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Results for “Synthetic Biology”

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bioRxiv2023

Cell-Free Protein Expression in Polymer Materials

While synthetic biology has advanced complex capabilities like sensing and molecule synthesis in aqueous solutions, important applications may also be pursued for biological systems in solid materials. Harsh processing conditions used to produce many synthetic materials such as plastics makes incorporation of biological functionality challenging. One technology that shows promise in circumventing these issues is cell-free protein synthesis (CFPS), where core cellular functionality is reconstituted outside the cell. CFPS enables genetic functions to be implemented without the complications of membrane transport or concerns over cellular viability or release of genetically modified organisms. Here we demonstrate that dried CFPS reactions have remarkable tolerance to heat and organic solvent exposure during the casting processes for polymer materials. We demonstrate the utility of this observation by creating plastics that have spatially patterned genetic functionality, produce antimicrobials in situ, and perform sensing reactions. The resulting materials unlock the potential to deliver DNA-programmable bio-functionality in a ubiquitous class of synthetic materials.

synthetic biology↗

bioRxiv2023

Transcriptomics elucidates metabolic regulation and functional promoters in the basidiomycete red yeast Xanthophyllomyces dendrorhous CBS 6938

Transcriptomics is a powerful approach for functional genomics and systems biology, yet it can also be used for genetic part discovery. Genetic part discovery has never been more necessary, as advances in synthetic biology increase the number of tractable organisms that need tunable gene expression for genetic circuits and metabolic pathways. Therefore, approaches are needed to assess a tractable organism and obtain a convenient set of genetic parts to support future research. Here, we describe a genomic and transcriptomic approach to derive a modular integrative part library with constitutive and regulated promoters in the basidiomycete yeast Xanthophyllomyces dendrorhous CBS 6938. X. dendrorhous is currently the sole biotechnologically relevant organism in the Tremellomycete family - it produces large amounts of astaxanthin, especially under oxidative stress and exposure to light. Particularly for this yeast, there are not large libraries of parts from related organisms that could be transferred. They must be derived. To do this, a contiguous genome was first obtained through combined short read and long read sequencing. Then, differential gene expression (DGE) analysis using transcriptomics was performed, comparing oxidative stress and exposure to different wavelengths of light. This revealed a set of putative light-responsive regulators that mediate a complex survival response to ultraviolet (UV) where X. dendrorhous upregulates aromatic amino acid and tetraterpenoid biosynthesis and downregulates central carbon metabolism and respiration. The DGE data was then used to derive 26 constitutive and regulated gene expression elements from the genome. The gene expression elements were designed to be compatible with a new modular cloning system for X. dendrorhous which includes integration sites, terminators, selection markers, and reporters. Each element was characterized by luciferase assay of an integrated gene expression cassette. Notably, a novel promoter from a hypothetical gene that has 9-fold activation upon UV exposure was characterized. This study defines an advanced modular genetic part collection for engineering the basidiomycete X. dendrorhous CBS 6938 while simultaneously discovering potential targets for increasing tetraterpenoid biosynthesis. Further, it demonstrates that -omics-to-parts workflows can simultaneously provide useful genomic data and advance genetic tools for nonconventional microbes, particularly those without a related model organism. This approach will be broadly useful in current efforts to engineer diverse microbes. KEY POINTSO_LIOmics-to-parts can be applied to non-model organisms for rapid "onboarding". C_LIO_LI26 promoters native to X. dendrorhous were identified. C_LIO_LIOmics revealed unique photobiology in X. dendrorhous. C_LI

synthetic biology↗

bioRxiv2026

Boosted cell-free gene expression for robust signal readout from a single-copy DNA template in microdroplets

Cell-free gene expression in micro-compartments constitutes a chassis for biotechnology and synthetic biology. Protein synthesis from low concentrations of DNA, a single copy per compartment, is essential for in vitro evolution of biomolecules and synthetic cells. However, insufficient yield of protein synthesized from typically sub-picomolar DNA results in undetectable signals or inadequate activity of desired protein functions. Here we identify and largely mitigate yield-limiting bottlenecks of reconstituted in vitro transcription and translation (IVTT) at low DNA input. Systematic comparison of commercial reconstituted IVTT kits revealed that gene expression starts becoming limited by mRNA scarcity around 20-200 pM DNA input. We further uncovered that the standard ribosome concentration is excessive at low-DNA input and shortens the lifetime of translation. These findings led to a simple optimization recipe that combines supplementation with a highly active T7 RNA polymerase and a reduction in ribosome concentration, which synergistically amplified gene expression by [~]10-fold across diverse fluorescent proteins and enzymes. This low-DNA-optimized formulation in picoliter droplets achieved [~]94 nM protein expression from a single copy of DNA ([~]0.12 pM). The user-friendly boosted IVTT protocol paves the way for straightforward functional screening and in vitro reconstitution of cellular functions in DNA-scarce environments. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/707295v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@14fffaborg.highwire.dtl.DTLVardef@11a4bd1org.highwire.dtl.DTLVardef@1679d79org.highwire.dtl.DTLVardef@1937ff6_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2026

Firewalled synthetic commensal blocks horizontal gene transfer in the gut

Synthetic biology enables the rational reprogramming of microorganisms into living therapeutics and agents for bioremediation. However, such genetically modified organisms (GMOs) disseminate their synthetic genetic information into natural microbial communities through horizontal gene transfer (HGT), posing biosafety risks that limit clinical and environmental deployment. Reassigning sense codons to an alternative amino acid identity establishes a genetic firewall that simultaneously prevents incoming and outgoing gene flow, but reported implementations compromise fitness, precluding clinical and industrial use. Here, we overcome this limitation using genome design and laboratory evolution to create a high-fitness genetically firewalled Escherichia coli commensal. By directly altering the amino acid identity of TCA and TCG serine codons in the genetic code without an unassigned intermediate, we establish a robust genetic firewall that remains stable for thousands of generations. This firewalled commensal stably colonizes the mouse gastrointestinal tract for more than 100 days and blocks viral infections and HGT. As the long-term within-gut evolution of this firewalled organism identified adaptive mutations in genes responsible for carbon source utilization, we rationally redesigned the strain's genome to increase fitness. Together, this work establishes a genetically firewalled commensal for safer living therapeutics development and provides a strategy for designing high-fitness, virus- and gene-transfer-resistant organisms for clinical and environmental use.

synthetic biology↗

bioRxiv2016

Self-destructive altruism in a synthetic developmental program enables complex feedstock utilization

Stochastic differentiation and programmed cell death are common developmental processes in microbes, driving diverse altruistic behaviors that promote cooperation. Utilizing cell death in developmental programs requires control over the rate of differentiation to balance cell proliferation against the utility of sacrifice. However, the regulatory networks that control these behaviors are often complex and have yet to be successfully harnessed as biotechnology. Here, we engineered a synthetic developmental gene network that couples stochastic differentiation with programmed cell death to implement a two-member division of labor. Progenitor cellobiose consumer cells were engineered to grow on cellobiose and differentiate at a controlled rate into self-destructive altruists that release an otherwise sequestered cellulase enzyme payload through autolysis to form a developmental Escherichia coli consortium that utilizes cellulose for growth. We used an experimentally parameterized model of task switching, payload delivery and cellulose conversion to nutrients to set key parameters to achieve overall population growth supported by cellulase release, liberating 14-23% of the available carbon. An inevitable consequence of engineering altruistic developmental behaviors is the emergence of cheaters that undermine cooperation. We observed cheater phenotypes for consumers and altruists, identified mutational hotspots and constructed a predictive model of circuit longeivity based on mutation rate estimates for each mode of evolutionary escape. This work introduces the altruistic developmental program as a new tool for synthetic biology, demonstrates the utility of population dynamics models to engineer complex phenotypes and provides a testbed for probing the evolutionary biology of self-destructive altruism.

synthetic biology↗

bioRxiv2021

Spacer2PAM: A computational framework for identification of functional PAM sequences for endogenous CRISPR systems

RNA-guided nucleases from clustered regularly interspaced short palindromic repeats (CRISPR) systems expand opportunities for precise, targeted genome modification. Endogenous CRISPR systems in many bacteria and archaea are particularly attractive to circumvent expression, functionality, and unintended activity hurdles posed by heterologous CRISPR effectors. However, each CRISPR system recognizes a unique set of PAM sequences, which requires extensive screening of randomized DNA libraries. This challenge makes it difficult to develop endogenous CRISPR systems, especially in organisms that are slow-growing or have transformation idiosyncrasies. To address this limitation, we present Spacer2PAM, an easy-to-use, easy-to-interpret R package built to identify potential PAM sequences for any CRISPR system given its corresponding CRISPR array as input. Spacer2PAM can be used in "Quick" mode to generate a single PAM prediction that is likely to be functional or in "Comprehensive" mode to inform targeted, unpooled PAM libraries small enough to screen in difficult to transform organisms. We demonstrate Spacer2PAM by predicting PAM sequences for industrially relevant organisms and experimentally identifying seven PAM sequences that mediate interference from the Spacer2PAM-predicted PAM library for the type I-B CRISPR system from Clostridium autoethanogenum. We anticipate that Spacer2PAM will facilitate the use of endogenous CRISPR systems for industrial biotechnology and synthetic biology.

synthetic biology↗

bioRxiv2024

Silaffins-Driven Genetic Engineering of Diatom Cell Walls: Insight into Biosilica Morphology and Nanomaterial Design

Diatoms synthesize silica cell walls (frustules) with genetically encoded morphologies, ranging from nanopatterns to micropatterns, that far exceed current synthetic chemistry. Silaffins, a family of phosphoproteins undergoing complex post-translational modifications, have been isolated from frustules and shown to facilitate and regulate biosilica formation in vitro with long-chain polyamines. However, their particular role in frustule morphogenesis and functionality remains unclear. In this study, functions of two representative silaffins, TpSil1 and TpSil3, were investigated in the model organism Thalassiosira pseudonana using gene overexpression and CRISPR/Cas9-mediated knockout approaches. Due to high sequence homology, TpSil2 was concurrently disrupted in TpSil1 knockout strains, while the homozygous knockout of TpSil3 proved to be lethal. Quantitative morphological analysis revealed distinct yet complementary roles: TpSil3 governs both microscale overall size and mesoscale features, including macropore (fultoportula) density and mesopore (cribrum pore) pattern, whereas TpSil1/2 exclusively contribute to macropore morphogenesis and mesopore density. Overexpression of silaffins increased silica deposition, while knockouts exhibited reduced silicification but enhanced cell growth and photosynthetic efficiency. Furthermore, these genetic modifications significantly influenced the physicochemical and optical properties of bulk frustules, potentially enhancing the hemostatic, catalytic and photonic performances, thereby positioning them as versatile candidates for a wide range of biotechnological and industrial applications. Collectively, our findings elucidate the distinct roles of TpSil1/2 and TpSil3 in diatom physiology and frustule morphology, highlighting a promising pathway for engineering nanostructured silica materials with tailored properties through synthetic biology.

synthetic biology↗

bioRxiv2026

Certified Steady-State Parameter-Interval Design for Uncertain Biomolecular Models using a Global Shaving Contractor

The design of parameter intervals that provably enforce steady-state specifications in biomolecular circuits is challenging due to nonlinear reaction kinetics, parametric uncertainty, and the under-determined nature of steady-state constraints. Most validated approaches either rely on recursive subdivision (set inversion) or may stall due to dependency effects when applied directly in parameter space, limiting scalability in moderate to high dimensions. This paper introduces a global shaving contractor that contracts an initial parameter box by repeatedly applying certified interval-exclusion tests against a prescribed steady-state set. The proposed procedure returns a guaranteed outer enclosure of the feasible parameter set and provides finite-termination guarantees, along with worst-case bounds on the number of inclusion-function evaluations. Case studies spanning low-dimensional motifs and a sixteen-parameter integral-feedback model, including bistability specifications for a CRISPRi toggle switch, demonstrate substantial contraction of design domains without subdivision. The resulting certificates support uncertainty-aware circuit tuning, rigorous parameter screening, and robust design workflows in systems & synthetic biology and related nonlinear dynamical-system design problems.

synthetic biology↗

bioRxiv2026

ARCHIVE: Machine-Guided Design of an Efficient Open-Ended DNA Recording Device to Increase Resolution of Multiplexed Cell History Tracking

Engineering cell-based devices to record events into DNA has potential both as a non-ablative research tool and in the clinic for enacting gene-circuit-based logic of cell therapies conditional on cell history. Whether as a means of understanding interactions on the single-cell level, or reconstructing histories of cellular events, a cellular DNA recording device has widespread utility, with prime editing-based methods at the forefront of this endeavor - notably peCHYRON. Yet, the resolution of such open-ended recording tools are inherently constrained by edit insertion efficiency and cannot yet capture RNA-polymerase II-transcribed signals, which represent a large segment of functionally-defined endogenous gene-regulatory architectures. Here we present ARCHIVE (Amplified Recording of Cellular Histories into Information-dense Vectors of Events), capable of integrating RNA-encoded signals into a predefined genomic recording locus with high efficiency. By utilizing deep-learning assisted prediction of prime-editing efficiency as a surrogate fitness model for generative in silico pegRNA evolution, we developed a recording device with an order-of-magnitude improvement in temporal resolution (efficiency of iterative message integration steps) compared to the state of the art - a capability we establish here at the level of constitutive promoter tracking. We expect ARCHIVE to serve as a launching point for more advanced mammalian synthetic-biology recording devices for both functional genomics and therapeutics research.

synthetic biology↗

bioRxiv2019

A Modular Computational Framework for the Rational Design and Exploration of Synthetic Development

Synthetic development is a nascent field of research that uses the tools of synthetic biology to design genetic programs directing cellular patterning and morphogenesis in higher eukaryotic cells, such as mammalian cells. One specific example of such synthetic genetic programs was based on cell-cell contact-dependent signaling using synthetic Notch pathways, and was shown to drive formation of multilayered spheroids by modulating cell-cell adhesion via differential expression of cadherin-family proteins. The design method for these genetic programs relied on trial and error, which limited the number of possible circuits and parameter ranges that could be explored. Here we build a parametrized computational framework that, given a cellcell communication network driving changes in cell adhesion and initial conditions as inputs, predicts developmental trajectories. We first built a general computational framework where contact-dependent cell-cell signaling networks and changes in cell-cell adhesion could be designed in a modular fashion. We then use a set of available in vitro results (that we call the "training set" in analogy to similar pipelines in the machine learning field) to parametrize the computational model with values for adhesion and signaling. We then show that this parametrized model can qualitatively predict experimental results from a "testing set" of available in vitro data that varied the genetic network in terms of adhesion combinations, initial number of cells and even changes to the network architecture. Finally, this parametrized model is used to recommend novel network implementation for the formation of a 4-layered structure that has not been reported previously. The framework that we develop here could function as a testing ground to identify the reachable space of morphologies that can be obtained by controlling contact-dependent cell-cell communications and adhesion. Additionally, we discuss how the model could be expanded to include other forms of communication or effectors for the computational design of the next generation of synthetic developmental trajectories.

synthetic biology↗

bioRxiv2026

Engineering a PD-L1-sensing synthetic receptor for programmable macrophage-mediated phagocytosis

Macrophages are abundant immune cells within the tumor microenvironment with intrinsic phagocytic capabilities, yet their antitumor functions are frequently suppressed by inhibitory signals. Synthetic biology enables the rational design of ligand-responsive genetic circuits to reprogram immune cell behavior. Here, we report the engineering of a synthetic Notch-based receptor that detects PD-L1, an immune-checkpoint broadly expressed by cancer cells. Upon PD-L1 engagement, the circuit triggers programmable outputs, including expression of a fluorescent reporter or CV1-Fc, that locally blocks the CD47 "dont eat me" signal. We show that circuit activation scales with PD-L1 levels, partially attenuates PD-1/PD-L1 signaling, and that conditional CV1-Fc expression enhances engulfment of SKOV-3 ovarian cancer cells by THP-1-derived macrophages in vitro. Collectively, this work reframes PD-L1 from an end-point therapeutic target to a primary input signal for synthetic circuit activation and establishes a modular framework for engineering macrophage behaviour through spatially confined, ligand-responsive control. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/700810v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@1cbb391org.highwire.dtl.DTLVardef@7a0900org.highwire.dtl.DTLVardef@1e4f6d6org.highwire.dtl.DTLVardef@109838d_HPS_FORMAT_FIGEXP M_FIG Graphical abstract. A novel -PDL1 SNIPR receptor to program macrophage outputs. PD-L1 expressed on cancer cells is detected by -PD-L1 SNIPR-engineered macrophages, triggering release of the GAL4-VP64 transcription factor and activation of a programmable actuator. Circuit activation leads to customized outputs, including biosensing and enhanced macrophage phagocytosis via CD47 blockade, as well as immunomodulatory effects through interference with the PD-1/PD-L1 checkpoint axis. This sensor-actuator framework enables spatially confined and ligand-dependent reprogramming of macrophage function. C_FIG

synthetic biology↗

bioRxiv2024

Fundamental trade-offs in the robustness of biological systems with feedback regulation

Natural biological systems use a complex network of feedback regulation to effectively respond to their changing environment. Even though in engineered systems we understand how accurate feedback can be depending on the electronic or mechanical parts that it is implemented with, we largely lack a similar theoretical framework to study biological feedback. Specifically, it is not fully understood or quantified how accurate or robust the implementation of biological feedback actually is. In this paper, we study the sensitivity of biological feedback to variations in biochemical parameters using five example circuits: positive autoregulation, negative autoregulation, double-positive feedback, positive-negative feedback and double-negative feedback (the toggle switch). We find that of these examples of biological feedback are subjected to fundamental trade-offs, and we propose multi-objective optimisation as a framework to study them. The impact of this work is to improve robust circuit design for synthetic biology and to improve our understanding of systems biology.

synthetic biology↗

bioRxiv2024

Impact of exogenous aminoacyl-tRNA synthetase and tRNA on temperature sensitivity in Escherichia coli: towards a genetic code-expanded biological logic gate

Genetic code expansion (GCE) is a powerful strategy that expands the genetic code of an organism for incorporating non-canonical amino acids (ncAAs) into proteins using engineered tRNAs and aminoacyl-tRNA synthetases (aaRSs). While GCE has opened up new possibilities for synthetic biology, little is known about the potential side effects of exogenous aaRS/tRNA pairs. In this study, we investigated the impact of exogenous aaRS and amber suppressor tRNA on gene expression in Escherichia coli. We discovered that in DH10{beta} {Delta}cyaA, transformed with the F1RP/F2P two-hybrid system, high consumption rate of cellular ATP by exogenous aaRS/tRNA at elevated temperatures induces temperature sensitivity in the expression of genes regulated by the catabolite activator protein. We harnessed this temperature sensitivity to create a novel biological AND gate in E. coli, responsive to both p-benzoylphenylalanine (BzF) and low temperature, using a BzF-dependent variant of E. coli chorismate mutase and split subunits of Bordetella pertussis adenylate cyclase. Our study provides new insights into the unexpected effects of exogenous aaRS/tRNA pairs and offers a new approach for constructing a biological logic gate.

synthetic biology↗

bioRxiv2014

Cooperative riboregulation in living cells through allosteric programming of toehold activation

Living cells rely on small non-coding RNAs (sRNAs) to regulate gene expression at the post-transcriptional level. Contrary to most protein-based activators of transcription, all known riboregulators do not exploit cooperative binding mechanisms to activate gene expression. We conceived a general strategy to design cooperative riboregulation by programming a hierarchical toehold activation cascade, which we implemented into a de novo sequence design algorithm. We engineered different riboregulatory systems relying on the conditional formation of a heterotrimeric species. We characterized the specificity of each RNA-RNA interaction in vitro and the cooperative activation of gene expression in Escherichia coli. As we only rely on a biochemical model to compute allosteric regulation, our strategy could be applied to reach more complex RNA-based nanostructures regulating gene expression for synthetic biology applications.

Synthetic Biology↗

bioRxiv2022

Building molecular band-pass filters via molecular sequestration

Engineered genetic circuits with tailored functions that mimic how cells process information in changing environments (e.g. cell fate decision, chemotaxis, immune response) have great applications in biomedicine and synthetic biology. Although there is a lot of progress toward the design of gene circuits yielding desired steady states (e.g. logic-based networks), building synthetic circuits for dynamic signal processing (e.g. filters, frequency modulation, and controllers) is still challenging. Here, we provide a model-based approach to build gene networks that can operate as band-pass filters by taking advantage of molecular sequestration. By suitably approximating the dynamics of molecular sequestration, we analyze an Incoherent Feed-Forward Loop (IFFL) and a Negative Feedback (NF) circuit and illustrate how they can achieve band-pass filter behavior. Computational analysis shows that a circuit that incorporates both IFFL and NF motifs improves the filter performance. Our approach facilitates the design of sequestration-based filters, and may support the synthesis of molecular controllers with desired specifications.

synthetic biology↗

bioRxiv2024

Design of Parameter Intervals to Meet Steady-State Specifications in Biomolecular Circuits using Interval Analysis

It is often desired, in the analysis or the design of biomolecular circuits, to search for parameters that satisfy certain specifications, such as on the number of the steady states or on their magnitudes. These problems are challenging because of the presence of multiple parameters, the nonlinear mapping between the parameters and the steady states, as well as the specifications themselves, such as when multiple steady states are desired. Typically, exact analytical solutions are limited and numerical approaches, if they converge, may not capture all solutions. We used Interval Analysis versions of Bisection and Constraint Propagation to obtain rigorous and guaranteed estimates of circuit parameters for the design problem. We established criteria that rule out the existence of design solutions in a given parameter space. We presented algorithms to rigorously bound all solutions and developed variants that enclosed the solutions as accurately as required. These theoretical results were illustrated on benchmark feedback and feedforward circuits. These results should aid in the analysis and design of biomolecular circuits as well as in other contexts with similar modelling frameworks. The rigorous nature of the results may be particularly useful for resource optimization and safety criticality in synthetic biology applications, such as in therapeutic applications and drug delivery.

synthetic biology↗

bioRxiv2017

Tn-Core: context-specific reconstruction of core metabolic models using Tn-seq data

MotivationTn-seq (transposon mutagenesis and sequencing) and constraint-based metabolic modelling represent highly complementary approaches. They can be used to probe the core genetic and metabolic networks underlying a biological process, revealing invaluable information for synthetic biology engineering of microbial cell factories. However, while algorithms exist for integration of -omics data sets with metabolic models, no method has been explicitly developed for integration of Tn-seq data with metabolic reconstructions.\n\nResultsWe report the development of Tn-Core, a Matlab toolbox designed to generate gene-centric, context-specific core reconstructions consistent with experimental Tn-seq data. Extensions of this algorithm allow: i) the generation of context-specific functional models through integration of both Tn-seq and RNA-seq data; ii) to visualize redundancy in core metabolic processes; and iii) to assist in curation of de novo draft metabolic models. The utility of Tn-Core is demonstrated primarily using a Sinorhizobium meliloti model as a case study.\n\nAvailability and implementationThe software can be downloaded from https://github.com/diCenzo-GC/Tn-Core. All results presented in this work have been obtained with Tn-Core v. 1.0.\n\nContactgeorgecolin.dicenzo@unifi.it, marco.fondi@unifi.it\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

systems biology↗

bioRxiv2018

Intrinsic limitations in mainstream methods of identifying network motifs in biology

Network motifs are connectivity structures that occur with significantly higher frequency than chance, and are thought to play important roles in complex biological networks, for example in gene regulation, interactomes, and metabolomes. Network motifs may also become pivotal in the rational design and engineering of complex biological systems underpinning the field of synthetic biology. Distinguishing true motifs from arbitrary substructures, however, remains a challenge. Here we demonstrate both theoretically and empirically that implicit assumptions present in mainstream methods for motif identification do not necessarily hold, with the ramification that motif studies using these mainstream methods are less able to effectively differentiate between spurious results and events of true statistical significance than is often presented. We show that these difficulties cannot be overcome without revising the methods of statistical analysis used to identify motifs. The implications of these findings are therefore far-reaching across diverse areas of biology.

systems biology↗