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Significant research progress in synthetic biology DING Mingzhu, LI Bingzhi, WANG Ying, XIE Zexiong, LIU Duo, YUAN Yingjin Synthetic Biology Journal    2020, 1 (1): 7-28.   DOI: 10.12211/2096-8280.2020-057 Abstract （8086）   HTML （1484）    PDF（pc） （3953KB）（10987）       Knowledge map    Save As an emerging, interdisciplinary field, synthetic biology has made great advances in many directions due to wide acceptance of its core principles and rapid progress in DNA synthesis. In this paper, recent development in gene circuits, genome design and synthesis, cell factories, and synthetic microbial consortia is reviewed. The complexity of artificial gene circuits that can be designed and constructed is gradually increasing with more refined control. Synthetic genomes are routinely assembled, expanding from prokaryotes (Mycoplasma to Escherichia coli) to eukaryotes (Saccharomyces cerevisiae), and improved capacity in genome design promotes the research of biological evolution. Metabolic pathways of ever-increasing lengths are constructed based on modularization and orthogonality principles to produce molecules of complex structures, and fundamental rewiring of cellular metabolism is performed for enhanced robustness and compatibility. The design and construction of synthetic microbial consortia have been expanded from two-species systems to multi-species systems, so that more sophisticated functions can be achieved. At the end of this paper, new research directions resulted from the interdisciplinary integration of synthetic biology and other disciplines are discussed. Table and Figures | Reference | Related Articles | Metrics

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From chemical synthesis to biosynthesis: trends toward total synthesis of natural products ZHANG Faguang, QU Ge, SUN Zhoutong, MA Jun′an Synthetic Biology Journal    2021, 2 (5): 674-696.   DOI: 10.12211/2096-8280.2021-039 Abstract （7828）   HTML （642）    PDF（pc） （6155KB）（5498）       Knowledge map    Save The complexity and diversity of natural products have made them a rich source for drug and agrochemical discovery. To overcome the supplying limitation of natural resources, tremendous effort has been made by the academic and industrial communities during the past two centuries for the total artificial synthesis of natural products. In this regard, total chemical synthesis has achieved significant progress, and numerous highly complex natural products have been synthesized through different chemical processes. Despite these great achievements in total chemical synthesis, there are still many challenges including expensive chemical reagents, harsh reaction conditions, difficult control on stereoselectivity, long synthetic route, and low product yield. Notably, the development of synthetic biology has allowed more and more natural products to be produced through biological cell factories, which provides a new and complementary strategy for the synthesis of natural products at a large scale. This review critically comments on the representative advances in total chemical synthesis of natural products (Section 1), and then highlight major progress and trends in the biosynthesis of pharmaceutically important natural products (Sections 2 and 3). In Section 2.1, we selected the production of penicillin, erythromycin, and avermectin as examples to analyze the modification and optimization of natural product biosynthetic pathways. The discovery and utilization of secondary metabolites from microorganisms has been a continuous driving force in the field of natural products. Notably, significant progress has been made in the total biosynthesis of natural products from secondary metabolism via the genetic manipulation of microbial cells. In Section 2.2, we selected Vitamin B12 and Tropane alkaloids as examples to demonstrate the use of heterologous expression and biological production for natural product synthesis. In recent years, on the basis of analyzing the structure of natural products in animals, plants, and microorganisms, great advances have emerged in exploring their biochemical reaction mechanisms and synthetic routes. More importantly, expressing and regulating the relative genes in heterologous microbial cells have enabled the complete biosynthesis of many natural products. Furthermore, in Section 3, human insulin, artemisinin, saframycin, azaphilone, kainic acid, and podophyllotoxin were selected as examples to showcase the power of merging chemical and biological processes for the total synthesis of natural products. Although there are still many challenges in the total synthesis of new and complex natural products, biosynthesis will ultimately play a significant role in the construction of natural molecules and their relative analogues. By taking advantage of the merits with organic chemistry, synthetic biology, and artificial intelligence, the development of highly efficient and automatic biosynthesis could be a trend in this field. Table and Figures | Reference | Related Articles | Metrics

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DNA information storage： bridging biological and digital world HAN Mingzhe, CHEN Weigang, SONG Lifu, LI Bingzhi, YUAN Yingjin Synthetic Biology Journal    2021, 2 (3): 309-322.   DOI: 10.12211/2096-8280.2021-001 Abstract （6835）   HTML （597）    PDF（pc） （3021KB）（4085）       Knowledge map    Save The external preservation of information enables reliable inheritance of human thoughts, playing important roles in the progress of human civilization. Starting from tying knots in ropes to storing data in magnetic and optical media, these technologies have documented and will continue to record the splendid civilization. However, driven by the global digitalization, the global data volume is growing rapidly and challenging the storage capability of existing storage technologies. DNA, as the natural carrier of genetic information, is believed to be a potential candidate to deal with the data storage challenge due to the revealed high density, long-term duration and low maintaining cost features. In this review, we first describe the fundamental principles and technical processes of DNA information storage. The pivotal position of DNA information storage bridging the biological and digital world is also pointed out. Then, according to the different characteristics of data writing and reading, we categorize these technologies into three storage modes, termed as "DNA hard drive", "DNA compact disc" and "DNA tape", by analogy with the popular storage media correspondingly. "DNA hard drive" mode shows the potential in the volume enlargement of the existing information storage system using oligonucleotide pools. "DNA compact disc" mode provides direct in vivo processing on DNA data storage enabling massive data distribution at low cost. "DNA tape" mode provides intracellular information recoding solutions, which may promote the future developments of cellular computing and communication. The up-to-date progress of these three modes is also summarized. We then discuss the main obstacles and potential technical routes towards practical applications of DNA information storage. We envision a cheaper, faster DNA information storage technology, and its appropriate integration with information storage systems in the future. Finally, we conclude that DNA information storage is a cutting-edge interdisciplinary technology and hope this review can bring more focus and research efforts from various fields to DNA information storage. Table and Figures | Reference | Related Articles | Metrics

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Microbial promoter engineering strategies in synthetic biology YU Huimin, ZHENG Yukun, DU Yan, WANG Miaomiao, LIANG Youxiang Synthetic Biology Journal    2021, 2 (4): 598-611.   DOI: 10.12211/2096-8280.2020-092 Abstract （6323）   HTML （689）    PDF（pc） （1858KB）（7866）       Knowledge map    Save Synthetic biology is of vital importance to the green biomanufacturing industry and sustainable development strategies of our country. Promoter is the core-component of synthetic biology, playing a significant role in highly efficient and fine-tuning expression and regulation of target genes at the transcriptional level. Herein we summarized and discussed the key progress and future frontiers of microbial promoter engineering, particularly for prokaryotic microorganisms. Firstly, we introduced the basic DNA sequence characteristics of promoters and the regular mechanism for promoter recognition and transcription-initiation by RNA polymerase sigma factors. Inducible mechanisms for both negative and positive regulation were particularly highlighted with the typical lac operator of Escherichia coli as an example. Then, effective strategies for obtaining improved-promoters were summarized, which were roughly divided into two categories: endogenous promoter mutation and heterologous promoter replacement. For the endogenous promoter mutation, the following strategies, e.g. point mutation toward sigma factor consensus sequence, coupling optimization of -35 and -10 regions with RBS sequence, random mutation or saturation mutagenesis of UP element or spacer sequences accompanying with promoter library construction and high-throughput screening were emphasized. For the heterologous promoter replacement, strategies such as substituting the native promoter into stronger ones from other microorganisms, introducing phage-source chimeric promoters, tuning the constitutive promoter into inducible pattern and integrating positive regulator(s), were mainly discussed. We further sorted out the representative inducers for inducible promoters reported so far, including both chemical molecules and physical signals. Progress in constitutive promoters of non-model and model microbial organisms were simply summarized as well. Next, arising from the breakthrough development of dynamic metabolic regulation and artificial intelligence (AI), we proposed that the innovative research on identification and evolution of new and unique promoters with dynamic-response features and AI de novo design for promoters with novel/superior functions will be the new frontiers of promoter engineering. Finally, we analyzed the challenging scientific issues in the microbial promoter engineering, from the viewpoint of both basic research and large-scale applications; and further discussed the research priority coupling with the vigorous development of synthetic biology. Table and Figures | Reference | Related Articles | Metrics

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Research advances in biosynthesis of natural product drugs within the past decade FENG Jin, PAN Haixue, TANG Gongli Synthetic Biology Journal    2024, 5 (3): 408-446.   DOI: 10.12211/2096-8280.2023-092 Abstract （5782）   HTML （545）    PDF（pc） （9525KB）（4024）       Knowledge map    Save Natural products have long been considered as an important source for potential drugs. In history, natural products and their structural analogs have contributed substantially to the treatment of various diseases, especially cancers and infectious diseases. After a long history of applications, people have gradually begun to explore active ingredients in natural products that truly exert therapeutic effects, and discovered a series of functional compounds, such as morphine, quinine, ephedrine, etc. Over the past two hundred years, the discovery and research of natural products has undergone tremendous changes, from traditional identification and isolation methods to multidisciplinary approaches in the modern genomic era. Strategies for discovering natural products and tools for their prediction have been developed continuously. Although many novel and active natural products have been mined and discovered in the past two decades, considering the huge reserve of natural products in nature, a large number of genes or gene clusters encoding key enzymes for the biosynthesis of natural products have not yet been characterized, and both terrestrial and marine natural product resources are to be explored. Compared with traditional chemically synthesized molecules, natural products possess diverse skeletons for structural complexity, which have shown remarkable advantages in the discovery of new drugs. While there are still many challenges in discovering new drugs from natural products, such as the effective mining of molecules with new structural features, identification and isolation of functional natural products with trace abundance, derivatization of natural product analogs for exploring connections between their structures and activities, and the complete synthesis of complicated active natural products at large scales, etc., the emergence of novel analytical technologies and mining strategies is expected to substantially renovate natural product discovery. This review comments on the natural product drugs and semisynthetic drugs derived from natural products approved by the U.S. Food and Drug Administration within the past decade from January 2014 to October 2023, and provides an overview on the research progress on the biosynthesis of these natural products and their precursors. In addition, important progress in the biosynthesis of some drugs approved by FDA before is also briefly summarized. An in-depth understanding of the biosynthetic pathways and mechanisms underlying their efficacy is expected to provide valuable insights for the discovery and research of more new drugs in the future. Table and Figures | Reference | Related Articles | Metrics

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Advances of CRISPR gene editing in microbial synthetic biology LI Yang, SHEN Xiaolin, SUN Xinxiao, YUAN Qipeng, YAN Yajun, WANG Jia Synthetic Biology Journal    2021, 2 (1): 106-120.   DOI: 10.12211/2096-8280.2020-039 Abstract （5573）   HTML （475）    PDF（pc） （2241KB）（5167）       Knowledge map    Save With the increase of global consumption on fossil resources for energy products and chemicals and their consequent impact on environment, construction of microbial cell factories for efficient production of biofuels and bio-based chemicals from renewable sources has gained much attention. Pathway engineering of the hosts, such as over-expression of key genes, disruption of competing pathways and integration of heterologous pathways, plays significant role in fulfilling such a purpose. Successful implementation of these pathway engineering strategies requires efficient and accurate gene editing tools. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) systems are a powerful gene editing strategy that was found in prokaryotic organisms such as archaea and bacteria, which provide adaptive immunity against foreign elements. When host cells are infected by viruses, a small sequence of the viral genome is integrated into the CRISPR locus to immunize the host cells, and this small sequence is transcribed into small RNA guide that directs the cleavage of the viral DNA by the Cas nuclease. Inspired by the natural talent, many modified CRISPR systems have been developed to modify genes and genomes, including knock-in, knock-down, large deletions, indels, replacements and chromosomal rearrangements. In this review, we briefly comment on the technical basis and advances in CRISPR-related genome editing tools applied for constructing microbial cell factories, with a focus on the CRISPR-based tools for metabolic engineering of the model organisms E. coli and S. cerevisiae. Furthermore, we highlight major challenges in developing CRISPR tools for multiplex genome editing and sophisticated expression regulation. Finally, we propose future perspectives on the application of CRISPR-based technologies for constructing microbial ecosystems toward high production of desired chemicals. We intend to provide insights and ideas for developing CRISPR-related genome editing tools to better serve the construction of efficient microbial cell factories. Table and Figures | Reference | Related Articles | Metrics

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Recent progress of synthetic biology applications in microbial pharmaceuticals research RAO Cong, YUN Xuan, YU Yi, DENG Zixin Synthetic Biology Journal    2020, 1 (1): 92-102.   DOI: 10.12211/2096-8280.2020-036 Abstract （5513）   HTML （559）    PDF（pc） （1980KB）（4680）       Knowledge map    Save Microbial natural products are a major source in the innovation of novel pharmaceuticals, including anti-bacterial, anti-tumor, and immunosuppressive agents for clinical use. Currently, the development of microbial drugs is facing significant challenges due to the growing prevalence of multidrug-resistant bacteria, the continuous emergence of new pathogens and viruses, and the increasing difficulties in the discovery of natural products with new scaffolds. Synthetic biology is an emerging interdisciplinary research area leading to great breakthrough in the field of biomedical sciences in the 21st century, which provides new methods and ideas for drug discovery and development. The application of synthetic biology could unlock the potential of natural product mining, design new biosynthetic routes, and generate much more “unnatural” natural products and structural analogs. This review summarizes the technical innovations of synthetic biology in the field of microbial pharmaceuticals, and its applications in the mining, biosynthesis, and new scaffold generation of aminoglycoside antibiotics, nucleotide antibiotics, ribosomally synthesized and posttranslationally modified peptides, terpenoids, and polyketides in the last five years. Table and Figures | Reference | Related Articles | Metrics

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Enzyme engineering in the age of artificial intelligence KANG Liqi, TAN Pan, HONG Liang Synthetic Biology Journal    2023, 4 (3): 524-534.   DOI: 10.12211/2096-8280.2023-009 Abstract （5144）   HTML （479）    PDF（pc） （1310KB）（4807）       Knowledge map    Save Enzymes have garnered significant attention in both research and industry due to their unparalleled specificity and functionality, and thus opportunities remain for enhancing their physichemical properties and fitness to improve catalytic performance. The primary objective of enzyme engineering is to optimize the fitness of targeted enzymes through various strategies for their modifications, even redesigning. This review provides a comprehensive overview for progress made in enzyme engineering, with a focus on artificial intelligence (AI)-guided design methodology. Several key strategies have been employed in enzyme engineering, including rational design, directed evolution, semi-rational design, and AI-guided design. Rational design relies on an extensive knowledge based on encompassing protein structures and catalytic mechanisms, allowing for purposeful manipulations of enzyme properties. Directed evolution, on the other hand, involves the generation of a library of random variants for subsequent high-throughput screening to identify beneficial mutations. Semi-rational design combines rational design and directed evolution, resulting in a smaller, yet more targeted, library of variants, which mitigates high cost associated with extensive screening of large libraries developed through directed evolution. In recent years, AI technologies, particularly deep neural networks, have emerged as a promising approach for enzyme engineering, and AI-guided methods leverage a vast amount of information regarding protein sequences, multiple sequence alignments, and protein structures to learn key features for correlations. These learned features can then be applied to various downstream tasks in enzyme engineering, such as predicting mutations with beneficial effect, optimizing protein stability, and enhancing catalytic activity. Herewith, we delves into advancements and successes in each of these strategies for enzyme engineering, highlighting the growing impact of AI-guided design on the process. By offering a detailed examination of the current state of enzyme engineering, we aim at providing valuable insight for researchers and engineers to further advance the development and optimization of enzymes for more applications. Table and Figures | Reference | Related Articles | Metrics

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Artificial intelligence-assisted protein engineering BIAN Jiahao, YANG Guangyu Synthetic Biology Journal    2022, 3 (3): 429-444.   DOI: 10.12211/2096-8280.2021-032 Abstract （5086）   HTML （491）    PDF（pc） （2486KB）（4125）       Knowledge map    Save Protein engineering is one of the important research fields of synthetic biology. However, de novo design of protein functions based on rational design is still challenging, because of the limited understanding on biological fundamentals such as protein folding and the natural evolution mechanism of enzymes. Directed evolution is capable of optimizing protein functions effectively by mimicking the principle of natural evolution in the laboratory without relying on structure and mechanism information. However, directed evolution is highly dependent on high-throughput screening methods, which also limits its applications on proteins which lack high-throughput screening methods. In recent years, artificial intelligence has been developed very rapidly for integrating into multidisciplinary fields. In synthetic biology, artificial intelligence-assisted protein engineering has become an efficient strategy for protein engineering besides rational design and directed evolution, which has shown unique advantages in predicting the structure, function, solubility of proteins and enzymes. Artificial intelligence models can learn the internal properties and relationships from given sequence-function data sets to make predictions on properties for virtual sequences. In this article, we review the application of artificial intelligence-assisted protein engineering. With the basic and process of the strategy introduced, three key points that affect the performance of the predictive model are analyzed: data, molecular descriptors and artificial intelligence algorithms. In order to provide useful tools for researchers who want to take advantage of this strategy, we summarize the main public database, diverse toolkits and web servers of the common molecular descriptors and artificial intelligence algorithms. We also comment on the functions, applications and websites of several artificial intelligence-assisted protein engineering platforms, through which a complete prediction task including protein sequences representation, feature analysis, model construction and output can be completed easily. Finally, we analyze some challenges that need to be solved in the artificial intelligence-assisted protein engineering, such as the lack of high-quality data, deviation in data sets and lacking of the universal models. However, with the development of automated gene annotations, ultra-high-throughput screening technologies and artificial intelligence algorithms, sufficient high-quality data and appropriate algorithms will be developed, which can enhance the performance of artificial intelligence-assisted protein engineering and thus facilitate the development of synthetic biology techniques. Table and Figures | Reference | Related Articles | Metrics

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Recent advances in photoenzymatic synthesis MING Yang, CHEN Bin, HUANG Xiaoqiang Synthetic Biology Journal    2023, 4 (4): 651-675.   DOI: 10.12211/2096-8280.2022-056 Abstract （4761）   HTML （410）    PDF（pc） （5786KB）（5021）       Knowledge map    Save Biocatalysis has the advantages in terms of sustainability, efficiency, selectivities and evolvability, thus it plays a more and more important role in green and sustainable synthesis, both in industrial production and academic research. However, compared with the well-known privileged chemocatalysts, enzymes suffer from the relatively limited types of reactions it can catalyze, which is unable to meet the future needs of green biomanufacturing. On the other hand, photocatalysis has emerged as one of the most effective strategies for the generation of reactive chemical intermediates under mild conditions, thereby providing a fertile testing ground for inventing new chemistry. However, the light-generated organic intermediates, including radicals, radical ions, ions, as well as excited states, are highly reactive resulting in the difficulties of controlling the chemo- and stereo-selectivities. The integration of biocatalysis and photocatalysis created a cross-disciplinary area, namely photoenzymatic catalysis, which can not only provide a new solution to stereochemical control of photochemical transformations with the exquisite and tunable active site of enzymes, but also open a new avenue to expand the reactivity of enzymes with visible-light-excitation. In addition, photoenzymatic catalysis inherits the inherent advantages of biocatalysis and photocatalysis, such as mild reaction conditions, representing green and sustainable synthetic methods. We have witnessed the booming development of photoenzymatic catalysis during the past several years. In this review paper, the recent advances in this field are highlighted. According to the cooperative modes of photocatalysis and enzymes, this paper is divided into following four parts: photoredox-enabled cofactor regeneration systems, cascade/cooperative reactions combining enzymes with photocatalysts, unnatural transformations with photoactivable oxidoreductase, and artificial photoenzymes. In this paper, we summarize the representative works and emphasize on the catalytic mechanisms of photoenzymatic transformations as well as the strategies for realizing abiological transformations. At the end of this review, by analyzing the challenges of photoenzymatic synthesis, the future directions are prospected. We hope that this review can inspire the discovery of more novel photoenzymatic systems and ultimately spur the applications of photoenzymes in industrial productions of high value-added enantiopure chiral products. Table and Figures | Reference | Related Articles | Metrics

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Recent advances in plant synthetic biology ZHANG Bo, MA Yongshuo, SHANG Yi, HUANG Sanwen Synthetic Biology Journal    2020, 1 (2): 121-140.   DOI: 10.12211/2096-8280.2020-016 Abstract （4593）   HTML （363）    PDF（pc） （2509KB）（4095）       Knowledge map    Save Synthetic biology is a new interdisciplinary field that combines engineering and biology. With an initial focus on microbial systems, it is now increasingly developed for plants. Plant synthetic biology has been applied to design crops for improved yield and nutritional value. It is also possible to transform plants into living factories for producing high-value natural products. In this review, we first summarize the definition of plant synthetic biology and introduce emerging technologies, including DNA synthesis and assembly, genome editing, genetic transformation targeting nucleus and plastid, and chromosome engineering. We then discuss recent applications in biosensor design, yield and nutrition improvement, and natural product and protein biosynthesis. We conclude with the current challenges and future perspective of this field. We envision plant synthetic biology will revolutionize crop breeding. Table and Figures | Reference | Related Articles | Metrics

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Applications and prospects of genome mining in the discovery of natural products YANG Qian, CHENG Botao, TANG Zhijun, LIU Wen Synthetic Biology Journal    2021, 2 (5): 697-715.   DOI: 10.12211/2096-8280.2021-012 Abstract （4510）   HTML （437）    PDF（pc） （6343KB）（5208）       Knowledge map    Save Natural products have been an abundant source of leader compounds for new drugs, but traditional isolation and analysis technologies to obtain novel natural products cannot satisfy the requirement for drug discovery. Genomic data have been utilized for identifying potential drug targets, or exploring biosynthesis pathways for natural products that were neglected before. Genome sequencing has unveiled a plethora of undeveloped chemical diversity in microorganisms and plants. From genome sequences, a large amount of information is available, from functional enzymes to conserved patterns/signatures, even potential structures and features that can be interpreted to hunt for new biocatalysts. With the advent of the genomic era, the computational mining of genomes has become an important part in the discovery of novel natural products as drug leads. Meanwhile, the development of high-throughput sequencing and the establishment of DNA database, genome mining methods and tools have contributed to the discovery and characterization of these natural products. In spite of the diversity of natural products, the biosynthetic rules and thus the biosynthetic machineries for many of these compounds are often remarkably conserved, which is highlighted in the high amino acid sequence similarity of the core biosynthetic enzymes, such as polyketides synthases (PKS), non-ribosomally peptides synthetases (NRPS), and many others. Besides, most of natural products are considered to be produced by the host to kill or limit the growth of competitors through the inhibition or inactivation of essential housekeeping enzymes. Therefore, accumulating knowledge on the self-resistance mechanisms, for instance, mining for SRE (self-resistance enzyme), have promoted research on natural products. Moreover, a phylogeny-guided mining approach provides a method to quickly screen a large number of microbial genomes or metagenomes to detect new biosynthetic gene clusters of interest, and many web tools and databases have been developed and utilized by researchers to mine for key enzymes. This paper reviews recent advances in the genome mining tools, databases and approaches, with a focus on the ways of mining biosynthetic gene clusters (BGCs) of natural products, from classical genome mining to resistance-based and phylogeny-guided mining, and also include a short overview on status and perspective in the discovery of novel natural products. Table and Figures | Reference | Related Articles | Metrics

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Recent development of directed evolution in protein engineering QI Yanping, ZHU Jin, ZHANG Kai, LIU Tong, WANG Yajie Synthetic Biology Journal    2022, 3 (6): 1081-1108.   DOI: 10.12211/2096-8280.2022-025 Abstract （4406）   HTML （400）    PDF（pc） （3627KB）（6336）       Knowledge map    Save Directed evolution aims to accelerate the natural evolution process in vitro or in vivo through iterative cycles of genetic diversification and screening or selection. It has been one of the most solid and widely used tools in protein engineering. This review outlines the representative methods developed in the past 10 years that increase the throughput of directed evolution, including in vitro and in vivo gene diversification methods, high-throughput selection and screening methods, continuous evolution strategies, automation-assisted evolution strategies, and AI-assisted protein engineering. To illustrate the significant applications of directed evolution in protein engineering, this review subsequently discusses some remarkable cases to show how directed evolution was used to improve various properties of enzymes, such as the tolerance to elevated temperature or organic solvent, the activities on non-native substrates, and chemo-, regio-, stereo-, and enantio-selectivities. In addition, directed evolution has also been widely used to expand the biocatalytic repertories by engineering enzymes with abiotic activities. In addition to the native enzymes, directed evolution has also been used to engineer de novo designed enzymes and artificial metalloenzymes with activities comparable to or exceeding the ones of the native enzymes. Finally, this review has pointed out that further improving the efficiency and effectiveness of directed evolution remains challenging. Some advanced continuous evolution and high throughput screening strategies have been succesfully demonstrated in improving the throughput of directed evolutions extensively, but they have been limited to engineering certain protein targets. To resolve those issues, continuously improved computational modeling tools and machine learning strategies can assist us to create a smaller but more accurate library to enhance the probabilities of discovering variants with improved properties. Additionally, laboratorial automation platforms coupled with advanced screening and selection techniques also have great potential to extensively explore the protein fitness landscape by evolving multiple targets continuously in a high throughput manner. Table and Figures | Reference | Related Articles | Metrics

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Microbiome-based biosynthetic gene cluster data mining techniques and application potentials LAI Qilong, YAO Shuai, ZHA Yuguo, BAI Hong, NING Kang Synthetic Biology Journal    2023, 4 (3): 611-627.   DOI: 10.12211/2096-8280.2022-075 Abstract （4366）   HTML （402）    PDF（pc） （3056KB）（3863）       Knowledge map    Save Biosynthetic gene cluster (BGC) is an important type of gene set, which is commonly found in the genomes of various organisms, and plays important metabolic and regulatory roles. In terms of linear gene structure, the set of genes in a BGC is usually located in close proximity to each other in the genome, but for functions, genes in a BGC usually work synergistically and are responsible for a class of pathways that generate specific small molecules. Therefore, BGCs are vital in synthetic biology research as a highly promising source for elements. However, current BGC databases and analytical platforms are limited by the number and types of experimentally validated BGCs, as well as by the preliminary BGC data mining techniques. The establishment of data-driven systematic discovery of BGCs and their validation, as well as translational studies, are of great value in both fundamental research and practical applications. This article focuses on mining BGCs from big data with microbiome for synthetic biology research. We start with discussing the definition and significance of BGC mining, and summarize current data resources and methods for BGC mining: including MIBiG, antiSMASH and IMG-ABC for artificial intelligence (AI) enabled web services to accelerate BGC mining. Then, we compile a walk-through on how a typical BGC data mining could be conducted, with the history of BGC mining methods highlighted, which underlines the route build-up from traditional machine learning to deep learning. We also diagnose bottlenecks in BGC mining, and propose possible solutions. Furthermore, according to several BGC mining and validation experiments, we demonstrate the profound diversity and breadth of application scenarios with BGC discovery, as well as the importance of combining dry and wet lab experiments for validating newly discovered BGCs. Finally, we envision that the combination of advanced BGC mining methods and synthetic biology could broaden and deepen current synthetic biology research. Table and Figures | Reference | Related Articles | Metrics

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Advances in synthetic biomanufacturing ZHANG Yuanyuan, ZENG Yan, WANG Qinhong Synthetic Biology Journal    2021, 2 (2): 145-160.   DOI: 10.12211/2096-8280.2020-052 Abstract （4292）   HTML （599）    PDF（pc） （2003KB）（4875）       Knowledge map    Save Synthetic biomanufacturing is a paradigm for material processing and synthesis via synthetic biology. It is expected to completely transform the traditional production mode for medicines, chemicals, food, energy, materials and agriculture in the future, trigger new industrial revolution, lead to new economic growth and reshape carbon-based civilization. In particular, the COVID-19 global spread that has accelerated the reshaping process of the world's economic and social development. In the foreseeable future, human life and production patterns will undergo profound changes in medicines and healthcare, food and agriculture, energy and materials, etc., during which demands for new technologies will promote evolution in the field of biotechnology, and the biomanufacturing industry in the post COVID-19 era is facing unprecedented opportunities for revitalization and new challenges. According to the analysis of the research report from the Ministry of Economy, Trade and Industry of Japan, engineered biological cells and their combination with information & artificial intelligence technologies will become the main driving force for the "post-fourth industrial revolution".Synthetic biomanufacturing has the characteristics of cleanliness, efficiency and renewableness that can reduce the impact of industrial economy on the ecological environment. Here, in this review, we summarize the progress of synthetic biomanufacturing with respect to bulk fermentation products, fine and pharmaceutical chemicals, renewable chemicals and bio-based polymeric materials, natural products, foods and the utilization of C1 raw materials. The technological progress, status and potential of industrial applications of many important bio-based products via synthetic biomanufacturing are analyzed and discussed. The development of synthetic biomanufacturing shows great potentials for building up the ecological route of industrial economy and addressing current issues of economic sustainability in terms of limited substrate, high cost, and poor viability, and to form whole new industry chain with sustainable growth. In the future, with the development of synthetic biology, and the integration of new technologies such as artificial intelligence and big data, more and more bio-based products can be produced via synthetic biomanufacturing. The formation of bioeconomy can be promoted, and the sustainable development of human society will be better served. Table and Figures | Reference | Related Articles | Metrics

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Design of synthetic biology components based on artificial intelligence and computational biology WANG Sheng, WANG Zechen, CHEN Weihua, CHEN Ke, PENG Xiangda, OU Fafen, ZHENG Liangzhen, SUN Jinyuan, SHEN Tao, ZHAO Guoping Synthetic Biology Journal    2023, 4 (3): 422-443.   DOI: 10.12211/2096-8280.2023-004 Abstract （4252）   HTML （492）    PDF（pc） （1930KB）（3293）       Knowledge map    Save The primary objective of synthetic biology is to conceptualize, engineer, and construct novel biological components, devices, and systems based on established principles and extant information or to reconfigure existing natural biological systems. The core concept of synthetic biology encompasses the design, modification, reconstruction, or fabrication of biological components, reaction systems, metabolic pathways and processes, and even the creation of cells and organisms with functions or living characteristics. This burgeoning field offers innovative technologies to address challenges with sustainable development in environment, resource, energy, and so on. Undeniably, synthetic biology has yielded significant progress in numerous fields, ranging from DNA recombination to gene circuit design, yet its full potential remains insufficiently explored, but the emergence and application of artificial intelligence (AI) definitely can facilitate the development of synthetic biology for more applications. From a synthetic biology perspective, essence for life is rooted in digitalization and designability. This article reviews current advances in computational biology, particularly AI for synthetic biology to be more efficient and effective, focusing on the development of biocatalysts, regulators, and sensors. De novo enzyme design has been successfully implemented by using Rosetta software, as AI exhibiting significant potential for generating innovative structures and protein sequences with diverse functions. Also, the reprogramming of natural enzymes for specific purposes is crucial for synthetic biology applications. By employing various force fields and sampling techniques, promiscuity and thermal stability can be modified to accommodate specific requirements rather than those with natural hosts. AI can be integrated into the life-cycle of synthetic biology through an active learning paradigm, which enables alterations in enzyme specificity, and demonstrates potential for accurately and rapidly predicting mutation effects, surpassing force-field-based methods. The rapidly decreasing cost of sequencing has facilitated the characterization of cis-regulators, primarily DNA and RNA, with high-throughput. Concurrently, more trans-regulators have been identified in sequenced genomes. The expanding wealth in big data serves as a driving force for AI. AI models have successfully predicted the strength of promoters, ribosome binding sites (RBSs), and enhancers, and generated artificial protomers and RBSs. Recent progress in RNA structure prediction is expected to aid the design of RNA elements. Sensors, vital for genetic circuits and other applications such as toxin detection, typically involve interactions among various molecules, including nucleic acids, proteins, small organic molecules, and metal ions. Consequently, sensor design necessitates the integration of diverse computational biology tools to balance accuracy and computational cost. As the pool of data keeps growing, we anticipate that AI will be increasingly applied to the design of more bio-parts. Table and Figures | Reference | Related Articles | Metrics

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Research advances in synthetic microbial communities QU Zepeng, CHEN Moxian, CAO Zhaohui, ZUO Wenlong, CHEN Ye, DAI Lei Synthetic Biology Journal    2020, 1 (6): 621-634.   DOI: 10.12211/2096-8280.2020-012 Abstract （4181）   HTML （447）    PDF（pc） （2495KB）（4271）       Knowledge map    Save Synthetic microbial communities are an emerging research field at the intersection of synthetic biology and microbiome. A synthetic microbial community is created artificially by co-culturing of multiple species under a well-defined condition. Synthetic communities that retain the key features of their natural counterparts can act as a model system to study the ecology and function of microbial communities in a controlled way. This review covers important topics and research progress in synthetic microbial communities. We start with a summary of ecological factors that shape the structure of microbial communities, including interactions among microbes, host metabolism and immunity and environmental conditions. We then discuss the methods and experimental techniques in design-build-test-learn (DBTL) cycle, used to study synthetic microbial communities. In addition, we review the potential applications of synthetic microbiome in human health, agriculture, industrial production and environmental remediation. Finally, we summarize key scientific questions for future studies of synthetic microbial communities,including how to construct a controllable and stable microbial interaction network, how to characterize and manage the spatial structure of microbial communities, and how to accurately shape the function of microbial communities. Table and Figures | Reference | Related Articles | Metrics

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Application of bacterial quorum sensing system in intercellular communication and its progress in synthetic biology LI Xiaomeng, JIANG Wei, LIANG Quanfeng, QI Qingsheng Synthetic Biology Journal    2020, 1 (5): 540-555.   DOI: 10.12211/2096-8280.2020-043 Abstract （3980）   HTML （253）    PDF（pc） （1959KB）（4366）       Knowledge map    Save Quorum sensing (QS) is a bacterial cell-to-cell communication system. Bacteria sense the density of bacterial population by secreting diffuse small molecular signals, thus causing the coordinated expression of a group of specific genes at the transcriptional level. With continuous research, the quorum-sensing related genetic elements and the regulatory principles have gradually become clear. In recent years, genetic circuits containing components of the bacterial QS system have been constructed through synthetic biology to achieve intra-species and inter-species artificial communication, and these genetic circuits based on QS have great application potential in biotechnology and biomedicine. This paper reviews several relatively clear and representative microbial quorum sensing systems and their functional roles, and introduces the application of genetic circuits based on quorum sensing systems to intra-species and inter-species cell communication, and discusses the microbial quorum sensing system in constructing biological computing tools, regulating the population density and the flow of metabolism of the future development prospect. For intra-cell communication, we mainly introduced the applications of quorum sensing system in the construction of biological computing tools, which are mainly reflected in the research of toggle switches, biosensors and logic gates in synthetic biology. Toggle switches, biosensors, and logic gates designed based on quorum sensing mechanism can better coordinate cell behavior at the population level by combining with some biological control circuits to achieve precise regulation at the spatial, temporal, and population level. For inter-species cell communication, we mainly discuss the influence of introducing quorum sensing system on controlling population density and regulating metabolic flow. Quorum sensing system is used to redistribute the metabolic fluxes of the desired pathways through the recombination of metabolic network, to realize the regulation of population density and co-culture of mixed strains. Meanwhile, it is also found that the combination of QS system and oscillator model has great potential in regulating the synchronicity of microbial complexes. In summary, the in-depth research on the quorum sensing mechanism and application not only lays a certain foundation for elucidating the mechanism of microbial ecological competition and dynamic balance, but also provides an idea for clarifying the regulation mechanism of pathogenic bacteria and developing new disease control strategies. Table and Figures | Reference | Related Articles | Metrics

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Synthetic biology and food manufacturing LIU Yanfeng, ZHOU Jingwen, LIU Long, CHEN Jian Synthetic Biology Journal    2020, 1 (1): 84-91.   DOI: 10.12211/2096-8280.2020-005 Abstract （3971）   HTML （374）    PDF（pc） （1189KB）（3476）       Knowledge map    Save As global environmental pollution intensifies, climate continues to change, and population continues to grow, how to ensure safe, nutritious and sustained food supply faces huge challenges. These challenges put forward new requirements for the future food supply and function. Using synthetic biology technologies to create cell factories applicable in the food industry to convert renewable raw materials into important food components, functional food additives and nutritional chemicals is an important way to solve the problems facing the food industry. This article first introduces the importance of synthetic biology to the innovation and breakthroughs in the field of food manufacturing. Secondly, taking artificial food, plant natural products and human milk oligosaccharide, three typical food products from biological manufacturing, as examples, the current tasks and challenges of food synthetic biology are discussed. Finally, the development trends of synthetic biology and food manufacturing in China are summarized and prospected. By strengthening the development and application of food synthetic biology and the related food biotechnologies and being the first to achieve their industrialization, researchers will be able to seize the frontiers of science and technology and industrial highlands globally and benefit mankind. Reference | Related Articles | Metrics

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Computational protein design: perspectives in methods and applications CAO Fan, CHEN Yaoxi, MIAO Yangyang, ZHANG Lu, LIU Haiyan Synthetic Biology Journal    2021, 2 (1): 15-32.   DOI: 10.12211/2096-8280.2020-067 Abstract （3965）   HTML （345）    PDF（pc） （2838KB）（3086）       Knowledge map    Save In computational protein design， the amino acid sequence of a protein is rationally chosen through computations so that the resulting molecule is of desired structure and function. Systematic methods for computational protein design have been developed and validated in increasing number of experiments. Exhibiting strong potential for broad applications， computational protein design has been considered as an important enabling technology for Synthetic Biology. Here we briefly review the history of methods for computational design， which are divided into three sections about heuristic design that based on rules， automatic optimization of amino acid sequences， and de novo main chain design respectively. In the next chapter， we introduce the basic approaches and strategies in details. In proteins energy calculation methods， we introduce physical energy terms and statistical energy terms. Based on these energy calculation methods， we introduce sequence and structure design methods including automated optimization of amino acid sequences， de novo design of polypeptide backbones （with fragment assembling method or sequence independent backbone potentials）， designing new interfaces for inter-molecule recognition such as protein-ligand interfaces and protein-protein interfaces， and the concept of negative design. Besides the history and detail of computational protein design methods that mentioned above， we also briefly discuss examples of using computational protein design to support application studies， including enhancing protein structural stability and redesign or de novo design of enzymes， vaccines and protein materials that related to interfaces design. These examples not only present current studies using the computational protein design methods， but also enlighten us on more broader applications in the future. Finally， we analyze some problems that need to be solved in the protein computational design method， such as inefficient in design accuracy， difficulty in characterizing polar interactions， and the need to consider the environment of non-aqueous solvents. We also discuss some aspects of possible application in synthetic biology like biological logic gates design and biosensor design， and application prospects in the medical field such as antibodies， vaccine design， etc. Table and Figures | Reference | Related Articles | Metrics