A synthetic biology framework for programming eukaryotic transcription functions

Synthetic Forms Most Beautiful: Engineering Insights into Self-Organization

Reflecting on the diversity of the natural world, Darwin famously observed that "from so simple a beginning endless forms most beautiful and most wonderful have been, and are being evolved." However, the examples that we are able to observe in nature are a consequence of chance, constrained by selection, drift, and epistasis. Here we explore how the efforts of synthetic biology to build new living systems can expand our understanding of the fundamental design principles that allow life to self-organize biological form, from cellular to organismal levels. We suggest that the ability to impose a length or timescale onto a biological activity is an essential strategy for self-organization in evolved systems and a key design target that is now being realized synthetically at all scales. By learning to integrate these strategies together, we are poised to expand on evolution's success and realize a space of synthetic forms not only beautiful but with diverse applications and transformative potential.

Upgraded circular single-stranded DNA regulators for multiple-input multiple-output gene circuits in mammalian cells

Synthetic gene networks hold promise for genetic diagnostics and gene therapy but face limitations due to insufficient molecular tools. Gene-encoded circular single-stranded DNA (Css DNA) has been developed as a switchable vector to enrich regulatory components beyond protein/RNA-based systems in mammalian cells. However, the previous Css DNA regulator suffered from constrained regulatory sequence flexibility, disability of multiple-input multiple-output (MIMO) signals, and lack of endogenous orthogonal regulation. Here, we address these challenges by engineering a "bridge" design into the Css DNA regulator. These bridges function as sequence-programmable switches to control gene expression, responding to endogenous molecular signals (such as ATP, APE1, and RNase H) and enabling trans-regulation within or between Css DNAs. We exploit the orthogonality of Css DNA regulator to construct the three-input three-output genetic circuits. The upgraded Css DNA-based regulatory strategy represents a versatile and powerful platform for gene regulation and provides a promising avenue for the development of synthetic gene networks.

Microbial Transcription Factor-Based Biosensors: Innovations from Design to Applications in Synthetic Biology

Transcription factor-based biosensors (TFBs) are powerful tools in microbial biosensor applications, enabling dynamic control of metabolic pathways, real-time monitoring of intracellular metabolites, and high-throughput screening (HTS) for strain engineering. These systems use transcription factors (TFs) to convert metabolite concentrations into quantifiable outputs, enabling precise regulation of metabolic fluxes and biosynthetic efficiency in microbial cell factories. Recent advancements in TFB, including improved sensitivity, specificity, and dynamic range, have broadened their applications in synthetic biology and industrial biotechnology. Computational tools such as Cello have further revolutionized TFB design, enabling in silico optimization and construction of complex genetic circuits for integrating multiple signals and achieving precise gene regulation. This review explores innovations in TFB systems for microbial biosensors, their role in metabolic engineering and adaptive evolution, and their future integration with artificial intelligence and advanced screening technologies to overcome critical challenges in synthetic biology and industrial bioproduction.

Genetically encoded protein oscillators for FM streaming of single-cell data

Radios and cellphones use frequency modulation (FM) of an oscillating carrier signal to reliably transmit multiplexed data while rejecting noise. Here, we establish a biochemical analogue of this paradigm using genetically encoded protein oscillators (GEOs) as carrier signals in circuits that enable continuous, real-time FM streaming of single-cell data. GEOs are constructed from evolutionarily diverse MinDE-family ATPase and activator modules that generate fast synthetic protein oscillations when co-expressed in human cells. These oscillations serve as a single-cell carrier signal, with frequency and amplitude controlled by GEO component levels and activity. We systematically characterize 169 ATPase/activator GEO pairs and engineer composite GEOs with multiple competing activators to develop a comprehensive platform for waveform programming. Using these principles, we design circuits that modulate GEO frequency in response to cellular activity and decode their responses using a calibrated machine-learning model to demonstrate sensitive, real-time FM streaming of transcription and proteasomal degradation dynamics in single cells. GEOs establish a dynamically controllable biochemical carrier signal, unlocking noise-resistant FM data-encoding paradigms that open new avenues for dynamic single-cell analysis.

Directed evolution of an orthogonal transcription engine for programmable gene expression in eukaryotes

T7 RNA polymerase (RNAP) has enabled orthogonal control of gene expression and recombinant protein production across diverse prokaryotic host chassis organisms for decades. However, the absence of 5' methyl guanosine caps on T7 RNAP-derived transcripts has severely limited its utility and widespread adoption in eukaryotic systems. To address this shortcoming, we evolved a fusion enzyme combining T7 RNAP with the single subunit capping enzyme from African swine fever virus using Saccharomyces cerevisiae. We isolated highly active variants of this fusion enzyme, which exhibited roughly two orders of magnitude higher protein expression compared to the wild-type enzyme. We demonstrate the programmable control of gene expression using T7 RNAP-based genetic circuits in yeast and validate enhanced performance of these engineered variants in mammalian cells. This study presents a robust, orthogonal gene regulatory system applicable across diverse eukaryotic hosts, enhancing the versatility and efficiency of synthetic biology applications.

Engineering synthetic phosphorylation signaling networks in human cells

Protein phosphorylation signaling networks have a central role in how cells sense and respond to their environment. We engineered artificial phosphorylation networks in which reversible enzymatic phosphorylation cycles were assembled from modular protein domain parts and wired together to create synthetic phosphorylation circuits in human cells. Our design scheme enabled model-guided tuning of circuit function and the ability to make diverse network connections; synthetic phosphorylation circuits can be coupled to upstream cell surface receptors to enable fast-timescale sensing of extracellular ligands, and downstream connections can regulate gene expression. We engineered cell-based cytokine controllers that dynamically sense and suppress activated T cells. Our work introduces a generalizable approach that allows the design of signaling circuits that enable user-defined sense-and-respond function for diverse biosensing and therapeutic applications.

Regulatory Components for Bacterial Cell-Free Systems Engineering

Cell-free systems are advancing synthetic biology through fast prototyping and modularity. Complex regulatory networks can now be implemented in cell-free systems enabling various applications, such as diagnostic tool development, gene circuit prototyping, and metabolic engineering. As functional complexity increases, the need for regulatory components also grows. This review provides a comprehensive overview of native as well as engineered regulatory components and their use in bacterial cell-free systems.

Directed evolution of an orthogonal transcription engine for programmable gene expression in eukaryotes

T7 RNA polymerase has enabled orthogonal control of gene expression and recombinant protein production across diverse prokaryotic host chassis organisms for decades. However, the absence of 5' methyl guanosine caps on T7 RNAP derived transcripts has severely limited its utility and widespread adoption in eukaryotic systems. To address this shortcoming, we evolved a fusion enzyme combining T7 RNAP with the single subunit capping enzyme from African swine fever virus using Saccharomyces cerevisiae. We isolated highly active variants of this fusion enzyme, which exhibited roughly two orders of magnitude higher protein expression compared to the wild-type enzyme. We demonstrate the programmable control of gene expression using T7 RNAP-based genetic circuits in yeast and validate enhanced performance of these engineered variants in mammalian cells. This study presents a robust, orthogonal gene regulatory system applicable across diverse eukaryotic hosts, enhancing the versatility and efficiency of synthetic biology applications.

AI in cellular engineering and reprogramming

During the last decade, artificial intelligence (AI) has increasingly been applied in biophysics and related fields, including cellular engineering and reprogramming, offering novel approaches to understand, manipulate, and control cellular function. The potential of AI lies in its ability to analyze complex datasets and generate predictive models. AI algorithms can process large amounts of data from single-cell genomics and multiomic technologies, allowing researchers to gain mechanistic insights into the control of cell identity and function. By integrating and interpreting these complex datasets, AI can help identify key molecular events and regulatory pathways involved in cellular reprogramming. This knowledge can inform the design of precision engineering strategies, such as the development of new transcription factor and signaling molecule cocktails, to manipulate cell identity and drive authentic cell fate across lineage boundaries. Furthermore, when used in combination with computational methods, AI can accelerate and improve the analysis and understanding of the intricate relationships between genes, proteins, and cellular processes. In this review article, we explore the current state of AI applications in biophysics with a specific focus on cellular engineering and reprogramming. Then, we showcase a couple of recent applications where we combined machine learning with experimental and computational techniques. Finally, we briefly discuss the challenges and prospects of AI in cellular engineering and reprogramming, emphasizing the potential of these technologies to revolutionize our ability to engineer cells for a variety of applications, from disease modeling and drug discovery to regenerative medicine and biomanufacturing.

Programmable promoter editing for precise control of transgene expression

Subtle changes in gene expression direct cells to distinct cellular states. Identifying and controlling dose-dependent transgenes require tools for precisely titrating expression. To this end, we developed a highly modular, extensible framework called DIAL for building editable promoters that allow for fine-scale, heritable changes in transgene expression. Using DIAL, we increase expression by recombinase-mediated excision of spacers between the binding sites of a synthetic zinc finger transcription factor and the core promoter. By nesting varying numbers and lengths of spacers, DIAL generates a tunable range of unimodal setpoints from a single promoter. Through small-molecule control of transcription factors and recombinases, DIAL supports temporally defined, user-guided control of transgene expression that is extensible to additional transcription factors. Lentiviral delivery of DIAL generates multiple setpoints in primary cells and iPSCs. As promoter editing generates stable states, DIAL setpoints are heritable, facilitating mapping of transgene levels to phenotypes. The DIAL framework opens new opportunities for tailoring transgene expression and improving the predictability and performance of gene circuits across diverse applications.

Enhancing extracellular vesicle cargo loading and functional delivery by engineering protein-lipid interactions

Naturally generated lipid nanoparticles termed extracellular vesicles (EVs) hold significant promise as engineerable therapeutic delivery vehicles. However, active loading of protein cargo into EVs in a manner that is useful for delivery remains a challenge. Here, we demonstrate that by rationally designing proteins to traffic to the plasma membrane and associate with lipid rafts, we can enhance loading of protein cargo into EVs for a set of structurally diverse transmembrane and peripheral membrane proteins. We then demonstrate the capacity of select lipid tags to mediate increased EV loading and functional delivery of an engineered transcription factor to modulate gene expression in target cells. We envision that this technology could be leveraged to develop new EV-based therapeutics that deliver a wide array of macromolecular cargo.

Brainwide silencing of prion protein by AAV-mediated delivery of an engineered compact epigenetic editor

Prion disease is caused by misfolding of the prion protein (PrP) into pathogenic self-propagating conformations, leading to rapid-onset dementia and death. However, elimination of endogenous PrP halts prion disease progression. In this study, we describe Coupled Histone tail for Autoinhibition Release of Methyltransferase (CHARM), a compact, enzyme-free epigenetic editor capable of silencing transcription through programmable DNA methylation. Using a histone H3 tail-Dnmt3l fusion, CHARM recruits and activates endogenous DNA methyltransferases, thereby reducing transgene size and cytotoxicity. When delivered to the mouse brain by systemic injection of adeno-associated virus (AAV), Prnp-targeted CHARM ablates PrP expression across the brain. Furthermore, we have temporally limited editor expression by implementing a kinetically tuned self-silencing approach. CHARM potentially represents a broadly applicable strategy to suppress pathogenic proteins, including those implicated in other neurodegenerative diseases.

Accelerating Genetic Sensor Development, Scale-up, and Deployment Using Synthetic Biology

Living cells are exquisitely tuned to sense and respond to changes in their environment. Repurposing these systems to create engineered biosensors has seen growing interest in the field of synthetic biology and provides a foundation for many innovative applications spanning environmental monitoring to improved biobased production. In this review, we present a detailed overview of currently available biosensors and the methods that have supported their development, scale-up, and deployment. We focus on genetic sensors in living cells whose outputs affect gene expression. We find that emerging high-throughput experimental assays and evolutionary approaches combined with advanced bioinformatics and machine learning are establishing pipelines to produce genetic sensors for virtually any small molecule, protein, or nucleic acid. However, more complex sensing tasks based on classifying compositions of many stimuli and the reliable deployment of these systems into real-world settings remain challenges. We suggest that recent advances in our ability to precisely modify nonmodel organisms and the integration of proven control engineering principles (e.g., feedback) into the broader design of genetic sensing systems will be necessary to overcome these hurdles and realize the immense potential of the field.

A high-throughput synthetic biology approach for studying combinatorial chromatin-based transcriptional regulation

The construction of synthetic gene circuits requires the rational combination of multiple regulatory components, but predicting their behavior can be challenging due to poorly understood component interactions and unexpected emergent behaviors. In eukaryotes, chromatin regulators (CRs) are essential regulatory components that orchestrate gene expression. Here, we develop a screening platform to investigate the impact of CR pairs on transcriptional activity in yeast. We construct a combinatorial library consisting of over 1,900 CR pairs and use a high-throughput workflow to characterize the impact of CR co-recruitment on gene expression. We recapitulate known interactions and discover several instances of CR pairs with emergent behaviors. We also demonstrate that supervised machine learning models trained with low-dimensional amino acid embeddings accurately predict the impact of CR co-recruitment on transcriptional activity. This work introduces a scalable platform and machine learning approach that can be used to study how networks of regulatory components impact gene expression.

Advancing in vivo reprogramming with synthetic biology

Reprogramming cells will play a fundamental role in shaping the future of cell therapies by developing new strategies to engineer cells for improved performance and higher-order physiological functions. Approaches in synthetic biology harness cells' natural ability to sense diverse signals, integrate environmental inputs to make decisions, and execute complex behaviors based on the health of the organism or tissue. In this review, we highlight strategies in synthetic biology to reprogram cells, and discuss how recent approaches in the delivery of modified mRNA have created new opportunities to alter cell function in vivo. Finally, we discuss how combining concepts from synthetic biology and the delivery of mRNA in vivo could provide a platform for innovation to advance in vivo cellular reprogramming.

A non-viral DNA delivery system consisting of multifunctional chimeric peptide fused with zinc-finger protein

Non-viral gene delivery systems have received sustained attention as a promising alternative to viral vectors for disease treatment and prevention in recent years. Numerous methods have been developed to enhance gene uptake and delivery in the cytoplasm; however, due to technical difficulties and delivery efficiency, these systems still face challenges in a range of biological applications, especially in vivo. To alleviate this challenge, we devised a novel system for gene delivery based on a recombinant protein eTAT-ZF9-NLS, which consisted of a multifunctional chimeric peptide and a zinc-finger protein with sequence-specific DNA-binding activity. High transfection efficiency was observed in several mammalian cells after intracellular delivery of plasmid containing ZF9-binding sites mediated by eTAT-ZF9-NLS. Our new approach provides a novel transfection strategy and the transfection efficiency was confirmed both in vitro and in vivo, making it a preferential transfection reagent for possible gene therapy.

Synthetic transcription factor engineering for cell and gene therapy

Synthetic transcription factors (synTFs) that control beneficial transgene expression are an important method to increase the safety and efficacy of cell and gene therapy. Reliance on synTF components from non-human sources has slowed progress in the field because of concerns about immunogenicity and inducer drug properties. Recent advances in human-derived DNA-binding domains (DBDs) and transcriptional activation domains (TADs) paired with novel control modules responsive to clinically approved small molecules have poised the synTF field to overcome these hurdles. Advances include controllers inducible by autonomous signaling inputs and more complex, multi-input synTF circuits. Demonstrations of advanced control strategies with human-derived transcription factor components in clinically relevant vectors and in vivo models will facilitate progression into the clinic.

Engineering transcriptional regulation for cell-based therapies

A major aim in the field of synthetic biology is developing tools capable of responding to user-defined inputs by activating therapeutically relevant cellular functions. Gene transcription and regulation in response to external stimuli are some of the most powerful and versatile of these cellular functions being explored. Motivated by the success of chimeric antigen receptor (CAR) T-cell therapies, transmembrane receptor-based platforms have been embraced for their ability to sense extracellular ligands and to subsequently activate intracellular signal transduction. The integration of transmembrane receptors with transcriptional activation platforms has not yet achieved its full potential. Transient expression of plasmid DNA is often used to explore gene regulation platforms in vitro. However, applications capable of targeting therapeutically relevant endogenous or stably integrated genes are more clinically relevant. Gene regulation may allow for engineered cells to traffic into tissues of interest and secrete functional proteins into the extracellular space or to differentiate into functional cells. Transmembrane receptors that regulate transcription have the potential to revolutionize cell therapies in a myriad of applications, including cancer treatment and regenerative medicine. In this review, we will examine current engineering approaches to control transcription in mammalian cells with an emphasis on systems that can be selectively activated in response to extracellular signals. We will also speculate on the potential therapeutic applications of these technologies and examine promising approaches to expand their capabilities and tighten the control of gene regulation in cellular therapies.

Integrated compact regulators of protein activity enable control of signaling pathways and genome-editing in vivo

Viral proteases and clinically safe inhibitors were employed to build integrated compact regulators of protein activity (iCROP) for post-translational regulation of functional proteins by tunable proteolytic activity. In the absence of inhibitor, the co-localized/fused protease cleaves a target peptide sequence introduced in an exposed loop of the protein of interest, irreversibly fragmenting the protein structure and destroying its functionality. We selected three proteases and demonstrated the versatility of the iCROP framework by validating it to regulate the functional activity of ten different proteins. iCROP switches can be delivered either as mRNA or DNA, and provide rapid actuation kinetics with large induction ratios, while remaining strongly suppressed in the off state without inhibitor. iCROPs for effectors of the NF-κB and NFAT signaling pathways were assembled and confirmed to enable precise activation/inhibition of downstream events in response to protease inhibitors. In lipopolysaccharide-treated mice, iCROP-sr-IκBα suppressed cytokine release ("cytokine storm") by rescuing the activity of IκBα, which suppresses NF-κB signaling. We also constructed compact inducible CRISPR-(d)Cas9 variants and showed that iCROP-Cas9-mediated knockout of the PCSK9 gene in the liver lowered blood LDL-cholesterol levels in mice. iCROP-based protein switches will facilitate protein-level regulation in basic research and translational applications.

Designing Epigenome Editors: Considerations of Biochemical and Locus Specificities

The advent of locus-specific protein recruitment technologies has enabled a new class of studies in chromatin biology. Epigenome editors (EEs) enable biochemical modifications of chromatin at almost any specific endogenous locus. Their locus-specificity unlocks unique information including the functional roles of distinct modifications at specific genomic loci. Given the growing interest in using these tools for biological and translational studies, there are many specific design considerations depending on the scientific question or clinical need. Here, we present and discuss important design considerations and challenges regarding the biochemical and locus specificities of epigenome editors. These include how to: account for the complex biochemical diversity of chromatin; control for potential interdependency of epigenome editors and their resultant modifications; avoid sequestration effects; quantify the locus specificity of epigenome editors; and improve locus-specificity by considering concentration, affinity, avidity, and sequestration effects.

Customizing cellular signal processing by synthetic multi-level regulatory circuits

As synthetic biology permeates society, the signal processing circuits in engineered living systems must be customized to meet practical demands. Towards this mission, novel regulatory mechanisms and genetic circuits with unprecedented complexity have been implemented over the past decade. These regulatory mechanisms, such as transcription and translation control, could be integrated into hybrid circuits termed "multi-level circuits". The multi-level circuit design will tremendously benefit the current genetic circuit design paradigm, from modifying basic circuit dynamics to facilitating real-world applications, unleashing our capabilities to customize cellular signal processing and address global challenges through synthetic biology.

Engineering synthetic phosphorylation signaling networks in human cells

Protein phosphorylation signaling networks play a central role in how cells sense and respond to their environment. Here, we describe the engineering of artificial phosphorylation networks in which "push-pull" motifs-reversible enzymatic phosphorylation cycles consisting of opposing kinase and phosphatase activities-are assembled from modular protein domain parts and then wired together to create synthetic phosphorylation circuits in human cells. We demonstrate that the composability of our design scheme enables model-guided tuning of circuit function and the ability to make diverse network connections; synthetic phosphorylation circuits can be coupled to upstream cell surface receptors to enable fast-timescale sensing of extracellular ligands, while downstream connections can regulate gene expression. We leverage these capabilities to engineer cell-based cytokine controllers that dynamically sense and suppress activated T cells. Our work introduces a generalizable approach for designing and building phosphorylation signaling circuits that enable user-defined sense-and-respond function for diverse biosensing and therapeutic applications.

Circular single-stranded DNA as switchable vector for gene expression in mammalian cells

Synthetic gene networks in mammalian cells are currently limited to either protein-based transcription factors or RNA-based regulators. Here, we demonstrate a regulatory approach based on circular single-stranded DNA (Css DNA), which can be used as an efficient expression vector with switchable activity, enabling gene regulation in mammalian cells. The Css DNA is transformed into its double-stranded form via DNA replication and used as vectors encoding a variety of different proteins in a wide range of cell lines as well as in mice. The rich repository of DNA nanotechnology allows to use sort single-stranded DNA effectors to fold Css DNA into DNA nanostructures of different complexity, leading the gene expression to programmable inhibition and subsequently re-activation via toehold-mediated strand displacement. The regulatory strategy from Css DNA can thus expand the molecular toolbox for the realization of synthetic regulatory networks with potential applications in genetic diagnosis and gene therapy.

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.

Cooperative assembly confers regulatory specificity and long-term genetic circuit stability

A ubiquitous feature of eukaryotic transcriptional regulation is cooperative self-assembly between transcription factors (TFs) and DNA cis-regulatory motifs. It is thought that this strategy enables specific regulatory connections to be formed in gene networks between otherwise weakly interacting, low-specificity molecular components. Here, using synthetic gene circuits constructed in yeast, we find that high regulatory specificity can emerge from cooperative, multivalent interactions among artificial zinc-finger-based TFs. We show that circuits "wired" using the strategy of cooperative TF assembly are effectively insulated from aberrant misregulation of the host cell genome. As we demonstrate in experiments and mathematical models, this mechanism is sufficient to rescue circuit-driven fitness defects, resulting in genetic and functional stability of circuits in long-term continuous culture. Our naturally inspired approach offers a simple, generalizable means for building high-fidelity, evolutionarily robust gene circuits that can be scaled to a wide range of host organisms and applications.

A universal deep-learning model for zinc finger design enables transcription factor reprogramming

Cys2His2 zinc finger (ZF) domains engineered to bind specific target sequences in the genome provide an effective strategy for programmable regulation of gene expression, with many potential therapeutic applications. However, the structurally intricate engagement of ZF domains with DNA has made their design challenging. Here we describe the screening of 49 billion protein-DNA interactions and the development of a deep-learning model, ZFDesign, that solves ZF design for any genomic target. ZFDesign is a modern machine learning method that models global and target-specific differences induced by a range of library environments and specifically takes into account compatibility of neighboring fingers using a novel hierarchical transformer architecture. We demonstrate the versatility of designed ZFs as nucleases as well as activators and repressors by seamless reprogramming of human transcription factors. These factors could be used to upregulate an allele of haploinsufficiency, downregulate a gain-of-function mutation or test the consequence of regulation of a single gene as opposed to the many genes that a transcription factor would normally influence.

Ultra-high throughput mapping of genetic design space

Massively parallel genetic screens have been used to map sequence-to-function relationships for a variety of genetic elements. However, because these approaches only interrogate short sequences, it remains challenging to perform high throughput (HT) assays on constructs containing combinations of sequence elements arranged across multi-kb length scales. Overcoming this barrier could accelerate synthetic biology; by screening diverse gene circuit designs, "composition-to-function" mappings could be created that reveal genetic part composability rules and enable rapid identification of behavior-optimized variants. Here, we introduce CLASSIC, a generalizable genetic screening platform that combines long- and short-read next-generation sequencing (NGS) modalities to quantitatively assess pooled libraries of DNA constructs of arbitrary length. We show that CLASSIC can measure expression profiles of >10 5 drug-inducible gene circuit designs (ranging from 6-9 kb) in a single experiment in human cells. Using statistical inference and machine learning (ML) approaches, we demonstrate that data obtained with CLASSIC enables predictive modeling of an entire circuit design landscape, offering critical insight into underlying design principles. Our work shows that by expanding the throughput and understanding gained with each design-build-test-learn (DBTL) cycle, CLASSIC dramatically augments the pace and scale of synthetic biology and establishes an experimental basis for data-driven design of complex genetic systems.

A noncommutative combinatorial protein logic circuit controls cell orientation in nanoenvironments

Single-protein-based devices that integrate signal sensing with logical operations to generate functional outputs offer exceptional promise for monitoring and modulating biological systems. Engineering such intelligent nanoscale computing agents is challenging, as it requires the integration of sensor domains into a functional protein via intricate allosteric networks. We incorporate a rapamycin-sensitive sensor (uniRapR) and a blue light-responsive LOV2 domain into human Src kinase, creating a protein device that functions as a noncommutative combinatorial logic circuit. In our design, rapamycin activates Src kinase, causing protein localization to focal adhesions, whereas blue light exerts the reverse effect that inactivates Src translocation. Focal adhesion maturation induced by Src activation reduces cell migration dynamics and shifts cell orientation to align along collagen nanolane fibers. Using this protein device, we reversibly control cell orientation by applying the appropriate input signals, a framework that may be useful in tissue engineering and regenerative medicine.

Transcriptional kinetic synergy: A complex landscape revealed by integrating modeling and synthetic biology

Transcription factors (TFs) control gene expression, often acting synergistically. Classical thermodynamic models offer a biophysical explanation for synergy based on binding cooperativity and regulated recruitment of RNA polymerase. Because transcription requires polymerase to transition through multiple states, recent work suggests that "kinetic synergy" can arise through TFs acting on distinct steps of the transcription cycle. These types of synergy are not mutually exclusive and are difficult to disentangle conceptually and experimentally. Here, we model and build a synthetic circuit in which TFs bind to a single shared site on DNA, such that TFs cannot synergize by simultaneous binding. We model mRNA production as a function of both TF binding and regulation of the transcription cycle, revealing a complex landscape dependent on TF concentration, DNA binding affinity, and regulatory activity. We use synthetic TFs to confirm that the transcription cycle must be integrated with recruitment for a quantitative understanding of gene regulation.

A cybergenetic framework for engineering intein-mediated integral feedback control systems

The ability of biological systems to tightly regulate targeted variables, despite external and internal disturbances, is known as Robust Perfect Adaptation (RPA). Achieved frequently through biomolecular integral feedback controllers at the cellular level, RPA has important implications for biotechnology and its various applications. In this study, we identify inteins as a versatile class of genetic components suitable for implementing these controllers and present a systematic approach for their design. We develop a theoretical foundation for screening intein-based RPA-achieving controllers and a simplified approach for modeling them. We then genetically engineer and test intein-based controllers using commonly used transcription factors in mammalian cells and demonstrate their exceptional adaptation properties over a wide dynamic range. The small size, flexibility, and applicability of inteins across life forms allow us to create a diversity of genetic RPA-achieving integral feedback control systems that can be used in various applications, including metabolic engineering and cell-based therapy.

Synthetic peptides for the precise transportation of proteins of interests to selectable subcellular areas

Proteins, as gifts from nature, provide structure, sequence, and function templates for designing biomaterials. As first reported here, one group of proteins called reflectins and derived peptides were found to present distinct intracellular distribution preferences. Taking their conserved motifs and flexible linkers as Lego bricks, a series of reflectin-derivates were designed and expressed in cells. The selective intracellular localization property leaned on an RMs (canonical conserved reflectin motifs)-replication-determined manner, suggesting that these linkers and motifs were constructional fragments and ready-to-use building blocks for synthetic design and construction. A precise spatiotemporal application demo was constructed in the work by integrating RLNto2 (as one representative of a synthetic peptide derived from RfA1) into the Tet-on system to effectively transport cargo peptides into nuclei at selective time points. Further, the intracellular localization of RfA1 derivatives was spatiotemporally controllable with a CRY2/CIB1 system. At last, the functional homogeneities of either motifs or linkers were verified, which made them standardized building blocks for synthetic biology. In summary, the work provides a modularized, orthotropic, and well-characterized synthetic-peptide warehouse for precisely regulating the nucleocytoplasmic localization of proteins.

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.

High throughput mutagenesis and screening for yeast engineering

The eukaryotic yeast Saccharomyces cerevisiae is a model host utilized for whole cell biocatalytic conversions, protein evolution, and scientific inquiries into the pathogenesis of human disease. Over the past decade, the scale and pace of such studies has drastically increased alongside the advent of novel tools for both genome-wide studies and targeted genetic mutagenesis. In this review, we will detail past and present (e.g., CRISPR/Cas) genome-scale screening platforms, typically employed in the context of growth-based selections for improved whole cell phenotype or for mechanistic interrogations. We will further highlight recent advances that enable the rapid and often continuous evolution of biomolecules with improved function. Additionally, we will detail the corresponding advances in high throughput selection and screening strategies that are essential for assessing or isolating cellular and protein improvements. Finally, we will describe how future developments can continue to advance yeast high throughput engineering.

Periodic spatial patterning with a single morphogen

During multicellular development, periodic spatial patterning systems generate repetitive structures, such as digits, vertebrae, and teeth. Turing patterning provides a foundational paradigm for understanding such systems. The simplest Turing systems are believed to require at least two morphogens to generate periodic patterns. Here, using mathematical modeling, we show that a simpler circuit, including only a single diffusible morphogen, is sufficient to generate long-range, spatially periodic patterns that propagate outward from transient initiating perturbations and remain stable after the perturbation is removed. Furthermore, an additional bistable intracellular feedback or operation on a growing cell lattice can make patterning robust to noise. Together, these results show that a single morphogen can be sufficient for robust spatial pattern formation and should provide a foundation for engineering pattern formation in the emerging field of synthetic developmental biology.

A Toolkit for Precise, Multigene Control in Saccharomyces cerevisiae

Systems that allow researchers to precisely control the expression of genes are fundamental to biological research, biotechnology, and synthetic biology. However, few inducible gene expression systems exist that can enable simultaneous multigene control under common nutritionally favorable conditions in the important model organism and chassis Saccharomyces cerevisiae. Here we repurposed ligand binding domains from mammalian type I nuclear receptors to establish a family of up to five orthogonal synthetic gene expression systems in yeast. Our systems enable tight, independent, multigene control through addition of inert hormones and are capable of driving robust and rapid gene expression outputs, in some cases achieving up to 600-fold induction. As a proof of principle, we placed expression of four enzymes from the violacein biosynthetic pathway under independent expression control to selectively route pathway flux by addition of specific inducer combinations. Our results establish a modular, versatile, and potentially expandable toolkit for multidimensional control of gene expression in yeast that can be used to construct and control naturally occurring and synthetic gene networks.

Multidimensional control of therapeutic human cell function with synthetic gene circuits

Synthetic gene circuits that precisely control human cell function could expand the capabilities of gene- and cell-based therapies. However, platforms for developing circuits in primary human cells that drive robust functional changes in vivo and have compositions suitable for clinical use are lacking. Here, we developed synthetic zinc finger transcription regulators (synZiFTRs), which are compact and based largely on human-derived proteins. As a proof of principle, we engineered gene switches and circuits that allow precise, user-defined control over therapeutically relevant genes in primary T cells using orthogonal, US Food and Drug Administration-approved small-molecule inducers. Our circuits can instruct T cells to sequentially activate multiple cellular programs such as proliferation and antitumor activity to drive synergistic therapeutic responses. This platform should accelerate the development and clinical translation of synthetic gene circuits in diverse human cell types and contexts.

Gene regulatory and gene editing tools and their applications for retinal diseases and neuroprotection: From proof-of-concept to clinical trial

Gene editing and gene regulatory fields are continuously developing new and safer tools that move beyond the initial CRISPR/Cas9 technology. As more advanced applications are emerging, it becomes crucial to understand and establish more complex gene regulatory and editing tools for efficient gene therapy applications. Ophthalmology is one of the leading fields in gene therapy applications with more than 90 clinical trials and numerous proof-of-concept studies. The majority of clinical trials are gene replacement therapies that are ideal for monogenic diseases. Despite Luxturna's clinical success, there are still several limitations to gene replacement therapies including the size of the target gene, the choice of the promoter as well as the pathogenic alleles. Therefore, further attempts to employ novel gene regulatory and gene editing applications are crucial to targeting retinal diseases that have not been possible with the existing approaches. CRISPR-Cas9 technology opened up the door for corrective gene therapies with its gene editing properties. Advancements in CRISPR-Cas9-associated tools including base modifiers and prime editing already improved the efficiency and safety profile of base editing approaches. While base editing is a highly promising effort, gene regulatory approaches that do not interfere with genomic changes are also becoming available as safer alternatives. Antisense oligonucleotides are one of the most commonly used approaches for correcting splicing defects or eliminating mutant mRNA. More complex gene regulatory methodologies like artificial transcription factors are also another developing field that allows targeting haploinsufficiency conditions, functionally equivalent genes, and multiplex gene regulation. In this review, we summarized the novel gene editing and gene regulatory technologies and highlighted recent translational progress, potential applications, and limitations with a focus on retinal diseases.

Dynamic regulation of Monascus azaphilones biosynthesis by the binary MrPigE-MrPigF oxidoreductase system

Monascus azaphilones (MAs) have been extensively applied as natural food coloring agents. MAs are classified into three categories: yellow MAs (YMAs), orange MAs (OMAs), and red MAs with various biological activities. However, the exact biosynthetic mechanism of OMAs and YMAs are not thoroughly elucidated. Firstly, we identified four DNA-binding residues of transcription factor MrPigB and constructed a multi-site saturation mutagenesis library of MrPigB. Then, comparative metabolite and gene expression of the mutants revealed that two oxidoreductases MrPigE and MrPigF were responsible for the formation of YMAs and OMAs. Finally, the in vitro and in vivo assays demonstrated the opposite roles of MrPigE and MrPigF in conversion of OMAs to YMAs. To our knowledge, this is the first report of a binary oxidoreductase system for dynamic regulation of fungal secondary metabolite biosynthesis. Broadly, our work also demonstrates the transcription factor engineering strategy for elucidating the biosynthetic pathway of secondary metabolite. KEY POINTS: • MrPigE converts orange Monascus azaphilones to yellow Monascus azaphilones • MrPigF oxidizes intermediates to afford orange Monascus azaphilones • MrPigE and MrPigF constitute a binary system in Monascus azaphilones biosynthesis.

Systematic analysis of low-affinity transcription factor binding site clusters in vitro and in vivo establishes their functional relevance

Binding to binding site clusters has yet to be characterized in depth, and the functional relevance of low-affinity clusters remains uncertain. We characterized transcription factor binding to low-affinity clusters in vitro and found that transcription factors can bind concurrently to overlapping sites, challenging the notion of binding exclusivity. Furthermore, small clusters with binding sites an order of magnitude lower in affinity give rise to high mean occupancies at physiologically-relevant transcription factor concentrations. To assess whether the observed in vitro occupancies translate to transcriptional activation in vivo, we tested low-affinity binding site clusters in a synthetic and native gene regulatory network in S. cerevisiae. In both systems, clusters of low-affinity binding sites generated transcriptional output comparable to single or even multiple consensus sites. This systematic characterization demonstrates that clusters of low-affinity binding sites achieve substantial occupancies, and that this occupancy can drive expression in eukaryotic promoters.

Engineering the next generation of cell-based therapeutics

Cell-based therapeutics are an emerging modality with the potential to treat many currently intractable diseases through uniquely powerful modes of action. Despite notable recent clinical and commercial successes, cell-based therapies continue to face numerous challenges that limit their widespread translation and commercialization, including identification of the appropriate cell source, generation of a sufficiently viable, potent and safe product that meets patient- and disease-specific needs, and the development of scalable manufacturing processes. These hurdles are being addressed through the use of cutting-edge basic research driven by next-generation engineering approaches, including genome and epigenome editing, synthetic biology and the use of biomaterials.

Hardware, Software, and Wetware Codesign Environment for Synthetic Biology

Synthetic biology is the process of forward engineering living systems. These systems can be used to produce biobased materials, agriculture, medicine, and energy. One approach to designing these systems is to employ techniques from the design of embedded electronics. These techniques include abstraction, standards, modularity, automated design, and formal semantic models of computation. Together, these elements form the foundation of "biodesign automation," where software, robotics, and microfluidic devices combine to create exciting biological systems of the future. This paper describes a "hardware, software, wetware" codesign vision where software tools can be made to act as "genetic compilers" that transform high-level specifications into engineered "genetic circuits" (wetware). This is followed by a process where automation equipment, well-defined experimental workflows, and microfluidic devices are explicitly designed to house, execute, and test these circuits (hardware). These systems can be used as either massively parallel experimental platforms or distributed bioremediation and biosensing devices. Next, scheduling and control algorithms (software) manage these systems' actual execution and data analysis tasks. A distinguishing feature of this approach is how all three of these aspects (hardware, software, and wetware) may be derived from the same basic specification in parallel and generated to fulfill specific cost, performance, and structural requirements.

Engineering and Design of Programmable Genome Editors

Programmable genome editors are enzymes that can be targeted to a specific location in the genome for making site-specific alterations or deletions. The engineering, design, and development of sequence-specific editors has resulted in a dramatic increase in the precision of editing for nucleotide sequences. These editors can target specific locations in a genome, in vivo. The genome editors are being deployed for the development of genetically modified organisms for agriculture and industry, and for gene therapy of inherited human genetic disorders, cancer, and immunotherapy. Experimental and computational studies of structure, binding, activity, dynamics, and folding, reviewed here, have provided valuable insights that have the potential for increasing the functional efficiency of these gene/genome editors. Biochemical and biophysical studies of the specificities of natural and engineered genome editors reveal that increased binding affinity can be detrimental because of the increase of off-target effects and that the engineering and design of genome editors with higher specificity may require modulation and control of the conformational dynamics.

Modulating gene regulation function by chemically controlled transcription factor clustering

Recent studies have suggested that transcriptional protein condensates (or clusters) may play key roles in gene regulation and cell fate determination. However, it remains largely unclear how the gene regulation function is quantitatively tuned by transcription factor (TF) clustering and whether TF clustering may confer emergent behaviors as in cell fate control systems. Here, to address this, we construct synthetic TFs whose clustering behavior can be chemically controlled. Through single-parameter tuning of the system (i.e., TF clustering propensity), we provide lines of evidence supporting the direct transcriptional activation and amplification of target genes by TF clustering. Single-gene imaging suggests that such amplification results from the modulation of transcriptional dynamics. Importantly, TF clustering propensity modulates the gene regulation function by significantly tuning the effective TF binding affinity and to a lesser extent the ultrasensitivity, contributing to bimodality and sustained response behavior that are reminiscent of canonical cell fate control systems. Collectively, these results demonstrate that TF clustering can modulate the gene regulation function to enable emergent behaviors, and highlight the potential applications of chemically controlled protein clustering.

Transcription factor (TF) condensates appear to be pervasive, yet their roles remain debated. Here, the authors use a synthetic biology approach to show that TF clusters causally amplify transcription and can confer bimodality and “memory”.

Mediator Engineering of Saccharomyces cerevisiae To Improve Multidimensional Stress Tolerance

Saccharomyces cerevisiae is a well-performing workhorse in chemical production, which encounters complex environmental stresses during industrial processes. We constructed a multiple stress tolerance mutant, Med15^V76R/R84K, that was obtained by engineering the KIX domain of Mediator tail subunit Med15. Med15^V76R/R84K interacted with transcription factor Hap5 to improve ARV1 expression for sterol homeostasis for decreasing membrane fluidity and thereby enhancing acid tolerance. Med15^V76R/R84K interacted with transcription factor Mga2 to improve GIT1 expression for phospholipid biosynthesis for increasing membrane integrity and thereby improving oxidative tolerance. Med15^V76R/R84K interacted with transcription factor Aft1 to improve NFT1 expression for inorganic ion transport for reducing membrane permeability and thereby enhancing osmotic tolerance. Based on this Med15 mutation, Med15^V76R/R84K, the engineered S. cerevisiae strain, showed a 28.1% increase in pyruvate production in a 1.0-L bioreactor compared to that of S. cerevisiae with its native Med15. These results indicated that Mediator engineering provides a potential alternative for improving multidimensional stress tolerance in S. cerevisiae. IMPORTANCE This study identified the role of the KIX domain of Mediator tail subunit Med15 in response to acetic acid, H₂O₂, and NaCl in S. cerevisiae. Engineered KIX domain by protein engineering, the mutant strain Med15^V76R/R84K, increased multidimensional stress tolerance and pyruvate production compared with that of S. cerevisiae with its native Med15. The Med15^V76R/R84K could increase membrane related genes expression possibly by enhancing interaction with transcription factor to improve membrane physiological functions under stress conditions.

Orthogonal control of gene expression in plants using synthetic promoters and CRISPR-based transcription factors

BACKGROUND

The construction and application of synthetic genetic circuits is frequently improved if gene expression can be orthogonally controlled, relative to the host. In plants, orthogonality can be achieved via the use of CRISPR-based transcription factors that are programmed to act on natural or synthetic promoters. The construction of complex gene circuits can require multiple, orthogonal regulatory interactions, and this in turn requires that the full programmability of CRISPR elements be adapted to non-natural and non-standard promoters that have few constraints on their design. Therefore, we have developed synthetic promoter elements in which regions upstream of the minimal 35S CaMV promoter are designed from scratch to interact via programmed gRNAs with dCas9 fusions that allow activation of gene expression.

RESULTS

A panel of three, mutually orthogonal promoters that can be acted on by artificial gRNAs bound by CRISPR regulators were designed. Guide RNA expression targeting these promoters was in turn controlled by either Pol III (U6) or ethylene-inducible Pol II promoters, implementing for the first time a fully artificial Orthogonal Control System (OCS). Following demonstration of the complete orthogonality of the designs, the OCS was tied to cellular metabolism by putting gRNA expression under the control of an endogenous plant signaling molecule, ethylene. The ability to form complex circuitry was demonstrated via the ethylene-driven, ratiometric expression of fluorescent proteins in single plants.

CONCLUSIONS

The design of synthetic promoters is highly generalizable to large tracts of sequence space, allowing Orthogonal Control Systems of increasing complexity to potentially be generated at will. The ability to tie in several different basal features of plant molecular biology (Pol II and Pol III promoters, ethylene regulation) to the OCS demonstrates multiple opportunities for engineering at the system level. Moreover, given the fungibility of the core 35S CaMV promoter elements, the derived synthetic promoters can potentially be utilized across a variety of plant species.

Design of Synthetic Mammalian Promoters Using Highly Palindromic Subsequences

To express transgenes in specific cell types and states, promoters for endogenous genes are commonly created by truncating the sequence upstream of the transcriptional start site until the promoter is no longer functional. In this paper, we developed a method to design shorter synthetic mammalian promoters for endogenous genes by concatenating only its highly palindromic subsequences with a minimal core promoter. After developing metrics for palindromic density, analysis across all the human and mouse promoters showed higher palindromic density than expected by random. As experimental demonstrations, we applied the method to the CMV promoter (reduced to 432 nucleotides) and the mouse synapsin-1 promoter (383 nucleotides) to express fluorescent protein as reporters. Remarkably, the highly palindromic subsequences of these synthetic promoters contained sites important for strong constitutive expression and neuron-specific expression. As a resource to the community, we created enhancer sequences for all the human and mouse promoters.

The evolution of synthetic receptor systems

Receptors enable cells to detect, process and respond to information about their environments. Over the past two decades, synthetic biologists have repurposed physical parts and concepts from natural receptors to engineer synthetic receptors. These technologies implement customized sense-and-respond programs that link a cell's interaction with extracellular and intracellular cues to user-defined responses. When combined with tools for information processing, these advances enable programming of sophisticated customized functions. In recent years, the library of synthetic receptors and their capabilities has substantially evolved-a term we employ here to mean systematic improvement and expansion. Here, we survey the existing mammalian synthetic biology toolkit of protein-based receptors and signal-processing components, highlighting efforts to evolve and integrate some of the foundational synthetic receptor systems. We then propose a generalized strategy for engineering and improving receptor systems to meet defined functional objectives called a 'metric-enabled approach for synthetic receptor engineering' (MEASRE).

Peptide-Dependent Growth in Yeast via Fine-Tuned Peptide/GPCR-Activated Essential Gene Expression

Building multicellular microbial consortia that communicate with each other and perform programmed functionalities is the next milestone for synthetic biology. Achieving cell-cell communication within these communities requires programming of the transduction of an extracellular signal into a customized intracellular response. G-protein-coupled receptors (GPCRs) are attractive candidates for engineering signal transduction as they can sense extracellular events with high sensitivity and specificity and transduce them into complex intracellular programs. We recently developed a scalable cell-cell communication language based on fungal mating GPCRs and their secreted peptide ligands. This language allows the assembly of engineered yeast strains into multicellular communication networks and allows them to be made interdependent by peptide signaling. In peptide signaling, one cell secretes a peptide that supports the growth of another cell at nanomolar concentrations, a scalable approach for engineering interdependence. Here we address the challenge of correlating the doubling time of Saccharomyces cerevisiae cells with an increasing external peptide concentration by linking GPCR activation to the expression of an essential gene. The required fine-tuning of downstream signaling is achieved via the transcriptional titration of a set of orthogonal GPCR-activated transcription factors, a series of corresponding promoters with different output dynamics, and the use of chemically recoded peptide ligands with varying activation potentials. As such, our work establishes three control points that allow the tuning of the basal and maximal activation of the GPCR response, fold change activation, and response sensitivity. The presented results enable the implementation of peptide-dependent and peptide-tunable growth but could also facilitate the design and calibration of more complex GPCR-controlled synthetic functionality in the future.

Synthetic multistability in mammalian cells

In multicellular organisms, gene regulatory circuits generate thousands of molecularly distinct, mitotically heritable states through the property of multistability. Designing synthetic multistable circuits would provide insight into natural cell fate control circuit architectures and would allow engineering of multicellular programs that require interactions among distinct cell types. We created MultiFate, a naturally inspired, synthetic circuit that supports long-term, controllable, and expandable multistability in mammalian cells. MultiFate uses engineered zinc finger transcription factors that transcriptionally self-activate as homodimers and mutually inhibit one another through heterodimerization. Using a model-based design, we engineered MultiFate circuits that generate as many as seven states, each stable for at least 18 days. MultiFate permits controlled state switching and modulation of state stability through external inputs and can be expanded with additional transcription factors. These results provide a foundation for engineering multicellular behaviors in mammalian cells.