Genome engineering

The design and engineering of synthetic genomes

Synthetic genomics seeks to design and construct entire genomes to mechanistically dissect fundamental questions of genome function and to engineer organisms for diverse applications, including bioproduction of high-value chemicals and biologics, advanced cell therapies, and stress-tolerant crops. Recent progress has been fuelled by advancements in DNA synthesis, assembly, delivery and editing. Computational innovations, such as the use of artificial intelligence to provide prediction of function, also provide increasing capabilities to guide synthetic genome design and construction. However, translating synthetic genome-scale projects from idea to implementation remains highly complex. Here, we aim to streamline this implementation process by comprehensively reviewing the strategies for design, construction, delivery, debugging and tailoring of synthetic genomes as well as their potential applications.

Recent progress in DNA data storage based on high-throughput DNA synthesis

DNA data storage has emerged as a solution for storing massive volumes of data by utilizing nucleic acids as a digital information medium. DNA offers exceptionally high storage density, long durability, and low maintenance costs compared to conventional storage media such as flash memory and hard disk drives. DNA data storage consists of the following steps: encoding, DNA synthesis (i.e., writing), preservation, retrieval, DNA sequencing (i.e., reading), and decoding. Out of these steps, DNA synthesis presents a bottleneck due to imperfect coupling efficiency, low throughput, and excessive use of organic solvents. Overcoming these challenges is essential to establish DNA as a viable data storage medium. In this review, we provide the overall process of DNA data storage, presenting the recent progress of each step. Next, we examine a detailed overview of DNA synthesis methods with an emphasis on their limitations. Lastly, we discuss the efforts to overcome the constraints of each method and their prospects.

Species-specific design of artificial promoters by transfer-learning based generative deep-learning model

Native prokaryotic promoters share common sequence patterns, but are species dependent. For understudied species with limited data, it is challenging to predict the strength of existing promoters and generate novel promoters. Here, we developed PromoGen, a collection of nucleotide language models to generate species-specific functional promoters, across dozens of species in a data and parameter efficient way. Twenty-seven species-specific models in this collection were finetuned from the pretrained model which was trained on multi-species promoters. When systematically compared with native promoters, the Escherichia coli- and Bacillus subtilis-specific artificial PromoGen-generated promoters (PGPs) were demonstrated to hold all distribution patterns of native promoters. A regression model was developed to score generated either by PromoGen or by another competitive neural network, and the overall score of PGPs is higher. Encouraged by in silico analysis, we further experimentally characterized twenty-two B. subtilis PGPs, results showed that four of tested PGPs reached the strong promoter level while all were active. Furthermore, we developed a user-friendly website to generate species-specific promoters for 27 different species by PromoGen. This work presented an efficient deep-learning strategy for de novo species-specific promoter generation even with limited datasets, providing valuable promoter toolboxes especially for the metabolic engineering of understudied microorganisms.

Towards Chinese text and DNA shift encoding scheme based on biomass plasmid storage

DNA, as the storage medium in organisms, can address the shortcomings of existing electromagnetic storage media, such as low information density, high maintenance power consumption, and short storage time. Current research on DNA storage mainly focuses on designing corresponding encoders to convert binary data into DNA base data that meets biological constraints. We have created a new Chinese character code table that enables exceptionally high information storage density for storing Chinese characters (compared to traditional UTF-8 encoding). To meet biological constraints, we have devised a DNA shift coding scheme with low algorithmic complexity, which can encode any strand of DNA even has excessively long homopolymer. The designed DNA sequence will be stored in a double-stranded plasmid of 744bp, ensuring high reliability during storage. Additionally, the plasmid's resistance to environmental interference ensuring long-term stable information storage. Moreover, it can be replicated at a lower cost.

In-vitro validated methods for encoding digital data in deoxyribonucleic acid (DNA)

Deoxyribonucleic acid (DNA) is emerging as an alternative archival memory technology. Recent advancements in DNA synthesis and sequencing have both increased the capacity and decreased the cost of storing information in de novo synthesized DNA pools. In this survey, we review methods for translating digital data to and/or from DNA molecules. An emphasis is placed on methods which have been validated by storing and retrieving real-world data via in-vitro experiments.

PCR-Based Assembly of Gene Sequences by Thermodynamically Balanced Inside-Out (TBIO) Gene Synthesis

The ability to enzymatically assemble DNA oligonucleotides into longer DNA duplexes in a process known as gene synthesis has wide-ranging applications in the fields of genetic engineering and synthetic biology. Thermodynamically balanced inside-out (TBIO) gene synthesis is one of several PCR-based primer extension gene synthesis protocols that have been developed. In TBIO gene synthesis, overlapping primers with equivalent melting temperatures (T_ms) are designed so that the 5' half of the DNA is encoded by sense primers and the 3' half of the DNA molecule is encoded by antisense primers. Primer extension is initiated at the center of the DNA and continues bidirectionally to progressively elongate the DNA molecule. Here we provide the protocols necessary for performing TBIO gene synthesis to generate a DNA molecule of interest.

High-throughput genetic engineering tools for regulating gene expression in a microbial cell factory

With the rapid advances in biotechnological tools and strategies, microbial cell factory-constructing strategies have been established for the production of value-added compounds. However, optimizing the tradeoff between the biomass, yield, and titer remains a challenge in microbial production. Gene regulation is necessary to optimize and control metabolic fluxes in microorganisms for high-production performance. Various high-throughput genetic engineering tools have been developed for achieving rational gene regulation and genetic perturbation, diversifying the cellular phenotype and enhancing bioproduction performance. In this paper, we review the current high-throughput genetic engineering tools for gene regulation. In particular, technological approaches used in a diverse range of genetic tools for constructing microbial cell factories are introduced, and representative applications of these tools are presented. Finally, the prospects for high-throughput genetic engineering tools for gene regulation are discussed.

Scalable Combinatorial Assembly of Synthetic DNA for Tracking Applications

Synthetic DNA barcodes are double-stranded DNA molecules designed to carry recoverable information, information that can be used to represent and track objects and organisms. DNA barcodes offer robust, sensitive detection using standard amplification and sequencing techniques. While numerous research groups have promoted DNA as an information storage medium, less attention has been devoted to the design of economical, scalable DNA barcode libraries. Here, we present an alternative modular approach to sequence design. Barcode sequences were constructed from smaller, interchangeable blocks, allowing for the combinatorial assembly of numerous distinct tags. We demonstrated the design and construction of first-generation (N = 256) and second-generation (N = 512) modular barcode libraries, from fewer than 50 total single-stranded oligonucleotides for each library. To avoid contamination during experimental validation, a liquid-handling robot was employed for oligonucleotide mixing. Generating barcode sequences in-house reduces dependency upon external entities for unique tag generation, increasing flexibility in barcode generation and deployment. Next generation sequencing (NGS) detection of 256 different samples in parallel highlights the multiplexing afforded by the modular barcode design coupled with high-throughput sequencing. Deletion variant analysis of the first-generation library informed sequence design for enhancing barcode assembly specificity in the second-generation library.

Mosquito tagging using DNA-barcoded nanoporous protein microcrystals

Conventional mosquito marking technology for mark-release-recapture (MRR) is quite limited in terms of information capacity and efficacy. To overcome both challenges, we have engineered, lab-tested, and field-evaluated a new class of marker particles, in which synthetic, short DNA oligonucleotides (DNA barcodes) are adsorbed and protected within tough, crosslinked porous protein microcrystals. Mosquitoes self-mark through ingestion of microcrystals in their larval habitat. Barcoded microcrystals persist trans-stadially through mosquito development if ingested by larvae, do not significantly affect adult mosquito survivorship, and individual barcoded mosquitoes are detectable in pools of up to at least 20 mosquitoes. We have also demonstrated crystal persistence following adult mosquito ingestion. Barcode sequences can be recovered by qPCR and next-generation sequencing (NGS) without detectable amplification of native mosquito DNA. These DNA-laden protein microcrystals have the potential to radically increase the amount of information obtained from future MRR studies compared to previous studies employing conventional mosquito marking materials.

dCas9-based gene editing for cleavage-free genomic knock-in of long sequences

Gene editing is a powerful tool for genome and cell engineering. Exemplified by CRISPR–Cas, gene editing could cause DNA damage and trigger DNA repair processes that are often error-prone. Such unwanted mutations and safety concerns can be exacerbated when altering long sequences. Here we couple microbial single-strand annealing proteins (SSAPs) with catalytically inactive dCas9 for gene editing. This cleavage-free gene editor, dCas9–SSAP, promotes the knock-in of long sequences in mammalian cells. The dCas9–SSAP editor has low on-target errors and minimal off-target effects, showing higher accuracy than canonical Cas9 methods. It is effective for inserting kilobase-scale sequences, with an efficiency of up to approximately 20% and robust performance across donor designs and cell types, including human stem cells. We show that dCas9–SSAP is less sensitive to inhibition of DNA repair enzymes than Cas9 references. We further performed truncation and aptamer engineering to minimize its size to fit into a single adeno-associated-virus vector for future application. Together, this tool opens opportunities towards safer long-sequence genome engineering.

Wang, Qu et al. developed a genome-editing system, utilizing catalytically inactive Cas9 fused to microbial single-strand annealing proteins, for kilobase-scale insertion in human cells without introducing DNA nicks or breaks.

Strategies for Heterologous Expression, Synthesis, and Purification of Animal Venom Toxins

Animal venoms are complex mixtures containing peptides and proteins known as toxins, which are responsible for the deleterious effect of envenomations. Across the animal Kingdom, toxin diversity is enormous, and the ability to understand the biochemical mechanisms governing toxicity is not only relevant for the development of better envenomation therapies, but also for exploiting toxin bioactivities for therapeutic or biotechnological purposes. Most of toxinology research has relied on obtaining the toxins from crude venoms; however, some toxins are difficult to obtain because the venomous animal is endangered, does not thrive in captivity, produces only a small amount of venom, is difficult to milk, or only produces low amounts of the toxin of interest. Heterologous expression of toxins enables the production of sufficient amounts to unlock the biotechnological potential of these bioactive proteins. Moreover, heterologous expression ensures homogeneity, avoids cross-contamination with other venom components, and circumvents the use of crude venom. Heterologous expression is also not only restricted to natural toxins, but allows for the design of toxins with special properties or can take advantage of the increasing amount of transcriptomics and genomics data, enabling the expression of dormant toxin genes. The main challenge when producing toxins is obtaining properly folded proteins with a correct disulfide pattern that ensures the activity of the toxin of interest. This review presents the strategies that can be used to express toxins in bacteria, yeast, insect cells, or mammalian cells, as well as synthetic approaches that do not involve cells, such as cell-free biosynthesis and peptide synthesis. This is accompanied by an overview of the main advantages and drawbacks of these different systems for producing toxins, as well as a discussion of the biosafety considerations that need to be made when working with highly bioactive proteins.

Minimal Genome Design Algorithms Using Whole-Cell Models

Synthetic biologists engineer cells and cellular functions using design-build-test cycles; when the task is to extensively engineer entire genomes, the lack of appropriate design tools and biological knowledge about each gene in a cell can lengthen the process, requiring time-consuming and expensive experimental iterations.Whole-cell models represent a new avenue for genome design; the bacteria Mycoplasma genitalium has the first (and currently only published) whole-cell model which combines 28 cellular submodels and represents the integrated functions of every gene and molecule in a cell.We created two minimal genome design algorithms, GAMA and Minesweeper, that produced 1000s of in silico minimal genomes by running simulations on multiple supercomputers. Here we describe the steps to produce in silico cells with reduced genomes, combining minimisation algorithms with whole-cell model simulations.We foresee that the combination of similar algorithms and whole-cell models could later be used for a broad spectrum of genome design applications across cellular species when appropriate models become available.

Efficient and Low-Cost Error Removal in DNA Synthesis by a High-Durability MutS

Enzyme-based error correction is a key step in de novo DNA synthesis, yet the inherent instability of error-correction enzymes such as MutS has hindered the throughput and efficiency of DNA synthesis workflows. Here we introduce a process called Improved MICC (iMICC), in which all error-correction steps of oligos and fragments within a complete gene-synthesis cycle are completed in a simple, efficient, and low-cost manner via a MutS protein engineered for high durability. By establishing a disulfide bond of L157C-G233C, full-activity shelf life of E. coli MutS (eMutS) was prolonged from 7 to 49 days and was further extended to 63 days via cellulose-bound 4 °C storage. In synthesis of 10 Cas9 homologues in-solution and 10 xylose reductase (XR) homologues on-chip, iMICC reduced error frequency to 0.64/Kb and 0.41/Kb, respectively, with 72.1% and 86.4% of assembled fragments being error-free. By elevating base accuracy by 37.6-fold while avoiding repetitive preparation of fresh enzymes, iMICC is more efficient and robust than the wild-type eMutS, and it is 6.6-fold more accurate and 26.7-fold cheaper than CorrectASE. These advantages promise its broad applications in industrial DNA synthesis.

Big data management: from hard drives to DNA drives

Information Communication and Technology is transforming all aspects of modern life and in this digital era, there is a tremendous increase in the amount of data that is being generated every day. The current, conventional storage devices are unable to keep pace with this rapidly growing data. Thus, there is a need to look for alternative storage devices. DNA being exceptional in storage of biological information offers a promising storage capacity. With its unique abilities of dense storage and reliability, it may prove better than all conventional storage devices in near future. The nucleotide bases are present in DNA in a particular sequence representing the coded information. These are the equivalent of binary letters (0 &1). To store data in DNA, binary data is first converted to ternary or quaternary which is then translated into the nucleotide code comprising 4 nucleotide bases (A, C, G, T). A DNA strand is then synthesized as per the code developed. This may either be stored in pools or sequenced back. The nucleotide code is converted back into ternary and subsequently the binary code which is read just like digital data. DNA drives may have a wide variety of applications in information storage and DNA steganography.

Engineering Biology to Construct Microbial Chassis for the Production of Difficult-to-Express Proteins

A large proportion of the recombinant proteins manufactured today rely on microbe-based expression systems owing to their relatively simple and cost-effective production schemes. However, several issues in microbial protein expression, including formation of insoluble aggregates, low protein yield, and cell death are still highly recursive and tricky to optimize. These obstacles are usually rooted in the metabolic capacity of the expression host, limitation of cellular translational machineries, or genetic instability. To this end, several microbial strains having precisely designed genomes have been suggested as a way around the recurrent problems in recombinant protein expression. Already, a growing number of prokaryotic chassis strains have been genome-streamlined to attain superior cellular fitness, recombinant protein yield, and stability of the exogenous expression pathways. In this review, we outline challenges associated with heterologous protein expression, some examples of microbial chassis engineered for the production of recombinant proteins, and emerging tools to optimize the expression of heterologous proteins. In particular, we discuss the synthetic biology approaches to design and build and test genome-reduced microbial chassis that carry desirable characteristics for heterologous protein expression.

Genome-driven cell engineering review: in vivo and in silico metabolic and genome engineering

Producing 'designer cells' with specific functions is potentially feasible in the near future. Recent developments, including whole-cell models, genome design algorithms and gene editing tools, have advanced the possibility of combining biological research and mathematical modelling to further understand and better design cellular processes. In this review, we will explore computational and experimental approaches used for metabolic and genome design. We will highlight the relevance of modelling in this process, and challenges associated with the generation of quantitative predictions about cell behaviour as a whole: although many cellular processes are well understood at the subsystem level, it has proved a hugely complex task to integrate separate components together to model and study an entire cell. We explore these developments, highlighting where computational design algorithms compensate for missing cellular information and underlining where computational models can complement and reduce lab experimentation. We will examine issues and illuminate the next steps for genome engineering.

pTrimmer: An efficient tool to trim primers of multiplex deep sequencing data

Background

With the widespread use of multiple amplicon-sequencing (MAS) in genetic variation detection, an efficient tool is required to remove primer sequences from short reads to ensure the reliability of downstream analysis. Although some tools are currently available, their efficiency and accuracy require improvement in trimming large scale of primers in high throughput target genome sequencing. This issue is becoming more urgent considering the potential clinical implementation of MAS for processing patient samples. We here developed pTrimmer that could handle thousands of primers simultaneously with greatly improved accuracy and performance.

Result

pTrimmer combines the two algorithms of k-mers and Needleman-Wunsch algorithm, which ensures its accuracy even with the presence of sequencing errors. pTrimmer has an improvement of 28.59% sensitivity and 11.87% accuracy compared to the similar tools. The simulation showed pTrimmer has an ultra-high sensitivity rate of 99.96% and accuracy of 97.38% compared to cutPrimers (70.85% sensitivity rate and 58.73% accuracy). And the performance of pTrimmer is notably higher. It is about 370 times faster than cutPrimers and even 17,000 times faster than cutadapt per threads. Trimming 2158 pairs of primers from 11 million reads (Illumina PE 150 bp) takes only 37 s and no more than 100 MB of memory consumption.

Conclusions

pTrimmer is designed to trim primer sequence from multiplex amplicon sequencing and target sequencing. It is highly sensitive and specific compared to other three similar tools, which could help users to get more reliable mutational information for downstream analysis.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2854-x) contains supplementary material, which is available to authorized users.

High information capacity DNA-based data storage with augmented encoding characters using degenerate bases

DNA-based data storage has emerged as a promising method to satisfy the exponentially increasing demand for information storage. However, practical implementation of DNA-based data storage remains a challenge because of the high cost of data writing through DNA synthesis. Here, we propose the use of degenerate bases as encoding characters in addition to A, C, G, and T, which augments the amount of data that can be stored per length of DNA sequence designed (information capacity) and lowering the amount of DNA synthesis per storing unit data. Using the proposed method, we experimentally achieved an information capacity of 3.37 bits/character. The demonstrated information capacity is more than twice when compared to the highest information capacity previously achieved. The proposed method can be integrated with synthetic technologies in the future to reduce the cost of DNA-based data storage by 50%.

Co-evolution of physical and social sciences in synthetic biology

Emerging technologies research often covers various perspectives in disciplines and research areas ranging from hard sciences, engineering, policymaking, and sociology. However, the interrelationship between these different disciplinary domains, particularly the physical and social sciences, often occurs many years after a technology has matured and moved towards commercialization. Synthetic biology may serve an exception to this idea, where, since 2000, the physical and the social sciences communities have increasingly framed their research in response to various perspectives in biological engineering, risk assessment needs, governance challenges, and the social implications that the technology may incur. This paper reviews a broad collection of synthetic biology literature from 2000-2016, and demonstrates how the co-development of physical and social science communities has grown throughout synthetic biology's earliest stages of development. Further, this paper indicates that future co-development of synthetic biology scholarship will assist with significant challenges of the technology's risk assessment, governance, and public engagement needs, where an interdisciplinary approach is necessary to foster sustainable, risk-informed, and societally beneficial technological advances moving forward.

Sc-ncDNAPred: A Sequence-Based Predictor for Identifying Non-coding DNA in Saccharomyces cerevisiae

With the rapid development of high-speed sequencing technologies and the implementation of many whole genome sequencing project, research in the genomics is advancing from genome sequencing to genome synthesis. Synthetic biology technologies such as DNA-based molecular assemblies, genome editing technology, directional evolution technology and DNA storage technology, and other cutting-edge technologies emerge in succession. Especially the rapid growth and development of DNA assembly technology may greatly push forward the success of artificial life. Meanwhile, DNA assembly technology needs a large number of target sequences of known information as data support. Non-coding DNA (ncDNA) sequences occupy most of the organism genomes, thus accurate recognizing of them is necessary. Although experimental methods have been proposed to detect ncDNA sequences, they are expensive for performing genome wide detections. Thus, it is necessary to develop machine-learning methods for predicting non-coding DNA sequences. In this study, we collected the ncDNA benchmark dataset of Saccharomyces cerevisiae and reported a support vector machine-based predictor, called Sc-ncDNAPred, for predicting ncDNA sequences. The optimal feature extraction strategy was selected from a group included mononucleotide, dimer, trimer, tetramer, pentamer, and hexamer, using support vector machine learning method. Sc-ncDNAPred achieved an overall accuracy of 0.98. For the convenience of users, an online web-server has been built at: http://server.malab.cn/Sc_ncDNAPred/index.jsp.

How to talk about genome editing

Background

Human genome editing is an area of growing prominence, with many potential therapeutic applications.

Sources of data

A project by two UK charities, whose participants included fertility sector patients and practitioners and also people affected by genetic disease and rare disease. Scientific research into, and wider discussion of, genomics and genome editing.

Areas of agreement

There is a need for improved public and professional understanding of genome editing.

Areas of controversy

The way genome editing is discussed is often inconsistent and confusing. Simply defining and explaining the term 'genome' can present challenges.

Growing points

There are approaches that lend themselves to achieving greater clarity and coherence in discussion of genome editing.

Areas timely for developing research

People's understanding should ideally be able to withstand and evolve alongside current developments in genome editing, rather than being tied firmly to specific aspects of genome editing (which may in future be supplanted).

An Oil-Free Picodrop Bioassay Platform for Synthetic Biology

Droplet microfluidics enables massively-parallel analysis of single cells, biomolecules, and chemicals, making it valuable for high-throughput screens. However, many hydrophobic analytes are soluble in carrier oils, preventing their quantitative analysis with the method. We apply Printed Droplet Microfluidics to construct defined reactions with chemicals and cells incubated under air on an open array. The method interfaces with most bioanalytical tools and retains hydrophobic compounds in compartmentalized reactors, allowing their quantitation.

CADS: CRISPR/Cas12a-Assisted DNA Steganography for Securing the Storage and Transfer of DNA-Encoded Information

Because DNA has the merit of high capacity and complexity, DNA steganography, which conceals DNA-encoded messages, is very promising in information storage. The classical DNA steganography method hides DNA with a "secret message" in a mount of junk DNA, and the message can be extracted by polymerase chain reaction (PCR) using specific primers (key), followed by DNA sequencing and sequence decoding. As leakage of the primer information may result in message insecurity, new methods are needed to better secure the DNA information. Here, we develop a pre-key by either mixing specific primers (real key) with nonspecific primers (fake key) or linking a real key with 3'-end redundant sequences. Then, the single-stranded DNA (ssDNA) trans cleavage activity of CRISPR/Cas12a is employed to cut a fake key or remove the 3'-end redundant sequences, generating a real key for further information extraction. Therefore, with the Cas12a-assisted DNA steganography method, both storage and transfer of DNA-encoding data can be better protected.

On-Chip Fluorescence Switching System for Constructing a Rewritable Random Access Data Storage Device

We report the development of on-chip fluorescence switching system based on DNA strand displacement and DNA hybridization for the construction of a rewritable and randomly accessible data storage device. In this study, the feasibility and potential effectiveness of our proposed system was evaluated with a series of wet experiments involving 40 bits (5 bytes) of data encoding a 5-charactered text (KRIBB). Also, a flexible data rewriting function was achieved by converting fluorescence signals between "ON" and "OFF" through DNA strand displacement and hybridization events. In addition, the proposed system was successfully validated on a microfluidic chip which could further facilitate the encoding and decoding process of data. To the best of our knowledge, this is the first report on the use of DNA hybridization and DNA strand displacement in the field of data storage devices. Taken together, our results demonstrated that DNA-based fluorescence switching could be applicable to construct a rewritable and randomly accessible data storage device through controllable DNA manipulations.

Combinatorial Evolution of DNA with RECODE

In past decades, DNA engineering protocols have led to the rapid development of synthetic biology. To engineer the natural proteins, many directed evolution methods based on molecular biology have been presented for generating genetic diversity or obtaining specific properties. Here, we provide a simple (PCR operation), efficient (larger amount of products), and powerful (multiple point mutations, deletions, insertions, and combinatorial multipoint mutagenesis) RECODE method, which is capable of reediting the target DNA flexibly to restructure regulatory regions and remodel enzymes by using the combined function of the thermostable DNA polymerase and DNA ligase in one pot. RECODE is expected to be an applicable choice to create diverse mutant libraries for rapid evolution and optimization of enzymes and synthetic pathways.

Long-Term Stability and Integrity of Plasmid-Based DNA Data Storage

Validation of long-term DNA stability and integrity are essential for the use of DNA in data storage applications. Because of this, we evaluated the plasmid-based DNA data storage in a manner that preserves DNA stability and integrity. A document consisting of 2046 words was encoded with DNA sequences using Perl script, and the encoded DNA sequences were synthesized for information storage. The DNA comprised a total of 22 chemically synthesized DNA fragments with 400 nucleotides each, which were incorporated into a plasmid vector. A long-term DNA stability study demonstrated that 3-year stored plasmid containing text information showed DNA stability at controlled conditions of −20 °C. The plasmid DNA under accelerated aging conditions (AAC) up to 65 °C for 20 days, which corresponds to approximately 20 years of storage at −20 °C, also exhibited no significant differences in DNA stability compared to newly produced plasmid. Also, the 3-year old plasmid stored at −20 °C and the AAC-tested plasmid stored up to 65 °C for 20 days had functional integrity and nucleotide integrity comparable to control sample, thereby allowing for retrieval of the original error-free text data. Finally, the nucleotides were sequenced, and then decoded to retrieve the original data, thereby allowing us to read the text with 100% accuracy, and amplify the DNA with a simple and quick bacterial transformation. To the best of our knowledge, this is the first report on examining the long-term stability and integrity of plasmid-based DNA data storage. Taken together, our results indicate that plasmid DNA data storage can be useful for long-term archival storage to recover the source text in a reproducible and accountable manner.

Refactoring the Genetic Code for Increased Evolvability

The standard genetic code is robust to mutations during transcription and translation. Point mutations are likely to be synonymous or to preserve the chemical properties of the original amino acid. Saturation mutagenesis experiments suggest that in some cases the best-performing mutant requires replacement of more than a single nucleotide within a codon. These replacements are essentially inaccessible to common error-based laboratory engineering techniques that alter a single nucleotide per mutation event, due to the extreme rarity of adjacent mutations. In this theoretical study, we suggest a radical reordering of the genetic code that maximizes the mutagenic potential of single nucleotide replacements. We explore several possible genetic codes that allow a greater degree of accessibility to the mutational landscape and may result in a hyperevolvable organism that could serve as an ideal platform for directed evolution experiments. We then conclude by evaluating the challenges of constructing such recoded organisms and their potential applications within the field of synthetic biology.

The conservative nature of the genetic code prevents bioengineers from efficiently accessing the full mutational landscape of a gene via common error-prone methods. Here, we present two computational approaches to generate alternative genetic codes with increased accessibility. These new codes allow mutational transitions to a larger pool of amino acids and with a greater extent of chemical differences, based on a single nucleotide replacement within the codon, thus increasing evolvability both at the single-gene and at the genome levels. Given the widespread use of these techniques for strain and protein improvement, along with more fundamental evolutionary biology questions, the use of recoded organisms that maximize evolvability should significantly improve the efficiency of directed evolution, library generation, and fitness maximization.

Genome Partitioner: A web tool for multi-level partitioning of large-scale DNA constructs for synthetic biology applications

Recent advances in lower-cost DNA synthesis techniques have enabled new innovations in the field of synthetic biology. Still, efficient design and higher-order assembly of genome-scale DNA constructs remains a labor-intensive process. Given the complexity, computer assisted design tools that fragment large DNA sequences into fabricable DNA blocks are needed to pave the way towards streamlined assembly of biological systems. Here, we present the Genome Partitioner software implemented as a web-based interface that permits multi-level partitioning of genome-scale DNA designs. Without the need for specialized computing skills, biologists can submit their DNA designs to a fully automated pipeline that generates the optimal retrosynthetic route for higher-order DNA assembly. To test the algorithm, we partitioned a 783 kb Caulobacter crescentus genome design. We validated the partitioning strategy by assembling a 20 kb test segment encompassing a difficult to synthesize DNA sequence. Successful assembly from 1 kb subblocks into the 20 kb segment highlights the effectiveness of the Genome Partitioner for reducing synthesis costs and timelines for higher-order DNA assembly. The Genome Partitioner is broadly applicable to translate DNA designs into ready to order sequences that can be assembled with standardized protocols, thus offering new opportunities to harness the diversity of microbial genomes for synthetic biology applications. The Genome Partitioner web tool can be accessed at https://christenlab.ethz.ch/GenomePartitioner.

Automated multiplex genome-scale engineering in yeast

Genome-scale engineering is indispensable in understanding and engineering microorganisms, but the current tools are mainly limited to bacterial systems. Here we report an automated platform for multiplex genome-scale engineering in Saccharomyces cerevisiae, an important eukaryotic model and widely used microbial cell factory. Standardized genetic parts encoding overexpression and knockdown mutations of >90% yeast genes are created in a single step from a full-length cDNA library. With the aid of CRISPR-Cas, these genetic parts are iteratively integrated into the repetitive genomic sequences in a modular manner using robotic automation. This system allows functional mapping and multiplex optimization on a genome scale for diverse phenotypes including cellulase expression, isobutanol production, glycerol utilization and acetic acid tolerance, and may greatly accelerate future genome-scale engineering endeavours in yeast.

High-throughput expression of animal venom toxins in Escherichia coli to generate a large library of oxidized disulphide-reticulated peptides for drug discovery

BACKGROUND

Animal venoms are complex molecular cocktails containing a wide range of biologically active disulphide-reticulated peptides that target, with high selectivity and efficacy, a variety of membrane receptors. Disulphide-reticulated peptides have evolved to display improved specificity, low immunogenicity and to show much higher resistance to degradation than linear peptides. These properties make venom peptides attractive candidates for drug development. However, recombinant expression of reticulated peptides containing disulphide bonds is challenging, especially when associated with the production of large libraries of bioactive molecules for drug screening. To date, as an alternative to artificial synthetic chemical libraries, no comprehensive recombinant libraries of natural venom peptides are accessible for high-throughput screening to identify novel therapeutics.

RESULTS

In the accompanying paper an efficient system for the expression and purification of oxidized disulphide-reticulated venom peptides in Escherichia coli is described. Here we report the development of a high-throughput automated platform, that could be adapted to the production of other families, to generate the largest ever library of recombinant venom peptides. The peptides were produced in the periplasm of E. coli using redox-active DsbC as a fusion tag, thus allowing the efficient formation of correctly folded disulphide bridges. TEV protease was used to remove fusion tags and recover the animal venom peptides in the native state. Globally, within nine months, out of a total of 4992 synthetic genes encoding a representative diversity of venom peptides, a library containing 2736 recombinant disulphide-reticulated peptides was generated. The data revealed that the animal venom peptides produced in the bacterial host were natively folded and, thus, are putatively biologically active.

CONCLUSIONS

Overall this study reveals that high-throughput expression of animal venom peptides in E. coli can generate large libraries of recombinant disulphide-reticulated peptides of remarkable interest for drug discovery programs.

Immobilized MutS-Mediated Error Removal of Microchip-Synthesized DNA

Applications of microchip-synthesized oligonucleotides for de novo gene synthesis are limited primarily by their high error rates. The mismatch binding protein MutS, which can specifically recognize and bind to mismatches, is one of the cheapest tools for error correction of synthetic DNA. Here, we describe a protocol for removing errors in microchip-synthesized oligonucleotides and for the assembly of DNA segments using these oligonucleotides. This protocol can also be used in traditional de novo gene DNA synthesis.

Physiological inputs regulate species-specific anatomy during embryogenesis and regeneration

A key problem in evolutionary developmental biology is identifying the sources of instructive information that determine species-specific anatomical pattern. Understanding the inputs to large-scale morphology is also crucial for efforts to manipulate pattern formation in regenerative medicine and synthetic bioengineering. Recent studies have revealed a physiological system of communication among cells that regulates pattern during embryogenesis and regeneration in vertebrate and invertebrate models. Somatic tissues form networks using the same ion channels, electrical synapses, and neurotransmitter mechanisms exploited by the brain for information-processing. Experimental manipulation of these circuits was recently shown to override genome default patterning outcomes, resulting in head shapes resembling those of other species in planaria and Xenopus. The ability to drastically alter macroscopic anatomy to that of other extant species, despite a wild-type genomic sequence, suggests exciting new approaches to the understanding and control of patterning. Here, we review these results and discuss hypotheses regarding non-genomic systems of instructive information that determine biological growth and form.

GENOME ENGINEERING. The Genome Project-Write

We need technology and an ethical framework for genome-scale engineering

Printing Peptide arrays with a complementary metal oxide semiconductor chip

: In this chapter, we discuss the state-of-the-art peptide array technologies, comparing the spot technique, lithographical methods, and microelectronic chip-based approaches. Based on this analysis, we describe a novel peptide array synthesis method with a microelectronic chip printer. By means of a complementary metal oxide semiconductor chip, charged bioparticles can be patterned on its surface. The bioparticles serve as vehicles to transfer molecule monomers to specific synthesis spots. Our chip offers 16,384 pixel electrodes on its surface with a spot-to-spot pitch of 100 μm. By switching the voltage of each pixel between 0 and 100 V separately, it is possible to generate arbitrary particle patterns for combinatorial molecule synthesis. Afterwards, the patterned chip surface serves as a printing head to transfer the particle pattern from its surface to a synthesis substrate. We conducted a series of proof-of-principle experiments to synthesize high-density peptide arrays. Our solid phase synthesis approach is based on the 9-fluorenylmethoxycarbonyl protection group strategy. After melting the particles, embedded monomers diffuse to the surface and participate in the coupling reaction to the surface. The method demonstrated herein can be easily extended to the synthesis of more complicated artificial molecules by using bioparticles with artificial molecular building blocks. The possibility of synthesizing artificial peptides was also shown in an experiment in which we patterned biotin particles in a high-density array format. These results open the road to the development of peptide-based functional modules for diverse applications in biotechnology.

Multiplexed Sequence Encoding: A Framework for DNA Communication

Synthetic DNA has great propensity for efficiently and stably storing non-biological information. With DNA writing and reading technologies rapidly advancing, new applications for synthetic DNA are emerging in data storage and communication. Traditionally, DNA communication has focused on the encoding and transfer of complete sets of information. Here, we explore the use of DNA for the communication of short messages that are fragmented across multiple distinct DNA molecules. We identified three pivotal points in a communication-data encoding, data transfer & data extraction-and developed novel tools to enable communication via molecules of DNA. To address data encoding, we designed DNA-based individualized keyboards (iKeys) to convert plaintext into DNA, while reducing the occurrence of DNA homopolymers to improve synthesis and sequencing processes. To address data transfer, we implemented a secret-sharing system-Multiplexed Sequence Encoding (MuSE)-that conceals messages between multiple distinct DNA molecules, requiring a combination key to reveal messages. To address data extraction, we achieved the first instance of chromatogram patterning through multiplexed sequencing, thereby enabling a new method for data extraction. We envision these approaches will enable more widespread communication of information via DNA.

Nucleic acid memory

Nucleic acid memory has a retention time far exceeding electronic memory. As an alternative storage media, DNA surpasses the information density and energy of operation offered by flash memory.

Phase-shift-controlled logic gates in Y-shaped nonlinearly coupled chains

We introduce a model system composed of two input discrete chains nonlinearly coupled to a single output chain which mimics the geometry of Y-shaped carbon nanotubes, photonic crystal wave guides, and DNA junctions. We explore the capability of the proposed system to perform logic gate operations based on the transmission of phase-shifted harmonic incoming waves. Within a tight-binding approach, we determine the exact transmission spectrum which exhibits a nonlinear induced bistability. Using a digitalization scheme of the output signal based on amplitude modulation, we show that AND, OR, and XOR logic operations can be achieved. Nonlinearity strongly favors the realization of logic operations in the regime of large wavelengths, while phase shifting is required for the OR logic gate to be realizable. A detailed analysis of the contrast ratio shows that optimal operation of the AND and OR logic gates takes place when the nonlinear response is the predominant physical property distinguishing the coupling and regular sites. These results point towards the possibility of Y-branched junctions to perform logic operations based on the transmission of traveling waves.

Combinatorial Evolution of Enzymes and Synthetic Pathways Using One-Step PCR

DNA engineering is the fundamental motive driving the rapid development of modern biotechnology. Here, we present a versatile evolution method termed "rapidly efficient combinatorial oligonucleotides for directed evolution" (RECODE) for rapidly introducing multiple combinatorial mutations to the target DNA by combined action of a thermostable high-fidelity DNA polymerase and a thermostable DNA Ligase in one reaction system. By applying this method, we rapidly constructed a variant library of the rpoS promoters (with activity of 8-460%), generated a novel heparinase from the highly specific leech hyaluronidase (with more than 30 mutant residues) and optimized the heme biosynthetic pathway by combinatorial evolution of regulatory elements and pathway enzymes (2500 ± 120 mg L(-1) with 20-fold increase). The simple RECODE method enabled researchers the unparalleled ability to efficiently create diverse mutant libraries for rapid evolution and optimization of enzymes and synthetic pathways.

Overcoming Challenges in Engineering the Genetic Code

Withstanding 3.5 billion years of genetic drift, the canonical genetic code remains such a fundamental foundation for the complexity of life that it is highly conserved across all three phylogenetic domains. Genome engineering technologies are now making it possible to rationally change the genetic code, offering resistance to viruses, genetic isolation from horizontal gene transfer, and prevention of environmental escape by genetically modified organisms. We discuss the biochemical, genetic, and technological challenges that must be overcome in order to engineer the genetic code.