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Results for “synthetic biology”

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bioRxiv2023

De novo design of modular protein hydrogels with programmable intra- and extracellular viscoelasticity

Relating the macroscopic properties of protein-based materials to their underlying component microstructure is an outstanding challenge. Here, we exploit computational design to specify the size, flexibility, and valency of de novo protein building blocks, as well as the interaction dynamics between them, to investigate how molecular parameters govern the macroscopic viscoelasticity of the resultant protein hydrogels. We construct gel systems from pairs of symmetric protein homo-oligomers, each comprising 2, 5, 24, or 120 individual protein components, that are crosslinked either physically or covalently into idealized step-growth biopolymer networks. Through rheological assessment and molecular dynamics (MD) simulation, we find that the covalent linkage of multifunctional precursors yields hydrogels whose viscoelasticity depends on the crosslink length between the constituent building blocks. In contrast, reversibly crosslinking the homo-oligomeric components with a computationally designed heterodimer results in non-Newtonian biomaterials exhibiting fluid-like properties under rest and low shear, but shear-stiffening solid-like behavior at higher frequencies. Exploiting the unique genetic encodability of these materials, we demonstrate the assembly of protein networks within living mammalian cells and show via fluorescence recovery after photobleaching (FRAP) that mechanical properties can be tuned intracellularly, in correlation with matching formulations formed extracellularly. We anticipate that the ability to modularly construct and systematically program the viscoelastic properties of designer protein-based materials could have broad utility in biomedicine, with applications in tissue engineering, therapeutic delivery, and synthetic biology. SignificanceProtein-based hydrogels have many applications in cellular engineering and medicine. Most genetically encodable protein hydrogels are made from naturally harvested proteins or protein-polymer hybrid constructs. Here we describe de novo protein hydrogels and systematically investigate the impact of microscopic properties of the building blocks (e.g., supramolecular interaction, valencies, geometries, flexibility) on the resultant macroscopic gel mechanics, both intra-and extracellularly. These de novo supramolecular protein assemblies, whose properties can be tuned from solid gels to non-Newtonian fluids, provide expanded opportunities for applications in synthetic biology and medicine.

bioengineering↗

bioRxiv2017

dRNA-seq implicates sulfide as master regulator of S(0) metabolism in Chlorobaculum tepidum and other green sulfur bacteria

The green sulfur bacteria (Chlorobiaceae) are anaerobes that use electrons from reduced sulfur compounds (sulfide, S(0), and thiosulfate) as electron donors for photoautotrophic growth. Chlorobaculum tepidum, the model system for the Chlorobiaceae, both produces and consumes extracellular S(0) globules depending on the availability of sulfide in the environment. These physiological changes imply significant changes in gene regulation, which has been observed when sulfide is added to Cba. tepidum growing on thiosulfate. However, the underlying mechanisms driving these gene expression changes, i.e. specific regulators and promoter elements involved, have not yet been defined. Here, differential RNA-seq (dRNA-seq) was used to globally identify transcript start sites (TSS) that were present during growth on sulfide, biogenic S(0), and thiosulfate as sole electron donors. TSS positions were used in combination with RNA-seq data from cultures growing on these same electron donors to identify both basal promoter elements and motifs associated with electron donor dependent transcriptional regulation. These motifs were conserved across homologous Chlorobiaceae promoters. Two lines of evidence suggest that sulfide mediated repression is the dominant regulatory mode in Cba. tepidum. First, motifs associated with genes regulated by sulfide overlap key basal promoter elements. Second, deletion of the gene CT1277, encoding a putative regulatory protein, leads to constitutive over-expression of the sulfide:quinone oxidoreductase CT1087 in the absence of sulfide. The results suggest that sulfide is the master regulator of sulfur metabolism in Cba. tepidum and the Chlorobiaceae. Finally, the identification of basal promoter elements with differing strengths will further the development of synthetic biology in Cba. tepidum and perhaps other Chlorobiaceae.\n\nImportanceElemental sulfur is a key intermediate in biogeochemical sulfur cycling. The photoautotrophic green sulfur bacterium Chlorobaculum tepidum both produces and consumes elemental sulfur depending on the availability of sulfide in the environment. Our results reveal transcriptional dynamics of Chlorobaculum tepidum on elemental sulfur, and increase our understanding of the mechanisms of transcriptional regulation governing growth on different reduced sulfur compounds. This study identifies new genes and sequence motifs that likely play significant roles in the production and consumption of elemental sulfur. Beyond this focused impact, this study paves the way for the development of synthetic biology in Chlorobaculum tepidum and other Chlorobiaceae by providing a comprehensive identification of promoter elements to control gene expression, a key element of strain engineering.

microbiology↗

bioRxiv2024

Temporal loss of genome-wide and immunogenetic diversity in a near-extinct parrot

Loss of genetic diversity threatens a species adaptive potential and long-term resilience. Predicted to be extinct by 2038, the orange-bellied parrot (Neophema chrysogaster) is a Critically Endangered migratory bird threatened by numerous viral, bacterial and fungal diseases. The species has undergone multiple population crashes, reaching a low of three wild-born females and 13 males in 2016 and is now represented by only a single wild population and individuals in the captive breeding program. Here we used our high-quality long-read reference genome, and contemporary and historical resequenced genomes from as early as 1829, to track the long-term genomic erosion and immunogenetic diversity decline in this species. 62% of genomic diversity was lost between historical (mean autosomal heterozygosity = 0.00149 {+/-} 0.000699 SD) and contemporary (0.00057 {+/-} 0.000026) parrots. A greater number and length of runs of homozygosity in contemporary samples was also observed. A temporal reduction of the number of alleles at Toll-like receptor genes was found (historical average alleles = 5.78 {+/-} 2.73; contemporary = 3.89 {+/-} 2.10), potentially exacerbating disease susceptibility in the contemporary population. Of particular concern is the new threat of avian influenza strain (HPAI) to Australia. We discuss the conservation implications of our findings and propose that hybridization and synthetic biology may be required to address the catastrophic loss of genetic diversity that has occurred this species in order to prevent extinction. Significance statementOrange-bellied parrots (Neophema chrysogaster) face a dire future, with extinction predicted by 2038 due to severe genetic diversity loss. This Critically Endangered species, now reduced to a single wild population and a captive breeding program, has lost 62% of its genomic diversity since 1829. Contemporary samples show a decline in immunogenetic diversity and signs of very recent inbreeding. Meaning birds today are more susceptible to disease events than birds a hundred years ago. Conservation efforts must consider hybridization and synthetic biology to counteract the catastrophic loss of genetic diversity to ensure the species survival. Our study underscores the urgent need for innovative strategies to preserve the adaptive potential and resilience of the orange-bellied parrot and other species in similar situations.

genomics↗

bioRxiv2018

High throughput gene expression profiling of yeast colonies with microgel-culture Drop-seq

Yeasts can be engineered into \"living foundries\" for non-natural chemical production by reprogramming their genome using a synthetic biology \"design-build-test\" cycle. While methods for \"design\" and \"build\" are scalable and efficient, \"test\" remains a labor-intensive bottleneck, limiting the effectiveness of the genetic reprogramming results. Here we describe Isogenic Colony Sequencing (ICO-seq), a massively-parallel strategy to assess the gene expression, and thus engineered pathway efficacy, of large numbers of genetically distinct yeast colonies. We use the approach to characterize opaque-white switching in 658 C. albicans colonies. By profiling transcriptomes of 1642 engineered S. cerevisiae strains, we use it to assess gene expression heterogeneity in a protein mutagenesis library. Our approach will accelerate synthetic biology by allowing facile and cost-effective transcriptional profiling of large numbers of genetically distinct yeast strains.

bioengineering↗

bioRxiv2024

Leaky ribosomal scanning enables tunable translation of bicistronic ORFs in green algae.

Advances in sequencing technology have unveiled examples of nucleus-encoded polycistronic genes, once considered rare. Exclusively polycistronic transcripts are prevalent in green algae, although the mechanism by which multiple polypeptides are translated from a single transcript is unknown. Here, we used bioinformatic and in vivo mutational analyses to evaluate competing mechanistic models for polycistronic expression in green algae. High-confidence manually curated datasets of bicistronic loci from two divergent green algae, Chlamydomonas reinhardtii and Auxenochlorella protothecoides, revealed 1) a preference for weak Kozak-like sequences for ORF 1 and 2) an underrepresentation of potential initiation codons before ORF 2, which are suitable conditions for leaky scanning to allow ORF 2 translation. We used mutational analysis in Auxenochlorella protothecoides to test the mechanism. In vivo manipulation of the ORF 1 Kozak-like sequence and start codon altered reporter expression at ORF 2, with a weaker Kozak-like sequence enhancing expression and a stronger one diminishing it. A synthetic bicistronic dual reporter demonstrated inversely adjustable activity of green fluorescent protein expressed from ORF 1 and luciferase from ORF 2, depending on the strength of the ORF 1 Kozak-like sequence. Our findings demonstrate that translation of multiple ORFs in green algal bicistronic transcripts is consistent with episodic leaky ribosome scanning of ORF 1 to allow translation at ORF 2. This work has implications for the potential functionality of upstream open reading frames found across eukaryotic genomes and for transgene expression in synthetic biology applications. Significance StatementTextbook dogma states that nucleus-encoded genes are monocistronic, producing transcripts with a single translated open reading frame. However, highly conserved bicistronic loci are pervasive in green algae that are separated by several hundred million years of evolution, speaking to their ancestral origins and functions within the Chlorophyte lineage. A combination of bioinformatic analysis and in vivo gene manipulation supports leaky ribosomal scanning as the primary mechanism for translation of multiple ORFs from bicistronic transcripts. We have successfully tuned synthesis levels of two proteins encoded on one mRNA by modifying the ORF 1 Kozak-like sequence. These findings may have broad applications in synthetic biology.

plant biology↗

bioRxiv2023

The "Duckweed Dip": Aquatic Spirodela polyrhiza Plants Can Efficiently Uptake Dissolved, DNA-Wrapped Carbon Nanotubes from Their Environment for Transient Gene Expression

Duckweeds (Lemnaceae) are aquatic non-grass monocots that are the smallest and fastest-growing flowering plants in the world. While having simplified morphologies, relatively small genomes, and many other ideal traits for emerging applications in plant biotechnology, duckweeds have been largely overlooked in this era of synthetic biology. Here, we report that Greater Duckweed (Spirodela polyrhiza), when simply incubated in a solution containing plasmid-wrapped carbon nanotubes (DNA-CNTs), can directly up-take the DNA-CNTs from their growth media with high efficiency and that transgenes encoded within the plasmids are expressed by the plants--without the usual need for large doses of nanomaterials or agrobacterium to be directly infiltrated into plant tissue. This process, called the "duckweed dip", represents a streamlined, hands-off tool for transgene delivery to a higher plant that we expect will enhance the throughput of duckweed engineering and help to realize duckweeds potential as a powerhouse for plant synthetic biology. (148 words)

bioengineering↗

bioRxiv2021

In-depth computational analysis of natural and artificial carbon fixation pathways

In the recent years, engineering new-to-nature CO2 and C1 fixing metabolic pathways made a leap forward. These new, artificial pathways promise higher yields and activity than natural ones like the Calvin-Benson-Bassham cycle. The question remains how to best predict their in vivo performance and what actually makes one pathway "better" than another. In this context, we explore aerobic carbon fixation pathways by a computational approach and compare them based on their ATP-efficiency and specific activity considering the kinetics and thermodynamics of the reactions. Beside natural pathways, this included the artificial Reductive Glycine Pathway, the CETCH cycle and two completely new cycles with superior stoichiometry: The Reductive Citramalyl-CoA cycle and the 2-Hydroxyglutarate-Reverse Tricarboxylic Acid cycle. A comprehensive kinetic data set was collected for all enzymes of all pathways and missing kinetic data was sampled with the Parameter Balancing algorithm. Kinetic and thermodynamic data were fed to the Enzyme Cost Minimization algorithm to check for respective inconsistencies and calculate pathway specific activities. We found that the Reductive Glycine Pathway, the CETCH cycle and the new Reductive Citramalyl-CoA cycle were predicted to have higher ATP-efficiencies and specific activities than the natural cycles. The Calvin Cycle performed better than previously thought, however. It can be concluded that the weaker overall characteristics in the design of the Calvin Cycle might be compensated by other benefits like robustness, low nutrient demand and a good compatibility with the hosts physiological requirements. Nevertheless, the artificial carbon fixation cycles hold great potential for future applications in Industrial Biotechnology and Synthetic Biology.

synthetic biology↗

bioRxiv2023

Accelerated evolution using the phage T7 and its application to evolve riboswitches

Leveraging riboswitches, non-coding mRNA fragments pivotal to gene regulation, poses a challenge in effectively selecting and enriching these functional genetic sensors, which can toggle between ON and OFF states in response to their cognate inducers. Here, we show our engineered phage T7, enabling the evolution of a theophylline riboswitch. We have replaced T7s DNA polymerase with a transcription factor controlled by a theophylline riboswitch and have created two types of host environments to propagate the engineered phage. Both types host an error-prone T7 DNA polymerase regulated by a T7 promoter along with another critical gene - either cmk or pifA, depending on the host type. The cmk gene is necessary for T7 replication and is used in the first host type for selection in the riboswitchs ON state. Conversely, the second host type incorporates the pifA gene, leading to abortive T7 infections and used for selection in the riboswitchs OFF state. This dual-selection system, termed T7AE, was then applied to a library of 65,536 engineered T7 phages, each carrying randomized riboswitch variants. Through successive passage in both host types with and without theophylline, we observed an enrichment of phages encoding functional riboswitches that conferred a fitness advantage to the phage in both hosts. The T7AE technique thereby opens new pathways for the evolution and advancement of gene switches, including non-coding RNA-based switches, setting the stage for significant strides in synthetic biology.

synthetic biology↗

bioRxiv2025

Carbon metabolism shapes FtsZ levels and cell division in a cyanobacterium

Cyanobacteria, as photoautotrophs, play key ecological roles and are widely used in synthetic biology research. While metabolism profoundly influences cellular processes like cell division, the regulatory mechanisms linking these pathways remain poorly understood in cyanobacteria. Here, we engineered the model cyanobacterium Anabaena sp. PCC 7120 by introducing an extra carboxylation module into the TCA pathway, perturbing this central metabolic pathway. This modification alters the division protein FtsZ levels, impairing cell division under varying light conditions. We found that 2-oxoglutarate, which is known as a metabolic signal, regulates ftsZ expression via the transcription factor NtcA. Furthermore, metabolic status modulates cell division in an NtcA-dependent manner, revealing a direct integration of metabolic control and cell division. Our findings uncover a coordination mechanism between metabolism and cell division in cyanobacteria, providing mechanistic insights for synthetic biology engineering and the understanding of metabolic regulation.

microbiology↗

bioRxiv2025

Evolutionary chemical learning in dimerization networks

We present a novel framework for chemical learning based on Com- petitive Dimerization Networks (CDNs)-- systems in which multiple molecular species, e.g. proteins or DNA/RNA oligomers, reversibly bind to form dimers. We show that these networks can be trained in vitro through directed evolution, enabling the implementation of complex learning tasks such as multiclass classification without digital hardware or explicit parameter tuning. Each molecular species functions analogously to a neuron, with binding affinities acting as tunable synaptic weights. A training protocol involving mutation, selection, and amplification of DNA-based components allows CDNs to robustly discriminate among noisy input patterns. The resulting classifiers exhibit strong output contrast and high mutual information between input and output, especially when guided by a contrastenhancing loss function. Comparative analysis with in silico gradient descent training reveals closely correlated performance. These results establish CDNs as a promising platform for analog physical computation, bridging synthetic biology and machine learning, and advancing the development of adaptive, energy-efficient molecular computing systems. Significance StatementThis study introduces a new paradigm for learning based on chemical reaction networks rather than digital circuits. Using Competitive Dimerization Networks (CDNs)--biomolecular systems in which species reversibly bind to form dimers--complex classification tasks are learned through in vitro directed evolution. This approach eliminates the need for digital hardware or gradient-based optimization, relying instead on intrinsic molecular dynamics for computation. The resulting chemical classifiers achieve high fidelity and robustness to noise, with performance comparable to that of gradient descent training. These findings establish CDNs as a scalable, energy-efficient platform for molecular computing, suggesting broad potential applications in diagnostics, biosensing, synthetic biology, and nanotechnology, where programmable, adaptive chemical systems could serve as alternatives to conventional electronic processors.

bioengineering↗

bioRxiv2023

Noise properties of adaptation-conferring biochemical control modules

A key goal of synthetic biology is to establish functional biochemical modules with network-independent properties. Antithetic integral feedback (AIF) is a recently developed control module in which two control species perfectly annihilate each others biological activity. The AIF module confers robust perfect adaptation to the steady-state average level of a controlled intracellular component when subjected to sustained perturbations. Recent work has suggested that such robustness comes at the unavoidable price of increased stochastic fluctuations around average levels. We present theoretical results that support and quantify this trade-off for the commonly analyzed AIF variant in the idealized limit with perfect annihilation. However, we also show that this trade-off is a singular limit of the control module: Even minute deviations from perfect adaptation allow systems to achieve effective noise suppression as long as cells can pay the corresponding energetic cost. We further show that a variant of the AIF control module can achieve significant noise suppression even in the idealized limit with perfect adaptation. This atypical configuration may thus be preferable in synthetic biology applications.

biophysics↗

bioRxiv2025

Integrative Transcriptomic and Network Analysis Reveals Small Open Reading Frames as Regulators of DNA Methylation-Linked Pathogenicity and Adaptability in Leptospira interrogans

Small open reading frames (sORFs) are increasingly recognized as crucial regulators in bacterial gene expression, yet their biological roles remain largely unexplored in pathogenic species. Here, we investigated the genome-wide regulatory landscape of sORFs in Leptospira interrogans serovar Manilae strain UP-MMC-NIID-LP using RNA-seq-based transcriptomic profiling integrated with weighted gene co-expression network analysis (WGCNA) following targeted disruption of lomA, a gene mediating 4-methylcytosine (4mC) DNA modification. Loss of 4mC was associated with broad transcriptional dysregulation and phenotypic impairments, including reduced motility, adhesion, and virulence. Analysis of 363 predicted sORFs identified 39 with significant differential expression (FDR < 0.05, |log2FC| [≥] 1) across wild-type, mutant, and complemented strains. Gene co-expression networks constructed using WGCNA and interrogated with Cytoscape tools (MCODE, CytoHubba, ClueGO) revealed ten differentially expressed sORFs (FDR-adjusted p < 0.05); eight upregulated and two downregulated, across the three pairwise comparisons of wild-type, mutant, and complemented strains. These sORFs were enriched in pathways related to flagellar assembly, DNA recombination, and transcriptional regulation, which are core processes supporting genome stability and adaptive stress responses. Several previously uncharacterized sORFs occupied hub-like positions within co-expression modules, highlighting their integrative roles in metabolic and regulatory networks. To our knowledge, this represents the first genome-wide integration of methylation-driven sORF regulation in Leptospira, revealing small proteins as central mediators that link epigenetic control with bacterial pathogenicity and adaptability. These findings provide a foundation for future antimicrobial and synthetic biology strategies targeting sORF-mediated regulation. ImportanceSmall open reading frames (sORFs) are emerging as important regulators of bacterial gene expression, yet their roles in pathogenic species remain largely unexplored. This study provides the first genome-wide framework linking methylation-driven sORF regulation to virulence and adaptive processes in Leptospira interrogans. We identify previously uncharacterized sORFs occupying central positions in regulatory networks, connecting epigenetic control to motility, adhesion, and stress adaptation. Understanding these mechanisms in a neglected tropical disease pathogen has implications for improving public health and informs future antimicrobial and synthetic biology strategies.

bioinformatics↗

bioRxiv2024

ON-OFF nanopores for optical control of transmembrane ionic communication

[Abstract]Nanoscale photoswitchable proteins could facilitate precise spatiotemporal control of transmembrane communication and support studies in synthetic biology, neuroscience, and bioelectronics. Through covalent modification of the -hemolysin protein pore with arylazopyrazole photoswitches, we have produced "photopores" that transition between iontronic resistor and diode modes in response to irradiation at orthogonal wavelengths. In the diode mode, a low-leak OFF-state nanopore exhibits a reversible increase in unitary conductance of more than 20-fold upon irradiation at 365 nm. A rectification ratio of >5 was achieved with photopores in the diode state by either direct or alternating voltage input. Unlike conventional electronic phototransistors with intensity-dependent photoelectric responses, the photopores regulated current output solely based on the wavelength(s) of monochromatic or dual-wavelength irradiation. Dual-wavelength irradiation at various relative intensities allowed graded adjustment of photopore conductance. By using these properties, photonic signals were converted into ionic signals, highlighting the potential applications of photopores as components of smart devices in synthetic biology.

biophysics↗

bioRxiv2026

AI-enabled rhodopsin design for blue-light enhanced bacterial growth

We developed an AI-guided design pipeline that generated and validated non-natural microbial rhodopsins with spectral properties not yet known in nature. The pipeline comprised a three-stage in silico design, a genetic algorithm (GA) for sequence generation, a stacked LASSO and XGBoost machine-learning (ML) regressor for spectral prediction and fitness ranking, and a Markov-based sequence plausibility filter to enforce proton pumping like characteristics. Four candidate rhodopsins (APR1, APR2, APR6, and APR7) targeting blue light absorption were designed and AlphaFold3 structural modelling predicted retinal binding pocket architecture consistent with outward proton-pumping function. Experimental characterisation confirmed that all four variants absorbed light at [~]410 nm and significantly promoted the growth of Cupriavidus necator under blue light illumination. This study demonstrates that AI-enabled design can engineer proteins with no natural precedent, generating light-harvesting rhodopsins with novel spectral properties while preserving biological function, marking a significant advance in programmable synthetic biology.

Synthetic Biology↗

bioRxiv2022

Precision engineering of biological function with large-scale measurements and machine learning

As synthetic biology expands and accelerates into real-world applications, methods for quantitatively and precisely engineering biological function become increasingly relevant. This is particularly true for applications that require programmed sensing to dynamically regulate gene expression in response to stimuli. However, few methods have been described that can engineer biological sensing with any level of quantitative precision. Here, we present two complementary methods for precision engineering of genetic sensors: in silico selection and machine-learning-enabled forward engineering. Both methods use a large-scale genotype-phenotype dataset to identify DNA sequences that encode sensors with quantitatively specified dose response. First, we show that in silico selection can be used to engineer sensors with a wide range of dose-response curves. To demonstrate in silico selection for precise, multi-objective engineering, we simultaneously tune a genetic sensors sensitivity (EC50) and saturating output to meet quantitative specifications. In addition, we engineer sensors with inverted dose-response and specified EC50. Second, we demonstrate a machine-learning-enabled approach to predictively engineer genetic sensors with mutation combinations that are not present in the large-scale dataset. We show that the interpretable machine learning results can be combined with a biophysical model to engineer sensors with improved inverted dose-response curves.

synthetic biology↗

bioRxiv2026

High-efficiency, site-specific integration of kilobase-scale DNA into plant genomic safe harbors via PrimeStack editors

Precise, site-specific integration of large DNA sequences into plant genomes is a cornerstone of crop biotechnology and synthetic biology, yet remains constrained by random insertion, inefficient homologous recombination, and gene targeting. Here, we present PrimeStack, a DSB-independent platform that integrates prime editing with the unidirectional large serine integrase Bxb1, leveraging evolved variants for enhanced activity, to achieve the programmable insertion of multigene, multikilobase cargos at predefined genomic safe harbors in rice. Optimized prime editors first install attP landing sites with high fidelity and heritability followed by Bxb1-mediated recombination that generates irreversible integration of genetic information. PrimeStack achieves integration frequencies of approximately 43-46% (as detected by junction-specific PCR in rice calli), with phenotypic neutrality in regenerated plants, comparing favorably with bidirectional Cre-lox systems. We validate its utility by achieving targeted insertion of a carotenoid cassette at an experimentally confirmed genomic safe harbor. PrimeStack delivers a modular, site-specific gene-stacking platform that enables predictable, multigene trait pyramiding and pathway construction at genomic safe harbors, thereby accelerating the development of improved and resilient crop varieties, as well as scalable plant-based biomanufacturing and a powerful chassis for synthetic biology. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/718181v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@59c915org.highwire.dtl.DTLVardef@a0ba4corg.highwire.dtl.DTLVardef@26f8d4org.highwire.dtl.DTLVardef@9a3efe_HPS_FORMAT_FIGEXP M_FIG C_FIG

plant biology↗

bioRxiv2023

Emergent digital bio-computation through spatial diffusion and engineered bacteria

Building computationally capable biological systems has long been an aim of synthetic biology. The potential utility of biocomputing devices ranges from biosafety and environmental applications to diagnosis and personalised medicine. Here we present work for the design of bacterial computers which use spatial patterning to process information. Our computers are composed of bacterial colonies which, inspired by patterning in embryo development, receive information in the form of diffusible morphogen-like signals. A computation is encoded by the physical locations of the input sources of morphogen and the output receiver colonies. We demonstrate, mathematically and with engineered Escherichia coli, the simple digital logic capability of single bacterial colonies and show how additional colonies are required to build complex functions. Inspired by electronic design automation, an algorithm for designing optimal spatial circuits computing two-level digital functions is presented. This enhances the capability of our system to complex digital functions without increasing the biological complexity. We extend our experimental system to incorporate biosensing colonies as morphogen sources, demonstrating how a diagnostic device might be constructed. Our approach will open up new ways to perform biological computation, with applications in bioengineering, biomaterials and biosensing. Ultimately, these computational bacterial communities will help us explore information processing in natural biological systems.

synthetic biology↗

bioRxiv2021

Golden Gate Assembly of Aerobic and Anaerobic Microbial Bioreporters

Microbial bioreporters provide direct insight into cellular processes by producing a quantifiable signal dictated by reporter gene expression. The core of a bioreporter is a genetic circuit in which a reporter gene (or operon) is fused to promoter and regulatory sequences that govern its expression. In this study, we develop a system for constructing novel Escherichia coli bioreporters based on Golden Gate assembly, a synthetic biology approach for the rapid and seamless fusion of DNA fragments. Gene circuits are generated by fusing promoter and reporter sequences encoding yellow fluorescent protein, mCherry, bacterial luciferase, and an anaerobically active flavin-based fluorescent protein. We address a barrier to the implementation of Golden Gate assembly by designing a series of compatible destination vectors that can accommodate the assemblies. We validate the approach by measuring the activity of constitutive bioreporters and mercury and arsenic biosensors in quantitative exposure assays. We also demonstrate anaerobic quantification of mercury and arsenic in biosensors that produce flavin-based fluorescent protein, highlighting the expanding range of redox conditions that can be examined by microbial bioreporters. IMPORTANCEMicrobial bioreporters are versatile genetic tools with wide-ranging applications, particularly in the field of environmental toxicology. For example, biosensors that produce a signal output in the presence of a specific analyte offer less costly alternatives to analytical methods for the detection of environmental toxins such as mercury and arsenic. Biosensors of specific toxins can also be used to test hypotheses regarding mechanisms of uptake, toxicity, and biotransformation. In this study, we develop an assembly platform that uses a synthetic biology technique to streamline construction of novel Escherichia coli bioreporters that produce fluorescent or luminescent signals. We validate the approach by synthesizing and testing an array of bioreporters, including arsenic and mercury biosensors, that produce signal outputs in environments ranging from aerobic to highly reduced anaerobic growth conditions.

molecular biology↗