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bioRxiv2021

Elucidating multi-input processing 3-node gene regulatory network topologies capable of generating striped gene expression patterns

BackgroundA central problem in developmental and synthetic biology is understanding the mechanisms by which cells in a tissue or a Petri dish process external cues and transform such information into a coherent response, e.g., a terminal differentiation state. It was long believed that this type of positional information could be entirely attributed to a gradient of concentration of a specific signaling molecule (i.e., a morphogen). However, advances in experimental methodologies and computer modeling have demonstrated the crucial role of the dynamics of a cells gene regulatory network (GRN) in decoding the information carried by the morphogen, which is eventually translated into a spatial pattern. This morphogen interpretation mechanism has gained much attention in systems biology as a tractable system to investigate the emergent properties of complex genotype-phenotype maps. MethodsIn this study, we apply a Markov chain Monte Carlo (MCMC)-like algorithm to probe the design space of three-node GRNs with the ability to generate a band-like expression pattern (target phenotype) in the middle of an arrangement of 30 cells, which resemble a simple (1-D) morphogenetic field in a developing embryo. Unlike most modeling studies published so far, here we explore the space of GRN topologies with nodes having the potential to perceive the same input signal differently. This allows for a lot more flexibility during the search space process, and thus enables us to identify a larger set of potentially interesting and realizable morphogen interpretation mechanisms. ResultsOut of 2061 GRNs selected using the search space algorithm, we found 714 classes of network topologies that could correctly interpret the morphogen. Notably, the main network motif that generated the target phenotype in response to the input signal was the type 3 Incoherent Feed-Forward Loop (I3-FFL), which agrees with previous theoretical expectations and experimental observations. Particularly, compared to a previously reported pattern forming GRN topologies, we have uncovered a great variety of novel network designs, some of which might be worth inquiring through synthetic biology methodologies to test for the ability of network design with minimal regulatory complexity to interpret a developmental cue robustly. Author summarySystems biology is a fast growing field largely powered by advances in high-performance computing and sophisticated mathematical modeling of biological systems. Based on these advances, we are now in a position to mechanistically understand and accurately predict the behavior of complex biological processes, including cell differentiation and spatial pattern formation during embryogenesis. In this article, we use an in silico approach to probe the design space of multi-input, three-node Gene Regulatory Networks (GRNs) capable of generating a striped gene expression pattern in the context of a simplified 1-D morphogenetic field.

systems biology↗

bioRxiv2017

Enhanced Guide-RNA Design And Targeting Analysis For Precise CRISPR Genome Editing Of Single And Consortia Of Industrially Relevant And Non-Model Organisms

MotivationGenetic diversity of non-model organisms offers a repertoire of unique phenotypic features for exploration and cultivation for synthetic biology and metabolic engineering applications. To realize this enormous potential, it is critical to have an efficient genome editing tool for rapid strain engineering of these organisms to perform novel programmed functions.\n\nResultsTo accommodate the use of CRISPR/Cas systems for genome editing across organisms, we have developed a novel method, named CASPER (CRISPR Associated Software for Pathway Engineering and Research), for identifying on- and off-targets with enhanced predictability coupled with an analysis of non-unique (repeated) targets to assist in editing any organism with various endonucleases. Utilizing CASPER, we demonstrated a modest 2.4% and significant 30.2% improvement (F-test, p<0.05) over the conventional methods for predicting on- and off-target activities, respectively. Further we used CASPER to develop novel applications in genome editing: multitargeting analysis (i.e. simultaneous multiple-site modification on a target genome with a sole guide-RNA (gRNA) requirement) and multispecies population analysis (i.e. gRNA design for genome editing across a consortium of organisms). Our analysis on a selection of industrially relevant organisms revealed a number of non-unique target sites associated with genes and transposable elements that can be used as potential sites for multitargeting. The analysis also identified shared and unshared targets that enable genome editing of single or multiple genomes in a consortium of interest. We envision CASPER as a useful platform to enhance the precise CRISPR genome editing for metabolic engineering and synthetic biology applications.

bioinformatics↗

bioRxiv2022

OPENPichia: building a free-to-operate Komagataella phaffii protein expression toolkit

In the standard toolkit for recombinant protein expression, the yeast known in biotechnology as Pichia pastoris (formally: Komagataella phaffii) takes up the position between E. coli and HEK293 or CHO mammalian cells, and is used by thousands of laboratories both in academia and industry. The organism is eukaryotic yet microbial, and grows to extremely high cell densities while secreting proteins into its fully defined growth medium, using very well established strong inducible or constitutive promoters. Many products made in Pichia are in the clinic and in industrial markets. Pichia is also a favoured host for the rapidly emerging area of precision fermentation for the manufacturing of food proteins. However, the earliest steps in the development of the industrial strain (NRRL Y-11430/CBS 7435) that is used throughout the world were performed prior to 1985 in industry (Phillips Petroleum Company) and are not in the public domain. Moreover, despite the long expiry of associated patents, the patent deposit NRRL Y-11430/CBS 7435 that is the parent to all commonly used industrial strains, is not or no longer made freely available through the resp. culture collections. This situation is far from ideal for what is a major chassis for synthetic biology, as it generates concern that novel applications of the system are still encumbered by licensing requirements of the very basic strains. In the spirit of open science and freedom to operate for what is a key component of biotechnology, we set out to resolve this by using genome sequencing of type strains, reverse engineering where necessary, and comparative protein expression and strain characterisation studies. We find that the industrial strains derive from the K. phaffii type strain lineage deposited as 54-11.239 in the UC Davis Phaff Yeast Strain collection by Herman Phaff in 1954. This type strain has valid equivalent deposits that are replicated/derived from it in other yeast strain collections, incl. in ARS-NRRL NRRL YB-4290 (deposit also made by Herman Phaff) and NRRL Y-7556, CBS 2612 and NCYC 2543. We furthermore discovered that NRRL Y-11430 and its derivatives carry an ORF-truncating mutation in the HOC1 cell wall synthesis gene, and that reverse engineering of a similar mutation in the NCYC 2543 type strain imparts the high transformability that is characteristic of the industrial strains. Uniquely, the NCYC 2543 type strain, which we propose to call OPENPichia henceforth, is freely available from the NCYC culture collection, incl. resale and commercial production licenses at nominal annual licensing fees1. Furthermore, our not-for-profit research institute VIB has also acquired a resale/distribution license from NCYC, which we presently use to openly provide to end-users our genome-sequenced OPENPichia subclone strain and its derivatives, i.e., currently the highly transformable hoc1tr and the his4 auxotrophic mutants. To complement the OPENPichia platform, a fully synthetic modular gene expression vector building toolkit was developed, which is also openly distributed, for any purpose. We invite other researchers to contribute to our open science resource-building effort to establish a new unencumbered standard chassis for Pichia synthetic biology.

molecular biology↗

bioRxiv2020

Rapid, robust plasmid verification by de novo assembly of short sequencing reads

Plasmids are a foundational tool for basic and applied research across all subfields of biology. Increasingly, researchers in synthetic biology are relying on and developing massive libraries of plasmids as vectors for directed evolution, combinatorial gene circuit tests, and for CRISPR multiplexing. Verification of plasmid sequences following synthesis is a crucial quality control step that creates a bottleneck in plasmid fabrication workflows. Crucially, researchers often elect to forego the cumbersome verification step, potentially leading to reproducibility and— depending on the application—security issues. In order to facilitate plasmid verification to improve the quality and reproducibility of life science research, we developed a fast, simple, and open source pipeline for assembly and verification of plasmid sequences from Illumina reads. We demonstrate that our pipeline, which relies on de novo assembly, can also be used to detect contaminating sequences in plasmid samples. In addition to presenting our pipeline, we discuss the role for verification and quality control in the increasingly complex life science workflows ushered in by synthetic biology.Competing Interest StatementJP holds an equity stake in GenoFAB Inc., a company that may benefit or may be perceived to benefit from the publication of this article. MR and CC are GenoFAB employees.View Full Text

bioinformatics↗

bioRxiv2025

RNAGym: Large-scale Benchmarks for RNA Fitness and Structure Prediction

Understanding RNA structure and predicting the functional consequences of mutations are fundamental challenges in computational biology with broad implications for therapeutic development and synthetic biology. Current evaluation of machine learning-based RNA models suffers from disparate experimental datasets and inconsistent performance assessments across different RNA families. To address these challenges, we introduce RNAGym, a large-scale benchmarking framework specifically designed for three core tasks-RNA fitness, secondary structure, and tertiary structure prediction. The framework integrates extensive datasets, including 70 standardized deep mutational scanning assays covering over a million mutations across diverse RNA types; 901k chemical-mapping reactivity profiles for secondary structure; and 215 diverse tertiary structures curated from the PDB. RNAGym is designed to facilitate a systematic comparison of RNA models, offering an essential resource to enhance the understanding and development of these models.

synthetic biology↗

bioRxiv2015

Characterizing and Prototyping Genetic Networks with Cell-Free Transcription-Translation Reactions

A central goal of synthetic biology is to engineer cellular behavior by engineering synthetic gene networks for a variety of biotechnology and medical applications. The process of engineering gene networks often involves an iterative design-build-test cycle, whereby the parts and connections that make up the network are built, characterized and varied until the desired network function is reached. Many advances have been made in the design and build portions of this cycle. However, the slow process of in vivo characterization of network function often limits the timescale of the testing step. Cell-free transcription-translation (TX-TL) systems offer a simple and fast alternative to performing these characterizations in cells. Here we provide an overview of a cell-free TX-TL system that utilizes the native Escherichia coli TX-TL machinery, thereby allowing a large repertoire of parts and networks to be characterized. As a way to demonstrate the utility of cell-free TX-TL, we illustrate the characterization of two genetic networks: an RNA transcriptional cascade and a protein regulated incoherent feed-forward loop. We also provide guidelines for designing TX-TL experiments to characterize new genetic networks. We end with a discussion of current and emerging applications of cell free systems.\n\nAbbreviations

Synthetic Biology↗

bioRxiv2021

The power of universal contextualised protein embeddings in cross-species protein function prediction

Computationally annotating proteins with a molecular function is a difficult problem that is made even harder due to the limited amount of available labelled protein training data. A recently published supervised molecular function predicting model partly circumvents this limitation by making its predictions based on the universal (i.e. task-agnostic) contextualised protein embeddings from the deep pre-trained unsupervised protein language model SeqVec. SeqVec embeddings incorporate contextual information of amino acids, thereby modelling the underlying principles of protein sequences insensitive to the context of species. We applied the existing SeqVec-based molecular function prediction model in a transfer learning task by training the model on annotated protein sequences of one training species and making predictions on the proteins of several test species with varying evolutionary distance. We show that this approach successfully generalises knowledge about protein function from one eukaryotic species to various other species, proving itself an effective method for molecular function prediction in inadequately annotated species from understudied taxonomic kingdoms. Furthermore, we submitted the performance of our SeqVec-based prediction models to detailed characterisation, first to advance the understanding of protein language models and second to determine areas of improvement. Author summaryProteins are diverse molecules that regulate all processes in biology. The field of synthetic biology aims to understand these protein functions to solve problems in medicine, manufacturing, and agriculture. Unfortunately, for many proteins only their amino acid sequence is known whereas their function remains unknown. Only a few species have been well-studied such as mouse, human and yeast. Hence, we need to increase knowledge on protein functions. Doing so is, however, complicated as determining protein functions experimentally is time-consuming, expensive, and technically limited. Computationally predicting protein functions offers a faster and more scalable approach but is hampered as it requires much data to design accurate function prediction algorithms. Here, we show that it is possible to computationally generalize knowledge on protein function from one well-studied training species to another test species. Additionally, we show that the quality of these protein function predictions depends on how structurally similar the proteins are between the species. Advantageously, the predictors require only the annotations of proteins from the training species and mere amino acid sequences of test species which may particularly benefit the function prediction of species from understudied taxonomic kingdoms such as the Plantae, Protozoa and Chromista.

bioinformatics↗

bioRxiv2024

Combinatorial Design Testing in Genomes with POLAR-seq

Synthetic biology projects increasingly use modular DNA assembly or synthetic in vivo recombination to generate diverse combinatorial libraries of genetic constructs for testing. But as these designs expand to multigene systems it becomes challenging to sequence these in a cost-effective way that reveals the genotype to phenotype relationships in the libraries. Here, we introduce a new quick, low-cost method designed for assessing combinational designs of genome-integrated multigene constructs that we call Pool of Long Amplified Reads (POLAR) sequencing. POLAR-seq takes genomic DNA isolated from library pools and uses long range PCR to amplify target genomic regions up to 35 kb long containing combinatorial designs. The pool of long amplicons is then directly read by nanopore sequencing with full length reads then used to identify the gene content and structural variation of individual genotypes in the library and read count indicating how abundant a genotype is within the pool. Using yeast cells with loxP-containing synthetic gene clusters that rearrange in vivo in the presence of Cre recombinase, we demonstrate how POLAR-seq can be used to identify global patterns from combinatorial experiments, find the most abundant genotypes in a pool and also be adapted to sequence-verify gene clusters from isolated strains.

synthetic biology↗

bioRxiv2025

Association Studies of Phage Metagenomes from Aquatic Environment Identify Known and Potentially New Key Players in the 2,6-Diaminopurine Biosynthesis Pathway

Advances in next-generation sequencing (NGS) and bioinformatics have expanded the potential of metagenomic studies, particularly for unculturable organisms such as phages with heavily modified genomes. In the evolutionary arms race between phages and their hosts, some phages develop a strategy to fully modify their DNAs to evade host-encoded antiphage defenses. Here, we developed a restriction-enzyme based method to selectively enrich all phages containing 2-aminoadenine (diaminopurine or dZ) directly from purified metagenomic DNA from environmental samples. Applying our previously established metagenomic genome-phenome association (metaGPA) pipeline, we identified 116 protein domains significantly associated with dZ phages. The top candidate domains fully recapitulated the phage-encoded dZ biosynthetic pathway. Study of individual enzymes, including PurZ and YfbR-like dATPase at residue resolution revealed key amino acids for the distinction between dZ and dA substrate. Additionally, we identified and validated two novel DNA polymerases with enhanced dZ incorporation activity and uncovered nucleoside 2-deoxyribosyltransferase (NDT) as a potential new component of the dZ biosynthetic pathway. Collectively, these findings refine current models of the dZ biosynthesis pathway, potentially reveal previously unrecognized enzymatic components, and expand the understanding of phage biology with implications for synthetic biology and DNA engineering.

genomics↗

bioRxiv2017

Engineering a Functional small RNA Negative Autoregulation Network with Model-guided Design

RNA regulators are powerful components of the synthetic biology toolbox. Here, we expand the repertoire of synthetic gene networks built from these regulators by constructing a transcriptional negative autoregulation (NAR) network out of small RNAs (sRNAs). NAR network motifs are core motifs of natural genetic networks, and are known for reducing network response time and steady state signal noise. Here we use cell-free transcription-translation (TX-TL) reactions and a computational model to design and prototype sRNA NAR constructs. Using parameter sensitivity analysis, we design a simple set of experiments that allow us to accurately predict NAR function in TX-TL. We transfer successful network designs in vivo and show that our sRNA transcriptional network reduces both network response time and noise in steady-state gene expression. This work broadens our ability to construct increasingly sophisticated RNA genetic networks with predictable function.

synthetic biology↗

bioRxiv2024

Engineering a Biosynthetic Pathway for the Production of (+)-Brevianamides A and B in Escherichia coli

The privileged fused-ring system comprising the bicyclo[2.2.2]diazaoctane (BDO) core is prevalent in diketopiperazine (DKP) natural products with potent and diverse biological activities, with some being explored as drug candidates. Typically, only low yields of these compounds can be extracted from native fungal producing strains and the available synthetic routes remain challenging due to their structural complexity. BDO-containing DKPs including (+)-brevianamides A and B are assembled via multi-component biosynthetic pathways incorporating non-ribosomal peptide synthetases, prenyltransferases, flavin monooxygenases, cytochrome P450s and semi-pinacolases. To simplify access to this class of alkaloids, we designed an engineered biosynthetic pathway in Escherichia coli, composed of six enzymes sourced from different kingdoms of life. The pathway includes a cyclodipeptide synthase (NascA), a cyclodipeptide oxidase (DmtD2/DmtE2), a prenyltransferase (NotF), a flavin-dependent monooxygenase (BvnB), and kinases (PhoN and IPK). Cultivated in glycerol supplemented with prenol, the engineered E. coli strain produces 5.3 mg/L of (-)-dehydrobrevianamide E (4), which undergoes a terminal, ex vivo lithium hydroxide catalyzed rearrangement reaction to yield (+)-brevianamides A and B with a 46% yield and a 92:8 diastereomeric ratio. Additionally, titers of 4 were increased eight-fold by enhancing NADPH pools in the engineered E. coli strain. Our study combines synthetic biology, biocatalysis and synthetic chemistry approaches to provide a five-step engineered biosynthetic pathway for producing complex indole alkaloids in E. coli. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/627567v2_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@399e92org.highwire.dtl.DTLVardef@d98faaorg.highwire.dtl.DTLVardef@1671ac1org.highwire.dtl.DTLVardef@d7bc6_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2022

Antigen-dependent inducible T cell reporter system for PET imaging of breast cancer and glioblastoma

For the past several decades, chimeric antigen receptor T cell (CAR T) therapies have shown promise in the treatment of cancers. These treatments would greatly benefit from companion imaging biomarkers to follow the trafficking of T cells in vivo. Using synthetic biology, we engineered T cells with a chimeric receptor SyNthetic Intramembrane Proteolysis Receptor (SNIPR) that induces overexpression of an exogenous reporter gene cassette upon recognition of specific tumor markers. We then applied a SNIPR-based positron emission tomography (PET) reporter system to two cancer-relevant antigens, human epidermal growth factor receptor 2 (HER2) and epidermal growth factor receptor variant III (EGFRvIII), commonly expressed in breast and glial tumors respectively. Antigen-specific reporter induction of the SNIPR-PET T cells was confirmed in vitro using GFP fluorescence, luciferase luminescence, and the HSV-TK PET reporter with [18F]FHBG. T cells associated with their target antigens were successfully imaged using PET in dual xenograft HER2+/HER2- and EGFRvIII+/EGFRvIII-animal models, with > 10-fold higher [18F]FHBG signals seen in antigen-expressing tumors versus the corresponding controls. The main innovation described is therefore PET detection of T cells via specific antigen-induced signals, in contrast to reporter systems relying on constitutive gene expression.

synthetic biology↗

bioRxiv2019

Rapid, Low-Cost Detection of Water Contaminants Using Regulated In Vitro Transcription

Synthetic biology has enabled the development of powerful nucleic acid diagnostic technologies for detecting pathogens and human health biomarkers. Here we expand the reach of synthetic biology-enabled diagnostics by developing a cell-free biosensing platform that uses RNA output sensors activated by ligand induction (ROSALIND) to detect harmful contaminants in aqueous samples. ROSALIND consists of three programmable components: highly-processive RNA polymerases, allosteric transcription factors, and synthetic DNA transcription templates. Together, these components allosterically regulate the in vitro transcription of a fluorescence-activating RNA aptamer: in the absence of a target compound, transcription is blocked, while in its presence a fluorescent signal is produced. We demonstrate that ROSALIND can be configured to detect a range of water contaminants, including antibiotics, toxic small molecules, and metals. Our cell-free biosensing platform, which can be freeze-dried for field deployment, creates a new capability for point-of-use monitoring of molecular species to address growing global crises in water quality and human health.

synthetic biology↗

bioRxiv2025

Light-Controlled Synthetic Communication Networks via Paired Connexon Nanopores

Living cells employ dynamic networks for intercellular communication and cooperation, leading to tissue-wide activity. One emerging challenge in the field of bottom-up synthetic biology is emulating such sophisticated behaviors in liposome-based synthetic cells (SCs). Fabricating communication networks in lipid bilayer-based SCs remains a challenge as signaling molecules must transit through two consecutive membranes to transfer information between different SCs. Here, we address this obstacle by engineering connexin channels that directly connect the lumens of adhering SC membranes. We focus on orthogonal channel-forming connexins, namely connexin 43 and connexin 32, and re-design their channel activity to be UV- and near IR-responsive, respectively. By combining engineered connexins into a single SC assembly, we demonstrate orthogonal transfer of reactive signaling molecules between SCs, giving rise to unique reaction products and network states in a wavelength-dependent manner - an important step toward synthetic communication networks.

synthetic biology↗

bioRxiv2025

Detergent-free reconstitution of transmembrane proteins in giant liposomes of complex curvature by the Synthetic Membrane Transfer

Transmembrane proteins perform many crucial functions in the cell, including transfer of matter and information across the membrane. Giant Unilamellar Vesicles (GUVs) are the ideal tool for studying these processes; yet functional transmembrane protein reconstitution in GUVs still represents a bottleneck in bottom-up synthetic biology. Here, we developed a novel approach that we call Synthetic Membrane Transfer (SMT), where transmembrane proteins reconstituted into styrene-maleic acid particles in a detergent-free environment can be transferred to the GUV membrane. The SMT approach is a one-step, facile and general method that works for structurally diverse proteins, and it does not require any specific lipid or buffer composition. Moreover, the SMT is fully compatible with the Synthetic Membrane Shaper (SMS) technology, which allows to deform GUVs in a controlled fashion, obtaining dumbbell-shaped GUVs exhibiting a catenoid-like geometry. The combination of SMT and SMS results in functional reconstitution of transmembrane proteins in catenoid membrane necks. Using this approach, we demonstrate that Mic10, a component of the MICOS complex, directly senses membrane curvature and localizes at the neck of dumbbells GUVs, a geometry that recapitulates the shape of mitochondria cristae junctions. This paves the way for bottom-up reconstitution of the MICOS complex on a physiological membrane geometry.

synthetic biology↗

bioRxiv2019

Securing the exchange of synthetic genetic constructs using digital signatures

Synthetic biology relies on an ever-growing supply chain of synthetic genetic material. Technologies to secure the exchange of this material are still in their infancy. Solutions proposed thus far have focused on watermarks, a dated security approach that can be used to claim authorship, but is subject to counterfeit, and does not provide any information about the integrity of the genetic material itself. We describe how data encryption and digital signature algorithms can be used to ensure the integrity and authenticity of synthetic genetic constructs. Using a pilot software that generates digital signatures and other encrypted data for plasmids, we demonstrate that we can predictably extract information about the author, the identity, and the integrity of plasmid sequences from sequencing data alone without a reference sequence, all without compromising the function of the plasmids. We discuss how this technology can be improved, applied, and expanded to support the new bioeconomy.

synthetic biology↗

bioRxiv2021

A de novo matrix for macroscopic living materials from bacteria

Summary ParagraphEngineered living materials (ELMs) are composites of living cells embedded in a biopolymer matrix that combine the desirable properties of natural biomaterials with non-natural, tailored properties. ELMs with a wide range of sophisticated biological functions have been created by engineering the embedded cells using synthetic biology. Engineering a de novo biomolecular matrix would offer control over material assembly, structure, and composition, thus enabling us to grow macroscopic ELMs with customizable mechanical properties. However, we have lacked the genetic tools and design rules to genetically encode a synthetic matrix that programs collective cell self-organization into macroscopic structures. Here we report growth of macroscopic ELMs from Caulobacter crescentus cells that display and secrete an engineered self-interacting protein. This protein formed an extracellular de novo matrix and assembled cells into hierarchically-ordered, centimeter-scale ELMs. We showed that the mechanical, catalytic, and morphological properties of these ELMs can be tuned through genetic modification of the matrix. Our work identifies novel genetic tools, design and assembly rules for growing macroscopic ELMs with both wide-ranging mechanical properties and customizable functions. We anticipate the modularity of this approach will permit the incorporation of different protein polymers in the de novo matrix, thus allowing to generate ELMs with a variety of desired structures and compositions of the bulk material. We envision specific matrix properties that can be combined synergistically with existing cellular functions to greatly expand the opportunities for ELMs in human health, energy, and the environment.

synthetic biology↗

bioRxiv2018

Establishing a cell-free Vibrio natriegens expression system

The fast growing bacterium Vibrio natriegens is an emerging microbial host for biotechnology. Harnessing its productive cellular components may offer a compelling platform for rapid protein production and prototyping of metabolic pathways or genetic circuits. Here, we report the development of a V. natriegens cell-free expression system. We devised a simplified crude extract preparation protocol and achieved >260 g/mL of super-folder GFP in a small-scale batch reaction after three hours. Culturing conditions, including growth media and cell density, significantly affect translation kinetics and protein yield of extracts. We observed maximal protein yield at incubation temperatures of 26{degrees}C or 30{degrees}C, and show improved yield by tuning ions crucial for ribosomal stability. This work establishes an initial V. natriegens cell-free expression system, enables probing of V. natriegens biology, and will serve as a platform to accelerate metabolic engineering and synthetic biology applications.

synthetic biology↗