Synthetic biology (Oxford, England)最新文献

{"title":"Analysis of primitive genetic interactions for the design of a genetic signal differentiator.","authors":"Wolfgang Halter, Richard M Murray, Frank Allgöwer","doi":"10.1093/synbio/ysz015","DOIUrl":"10.1093/synbio/ysz015","url":null,"abstract":"Abstract We study the dynamic and static input–output behavior of several primitive genetic interactions and their effect on the performance of a genetic signal differentiator. In a simplified design, several requirements for the linearity and time-scales of processes like transcription, translation and competitive promoter binding were introduced. By experimentally probing simple genetic constructs in a cell-free experimental environment and fitting semi-mechanistic models to these data, we show that some of these requirements can be verified, while others are only met with reservations in certain operational regimes. Analyzing the linearized model of the resulting genetic network, we conclude that it approximates a differentiator with relative degree one. Taking also the discovered nonlinearities into account and using a describing function approach, we further determine the particular frequency and amplitude ranges where the genetic differentiator can be expected to behave as such.","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz015"},"PeriodicalIF":0.0,"publicationDate":"2019-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439146","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}

{"title":"Life simplified: recompiling a bacterial genome for synonymous codon compression.","authors":"Joshua T Atkinson","doi":"10.1093/synbio/ysz017","DOIUrl":"https://doi.org/10.1093/synbio/ysz017","url":null,"abstract":"Researchers in the UK recently reported a strain of Escherichia coli with a completely synthetic 4-million-base-pair genome (1). This achievement sets a new world record in synthetic genomics by yielding a genome that is four times larger than the pioneering synthesis of the 1-million-base-pair Mycoplasma mycoides genome (2). Synthetic genomics is enabling the simplification of recoded organisms, the previous study minimized the total number of genes and this new study simplified the way those genes are encoded. Fredens and co-workers constructed an E. coli strain, dubbed Syn61, that utilizes just 61 codons for protein synthesis. Cells typically use 64 codons including 3 that encode termination of protein translation (stop codons). Eighteen of the 20 amino acids are encoded by 2–6 synonymous codons. Nature leverages these redundant codons to regulate the transfer of information from DNA to RNA to protein in a variety of ways (3). The extent to which these degenerate codons are needed for cell fitness is not known. To assess this question systematically, the team performed ‘synonymous codon compression’ on the E. coli genome, recoding 2 of the 6 codons encoding serine (TCG and TCA) and the amber stop codon (TAG) with synonymous codons. This study recoded an astonishing 18 214 codons, exceeding past recoding efforts by >50-fold (4). To accomplish this tour de force, the authors used homologous recombination in Saccharomyces cerevisiae to assemble 37 bacterial artificial chromosomes ( 100 kilobase long) from 409 smaller synthetic DNA ( 10 kilobase). Using a method called ‘replicon excision for enhanced genome engineering through programmed recombination’, or REXER (3), they iteratively replaced segments of the E. coli genome with the synthetic DNA fragments. REXER uses a double selection strategy that leverages unique pairs of positive and negative selection markers embedded in both the genome and the synthetic DNA fragment and CRISPR/Cas9 DNA excision to increase the efficiency of lambda red recombination for large DNA fragments (3). The authors first performed REXER in parallel targeting eight different genomic regions to generate a library of partially recoded strains. Then, to assemble the full synthetic genome, they merged the engineered DNA in their strains using conjugative transfer and recombination. Relative to the parental strain, Syn61 displayed only minor growth defects with slightly elongated cells and enabled the deletion of a previously essential tRNA. This strain also showed increased viability when expressing tRNAs charged with a noncanonical amino acid (ncAA) that targets one of the removed codons. The application of synthetic genomics to the laboratory workhorse E. coli represents an important step towards enabling a future where synthetic biologists can readily design and write tailor-made genomes to generate synthetic organisms with user-specified functions. Codon compression leads to decreased infection by bacteriophage, as pha","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz017"},"PeriodicalIF":0.0,"publicationDate":"2019-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439147","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}

{"title":"PartCrafter: find, generate and analyze BioParts.","authors":"Emily Scher,&nbsp;Shay B Cohen,&nbsp;Guido Sanguinetti","doi":"10.1093/synbio/ysz014","DOIUrl":"https://doi.org/10.1093/synbio/ysz014","url":null,"abstract":"<p><p>The field of Synthetic Biology is both practically and philosophically reliant on the idea of BioParts-concrete DNA sequences meant to represent discrete functionalities. While there are a number of software tools which allow users to design complex DNA sequences by stitching together BioParts or genetic features into genetic devices, there is a lack of tools assisting Synthetic Biologists in finding BioParts and in generating new ones. In practice, researchers often find BioParts in an <i>ad hoc</i> way. We present PartCrafter, a tool which extracts and aggregates genomic feature data in order to facilitate the search for new BioParts with specific functionalities. PartCrafter can also turn a genomic feature into a BioPart by packaging it according to any manufacturing standard, codon optimizing it for a new host, and removing forbidden sites. PartCrafter is available at partcrafter.com.</p>","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz014"},"PeriodicalIF":0.0,"publicationDate":"2019-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439145","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}

{"title":"Broad range shuttle vector construction and promoter evaluation for the use of <i>Lactobacillus plantarum</i> WCFS1 as a microbial engineering platform.","authors":"Joseph R Spangler,&nbsp;Julie C Caruana,&nbsp;Daniel A Phillips,&nbsp;Scott A Walper","doi":"10.1093/synbio/ysz012","DOIUrl":"https://doi.org/10.1093/synbio/ysz012","url":null,"abstract":"<p><p>As the field of synthetic biology grows, efforts to deploy complex genetic circuits in nonlaboratory strains of bacteria will continue to be a focus of research laboratories. Members of the <i>Lactobacillus</i> genus are good targets for synthetic biology research as several species are already used in many foods and as probiotics. Additionally, <i>Lactobacilli</i> offer a relatively safe vehicle for microbiological treatment of various health issues considering these commensals are often minor constituents of the gut microbial community and maintain allochthonous behavior. In order to generate a foundation for engineering, we developed a shuttle vector for subcloning in <i>Escherichia coli</i> and used it to characterize the transcriptional and translational activities of a number of promoters native to <i>Lactobacillus plantarum</i> WCFS1. Additionally, we demonstrated the use of this vector system in multiple <i>Lactobacillus</i> species, and provided examples of non-native promoter recognition by both <i>L. plantarum</i> and <i>E. coli</i> strains that might allow a shortcut assessment of circuit outputs. A variety of promoter activities were observed covering a range of protein expression levels peaking at various times throughout growth, and subsequent directed mutations were demonstrated and suggested to further increase the degree of output tuning. We believe these data show the potential for <i>L. plantarum</i> WCFS1 to be used as a nontraditional synthetic biology chassis and provide evidence that our system can be transitioned to other probiotic <i>Lactobacillus</i> species as well.</p>","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz012"},"PeriodicalIF":0.0,"publicationDate":"2019-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439144","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}

{"title":"Speaking to nature: a deep learning representational model of proteins ushers in protein linguistics.","authors":"Daniel Bojar","doi":"10.1093/synbio/ysz013","DOIUrl":"https://doi.org/10.1093/synbio/ysz013","url":null,"abstract":"Understanding, modifying and designing proteins require an intimate knowledge of their 3D structure. Even structure-agnostic protein engineering approaches, such as directed evolution, are limited in scope because of the vast potential sequence space and the epistatic effects that multiple mutations have on protein function. To overcome these difficulties, a holistic understanding of sequence–structure–function relationships has to be established. In their recent preprint, members of the Church Group at the Wyss Institute and collaborators describe a novel approach to predicting protein stability and functionality from raw sequence (1). Their representational model UniRep (unified representation), for the first time, demonstrates an advanced understanding of protein features by means of language modeling. Using deep learning techniques, which were recently recognized with the prestigious Turing Award, Alley et al. built a language model for proteins with amino acids as characters based on natural language processing (NLP) techniques. NLP has not only revolutionized our computational understanding of language—think for instance voice-to-text software—but has been coopted for exciting applications in synthetic biology. The recurrent neural network (RNN; a type of neural network which can process sequential inputs such as text) used by Alley et al. was trained by iteratively predicting the next amino acid given the preceding amino acids for the 24 million protein sequences contained in the UniRef50 database. The RNN thus gathered implicit knowledge about the context of a given amino acid and higher-level features such as secondary structure. The authors then averaged the protein representation of their RNN at every sequence position to yield a protein language representation they call UniRep. They then extended UniRep by adding representations of the final sequence position of their RNN to generate the more complete representation called ‘UniRep Fusion’, which serves as an overview of the entire protein sequence. UniRep Fusion was then used as an input for a machine learning model to predict protein stability. Notably, this architecture was more accurate than Rosetta, the de facto state-ofthe-art for predicting protein stability. Their protein language representation allowed the authors to predict the relative brightness of 64 800 GFP mutants differing in as few as one amino acids. Remarkably, their predicted relative brightness values correlated strongly with experimental observation (r1⁄4 0.98). UniRep, as the representation of 24 million proteins, captures many phenomena of general importance for protein structure and function. These general features can be complemented by dataset-specific attributes when training on a subset of protein mutants or de novo designed proteins. This approach could for instance be adopted for screening novel proteins generated by deep learning models. Analogous to de novo designed proteins by Rosetta, generating prote","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz013"},"PeriodicalIF":0.0,"publicationDate":"2019-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439143","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}

{"title":"Turning G protein-coupled receptors into tunable biosensors.","authors":"Konstantinos Vavitsas","doi":"10.1093/synbio/ysz011","DOIUrl":"https://doi.org/10.1093/synbio/ysz011","url":null,"abstract":"In 2012, the Nobel prize in Chemistry was awarded to Robert Lefkowitz and Brian Kobilka for their work in understanding the structure and function of G protein-coupled receptors (GPCRs), one of the largest families of signaling proteins. GPCRs are notoriously difficult to work with (due to their many transmembrane domains) and they operate in a complex way, interacting with several compounds and many internal metabolic pathways. What is more, GPCRs are present in most lifeforms and have an important role in many vital signaling processes. They therefore seem like a very unlikely choice for a biosensor. However, William Shaw and his colleagues proved otherwise in their recent article published in Cell (1). The research group from Imperial College, UK, heavily modified the yeast Saccharomyces cerevisiae to obtain a platform for their biosensors. A sensor can be roughly divided into three parts: the detector, the signal transduction/translation component and the reporter. The idea was to create a modular system where GPCRs act as plug-ins dedicated to a compound, while the signal transduction and reporting mechanism will remain the same. S. cerevisiae already contains a signaling pathway with its own self-regulation, the MAP kinase cascade, that can be used to translate a GPCR signal to a linear and graded translational response. Using CRISPR-mediated editing the researchers modified 18 genetic loci and removed the rest of the GPCRrelated genes, generating a ‘clean’ environment without crosspathway interactions. In theory, the derived strain can heterologously express a GPCR that recognizes any compound, and receptor activation will stimulate the same pathway and the same reporting event. Shaw and colleagues modified components of the GPCR receptor and measured the impact on its biosensor properties: the detection threshold, the saturation point and the linearity of response. The experiments took place using the yeast mating pheromone response pathway, where the presence of a-Factor pheromone stimulates a transcriptional response (2). By varying the expression levels of the GPCR components, using different promoters, the researchers showed that it is possible to titrate the signal response, generate a mathematical model with robust predictions and tune the receptor and reporter to function in a certain operational range. To alter the linearity of response—whether the sensor operates in a linear manner or as an on-off switch—the researchers employed microbial consortia with differently tuned strains. This was displayed in two different scenarios. In the first instance, the presence of melatonin in the media was quantified. The researchers employed two strains with different sensitivities to melatonin, thus increasing the operational range. In the second instance, the presence of the pathogenic fungus Paracoccidioides brasiliensis was detected in a yes/no manner. The two cell types used here had different functions: one detected the fungus and release","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz011"},"PeriodicalIF":0.0,"publicationDate":"2019-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439142","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}

{"title":"Principles of synthetic biology: a MOOC for an emerging field.","authors":"Daniel A Anderson,&nbsp;Ross D Jones,&nbsp;Adam P Arkin,&nbsp;Ron Weiss","doi":"10.1093/synbio/ysz010","DOIUrl":"https://doi.org/10.1093/synbio/ysz010","url":null,"abstract":"<p><p>Synthetic biology requires students and scientists to draw upon knowledge and expertise from many disciplines. While this diversity is one of the field's primary strengths, it also makes it challenging for newcomers to acquire the background knowledge necessary to thrive. To address this gap, we developed a course that provides a structured approach to learning the biological principles and theoretical underpinnings of synthetic biology. Our course, Principles of Synthetic Biology (PoSB), was released on the massively open online course platform edX in 2016. PoSB seeks to teach synthetic biology through five key fundamentals: (i) parts and layers of abstraction, (ii) biomolecular modeling, (iii) digital logic abstraction, (iv) circuit design principles and (v) extended circuit modalities. In this article, we describe the five fundamentals, our formulation of the course, and impact and metrics data from two runs of the course through the edX platform.</p>","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz010"},"PeriodicalIF":0.0,"publicationDate":"2019-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439141","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}

{"title":"Erratum: New adaptive laboratory evolution database highlights the need for consolidating directed evolution data.","authors":"Bojar Daniel","doi":"10.1093/synbio/ysz009","DOIUrl":"https://doi.org/10.1093/synbio/ysz009","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1093/synbio/ysz004.][This corrects the article DOI: 10.1093/synbio/ysz004.].</p>","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz009"},"PeriodicalIF":0.0,"publicationDate":"2019-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38440222","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}

{"title":"Marionette strains aim to make refining metabolic pathways faster and easier.","authors":"William G Alexander","doi":"10.1093/synbio/ysz007","DOIUrl":"https://doi.org/10.1093/synbio/ysz007","url":null,"abstract":"The Voigt lab at The Massachusetts Institute of Technology recently reported the optimization of 12 transcription factor sensors and their integration into a series of E. coli strains, collectively referred to as the Marionette strains (1). While transcription factors that can be controlled with small molecules are not new (the lactose and tetracycline inducible systems have been around for decades), synthetic biologists are limited to using only a few simultaneously in a cell due to issues such as unintended activation by cognate or non-cognate molecules, cross-interactions with the other sensors, and ‘leakiness’, or low-level transcription in the absence of the activating molecule. Previously, the maximum number of transcription factor sensors used simultaneously in a cell was four. The Marionette strains could make optimizing heterologous metabolic pathways faster and easier by expanding the design space for complex genetic circuits. The Voigt lab used directed evolution to find variants of sensors with high specificity, low leakiness and greater activation ranges (in other words the difference between the ‘off’ and ‘on’ states). A dual selection system was designed: a negativeselection marker (the promiscuous PheS allele) would kill cells with sensor variants that had leaky expression or were reactive with unintended small molecules, while positive selection to find highly sensitive and specific variants was achieved by the expression of a DNA polymerase (DNAP) and subsequent emulsified polymerase chain reaction. The emulsification isolates the sensors, and those responsible for the highest levels of expression are amplified more strongly. In addition, the DNAP used in the positive selection could be alternated between a stringent or error-prone polymerase in order to produce and control the diversity on which the selections would act, and these mutagenized sequences would be incorporated into the next round of selections. To demonstrate the utility of a Marionette strain in tuning the expression of a metabolic pathway, the lycopene synthesis pathway was used as a model (2). The five genes in the lycopene synthesis pathway were placed under the control of five different sensors, and three levels (zero, maximum and 50% maximum) of each inducer were added to the culture resulting in 243 combinations. Lycopene concentrations were measured for all 243 combinations, and new minima, maxima and midpoints were derived for each of the five transcription factors. The experiment was repeated this way for a total of four iterations, resulting in a maximum lycopene titer of 90 mg/l. To equal the design space explored in the Marionette lycopene optimization example (243 combinations screened four times), you would have to synthesize 972 constructs. Synthesizing these 972 constructs (7 Mb total), would cost $700 000 (assuming $0.10/base), not to mention the enzyme and labor costs to clone all of those variants, the lost time due to human error, unforeseen i","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz007"},"PeriodicalIF":0.0,"publicationDate":"2019-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439140","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}

{"title":"New adaptive laboratory evolution database highlights the need for consolidating directed evolution data.","authors":"Daniel Bojar","doi":"10.1093/synbio/ysz004","DOIUrl":"https://doi.org/10.1093/synbio/ysz004","url":null,"abstract":"Directed evolution, honored by the 2018 chemistry Nobel prize, uses mutagenesis and selective pressure to drive proteins towards the development of new and improved functionalities. A closely related approach, known as Adaptive Laboratory Evolution (ALE) applies similar principles to optimize whole strains for desired growth conditions. While these approaches have resulted in considerable advances in the realms of enzyme and strain optimization, they remain isolated endeavors. A new resource, the Adaptive Laboratory Evolution Database (ALEdb), is a first step towards concentrating efforts to harness the power of evolution for new and improved phenotypes. In ALE experiments, organisms such as Escherichia coli or Saccharomyces cerevisiae are grown for extended periods of time under specified culture conditions to enable the acquisition of advantageous or adaptive mutations. Developed as a web-based platform hosted by the University of California, San Diego, ALEdb was launched with over 11 000 mutations and the corresponding culture conditions gathered from 11 publications and is built to be expanded by further studies. The mutations stored at ALEdb are characterized by the genome position, the affected gene, the type of mutation, and the cell culture conditions used in the ALE experiment. Data from different studies can be exported and analyzed from ALEdb by data mining for trends or patterns in mutations to generalize and advance the pursuit of improved and novel functionalities. Additionally, ALEdb serves as a knowledge database where scientists can functionally characterize new mutations discovered by comparing them to records stored in ALEdb. To showcase the utility of ALEdb, the authors investigated mutation type distributions from already cataloged studies. Single nucleotide polymorphisms (SNPs) were found to be the most frequent. The authors argue that this trend suggests the importance of SNPs for adaptive evolution, though it is hard to support this claim without taking into account the baseline frequency of different mutation types. In the context of synthetic biology, a concerted database of adaptive mutations like ALEdb could help guide the rational design of new and improved functionalities. However, ALEdb currently catalogs ALE-derived mutations only in naturally occurring genes. Expanding the database to include variations resulting from directed evolution of standard genetic parts that may not be native to the host organism would greatly increase its influence. Additionally, databases such as ALEdb are dependent on continued submissions. Since it was first described in early October, the publication count on ALEdb has expanded from 11 to 33. This early momentum is a promising sign, but it is unclear how the authors envision the assured spread and maintenance of ALEdb. Potential ways forward could include a pledge by journals to require data submission—similar to the way the protein data bank PDB (Protein Data Bank) handles 3D protei","PeriodicalId":74902,"journal":{"name":"Synthetic biology (Oxford, England)","volume":"4 1","pages":"ysz004"},"PeriodicalIF":0.0,"publicationDate":"2019-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/synbio/ysz004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38439137","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}