Degradation tags, otherwise known as degrons, are portable sequences that can be used to alter protein stability. Here, we report that degron-tagged proteins compete for cellular degradation resources in engineered mammalian cells leading to coupling of the degradation rates of otherwise independently expressed proteins when constitutively targeted human degrons are adopted. We show the effect of this competition to be dependent on the context of the degrons. By considering different proteins, degron position and cellular hosts, we highlight how the impact of the degron on both degradation strength and resource coupling changes, with identification of orthogonal combinations. By adopting inducible bacterial and plant degrons we also highlight how controlled uncoupling of synthetic construct degradation from the native machinery can be achieved. We then build a genomically integrated capacity monitor tagged with different degrons and confirm resource competition between genomic and transiently expressed DNA constructs. This work expands the characterisation of resource competition in engineered mammalian cells to protein degradation also including integrated systems, providing a framework for the optimisation of heterologous expression systems to advance applications in fundamental and applied biological research.

Plasmids are central to modern biotechnology, especially therapeutic development, yet their propagation in Escherichia coli remains difficult to predict. Although expression-induced burden is well understood and can be mitigated, the impact of foreign DNA segments that do not function in bacteria on plasmid propagation and stability remains largely unknown. Here we developed a pooled, sequencing-based framework that performs quantitative profiling across millions of bases, enabling high-resolution assessment of plasmid fitness at scale and revealing cryptic, sequence-encoded interactions between foreign DNA elements and bacterial hosts. Promoter-like motifs, transcription factor binding site homology, and recombination-prone architectures emerge as major determinants of propagation efficiency, with context-dependent effects demonstrating that plasmid behaviour arises from higher-order interactions between parts rather than isolated elements. Extending this framework, we introduce TRACE, a neural-network model trained on degenerate sequence libraries that predicts plasmid propagation directly from sequence. TRACE generalises across plasmid architectures and can be fine-tuned on experimental datasets to improve predictions of manufacturability and host compatibility. These advances establish a generalisable, data-driven framework for understanding and designing host-aware plasmids, transforming plasmid production from an empirical process into a predictable property of DNA sequence.

Cell burden impacts the performance of engineered genetic constructs with great interest towards the development of tools to track it and improve biotechnology applications. Fluorogenic RNA aptamers are excellent candidates for live monitoring of burden because their production is expected to impose negligible load on the host. Here, we characterised a library of aptamers when expressed from different promoters in two Escherichia coli strains. We found that aptamer performance is dependent on the context of expression, and that, contrary to expectation, aptamer production impacts host fitness. We then built a library of burden-responsive biosensors testing their response to heterologous expression. The tRNA-Broc biosensor was selected for its fluorescence response, minimal impact on growth and ability to differentiate the burden imposed by different expression levels and constructs. The biosensor developed here adds to the collection of tools available to characterise burden and support applications where improved host performance is sought.

Protein secretion in mammalian cells is the active transport of proteins from the cytoplasm to the extracellular space. It plays a fundamental role in mammalian physiology and signaling, as well as biotherapeutics production and cell and gene therapies. The efficacy of protein secretion, however, is impacted by features of the secreted protein itself, and the host-cell machinery that supports each step of the secretion process. High-throughput techniques such as microfluidics, cell display, and cell encapsulation assays for the study and engineering of secreted proteins are transforming biomedical knowledge and our ability to modulate protein secretion. In addition, computational advances, including signal peptide modeling, whole-protein machine learning models, and genome-scale simulations, are opening new pathways for rational design of protein secretion. Here, we highlight recent developments in secretion engineering that are leading to the convergence of high-throughput experimentation and machine learning methods and can help address current challenges in bioproduction and support future efforts in cell and gene therapy while enabling new modalities.

While secretion plays a key role in the diverse applications of cell engineering, to date only a handful of mammalian signal peptides have been characterised in depth and systematic efforts to build novel variants remain sporadic. We present STAMPS (Signal-peptide Transformer for Augmenting Mammalian Protein Secretion), a generative, autoregressive transformer fine-tuned on ∼6,000 mammalian signal peptides to design de novo sequences that modulate and enhance secretion across proteins and hosts. We show that STAMPS can be used to identify candidate signal peptides that outperform the widely used IgG κ light-chain leader (IgKL) when used to secrete EGFP in HEK293T and CHO cells, and hEPO in HEK293T cells. When incorporated in an industrial cell line development framework, STAMPS leads to the generation of signal peptides that yield ∼2.3-fold gain in secretion of a VHH-Fc compared to the internal industrial benchmark in CHO G22 cells, with the same candidates ranking highly in both CHO and HEK293T hosts. Sequence-to–function analysis highlights a longer, strongly hydrophobic core and a tightly positioned cleavage site as drivers of this strong performance. Together, these results establish data-driven, generative design of mammalian signal peptides as a practical route to tune and improve secretion for bioproduction and cell engineering applications. ### Competing Interest Statement The authors have declared no competing interest.

Both Japan and the UK have recognized the growing importance of synthetic and engineering biology for transforming life science research and transitioning toward a sustainable biobased economy. Such a shift will require extensive international cooperation and collaboration. In this viewpoint, we provide a summary of the recent "Japan-UK Synthetic Biology Conference, Spring 2025" that aimed to facilitate new links between researchers across the broad field of synthetic biology. We cover the core scientific topics discussed, distill some of the emerging trends, and outline the remaining challenges that are hampering progress. We end by highlighting some of the ways in which international collaborations may help address these issues through a combination of sharing expertise, national infrastructures, and aligned funding.

Tools that manipulate gene expression in mammalian cells without any additional expression are critical for cell engineering applications. Here, we demonstrate the use of arrays of transcription factor (TF) recognition elements (REs) as DNA tools for controlling gene expression. We first demonstrate that TetR-based RE arrays can alter synthetic gene circuit performance. We then open the approach to any TF with a known binding site by developing a new technique called Cloning Troublesome Repeats in Loops (CTRL), which can assemble plasmids with up to 256 RE repeats. Transfection of custom RE array plasmids assembled by CTRL into mammalian cells modifies host cell gene regulation by sequestration of TFs of interest and can sequester both synthetic and native TFs, offering applications in the control of gene circuits and for directing cell fate. This work advances our ability to assemble repetitive DNA arrays and shows how TF-binding RE arrays expand possibilities in mammalian cell engineering.

Robust and stable expression of genes of interest is crucial for studying and engineering biology. While expressing desired gene products in some microorganisms is well established, achieving stable expression in mammalian systems is still a complex task. Over the years, various methods have been developed to integrate transgenes into mammalian cells, including the use of viral vectors, transposases, nucleases, and recombinases. This review aims to provide an overview of some of the commonly used integration strategies in mammalian cells, with a particular focus on methods toward site-specific integration, highlighting respective advantages and limitations and providing a summary of recent advances. Additionally, it also explores some of the challenges in the field, offering insights into potential directions for future development.

We combine RNA thermometer genetic switches, cell-free protein expression and synthetic cell design to create cell-sized systems that can initiate the synthesis of soluble proteins at defined temperatures. We show that when these switches are used to control the expression of a pore-forming membrane protein, temperature-controlled cargo release is achieved, with potential future applications in biomedicine.

Automated high-throughput methods that support tracking of mammalian cell growth are currently needed to advance cell line characterization and identification of desired genetic components required for cell engineering. Here, we describe a high-throughput noninvasive assay based on plate reader measurements. The assay relies on the change in absorbance of the pH indicator phenol red. We show that its basic and acidic absorbance profiles can be converted into a cell growth index consistent with cell count profiles, and that, by adopting a computational pipeline and calibration measurements, it is possible to identify a conversion that enables prediction of cell numbers from plate measurements alone. The assay is suitable for growth characterization of both suspension and adherent cell lines when these are grown under different environmental conditions and treated with chemotherapeutic drugs. The method also supports characterization of stably engineered cell lines and identification of desired promoters based on fluorescence output.

Synthetic cells containing genetic programs and protein expression machinery are increasingly recognized as powerful counterparts to engineered living cells in the context of biotechnology, therapeutics and cellular modelling. So far, genetic regulation of synthetic cell activity has been largely confined to chemical stimuli; to unlock their potential in applied settings, engineering stimuli-responsive synthetic cells under genetic regulation is imperative. Here we report the development of temperature-sensitive synthetic cells that control protein production by exploiting heat-responsive mRNA elements. This is achieved by combining RNA thermometer technology, cell-free protein expression and vesicle-based synthetic cell design to create cell-sized capsules able to initiate synthesis of both soluble proteins and membrane proteins at defined temperatures. We show that the latter allows for temperature-controlled cargo release phenomena with potential implications for biomedicine. Platforms like the one presented here can pave the way for customizable, genetically programmed synthetic cells under thermal control to be used in biotechnology.

Synthetic gene expression in engineered cells typically depends on the host cell’s limited pool of intracellular resources, which can lead to resource competition between native and engineered functions and may cause unanticipated effects in the host and synthetic gene circuit. For example, competition for shared resources may lead to cellular overload affecting physiological functions (that is, cellular burden) and negatively affect synthetic construct performance to the point of unreliability. This fundamental problem has implications for the use of synthetic genetic constructs in cell engineering for foundational research, therapy and bioprocessing. Resource competition has mainly been investigated in model bacteria systems, but also considerably affects eukaryotic systems, including mammalian cells. In this Review, we discuss resource competition beyond bacteria, outlining how it can lead to gene expression coupling, gene expression and metabolic burden. We also examine ways to quantify cellular burden in mammalian cells, and investigate circuit-centric and host-centric mitigation strategies, highlighting important implications of resource competition for cell engineering in therapeutic and bioproduction applications as well as in fundamental biology studies. Cell engineering by synthetic biology typically relies on synthetic gene constructs that compete with the host cell for intracellular resources. This Review discusses how such resource competition can impact mammalian cell engineering and outlines strategies for how to mitigate cellular burden using circuit-centric and host-centric approaches.

Eukaryotic mRNAs are characterized by terminal 5' cap structures and 3' polyadenylation sites, which are essential for posttranscriptional processing, translation initiation, and stability. Here, we describe a novel biosensor method designed to detect the presence of both cap structures and polyadenylation sites on mRNA molecules. This novel biosensor is sensitive to mRNA degradation and can quantitatively determine capping levels of mRNA molecules within a mixture of capped and uncapped mRNA molecules. The biosensor displays a constant dynamic range between 254 nt and 6507 nt with reproducible sensitivity to increases in capping level of at least 20% and a limit of detection of 2.4 pmol of mRNA. Overall, the biosensor can provide key information about mRNA quality before mammalian cell transfection.

Dermal tattoo biosensors are promising platforms for real-time monitoring of biomarkers, with skin used as a diagnostic interface. Traditional tattoo sensors have utilized small molecules as biosensing elements. However, the rise of synthetic biology has enabled the potential employment of engineered bacteria as living analytical tools. Exploiting engineered bacterial sensors will allow for potentially more sensitive detection across a broad biomarker range, with advanced processing and sense/response functionalities using genetic circuits. Here, the interfacing of bacterial biosensors as living analytics in tattoos is shown. Engineered bacteria are encapsulated into micron-scale hydrogel beads prepared through scalable microfluidics. These biosensors can sense both biochemical cues (model biomarkers) and biophysical cues (temperature changes, using RNA thermometers), with fluorescent readouts. By tattooing beads into skin models and confirming sensor activity post-tattooing, our study establishes a foundation for integrating bacteria as living biosensing entities in tattoos.

Eukaryotic cells are characterized by multiple chemically distinct compartments, one of the most notable being the nucleus. Within these compartments, there is a continuous exchange of information, chemicals, and signaling molecules, essential for coordinating and regulating cellular activities. One of the main goals of bottom-up synthetic biology is to enhance the complexity of synthetic cells by establishing functional compartmentalization. There is a need to mimic autonomous signaling between compartments, which in living cells, is often regulated at the genetic level within the nucleus. This advancement is key to unlocking the potential of synthetic cells as cell models and as microdevices in biotechnology. However, a technological bottleneck exists preventing the creation of synthetic cells with a defined nucleus-like compartment capable of genetically programmed intercompartment signaling events. Here, we present an approach for creating synthetic cells with distinct nucleus-like compartments that can encapsulate different biochemical mixtures in discrete compartments. Our system enables in situ protein expression of membrane proteins, enabling autonomous chemical communication between nuclear and cytoplasmic compartments, leading to downstream activation of enzymatic pathways within the cell.

Automated and non-invasive mammalian cell analysis is currently lagging behind due to a lack of methods suitable for a variety of cell lines and applications. Here, we report the development of a high throughput non-invasive method for tracking mammalian cell growth and performance based on plate reader measurements. We show the method to be suitable for both suspension and adhesion cell lines, and we demonstrate it can be adopted when cells are grown under different environmental conditions. We establish that the method is suitable to inform on effective drug treatments to be used depending on the cell line considered, and that it can support characterisation of engineered mammalian cells over time. This work provides the scientific community with an innovative approach to mammalian cell screening, also contributing to the current efforts towards high throughput and automated mammalian cell engineering.

Resource competition can be the cause of unintended coupling between co-expressed genetic constructs. Here we report the quantification of the resource load imposed by different mammalian genetic components and identify construct designs with increased performance and reduced resource footprint. We use these to generate improved synthetic circuits and optimise the co-expression of transfected cassettes, shedding light on how this can be useful for bioproduction and biotherapeutic applications. This work provides the scientific community with a framework to consider resource demand when designing mammalian constructs to achieve robust and optimised gene expression.

The use of cell-free protein synthesis (CFPS) has become increasingly widespread in synthetic biology over recent years, providing an effective platform for the study and engineering of cellular processes. The versatility and portability of CFPS systems have also boosted their potential for usage outside of the laboratory in a wide number of applications, from construct prototyping to bioproduction. CFPS is particularly well suited to biomedical applications, such as the production of clinical molecules and vaccines. It can also be integrated with additional technologies such as microfluidics and liposomal encapsulation to provide a new route for on-demand therapeutic expression. In this review we outline the key features of CFPS that make it a powerful platform for biomedical applications. We also discuss existing limitations with respect to the use of CFPS in the production of complex protein products and the limited production capacity of current systems. Addressing these will be integral in expanding the application of CFPS in biotherapy.(c) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Construction of DNA-encoded programs is central to synthetic biology and the chosen method often determines the time required to design and build constructs for testing. Here, we describe and summarise key features of the available toolkits for DNA construction for mammalian cells. We compare the different cloning strategies based on their complexity and the time needed to generate constructs of different sizes, and we reflect on why Golden Gate toolkits now dominate due to their modular design. We look forward to future advances, including accessory packs for cloning toolkits that can facilitate editing, orthogonality, advanced regulation, and integration into synthetic chromosome construction.