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Cells interact with their environment, communicate among themselves, track time and make decisions through functions controlled by natural regulatory genetic circuits consisting of interacting biological components. Synthetic programmable circuits used in therapeutics and other applications can be automatically designed by computer-aided tools. The Cello software designs the DNA sequences for programmable circuits based on a high-level software description and a library of characterized DNA parts representing Boolean logic gates. This process allows for design specification reuse, modular DNA part library curation and formalized circuit transformations based on experimental data. This protocol describes Cello 2.0, a freely available cross-platform software written in Java. Cello 2.0 enables flexible descriptions of the logic gates' structure and their mathematical models representing dynamic behavior, new formal rules for describing the placement of gates in a genome, a new graphical user interface, support for Verilog 2005 syntax and a connection to the SynBioHub parts repository software environment. Collectively, these features expand Cello's capabilities beyond Escherichia coli plasmids to new organisms and broader genetic contexts, including the genome. Designing circuits with Cello 2.0 produces an abstract Boolean network from a Verilog file, assigns biological parts to each node in the Boolean network, constructs a DNA sequence and generates highly structured and annotated sequence representations suitable for downstream processing and fabrication, respectively. The result is a sequence implementing the specified Boolean function in the organism and predictions of circuit performance. Depending on the size of the design space and users' expertise, jobs may take minutes or hours to complete.

We designed two probiotic treatments to control chytridiomycosis caused by Batrachochytrium dendrobatidis (Bd) on infected Panamanian golden frogs (Atelopus zeteki), a species that is thought to be extinct in the wild due to Bd. The first approach disrupted the existing skin microbe community with antibiotics then exposed the frogs to a core golden frog skin microbe (Diaphorobacter sp.) that we genetically modified to produce high titers of violacein, a known antifungal compound. One day following probiotic treatment, the engineered Diaphorobacter and the violacein-producing pathway could be detected on the frogs but the treatment failed to improve frog survival when exposed to Bd. The second approach exposed frogs to the genetically modified bacterium mixed into a consortium with six other known anti-Bd bacteria isolated from captive A. zeteki, with no preliminary antibiotic treatment. The consortium treatment increased the frequency and abundance of three probiotic isolates (Janthinobacterium, Chryseobacterium, and Stenotrophomonas) and these persisted on the skin 4 weeks after probiotic treatment. There was a temporary increase in the frequency and abundance of three other probiotics isolates (Masillia, Serratia, and Pseudomonas) and the engineered Diaphorobacter isolate, but they subsequently disappeared from the skin. This treatment also failed to reduce frog mortality upon exposure.

RiPPs (ribosomally-synthesized and post-translationally modified peptides) are a class of pharmaceutically-relevant natural products expressed as precursor peptides before being enzymatically processed into their final functional forms. Bioinformatic methods have illuminated hundreds of thousands of RiPP enzymes in sequence databases and the number of characterized chemical modifications is growing rapidly; however, it remains difficult to functionally express them in a heterologous host. One challenge is peptide stability, which we addressed by designing a RiPP stabilization tag (RST) based on a small ubiquitin-like modifier (SUMO) domain that can be fused to the N- or C-terminus of the precursor peptide and proteolytically removed after modification. This is demonstrated to stabilize expression of eight RiPPs representative of diverse phyla. Further, using Escherichia coli for heterologous expression, we identify a common set of media and growth conditions where 24 modifying enzymes, representative of diverse chemistries, are functional. The high success rate and broad applicability of this system facilitates: (i) RiPP discovery through high-throughput “mining” and (ii) artificial combination of enzymes from different pathways to create a desired peptide.

A design for genetically encoded counters is proposed via repressor-based circuits. An N-bit counter reads sequences of input pulses and displays the total number of pulses, modulo 2 N . The design is based on distributed computation with specialized cell types allocated to specific tasks. This allows scalability and bypasses constraints on the maximal number of circuit genes per cell due to toxicity or failures due to resource limitations. The design starts with a single-bit counter. The N-bit counter is then obtained by interconnecting (using diffusible chemicals) a set of N single-bit counters and connector modules. An optimization framework is used to determine appropriate gate parameters and to compute bounds on admissible pulse widths and relaxation (inter-pulse) times, as well as to guide the construction of novel gates. This work can be viewed as a step toward obtaining circuits that are capable of finite automaton computation in analogy to digital central processing units.

Abstract Motivation Applications in synthetic and systems biology can benefit from measuring whole-cell response to biochemical perturbations. Execution of experiments to cover all possible combinations of perturbations is infeasible. In this paper, we present the host response model (HRM), a machine learning approach that maps response of single perturbations to transcriptional response of the combination of perturbations. Results The HRM combines high-throughput sequencing with machine learning to infer links between experimental context, prior knowledge of cell regulatory networks, and RNASeq data to predict a gene’s dysregulation. We find that the HRM can predict the directionality of dysregulation to a combination of inducers with an accuracy of >90% using data from single inducers. We further find that the use of prior, known cell regulatory networks doubles the predictive performance of the HRM (an R2 from 0.3 to 0.65). The model was validated in two organisms, Escherichia coli and Bacillus subtilis, using new experiments conducted after training. Finally, while the HRM is trained with gene expression data, the direct prediction of differential expression makes it possible to also conduct enrichment analyses using its predictions. We show that the HRM can accurately classify >95% of the pathway regulations. The HRM reduces the number of RNASeq experiments needed as responses can be tested in silico prior to the experiment. Availability and implementation The HRM software and tutorial are available at https://github.com/sd2e/CDM and the configurable differential expression analysis tools and tutorials are available at https://github.com/SD2E/omics_tools. Supplementary information Supplem

Significance Inoculation of cereals with diazotrophic (N 2 -fixing) bacteria offers a sustainable alternative to the application of nitrogen fertilizers in agriculture. While natural diazotrophs have evolved multilayered regulatory mechanisms that couple N 2 fixation with assimilation of the product NH 3 and prevent release to plants, genetic modifications can permit excess production and excretion of NH 3 . However, a lack of stringent host-specificity for root colonization by the bacteria would allow growth promotion of target and nontarget plants species alike. Here, we exploit synthetic transkingdom signaling to establish plant host-specific control of the N 2 -fixation catalyst nitrogenase in Azorhizobium caulinodans occupying barley roots. This work demonstrates how partner-specific interactions can be established to avoid potential growth promotion of nontarget plants.

Engineered living materials could have the capacity to self-repair and self-replicate, sense local and distant disturbances in their environment, and respond with functionalities for reporting, actuation or remediation. However, few engineered living materials are capable of both responsivity and use in macroscopic structures. Here we describe the development, characterization and engineering of a fungal-bacterial biocomposite grown on lignocellulosic feedstocks that can form mouldable, foldable and regenerative living structures. We have developed strategies to make human-scale biocomposite structures using mould-based and origami-inspired growth and assembly paradigms. Microbiome profiling of the biocomposite over multiple generations enabled the identification of a dominant bacterial component, Pantoea agglomerans, which was further isolated and developed into a new chassis. We introduced engineered P. agglomerans into native feedstocks to yield living blocks with new biosynthetic and sensing-reporting capabilities. Bioprospecting the native microbiota to develop engineerable chassis constitutes an important strategy to facilitate the development of living biomaterials with new properties and functionalities.

Living materials combine a material scaffold, that is often porous, with engineered cells that perform sensing, computing, and biosynthetic tasks. Designing such systems is difficult because little is known regarding signaling transport parameters in the material. Here, the development of a porous microplate is presented. Hydrogel barriers between wells have a porosity of 60% and a tortuosity factor of 1.6, allowing molecular diffusion between wells. The permeability of dyes, antibiotics, inducers, and quorum signals between wells were characterized. A "sentinel" strain was constructed by introducing orthogonal sensors into the genome of Escherichia coli MG1655 for IPTG, anhydrotetracycline, L-arabinose, and four quorum signals. The strain's response to inducer diffusion through the wells was quantified up to 14 mm, and quorum and antibacterial signaling were measured over 16 h. Signaling distance is dictated by hydrogel adsorption, quantified using a linear finite element model that yields adsorption coefficients from 0 to 0.1 mol m-3 . Parameters derived herein will aid the design of living materials for pathogen remediation, computation, and self-organizing biofilms.

Engineered bacteria could perform many functions in the environment, for example, to remediate pollutants, deliver nutrients to crops or act as in-field biosensors. Model organisms can be unreliable in the field, but selecting an isolate from the thousands that naturally live there and genetically manipulating them to carry the desired function is a slow and uninformed process. Here, we demonstrate the parallel engineering of isolates from environmental samples by using the broad-host-range XPORT conjugation system (Bacillus subtilis mini-ICEBs1) to transfer a genetic payload to many isolates in parallel. Bacillus and Lysinibacillus species were obtained from seven soil and water samples from different locations in Israel. XPORT successfully transferred a genetic function (reporter expression) into 25 of these isolates. They were then screened to identify the best-performing chassis based on the expression level, doubling time, functional stability in soil, and environmentally-relevant traits of its closest annotated reference species, such as the ability to sporulate and temperature tolerance. From this library, we selected Bacillus frigoritolerans A3E1, re-introduced it to soil, and measured function and genetic stability in a contained environment that replicates jungle conditions. After 21 months of storage, the engineered bacteria were viable, could perform their function, and did not accumulate disruptive mutations.

© 2018 American Chemical Society. Centralized facilities for genetic engineering, or "biofoundries", offer the potential to design organisms to address emerging needs in medicine, agriculture, industry, and defense. The field has seen rapid advances in technology, but it is difficult to gauge current capabilities or identify gaps across projects. To this end, our foundry was assessed via a timed "pressure test", in which 3 months were given to build organisms to produce 10 molecules unknown to us in advance. By applying a diversity of new approaches, we produced the desired molecule or a closely related one for six out of 10 targets during the performance period and made advances toward production of the others as well. Specifically, we increased the titers of 1-hexadecanol, pyrrolnitrin, and pacidamycin D, found novel routes to the enediyne warhead underlying powerful antimicrobials, established a cell-free system for monoterpene production, produced an intermediate toward vincristine biosynthesis, and encoded 7802 individually retrievable pathways to 540 bisindoles in a DNA pool. Pathways to tetrahydrofuran and barbamide were designed and constructed, but toxicity or analytical tools inhibited further progress. In sum, we constructed 1.2 Mb DNA, built 215 strains spanning five species (Saccharomyces cerevisiae, Escherichia coli, Streptomyces albidoflavus, Streptomyces coelicolor, and Streptomyces albovinaceus), established two cell-free systems, and performed 690 assays developed in-house for the molecules.

Accurate measurements of promoter activities are crucial for predictably building genetic systems. Here we report a method to simultaneously count plasmid DNA, RNA transcripts, and protein expression in single living bacteria. From these data, the activity of a promoter in units of RNAP/s can be inferred. This work facilitates the reporting of promoters in absolute units, the variability in their activity across a population, and their quantitative toll on cellular resources, all of which provide critical insights for cellular engineering.

Catalytically dead Cas9 (dCas9) is a programmable transcription factor that can be targeted to promoters through the design of small guide RNAs (sgRNAs), where it can function as an activator or repressor. Natural promoters use overlapping binding sites as a mechanism for signal integration, where the binding of one can block, displace, or augment the activity of the other. Here, we implemented this strategy in Escherichia coli using pairs of sgRNAs designed to repress and then derepress transcription through competitive binding. When designed to target a promoter, this led to 27-fold repression and complete derepression. This system was also capable of ratiometric input comparison over two orders of magnitude. Additionally, we used this mechanism for promoter sequence-independent control by adopting it for elongation control, achieving 8-fold repression and 4-fold derepression. This work demonstrates a new genetic control mechanism that could be used to build analog circuit or implement cis-regulatory logic on CRISPRi-targeted native genes.

Copyright © 2020 American Chemical Society. Starting in the early 2000s, sophisticated technologies have been developed for the rational construction of synthetic genetic networks that implement specified logical functionalities. Despite impressive progress, however, the scaling necessary in order to achieve greater computational power has been hampered by many constraints, including repressor toxicity and the lack of large sets of mutually orthogonal repressors. As a consequence, a typical circuit contains no more than roughly seven repressor-based gates per cell. A possible way around this scalability problem is to distribute the computation among multiple cell types, each of which implements a small subcircuit, which communicate among themselves using diffusible small molecules (DSMs). Examples of DSMs are those employed by quorum sensing systems in bacteria. This paper focuses on systematic ways to implement this distributed approach, in the context of the evaluation of arbitrary Boolean functions. The unique characteristics of genetic circuits and the properties of DSMs require the development of new Boolean synthesis methods, distinct from those classically used in electronic circuit design. In this work, we propose a fast algorithm to synthesize distributed realizations for any Boolean function, under constraints on the number of gates per cell and the number of orthogonal DSMs. The method is based on an exact synthesis algorithm to find the minimal circuit per cell, which in turn allows us to build an extensive database of Boolean functions up to a given number of inputs. For concreteness, we will specifically focus on circuits of up to 4 inputs, which might represent, for example, two chemical inducers and two light inputs at different frequencies. Our method shows that, with a constraint of no more than seven gates per cell, the use of a single DSM increases the total number of realizable circuits by at least 7.58-fold compared to centralized computation.

© 2020, The Author(s), under exclusive licence to Springer Nature Limited. Cells can be programmed to monitor and react to their environment using genetic circuits. Design automation software maps a desired circuit function to a DNA sequence, a process that requires units of gene regulation (gates) that are simple to connect and behave predictably. This poses a challenge for eukaryotes due to their complex mechanisms of transcription and translation. To this end, we have developed gates for yeast (Saccharomyces cerevisiae) that are connected using RNA polymerase flux as the signal carrier and are insulated from each other and host regulation. They are based on minimal constitutive promoters (~120 base pairs), for which rules are developed to insert operators for DNA-binding proteins. Using this approach, we constructed nine NOT/NOR gates with nearly identical response functions and 400-fold dynamic range. In circuits, they are transcriptionally insulated from each other by placing ribozymes downstream of terminators to block nuclear export of messenger RNAs resulting from RNA polymerase readthrough. Based on these gates, Cello 2.0 was used to build circuits with up to 11 regulatory proteins. A simple dynamic model predicts the circuit response over days. Genetic circuit design automation for eukaryotes simplifies the construction of regulatory networks as part of cellular engineering projects, whether it be to stage processes during bioproduction, serve as environmental sentinels or guide living therapeutics.

Aerogels are ultralight porous materials whose matrix structure can be formed by interlinking 880 nm long M13 phage particles. In theory, changing the phage properties would alter the aerogel matrix, but attempting this using the current production system leads to heterogeneous lengths. A phagemid system that yields a narrow length distribution that can be tuned in 0.3 nm increments from 50 to 2500 nm is designed and, independently, the persistence length varies from 14 to 68 nm by mutating the coat protein. A robotic workflow that automates each step from DNA construction to aerogel synthesis is used to build 1200 aerogels. This is applied to compare Ni–MnOx cathodes built using different matrixes, revealing a pareto-optimal relationship between performance metrics. This work demonstrates the application of genetic engineering to create “tuning knobs” to sweep through material parameter space; in this case, toward creating a physically strong and high-capacity battery.

© 2020 The Authors. Published under the terms of the CC BY 4.0 license Genetic circuits have many applications, from guiding living therapeutics to ordering process in a bioreactor, but to be useful they have to be genetically stable and not hinder the host. Encoding circuits in the genome reduces burden, but this decreases performance and can interfere with native transcription. We have designed genomic landing pads in Escherichia coli at high-expression sites, flanked by ultrastrong double terminators. DNA payloads >8 kb are targeted to the landing pads using phage integrases. One landing pad is dedicated to carrying a sensor array, and two are used to carry genetic circuits. NOT/NOR gates based on repressors are optimized for the genome and characterized in the landing pads. These data are used, in conjunction with design automation software (Cello 2.0), to design circuits that perform quantitatively as predicted. These circuits require fourfold less RNA polymerase than when carried on a plasmid and are stable for weeks in a recA+ strain without selection. This approach enables the design of synthetic regulatory networks to guide cells in environments or for applications where plasmid use is infeasible.

© 2020, The Author(s). To perform their computational function, genetic circuits change states through a symphony of genetic parts that turn regulator expression on and off. Debugging is frustrated by an inability to characterize parts in the context of the circuit and identify the origins of failures. Here, we take snapshots of a large genetic circuit in different states: RNA-seq is used to visualize circuit function as a changing pattern of RNA polymerase (RNAP) flux along the DNA. Together with ribosome profiling, all 54 genetic parts (promoters, ribozymes, RBSs, terminators) are parameterized and used to inform a mathematical model that can predict circuit performance, dynamics, and robustness. The circuit behaves as designed; however, it is riddled with genetic errors, including cryptic sense/antisense promoters and translation, attenuation, incorrect start codons, and a failed gate. While not impacting the expected Boolean logic, they reduce the prediction accuracy and could lead to failures when the parts are used in other designs. Finally, the cellular power (RNAP and ribosome usage) required to maintain a circuit state is calculated. This work demonstrates the use of a small number of measurements to fully parameterize a regulatory circuit and quantify its impact on host.

Copyright © 2020 American Chemical Society. Starting in the early 2000s, sophisticated technologies have been developed for the rational construction of synthetic genetic networks that implement specified logical functionalities. Despite impressive progress, however, the scaling necessary in order to achieve greater computational power has been hampered by many constraints, including repressor toxicity and the lack of large sets of mutually orthogonal repressors. As a consequence, a typical circuit contains no more than roughly seven repressor-based gates per cell. A possible way around this scalability problem is to distribute the computation among multiple cell types, each of which implements a small subcircuit, which communicate among themselves using diffusible small molecules (DSMs). Examples of DSMs are those employed by quorum sensing systems in bacteria. This paper focuses on systematic ways to implement this distributed approach, in the context of the evaluation of arbitrary Boolean functions. The unique characteristics of genetic circuits and the properties of DSMs require the development of new Boolean synthesis methods, distinct from those classically used in electronic circuit design. In this work, we propose a fast algorithm to synthesize distributed realizations for any Boolean function, under constraints on the number of gates per cell and the number of orthogonal DSMs. The method is based on an exact synthesis algorithm to find the minimal circuit per cell, which in turn allows us to build an extensive database of Boolean functions up to a given number of inputs. For concreteness, we will specifically focus on circuits of up to 4 inputs, which might represent, for example, two chemical inducers and two light inputs at different frequencies. Our method shows that, with a constraint of no more than seven gates per cell, the use of a single DSM increases the total number of realizable circuits by at least 7.58-fold compared to centralized computation.

© 2018 American Chemical Society. Centralized facilities for genetic engineering, or "biofoundries", offer the potential to design organisms to address emerging needs in medicine, agriculture, industry, and defense. The field has seen rapid advances in technology, but it is difficult to gauge current capabilities or identify gaps across projects. To this end, our foundry was assessed via a timed "pressure test", in which 3 months were given to build organisms to produce 10 molecules unknown to us in advance. By applying a diversity of new approaches, we produced the desired molecule or a closely related one for six out of 10 targets during the performance period and made advances toward production of the others as well. Specifically, we increased the titers of 1-hexadecanol, pyrrolnitrin, and pacidamycin D, found novel routes to the enediyne warhead underlying powerful antimicrobials, established a cell-free system for monoterpene production, produced an intermediate toward vincristine biosynthesis, and encoded 7802 individually retrievable pathways to 540 bisindoles in a DNA pool. Pathways to tetrahydrofuran and barbamide were designed and constructed, but toxicity or analytical tools inhibited further progress. In sum, we constructed 1.2 Mb DNA, built 215 strains spanning five species (Saccharomyces cerevisiae, Escherichia coli, Streptomyces albidoflavus, Streptomyces coelicolor, and Streptomyces albovinaceus), established two cell-free systems, and performed 690 assays developed in-house for the molecules.

Abstract People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species. Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.3 of SBOL Visual, which builds on the prior SBOL Visual 2.2 in several ways. First, the specification now includes higher-level “interactions with interactions,” such as an inducer molecule stimulating a repression interaction. Second, binding with a nucleic acid backbone can be shown by overlapping glyphs, as with other molecular complexes. Finally, a new “unspecified interaction” glyph is added for visualizing interactions whose nature is unknown, the “insulator” glyph is deprecated in favor of a new “inert DNA spacer” glyph, and the polypeptide region glyph is recommended for showing 2A sequences.