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Results for “synthetic biology”

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bioRxiv2026

Genetic Programming of Bacterial Microcompartments: Operon Order as a Tool for Nanoscale Morphogenesis

Gene order is a powerful design principle for protein nanomachines. In nature, gene organisation ensures the precise assembly of functional protein nanostructures. We demonstrate how genetic repositioning of the key structural gene pduN, within the operon encoding a self-assembling protein nanocompartment, sculpts the morphology and function of bacterial microcompartments (BMCs). Relocating pduN to new operonic positions dramatically altered the size, shape, and catalytic output of BMCs, despite identical protein sequences. These shifts reveal how gene order may control nanoscale assembly and compartmentalised function. Our findings establish operon architecture as a programmable genetic framework for nanostructure morphogenesis and provide a synthetic biology strategy to engineer self-assembling nanodevices with customised geometries and activities.

synthetic biology↗

bioRxiv2026

The proteome as a whole: from a passive reflection of the transcriptome to an active cellular organizer

Despite advances in proteomics, the proteome is still often viewed as a passive reflection of the transcriptome. Using Mycoplasma gallisepticum as a minimal cell model, we analyzed large-scale datasets across multiple stress conditions to investigate whether the proteome functions as an integrated regulatory system. The proteome remained quantitatively stable under stress, yet the bacteria adapted successfully. We identified a minimal core of 17 major proteins constituting 35% of cellular protein mass. These proteins exhibit distinct physicochemical properties--higher positive charge, lower hydrophilicity, and enrichment in intrinsically disordered regions--suggesting they shape cytoplasmic organization and may drive liquid-liquid phase separation. Minor proteins form tightly correlated clusters, while stress conditions trigger rearrangement of protein complexes without abundance changes, representing an energy-efficient adaptation strategy. Cross linking mass spectrometry revealed condition specific interactome remodeling, which may underlie mycoplasma adaptation to diverse stresses. Our findings suggest that the proteome operates as an active cellular organizer, where physicochemical properties and dynamic complex rearrangements enable adaptation independently of transcriptional control. This framework may inform synthetic biology efforts to engineer minimal cells.

synthetic biology↗

bioRxiv2019

Engineering gene overlaps to sustain genetic constructs in vivo

Evolution is often an obstacle to the engineering of stable biological systems due to the selection of mutations inactivating costly gene circuits. Gene overlaps induce important constraints on sequences and their evolution. We show that these constraints can be harnessed to increase the stability of synthetic circuits by purging loss-of-function mutations. We combine computational and synthetic biology approaches to rationally design an overlapping reading frame expressing an essential gene within an existing gene to protect. Our algorithm succeeded in creating overlapping reading frames in 80% of E. coli genes. Experimentally, scoring mutations in both genes of such overlapping construct, we found that a significant fraction of mutations impacting the gene to protect have a deleterious effect on the essential gene. Such an overlap thus protects a costly gene from removal by natural selection by associating the benefit of this removal with a larger or even lethal cost. In our synthetic constructs, the overlap converts many of the possible mutants into evolutionary dead-ends, effectively changing the fitness landscape and reducing the evolutionary potential of the system.

synthetic biology↗

bioRxiv2026

Surface Display For Phage Assisted Continuous Evolution: A Platform For Evolving / Screening Nanobodies In Prokaryote Systems

Despite >50 years of methods development, specific antibodies are still generated at low throughput and remain in high demand across biotechnology. Most biologics and immunoprobes are monoclonal antibodies, developed using a combination of inoculating animals with a target antigen, engineered candidate libraries, and multiple rounds of selection using phage or yeast display. Here we introduce a synthetic biology scheme to eliminate the need for nearly all of these steps, by combining Surface display on E. coli and Phage display with the microvirus {Phi}X174, Assisting Continuous Evolution (SurPhACE). Instead of building libraries for screening, SurPhACE runs a closed evolutionary program. A typical experiment can have 1011 mutant candidates under active selection, with complete turnover of the mutant population every 30min, or >5x1012 unique mutants per day, using less than 100mL of bacterial culture media. We demonstrate SurPhACE for optimizing a nanobody to a related epitope, and develop novel nanobodies for an arbitrary target using a minimal starting library to establish a proof of concept and identify best practices for this scalable method for generating protein binders.

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bioRxiv2016

Achieving large dynamic range control of gene expression with a compact RNA transcription-translation regulator

RNA transcriptional regulators are emerging as versatile components for genetic circuit construction. However, RNA transcriptional regulators suffer from incomplete repression, making their dynamic range less than that of their protein counterparts. This incomplete repression can cause expression leak, which impedes the construction of larger RNA synthetic regulatory networks. Here we demonstrate how naturally derived antisense RNA-mediated transcriptional regulators can be configured to regulate both transcription and translation in a single compact RNA mechanism that functions in Escherichia coli. Using in vivo gene expression assays, we show that a combination of transcriptional termination and RBS sequestration increases repression from 85% to 98% and activation from 10 fold to over 900 fold in response to cognate antisense RNAs. We also show that orthogonal versions of this mechanism can be created through engineering minimal antisense RNAs. Finally, to demonstrate the utility of this dual control mechanism, we use it to reduce circuit leak in an RNA-only transcriptional cascade that activates gene expression as a function of a small molecule input. We anticipate these regulators will find broad use as synthetic biology moves beyond parts engineering to the design and construction of larger and more sophisticated circuits.

Synthetic Biology↗

bioRxiv2023

Engineering Material Properties of Transcription Factor Condensates to Control Gene Expression in Mammalian Cells and Mice

Phase separation of biomolecules into condensates is a key mechanism in the spatiotemporal organization of biochemical processes in cells. However, the impact of the material properties of biomolecular condensates on important processes, such as the control of gene expression, remains largely elusive. Here, we systematically tune the material properties of optogenetically induced transcription factor condensates and probe their impact on the activation of target promoters. We demonstrate that transcription factors in rather liquid condensates correlate with increased gene expression levels, whereas stiffer transcription factor condensates correlate with the opposite effect, a reduced activation of gene expression. We demonstrate the broad nature of these findings in mammalian cells and mice, as well as by using different synthetic and natural transcription factors. We observe these effects for both transgenic and cell-endogenous promoters. Our findings provide a novel materials-based layer in the control of gene expression, which opens novel opportunities in optogenetic engineering and synthetic biology.

synthetic biology↗

bioRxiv2023

GADY algorithm: Towards an evolutionary protocol for bottom-up design of synthetic bacteria

Synthetic biology applications are currently based on the programming of bacteria with tailor-made circuits designed ad hoc by applying a top-down strategy. We introduce a novel algorithm oriented to design synthetic bacteria according to a bottom-up approach, i.e. via an evolutionary programming algorithm. The proposed algorithm has been referred to as GADY: an acronym for Get signal, Antidote, Die when a killer gene is expressed, emits Yellow fluorescence. We include in this technical note a script of the algorithm in Gro cellular programming language, programming a colony of synthetic bacteria and illustrating its usefulness in a case of bioremediation or elimination of a strain of pathogenic bacteria.

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bioRxiv2025

Construction and Functional Characterization of a Heterologous Quorum Sensing Circuit in Clostridium sporogenes

Quorum sensing (QS) is a bacterial communication mechanism that regulates gene expression in a population density-dependent manner. Substantial progress has been made in the engineering of QS systems in Gram-negative bacteria, but development of engineered QS systems in Gram positive bacteria remains limited. In this study, obligate anaerobic Gram-positive bacterium Clostridium sporogenes was engineered with the Staphylococcus aureus agr-QS system to enable density-dependent gene regulation. Using LC-MS/MS, we confirmed production of autoinducing peptides in the engineered C. sporogenes strain. A QS-regulated GFP reporter demonstrated activation of expression in response to both exogenous AIP addition and increasing cell density, confirming functional integration of the agr operon. A media refreshment experiment showed that replacing the culture supernatant delayed QS activation, highlighting the importance of signal accumulation. Moreover, we observed that a non-cognate AIP from another agr specificity group acts as a competitive antagonist, inhibiting gene expression under the QS promoter. To our knowledge, this study presents the first successful engineering of the agr quorum sensing system in an obligate anaerobe, expanding the synthetic biology toolkit and offers new opportunities for bacterial therapies and metabolic engineering.

synthetic biology↗

bioRxiv2025

Engineered translation release factor 1 suppresses disease-causing nonsense mutations and enables multi-site nonstandard amino acids incorporation

Nonsense mutations convert sense codons into premature termination codons (PTC), resulting in early termination of translation of mRNAs, underlie [~]11% of human genetic diseases. Restoring translation of genes carrying nonsense mutations remains a major therapeutic challenge. Here we present OPENER (Overexpression of Protein-engineered eRF1 for Nonsense Elision and Readthrough), a strategy to efficiently suppress nonsense mutations based on engineered variants of the eukaryotic translation termination factor eRF1. Through saturation mutagenesis of the human eRF1 N-domain, we identified variants, notably eRF1S77E, that promote efficient readthrough of all three PTCs (UAG, UGA, UAA) and rescue 12 pathogenic PTCs reporters in multiple disease contexts. Systemic delivery of OPENER-S77E via AAV8 in a Duchenne muscular dystrophy mouse model (DmdQ995X) restored dystrophin expression, improved muscle function, and ameliorated pathology without detected toxicity. Furthermore, when combined with orthogonal engineered aminoacyl-tRNA synthetase/tRNA pairs, OPENER-S77E enabled efficient, multi-site incorporation of nonstandard amino acids (BocK and AzF) into a single protein in mammalian cells, achieving efficiency of 27.77% and 19.83%, respectively. The incorporation efficiency of BocK was further enhanced to 32.80% in conditional eRF1-knockout cells. OPENER thus provides a platform for treating nonsense-mediated diseases and expands the synthetic biology toolkit for precise protein engineering.

synthetic biology↗

bioRxiv2026

Complete elucidation and heterologous reconstruction of the biosynthetic pathway of camptothecin

Camptothecin derivatives are first-line anticancer drugs used worldwide for the treatment of diverse malignant tumors. However, the biosynthetic pathway of camptothecin has remained elusive for five decades. Here, we fully map its entire biosynthetic route. We discovered five key missing enzymes (OpCAR, OpSDR11, OpCS, OpGH1, and OpSTR) via the combination of MALDI mass spectrometry imaging, single-cell RNA sequencing and co-expression analysis. Meanwhile, we demonstrated a free flavin mononucleotide triggered the non-enzymatic 6-5-6 to 6-6-5 fused-ring skeleton rearrangement, filling the last gap in camptothecin biosynthesis. Finally, we validated this identified pathway and achieved the de novo biosynthesis of camptothecin in Saccharomyces cerevisiae. These discoveries uncover the long-standing mystery underlying camptothecin and pave the way for manufacturing camptothecin and its derivatives through synthetic biology approaches.

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bioRxiv2025

Engineering Basal Cognition: Minimal Genetic Circuits for Habituation, Sensitization, and Massed-Spaced Learning

Cognition is often associated with complex brains, yet many forms of learning--such as habituation, sensitization, and even spacing effects--have been observed in single cells and aneural organisms. These simple cognitive abilities, despite their cost, offer evolutionary advantages by allowing organisms to reduce environmental uncertainty and improve survival. Recent studies have confirmed early claims of learning-like behavior in protists and slime molds, pointing to the presence of basal cognitive functions long before the emergence of nervous systems. In this work, we adopt a synthetic biology approach to explore how minimal genetic circuits can implement non-associative learning in unicellular and multicellular systems. Building on theoretical models and using well-characterized regulatory elements, we design and simulate synthetic circuits capable of reproducing habituation, sensitization, and the massed-spaced learning effect. Our designs incorporate activators, repressors, fluorescent reporters, and quorum-sensing molecules, offering a platform for experimental validation. By examining the structural and dynamical constraints of these circuits, we highlight the distinct temporal dynamics of gene-based learning systems compared to neural counterparts and provide insights into the evolutionary and engineering challenges of building synthetic cognitive behavior at the cellular level.

synthetic biology↗

bioRxiv2025

Sequestration-Based Neural Networks That Operate Out of Equilibrium

Classification of high-dimensional information is a ubiquitous computing paradigm across diverse biological systems, including organs such as the brain, down to signaling between individual cells. Inspired by the success of artificial neural networks in machine learning, the idea of engineering genetic circuits that operate as neural networks emerges as a strategy to expand the classification capabilities of living systems. In this work, we design these biomolecular neural networks (BNNs) based on the molecular sequestration reaction, and experimentally characterize their behavior as linear classifiers for increasing levels of complexity. Initially, we demonstrate that a static, DNA-based system can effectively prototype a linear classifier, though we also identify its limitations to easily tune the slope of the decision boundary it generates. We then propose and experimentally validate a BNN at the protein level using a cell-free transcription-translation (TXTL) system, which overcomes the DNA-based systems limitation and behaves as a linear classifier even before it reaches its steady state (or, equivalently, out-of-equilibrium). Ultimately, we test a CRISPR-based design and its out-of-equilibrium behavior in a biological context by successfully constructing a linear classifier within mammalian cells. Overall, by leveraging mathematical modeling and experimental automation, we establish molecular sequestration as a universal scheme for implementing neural networks within living systems, paving the way for transformative advances in synthetic biology and programmable biocomputing systems.

synthetic biology↗

bioRxiv2025

Predictive design of tissue-specific mammalian enhancers that function in vivo in the mouse embryo

Enhancers control tissue-specific gene expression across metazoans. Although deep learning has enabled enhancer prediction and design in mammalian cell lines and invertebrate systems, it remains unclear whether such approaches can operate within the regulatory complexity of mammalian tissues in vivo. Here, we present a general strategy for designing tissue-specific enhancers that function reliably in mice. We use deep learning to train compact convolutional neural networks (CNNs) on genome-wide chromatin accessibility and fine-tune them via transfer learning on validated human and mouse enhancers. Guided by these models, we design fifteen synthetic enhancers for the heart, limb, and central nervous system (CNS) in mouse embryos, all of which are active in their intended target tissue. Our work establishes a generalizable framework for programmable control of mammalian gene expression in vivo, opening new avenues in functional genomics, synthetic biology, and gene therapy.

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bioRxiv2021

Real-time environmental monitoring of contaminants using living electronic sensors

Real-time chemical sensing is needed to counter the global threats posed by pollution. We combine synthetic biology and materials engineering to develop a living bioelectronic sensor platform with minute detection times. Escherichia coli was programmed to reduce an electrode in a chemical-dependent manner using a modular, eight-component, synthetic electron transport chain. This strain produced significantly more current upon exposure to thiosulfate, an anion that causes microbial blooms. Incorporating a protein switch into the synthetic pathway and encapsulation of microbes with electrodes and conductive nanomaterials yielded a living bioelectronic sensor that could detect an endocrine disruptor within two minutes in riverine water, implicating the signal as mass transfer limited. These findings provide a new platform for miniature, low-power sensors that safeguard ecological and human health. One Sentence SummaryChemicals are detected electrically using an allosterically-regulated electron transfer pathway in designer microbes.

synthetic biology↗

bioRxiv2021

Acoustic Remote Control of Bacterial Immunotherapy

Rapid advances in synthetic biology are driving the development of genetically engineered microbes as therapeutic agents for a multitude of human diseases, including cancer. In particular, the immunosuppressive microenvironment of solid tumors creates a favorable niche for systemically administered bacteria to engraft in the tumor and release therapeutic payloads. However, such payloads can be harmful if released in healthy tissues where the bacteria also engraft in smaller numbers. To address this limitation, we engineer therapeutic bacteria to be controlled by focused ultrasound, a form of energy that can be applied noninvasively to specific anatomical sites such as solid tumors. This control is provided by a temperature-actuated genetic state switch that produces lasting therapeutic output in response to briefly applied focused ultrasound hyperthermia. Using a combination of rational design and high-throughput screening we optimized the switching circuits of engineered cells and connected their activity to the release of immune checkpoint inhibitors. In a clinically relevant cancer model, ultrasound-activated therapeutic microbes successfully turned on in situ and induced a marked suppression of tumor growth. This technology provides a critical tool for the spatiotemporal targeting of potent bacterial therapeutics in a variety of biological and clinical scenarios.

synthetic biology↗

bioRxiv2021

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

Site-specific recombination (SSR) is an important tool in genome editing and gene circuit design. However, its applications are limited by the inability to simply and predictably tune SSR reaction rates across orders of magnitude. Facile rate manipulation can in principle be achieved by modifying the nucleotide sequence of the DNA substrate of the recombinase, but the design principles for rationally doing so have not been elucidated. To enable predictable tuning of SSR reaction kinetics via DNA sequence, we developed an integrated experimental and computational method to parse individual nucleotide contributions to the overall reaction rate, which we used to analyze and engineer the DNA attachment sequence attP for the inversion reaction mediated by the serine recombinase Bxb1. A quantitative PCR method was developed to measure the Bxb1 reaction rate in vitro. Then, attP sequence libraries were designed, selected, and sequenced to inform a machine-learning model, which revealed that the Bxb1 reaction rate can be accurately represented assuming independent contributions of nucleotides at key positions. Next, we used the model to predict the performance of DNA site variants in reaction rate assays both in vitro and in Escherichia coli, with flipping rates ranging from 0.01- to 10-fold that of the wild-type attP sequence. Finally, we demonstrate that attP variants with predictable DNA recombination rates can be used in concert to achieve kinetic control in gene circuit design by coordinating the coexpression of two proteins in both their relative proportion and their total amount. Our high-throughput, data-driven method for rationally tuning SSR reaction rates through DNA sequence modification enhances our understanding of recombinase function and expands the synthetic biology toolbox. Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

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bioRxiv2024

Towards self-regeneration: exploring the limits of protein synthesis in the PURE cell-free transcription -translation system

Self-regeneration is a key function of living systems that needs to be recapitulated in vitro to create a living synthetic cell. A major limiting factor for protein self-regeneration in the PURE cell-free transcription-translation system is its high protein concentration, which far exceed the systems protein synthesis rate. Here we were able to drastically reduce the non-ribosomal PURE protein concentration up to 97.3% while increasing protein synthesis efficiency. Although crowding agents were not effective in the original PURE formulation, we found that in highly dilute PURE formulations addition of 6% dextran considerably increased protein synthesis rate and total protein yield. These new PURE formulations will be useful for many cell-free synthetic biology applications and we estimate that PURE can now support the complete self-regeneration of all 36 non-ribosomal proteins, which is a critical step towards the development of a universal biochemical constructor and living synthetic cell.

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bioRxiv2022

High-throughput functional characterization of combinations of transcriptional activators and repressors

Despite growing knowledge of the functions of individual human transcriptional effector domains, much less is understood about how multiple effector domains within the same protein combine to regulate gene expression. Here, we measure transcriptional activity for 8,400 effector domain combinations by recruiting them to reporter genes in human cells. In our assay, weak and moderate activation domains synergize to drive strong gene expression, while combining strong activators often results in weaker activation. In contrast, repressors combine linearly and produce full gene silencing, and repressor domains often overpower activation domains. We use this information to build a synthetic transcription factor whose function can be tuned between repression and activation independent of recruitment to target genes by using a small molecule drug. Altogether, we outline the basic principles of how effector domains combine to regulate gene expression and demonstrate their value in building precise and flexible synthetic biology tools.

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