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Results for “Synthetic Biology”

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bioRxiv2018

Synthetic mammalian pattern formation driven by differential diffusivity of Nodal and Lefty

Pattern formation is fundamental for embryonic development. Although synthetic biologists have created several patterns, a synthetic mammalian reaction-diffusion pattern has yet to be realized. TGF-{beta} family proteins Nodal and Lefty have been proposed to meet the conditions for reaction-diffusion patterning: Nodal is a short-range activator that enhances the expression of Nodal and Lefty whereas Lefty acts as a long-range inhibitor against Nodal. However, the pattern forming possibility of the Nodal-Lefty signaling has never been directly tested, and the underlying mechanisms of differential diffusivity of Nodal and Lefty remain unclear. Here, through a combination of synthetic biology and theoretical modeling, we show that a reconstituted minimal network of the Nodal-Lefty signaling spontaneously gives rise to a pattern in mammalian cell culture. Surprisingly, extracellular Nodal was confined underneath the cells as small clusters, resulting in a narrow distribution range compared with Lefty. We further found that the finger 1 domain of the Nodal protein is responsible for its short-range distribution. By transplanting the finger 1 domain of Nodal into Lefty, we converted the originally long-range distribution of Lefty to a short-range one, successfully preventing the pattern formation. These results indicate that the differences in the localization and domain structures between Nodal and Lefty, combined with the activator-inhibitor topology, are sufficient for reaction-diffusion pattern formation in mammalian cells.

synthetic biology↗

bioRxiv2024

Expanding salivary biomarker detection by creating a synthetic neuraminic acid sensor via chimeragenesis

Accurate and timely diagnosis of oral squamous cell carcinoma (OSCC) is crucial in preventing its progression to advanced stages with poorer prognosis. As such, the construction of sensors capable of detecting previously established disease biomarkers for the early and non-invasive diagnosis of this and many other conditions has enormous therapeutic potential. In this work, we apply synthetic biology techniques for the development of a whole-cell biosensor (WCB) that leverages the physiology of engineered bacteria in vivo to promote the expression of an observable effector upon detection of a soluble molecule. To this end, we have constructed a bacterial strain expressing a novel chimeric transcription factor (Sphnx) for the detection of N-acetyl-D-neuraminic acid (Neu5Ac), a salivary biomolecule correlated with the onset of OSCC. This WCB serves as the proof-of-concept of a platform that can eventually be applied to clinical screening panels for a multitude of oral and systemic medical conditions whose biomarkers are present in saliva.

synthetic biology↗

bioRxiv2024

Designing minimal E. coli genomes using variational autoencoders

Designing minimal bacterial genomes remains a key challenge in synthetic biology. There is currently a lack of efficient tools for the rapid generation of streamlined bacterial genomes, limiting research in this area. Here, using a pangenome dataset for Escherichia coli, we show that variational autoencoders with modified loss functions can successfully create minimised genomes retaining the essential genes identified in the literature. We then sampled new genomes from our fitted model and performed computational validation using an E. coli whole-cell model. We found 6 out of 100 of the sampled genomes were viable in the computer model. These underwent a minimization routine starting from the MG1655 genome giving rise to six new minimal genomes with around a 40 % reduction in size. This study proposes a rapid, machine learning-based approach for bacterial sequence generation, that could accelerate the genomic design process.

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bioRxiv2020

CFPU: a cell-free processing unit for high-throughput, automated in vitro circuit characterization

Forward engineering synthetic circuits is at the core of synthetic biology. Automated solutions will be required to facilitate circuit design and implementation. Circuit design is increasingly being automated with design software, but innovations in experimental automation are lagging behind. Microfluidic technologies made it possible to perform in vitro transcription-translation (tx-tl) reactions with increasing throughput and sophistication, enabling screening and characterization of individual circuit elements and complete circuit designs. Here we developed an automated microfluidic cell-free processing unit (CFPU) that extends high-throughput screening capabilities to a continuous reaction environment, which is essential for the implementation and analysis of more complex and dynamic circuits. The CFPU contains 280 chemostats that can be individually programmed with DNA circuits. Each chemostat is periodically supplied with tx-tl reagents, giving rise to sustained, long-term steady state conditions. Using microfluidic pulse width modulation (PWM) the device is able to generate tx-tl reagent compositions in real-time. The device has higher throughput, lower reagent consumption, and overall higher functionality than current chemostat devices. We applied this technology to map transcription factor based repression under equilibrium conditions and implemented dynamic gene circuits switchable by small molecules. We expect the CFPU to help bridge the gap between circuit design and experimental automation for in vitro development of synthetic gene circuits.

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bioRxiv2026

Generative Neuromorphic Programming of Mammalian Cells

Cells make decisions through densely interconnected regulatory networks that compute graded, analog responses. Synthetic biology has made cells programmable, but the field's dominant abstractions poorly match the analog nature of cells. Designing analog circuits that work in cells is challenging: predicting how components combine remains difficult, and the vast combinatorial space of parts, weights and topologies exceeds what experiments can explore. Here we establish generative programming of mammalian cells through a neuromorphic framework that compiles desired behavior into DNA. Composable regulatory devices built from RNA-targeting endoribonucleases (ERNs) supply signed weights and nonlinear activation, enabling multi-layer circuits with diverse multi-input analog responses. To predict and design such circuits, we develop biomorphic neural networks (BMNs): a compositional architecture that mirrors biological interactions, in which each basic process (transcription, translation, cleavage) is captured by a reusable neural block learned from the behavior of whole circuits that contain it. Recomposed into architectures absent from training, these models predict responses with errors often comparable to variability between experimental repeats. Inverting this process, our software package, the biocompiler, jointly optimizes topology, parts, and weights to realize specified target behaviors. Challenged with three target behaviors, the biocompiler proposed three previously unseen architectures; we built all three, and each reproduced its target behavior in mammalian cells in a single design pass without manual tuning. Generative neuromorphic programming thus offers a systematic route to engineering the analog computation native to living cells.

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bioRxiv2021

Genetically engineered coral: A mixed-methods analysis of initial public opinion

Rising sea surface water temperatures is contributing to coral degradation in the Great Barrier Reef. Synthetic biology technologies offer the potential to enhance coral resilience to higher water temperatures. To explore what the public think of genetically engineered coral, qualitative responses to an open-ended question in a survey of 1,148 of the Australian public were analysed. More respondents supported the technology (59%) than did not (11%). However, a considerable proportion indicated moderate or neutral support (29%). Participants commented about the (moral) right to interfere with nature and uncertainty regarding the consequences of implementing the technology. Participants also mentioned the need to take responsibility and act to save the reef, as well as the benefits likely to result from implementing the technology. Other themes included a desire for further testing and proof, more information, and tight regulation and controls when introducing the technology.

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bioRxiv2021

A Codon Constrained Method for Both Eliminating and Creating Intragenic Bacterial Promoters

Future applications of synthetic biology will require refactored genetic sequences devoid of internal regulatory elements within coding sequences. These regulatory elements include cryptic and intragenic promoters which may constitute up to a third of predicted Escherichia coli promoters. Promoter activity is dependent on the structural interaction of core bases with a {sigma} factor. Rational engineering can be used to alter key promoter element nucleotides interacting with {sigma} factors and eliminate downstream transcriptional activity. In this paper, we present COdon Restrained Promoter SilEncing (CORPSE), a system for removing intragenic promoters. CORPSE exploits the DNA-{sigma} factor structural relationship to disrupt {sigma}70 promoters embedded within gene coding sequences, with a minimum of synonymous codon changes. Additionally, we present an inverted CORPSE system, iCORPSE, which can create highly active promoters within a gene sequence while not perturbing the function of the modified gene.

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bioRxiv2024

Multiplexing bacteriocin synthesis to kill and prevent antimicrobial resistance

Antibiotic resistance represents an emergency for global public health. This calls for using alternative drugs and developing innovative therapies based on a clear understanding of their mechanisms of action and resistance in bacteria. Bacteriocins represent a unique class of natural molecules selectively eliminating bacteria. These secreted proteins exhibit a narrower spectrum of activity compared to conventional broad-spectrum antimicrobials by interacting with specific protein and lipid receptors on bacterial cell envelopes. Despite their diverse molecular structures, the commonality of being genetically encoded makes bacteriocins amenable to synthetic biology design. In using cell-free gene expression (CFE) and continuous-exchange CFE (CECFE), we produced controlled combinations (cocktails) of bacteriocins in single synthesis reactions for the first time. A first set of bacteriocin cocktails comprising both linear and circular proteins allowed the targeting of different bacterial species. Other cocktails were designed to target one bacterial species and considering bacteriocins pathways to cross the cell-envelope. Such combinations demonstrated efficient bacterial eradication and prevention of resistance. We illustrate the effectiveness of these bacteriocin mixtures in eradicating various human pathogenic-multiresistant--isolates. Finally, we highlight their potential as targeted and versatile tools in antimicrobial therapy by testing a combination of bacteriocins for treatment in vivo in the animal model Galleria mellonella.

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bioRxiv2023

Effects of growth feedback on gene circuits: A dynamical understanding

The successful integration of engineered gene circuits into host cells remains a significant challenge in synthetic biology due to circuit-host interactions, such as growth feedback, where the circuit influences cell growth and vice versa. Understanding the dynamics of circuit failures and identifying topologies resilient to growth feedback are crucial for both fundamental and applied research. Utilizing transcriptional regulation circuits with adaptation as a paradigm, we systematically study more than four hundred topological structures and uncover various categories of failures. Three dynamical mechanisms of circuit failures are identified: continuous deformation of the response curve, strengthened or induced oscillations, and sudden switching to coexisting attractors. Our extensive computations also uncover a scaling law between a circuit robustness measure and the strength of growth feedback. Despite the negative effects of growth feedback on the majority of circuit topologies, we identify several circuits that maintain optimal performance as designed, a feature important for applications.

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bioRxiv2017

Refactoring gene sequences for broad assembly standards compatibility

Four cloning standards in synthetic biology are BioBrick, BglBrick, MoClo and GoldenBraid, with each requiring their constitutive parts be compatible with the associated restriction enzymes. To standardize parts for the broadest usage, it would be useful to synthesize genes that are simultaneously compatible with all 4 popular assembly strategies. Here it is shown that using a defined set of rules, implemented in a computational program, any protein coding sequence can be made compatible with all four standards by silent mutations. Using a coding sequence as an input, all BioBrick, BglBrick, MoClo, and GoldenBraid restriction sites and chi recombination hot spots can be destroyed with silent mutations that approximate the codon usage of the organism. As an application, all open reading frames in the model organisms Escherichia Coli and Bacillus Subtilis are computationally refactored, showing the feasibility of implementing this umbrella strategy for synthesizing genes with the broadest compatibility.

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bioRxiv2024

Sustainable Regeneration of 20 Aminoacyl-tRNA Synthetases in a Reconstituted System Toward Self-Synthesizing Artificial Systems

In vitro construction of self-reproducible artificial systems is a major challenge in bottom-up synthetic biology. Here, we developed a reconstituted system capable of sustainably regenerating all 20 aminoacyl-tRNA synthetases (aaRSs), which are major components of the translation system. To achieve this, we needed five types of improvements: 1) optimization of aaRS sequences for efficient translation, 2) optimization of the composition of the translation system to enhance translation, 3) employment of another bacterial AlaRS and SerRS to improve each aminoacylation activity, 4) diminishing the translational inhibition caused by certain aaRS sequences by codon optimization and EF-P addition, and 5) balancing the DNA concentrations of 20 aaRSs to match each requirement. After these improvements, we succeeded in the sustainable regeneration of all 20 aaRSs for up to 20 cycles of 2.5-fold serial dilutions. These methodologies and results provide a substantial advancement toward the realization of self-reproducible artificial systems.

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bioRxiv2016

Ribo-attenuators: novel elements for reliable and modular riboswitch engineering

Riboswitches are structural genetic regulatory elements that directly couple the sensing of small molecules to gene expression. They have considerable potential for applications throughout synthetic biology and bio-manufacturing as they are able to sense a wide range of small molecules and regulate gene expression in response. Despite over a decade of research they have yet to reach this considerable potential as they cannot yet be treated as modular components. This is due to several limitations including sensitivity to changes in genetic context, low tunability, and variability in performance. To overcome the associated difficulties with riboswitches, we have designed and introduced a novel genetic element called a Ribo-attenuator in Bacteria. This genetic element allows for predictable tuning, insulation from contextual changes, and a reduction in expression variation. Ribo-attenuators allow riboswitches to be treated as truly modular and tunable components, and thus increases their reliability for a wide range of applications.

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bioRxiv2020

Improved stability of an engineered function using adapted bacterial strains

Engineering useful functions into cells is one of the primary goals of synthetic biology. However, engineering novel functions that remain stable for multiple generations remains a significant challenge. Here we report the importance of host fitness on the stability of an engineered function. We find that the initial fitness of the host cell affects the stability of the engineered function. We demonstrate that adapting a strain to the intended growth condition increases fitness and in turn improves the stability of the engineered function over hundreds of generations. This approach offers a simple and effective method to increase the stability of engineered functions without genomic modification or additional engineering and will be useful in improving the stability of novel, engineered functions in living cells. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/979385v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@dfeebeorg.highwire.dtl.DTLVardef@1b31a24org.highwire.dtl.DTLVardef@1795435org.highwire.dtl.DTLVardef@8775c4_HPS_FORMAT_FIGEXP M_FIG C_FIG

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bioRxiv2021

PccGEO: prior constraints conditioned genetic elements optimization

Functional genetic elements are one of the most essential units for synthetic biology. However, both knowledge-driven and data-driven methodology can hardly accomplish the complicated task of genetic elements design efficiently due to the lack of explicit regulatory logics and training samples. Here, we proposed a knowledge-constraint deep learning model named PccGEO to automatically design functional genetic elements with high success rate and efficiency. PccGEO utilized a novel "fill-in-the-flank" strategy with a conditional generative adversarial network structure to optimize the flanking regions of known functional sequences derived from the biological prior knowledge, which can efficiently capture the implicit patterns with a reduced searching space. We applied PccGEO in the design of Escherichia coli promoters, and found that the implicit patterns in flanking regions matter to the properties of promoters such as the expression level. The PccGEO-designed constitutive and inducible promoters showed more than 91.6% chance of success by in vivo validation. We further utilized PccGEO by setting a limited frequency of nucleotide modifications and surprisingly found that the expression level of E. coli sigma 70 promoters could show up to a 159.3-fold increase with only 10-bp nucleotide modifications. The results supported that the implicit patterns are important in the design of functional gene elements and validated the strong capacity of our method in the efficient design of functional genetic elements. Availabilityhttps://github.com/WangLabTHU/PccGEO

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bioRxiv2025

Chromatin landscape of budding yeast acquiring H3K9 methylation and its reader molecule HP1

Histone H3 lysine 9 (H3K9) methylation and heterochromatin protein 1 (HP1) are well conserved heterochromatin epigenome and its reader molecule. However, the details of how importance of them in heterochromatin formation still remain unclear. One of the reasons is the redundancy aspects, as there are multiple H3K9 methylation reader molecules, including HP1, and HP1 itself functions as a hub recruiting various effector molecules. To overcome those issues, we took a synthetic biology approach and introduced H3K9 methylation and HP1 into budding yeast Saccharomyces cerevisiae, which does not have this system, and examined its impact on transcription and chromatin compaction. We observed that the mammalian H3K9 methyltransferase can induce genome-wide H3K9 di- and tri-methylation (H3K9me2,3) in the budding yeast which mainly in the gene body region, and HP1 accumulates over the H3K9 methylated regions. The forced expression of H3K9 methyltransferase and HP1 had little impact on transcription. Furthermore, Micro-C-seq analysis revealed no significant effects on the chromatin 3D structure. These results suggest that although H3K9 methylation and recruitment of HP1 play essential roles in the epigenetic regulation of heterochromatin, they alone are not sufficient to alter the higher-order chromatin structure, at least in the gene body regions in budding yeast.

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bioRxiv2023

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

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

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bioRxiv2025

Harnessing Mass Spectrometry-Based Proteomics for Continuous Directed Evolution

Continuous directed evolution is a powerful Synthetic Biology tool to engineer proteins with desired functions in vivo. Mimicking natural evolution, it involves repeated cycles of high-frequency mutagenesis, selection, and replication within platform cells, where the function of the target gene is tightly linked to the host cells fitness. However, cells might escape the selection pressure due to the inherent flexibility of their metabolism, which allows for adaptation. Whole-proteome analysis as well as targeted proteomics offer valuable insights into global and specific cellular changes. They can identify modifications in the target protein and its interactors to help understand its evolution and network integration. Using the continuous evolution of the Arabidopsis methionine synthases AtMS1 and AtMS2 as an example, we demonstrate how mass spectrometry-based proteomics can be applied in CDE, propose specific checkpoints for its integration and illustrate its role in informed decision making.

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bioRxiv2026

Theoretical framework and experimental demonstration of sustainable in vitro regeneration of major translation factors EF-Tu and IF3

The development of molecular systems capable of self-regeneration, much like living organisms, is a major goal in synthetic biology. Previous efforts to expand the repertoire of regenerating proteins have relied on empirical optimization without a theoretical foundation, fundamentally limiting the scalability of this approach. Here, we developed the first theoretical framework, based on measurable parameters of translational proteins, to rationally predict the dilution rate that enables sustainable regeneration and the steady-state translation level. Using this framework, we successfully demonstrated sustainable regeneration of EF-Tu, the most abundant translation factor, for up to 15 rounds of serial dilution. We further extended this framework to the co-regeneration of multiple translation factors and demonstrated sustainable co-regeneration of EF-Tu and IF3, another major essential translation protein, for up to 20 rounds. These results establish a rational methodology for systematically expanding the number of regenerating proteins, providing a clear path toward the realization of a fully self-regenerating system.

Synthetic Biology↗