Pub Date : 2020-09-03eCollection Date: 2020-01-01DOI: 10.1093/synbio/ysaa015
Avery J C Noonan, Yilin Qiu, Joe C H Ho, Jewel Ocampo, K A Vreugdenhil, R Alexander Marr, Zhiying Zhao, Yasuo Yoshikuni, Steven J Hallam
Monitoring population dynamics in co-culture is necessary in engineering microbial consortia involved in distributed metabolic processes or biosensing applications. However, it remains difficult to measure strain-specific growth dynamics in high-throughput formats. This is especially vexing in plate-based functional screens leveraging whole-cell biosensors to detect specific metabolic signals. Here, we develop an experimental high-throughput co-culture system to measure and model the relationship between fluorescence and cell abundance, combining chassis-independent recombinase-assisted genome engineering (CRAGE) and whole-cell biosensing with a PemrR-green fluorescent protein (GFP) monoaromatic reporter used in plate-based functional screening. CRAGE was used to construct Escherichia coli EPI300 strains constitutively expressing red fluorescent protein (RFP) and the relationship between RFP expression and optical density (OD600) was determined throughout the EPI300 growth cycle. A linear equation describing the increase of normalized RFP fluorescence during deceleration phase was derived and used to predict biosensor strain dynamics in co-culture. Measured and predicted values were compared using flow cytometric detection methods. Induction of the biosensor lead to increased GFP fluorescence normalized to biosensor cell abundance, as expected, but a significant decrease in relative abundance of the biosensor strain in co-culture and a decrease in bulk GFP fluorescence. Taken together, these results highlight sensitivity of population dynamics to variations in metabolic activity in co-culture and the potential effect of these dynamics on the performance of functional screens in plate-based formats. The engineered strains and model used to evaluate these dynamics provide a framework for optimizing growth of synthetic co-cultures used in screening, testing and pathway engineering applications.
{"title":"CRAGE-mediated insertion of fluorescent chromosomal markers for accurate and scalable measurement of co-culture dynamics in <i>Escherichia coli</i>.","authors":"Avery J C Noonan, Yilin Qiu, Joe C H Ho, Jewel Ocampo, K A Vreugdenhil, R Alexander Marr, Zhiying Zhao, Yasuo Yoshikuni, Steven J Hallam","doi":"10.1093/synbio/ysaa015","DOIUrl":"https://doi.org/10.1093/synbio/ysaa015","url":null,"abstract":"<p><p>Monitoring population dynamics in co-culture is necessary in engineering microbial consortia involved in distributed metabolic processes or biosensing applications. However, it remains difficult to measure strain-specific growth dynamics in high-throughput formats. This is especially vexing in plate-based functional screens leveraging whole-cell biosensors to detect specific metabolic signals. Here, we develop an experimental high-throughput co-culture system to measure and model the relationship between fluorescence and cell abundance, combining chassis-independent recombinase-assisted genome engineering (CRAGE) and whole-cell biosensing with a P<sub>emrR</sub>-green fluorescent protein (GFP) monoaromatic reporter used in plate-based functional screening. CRAGE was used to construct <i>Escherichia coli</i> EPI300 strains constitutively expressing red fluorescent protein (RFP) and the relationship between RFP expression and optical density (OD<sub>600</sub>) was determined throughout the EPI300 growth cycle. A linear equation describing the increase of normalized RFP fluorescence during deceleration phase was derived and used to predict biosensor strain dynamics in co-culture. Measured and predicted values were compared using flow cytometric detection methods. Induction of the biosensor lead to increased GFP fluorescence normalized to biosensor cell abundance, as expected, but a significant decrease in relative abundance of the biosensor strain in co-culture and a decrease in bulk GFP fluorescence. Taken together, these results highlight sensitivity of population dynamics to variations in metabolic activity in co-culture and the potential effect of these dynamics on the performance of functional screens in plate-based formats. The engineered strains and model used to evaluate these dynamics provide a framework for optimizing growth of synthetic co-cultures used in screening, testing and pathway engineering applications.</p>","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"5 1","pages":"ysaa015"},"PeriodicalIF":0.0,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysaa015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38768150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-19eCollection Date: 2020-01-01DOI: 10.1093/synbio/ysaa014
Michael Fitzgerald, Mark Livingston, Chelsea Gibbs, Tara L Deans
Approaches in mammalian synthetic biology have transformed how cells can be programmed to have reliable and predictable behavior, however, the majority of mammalian synthetic biology has been accomplished using immortalized cell lines that are easy to grow and easy to transfect. Genetic circuits that integrate into the genome of these immortalized cell lines remain functional for many generations, often for the lifetime of the cells, yet when genetic circuits are integrated into the genome of stem cells gene silencing is observed within a few generations. To investigate the reactivation of silenced genetic circuits in stem cells, the Rosa26 locus of mouse pluripotent stem cells was modified to contain docking sites for site-specific integration of genetic circuits. We show that the silencing of genetic circuits can be reversed with the addition of sodium butyrate, a histone deacetylase inhibitor. These findings demonstrate an approach to reactivate the function of genetic circuits in pluripotent stem cells to ensure robust function over many generations. Altogether, this work introduces an approach to overcome the silencing of genetic circuits in pluripotent stem cells that may enable the use of genetic circuits in pluripotent stem cells for long-term function.
{"title":"Rosa26 docking sites for investigating genetic circuit silencing in stem cells.","authors":"Michael Fitzgerald, Mark Livingston, Chelsea Gibbs, Tara L Deans","doi":"10.1093/synbio/ysaa014","DOIUrl":"10.1093/synbio/ysaa014","url":null,"abstract":"<p><p>Approaches in mammalian synthetic biology have transformed how cells can be programmed to have reliable and predictable behavior, however, the majority of mammalian synthetic biology has been accomplished using immortalized cell lines that are easy to grow and easy to transfect. Genetic circuits that integrate into the genome of these immortalized cell lines remain functional for many generations, often for the lifetime of the cells, yet when genetic circuits are integrated into the genome of stem cells gene silencing is observed within a few generations. To investigate the reactivation of silenced genetic circuits in stem cells, the Rosa26 locus of mouse pluripotent stem cells was modified to contain docking sites for site-specific integration of genetic circuits. We show that the silencing of genetic circuits can be reversed with the addition of sodium butyrate, a histone deacetylase inhibitor. These findings demonstrate an approach to reactivate the function of genetic circuits in pluripotent stem cells to ensure robust function over many generations. Altogether, this work introduces an approach to overcome the silencing of genetic circuits in pluripotent stem cells that may enable the use of genetic circuits in pluripotent stem cells for long-term function.</p>","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"5 1","pages":"ysaa014"},"PeriodicalIF":0.0,"publicationDate":"2020-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/67/56/ysaa014.PMC7644442.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38615937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-19eCollection Date: 2020-01-01DOI: 10.1093/synbio/ysaa016
Pablo Cárdenas
The survival of genetic information hinges on identifying repetition. Genomes are repaired by mechanisms such as homologous recombination, in which matching DNA sequences are used as a template to replace missing information. This strategy works provided sequences in the genome are mostly unique. While sequence diversity has kept genomes stable enough to replicate for millions of years, it poses a problem for those trying to engineer DNA (1). After all, one of the central tenets of synthetic biology is the reutilization of standard parts. How, then, can we design stable, non-repetitive genetic systems with a limited toolkit of synthetic parts? Researchers in Howard Salis’s lab at Pennsylvania State University set out to address this challenge through the Non-Repetitive Parts Calculator (NRPC), a set of new algorithms described in a recent publication by Hossain et al. (2) and available online (https://sali slab.net/software/). As the name implies, NRPC builds collections of biological parts containing minimal repetitive sequences, where the repetitiveness of a collection is defined by Lmax, the maximum length of the longest shared repeat. Collections can be created using two different modes. The ‘Finder’ mode determines the largest subset of nonrepetitive elements within any given database of parts, given a maximum Lmax set by the user. The sheer number of possible subsets to evaluate can make this computationally impractical for large libraries. The authors solve this problem by representing parts as nodes on a graph and improving on existing algorithms in graph theory to efficiently maximize the number of disconnected components. The ‘Maker’ mode creates a new library of non-repetitive parts within the design constraints set by the user, which may include a degenerate DNA sequence or RNA structure template and a set Lmax value. In this case, all possible sequences are represented as a decision tree and hash tables are used to store and check for occurrences of sub-sequences within parts. Hossain et al. tested their new ‘Maker’ algorithm by generating libraries of 4350 synthetic, non-repetitive bacterial promoters and 1722 yeast promoters, designed to have a wide range of transcription rates. The authors validated each library’s predicted transcriptional behavior by assembling and characterizing every promoter through next-generation DNA and RNA sequencing in Escherichia coli and Saccharomyces cerevisiae. The increased stability of NRPC designs was demonstrated in E. coli by comparing versions of a construct with either repetitive or non-repetitive promoters. The former rapidly lost fluorescence and DNA content while the latter remained stable. Finally, the authors applied regression models and neural networks developed elsewhere (3) to explain and predict the strength of the synthetic promoters they created. This work can have tremendous, immediate impact in two ways. Not only did Hossain et al. produce vast libraries of bacterial and yeast pro
{"title":"Designing for durability: new tools to build stable, non-repetitive DNA.","authors":"Pablo Cárdenas","doi":"10.1093/synbio/ysaa016","DOIUrl":"https://doi.org/10.1093/synbio/ysaa016","url":null,"abstract":"The survival of genetic information hinges on identifying repetition. Genomes are repaired by mechanisms such as homologous recombination, in which matching DNA sequences are used as a template to replace missing information. This strategy works provided sequences in the genome are mostly unique. While sequence diversity has kept genomes stable enough to replicate for millions of years, it poses a problem for those trying to engineer DNA (1). After all, one of the central tenets of synthetic biology is the reutilization of standard parts. How, then, can we design stable, non-repetitive genetic systems with a limited toolkit of synthetic parts? Researchers in Howard Salis’s lab at Pennsylvania State University set out to address this challenge through the Non-Repetitive Parts Calculator (NRPC), a set of new algorithms described in a recent publication by Hossain et al. (2) and available online (https://sali slab.net/software/). As the name implies, NRPC builds collections of biological parts containing minimal repetitive sequences, where the repetitiveness of a collection is defined by Lmax, the maximum length of the longest shared repeat. Collections can be created using two different modes. The ‘Finder’ mode determines the largest subset of nonrepetitive elements within any given database of parts, given a maximum Lmax set by the user. The sheer number of possible subsets to evaluate can make this computationally impractical for large libraries. The authors solve this problem by representing parts as nodes on a graph and improving on existing algorithms in graph theory to efficiently maximize the number of disconnected components. The ‘Maker’ mode creates a new library of non-repetitive parts within the design constraints set by the user, which may include a degenerate DNA sequence or RNA structure template and a set Lmax value. In this case, all possible sequences are represented as a decision tree and hash tables are used to store and check for occurrences of sub-sequences within parts. Hossain et al. tested their new ‘Maker’ algorithm by generating libraries of 4350 synthetic, non-repetitive bacterial promoters and 1722 yeast promoters, designed to have a wide range of transcription rates. The authors validated each library’s predicted transcriptional behavior by assembling and characterizing every promoter through next-generation DNA and RNA sequencing in Escherichia coli and Saccharomyces cerevisiae. The increased stability of NRPC designs was demonstrated in E. coli by comparing versions of a construct with either repetitive or non-repetitive promoters. The former rapidly lost fluorescence and DNA content while the latter remained stable. Finally, the authors applied regression models and neural networks developed elsewhere (3) to explain and predict the strength of the synthetic promoters they created. This work can have tremendous, immediate impact in two ways. Not only did Hossain et al. produce vast libraries of bacterial and yeast pro","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"5 1","pages":"ysaa016"},"PeriodicalIF":0.0,"publicationDate":"2020-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysaa016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38624017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-10eCollection Date: 2020-01-01DOI: 10.1093/synbio/ysaa013
Tetsuhiro Harimoto
Living cells produce countless numbers of valuable compounds. By engineering these living ‘biofactories’, synthetic biologists have been making novel molecules that can be used for medicine, food, energy and everyday applications. However, crosstalk between engineered modules and host factors can significantly interfere with biomolecule production by competing for common resources. To address this challenge, scientists have been trying to minimize unwanted crosstalk between the host and synthetic networks by deleting proteins that drain resources such as proteases and metabolizing enzymes. In a recent study in the journal Nature Communications, the research team from Cheemeng Tan’s group at the University of California in Davis took a novel approach (1). Instead of minimizing crosstalk, they intentionally re-engineered crosstalk between the host and synthetic networks in order to create a more favorable environment for protein synthesis. This ‘holistic’ engineering approach achieved a global proteome reprogramming and enabled the production of complex proteins. The research team, led by Luis E. Contreras-Llano and Conary Meyer, utilized a cell-free protein synthesis system to construct consortia of bacteria, each expressing core proteins involved with protein translation. Because expressing multiple proteins in a single strain results in high metabolic burdens to the cells, distribution of the labor between the members of the consortium can improve overall protein expression. In addition, the use of this consortium enabled a rapid investigation of multiple pathways by inoculating different combinations of bacterial cells (2). To prepare the cell-free expression system, the researchers simply obtained cell lysates from the consortia without the need to purify and supplement individual proteins. The researchers first tested the protein expression capability of their consortia by measuring deGFP levels. They tested 18and 7-strain consortia expressing various initiation, elongation and termination factors, as well as aminoacyl-tRNA transferases, and found their expression levels to be comparable. In comparison to the wildtype bacteria and commercially available expression system (S30 T7 system), the consortium demonstrated >2-fold increase in deGFP production. Interestingly, when the team investigated the underlying mechanism of the improvement, they found that simple addition of translation machineries did not fully explain the increase in protein synthesis. Thus, they hypothesized that the overexpression of translation machineries in cells led to host reprogramming of the proteome that favors protein synthesis. To investigate the shift in the proteome, the researchers analyzed protein composition using mass spectrometry. They found that the consortium indeed exhibited a global proteome shift compared to the controls, resulting in changes in the expression level of more than 700 proteins. Importantly, these changes were associated with upregulation
{"title":"Reprogramming the proteome for cell-free protein expression.","authors":"Tetsuhiro Harimoto","doi":"10.1093/synbio/ysaa013","DOIUrl":"https://doi.org/10.1093/synbio/ysaa013","url":null,"abstract":"Living cells produce countless numbers of valuable compounds. By engineering these living ‘biofactories’, synthetic biologists have been making novel molecules that can be used for medicine, food, energy and everyday applications. However, crosstalk between engineered modules and host factors can significantly interfere with biomolecule production by competing for common resources. To address this challenge, scientists have been trying to minimize unwanted crosstalk between the host and synthetic networks by deleting proteins that drain resources such as proteases and metabolizing enzymes. In a recent study in the journal Nature Communications, the research team from Cheemeng Tan’s group at the University of California in Davis took a novel approach (1). Instead of minimizing crosstalk, they intentionally re-engineered crosstalk between the host and synthetic networks in order to create a more favorable environment for protein synthesis. This ‘holistic’ engineering approach achieved a global proteome reprogramming and enabled the production of complex proteins. The research team, led by Luis E. Contreras-Llano and Conary Meyer, utilized a cell-free protein synthesis system to construct consortia of bacteria, each expressing core proteins involved with protein translation. Because expressing multiple proteins in a single strain results in high metabolic burdens to the cells, distribution of the labor between the members of the consortium can improve overall protein expression. In addition, the use of this consortium enabled a rapid investigation of multiple pathways by inoculating different combinations of bacterial cells (2). To prepare the cell-free expression system, the researchers simply obtained cell lysates from the consortia without the need to purify and supplement individual proteins. The researchers first tested the protein expression capability of their consortia by measuring deGFP levels. They tested 18and 7-strain consortia expressing various initiation, elongation and termination factors, as well as aminoacyl-tRNA transferases, and found their expression levels to be comparable. In comparison to the wildtype bacteria and commercially available expression system (S30 T7 system), the consortium demonstrated >2-fold increase in deGFP production. Interestingly, when the team investigated the underlying mechanism of the improvement, they found that simple addition of translation machineries did not fully explain the increase in protein synthesis. Thus, they hypothesized that the overexpression of translation machineries in cells led to host reprogramming of the proteome that favors protein synthesis. To investigate the shift in the proteome, the researchers analyzed protein composition using mass spectrometry. They found that the consortium indeed exhibited a global proteome shift compared to the controls, resulting in changes in the expression level of more than 700 proteins. Importantly, these changes were associated with upregulation ","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"5 1","pages":"ysaa013"},"PeriodicalIF":0.0,"publicationDate":"2020-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysaa013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38436595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-06eCollection Date: 2020-01-01DOI: 10.1093/synbio/ysaa012
Mark S Dunstan, Christopher J Robinson, Adrian J Jervis, Cunyu Yan, Pablo Carbonell, Katherine A Hollywood, Andrew Currin, Neil Swainston, Rosalind Le Feuvre, Jason Micklefield, Jean-Loup Faulon, Rainer Breitling, Nicholas Turner, Eriko Takano, Nigel S Scrutton
Natural plant-based flavonoids have drawn significant attention as dietary supplements due to their potential health benefits, including anti-cancer, anti-oxidant and anti-asthmatic activities. Naringenin, pinocembrin, eriodictyol and homoeriodictyol are classified as (2S)-flavanones, an important sub-group of naturally occurring flavonoids, with wide-reaching applications in human health and nutrition. These four compounds occupy a central position as branch point intermediates towards a broad spectrum of naturally occurring flavonoids. Here, we report the development of Escherichia coli production chassis for each of these key gatekeeper flavonoids. Selection of key enzymes, genetic construct design and the optimization of process conditions resulted in the highest reported titers for naringenin (484 mg/l), improved production of pinocembrin (198 mg/l) and eriodictyol (55 mg/l from caffeic acid), and provided the first example of in vivo production of homoeriodictyol directly from glycerol (17 mg/l). This work provides a springboard for future production of diverse downstream natural and non-natural flavonoid targets.
{"title":"Engineering <i>Escherichia coli</i> towards <i>de novo</i> production of gatekeeper (2<i>S</i>)-flavanones: naringenin, pinocembrin, eriodictyol and homoeriodictyol.","authors":"Mark S Dunstan, Christopher J Robinson, Adrian J Jervis, Cunyu Yan, Pablo Carbonell, Katherine A Hollywood, Andrew Currin, Neil Swainston, Rosalind Le Feuvre, Jason Micklefield, Jean-Loup Faulon, Rainer Breitling, Nicholas Turner, Eriko Takano, Nigel S Scrutton","doi":"10.1093/synbio/ysaa012","DOIUrl":"10.1093/synbio/ysaa012","url":null,"abstract":"<p><p>Natural plant-based flavonoids have drawn significant attention as dietary supplements due to their potential health benefits, including anti-cancer, anti-oxidant and anti-asthmatic activities. Naringenin, pinocembrin, eriodictyol and homoeriodictyol are classified as (2<i>S</i>)-flavanones, an important sub-group of naturally occurring flavonoids, with wide-reaching applications in human health and nutrition. These four compounds occupy a central position as branch point intermediates towards a broad spectrum of naturally occurring flavonoids. Here, we report the development of <i>Escherichia coli</i> production chassis for each of these key gatekeeper flavonoids. Selection of key enzymes, genetic construct design and the optimization of process conditions resulted in the highest reported titers for naringenin (484 mg/l), improved production of pinocembrin (198 mg/l) and eriodictyol (55 mg/l from caffeic acid), and provided the first example of <i>in vivo</i> production of homoeriodictyol directly from glycerol (17 mg/l). This work provides a springboard for future production of diverse downstream natural and non-natural flavonoid targets.</p>","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"5 1","pages":"ysaa012"},"PeriodicalIF":0.0,"publicationDate":"2020-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysaa012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38615936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-09eCollection Date: 2020-01-01DOI: 10.1093/synbio/ysaa010
Marko Storch, Matthew C Haines, Geoff S Baldwin
Multi-part DNA assembly is the physical starting point for many projects in Synthetic and Molecular Biology. The ability to explore a genetic design space by building extensive libraries of DNA constructs is essential for creating programmed biological systems. With multiple DNA assembly methods and standards adopted in the Synthetic Biology community, automation of the DNA assembly process is now receiving serious attention. Automation will enable larger builds using less researcher time, while increasing the accessible design space. However, these benefits currently incur high costs for both equipment and consumables. Here, we address this limitation by introducing low-cost DNA assembly with BASIC on OpenTrons (DNA-BOT). For this purpose, we developed an open-source software package and demonstrated the performance of DNA-BOT by simultaneously assembling 88 constructs composed of 10 genetic parts, evaluating the promoter, ribosome binding site and gene order design space for a three-gene operon. All 88 constructs were assembled with high accuracy, at a consumables cost of $1.50-$5.50 per construct. This illustrates the efficiency, accuracy and affordability of DNA-BOT, making it accessible for most labs and democratizing automated DNA assembly.
{"title":"DNA-BOT: a low-cost, automated DNA assembly platform for synthetic biology.","authors":"Marko Storch, Matthew C Haines, Geoff S Baldwin","doi":"10.1093/synbio/ysaa010","DOIUrl":"https://doi.org/10.1093/synbio/ysaa010","url":null,"abstract":"<p><p>Multi-part DNA assembly is the physical starting point for many projects in Synthetic and Molecular Biology. The ability to explore a genetic design space by building extensive libraries of DNA constructs is essential for creating programmed biological systems. With multiple DNA assembly methods and standards adopted in the Synthetic Biology community, automation of the DNA assembly process is now receiving serious attention. Automation will enable larger builds using less researcher time, while increasing the accessible design space. However, these benefits currently incur high costs for both equipment and consumables. Here, we address this limitation by introducing low-cost DNA assembly with BASIC on OpenTrons (DNA-BOT). For this purpose, we developed an open-source software package and demonstrated the performance of DNA-BOT by simultaneously assembling 88 constructs composed of 10 genetic parts, evaluating the promoter, ribosome binding site and gene order design space for a three-gene operon. All 88 constructs were assembled with high accuracy, at a consumables cost of $1.50-$5.50 per construct. This illustrates the efficiency, accuracy and affordability of DNA-BOT, making it accessible for most labs and democratizing automated DNA assembly.</p>","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"5 1","pages":"ysaa010"},"PeriodicalIF":0.0,"publicationDate":"2020-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysaa010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38436594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-19eCollection Date: 2020-01-01DOI: 10.1093/synbio/ysaa009
Marilyn S Lee, Matthew W Lux, Jared B DeCoste
To maximize innovation in materials science and synthetic biology, it is critical to master interdisciplinary understanding and communication within an organization. Programming aimed at this juncture has the potential to bring members of the workforce together to frame new networks and spark collaboration. In this article, we recognize the potential synergy between materials and synthetic biology research and describe our approach to this challenge as a case study. A workforce development program was devised consisting of a lecture series, laboratory demonstrations and a hands-on laboratory competition to produce a bacterial cellulose material with the highest tensile strength. This program, combined with support for infrastructure and research, resulted in a significant return on investment with new externally funded synthetic biology for materials programs for our organization. The learning elements described here may be adapted by other institutions for a variety of settings and goals.
{"title":"BEAMS: a workforce development program to bridge the gap between biologists and material scientists.","authors":"Marilyn S Lee, Matthew W Lux, Jared B DeCoste","doi":"10.1093/synbio/ysaa009","DOIUrl":"https://doi.org/10.1093/synbio/ysaa009","url":null,"abstract":"<p><p>To maximize innovation in materials science and synthetic biology, it is critical to master interdisciplinary understanding and communication within an organization. Programming aimed at this juncture has the potential to bring members of the workforce together to frame new networks and spark collaboration. In this article, we recognize the potential synergy between materials and synthetic biology research and describe our approach to this challenge as a case study. A workforce development program was devised consisting of a lecture series, laboratory demonstrations and a hands-on laboratory competition to produce a bacterial cellulose material with the highest tensile strength. This program, combined with support for infrastructure and research, resulted in a significant return on investment with new externally funded synthetic biology for materials programs for our organization. The learning elements described here may be adapted by other institutions for a variety of settings and goals.</p>","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"5 1","pages":"ysaa009"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysaa009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38658944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-19eCollection Date: 2020-01-01DOI: 10.1093/synbio/ysaa008
Daniel Bojar
As synthetic biologists, we sometimes forget the toggle switch and the self-activating switch, the foundational advances that launched the entire field of synthetic biology a mere two decades ago. As the first in a long line of increasingly sophisticated gene circuits with applications in biocomputing and biomedical therapies, these combinations of genetic parts in the humble bacterium Escherichia coli demonstrated that biology can—in principle—be programmed. In a recent study in the journal Nature Chemical Biology (1), Zhang et al. from the group of XiaoJun Tian at Arizona State University revisited the toggle switch and the self-activating switch, demonstrating the differential impact of cell division and growth on the function of these circuits, which could make some circuit designs unviable in the environment of dilution or growth characterizing many applications. As the output of the self-activating switch activates its own transcription, it should exhibit a stable ON-state beyond a certain inducer threshold. Yet what Zhang et al. discovered was that, once these green fluorescent protein (GFP)-positive, ONstate bacteria are diluted, the formerly stable ON-state disintegrates and the bacteria were suddenly indistinguishable from those that were never stimulated in the first place. Theory and their mathematical models, however, predicted that these once-ON-bacteria would remain ON, even after dilution. The supposedly stable memory of the self-activating switch was broken by a simple dilution. The hidden variable that accounted for the circuit’s memory lapse was growth. It has been recently appreciated that gene circuits place a metabolic burden on cells and therefore inhibit growth (2), while Zhang et al. additionally discovered that growth inhibited the functionality of their gene circuit. This resulted in a seesaw dynamic after diluting cells into medium rich with inducer: first, GFP fluorescence crashed, and then, after cell growth subsided, GFP resumed production. Factoring in the interfacing of growth and gene circuit into their models indeed resolved any unexplained differences in circuit memory. Interestingly, dilution into conditioned rather than fresh medium, thus inhibiting rapid growth, did preserve the memory of the self-activating switch. Naturally, Zhang et al. investigated whether this growth feedback also affected other circuit architectures, such as the toggle switch that can be used to switch between two stable states. Yet, overall, the toggle switch seemed to exhibit a much broader resistance to memory loss through growth effects, as long as the two constituting transcription factors operated on a similar timescale. Dilution into fresh or conditioned medium led to nearly the same output in terms of GFP fluorescence, demonstrating the perseverance of memory. The authors also note the crucial difference between transcriptional activation (self-activating switch) and inhibition (toggle switch), as the former seemed much more se
{"title":"Structure determines function-the role of topology in the functionality of gene circuits.","authors":"Daniel Bojar","doi":"10.1093/synbio/ysaa008","DOIUrl":"https://doi.org/10.1093/synbio/ysaa008","url":null,"abstract":"As synthetic biologists, we sometimes forget the toggle switch and the self-activating switch, the foundational advances that launched the entire field of synthetic biology a mere two decades ago. As the first in a long line of increasingly sophisticated gene circuits with applications in biocomputing and biomedical therapies, these combinations of genetic parts in the humble bacterium Escherichia coli demonstrated that biology can—in principle—be programmed. In a recent study in the journal Nature Chemical Biology (1), Zhang et al. from the group of XiaoJun Tian at Arizona State University revisited the toggle switch and the self-activating switch, demonstrating the differential impact of cell division and growth on the function of these circuits, which could make some circuit designs unviable in the environment of dilution or growth characterizing many applications. As the output of the self-activating switch activates its own transcription, it should exhibit a stable ON-state beyond a certain inducer threshold. Yet what Zhang et al. discovered was that, once these green fluorescent protein (GFP)-positive, ONstate bacteria are diluted, the formerly stable ON-state disintegrates and the bacteria were suddenly indistinguishable from those that were never stimulated in the first place. Theory and their mathematical models, however, predicted that these once-ON-bacteria would remain ON, even after dilution. The supposedly stable memory of the self-activating switch was broken by a simple dilution. The hidden variable that accounted for the circuit’s memory lapse was growth. It has been recently appreciated that gene circuits place a metabolic burden on cells and therefore inhibit growth (2), while Zhang et al. additionally discovered that growth inhibited the functionality of their gene circuit. This resulted in a seesaw dynamic after diluting cells into medium rich with inducer: first, GFP fluorescence crashed, and then, after cell growth subsided, GFP resumed production. Factoring in the interfacing of growth and gene circuit into their models indeed resolved any unexplained differences in circuit memory. Interestingly, dilution into conditioned rather than fresh medium, thus inhibiting rapid growth, did preserve the memory of the self-activating switch. Naturally, Zhang et al. investigated whether this growth feedback also affected other circuit architectures, such as the toggle switch that can be used to switch between two stable states. Yet, overall, the toggle switch seemed to exhibit a much broader resistance to memory loss through growth effects, as long as the two constituting transcription factors operated on a similar timescale. Dilution into fresh or conditioned medium led to nearly the same output in terms of GFP fluorescence, demonstrating the perseverance of memory. The authors also note the crucial difference between transcriptional activation (self-activating switch) and inhibition (toggle switch), as the former seemed much more se","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"5 1","pages":"ysaa008"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysaa008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38436593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-08eCollection Date: 2020-01-01DOI: 10.1093/synbio/ysaa006
Simone Balzer Le, Ingerid Onsager, Jon Andreas Lorentzen, Rahmi 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, utilizing 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 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 maximization of protein production.
{"title":"Dual UTR-A novel 5' untranslated region design for synthetic biology applications.","authors":"Simone Balzer Le, Ingerid Onsager, Jon Andreas Lorentzen, Rahmi Lale","doi":"10.1093/synbio/ysaa006","DOIUrl":"https://doi.org/10.1093/synbio/ysaa006","url":null,"abstract":"<p><p>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, utilizing 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 <i>de novo</i> translation initiation. We rationally create dual UTRs with a wide range of expression profiles and demonstrate the functionality of the novel design concept in <i>Escherichia coli</i> and <i>Pseudomonas putida</i> 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 maximization of protein production.</p>","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"5 1","pages":"ysaa006"},"PeriodicalIF":0.0,"publicationDate":"2020-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysaa006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38436591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01eCollection Date: 2020-01-01DOI: 10.1093/synbio/ysaa005
Kira Tiedge, Andrew Muchlinski, Philipp Zerbe
Plants produce a staggering diversity of specialized small molecule metabolites that play vital roles in mediating environmental interactions and stress adaptation. This chemical diversity derives from dynamic biosynthetic pathway networks that are often species-specific and operate under tight spatiotemporal and environmental control. A growing divide between demand and environmental challenges in food and bioenergy crop production has intensified research on these complex metabolite networks and their contribution to crop fitness. High-throughput omics technologies provide access to ever-increasing data resources for investigating plant metabolism. However, the efficiency of using such system-wide data to decode the gene and enzyme functions controlling specialized metabolism has remained limited; due largely to the recalcitrance of many plants to genetic approaches and the lack of 'user-friendly' biochemical tools for studying the diverse enzyme classes involved in specialized metabolism. With emphasis on terpenoid metabolism in the bioenergy crop switchgrass as an example, this review aims to illustrate current advances and challenges in the application of DNA synthesis and synthetic biology tools for accelerating the functional discovery of genes, enzymes and pathways in plant specialized metabolism. These technologies have accelerated knowledge development on the biosynthesis and physiological roles of diverse metabolite networks across many ecologically and economically important plant species and can provide resources for application to precision breeding and natural product metabolic engineering.
植物产生的特化小分子代谢物种类繁多,在介导环境相互作用和压力适应方面发挥着重要作用。这种化学多样性来自动态的生物合成途径网络,通常具有物种特异性,并在严格的时空和环境控制下运行。在粮食和生物能源作物生产中,需求与环境挑战之间的鸿沟越来越大,这加强了对这些复杂代谢物网络及其对作物适应性贡献的研究。高通量组学技术为研究植物代谢提供了越来越多的数据资源。然而,利用这些全系统数据来解码控制专化代谢的基因和酶功能的效率仍然有限;这主要是由于许多植物对遗传方法不感兴趣,以及缺乏 "用户友好型 "生化工具来研究参与专化代谢的各种酶类。本综述以生物能源作物开关草中的萜类代谢为例,旨在说明目前在应用 DNA 合成和合成生物学工具加速植物特化代谢中基因、酶和途径的功能发现方面所取得的进展和面临的挑战。这些技术加快了对许多具有重要生态和经济价值的植物物种中不同代谢物网络的生物合成和生理作用的了解,并为精准育种和天然产品代谢工程的应用提供了资源。
{"title":"Genomics-enabled analysis of specialized metabolism in bioenergy crops: current progress and challenges.","authors":"Kira Tiedge, Andrew Muchlinski, Philipp Zerbe","doi":"10.1093/synbio/ysaa005","DOIUrl":"10.1093/synbio/ysaa005","url":null,"abstract":"<p><p>Plants produce a staggering diversity of specialized small molecule metabolites that play vital roles in mediating environmental interactions and stress adaptation. This chemical diversity derives from dynamic biosynthetic pathway networks that are often species-specific and operate under tight spatiotemporal and environmental control. A growing divide between demand and environmental challenges in food and bioenergy crop production has intensified research on these complex metabolite networks and their contribution to crop fitness. High-throughput omics technologies provide access to ever-increasing data resources for investigating plant metabolism. However, the efficiency of using such system-wide data to decode the gene and enzyme functions controlling specialized metabolism has remained limited; due largely to the recalcitrance of many plants to genetic approaches and the lack of 'user-friendly' biochemical tools for studying the diverse enzyme classes involved in specialized metabolism. With emphasis on terpenoid metabolism in the bioenergy crop switchgrass as an example, this review aims to illustrate current advances and challenges in the application of DNA synthesis and synthetic biology tools for accelerating the functional discovery of genes, enzymes and pathways in plant specialized metabolism. These technologies have accelerated knowledge development on the biosynthesis and physiological roles of diverse metabolite networks across many ecologically and economically important plant species and can provide resources for application to precision breeding and natural product metabolic engineering.</p>","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"5 1","pages":"ysaa005"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445794/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38436592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}