Microfluidic approaches for synthetic gene circuits' construction and analysis

Background:Microfluidic systems have advantages such as a high throughput,small reaction volume,and precise control of the cellular position and environment.These advantages have allowed microfluidics to be widely used in several fields of synthetic biology in recent years.Results'.In this article,we reviewed the microfluidic-based methods for synthetic biology from two aspects:the construction of synthetic gene circuits and the analysis of synthetic gene systems.We used some examples to illuminate the progresses and challenges in the steps of synthetic gene circuits construction and approaches of gene expression analysis with microfluidic systems.Conclusion:Comparing to traditional methods,microfluidic tools promise great advantages in the synthetic genetic circuit building and analysis process.Moreover,new microfluidic systems together with the mathematical modeling of synthetic circuits or consortiums are desirable to perform complex genetic circuit construction and understand the natural gene regulation in cells and population interactions better.

纳米材料助力合成生物学的生物医学应用

合成生物学是借助基因工具改造活细胞和生物体的学科,其经历了蓬勃发展阶段,在生物医学领域得到广泛应用,包括新型生物传感器和生物材料设计,以及最新临床治疗药物和疫苗的开发.纳米材料具有独特的物理、化学和生物特性,在拓展合成生物学的生物医学应用场景上具有巨大的潜力,可以提高治疗剂的生产效率,并增强改造生物体的功能.在此,我们简要概述了纳米材料应用于合成生物学领域的最新进展,主要涵盖纳米材料作为递送载体、信号转导器和功能增强剂的角色及其制备过程和性能特点.本综述首先强调了纳米材料作为基因载体的最新成果,包括有机、无机和仿生递送系统;其次,回顾了纳米材料介导的刺激响应型基因表达调控的研究;第三,总结了在可编程的杂化生物活性材料方面的开创性工作,包括纳米材料/细菌杂合系统和纳米材料/哺乳动物细胞杂合系统;最后,讨论了该领域当前面临的挑战,并从个人观点展望了未来的发展前景.

Synthetic biology approaches for improving the specificity and efficacy of cancer immunotherapy

Immunotherapy has shown robust efficacy in treating a broad spectrum of hematological and solid cancers.Despite the transformative impact of immunotherapy on cancer treatment,several outstanding challenges remain.These challenges include on-target off-tumor toxicity,systemic toxicity,and the complexity of achieving potent and sustainable therapeutic efficacy.Synthetic biology has emerged as a promising approach to overcome these obstacles,offering innovative tools for engineering living cells with customized functions.This review provides an overview of the current landscape and future prospects of cancer immunotherapy,particularly emphasizing the role of synthetic biology in augmenting its specificity,controllability,and efficacy.We delineate and discuss two principal synthetic biology strategies:those targeting tumor surface antigens with engineered immune cells and those detecting intratumoral disease signatures with engineered gene circuits.This review concludes with a forwardlooking perspective on the enduring challenges in cancer immunotherapy and the potential breakthroughs that synthetic biology may contribute to the field.

Engineering synthetic optogenetic networks for biomedical applications

Background： Recently, optogenetics based on genetically encoded photosensitive proteins has emerged as an innovative technology platform to revolutionize manipulation of cellular behavior through fight stimulation. It has enabled user defined control of various cellular behaviors with spatiotemporal precision and minimal invasiveness, creating unprecedented opportunities for biomedical applications. Results： This article reviews current advances in optogenetic networks designed for the treatment of human diseases. We highlight the advantages of these optogenetic networks, as well as emerging questions and future perspectives. Conclusions： Various optogenetic systems have been engineered to control biological processes at all levels using light and applied for numerous diseases, such as metabolic disorders, cancer, and immune diseases. Continued development of optogenetic modules will be necessary to precisely control of gene expression magnitude towards clinical medical practice in the context of real-world problems.

Recent advances in bacterial therapeutics based on sense and response

Intelligent drug delivery is a promising strategy for cancer therapies.In recent years,with the rapid development of synthetic biology,some properties of bacteria,such as gene operability,excellent tumor colonization ability,and host-independent structure,make them ideal intelligent drug carriers and have attracted extensive attention.By implanting condition-responsive elements or gene circuits into bacteria,they can synthesize or release drugs by sensing stimuli.Therefore,compared with traditional drug delivery,the usage of bacteria for drug loading has better targeting ability and controllability,and can cope with the complex delivery environment of the body to achieve the intelligent delivery of drugs.This review mainly introduces the development of bacterial-based drug delivery carriers,including mechanisms of bacterial targeting to tumor colonization,gene deletions or mutations,environment-responsive elements,and gene circuits.Meanwhile,we summarize the challenges and prospects faced by bacteria in clinical research,and hope to provide ideas for clinical translation.

Enabling technology and core theory of synthetic biology

Synthetic biology provides a new paradigm for life science research(“build to learn”)and opens the future journey of biotechnology(“build to use”).Here,we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology,including synthesis and assembly of a genome,DNA storage,gene editing,molecular evolution and de novo design of function proteins,cell and gene circuit engineering,cell-free synthetic biology,artificial intelligence(AI)-aided synthetic biology,as well as biofoundries.We also introduce the concept of quantitative synthetic biology,which is guiding synthetic biology towards increased accuracy and predictability or the real rational design.We conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.

构建重定向的NF-κB/OIP5表达程序以增强化疗对膀胱癌的治疗效果

NF-κB是重要的转录调控因子,对下游肿瘤耐药基因起关键调控作用.基于CRISPR基因编辑技术,可在膀胱癌中构建人工合成的基因表达程序,以重编程肿瘤药物应答过程.本研究发现Opa相互作用蛋白5(OIP5)在NF-κB激活后上调,并引起膀胱癌对长春新碱耐药.通过整合连接靶向OIP5的引导RNA与NF-κB的适配体RNA,成功获得兼具编码靶向位点和调控功能的模块化RNA.此模块化RNA可识别并与长春新碱活化的NF-κB相结合,促使NF-κB从上调逆转为下调OIP5表达,并阻断多条NF-κB介导的耐药通路,从而高效阻止肿瘤耐药的发生.本研究还开发了一种纳米递药系统共递送模块化RNA和长春新碱,体内外实验表明两者协同增强药物的抗肿瘤疗效.通过基于纳米递药系统的联合治疗策略,我们证实了CRISPR技术在膀胱癌中构建人工合成基因表达程序的有效性,可重编程肿瘤的药物应答过程,达到增强膀胱癌化疗敏感性的目的.

Application of synthetic biology in bladder cancer

Bladder cancer(BC)is the most common malignant tumor of the genitourinary system.The age of individuals diagnosed with BC tends to decrease in recent years.A variety of standard therapeutic options are available for the clinical management of BC,but limitations exist.It is difficult to surgically eliminate small lesions,while radiation and chemotherapy damage normal tissues,leading to severe side effects.Therefore,new approaches are required to improve the efficacy and specificity of BC treatment.Synthetic biology is a field emerging in the last decade that refers to biological elements,devices,and materials that are artificially synthesized according to users’needs.In this review,we discuss how to utilize genetic elements to regulate BC-related gene expression periodically and quantitatively to inhibit the initiation and progression of BC.In addition,the design and construction of gene circuits to distinguish cancer cells from normal cells to kill the former but spare the latter are elaborated.Then,we introduce the development of genetically modified T cells for targeted attacks on BC.Finally,synthetic nanomaterials specializing in detecting and killing BC cells are detailed.This review aims to describe the innovative details of the clinical diagnosis and treatment of BC from the perspective of synthetic biology.

Construction, visualization, and analysis of aiological network models in Dynetica

Mathematical modeling has become an increasingly important aspect of biological research. Computer simulations help to improve our understanding of complex systems by testing the validity of proposed mechanisms and generating experimentally testable hypotheses. However, significant overhead is generated by the creation, debugging, and perturbation of these computational models and their parameters, especially for researchers who are unfamiliar with programming or numerical methods. Dynetica 2.0 is a user-friendly dynamic network simulator designed to expedite this process. Models are created and visualized in an easy-to-use graphical interface, which displays all of the species and reactions involved in a graph layout. System inputs and outputs, indicators, and intermediate expressions may be incorporated into the model via the versatile ＂expression variable＂ entity. Models can also be modular, allowing for the quick construction of complex systems from simpler components. Dynetica 2.0 supports a number of deterministic and stochastic algorithms for performing time-course simulations. Additionally, Dynetica 2.0 provides built-in tools for performing sensitivity or dose response analysis for a number of different metrics. Its parameter searching tools can optimize specific objectives of the time course or dose response of the system. Systems can be translated from Dynetica 2.0 into MATLAB code or the Systems Biology Markup Language （SBML） format for further analysis or publication. Finally, since it is written in Java, Dynetica 2.0 is platform independent, allowing for easy sharing and collaboration between researchers.

Rational design of a biosensor circuit with semi-log dose-response function in Escherichia coli

A central goal of synthetic biology is to apply successful principles that have been developed in electronic and chemical engineering to construct basic biological functional modules, and through rational design, to build synthetic biological systems with predetermined functions. Here, we apply the reverse engineering design principle of biological networks to synthesize a gene circuit that executes semi-log dose-response, a logarithmically linear sensing function, in Escherichia coil cells. We first mathematically define the object function semi-log dose-response, and then search for tri-node network topologies that can most robustly execute the object function. The simplest topology, transcriptional coherent feed-forward loop （TCFL）, among the searching results is mathematically analyzed; we find that, in TCFL topology, the semi-log dose-response function arises from the additive effect of logarithmical linearity intervals of Hill functions. TCFL is then genetically implemented in E. coil as a logarithmically linear sensing biosensor for heavy metal ions [mercury （II）]. Functional characterization shows that this rationally designed biosensor circuit works as expected. Through this study we demonstrated the potential application of biological network reverse engineering to broaden the computational power of synthetic biology.