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DNA information storage： bridging biological and digital world Mingzhe HAN, Weigang CHEN, Lifu SONG, Bingzhi LI, Yingjin YUAN Synthetic Biology Journal    2021, 2 (3): 309-322.   DOI: 10.12211/2096-8280.2021-001 Abstract （6153）   HTML （566）    PDF（pc） （3021KB）（3318）       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. Reference | Related Articles | Metrics

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From chemical synthesis to biosynthesis: trends toward total synthesis of natural products Faguang ZHANG, Ge QU, Zhoutong SUN, Jun′an MA Synthetic Biology Journal    2021, 2 (5): 674-696.   DOI: 10.12211/2096-8280.2021-039 Abstract （6089）   HTML （532）    PDF（pc） （6155KB）（4039）       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. Reference | Related Articles | Metrics

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Microbial promoter engineering strategies in synthetic biology Huimin YU, Yukun ZHENG, Yan DU, Miaomiao WANG, Youxiang LIANG Synthetic Biology Journal    2021, 2 (4): 598-611.   DOI: 10.12211/2096-8280.2020-092 Abstract （4185）   HTML （492）    PDF（pc） （1858KB）（5045）       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. Reference | Related Articles | Metrics

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Artificial intelligence-assisted protein engineering Jiahao BIAN, Guangyu YANG Synthetic Biology Journal    2022, 3 (3): 429-444.   DOI: 10.12211/2096-8280.2021-032 Abstract （3709）   HTML （396）    PDF（pc） （2456KB）（3124）       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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Applications and prospects of genome mining in the discovery of natural products Qian YANG, Botao CHENG, Zhijun TANG, Wen LIU Synthetic Biology Journal    2021, 2 (5): 697-715.   DOI: 10.12211/2096-8280.2021-012 Abstract （3076）   HTML （311）    PDF（pc） （6343KB）（3095）       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 advances in photoenzymatic synthesis Yang MING, Bin CHEN, Xiaoqiang HUANG Synthetic Biology Journal    2023, 4 (4): 651-675.   DOI: 10.12211/2096-8280.2022-056 Abstract （2938）   HTML （271）    PDF（pc） （5785KB）（2367）       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. {L-End} Table and Figures | Reference | Related Articles | Metrics

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Enzyme engineering in the age of artificial intelligence Liqi KANG, Pan TAN, Liang HONG Synthetic Biology Journal    2023, 4 (3): 524-534.   DOI: 10.12211/2096-8280.2023-009 Abstract （2771）   HTML （303）    PDF（pc） （1310KB）（2082）       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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Production of sesquiterpenoids α-neoclovene and β-caryophyllene by engineered Saccharomyces cerevisiae Xiaodong LI, Chengshuai YANG, Pingping WANG, Xing YAN, Zhihua ZHOU Synthetic Biology Journal    2021, 2 (5): 792-803.   DOI: 10.12211/2096-8280.2021-014 Abstract （2685）   HTML （350）    PDF（pc） （2407KB）（1615）       Knowledge map    Save Sesquiterpenoids α-neoclovene and β-caryophyllene are major components in volatile oils from Panax ginseng, which have been demonstrated to play important roles in antibacteria, antitumor and cardiovascular protection. Moreover, they have attracted attentions for potential use as biofuels with high-energy-density. However, the industrial production of α-neoclovene and β-caryophyllene as well as other sesquiterpenoids are mainly relied on extraction from plant materials, which is too costly for applications at a large scale. Currently, this challenge could be addressed by advances in synthetic biology for natural product biosynthesis. Through heterologously assembling and integrating of their biosynthetic pathways into microbial chassis cells, targeted natural compounds from plants could be produced by microbial fermentation in a sustainable, low-cost and large-scale way. In this study, by comparing the production potential of sesquiterpenes between different Saccharomyces cerevisiae strainsand followed by enhancing the endogenous mevalonate pathway, a yeast sesquiterpene chassis strain (SQTBY03) with an increase of 458 times in farnesyl pyrophosphate production was constructed. Then by inserting the codon-optimized sesquiterpene synthase gene ec38-cs from the endophytic fungi Hypoxylon sp. EC38 and the codon-optimized caryophyllene synthase gene QHS1 from Artemisia annua into SQTBY03, respectively, we built yeast cell factories NCVBY01 and CPLBY01 for de novo production of α-neoclovene and β-caryophyllene at their titers of 25.8 mg/L and 250.4 mg/L, respectively, in shake flasks. Furthermore, fed-batch fermentation using NCVBY01 and CPLBY01 resulted in the de novo production of 487.1 mg/L α-neoclovene and 2949.1 mg/L β-caryophyllene from glucose. It is also possible to further chemically catalyze β-caryophyllene to produce α-neoclovene. Our work provides strategies for the sustainable production of α-neoclovene and β-caryophyllene from glucose through microbial fermentation, which would benefit their applications as medicine and other functional products. In addition, our yeast chassis for the sesquiterpene production could offer a platform for the sustainable production of other valuable sesquiterpenoids via synthetic biology approach. Reference | Related Articles | Metrics

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Green biomanufacturing of steroids: from biotransformation to de novo synthesis by microorganisms Liangbin XIONG, Lu SONG, Yunqiu ZHAO, Kun LIU, Yongjun LIU, Fengqing WANG, Dongzhi WEI Synthetic Biology Journal    2021, 2 (6): 942-963.   DOI: 10.12211/2096-8280.2021-061 Abstract （2669）   HTML （182）    PDF（pc） （2746KB）（2482）       Knowledge map    Save Steroids are widely distributed in natural organisms and play essential roles in growth, breeding, metabolic regulation, and endocrine homeostasis. To date, diverse steroids have been proved to have numerous therapeutic effects on reproductive health, endocrine regulation, inflammation, etc. and can be used as life-saving drugs for some serious diseases, such as cancer, organ transplantation, and serious infection. Therefore, the industrial synthesis of steroid drugs has developed rapidly and steroid drugs have become the second largest drug category just ranked after antibiotics. Due to the complex structure and delicate configuration, steroids are difficult to be produced at an industrial scale by chemical total synthesis. At present, steroids are mainly produced by semi-synthesis ways with natural steroidal sapogenins or sterols as raw materials via the combination of chemical and biological transformations. However, the above routes are long and complex resulting in the low yield and the overuse of toxic reagents and heavy metal catalysts, thus resulting in a large quantity of wastewater and residue as well as high production costs. Therefore, it is necessary to develop green biomanufacturing technologies, such as biocatalysis, biotransformation, and biosynthesis, for the industrial production of steroids. Currently, the production mode of steroids has been profoundly changed due to the successful application of enzyme-catalyzed reactions and microbial transformations in the industrial production of steroids. It is expected that the production of steroids will be changed into a biomanufacturing mode if the robust microbial cell factories for the de novo biosynthesis of steroids can be developed via the biosynthetic way. The de novo synthesis of steroids by microorganisms has been materialized. However, due to the extraordinarily complex metabolic mechanism of steroids in the nature, the efficient production of steroids in engineered hosts still remains a challenge. Here, starting from the evolution of steroidal pharmaceutical industry, we systematically review recent advances in biomanufacturing technologies of steroids, including the identification and application of steroidal biocatalysis and biotransformation, the characterization and modification of the metabolic mechanisms of steroids in certain microorganisms, and the development of de novo biosynthesis pathways of steroids in engineered cell factories. From the above three aspects, this review provides a reasonable summary and prospect for the current status and future development trend of green bio-manufacturing technologies in the steroidal pharmaceutical industry. Table and Figures | Reference | Related Articles | Metrics

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Design, optimization and application of whole-cell microbial biosensors with engineered genetic circuits Lu YANG, Nan WU, Rongrong BAI, Weiliang DONG, Jie ZHOU, Min JIANG Synthetic Biology Journal    2022, 3 (6): 1061-1080.   DOI: 10.12211/2096-8280.2021-021 Abstract （2662）   HTML （301）    PDF（pc） （2989KB）（1825）       Knowledge map    Save Whole-cell microbial biosensors with engineered genetic circuits constructed based on the concept of synthetic biology is an important branch of the biosensor. Whole-cell microbial biosensor is mainly composed of the sensing module, the computing module and the output actuating module. It can sense the concentration of specific substances in the environment and then transfer it to specific signal outputs in time according to certain rules, which shows great potential in bioengineering process control, environmental monitoring, food safety, environmental quality monitoring and disease diagnosis and control, etc. With the improvement of various technologies in synthetic biology and the enrichment of genetic elements, more and more whole-cell microbial sensors based on different response mechanisms, different logic gates and logic circuits have been developed. However, the design and construction of genetically engineered whole-cell microbial biosensor still mainly rely on the empirical method of trial-and error-learning. Therefore, how to design and construct high performance genetically engineered microbial whole-cell biosensors and how to tune its response curves by optimizing genetic elements or circuits to meet the detection requirements of different practical application scenarios is the new and important challenge. Here we reviewed the principle, classification and development process of genetically engineered whole-cell biosensor. We also focused on the design and construction of genetic circuit based on transcription factors and riboswitches, discussed optimization strategies for improving biosensor detection performance including dynamic range, specificity and working range, and then summarized its application progress in different detection fields. The optimization strategies are mainly involved in changing the expression level of genetic elements, adjusting the binding affinity between metabolites and genetic elements, restructuring the position of functional domains, etc. Finally, some challenges, such as biological safety, cumbersome design and construction, and inconvenience to enter the sensor market were discussed. It is expected that emerging technologies such as artificial intelligence, synthetic biology, and droplet microfluidics, will accelerate the development of genetic regulatory elements and the design and construction of novel biosensors. Table and Figures | Reference | Related Articles | Metrics

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Cell-free protein synthesis: from basic research to engineering applications Jiaqi HOU, Nan JIANG, Lianju MA, Yuan LU Synthetic Biology Journal    2022, 3 (3): 465-486.   DOI: 10.12211/2096-8280.2021-064 Abstract （2656）   HTML （248）    PDF（pc） （2584KB）（2289）       Knowledge map    Save Cell-free protein synthesis (CFPS), also known as in vitro gene expression, is a multifunctional technique used to complement cell-based protein expression, which is at the core of cell-free synthetic biology. Since the CFPS system does not require a living cell, it can simulate the entire cellular transcription and translation process in vitro in a controlled environment, and allows for an in-depth study of individual components and biological networks. Therefore, as a platform technology, it is expected to overcome the loopholes caused by the limitations of cell membranes in the current in vivo manufacturing systems, which has a broad research prospect in fundamental and applied scientific research. The cell-free operation is simple and easy to control, and its advantages over in vivo protein expression include its nature with open systems, eliminating the dependence on living cells and using all system energy for the production of the target proteins. This article reviews the composition of CFPS systems and their development based on different component types, including different biological extracts or purified transcription and translation components. Furthermore, different CFPS reaction patterns are introduced, including batch and continuous exchange modes, and the research progress of CFPS systems in genetic circuits, protein engineering, and the construction of artificial life is described. Among them, the genetic circuit research progress mainly summarizes the latest applications and contributions of cell-free technology in the prototype design, biosensors, and in vitro metabolic engineering. The protein engineering research progress lists the advantages and advances of the CFPS systems for producing membrane proteins, virus-like particles, post-translational modifications, unnatural amino acid incorporation and protein evolution. In the construction of artificial "living systems", the synthesis of bacteriophages and the construction of artificial cells have opened up a novel frontier field. Finally, the opportunities and challenges of the CFPS platforms for future scientific research and industrial applications are highlighted. Table and Figures | Reference | Related Articles | Metrics

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Computational design and directed evolution strategies for optimizing protein stability Qingyun RUAN, Xin HUANG, Zijun MENG, Shu QUAN Synthetic Biology Journal    2023, 4 (1): 5-29.   DOI: 10.12211/2096-8280.2022-038 Abstract （2636）   HTML （343）    PDF（pc） （2169KB）（3547）       Knowledge map    Save Most natural proteins tend to be marginally stable, which allows them to gain flexibility for biological functions. However, marginal stability is often associated with protein misfolding and aggregation under stress conditions, presenting a challenge for protein research and applications such as proteins as biocatalysts and therapeutic agents. In addition, protein instability has been increasingly recognized as one of the major factors causing human diseases. For example, the formation of toxic protein aggregates is the hallmark of many neurodegenerative diseases, including Alzheimer's and Parkinson's diseases. Therefore, optimizing protein folding and maintaining protein homeostasis in cells are long-standing goals for the scientific community. Confronting these challenges, various methods have been developed to stabilize proteins. In this review, we classify and summarize various techniques for engineering protein stability, with a focus on strategies for optimizing protein sequences or cellular folding environments. We first outline the principles of protein folding, and describe factors that affect protein stability. Then, we describe two main approaches for protein stability engineering, namely, computational design and directed evolution. Computational design can be further classified into structure-based, phylogeny-based, folding energy calculation-based and artificial intelligence-assisted methods. We present the principles of several methods under each category, and also introduce easily accessible web-based tools. For directed evolution approaches, we focus on library-based, high-throughput screening or selection techniques, including cellular or cell-free display and stability biosensors, which link protein stability to easily detectable phenotypes. We not only introduce the applications of these techniques in protein sequence optimization, but also highlight their roles in identifying novel folding factors, including molecular chaperones, chemical chaperones, and inhibitors of protein aggregation. Moreover, we demonstrate the applications of protein stability engineering in biomedicine and pharmacotherapeutics, including identifying small molecules to stabilize disease-related, aggregation-prone proteins, obtaining conformation-fixed and stable antigens for vaccine development, and targeting protein stability as a means to control protein homeostasis. Finally, we look forward to the trends and prospects of protein stabilization technologies, and believe that protein stability engineering will lead to a better understanding of protein folding processes to facilitate the development of precision medicine. {L-End} Table and Figures | Reference | Related Articles | Metrics

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Recent development of directed evolution in protein engineering Yanping QI, Jin ZHU, Kai ZHANG, Tong LIU, Yajie WANG Synthetic Biology Journal    2022, 3 (6): 1081-1108.   DOI: 10.12211/2096-8280.2022-025 Abstract （2634）   HTML （288）    PDF（pc） （3627KB）（3353）       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 Qilong LAI, Shuai YAO, Yuguo ZHA, Hong BAI, Kang NING Synthetic Biology Journal    2023, 4 (3): 611-627.   DOI: 10.12211/2096-8280.2022-075 Abstract （2584）   HTML （268）    PDF（pc） （3056KB）（1524）       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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Synthetic nanobiology——fusion of synthetic biology and nanobiology Qingqing FENG, Tianjiao ZHANG, Xiao ZHAO, Guangjun NIE Synthetic Biology Journal    2022, 3 (2): 260-278.   DOI: 10.12211/2096-8280.2021-035 Abstract （2572）   HTML （212）    PDF（pc） （2189KB）（2259）       Knowledge map    Save In recent years, nanomaterials have been widely used in biological research due to their unique particle size effect, large specific surface area and easy surface embellishment. These properties drive technological innovation in biotechnology. However, most of these nanomaterials are obtained through chemical synthesis, and their biological functions and compatibility are limited. Synthetic biology is an important emerging discipline, and the interdisciplinary study with nanomaterials is the inevitable result of scientific development, so as to produce a new research field, synthetic nanobiology: on the one hand, we can use the technology of synthetic biology to engineer bacteria or cells and obtain biogenic nanomaterials with special biological functions, thereby forming a novel biological technology-driven nanomaterial synthesis platform; on the other hand, nanomaterials can be used to enhance the functions of living organisms or simulate life activities, so as to expand the engineering design and construction concept for synthetic biology. Herein, according to the latest development, we divide synthetic nanobiology into three subclass fields: “pseudo-organism” research on genetically engineering-modified biogenic nanomaterials, “semi-organism” research on heterozygous biological systems based on functional enhancement with nanomaterials, and “organismoid” research on the simulation of life activities based on nanomaterials. Furthermore, the modification and functional research of biogenic nanomaterials, such as biomimetic cell membranes, exosomes, bacterial outer membrane vesicles, virus-like particles, and bacterial biofilms, as well as the construction and application of artificial heterozygous bacteria and cells and artificial photosynthetic systems are introduced. Moreover, the latest research progress in biomimetic artificial synthetic biology composed of nanomaterial components, such as nano-enzymes, artificial antigen presenting cells, motion nanorobots and DNA nanorobots, is also presented. Finally, development on the intersection of nanotechnology and synthetic biology is prospected, including its application potential in tumor therapy, environmental remediation and energy production. Table and Figures | Reference | Related Articles | Metrics

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Design of synthetic biology components based on artificial intelligence and computational biology Sheng WANG, Zechen WANG, Weihua CHEN, Ke CHEN, Xiangda PENG, Fafen OU, Liangzhen ZHENG, Jinyuan SUN, Tao SHEN, Guoping ZHAO Synthetic Biology Journal    2023, 4 (3): 422-443.   DOI: 10.12211/2096-8280.2023-004 Abstract （2539）   HTML （356）    PDF（pc） （1930KB）（1977）       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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From single-enzyme catalysis to multienzyme cascade： inspired from Professor Daniel I.C. Wang’s pioneer work in enzyme technology Shuke WU, Yi ZHOU, Wen WANG, Wei ZHANG, Pengfei GAO, Zhi LI Synthetic Biology Journal    2021, 2 (4): 543-558.   DOI: 10.12211/2096-8280.2021-004 Abstract （2536）   HTML （155）    PDF（pc） （3253KB）（1714）       Knowledge map    Save As the founder and pioneer in the fields of bioengineering and biotechnology, Professor Daniel I. C. Wang at the Massachusetts Institute of Technology (MIT) had made tremendous contributions in many aspects in the up-, mid- and downstream of biochemical engineering for over 50 years. In the area of enzyme technology, he had impell several significant advances from the 1970s to 1990s, such as enzymatic digestion of fish protein, immobilization of methanol oxidase, cell-free multi-enzyme synthesis, and enzyme catalysis in organic medium, etc. From 2005 to 2015 through the Singapore-MIT Alliance Program, Prof. Wang had jointly supervised several PhD students with Prof. Li Zhi at the National University of Singapore, and achieved important contributions biocatalysis, including: 1) developed enzyme immobilization methods for fabrication of highly active and recyclable magnetic nano-biocatalysts; 2) explored P450 monooxygenase for asymmetric sulfur oxidation in aqueous phase-ionic liquid systems; 3) developed an NADPH regeneration system based on permeabilized whole cells; 4) successfully developed modular multi-enzyme cascade catalysis to synthesize high-value chiral compounds, which significantly expanded the realm of biocatalysis. Among them, multi-enzyme cascade catalysis has become a research hotspot in the field of enzyme technology, due to its several desirable features, including the possibility of retrosynthetic design of various synthetic routes, the facile one-pot synthesis of final products, the reduction of additional unit operations, the saving of inputs from manpower and materials, and the minimization of waste generation. In this account, we also review the latest progress of multi-enzyme cascades for the synthesis of chiral compounds (e.g., chiral amines, amino acids) and bulk chemicals (e.g., precursors for polymers), and discuss its future development directions. Last but not the least, we provide an outlook for integrating multi-enzyme cascades with synthetic biology, and thus assembling biochemical reactions together with quantitative analysis and engineering concepts, as advocated by Prof. Wang throughout his scientific career. Reference | Related Articles | Metrics

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Overview on platform for synthetic biology research at Shenzhen Ting ZHANG, Mengtian LENG, Fan JIN, Hai YUAN Synthetic Biology Journal    2022, 3 (1): 184-194.   DOI: 10.12211/2096-8280.2021-077 Abstract （2393）   HTML （227）    PDF（pc） （2652KB）（1995）       Knowledge map    Save With the rapid development of synthetic biology, traditional labor-intensive research paradigm no longer satisfies the demand from increased numbers for trial-and-error experiments and processing and analysis of mega data. With the support from national, provincial and municipal governments, platform for synthetic biology research, established by Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences is now ready for operation, and expected to put into running in 2023. This report presents a brief introduction to The Major Scientific and Technological Infrastructure for Synthetic Biology Research. The first phase development for the Infrastructure includes three platforms: Design and Learning, Synthesis, and User Testing, and the second phase is for the medical transformation platform. The Infrastructure mainly focus on automated synthetic biotechnology, and introduces the concepts of intelligent manufacturing into synthetic biology research for high-throughput synthesis of living organisms. Through the establishment of such an intelligent production unit based on the information management system, the closed loop of “design-build-test-learn (DBTL)” can be implemented more efficiently with high-throughput and low-cost, which can realize rational and predictable design and synthesis, and also achieve remote design and economical production of synthetic living organisms at large scale. In addition, the platform integrates information technology (IT) and biological technology (BT) through information interconnection and internet of thing (IoT) devices for being fully automated and intelligent to conduct standardized tests, algorithms, processes and other workflows, which ultimately helps to inspire breakthroughs in basic research and interdisciplinary integration for technological innovations. Table and Figures | Reference | Related Articles | Metrics

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DNA synthesis technology: foundation of DNA data storage Xiaoluo HUANG, Junbiao DAI Synthetic Biology Journal    2021, 2 (3): 335-353.   DOI: 10.12211/2096-8280.2020-088 Abstract （2292）   HTML （263）    PDF（pc） （1954KB）（2402）       Knowledge map    Save DNA-based data storage technology has many considerable advantages, and been suggested as one of the most promising technologies to cope up with future crisis in information storage. It involves the conversion of real information into A/T/C/G sequences, synthesis of preservable DNA polymers by DNA synthesis technology, and data deciphering by DNA sequencing technology. Nevertheless, the current cost of DNA synthesis is still high, which greatly limits the rapid development and industrial application of DNA data storage. As the key technology of DNA data storage, DNA synthesis lays the foundation for the practical application of DNA data storage. Since the first oligonucleotides were made in the 1950 s, DNA synthesis technology has been rapidly developed and commercialized, spawning the emergence of DNA synthesizers with different throughput, which achieved oligonucleotides synthesis with dozens of nucleotides to MB-level microbial genomes. In this review, we systematically summarized the key research progress of DNA synthesis technology in terms of its historical development, which includes column-based chemical oligonucleotide synthesis, chip-based chemical oligonucleotide synthesis, oligonucleotide purification, oligonucleotide assembly, error correction and gene cloning, large fragment gene synthesis, genome synthesis and next generation enzymatic DNA synthesis. Currently, the widely used DNA synthesis technology starts from chemical synthesis of oligonucleotide. Although a number of chemical technologies have been proposed, the one typically used is the "phosphoramide" method, which includes the steps of "deprotection","coupling","capping" and "oxidation". The chemical synthesis generally produces single-stranded oligonucleotide with less than 200 nt. For double-stranded DNA synthesis, the single-stranded oligonucleotides need to be assembled. The oligonucleotide assembly technologies including ligase chain assembly (LCA) and polymerase chain assembly (PCA) were thus developed, and have been well applied in the commercialized gene synthesis. Following the development of chemical oligonucleotide synthesis technology and gene synthesis technology, several bacterial genomes and yeast chromosomes have been successfully synthesized, by employing the strategies of "one time de novo synthesis" or "gradual replacement synthesis". Meanwhile, new enzymatic DNA synthesis technology has also made considerable progress in the recent years, opening up a new path for synthetic biologists. In addition to these key research developments, we further summarized and analyzed the impact of key parameters of DNA synthesis technology, such as length, cost and speed, on DNA data storage, in order to provide some references and ideas for the development and the practical application of the entire DNA data storage process. Finally, we envisioned the future trend of DNA synthesis technology, including cost reduction, further development of genome synthesis technology and enzymatic DNA synthesis technology, as well as the establishment of a faster DNA synthesis technology with a longer fragment and lower-cost for DNA data storage. Table and Figures | Reference | Related Articles | Metrics

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Application of imine reductase in the synthesis of chiral amines Lu YANG, Xudong QU Synthetic Biology Journal    2022, 3 (3): 516-529.   DOI: 10.12211/2096-8280.2021-054 Abstract （2289）   HTML （139）    PDF（pc） （2499KB）（1845）       Knowledge map    Save Chiral amines with bioactivities are important chiral auxiliaries, and also key intermediates for the synthesis of many natural products and chiral drugs. Among the top 200 drugs for market revenues in 2019, more than 30% contain chiral amine structures. Therefore, the development of efficient and effective methods to synthesize chiral amine compounds is of interest for research. Due to its high efficiency, environmental friendliness and economic competitiveness, more attention has been paid on the enzyme-catalyzed production of chiral amines by academia and industry. Imine reductases (IREDs) reviewed in this article are a class of NAD(P) H-dependent oxidoreductases that catalyze asymmetric reduction of imines to chiral amines. The reduction of C\underset{\text{??????}}{?}N bonds constitutes a physiological reaction present in a number of biosynthetic pathways, leading to a variety of metabolites. The imine reductases have excellent characteristics such as high catalytic efficiency, strong regioselectivity and stereoselectivity, etc., which stand out among many other methods for the synthesis of chiral amines, and attract attention and enthusiasm of many researchers. In the past decade, with the rapid development of bioinformatics, structural biology, high-throughput screening approaches and the continuous expansion of the gene databases, many imine reductases with different functions have been identified. Significant achievements have been made in the discovery of IREDs, protein engineering and multi-enzyme cascade applications, among which some successful modification cases have industrial application potentials. This review summarizes the structural characteristics, catalytic mechanisms and applications of IREDs, with emphasis on their protein engineering and applications in multi-enzyme cascade reactions, as well as the bottleneck, breakthrough and progress in asymmetric catalytic chiral amine biosynthesis. In addition, the challenges and potentials of the enzymatic synthesis of chiral amine compounds for industrial production, and the importance of novel artificial biosynthesis pathway design to overcome these challenges are highlighted. Table and Figures | Reference | Related Articles | Metrics