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Fighting the battle against evolution: designing genetically modified organisms for evolutionary stability
Abstract
Synthetic biology has made significant progress in many areas, but a major challenge that has received limited attention is the evolutionary stability of synthetic constructs made of heterologous genes. The expression of these constructs in microorganisms, that is, production of proteins that are not necessary for the organism, is a metabolic burden, leading to a decrease in relative fitness and make the synthetic constructs unstable over time. This is a significant concern for the synthetic biology community, particularly when it comes to bringing this technology out of the laboratory. In this review, we discuss the issue of evolutionary stability in synthetic biology and review the available tools to address this challenge.
... When engineered bacteria with synthetic biology designs are used in natural environments, their engineered functions can be lost rapidly due to genetic instability or can be horizontally acquired by native bacteria (Kumar and Hasty, 2023). One strategy to prolong the desired function and limit horizontal gene transfer (HGT) is to design two genes in overlapping reading frames, referred to as "gene entanglement", which can be partial or complete (Arbel-Groissman et al., 2023). An example of the partial approach is when the two reading frames overlap, but not the actual coding sequences of the corresponding pair of proteins (Decrulle et al., 2021). ...
... More recently, an effort was made to distribute CAMEOS in a virtual machine to expand accessibility to the original software (Logel and Jaschke, 2023). Nevertheless, the original code remains limited in the ability to efficiently evaluate new gene pairs (Arbel-Groissman et al., 2023). To automate the entire process of gene entanglement, enhance its computational scalability, improve software portability, and add new functional and analysis capabilities, we developed GENTANGLE, a computational biology pipeline built around CAMEOX (CAMEOs eXtended), an enhanced, parallelized version of CAMEOS that we release as part of GENTANGLE. ...
The design of two overlapping genes in a microbial genome is an emerging technique for adding more reliable control mechanisms in engineered organisms for increased safety. The design of functional gene pairs is a challenging procedure and computational design tools are used to improve the efficiency to deploy successful designs in genetically engineered systems. GENTANGLE (Gene Tuples ArraNGed in overLapping Elements) is a high performance containerized pipeline for the computational design of two overlapping genes translated in different reading frames of the genome. This new software package can be used to design and test gene entanglements for microbial engineering projects using arbitrary sets of user specified gene pairs.
Availability and Implementation
The GENTANGLE source code and its submodules are freely available on GitHub at https://github.com/BiosecSFA/gentangle . The DATANGLE (DATA for genTANGLE) repository contains related data and results, and is freely available on GitHub at https://github.com/BiosecSFA/datangle . The GENTANGLE repository wiki contains detailed instructions on how to use the container and the different components of software and data, including reproducing the results. The code is licensed under the GNU Affero General Public License version 3 ( https://www.gnu.org/licenses/agpl.html ).
Contact
martimartine1@llnl.gov and allen99@llnl.gov
... Additionally, allele segregation issues arise when non-productive plasmids outcompete productive ones, leading to a population of cells that do not contribute to the desired product yield. These factors collectively result in reduced productivity and reliability, undermining the feasibility of large-scale production [4][5][6][7]. Therefore, integrating and expressing the target gene in the genome is preferred for industrial-scale fermentation. ...
Strengthening the expression level of integrated genes on the genome is crucial for consistently expressing key enzymes in microbial cell factories for efficient bioproduction in synthetic biology. In comparison to plasmid-based multi-copy expression, the utilization of chromosomal multi-copy genes offers increased stability of expression level, diminishes the metabolic burden on host cells, and enhances overall genetic stability. In this study, we developed the “BacAmp”, a stabilized gene integration expression and copy number amplification system for high-level expression in Bacillus subtilis, which was achieved by employing a combination of repressor and non-natural amino acids (ncAA)-dependent expression system to create a reversible switch to control the key gene recA for homologous recombination. When the reversible switch is turned on, genome editing and gene amplification can be achieved. Subsequently, the reversible switch was turned off therefore stabilizing the gene copy number. The stabilized gene amplification system marked by green fluorescent protein, achieved a 3-fold increase in gene expression by gene amplification and maintained the average gene copy number at 10 after 110 generations. When we implemented the gene amplification system for the regulation of N-acetylneuraminic acid (NeuAc) synthesis, the copy number of the critical gene increased to an average of 7.7, which yielded a 1.3-fold NeuAc titer. Our research provides a new avenue for gene expression in synthetic biology and can be applied in metabolic engineering in B. subtilis.
Differentiation is crucial for multicellularity. However, it is inherently susceptible to mutant cells that fail to differentiate. These mutants outcompete normal cells by excessive self-renewal. It remains unclear what mechanisms can resist such mutant expansion. Here, we demonstrate a solution by engineering a synthetic differentiation circuit in Escherichia coli that selects against these mutants via a biphasic fitness strategy. The circuit provides tunable production of synthetic analogs of stem, progenitor, and differentiated cells. It resists mutations by coupling differentiation to the production of an essential enzyme, thereby disadvantaging non-differentiating mutants. The circuit selected for and maintained a positive differentiation rate in long-term evolution. Surprisingly, this rate remained constant across vast changes in growth conditions. We found that transit-amplifying cells (fast-growing progenitors) underlie this environmental robustness. Our results provide insight into the stability of differentiation and demonstrate a powerful method for engineering evolutionarily stable multicellular consortia.
Biodesulfurization is a biotechnological process that employs microorganisms as biocatalysts to remove sulfur from fuels usually at mesophilic conditions, targeting recalcitrant organosulfur compounds without affecting their hydrocarbon structure. One of...
The development of synthetic biological circuits that maintain functionality over application-relevant time scales remains a significant challenge. Here, we employed synthetic overlapping sequences in which one gene is encoded or 'entangled' entirely within an alternative reading frame of another gene. In this design, the toxin-encoding relE was entangled within ilvA, which encodes threonine deaminase, an enzyme essential for isoleucine biosynthesis. A functional entanglement construct was obtained upon modification of the ribosome-binding site of the internal relE gene. Using this optimized design, we found that the selection pressure to maintain functional IlvA stabilized the production of burdensome RelE for >130 generations, which compares favorably with the most stable kill-switch circuits developed to date. This stabilizing effect was achieved through a complete alteration of the allowable landscape of mutations such that mutations inactivating the entangled genes were disfavored. Instead, the majority of lineages accumulated mutations within the regulatory region of ilvA. By reducing baseline relE expression, these more 'benign' mutations lowered circuit burden, which suppressed the accumulation of relE-inactivating mutations, thereby prolonging kill-switch function. Overall, this work demonstrates the utility of sequence entanglement paired with an adaptive laboratory evolution campaign to increase the evolutionary stability of burdensome synthetic circuits.
To elucidate principles operating in native biological systems and to develop novel biotechnologies, synthetic biology aims to build and integrate synthetic gene circuits within native transcriptional networks. The utility of synthetic gene circuits for cell engineering relies on the ability to control the expression of all constituent transgene components. Transgene silencing, defined as the loss of expression over time, persists as an obstacle for engineering primary cells and stem cells with transgenic cargos. In this review, we highlight the challenge that transgene silencing poses to the robust engineering of mammalian cells, outline potential molecular mechanisms of silencing, and present approaches for preventing transgene silencing. We conclude with a perspective identifying future research directions for improving the performance of synthetic gene circuits.
Heterologous gene activation causes non-physiological burden on cellular resources that cells are unable to adjust to. Here, we introduce a feedforward controller that actuates growth rate upon activation of a gene of interest (GOI) to compensate for such a burden. The controller achieves this by activating a modified SpoT enzyme (SpoTH) with sole hydrolysis activity, which lowers ppGpp level and thus increases growth rate. An inducible RelA+ expression cassette further allows to precisely set the basal level of ppGpp, and thus nominal growth rate, in any bacterial strain. Without the controller, activation of the GOI decreased growth rate by more than 50%. With the controller, we could activate the GOI to the same level without growth rate defect. A cell strain armed with the controller in co-culture enabled persistent population-level activation of a GOI, which could not be achieved by a strain devoid of the controller. The feedforward controller is a tunable, modular, and portable tool that allows dynamic gene activation without growth rate defects for bacterial synthetic biology applications. Heterologous gene activation causes non-physiological burden on cellular resources that cells are unable to adjust to. Here the authors present a tunable, modular, and portable feedforward controller that allows dynamic modulation of a genes expression to possibly high-levels without substantially affecting growth rate.
Advances in synthetic biology, bioengineering, and computation allow us to rapidly and reliably program cells with increasingly complex and useful functions. However, because the functions we engineer cells to perform are typically burdensome to cell growth, they can be rapidly lost due to the processes of mutation and natural selection. Here, we show that a strategy of terminal differentiation improves the evolutionary stability of burdensome functions in a general manner by realizing a reproductive and metabolic division of labor. To implement this strategy, we develop a genetic differentiation circuit in Escherichia coli using unidirectional integrase-recombination. With terminal differentiation, differentiated cells uniquely express burdensome functions driven by the orthogonal T7 RNA polymerase, but their capacity to proliferate is limited to prevent the propagation of advantageous loss-of-function mutations that inevitably occur. We demonstrate computationally and experimentally that terminal differentiation increases duration and yield of high-burden expression and that its evolutionary stability can be improved with strategic redundancy. Further, we show this strategy can even be applied to toxic functions. Overall, this study provides an effective, generalizable approach for protecting burdensome engineered functions from evolutionary degradation.
Human enterprises through the solar system will entail long-duration voyages and habitation creating challenges in maintaining healthy diets. We discuss consolidating multiple sensory and nutritional attributes into microorganisms to develop customizable food production systems with minimal inputs, physical footprint, and waste. We envisage that a yeast collection bioengineered for one-carbon metabolism, optimal nutrition, and diverse textures, tastes, aromas, and colors could serve as a flexible food-production platform. Beyond its potential for supporting humans in space, bioengineered microbial-based food could lead to a new paradigm for Earth’s food manufacturing that provides greater self-sufficiency and removes pressure from natural ecosystems.
The production and large-scale application of traditional chemical pesticides will bring environmental pollution and food safety problems. With the advantages of high safety and environmental friendliness, botanical biopesticides are in line with the development trend of modern agriculture and have gradually become the mainstream of modern pesticide development. However, the traditional production of botanical biopesticides has long been faced with prominent problems, such as limited source and supply, complicated production processes, and excessive consumption of resources. In recent years, the rapid development of synthetic biology will break through these bottlenecks, and many botanical biopesticides are produced using synthetic biology, such as emodin, celangulin, etc. This paper reviews the latest progress and application prospect of synthetic biology in the development of botanical pesticides so as to provide new ideas for the analysis of synthetic pathways and heterologous and efficient production of botanical biopesticides and accelerate the research process of synthetic biology of natural products.
Continuous rising anthropogenic sources such as industrialization caused, environmental contamination and health hazards. Approximately 300–400 million tons of industrial waste containing toxic materials, heavy metals, hydrocarbons, and radioactive elements are released into the environment each year without proper treatment. Such dangerous chemicals have mutagenic and cancerous impacts on human health, wildlife, and vegetation when they are released into the environment. Several innovative technical approaches are currently being explored to speed up the clean-up of polluted sites.. Through the all-encompassing activity of microbes, remediation is heavily involved in the deterioration, removal, immobilization, or detoxification of various chemical wastes and physical harmful elements from the surrounding environment. Microbes may thrive in a wide range of conditions and produce metabolites that degrade and convert pollutants, allowing contaminated facilities to be naturally rejuvenated. The focus of this article will be on a microbiological technique that is reportedly employed in pollution monitoring to reduce pollutant concentrations. We investigate the prerequisites for analysing scientific data in order to construct synthetic biological models of microbial bioremediation in this review, which includes studying the prerequisites for developing synthetic biological models of microbial bioremediation. In addition, the importance of microbial technology in bioremediation for the future has been described.
Several viral infectious diseases have appeared limitless since the beginning of the 21st century, expanding into pandemic lengths. Thus, there are extensive efforts to provide more efficient means of diagnosis, a better understanding of acquired immunity, and improved monitoring of inflammatory biomarkers, as these are all crucial for controlling the spread of infection while aiding in vaccine development and improving patient outcomes. In this regard, various biosensors have been developed over the last years to streamline pathogen and immune response detection by addressing the limitations of traditional methods, including isothermal amplification‐based systems and lateral flow assays. This review explores state‐of‐the‐art biosensors for detecting viral pathogens, serological assays, and inflammatory biomarkers from the material perspective, by discussing their advantages, limitations, and further potential regarding their analytical performance, clinical utility, and point‐of‐care adaptability. Additionally, next‐generation biosensing technologies that offer better sensitivity and selectivity, and easy handling for end‐users are highlighted. An emerging example of these next‐generation biosensors are those powered by novel synthetic biology tools, such as clustered regularly interspaced short palindromic repeats (CRISPR) with CRISPR‐associated proteins (Cas), in combination with integrated point‐of‐care devices. Lastly, we discuss the current challenges and provide a roadmap for furthering these advanced biosensing technologies to manage future pandemics.
Many industrial chemicals that are produced from fossil resources could be manufactured more sustainably through fermentation. Here we describe the development of a carbon-negative fermentation route to producing the industrially important chemicals acetone and isopropanol from abundant, low-cost waste gas feedstocks, such as industrial emissions and syngas. Using a combinatorial pathway library approach, we first mined a historical industrial strain collection for superior enzymes that we used to engineer the autotrophic acetogen Clostridium autoethanogenum. Next, we used omics analysis, kinetic modeling and cell-free prototyping to optimize flux. Finally, we scaled-up our optimized strains for continuous production at rates of up to ~3 g/L/h and ~90% selectivity. Life cycle analysis confirmed a negative carbon footprint for the products. Unlike traditional production processes, which result in release of greenhouse gases, our process fixes carbon. These results show that engineered acetogens enable sustainable, high-efficiency, high-selectivity chemicals production. We expect that our approach can be readily adapted to a wide range of commodity chemicals. Two industrial chemicals are sustainably produced at large scale by microbial gas fermentation.
Optimization of metabolism to maximize production of bio-based chemicals must consistently balance cellular resources for biocatalyst growth and desired compound synthesis. This mini-review discusses synthetic biology strategies for dynamically controlling expression of genes to enable dual-phase fermentations in which growth and production are separated into dedicated phases. Emphasis is placed on practical examples which can be reliably scaled to commercial production with the current state of technology. Recent case studies are presented, and recommendations are provided for environmental signals and genetic control circuits.
DNA methylation is a process in which methyl (CH3) groups are added to the DNA molecule. The DNA segment does not change in the sequence, but DNA methylation could alter the action of DNA. Different enzymes like DNA methyltransferases (DNMTs) take part in methylation of cytosine/adenine nucleosides in DNA. In prokaryotes, DNA methylation is performed to prevent the attack of phage and also plays a role in the chromosome replication and repair. In fungi, DNA methylation is studied to see the transcriptional changes, as in insects, the DNA methylation is not that well-known, it plays a different role like other organisms. In mammals, the DNA methylation is related to different types of cancers and plays the most important role in the placental development and abnormal DNA methylation connected with diseases like cancer, autoimmune diseases, and rheumatoid arthritis.
Modern synthetic biology procedures rely on the ability to generate stable genetic constructs that keep their functionality over long periods of time. However, maintenance of these constructs requires energy from the cell and thus reduces the host's fitness. Natural selection results in loss-of-functionality mutations that negate the expression of the construct in the population. Current approaches for the prevention of this phenomenon focus on either small-scale, manual design of evolutionary stable constructs or the detection of mutational sites with unstable tendencies. We designed the Evolutionary Stability Optimizer (ESO), a software tool that enables the large-scale automatic design of evolutionarily stable constructs with respect to both mutational and epigenetic hotspots and allows users to define custom hotspots to avoid. Furthermore, our tool takes the expression of the input constructs into account by considering the guanine-cytosine (GC) content and codon usage of the host organism, balancing the trade-off between stability and gene expression, allowing to increase evolutionary stability while maintaining the high expression. In this study, we present the many features of the ESO and show that it accurately predicts the evolutionary stability of endogenous genes. The ESO was created as an easy-to-use, flexible platform based on the notion that directed genetic stability research will continue to evolve and revolutionize current applications of synthetic biology. The ESO is available at the following link: https://www.cs.tau.ac.il/~tamirtul/ESO/.
Antibiotic resistance is spreading rapidly around the world and seriously impeding efforts to control microbial infections. Although nucleic acid testing is widely deployed for the detection of antibiotic resistant bacteria, the current techniques—mainly based on polymerase chain reaction (PCR)—are time-consuming and laborious. There is an urgent need to develop new strategies to control bacterial infections and the spread of antimicrobial resistance (AMR). The CRISPR-Cas system is an adaptive immune system found in many prokaryotes that presents attractive opportunities to target and edit nucleic acids with high precision and reliability. Engineered CRISPR-Cas systems are reported to effectively kill bacteria or even revert bacterial resistance to antibiotics (resensitizing bacterial cells to antibiotics). Strategies for combating antimicrobial resistance using CRISPR (i.e., Cas9, Cas12, Cas13, and Cas14) can be of great significance in detecting bacteria and their resistance to antibiotics. This review discusses the structures, mechanisms, and detection methods of CRISPR-Cas systems and how these systems can be engineered for the rapid and reliable detection of bacteria using various approaches, with a particular focus on nanoparticles. In addition, we summarize the most recent advances in applying the CRISPR-Cas system for virulence modulation of bacterial infections and combating antimicrobial resistance.
Graphical Abstract
Models of gene expression considering host–circuit interactions are relevant for understanding both the strategies and associated trade-offs that cell endogenous genes have evolved and for the efficient design of heterologous protein expression systems and synthetic genetic circuits. Here, we consider a small-size model of gene expression dynamics in bacterial cells accounting for host–circuit interactions due to limited cellular resources. We define the cellular resources recruitment strength as a key functional coefficient that explains the distribution of resources among the host and the genes of interest and the relationship between the usage of resources and cell growth. This functional coefficient explicitly takes into account lab-accessible gene expression characteristics, such as promoter and ribosome binding site (RBS) strengths, capturing their interplay with the growth-dependent flux of available free cell resources. Despite its simplicity, the model captures the differential role of promoter and RBS strengths in the distribution of protein mass fractions as a function of growth rate and the optimal protein synthesis rate with remarkable fit to the experimental data from the literature for Escherichia coli. This allows us to explain why endogenous genes have evolved different strategies in the expression space and also makes the model suitable for model-based design of exogenous synthetic gene expression systems with desired characteristics.
Microalgae have been recognized as one of the most efficient microorganisms to remediate industrial effluents. Among microalgae diatoms are silica shelled unicellular eukaryotes, found in all types of water bodies and flourish very well even in wastewater. They have their silica cell wall made up of nano arrayed pores arranged in a uniform fashion. Therefore, they act as smart nanocontainers to adsorb various trace metals, dyes, polymers, and drugs which are hazardous to human as well to aquatic life. The beautiful nanoarchitecture in diatoms allows them to easily bind to ligands of choice to form a nanocomposite structure with the pollutants which can be a chemical or biological component. Such naturally available diatom nanomaterials are economical and highly sensitive compared to manmade artificial silica nanomaterials to help in facile removal of the toxic pollutants from wastewater. This review is thus focused on employing diatoms to remediate various pollutants such as heavy metals, dyes, hydrocarbons detected in the wastewater. It also includes different microalgae as biosensors for determination of pollutants in effluents and the perspectives for nanotechnological applications in the field of remediating pollutants through microalgae. The review also discusses in length the hurdles and perspectives of employing microalgae in wastewater remediation.
In phenylketonuria (PKU) patients, a genetic defect in the enzyme phenylalanine hydroxylase (PAH) leads to elevated systemic phenylalanine (Phe), which can result in severe neurological impairment. As a treatment for PKU, Escherichia coli Nissle (EcN) strain SYNB1618 was developed under Synlogic’s Synthetic Biotic™ platform to degrade Phe from within the gastrointestinal (GI) tract. This clinical-stage engineered strain expresses the Phe-metabolizing enzyme phenylalanine ammonia lyase (PAL), catalyzing the deamination of Phe to the non-toxic product trans -cinnamate (TCA). In the present work, we generate a more potent EcN-based PKU strain through optimization of whole cell PAL activity, using biosensor-based high-throughput screening of mutant PAL libraries. A lead enzyme candidate from this screen is used in the construction of SYNB1934, a chromosomally integrated strain containing the additional Phe-metabolizing and biosafety features found in SYNB1618. Head-to-head, SYNB1934 demonstrates an approximate two-fold increase in in vivo PAL activity compared to SYNB1618.
Mutagenesis is a key hallmark and enabling characteristic of cancer cells, yet the diverse underlying mutagenic mechanisms that shape cancer genomes are not understood. This review will consider the emerging challenge of determining how DNA damage response pathways—both tolerance and repair—act upon specific forms of DNA damage to generate mutations characteristic of tumors. DNA polymerases are typically the ultimate mutagenic effectors of DNA repair pathways. Therefore, understanding the contributions of DNA polymerases is critical to develop a more comprehensive picture of mutagenic mechanisms in tumors. Selection of an appropriate DNA polymerase—whether error-free or error-prone—for a particular DNA template is critical to the maintenance of genome stability. We review different modes of DNA polymerase dysregulation including mutation, polymorphism, and over-expression of the polymerases themselves or their associated activators. Based upon recent findings connecting DNA polymerases with specific mechanisms of mutagenesis, we propose that compensation for DNA repair defects by error-prone polymerases may be a general paradigm molding the mutational landscape of cancer cells. Notably, we demonstrate that correlation of error-prone polymerase expression with mutation burden in a subset of patient tumors from The Cancer Genome Atlas can identify mechanistic hypotheses for further testing. We contrast experimental approaches from broad, genome-wide strategies to approaches with a narrower focus on a few hundred base pairs of DNA. In addition, we consider recent developments in computational annotation of patient tumor data to identify patterns of mutagenesis. Finally, we discuss the innovations and future experiments that will develop a more comprehensive portrait of mutagenic mechanisms in human tumors.
Evolution is often an obstacle to the engineering of stable biological systems due to the selection of mutations inactivating costly gene circuits. Gene overlaps induce important constraints on sequences and their evolution. We show that these constraints can be harnessed to increase the stability of costly genes by purging loss-of-function mutations. We combine computational and synthetic biology approaches to rationally design an overlapping reading frame expressing an essential gene within an existing gene to protect. Our algorithm succeeded in creating overlapping reading frames in 80% of E. coli genes. Experimentally, scoring mutations in both genes of such overlapping construct, we found that a significant fraction of mutations impacting the gene to protect have a deleterious effect on the essential gene. Such an overlap thus protects a costly gene from removal by natural selection by associating the benefit of this removal with a larger or even lethal cost. In our synthetic constructs, the overlap converts many of the possible mutants into evolutionary dead-ends, reducing the evolutionary potential of the system and thus increasing its stability over time.
The availability of l-arginine in tumours is a key determinant of an efficient anti-tumour T cell response1–4. Consequently, increases of typically low l-arginine concentrations within the tumour may greatly potentiate the anti-tumour responses of immune checkpoint inhibitors, such as programmed death-ligand 1 (PD-L1)-blocking antibodies⁵. However, currently no means are available to locally increase intratumoural l-arginine levels. Here we used a synthetic biology approach to develop an engineered probiotic Escherichia coli Nissle 1917 strain that colonizes tumours and continuously converts ammonia, a metabolic waste product that accumulates in tumours⁶, to l-arginine. Colonization of tumours with these bacteria increased intratumoural l-arginine concentrations, increased the number of tumour-infiltrating T cells and had marked synergistic effects with PD-L1 blocking antibodies in the clearance of tumours. The anti-tumour effect of these bacteria was mediated by l-arginine and was dependent on T cells. These results show that engineered microbial therapies enable metabolic modulation of the tumour microenvironment leading to enhanced efficacy of immunotherapies.
The well-established Shine-Dalgarno model suggests that translation initiation in bacteria is regulated via base-pairing between ribosomal RNA (rRNA) and mRNA. We used novel computational analyses and modelling of 823 bacterial genomes coupled with experiments to demonstrate that rRNA-mRNA interactions are diverse and regulate all translation steps from pre-initiation to termination. Previous research has reported the significant influence of rRNA-mRNA interactions, mainly in the initiation phase of translation. The results reported in this paper suggest that, in addition to the rRNA-mRNA interactions near the start codon that trigger initiation in bacteria, rRNA-mRNA interactions affect all sub-stages of the translation process (pre-initiation, initiation, elongation, termination). As these interactions dictate translation efficiency, they serve as an evolutionary driving force for shaping transcripts in bacteria while considering trade-offs between the effects of different interactions across different transcript regions on translation efficacy and efficiency. We observed selection for strong interactions in regions where such interactions are likely to enhance initiation, regulate early elongation, and ensure translation termination fidelity. We discovered selection against strong interactions and for intermediate interactions in coding regions and presented evidence that these patterns maximize elongation efficiency while also enhancing initiation. These finding are relevant to all biomedical disciplines due to the centrality of the translation process and the effect of rRNA-mRNA interactions on transcript evolution. ARTICLE HISTORY
Diverse applications rely on engineering microbes to carry and express foreign transgenes. This engineered baggage rarely benefits the microbe and is thus prone to rapid evolutionary loss when the microbe is propagated. For applications where a transgene must be maintained for extended periods of growth, slowing the rate of transgene evolution is critical and can be achieved by reducing either the rate of mutation or the strength of selection. Because the benefits realized by changing these quantities will not usually be equal, it is important to know which will yield the greatest improvement to the evolutionary half-life of the engineering. Here, we provide a method for jointly estimating the mutation rate of transgene loss and the strength of selection favoring these transgene-free, revertant individuals. The method requires data from serial transfer experiments in which the frequency of engineered genomes is monitored periodically. Simple mathematical models are developed that use these estimates to predict the half-life of the engineered transgene and provide quantitative predictions for how alterations to mutation and selection will influence longevity. The estimation method and predictive tools have been implemented as an interactive web application, MuSe.
Bacteria are one of the main groups of organisms, which dynamically and closely participate in human health and disease development. With the integration of chemical biotechnology, bacteria have been utilized as an emerging delivery system for various biomedical applications. Given the unique features of bacteria such as their intrinsic biocompatibility and motility, bacteria-based delivery systems have drawn wide interest in the diagnosis and treatment of various diseases, including cancer, infectious diseases, kidney failure, and hyperammonemia. Notably, at the interface of chemical biotechnology and bacteria, many research opportunities have been initiated, opening a promising frontier in biomedical application. Herein, the current synergy of chemical biotechnology and bacteria, the design principles for bacteria-based delivery systems, the microbial modulation, and the clinical translation are reviewed, with a special focus on the emerging advances in diagnosis and therapy.
Natural drugs have been transformed and optimized during the long process of evolution. These compounds play a very important role in the protection of human health and treatment of human diseases. Sustainable approaches to the generation of raw materials for pharmaceutical products have been extensively investigated in drug research and development because chemical synthesis is costly and generates pollution. The present review provides an overview of the recent advances in the synthetic biology of natural drugs. Particular attention is paid to the investigations of drugs that may be mass-produced by the pharmaceutical industry after optimization of the corresponding synthetic systems. The present review describes the reconstruction and optimization of biosynthetic pathways for nine drugs, including seven drugs from plant sources and two drugs from microbial sources, suggesting a new strategy for the large-scale preparation of some rare natural plant metabolites and highly bioactive microbial compounds. Some of the suggested synthetic methods remain in a preliminary exploration stage; however, a number of these methods demonstrated considerable application potential. The authors also discuss the advantages and disadvantages of the application of synthetic biology and various expression systems for heterologous expression of natural drugs. Thus, the present review provides a useful perspective for researchers attempting to use synthetic biology to produce natural drugs.
Integrating synthetic biology into wearables could expand opportunities for noninvasive monitoring of physiological status, disease states and exposure to pathogens or toxins. However, the operation of synthetic circuits generally requires the presence of living, engineered bacteria, which has limited their application in wearables. Here we report lightweight, flexible substrates and textiles functionalized with freeze-dried, cell-free synthetic circuits, including CRISPR-based tools, that detect metabolites, chemicals and pathogen nucleic acid signatures. The wearable devices are activated upon rehydration from aqueous exposure events and report the presence of specific molecular targets by colorimetric changes or via an optical fiber network that detects fluorescent and luminescent outputs. The detection limits for nucleic acids rival current laboratory methods such as quantitative PCR. We demonstrate the development of a face mask with a lyophilized CRISPR sensor for wearable, noninvasive detection of SARS-CoV-2 at room temperature within 90 min, requiring no user intervention other than the press of a button. Wearable materials are endowed with synthetic biology circuits to detect biomolecules, including SARS-CoV-2 RNA.
Trillions of commensal bacteria colonizing humans (microbiome) have emerged as essential player(s) in human health. The alteration of the same has been linked with diseases including autoimmune disorders such as multiple sclerosis, rheumatoid arthritis, systemic lupus erythematosus, and ankylosing spondylitis. Gut bacteria are separated from the host through a physical barrier such as skin or gut epithelial lining. However, the perturbation in the healthy bacterial community (gut dysbiosis) can compromise gut barrier integrity, resulting in translocation of bacterial contents across the epithelial barrier (leaky gut). Bacterial contents such as lipopolysaccharide and bacterial antigens can induce a systemic inflammatory environment through activation and induction of immune cells. The biggest question in the field is whether inflammation causes gut dysbiosis or dysbiosis leads to disease induction or propagation, i.e., it is inside out or outside in or both. In this review, we first discuss the microbiome profiling studies in various autoimmune disorders, followed by a discussion of potential mechanisms through which microbiome is involved in the pathobiology of diseases. A better understanding of the role of the microbiome in health and disease will help us harness the power of commensal bacteria for the development of novel therapeutic agents to treat autoimmune disorders.
Food is essential to provide energy for human cellular metabolism, and is usually made from plants or animals. Beside plants and animals, other important food sources are made by microorganisms, typically products of fermentation (e.g bread, wine, beer, soy sauce, etc). Nowadays, because of the increasing environmental pollution, climate change and population growth, is becoming challenging to keep the food supply safe, nutritious and sustainable. Importantly, the development of the synthetic biology field enable the engineering of cells that can be used in food manufacturing. These engineered cells can transform renewable raw materials into important food components, functional food additives and nutritional chemicals. This review discusses the major challenges in food industry and how synthetic biology has the potential to revolutionize the future of the food. Finally, the prospects and challenges of synthetic biology for a sustainable food manufacturing are discussed.
Synthetic biology holds great promise for addressing global needs. However, most current developments are not immediately translatable to ‘outside-the-lab’ scenarios that differ from controlled laboratory settings. Challenges include enabling long-term storage stability as well as operating in resource-limited and off-the-grid scenarios using autonomous function. Here we analyze recent advances in developing synthetic biological platforms for outside-the-lab scenarios with a focus on three major application spaces: bioproduction, biosensing, and closed-loop therapeutic and probiotic delivery. Across the Perspective, we highlight recent advances, areas for further development, possibilities for future applications, and the needs for innovation at the interface of other disciplines. Current developments in synthetic biology are not immediately applicable outside of the controlled laboratory environment. In this Perspective, the authors outline the advances and challenges the field faces in operating in resource limited and off-the-grid scenarios.
We report that epigenetic silencing causes the loss of function of multi-transcript unit constructs that are integrated using CRISPR-Cas9. Using a modular two color reporter system flanked by selection markers, we demonstrate that expression heterogeneity does not correlate with sequence alteration but instead correlates with chromosomal accessibility. We partially reverse this epigenetic silencing via small-molecule inhibitors of methylation and histone deacetylation. We then correlate each heterogeneously-expressing phenotype with its expected epigenetic state by employing ATAC-seq. The stability of each expression phenotype is reinforced by selective pressure, which indicates that ongoing epigenetic remodeling can occur for over one month after integration. Collectively, our data suggests that epigenetic silencing limits the utility of multi-transcript unit constructs that are integrated via double-strand repair pathways. Our research implies that mammalian synthetic biologists should consider localized epigenetic outcomes when designing complex genetic circuits.
Synthetic biology will transform how we grow food, what we eat, and where we source materials and medicines. Here I have selected six products that are now on the market, highlighting the underlying technologies and projecting forward to the future that can be expected over the next ten years.
Unfavorable cell heterogeneity is a frequent risk during bioprocess scale-up and characterized by rising frequencies of low-producing cells. Low-producing cells emerge by both non-genetic and genetic variation and will enrich due to their higher specific growth rate during the extended number of cell divisions of large-scale bioproduction. Here, we discuss recent strategies for synthetic stabilization of fermentation populations and argue for their application to make cell factory designs that better suit industrial needs. Genotype-directed strategies leverage DNA-sequencing data to inform strain design. Self-selecting phenotype-directed strategies couple high production with cell proliferation, either by redirected metabolic pathways or synthetic product biosensing to enrich for high-performing cell variants. Evaluating production stability early in new cell factory projects will guide heterogeneity-reducing design choices. As good initial metrics, we propose production half-life from standardized serial-passage stability screens and production load, quantified as production-associated percent-wise growth rate reduction. Incorporating more stable genetic designs will greatly increase scalability of future cell factories through sustaining a high-production phenotype and enabling stable long-term production.
Creating a magic bullet that can selectively kill cancer cells while sparing nearby healthy cells remains one of the most ambitious objectives in pharmacology. Nanomedicine, which relies on the use of nanotechnologies to fight disease, was envisaged to fulfill this coveted goal. Despite substantial progress, the structural complexity of therapeutic vehicles impedes their broad clinical application. Novel modular manufacturing approaches for engineering programmable drug carriers may be able to overcome some fundamental limitations of nanomedicine. We discuss how bottom-up synthetic biology principles, empowered by microfluidics, can palliate current drug carrier assembly limitations, and we demonstrate how such a magic bullet could be engineered from the bottom up to ultimately improve clinical outcomes for patients.
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Advances in synthetic biology and microbiology have enabled the creation of engineered bacteria which can sense and report on intracellular and extracellular signals. When deployed in vivo these whole-cell bacterial biosensors can act as sentinels to monitor biomolecules of interest in human health and disease settings. This is particularly interesting in the context of the gut microbiota, which interacts extensively with the human host throughout time and transit of the gut and can be accessed from feces without requiring invasive collection. Leveraging rational engineering approaches for genetic circuits as well as an expanding catalog of disease-associated biomarkers, bacterial biosensors can act as non-invasive and easy-to-monitor reporters of the gut. Here, we summarize recent engineering approaches applied in vivo in animal models and then highlight promising technologies for designing the next generation of bacterial biosensors.
Engineering resource allocation in biological systems is an ongoing challenge. Organisms allocate resources for ensuring survival, reducing the productivity of synthetic biology functions. Here we present a new approach for engineering the resource allocation of Escherichia coli by rationally modifying its transcriptional regulatory network. Our method (ReProMin) identifies the minimal set of genetic interventions that maximizes the savings in cell resources. To this end, we categorized transcription factors according to the essentiality of its targets and we used proteomic data to rank them. We designed the combinatorial removal of transcription factors that maximize the release of resources. Our resulting strain containing only three mutations, theoretically releasing 0.5% of its proteome, had higher proteome budget, increased production of an engineered metabolic pathway and showed that the regulatory interventions are highly specific. This approach shows that combining proteomic and regulatory data is an effective way of optimizing strains using conventional molecular methods. An econometric model built on regulatory networks and calibrated by proteomics data identifies nonessential transcription factors that when deleted in Escherichia coli result in a strain with an expanded proteome for engineering applications.
Engineered genetic systems are prone to failure when their genetic parts contain repetitive sequences. Designing many nonrepetitive genetic parts with desired functionalities remains a difficult challenge with high computational complexity. To overcome this challenge, we developed the Nonrepetitive Parts Calculator to rapidly generate thousands of highly nonrepetitive genetic parts from specified design constraints, including promoters, ribosome-binding sites and terminators. As a demonstration, we designed and experimentally characterized 4,350 nonrepetitive bacterial promoters with transcription rates that varied across a 820,000-fold range, and 1,722 highly nonrepetitive yeast promoters with transcription rates that varied across a 25,000-fold range. We applied machine learning to explain how specific interactions controlled the promoters’ transcription rates. We also show that using nonrepetitive genetic parts substantially reduces homologous recombination, resulting in greater genetic stability. An algorithm to design nonrepetitive genetic parts enables synthetic biologists to reliably engineer stable circuits.
An in planta gene editing approach was developed wherein Cas9 transgenic plants are infected with an RNA virus that expresses single guide RNAs (sgRNAs). The sgRNAs are augmented with sequences that promote cell-to-cell mobility. Mutant progeny are recovered in the next generation at frequencies ranging from 65 to 100%; up to 30% of progeny derived from plants infected with a virus expressing three sgRNAs have mutations in all three targeted loci. An efficient and multiplexed in planta gene editing approach is developed by infecting Cas9 transgenic plants with an RNA virus that expresses single guide RNAs carrying sequences that confer cell-to-cell mobility.
Tracking progress towards Target 6.1 of the United Nations Sustainable Development Goals, “achieving universal and equitable access to safe and affordable drinking water for all”, necessitates the development of simple, inexpensive tools to monitor water quality. The rapidly growing field of synthetic biology has the potential to address this need by isolating DNA-encoded sensing elements from nature and reassembling them to create field-deployable “biosensors” that can detect pathogenic or chemical water contaminants. Here, we describe current water quality monitoring strategies enabled by synthetic biology and compare them to previous approaches used to detect three priority water contaminants (i.e., fecal pathogens, arsenic, and fluoride), as well as explain the potential for engineered biosensors to simplify and decentralize water quality monitoring. We conclude with an outlook on the future of biosensor development, in which we discuss their adaptability to emerging contaminants (e.g., metals, agricultural products, and pharmaceuticals), outline current limitations, and propose steps to overcome the field’s outstanding challenges to facilitate global water quality monitoring.
As engineered microbes are used in increasingly diverse applications across human health and bioproduction, the field of synthetic biology will need to focus on strategies that stabilize and contain the function of these populations within target environments. To this end, recent advancements have created layered sensing circuits that can compute cell survival, genetic contexts that are less susceptible to mutation, burden, and resource control circuits, and methods for population variability reduction. These tools expand the potential for real-world deployment of complex microbial systems by enhancing their environmental robustness and functional stability in the face of unpredictable host response and evolutionary pressure.
Cracking is one of the major deteriorating causes of concrete, which allows the entrance of chemicals and leads to the loss of physico-mechanical and durability properties of concrete structures. To protect, repair, and rehabilitate concrete structures, the application of different surface coating agents and sealants, binding agents, as well as adhesives has been commonly practiced. Although such techniques have mostly been applicable, due to their inherent mechanism difference, major challenges such as delamination and lack of cost effectiveness have resulted in searching for alternative methods of crack sealing or self-healing. One of the novel self-healing mechanisms is using bacterial induced calcite precipitation in concrete mixtures to heal concrete cracks. In this technique, bacterial mineralization (biomineralization) is performed through decomposing urea and calcium to produce calcium carbonate (CaCO3), which can fill cracks. To review the mechanisms ruling this precipitation, this article aims to present an in-depth analysis of biomineralization, CaCO3 precipitation, physico-mechanical, durability and microstructural properties of bacterial concrete. To do this, over 70 research articles have been reviewed and their data including the types and dosage of bacteria, mixture proportions, as well as the result of mechanical and durability tests are gathered, provided and analyzed. It is found that the biomineralization is mostly dependent on factors such as the applying method and consistent preservation of the living bacteria. In addition, the environmental impact of bacterial concrete is found to be directly linked with the urea content in the concrete mixture.
RNA cargo is transferred into cultured cells using a fully human delivery system.
Cellular burden limits the applications of bacterial synthetic biology. Experimental approaches for burden minimisation have recently become available. Tools to identify construct design with low footprint on the host include capacity monitors that quantify cellular capacity, high-throughput approaches and cell-free systems for construct prototyping. Orthogonal ribosomes and feedback controllers are instead useful to seek control of resource allocation and lower burden. Other approaches include genome reduction to increase the available resource pool and synthetic addiction to couple cell fitness and product accumulation. However, controlling the cellular response to exogenous expression is still a challenge, and more tools are needed in order to widen the applications of synthetic biology. Further effort that combines novel evolutionary data with burden-aware tools can set the foundation to increase the stability and robustness of future genetic systems.
The steadfast advance of the synthetic biology field has enabled scientists to use genetically engineered cells, instead of small molecules or biologics, as the basis for the development of novel therapeutics. Cells endowed with synthetic gene circuits can control the localization, timing and dosage of therapeutic activities in response to specific disease biomarkers and thus represent a powerful new weapon in the fight against disease. Here, we conceptualize how synthetic biology approaches can be applied to programme living cells with therapeutic functions and discuss the advantages that they offer over conventional therapies in terms of flexibility, specificity and predictability, as well as challenges for their development. We present notable advances in the creation of engineered cells that harbour synthetic gene circuits capable of biological sensing and computation of signals derived from intracellular or extracellular biomarkers. We categorize and describe these developments based on the cell scaffold (human or microbial) and the site at which the engineered cell exerts its therapeutic function within its human host. The design of cell-based therapeutics with synthetic biology is a rapidly growing strategy in medicine that holds great promise for the development of effective treatments for a wide variety of human diseases.
Metabolic engineering can have a pivotal role in increasing the environmental sustainability of the transportation and chemical manufacturing sectors. The field has already developed engineered microorganisms that are currently being used in industrial-scale processes. However, it is often challenging to achieve the titres, yields and productivities required for commercial viability. The efficiency of microbial chemical production is usually dependent on the physiological traits of the host organism, which may either impose limitations on engineered biosynthetic pathways or, conversely, boost their performance. In this Review, we discuss different aspects of microbial physiology that often create obstacles for metabolic engineering, and present solutions to overcome them. We also describe various instances in which natural or engineered physiological traits in host organisms have been harnessed to benefit engineered metabolic pathways for chemical production.
The past 20 years have witnessed enormous progress in synthetic biology in the development of engineered cells for diverse applications, including biomanufacturing, materials fabrication, and potential therapeutics and diagnostics. However, it still remains a major challenge to maintain long-term performance of synthetic gene circuits, due to the emergence of mutants that lose circuit function. Here, we highlight major vulnerabilities of synthetic gene circuits resulting in circuit failure and mutant escape. We also discuss engineering strategies to enhance long-term circuit stability and performance. These approaches can be divided into two strategies: the suppression of the emergence of mutants and the suppression of their relative fitness if mutants do emerge. We anticipate that mechanistic understanding of the modes of circuit failure will facilitate future efforts to design evolutionarily robust synthetic biology-inspired applications.
Some cancer treatment failures have been attributed to the tumour microbiota, with implications that microbiota manipulation may improve treatment efficacy. While antibiotics have been used to control bacterial growth, their dysbiotic effects on the microbiome, failure to penetrate biofilms and decreased efficacy due to increasing antimicrobial resistance by bacteria, suggest alternatives are needed. Bacteriophages may provide a precise means for targeting oncobacteria whose relative abundance is increased in tumour tissue microbiomes. Fusobacterium, Streptococcus, Peptostreptococcus, Prevotella, Parvimonas, and Treponema species are prevalent in tumour tissue microbiomes of some cancers. They may promote cancer growth by dampening immunity, stimulating release of proinflammatory cytokines, and directly interacting with cancer cells to stimulate proliferation. Lytic bacteriophages against some of these oncobacteria have been isolated and characterised. The search continues for others. The possibility exists for their testing as adjuncts to complement existing therapies. In this review, we highlight the role of oncobacteria, specifically those whose relative abundance in the intra-tumour microbiome is increased, and discuss the potential for bacteriophages against these micro-organisms to augment existing cancer therapies. The capacity for bacteriophages to modulate immunity and kill specific bacteria makes them suitable candidates to manipulate the tumour microbiome and negate the effects of these oncobacteria.
Separating microbes and cancers
The role of microorganisms in causing and sustaining cancers has been in dispute for centuries. Through the lens of gut- and tumor-associated microbes, Sepich-Poore et al. review our current understanding of the microbiota in cancer, building a “microbially conscious” framework. The authors argue that humans should be considered as a meta-organism, but how our microbiota influences cancer is still not well understood mechanistically. Nevertheless, advances in microbiome research are improving our understanding of immuno-oncology and driving new diagnostic and therapeutic approaches.
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Synthetic biology is a design-driven discipline centered on engineering novel biological functions through the discovery, characterization, and repurposing of molecular parts. Several synthetic biological solutions to critical biomedical problems are on the verge of widespread adoption and demonstrate the burgeoning maturation of the field. Here, we highlight applications of synthetic biology in vaccine development, molecular diagnostics, and cell-based therapeutics, emphasizing technologies approved for clinical use or in active clinical trials. We conclude by drawing attention to recent innovations in synthetic biology that are likely to have a significant impact on future applications in biomedicine.
The vaccines industry has not changed appreciably in decades regarding technology, and has struggled to remain viable, with large companies withdrawing from production. Meanwhile, there has been no let-up in outbreaks of viral disease, at a time when the biopharmaceuticals industry is discussing downsizing. The distributed manufacturing model aligns well with this, and the advent of synthetic biology promises much in terms of vaccine design. Biofoundries separate design from manufacturing, a hallmark of modern engineering. Once designed in a biofoundry, digital code can be transferred to a small-scale manufacturing facility close to the point of care, rather than physically transferring cold-chain-dependent vaccine. Thus, biofoundries and distributed manufacturing have the potential to open up a new era of biomanufacturing, one based on digital biology and information systems. This seems a better model for tackling future outbreaks and pandemics.
Animal-derived protein production is one of the major traditional protein supply methods, which continues to face increasing challenges to satisfy global needs due to population growth, augmented individual protein consumption, and aggravated environmental pollution. Thus, ensuring a sustainable protein source is a considerable challenge. The emergence and development of food synthetic biology has enabled the establishment of cell factories that effectively synthesize proteins, which is an important way to solve the protein supply problem. This review aims to discuss the existing problems of traditional protein supply and to elucidate the feasibility of synthetic biology in the process of protein synthesis. Moreover, using artificial bioengineered milk and artificial bioengineered eggs as examples, the progress of food protein supply transition based on synthetic biology has been systematically summarized. Additionally, the future of food synthetic biology as a potential source of protein has been also discussed. By strengthening and innovating the application of food synthetic biology technologies, including genetic engineering and high-throughput screening methods, the current limitations of artificial foods for protein synthesis and production should be addressed. Therefore, the development and industrial production of new food resources should be explored to ensure safe, high-quality, and sustainable global protein supply.