Gene synthesis design: a pythonic approach.

Researchers often need to synthesize genes of interest in this era of synthetic biology. Gene synthesis by PCR assembly of multiple DNA fragments is a quick and economical method that is widely applied. Up to now, there have been a few software solutions for designing fragments in gene synthesis. However, some of these software solutions use programming languages that are not popular now, other software products are commercial or require users to visit servers. In this study, we propose a Python program to design DNA fragments for gene synthesis. The algorithm is designed to meet the experimental needs. Also, the source code with detailed annotation is freely available for all users. Furthermore, the feasibility of the algorithm and the program is validated by experiments. Our program can be useful for the design of gene synthesis in the labs and help the study of gene structure and function.

Two teams supercharge gene spread in plants.

First synthetic "gene drive" for plants could help tame weeds-or transform them.

[Closed-loop synthetic gene circuits for cell-based therapies]. / Les circuits synthétiques de gènes fonctionnant en boucle fermée - Concept et dernières avancées.

Recent advances in synthetic biology have paved the way for new cellular therapies, using cells capable of autonomously treating chronic diseases. These cells integrate a set of genes functioning in a closed-loop synthetic circuit, delivering a therapeutic effector in response to a specific pathological signal. While promising in mice, these therapies face clinical challenges related to safety and feasibility of in vivo implementation. The latest generations of synthetic circuits aim to address these issues through advanced bioengineering strategies outlined in this article.

Title: Les circuits synthétiques de gènes fonctionnant en boucle fermée - Concept et dernières avancées. Abstract: Les progrès récents de la biologie synthétique ont ouvert la voie à de nouvelles thérapies fondées sur des cellules rendues aptes à produire de manière autonome des substrats afin de traiter des maladies chroniques. Ces cellules modifiées intègrent un ensemble de gènes fonctionnant en circuit synthétique à boucle fermée, qui permettent de délivrer un effecteur thérapeutique en réponse à un signal pathologique déterminé. Bien que prometteuses chez la souris, ces thérapies font face à des obstacles cliniques liés à leur sûreté et à leur implémentation in vivo. Les dernières générations de circuits synthétiques cherchent à résoudre ces problèmes grâce à des stratégies de bioingénierie avancées, que nous présentons dans cet article.

Engineering a synthetic gene circuit for high-performance inducible expression in mammalian systems.

Inducible gene expression systems can be used to control the expression of a gene of interest by means of a small-molecule. One of the most common designs involves engineering a small-molecule responsive transcription factor (TF) and its cognate promoter, which often results in a compromise between minimal uninduced background expression (leakiness) and maximal induced expression. Here, we focus on an alternative strategy using quantitative synthetic biology to mitigate leakiness while maintaining high expression, without modifying neither the TF nor the promoter. Through mathematical modelling and experimental validations, we design the CASwitch, a mammalian synthetic gene circuit based on combining two well-known network motifs: the Coherent Feed-Forward Loop (CFFL) and the Mutual Inhibition (MI). The CASwitch combines the CRISPR-Cas endoribonuclease CasRx with the state-of-the-art Tet-On3G inducible gene system to achieve high performances. To demonstrate the potentialities of the CASwitch, we apply it to three different scenarios: enhancing a whole-cell biosensor, controlling expression of a toxic gene and inducible production of Adeno-Associated Virus (AAV) vectors.

Synthetic Genes For Dynamic Regulation Of DNA-Based Receptors.

We present a strategy to control dynamically the loading and release of molecular ligands from synthetic nucleic acid receptors using in vitro transcription. We demonstrate this by engineering three model synthetic DNA-based receptors: a triplex-forming DNA complex, an ATP-binding aptamer, and a hairpin strand, whose ability to bind their specific ligands can be cotranscriptionally regulated (activated or inhibited) through specific RNA molecules produced by rationally designed synthetic genes. The kinetics of our DNA sensors and their genetically generated inputs can be captured using differential equation models, corroborating the predictability of the approach used. This approach shows that highly programmable nucleic acid receptors can be controlled with molecular instructions provided by dynamic transcriptional systems, illustrating their promise in the context of coupling DNA nanotechnology with biological signaling.

Synthetic reversed sequences reveal default genomic states.

Pervasive transcriptional activity is observed across diverse species. The genomes of extant organisms have undergone billions of years of evolution, making it unclear whether these genomic activities represent effects of selection or 'noise'1-4. Characterizing default genome states could help understand whether pervasive transcriptional activity has biological meaning. Here we addressed this question by introducing a synthetic 101-kb locus into the genomes of Saccharomyces cerevisiae and Mus musculus and characterizing genomic activity. The locus was designed by reversing but not complementing human HPRT1, including its flanking regions, thus retaining basic features of the natural sequence but ablating evolved coding or regulatory information. We observed widespread activity of both reversed and native HPRT1 loci in yeast, despite the lack of evolved yeast promoters. By contrast, the reversed locus displayed no activity at all in mouse embryonic stem cells, and instead exhibited repressive chromatin signatures. The repressive signature was alleviated in a locus variant lacking CpG dinucleotides; nevertheless, this variant was also transcriptionally inactive. These results show that synthetic genomic sequences that lack coding information are active in yeast, but inactive in mouse embryonic stem cells, consistent with a major difference in 'default genomic states' between these two divergent eukaryotic cell types, with implications for understanding pervasive transcription, horizontal transfer of genetic information and the birth of new genes.

dCas12a:Pre-crRNA: A New Tool to Induce mRNA Degradation in Saccharomyces cerevisiae Synthetic Gene Circuits.

We describe a new way to trigger mRNA degradation in Saccharomyces cerevisiae synthetic gene circuits. Our method demands to modify either the 5'- or the 3'-UTR that flanks a target gene with elements from the pre-crRNA of type V Cas12a proteins and expresses a DNase-deficient Cas12a (dCas12a). dCas12a recognizes and cleaves the pre-crRNA motifs on mRNA sequences. Our tool does not require complex engineering operations and permits an efficient control of protein expression via mRNA degradation.

A coarse-grained bacterial cell model for resource-aware analysis and design of synthetic gene circuits.

Within a cell, synthetic and native genes compete for expression machinery, influencing cellular process dynamics through resource couplings. Models that simplify competitive resource binding kinetics can guide the design of strategies for countering these couplings. However, in bacteria resource availability and cell growth rate are interlinked, which complicates resource-aware biocircuit design. Capturing this interdependence requires coarse-grained bacterial cell models that balance accurate representation of metabolic regulation against simplicity and interpretability. We propose a coarse-grained E. coli cell model that combines the ease of simplified resource coupling analysis with appreciation of bacterial growth regulation mechanisms and the processes relevant for biocircuit design. Reliably capturing known growth phenomena, it provides a unifying explanation to disparate empirical relations between growth and synthetic gene expression. Considering a biomolecular controller that makes cell-wide ribosome availability robust to perturbations, we showcase our model's usefulness in numerically prototyping biocircuits and deriving analytical relations for design guidance.

Enzymatic Assembly of Small Synthetic Genes with Repetitive Elements.

Gene synthesis efficiency has greatly improved in recent years but is limited when it comes to repetitive sequences, which results in synthesis failure or delays by DNA synthesis vendors. This represents a major obstacle for the development of synthetic biology since repetitive elements are increasingly being used in the design of genetic circuits and design of biomolecular nanostructures. Here, we describe a method for the assembly of small synthetic genes with repetitive elements: First, a gene of interest is split in silico into small synthons of up to 80 base pairs flanked by Golden-Gate-compatible overhangs. Then, synthons are made by oligo extension and finally assembled into a synthetic gene by Golden Gate Assembly. We demonstrate the method by constructing eight challenging genes with repetitive elements, e.g., multiple repeats of RNA aptamers and RNA origami scaffolds with multiple identical aptamers. The genes range in size from 133 to 456 base pairs and are assembled with fidelities of up to 87.5%. The method was developed to facilitate our own specific research but may be of general use for constructing challenging and repetitive genes and, thus, a valuable addition to the molecular cloning toolbox.

Context-dependent redesign of robust synthetic gene circuits.

Cells provide dynamic platforms for executing exogenous genetic programs in synthetic biology, resulting in highly context-dependent circuit performance. Recent years have seen an increasing interest in understanding the intricacies of circuit-host relationships, their influence on the synthetic bioengineering workflow, and in devising strategies to alleviate undesired effects. We provide an overview of how emerging circuit-host interactions, such as growth feedback and resource competition, impact both deterministic and stochastic circuit behaviors. We also emphasize control strategies for mitigating these unwanted effects. This review summarizes the latest advances and the current state of host-aware and resource-aware design of synthetic gene circuits.

Protein design meets biosecurity.

The power and accuracy of computational protein design have been increasing rapidly with the incorporation of artificial intelligence (AI) approaches. This promises to transform biotechnology, enabling advances across sustainability and medicine. DNA synthesis plays a critical role in materializing designed proteins. However, as with all major revolutionary changes, this technology is vulnerable to misuse and the production of dangerous biological agents. To enable the full benefits of this revolution while mitigating risks that may emerge, all synthetic gene sequence and synthesis data should be collected and stored in repositories that are only queried in emergencies to ensure that protein design proceeds in a safe, secure, and trustworthy manner.

Synthetic Gene Circuits for Regulation of Next-Generation Cell-Based Therapeutics.

Arming human cells with synthetic gene circuits enables to expand their capacity to execute superior sensing and response actions, offering tremendous potential for innovative cellular therapeutics. This can be achieved by assembling components from an ever-expanding molecular toolkit, incorporating switches based on transcriptional, translational, or post-translational control mechanisms. This review provides examples from the three classes of switches, and discusses their advantages and limitations to regulate the activity of therapeutic cells in vivo. Genetic switches designed to recognize internal disease-associated signals often encode intricate actuation programs that orchestrate a reduction in the sensed signal, establishing a closed-loop architecture. Conversely, switches engineered to detect external molecular or physical cues operate in an open-loop fashion, switching on or off upon signal exposure. The integration of such synthetic gene circuits into the next generation of chimeric antigen receptor T-cells is already enabling precise calibration of immune responses in terms of magnitude and timing, thereby improving the potency and safety of therapeutic cells. Furthermore, pre-clinical engineered cells targeting other chronic diseases are gathering increasing attention, and this review discusses the path forward for achieving clinical success. With synthetic biology at the forefront, cellular therapeutics holds great promise for groundbreaking treatments.

Efficient design of synthetic gene circuits under cell-to-cell variability.

BACKGROUND: Synthetic biologists use and combine diverse biological parts to build systems such as genetic circuits that perform desirable functions in, for example, biomedical or industrial applications. Computer-aided design methods have been developed to help choose appropriate network structures and biological parts for a given design objective. However, they almost always model the behavior of the network in an average cell, despite pervasive cell-to-cell variability. RESULTS: Here, we present a computational framework and an efficient algorithm to guide the design of synthetic biological circuits while accounting for cell-to-cell variability explicitly. Our design method integrates a Non-linear Mixed-Effects (NLME) framework into a Markov Chain Monte-Carlo (MCMC) algorithm for design based on ordinary differential equation (ODE) models. The analysis of a recently developed transcriptional controller demonstrates first insights into design guidelines when trying to achieve reliable performance under cell-to-cell variability. CONCLUSION: We anticipate that our method not only facilitates the rational design of synthetic networks under cell-to-cell variability, but also enables novel applications by supporting design objectives that specify the desired behavior of cell populations.

Researchers close in on fully artificial yeast genome.

Cells can survive when nearly half their chromosomes are humanmade.

Adaptive DNA amplification of synthetic gene circuit opens a way to overcome cancer chemoresistance.

Drug resistance continues to impede the success of cancer treatments, creating a need for experimental model systems that are broad, yet simple, to allow the identification of mechanisms and novel countermeasures applicable to many cancer types. To address these needs, we investigated a set of engineered mammalian cell lines with synthetic gene circuits integrated into their genome that evolved resistance to Puromycin. We identified DNA amplification as the mechanism underlying drug resistance in 4 out of 6 replicate populations. Triplex-forming oligonucleotide (TFO) treatment combined with Puromycin could efficiently suppress the growth of cell populations with DNA amplification. Similar observations in human cancer cell lines suggest that TFOs could be broadly applicable to mitigate drug resistance, one of the major difficulties in treating cancer.

Automated Design of Synthetic Gene Circuits in the Presence of Molecular Noise.

Microorganisms (mainly bacteria and yeast) are frequently used as hosts for genetic constructs in synthetic biology applications. Molecular noise might have a significant effect on the dynamics of gene regulation in microbial cells, mainly attributed to the low copy numbers of mRNA species involved. However, the inclusion of molecular noise in the automated design of biocircuits is not a common practice due to the computational burden linked to the chemical master equation describing the dynamics of stochastic gene regulatory circuits. Here, we address the automated design of synthetic gene circuits under the effect of molecular noise combining a mixed integer nonlinear global optimization method with a partial integro-differential equation model describing the evolution of stochastic gene regulatory systems that approximates very efficiently the chemical master equation. We demonstrate the performance of the proposed methodology through a number of examples of relevance in synthetic biology, including different bimodal stochastic gene switches, robust stochastic oscillators, and circuits capable of achieving biochemical adaptation under noise.

Dynamic context-dependent regulation of auxin feedback signaling in synthetic gene circuits.

Phytohormone auxin plays a key role in regulating plant organogenesis. However, understanding the complex feedback signaling network that involves at least 29 proteins in Arabidopsis in the dynamic context remains a significant challenge. To address this, we transplanted an auxin-responsive feedback circuit responsible for plant organogenesis into yeast. By generating dynamic microfluidic conditions controlling gene expression, protein degradation, and binding affinity of auxin response factors to DNA, we illuminate feedback signal processing principles in hormone-driven gene expression. In particular, we recorded the regulatory mode shift between stimuli counting and rapid signal integration that is context-dependent. Overall, our study offers mechanistic insights into dynamic auxin response interplay trackable by synthetic gene circuits, thereby offering instructions for engineering plant architecture.

Synthetic Gene Circuits Combining CRISPR Interference and CRISPR Activation in E. coli: Importance of Equal Guide RNA Binding Affinities to Avoid Context-Dependent Effects.

Gene expression control based on clustered regularly interspaced short palindromic repeats (CRISPR) has emerged as a powerful approach for constructing synthetic gene circuits. While the use of CRISPR interference (CRISPRi) is already well-established in prokaryotic circuits, CRISPR activation (CRISPRa) is less mature, and a combination of the two in the same circuits is only just emerging. Here, we report that combining CRISPRi with SoxS-based CRISPRa in Escherichia coli can lead to context-dependent effects due to different affinities in the formation of CRISPRa and CRISPRi complexes, resulting in loss of predictable behavior. We show that this effect can be avoided by using the same scaffold guide RNA structure for both complexes.

Expression of Synthetic cyp102A1-LG23 Gene and Functional Analysis of Recombinant Cytochrome P450 BM3-LG23 in the Actinobacterium Mycolicibacterium smegmatis.

Cytochrome CYP102A1 (P450 BM3) of Priestia megaterium (bas. Bacillus megaterium) has several unique functional features and thus provides an ideal object for directed evolution and other synthetic applications. Previously, the CYP102A1-LG23 mutant with 14 mutations in the heme part was obtained that hydroxylates several androstanes at C7ß with the formation of products with the anti-inflammatory and neuroprotective activities. In this study, synthetic cyp102A1-LG23 gene encoding the P450 BM3 mutant was expressed as a component of either monocistronic operon or bicistronic operon containing the gdh (glucose dehydrogenase, GDH) or zwf2 (glucose 6-phosphate dehydrogenase, G6PD) gene in Mycolicibacterium smegmatis BD cells. The recombinant bacteria were able hydroxylate androst-4-ene-3,17-dione (AD) into 7ß-OH-AD. Their biocatalytic activity was increased twice by increasing the solubility of CYP102A1-LG23 protein in the cells and supplementing the cells with the additional cofactor regeneration system by introducing GDH and G6PD. The maximum 7ß-OH-AD yield (37.68 mol%) was achieved by co-expression of cyp102A1-LG23 and gdh genes in M. smegmatis. These results demonstrate the possibility of using synthetic genes to obtain recombinant enzymes and expand our understanding of the processes involved in steroid hydroxylation by bacterial cytochromes. The data obtained can be used to develop new approaches for microbiological production of 7ß-hydroxylated steroids in genetically modified Mycolicibacterium species.

Establishing artificial gene connections through RNA displacement-assembly-controlled CRISPR/Cas9 function.

Construction of synthetic circuits that can reprogram genetic networks and signal pathways is a long-term goal for manipulation of biosystems. However, it is still highly challenging to build artificial genetic communications among endogenous RNA species due to their sequence independence and structural diversities. Here we report an RNA-based synthetic circuit that can establish regulatory linkages between expression of endogenous genes in both Escherichiacoli and mammalian cells. This design employs a displacement-assembly approach to modulate the activity of guide RNA for function control of CRISPR/Cas9. Our experiments demonstrate the great effectiveness of this RNA circuit for building artificial connections between expression of originally unrelated genes. Both exogenous and naturally occurring RNAs, including small/microRNAs and long mRNAs, are capable of controlling expression of another endogenous gene through this approach. Moreover, an artificial signal pathway inside mammalian cells is also successfully established to control cell apoptosis through our designed synthetic circuit. This study provides a general strategy for constructing synthetic RNA circuits, which can introduce artificial connections into the genetic networks of mammalian cells and alter the cellular phenotypes.