Rapid cell-free forward engineering of novel genetic ring oscillators

Cell-Free Synthesis: Expediting Biomanufacturing of Chemical and Biological Molecules

The increasing demand for sustainable alternatives underscores the critical need for a shift away from traditional hydrocarbon-dependent processes. In this landscape, biomanufacturing emerges as a compelling solution, offering a pathway to produce essential chemical materials with significantly reduced environmental impacts. By utilizing engineered microorganisms and biomass as raw materials, biomanufacturing seeks to achieve a carbon-neutral footprint, effectively counteracting the carbon dioxide emissions associated with fossil fuel use. The efficiency and specificity of biocatalysts further contribute to lowering energy consumption and enhancing the sustainability of the production process. Within this context, cell-free synthesis emerges as a promising approach to accelerate the shift towards biomanufacturing. Operating with cellular machinery in a controlled environment, cell-free synthesis offers multiple advantages: it enables the rapid evaluation of biosynthetic pathways and optimization of the conditions for the synthesis of specific chemicals. It also holds potential as an on-demand platform for the production of personalized and specialized products. This review explores recent progress in cell-free synthesis, highlighting its potential to expedite the transformation of chemical processes into more sustainable biomanufacturing practices. We discuss how cell-free techniques not only accelerate the development of new bioproducts but also broaden the horizons for sustainable chemical production. Additionally, we address the challenges of scaling these technologies for commercial use and ensuring their affordability, which are critical for cell-free systems to meet the future demands of industries and fully realize their potential.

Efficiency of transcription and translation of cell-free protein synthesis systems in cell-sized lipid vesicles with changing lipid composition determined by fluorescence measurements

To develop artificial cell models that mimic living cells, cell-sized lipid vesicles encapsulating cell-free protein synthesis (CFPS) systems are useful for protein expressions or artificial gene circuits for vesicle-vesicle communications. Therefore, investigating the transcriptional and translational properties of CFPS systems in lipid vesicles is important for maximizing the synthesis and functions of proteins. Although transcription and translation using CFPS systems inside lipid vesicles are more important than that outside lipid vesicles, the former processes are not investigated by changing the lipid composition of lipid vesicles. Herein, we investigated changes in transcription and translation using CFPS systems inside giant lipid vesicles (approximately 5-20 μm in diameter) caused by changing the lipid composition of lipid vesicles containing neutral, positively, and negatively charged lipids. After incubating for 30 min, 1 h, 2 h, and 4 h, the transcriptional and translational activities in these lipid vesicles were determined by detecting the fluorescence intensities of the fluorogenic RNA aptamer on the 3'-untranslated region of mRNA (transcription) and the fluorescent protein sfCherry (translation), respectively. The results revealed that transcriptional and translational activities in a lipid vesicle containing positively charged lipids were high when the protein was synthesized using the CFPS system inside the lipid vesicle. Thus, the present study provides an experimental basis for constructing complex artificial cell models using bottom-up approaches.

A genetic circuit on a single DNA molecule as an autonomous dissipative nanodevice

Realizing genetic circuits on single DNA molecules as self-encoded dissipative nanodevices is a major step toward miniaturization of autonomous biological systems. A circuit operating on a single DNA implies that genetically encoded proteins localize during coupled transcription-translation to DNA, but a single-molecule measurement demonstrating this has remained a challenge. Here, we use a genetically encoded fluorescent reporter system with improved temporal resolution and observe the synthesis of individual proteins tethered to a DNA molecule by transient complexes of RNA polymerase, messenger RNA, and ribosome. Against expectations in dilute cell-free conditions where equilibrium considerations favor dispersion, these nascent proteins linger long enough to regulate cascaded reactions on the same DNA. We rationally design a pulsatile genetic circuit by encoding an activator and repressor in feedback on the same DNA molecule. Driven by the local synthesis of only several proteins per hour and gene, the circuit dynamics exhibit enhanced variability between individual DNA molecules, and fluctuations with a broad power spectrum. Our results demonstrate that co-expressional localization, as a nonequilibrium process, facilitates single-DNA genetic circuits as dissipative nanodevices, with implications for nanobiotechnology applications and artificial cell design.

Advancing Biomimetic Functions of Synthetic Cells through Compartmentalized Cell-Free Protein Synthesis

Synthetic cells are artificial constructs that mimic the structures and functions of living cells. They are attractive for studying diverse biochemical processes and elucidating the origins of life. While creating a living synthetic cell remains a grand challenge, researchers have successfully synthesized hundreds of unique synthetic cell platforms. One promising approach to developing more sophisticated synthetic cells is to integrate cell-free protein synthesis (CFPS) mechanisms into vesicle platforms. This makes it possible to create synthetic cells with complex biomimetic functions such as genetic circuits, autonomous membrane modifications, sensing and communication, and artificial organelles. This Review explores recent advances in the use of CFPS to impart advanced biomimetic structures and functions to bottom-up synthetic cell platforms. We also discuss the potential applications of synthetic cells in biomedicine as well as the future directions of synthetic cell research.

Cell-free protein synthesis system: A new frontier for sustainable biotechnology-based products

Cell-free protein synthesis (CFPS) system is an innovative technology with a wide range of potential applications that could challenge current thinking and provide solutions to environmental and health issues. CFPS system has been demonstrated to be a successful way of producing biomolecules in a variety of applications, including the biomedical industry. Although there are still obstacles to overcome, its ease of use, versatility, and capacity for integration with other technologies open the door for it to continue serving as a vital instrument in synthetic biology research and industry. In this review, we mainly focus on the cell-free based platform for various product productions. Moreover, the challenges in the bio-therapeutic aspect using cell-free systems and their future prospective for the improvement and sustainability of the cell free systems.

On biochemical constructors and synthetic cells

Is it possible to build life? More specifically, is it possible to create a living synthetic cell from inanimate building blocks? This question precipitated into one of the most significant grand challenges in biochemistry and synthetic biology, with several large research consortia forming around this endeavour in Europe (European Synthetic Cell Initiative), the USA (Build-a-Cell Initiative) and Japan (Japanese Society for Cell Synthesis Research). The mature field of biochemistry, the advent of synthetic biology in the early 2000s, and the burgeoning field of cell-free synthetic biology made it feasible to tackle this grand challenge.

What remains from living cells in bacterial lysate-based cell-free systems

Because they mimic cells while offering an accessible and controllable environment, lysate-based cell-free systems (CFS) have emerged as valuable biotechnology tools for synthetic biology. Historically used to uncover fundamental mechanisms of life, CFS are nowadays used for a multitude of purposes, including protein production and prototyping of synthetic circuits. Despite the conservation of fundamental functions in CFS like transcription and translation, RNAs and certain membrane-embedded or membrane-bound proteins of the host cell are lost when preparing the lysate. As a result, CFS largely lack some essential properties of living cells, such as the ability to adapt to changing conditions, to maintain homeostasis and spatial organization. Regardless of the application, shedding light on the black-box of the bacterial lysate is necessary to fully exploit the potential of CFS. Most measurements of the activity of synthetic circuits in CFS and in vivo show significant correlations because these only require processes that are preserved in CFS, like transcription and translation. However, prototyping circuits of higher complexity that require functions that are lost in CFS (cell adaptation, homeostasis, spatial organization) will not show such a good correlation with in vivo conditions. Both for prototyping circuits of higher complexity and for building artificial cells, the cell-free community has developed devices to reconstruct cellular functions. This mini-review compares bacterial CFS to living cells, focusing on functional and cellular process differences and the latest developments in restoring lost functions through complementation of the lysate or device engineering.

A blueprint for a synthetic genetic feedback optimizer

Biomolecular control enables leveraging cells as biomanufacturing factories. Despite recent advancements, we currently lack genetically encoded modules that can be deployed to dynamically fine-tune and optimize cellular performance. Here, we address this shortcoming by presenting the blueprint of a genetic feedback module to optimize a broadly defined performance metric by adjusting the production and decay rate of a (set of) regulator species. We demonstrate that the optimizer can be implemented by combining available synthetic biology parts and components, and that it can be readily integrated with existing pathways and genetically encoded biosensors to ensure its successful deployment in a variety of settings. We further illustrate that the optimizer successfully locates and tracks the optimum in diverse contexts when relying on mass action kinetics-based dynamics and parameter values typical in Escherichia coli.

L-2L ladder digital-to-analogue converter for dynamics generation of chemical concentrations

Cellular response to dynamic chemical stimulation encodes rich information about the underlying reaction pathways and their kinetics. Microfluidic chemical stimulators play a key role in generating dynamic concentration waveforms by mixing several aqueous solutions. In this article, we propose a multi-layer microfluidic chemical stimulator capable of modulating chemical concentrations by a simple binary logic based on the electronic-hydraulic analogy of electronic R-2R ladder circuits. The proposed device, which we call L-2L ladder digital-to-analogue converter (DAC), allows us to systematically modulate 2 ⁿ levels of concentrations from single sources of solution and solvent by a single operation of 2n membrane valves, which contrasts with existing devices that require complex channel geometry with multiple input sources and valve operations. We fabricated the L-2L ladder DAC with n = 3 bit resolution and verified the concept by comparing the generated waveforms with computational simulations. The response time of the proposed DAC was within the order of seconds because of its simple operation logic of membrane valves. Furthermore, detailed analysis of the waveforms revealed that the transient concentration can be systematically predicted by a simple addition of the transient waveforms of 2n = 6 base patterns, enabling facile optimization of the channel geometry to fine-tune the output waveforms.

Established and Emerging Methods for Protecting Linear DNA in Cell-Free Expression Systems

Cell-free protein synthesis (CFPS) is a method utilized for producing proteins without the limits of cell viability. The plug-and-play utility of CFPS is a key advantage over traditional plasmid-based expression systems and is foundational to the potential of this biotechnology. A key limitation of CFPS is the varying stability of DNA types, limiting the effectiveness of cell-free protein synthesis reactions. Researchers generally rely on plasmid DNA for its ability to support robust protein expression in vitro. However, the overhead required to clone, propagate, and purify plasmids reduces the potential of CFPS for rapid prototyping. While linear templates overcome the limits of plasmid DNA preparation, linear expression templates (LETs) were under-utilized due to their rapid degradation in extract based CFPS systems, limiting protein synthesis. To reach the potential of CFPS using LETs, researchers have made notable progress toward protection and stabilization of linear templates throughout the reaction. The current advancements range from modular solutions, such as supplementing nuclease inhibitors and genome engineering to produce strains lacking nuclease activity. Effective application of LET protection techniques improves expression yields of target proteins to match that of plasmid-based expression. The outcome of LET utilization in CFPS is rapid design–build–test–learn cycles to support synthetic biology applications. This review describes the various protection mechanisms for linear expression templates, methodological insights for implementation, and proposals for continued efforts that may further advance the field.

Bottom-Up Synthetic Biology Using Cell-Free Protein Synthesis

Technical advances in biotechnology have greatly accelerated the development of bottom-up synthetic biology. Unlike top-down approaches, bottom-up synthetic biology focuses on the construction of a minimal cell from scratch and the application of these principles to solve challenges. Cell-free protein synthesis (CFPS) systems provide minimal machinery for transcription and translation, from either a fractionated cell lysate or individual purified protein elements, thus speeding up the development of synthetic cell projects. In this review, we trace the history of the cell-free technique back to the first in vitro fermentation experiment using yeast cell lysate. Furthermore, we summarized progresses of individual cell mimicry modules, such as compartmentalization, gene expression regulation, energy regeneration and metabolism, growth and division, communication, and motility. Finally, current challenges and future perspectives on the field are outlined.

Programmable Synthesis of Biobased Materials Using Cell-Free Systems

Motivated by the intricate mechanisms underlying biomolecule syntheses in cells that chemistry is currently unable to mimic, researchers have harnessed biological systems for manufacturing novel materials. Cell-free systems (CFSs) utilizing the bioactivity of transcriptional and translational machineries in vitro are excellent tools that allow supplementation of exogenous materials for production of innovative materials beyond the capability of natural biological systems. Herein, recent studies that have advanced the ability to expand the scope of biobased materials using CFS are summarized and approaches enabling the production of high-value materials, prototyping of genetic parts and modules, and biofunctionalization are discussed. By extending the reach of chemical and enzymatic reactions complementary to cellular materials, CFSs provide new opportunities at the interface of materials science and synthetic biology.

Compartmentalized Cell-Free Expression Systems for Building Synthetic Cells

One of the grand challenges in bottom-up synthetic biology is the design and construction of synthetic cellular systems. One strategy toward this goal is the systematic reconstitution of biological processes using purified or non-living molecular components to recreate specific cellular functions such as metabolism, intercellular communication, signal transduction, and growth and division. Cell-free expression systems (CFES) are in vitro reconstitutions of the transcription and translation machinery found in cells and are a key technology for bottom-up synthetic biology. The open and simplified reaction environment of CFES has helped researchers discover fundamental concepts in the molecular biology of the cell. In recent decades, there has been a drive to encapsulate CFES reactions into cell-like compartments with the aim of building synthetic cells and multicellular systems. In this chapter, we discuss recent progress in compartmentalizing CFES to build simple and minimal models of biological processes that can help provide a better understanding of the process of self-assembly in molecularly complex systems.

Synthetic Micrographs of Bacteria (SyMBac) allows accurate segmentation of bacterial cells using deep neural networks

BACKGROUND

Deep-learning-based image segmentation models are required for accurate processing of high-throughput timelapse imaging data of bacterial cells. However, the performance of any such model strictly depends on the quality and quantity of training data, which is difficult to generate for bacterial cell images. Here, we present a novel method of bacterial image segmentation using machine learning models trained with Synthetic Micrographs of Bacteria (SyMBac).

RESULTS

We have developed SyMBac, a tool that allows for rapid, automatic creation of arbitrary amounts of training data, combining detailed models of cell growth, physical interactions, and microscope optics to create synthetic images which closely resemble real micrographs, and is capable of training accurate image segmentation models. The major advantages of our approach are as follows: (1) synthetic training data can be generated virtually instantly and on demand; (2) these synthetic images are accompanied by perfect ground truth positions of cells, meaning no data curation is required; (3) different biological conditions, imaging platforms, and imaging modalities can be rapidly simulated, meaning any change in one's experimental setup no longer requires the laborious process of manually generating new training data for each change. Deep-learning models trained with SyMBac data are capable of analysing data from various imaging platforms and are robust to drastic changes in cell size and morphology. Our benchmarking results demonstrate that models trained on SyMBac data generate more accurate cell identifications and precise cell masks than those trained on human-annotated data, because the model learns the true position of the cell irrespective of imaging artefacts. We illustrate the approach by analysing the growth and size regulation of bacterial cells during entry and exit from dormancy, which revealed novel insights about the physiological dynamics of cells under various growth conditions.

CONCLUSIONS

The SyMBac approach will help to adapt and improve the performance of deep-learning-based image segmentation models for accurate processing of high-throughput timelapse image data.

Steady-State Operation of a Cell-Free Genetic Band-Detection Circuit

Pattern formation processes play a decisive role during embryogenesis and involve the precise spatial and temporal orchestration of intricate gene regulatory processes. Synthetic gene circuits modeled after their biological counterparts can be used to investigate such processes under well-controlled conditions and may, in the future, be utilized for autonomous position determination in synthetic biological materials. Here, we investigated a three-node feed-forward gene regulatory circuit in vitro that generates three distinct fluorescent outputs in response to varying concentrations of a single externally supplied morphogen. The circuit acts as a band detector for the morphogen concentration and, in a spatial context, could serve as a stripe-forming gene circuit. We simulated the behavior of the genetic circuit in the presence of a morphogen gradient using a system of ordinary differential equations and determined optimal parameters for stripe-pattern formation using an evolutionary algorithm. To analyze the subcircuits of the system, we conducted cell-free characterization experiments and finally tested the whole genetic circuit in nanoliter-scale microfluidic flow reactors that provided a continuous supply of cell extract and metabolites and allowed removal of degradation products. To make use of the widely employed promoters P_LlacO-1 and P_LtetO-1 in our design, we removed LacI from our bacterial cell extract by genome engineering Escherichia coli using a pORTMAGE workflow. Our results show that the band-detector works as designed when operated out of equilibrium within the flow reactors. On the other hand, subcircuits of the system and the whole circuit fail to generate the desired gene expression response when operated in a closed reactor. Our work thus underlines the importance of out-of-equilibrium operation of complex gene circuits, which cannot settle to a steady-state expression pattern within the finite lifetime of a cell-free expression system.

Microfluidics for long-term single-cell time-lapse microscopy: Advances and applications

Cells are inherently dynamic, whether they are responding to environmental conditions or simply at equilibrium, with biomolecules constantly being made and destroyed. Due to their small volumes, the chemical reactions inside cells are stochastic, such that genetically identical cells display heterogeneous behaviors and gene expression profiles. Studying these dynamic processes is challenging, but the development of microfluidic methods enabling the tracking of individual prokaryotic cells with microscopy over long time periods under controlled growth conditions has led to many discoveries. This review focuses on the recent developments of one such microfluidic device nicknamed the mother machine. We overview the original device design, experimental setup, and challenges associated with this platform. We then describe recent methods for analyzing experiments using automated image segmentation and tracking. We further discuss modifications to the experimental setup that allow for time-varying environmental control, replicating batch culture conditions, cell screening based on their dynamic behaviors, and to accommodate a variety of microbial species. Finally, this review highlights the discoveries enabled by this technology in diverse fields, such as cell-size control, genetic mutations, cellular aging, and synthetic biology.

Effects of DNA template preparation on variability in cell-free protein production

DNA templates for protein production remain an unexplored source of variability in the performance of cell-free expression (CFE) systems. To characterize this variability, we investigated the effects of two common DNA extraction methodologies, a postprocessing step and manual versus automated preparation on protein production using CFE. We assess the concentration of the DNA template, the quality of the DNA template in terms of physical damage and the quality of the DNA solution in terms of purity resulting from eight DNA preparation workflows. We measure the variance in protein titer and rate of protein production in CFE reactions associated with the biological replicate of the DNA template, the technical replicate DNA solution prepared with the same workflow and the measurement replicate of nominally identical CFE reactions. We offer practical guidance for preparing and characterizing DNA templates to achieve acceptable variability in CFE performance.

Variability in cell-free expression reactions can impact qualitative genetic circuit characterization

Cell-free expression systems provide a suite of tools that are used in applications from sensing to biomanufacturing. One of these applications is genetic circuit prototyping, where the lack of cloning is required and a high degree of control over reaction components and conditions enables rapid testing of design candidates. Many studies have shown utility in the approach for characterizing genetic regulation elements, simple genetic circuit motifs, protein variants or metabolic pathways. However, variability in cell-free expression systems is a known challenge, whether between individuals, laboratories, instruments, or batches of materials. While the issue of variability has begun to be quantified and explored, little effort has been put into understanding the implications of this variability. For genetic circuit prototyping, it is unclear when and how significantly variability in reaction activity will impact qualitative assessments of genetic components, e.g. relative activity between promoters. Here, we explore this question by assessing DNA titrations of seven genetic circuits of increasing complexity using reaction conditions that ostensibly follow the same protocol but vary by person, instrument and material batch. Although the raw activities vary widely between the conditions, by normalizing within each circuit across conditions, reasonably consistent qualitative performance emerges for the simpler circuits. For the most complex case involving expression of three proteins, we observe a departure from this qualitative consistency, offering a provisional cautionary line where normal variability may disrupt reliable reuse of prototyping results. Our results also suggest that a previously described closed loop controller circuit may help to mitigate such variability, encouraging further work to design systems that are robust to variability. Graphical Abstract.

Characterizing a New Fluorescent Protein for a Low Limit of Detection Sensing in the Cell-Free System

Cell-free protein synthesis-based biosensors have been developed as highly accurate, low-cost biosensors. However, since most biomarkers exist at low concentrations in various types of biopsies, the biosensor's dynamic range must be increased in the system to achieve low limits of detection necessary while deciphering from higher background signals. Many attempts to increase the dynamic range have relied on amplifying the input signal from the analyte, which can lead to complications of false positives. In this study, we aimed to increase the protein synthesis capability of the cell-free protein synthesis system and the output signal of the reporter protein to achieve a lower limit of detection. We utilized a new fluorescent protein, mNeonGreen, which produces a higher output than those commonly used in cell-free biosensors. Optimizations of DNA sequence and the subsequent cell-free protein synthesis reaction conditions allowed characterizing protein expression variability by given DNA template types, reaction environment, and storage additives that cause the greatest time constraint on designing the cell-free biosensor. Finally, we characterized the fluorescence kinetics of mNeonGreen compared to the commonly used reporter protein, superfolder green fluorescent protein. We expect that this finely tuned cell-free protein synthesis platform with the new reporter protein can be used with sophisticated synthetic gene circuitry networks to increase the dynamic range of a cell-free biosensor to reach lower detection limits and reduce the false-positive proportion.

Biochemistry of Aminoacyl tRNA Synthetase and tRNAs and Their Engineering for Cell-Free and Synthetic Cell Applications

Cell-free biology is increasingly utilized for engineering biological systems, incorporating novel functionality, and circumventing many of the complications associated with cells. The central dogma describes the information flow in biology consisting of transcription and translation steps to decode genetic information. Aminoacyl tRNA synthetases (AARSs) and tRNAs are key components involved in translation and thus protein synthesis. This review provides information on AARSs and tRNA biochemistry, their role in the translation process, summarizes progress in cell-free engineering of tRNAs and AARSs, and discusses prospects and challenges lying ahead in cell-free engineering.

A microfluidic optimal experimental design platform for forward design of cell-free genetic networks

Cell-free protein synthesis has been widely used as a “breadboard” for design of synthetic genetic networks. However, due to a severe lack of modularity, forward engineering of genetic networks remains challenging. Here, we demonstrate how a combination of optimal experimental design and microfluidics allows us to devise dynamic cell-free gene expression experiments providing maximum information content for subsequent non-linear model identification. Importantly, we reveal that applying this methodology to a library of genetic circuits, that share common elements, further increases the information content of the data resulting in higher accuracy of model parameters. To show modularity of model parameters, we design a pulse decoder and bistable switch, and predict their behaviour both qualitatively and quantitatively. Finally, we update the parameter database and indicate that network topology affects parameter estimation accuracy. Utilizing our methodology provides us with more accurate model parameters, a necessity for forward engineering of complex genetic networks.

Characterization of cell-free genetic networks is inherently difficult. Here the authors use optimal experimental design and microfluidics to improve characterization, demonstrating modularity and predictability of parts in applied test cases.

Complex dynamics in a synchronized cell-free genetic clock

Complex dynamics such as period doubling and chaos occur in a wide variety of non-linear dynamical systems. In the context of biological circadian clocks, such phenomena have been previously found in computational models, but their experimental study in biological systems has been challenging. Here, we present experimental evidence of period doubling in a forced cell-free genetic oscillator operated in a microfluidic reactor, where the system is periodically perturbed by modulating the concentration of one of the oscillator components. When the external driving matches the intrinsic period, we experimentally find period doubling and quadrupling in the oscillator dynamics. Our results closely match the predictions of a theoretical model, which also suggests conditions under which our system would display chaotic dynamics. We show that detuning of the external and intrinsic period leads to more stable entrainment, suggesting a simple design principle for synchronized synthetic and natural genetic clocks.

In theory, driven biological oscillators can display complex dynamic behaviors, but these are experimentally difficult to observe. Here the authors, using microfluidics, show that a synthetic cell-free gene oscillator displays period doubling and even quadrupling.

Combined multiple transcriptional repression mechanisms generate ultrasensitivity and oscillations

Transcriptional repression can occur via various mechanisms, such as blocking, sequestration and displacement. For instance, the repressors can hold the activators to prevent binding with DNA or can bind to the DNA-bound activators to block their transcriptional activity. Although the transcription can be completely suppressed with a single mechanism, multiple repression mechanisms are used together to inhibit transcriptional activators in many systems, such as circadian clocks and NF-κB oscillators. This raises the question of what advantages arise if seemingly redundant repression mechanisms are combined. Here, by deriving equations describing the multiple repression mechanisms, we find that their combination can synergistically generate a sharply ultrasensitive transcription response and thus strong oscillations. This rationalizes why the multiple repression mechanisms are used together in various biological oscillators. The critical role of such combined transcriptional repression for strong oscillations is further supported by our analysis of formerly identified mutations disrupting the transcriptional repression of the mammalian circadian clock. The hitherto unrecognized source of the ultrasensitivity, the combined transcriptional repressions, can lead to robust synthetic oscillators with a previously unachievable simple design.

Programmable Fusion and Differentiation of Synthetic Minimal Cells

Synthetic cells can mimic the intricate complexities of live cells, while mitigating the level of noise that is present natural systems; however, many crucial processes still need to be demonstrated in synthetic cells to use them to comprehensively study and engineer biology. Here we demonstrate key functionalities of synthetic cells previously available only to natural life: differentiation and mating. This work presents a toolset for engineering combinatorial genetic circuits in synthetic cells. We demonstrate how progenitor populations can differentiate into new lineages in response to small molecule stimuli or as a result of fusion, and we provide practical demonstration of utility for metabolic engineering. This work provides a tool for bioengineering and for natural pathway studies, as well as paving the way toward the construction of live artificial cells.

Cell-Free Gene Expression Dynamics in Synthetic Cell Populations

The ability to build synthetic cellular populations from the bottom-up provides the groundwork to realize minimal living tissues comprising single cells which can communicate and bridge scales into multicellular systems. Engineered systems made of synthetic micron-sized compartments and integrated reaction networks coupled with mathematical modeling can facilitate the design and construction of complex and multiscale chemical systems from the bottom-up. Toward this goal, we generated populations of monodisperse liposomes encapsulating cell-free expression systems (CFESs) using double-emulsion microfluidics and quantified transcription and translation dynamics within individual synthetic cells of the population using a fluorescent Broccoli RNA aptamer and mCherry protein reporter. CFE dynamics in bulk reactions were used to test different coarse-grained resource-limited gene expression models using model selection to obtain transcription and translation rate parameters by likelihood-based parameter estimation. The selected model was then applied to quantify cell-free gene expression dynamics in populations of synthetic cells. In combination, our experimental and theoretical approaches provide a statistically robust analysis of CFE dynamics in bulk and monodisperse synthetic cell populations. We demonstrate that compartmentalization of CFESs leads to different transcription and translation rates compared to bulk CFE and show that this is due to the semipermeable lipid membrane that allows the exchange of materials between the synthetic cells and the external environment.

Best Practices for DNA Template Preparation Toward Improved Reproducibility in Cell-Free Protein Production

Performance variability is a common challenge in cell-free protein production and hinders a wider adoption of these systems for both research and biomanufacturing. While the inherent stochasticity and complexity of biology likely contributes to variability, other systematic factors may also play a role, including the source and preparation of the cell extract, the composition of the supplemental reaction buffer, the facility at which experiments are conducted, and the human operator (Cole et al. ACS Synth Biol 8:2080-2091, 2019). Variability in protein production could also arise from differences in the DNA template-specifically the amount of functional DNA added to a cell-free reaction and the quality of the DNA preparation in terms of contaminants and strand breakage. Here, we present protocols and suggest best practices optimized for DNA template preparation and quantitation for cell-free systems toward reducing variability in cell-free protein production.

Identification, visualization, statistical analysis and mathematical modeling of high-feedback loops in gene regulatory networks

Background

Feedback loops in gene regulatory networks play pivotal roles in governing functional dynamics of cells. Systems approaches demonstrated characteristic dynamical features, including multistability and oscillation, of positive and negative feedback loops. Recent experiments and theories have implicated highly interconnected feedback loops (high-feedback loops) in additional nonintuitive functions, such as controlling cell differentiation rate and multistep cell lineage progression. However, it remains challenging to identify and visualize high-feedback loops in complex gene regulatory networks due to the myriad of ways in which the loops can be combined. Furthermore, it is unclear whether the high-feedback loop structures with these potential functions are widespread in biological systems. Finally, it remains challenging to understand diverse dynamical features, such as high-order multistability and oscillation, generated by individual networks containing high-feedback loops. To address these problems, we developed HiLoop, a toolkit that enables discovery, visualization, and analysis of several types of high-feedback loops in large biological networks.

Results

HiLoop not only extracts high-feedback structures and visualize them in intuitive ways, but also quantifies the enrichment of overrepresented structures. Through random parameterization of mathematical models derived from target networks, HiLoop presents characteristic features of the underlying systems, including complex multistability and oscillations, in a unifying framework. Using HiLoop, we were able to analyze realistic gene regulatory networks containing dozens to hundreds of genes, and to identify many small high-feedback systems. We found more than a 100 human transcription factors involved in high-feedback loops that were not studied previously. In addition, HiLoop enabled the discovery of an enrichment of high feedback in pathways related to epithelial-mesenchymal transition.

Conclusions

HiLoop makes the study of complex networks accessible without significant computational demands. It can serve as a hypothesis generator through identification and modeling of high-feedback subnetworks, or as a quantification method for motif enrichment analysis. As an example of discovery, we found that multistep cell lineage progression may be driven by either specific instances of high-feedback loops with sparse appearances, or generally enriched topologies in gene regulatory networks. We expect HiLoop’s usefulness to increase as experimental data of regulatory networks accumulate. Code is freely available for use or extension at https://github.com/BenNordick/HiLoop.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04405-z.

Chaos-hyperchaos transition in three identical quorum-sensing mean-field coupled ring oscillators

We investigate the dynamics of three identical three-dimensional ring synthetic genetic oscillators (repressilators) located in different cells and indirectly globally coupled by quorum sensing whereby it is meant that a mechanism in which special signal molecules are produced that, after the fast diffusion mixing and partial dilution in the environment, activate the expression of a target gene, which is different from the gene responsible for their production. Even at low coupling strengths, quorum sensing stimulates the formation of a stable limit cycle, known in the literature as a rotating wave (all variables have identical waveforms shifted by one third of the period), which, at higher coupling strengths, converts to complex tori. Further torus evolution is traced up to its destruction to chaos and the appearance of hyperchaos. We hypothesize that hyperchaos is the result of merging the saddle-focus periodic orbit (or limit cycle) corresponding to the rotating wave regime with chaos and present considerations in favor of this conclusion.

Cut the noise or couple up: Coordinating circadian and synthetic clocks

Circadian clocks are important to much of life on Earth and are of inherent interest to humanity, implicated in fields ranging from agriculture and ecology to developmental biology and medicine. New techniques show that it is not simply the presence of clocks, but coordination between them that is critical for complex physiological processes across the kingdoms of life. Recent years have also seen impressive advances in synthetic biology to the point where parallels can be drawn between synthetic biological and circadian oscillators. This review will emphasize theoretical and experimental studies that have revealed a fascinating dichotomy of coupling and heterogeneity among circadian clocks. We will also consolidate the fields of chronobiology and synthetic biology, discussing key design principles of their respective oscillators.

Decentralizing Cell-Free RNA Sensing With the Use of Low-Cost Cell Extracts

Cell-free gene expression systems have emerged as a promising platform for field-deployed biosensing and diagnostics. When combined with programmable toehold switch-based RNA sensors, these systems can be used to detect arbitrary RNAs and freeze-dried for room temperature transport to the point-of-need. These sensors, however, have been mainly implemented using reconstituted PURE cell-free protein expression systems that are difficult to source in the Global South due to their high commercial cost and cold-chain shipping requirements. Based on preliminary demonstrations of toehold sensors working on lysates, we describe the fast prototyping of RNA toehold switch-based sensors that can be produced locally and reduce the cost of sensors by two orders of magnitude. We demonstrate that these in-house cell lysates provide sensor performance comparable to commercial PURE cell-free systems. We further optimize these lysates with a CRISPRi strategy to enhance the stability of linear DNAs by knocking-down genes responsible for linear DNA degradation. This enables the direct use of PCR products for fast screening of new designs. As a proof-of-concept, we develop novel toehold sensors for the plant pathogen Potato Virus Y (PVY), which dramatically reduces the yield of this important staple crop. The local implementation of low-cost cell-free toehold sensors could enable biosensing capacity at the regional level and lead to more decentralized models for global surveillance of infectious disease.

The all-E. coliTXTL toolbox 3.0: new capabilities of a cell-free synthetic biology platform

The new generation of cell-free gene expression systems enables the prototyping and engineering of biological systems in vitro over a remarkable scope of applications and physical scales. As the utilization of DNA-directed in vitro protein synthesis expands in scope, developing more powerful cell-free transcription-translation (TXTL) platforms remains a major goal to either execute larger DNA programs or improve cell-free biomanufacturing capabilities. In this work, we report the capabilities of the all-E. coli TXTL toolbox 3.0, a multipurpose cell-free expression system specifically developed for synthetic biology. In non-fed batch-mode reactions, the synthesis of the fluorescent reporter protein eGFP (enhanced green fluorescent protein) reaches 4 mg/ml. In synthetic cells, consisting of liposomes loaded with a TXTL reaction, eGFP is produced at concentrations of >8 mg/ml when the chemical building blocks feeding the reaction diffuse through membrane channels to facilitate exchanges with the outer solution. The bacteriophage T7, encoded by a genome of 40 kb and ∼60 genes, is produced at a concentration of 1013 PFU/ml (plaque forming unit/ml). This TXTL system extends the current cell-free expression capabilities by offering unique strength and properties, for testing regulatory elements and circuits, biomanufacturing biologics or building synthetic cells.

Towards a physical understanding of developmental patterning

The temporal coordination of events at cellular and tissue scales is essential for the proper development of organisms, and involves cell-intrinsic processes that can be coupled by local cellular signalling and instructed by global signalling, thereby creating spatial patterns of cellular states that change over time. The timing and structure of these patterns determine how an organism develops. Traditional developmental genetic methods have revealed the complex molecular circuits regulating these processes but are limited in their ability to predict and understand the emergent spatio-temporal dynamics. Increasingly, approaches from physics are now being used to help capture the dynamics of the system by providing simplified, generic descriptions. Combined with advances in imaging and computational power, such approaches aim to provide insight into timing and patterning in developing systems.

Effective Use of Linear DNA in Cell-Free Expression Systems

Cell-free expression systems (CFEs) are cutting-edge research tools used in the investigation of biological phenomena and the engineering of novel biotechnologies. While CFEs have many benefits over in vivo protein synthesis, one particularly significant advantage is that CFEs allow for gene expression from both plasmid DNA and linear expression templates (LETs). This is an important and impactful advantage because functional LETs can be efficiently synthesized in vitro in a few hours without transformation and cloning, thus expediting genetic circuit prototyping and allowing expression of toxic genes that would be difficult to clone through standard approaches. However, native nucleases present in the crude bacterial lysate (the basis for the most affordable form of CFEs) quickly degrade LETs and limit expression yield. Motivated by the significant benefits of using LETs in lieu of plasmid templates, numerous methods to enhance their stability in lysate-based CFEs have been developed. This review describes approaches to LET stabilization used in CFEs, summarizes the advancements that have come from using LETs with these methods, and identifies future applications and development goals that are likely to be impactful to the field. Collectively, continued improvement of LET-based expression and other linear DNA tools in CFEs will help drive scientific discovery and enable a wide range of applications, from diagnostics to synthetic biology research tools.

Cell-Free Characterization of Coherent Feed-Forward Loop-Based Synthetic Genetic Circuits

Regulatory pathways inside living cells employ feed-forward architectures to fulfill essential signal processing functions that aid in the interpretation of various types of inputs through noise-filtering, fold-change detection and adaptation. Although it has been demonstrated computationally that a coherent feed-forward loop (CFFL) can function as noise filter, a property essential to decoding complex temporal signals, this motif has not been extensively characterized experimentally or integrated into larger networks. Here we use post-transcriptional regulation to implement and characterize a synthetic CFFL in an Escherichia coli cell-free transcription-translation system and build larger composite feed-forward architectures. We employ microfluidic flow reactors to probe the response of the CFFL circuit using both persistent and short, noise-like inputs and analyze the influence of different circuit components on the steady-state and dynamics of the output. We demonstrate that our synthetic CFFL implementation can reliably repress background activity compared to a reference circuit, but displays low potential as a temporal filter, and validate these findings using a computational model. Our results offer practical insight into the putative noise-filtering behavior of CFFLs and show that this motif can be used to mitigate leakage and increase the fold-change of the output of synthetic genetic circuits.

Increasing MinD's Membrane Affinity Yields Standing Wave Oscillations and Functional Gradients on Flat Membranes

The formation of large-scale patterns through molecular self-organization is a basic principle of life. Accordingly, the engineering of protein patterns and gradients is of prime relevance for synthetic biology. As a paradigm for such pattern formation, the bacterial MinDE protein system is based on self-organization of the ATPase MinD and ATPase-activating protein MinE on lipid membranes. Min patterns can be tightly regulated by tuning physical or biochemical parameters. Among the biochemically engineerable modules, MinD's membrane targeting sequence, despite being a key regulating element, has received little attention. Here we attempt to engineer patterns by modulating the membrane affinity of MinD. Unlike the traveling waves or stationary patterns commonly observed in vitro on flat supported membranes, standing-wave oscillations emerge upon elongating MinD's membrane targeting sequence via rationally guided mutagenesis. These patterns are capable of forming gradients and thereby spatially target co-reconstituted downstream proteins, highlighting their functional potential in designing new life-like systems.

Applications of Bacterial Degrons and Degraders - Toward Targeted Protein Degradation in Bacteria

A repertoire of proteolysis-targeting signals known as degrons is a necessary component of protein homeostasis in every living cell. In bacteria, degrons can be used in place of chemical genetics approaches to interrogate and control protein function. Here, we provide a comprehensive review of synthetic applications of degrons in targeted proteolysis in bacteria. We describe recent advances ranging from large screens employing tunable degradation systems and orthogonal degrons, to sophisticated tools and sensors for imaging. Based on the success of proteolysis-targeting chimeras as an emerging paradigm in cancer drug discovery, we discuss perspectives on using bacterial degraders for studying protein function and as novel antimicrobials.

Degradation study on molecules released from laser-based jet injector

Development of needle-free methods to administer injectable therapeutics has been researched for a few decades. We focused our attention on a laser-based jet injection technique where the liquid-jet actuation mechanism is based on optical cavitation. This study investigates the potential damage to therapeutic molecules which are exposed to nanosecond laser pulses in the configuration of a compact laser-based jet injection device. Implementation of a pulsed laser source at 1574 nm wavelength allowed us to generate jets from pure water solutions and circumvent the need to reformulate therapeutics with absorbing dyes. We performed H1-NMR analysis on exposed samples of Lidocaine and δ-Aminolevulinic acid. We made several tests with linear and plasmid DNA to assess the structural integrity and functional potency after ejection with our device. The tests showed no significant degradation or detectable side products, which is promising for further development and eventually clinical applications.

Synthetic logic circuits using RNA aptamer against T7 RNA polymerase

Recent advances in nucleic acids engineering introduced several RNA-based regulatory components for synthetic gene circuits, expanding the toolsets to engineer organisms. In this work, we designed genetic circuits implementing an RNA aptamer previously described to have the capability of binding to the T7 RNA polymerase and inhibiting its activity in vitro. We first demonstrated the utility of the RNA aptamer in combination with programmable synthetic transcription networks in vitro. As a step to quickly assess the feasibility of aptamer functions in vivo, we tested the aptamer and its sequence variants in the cell-free expression system, verifying the aptamer functionality in the cell-free testbed. The expression of aptamer in E. coli demonstrated control over GFP expression driven by T7 RNA polymerase, indicating its ability to serve as building blocks for logic circuits and transcriptional cascades. This work elucidates the potential of T7 RNA polymerase aptamer as regulators for synthetic biological circuits and metabolic engineering.

Small Antisense DNA-Based Gene Silencing Enables Cell-Free Bacteriophage Manipulation and Genome Replication

Cell-free systems allow interference with gene expression processes without requiring elaborate genetic engineering procedures. This makes it ideally suited for rapid prototyping of synthetic biological parts. Inspired by nature's strategies for the control of gene expression via short antisense RNA molecules, we here investigated the use of small DNA (sDNA) for translational inhibition in the context of cell-free protein expression. We designed sDNA molecules to be complementary to the ribosome binding site (RBS) and the downstream coding sequence of targeted mRNA molecules. Depending on sDNA concentration and the promoter used for transcription of the mRNA, this resulted in a reduction of gene expression of targeted genes by up to 50-fold. We applied the cell-free sDNA technique (CF-sDNA) to modulate cell-free gene expression from the native T7 phage genome by suppressing the production of the major capsid protein of the phage. This resulted in a reduced phage titer, but at the same time drastically improved cell-free replication of the phage genome, which we utilized to amplify the T7 genome by more than 15 000-fold in a droplet-based serial dilution experiment. Our simple antisense sDNA approach extends the possibilities to exert translational control in cell-free expression systems, which should prove useful for cell-free prototyping of native phage genomes and also cell-free phage manipulation.

Harnessing the central dogma for stringent multi-level control of gene expression

Strictly controlled inducible gene expression is crucial when engineering biological systems where even tiny amounts of a protein have a large impact on function or host cell viability. In these cases, leaky protein production must be avoided, but without affecting the achievable range of expression. Here, we demonstrate how the central dogma offers a simple solution to this challenge. By simultaneously regulating transcription and translation, we show how basal expression of an inducible system can be reduced, with little impact on the maximum expression rate. Using this approach, we create several stringent expression systems displaying >1000-fold change in their output after induction and show how multi-level regulation can suppress transcriptional noise and create digital-like switches between ‘on’ and ‘off’ states. These tools will aid those working with toxic genes or requiring precise regulation and propagation of cellular signals, plus illustrate the value of more diverse regulatory designs for synthetic biology.

Inducible gene expression systems should minimise leaky output and offer a large achievable range of expression. Here, the authors regulate transcription and translation together to suppress noise and create digital-like responses, while maintaining a large expression range in vivo and in vitro.

Boundary-Free Ribosome Compartmentalization by Gene Expression on a Surface

The design of artificial cell models based on minimal surface-bound transcription-translation reactions aims to mimic the compartmentalization facilitated by organelles and inner interfaces in living cells. Dense DNA brushes as localized sources of RNA and proteins serve as synthetic operons that have recently proven useful for the autonomous synthesis and assembly of cellular machines. Here, we studied ribosome compartmentalization in a minimal gene-expression reaction on a surface in contact with a macroscopic reservoir. We first observed the accumulation and colocalization of RNA polymerases, ribosomes, nascent RNAs and proteins, in dense DNA brushes using evanescent field fluorescence, showing transcription-translation coupling in the brush. Fluorescence recovery after photobleaching showed that ribosomes engaged in translation in the brush had a 4-fold slower diffusion constant. In addition, ribosomes in the brush had over a 10-fold higher local concentration relative to free ribosomes, creating a boundary-free functional ribosome-rich compartment. To decouple translation from transcription, we immobilized dense phases of ribosomes next to DNA brushes. We demonstrated that immobilized ribosomes were capable of protein synthesis, forming 2D subcompartments of active ribosome patterns induced and regulated by DNA brush layout of coding and inhibitory genes. Localizing additional molecular components on the surface will further compartmentalize gene-expression reactions.

CFPU: A Cell-Free Processing Unit for High-Throughput, Automated In Vitro Circuit Characterization in Steady-State Conditions

Forward engineering synthetic circuits are at the core of synthetic biology. Automated solutions will be required to facilitate circuit design and implementation. Circuit design is increasingly being automated with design software, but innovations in experimental automation are lagging behind. Microfluidic technologies made it possible to perform in vitro transcription-translation (tx-tl) reactions with increasing throughput and sophistication, enabling screening and characterization of individual circuit elements and complete circuit designs. Here, we developed an automated microfluidic cell-free processing unit (CFPU) that extends high-throughput screening capabilities to a steady-state reaction environment, which is essential for the implementation and analysis of more complex and dynamic circuits. The CFPU contains 280 chemostats that can be individually programmed with DNA circuits. Each chemostat is periodically supplied with tx-tl reagents, giving rise to sustained, long-term steady-state conditions. Using microfluidic pulse width modulation (PWM), the device is able to generate tx-tl reagent compositions in real time. The device has higher throughput, lower reagent consumption, and overall higher functionality than current chemostat devices. We applied this technology to map transcription factor-based repression under equilibrium conditions and implemented dynamic gene circuits switchable by small molecules. We expect the CFPU to help bridge the gap between circuit design and experimental automation for in vitro development of synthetic gene circuits.

A MATLAB toolbox for modeling genetic circuits in cell-free systems

We introduce a MATLAB-based simulation toolbox, called txtlsim, for an Escherichia coli-based Transcription-Translation (TX-TL) system. This toolbox accounts for several cell-free-related phenomena, such as resource loading, consumption and degradation, and in doing so, models the dynamics of TX-TL reactions for the entire duration of solution phase batch-mode experiments. We use a Bayesian parameter inference approach to characterize the reaction rate parameters associated with the core transcription, translation and mRNA degradation mechanics of the toolbox, allowing it to reproduce constitutive mRNA and protein-expression trajectories. We demonstrate the use of this characterized toolbox in a circuit behavior prediction case study for an incoherent feed-forward loop.

Using Models to (Re-)Design Synthetic Circuits

Mathematical models play an important role in the design of synthetic gene circuits, by guiding the choice of biological components and their assembly into novel gene networks. Here, we present a guide for biologists to build and utilize models of gene networks (synthetic or natural) to analyze dynamical properties of these networks while considering the low numbers of molecules inside cells that results in stochastic gene expression. We start by describing how to write down a model and discussing the level of details to include. We then briefly demonstrate how to simulate a network's dynamics using deterministic differential equations that assume high numbers of molecules. To consider the role of stochastic gene expression in single cells, we provide a detailed tutorial on running stochastic Gillespie simulations of a network, including instructions on coding the Gillespie algorithm with example code. Finally, we illustrate how using a combination of quantitative experimental characterization of a synthetic circuit and mathematical modeling can guide the iterative redesign of a synthetic circuit to achieve the desired properties. This is shown using a classic synthetic oscillator, the repressilator, which we recently redesigned into the most precise and robust synthetic oscillator to date. We thus provide a toolkit for synthetic biologists to build more precise and robust synthetic circuits, which should lead to a deeper understanding of the dynamics of gene regulatory networks.

Steady-State Cell-Free Gene Expression with Microfluidic Chemostats

Cell-free synthetic biology offers an approach to building and testing gene circuits in a simplified environment free from the complexity of a living cell. Recent advances in microfluidic devices allowed cell-free reactions to run under nonequilibrium, steady-state conditions enabling the implementation of dynamic gene regulatory circuits in vitro. In this chapter, we present a detailed protocol to fabricate a microfluidic chemostat device which enables such an operation, detailing essential steps in photolithography, soft lithography, and hardware setup.

Single Cell Characterization of a Synthetic Bacterial Clock with a Hybrid Feedback Loop Containing dCas9-sgRNA

Genetic networks that generate oscillations in gene expression activity are found in a wide range of organisms throughout all kingdoms of life. Oscillatory dynamics facilitates the temporal orchestration of metabolic and growth processes inside cells and organisms, as well as the synchronization of such processes with periodically occurring changes in the environment. Synthetic oscillator gene circuits such as the "repressilator" can perform similar functions in bacteria. Until recently, such circuits were mainly based on a relatively small set of well-characterized transcriptional repressors and activators. A promising, sequence-programmable alternative for gene regulation is given by CRISPR interference (CRISPRi), which enables transcriptional repression of nearly arbitrary gene targets directed by short guide RNA molecules. In order to demonstrate the use of CRISPRi in the context of dynamic gene circuits, we here replaced one of the nodes of a repressilator circuit by the RNA-guided dCas9 protein. Using single cell experiments in microfluidic reactors we show that this system displays robust relaxation oscillations over multiple periods and over several days. With a period of ≈14 bacterial generations, our oscillator is similar in speed as previously reported oscillators. Using an information-theoretic approach for the analysis of the single cell data, the potential of the circuit to act as a synthetic pacemaker for cellular processes is evaluated. We also observe that the oscillator appears to affect cellular growth, leading to variations in growth rate with the oscillator's frequency.