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Integrating synthetic biology into wearables could expand opportunities for noninvasive monitoring of physiological status, disease states and exposure to pathogens or toxins. However, the operation of synthetic circuits generally requires the presence of living, engineered bacteria, which has limited their application in wearables. Here we report lightweight, flexible substrates and textiles functionalized with freeze-dried, cell-free synthetic circuits, including CRISPR-based tools, that detect metabolites, chemicals and pathogen nucleic acid signatures. The wearable devices are activated upon rehydration from aqueous exposure events and report the presence of specific molecular targets by colorimetric changes or via an optical fiber network that detects fluorescent and luminescent outputs. The detection limits for nucleic acids rival current laboratory methods such as quantitative PCR. We demonstrate the development of a face mask with a lyophilized CRISPR sensor for wearable, noninvasive detection of SARS-CoV-2 at room temperature within 90 min, requiring no user intervention other than the press of a button. Wearable materials are endowed with synthetic biology circuits to detect biomolecules, including SARS-CoV-2 RNA.

Cellular processes are carried out by many genes, and their study and optimization requires multiple levers by which they can be independently controlled. The most common method is via a genetically encoded sensor that responds to a small molecule. However, these sensors are often suboptimal, exhibiting high background expression and low dynamic range. Further, using multiple sensors in one cell is limited by cross-talk and the taxing of cellular resources. Here, we have developed a directed evolution strategy to simultaneously select for lower background, high dynamic range, increased sensitivity, and low cross-talk. This is applied to generate a set of 12 high-performance sensors that exhibit >100-fold induction with low background and cross-reactivity. These are combined to build a single “sensor array” in the genomes of E. coli MG1655 (wild-type), DH10B (cloning), and BL21 (protein expression). These “Marionette” strains allow for the independent control of gene expression using 12 small-molecule inducers. A directed evolution approach was applied to optimize a set of 12 small-molecule-responsive biosensors, which led to the engineering of “Marionette” strains of Escherichia coli incorporating these sensors for biotechnological applications.

Prediction of enzyme kinetic parameters is essential for designing and optimizing enzymes for various biotechnological and industrial applications, but the limited performance of current prediction tools on diverse tasks hinders their practical applications. Here, we introduce UniKP, a unified framework based on pretrained language models for the prediction of enzyme kinetic parameters, including enzyme turnover number ( k cat ), Michaelis constant ( K m ), and catalytic efficiency ( k cat / K m ), from protein sequences and substrate structures. A two-layer framework derived from UniKP (EF-UniKP) has also been proposed to allow robust k cat prediction in considering environmental factors, including pH and temperature. In addition, four representative re-weighting methods are systematically explored to successfully reduce the prediction error in high-value prediction tasks. We have demonstrated the application of UniKP and EF-UniKP in several enzyme discovery and directed evolution tasks, leading to the identification of new enzymes and enzyme mutants with higher activity. UniKP is a valuable tool for deciphering the mechanisms of enzyme kinetics and enables novel insights into enzyme engineering and their industrial applications. Prediction of enzyme kinetic parameters is essential for designing and optimising enzymes for various biotechnological and industrial applications. Here, authors presented a prediction framework (UniKP), which improves the accuracy of predictions for three enzyme kinetic parameters.

Advances in synthetic biology enable microbial hosts to synthesize valuable natural products in an efficient, cost-competitive and safe manner. However, current engineering endeavors focus mainly on enzyme engineering and pathway optimization, leaving the role of cofactors in microbial production of natural products and cofactor engineering largely ignored. Here we systematically engineered the supply and recycling of three cofactors (FADH2, S-adenosyl-l-methion and NADPH) in the yeast Saccharomyces cerevisiae, for high-level production of the phenolic acids caffeic acid and ferulic acid, the precursors of many pharmaceutical molecules. Tailored engineering strategies were developed for rewiring biosynthesis, compartmentalization and recycling of the cofactors, which enabled the highest production of caffeic acid (5.5 ± 0.2 g l−1) and ferulic acid (3.8 ± 0.3 g l−1) in microbial cell factories. These results demonstrate that cofactors play an essential role in driving natural product biosynthesis and the engineering strategies described here can be easily adopted for regulating the metabolism of other cofactors.Engineering the biosynthesis, compartmentalization and recycling of three cofactors enables increased production of caffeic acid and ferulic acid in yeast, suggesting that these strategies could improve metabolic flux to other desirable compounds.

The formation of biomolecular condensates mediated by a coupling of associative and segregative phase transitions plays a critical role in controlling diverse cellular functions in nature. This has inspired the use of phase transitions to design synthetic systems. While design rules of phase transitions have been established for many synthetic intrinsically disordered proteins, most efforts have focused on investigating their phase behaviors in a test tube. Here, we present a rational engineering approach to program the formation and physical properties of synthetic condensates to achieve intended cellular functions. We demonstrate this approach through targeted plasmid sequestration and transcription regulation in bacteria and modulation of a protein circuit in mammalian cells. Our approach lays the foundation for engineering designer condensates for synthetic biology applications. Dai et al. present a streamlined approach for the design and engineering of synthetic biomolecular condensates for controlling different cellular processes, such as gene flow, transcriptional regulation and modulation of protein circuits.

Liquid–liquid phase separation has emerged as an important means of intracellular RNA compartmentalization. Some membraneless organelles host two or more compartments serving different putative biochemical roles. The mechanisms for, and functional consequences of, this subcompartmentalization are not yet well understood. Here we show that adjacent phases of decapeptide-based multiphase model membraneless organelles differ markedly in their interactions with RNA. Single- and double-stranded RNAs preferentially accumulate in different phases within the same droplet, and one phase is more destabilizing for RNA duplexes than the other. Single-phase peptide droplets did not capture this behaviour. Phase coexistence introduces new thermodynamic equilibria that alter RNA duplex stability and RNA sorting by hybridization state. These effects require neither biospecific RNA-binding sites nor full-length proteins. As such, they are more general and point to primitive versions of mechanisms operating in extant biology that could aid understanding and enable the design of functional artificial membraneless organelles. The biochemical roles and mechanisms of multiphase membraneless organelles are not yet well understood. Now, multiphase peptide droplets have been shown to sort RNA based on whether it is single- or double-stranded, as well as impact RNA duplexation through in-droplet thermodynamic equilibria. This work provides insight into possible primitive mechanisms for multicompartment intracellular condensates and can aid in the design of functional artificial membraneless organelles.

Protein condensates are distinct structures assembled in living cells that concentrate molecules via phase separation in a confined subcellular compartment. In the past decade, remarkable advances have been made to discover the fundamental roles of the condensates in spatiotemporal control of cellular metabolism and physiology and to reveal the molecular principles, components and driving forces that underlie their formation. Here we review the unique properties of the condensates, the promise and hurdles for harnessing them toward purposeful design and manipulation of biological functions in living cells. In particular, we highlight recent advances in mining and understanding the proteinaceous components for creating designer condensates, along with the engineering approaches to manipulate their material properties and biological functions. With these advances, a greater variety of complex organelle-like structures can be built for diverse applications, with unprecedented effects on synthetic biology.Protein condensates are subcellular structures that enrich and confine molecules in cells. This Review details how condensates can be engineered with responsiveness and on-demand functions, thus pushing cellular and metabolic engineering to a new level.

Cell-free biosensors are powerful platforms for monitoring human and environmental health. Here, we expand their capabilities by interfacing them with toehold-mediated strand displacement circuits, a dynamic DNA nanotechnology that enables molecular computation through programmable interactions between nucleic acid strands. We develop design rules for interfacing a small molecule sensing platform called ROSALIND with toehold-mediated strand displacement to construct hybrid RNA–DNA circuits that allow fine-tuning of reaction kinetics. We use these design rules to build 12 different circuits that implement a range of logic functions (NOT, OR, AND, IMPLY, NOR, NIMPLY, NAND). Finally, we demonstrate a circuit that acts like an analog-to-digital converter to create a series of binary outputs that encode the concentration range of the molecule being detected. We believe this work establishes a pathway to create ‘smart’ diagnostics that use molecular computations to enhance the speed and utility of biosensors.Equipping ROSALIND, a cell-free biosensing platform, with information processing circuits based on toehold-mediated DNA strand displacement enhances sensor performance and enables logic gate computation.

Transient molecules in the gastrointestinal tract such as nitric oxide and hydrogen sulfide are key signals and mediators of inflammation. Owing to their highly reactive nature and extremely short lifetime in the body, these molecules are difficult to detect. Here we develop a miniaturized device that integrates genetically engineered probiotic biosensors with a custom-designed photodetector and readout chip to track these molecules in the gastrointestinal tract. Leveraging the molecular specificity of living sensors 1 , we genetically encoded bacteria to respond to inflammation-associated molecules by producing luminescence. Low-power electronic readout circuits 2 integrated into the device convert the light emitted by the encapsulated bacteria to a wireless signal. We demonstrate in vivo biosensor monitoring in the gastrointestinal tract of small and large animal models and the integration of all components into a sub-1.4 cm 3 form factor that is compatible with ingestion and capable of supporting wireless communication. With this device, diseases such as inflammatory bowel disease could be diagnosed earlier than is currently possible, and disease progression could be more accurately tracked. The wireless detection of short-lived, disease-associated molecules with our device could also support timely communication between patients and caregivers, as well as remote personalized care. A biosensor comprising bacteria engineered to respond to transient inflammatory signals has been packaged with electronic readout and transmission circuits in a small device that could be swallowed to monitor gastrointestinal health.

Cells harbour numerous mesoscale membraneless compartments that house specific biochemical processes and perform distinct cellular functions. These protein- and RNA-rich bodies are thought to form through multivalent interactions among proteins and nucleic acids, resulting in demixing via liquid–liquid phase separation. Proteins harbouring intrinsically disordered regions (IDRs) predominate in membraneless organelles. However, it is not known whether IDR sequence alone can dictate the formation of distinct condensed phases. We identified a pair of IDRs capable of forming spatially distinct condensates when expressed in cells. When reconstituted in vitro, these model proteins do not co-partition, suggesting condensation specificity is encoded directly in the polypeptide sequences. Through computational modelling and mutagenesis, we identified the amino acids and chain properties governing homotypic and heterotypic interactions that direct selective condensation. These results form the basis of physicochemical principles that may direct subcellular organization of IDRs into specific condensates and reveal an IDR code that can guide construction of orthogonal membraneless compartments. Cells spatially organize biochemical reactions within membrane-bound and membraneless compartments. The extent to which intrinsically disordered proteins themselves can form discrete compartments or condensed phases is poorly understood. Now a pair of model IDRs that display orthogonality in condensation and the chain features governing selective assembly have been identified.