SEARCH · bioRxiv Science

Results for “synthetic biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6Linked to original sources

bioRxiv2017

Multiplex genome editing for synthetic biology in Vibrio natriegens

Vibrio natriegens has recently emerged as an alternative to Escherichia coli for molecular biology and biotechnology, but low-efficiency genetic tools hamper its development. Here, we uncover how to induce natural competence in V. natriegens and describe methods for multiplex genome editing by natural transformation (MuGENT). MuGENT promotes integration of large genome edits at high-efficiency on unprecedented timescales, which will extend the utility of this species for diverse applications.\n\nV. natriegens is the fastest growing organism known, with a doubling time of <10 min1,2. With broad metabolic capabilities, lack of pathogenicity, and its rapid growth rate, it is an attractive alternative to E. coli for diverse molecular biology and biotechnology applications3. Methods for classical genetic techniques have been developed for V. natriegens, but these are rel ...

synthetic biology↗

bioRxiv2026

Dual-Chassis Strategy for Bridging Adaptive Evolution and Rational Design for Synthetic Biology

Genome streamlining and pathway refactoring are powerful strategies for constructing controllable microbial chassis for both fundamental studies and applications. While rational design benefits from reduced genetic complexity, adaptive laboratory evolution (ALE) thrives on metabolic redundancy, creating a mismatch between optimal hosts for design and evolution. Here, we introduce a dual chassis framework (DUET) in which rational pathway construction and adaptive evolution are first carried out in an evolution-competent host, and the resulting optimized designs are subsequently transferred into a genetically stable chassis for deployment. Using the naturally evolvable bacterium Acinetobacter baylyi ADP1 and its genome-stabilized derivative (ISx), we applied this framework to the {beta}-ketoadipate pathway, a central hub for aromatic compound catabolism. We first streamlined the native network by deleting individual pathway branches and then engineered a minimal synthetic route that merges protocatechuate and catechol metabolism. Subsequent ALE enabled efficient growth through this synthetic pathway, and reverse-engineering identified key adaptive mutations underlying functional recovery. Both the synthetic pathway and the mutations were transferred unchanged into ISx, where robust growth was maintained without further adaptation. These results demonstrate that DUET enables portable, host-independent deployment of rational metabolic streamlining combined with evolution, providing a generalizable strategy for building reduced yet robust microbial platforms. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/729570v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@19ba68forg.highwire.dtl.DTLVardef@1d40eb4org.highwire.dtl.DTLVardef@1115597org.highwire.dtl.DTLVardef@10a50f4_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2026

A synthetic biology approach to bacterial transcription initiation: RNA aptamer based in vitro transcription assay for rapidly testing bacterial RNA polymerases, promoters and inhibitors.

We present a robust and versatile in vitro transcription (IVT) assay based on an optimized Broccoli RNA aptamer sequence. When paired with the fluorophore DFHBI-1T, this system enables real-time monitoring of multi-round transcription over several hours. To facilitate streamlined promoter analysis, we developed the pIVT3 plasmid backbone. The system was validated using both the single-subunit T7 RNA polymerase and the multi-subunit Escherichia coli RNA polymerase; notably, the activity of the E. coli enzyme remained strictly dependent on the presence of a {sigma} factor and a cognate promoter. To optimize the signal-to-noise ratio, we incorporated two rrnBT1 terminators upstream of the promoter of interest. This modification effectively eliminated background transcription for weak promoters (PlivJ) and prevented interference from read-through transcription in strong synthetic promoters (Ptrc*). Furthermore, we demonstrated the assays utility for drug discovery by characterizing the time- and dose-dependent inhibitory kinetics of rifampicin. Collectively, these results establish the Broccoli-based IVT system as a highly adaptable platform for quantifying promoter strength and screening small-molecule inhibitors of bacterial transcription. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/744185v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@1632360org.highwire.dtl.DTLVardef@1a77977org.highwire.dtl.DTLVardef@1780c9org.highwire.dtl.DTLVardef@1082e05_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2021

FPCountR: Absolute quantification of fluorescent proteins for synthetic biology

This paper presents a generalisable method for the calibration of fluorescence readings on microplate readers, in order to convert arbitrary fluorescence units into absolute units. FPCountR relies on the generation of bespoke fluorescent protein (FP) calibrants, assays to determine protein concentration and activity, and a corresponding analytical workflow. We systematically characterise the assay protocols for accuracy, sensitivity and simplicity, and describe a novel ECmax assay that outperforms the others and even enables accurate calibration without requiring the purification of FPs. To obtain cellular protein concentrations, we consider methods for the conversion of optical density to either cell counts or alternatively to cell volumes, as well as examining how cells can interfere with protein counting via fluorescence quenching, which we quantify and correct for the first time. Calibration across different instruments, disparate filter sets and mismatched gains is demonstrated to yield equivalent results. It also reveals that mCherry absorption at 600nm does not confound cell density measurements unless expressed to over 100,000 proteins per cell. FPCountR is presented as pair of open access tools (protocol and R package) to enable the community to use this method, and ultimately to facilitate the quantitative characterisation of synthetic microbial circuits.

synthetic biology↗

bioRxiv2019

Design of a genetic layered feedback controller in synthetic biological circuitry

Feedback control is the key to achieve robust performances for many engineered systems. However, its application in biological contexts is still largely unexplored. In this work, we designed, analyzed and simulated a layered controller functioning at both molecular and populational levels. First, we used a minimal model of three states to represent a system where state A activates state B; state R is a by-product of state B that acts as a negative feedback regulating both state A, B, and sequentially R. We call the feedback applied to state B a cis feedback and the one applied to state A a trans feedback. Through stability analysis via linearization at equilibrium and sensitivity analysis at transient state, we found that the cis feedback attenuates disturbances better but recovers slower; the trans feedback recovers faster but has more dramatic responses to fluctuations; the layered feedback demonstrates both advantageous traits of the two single layers. Then we designed two versions of synthetic genetic circuits to implement the layered controller in living cells. One version with an sRNA as regulator R, the other with a transcription factor protein as the regulator R. The analysis and dynamical simulation of the models confirmed the analytical results from the minimal model. At the same time, we found that the protein regulated feedback controls have faster recovery speed but the RNA version has a stronger disturbance attenuation effect.

synthetic biology↗

bioRxiv2024

A robust synthetic biology toolkit to advance carboxysome study and design

Carboxysomes are polyhedral protein organelles that microorganisms use to facilitate carbon dioxide assimilation. They are composed of a modular protein shell which envelops an enzymatic core mainly comprised of physically coupled Rubisco and carbonic anhydrase. While the modular construction principles of carboxysomes make them attractive targets as customizable metabolic platforms, their size and complexity can be a hinderance. In this work, we design and validate a plasmid set - the pXpressome toolkit -in which -carboxysomes are robustly expressed and remain intact and functional after purification. We tested this toolkit by introducing mutations which influence carboxysome structure and performance. We find that deletion of vertex-capping genes results in formation of larger carboxysomes while deletion of facet forming genes produces smaller particles, suggesting that adjusting the ratio of these proteins can rationally affect morphology. Through a series of fluorescently labeled constructs, we observe this toolkit leads to more uniform expression and better cell health than previously published carboxysome expression systems. Overall, the pXpressome toolkit facilitates the study and redesign of carboxysomes with robust performance and improved phenotype uniformity. The pXpressome toolkit will support efforts to remodel carboxysomes for enhanced carbon fixation or serve as a platform for other nanoencapsulation goals.

synthetic biology↗

bioRxiv2025

Rhodo-Box: a Synthetic Biology Toolbox to Facilitate Metabolic Engineering of Rhodobacter sphaeroides

Rhodobacter sphaeroides is a purple non-sulphur alphaproteobacterium with a highly versatile metabolism. This microorganism holds promise as a chassis for sustainable biomanufacturing of numerous chemicals. Yet, its potential is constrained by a lack of standardized, well-characterized genetic elements to tune gene expression such as transcriptional promoters and ribosome binding sites (RBSs). In this study, we present Rhodo-Box, a comprehensive toolkit for R. sphaeroides created by adapting and extending the Zymo-Parts modular cloning framework. Using Rhodo-Box we built and characterized: (a) three broad-host origins of replication (pBBR1, RK2 and RSF1010), (b) a set of 13 promoters, (c) four inducible expression systems (NahR-PsalTTC, LacI-PlacT7A1_O3O4, VanR-PvanCC, and XylS-Pm), (d) 11 RBSs, and (e) four transcriptional terminators. Furthermore, we present a semi-automated, user-friendly cloning approach which enables rapid construction of R. sphaeroides strains. The Rhodo-Box toolkit equips R. sphaeroides with a standardized, automation-compatible collection of parts and workflows essential for efficient design-build-test-learn cycles and advanced metabolic engineering. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/685836v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@fcb172org.highwire.dtl.DTLVardef@1e5eb44org.highwire.dtl.DTLVardef@1b8df28org.highwire.dtl.DTLVardef@42eb2a_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

Exploration of mRNA-sized RNA import into Saccharomyces cerevisiae mitochondria by a combined synthetic biology and adaptive laboratory evolution approach

Efficient gene integration using RNA-guided endonucleases has not yet been achieved in the mitochondrial genome. Import of nucleic acids into mitochondria, a controversial feature, is essential for implementation of Cas9-mediated genome engineering of mitochondria. Import of short RNAs naturally occurs in mitochondria, and several putative import mechanisms and determinants have been proposed. However to date, import of gene-length RNA, required for gene integration in the mitochondrial genome, has never been described. The goal of this study was to devise and test experimental strategies to detect and improve the import of mRNA-sized RNA in mitochondria, using S. cerevisiae as model. A first fluorescence-based screening approach, relying on mitochondrial import of a fluorescent protein encoding mRNA was analyzed by fluorescence measurements, western blot and mRNA-FISH. Confounding results obtained with these different techniques made it difficult to unambiguously conclude on the occurrence of import of mRNA-sized RNAs into mitochondria. An adaptive laboratory evolution (ALE) approach, imposing a strong selection pressure for mRNA import to mitochondria, was then designed and tested to improve mitochondrial mRNA import. While the ALE approach did not improve mitochondrial mRNA import in the present study, it is a promising, unambiguous method for future studies testing different RNAs or mutants. The present study highlights remaining challenges in analytical techniques to identify RNA import to mitochondria, and introduces a novel application of ALE for studies on mitochondrial import of short and long RNA species.

synthetic biology↗

bioRxiv2025

Expanding the Bacteroides synthetic biology toolkit to develop an in vivo intestinal malabsorption biosensor.

The human gut is a highly dynamic physical environment where perturbations--including factors such as acidification, oxygenation, and particle concentration (osmolality)--can influence microbiota composition and contribute to disease states. Understanding gut environmental changes is essential for advancing diagnostic and therapeutic strategies for gut health. However, non-invasive methods for continuous monitoring remain limited. The bacterial gut microbiota represents a powerful platform for continuous, non-invasive biosensing technologies for the gut environment, with genetically tractable commensal species like Bacteroides thetaiotaomicron (B. theta) emerging as promising hosts for engineered biosensors. However, the availability of genetic tools for precise, modular environmental sensing and reporting control in B. theta remains limited. Here, we present an expanded genetic engineering toolkit for B. theta that enables precise, fluorescence-based environmental sensing of the gut environment. This toolkit includes i) three libraries of orthogonally inducible promoters capable of driving fluorescence expression, ii) a DNA-based system to tune repressor activity in B. theta, iii) a resulting modular transcriptional reporter circuit that integrates native promoter activation with fluorescent outputs, and iv) characterization of a novel plasmid integration mode in B. theta. To demonstrate its utility, we engineered biosensors for gut malabsorption, a condition characterized by increased luminal osmolality. Using identified osmolality-responsive native promoters from B. theta, we made biosensors capable of detecting changes in gut physiology through graded fluorescent outputs. These biosensors were validated both in vitro and in vivo using a murine model of laxative-induced malabsorption, where they enabled continuous, long-term, non-invasive monitoring of single-cell response from fecal samples with sensitivity to subclinical malabsorption levels. By expanding the genetic toolkit for Bacteroides and demonstrating its use in a physiologically relevant context, this approach highlights the potential of engineered gut bacteria as a monitoring platform for diverse gut health applications. This work advances strategies for microbial biosensing and positions gut commensals as key players in next-generation diagnostic methods.

synthetic biology↗

bioRxiv2024

A differentiable Gillespie algorithm for simulating chemical kinetics, parameter estimation, and designing synthetic biological circuits

The Gillespie algorithm is commonly used to simulate and analyze complex chemical reaction networks. Here, we leverage recent breakthroughs in deep learning to develop a fully differentiable variant of the Gillespie algorithm. The differentiable Gillespie algorithm (DGA) approximates discontinuous operations in the exact Gillespie algorithm using smooth functions, allowing for the calculation of gradients using backpropagation. The DGA can be used to quickly and accurately learn kinetic parameters using gradient descent and design biochemical networks with desired properties. As an illustration, we apply the DGA to study stochastic models of gene promoters. We show that the DGA can be used to: (i) successfully learn kinetic parameters from experimental measurements of mRNA expression levels from two distinct E. coli promoters and (ii) design nonequilibrium promoter architectures with desired input-output relationships. These examples illustrate the utility of the DGA for analyzing stochastic chemical kinetics, including a wide variety of problems of interest to synthetic and systems biology.

biophysics↗

bioRxiv2021

Fluorinated oil-surfactant mixtures with the density of water: artificial cells for synthetic biology

There is a rising interest in biotechnology for the compartmentalization of biochemical reactions in water droplets. Several applications, such as the widely used digital PCR, seek to encapsulate a single molecule in a droplet to be amplified. Directed evolution, another technology with growing popularity, seeks to replicate what happens in nature by encapsulating a single gene and the protein encoded by this gene, linking genotype with phenotype. Compartmentalizing reactions in droplets also allows the experimentalist to run millions of different reactions in parallel. Compartmentalization requires a fluid that is immiscible with water and a surfactant to stabilize the droplets. While there are fluids and surfactants on the market that have been used to accomplish encapsulation, there are reported concerns with these. Span(R) 80, for example, a commonly used surfactant, has contaminants that interfere with various biochemical reactions. Similarly, synthetic fluids distributed by the cosmetic industry allow some researchers to produce experimental results that can be published, but then other researchers fail to reproduce some of these protocols due to the unreliable nature of these products, which are not manufactured with the intent of being used in biotechnology. The most reliable fluids, immiscible with water and suitable for biochemical reactions, are fluorinated fluids. Fluorinated compounds have the peculiar characteristic of being immiscible with water while at the same time not mixing with hydrophobic molecules. This peculiar characteristic has made fluorinated fluids attractive because it seems to be the basis of their being biologically inert. However, commercially available fluorinated fluids have densities between 1.4 to 1.6 g/mL. The higher-than-water density of fluorinated oils complicates handling of the droplets since these would float on the fluid since the water droplets would be less dense. This can cause aggregation and coalescence of the droplets. Here, we report the synthesis, characterization, and use of fluorinated polysiloxane oils that have densities similar to the one of water at room temperature, and when mixed with non-ionic fluorinated surfactants, can produce droplets encapsulating biochemical reactions. We show how droplets in these emulsions can host many biological processes, including PCR, DNA origami, rolling circle amplification (RCA), and Taqman(R) assays. Some of these use unnatural DNA built from an Artificially Expanded Genetic Information System (AEGIS) with six nucleotide "letters".

synthetic biology↗

bioRxiv2025

Synthetic Biology Driven Melanin Deposition for Wood Coating

Pigments are widely utilized in industries such as textiles, cosmetics, food, and packaging. However, conventional synthetic pigment production relies on petroleum-based feedstocks, consumes significant energy, and involves toxic chemicals raising environmental and safety concerns. Natural pigments offer a sustainable and biodegradable alternative, yet their large-scale application is hindered by limited availability, batch variability, and geographical dependence. To overcome this, microbial biosynthesis has attracted attention as a controllable and scalable route for pigment production independent of environmental fluctuations. Nevertheless, most existing approaches retain multistep workflows - pigment synthesis, extraction, purification, and application. This compromises process efficiency and reproducibility. Herein, we present a whole-cell biocatalytic approach for melanin synthesis and deposition, wherein recombinant E. coli expressing tyrosinase is employed to convert L-tyrosine into melanin through copper-dependent oxidative polymerization. By harnessing intact microbial cells as self-contained biocatalytic units, this system bypasses the need for enzyme extraction and purification. Prior to applying the culture media containing melanin on material surfaces such as cotton and wood, the process conditions were optimized to enhance melanin yield. Subsequently, the material surfaces incubated in the melanin culture medium were characterized for their surface morphology and chemical modifications through scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy. The color fastness properties of the material were also evaluated in the presence of water and detergents and subsequently improved through post-treatment processes. In addition, the melanin-coated cotton demonstrated enhanced photothermal performance compared to uncoated controls. All these taken together, this work establishes a simplified and potentially scalable route toward sustainable pigment production and direct application through enzyme-driven in situ biocatalysis on various material surfaces.

bioengineering↗

bioRxiv2020

Transcriptional kinetic synergy: a complex landscape revealed by integrating modelling and synthetic biology

1Gene regulation involves synergistic interactions between transcription factors (TFs). Classical thermodynamic models offer a biophysical understanding of synergy based on binding cooperativity and regulated recruitment of RNA polymerase. However, transcription requires polymerase to transition through multiple states. Accordingly, recent work has suggested that "kinetic synergy" can arise through TFs differentially regulating distinct steps of the transcription cycle. Disentangling both sources of synergy has been challenging. Here, we combine theory and experiment to analyze TFs binding to a single shared site, thereby removing simultaneous specific DNA binding. Using the graph-based linear framework, we integrate TF binding with regulation of the transcription cycle, and reveal a complex kinetic synergy landscape dependent on TF concentration, DNA binding and transcriptional activity. We exploit synthetic zinc-finger TF fusions to experimentally interrogate these predictions. Our results confirm that transcription cycle regulation must be integrated with recruitment for a quantitative understanding of transcriptional control.

systems biology↗

bioRxiv2017

A synthetic biology approach to probing nucleosome symmetry

The repeating subunit of chromatin, the nucleosome, includes two copies of each of the four core histones, and several recent studies have reported that asymmetrically-modified nucleosomes occur at regulatory elements in vivo. To probe the mechanisms by which histone modifications are read out, we designed an obligate pair of H3 heterodimers, termed H3X and H3Y, which we extensively validated genetically and biochemically. Comparing the effects of asymmetric histone tail point mutants with those of symmetric double mutants revealed that a single methylated H3K36 per nucleosome was sufficient to silence cryptic transcription in vivo. We also demonstrate the utility of this system for analysis of histone modification crosstalk, using mass spectrometry to separately identify modifications on each H3 molecule within asymmetric nucleosomes. The ability to generate asymmetric nucleosomes in vivo and in vitro provides a powerful and generalizable tool to probe the mechanisms by which H3 tails are read out by effector proteins in the cell.

molecular biology↗

bioRxiv2022

Novel Context-Specific Genome-Scale Modelling Explores the Potential of Chlamydomonas reinhardtii for Synthetic Biology Applications

Gene expression data of cell cultures is commonly measured in biological and medical studies to understand cellular decision-making in various conditions. Metabolism, affected but not solely determined by the expression, is much more difficult to measure experimentally. Thus, finding a reliable method to predict cell metabolism for given expression data will greatly benefit model-aided metabolic engineering. We have developed such a pipeline that can explore cellular fluxomics from expression data, using only a high-quality genome-scale metabolic model. This is done through two main steps: first, construct a protein-constrained metabolic model by integrating protein and enzyme information into the metabolic model. Secondly, overlay the expression data onto the modified model using a new two-step non-convex and convex optimization formulation, resulting in context-specific models with optionally calibrated rate constants. The resulting model computes proteomes and intracellular flux states that are consistent with the measured transcriptomes. Therefore, it provides detailed cellular insights that are difficult to glean individually from the omic data or metabolic models alone. As a case study, we apply the pipeline to interpret triacylglycerol (TAG) overproduction by Chlamydomonas reinhardtii, using time-course RNA-Seq data. The pipeline allows us to compute C. reinhardtii metabolism under nitrogen deprivation and metabolic shifts after an acetate boost. We also suggest a list of possible bottlenecking proteins that need to be overexpressed to increase the TAG accumulation rate, as well as discussing other TAG-overproduction strategies.

systems biology↗

bioRxiv2024

Network for Knowledge Organization (NEKO): an AI knowledge mining workflow for synthetic biology research

Large language models (LLMs) can complete general scientific question-and-answer, yet they are constrained by their pretraining cut-off dates and lack the ability to provide specific, cited scientific knowledge. Here, we introduce Network for Knowledge Organization (NEKO), a workflow that uses LLM Qwen to extract knowledge through scientific literature text mining. When user inputs a keyword of interest, NEKO can generate knowledge graphs and comprehensive summaries from PubMed search. NEKO has immediate applications in daily academic tasks such as education of young scientists, literature review, paper writing, experiment planning/troubleshooting, and new hypothesis generation. We exemplified this workflows applicability through several case studies on yeast fermentation and cyanobacterial biorefinery. NEKOs output is more informative, specific, and actionable than GPT-4s zero-shot Q&A. NEKO offers flexible, lightweight local deployment options. NEKO democratizes artificial intelligence (AI) tools, making scientific foundation model more accessible to researchers without excessive computational power.

bioengineering↗

bioRxiv2021

High-throughput aminoacyl-tRNA synthetase engineering for genetic code expansion in yeast

Protein expression with genetically encoded noncanonical amino acids (ncAAs) benefits a broad range of applications, from the discovery of biological therapeutics to fundamental biological studies. A major factor limiting the use of ncAAs is the lack of orthogonal translation systems (OTSs) that support efficient genetic code expansion at repurposed stop codons. Aminoacyl-tRNA synthetases (aaRSs) have been extensively evolved in E. coli but are not always orthogonal in eukaryotes. In this work, we use a yeast display-based ncAA incorporation reporter platform with fluorescence-activated cell sorting to screen libraries of aaRSs in high throughput for 1) incorporation of ncAAs not previously encoded in yeast; 2) improvement of the performance of an existing aaRS; 3) highly selective OTSs capable of discriminating between closely related ncAA analogs; and 4) OTSs exhibiting enhanced polyspecificity to support translation with structurally diverse sets of ncAAs. The number of previously undiscovered aaRS variants we report in this work more than doubles the total number of translationally active aaRSs available for genetic code manipulation in yeast. The success of myriad screening strategies has important implications related to the fundamental properties and evolvability of aaRSs. Furthermore, access to OTSs with diverse activities and specific or polyspecific properties is invaluable for a range of applications within chemical biology, synthetic biology, and protein engineering. SynopsisA range of flow cytometry-based screens yielded diverse translational machinery for genetic code expansion in yeast, facilitating access to new chemistries and tunable specificity profiles. O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

synthetic biology↗

bioRxiv2020

Enhancing multi-bioreactor platforms for automated measurements and reactive experiment control

New small-scale, low-cost bioreactors provide researchers with exquisite control of environmental parameters of microbial cultures over long durations, allowing them to perform sophisticated, high-quality quantitative experiments that are particularly useful in systems biology, synthetic biology and bioengineering. However, existing setups are limited in their automated measurement capabilities, primarily because sensitive and specific measurements require bulky, expensive, stand-alone instruments. Here, we present ReacSight, a generic and flexible strategy to enhance bioreactor arrays for automated measurements and reactive experiment control. On the hardware side, ReacSight leverages a pipetting robot for sample collection, handling and loading. On the software side, ReacSight provides a versatile instrument control architecture and a generic event system for reactive experiment control. ReacSight is ideally suited to integrate open-source, open-hardware components but can also accommodate closed-source, GUI-only components (e.g. cytometers). We use ReacSight to assemble a platform for cytometry-based characterization and reactive optogenetic control of parallel yeast continuous cultures. Using a dedicated bioreactor array, we showcase its capabilities on three applications. First, we achieve parallel real-time control of gene expression with light in different bioreactors. Second, we explore the impact of nutrient scarcity on fitness and cellular stress using well-controlled, high-information content competition assays. Third, we exploit nutrient scarcity to achieve dynamic control over the composition of a two-strain consortium. To illustrate the genericity of ReacSight, we also assemble an equivalent platform using the optogenetic-ready, open-hardware and commercially available Chi.Bio bioreactors.

synthetic biology↗