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Enzyme engineering and in vivo testing of a formate reduction pathway. 甲酸还原途径的酶工程和体内测试。
Q2 BIOCHEMICAL RESEARCH METHODS Pub Date : 2021-08-06 eCollection Date: 2021-01-01 DOI: 10.1093/synbio/ysab020
Jue Wang, Karl Anderson, Ellen Yang, Lian He, Mary E Lidstrom

Formate is an attractive feedstock for sustainable microbial production of fuels and chemicals, but its potential is limited by the lack of efficient assimilation pathways. The reduction of formate to formaldehyde would allow efficient downstream assimilation, but no efficient enzymes are known for this transformation. To develop a 2-step formate reduction pathway, we screened natural variants of acyl-CoA synthetase (ACS) and acylating aldehyde dehydrogenase (ACDH) for activity on one-carbon substrates and identified active and highly expressed homologs of both enzymes. We then performed directed evolution, increasing ACDH-specific activity by 2.5-fold and ACS lysate activity by 5-fold. To test for the in vivo activity of our pathway, we expressed it in a methylotroph which can natively assimilate formaldehyde. Although the enzymes were active in cell extracts, we could not detect formate assimilation into biomass, indicating that further improvement will be required for formatotrophy. Our work provides a foundation for further development of a versatile pathway for formate assimilation.

甲酸是一种有吸引力的燃料和化学品可持续微生物生产的原料,但其潜力受到缺乏有效的同化途径的限制。甲酸还原为甲醛将允许有效的下游同化,但没有有效的酶知道这种转化。为了建立两步甲酸还原途径,我们筛选了酰基辅酶a合成酶(ACS)和酰化醛脱氢酶(ACDH)在单碳底物上的活性的天然变体,并鉴定了这两种酶的活性和高表达的同源物。然后我们进行了定向进化,将acdh特异性活性提高了2.5倍,ACS裂解物活性提高了5倍。为了测试我们的途径在体内的活性,我们将其表达在甲基化菌中,甲基化菌可以天然吸收甲醛。虽然这些酶在细胞提取物中有活性,但我们无法检测到甲酸盐对生物质的同化,这表明需要进一步改善甲酸盐的形成。我们的工作为进一步开发甲酸盐同化的多用途途径提供了基础。
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引用次数: 5
Rational gRNA design based on transcription factor binding data. 基于转录因子结合数据的合理gRNA设计。
Q2 BIOCHEMICAL RESEARCH METHODS Pub Date : 2021-07-27 eCollection Date: 2021-01-01 DOI: 10.1093/synbio/ysab014
David Bergenholm, Yasaman Dabirian, Raphael Ferreira, Verena Siewers, Florian David, Jens Nielsen

The clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system has become a standard tool in many genome engineering endeavors. The endonuclease-deficient version of Cas9 (dCas9) is also a powerful programmable tool for gene regulation. In this study, we made use of Saccharomyces cerevisiae transcription factor (TF) binding data to obtain a better understanding of the interplay between TF binding and binding of dCas9 fused to an activator domain, VPR. More specifically, we targeted dCas9-VPR toward binding sites of Gcr1-Gcr2 and Tye7 present in several promoters of genes encoding enzymes engaged in the central carbon metabolism. From our data, we observed an upregulation of gene expression when dCas9-VPR was targeted next to a TF binding motif, whereas a downregulation or no change was observed when dCas9 was bound on a TF motif. This suggests a steric competition between dCas9 and the specific TF. Integrating TF binding data, therefore, proved to be useful for designing guide RNAs for CRISPR interference or CRISPR activation applications.

聚集规律间隔短回文重复序列(CRISPR)/Cas9系统已成为许多基因组工程努力的标准工具。Cas9的内切酶缺陷版本(dCas9)也是一个强大的基因调控可编程工具。在本研究中,我们利用酿酒酵母转录因子(Saccharomyces cerevisiae转录因子(TF)结合数据,更好地了解TF结合与dCas9融合到激活子结构域VPR之间的相互作用。更具体地说,我们将dCas9-VPR靶向Gcr1-Gcr2和Tye7的结合位点,这些Gcr1-Gcr2和Tye7存在于几个编码中枢碳代谢酶的基因启动子中。从我们的数据中,我们观察到当dCas9- vpr与TF结合基序结合时,基因表达上调,而当dCas9与TF结合基序结合时,基因表达下调或没有变化。这表明dCas9和特异性TF之间存在空间竞争。因此,整合TF结合数据被证明对设计用于CRISPR干扰或CRISPR激活应用的引导rna是有用的。
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引用次数: 0
Building Biofoundry India: challenges and path forward. 建设印度生物铸造厂:挑战和前进道路。
Q2 BIOCHEMICAL RESEARCH METHODS Pub Date : 2021-06-25 eCollection Date: 2021-01-01 DOI: 10.1093/synbio/ysab015
Binay Panda, Pawan K Dhar

Biofoundry is a place where biomanufacturing meets automation. The highly modular structure of a biofoundry helps accelerate the design-build-test-learn workflow to deliver products fast and in a streamlined fashion. In this perspective, we describe our efforts to build Biofoundry India, where we see the facility add a substantial value in supporting research, innovation and entrepreneurship. We describe three key areas of our focus, harnessing the potential of non-expressing parts of the sequenced genomes, using deep learning in pathway reconstruction and synthesising enzymes and metabolites. Toward the end, we describe specific challenges in building such facility in India and the path to mitigate some of those working with the other biofoundries worldwide.

生物铸造厂是生物制造与自动化相结合的地方。生物铸造厂的高度模块化结构有助于加快设计-构建-测试-学习的工作流程,以快速且流线型的方式交付产品。从这个角度来看,我们描述了我们为建立印度生物铸造厂所做的努力,我们认为该设施在支持研究、创新和创业方面增加了巨大的价值。我们描述了我们关注的三个关键领域,利用测序基因组非表达部分的潜力,在途径重建和合成酶和代谢物中使用深度学习。最后,我们描述了在印度建立这样的设施所面临的具体挑战,以及缓解与世界其他生物代工厂合作所面临的一些挑战的途径。
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引用次数: 1
Pathway engineering for high-yield production of lutein in Escherichia coli. 大肠杆菌高产叶黄素的途径工程。
Q2 BIOCHEMICAL RESEARCH METHODS Pub Date : 2021-05-15 eCollection Date: 2021-01-01 DOI: 10.1093/synbio/ysab012
Miho Takemura, Akiko Kubo, Asuka Watanabe, Hanayo Sakuno, Yuka Minobe, Takehiko Sahara, Masahiro Murata, Michihiro Araki, Hisashi Harada, Yoshinobu Terada, Katsuro Yaoi, Kohji Ohdan, Norihiko Misawa

Lutein is an industrially important carotenoid pigment, which is essential for photoprotection and photosynthesis in plants. Lutein is crucial for maintaining human health due to its protective ability from ocular diseases. However, its pathway engineering research has scarcely been performed for microbial production using heterologous hosts, such as Escherichia coli, since the engineering of multiple genes is required. These genes, which include tricky key carotenoid biosynthesis genes typically derived from plants, encode two sorts of cyclases (lycopene ε- and β-cyclase) and cytochrome P450 CYP97C. In this study, upstream genes effective for the increase in carotenoid amounts, such as isopentenyl diphosphate isomerase (IDI) gene, were integrated into the E. coli JM101 (DE3) genome. The most efficient set of the key genes (MpLCYe, MpLCYb and MpCYP97C) was selected from among the corresponding genes derived from various plant (or bacterial) species using E. coli that had accumulated carotenoid substrates. Furthermore, to optimize the production of lutein in E. coli, we introduced several sorts of plasmids that contained some of the multiple genes into the genome-inserted strain and compared lutein productivity. Finally, we achieved 11 mg/l as lutein yield using a mini jar. Here, the high-yield production of lutein was successfully performed using E. coli through approaches of pathway engineering. The findings obtained here should be a base reference for substantial lutein production with microorganisms in the future.

叶黄素是工业上重要的类胡萝卜素色素,对植物的光保护和光合作用至关重要。叶黄素对眼部疾病具有保护作用,对维持人体健康至关重要。然而,由于需要对多个基因进行工程处理,其途径工程研究很少用于利用异源宿主(如大肠杆菌)进行微生物生产。这些基因,包括棘手的关键类胡萝卜素生物合成基因,通常来自植物,编码两种环化酶(番茄红素ε和β环化酶)和细胞色素P450 CYP97C。本研究将能增加类胡萝卜素数量的上游基因,如异戊烯基二磷酸异构酶(IDI)基因整合到大肠杆菌JM101 (DE3)基因组中。利用积累了类胡萝卜素底物的大肠杆菌,从各种植物(或细菌)衍生的相应基因中选择了效率最高的关键基因(MpLCYe、MpLCYb和MpCYP97C)。此外,为了优化大肠杆菌中叶黄素的生产,我们将几种含有多个基因的质粒引入到基因组插入菌株中,并比较了叶黄素的产量。最后,我们使用迷你罐获得了11 mg/l的叶黄素产量。本研究通过途径工程的方法,成功地利用大肠杆菌实现了叶黄素的高产。本研究结果将为今后利用微生物大量生产叶黄素提供基础参考。
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引用次数: 6
A computational walk to the hidden peaks of protein performance. 通过计算走到蛋白质性能的隐藏峰值。
Q2 BIOCHEMICAL RESEARCH METHODS Pub Date : 2021-05-14 eCollection Date: 2021-01-01 DOI: 10.1093/synbio/ysab011
Sonja Billerbeck
Spiders use them to catch their prey, plants rely on them to fix carbon and mammals need them for eye vision—proteins. Proteins play critical roles in nature, and not surprisingly, synthetic biologists heavily rely on their functional diversity to build new therapeutics (1), catalysts (2) and materials (3). But natural proteins are rarely optimal for their envisioned human uses. They rather need to be engineered to enhance their performance. Recently, researchers introduced a machine-learning guided paradigm that can predict which mutations in a protein will enhance function with only 24 functional data sets as input (4). This paradigm could significantly accelerate the engineering of improved proteins for medicine, food, agriculture and industrial applications. The desire to optimize a protein’s function has always been a centerpiece of synthetic biology, and for decades, protein engineers have innovated the capacities of directed evolution (2) and rational protein engineering. One prominent bottleneck for the engineering of proteins is the difficulty in understanding a protein’s so-called fitness landscape. That means to know, which mutationwillmake a protein better, while in fact, mostmutations render a protein dysfunctional. The function of a protein is dictated by its amino acid sequence, and protein scientists picture the relationship between sequence and function of a protein as if it was a rugged landscape with shallow hills and high peaks, separated by valleys (5). Valleys represent sequence variants that are not functional, while the highest peaks represent the most functional mutations. Protein engineers now seek to walk through this landscape—each step being one mutation away from the wild-type sequence—in order to explore if they can find higher peaks of performance in sequence space. As the shape of the landscape is mostly unknown, the walk is random and requires the generation of many sequences and the evaluation of their function. Generating this data is often experimentally difficult or expensive. Most importantly, very distant regions of the landscape, where functional peak performance might hide, are not accessible by this search. Recently, researchers have started to perform this walk through a protein’s sequence space computationally, using deep learning (6). Although several success stories have been reported, each case still relies on a large number of experimental input data. The Church group at Harvard Medical School and the Wyss Institute for Biologically Inspired Engineering now developed a way to mitigate the notorious shortage in experimental data that constrains the engineering of many proteins, by making use of the vast number of publicly available protein sequence data (4, 7). Instead of learning the fitness landscape of an individual protein from experimental data, they first built a deep learning algorithm that extracts the fundamental features of all functional proteins from the >20 million available unlabeled a
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引用次数: 0
Three overlooked key functional classes for building up minimal synthetic cells. 构建最小合成细胞的三个被忽视的关键功能类别。
Q2 BIOCHEMICAL RESEARCH METHODS Pub Date : 2021-04-20 eCollection Date: 2021-01-01 DOI: 10.1093/synbio/ysab010
Antoine Danchin

Assembly of minimal genomes revealed many genes encoding unknown functions. Three overlooked functional categories account for some of them. Cells are prone to make errors and age. As a first key function, discrimination between proper and changed entities is indispensable. Discrimination requires management of information, an authentic, yet abstract, currency of reality. For example proteins age, sometimes very fast. The cell must identify, then get rid of old proteins without destroying young ones. Implementing discrimination in cells leads to the second set of functions, usually ignored. Being abstract, information must nevertheless be embodied into material entities, with unavoidable idiosyncratic properties. This brings about novel unmet needs. Hence, the buildup of cells elicits specific but awkward material implementations, 'kludges' that become essential under particular settings, while difficult to identify. Finally, a third functional category characterizes the need for growth, with metabolic implementations allowing the cell to put together the growth of its cytoplasm, membranes, and genome, spanning different spatial dimensions. Solving this metabolic quandary, critical for engineering novel synthetic biology chassis, uncovered an unexpected role for CTP synthetase as the coordinator of nonhomothetic growth. Because a significant number of SynBio constructs aim at creating cell factories we expect that they will be attacked by viruses (it is not by chance that the function of the CRISPR system was identified in industrial settings). Substantiating the role of CTP, natural selection has dealt with this hurdle via synthesis of the antimetabolite 3'-deoxy-3',4'-didehydro-CTP, recruited for antiviral immunity in all domains of life.

最小基因组的组装揭示了许多编码未知功能的基因。其中有三种被忽视的功能类别。细胞容易出错和老化。作为第一个关键功能,区分适当的实体和已改变的实体是必不可少的。辨别需要对信息进行管理,这是一种真实但抽象的现实货币。例如,蛋白质老化,有时非常快。细胞必须识别,然后在不破坏新蛋白质的情况下清除旧蛋白质。在细胞中实施区分会导致第二组通常被忽略的功能。由于信息是抽象的,它必须体现为具有不可避免的特殊属性的物质实体。这带来了新的未被满足的需求。因此,细胞的积累引发了特定但尴尬的材料实现,“拼凑物”在特定环境下变得必不可少,但难以识别。最后,第三种功能类别描述了生长的需要,代谢实现允许细胞将其细胞质、膜和基因组的生长放在一起,跨越不同的空间维度。解决这一代谢困境,揭示了CTP合成酶作为非同质生长协调者的意想不到的作用,这对工程合成生物学的新基础至关重要。由于大量的SynBio构建旨在创建细胞工厂,我们预计它们将受到病毒的攻击(CRISPR系统的功能在工业环境中被识别并不是偶然的)。为了证实CTP的作用,自然选择通过合成抗代谢物3'-脱氧-3',4'-二脱氢-CTP来解决这一障碍,该抗代谢物在生命的所有领域都被用于抗病毒免疫。
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引用次数: 8
Moving towards chemical-free agriculture, 37 kb at a time. 向无化学品农业迈进,一次3.7万美元。
Q2 BIOCHEMICAL RESEARCH METHODS Pub Date : 2021-02-15 eCollection Date: 2021-01-01 DOI: 10.1093/synbio/ysab009
Sonja Billerbeck
Domestic crop plants are modern marvels of extensive breeding; however, many of their natural defenses against pests and pathogens have been lost. Wild relatives still harbor disease resistance genes, but transferring these large sequences into complex, polyploid plant genomes calls for advanced genomic engineering technologies. Recently, government researchers in Australia, successfully transferred a 37kb resistance stack into the genome of a domesticated wheat species such that it is pro-tected against the rapidly evolving wheat leaf rust pathogen Puccinia graminis f. sp. tritici ( Pgt ) without losing any agronomic features. 1 Plant diseases caused by pathogenic fungi can devastate crop yield and pose a threat to food security. 2,3 About 30% of our most important crops are lost every year to fungal diseases. 3 Over decades, agricultural crops have been bred towards maxi-mum productivity under high fungicide treatment, meanwhile breeding out the plants’ own defense genes. 3 The genetic ar-mory still intact in wild crop relatives (so-called R genes) could provide an effective means towards a chemical-free disease control. 4 Introducing those genes into domestic crops is a multi-factorial challenge yet underappreciated by much of the synthetic biology community.
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引用次数: 0
Transcriptional control of Clostridium autoethanogenum using CRISPRi. 利用CRISPRi对自产乙醇梭菌的转录调控。
Q2 BIOCHEMICAL RESEARCH METHODS Pub Date : 2021-02-10 eCollection Date: 2021-01-01 DOI: 10.1093/synbio/ysab008
Nicholas Fackler, James Heffernan, Alex Juminaga, Damien Doser, Shilpa Nagaraju, R Axayacatl Gonzalez-Garcia, Séan D Simpson, Esteban Marcellin, Michael Köpke

Gas fermentation by Clostridium autoethanogenum is a commercial process for the sustainable biomanufacturing of fuels and valuable chemicals using abundant, low-cost C1 feedstocks (CO and CO2) from sources such as inedible biomass, unsorted and nonrecyclable municipal solid waste, and industrial emissions. Efforts toward pathway engineering and elucidation of gene function in this microbe have been limited by a lack of genetic tools to control gene expression and arduous genome engineering methods. To increase the pace of progress, here we developed an inducible CRISPR interference (CRISPRi) system for C. autoethanogenum and applied that system toward transcriptional repression of genes with ostensibly crucial functions in metabolism.

自产乙醇梭状芽胞杆菌的气体发酵是一种可持续生物制造燃料和有价值化学品的商业过程,它使用大量低成本的C1原料(CO和CO2),这些原料来自不可食用的生物质、未分类和不可回收的城市固体废物和工业排放。由于缺乏控制基因表达的遗传工具和艰巨的基因组工程方法,对这种微生物的途径工程和基因功能的阐明受到限制。为了加快进展的步伐,我们开发了一种可诱导的CRISPR干扰(CRISPRi)系统,用于C. autoethanogenum,并将该系统应用于在代谢中具有表面上至关重要功能的基因的转录抑制。
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引用次数: 13
Joint universal modular plasmids (JUMP): a flexible vector platform for synthetic biology. 联合通用模块质粒(JUMP):一个灵活的合成生物学载体平台。
Q2 BIOCHEMICAL RESEARCH METHODS Pub Date : 2021-02-02 eCollection Date: 2021-01-01 DOI: 10.1093/synbio/ysab003
Marcos Valenzuela-Ortega, Christopher French

Generation of new DNA constructs is an essential process in modern life science and biotechnology. Modular cloning systems based on Golden Gate cloning, using Type IIS restriction endonucleases, allow assembly of complex multipart constructs from reusable basic DNA parts in a rapid, reliable and automation-friendly way. Many such toolkits are available, with varying degrees of compatibility, most of which are aimed at specific host organisms. Here, we present a vector design which allows simple vector modification by using modular cloning to assemble and add new functions in secondary sites flanking the main insertion site (used for conventional modular cloning). Assembly in all sites is compatible with the PhytoBricks standard, and vectors are compatible with the Standard European Vector Architecture (SEVA) as well as BioBricks. We demonstrate that this facilitates the construction of vectors with tailored functions and simplifies the workflow for generating libraries of constructs with common elements. We have made available a collection of vectors with 10 different microbial replication origins, varying in copy number and host range, and allowing chromosomal integration, as well as a selection of commonly used basic parts. This design expands the range of hosts which can be easily modified by modular cloning and acts as a toolkit which can be used to facilitate the generation of new toolkits with specific functions required for targeting further hosts.

新DNA结构的生成是现代生命科学和生物技术的一个重要过程。基于金门克隆的模块化克隆系统,使用IIS型限制性内切酶,允许从可重复使用的基本DNA部分以快速,可靠和自动化友好的方式组装复杂的多部分结构。有许多这样的工具包,具有不同程度的兼容性,其中大多数针对特定的宿主生物。在这里,我们提出了一种载体设计,它允许简单的载体修改,通过使用模块化克隆在主插入位点侧翼的次要位点上组装和添加新的功能(用于传统的模块化克隆)。所有站点的组装都与PhytoBricks标准兼容,载体与欧洲标准载体架构(SEVA)以及BioBricks兼容。我们证明,这有助于构造具有定制函数的向量,并简化了生成具有公共元素的构造库的工作流程。我们已经收集了10种不同微生物复制起点的载体,这些载体在拷贝数和宿主范围上有所不同,并允许染色体整合,以及选择常用的基本部分。这种设计扩大了宿主的范围,可以通过模块化克隆轻松修改,并作为一个工具包,可以用来促进生成具有特定功能的新工具包,以针对更多的宿主。
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引用次数: 13
Starting from scratch: a workflow for building truly novel proteins. 从头开始:构建真正新颖蛋白质的工作流程。
Q2 BIOCHEMICAL RESEARCH METHODS Pub Date : 2021-01-30 eCollection Date: 2021-01-01 DOI: 10.1093/synbio/ysab005
Pablo Cárdenas
In its early days, synthetic biology was often defined as repurposing existing biological parts for new applications. More recently, we have seen work that pushes the boundaries of the field past repurposing and into the design of truly novel biological parts. To date, most attempts at designing complex, non-structural protein functions have hinged on grafting protein motifs with known functions onto synthetic protein scaffolds. This ‘top-down’ approach to synthetic protein design unfortunately depends on the structural compatibility of the functional sites with rigid scaffolds used. A study recently published in Nature Chemical Biology describes an alternative ‘bottom-up’ approach in which structural elements are created de novo to support the functional elements in whatever conformation they are specified in (1). The multi-institutional team led by Bruno Correira’s lab at École Polytechnique Fédérale de Lausanne demonstrated the efficacy of their novel approach by building tunable biosensors for epitope-specific antibodies and dual-specific ligands for synthetic cell receptors. To achieve this ‘bottom-up’ design, the authors used TopoBuilder (2), a previously published computational tool, to generate three-dimensional ‘sketches’ of a given protein of interest with specific functional motifs in their idealized conformations. With the help of another software tool, Rosetta FunFoldDes (3), the authors created and simulated tens of thousands of possible designs fulfilling the design criteria, which were filtered by favorable thermodynamic predictions for stability and folding. A combinatorial library of up to 10 million variants was built from elements of the best designs. The libraries were then screened by binding affinity to the desired target(s) and protease digestion using yeast surface display, and the best protein variants were selected by sequencing the output. Finally, the structure and behavior of the final products were determined using a variety of different physical and chemical assays. The authors used their workflow to design a biosensor based on bioluminescence resonant energy transfer (4) to sense antibodies with affinities for a single, specific epitope found in respiratory syncytial virus and metapneumovirus, two respiratory pathogens. The novel design pipeline made it possible to present the single epitope in scaffolds with different binding affinities to the target antibody. This, in turn, allowed for tuning the biosensor’s response. Furthermore, the workflow was used to create a synthetic ligand capable of binding to two different, previously created synthetic mammalian signal receptors, which trigger expression of a reporter gene (5). The authors demonstrated the ligand simultaneously bound its two distinct targets by showing it only triggered output signal when both types of receptor were present in a cell. The work presented by Yang et al. is exciting for its practically universal applicability in biological research. Appli
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引用次数: 1
期刊
Synthetic biology (Oxford, England)
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