Rule-based design of synthetic transcription factors in eukaryotes

The art of designed coiled-coils for the regulation of mammalian cells

Synthetic biology aims to engineer complex biological systems using modular elements, with coiled-coil (CC) dimer-forming modules are emerging as highly useful building blocks in the regulation of protein assemblies and biological processes. Those small modules facilitate highly specific and orthogonal protein-protein interactions, offering versatility for the regulation of diverse biological functions. Additionally, their design rules enable precise control and tunability over these interactions, which are crucial for specific applications. Recent advancements showcase their potential for use in innovative therapeutic interventions and biomedical applications. In this review, we discuss the potential of CCs, exploring their diverse applications in mammalian cells, such as synthetic biological circuit design, transcriptional and allosteric regulation, cellular assemblies, chimeric antigen receptor (CAR) T cell regulation, and genome editing and their role in advancing the understanding and regulation of cellular processes.

Synthetic gene circuit evolution: Insights and opportunities at the mid-scale

Directed evolution focuses on optimizing single genetic components for predefined engineering goals by artificial mutagenesis and selection. In contrast, experimental evolution studies the adaptation of entire genomes in serially propagated cell populations, to provide an experimental basis for evolutionary theory. There is a relatively unexplored gap at the middle ground between these two techniques, to evolve in vivo entire synthetic gene circuits with nontrivial dynamic function instead of single parts or whole genomes. We discuss the requirements for such mid-scale evolution, with hypothetical examples for evolving synthetic gene circuits by appropriate selection and targeted shuffling of a seed set of genetic components in vivo. Implementing similar methods should aid the rapid generation, functionalization, and optimization of synthetic gene circuits in various organisms and environments, accelerating both the development of biomedical and technological applications and the understanding of principles guiding regulatory network evolution.

Diffusion-Based Generative Network for de Novo Synthetic Promoter Design

Computer-aided promoter design is a major development trend in synthetic promoter engineering. Various deep learning models have been used to evaluate or screen synthetic promoters, but there have been few works on de novo promoter design. To explore the potential ability of generative models in promoter design, we established a diffusion-based generative model for promoter design in Escherichia coli. The model was completely driven by sequence data and could study the essential characteristics of natural promoters, thus generating synthetic promoters similar to natural promoters in structure and component. We also improved the calculation method of FID indicator, using a convolution layer to extract the feature matrix of the promoter sequence instead. As a result, we got an FID equal to 1.37, which meant synthetic promoters have a distribution similar to that of natural ones. Our work provides a fresh approach to de novo promoter design, indicating that a completely data-driven generative model is feasible for promoter design.

Versatile Strategy for the Construction of a Transcription Factor-Based Orthogonal Gene Expression Toolbox in Monascus spp

Gene expression is needed to be conducted in an orthogonal manner and controllable independently from the host's native regulatory system. However, there is a shortage of gene expression regulatory toolboxes that function orthogonally from each other and toward the host. Herein, we developed a strategy based on the mutant library to generate orthogonal gene expression toolboxes. A transcription factor, MaR, located in the Monascus azaphilone biosynthetic gene cluster, was taken as a typical example. Nine DNA-binding residues of MaR were identified by molecular simulation and site-directed mutagenesis. We created five MaR multi-site saturation mutagenesis libraries consisting of 10743 MaR variants on the basis of five cognate promoters. A functional analysis revealed that all five tested promoters were orthogonally regulated by five different MaR variants, respectively. Furthermore, fine gene expression tunability and high signal sensitivity of this toolbox are demonstrated by introducing chemically inducible expression modules, designing synthetic promoter elements, and creating protein-protein interaction between MaRs. This study paves the way for a bottom-up approach to build orthogonal gene expression toolboxes.

EMMA-CAD: Design Automation for Synthetic Mammalian Constructs

Computational design tools are the cornerstone of synthetic biology and have underpinned its rapid development over the past two decades. As the field has matured, the scale of biological investigation has expanded dramatically, and researchers often must rely on computational tools to operate in the high-throughput investigational space. This is especially apparent in the modular design of DNA expression circuits, where complexity is accumulated rapidly. Alongside our automated pipeline for the high-throughput construction of Extensible Modular Mammalian Assembly (EMMA) expression vectors, we recognized the need for an integrated software solution for EMMA vector design. Here we present EMMA-CAD (https://emma.cailab.org), a powerful web-based computer-aided design tool for the rapid design of bespoke mammalian expression vectors. EMMA-CAD features a variety of functionalities, including a user-friendly design interface, automated connector selection underpinned by rigorous computer optimization algorithms, customization of part libraries, and personalized design spaces. Capable of translating vector assembly designs into human- and machine-readable protocols for vector construction, EMMA-CAD integrates seamlessly into our automated EMMA pipeline, hence completing an end-to-end design to production workflow.

Designing synthetic transcription factors: A structural perspective

In this chapter, we discuss different design strategies of synthetic proteins, especially synthetic transcription factors. Design and engineering of synthetic transcription factors is particularly relevant for the need-based manipulation of gene expression. With recent advances in structural biology techniques and with the emergence of other precision biochemical/physical tools, accurate knowledge on structure-function relations is increasingly becoming available. Besides discussing the underlying principles of design, we go through individual cases, especially those involving four major groups of transcription factors-basic leucine zippers, zinc fingers, helix-turn-helix and homeodomains. We further discuss how synthetic biology can come together with structural biology to alter the genetic blueprint of life.

Statistical Design of Experiments for Synthetic Biology

The design and optimization of biological systems is an inherently complex undertaking that requires careful balancing of myriad synergistic and antagonistic variables. However, despite this complexity, much synthetic biology research is predicated on One Factor at A Time (OFAT) experimentation; the genetic and environmental variables affecting the activity of a system of interest are sequentially altered while all other variables are held constant. Beyond being time and resource intensive, OFAT experimentation crucially ignores the effect of interactions between factors. Given the ubiquity of interacting genetic and environmental factors in biology this failure to account for interaction effects in OFAT experimentation can result in the development of suboptimal systems. To address these limitations, an increasing number of studies have turned to Design of Experiments (DoE), a suite of methods that enable efficient, systematic exploration and exploitation of complex design spaces. This review provides an overview of DoE for synthetic biologists. Key concepts and commonly used experimental designs are introduced, and we discuss the advantages of DoE as compared to OFAT experimentation. We dissect the applicability of DoE in the context of synthetic biology and review studies which have successfully employed these methods, illustrating the potential of statistical experimental design to guide the design, characterization, and optimization of biological protocols, pathways, and processes.

Daisy Chain Topology Based Mammalian Synthetic Circuits for RNA-Only Delivery

Owing to superior safety, the RNA-only delivery synthetic circuit is more suitable for cell-based medicine. Modules which possess matching inputs and outputs could be strung by daisy-chaining to compose RNA-only delivery synthetic gene circuits. In this study, we engineered well-characterized biological parts to construct composable modules, each of which could receive signals from the upstream module and transmit the processed signal to the next module using standard interfaces. Capsid-cNOT7, through which logic gates could be changed by merely changing the type of it, was used as the core element for logical process. Daisy chain topology was used to build RNA-only delivery mammalian synthetic circuits which possess validated functions such as fan out, protein sensing, drug sensing, light sensing, 2-input logic gate, 3-input logic gate, and volatile memory, providing a new method to simplify the design of RNA-only delivery synthetic circuits.

Programmable T7-based synthetic transcription factors

Despite recent progress on synthetic transcription factor generation in eukaryotes, there remains a need for high-activity bacterial versions of these systems. In synthetic biology applications, it is useful for transcription factors to have two key features: they should be orthogonal (influencing only their own targets, with minimal off-target effects), and programmable (able to be directed to a wide range of user-specified transcriptional start sites). The RNA polymerase of the bacteriophage T7 has a number of appealing properties for synthetic biological designs: it can produce high transcription rates; it is a compact, single-subunit polymerase that has been functionally expressed in a variety of organisms; and its viral origin reduces the connection between its activity and that of its host's transcriptional machinery. We have created a system where a T7 RNA polymerase is recruited to transcriptional start sites by DNA binding proteins, either directly or bridged through protein–protein interactions, yielding a modular and programmable system for strong transcriptional activation of multiple orthogonal synthetic transcription factor variants in Escherichia coli. To our knowledge this is the first exogenous, programmable activator system in bacteria.

Cellular Biosensors with Engineered Genetic Circuits

An increasing interest in building novel biological devices with designed cellular functionalities has triggered the search of innovative tools for biocomputation. Utilizing the tools of synthetic biology, numerous genetic circuits have been implemented such as engineered logic operation in analog and digital circuits. Whole cell biosensors are widely used biological devices that employ several biocomputation tools to program cells for desired functions. Up to the present date, a wide range of whole-cell biosensors have been designed and implemented for disease theranostics, biomedical applications, and environmental monitoring. In this review, we investigated the recent developments in biocomputation tools such as analog, digital, and mix circuits, logic gates, switches, and state machines. Additionally, we stated the novel applications of biological devices with computing functionalities for diagnosis and therapy of various diseases such as infections, cancer, or metabolic diseases, as well as the detection of environmental pollutants such as heavy metals or organic toxic compounds. Current whole-cell biosensors are innovative alternatives to classical biosensors; however, there is still a need to advance decision making capabilities by developing novel biocomputing devices.

Discovery of cell-type specific DNA motif grammar in cis-regulatory elements using random Forest

Background

It has been observed that many transcription factors (TFs) can bind to different genomic loci depending on the cell type in which a TF is expressed in, even though the individual TF usually binds to the same core motif in different cell types. How a TF can bind to the genome in such a highly cell-type specific manner, is a critical research question. One hypothesis is that a TF requires co-binding of different TFs in different cell types. If this is the case, it may be possible to observe different combinations of TF motifs – a motif grammar – located at the TF binding sites in different cell types. In this study, we develop a bioinformatics method to systematically identify DNA motifs in TF binding sites across multiple cell types based on published ChIP-seq data, and address two questions: (1) can we build a machine learning classifier to predict cell-type specificity based on motif combinations alone, and (2) can we extract meaningful cell-type specific motif grammars from this classifier model.

Results

We present a Random Forest (RF) based approach to build a multi-class classifier to predict the cell-type specificity of a TF binding site given its motif content. We applied this RF classifier to two published ChIP-seq datasets of TF (TCF7L2 and MAX) across multiple cell types. Using cross-validation, we show that motif combinations alone are indeed predictive of cell types. Furthermore, we present a rule mining approach to extract the most discriminatory rules in the RF classifier, thus allowing us to discover the underlying cell-type specific motif grammar.

Conclusions

Our bioinformatics analysis supports the hypothesis that combinatorial TF motif patterns are cell-type specific.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4340-z) contains supplementary material, which is available to authorized users.

Plant-Derived Transcription Factors for Orthologous Regulation of Gene Expression in the Yeast Saccharomyces cerevisiae

Control of gene expression by transcription factors (TFs) is central in many synthetic biology projects for which a tailored expression of one or multiple genes is often needed. As TFs from evolutionary distant organisms are unlikely to affect gene expression in a host of choice, they represent excellent candidates for establishing orthogonal control systems. To establish orthogonal regulators for use in yeast (Saccharomyces cerevisiae), we chose TFs from the plant Arabidopsis thaliana. We established a library of 106 different combinations of chromosomally integrated TFs, activation domains (yeast GAL4 AD, herpes simplex virus VP64, and plant EDLL) and synthetic promoters harboring cognate cis-regulatory motifs driving a yEGFP reporter. Transcriptional output of the different driver/reporter combinations varied over a wide spectrum, with EDLL being a considerably stronger transcription activation domain in yeast than the GAL4 activation domain, in particular when fused to Arabidopsis NAC TFs. Notably, the strength of several NAC-EDLL fusions exceeded that of the strong yeast TDH3 promoter by 6- to 10-fold. We furthermore show that plant TFs can be used to build regulatory systems encoded by centromeric or episomal plasmids. Our library of TF-DNA binding site combinations offers an excellent tool for diverse synthetic biology applications in yeast.

Towards combinatorial transcriptional engineering

The modular nature of the transcriptional unit makes it possible to design robust modules with predictable input-output characteristics using a ‘parts- off a shelf’ approach. Customized regulatory circuits composed of multiple such transcriptional units have immense scope for application in diverse fields of basic and applied research. Synthetic transcriptional engineering seeks to construct such genetic cascades. Here, we discuss the three principle strands of transcriptional engineering: promoter and transcriptional factor engineering, and programming inducibilty into synthetic modules. In this context, we review the scope and limitations of some recent technologies that seek to achieve these ends. Our discussion emphasizes a requirement for rational combinatorial engineering principles and the promise this approach holds for the future development of this field.

GenoCAD Plant Grammar to Design Plant Expression Vectors for Promoter Analysis

With the rapid advances in prediction tools for discovery of new promoters and their cis-elements, there is a need to improve plant expression methodologies in order to facilitate a high-throughput functional validation of these promoters in planta. The promoter-reporter analysis is an indispensible approach for characterization of plant promoters. It requires the design of complex plant expression vectors, which can be challenging. Here, we describe the use of a plant grammar implemented in GenoCAD that will allow the users to quickly design constructs for promoter analysis experiments but also for other in planta functional studies. The GenoCAD plant grammar includes a library of plant biological parts organized in structural categories to facilitate their use and management and a set of rules that guides the process of assembling these biological parts into large constructs.

A Barcoding Strategy Enabling Higher-Throughput Library Screening by Microscopy

Dramatic progress has been made in the design and build phases of the design-build-test cycle for engineering cells. However, the test phase usually limits throughput, as many outputs of interest are not amenable to rapid analytical measurements. For example, phenotypes such as motility, morphology, and subcellular localization can be readily measured by microscopy, but analysis of these phenotypes is notoriously slow. To increase throughput, we developed microscopy-readable barcodes (MiCodes) composed of fluorescent proteins targeted to discernible organelles. In this system, a unique barcode can be genetically linked to each library member, making possible the parallel analysis of phenotypes of interest via microscopy. As a first demonstration, we MiCoded a set of synthetic coiled-coil leucine zipper proteins to allow an 8 × 8 matrix to be tested for specific interactions in micrographs consisting of mixed populations of cells. A novel microscopy-readable two-hybrid fluorescence localization assay for probing candidate interactions in the cytosol was also developed using a bait protein targeted to the peroxisome and a prey protein tagged with a fluorescent protein. This work introduces a generalizable, scalable platform for making microscopy amenable to higher-throughput library screening experiments, thereby coupling the power of imaging with the utility of combinatorial search paradigms.

Rule-Based Design of Plant Expression Vectors Using GenoCAD

Plant synthetic biology requires software tools to assist on the design of complex multi-genic expression plasmids. Here a vector design strategy to express genes in plants is formalized and implemented as a grammar in GenoCAD, a Computer-Aided Design software for synthetic biology. It includes a library of plant biological parts organized in structural categories and a set of rules describing how to assemble these parts into large constructs. Rules developed here are organized and divided into three main subsections according to the aim of the final construct: protein localization studies, promoter analysis and protein-protein interaction experiments. The GenoCAD plant grammar guides the user through the design while allowing users to customize vectors according to their needs. Therefore the plant grammar implemented in GenoCAD will help plant biologists take advantage of methods from synthetic biology to design expression vectors supporting their research projects.

Mammalian designer cells: Engineering principles and biomedical applications

Biotechnology is a widely interdisciplinary field focusing on the use of living cells or organisms to solve established problems in medicine, food production and agriculture. Synthetic biology, the science of engineering complex biological systems that do not exist in nature, continues to provide the biotechnology industry with tools, technologies and intellectual property leading to improved cellular performance. One key aspect of synthetic biology is the engineering of deliberately reprogrammed designer cells whose behavior can be controlled over time and space. This review discusses the most commonly used techniques to engineer mammalian designer cells; while control elements acting on the transcriptional and translational levels of target gene expression determine the kinetic and dynamic profiles, coupling them to a variety of extracellular stimuli permits their remote control with user-defined trigger signals. Designer mammalian cells with novel or improved biological functions not only directly improve the production efficiency during biopharmaceutical manufacturing but also open the door for cell-based treatment strategies in molecular and translational medicine. In the future, the rational combination of multiple sets of designer cells could permit the construction and regulation of higher-order systems with increased complexity, thereby enabling the molecular reprogramming of tissues, organisms or even populations with highest precision.

Engineering protocells: prospects for self-assembly and nanoscale production-lines

The increasing ease of producing nucleic acids and proteins to specification offers potential for design and fabrication of artificial synthetic "organisms" with a myriad of possible capabilities. The prospects for these synthetic organisms are significant, with potential applications in diverse fields including synthesis of pharmaceuticals, sources of renewable fuel and environmental cleanup. Until now, artificial cell technology has been largely restricted to the modification and metabolic engineering of living unicellular organisms. This review discusses emerging possibilities for developing synthetic protocell "machines" assembled entirely from individual biological components. We describe a host of recent technological advances that could potentially be harnessed in design and construction of synthetic protocells, some of which have already been utilized toward these ends. More elaborate designs include options for building self-assembling machines by incorporating cellular transport and assembly machinery. We also discuss production in miniature, using microfluidic production lines. While there are still many unknowns in the design, engineering and optimization of protocells, current technologies are now tantalizingly close to the capabilities required to build the first prototype protocells with potential real-world applications.

Recent applications of synthetic biology tools for yeast metabolic engineering

The last 20 years of metabolic engineering has enabled bio-based production of fuels and chemicals from renewable carbon sources using cost-effective bioprocesses. Much of this work has been accomplished using engineered microorganisms that act as chemical factories. Although the time required to engineer microbial chemical factories has steadily decreased, improvement is still needed. Through the development of synthetic biology tools for key microbial hosts, it should be possible to further decrease the development times and improve the reliability of the resulting microorganism. Together with continuous decreases in price and improvements in DNA synthesis, assembly and sequencing, synthetic biology tools will rationalize time-consuming strain engineering, improve control of metabolic fluxes, and diversify screening assays for cellular metabolism. This review outlines some recently developed synthetic biology tools and their application to improve production of chemicals and fuels in yeast. Finally, we provide a perspective for the challenges that lie ahead.

Transcription activator-like effectors: a toolkit for synthetic biology

Transcription activator-like effectors (TALEs) are proteins secreted by Xanthomonas bacteria to aid the infection of plant species. TALEs assist infections by binding to specific DNA sequences and activating the expression of host genes. Recent results show that TALE proteins consist of a central repeat domain, which determines the DNA targeting specificity and can be rapidly synthesized de novo. Considering the highly modular nature of TALEs, their versatility, and the ease of constructing these proteins, this technology can have important implications for synthetic biology applications. Here, we review developments in the area with a particular focus on modifications for custom and controllable gene regulation.

Principles of genetic circuit design

Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform tasks or create chemicals and materials that match the complexity seen in nature. This Review describes new tools that aid the construction of genetic circuits. Circuit dynamics can be influenced by the choice of regulators and changed with expression 'tuning knobs'. We collate the failure modes encountered when assembling circuits, quantify their impact on performance and review mitigation efforts. Finally, we discuss the constraints that arise from circuits having to operate within a living cell. Collectively, better tools, well-characterized parts and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.

Multiplexed and programmable regulation of gene networks with an integrated RNA and CRISPR/Cas toolkit in human cells

RNA-based regulation and CRISPR/Cas transcription factors (CRISPR-TFs) have the potential to be integrated for the tunable modulation of gene networks. A major limitation of this methodology is that guide RNAs (gRNAs) for CRISPR-TFs can only be expressed from RNA polymerase III promoters in human cells, limiting their use for conditional gene regulation. We present new strategies that enable expression of functional gRNAs from RNA polymerase II promoters and multiplexed production of proteins and gRNAs from a single transcript in human cells. We use multiple RNA regulatory strategies, including RNA-triple-helix structures, introns, microRNAs, and ribozymes, with Cas9-based CRISPR-TFs and Cas6/Csy4-based RNA processing. Using these tools, we efficiently modulate endogenous promoters and implement tunable synthetic circuits, including multistage cascades and RNA-dependent networks that can be rewired with Csy4 to achieve complex behaviors. This toolkit can be used for programming scalable gene circuits and perturbing endogenous networks for biology, therapeutic, and synthetic biology applications.