P. Salerno, Matthew W. Leckenby, Bruce Humphrey, Rocky M. Cranenburgh
Abstract Antibiotic resistance genes are widely used to select bacteria transformed with plasmids and to prevent plasmid loss from cultures, yet antibiotics represent contaminants in the biopharmaceutical manufacturing process, and retaining antibiotic resistance genes in vaccines and biological therapies is discouraged by regulatory agencies. To overcome these limitations, we have developed X-mark™, a novel technology that leverages Xer recombination to generate selectable marker gene-free plasmids for downstream therapeutic applications. Using this technique, X-mark plasmids with antibiotic resistance genes flanked by XerC/D target sites are generated in Escherichia coli cytosol aminopeptidase (E. coli pepA) mutants, which are deficient in Xer recombination on plasmids, and subsequently transformed into enteric bacteria with a functional Xer system. This results in rapid deletion of the resistance gene at high resolution (100%) and stable replication of resolved plasmids for more than 40 generations in the absence of antibiotic selective pressure. This technology is effective in both Escherichia coli and Salmonella enterica bacteria due to the high degree of homology between accessory sequences, including strains that have been developed as oral vaccines for clinical use. X-mark effectively eliminates any regulatory and safety concerns around antibiotic resistance carryover in biopharmaceutical products, such as vaccines and therapeutic proteins. Graphical Abstract
摘要:抗生素耐药基因被广泛用于选择用质粒转化的细菌和防止质粒从培养中丢失，然而抗生素在生物制药生产过程中是污染物，在疫苗和生物疗法中保留抗生素耐药基因是监管机构不鼓励的。为了克服这些限制，我们开发了X-mark™，这是一种利用Xer重组产生可选择的无标记基因质粒的新技术，用于下游治疗应用。利用该技术，在大肠杆菌胞浆氨基肽酶(e.c oli pepA)突变体中产生带有XerC/D靶位的抗生素耐药基因的x标记质粒，并将其转化为具有功能Xer系统的肠道细菌。这导致在没有抗生素选择压力的情况下，以高分辨率(100%)快速删除抗性基因，并稳定地复制已分解的质粒超过40代。这项技术对大肠杆菌和肠沙门氏菌都有效，因为附属序列之间的高度同源性，包括已开发为临床使用的口服疫苗的菌株。X-mark有效地消除了对生物制药产品(如疫苗和治疗性蛋白质)中抗生素耐药性遗留的任何监管和安全担忧。图形抽象
{"title":"Xer recombination for the automatic deletion of selectable marker genes from plasmids in enteric bacteria","authors":"P. Salerno, Matthew W. Leckenby, Bruce Humphrey, Rocky M. Cranenburgh","doi":"10.1093/synbio/ysac005","DOIUrl":"https://doi.org/10.1093/synbio/ysac005","url":null,"abstract":"Abstract Antibiotic resistance genes are widely used to select bacteria transformed with plasmids and to prevent plasmid loss from cultures, yet antibiotics represent contaminants in the biopharmaceutical manufacturing process, and retaining antibiotic resistance genes in vaccines and biological therapies is discouraged by regulatory agencies. To overcome these limitations, we have developed X-mark™, a novel technology that leverages Xer recombination to generate selectable marker gene-free plasmids for downstream therapeutic applications. Using this technique, X-mark plasmids with antibiotic resistance genes flanked by XerC/D target sites are generated in Escherichia coli cytosol aminopeptidase (E. coli pepA) mutants, which are deficient in Xer recombination on plasmids, and subsequently transformed into enteric bacteria with a functional Xer system. This results in rapid deletion of the resistance gene at high resolution (100%) and stable replication of resolved plasmids for more than 40 generations in the absence of antibiotic selective pressure. This technology is effective in both Escherichia coli and Salmonella enterica bacteria due to the high degree of homology between accessory sequences, including strains that have been developed as oral vaccines for clinical use. X-mark effectively eliminates any regulatory and safety concerns around antibiotic resistance carryover in biopharmaceutical products, such as vaccines and therapeutic proteins. Graphical Abstract","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2022-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91366580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Advances in synthetic biology have allowed the generation of strains of bacteria that are genetically altered to have specific therapeutic benefits. These synthetic biotics, also widely referred to as engineered living therapeutics, have tremendous potential as a new therapeutic modality, and several have advanced into the clinic and human testing. This review outlines some of the unique attributes of synthetic biotics as well as some of the challenges in their development as prescription products. Regulatory considerations are discussed, and a case study of a program that has advanced into Phase 2 testing is provided: SYNB1618 for the treatment of PKU.
{"title":"Development of synthetic biotics as treatment for human diseases","authors":"A. Brennan","doi":"10.1093/synbio/ysac001","DOIUrl":"https://doi.org/10.1093/synbio/ysac001","url":null,"abstract":"Abstract Advances in synthetic biology have allowed the generation of strains of bacteria that are genetically altered to have specific therapeutic benefits. These synthetic biotics, also widely referred to as engineered living therapeutics, have tremendous potential as a new therapeutic modality, and several have advanced into the clinic and human testing. This review outlines some of the unique attributes of synthetic biotics as well as some of the challenges in their development as prescription products. Regulatory considerations are discussed, and a case study of a program that has advanced into Phase 2 testing is provided: SYNB1618 for the treatment of PKU.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86028452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Dang, Alissa Lance-Byrne, Angela Tung, Xiaoge Guo, Ryan J. Cecchi, Joanna Buchthal, Alejandro Chavez, N. C. Yeo
CRISPR/Cas9 has revolutionized the field of genome engineering. Yet, as the CRISPR toolbox has rapidly expanded, there remains a need for a comprehensive library of CRISPR/Cas9 reagents that allow users to perform complex cellular and genetic manipulations without requiring labor-intensive generation of reagents to meet each user’s unique experimental circumstances. Here we described the creation and validation of a pNAX CRISPR library consisting of 72 different Cas9 and gRNA expression plasmids to allow for efficient multiplex gene editing, activation, and repression in mammalian cells. The toolkit plasmids, which are piggyBac or lentiviral based, provide the means for reliable and rapid delivery of Cas9/gRNA through either transient transfection or stable integration. Using the toolkit, we demonstrate the ease with which users can perform single or multiplex gene editing and modulate the expression of both coding and non-coding genes. We also highlight the use of the comprehensive toolkit to perform combinatorial gene knockout to identify factors that regulate homologous recombination, along with investigating the regulatory role of a 68-kb intronic region associated with human disease.
{"title":"Generation and Application of a Versatile CRISPR Toolkit for Mammalian Cell Engineering","authors":"N. Dang, Alissa Lance-Byrne, Angela Tung, Xiaoge Guo, Ryan J. Cecchi, Joanna Buchthal, Alejandro Chavez, N. C. Yeo","doi":"10.1093/synbio/ysab033","DOIUrl":"https://doi.org/10.1093/synbio/ysab033","url":null,"abstract":"\u0000 CRISPR/Cas9 has revolutionized the field of genome engineering. Yet, as the CRISPR toolbox has rapidly expanded, there remains a need for a comprehensive library of CRISPR/Cas9 reagents that allow users to perform complex cellular and genetic manipulations without requiring labor-intensive generation of reagents to meet each user’s unique experimental circumstances. Here we described the creation and validation of a pNAX CRISPR library consisting of 72 different Cas9 and gRNA expression plasmids to allow for efficient multiplex gene editing, activation, and repression in mammalian cells. The toolkit plasmids, which are piggyBac or lentiviral based, provide the means for reliable and rapid delivery of Cas9/gRNA through either transient transfection or stable integration. Using the toolkit, we demonstrate the ease with which users can perform single or multiplex gene editing and modulate the expression of both coding and non-coding genes. We also highlight the use of the comprehensive toolkit to perform combinatorial gene knockout to identify factors that regulate homologous recombination, along with investigating the regulatory role of a 68-kb intronic region associated with human disease.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2021-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83629927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laboratory automation and mathematical optimisation are key to improving the efficiency of synthetic biology research. While there are algorithms optimising the construct designs and synthesis strategies for DNA assembly, the optimisation of how DNA assembly reaction mixes are prepared remains largely unexplored. Here, we focus on reducing the pipette tip consumption of a liquid-handling robot as it delivers DNA parts across a multi-well plate where several constructs are being assembled in parallel. We propose a linear programming formulation of this problem based on the capacitated vehicle routing problem, along with an algorithm which applies a linear programming solver to our formulation, hence providing a strategy to prepare a given set of DNA assembly mixes using fewer pipette tips. The algorithm performed well in randomly generated and real-life scenarios concerning several modular DNA assembly standards, proving capable of reducing the pipette tip consumption by up to 61% in large-scale cases. Combining automatic process optimisation and robotic liquid-handling, our strategy promises to greatly improve the efficiency of DNA assembly, either used alone or in combination with other algorithmic methods.
{"title":"A linear programming-based strategy to save pipette tips in automated DNA assembly","authors":"Kirill Sechkar, Z. Tuza, G. Stan","doi":"10.1093/synbio/ysac004","DOIUrl":"https://doi.org/10.1093/synbio/ysac004","url":null,"abstract":"Laboratory automation and mathematical optimisation are key to improving the efficiency of synthetic biology research. While there are algorithms optimising the construct designs and synthesis strategies for DNA assembly, the optimisation of how DNA assembly reaction mixes are prepared remains largely unexplored. Here, we focus on reducing the pipette tip consumption of a liquid-handling robot as it delivers DNA parts across a multi-well plate where several constructs are being assembled in parallel. We propose a linear programming formulation of this problem based on the capacitated vehicle routing problem, along with an algorithm which applies a linear programming solver to our formulation, hence providing a strategy to prepare a given set of DNA assembly mixes using fewer pipette tips. The algorithm performed well in randomly generated and real-life scenarios concerning several modular DNA assembly standards, proving capable of reducing the pipette tip consumption by up to 61% in large-scale cases. Combining automatic process optimisation and robotic liquid-handling, our strategy promises to greatly improve the efficiency of DNA assembly, either used alone or in combination with other algorithmic methods.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2021-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84976747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jing Wui Yeoh, Neil Swainston, Peter Vegh, Valentin Zulkower, Pablo Carbonell, M. B. Holowko, Gopal Peddinti, C. Poh
Abstract Advances in hardware automation in synthetic biology laboratories are not yet fully matched by those of their software counterparts. Such automated laboratories, now commonly called biofoundries, require software solutions that would help with many specialized tasks such as batch DNA design, sample and data tracking, and data analysis, among others. Typically, many of the challenges facing biofoundries are shared, yet there is frequent wheel-reinvention where many labs develop similar software solutions in parallel. In this article, we present the first attempt at creating a standardized, open-source Python package. A number of tools will be integrated and developed that we envisage will become the obvious starting point for software development projects within biofoundries globally. Specifically, we describe the current state of available software, present usage scenarios and case studies for common problems, and finally describe plans for future development. SynBiopython is publicly available at the following address: http://synbiopython.org.
{"title":"SynBiopython: an open-source software library for Synthetic Biology","authors":"Jing Wui Yeoh, Neil Swainston, Peter Vegh, Valentin Zulkower, Pablo Carbonell, M. B. Holowko, Gopal Peddinti, C. Poh","doi":"10.1093/synbio/ysab001","DOIUrl":"https://doi.org/10.1093/synbio/ysab001","url":null,"abstract":"Abstract Advances in hardware automation in synthetic biology laboratories are not yet fully matched by those of their software counterparts. Such automated laboratories, now commonly called biofoundries, require software solutions that would help with many specialized tasks such as batch DNA design, sample and data tracking, and data analysis, among others. Typically, many of the challenges facing biofoundries are shared, yet there is frequent wheel-reinvention where many labs develop similar software solutions in parallel. In this article, we present the first attempt at creating a standardized, open-source Python package. A number of tools will be integrated and developed that we envisage will become the obvious starting point for software development projects within biofoundries globally. Specifically, we describe the current state of available software, present usage scenarios and case studies for common problems, and finally describe plans for future development. SynBiopython is publicly available at the following address: http://synbiopython.org.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90839804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alejandro Arce-Rodríguez, Ilaria Benedetti, Rafael Silva-Rocha, V. de Lorenzo
Although inducible heterologous expression systems have been available since the birth of recombinant DNA technology, the diversity of devices and genetic architectures of the corresponding vectors have often resulted in a lack of reproducibility and interoperability. In an effort to increase predictability of expression of genes of interest in a variety of possible bacterial hosts we propose a composition standard for debugging and reassembling all regulatory parts that participate in the performance of such devices. As a case study we address the n-octane and dicyclopropyl ketone (DCPK)-inducible PalkB promoter of the alkane biodegradation pOCT plasmid of Pseudomonas putida. The standardized expression module consisted of an edited alkS regulatory gene that is divergently expressed and separated of PalkB by a synthetic DNA buffer sequence. The native DNA sequence of the structural alkS gene was modified to alleviate the catabolite repression exerted by some carbon and nitrogen sources through the Crc/Hfq complex of some hosts. The PalkB promoter along with the alkS variants were then formatted as SEVA (Standard European Vector Architecture) cargoes and their activity parameters in P. putida determined with GFP and luminiscent reporters. The thereby refactored system showed improvements in various features desirable in conditional expression modules: inducibility, capacity, noise reduction and on/off ratio. When applied to other promoter/regulator pairs, the compositional standard thereby implemented in the AlkS/PalkB module will enable more complex genetic programming in non-model bacteria.
{"title":"Standardization of inducer-activated broad host range expression modules: debugging and refactoring an alkane-responsive AlkS/PalkB device","authors":"Alejandro Arce-Rodríguez, Ilaria Benedetti, Rafael Silva-Rocha, V. de Lorenzo","doi":"10.1093/synbio/ysab030","DOIUrl":"https://doi.org/10.1093/synbio/ysab030","url":null,"abstract":"Although inducible heterologous expression systems have been available since the birth of recombinant DNA technology, the diversity of devices and genetic architectures of the corresponding vectors have often resulted in a lack of reproducibility and interoperability. In an effort to increase predictability of expression of genes of interest in a variety of possible bacterial hosts we propose a composition standard for debugging and reassembling all regulatory parts that participate in the performance of such devices. As a case study we address the n-octane and dicyclopropyl ketone (DCPK)-inducible PalkB promoter of the alkane biodegradation pOCT plasmid of Pseudomonas putida. The standardized expression module consisted of an edited alkS regulatory gene that is divergently expressed and separated of PalkB by a synthetic DNA buffer sequence. The native DNA sequence of the structural alkS gene was modified to alleviate the catabolite repression exerted by some carbon and nitrogen sources through the Crc/Hfq complex of some hosts. The PalkB promoter along with the alkS variants were then formatted as SEVA (Standard European Vector Architecture) cargoes and their activity parameters in P. putida determined with GFP and luminiscent reporters. The thereby refactored system showed improvements in various features desirable in conditional expression modules: inducibility, capacity, noise reduction and on/off ratio. When applied to other promoter/regulator pairs, the compositional standard thereby implemented in the AlkS/PalkB module will enable more complex genetic programming in non-model bacteria.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2020-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85708124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nymul E. Khan, Enoch Yeung, Yuliya Farris, S. Fansler, Hans C. Bernstein
Modern microbial biodesign relies on the principle that well-characterized genetic parts can be reused and reconfigured for different functions. However, this paradigm has only been successful in a limited set of hosts, mostly comprised from common lab strains of Escherichia coli. It is clear that new applications such as chemical sensing and event logging in complex environments will benefit from new host chassis. This study quantitatively compared how the same chemical event logger performed across four strains and three different microbial species. An integrase-based sensor and memory device was operated by two representative soil Pseudomonads—Pseudomonas fluorescens SBW25 and Pseudomonas putida DSM 291. Quantitative comparisons were made between these two non-traditional hosts and two benchmark E. coli chassis including the probiotic Nissle 1917 and common cloning strain DH5α. The performance of sensor and memory components changed according to each host, such that a clear chassis effect was observed and quantified. These results were obtained via fluorescence from reporter proteins that were transcriptionally fused to the integrase and downstream recombinant region and via data-driven kinetic models. The Pseudomonads proved to be acceptable chassis for the operation of this event logger, which outperformed the common E. coli DH5α in many ways. This study advances an emerging frontier in synthetic biology that aims to build broad-host-range devices and understand the context by which different species can execute programmable genetic operations.
{"title":"A broad-host-range event detector: expanding and quantifying performance between Escherichia coli and Pseudomonas species","authors":"Nymul E. Khan, Enoch Yeung, Yuliya Farris, S. Fansler, Hans C. Bernstein","doi":"10.1093/synbio/ysaa002","DOIUrl":"https://doi.org/10.1093/synbio/ysaa002","url":null,"abstract":"Modern microbial biodesign relies on the principle that well-characterized genetic parts can be reused and reconfigured for different functions. However, this paradigm has only been successful in a limited set of hosts, mostly comprised from common lab strains of Escherichia coli. It is clear that new applications such as chemical sensing and event logging in complex environments will benefit from new host chassis. This study quantitatively compared how the same chemical event logger performed across four strains and three different microbial species. An integrase-based sensor and memory device was operated by two representative soil Pseudomonads—Pseudomonas fluorescens SBW25 and Pseudomonas putida DSM 291. Quantitative comparisons were made between these two non-traditional hosts and two benchmark E. coli chassis including the probiotic Nissle 1917 and common cloning strain DH5α. The performance of sensor and memory components changed according to each host, such that a clear chassis effect was observed and quantified. These results were obtained via fluorescence from reporter proteins that were transcriptionally fused to the integrase and downstream recombinant region and via data-driven kinetic models. The Pseudomonads proved to be acceptable chassis for the operation of this event logger, which outperformed the common E. coli DH5α in many ways. This study advances an emerging frontier in synthetic biology that aims to build broad-host-range devices and understand the context by which different species can execute programmable genetic operations.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85385553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gledon Doçi, Lukas Fuchs, Y. Kharbanda, Paul Schickling, Valentin Zulkower, N. Hillson, Ernst Oberortner, Neil Swainston, Johannes Kabisch
DNA synthesis has become a major enabler of modern bioengineering, allowing scientists to simply order online in silico-designed DNA molecules. Rapidly decreasing DNA synthesis service prices and the concomitant increase of research and development scales bolstered by computer-aided DNA design tools and laboratory automation has driven up the demand for synthetic DNA. While vendors provide user-friendly online portals for purchasing synthetic DNA, customers still face the time-consuming task of checking each vendor of choice for their ability and pricing to synthesize the desired sequences. As a result, ordering large batches of DNA sequences can be a laborious manual procedure in an otherwise increasingly automatable workflow. Even when they are available, there is a high degree of technical knowledge and effort required to integrate vendors’ application programming interfaces (APIs) into computer-aided DNA design tools or automated lab processes. Here, we introduce DNA Scanner, a software package comprising (i) a web-based user interface enabling users to compare the feasibility, price and turnaround time of synthetic DNA sequences across selected vendors and (ii) a Python API enabling integration of these functionalities into computer-aided DNA design tools and automated lab processes. We have developed DNA Scanner to uniformly streamline interactions between synthetic DNA vendors, members of the Global Biofoundry Alliance and the scientific community at large.
{"title":"DNA Scanner: a web application for comparing DNA synthesis feasibility, price and turnaround time across vendors","authors":"Gledon Doçi, Lukas Fuchs, Y. Kharbanda, Paul Schickling, Valentin Zulkower, N. Hillson, Ernst Oberortner, Neil Swainston, Johannes Kabisch","doi":"10.1093/synbio/ysaa011","DOIUrl":"https://doi.org/10.1093/synbio/ysaa011","url":null,"abstract":"\u0000 DNA synthesis has become a major enabler of modern bioengineering, allowing scientists to simply order online in silico-designed DNA molecules. Rapidly decreasing DNA synthesis service prices and the concomitant increase of research and development scales bolstered by computer-aided DNA design tools and laboratory automation has driven up the demand for synthetic DNA. While vendors provide user-friendly online portals for purchasing synthetic DNA, customers still face the time-consuming task of checking each vendor of choice for their ability and pricing to synthesize the desired sequences. As a result, ordering large batches of DNA sequences can be a laborious manual procedure in an otherwise increasingly automatable workflow. Even when they are available, there is a high degree of technical knowledge and effort required to integrate vendors’ application programming interfaces (APIs) into computer-aided DNA design tools or automated lab processes. Here, we introduce DNA Scanner, a software package comprising (i) a web-based user interface enabling users to compare the feasibility, price and turnaround time of synthetic DNA sequences across selected vendors and (ii) a Python API enabling integration of these functionalities into computer-aided DNA design tools and automated lab processes. We have developed DNA Scanner to uniformly streamline interactions between synthetic DNA vendors, members of the Global Biofoundry Alliance and the scientific community at large.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82107994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Could cells without genomes become the new synthetic biology chassis?","authors":"Konstantinos Vavitsas","doi":"10.1093/synbio/ysaa003","DOIUrl":"https://doi.org/10.1093/synbio/ysaa003","url":null,"abstract":"","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77065951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Robinson, Megan D. Smith, J. Richman, Kelly G. Aukema, L. Wackett
Enzymes in the thiolase superfamily catalyze carbon–carbon bond formation for the biosynthesis of polyhydroxyalkanoate storage molecules, membrane lipids and bioactive secondary metabolites. Natural and engineered thiolases have applications in synthetic biology for the production of high-value compounds, including personal care products and therapeutics. A fundamental understanding of thiolase substrate specificity is lacking, particularly within the OleA protein family. The ability to predict substrates from sequence would advance (meta)genome mining efforts to identify active thiolases for the production of desired metabolites. To gain a deeper understanding of substrate scope within the OleA family, we measured the activity of 73 diverse bacterial thiolases with a library of 15 p-nitrophenyl ester substrates to build a training set of 1095 unique enzyme–substrate pairs. We then used machine learning to predict thiolase substrate specificity from physicochemical and structural features. The area under the receiver operating characteristic curve was 0.89 for random forest classification of enzyme activity, and our regression model had a test set root mean square error of 0.22 (R2 = 0.75) to quantitatively predict enzyme activity levels. Substrate aromaticity, oxygen content and molecular connectivity were the strongest predictors of enzyme–substrate pairing. Key amino acid residues A173, I284, V287, T292 and I316 in the Xanthomonas campestris OleA crystal structure lining the substrate binding pockets were important for thiolase substrate specificity and are attractive targets for future protein engineering studies. The predictive framework described here is generalizable and demonstrates how machine learning can be used to quantitatively understand and predict enzyme substrate specificity.
{"title":"Machine learning-based prediction of activity and substrate specificity for OleA enzymes in the thiolase superfamily","authors":"S. Robinson, Megan D. Smith, J. Richman, Kelly G. Aukema, L. Wackett","doi":"10.1093/synbio/ysaa004","DOIUrl":"https://doi.org/10.1093/synbio/ysaa004","url":null,"abstract":"\u0000 Enzymes in the thiolase superfamily catalyze carbon–carbon bond formation for the biosynthesis of polyhydroxyalkanoate storage molecules, membrane lipids and bioactive secondary metabolites. Natural and engineered thiolases have applications in synthetic biology for the production of high-value compounds, including personal care products and therapeutics. A fundamental understanding of thiolase substrate specificity is lacking, particularly within the OleA protein family. The ability to predict substrates from sequence would advance (meta)genome mining efforts to identify active thiolases for the production of desired metabolites. To gain a deeper understanding of substrate scope within the OleA family, we measured the activity of 73 diverse bacterial thiolases with a library of 15 p-nitrophenyl ester substrates to build a training set of 1095 unique enzyme–substrate pairs. We then used machine learning to predict thiolase substrate specificity from physicochemical and structural features. The area under the receiver operating characteristic curve was 0.89 for random forest classification of enzyme activity, and our regression model had a test set root mean square error of 0.22 (R2 = 0.75) to quantitatively predict enzyme activity levels. Substrate aromaticity, oxygen content and molecular connectivity were the strongest predictors of enzyme–substrate pairing. Key amino acid residues A173, I284, V287, T292 and I316 in the Xanthomonas campestris OleA crystal structure lining the substrate binding pockets were important for thiolase substrate specificity and are attractive targets for future protein engineering studies. The predictive framework described here is generalizable and demonstrates how machine learning can be used to quantitatively understand and predict enzyme substrate specificity.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89910562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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