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":"21 1","pages":""},"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":"506 1","pages":""},"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":"18 1","pages":""},"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}
S. B. Le, Ingerid Onsager, J. A. Lorentzen, R. Lale
Bacterial 5′ untranslated regions of mRNA (UTR) involve in a complex regulation of gene expression; however, the exact sequence features contributing to gene regulation are not yet fully understood. In this study, we report the design of a novel 5′ UTR, dual UTR, utilising the transcriptional and translational characteristics of 5′ UTRs in a single expression cassette. The dual UTR consists of two 5′ UTRs, each separately leading to either increase in transcription or translation of the reporter, that are separated by a spacer region, enabling de novo translation initiation. We rationally create dual UTRs with a wide range of expression profiles and demonstrate the functionality of the novel design concept in Escherichia coli and in Pseudomonas putida using different promoter systems and coding sequences. Overall, we demonstrate the application potential of dual UTR design concept in various synthetic biology applications ranging from fine-tuning of gene expression to maximisation of protein production.
{"title":"Dual UTR-A novel 5′ untranslated region design for synthetic biology applications","authors":"S. B. Le, Ingerid Onsager, J. A. Lorentzen, R. Lale","doi":"10.1101/775643","DOIUrl":"https://doi.org/10.1101/775643","url":null,"abstract":"Bacterial 5′ untranslated regions of mRNA (UTR) involve in a complex regulation of gene expression; however, the exact sequence features contributing to gene regulation are not yet fully understood. In this study, we report the design of a novel 5′ UTR, dual UTR, utilising the transcriptional and translational characteristics of 5′ UTRs in a single expression cassette. The dual UTR consists of two 5′ UTRs, each separately leading to either increase in transcription or translation of the reporter, that are separated by a spacer region, enabling de novo translation initiation. We rationally create dual UTRs with a wide range of expression profiles and demonstrate the functionality of the novel design concept in Escherichia coli and in Pseudomonas putida using different promoter systems and coding sequences. Overall, we demonstrate the application potential of dual UTR design concept in various synthetic biology applications ranging from fine-tuning of gene expression to maximisation of protein production.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":"57 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2019-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83118711","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}
Engineering metabolism for the synthesis of bio-based products in non-model organisms can be challenging. One specific challenge is that biosynthetic pathways are often built from enzyme candidates sourced from diverse organisms, which can prove difficult to implement in recombinant hosts due to differences in their cellular environments (e.g. pH, cofactor balance). To address this problem, we report a cell-free synthetic biology approach for understanding metabolism in a range of environmental conditions, specifically under varied pH. The key idea is to control the pH of Escherichia coli-based cell-free systems for assessing pathway performance using enzymes sourced from organisms other than E. coli. As a model, we apply this approach to study the impact of pH on the n-butanol biosynthesis pathway derived from clostridia in E. coli lysates. Specifically, we exploit the open, cell-free reaction environment to explore pH outside the habitable range of E. coli, revealing insights into how chemical context impacts the interaction between native metabolism and heterologous enzymes. We find that the pH optimum for butanol production from acetyl-CoA is substantially lower than the optimal pH of glycolysis in E. coli-based crude lysates. In addition, pH is an essential factor to consider when activating metabolic pathways in the cell-free environment due to its effect on reaction yield or enzyme activity, the latter of which is demonstrated in this work for alcohol dehydrogenases from a range of extremophiles. Ultimately, altering metabolism through pH control will allow cell-free systems to be used in studying the metabolic state of organisms and identify suitable enzymes for pathway engineering.
{"title":"Enhancing control of cell-free metabolism through pH modulation","authors":"Ashty S. Karim, Blake J. Rasor, M. Jewett","doi":"10.1093/synbio/ysz027","DOIUrl":"https://doi.org/10.1093/synbio/ysz027","url":null,"abstract":"Engineering metabolism for the synthesis of bio-based products in non-model organisms can be challenging. One specific challenge is that biosynthetic pathways are often built from enzyme candidates sourced from diverse organisms, which can prove difficult to implement in recombinant hosts due to differences in their cellular environments (e.g. pH, cofactor balance). To address this problem, we report a cell-free synthetic biology approach for understanding metabolism in a range of environmental conditions, specifically under varied pH. The key idea is to control the pH of Escherichia coli-based cell-free systems for assessing pathway performance using enzymes sourced from organisms other than E. coli. As a model, we apply this approach to study the impact of pH on the n-butanol biosynthesis pathway derived from clostridia in E. coli lysates. Specifically, we exploit the open, cell-free reaction environment to explore pH outside the habitable range of E. coli, revealing insights into how chemical context impacts the interaction between native metabolism and heterologous enzymes. We find that the pH optimum for butanol production from acetyl-CoA is substantially lower than the optimal pH of glycolysis in E. coli-based crude lysates. In addition, pH is an essential factor to consider when activating metabolic pathways in the cell-free environment due to its effect on reaction yield or enzyme activity, the latter of which is demonstrated in this work for alcohol dehydrogenases from a range of extremophiles. Ultimately, altering metabolism through pH control will allow cell-free systems to be used in studying the metabolic state of organisms and identify suitable enzymes for pathway engineering.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":"27 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73610027","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 Synthetic biology aims to introduce engineering principles into biology, for example, the construction of biological devices by assembling previously-characterized, functional parts. This approach demands new resources for cataloging and sharing biological components and designs, in order to accelerate the design-build-test-learn cycle. We evaluated two free, open source software platforms for managing synthetic biology data: Joint Bioenergy Institute-Inventory of Composable Elements (JBEI-ICE) and SynBioHub. We analyzed the systems from the perspective of experimental biology research groups in academia, which seek to incorporate the repositories into their synthetic biology workflow. Here, we define the minimal requirements for a repository in this context and develop three usage scenarios, where we then examine the two platforms: (i) supporting the synthetic biology design-build-test-learn cycle, (ii) batch deposit of existing designs into the repository and (iii) discovery and reuse of designs from the repository. Our evaluation of JBEI-ICE and SynBioHub provides an insight into the current state of synthetic biology resources, might encourage their wider adoption and should guide future development to better meet the needs of this user group.
{"title":"Better research by efficient sharing: evaluation of free management platforms for synthetic biology designs","authors":"Uriel Urquiza-García, Tomasz Zieliński, A. Millar","doi":"10.1093/synbio/ysz016","DOIUrl":"https://doi.org/10.1093/synbio/ysz016","url":null,"abstract":"Abstract Synthetic biology aims to introduce engineering principles into biology, for example, the construction of biological devices by assembling previously-characterized, functional parts. This approach demands new resources for cataloging and sharing biological components and designs, in order to accelerate the design-build-test-learn cycle. We evaluated two free, open source software platforms for managing synthetic biology data: Joint Bioenergy Institute-Inventory of Composable Elements (JBEI-ICE) and SynBioHub. We analyzed the systems from the perspective of experimental biology research groups in academia, which seek to incorporate the repositories into their synthetic biology workflow. Here, we define the minimal requirements for a repository in this context and develop three usage scenarios, where we then examine the two platforms: (i) supporting the synthetic biology design-build-test-learn cycle, (ii) batch deposit of existing designs into the repository and (iii) discovery and reuse of designs from the repository. Our evaluation of JBEI-ICE and SynBioHub provides an insight into the current state of synthetic biology resources, might encourage their wider adoption and should guide future development to better meet the needs of this user group.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":"26 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78154452","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}
Brian E. Hew, Ryuei Sato, D. Mauro, I. Stoytchev, Jesse B. Owens
Abstract Safer and more efficient methods for directing therapeutic genes to specific sequences could increase the repertoire of treatable conditions. Many current approaches act passively, first initiating a double-stranded break, then relying on host repair to uptake donor DNA. Alternatively, we delivered an actively integrating transposase to the target sequence to initiate gene insertion. We fused the hyperactive piggyBac transposase to the highly specific, catalytically dead SpCas9-HF1 (dCas9) and designed guide RNAs (gRNAs) to the CCR5 safe harbor sequence. We introduced mutations to the native DNA-binding domain of piggyBac to reduce non-specific binding of the transposase and cause the fusion protein to favor binding by dCas9. This strategy enabled us, for the first time, to direct transposition to the genome using RNA. We showed that increasing the number of gRNAs improved targeting efficiency. Interestingly, over half of the recovered insertions were found at a single TTAA hotspot. We also found that the fusion increased the error rate at the genome-transposon junction. We isolated clonal cell lines containing a single insertion at CCR5 and demonstrated long-term expression from this locus. These vectors expand the utility of the piggyBac system for applications in targeted gene addition for biomedical research and gene therapy.
{"title":"RNA-guided piggyBac transposition in human cells","authors":"Brian E. Hew, Ryuei Sato, D. Mauro, I. Stoytchev, Jesse B. Owens","doi":"10.1093/synbio/ysz018","DOIUrl":"https://doi.org/10.1093/synbio/ysz018","url":null,"abstract":"Abstract Safer and more efficient methods for directing therapeutic genes to specific sequences could increase the repertoire of treatable conditions. Many current approaches act passively, first initiating a double-stranded break, then relying on host repair to uptake donor DNA. Alternatively, we delivered an actively integrating transposase to the target sequence to initiate gene insertion. We fused the hyperactive piggyBac transposase to the highly specific, catalytically dead SpCas9-HF1 (dCas9) and designed guide RNAs (gRNAs) to the CCR5 safe harbor sequence. We introduced mutations to the native DNA-binding domain of piggyBac to reduce non-specific binding of the transposase and cause the fusion protein to favor binding by dCas9. This strategy enabled us, for the first time, to direct transposition to the genome using RNA. We showed that increasing the number of gRNAs improved targeting efficiency. Interestingly, over half of the recovered insertions were found at a single TTAA hotspot. We also found that the fusion increased the error rate at the genome-transposon junction. We isolated clonal cell lines containing a single insertion at CCR5 and demonstrated long-term expression from this locus. These vectors expand the utility of the piggyBac system for applications in targeted gene addition for biomedical research and gene therapy.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":"105 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74270042","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}
Pub Date : 2018-10-01DOI: 10.1007/978-981-10-8693-9_9
A. Nandy, Antara De, P. Roy, Munna Dutta, Moumita Roy, Dwaipayan Sen, S. Basak
{"title":"Alignment-Free Analyses of Nucleic Acid Sequences Using Graphical Representation (with Special Reference to Pandemic Bird Flu and Swine Flu)","authors":"A. Nandy, Antara De, P. Roy, Munna Dutta, Moumita Roy, Dwaipayan Sen, S. Basak","doi":"10.1007/978-981-10-8693-9_9","DOIUrl":"https://doi.org/10.1007/978-981-10-8693-9_9","url":null,"abstract":"","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":"65 1","pages":"141 - 188"},"PeriodicalIF":3.2,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79587756","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}
Á. Nyerges, B. Bálint, Judit Cseklye, I. Nagy, Csaba Pál, T. Fehér
Spontaneous mutagenesis of synthetic genetic constructs by mobile genetic elements frequently results in the rapid loss of advantageous functions. Previous efforts to minimize such mutations required the exceedingly time-consuming manipulation of bacterial chromosomes and the complete removal of insertional sequences (ISes). To this aim, we developed a single plasmid-based system (pCRIS) that applies CRISPR-interference to inhibit the transposition of bacterial ISes. pCRIS expresses multiple guide RNAs to direct inactivated Cas9 (dCas9) to simultaneously silence IS1, IS3, IS5, and IS150 at up to 38 chromosomal loci in Escherichia coli, in vivo. As a result, the transposition rate of all four targeted ISes dropped to negligible levels at both chromosomal and episomal targets, increasing the half-life of exogenous protein expression. Most notably, pCRIS, while requiring only a single plasmid delivery performed within a single day, provided a reduction of IS-mobility comparable to that seen in genome-scale chromosome engineering projects. Global transcriptomics analysis revealed nevertheless only minute alterations in the expression of untargeted genes. Finally, the transposition-silencing effect of pCRIS was easily transferable across multiple E. coli strains. The plasticity and robustness of our IS-silencing system make it a promising tool to stabilize bacterial genomes for synthetic biology and industrial biotechnology applications.
{"title":"CRISPR-interference-based modulation of mobile genetic elements in bacteria","authors":"Á. Nyerges, B. Bálint, Judit Cseklye, I. Nagy, Csaba Pál, T. Fehér","doi":"10.1101/428029","DOIUrl":"https://doi.org/10.1101/428029","url":null,"abstract":"Spontaneous mutagenesis of synthetic genetic constructs by mobile genetic elements frequently results in the rapid loss of advantageous functions. Previous efforts to minimize such mutations required the exceedingly time-consuming manipulation of bacterial chromosomes and the complete removal of insertional sequences (ISes). To this aim, we developed a single plasmid-based system (pCRIS) that applies CRISPR-interference to inhibit the transposition of bacterial ISes. pCRIS expresses multiple guide RNAs to direct inactivated Cas9 (dCas9) to simultaneously silence IS1, IS3, IS5, and IS150 at up to 38 chromosomal loci in Escherichia coli, in vivo. As a result, the transposition rate of all four targeted ISes dropped to negligible levels at both chromosomal and episomal targets, increasing the half-life of exogenous protein expression. Most notably, pCRIS, while requiring only a single plasmid delivery performed within a single day, provided a reduction of IS-mobility comparable to that seen in genome-scale chromosome engineering projects. Global transcriptomics analysis revealed nevertheless only minute alterations in the expression of untargeted genes. Finally, the transposition-silencing effect of pCRIS was easily transferable across multiple E. coli strains. The plasticity and robustness of our IS-silencing system make it a promising tool to stabilize bacterial genomes for synthetic biology and industrial biotechnology applications.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":"301 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2018-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89039674","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}
DNA origami, a method for constructing nanoscale objects, relies on a long single strand of DNA to act as the “scaffold” to template assembly of numerous short DNA oligonucleotide “staples”. The ability to generate custom scaffold sequences can greatly benefit DNA origami design processes. Custom scaffold sequences can provide better control of the overall size of the final object and better control of low-level structural details, such as locations of specific base pairs within an object. Filamentous bacteriophages and related phagemids can work well as sources of custom scaffold DNA. However, scaffolds derived from phages require inclusion of multi-kilobase DNA sequences in order to grow in host bacteria, and thus cannot be altered or removed. These fixed-sequence regions constrain the design possibilities of DNA origami. Here we report the construction of a novel phagemid, pScaf, to produce scaffolds that have a custom sequence with a much smaller fixed region of only 381 bases. We used pScaf to generate new scaffolds ranging in size from 1,512 to 10,080 bases and demonstrated their use in various DNA origami shapes and assemblies. We anticipate our pScaf phagemid will enhance development of the DNA origami method and its future applications.
{"title":"Construction of a novel phagemid to produce custom DNA origami scaffolds","authors":"Parsa M. Nafisi, Tural Aksel, Shawn M. Douglas","doi":"10.1101/309682","DOIUrl":"https://doi.org/10.1101/309682","url":null,"abstract":"DNA origami, a method for constructing nanoscale objects, relies on a long single strand of DNA to act as the “scaffold” to template assembly of numerous short DNA oligonucleotide “staples”. The ability to generate custom scaffold sequences can greatly benefit DNA origami design processes. Custom scaffold sequences can provide better control of the overall size of the final object and better control of low-level structural details, such as locations of specific base pairs within an object. Filamentous bacteriophages and related phagemids can work well as sources of custom scaffold DNA. However, scaffolds derived from phages require inclusion of multi-kilobase DNA sequences in order to grow in host bacteria, and thus cannot be altered or removed. These fixed-sequence regions constrain the design possibilities of DNA origami. Here we report the construction of a novel phagemid, pScaf, to produce scaffolds that have a custom sequence with a much smaller fixed region of only 381 bases. We used pScaf to generate new scaffolds ranging in size from 1,512 to 10,080 bases and demonstrated their use in various DNA origami shapes and assemblies. We anticipate our pScaf phagemid will enhance development of the DNA origami method and its future applications.","PeriodicalId":22158,"journal":{"name":"Synthetic Biology","volume":"8 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82145364","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：