Synthetic recombinase-based state machines in living cells

Collaborative light-off and light-on bacterial luciferase biosensors: Innovative approach for rapid contaminant detection

Bioluminescence-based light-off and light-on biosensors are widely used in environmental monitoring due to their rapid, cost-effective, real-time, and easy operation. However, stability and sensitivity issues in detecting real samples remain challenging. This study introduces a novel approach utilizing combined light-off and light-on biosensors for rapid and sensitive contaminants detection within 45 min in real samples. First, a recombinase-based state machine (RSM) was used to construct light-off RSM biosensors (light-off RSMs) for continuously strong light emission and overexpressing of outer membrane porins OmpC and OmpF enhanced their sensitivity to toxic contaminants. Additionally, a new experimental protocol containing the cell culture, collection, preparation, and the contaminant measurement was established for bioluminescent light-on whole-cell biosensors (light-on WCBs) in contaminant detection, initially developed using cadmium (Cd) and later applied to lead (Pb) and mercury (Hg). For Cd light-on WCBs, overexpressing OmpC and knocking out the contaminant exporter ZntA enhanced the accumulation of intracellular Cd in WCB cells, resulting in increased sensitivity to low concentrations of contaminants. Further, metabolic modifications in light-on WCBs significantly boosted luminescence. These genetic modified bacterial strains, whether freshly harvested or as freeze-dried powders, showed rapid luminescent responses to contaminants in the picomolar (pM) to nanomolar (nM) range within 45 min. Finally, the combined use of light-off RSMs and light-on WCBs successfully assessed toxicity and detected specific contaminants in real environmental and food samples. These strategies could be applied to developing other bacterial luciferase-based biosensors and even other types such as colorimetric biosensors.

DNA storage: The future direction for medical cold data storage

DNA storage, characterized by its durability, data density, and cost-effectiveness, is a promising solution for managing the increasing data volumes in healthcare. This review explores state-of-the-art DNA storage technologies, and provides insights into designing a DNA storage system tailored for medical cold data. We anticipate that a practical approach for medical cold data storage will involve establishing regional, in vitro DNA storage centers that can serve multiple hospitals. The immediacy of DNA storage for medical data hinges on the development of novel, high-density, specialized coding methods. Established commercial techniques, such as DNA chemical synthesis and next-generation sequencing (NGS), along with mixed drying with alkaline salts and refined Polymerase Chain Reaction (PCR), potentially represent the optimal options for data writing, reading, storage, and accessing, respectively. Data security could be promised by the integration of traditional digital encryption and DNA steganography. Although breakthrough developments like artificial nucleotides and DNA nanostructures show potential, they remain in the laboratory research phase. In conclusion, DNA storage is a viable preservation strategy for medical cold data in the near future.

Integrase enables synthetic intercellular logic via bacterial conjugation

Integrases have been widely used in synthetic biology for genome engineering and genetic circuit design. They mediate DNA recombination to alter the genotypes of single cell lines in vivo, with these changes being permanently recorded and inherited via vertical gene transfer. However, integrase-based intercellular DNA messaging and its regulation via horizontal gene transfer remain underexplored. Here, we introduce a versatile strategy to design, build, and test integrase-based intercellular DNA messaging through bacterial conjugation. First, we screened conjugative plasmids and recipient cells for efficient conjugation. Then, we established a layered framework to describe the interactions among hierarchical E. coli strains and implemented dual-layer Boolean logic gates to demonstrate intercellular DNA messaging and management. Finally, we expanded the design to include four-layer single-processing pathways and dual-layer multi-processing systems. This strategy advances intercellular DNA messaging, hierarchical signal processing, and the application of integrase in systems and synthetic biology.

Preventing Multimer Formation in Commonly Used Synthetic Biology Plasmids

Plasmids are an essential tool for basic research and biotechnology applications. To optimize plasmid-based circuits, it is crucial to control plasmid integrity, including the formation of plasmid multimers. Multimers are tandem repeats of entire plasmids formed by failed dimer resolution during replication. Multimers can affect the behavior of synthetic circuits, especially ones that include DNA-editing enzymes. However, occurrence of multimers is not commonly assayed. Here we survey four commonly used plasmid backbones for occurrence of multimers in cloning (JM109) and wild-type (MG1655) strains of Escherichia coli. We find that multimers occur appreciably only in MG1655, with the fraction of plasmids existing as multimers increasing with both plasmid copy number and culture passaging. In contrast, transforming multimers into JM109 can yield strains that contain no singlet plasmids. We present an MG1655 ΔrecA single-locus knockout that avoids multimer production. These results can aid synthetic biologists in improving design and reliability of plasmid-based circuits.

The lives of cells, recorded

A paradigm for biology is emerging in which cells can be genetically programmed to write their histories into their own genomes. These records can subsequently be read, and the cellular histories reconstructed, which for each cell could include a record of its lineage relationships, extrinsic influences, internal states and physical locations, over time. DNA recording has the potential to transform the way that we study developmental and disease processes. Recent advances in genome engineering are driving the development of systems for DNA recording, and meanwhile single-cell and spatial omics technologies increasingly enable the recovery of the recorded information. Combined with advances in computational and phylogenetic inference algorithms, the DNA recording paradigm is beginning to bear fruit. In this Perspective, we explore the rationale and technical basis of DNA recording, what aspects of cellular biology might be recorded and how, and the types of discovery that we anticipate this paradigm will enable.

Bacterial Autonomous Intelligent Microrobots for Biomedical Applications

Micro/nanorobots are being increasingly utilized as new diagnostic and therapeutic platforms in the biomedical field, enabling remote navigation to hard-to-reach tissues and the execution of various medical procedures. Although significant progress has been made in the development of biomedical micro/nanorobots, how to achieve closed-loop control of them from sensing, memory, and precise trajectory planning to feedback to carry out biomedical tasks remains a challenge. Bacteria with self-propulsion and autonomous intelligence properties are well suited to be engineered as microrobots to achieve closed-loop control for biomedical applications. By virtue of synthetic biology, bacterial microrobots possess an expanded genetic toolbox, allowing them to load input sensors to respond or remember external signals. To achieve accurate control in the complex physiological environment, the development of bacterial microrobots should be matched with the corresponding control system design. In this review, a detailed summary of the sensing and control mechanisms of bacterial microrobots is presented. The engineering and applications of bacterial microrobots in the biomedical field are highlighted. Their future directions of bacterial autonomous intelligent microrobots for precision medicine are forecasted.

Synthetic gene circuits in plants: recent advances and challenges

Plant synthetic biology is a rapidly advancing multidisciplinary research area that applies engineering principles to design, construct, and implement new plant capabilities at the molecular, cellular, and whole organism scales. Synthetic gene circuits are important tools for enabling increased customizability in the control of gene expression in plants, with widespread applications spanning new approaches for basic biology to introduction of new traits for advancing agriculture. In this review, we first aimed to provide a comprehensive understanding of synthetic circuits. Next, we discuss recent progress in the construction of advanced synthetic gene circuits in plants for programmable control of gene expression. Finally, we discuss the current challenges associated with developing and applying effective circuits while also highlighting future prospects and research directions, including quantitative measurement, high-throughput testing, and circuit modelling.

Enzymes as green and sustainable tools for DNA data storage

DNA is considered as an ideal supramolecular material for information storage with high storage density and long-term stability. Enzymes, as green and sustainable tools, offer several unique advantages for DNA-based information storage. These advantages include low cost and reduced generation of hazardous wastes during DNA synthesis, as well as the improvements in data reading speed and data recovery accuracy. Moreover, enzymes could achieve scalable data steganography. In this review, we introduced the exciting application strategies of enzymatic tools in each step of DNA information storage (writing, storing, retrieval and reading). We further address the challenges and opportunities associated with enzymatic tools for DNA information storage, aiming at developing new techniques to overcome these obstacles.

Post-translational digital data encoding into the genomes of mammalian cell populations

High resolution cellular signal encoding is critical for better understanding of complex biological phenomena. DNA-based biosignal encoders alter genomic or plasmid DNA in a signal dependent manner. Current approaches involve the signal of interest affecting a DNA edit by interacting with a signal specific promoter which then results in expression of the effector molecule (DNA altering enzyme). Here, we present the proof of concept of a biosignal encoding system where the enzyme terminal deoxynucleotidyl transferase (TdT) acts as the effector molecule upon directly interacting with the signal of interest. A template independent DNA polymerase (DNAp), TdT incorporates nucleotides at the 3' OH ends of DNA substrate in a signal dependent manner. By employing CRISPR-Cas9 to create double stranded breaks in genomic DNA, we make 3'OH ends available to act as substrate for TdT. We show that this system can successfully resolve and encode different concentrations of various biosignals into the genomic DNA of HEK-293T cells. Finally, we develop a simple encoding scheme associated with the tested biosignals and encode the message "HELLO WORLD" into the genomic DNA of HEK-293T cells at a population level with 91% accuracy. This work demonstrates a simple and engineerable system that can reliably store local biosignal information into the genomes of mammalian cell populations.

A history-dependent integrase recorder of plant gene expression with single-cell resolution

During development, most cells experience a progressive restriction of fate that ultimately results in a fully differentiated mature state. Understanding more about the gene expression patterns that underlie developmental programs can inform engineering efforts for new or optimized forms. Here, we present a four-state integrase-based recorder of gene expression history and demonstrate its use in tracking gene expression events in Arabidopsis thaliana in two developmental contexts: lateral root initiation and stomatal differentiation. The recorder uses two serine integrases to mediate sequential DNA recombination events, resulting in step-wise, history-dependent switching between expression of fluorescent reporters. By using promoters that express at different times along each of the two differentiation pathways to drive integrase expression, we tie fluorescent status to an ordered progression of gene expression along the developmental trajectory. In one snapshot of a mature tissue, our recorder is able to reveal past gene expression with single cell resolution. In this way, we are able to capture heterogeneity in stomatal development, confirming the existence of two alternate paths of differentiation.

Reconstructing signaling history of single cells with imaging-based molecular recording

The intensity and duration of biological signals encode information that allows a few pathways to regulate a wide array of cellular behaviors. Despite the central importance of signaling in biomedical research, our ability to quantify it in individual cells over time remains limited. Here, we introduce INSCRIBE, an approach for reconstructing signaling history in single cells using endpoint fluorescence images. By regulating a CRISPR base editor, INSCRIBE generates mutations in genomic target sequences, at a rate proportional to signaling activity. The number of edits is then recovered through a novel ratiometric readout strategy, from images of two fluorescence channels. We engineered human cell lines for recording WNT and BMP pathway activity, and demonstrated that INSCRIBE faithfully recovers both the intensity and duration of signaling. Further, we used INSCRIBE to study the variability of cellular response to WNT and BMP stimulation, and test whether the magnitude of response is a stable, heritable trait. We found a persistent memory in the BMP pathway. Progeny of cells with higher BMP response levels are likely to respond more strongly to a second BMP stimulation, up to 3 weeks later. Together, our results establish a scalable platform for genetic recording and in situ readout of signaling history in single cells, advancing quantitative analysis of cell-cell communication during development and disease.

Algorithms for Autonomous Formation of Multicellular Shapes from Single Cells

Multicellular organisms originate from a single cell, ultimately giving rise to mature organisms of heterogeneous cell type composition in complex structures. Recent work in the areas of stem cell biology and tissue engineering has laid major groundwork in the ability to convert certain types of cells into other types, but there has been limited progress in the ability to control the morphology of cellular masses as they grow. Contemporary approaches to this problem have included the use of artificial scaffolds, 3D bioprinting, and complex media formulations; however, there are no existing approaches to controlling this process purely through genetics and from a single-cell starting point. Here we describe a computer-aided design approach, called CellArchitect, for designing recombinase-based genetic circuits for controlling the formation of multicellular masses into arbitrary shapes in human cells.

Toward DNA-Based Recording of Biological Processes

Exploiting the inherent compatibility of DNA-based data storage with living cells, various cellular recording approaches have been developed for recording and retrieving biologically relevant signals in otherwise inaccessible locations, such as inside the body. This review provides an overview of the current state of engineered cellular memory systems, highlighting their design principles, advantages, and limitations. We examine various technologies, including CRISPR-Cas systems, recombinases, retrons, and DNA methylation, that enable these recording systems. Additionally, we discuss potential strategies for improving recording accuracy, scalability, and durability to address current limitations in the field. This emerging modality of biological measurement will be key to gaining novel insights into diverse biological processes and fostering the development of various biotechnological applications, from environmental sensing to disease monitoring and beyond.

Biocomputing in plants, from proof of concept to application

In response to the challenges of climate change and the transition toward sustainability, synthetic biology offers innovative solutions. Most current plant synthetic biology applications rely on the constitutive expression of enzymes and regulators. To engineer plant phenotypes tuneable to environmental conditions and plant cellular states, the integration of multiple signals in synthetic circuits is required. While most circuits are developed in model organisms, numerous tools were recently developed to implement biocomputation in plant synthetic circuits. I presented in this review the tools and design methods for logic circuit implementation in plants. I highlighted recent and potential applications of those circuits to understand and engineer plant interaction with the environment, development, and metabolic pathways.

Protocol for the establishment of a serine integrase-based platform for functional validation of genetic switch controllers in eukaryotic cells

Serine integrases (Ints) are a family of site-specific recombinases (SSRs) encoded by some bacteriophages to integrate their genetic material into the genome of a host. Their ability to rearrange DNA sequences in different ways including inversion, excision, or insertion with no help from endogenous molecular machinery, confers important biotechnological value as genetic editing tools with high host plasticity. Despite advances in their use in prokaryotic cells, only a few Ints are currently used as gene editors in eukaryotes, partly due to the functional loss and cytotoxicity presented by some candidates in more complex organisms. To help expand the number of Ints available for the assembly of more complex multifunctional circuits in eukaryotic cells, this protocol describes a platform for the assembly and functional screening of serine-integrase-based genetic switches designed to control gene expression by directional inversions of DNA sequence orientation. The system consists of two sets of plasmids, an effector module and a reporter module, both sets assembled with regulatory components (as promoter and terminator regions) appropriate for expression in mammals, including humans, and plants. The complete method involves plasmid design, DNA delivery, testing and both molecular and phenotypical assessment of results. This platform presents a suitable workflow for the identification and functional validation of new tools for the genetic regulation and reprogramming of organisms with importance in different fields, from medical applications to crop enhancement, as shown by the initial results obtained. This protocol can be completed in 4 weeks for mammalian cells or up to 8 weeks for plant cells, considering cell culture or plant growth time.

Engineering intelligent chassis cells via recombinase-based MEMORY circuits

Synthetic biologists seek to engineer intelligent living systems capable of decision-making, communication, and memory. Separate technologies exist for each tenet of intelligence; however, the unification of all three properties in a living system has not been achieved. Here, we engineer completely intelligent Escherichia coli strains that harbor six orthogonal and inducible genome-integrated recombinases, forming Molecularly Encoded Memory via an Orthogonal Recombinase arraY (MEMORY). MEMORY chassis cells facilitate intelligence via the discrete multi-input regulation of recombinase functions enabling inheritable DNA inversions, deletions, and genomic insertions. MEMORY cells can achieve programmable and permanent gain (or loss) of functions extrachromosomally or from a specific genomic locus, without the loss or modification of the MEMORY platform - enabling the sequential programming and reprogramming of DNA circuits within the cell. We demonstrate all three tenets of intelligence via a probiotic (Nissle 1917) MEMORY strain capable of information exchange with the gastrointestinal commensal Bacteroides thetaiotaomicron.

Genetic Parts and Enabling Tools for Biocircuit Design

Synthetic biology aims to engineer biological systems for customized tasks through the bottom-up assembly of fundamental building blocks, which requires high-quality libraries of reliable, modular, and standardized genetic parts. To establish sets of parts that work well together, synthetic biologists created standardized part libraries in which every component is analyzed in the same metrics and context. Here we present a state-of-the-art review of the currently available part libraries for designing biocircuits and their gene expression regulation paradigms at transcriptional, translational, and post-translational levels in Escherichia coli. We discuss the necessary facets to integrate these parts into complex devices and systems along with the current efforts to catalogue and standardize measurement data. To better display the range of available parts and to facilitate part selection in synthetic biology workflows, we established biopartsDB, a curated database of well-characterized and useful genetic part and device libraries with detailed quantitative data validated by the published literature.

Order-of-Mutation Effects on Cancer Progression: Models for Myeloproliferative Neoplasm

In some patients with myeloproliferative neoplasms (MPN), two genetic mutations are often found: JAK2 V617F and one in the TET2 gene. Whether one mutation is present influences how the other subsequent mutation will affect the regulation of gene expression. In other words, when a patient carries both mutations, the order of when they first arose has been shown to influence disease progression and prognosis. We propose a nonlinear ordinary differential equation, the Moran process, and Markov chain models to explain the non-additive and non-commutative mutation effects on recent clinical observations of gene expression patterns, proportions of cells with different mutations, and ages at diagnosis of MPN. Combined, these observations are used to shape our modeling framework. Our key proposal is that bistability in gene expression provides a natural explanation for many observed order-of-mutation effects. We also propose potential experimental measurements that can be used to confirm or refute predictions of our models.

A synthetic differentiation circuit in Escherichia coli for suppressing mutant takeover

Differentiation is crucial for multicellularity. However, it is inherently susceptible to mutant cells that fail to differentiate. These mutants outcompete normal cells by excessive self-renewal. It remains unclear what mechanisms can resist such mutant expansion. Here, we demonstrate a solution by engineering a synthetic differentiation circuit in Escherichia coli that selects against these mutants via a biphasic fitness strategy. The circuit provides tunable production of synthetic analogs of stem, progenitor, and differentiated cells. It resists mutations by coupling differentiation to the production of an essential enzyme, thereby disadvantaging non-differentiating mutants. The circuit selected for and maintained a positive differentiation rate in long-term evolution. Surprisingly, this rate remained constant across vast changes in growth conditions. We found that transit-amplifying cells (fast-growing progenitors) underlie this environmental robustness. Our results provide insight into the stability of differentiation and demonstrate a powerful method for engineering evolutionarily stable multicellular consortia.

Combinatorial optimization of gene expression through recombinase-mediated promoter and terminator shuffling in yeast

Microbes are increasingly employed as cell factories to produce biomolecules. This often involves the expression of complex heterologous biosynthesis pathways in host strains. Achieving maximal product yields and avoiding build-up of (toxic) intermediates requires balanced expression of every pathway gene. However, despite progress in metabolic modeling, the optimization of gene expression still heavily relies on trial-and-error. Here, we report an approach for in vivo, multiplexed Gene Expression Modification by LoxPsym-Cre Recombination (GEMbLeR). GEMbLeR exploits orthogonal LoxPsym sites to independently shuffle promoter and terminator modules at distinct genomic loci. This approach facilitates creation of large strain libraries, in which expression of every pathway gene ranges over 120-fold and each strain harbors a unique expression profile. When applied to the biosynthetic pathway of astaxanthin, an industrially relevant antioxidant, a single round of GEMbLeR improved pathway flux and doubled production titers. Together, this shows that GEMbLeR allows rapid and efficient gene expression optimization in heterologous biosynthetic pathways, offering possibilities for enhancing the performance of microbial cell factories.

Engineering the next generation of theranostic biomaterials with synthetic biology

Biomaterials have evolved from inert materials to responsive entities, playing a crucial role in disease diagnosis, treatment, and modeling. However, their advancement is hindered by limitations in chemical and mechanical approaches. Synthetic biology enabling the genetically reprograming of biological systems offers a new paradigm. It has achieved remarkable progresses in cell reprogramming, engineering designer cells for diverse applications. Synthetic biology also encompasses cell-free systems and rational design of biological molecules. This review focuses on the application of synthetic biology in theranostics, which boost rapid development of advanced biomaterials. We introduce key fundamental concepts of synthetic biology and highlight frontier applications thereof, aiming to explore the intersection of synthetic biology and biomaterials. This integration holds tremendous promise for advancing biomaterial engineering with programable complex functions.

Data Storage Using DNA

The exponential growth of global data has outpaced the storage capacities of current technologies, necessitating innovative storage strategies. DNA, as a natural medium for preserving genetic information, has emerged as a highly promising candidate for next-generation storage medium. Storing data in DNA offers several advantages, including ultrahigh physical density and exceptional durability. Facilitated by significant advancements in various technologies, such as DNA synthesis, DNA sequencing, and DNA nanotechnology, remarkable progress has been made in the field of DNA data storage over the past decade. However, several challenges still need to be addressed to realize practical applications of DNA data storage. In this review, the processes and strategies of in vitro DNA data storage are first introduced, highlighting recent advancements. Next, a brief overview of in vivo DNA data storage is provided, with a focus on the various writing strategies developed to date. At last, the challenges encountered in each step of DNA data storage are summarized and promising techniques are discussed that hold great promise in overcoming these obstacles.

Sentinel cells programmed to respond to environmental DNA including human sequences

Monitoring environmental DNA can track the presence of organisms, from viruses to animals, but requires continuous sampling of transient sequences from a complex milieu. Here we designed living sentinels using Bacillus subtilis to report the uptake of a DNA sequence after matching it to a preencoded target. Overexpression of ComK increased DNA uptake 3,000-fold, allowing for femtomolar detection in samples dominated by background DNA. This capability was demonstrated using human sequences containing single-nucleotide polymorphisms (SNPs) associated with facial features. Sequences were recorded with high efficiency and were protected from nucleases for weeks. The SNP could be determined by sequencing or in vivo using CRISPR interference to turn on reporter expression in response to a specific base. Multiple SNPs were recorded by one cell or through a consortium in which each member recorded a different sequence. Sentinel cells could surveil for specific sequences over long periods of time for applications spanning forensics, ecology and epidemiology.

DNA Barcoding Technology for Lineage Recording and Tracing to Resolve Cell Fate Determination

In various biological contexts, cells receive signals and stimuli that prompt them to change their current state, leading to transitions into a future state. This change underlies the processes of development, tissue maintenance, immune response, and the pathogenesis of various diseases. Following the path of cells from their initial identity to their current state reveals how cells adapt to their surroundings and undergo transformations to attain adjusted cellular states. DNA-based molecular barcoding technology enables the documentation of a phylogenetic tree and the deterministic events of cell lineages, providing the mechanisms and timing of cell lineage commitment that can either promote homeostasis or lead to cellular dysregulation. This review comprehensively presents recently emerging molecular recording technologies that utilize CRISPR/Cas systems, base editing, recombination, and innate variable sequences in the genome. Detailing their underlying principles, applications, and constraints paves the way for the lineage tracing of every cell within complex biological systems, encompassing the hidden steps and intermediate states of organism development and disease progression.

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 Ca2+-Dependent DNA Polymerase Activity

Advancements in synthetic biology have provided new opportunities in biosensing, with applications ranging from genetic programming to diagnostics. Next generation biosensors aim to expand the number of accessible environments for measurements, increase the number of measurable phenomena, and improve the quality of the measurement. To this end, an emerging area in the field has been the integration of DNA as an information storage medium within biosensor outputs, leveraging nucleic acids to record the biosensor state over time. However, slow signal transduction steps, due to the time scales of transcription and translation, bottleneck many sensing-DNA recording approaches. DNA polymerases (DNAPs) have been proposed as a solution to the signal transduction problem by operating as both the sensor and responder, but there is presently a lack of DNAPs with functional sensitivity to many desirable target ligands. Here, we engineer components of the Pol δ replicative polymerase complex of Saccharomyces cerevisiae to sense and respond to Ca2+, a metal cofactor relevant to numerous biological phenomena. Through domain insertion and binding site grafting to Pol δ subunits, we demonstrate functional allosteric sensitivity to Ca2+. Together, this work provides an important foundation for future efforts in the development of DNAP-based biosensors.

Order-of-mutation effects on cancer progression: models for myeloproliferative neoplasm

In some patients with myeloproliferative neoplasms (MPN), two genetic mutations are often found, JAK2 V617F and one in the TET2 gene. Whether or not one mutation is present will influence how the other subsequent mutation affects the regulation of gene expression. When both mutations are present, the order of their occurrence has been shown to influence disease progression and prognosis. We propose a nonlinear ordinary differential equation (ODE), Moran process, and Markov chain models to explain the non-additive and non-commutative mutation effects on recent clinical observations of gene expression patterns, proportions of cells with different mutations, and ages at diagnosis of MPN. These observations consistently shape our modeling framework. Our key proposal is that bistability in gene expression provides a natural explanation for many observed order-of-mutation effects. We also propose potential experimental measurements that can be used to confirm or refute predictions of our models.

Modularized synthetic biology enabled intelligent biosensors

Biosensors that sense the concentration of a specified target and produce a specific signal output have become important technology for biological analysis. Recently, intelligent biosensors have received great interest due to their adaptability to meet sophisticated demands. Advances in developing standard modules and carriers in synthetic biology have shed light on intelligent biosensors that can implement advanced analytical processing to better accommodate practical applications. This review focuses on intelligent synthetic biology-enabled biosensors (SBBs). First, we illustrate recent progress in intelligent SBBs with the capability of computation, memory storage, and self-calibration. Then, we discuss emerging applications of SBBs in point-of-care testing (POCT) and wearable monitoring. Finally, future perspectives on intelligent SBBs are proposed.

Engineering bacteria to modulate host metabolism

The microbial community of the gut, collectively termed the gut microbiota, modulates both host metabolism and disease development in a variety of clinical contexts. The microbiota can have detrimental effects and be involved in disease development and progression, but it can also offer benefits to the host. This has led in the last years to the development of different therapeutic strategies targeting the microbiota. In this review, we will focus on one of these strategies that involve the use of engineered bacteria to modulate gut microbiota in the treatment of metabolic disorders. We will discuss the recent developments and challenges in the use of these bacterial strains with an emphasis on their use for the treatment of metabolic diseases.

Pneumatic computers for embedded control of microfluidics

Alternative computing approaches that interface readily with physical systems are well suited for embedded control of those systems. We demonstrate finite state machines implemented as pneumatic circuits of microfluidic valves and use these controllers to direct microfluidic liquid handling procedures on the same chip. These monolithic integrated systems require only power to be supplied externally, in the form of a vacuum source. User input can be provided directly to the chip by covering pneumatic ports with a finger. State machines with up to four bits of state memory are demonstrated, and next-state combinational logic can be fully reprogrammed by changing the hole-punch pattern on a membrane in the chip. These pneumatic computers demonstrate a framework for the embedded control of physical systems and open a path to stand-alone lab-on-a-chip devices capable of highly complex functionality.

Temporally resolved transcriptional recording in E. coli DNA using a Retro-Cascorder

Biological signals occur over time in living cells. Yet most current approaches to interrogate biology, particularly gene expression, use destructive techniques that quantify signals only at a single point in time. A recent technological advance, termed the Retro-Cascorder, overcomes this limitation by molecularly logging a record of gene expression events in a temporally organized genomic ledger. The Retro-Cascorder works by converting a transcriptional event into a DNA barcode using a retron reverse transcriptase and then storing that event in a unidirectionally expanding clustered regularly interspaced short palindromic repeats (CRISPR) array via acquisition by CRISPR-Cas integrases. This CRISPR array-based ledger of gene expression can be retrieved at a later point in time by sequencing. Here we describe an implementation of the Retro-Cascorder in which the relative timing of transcriptional events from multiple promoters of interest is recorded chronologically in Escherichia coli populations over multiple days. We detail the molecular components required for this technology, provide a step-by-step guide to generate the recording and retrieve the data by Illumina sequencing, and give instructions for how to use custom software to infer the relative transcriptional timing from the sequencing data. The example recording is generated in 2 d, preparation of sequencing libraries and sequencing can be accomplished in 2-3 d, and analysis of data takes up to several hours. This protocol can be implemented by someone familiar with basic bacterial culture, molecular biology and bioinformatics. Analysis can be minimally run on a personal computer.

Toward Memory in a DNA Brush: Site-Specific Recombination Responsive to Polymer Density, Orientation, and Conformation

Site-specific recombination is a cellular process for the integration, inversion, and excision of DNA segments that could be tailored for memory transactions in artificial cells. Here, we demonstrate the compartmentalization of cascaded gene expression reactions in a DNA brush, starting from the cell-free synthesis of a unidirectional recombinase that exchanges information between two DNA molecules, leading to gene expression turn-on/turn-off. We show that recombination yield in the DNA brush was responsive to gene composition, density, and orientation, with kinetics faster than in a homogeneous dilute bulk solution reaction. Recombination yield scaled with a power law greater than 1 with respect to the fraction of recombining DNA polymers in a dense brush. The exponent approached either 1 or 2, depending on the intermolecular distance in the brush and the position of the recombination site along the DNA contour length, suggesting that a restricted-reach effect between the recombination sites governs the recombination yield. We further demonstrate the ability to encode the DNA recombinase in the same DNA brush with its substrate constructs, enabling multiple spatially resolved orthogonal recombination transactions within a common reaction volume. Our results highlight the DNA brush as a favorable compartment to study DNA recombination, with unique properties for encoding autonomous memory transactions in DNA-based artificial cells.

Genetic circuits in microbial biosensors for heavy metal detection in soil and water

With the rapid population growth, the world is witnessing an ever-increasing demand for energy and natural resources. Consequently, soil, air, and water are polluted with diverse pollutants, including heavy metals (HM). The detection of heavy metals is necessary to remediate them, which is achieved with biosensors. Initially, these HM were detected using atomic absorption spectroscopy (AAS), emission spectroscopy, mass spectrometry, gas chromatography etc., but these were costly and time consuming which further paved a way for microbe-based biosensors. The development of genetic circuits for microbe-based biosensors has become more popular in recent years for heavy metal detection. In this review, we have especially discussed the various types of genetic circuits such as toggle switches, logic gates, and amplification modules used in these biosensors as they are used to enhance sensitivity and specificity. Genetic circuits also allow for rapid and multiple analyte detection at the same time. The use of microbial biosensors for the detection of HM in the soil as well as the water is also described below. Although with a higher success rate than classical biosensors, these microbial biosensors still have some drawbacks like bioavailability and size of the analyte which are needed to be addressed.

Computational capabilities of a multicellular reservoir computing system

The capacity of cells to process information is currently used to design cell-based tools for ecological, industrial, and biomedical applications such as detecting dangerous chemicals or for bioremediation. In most applications, individual cells are used as the information processing unit. However, single cell engineering is limited by the necessary molecular complexity and the accompanying metabolic burden of synthetic circuits. To overcome these limitations, synthetic biologists have begun engineering multicellular systems that combine cells with designed subfunctions. To further advance information processing in synthetic multicellular systems, we introduce the application of reservoir computing. Reservoir computers (RCs) approximate a temporal signal processing task via a fixed-rule dynamic network (the reservoir) with a regression-based readout. Importantly, RCs eliminate the need of network rewiring, as different tasks can be approximated with the same reservoir. Previous work has already demonstrated the capacity of single cells, as well as populations of neurons, to act as reservoirs. In this work, we extend reservoir computing in multicellular populations with the widespread mechanism of diffusion-based cell-to-cell signaling. As a proof-of-concept, we simulated a reservoir made of a 3D community of cells communicating via diffusible molecules and used it to approximate a range of binary signal processing tasks, focusing on two benchmark functions-computing median and parity functions from binary input signals. We demonstrate that a diffusion-based multicellular reservoir is a feasible synthetic framework for performing complex temporal computing tasks that provides a computational advantage over single cell reservoirs. We also identified a number of biological properties that can affect the computational performance of these processing systems.

An integrase toolbox to record gene-expression during plant development

There are many open questions about the mechanisms that coordinate the dynamic, multicellular behaviors required for organogenesis. Synthetic circuits that can record in vivo signaling networks have been critical in elucidating animal development. Here, we report on the transfer of this technology to plants using orthogonal serine integrases to mediate site-specific and irreversible DNA recombination visualized by switching between fluorescent reporters. When combined with promoters expressed during lateral root initiation, integrases amplify reporter signal and permanently mark all descendants. In addition, we present a suite of methods to tune the threshold for integrase switching, including: RNA/protein degradation tags, a nuclear localization signal, and a split-intein system. These tools improve the robustness of integrase-mediated switching with different promoters and the stability of switching behavior over multiple generations. Although each promoter requires tuning for optimal performance, this integrase toolbox can be used to build history-dependent circuits to decode the order of expression during organogenesis in many contexts.

High fidelity one-pot DNA assembly using orthogonal serine integrases

BACKGROUND

Large serine integrases (LSIs, derived from temperate phages) have been adapted for use in a multipart DNA assembly process in vitro, called serine integrase recombinational assembly (SIRA). The versatility, efficiency, and fidelity of SIRA is limited by lack of a sufficient number of LSIs whose activities have been characterized in vitro.

METHODS AND MAJOR RESULTS

In this report, we compared the activities in vitro of 10 orthogonal LSIs to explore their suitability for multiplex SIRA reactions. We found that Bxb1, ϕR4, and TG1 integrases were the most active among the set we studied, but several others were also usable. As proof of principle, we demonstrated high-efficiency one-pot assembly of six DNA fragments (made by PCR) into a 7.5 kb plasmid that expresses the enzymes of the β-carotenoid pathway in Escherichia coli, using six different LSIs. We further showed that a combined approach using a few highly active LSIs, each acting on multiple pairs of att sites with distinct central dinucleotides, can be used to scale up "poly-part" gene assembly and editing.

CONCLUSIONS AND IMPLICATIONS

We conclude that use of multiple orthogonal integrases may be the most predictable, efficient, and programmable approach for SIRA and other in vitro applications.

A DNA Finite-State Machine Based on the Programmable Allosteric Strategy of DNAzyme

Living organisms can produce corresponding functions by responding to external and internal stimuli, and this irritability plays a pivotal role in nature. Inspired by such natural temporal responses, the development and design of nanodevices with the ability to process time-related information could facilitate the development of molecular information processing systems. Here, we proposed a DNA finite-state machine that can dynamically respond to sequential stimuli signals. To build this state machine, a programmable allosteric strategy of DNAzyme was developed. This strategy performs the programmable control of DNAzyme conformation using a reconfigurable DNA hairpin. Based on this strategy, we first implemented a finite-state machine with two states. Through the modular design of the strategy, we further realized the finite-state machine with five states. The DNA finite-state machine endows molecular information systems with the ability of reversible logic control and order detection, which can be extended to more complex DNA computing and nanomachines to promote the development of dynamic nanotechnology.

Molecular recording: transcriptional data collection into the genome

Advances in regenerative medicine depend upon understanding the complex transcriptional choreography that guides cellular development. Transcriptional molecular recorders, tools that record different transcriptional events into the genome of cells, hold promise to elucidate both the intensity and timing of transcriptional activity at single-cell resolution without requiring destructive multitime point assays. These technologies are dependent on DNA writers, which translate transcriptional signals into stable genomic mutations that encode the duration, intensity, and order of transcriptional events. In this review, we highlight recent progress toward more informative and multiplexable transcriptional recording through the use of three different types of DNA writing - recombineering, Cas1-Cas2 acquisition, and prime editing - and the architecture of the genomic data generated.

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.

Synthetic memory circuits for stable cell reprogramming in plants

Plant biotechnology predominantly relies on a restricted set of genetic parts with limited capability to customize spatiotemporal and conditional expression patterns. Synthetic gene circuits have the potential to integrate multiple customizable input signals through a processing unit constructed from biological parts to produce a predictable and programmable output. Here we present a suite of functional recombinase-based gene circuits for use in plants. We first established a range of key gene circuit components compatible with plant cell functionality. We then used these to develop a range of operational logic gates using the identify function (activation) and negation function (repression) in Arabidopsis protoplasts and in vivo, demonstrating their utility for programmable manipulation of transcriptional activity in a complex multicellular organism. Specifically, using recombinases and plant control elements, we activated transgenes in YES, OR and AND gates and repressed them in NOT, NOR and NAND gates; we also implemented the A NIMPLY B gate that combines activation and repression. Through use of genetic recombination, these circuits create stable long-term changes in expression and recording of past stimuli. This highly compact programmable gene circuit platform provides new capabilities for engineering sophisticated transcriptional programs and previously unrealized traits into plants.

Synthetic neuromorphic computing in living cells

Computational properties of neuronal networks have been applied to computing systems using simplified models comprising repeated connected nodes, e.g., perceptrons, with decision-making capabilities and flexible weighted links. Analogously to their revolutionary impact on computing, neuro-inspired models can transform synthetic gene circuit design in a manner that is reliable, efficient in resource utilization, and readily reconfigurable for different tasks. To this end, we introduce the perceptgene, a perceptron that computes in the logarithmic domain, which enables efficient implementation of artificial neural networks in Escherichia coli cells. We successfully modify perceptgene parameters to create devices that encode a minimum, maximum, and average of analog inputs. With these devices, we create multi-layer perceptgene circuits that compute a soft majority function, perform an analog-to-digital conversion, and implement a ternary switch. We also create a programmable perceptgene circuit whose computation can be modified from OR to AND logic using small molecule induction. Finally, we show that our approach enables circuit optimization via artificial intelligence algorithms.

Achieving spatially precise diagnosis and therapy in the mammalian gut using synthetic microbial gene circuits

The mammalian gut and its microbiome form a temporally dynamic and spatially heterogeneous environment. The inaccessibility of the gut and the spatially restricted nature of many gut diseases translate into difficulties in diagnosis and therapy for which novel tools are needed. Engineered bacterial whole-cell biosensors and therapeutics have shown early promise at addressing these challenges. Natural and engineered sensing systems can be repurposed in synthetic genetic circuits to detect spatially specific biomarkers during health and disease. Heat, light, and magnetic signals can also activate gene circuit function with externally directed spatial precision. The resulting engineered bacteria can report on conditions in situ within the complex gut environment or produce biotherapeutics that specifically target host or microbiome activity. Here, we review the current approaches to engineering spatial precision for in vivo bacterial diagnostics and therapeutics using synthetic circuits, and the challenges and opportunities this technology presents.

Engineered living materials (ELMs) design: From function allocation to dynamic behavior modulation

Natural materials possess many distinctive "living" attributes, such as self-growth, self-healing, environmental responsiveness, and evolvability, that are beyond the reach of many existing synthetic materials. The emerging field of engineered living materials (ELMs) takes inspiration from nature and harnesses engineered living systems to produce dynamic and responsive materials with genetically programmable functionalities. Here, we identify and review two main directions for the rational design of ELMs: first, engineering of living materials with enhanced performances by incorporating functional material modules, including engineered biological building blocks (proteins, polysaccharides, and nucleic acids) or well-defined artificial materials; second, engineering of smart ELMs that can sense and respond to their surroundings by programming dynamic cellular behaviors regulated via cell-cell or cell-environment interactions. We next discuss the strengths and challenges of current ELMs and conclude by providing a perspective of future directions in this promising area.

A time-resolved, multi-symbol molecular recorder via sequential genome editing

DNA is naturally well suited to serve as a digital medium for in vivo molecular recording. However, contemporary DNA-based memory devices are constrained in terms of the number of distinct 'symbols' that can be concurrently recorded and/or by a failure to capture the order in which events occur1. Here we describe DNA Typewriter, a general system for in vivo molecular recording that overcomes these and other limitations. For DNA Typewriter, the blank recording medium ('DNA Tape') consists of a tandem array of partial CRISPR-Cas9 target sites, with all but the first site truncated at their 5' ends and therefore inactive. Short insertional edits serve as symbols that record the identity of the prime editing guide RNA2 mediating the edit while also shifting the position of the 'type guide' by one unit along the DNA Tape, that is, sequential genome editing. In this proof of concept of DNA Typewriter, we demonstrate recording and decoding of thousands of symbols, complex event histories and short text messages; evaluate the performance of dozens of orthogonal tapes; and construct 'long tape' potentially capable of recording as many as 20 serial events. Finally, we leverage DNA Typewriter in conjunction with single-cell RNA-seq to reconstruct a monophyletic lineage of 3,257 cells and find that the Poisson-like accumulation of sequential edits to multicopy DNA tape can be maintained across at least 20 generations and 25 days of in vitro clonal expansion.

Recording gene expression order in DNA by CRISPR addition of retron barcodes

Biological processes depend on the differential expression of genes over time, but methods to make physical recordings of these processes are limited. Here we report a molecular system for making time-ordered recordings of transcriptional events into living genomes. We do this through engineered RNA barcodes, based on prokaryotic retrons1, that are reverse transcribed into DNA and integrated into the genome using the CRISPR-Cas system2. The unidirectional integration of barcodes by CRISPR integrases enables reconstruction of transcriptional event timing based on a physical record through simple, logical rules rather than relying on pretrained classifiers or post hoc inferential methods. For disambiguation in the field, we will refer to this system as a Retro-Cascorder.

Model-guided engineering of DNA sequences with predictable site-specific recombination rates

Site-specific recombination (SSR) is an important tool in synthetic biology, but its applications are limited by the inability to predictably tune SSR reaction rates. Facile rate manipulation could be achieved by modifying the DNA substrate sequence; however, this approach lacks rational design principles. Here, we develop an integrated experimental and computational method to engineer the DNA attachment sequence attP for predictably modulating the inversion reaction mediated by the recombinase Bxb1. After developing a qPCR method to measure SSR reaction rate, we design, select, and sequence attP libraries to inform a machine-learning model that computes Bxb1 inversion rate as a function of attP sequence. We use this model to predict reaction rates of attP variants in vitro and demonstrate their utility in gene circuit design in Escherichia coli. Our high-throughput, model-guided approach for rationally tuning SSR reaction rates enhances our understanding of recombinase function and expands the synthetic biology toolbox.

Preservation and Encryption in DNA Digital Data Storage

The exponential growth of the total amount of global data presents a huge challenge to mainstream storage media. The emergence of molecular digital storage inspires the development of the new-generation higher-density digital data storage. In particular, DNA with high storage density, reproducibility, and long recoverable lifetime behaves the ideal representative of molecular digital storage media. With the development of DNA synthesis and sequencing technologies and the reduction of cost, DNA digital storage has attracted more and more attention and achieved significant breakthroughs. Herein, this Review briefly describes the workflow of DNA storage, and highlights the storage step of DNA digital data storage. Then, according to different information storage forms, the current DNA information encryption methods are emphatically expounded. Finally, the brief perspectives on the current challenges and optimizing proposals in DNA information preservation and encryption are presented.

DNA nanotechnology-empowered finite state machines

A finite state machine (FSM, or automaton) is an abstract machine that can switch among a finite number of states in response to temporally ordered inputs, which allows storage and processing of information in an order-sensitive manner. In recent decades, DNA molecules have been actively exploited to develop information storage and nanoengineering materials, which hold great promise for smart nanodevices and nanorobotics under the framework of FSM. In this review, we summarize recent progress in utilizing DNA self-assembly and DNA nanostructures to implement FSMs. We describe basic principles for representative DNA FSM prototypes and highlight their advantages and potential in diverse applications. The challenges in this field and future directions have also been discussed.

Synthetic nonlinear computation for genetic circuit design

Computation frameworks have been studied in synthetic biology to achieve biosignals integration and processing, for biosensing and therapeutics applications. Biological systems exhibit nonlinearity across scales from the molecular level, to biochemical network and intercellular systems. At the molecular level, cooperative bindings contribute to nonlinear molecular signal processing in a way similar to weight variables. At the intracellular network level, feedback and feedforward regulations result in cell behaviors such as multistability and adaptation. When biochemical networks are distributed in different cell groups, intercelluar networks can generate population dynamics. Here, we review works that highlight nonlinear computations in synthetic biology. We group the works according to the scale of implementations, from the cis-transcription level, to biochemical circuit level and cellular networks.