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bioRxiv2025

Active learning-guided optimization of cell-free biosensors for lead testing in drinking water

Point-of-use diagnostics based on allosteric transcription factors (aTFs) are promising tools for environmental monitoring and human health. However, biosensors relying on natural aTFs rarely exhibit the sensitivity and selectivity needed for real-world applications, and traditional directed evolution struggles to optimize multiple biosensor properties at once. To overcome these challenges, we develop a multi-objective, machine learning (ML)-guided cell-free gene expression workflow for engineering aTF-based biosensors. Our approach rapidly generates high-quality sequence-to-function data, which we transform into an augmented paired dataset to train an ML model using directional labels that capture how aTF mutations alter performance. We apply our workflow to engineer the aTF PbrR as a point-of-use diagnostic for lead contamination in water. We tune the sensitivity of PbrR to sense at the U.S. Environmental Protection Agency (EPA) action level for lead and modify the selectivity away from zinc, a common metal found in water supplies. Finally, we show that the engineered PbrR functions in freeze-dried cell-free reactions, enabling a diagnostic capable of detecting lead in drinking water down to [~]5.7 ppb. Our ML-driven, multi-objective framework--powered by directional tokens-- can generalize to other biosensors and proteins, accelerating the development of synthetic biology tools for biotechnology applications.

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bioRxiv2026

Host background shapes the portability of a non-canonical translation initiation system across Escherichia coli strains

Translation initiation has become an attractive target for engineering orthogonal translation systems, yet the extent to which these systems retain functionality across distinct host backgrounds remains poorly defined. In bacteria, start codon recognition depends on pairing between the initiator tRNA anticodon and a suitable start codon within the appropriate distance from the Shine-Dalgarno sequence. These sequence-specific interactions enable translation initiation to be reprogrammed through anticodon engineering. What is currently missing is an understanding of how anticodon mutants of initiator tRNAs function across different bacterial strains. Here, we systematically evaluated the portability of a library of twelve i-tRNA anticodon mutants paired with their complementary non-canonical start codons. Most i-tRNA-start codon pairs supported detectable translation initiation across multiple strains, demonstrating broad functional portability. However, initiation efficiency, absolute system output, and fitness effects varied substantially between strains. Comparative genomic analyses revealed host-specific gene differences broadly, and endogenous tRNA gene sequence and copy number specifically, was associated with this variability. While most i-tRNA variants were well tolerated, a subset produced strain-dependent growth defects that primarily affected growth rate rather than final culture density. Together, these findings show that translation initiation efficacy of engineered i-tRNAs is partially strain-dependent and that host background must be considered a key design variable when deploying these translation systems. Looking forward, this study provides a framework for host-aware selection of microbial chassis for orthogonal translation applications in synthetic biology. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/719103v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@9c75deorg.highwire.dtl.DTLVardef@1fe704borg.highwire.dtl.DTLVardef@17e7808org.highwire.dtl.DTLVardef@1fa6fa1_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2026

Engineered probiotics target granulomas to treat mycobacterial infection

Granulomas are a pathological niche for mycobacteria that remain difficult to access with conventional therapies. Here we show that probiotic Escherichia coli Nissle 1917 (EcN) infiltrates and colonizes granulomas and can be engineered as a delivery system that senses the local microenvironment and releases antimycobacterial payloads. Specifically, we leveraged the hypoxic microenvironment of necrotic granulomas to restrict bacterial growth, and developed a dual-mode lysis circuit combining intracellular and extracellular killing for sustained payload release with limited evolutionary escape. We further engineered EcN to express a mycobacteriophage-derived enzyme, generating a strain that suppressed drug-sensitive and drug-resistant mycobacteria in vitro and potentiated conventional antibiotic activity. Engineered probiotics also reduced mycobacterial burden in vivo, and in a murine model of rifampicin-resistant infection, combination treatment with pretomanid achieved greater bacterial reduction than either monotherapy. Together, these results establish a synthetic biology framework for targeting granulomatous infections with programmable living microbes.

synthetic biology↗

bioRxiv2026

DNA condensate-based organelles for spatially regulated gene expression and protein targeting in synthetic cells

Spatial organization of gene expression is a key feature of cells but remains a major challenge in bottom-up synthetic biology. While phase-separated DNA condensates have been used to spatially confine transcription, achieving efficient recruitment of protein-coding DNA for full protein biosynthesis within these membrane-less structures has remained a major challenge. Here, we present a modular DNA nanostructure that enables tunable and highly efficient partitioning of long client DNA into condensate-based synthetic nuclei, thereby surpassing present limitations. This serves as the starting point for a multimodal DNA organelle-based system for spatially regulated gene expression in synthetic cell environments. The flow of information includes localized transcription within this synthetic nucleus, followed by translation and product release into the surrounding cytosol. Furthermore, we extend the toolkit of spatiotemporal organization by designing protein targeting of cell-cycle protein ParR within parC-enriched orthogonal DNA condensates. Quantitative analysis reveals a trend toward higher protein yield in the condensate-based system compared to standard PURE expression, indicating a functional advantage of spatial organization even in such minimal systems. Hence, we demonstrate how protein expression can be engineered not only by molecular composition, but by spatial architecture itself. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=123 SRC="FIGDIR/small/728287v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@1db026aorg.highwire.dtl.DTLVardef@17bb05dorg.highwire.dtl.DTLVardef@177ca3aorg.highwire.dtl.DTLVardef@17dcf9f_HPS_FORMAT_FIGEXP M_FIG C_FIG

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bioRxiv2021

Modular, robust and extendible multicellular circuit design in yeast

Division of labor between cells is ubiquitous in biology but the use of multi-cellular consortia for engineering applications is only beginning to be explored. A significant advantage of multi-cellular circuits is their potential to be modular with respect to composition but this claim has not yet been extensively tested using experiments and quantitative modeling. Here, we construct a library of 24 yeast strains capable of sending, receiving or responding to three molecular signals, characterize them experimentally and build quantitative models of their input-output relationships. We then compose these strains into two- and three-strain cascades as well a four-strain bistable switch and show that experimentally measured consortia dynamics can be predicted from the models of the constituent parts. To further explore the achievable range of behaviors, we perform a fully automated computational search over all two-, three- and four-strain consortia to identify combinations that realize target behaviors including logic gates, band-pass filters and time pulses. Strain combinations that are predicted to map onto a target behavior are further computationally optimized and then experimentally tested. Experiments closely track computational predictions. The high reliability of these model descriptions further strengthens the feasibility and highlights the potential for distributed computing in synthetic biology.

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bioRxiv2020

Integrating continuous hypermutation with high-throughput screening for optimization of cis,cis-muconic acid production in yeast

Directed evolution is a powerful method to optimize proteins and metabolic reactions towards user-defined goals. It usually involves subjecting genes or pathways to iterative rounds of mutagenesis, selection, and amplification. While powerful, systematic searches through large sequence-spaces is a labor-intensive task, and can be further limited by a priori knowledge about the optimal initial search space, and/or limits in terms of screening throughput. Here we demonstrate an integrated directed evolution workflow for metabolic pathway enzymes that continuously generates enzyme variants using the recently developed orthogonal replication system, OrthoRep, and screens for optimal performance in high-throughput using a transcription factor-based biosensor. We demonstrate the strengths of this workflow by evolving a ratelimiting enzymatic reaction of the biosynthetic pathway for cis,cis-muconic acid (CCM), a precursor used for bioplastic and coatings, in Saccharomyces cerevisiae. After two weeks of simply iterating between passaging of cells to generate variant enzymes via OrthoRep and high-throughput sorting of best-performing variants using a transcription factor-based biosensor for CCM, we ultimately identified variant enzymes improving CCM titers >13-fold compared to reference enzymes. Taken together, the combination of synthetic biology tools as adopted in this study, is an efficient approach to debottleneck repetitive workflows associated with directed evolution of metabolic enzymes.

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bioRxiv2024

Effect of translation enhancing nascent SKIK peptide on the arrest peptides containing consecutive Proline

Ribosome arrest peptides (RAPs) such as SecM arrest peptide (SecM AP) and WPPP with consecutive Pro residues, are known to induce translational stalling in Escherichia coli. We demonstrate that the translation enhancing SKIK peptide tag, which consisted of four amino acid residues Ser-Lys-Ile-Lys, effectively alleviate translational arrest caused by WPPP. Moreover, the proximity between SKIK and WPPP significantly influences the extent of this alleviation, observed in both PURE cell-free protein synthesis and in vivo protein production systems, resulting in a substantial increase in the yield of proteins containing such RAPs. Furthermore, we unveil that nascent SKIK peptide tag and translation elongation factor P (EF-P) which alleviate ribosome stalling in consecutive-Pro rich protein, synergistically promote translation. A kinetic analysis based on the generation of super folder green fluorescent protein under in vitro translation reaction reveals that the ribosome turnover is enhanced by more than 10-fold when the SKIK peptide tag is positioned immediately upstream of the SecM AP sequence. Our findings provide valuable insights into optimizing protein production processes, which are essential for advancing synthetic biology applications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/582505v2_ufig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@c97150org.highwire.dtl.DTLVardef@12e3fb1org.highwire.dtl.DTLVardef@157af4forg.highwire.dtl.DTLVardef@1b67da9_HPS_FORMAT_FIGEXP M_FIG C_FIG

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bioRxiv2023

Efficient Natural Plasmid Transformation of Vibrio natriegens Enables Zero-capital Molecular Biology

The fast-growing microbe Vibrio natriegens is capable of natural transformation where it draws DNA in from media via an active process under physiological conditions. Using an engineered strain with a genomic copy of the master competence regulator tfoX from Vibrio cholera in combination with a new minimal competence media (MCM) that uses acetate as an energy source, we demonstrate naturally competent cells which are created, transformed, and recovered entirely in the same media, without exchange or addition of new media. Cells are naturally competent to plasmids, recombination with linear DNA, and co-transformation of both to select for scarless and markerless genomic edits. The entire process is simple and inexpensive, requiring no capital equipment for an entirely room temperature process (Zero Capital protocol, 104 cfu/{micro}g), or just an incubator (High Efficiency protocol, 105-6 cfu/{micro}g). These cells retain their naturally competent state when frozen and are transformable immediately upon thawing like a typical chemical or electrochemical competent cell. Since the optimized transformation protocol requires only 50 minutes of hands-on time, and V. natriegens grows quickly even on plates, a transformation started at 9 AM yields abundant culturable single colonies by 5 PM. Further, because all stages of transformation occur in the same media, and the process can be arbitrarily scaled in volume, this natural competence strain and media could be ideal for automated directed evolution applications. As a result, naturally competent V. natriegens could compete with E. coli as an excellent chassis for low-cost and highly scalable synthetic biology.

synthetic biology↗

bioRxiv2019

Tuning Extracellular Electron Transfer by Shewanella oneidensis Using Transcriptional Logic Gates

Extracellular electron transfer pathways, such as those in the bacterium Shewanella oneidensis, interface cellular metabolism with a variety of redox-driven applications. However, designer control over EET flux in S. oneidensis has proven challenging since a functional understanding of its EET pathway proteins and their effect on engineering parameterizations (e.g., response curves, dynamic range) is generally lacking. To address this, we systematically altered transcription and translation of single genes encoding parts of the primary EET pathway of S. oneidensis, CymA/MtrCAB, and examined how expression differences affected model-fitted parameters for Fe(III) reduction kinetics. Using a suite of plasmid-based inducible circuits maintained by appropriate S. oneidensis knockout strains, we pinpointed construct/strain pairings that expressed cymA, mtrA, and mtrC with maximal dynamic range of Fe(III) reduction rate. These optimized EET gene constructs were employed to create Buffer and NOT gate architectures, that predictably turn on and turn off EET flux, respectively, in response to IPTG. Furthermore, we found that response functions generated by these logic gates (i.e., EET activity vs. inducer concentration) were comparable to those generated by conventional synthetic biology circuits, where fluorescent reporters are the output. Our results provide insight on programming EET activity with transcriptional logic gates and suggest that previously developed transcriptional circuitry can be adapted to predictably control EET flux.

synthetic biology↗

bioRxiv2023

A red light-induced genetic system for control of extracellular electron transfer

Optogenetics is a powerful tool for spatiotemporal control of gene expression. Several light-inducible gene regulators have been developed to function in bacteria, and these regulatory circuits have been ported into new host strains. Here, we developed and adapted a red light-inducible transcription factor for Shewanella oneidensis. This regulatory circuit is based on the iLight optogenetic system, which controls gene expression using red light. Promoter engineering and a thermodynamic model were used to adapt this system to achieve differential gene expression in light and dark conditions within a S. oneidensis host strain. We further improved the iLight optogenetic system by adding a repressor to invert the genetic circuit and activate gene expression under red light illumination. The inverted iLight genetic circuit was used to control extracellular electron transfer (EET) within S. oneidensis. The ability to use both red and blue light-induced optogenetic circuits simultaneously was demonstrated. Our work expands the synthetic biology toolbox of Shewanella, which could facilitate future advances in applications with electrogenic bacteria.

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bioRxiv2024

Design of bacterial DNT sensors based on computational models

Detecting explosive compounds such as 2,4,6-trinitrotoluene (TNT) and its volatile byproduct 2,4-dinitrotoluene (DNT) is paramount for public health and environmental safety. In this study, we present the successful application of diverse computational and data analysis models toward developing a bacterial biosensor engineered to detect DNT with high sensitivity and specificity. The Escherichia coli-based biosensor harbors a plasmid-based fusion of a gene promoter acting as the sensing element to a microbial bioluminescence gene cassette as the reporter. By analyzing endogenous and heterologous promoter data under conditions of DNT exposure, a total of 367 novel variants were generated. The biosensors engineered with these modifications demonstrated a remarkable amplification of up to 4-fold change in signal intensity upon exposure to 2,4-dinitrotoluene compared to non-modified biosensors, accompanied by a decrease in the detection threshold. Our analysis suggests that the sequence features with the highest contribution to biosensor performances are DNA folding patterns and nucleotide motifs associated with DNT sensing. These computational insights guided the rational design of the biosensor, leading to significantly improved DNT detection capabilities compared to the previous biosensor strain. Our results demonstrate the effectiveness of integrating computational modeling with synthetic biology techniques to develop advanced biosensors tailored for environmental monitoring applications. A similar approach may be applied to a wide array of ecological, industrial, and medical sensing endeavors.

synthetic biology↗

bioRxiv2018

Engineered cell-to-cell signalling within growing bacterial cellulose pellicles

Bacterial cellulose is a strong and flexible biomaterial produced at high yields by Acetobacter species and has applications in healthcare, biotechnology and electronics. Naturally, bacterial cellulose grows as a large unstructured polymer network around the bacteria that produce it, and tools to enable these bacteria to respond to different locations are required to grow more complex structured materials. Here, we introduce engineered cell-to-cell communication into a bacterial cellulose-producing strain of Komagataeibacter rhaeticus to enable different cells to detect their proximity within growing material and trigger differential gene expression in response. Using synthetic biology tools, we engineer Sender and Receiver strains of K. rhaeticus to produce and respond to the diffusible signalling molecule, acyl-homoserine lactone (AHL). We demonstrate that communication can occur both within and between growing pellicles and use this in a boundary detection experiment, where spliced and joined pellicles sense and reveal their original boundary. This work sets the basis for synthetic cell-to-cell communication within bacterial cellulose and is an important step forward for pattern formation within engineered living materials.

synthetic biology↗

bioRxiv2022

Rapid and accurate assembly of large DNA assisted by in vitro packaging of bacteriophage

Development of DNA assembly methods made it possible to construct large DNA. However, achieving the large DNA assembly easily, accurately, and at low cost remains a challenge. This study shows that DNA assembled only by annealing of overlapping single-stranded DNA ends, which are generated by exonuclease treatment, without ligation can be packaged in phage particles and can also be transduced into bacterial cells. Based on this, I developed a simple method to construct long DNA of about 40 - 50 kb from multiple PCR fragments using the bacteriophage in vitro packaging system. This method, named iPac (in vitro Packaging-assisted DNA assembly), allowed accurate and rapid construction of large plasmids and phage genomes. This simple method will accelerate research in molecular and synthetic biology, including the construction of gene circuits or the engineering of metabolic pathways. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/502418v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@13aa8f6org.highwire.dtl.DTLVardef@2aea9aorg.highwire.dtl.DTLVardef@19054c2org.highwire.dtl.DTLVardef@acb76a_HPS_FORMAT_FIGEXP M_FIG C_FIG

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bioRxiv2017

A systematic comparison of error correction enzymes by next-generation sequencing

Gene synthesis, the process of assembling gene-length fragments from shorter groups of oligonucleotides (oligos), is becoming an increasingly important tool in molecular and synthetic biology. The length, quality, and cost of gene synthesis is limited by errors produced during oligo synthesis and subsequent assembly. Enzymatic error correction methods are cost-effective means to ameliorate errors in gene synthesis. Previous analyses of these methods relied on cloning and Sanger sequencing to evaluate their efficiencies, limiting quantitative assessment and throughput. Here we develop a method to quantify errors in synthetic DNA by next-generation sequencing. We analyzed errors in a model gene assembly and systematically compared six different error correction enzymes across 11 conditions. We find that ErrASE and T7 Endonuclease I are the most effective at decreasing average error rates (up to 5.8-fold relative to the input), whereas MutS is the best for increasing the number of perfect assemblies (up to 25.2-fold). We are able to quantify differential specificities such as ErrASE preferentially corrects C/G [->] G/C transversions whereas T7 Endonuclease I preferentially corrects A/T [->] T/A transversions. More generally, this experimental and computational pipeline is a fast, scalable, and extensible way to analyze errors in gene assemblies, to profile error correction methods, and to benchmark DNA synthesis methods.

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bioRxiv2021

Virtual Parts Repository 2: Model-driven design of genetic regulatory circuits

Engineering genetic regulatory circuits is key to the creation of biological applications that are responsive to environmental changes. Computational models can assist in understanding especially large and complex circuits where manual analysis is infeasible, permitting a model-driven design process. However, there are still few tools that offer the ability to simulate the system under design. One of the reasons for this is the lack of accessible model repositories or libraries that cater for the modular composition of models of synthetic systems that do not yet exist in nature. Here, we present the Virtual Parts Repository 2, a resource to facilitate the model-driven design of genetic regulatory circuits, which provides reusable, modular and composable models. The repository is service-oriented and can be utilized by design tools in computational workflows. Designs provided in Synthetic Biology Open Language documents are used to derive system-scale and hierarchical Systems Biology Markup Language models. We also present a rule-based modeling abstraction based on reaction networks to facilitate scalable and modular modeling of complex and large designs. This modeling abstraction incorporates design patterns such as roadblocking, distributed deployment of genetic circuits using plasmids and cellular resource dependency. The computational resources and the modeling abstraction presented in this paper allow computational design tools to take advantage of computational simulations and ultimately help facilitate more predictable applications. Graphical TOC Entry O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/439316v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@be045dorg.highwire.dtl.DTLVardef@110856forg.highwire.dtl.DTLVardef@1a861eforg.highwire.dtl.DTLVardef@1b5cf48_HPS_FORMAT_FIGEXP M_FIG C_FIG

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bioRxiv2020

Rational engineering of Kluyveromyces marxianus to create a chassis for the production of aromatic products

The yeast Kluyveromyces marxianus offers unique potential for industrial biotechnology because of useful features like rapid growth, thermotolerance and a wide substrate range. As an emerging alternative platform, K. marxianus requires the development and validation of metabolic engineering strategies to best utilize its metabolism as a basis for bio-based production. To illustrate the synthetic biology strategies to be followed and showcase its potential, we describe a comprehensive approach to rationally engineer a metabolic pathway in K. marxianus. We use the phenylalanine biosynthetic pathway both as a prototype and because phenylalanine is a precursor for commercially valuable secondary metabolites. First, we modify and overexpress the pathway to be resistant to feedback inhibition so as to overproduce phenylalanine de novo from synthetic minimal medium. Second, we assess native and heterologous means to increase precursor supply to the biosynthetic pathway. Finally, we eliminate branch points and competing reactions in the pathway and rebalance precursors to redirect metabolic flux to a specific product, 2-phenylethanol (2-PE). As a result, we are able to construct robust strains capable of producing over 800 mg L-1 2-PE from minimal medium. The strains we constructed are a promising platform for the production of aromatic amino acid-based biochemicals, and our results illustrate challenges with attempting to combine individually beneficial modifications in an integrated platform.

synthetic biology↗

bioRxiv2021

Design and modular assembly of synthetic intramembrane proteolysis receptors for custom gene regulation in therapeutic cells

Synthetic biology has established powerful tools to precisely control cell function. Engineering these systems to meet clinical requirements has enormous medical implications. Here, we adopted a clinically driven design process to build receptors for the autonomous control of therapeutic cells. We examined the function of key domains involved in regulated intramembrane proteolysis and showed that systematic modular engineering can generate a class of receptors we call SyNthetic Intramembrane Proteolysis Receptors (SNIPRs) that have tunable sensing and transcriptional response abilities. We demonstrate the potential transformative utility of the receptor platform by engineering human primary T cells for multi-antigen recognition and production of dosed, bioactive payloads relevant to the treatment of disease. Our design framework enables the development of fully humanized and customizable transcriptional receptors for the programming of therapeutic cells suitable for clinical translation.

synthetic biology↗

bioRxiv2022

Creating De Novo Overlapped Genes

Future applications of synthetic biology will rely on deploying engineered cells outside of lab environments for long periods of time. Currently, a significant roadblock to this application is the potential for deactivating mutations in engineered genes. A recently developed method to protect engineered coding sequences from mutation is called Constraining Adaptive Mutations using Engineered Overlapping Sequences (CAMEOS). In this chapter we provide a workflow for utilising CAMEOS to create synthetic overlaps between two genes, one essential (infA) and one non-essential (aroB), to protect the non-essential gene from mutation and loss of protein function. In this workflow we detail the methods to collect large numbers of related protein sequences, produce multiple sequence alignments (MSAs), use the MSAs to generate Hidden Markov Models and Markov Random Field models, and finally generate a library of overlapping coding sequences through CAMEOS scripts. To assist practitioners with basic coding skills to try out the CAMEOS method, we have created a virtual machine containing all the required packages already installed, that can be downloaded and run locally.

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