Programmable protein circuit design

Microbial Synthetic Epigenetic Tools Design and Applications

Microbial synthetic epigenetics offers significant opportunities for the design of synthetic biology tools by leveraging reversible gene control mechanisms without altering DNA sequences. However, limited understanding and a lack of technologies for thorough analysis of the mechanisms behind epigenetic modifications have hampered their utilization in biotechnological applications. In this review, we explore advancements in developing epigenetic-based synthetic gene regulatory tools at both transcriptional and post-transcriptional levels. Furthermore, we examine strategies developed to construct epigenetic-based circuits that provide controllable and stable gene regulation, aiming to boost the performance of microbial chassis cells. Finally, we discuss the current challenges and perspectives in the development of synthetic epigenetic tools.

On knowing a gene: A distributional hypothesis of gene function

As words can have multiple meanings that depend on sentence context, genes can have various functions that depend on the surrounding biological system. This pleiotropic nature of gene function is limited by ontologies, which annotate gene functions without considering biological contexts. We contend that the gene function problem in genetics may be informed by recent technological leaps in natural language processing, in which representations of word semantics can be automatically learned from diverse language contexts. In contrast to efforts to model semantics as "is-a" relationships in the 1990s, modern distributional semantics represents words as vectors in a learned semantic space and fuels current advances in transformer-based models such as large language models and generative pre-trained transformers. A similar shift in thinking of gene functions as distributions over cellular contexts may enable a similar breakthrough in data-driven learning from large biological datasets to inform gene function.

Building RNA-Mediated Artificial Signaling Pathways between Endogenous Genes

ConspectusSophisticated genetic networks play a pivotal role in orchestrating cellular responses through intricate signaling pathways across diverse environmental conditions. Beyond the inherent complexity of natural cellular signaling networks, the construction of artificial signaling pathways (ASPs) introduces a vast array of possibilities for reshaping cellular responses, enabling programmable control of living organisms. ASPs can be integrated with existing cellular networks and redirect output responses as desired, allowing seamless communication and coordination with other cellular processes, thereby achieving designable transduction within cells. Among diversified ASPs, establishing connections between originally independent endogenous genes is of particular significance in modifying the genetic networks, so that cells can be endowed with new capabilities to sense and deal with abnormal factors related to differentiated gene expression (i.e., solve the issues of the aberrant gene expression induced by either external or internal stimuli). In a typical scenario, the two genes X and Y in the cell are originally expressed independently. After the introduction of an ASP, changes in the expression of gene X may exert a designed impact on gene Y, subsequently inducing the cellular response related to gene Y. If X represents a disease signal and Y serves as a therapeutic module, the introduction of the ASP empowers cells with a new spontaneous defense system to handle potential risks, which holds great potential for both fundamental and translational studies.In this Account, we primarily review our endeavors in the construction of RNA-mediated ASPs between endogenous genes that can respond to differentiated RNA expression. In contrast to other molecules that may be restricted to specific pathways, synthetic RNA circuits can be easily utilized and expanded as a general platform for constructing ASPs with a high degree of programmability and tunability for diversified functionalities through predictable Watson-Crick base pairing. We first provide an overview of recent advancements in RNA-based genetic circuits, encompassing but not limited to utilization of RNA toehold switches, siRNA and CRISPR systems. Despite notable progress, most reported RNA circuits have to contain at least one exogenous RNA X as input or one engineered RNA Y as a target, which is not suitable for establishing endogenous gene connections. While exogenous RNAs can be engineered and controlled as desired, constructing a general and efficient platform for manipulation of naturally occurring RNAs poses a formidable challenge, especially for the mammalian system. With a focus on this goal, we are devoted to developing efficient strategies to manipulate cell responses by establishing RNA-mediated ASPs between endogenous genes, particularly in mammalian cells. Our step-by-step progress in engineering customized cell signaling circuits, from bacterial cells to mammalian cells, from gene expression regulation to phenotype control, and from small RNA to long mRNA of low abundance and more complex secondary structures, is systematically described. Finally, future perspectives and potential applications of these RNA-mediated ASPs between endogenous genes are also discussed.

Integrating microfluidics and synthetic biology: advancements and diverse applications across organisms

Synthetic biology is the design and modification of biological systems for specific functions, integrating several disciplines like engineering, genetics, and computer science. The field of synthetic biology is to understand biological processes within host organisms through the manipulation and regulation of their genetic pathways and the addition of biocontrol circuits to enhance their production capabilities. This pursuit serves to address global challenges spanning diverse domains that are difficult to tackle through conventional routes of production. Despite its impact, achieving precise, dynamic, and high-throughput manipulation of biological processes is still challenging. Microfluidics offers a solution to those challenges, enabling controlled fluid handling at the microscale, offering lower reagent consumption, faster analysis of biochemical reactions, automation, and high throughput screening. In this review, we diverge from conventional focus on automating the synthetic biology design-build-test-learn cycle, and instead, focus on microfluidic platforms and their role in advancing synthetic biology through its integration with host organisms - bacterial cells, yeast, fungi, animal cells - and cell-free systems. The review illustrates how microfluidic devices have been instrumental in understanding biological systems by showcasing microfluidics as an essential tool to create synthetic genetic circuits, pathways, and organisms within controlled environments. In conclusion, we show how microfluidics expedite synthetic biology applications across diverse domains including but not limited to personalized medicine, bioenergy, and agriculture.

Synthetic protein circuits for programmable control of mammalian cell death

Natural cell death pathways such as apoptosis and pyroptosis play dual roles: they eliminate harmful cells and modulate the immune system by dampening or stimulating inflammation. Synthetic protein circuits capable of triggering specific death programs in target cells could similarly remove harmful cells while appropriately modulating immune responses. However, cells actively influence their death modes in response to natural signals, making it challenging to control death modes. Here, we introduce naturally inspired "synpoptosis" circuits that proteolytically regulate engineered executioner proteins and mammalian cell death. These circuits direct cell death modes, respond to combinations of protease inputs, and selectively eliminate target cells. Furthermore, synpoptosis circuits can be transmitted intercellularly, offering a foundation for engineering synthetic killer cells that induce desired death programs in target cells without self-destruction. Together, these results lay the groundwork for programmable control of mammalian cell death.

Post-Transcriptional Modular Synthetic Receptors

Inspired by the power of transcriptional synthetic receptors and hoping to complement them to expand the toolbox for cell engineering, we establish LIDAR (Ligand-Induced Dimerization Activating RNA editing), a modular post-transcriptional synthetic receptor platform that harnesses RNA editing by ADAR. LIDAR is compatible with various receptor architectures in different cellular contexts, and enables the sensing of diverse ligands and the production of functional outputs. Furthermore, LIDAR can sense orthogonal signals in the same cell and produce synthetic spatial patterns, potentially enabling the programming of complex multicellular behaviors. Finally, LIDAR is compatible with compact encoding and can be delivered by synthetic mRNA. Thus, LIDAR expands the family of synthetic receptors, holding the promise to empower basic research and therapeutic applications.

Chemical Logic Gates on Active Colloids

Recent studies have shown that active colloidal motors using enzymatic reactions for propulsion hold special promise for applications in fields ranging from biology to material science. It will be desirable to have active colloids with capability of computation so that they can act autonomously to sense their surroundings and alter their own dynamics. It is shown how small chemical networks that make use of enzymatic chemical reactions on the colloid surface can be used to construct motor-based chemical logic gates. The basic features of coupled enzymatic reactions that are responsible for propulsion and underlie the construction and function of chemical gates are described using continuum theory and molecular simulation. Examples are given that show how colloids with specific chemical logic gates, can perform simple sensing tasks. Due to the diverse functions of different enzyme gates, operating alone or in circuits, the work presented here supports the suggestion that synthetic motors using such gates could be designed to operate in an autonomous way in order to complete complicated tasks.

A molecular proximity sensor based on an engineered, dual-component guide RNA

One of the goals of synthetic biology is to enable the design of arbitrary molecular circuits with programmable inputs and outputs. Such circuits bridge the properties of electronic and natural circuits, processing information in a predictable manner within living cells. Genome editing is a potentially powerful component of synthetic molecular circuits, whether for modulating the expression of a target gene or for stably recording information to genomic DNA. However, programming molecular events such as protein-protein interactions or induced proximity as triggers for genome editing remains challenging. Here we demonstrate a strategy termed "P3 editing", which links protein-protein proximity to the formation of a functional CRISPRCas9 dual-component guide RNA. By engineering the crRNA:tracrRNA interaction, we demonstrate that various known protein-protein interactions, as well as the chemically-induced dimerization of protein domains, can be used to activate prime editing or base editing in human cells. Additionally, we explore how P3 editing can incorporate outputs from ADAR-based RNA sensors, potentially allowing specific RNAs to induce specific genome edits within a larger circuit. Our strategy enhances the controllability of CRISPR-based genome editing, facilitating its use in synthetic molecular circuits deployed in living cells.

Harnessing Catalytic RNA Circuits for Construction of Artificial Signaling Pathways in Mammalian Cells

Engineering of genetic networks with artificial signaling pathways (ASPs) can reprogram cellular responses and phenotypes under different circumstances for a variety of diagnostic and therapeutic purposes. However, construction of ASPs between originally independent endogenous genes in mammalian cells is highly challenging. Here we report an amplifiable RNA circuit that can theoretically build regulatory connections between any endogenous genes in mammalian cells. We harness the system of catalytic hairpin assembly with combination of controllable CRISPR-Cas9 function to transduce the signals from distinct messenger RNA expression of trigger genes into manipulation of target genes. Through introduction of these RNA-based genetic circuits, mammalian cells are endowed with autonomous capabilities to sense the changes of RNA expression either induced by ligand stimuli or from various cell types and control the cellular responses and fates via apoptosis-related ASPs. Our design provides a generalized platform for construction of ASPs inside the genetic networks of mammalian cells based on differentiated RNA expression.

Small-Molecule Regulators for Gene Switches to Program Mammalian Cell Behaviour

Synthetic or natural small molecules have been extensively employed as trigger signals or inducers to regulate engineered gene circuits introduced into living cells in order to obtain desired outputs in a controlled and predictable manner. Here, we provide an overview of small molecules used to drive synthetic-biology-based gene circuits in mammalian cells, together with examples of applications at different levels of control, including regulation of DNA manipulation, RNA synthesis and editing, and protein synthesis, maturation, and trafficking. We also discuss the therapeutic potential of these small-molecule-responsive gene circuits, focusing on the advantages and disadvantages of using small molecules as triggers, the mechanisms involved, and the requirements for selecting suitable molecules, including efficiency, specificity, orthogonality, and safety. Finally, we explore potential future directions for translation of these devices to clinical medicine.

Leveraging yeast sequestration to study and engineer posttranslational modification enzymes

Enzymes that catalyze posttranslational modifications (PTMs) of peptides and proteins (PTM-enzymes)-proteases, protein ligases, oxidoreductases, kinases, and other transferases-are foundational to our understanding of health and disease and empower applications in chemical biology, synthetic biology, and biomedicine. To fully harness the potential of PTM-enzymes, there is a critical need to decipher their enzymatic and biological mechanisms, develop molecules that can probe and modulate them, and endow them with improved and novel functions. These objectives are contingent upon implementation of high-throughput functional screens and selections that interrogate large sequence libraries to isolate desired PTM-enzyme properties. This review discusses the principles of Saccharomyces cerevisiae organelle sequestration to study and engineer PTM-enzymes. These include outer membrane sequestration, specifically methods that modify yeast surface display, and cytoplasmic sequestration based on enzyme-mediated transcription activation. Furthermore, we present a detailed discussion of yeast endoplasmic reticulum sequestration for the first time. Where appropriate, we highlight the major features and limitations of different systems, specifically how they can measure and control enzyme catalytic efficiencies. Taken together, yeast-based high-throughput sequestration approaches significantly lower the barrier to understanding how PTM-enzymes function and how to reprogram them.

Synthetic biological neural networks: From current implementations to future perspectives

Artificial neural networks, inspired by the biological networks of the human brain, have become game-changing computing models in modern computer science. Inspired by their wide scope of applications, synthetic biology strives to create their biological counterparts, which we denote synthetic biological neural networks (SYNBIONNs). Their use in the fields of medicine, biosensors, biotechnology, and many more shows great potential and presents exciting possibilities. So far, many different synthetic biological networks have been successfully constructed, however, SYNBIONN implementations have been sparse. The latter are mostly based on neural networks pretrained in silico and being heavily dependent on extensive human input. In this paper, we review current implementations and models of SYNBIONNs. We briefly present the biological platforms that show potential for designing and constructing perceptrons and/or multilayer SYNBIONNs. We explore their future possibilities along with the challenges that must be overcome to successfully implement a scalable in vivo biological neural network capable of online learning.

Degron-based bioPROTACs for controlling signaling in CAR T cells

Chimeric antigen receptor (CAR) T cells have made a tremendous impact in the clinic, but potent signaling through the CAR can be detrimental to treatment safety and efficacy. The use of protein degradation to control CAR signaling can address these issues in pre-clinical models. Existing strategies for regulating CAR stability rely on small molecules to induce systemic degradation. In contrast to small molecule regulation, genetic circuits offer a more precise method to control CAR signaling in an autonomous, cell-by-cell fashion. Here, we describe a programmable protein degradation tool that adopts the framework of bioPROTACs, heterobifunctional proteins that are composed of a target recognition domain fused to a domain that recruits the endogenous ubiquitin proteasome system. We develop novel bioPROTACs that utilize a compact four residue degron and demonstrate degradation of cytosolic and membrane protein targets using either a nanobody or synthetic leucine zipper as a protein binder. Our bioPROTACs exhibit potent degradation of CARs and can inhibit CAR signaling in primary human T cells. We demonstrate the utility of our bioPROTACs by constructing a genetic circuit to degrade the tyrosine kinase ZAP70 in response to recognition of a specific membrane-bound antigen. This circuit is able to disrupt CAR T cell signaling only in the presence of a specific cell population. These results suggest that bioPROTACs are a powerful tool for expanding the cell engineering toolbox for CAR T cells.

Compact RNA sensors for increasingly complex functions of multiple inputs

Designing single molecules that compute general functions of input molecular partners represents a major unsolved challenge in molecular design. Here, we demonstrate that high-throughput, iterative experimental testing of diverse RNA designs crowdsourced from Eterna yields sensors of increasingly complex functions of input oligonucleotide concentrations. After designing single-input RNA sensors with activation ratios beyond our detection limits, we created logic gates, including challenging XOR and XNOR gates, and sensors that respond to the ratio of two inputs. Finally, we describe the OpenTB challenge, which elicited 85-nucleotide sensors that compute a score for diagnosing active tuberculosis, based on the ratio of products of three gene segments. Building on OpenTB design strategies, we created an algorithm Nucleologic that produces similarly compact sensors for the three-gene score based on RNA and DNA. These results open new avenues for diverse applications of compact, single molecule sensors previously limited by design complexity.

Programmable synthetic receptors: the next-generation of cell and gene therapies

Cell and gene therapies hold tremendous promise for treating a range of difficult-to-treat diseases. However, concerns over the safety and efficacy require to be further addressed in order to realize their full potential. Synthetic receptors, a synthetic biology tool that can precisely control the function of therapeutic cells and genetic modules, have been rapidly developed and applied as a powerful solution. Delicately designed and engineered, they can be applied to finetune the therapeutic activities, i.e., to regulate production of dosed, bioactive payloads by sensing and processing user-defined signals or biomarkers. This review provides an overview of diverse synthetic receptor systems being used to reprogram therapeutic cells and their wide applications in biomedical research. With a special focus on four synthetic receptor systems at the forefront, including chimeric antigen receptors (CARs) and synthetic Notch (synNotch) receptors, we address the generalized strategies to design, construct and improve synthetic receptors. Meanwhile, we also highlight the expanding landscape of therapeutic applications of the synthetic receptor systems as well as current challenges in their clinical translation.

Cell Surface Engineering Tools for Programming Living Assemblies

Breakthroughs in precision cell surface engineering tools are supporting the rapid development of programmable living assemblies with valuable features for tackling complex biological problems. Herein, the authors overview the most recent technological advances in chemically- and biologically-driven toolboxes for engineering mammalian cell surfaces and triggering their assembly into living architectures. A particular focus is given to surface engineering technologies for enabling biomimetic cell-cell social interactions and multicellular cell-sorting events. Further advancements in cell surface modification technologies may expand the currently available bioengineering toolset and unlock a new generation of personalized cell therapeutics with clinically relevant biofunctionalities. The combination of state-of-the-art cell surface modifications with advanced biofabrication technologies is envisioned to contribute toward generating living materials with increasing tissue/organ-mimetic bioactivities and therapeutic potential.

Design and mathematical analysis of activating transcriptional amplifiers that enable modular temporal control in synthetic juxtacrine circuits

The ability to control mammalian cells such that they self-organize or enact therapeutic effects as desired has incredible implications. Not only would it further our understanding of native processes such as development and the immune response, but it would also have powerful applications in medical fields such as regenerative medicine and immunotherapy. This control is typically obtained by synthetic circuits that use synthetic receptors, but control remains incomplete. The synthetic juxtacrine receptors (SJRs) are widely used as they are fully modular and enable spatial control, but they have limited gene expression amplification and temporal control. As these are integral facets to cell control, I therefore designed transcription factor based amplifiers that amplify gene expression and enable unidirectional temporal control by prolonging duration of target gene expression. Using a validated in silico framework for SJR signaling, I combined these amplifiers with SJRs and show that these SJR amplifier circuits can direct spatiotemporal patterning and improve the quality of self-organization. I then show that these circuits can improve chimeric antigen receptor (CAR) T cell tumor killing against various heterogenous antigen expression tumors. These amplifiers are flexible tools that improve control over SJR based circuits with both basic and therapeutic applications.

Epistemology of synthetic biology: a new theoretical framework based on its potential objects and objectives

Synthetic biology is a new research field which attempts to understand, modify, and create new biological entities by adopting a modular and systemic conception of the living organisms. The development of synthetic biology has generated a pluralism of different approaches, bringing together a set of heterogeneous practices and conceptualizations from various disciplines, which can lead to confusion within the synthetic biology community as well as with other biological disciplines. I present in this manuscript an epistemological analysis of synthetic biology in order to better define this new discipline in terms of objects of study and specific objectives. First, I present and analyze the principal research projects developed at the foundation of synthetic biology, in order to establish an overview of the practices in this new emerging discipline. Then, I analyze an important scientometric study on synthetic biology to complete this overview. Afterwards, considering this analysis, I suggest a three-level classification of the object of study for synthetic biology (which are different kinds of living entities that can be built in the laboratory), based on three successive criteria: structural hierarchy, structural origin, functional origin. Finally, I propose three successively linked objectives in which synthetic biology can contribute (where the achievement of one objective led to the development of the other): interdisciplinarity collaboration (between natural, artificial, and theoretical sciences), knowledge of natural living entities (past, present, future, and alternative), pragmatic definition of the concept of "living" (that can be used by biologists in different contexts). Considering this new theoretical framework, based on its potential objects and objectives, I take the position that synthetic biology has not only the potential to develop its own new approach (which includes methods, objects, and objectives), distinct from other subdisciplines in biology, but also the ability to develop new knowledge on living entities.

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.

Rational design of microRNA-responsive switch for programmable translational control in mammalian cells

Artificial RNA translation modulation usually relies on multiple components, such as RNA binding proteins (RBPs) or microRNAs (miRNAs) for off-switches and double-inverter cascades for on-switches. Recently, translational circular RNAs (circRNAs) were developed as promising alternatives for linear messenger RNAs (mRNAs). However, circRNAs still lack straightforward and programmable translation control strategies. Here, we rationally design a programmable miRNA-responsive internal ribosome entry site (IRES) translation activation and repression (PROMITAR) platform capable of implementing miRNA-based translation upregulation and downregulation in a single RNA construct. Based on the PROMITAR platform, we construct logic gates and cell-type classifier circRNAs and successfully identify desired mammalian cell types. We also demonstrate the potential therapeutic application of our platform for targeted cancer cell killing by encoding a cytotoxic protein in our engineered circRNAs. We expect our platform to expand the toolbox for RNA synthetic biology and provide an approach for potential biomedical applications in the future.

Chemical reaction motifs driving non-equilibrium behaviours in phase separating materials

Chemical reactions that couple to systems that phase separate have been implicated in diverse contexts from biology to materials science. However, how a particular set of chemical reactions (chemical reaction network, CRN) would affect the behaviours of a phase separating system is difficult to fully predict theoretically. In this paper, we analyse a mean field theory coupling CRNs to a combined system of phase separating and non-phase separating materials and analyse how the properties of the CRNs affect different classes of non-equilibrium behaviour: microphase separation or temporally oscillating patterns. We examine the problem of achieving microphase separated condensates by statistical analysis of the Jacobians, of which the most important motifs are negative feedback of the phase separating component and combined inhibition/activation by the non-phase separating components. We then identify CRN motifs that are likely to yield microphase by examining randomly generated networks and parameters. Molecular sequestration of the phase separating motif is shown to be the most robust towards yielding microphase separation. Subsequently, we find that dynamics of the phase separating species is promoted most easily by inducing oscillations in the diffusive components coupled to the phase separating species. Our results provide guidance towards the design of CRNs that manage the formation, dissolution and organization of compartments.

Compact Programmable Control of Protein Secretion in Mammalian Cells

Synthetic biology currently holds immense potential to engineer the spatiotemporal control of intercellular signals for biomedicine. Programming behaviors using protein-based circuits has advantages over traditional gene circuits such as compact delivery and direct interactions with signaling proteins. Previously, we described a generalizable platform called RELEASE to enable the control of intercellular signaling through the proteolytic removal of ER-retention motifs compatible with pre-existing protease-based circuits. However, these tools lacked the ability to reliably program complex expression profiles and required numerous proteases, limiting delivery options. Here, we harness the recruitment and antagonistic behavior of endogenous 14-3-3 proteins to create RELEASE-NOT to turn off protein secretion in response to protease activity. By combining RELEASE and RELEASE-NOT, we establish a suite of protein-level processing and output modules called Compact RELEASE (compRELEASE). This innovation enables functions such as logic processing and analog signal filtering using a single input protease. Furthermore, we demonstrate the compactness of the post-translational design by using polycistronic single transcripts to engineer cells to control protein secretion via lentiviral integration and leverage mRNA delivery to selectively express cell surface proteins only in engineered cells harboring inducible proteases. CompRELEASE enables complex control of protein secretion and enhances the potential of synthetic protein circuits for therapeutic applications, while minimizing the overall genetic payload.

Systems Medicine for Precise Targeting of Glioblastoma

Glioblastoma (GBM) is a malignant cancer that is fatal even after standard therapy and the effects of current available therapeutics are not promising due its complex and evolving epigenetic and genetic profile. The mysteries that lead to GBM intratumoral heterogeneity and subtype transitions are not entirely clear. Systems medicine is an approach to view the patient in a whole picture integrating systems biology and synthetic biology along with computational techniques. Since the GBM oncogenesis involves genetic mutations, various therapies including gene therapeutics based on CRISPR-Cas technique, MicroRNAs, and implanted synthetic cells endowed with synthetic circuits against GBM with neural stem cells and mesenchymal stem cells acting as potential vehicles carrying therapeutics via the intranasal route, avoiding the risks of invasive methods in order to reach the GBM cells in the brain are discussed and proposed in this review. Systems medicine approach is a rather novel strategy, and since the GBM of a patient is complex and unique, thus to devise an individualized treatment strategy to tailor personalized multimodal treatments for the individual patient taking into account the phenotype of the GBM, the unique body health profile of the patient and individual responses according to the systems medicine concept might show potential to achieve optimum effects.

Creation of Environmentally Friendly Super "Dinitrotoluene Scavenger" Plants

Pervasive environmental contamination due to the uncontrolled dispersal of 2,4-dinitrotoluene (2,4-DNT) represents a substantial global health risk, demanding urgent intervention for the removal of this detrimental compound from affected sites and the promotion of ecological restoration. Conventional methodologies, however, are energy-intensive, susceptible to secondary pollution, and may inadvertently increase carbon emissions. In this study, a 2,4-DNT degradation module is designed, assembled, and validated in rice plants. Consequently, the modified rice plants acquire the ability to counteract the phytotoxicity of 2,4-DNT. The most significant finding of this study is that these modified rice plants can completely degrade 2,4-DNT into innocuous substances and subsequently introduce them into the tricarboxylic acid cycle. Further, research reveals that the modified rice plants enable the rapid phytoremediation of 2,4-DNT-contaminated soil. This innovative, eco-friendly phytoremediation approach for dinitrotoluene-contaminated soil and water demonstrates significant potential across diverse regions, substantially contributing to carbon neutrality and sustainable development objectives by repurposing carbon and energy from organic contaminants.

Massively parallel protein-protein interaction measurement by sequencing (MP3-seq) enables rapid screening of protein heterodimers

Protein-protein interactions (PPIs) regulate many cellular processes, and engineered PPIs have cell and gene therapy applications. Here we introduce massively parallel protein-protein interaction measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast-two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs, and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Finally, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics simulation energy terms to predict MP3-seq values. We find that AF-M and AF-M complex prediction-based models could be valuable for pre-screening interactions, but that measuring interactions experimentally remains necessary to rank their strengths quantitatively.

Algorithms for de-novo sequencing of peptides by tandem mass spectrometry: A review

Peptide sequencing is of great significance to fundamental and applied research in the fields such as chemical, biological, medicinal and pharmaceutical sciences. With the rapid development of mass spectrometry and sequencing algorithms, de-novo peptide sequencing using tandem mass spectrometry (MS/MS) has become the main method for determining amino acid sequences of novel and unknown peptides. Advanced algorithms allow the amino acid sequence information to be accurately obtained from MS/MS spectra in short time. In this review, algorithms from exhaustive search to the state-of-art machine learning and neural network for high-throughput and automated de-novo sequencing are introduced and compared. Impacts of datasets on algorithm performance are highlighted. The current limitations and promising direction of de-novo peptide sequencing are also discussed in this review.

Enabling technology and core theory of synthetic biology

Synthetic biology provides a new paradigm for life science research ("build to learn") and opens the future journey of biotechnology ("build to use"). Here, we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology, including synthesis and assembly of a genome, DNA storage, gene editing, molecular evolution and de novo design of function proteins, cell and gene circuit engineering, cell-free synthetic biology, artificial intelligence (AI)-aided synthetic biology, as well as biofoundries. We also introduce the concept of quantitative synthetic biology, which is guiding synthetic biology towards increased accuracy and predictability or the real rational design. We conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.

Deploying synthetic coevolution and machine learning to engineer protein-protein interactions

Fine-tuning of protein-protein interactions occurs naturally through coevolution, but this process is difficult to recapitulate in the laboratory. We describe a platform for synthetic protein-protein coevolution that can isolate matched pairs of interacting muteins from complex libraries. This large dataset of coevolved complexes drove a systems-level analysis of molecular recognition between Z domain-affibody pairs spanning a wide range of structures, affinities, cross-reactivities, and orthogonalities, and captured a broad spectrum of coevolutionary networks. Furthermore, we harnessed pretrained protein language models to expand, in silico, the amino acid diversity of our coevolution screen, predicting remodeled interfaces beyond the reach of the experimental library. The integration of these approaches provides a means of simulating protein coevolution and generating protein complexes with diverse molecular recognition properties for biotechnology and synthetic biology.

Multi-input Drug-Controlled Switches of Mammalian Gene Expression Based on Engineered Nuclear Hormone Receptors

Protein-based switches that respond to different inputs to regulate cellular outputs, such as gene expression, are central to synthetic biology. For increased controllability, multi-input switches that integrate several cooperating and competing signals for the regulation of a shared output are of particular interest. The nuclear hormone receptor (NHR) superfamily offers promising starting points for engineering multi-input-controlled responses to clinically approved drugs. Starting from the VgEcR/RXR pair, we demonstrate that novel (multi)drug regulation can be achieved by exchange of the ecdysone receptor (EcR) ligand binding domain (LBD) for other human NHR-derived LBDs. For responses activated to saturation by an agonist for the first LBD, we show that outputs can be boosted by an agonist targeting the second LBD. In combination with an antagonist, output levels are tunable by up to three simultaneously present small-molecule drugs. Such high-level control validates NHRs as a versatile, engineerable platform for programming multidrug-controlled responses.

Reprogramming cellular metabolism to increase the efficiency of microbial cell factories

Recent studies are increasingly focusing on advanced biotechnological tools, self-adjusting smart microorganisms, and artificial intelligent networks, to engineer microorganisms with various functions. Microbial cell factories are a vital platform for improving the bioproduction of medicines, biofuels, and biomaterials from renewable carbon sources. However, these processes are significantly affected by cellular metabolism, and boosting the efficiency of microbial cell factories remains a challenge. In this review, we present a strategy for reprogramming cellular metabolism to enhance the efficiency of microbial cell factories for chemical biosynthesis, which improves our understanding of microbial physiology and metabolic control. Current methods are mainly focused on synthetic pathways, metabolic resources, and cell performance. This review highlights the potential biotechnological strategy to reprogram cellular metabolism and provide novel guidance for designing more intelligent industrial microbes with broader applications in this growing field.

The computational capabilities of many-to-many protein interaction networks

Many biological circuits comprise sets of protein variants that interact with one another in a many-to-many, or promiscuous, fashion. These architectures can provide powerful computational capabilities that are especially critical in multicellular organisms. Understanding the principles of biochemical computations in these circuits could allow more precise control of cellular behaviors. However, these systems are inherently difficult to analyze, due to their large number of interacting molecular components, partial redundancies, and cell context dependence. Here, we discuss recent experimental and theoretical advances that are beginning to reveal how promiscuous circuits compute, what roles those computations play in natural biological contexts, and how promiscuous architectures can be applied for the design of synthetic multicellular behaviors.

Multi-input drug-controlled switches of mammalian gene expression based on engineered nuclear hormone receptors

Protein-based switches that respond to different inputs to regulate cellular outputs, such as gene expression, are central to synthetic biology. For increased controllability, multi-input switches that integrate several cooperating and competing signals for the regulation of a shared output are of particular interest. The nuclear hormone receptor (NHR) superfamily offers promising starting points for engineering multi-input-controlled responses to clinically approved drugs. Starting from the VgEcR/RXR pair, we demonstrate that novel (multi-)drug regulation can be achieved by exchange of the ecdysone receptor (EcR) ligand binding domain (LBD) for other human NHR-derived LBDs. For responses activated to saturation by an agonist for the first LBD, we show that outputs can be boosted by an agonist targeting the second LBD. In combination with an antagonist, output levels are tunable by up to three simultaneously present small-molecule drugs. Such high-level control validates NHRs as a versatile, engineerable platform for programming multi-drug-controlled responses.

The cyclic peptide G4CP2 enables the modulation of galactose metabolism in yeast by interfering with GAL4 transcriptional activity

Genetically-encoded combinatorial peptide libraries are convenient tools to identify peptides to be used as therapeutics, antimicrobials and functional synthetic biology modules. Here, we report the identification and characterization of a cyclic peptide, G4CP2, that interferes with the GAL4 protein, a transcription factor responsible for the activation of galactose catabolism in yeast and widely exploited in molecular biology. G4CP2 was identified by screening CYCLIC, a Yeast Two-Hybrid-based combinatorial library of cyclic peptides developed in our laboratory. G4CP2 interferes with GAL4-mediated activation of galactose metabolic enzymes both when expressed intracellularly, as a recombinant peptide, and when provided exogenously, as a chemically-synthesized cyclic peptide. Our results support the application of G4CP2 in microbial biotechnology and, additionally, demonstrate that CYCLIC can be used as a tool for the rapid identification of peptides, virtually without any limitations with respect to the target protein. The possible biotechnological applications of cyclic peptides are also discussed.

Dynamic RNA synthetic biology: new principles, practices and potential

An increased appreciation of the role of RNA dynamics in governing RNA function is ushering in a new wave of dynamic RNA synthetic biology. Here, we review recent advances in engineering dynamic RNA systems across the molecular, circuit and cellular scales for important societal-scale applications in environmental and human health, and bioproduction. For each scale, we introduce the core concepts of dynamic RNA folding and function at that scale, and then discuss technologies incorporating these concepts, covering new approaches to engineering riboswitches, ribozymes, RNA origami, RNA strand displacement circuits, biomaterials, biomolecular condensates, extracellular vesicles and synthetic cells. Considering the dynamic nature of RNA within the engineering design process promises to spark the next wave of innovation that will expand the scope and impact of RNA biotechnologies.

Design and engineering of genetically encoded protein biosensors for small molecules

Genetically encoded protein biosensors controlled by small organic molecules are valuable tools for many biotechnology applications, including control of cellular decisions in living cells. Here, we review recent advances in protein biosensor design and engineering for binding to novel ligands. We categorize sensor architecture as either integrated or portable, where portable biosensors uncouple molecular recognition from signal transduction. Proposed advances to improve portable biosensor development include standardizing a limited set of protein scaffolds, and automating ligand-compatibility screening and ligand-protein-interface design.

Recognition of a Clickable Abasic Site Analog by DNA Polymerases and DNA Repair Enzymes

Azide–alkyne cycloaddition (“click chemistry”) has found wide use in the analysis of molecular interactions in living cells. 5-ethynyl-2-(hydroxymethyl)tetrahydrofuran-3-ol (EAP) is a recently developed apurinic/apyrimidinic (AP) site analog functionalized with an ethynyl moiety, which can be introduced into cells in DNA constructs to perform labeling or cross-linking in situ. However, as a non-natural nucleoside, EAP could be subject to removal by DNA repair and misreading by DNA polymerases. Here, we investigate the interaction of this clickable AP site analog with DNA polymerases and base excision repair enzymes. Similarly to the natural AP site, EAP was non-instructive and followed the “A-rule”, directing residual but easily detectable incorporation of dAMP by E. coli DNA polymerase I Klenow fragment, bacteriophage RB69 DNA polymerase and human DNA polymerase β. On the contrary, EAP was blocking for DNA polymerases κ and λ. EAP was an excellent substrate for the major human AP endonuclease APEX1 and E. coli AP exonucleases Xth and Nfo but was resistant to the AP lyase activity of DNA glycosylases. Overall, our data indicate that EAP, once within a cell, would represent a replication block and would be removed through an AP endonuclease-initiated long-patch base excision repair pathway.

Design of programmable post-translational switch control platform for on-demand protein secretion in mammalian cells

The development of novel strategies to program cellular behaviors is a central goal in synthetic biology, and post-translational control mediated by engineered protein circuits is a particularly attractive approach to achieve rapid protein secretion on demand. We have developed a programmable protease-mediated post-translational switch (POSH) control platform composed of a chimeric protein unit that consists of a protein of interest fused via a transmembrane domain to a cleavable ER-retention signal, together with two cytosolic inducer-sensitive split protease components. The protease components combine in the presence of the specific inducer to generate active protease, which cleaves the ER-retention signal, releasing the transmembrane-domain-linked protein for trafficking to the trans-Golgi region. A furin site placed downstream of the protein ensures cleavage and subsequent secretion of the desired protein. We show that stimuli ranging from plant-derived, clinically compatible chemicals to remotely controllable inducers such as light and electrostimulation can program protein secretion in various POSH-engineered designer mammalian cells. As proof-of-concept, an all-in-one POSH control plasmid encoding insulin and abscisic acid-activatable split protease units was hydrodynamically transfected into the liver of type-1 diabetic mice. Induction with abscisic acid attenuated glycemic excursions in glucose-tolerance tests. Increased blood levels of insulin were maintained for 12 days.

The present and the future of protein biosensor engineering

Protein biosensors play increasingly important roles in cell and neurobiology and have the potential to revolutionise the way clinical and industrial analytics are performed. The gradual transition from multicomponent biosensors to fully integrated single chain allosteric biosensors has brought the field closer to commercial applications. We evaluate various approaches for converting constitutively active protein reporter domains into analyte operated switches. We discuss the paucity of the natural receptors that undergo conformational changes sufficiently large to control the activity of allosteric reporter domains. This problem can be overcome by constructing artificial versions of such receptors. The design path to such receptors involves the construction of Chemically Induced Dimerisation systems (CIDs) that can be configured to operate single and two-component biosensors.

Catalyst-Based Biomolecular Logic Gates

Regulatory processes in biology can be re-conceptualized in terms of logic gates, analogous to those in computer science. Frequently, biological systems need to respond to multiple, sometimes conflicting, inputs to provide the correct output. The language of logic gates can then be used to model complex signal transduction and metabolic processes. Advances in synthetic biology in turn can be used to construct new logic gates, which find a variety of biotechnology applications including in the production of high value chemicals, biosensing, and drug delivery. In this review, we focus on advances in the construction of logic gates that take advantage of biological catalysts, including both protein-based and nucleic acid-based enzymes. These catalyst-based biomolecular logic gates can read a variety of molecular inputs and provide chemical, optical, and electrical outputs, allowing them to interface with other types of biomolecular logic gates or even extend to inorganic systems. Continued advances in molecular modeling and engineering will facilitate the construction of new logic gates, further expanding the utility of biomolecular computing.

Robust boundary formation in a morphogen gradient via cell-cell signaling

Establishing sharp and correctly positioned boundaries in spatial gene expression patterns is a central task in both developmental and synthetic biology. We consider situations where a global morphogen gradient provides positional information to cells but is insufficient to ensure the required boundary precision, due to different types of noise in the system. In a conceptual model, we quantitatively compare three mechanisms, which combine the global signal with local signaling between neighboring cells, to enhance the boundary formation process. These mechanisms differ with respect to the way in which they combine the signals by following either an AND, an OR, or a SUM rule. Within our model, we analyze the dynamics of the boundary formation process, and the fuzziness of the resulting boundary. Furthermore, we consider the tunability of the boundary position and its scaling with system size. We find that all three mechanisms produce less fuzzy boundaries than the purely gradient-based reference mechanism, even in the regime of high noise in the local signals relative to the noise in the global signal. Among the three mechanisms, the SUM rule produces the most accurate boundary. However, in contrast to the other two mechanisms, it requires noise to exit metastable states and rapidly reach the stable boundary pattern.

Advances in the Computational Design of Small-Molecule-Controlled Protein-Based Circuits for Synthetic Biology

Synthetic biology approaches living systems with an engineering perspective and promises to deliver solutions to global challenges in healthcare and sustainability. A critical component is the design of biomolecular circuits with programmable input-output behaviors. Such circuits typically rely on a sensor module that recognizes molecular inputs, which is coupled to a functional output via protein-level circuits or regulating the expression of a target gene. While gene expression outputs can be customized relatively easily by exchanging the target genes, sensing new inputs is a major limitation. There is a limited repertoire of sensors found in nature, and there are often difficulties with interfacing them with engineered circuits. Computational protein design could be a key enabling technology to address these challenges, as it allows for the engineering of modular and tunable sensors that can be tailored to the circuit's application. In this article, we review recent computational approaches to design protein-based sensors for small-molecule inputs with particular focus on those based on the widely used Rosetta software suite. Furthermore, we review mechanisms that have been harnessed to couple ligand inputs to functional outputs. Based on recent literature, we illustrate how the combination of protein design and synthetic biology enables new sensors for diverse applications ranging from biomedicine to metabolic engineering. We conclude with a perspective on how strategies to address frontiers in protein design and cellular circuit design may enable the next generation of sense-response networks, which may increasingly be assembled from de novo components to display diverse and engineerable input-output behaviors.

Cellular Computational Logic Using Toehold Switches

The development of computational logic that carries programmable and predictable features is one of the key requirements for next-generation synthetic biological devices. Despite considerable progress, the construction of synthetic biological arithmetic logic units presents numerous challenges. In this paper, utilizing the unique advantages of RNA molecules in building complex logic circuits in the cellular environment, we demonstrate the RNA-only bitwise logical operation of XOR gates and basic arithmetic operations, including a half adder, a half subtractor, and a Feynman gate, in Escherichia coli. Specifically, de-novo-designed riboregulators, known as toehold switches, were concatenated to enhance the functionality of an OR gate, and a previously utilized antisense RNA strategy was further optimized to construct orthogonal NIMPLY gates. These optimized synthetic logic gates were able to be seamlessly integrated to achieve final arithmetic operations on small molecule inputs in cells. Toehold-switch-based ribocomputing devices may provide a fundamental basis for synthetic RNA-based arithmetic logic units or higher-order systems in cells.

Breadth and Specificity in Pleiotropic Protein Kinase A Activity and Environmental Responses

Protein Kinase A (PKA) is an essential kinase that is conserved across eukaryotes and plays fundamental roles in a wide range of organismal processes, including growth control, learning and memory, cardiovascular health, and development. PKA mediates these responses through the direct phosphorylation of hundreds of proteins-however, which proteins are phosphorylated can vary widely across cell types and environmental cues, even within the same organism. A major question is how cells enact specificity and precision in PKA activity to mount the proper response, especially during environmental changes in which only a subset of PKA-controlled processes must respond. Research over the years has uncovered multiple strategies that cells use to modulate PKA activity and specificity. This review highlights recent advances in our understanding of PKA signaling control including subcellular targeting, phase separation, feedback control, and standing waves of allosteric regulation. We discuss how the complex inputs and outputs to the PKA network simultaneously pose challenges and solutions in signaling integration and insulation. PKA serves as a model for how the same regulatory factors can serve broad pleiotropic functions but maintain specificity in localized control.

Protease-controlled secretion and display of intercellular signals

To program intercellular communication for biomedicine, it is crucial to regulate the secretion and surface display of signaling proteins. If such regulations are at the protein level, there are additional advantages, including compact delivery and direct interactions with endogenous signaling pathways. Here we create a modular, generalizable design called Retained Endoplasmic Cleavable Secretion (RELEASE), with engineered proteins retained in the endoplasmic reticulum and displayed/secreted in response to specific proteases. The design allows functional regulation of multiple synthetic and natural proteins by synthetic protease circuits to realize diverse signal processing capabilities, including logic operation and threshold tuning. By linking RELEASE to additional sensing and processing circuits, we can achieve elevated protein secretion in response to "undruggable" oncogene KRAS mutants. RELEASE should enable the local, programmable delivery of intercellular cues for a broad variety of fields such as neurobiology, cancer immunotherapy and cell transplantation.

OUP accepted manuscript

Potyviridae, the largest family of known RNA viruses (realm Riboviria), belongs to the picorna-like supergroup and has important agricultural and ecological impacts. Potyvirid genomes are translated into polyproteins, which are in turn hydrolyzed to release mature products. Recent sequencing efforts revealed an unprecedented number of potyvirids with a rich variability in gene content and genomic layouts. Here, we review the heterogeneity of non-core modules that expand the structural and functional diversity of the potyvirid proteomes. We provide a family-wide classification of P1 proteinases into the functional Types A and B, and discuss pretty interesting sweet potato potyviral ORF (PISPO), putative zinc fingers, and alkylation B (AlkB)—non-core modules found within P1 cistrons. The atypical inosine triphosphate pyrophosphatase (ITPase/HAM1), as well as the pseudo tobacco mosaic virus-like coat protein (TMV-like CP) are discussed alongside homologs of unrelated virus taxa. Family-wide abundance of the multitasking helper component proteinase (HC-pro) is revised. Functional connections between non-core modules are highlighted to support host niche adaptation and immune evasion as main drivers of the Potyviridae evolutionary radiation. Potential biotechnological and synthetic biology applications of potyvirid leader proteinases and non-core modules are finally explored.

Multiplexed direct detection of barcoded protein reporters on a nanopore array

Detection of specific proteins using nanopores is currently challenging. To address this challenge, we developed a collection of over twenty nanopore-addressable protein tags engineered as reporters (NanoporeTERs, or NTERs). NTERs are constructed with a secretion tag, folded domain and a nanopore-targeting C-terminal tail in which arbitrary peptide barcodes can be encoded. We demonstrate simultaneous detection of up to nine NTERs expressed in bacterial or human cells using MinION nanopore sensor arrays.

Synthetic Protein Circuits and Devices Based on Reversible Protein-Protein Interactions: An Overview

Protein-protein interactions (PPIs) contribute to regulate many aspects of cell physiology and metabolism. Protein domains involved in PPIs are important building blocks for engineering genetic circuits through synthetic biology. These domains can be obtained from known proteins and rationally engineered to produce orthogonal scaffolds, or computationally designed de novo thanks to recent advances in structural biology and molecular dynamics prediction. Such circuits based on PPIs (or protein circuits) appear of particular interest, as they can directly affect transcriptional outputs, as well as induce behavioral/adaptational changes in cell metabolism, without the need for further protein synthesis. This last example was highlighted in recent works to enable the production of fast-responding circuits which can be exploited for biosensing and diagnostics. Notably, PPIs can also be engineered to develop new drugs able to bind specific intra- and extra-cellular targets. In this review, we summarize recent findings in the field of protein circuit design, with particular focus on the use of peptides as scaffolds to engineer these circuits.

Synthetic biology applications of the yeast mating signal pathway

Cell fusion is a fundamental biological process that is involved in the development of most eukaryotic organisms. During the fusion process in Saccharomyces cerevisiae, cells respond to pheromones to trigger the MAPK (mitogen-activated protein kinase) cascade to initiate mating, followed by polarization, cell-wall remodeling, membrane fusion, and karyogamy. We highlight the applications of the yeast mating signal pathway in promoter engineering for tuning the expression of output genes, as well as in metabolic engineering for decoupling growth and metabolism, biosensors for sensitive detection and signal amplification, genetic circuits for programmable biological functionalities, and artificial consortia for cell-cell communication. Strategies such as exploiting rational engineering of modular circuits and optimizing the reproductive pathway to precisely maneuver physiological events have implications for scientific research and industrial development.

Engineering a CRISPRi Circuit for Autonomous Control of Metabolic Flux in Escherichia coli

Building autonomous switches is an effective approach for rewiring metabolic flux during microbial synthesis of chemicals. However, current autonomous switches largely rely on metabolite-responsive biosensors or quorum-sensing circuits. In this study, a stationary phase promoter (SPP) and a protein degradation tag (PDT) were combined with the CRISPR interference (CRISPRi) system to construct an autonomous repression system that could shut down multiple-gene expression depending on the cellular physiological state. With this autonomous CRISPRi system to regulate one target gene, a fermenter-scale titer of shikimic acid reached 21 g/L, which was the highest titer ever reported by Escherichia coli in a minimal medium without any chemical inducers. With three target genes repressed, 26 g/L glutaric acid could be achieved with decreased byproduct accumulation. These results highlight the applicability of the autonomous CRISPRi system for microbial production of value-added chemicals.