Gene Circuits Research Articles

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.

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.

Homogeneous detection of viral nucleic acid via selective recognition proximity ligation and signal amplification with T7 transcription and CRISPR/Cas12a system

The synthetic biology has employed the synthetic gene networks through engineering to construct various functions in biological systems. However, the use of gene circuits to create sensors for detecting low-abundance targets has been limited due to the lack of signal amplification strategies beyond direct output of detection signals. To address this issue, we introduce a novel method utilizing Selective Recognition Proximity Ligation and signal amplification with T7 Transcription and CRISPR/Cas12a system (SRPL-TraCs), which permits the incorporation of cell-free gene circuits with signal amplification and enables the construction of high-order cascade signal amplification strategy to detect biomarkers in homogeneous systems. Specifically, the SRPL-TraCs utilizes selective recognition proximity ligation with high-fidelity T4 DNA ligase and generates a unique crRNA via T7 transcription, along with target-activated Cas12a/crRNA system to achieve excellent specificity for HIV-1 DNA. With this straightforward synthetic biology-based method, the proposed SRPL-TraCs has the potential to detect numerous other interesting targets beyond the nucleic acids.

Front Cover: Bidirectional Communication between Droplet Interface Bilayers Driven by Cell‐Free Quorum Sensing Gene Circuits (ChemSystemsChem 6/2023)

Front Cover: Bidirectional Communication between Droplet Interface Bilayers Driven by Cell‐Free Quorum Sensing Gene Circuits (ChemSystemsChem 6/2023)

Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease

Genetic variants associated with complex traits are primarily noncoding, and their effects on gene-regulatory activity remain largely uncharacterized. To address this, we profile epigenomic variation of histone mark H3K27ac across 387 brain, heart, muscle and lung samples from Genotype-Tissue Expression (GTEx). We annotate 282 k active regulatory elements (AREs) with tissue-specific activity patterns. We identify 2,436 sex-biased AREs and 5,397 genetically influenced AREs associated with 130 k genetic variants (haQTLs) across tissues. We integrate genetic and epigenomic variation to provide mechanistic insights for disease-associated loci from 55 genome-wide association studies (GWAS), by revealing candidate tissues of action, driver SNPs and impacted AREs. Lastly, we build ARE–gene linking scores based on genetics (gLink scores) and demonstrate their unique ability to prioritize SNP–ARE–gene circuits. Overall, our epigenomic datasets, computational integration and mechanistic predictions provide valuable resources and important insights for understanding the molecular basis of human diseases/traits such as schizophrenia.

In situ immunomodulation of tumors with biosynthetic bacteria promote anti-tumor immunity

Immune checkpoint blockade (ICB) therapy potently revives T cell's response to cancer. However, patients suffered with tumors that had inadequate infiltrated immune cells only receive limited therapeutic benefits from ICB therapy. Synthetic biology promotes the alternative strategy of harnessing tumor-targeting bacteria to synthesize therapeutics to modulate immunity in situ. Herein, we engineered attenuated Salmonella typhimurium VNP20009 with gene circuits to synthetize granulocyte-macrophage colony-stimulating factor (GM-CSF) and interleukin 7 (IL-7) within tumors, which recruited dendritic cells (DCs) and enhanced T cell priming to elicit anti-tumor response. The bacteria-produced GM-CSF stimulated the maturation of bone marrow-derived dendritic cells (BMDCs), while IL-7 promoted the proliferation of spleen isolated T cells and inhibited cytotoxicity T cell apoptosis in vitro. Virtually, engineered VNP20009 prefer to colonize in tumors, and inhibited tumor growth by enhancing DCs and T cell infiltration. Moreover, the tumor-toxic GZMB+ CD8+ T cell and IFN-γ+ CD8+ T cell populations conspicuously increased with the treatment of engineered bacteria. The combination of GM–CSF–IL-7-VNP20009 with PD-1 antibody synergistically stunted the tumor progress and metastasis.

Hybrid Boolean gates show that Cas12c controls transcription activation effectively in the yeast S. cerevisiae.

Among CRISPR-Cas systems, type V CRISPR-Cas12c is of significant interest because Cas12c recognizes a very simple PAM (TN) and has the ability to silence gene expression without cleaving the DNA. We studied how new transcription factors for the yeast Saccharomyces cerevisiae can be built on Cas12c. We found that, upon fusion to a strong activation domain, Cas12c is an efficient activator. Its functionality was proved as a component of hybrid Boolean gates, i.e., logic circuits that mix transcriptional and translational control (the latter reached via tetracycline-responsive riboswitches). Moreover, Cas12c activity can be strongly inhibited by the anti-CRISPR AcrVA1 protein. Thus, Cas12c has the potential to be a new tool to control the activation of gene expression within yeast synthetic gene circuits.

Input-to-state stability of stochastic Markovian jump genetic regulatory networks

The development of gene circuits in logic modules that start enormous output distributions with low signal-to-noise ratios is a difficult problem in engineering. As a result, the gene model depicts the transcription and translation of a single gene produced in the modification of noise in isolated logic modules. Our goal is to construct such networks with all types of connectivity. Further, the impacts of noise on further complex genetic networks have been investigated using stochastic gene models. Using this information as a foundation, our research investigates the input-to-state stability investigation for stochastic Markovian jump genetic regulatory networks with time-varying delay components. The goal of this article is to develop genetic networks with temporal delays, which are crucial for genetic regulation because slow biochemical processes like gene transcription and translation need time to occur. Additionally, the Markovian chain is essential for demonstrating how a system shifts from one mode to another with known transition probabilities. In the stochastic case, some complex systems with random disturbance will occur. Due to this significance the genetic regulatory network with stochastic case is applied to identify the complex behaviour among genes and proteins of the micro perspective. By establishing the Lyapunov functional with Ito’s and Dynkin’s formula, new stability conditions are derived and which is effectively solved by MATLAB toolbox. The efficiency of the suggested technique is demonstrated using a numerical example.

Bidirectional Communication between Droplet Interface Bilayers Driven by Cell‐Free Quorum Sensing Gene Circuits**

AbstractBuilding synthetic multicellular systems using non‐living molecular components is a grand challenge in the field of bottom‐up synthetic biology. Towards this goal, a diverse range of chemistries have been developed to provide mechanisms of intercellular communication and methods to assemble multicellular compartments. However, building bottom‐up synthetic multicellular systems is still challenging because it requires the integration of intercellular reaction networks with compatible cellular compartment properties. In this study, we encapsulated cell‐free expression systems (CFES) expressing two quorum sensing genetic circuits into droplet interface bilayer (DIB) synthetic cells to demonstrate bidirectional communication. We further develop a method of generating custom DIB multicellular structures by acoustic liquid handling to automatically dispense the CFES droplets and show the potential for multiplexing compartmentalized gene circuits for generating heterogeneous populations of cells. Our work provides a step towards building more complex multicellular systems with intercellular communication from the bottom‐up to study and experimentally model biological multiscalar processes.

The σB alternative sigma factor circuit modulates noise to generate different types of pulsing dynamics.

Single-cell approaches are revealing a high degree of heterogeneity, or noise, in gene expression in isogenic bacteria. How gene circuits modulate this noise in gene expression to generate robust output dynamics is unclear. Here we use the Bacillus subtilis alternative sigma factor σB as a model system for understanding the role of noise in generating circuit output dynamics. σB controls the general stress response in B. subtilis and is activated by a range of energy and environmental stresses. Recent single-cell studies have revealed that the circuit can generate two distinct outputs, stochastic pulsing and a single pulse response, but the conditions under which each response is generated are under debate. We implement a stochastic mathematical model of the σB circuit to investigate this and find that the system's core circuit can generate both response types. This is despite one response (stochastic pulsing) being stochastic in nature, and the other (single response pulse) being deterministic. We demonstrate that the main determinant for whichever response is generated is the degree with which the input pathway activates the core circuit, although the noise properties of the input pathway also biases the system towards one or the other type of output. Thus, our work shows how stochastic modelling can reveal the mechanisms behind non-intuitive gene circuit output dynamics.

Cooperative assembly confers regulatory specificity and long-term genetic circuit stability

A ubiquitous feature of eukaryotic transcriptional regulation is cooperative self-assembly between transcription factors (TFs) and DNA cis-regulatory motifs. It is thought that this strategy enables specific regulatory connections to be formed in gene networks between otherwise weakly interacting, low-specificity molecular components. Here, using synthetic gene circuits constructed in yeast, we find that high regulatory specificity can emerge from cooperative, multivalent interactions among artificial zinc-finger-based TFs. We show that circuits "wired" using the strategy of cooperative TF assembly are effectively insulated from aberrant misregulation of the host cell genome. As we demonstrate in experiments and mathematical models, this mechanism is sufficient to rescue circuit-driven fitness defects, resulting in genetic and functional stability of circuits in long-term continuous culture. Our naturally inspired approach offers a simple, generalizable means for building high-fidelity, evolutionarily robust gene circuits that can be scaled to a wide range of host organisms and applications.

Biosynthetic Melanin/Ce6-Based Photothermal and Sonodynamic Therapies Significantly Improved the Anti-Tumor Efficacy.

Photothermal therapy (PTT) and sonodynamic therapy (SDT) are becoming promising therapeutic modalities against various tumors in recent years. However, the single therapeutic modality with SDT or PTT makes it difficult to achieve a satisfactory anti-tumor outcome due to their own inherent limitations, such as poor tissue penetration for the near-infrared (NIR) laser and the limited cytotoxic reactive oxygen species (ROS) generated from conventional sonosensitizers irradiated by ultrasound (US). Here, we successfully biosynthesized melanin with a controllable particle size with genetically engineered bacteria harboring a heat-inducible gene circuit. The biosynthetic melanin with 8 nm size and chlorin e6 (Ce6) was further encapsulated into liposomes and obtained SDT/PTT dual-functional liposomes (designated as MC@Lip). The resulting MC@Lip had an approximately 100 nm particle size, with 74.71% ± 0.54% of encapsulation efficiency for melanin and 94.52% ± 0.78% for Ce6. MC@Lip exhibited efficient 1O2 production and photothermal conversion capability upon receiving irradiation by US and NIR laser, producing significantly enhanced anti-tumor efficacy in vitro and in vivo. Especially, US and NIR laser irradiation of tumors received with MC@Lip lead to complete tumor regression in all tested tumor-bearing mice, indicating the great advantage of the combined use of SDT and PTT. More importantly, MC@Lip possessed good photoacoustic (PA) and fluorescence dual-modal imaging performance, making it possible to treat tumors under imaging guidance. Our study provides a novel approach to synthesize a melanin nanoparticle with controllable size and develops a promising combined SDT/PTT strategy to treat tumors.

Genome-wide identification of core components of ABA signaling and transcriptome analysis reveals gene circuits involved in castor bean (Ricinus communis L.) response to drought

Castor bean (Ricinus communis L.) can withstand long periods of water deficit and high temperatures, and therefore has been recognized as a drought-resistant plant species, allowing the study of gene networks involved in drought response and tolerance. The identification of genes networks related to drought response in this plant may yield important information in the characterization of molecular mechanisms correlating changes in the gene expression with the physiological adaptation processes. In this context, gene families related to abscisic acid (ABA) signaling play a crucial role in developmental and environmental adaptation processes of plants to drought stress. However, the families that function as the core components of ABA signaling, as well as genes networks related to drought response, are not well understood in castor bean. In this study 7 RcPYL, 63 RcPP2C, and 6 RcSnRK2 genes were identified in castor bean genome, which was further supported by chromosomal distribution, gene structure, evolutionary relationships, and conserved motif analyses. The castor bean general expression profile was investigated by RNAseq in root and leaf tissues in response to drought stress. These analyses allowed the identification of genes differentially expressed, including genes from the ABA signaling core, genes related to photosynthesis, cell wall, energy transduction, antioxidant response, and transcription factors. These analyses provide new insights into the core components of ABA signaling in castor bean, allow the identification of several molecular responses associated with the high physiological adaptation of castor bean to drought stress, and contribute to the identification of candidate genes for genetic improvement.

Noise Minimization in Cell-Free Gene Expression.

Biochemical reactions that involve small numbers of molecules are accompanied by a degree of inherent randomness that results in noisy reaction outcomes. In synthetic biology, the ability to minimize noise particularly during the reconstitution of future synthetic protocells is an outstanding challenge to secure robust and reproducible behavior. Here we show that by encapsulation of a bacterial cell-free gene expression system in water-in-oil droplets, in vitro-synthesized MazF reduces cell-free gene expression noise >2-fold. With stochastic simulations we identify that this noise minimization acts through both increased degradation and the autoregulatory feedback of MazF. Specifically, we find that the expression of MazF enhances the degradation rate of mRNA up to 18-fold in a sequence-dependent manner. This sequence specificity of MazF would allow targeted noise control, making it ideal to integrate into synthetic gene networks. Therefore, including MazF production in synthetic biology can significantly minimize gene expression noise, impacting future design principles of more complex cell-free gene circuits.

Multidimensional characterization of inducible promoters and a highly light-sensitive LOV-transcription factor

The ability to independently control the expression of different genes is important for quantitative biology. Using budding yeast, we characterize GAL1pr, GALL, MET3pr, CUP1pr, PHO5pr, tetOpr, terminator-tetOpr, Z3EV, blue-light inducible optogenetic systems El222-LIP, El222-GLIP, and red-light inducible PhyB-PIF3. We report kinetic parameters, noise scaling, impact on growth, and the fundamental leakiness of each system using an intuitive unit, maxGAL1. We uncover disadvantages of widely used tools, e.g., nonmonotonic activity of MET3pr and GALL, slow off kinetics of the doxycycline- and estradiol-inducible systems tetOpr and Z3EV, and high variability of PHO5pr and red-light activated PhyB-PIF3 system. We introduce two previously uncharacterized systems: strongLOV, a more light-sensitive El222 mutant, and ARG3pr, which is induced in the absence of arginine or presence of methionine. To demonstrate fine control over gene circuits, we experimentally tune the time between cell cycle Start and mitosis, artificially simulating near-wild-type timing. All strains, constructs, code, and data (https://promoter-benchmark.epfl.ch/) are made available.

Growth feedback confers cooperativity in resource-competing synthetic gene circuits

Modularity is a key concept in designing synthetic gene circuits, as it allows for constructing complex molecular systems using well-characterized building blocks. One of the major challenges in this field is that these modular components often do not function as expected when assembled into larger circuits. One of the major issues is caused by resource competition, where multiple genes in the circuit compete for the same limited cellular resources, such as transcription factors and ribosomes. In addition, the mutual inhibition between synthetic gene circuits and cell growth results in growth feedback that significantly impacts its host-circuit dynamics. However, the complexity of the gene circuit dynamics under intertwined resource competition and growth feedback is not fully understood. This study developed a theoretical framework to examine the dynamics of synthetic gene circuits by considering both growth feedback and resource competition. Our results suggest a cooperative behavior between resource-competing gene circuits under growth feedback. Cooperation or competition is non-monotonically determined by the metabolic burden threshold. These two diverse effects could lead to the activation or deactivation of one circuit by the other. Lastly, the cooperativity mediated by growth feedback can attenuate the winner-takes-all resource competition. These findings show that coupling growth feedback and resource competition plays a crucial role in the dynamics of the host-circuit system, and understanding its effects helps control unexpected gene expression behaviors.

Bayesian Optimization for Design of Multiscale Biological Circuits.

Recent advances in synthetic biology have enabled the construction of molecular circuits that operate across multiple scales of cellular organization, such as gene regulation, signaling pathways, and cellular metabolism. Computational optimization can effectively aid the design process, but current methods are generally unsuited for systems with multiple temporal or concentration scales, as these are slow to simulate due to their numerical stiffness. Here, we present a machine learning method for the efficient optimization of biological circuits across scales. The method relies on Bayesian optimization, a technique commonly used to fine-tune deep neural networks, to learn the shape of a performance landscape and iteratively navigate the design space toward an optimal circuit. This strategy allows the joint optimization of both circuit architecture and parameters, and provides a feasible approach to solve a highly nonconvex optimization problem in a mixed-integer input space. We illustrate the applicability of the method on several gene circuits for controlling biosynthetic pathways with strong nonlinearities, multiple interacting scales, and using various performance objectives. The method efficiently handles large multiscale problems and enables parametric sweeps to assess circuit robustness to perturbations, serving as an efficient in silico screening method prior to experimental implementation.

Comments on several review eBooks promoting a novel kinetic modelling framework of metabolic processes and of genetic regulatory circuits in living cells

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Rewired Gene Circuit Dramatically Increases Yeast Cell Longevity

Genetic Engineering & Biotechnology NewsVol. 43, No. 6 News & AnalysisRewired Gene Circuit Dramatically Increases Yeast Cell LongevityPublished Online:5 Jun 2023https://doi.org/10.1089/gen.43.06.03AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Rewired Gene Circuit Dramatically Increases Yeast Cell Longevity." Genetic Engineering & Biotechnology News, 43(6), p. 10FiguresReferencesRelatedDetails Volume 43Issue 6Jun 2023 Information© 2023 by GEN PublishingTo cite this article:Rewired Gene Circuit Dramatically Increases Yeast Cell Longevity.Genetic Engineering & Biotechnology News.Jun 2023.10-10.http://doi.org/10.1089/gen.43.06.03Published in Volume: 43 Issue 6: June 5, 2023PDF download

Nonmonotone invasion landscape by noise-aware control of metastasis activator levels

A major pharmacological assumption is that lowering disease-promoting protein levels is generally beneficial. For example, inhibiting metastasis activator BACH1 is proposed to decrease cancer metastases. Testing such assumptions requires approaches to measure disease phenotypes while precisely adjusting disease-promoting protein levels. Here we developed a two-step strategy to integrate protein-level tuning, noise-aware synthetic gene circuits into a well-defined human genomic safe harbor locus. Unexpectedly, engineered MDA-MB-231 metastatic human breast cancer cells become more, then less and then more invasive as we tune BACH1 levels up, irrespective of the native BACH1. BACH1 expression shifts in invading cells, and expression of BACH1ʼs transcriptional targets confirm BACH1ʼs nonmonotone phenotypic and regulatory effects. Thus, chemical inhibition of BACH1 could have unwanted effects on invasion. Additionally, BACH1ʼs expression variability aids invasion at high BACH1 expression. Overall, precisely engineered, noise-aware protein-level control is necessary and important to unravel disease effects of genes to improve clinical drug efficacy.