暂无摘要。

UNASSIGNED: Synthetic DNA technology is rapidly emerging as a key driver of innovation in the fields of medicine, biotechnology, and more. But it also poses significant risk, particularly in lowering barriers to the production of dangerous pathogens and toxins. At present, oversight of this technology is voluntarily coordinated among synthetic DNA providers and stakeholders, and detailed understanding of security processes, infrastructures, and insights from these providers is imperative to understand how to best mitigate the inherent risks of this technology.
UNASSIGNED: In this study, we aimed to determine the trends, outliers, strengths, and gaps in current DNA provider security practices through a broad survey of the gene synthesis field.
UNASSIGNED: We interviewed synthetic DNA providers and stakeholders about their customer and sequence screening procedures. Respondents were divided into groups based on membership in the International Gene Synthesis Consortium, nationality, whether they were a new or established company, and whether they synthesize de novo DNA or not. We then performed meta-analysis and intergroup analysis to elucidate larger trends and points of variance.
UNASSIGNED: In total, we interviewed 18 companies. We found that synthetic DNA providers and stakeholders tend to operate under a \"zero-trust model\" for screenings and utilize common governmental and private resources to navigate international import/export policies. Major variabilities were identified in the sensitivity of screening, monitoring and evaluation practices, screening pipelines, and approaches to synthetic oligonucleotide screening. In addition, we identified a significant vulnerability of lacking awareness among providers of formal law enforcement reporting procedures.
UNASSIGNED: Collectively, we observed significant heterogeneity in security practice throughout the field, reflective of the current lack of codified oversight for DNA synthesis. The results presented in this study provide insight into the specifics, strengths, and shortcomings of current DNA provider security practices, and are important considerations for the biosecurity community in ongoing deliberations of if, when, and how to approach oversight of synthetic DNA technology.

UNASSIGNED: The integration of Artificial Intelligence (AI) with synthetic biology is driving unprecedented progress in both fields. However, this integration introduces complex biosecurity challenges. Addressing these concerns, this article proposes a specialized biosecurity risk assessment process designed to evaluate the incorporation of AI in synthetic biology.
UNASSIGNED: A set of tailored tools and methodology was developed for conducting biosecurity risk assessments of AI language models used for synthetic biology. These resources were developed to guide risk management professionals through a systematic process of identifying, evaluating, and mitigating potential risks.
UNASSIGNED: The tools and methodology provided offer a structured approach to risk assessment, enabling risk management professionals to comprehensively analyze the biosecurity implications of AI applications in synthetic biology. They facilitate the identification of potential risks and the development of effective mitigation strategies. An example of a risk assessment performed on the large language model \"ChatGPT 4.0\" is provided here.
UNASSIGNED: AI\'s role in synthetic biology is rapidly expanding; thus, establishing proactive and secure practices is crucial. The biosecurity risk assessment tools and methodology presented here are the first provided in the literature and will be instrumental steps toward the responsible integration of AI in synthetic biology. By adopting these resources, the biorisk management community can effectively navigate and manage the biosecurity challenges posed by AI, ensuring its responsible and secure application in the field of synthetic biology.

Naringenin is a plant polyphenol, widely explored due to its interesting biological activities, namely anticancer, antioxidant, and anti-inflammatory. Due to its potential applications and attempt to overcome the industrial demand, there has been an increased interest in its heterologous production. The microbial biosynthetic pathway to produce naringenin is composed of tyrosine ammonia-lyase (TAL), 4-coumarate-CoA ligase (4CL), chalcone synthase (CHS), and chalcone isomerase (CHI). Herein, we targeted the efficient de novo production of naringenin in Escherichia coli by performing a step-by-step validation and optimization of the pathway. For that purpose, we first started by expressing two TAL genes from different sources in three different E. coli strains. The highest p-coumaric acid production (2.54 g/L) was obtained in the tyrosine-overproducing M-PAR-121 strain carrying TAL from Flavobacterium johnsoniae (FjTAL). Afterwards, this platform strain was used to express different combinations of 4CL and CHS genes from different sources. The highest naringenin chalcone production (560.2 mg/L) was achieved by expressing FjTAL combined with 4CL from Arabidopsis thaliana (At4CL) and CHS from Cucurbita maxima (CmCHS). Finally, different CHIs were tested and validated, and 765.9 mg/L of naringenin was produced by expressing CHI from Medicago sativa (MsCHI) combined with the other previously chosen genes. To our knowledge, this titer corresponds to the highest de novo production of naringenin reported so far in E. coli. KEY POINTS: • Best enzyme and strain combination were selected for de novo naringenin production. • After genetic and operational optimizations, 765.9 mg/L of naringenin was produced. • This de novo production is the highest reported so far in E. coli.

The rational design, activity prediction, and adaptive application of biological elements (bio-elements) are crucial research fields in synthetic biology. Currently, a major challenge in the field is efficiently designing desired bio-elements and accurately predicting their activity using vast datasets. The advancement of artificial intelligence (AI) technology has enabled machine learning and deep learning algorithms to excel in uncovering patterns in bio-element data and predicting their performance. This review explores the application of AI algorithms in the rational design of bio-elements, activity prediction, and the regulation of transcription-factor-based biosensor response performance using AI-designed elements. We discuss the advantages, adaptability, and biological challenges addressed by the AI algorithms in various applications, highlighting their powerful potential in analyzing biological data. Furthermore, we propose innovative solutions to the challenges faced by AI algorithms in the field and suggest future research directions. By consolidating current research and demonstrating the practical applications and future potential of AI in synthetic biology, this review provides valuable insights for advancing both academic research and practical applications in biotechnology.

Withanolides are naturally occurring steroidal lactones found in certain species of the Withania genus, especially Withania somnifera (commonly known as Ashwagandha). These compounds have gained considerable attention due to their wide range of therapeutic properties and potential applications in modern medicine. To meet the rapidly growing demand for withanolides, innovative approaches such as in vitro culture techniques and synthetic biology offer promising solutions. In recent years, synthetic biology has enabled the production of engineered withanolides using heterologous systems, such as yeast and bacteria. Additionally, in vitro methods like cell suspension culture and hairy root culture have been employed to enhance withanolide production. Nevertheless, one of the primary obstacles to increasing the production of withanolides using these techniques has been the intricacy of the biosynthetic pathways for withanolides. The present article examines new developments in withanolide production through in vitro culture. A comprehensive summary of viable traditional methods for producing withanolide is also provided. The development of withanolide production in heterologous systems is examined and emphasized. The use of machine learning as a potent tool to model and improve the bioprocesses involved in the generation of withanolide is then discussed. In addition, the control and modification of the withanolide biosynthesis pathway by metabolic engineering mediated by CRISPR are discussed.

This paper will focus on analyzing the argument with appealing to nature against synthetic biology and provide a counter-argument against it through demonstrating the ambiguity of the concept of nature, denying the existence of a morally significant line between natural and non/unnatural, and disproving the allegations against synthetic biology raised by the argument appealing to nature. The paper consists of two parts following a brief introduction. The first part will describe the argument appealing to nature against synthetic biology, and identify the deficiencies of the argument per se, e.g., the ambiguity of the concept \'nature\'; and the problems in the morally significant line between the natural and the non/unnatural. The second part will discuss the allegations to synthetic biology stemming from this argument, e.g., committing metaphysical and ethical mistakes, and doing possible harms to the environment.

Hierarchical compartmentalization responding to changes in intracellular and extracellular environments is ubiquitous in living eukaryotic cells but remains a formidable task in synthetic systems. Here we report a two-level compartmentalization approach based on a thermo-responsive aqueous two-phase system (TR-ATPS) comprising poly(N-isopropylacrylamide) (PNIPAM) and dextran (DEX). Liquid membraneless compartments enriched in PNIPAM are phase-separated from the continuous DEX solution via liquid-liquid phase separation at 25 °C and shrink dramatically with small second-level compartments generated at the interface, resembling the structure of colloidosome, by increasing the temperature to 35 °C. The TR-ATPS can store biomolecules, program the spatial distribution of enzymes, and accelerate the overall biochemical reaction efficiency by nearly 7-fold. The TR-ATPS inspires on-demand, stimulus-triggered spatiotemporal enrichment of biomolecules via two-level compartmentalization, creating opportunities in synthetic biology and biochemical engineering.

Saccharomyces cerevisiae is a commonly used microorganism in the biotechnological industry. For the industrial heterologous production of compounds, it is of great advantage to work with growth-controllable yeast strains. In our work, we utilized the natural pheromone system of S. cerevisiae and generated a set of different strains possessing an α-pheromone controllable growth behavior. Naturally, the α-factor pheromone is involved in communication between haploid S. cerevisiae cells. Perception of the pheromone initiates several cellular changes, enabling the cells to prepare for an upcoming mating event. We exploited this natural pheromone response system and developed two different plasmid-based modules, in which the target genes, MET15 and FAR1, are under control of the α-factor sensitive FIG1 promoter for a controlled expression in S. cerevisiae. Whereas expression of MET15 led to a growth induction, FAR1 expression inhibited growth. The utilization of low copy number or high copy number plasmids for target gene expression and different concentrations of α-factor allow a finely adjustable control of yeast growth rate.

Flavin-dependent monooxygenases (FMOs) are a valuable group of biocatalysts that can regioselectively introduce a hydroxy group for the targeted modification of biologically active compounds. Here, we present the fdeE, the FMO from Herbaspirillum seropedicae SmR1 that is a part of the naringenin degradation pathway and is active towards a wide range of flavonoids-flavanones, flavones, isoflavones, and flavonols. Bioinformatics and biochemical analysis revealed a high similarity between the analyzed enzyme and other F8H FMOs what might indicate convergent evolutionary mechanism of flavonoid degradation pathway emergence by microorganism. A simple approach with the manipulation of the reaction environment allowed the stable formation of hydroxylation products, which showed very high reactivity in both in vivo and in vitro assays. This approach resulted in an 8-hydroxyquercetin-gossypetin titer of 0.16 g/L and additionally it is a first report of production of this compound.