Synthetic biology (Oxford, England)最新文献_第8页

Speaking to nature: a deep learning representational model of proteins ushers in protein linguistics. 与自然对话:蛋白质的深度学习表征模型引入了蛋白质语言学。

Q2 BIOCHEMICAL RESEARCH METHODS

Synthetic biology (Oxford, England)

Pub Date : 2019-05-21 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz013

Daniel Bojar

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

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引用次数: 0

Turning G protein-coupled receptors into tunable biosensors. 将G蛋白偶联受体转化为可调生物传感器。

Q2 BIOCHEMICAL RESEARCH METHODS

Synthetic biology (Oxford, England)

Pub Date : 2019-05-21 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz011

Konstantinos Vavitsas

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

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引用次数: 4

Principles of synthetic biology: a MOOC for an emerging field. 合成生物学原理:面向新兴领域的MOOC。

Q2 BIOCHEMICAL RESEARCH METHODS

Synthetic biology (Oxford, England)

Pub Date : 2019-05-10 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz010

Daniel A Anderson, Ross D Jones, Adam P Arkin, Ron Weiss

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.

合成生物学要求学生和科学家利用许多学科的知识和专业知识。虽然这种多样性是该领域的主要优势之一，但它也使新来者难以获得发展所需的背景知识。为了解决这一差距，我们开发了一门课程，提供了一种结构化的方法来学习合成生物学的生物学原理和理论基础。我们的课程《合成生物学原理》(PoSB)于2016年在大型开放在线课程平台edX上发布。PoSB寻求通过五个关键基础来教授合成生物学:(i)抽象的部分和层，(ii)生物分子建模，(iii)数字逻辑抽象，(iv)电路设计原则和(v)扩展电路模式。在本文中，我们描述了五个基本原理，我们的课程制定，以及通过edX平台运行的两次课程的影响和指标数据。

引用次数: 9

Erratum: New adaptive laboratory evolution database highlights the need for consolidating directed evolution data. 勘误:新的适应实验室进化数据库强调需要巩固定向进化数据。

Q2 BIOCHEMICAL RESEARCH METHODS

Synthetic biology (Oxford, England)

Pub Date : 2019-03-25 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz009

Bojar Daniel

[This corrects the article DOI: 10.1093/synbio/ysz004.][This corrects the article DOI: 10.1093/synbio/ysz004.].

[这更正了文章DOI: 10.1093/synbio/ysz004。][更正文章DOI: 10.1093/synbio/ysz004.]。

引用次数: 0

Marionette strains aim to make refining metabolic pathways faster and easier. 木偶菌株旨在使精炼代谢途径更快、更容易。

Q2 BIOCHEMICAL RESEARCH METHODS

Synthetic biology (Oxford, England)

Pub Date : 2019-02-04 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz007

William G Alexander

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

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引用次数: 0

New adaptive laboratory evolution database highlights the need for consolidating directed evolution data. 新的自适应实验室进化数据库强调了整合定向进化数据的需求。

Q2 BIOCHEMICAL RESEARCH METHODS

Synthetic biology (Oxford, England)

Pub Date : 2019-02-04 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz004

Daniel Bojar

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

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引用次数: 2

Arch enemy no more: designing the first synthetic globular all-beta proteins with beta-arches. 不再是宿敌了:设计出第一个带有-拱门的合成球形全-蛋白。

Q2 BIOCHEMICAL RESEARCH METHODS

Synthetic biology (Oxford, England)

Pub Date : 2019-02-04 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz002

Daniel Bojar

De novo protein design, taking its first steps at the turn of the century (1), aims to create novel proteins without an existing protein scaffold wholly from foundational structural principles and simulations. These designed proteins often have sequences and functions that are unlike anything found in nature and can even exhibit completely novel protein folds. The wholesale design of new proteins thus requires an exquisite understanding of their 3D structure. Thanks to their modular properties, proteins consisting solely of alpha-helices were the first to yield to protein design de novo. In a recent publication in the journal Nature Structural & Molecular Biology, David Baker’s team at the University of Washington made a foray into uncharted territory and for the first time succeeded in designing a globular all-beta protein de novo (2). To understand their success, it is paramount to understand why it is so difficult to design globular proteins consisting only of beta-sheets. In contrast to amino acid residues in alphahelices, which establish most of their contacts with residues nearby, residues in beta-sheets frequently interact with residues that are farther apart on the sequence, making them harder to design. For example, beta-arches are loops that connect two beta-strands that do not form a continuous beta-sheet. In this publication, the authors discovered and utilized structural principles of all-beta proteins to facilitate their design process. These principles for instance constrained the geometry of beta-arches by assigning amino acid frequencies as well as the orientation of their side chains to specific types of beta-arches. Led by researchers Enrique Marcos and Tamuka M. Chidyausiku, the team used the protein modeling software Rosetta to construct candidates for globular all-beta proteins with differing lengths of beta-strands and beta-arches. Choosing 19 of these final jellyroll protein structure candidates consisting of eight antiparallel beta-strands for experimental characterization, they recombinantly expressed them in E. coli. Obtaining an nuclear magnetic resonance (NMR) spectroscopy structure of one of these expressed designer proteins, the authors could demonstrate that the actual protein structure closely resembled their de novo design. While proteins consisting of beta-strands connected by tight loops (effectively forming a flowing carpet of paired beta-strands) have been attempted before, the de novo design of beta-arches is definitely a novelty. This characteristic allows all-beta proteins to fold into globular proteins, in contrast to the previous elongated designs, and is needed for complex proteins such as antibodies. Why is all of this important? In addition to a profound conceptual leap in our ability to design proteins de novo, this work furthers our structural understanding of all-beta proteins. Many important proteins, such as the nucleosome-chaperone nucleoplasmin and many viral capsid proteins, contain jellyroll

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引用次数: 0

Developing a graduate training program in Synthetic Biology: SynBioCDT. 开发合成生物学研究生培训计划:SynBioCDT。

Q2 BIOCHEMICAL RESEARCH METHODS

Synthetic biology (Oxford, England)

Pub Date : 2019-01-30 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz006

Idil Cazimoglu, Alexander P S Darlington, Aurelija Grigonyte, Charlotte E G Hoskin, Juntai Liu, Robert Oppenheimer, Jesús A Siller-Farfán, Claire Grierson, Antonis Papachristodoulou

This article presents the experience of a team of students and academics in developing a post-graduate training program in the new field of Synthetic Biology. Our Centre for Doctoral Training in Synthetic Biology (SynBioCDT) is an initiative funded by the United Kingdom's Research Councils of Engineering and Physical Sciences (EPSRC), and Biotechnology and Biological Sciences (BBSRC). SynBioCDT is a collaboration between the Universities of Oxford, Bristol and Warwick, and has been successfully running since 2014, training 78 students in this field. In this work, we discuss the organization of the taught, research and career development training. We also address the challenges faced when offering an interdisciplinary program. The article concludes with future directions to continue the development of the SynBioCDT.

本文介绍了一个由学生和学者组成的团队在合成生物学新领域开展研究生培训计划的经验。我们的合成生物学博士培训中心(SynBioCDT)是由英国工程与物理科学研究委员会(EPSRC)和生物技术与生物科学研究委员会(BBSRC)资助的一项倡议。SynBioCDT是牛津大学、布里斯托尔大学和华威大学之间的合作项目，自2014年以来一直成功运行，培训了78名该领域的学生。在本工作中，我们讨论了教学、研究和职业发展培训的组织。我们还解决了提供跨学科课程时面临的挑战。文章最后提出了今后SynBioCDT继续发展的方向。

引用次数: 3

An educational module to explore CRISPR technologies with a cell-free transcription-translation system. 一个教育模块，探索CRISPR技术与无细胞转录翻译系统。

Q2 BIOCHEMICAL RESEARCH METHODS

Synthetic biology (Oxford, England)

Pub Date : 2019-01-21 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysz005

Daphne Collias, Ryan Marshall, Scott P Collins, Chase L Beisel, Vincent Noireaux

Within the last 6 years, CRISPR-Cas systems have transitioned from adaptive defense systems in bacteria and archaea to revolutionary genome-editing tools. The resulting CRISPR technologies have driven innovations for treating genetic diseases and eradicating human pests while raising societal questions about gene editing in human germline cells as well as crop plants. Bringing CRISPR into the classroom therefore offers a means to expose students to cutting edge technologies and to promote discussions about ethical questions at the intersection of science and society. However, working with these technologies in a classroom setting has been difficult because typical experiments rely on cellular systems such as bacteria or mammalian cells. We recently reported the use of an E. coli cell-free transcription-translation (TXTL) system that simplifies the demonstration and testing of CRISPR technologies with shorter experiments and limited equipment. Here, we describe three educational modules intended to expose undergraduate students to CRISPR technologies using TXTL. The three sequential modules comprise (i) designing the RNAs that guide DNA targeting, (ii) measuring DNA cleavage activity in TXTL and (iii) testing how mutations to the targeting sequence or RNA backbone impact DNA binding and cleavage. The modules include detailed protocols, questions for group discussions or individual evaluation, and lecture slides to introduce CRISPR and TXTL. We expect these modules to allow students to experience the power and promise of CRISPR technologies in the classroom and to engage with their instructor and peers about the opportunities and potential risks for society.

在过去的6年里，CRISPR-Cas系统已经从细菌和古细菌的适应性防御系统转变为革命性的基因组编辑工具。由此产生的CRISPR技术推动了治疗遗传疾病和根除人类害虫的创新，同时也引发了关于人类生殖细胞和农作物基因编辑的社会问题。因此，将CRISPR引入课堂提供了一种让学生接触尖端技术的手段，并促进了对科学与社会交叉领域伦理问题的讨论。然而，在课堂环境中使用这些技术一直很困难，因为典型的实验依赖于细胞系统，如细菌或哺乳动物细胞。我们最近报道了一种大肠杆菌无细胞转录-翻译(TXTL)系统的使用，该系统用更短的实验时间和有限的设备简化了CRISPR技术的演示和测试。在这里，我们描述了三个教育模块，旨在让本科生使用TXTL接触CRISPR技术。三个序列模块包括(i)设计引导DNA靶向的RNA， (ii)测量TXTL中的DNA切割活性，(iii)测试靶向序列或RNA骨干的突变如何影响DNA结合和切割。这些模块包括详细的协议，小组讨论或个人评估的问题，以及介绍CRISPR和TXTL的讲座幻灯片。我们希望这些模块能让学生在课堂上体验到CRISPR技术的力量和前景，并与他们的老师和同龄人一起讨论社会的机遇和潜在风险。

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引用次数: 24

Expanding the toolbox of synthetic riboswitches with guanine-dependent aptazymes. 用鸟嘌呤依赖性适配酶扩展合成核糖开关工具箱。

Q2 BIOCHEMICAL RESEARCH METHODS

Synthetic biology (Oxford, England)

Pub Date : 2019-01-12 eCollection Date: 2019-01-01 DOI: 10.1093/synbio/ysy022

Julia Stifel, Maike Spöring, Jörg Steffen Hartig

Artificial riboswitches based on ribozymes serve as versatile tools for ligand-dependent gene expression regulation. Advantages of these so-called aptazymes are their modular architecture and the comparably little coding space they require. A variety of aptamer-ribozyme combinations were constructed in the past 20 years and the resulting aptazymes were applied in diverse contexts in prokaryotic and eukaryotic systems. Most in vivo functional aptazymes are OFF-switches, while ON-switches are more advantageous regarding potential applications in e.g. gene therapy vectors. We developed new ON-switching aptazymes in the model organism Escherichia coli and in mammalian cell culture using the intensely studied guanine-sensing xpt aptamer. Utilizing a high-throughput screening based on fluorescence-activated cell sorting in bacteria we identified up to 9.2-fold ON-switches and OFF-switches with a dynamic range up to 32.7-fold. For constructing ON-switches in HeLa cells, we used a rational design approach based on existing tetracycline-sensitive ON-switches. We discovered that communication modules responding to tetracycline are also functional in the context of guanine aptazymes, demonstrating a high degree of modularity. Here, guanine-responsive ON-switches with a four-fold dynamic range were designed. Summarizing, we introduce a series of novel guanine-dependent ribozyme switches operative in bacteria and human cell culture that significantly broaden the existing toolbox.

基于核酶的人工核开关是调节配体依赖性基因表达的通用工具。这些所谓的适配酶的优点是它们的模块化结构和相对较少的编码空间。在过去的20年里，各种核酸适体-核酶组合被构建出来，所得到的核酸适体酶在原核和真核生物系统中得到了广泛的应用。大多数体内功能适配酶是off开关，而on开关在基因治疗载体等潜在应用方面更有利。我们在模式生物大肠杆菌和哺乳动物细胞培养中利用已深入研究的鸟嘌呤感应适体开发了新的on开关适体酶。利用基于细菌荧光激活细胞分选的高通量筛选，我们鉴定了高达9.2倍的on和off开关，动态范围高达32.7倍。为了在HeLa细胞中构建on -开关，我们采用了基于现有四环素敏感on -开关的合理设计方法。我们发现响应四环素的通信模块在鸟嘌呤适配酶的环境下也起作用，显示出高度的模块化。在这里，鸟嘌呤响应开关具有四倍的动态范围设计。综上所述，我们介绍了一系列新的鸟嘌呤依赖核酶开关在细菌和人类细胞培养中工作，大大拓宽了现有的工具箱。

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引用次数: 21