regulation of genetic circuits.

Design of Gene Boolean Gates and Circuits with Convergent Promoters

Gene digital circuits are the subject of many research works due to their various potential applications, from hazard detection to medical diagnostic. Moreover, a remarkable number of techniques, developed in electronics, can be used for the construction of biological digital systems. In our previous works, we showed how to automatize the design and modeling of gene digital circuits whose gates were based on transcription and translation regulation. In this chapter, we illustrate how Boolean gates could be implemented by following a particular architecture, the convergent promoter one, rather diffuse in nature but seldom adopted in Synthetic Biology. Beside gate design, we also explain how to extend our previous modeling approach, based on composable parts and pools of molecules, to quantitatively describe and simulate this particular kind of digital biological devices.

Two-input protein logic gate for computation in living cells

Advances in protein design have brought us within reach of developing a nanoscale programming language, in which molecules serve as operands and their conformational states function as logic gates with precise input and output behaviors. Combining these nanoscale computing agents into larger molecules and molecular complexes will allow us to write and execute "code". Here, in an important step toward this goal, we report an engineered, single protein design that is allosterically regulated to function as a 'two-input logic OR gate'. Our system is based on chemo- and optogenetic regulation of focal adhesion kinase. In the engineered FAK, all of FAK domain architecture is retained and key intramolecular interactions between the kinase and the FERM domains are externally controlled through a rapamycin-inducible uniRapR module in the kinase domain and a light-inducible LOV2 module in the FERM domain. Orthogonal regulation of protein function was possible using the chemo- and optogenetic switches. We demonstrate that dynamic FAK activation profoundly increased cell multiaxial complexity in the fibrous extracellular matrix microenvironment and decreased cell motility. This work provides proof-of-principle for fine multimodal control of protein function and paves the way for construction of complex nanoscale computing agents.

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.

Coinducible Catabolism of 1-Naphthol via Synergistic Regulation of the Initial Hydroxylase Genes in Sphingobium sp. Strain B2

1-Naphthol, a widely used raw material for organic synthesis, is also a well-known organic pollutant. Due to its high toxicity, 1-naphthol is rarely used by microorganisms as the sole carbon source for growth. In this study, catabolism of 1-naphthol by Sphingobium sp. strain B2 was found to be greatly enhanced by additional supplementation with primary carbon sources (e.g., glucose, maltose, and sucrose), and 1-naphthol was even used as the carbon source for growth when strain B2 cells had been preinduced by both 1-naphthol and glucose. A distinct two-component flavin-dependent monooxygenase, NdcA1A2, was found to be responsible for the initial hydroxylation of 1-naphthol to 1,2-dihydroxynaphthalene, a more toxic compound. Transcriptional levels of ndcA1A2 genes were significantly upregulated when strain B2 cells were cultured with both 1-naphthol and glucose compared to cells cultured with only 1-naphthol or glucose. Two transcriptional regulators, the activator NdcS and the inhibitor NdcR, were found to play key roles in the synergistic regulation of the transcription of the 1-naphthol initial catabolism genes ndcA1A2 IMPORTANCE Cometabolism is a widely observed phenomenon, especially in the field of microbial catabolism of highly toxic xenobiotics. However, the mechanisms of cometabolism are ambiguous, and the roles of the obligately coexisting growth substrates remain largely unknown. In this study, we revealed that the roles of the coexisting primary carbon sources (e.g., glucose) in the enhanced catabolism of the toxic compound 1-naphthol in Sphingobium sp. strain B2 were not solely because they were used as growth substrates to support cell growth but, more importantly, because they acted as coinducers to interact with two transcriptional regulators, the activator NdcS and the inhibitor NdcR, to synergistically regulate the transcription of the 1-naphthol initial catabolism genes ndcA1A2 Our findings provide new insights into the cometabolic mechanism of highly toxic compounds in microorganisms.

Engineering Transcriptional Interference through RNA Polymerase Processivity Control

Antisense transcription is widespread in all kingdoms of life and has been shown to influence gene expression through transcriptional interference (TI), a phenomenon in which one transcriptional process negatively influences another in cis. The processivity, or uninterrupted transcription, of an RNA polymerase (RNAP) is closely tied to levels of antisense transcription in bacterial genomes, but its influence on TI, while likely important, is not well-characterized. Here, we show that TI can be tuned through processivity control via three distinct antitermination strategies: the antibiotic bicyclomycin, phage protein Psu, and ribosome-RNAP coupling. We apply these methods toward TI and tune ribosome-RNAP coupling to produce 38-fold transcription-level gene repression due to both RNAP collisions and antisense RNA interference. We then couple protein roadblock and TI to design minimal genetic NAND and NOR logic gates. Together, these results show the importance of processivity control for strong TI and demonstrate TI's potential for synthetic biology.

Facile accelerated specific therapeutic (FAST) platform develops antisense therapies to counter multidrug-resistant bacteria

Multidrug-resistant (MDR) bacteria pose a grave concern to global health, which is perpetuated by a lack of new treatments and countermeasure platforms to combat outbreaks or antibiotic resistance. To address this, we have developed a Facile Accelerated Specific Therapeutic (FAST) platform that can develop effective peptide nucleic acid (PNA) therapies against MDR bacteria within a week. Our FAST platform uses a bioinformatics toolbox to design sequence-specific PNAs targeting non-traditional pathways/genes of bacteria, then performs in-situ synthesis, validation, and efficacy testing of selected PNAs. As a proof of concept, these PNAs were tested against five MDR clinical isolates: carbapenem-resistant Escherichia coli, extended-spectrum beta-lactamase Klebsiella pneumoniae, New Delhi Metallo-beta-lactamase-1 carrying Klebsiella pneumoniae, and MDR Salmonella enterica. PNAs showed significant growth inhibition for 82% of treatments, with nearly 18% of treatments leading to greater than 97% decrease. Further, these PNAs are capable of potentiating antibiotic activity in the clinical isolates despite presence of cognate resistance genes. Finally, the FAST platform offers a novel delivery approach to overcome limited transport of PNAs into mammalian cells by repurposing the bacterial Type III secretion system in conjunction with a kill switch that is effective at eliminating 99.6% of an intracellular Salmonella infection in human epithelial cells.

Eller et al. develop a Facile Accelerated Specific Therapeutic (FAST) platform of antisense therapeutics that targets MDR bacterial pathogens with peptide nucleic acids (PNAs). This platform designs species and/or sequence specific PNAS based on a bioinformatics toolbox and offers a new delivery approach by repurposing the bacterial Type III secretion system in conjunction with a kill switch to overcome limited transport of PNAs into mammalian cells.

Third Generation Whole-Cell Sensing Systems: Synthetic Biology Inside, Nanomaterial Outside

Whole-cell sensing systems (WCSSs) are highly anticipated in the field of on-site detection. However, due to their low specificity, poor stability, and potential environmental problems, their commercial application is unrealistic. Recently, synthetic biology and nanomaterials have provided potential solutions to these problems, propelling WCSSs into a new generation. Synthetic biology provides a complete solution for the intelligent design and assembly of elements, modules, and genetic circuits. Nanomaterials covering the exterior of the cells provide stable protection, remote control capability, and catalytic ability for the WCSSs, and they can limit the horizontal transfer of genetic elements. These advancements enable personalized customization, intelligent control, and self-destruction in the next generation of cell sensors, promoting their industrialization.