Genomes by design

Enhanced eMAGE applied to identify genetic factors of nuclear hormone receptor dysfunction via combinatorial gene editing

Technologies that generate precise combinatorial genome modifications are well suited to dissect the polygenic basis of complex phenotypes and engineer synthetic genomes. Genome modifications with engineered nucleases can lead to undesirable repair outcomes through imprecise homology-directed repair, requiring non-cleavable gene editing strategies. Eukaryotic multiplex genome engineering (eMAGE) generates precise combinatorial genome modifications in Saccharomyces cerevisiae without generating DNA breaks or using engineered nucleases. Here, we systematically optimize eMAGE to achieve 90% editing frequency, reduce workflow time, and extend editing distance to 20 kb. We further engineer an inducible dominant negative mismatch repair system, allowing for high-efficiency editing via eMAGE while suppressing the elevated background mutation rate 17-fold resulting from mismatch repair inactivation. We apply these advances to construct a library of cancer-associated mutations in the ligand-binding domains of human estrogen receptor alpha and progesterone receptor to understand their impact on ligand-independent autoactivation. We validate that this yeast model captures autoactivation mutations characterized in human breast cancer models and further leads to the discovery of several previously uncharacterized autoactivating mutations. This work demonstrates the development and optimization of a cleavage-free method of genome editing well suited for applications requiring efficient multiplex editing with minimal background mutations.

Cofitness network connectivity determines a fuzzy essential zone in open bacterial pangenome

Most in silico evolutionary studies commonly assumed that core genes are essential for cellular function, while accessory genes are dispensable, particularly in nutrient-rich environments. However, this assumption is seldom tested genetically within the pangenome context. In this study, we conducted a robust pangenomic Tn-seq analysis of fitness genes in a nutrient-rich medium for Sinorhizobium strains with a canonical open pangenome. To evaluate the robustness of fitness category assignment, Tn-seq data for three independent mutant libraries per strain were analyzed by three methods, which indicates that the Hidden Markov Model (HMM)-based method is most robust to variations between mutant libraries and not sensitive to data size, outperforming the Bayesian and Monte Carlo simulation-based methods. Consequently, the HMM method was used to classify the fitness category. Fitness genes, categorized as essential (ES), advantage (GA), and disadvantage (GD) genes for growth, are enriched in core genes, while nonessential genes (NE) are over-represented in accessory genes. Accessory ES/GA genes showed a lower fitness effect than core ES/GA genes. Connectivity degrees in the cofitness network decrease in the order of ES, GD, and GA/NE. In addition to accessory genes, 1599 out of 3284 core genes display differential essentiality across test strains. Within the pangenome core, both shared quasi-essential (ES and GA) and strain-dependent fitness genes are enriched in similar functional categories. Our analysis demonstrates a considerable fuzzy essential zone determined by cofitness connectivity degrees in Sinorhizobium pangenome and highlights the power of the cofitness network in understanding the genetic basis of ever-increasing prokaryotic pangenome data.

High fidelity one-pot DNA assembly using orthogonal serine integrases

BACKGROUND

Large serine integrases (LSIs, derived from temperate phages) have been adapted for use in a multipart DNA assembly process in vitro, called serine integrase recombinational assembly (SIRA). The versatility, efficiency, and fidelity of SIRA is limited by lack of a sufficient number of LSIs whose activities have been characterized in vitro.

METHODS AND MAJOR RESULTS

In this report, we compared the activities in vitro of 10 orthogonal LSIs to explore their suitability for multiplex SIRA reactions. We found that Bxb1, ϕR4, and TG1 integrases were the most active among the set we studied, but several others were also usable. As proof of principle, we demonstrated high-efficiency one-pot assembly of six DNA fragments (made by PCR) into a 7.5 kb plasmid that expresses the enzymes of the β-carotenoid pathway in Escherichia coli, using six different LSIs. We further showed that a combined approach using a few highly active LSIs, each acting on multiple pairs of att sites with distinct central dinucleotides, can be used to scale up "poly-part" gene assembly and editing.

CONCLUSIONS AND IMPLICATIONS

We conclude that use of multiple orthogonal integrases may be the most predictable, efficient, and programmable approach for SIRA and other in vitro applications.

Understanding Metabolic Flux Behaviour in Whole-Cell Model Output

Whole-cell modelling is a newly expanding field that has many applications in lab experiment design and predictive drug testing. Although whole-cell model output contains a wealth of information, it is complex and high dimensional and thus hard to interpret. Here, we present an analysis pipeline that combines machine learning, dimensionality reduction, and network analysis to interpret and visualise metabolic reaction fluxes from a set of single gene knockouts simulated in the Mycoplasma genitalium whole-cell model. We found that the reaction behaviours show trends that correlate with phenotypic classes of the simulation output, highlighting particular cellular subsystems that malfunction after gene knockouts. From a graphical representation of the metabolic network, we saw that there is a set of reactions that can be used as markers of a phenotypic class, showing their importance within the network. Our analysis pipeline can support the understanding of the complexity of in silico cells without detailed knowledge of the constituent parts, which can help to understand the effects of gene knockouts and, as whole-cell models become more widely built and used, aid genome design.

Escherichia coli Data-Driven Strain Design Using Aggregated Adaptive Laboratory Evolution Mutational Data

Microbes are being engineered for an increasingly large and diverse set of applications. However, the designing of microbial genomes remains challenging due to the general complexity of biological systems. Adaptive Laboratory Evolution (ALE) leverages nature’s problem-solving processes to generate optimized genotypes currently inaccessible to rational methods. The large amount of public ALE data now represents a new opportunity for data-driven strain design. This study describes how novel strain designs, or genome sequences not yet observed in ALE experiments or published designs, can be extracted from aggregated ALE data and demonstrates this by designing, building, and testing three novel Escherichia coli strains with fitnesses comparable to ALE mutants. These designs were achieved through a meta-analysis of aggregated ALE mutations data (63 Escherichia coli K-12 MG1655 based ALE experiments, described by 93 unique environmental conditions, 357 independent evolutions, and 13 957 observed mutations), which additionally revealed global ALE mutation trends that inform on ALE-derived strain design principles. Such informative trends anticipate ALE-derived strain designs as largely gene-centric, as opposed to noncoding, and composed of a relatively small number of beneficial variants (approximately 6). These results demonstrate how strain design efforts can be enhanced by the meta-analysis of aggregated ALE data.

Potential of Producing Flavonoids Using Cyanobacteria As a Sustainable Chassis

Numerous plant secondary metabolites have remarkable impacts on both food supplements and pharmaceuticals for human health improvement. However, higher plants can only generate small amounts of these chemicals with specific temporal and spatial arrangements, which are unable to satisfy the expanding market demands. Cyanobacteria can directly utilize CO₂, light energy, and inorganic nutrients to synthesize versatile plant-specific photosynthetic intermediates and organic compounds in large-scale photobioreactors with outstanding economic merit. Thus, they have been rapidly developed as a "green" chassis for the synthesis of bioproducts. Flavonoids, chemical compounds based on aromatic amino acids, are considered to be indispensable components in a variety of nutraceutical, pharmaceutical, and cosmetic applications. In contrast to heterotrophic metabolic engineering pioneers, such as yeast and Escherichia coli, information about the biosynthesis flavonoids and their derivatives is less comprehensive than that of their photosynthetic counterparts. Here, we review both benefits and challenges to promote cyanobacterial cell factories for flavonoid biosynthesis. With increasing concerns about global environmental issues and food security, we are confident that energy self-supporting cyanobacteria will attract increasing attention for the generation of different kinds of bioproducts. We hope that the work presented here will serve as an index and encourage more scientists to join in the relevant research area.

Exploring and mapping chemical space with molecular assembly trees

The rule-based search of chemical space can generate an almost infinite number of molecules, but exploration of known molecules as a function of the minimum number of steps needed to build up the target graphs promises to uncover new motifs and transformations. Assembly theory is an approach to compare the intrinsic complexity and properties of molecules by the minimum number of steps needed to build up the target graphs. Here, we apply this approach to prebiotic chemistry, gene sequences, plasticizers, and opiates. This allows us to explore molecules connected to the assembly tree, rather than the entire space of molecules possible. Last, by developing a reassembly method, based on assembly trees, we found that in the case of the opiates, a new set of drug candidates could be generated that would not be accessible via conventional fragment-based drug design, thereby demonstrating how this approach might find application in drug discovery.

Centromere identity and function put to use: construction and transfer of mammalian artificial chromosomes to animal models

Mammalian artificial chromosomes (MACs) are widely used as gene expression vectors and have various advantages over conventional expression vectors. We review and discuss breakthroughs in MAC construction, initiation of functional centromeres allowing their faithful inheritance, and transfer from cell culture to animal model systems. These advances have contributed to advancements in synthetic biology, biomedical research, and applications in industry and in the clinic.

Site-Selective and Rewritable Labeling of DNA through Enzymatic, Reversible, and Click Chemistries

Current methods for bioconjugation rely on the introduction of stable linkers that lack the required versatility to perform sequential functionalizations. However, sequential manipulations are an increasing requirement in chemical biology because they can underpin multiple analyses of the same sample to provide a wider understanding of cell behavior. Here, we present a new method to site-selectively write, remove, and rewrite chemical functionality to a biomolecule, DNA in this case. Our method combines the precision and robustness of methyltransferase-directed labeling with the reversibility of acyl hydrazones and the efficiency of click chemistry. Underpinning the method is a new S-adenosyl-l-methionine derivative to site-selectively label DNA with a bifunctional chemical handle containing an acyl hydrazone-linker and a terminal azide. Functional tags are conjugated via the azide and can be removed (i.e., untagged) when needed at the acyl hydrazone via exchange with hydroxyl amine. The formed hydrazide-labeled DNA is a versatile intermediate that can be either rewritten to reset the original chemical handle or covalently reacted with a permanent tag. This ability to write, tag, untag, and permanently tag DNA is exploited to sequentially introduce two fluorescent dyes on DNA. Finally, we demonstrate the potential of the method by developing a protocol to sort labeled DNA using magnetic beads, with subsequent amplification of the sorted DNA sample for further analysis. The presented method opens new avenues for site-selective bioconjugation and should underpin integrative approaches in chemical biology where sequential functionalizations of the same sample are required.

Amplification of Salt-Induced Protein Diffusiophoresis by Varying Salt from Potassium to Sodium to Magnesium Chloride in Water

Salt-induced diffusiophoresis is the migration of a macromolecule or a colloidal particle induced by a concentration gradient of salt in water. Here, the effect of salt type on salt-induced diffusiophoresis of the protein lysozyme at pH 4.5 and 25 °C was examined as a function of salt concentration for three chloride salts: NaCl, KCl, and MgCl₂. Diffusiophoresis coefficients were calculated from experimental ternary diffusion coefficients on lysozyme-salt-water mixtures. In all cases, diffusiophoresis of this positively charged protein occurs from high to low salt concentration. An appropriate mass transfer process was theoretically examined to show that concentration gradients of MgCl₂ produce significant lysozyme diffusiophoresis. This is attributed to the relatively low mobility of Mg²⁺ ions compared to that of Cl^- ions at low salt concentration and a strong thermodynamic nonideality of this salt at high salt concentration. These findings indicate that MgCl₂ concentration gradients could be exploited for protein manipulation in solution (e.g., using microfluidic technologies) with applications to protein adsorption and purification. The dependence of lysozyme diffusiophoresis on salt type was theoretically examined and linked to protein charge. The effect of salts on hydrogen-ion titration curves was experimentally characterized to understand the role of salt type on protein charge. Our results indicate that binding of Mg²⁺ ions to lysozyme further enhances protein diffusiophoresis.

Recent insights into the genotype-phenotype relationship from massively parallel genetic assays

With the molecular revolution in Biology, a mechanistic understanding of the genotype-phenotype relationship became possible. Recently, advances in DNA synthesis and sequencing have enabled the development of deep mutational scanning assays, capable of scoring comprehensive libraries of genotypes for fitness and a variety of phenotypes in massively parallel fashion. The resulting empirical genotype-fitness maps pave the way to predictive models, potentially accelerating our ability to anticipate the behaviour of pathogen and cancerous cell populations from sequencing data. Besides from cellular fitness, phenotypes of direct application in industry (e.g. enzyme activity) and medicine (e.g. antibody binding) can be quantified and even selected directly by these assays. This review discusses the technological basis of and recent developments in massively parallel genetics, along with the trends it is uncovering in the genotype-phenotype relationship (distribution of mutation effects, epistasis), their possible mechanistic bases and future directions for advancing towards the goal of predictive genetics.

The Role of Orthogonality in Genetic Code Expansion

The genetic code defines how information in the genome is translated into protein. Aside from a handful of isolated exceptions, this code is universal. Researchers have developed techniques to artificially expand the genetic code, repurposing codons and translational machinery to incorporate nonstandard amino acids (nsAAs) into proteins. A key challenge for robust genetic code expansion is orthogonality; the engineered machinery used to introduce nsAAs into proteins must co-exist with native translation and gene expression without cross-reactivity or pleiotropy. The issue of orthogonality manifests at several levels, including those of codons, ribosomes, aminoacyl-tRNA synthetases, tRNAs, and elongation factors. In this concept paper, we describe advances in genome recoding, translational engineering and associated challenges rooted in establishing orthogonality needed to expand the genetic code.

Syntrophic co-culture amplification of production phenotype for high-throughput screening of microbial strain libraries

Microbes can be engineered to synthesize a wide array of bioproducts, yet production phenotype evaluation remains a frequent bottleneck in the design-build-test cycle where strain development requires iterative rounds of library construction and testing. Here, we present Syntrophic Co-culture Amplification of Production phenotype (SnoCAP). Through a metabolic cross-feeding circuit, the production level of a target molecule is translated into highly distinguishable co-culture growth characteristics, which amplifies differences in production into highly distinguishable growth phenotypes. We demonstrate SnoCAP with the screening of Escherichia coli strains for production of two target molecules: 2-ketoisovalerate, a precursor of the drop-in biofuel isobutanol, and L-tryptophan. The dynamic range of the screening can be tuned by employing an inhibitory analog of the target molecule. Screening based on this framework requires compartmentalization of individual producers with the sensor strain. We explore three formats of implementation with increasing throughput capability: confinement in microtiter plates (102-104 assays/experiment), spatial separation on agar plates (104-105 assays/experiment), and encapsulation in microdroplets (105-107 assays/experiment). Using SnoCAP, we identified an efficient isobutanol production strain from a random mutagenesis library, reaching a final titer that is 5-fold higher than that of the parent strain. The framework can also be extended to screening for secondary metabolite production using a push-pull strategy. We expect that SnoCAP can be readily adapted to the screening of various microbial species, to improve production of a wide range of target molecules.

ZeBRα a universal, multi-fragment DNA-assembly-system with minimal hands-on time requirement

The recently evolved field of synthetic biology has revolutionized the way we think of biology as an "engineerable" discipline. The newly sprouted branch is constantly in need of simple, cost-effective and automatable DNA-assembly methods. We have developed a reliable DNA-assembly system, ZeBRα (Zero-Background Redα), for cloning multiple DNA-fragments seamlessly with very high efficiency. The hallmarks of ZeBRα are the greatly reduced hands-on time and costs and yet excellent efficiency and flexibility. ZeBRα combines a "zero-background vector" with a highly efficient in vitro recombination method. The suicide-gene in the vector acts as placeholder, and is replaced by the fragments-of-interest, ensuring the exclusive survival of the successful recombinants. Thereby the background from uncut or re-ligated vector is absent and screening for recombinant colonies is unnecessary. Multiple fragments-of-interest can be assembled into the empty vector by a recombinogenic E. coli-lysate (SLiCE) with a total time requirement of less than 48 h. We have significantly simplified the preparation of the high recombination-competent E. coli-lysate compared to the original protocol. ZeBRα is the least labor intensive among comparable state-of-the-art assembly/cloning methods without a trade-off in efficiency.

History, Current State, and Emerging Applications of Industrial Biotechnology

The past 150 years have seen remarkable discoveries, rapidly growing biological knowledge, and giant technological leaps providing biotechnological solutions for healthcare, food production, and other societal needs. Genetic engineering, miniaturization, and ever-increasing computing power, in particular, have been key technological drivers for the past few decades. Looking ahead, the eventual transition from fossil resources to biomass and CO₂ demands a shift toward a 'bio-economy' based on novel production processes and engineered organisms.

Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow

Understanding the complex interactions of protein posttranslational modifications (PTMs) represents a major challenge in metabolic engineering, synthetic biology, and the biomedical sciences. Here, we present a workflow that integrates multiplex automated genome editing (MAGE), genome-scale metabolic modeling, and atomistic molecular dynamics to study the effects of PTMs on metabolic enzymes and microbial fitness. This workflow incorporates complementary approaches across scientific disciplines; provides molecular insight into how PTMs influence cellular fitness during nutrient shifts; and demonstrates how mechanistic details of PTMs can be explored at different biological scales. As a proof of concept, we present a global analysis of PTMs on enzymes in the metabolic network of Escherichia coli Based on our workflow results, we conduct a more detailed, mechanistic analysis of the PTMs in three proteins: enolase, serine hydroxymethyltransferase, and transaldolase. Application of this workflow identified the roles of specific PTMs in observed experimental phenomena and demonstrated how individual PTMs regulate enzymes, pathways, and, ultimately, cell phenotypes.

Upgrading aminoacyl-tRNA synthetases for genetic code expansion

Synthesis of proteins with non-canonical amino acids via genetic code expansion is at the forefront of synthetic biology. Progress in this field has enabled site-specific incorporation of over 200 chemically and structurally diverse amino acids into proteins in an increasing number of organisms. This has been facilitated by our ability to repurpose aminoacyl-tRNA synthetases to attach non-canonical amino acids to engineered tRNAs. Current efforts in the field focus on overcoming existing limitations to the simultaneous incorporation of multiple non-canonical amino acids or amino acids that differ from the l-α-amino acid structure (e.g. d-amino acid or β-amino acid). Here, we summarize the progress and challenges in developing more selective and efficient aminoacyl-tRNA synthetases for genetic code expansion.

A Novel Tool for Microbial Genome Editing Using the Restriction-Modification System

Scarless genetic manipulation of genomes is an essential tool for biological research. The restriction-modification (R-M) system is a defense system in bacteria that protects against invading genomes on the basis of its ability to distinguish foreign DNA from self DNA. Here, we designed an R-M system-mediated genome editing (RMGE) technique for scarless genetic manipulation in different microorganisms. For bacteria with Type IV REase, an RMGE technique using the inducible DNA methyltransferase gene, bceSIIM (RMGE-bceSIIM), as the counter-selection cassette was developed to edit the genome of Escherichia coli. For bacteria without Type IV REase, an RMGE technique based on a restriction endonuclease (RMGE-mcrA) was established in Bacillus subtilis. These techniques were successfully used for gene deletion and replacement with nearly 100% counter-selection efficiencies, which were higher and more stable compared to conventional methods. Furthermore, precise point mutation without limiting sites was achieved in E. coli using RMGE-bceSIIM to introduce a single base mutation of A128C into the rpsL gene. In addition, the RMGE-mcrA technique was applied to delete the CAN1 gene in Saccharomyces cerevisiae DAY414 with 100% counter-selection efficiency. The effectiveness of the RMGE technique in E. coli, B. subtilis, and S. cerevisiae suggests the potential universal usefulness of this technique for microbial genome manipulation.

Beyond editing to writing large genomes

Recent exponential advances in genome sequencing and engineering technologies have enabled an unprecedented level of interrogation into the impact of DNA variation (genotype) on cellular function (phenotype). Furthermore, these advances have also prompted realistic discussion of writing and radically re-writing complex genomes. In this Perspective, we detail the motivation for large-scale engineering, discuss the progress made from such projects in bacteria and yeast and describe how various genome-engineering technologies will contribute to this effort. Finally, we describe the features of an ideal platform and provide a roadmap to facilitate the efficient writing of large genomes.

Nucleosomal organization and DNA base composition patterns

Nucleosomes are the basic units of chromatin. They compact the genome inside the nucleus and regulate the access of proteins to DNA. In the yeast genome, most nucleosomes occupy well-defined positions, which are maintained under many different physiological situations and genetic backgrounds. Although several short sequence elements have been described that favor or reduce the affinity between histones and DNA, the extent to which the DNA sequence affects nucleosome positioning in the genomic context remains unclear. Recent analyses indicate that the base composition pattern of mononucleosomal DNA differs among species, and that the same sequence elements have a different impact on nucleosome positioning in different genomes despite the high level of phylogenetic conservation of histones. These studies have also shown that the DNA sequence contributes to nucleosome positioning to the point that it is possible to design synthetic DNA molecules capable of generating regular and species-specific nucleosomal patterns in vivo.

Millstone: software for multiplex microbial genome analysis and engineering

Inexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. We describe Millstone, a web-based platform that automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab.

Biofuel metabolic engineering with biosensors

Metabolic engineering offers the potential to renewably produce important classes of chemicals, particularly biofuels, at an industrial scale. DNA synthesis and editing techniques can generate large pathway libraries, yet identifying the best variants is slow and cumbersome. Traditionally, analytical methods like chromatography and mass spectrometry have been used to evaluate pathway variants, but such techniques cannot be performed with high throughput. Biosensors - genetically encoded components that actuate a cellular output in response to a change in metabolite concentration - are therefore a promising tool for rapid and high-throughput evaluation of candidate pathway variants. Applying biosensors can also dynamically tune pathways in response to metabolic changes, improving balance and productivity. Here, we describe the major classes of biosensors and briefly highlight recent progress in applying them to biofuel-related metabolic pathway engineering.

Nucleosomal signatures impose nucleosome positioning in coding and noncoding sequences in the genome

In the yeast genome, a large proportion of nucleosomes occupy well-defined and stable positions. While the contribution of chromatin remodelers and DNA binding proteins to maintain this organization is well established, the relevance of the DNA sequence to nucleosome positioning in the genome remains controversial. Through quantitative analysis of nucleosome positioning, we show that sequence changes distort the nucleosomal pattern at the level of individual nucleosomes in three species of Schizosaccharomyces and in Saccharomyces cerevisiae. This effect is equally detected in transcribed and nontranscribed regions, suggesting the existence of sequence elements that contribute to positioning. To identify such elements, we incorporated information from nucleosomal signatures into artificial synthetic DNA molecules and found that they generated regular nucleosomal arrays indistinguishable from those of endogenous sequences. Strikingly, this information is species-specific and can be combined with coding information through the use of synonymous codons such that genes from one species can be engineered to adopt the nucleosomal organization of another. These findings open the possibility of designing coding and noncoding DNA molecules capable of directing their own nucleosomal organization.

Emerging developmental genetic model systems in holometabolous insects

The number of insect species that are amenable to functional genetic studies is growing rapidly and provides many new research opportunities in developmental and evolutionary biology. The holometabolous insects represent a disproportionate percentage of animal diversity and are thus well positioned to provide model species for a wide variety of developmental processes. Here we discuss emerging holometabolous models, and review some recent breakthroughs. For example, flies and midges were found to use structurally unrelated long-range pattern organizers, butterflies and moths revealed extensive pattern formation during oogenesis, new imaging possibilities in the flour beetle Tribolium castaneum showed how embryos break free of their extraembryonic membranes, and the complex genetics governing interspecies difference in head shape were revealed in Nasonia wasps.

GENOME ENGINEERING. The Genome Project-Write

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

How does plant chemical diversity contribute to biodiversity at higher trophic levels?

Plants, perhaps Earth's most accomplished chemists, produce thousands of specialized metabolites having no direct role in cell division or growth. These phytochemicals vary by taxon, with many taxa producing characteristic substance classes; and within taxa, with individual variation in structural variety and production patterns. Observations of corresponding variation in herbivore metabolism, behavior, and diet breadth motivated the development of chemical ecology research. We discuss the importance of plant biodiversity in general and phytochemical diversity in particular for biodiversity and ecological interactions at higher trophic levels. We then provide an overview of the descriptive, molecular and analytical tools which allow modern biologists to investigate phytochemical diversity and its effects on higher trophic levels, from physiological mechanisms to ecological communities.

Site-specific recombinases: molecular machines for the Genetic Revolution

The fields of molecular genetics, biotechnology and synthetic biology are demanding ever more sophisticated molecular tools for programmed precise modification of cell genomic DNA and other DNA sequences. This review presents the current state of knowledge and development of one important group of DNA-modifying enzymes, the site-specific recombinases (SSRs). SSRs are Nature's 'molecular machines' for cut-and-paste editing of DNA molecules by inserting, deleting or inverting precisely defined DNA segments. We survey the SSRs that have been put to use, and the types of applications for which they are suitable. We also discuss problems associated with uses of SSRs, how these problems can be minimized, and how recombinases are being re-engineered for improved performance and novel applications.

Small Genetic Circuits and MicroRNAs: Big Players in Polymerase II Transcriptional Control in Plants

RNA Polymerase II (Pol II) regulatory cascades involving transcription factors (TFs) and their targets orchestrate the genetic circuitry of every eukaryotic organism. In order to understand how these cascades function, they can be dissected into small genetic networks, each containing just a few Pol II transcribed genes, that generate specific signal-processing outcomes. Small RNA regulatory circuits involve direct regulation of a small RNA by a TF and/or direct regulation of a TF by a small RNA and have been shown to play unique roles in many organisms. Here, we will focus on small RNA regulatory circuits containing Pol II transcribed microRNAs (miRNAs). While the role of miRNA-containing regulatory circuits as modular building blocks for the function of complex networks has long been on the forefront of studies in the animal kingdom, plant studies are poised to take a lead role in this area because of their advantages in probing transcriptional and posttranscriptional control of Pol II genes. The relative simplicity of tissue- and cell-type organization, miRNA targeting, and genomic structure make the Arabidopsis thaliana plant model uniquely amenable for small RNA regulatory circuit studies in a multicellular organism. In this Review, we cover analysis, tools, and validation methods for probing the component interactions in miRNA-containing regulatory circuits. We then review the important roles that plant miRNAs are playing in these circuits and summarize methods for the identification of small genetic circuits that strongly influence plant function. We conclude by noting areas of opportunity where new plant studies are imminently needed.

CRISPR/Cas9 advances engineering of microbial cell factories

One of the key drivers for successful metabolic engineering in microbes is the efficacy by which genomes can be edited. As such there are many methods to choose from when aiming to modify genomes, especially those of model organisms like yeast and bacteria. In recent years, clustered regularly interspaced palindromic repeats (CRISPR) and its associated proteins (Cas) have become the method of choice for precision genome engineering in many organisms due to their orthogonality, versatility and efficacy. Here we review the strategies adopted for implementation of RNA-guided CRISPR/Cas9 genome editing with special emphasis on their application for metabolic engineering of yeast and bacteria. Also, examples of how nuclease-deficient Cas9 has been applied for RNA-guided transcriptional regulation of target genes will be reviewed, as well as tools available for computer-aided design of guide-RNAs will be highlighted. Finally, this review will provide a perspective on the immediate challenges and opportunities foreseen by the use of CRISPR/Cas9 genome engineering and regulation in the context of metabolic engineering.

Industrial systems biology and its impact on synthetic biology of yeast cell factories

Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc.

Recent advances and versatility of MAGE towards industrial applications

The genome engineering toolkit has expanded significantly in recent years, allowing us to study the functions of genes in cellular networks and assist in over-production of proteins, drugs, chemicals and biofuels. Multiplex automated genome engineering (MAGE) has been recently developed and gained more scientific interest towards strain engineering. MAGE is a simple, rapid and efficient tool for manipulating genes simultaneously in multiple loci, assigning genetic codes and integrating non-natural amino acids. MAGE can be further expanded towards the engineering of fast, robust and over-producing strains for chemicals, drugs and biofuels at industrial scales.

Augmented genetic decoding: global, local and temporal alterations of decoding processes and codon meaning

The non-universality of the genetic code is now widely appreciated. Codes differ between organisms, and certain genes are known to alter the decoding rules in a site-specific manner. Recently discovered examples of decoding plasticity are particularly spectacular. These examples include organisms and organelles with disruptions of triplet continuity during the translation of many genes, viruses that alter the entire genetic code of their hosts and organisms that adjust their genetic code in response to changing environments. In this Review, we outline various modes of alternative genetic decoding and expand existing terminology to accommodate recently discovered manifestations of this seemingly sophisticated phenomenon.