Programming cells by multiplex genome engineering and accelerated evolution

Structural Basis for the Interaction of Redβ Single-Strand Annealing Protein with Escherichia coli Single-Stranded DNA-Binding Protein

Redβ is a protein from bacteriophage λ that binds to single-stranded DNA (ssDNA) to promote the annealing of complementary strands. Together with λ-exonuclease (λ-exo), Redβ is part of a two-component DNA recombination system involved in multiple aspects of genome maintenance. The proteins have been exploited in powerful methods for bacterial genome engineering in which Redβ can anneal an electroporated oligonucleotide to a complementary target site at the lagging strand of a replication fork. Successful annealing in vivo requires the interaction of Redβ with E. coli single-stranded DNA-binding protein (SSB), which coats the ssDNA at the lagging strand to coordinate access of numerous replication proteins. Previous mutational analysis revealed that the interaction between Redβ and SSB involves the C-terminal domain (CTD) of Redβ and the C-terminal tail of SSB (SSB-Ct), the site for binding of numerous host proteins. Here, we have determined the x-ray crystal structure of Redβ CTD in complex with a peptide corresponding to the last nine residues of SSB (MDFDDDIPF). Formation of the complex is predominantly mediated by hydrophobic interactions between two phenylalanine side chains of SSB (Phe-171 and Phe-177) and an apolar groove on the CTD, combined with electrostatic interactions between the C-terminal carboxylate of SSB and Lys-214 of the CTD. Mutation of any of these residues to alanine significantly disrupts the interaction of full-length Redβ and SSB proteins. Structural knowledge of this interaction will help to expand the utility of Redβ-mediated recombination to a wider range of bacterial hosts for applications in synthetic biology.

Genome engineering on size reduction and complexity simplification: A review

BACKGROUND

Genome simplification is an important topic in the field of life sciences that has attracted attention from its conception to the present day. It can help uncover the essential components of the genome and, in turn, shed light on the underlying operating principles of complex biological systems. This has made it a central focus of both basic and applied research in the life sciences. With the recent advancements in related technologies and our increasing knowledge of the genome, now is an opportune time to delve into this topic.

AIM OF REVIEW

Our review investigates the progress of genome simplification from two perspectives: genome size reduction and complexity simplification. In addition, we provide insights into the future development trends of genome simplification.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Reducing genome size requires eliminating non-essential elements as much as possible. This process has been facilitated by advances in genome manipulation and synthesis techniques. However, we still need a better and clearer understanding of living systems to reduce genome complexity. As there is a lack of quantitative and clearly defined standards for this task, we have opted to approach the topic from various perspectives and present our findings accordingly.

Optimizing enzyme properties to enhance dihydroxyacetone production via methylglyoxal biosensor development

BACKGROUND

Dihydroxyacetone (DHA) stands as a crucial chemical material extensively utilized in the cosmetics industry. DHA production through the dephosphorylation of dihydroxyacetone phosphate, an intermediate product of the glycolysis pathway in Escherichia coli, presents a prospective alternative for industrial production. However, insights into the pivotal enzyme, dihydroxyacetone phosphate dephosphorylase (HdpA), remain limited for informed engineering. Consequently, the development of an efficient tool for high-throughput screening of HdpA hypermutants becomes imperative.

RESULTS

This study introduces a methylglyoxal biosensor, based on the formaldehyde-responding regulator FrmR, for the selection of HdpA. Initial modifications involved the insertion of the FrmR binding site upstream of the -35 region and into the spacer region between the -10 and -35 regions of the constitutive promoter J23110. Although the hybrid promoter retained constitutive expression, expression of FrmR led to complete repression. The addition of 350 μM methylglyoxal promptly alleviated FrmR inhibition, enhancing promoter activity by more than 40-fold. The methylglyoxal biosensor system exhibited a gradual increase in fluorescence intensity with methylglyoxal concentrations ranging from 10 to 500 μM. Notably, the biosensor system responded to methylglyoxal spontaneously converted from added DHA, facilitating the separation of DHA producing and non-producing strains through flow cytometry sorting. Subsequently, the methylglyoxal biosensor was successfully applied to screen a library of HdpA mutants, identifying two strains harboring specific mutants 267G > T and D110G/G151C that showed improved DHA production by 68% and 114%, respectively. Expressing of these two HdpA mutants directly in a DHA-producing strain also increased DHA production from 1.45 to 1.92 and 2.29 g/L, respectively, demonstrating the enhanced enzyme properties of the HdpA mutants.

CONCLUSIONS

The methylglyoxal biosensor offers a novel strategy for constructing genetically encoded biosensors and serves as a robust platform for indirectly determining DHA levels by responding to methylglyoxal. This property enables efficiently screening of HdpA hypermutants to enhance DHA production.

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.

Synthetic Genomics: Repurposing Biological Systems for Applications in Engineering Biology

Substantial improvements in DNA sequencing and synthesis technologies and increased understanding of genome biology have empowered the development of synthetic genomics. The ability to design and construct engineered living cells boosted up by synthetic chromosomes provides opportunities to tackle enormous current and future challenges faced by humanity and the planet. Here we review the progresses, considerations, challenges, and future direction of the "design-build-test-learn" cycle used in synthetic genomics. We also discuss future applications enabled by synthetic genomics as this emerging field shapes and revolutionizes biomanufacturing and biomedicine.

Engineering the Signal Resolution of a Paper-Based Cell-Free Glutamine Biosensor with Genetic Engineering, Metabolic Engineering, and Process Optimization

Specialized cancer treatments have the potential to exploit glutamine dependence to increase patient survival rates. Glutamine diagnostics capable of tracking a patient's response to treatment would enable a personalized treatment dosage to optimize the tradeoff between treatment success and dangerous side effects. Current clinical glutamine testing requires sophisticated and expensive lab-based tests, which are not broadly available on a frequent, individualized basis. To address the need for a low-cost, portable glutamine diagnostic, this work engineers a cell-free glutamine biosensor to overcome assay background and signal-to-noise limitations evident in previously reported studies. The findings from this work culminate in the development of a shelf-stable, paper-based, colorimetric glutamine test with a high signal strength and a high signal-to-background ratio for dramatically improved signal resolution. While the engineered glutamine test is important progress towards improving the management of cancer and other health conditions, this work also expands the assay development field of the promising cell-free biosensing platform, which can facilitate the low-cost detection of a broad variety of target molecules with high clinical value.

ORBIT for E. coli: kilobase-scale oligonucleotide recombineering at high throughput and high efficiency

Microbiology and synthetic biology depend on reverse genetic approaches to manipulate bacterial genomes; however, existing methods require molecular biology to generate genomic homology, suffer from low efficiency, and are not easily scaled to high throughput. To overcome these limitations, we developed a system for creating kilobase-scale genomic modifications that uses DNA oligonucleotides to direct the integration of a non-replicating plasmid. This method, Oligonucleotide Recombineering followed by Bxb-1 Integrase Targeting (ORBIT) was pioneered in Mycobacteria, and here we adapt and expand it for Escherichia coli. Our redesigned plasmid toolkit for oligonucleotide recombineering achieved significantly higher efficiency than λ Red double-stranded DNA recombineering and enabled precise, stable knockouts (≤134 kb) and integrations (≤11 kb) of various sizes. Additionally, we constructed multi-mutants in a single transformation, using orthogonal attachment sites. At high throughput, we used pools of targeting oligonucleotides to knock out nearly all known transcription factor and small RNA genes, yielding accurate, genome-wide, single mutant libraries. By counting genomic barcodes, we also show ORBIT libraries can scale to thousands of unique members (>30k). This work demonstrates that ORBIT for E. coli is a flexible reverse genetic system that facilitates rapid construction of complex strains and readily scales to create sophisticated mutant libraries.

Mobile genetic element-based gene editing and genome engineering: Recent advances and applications

Genome engineering has revolutionized several scientific fields, ranging from biochemistry and fundamental research to therapeutic uses and crop development. Diverse engineering toolkits have been developed and used to effectively modify the genome sequences of organisms. However, there is a lack of extensive reviews on genome engineering technologies based on mobile genetic elements (MGEs), which induce genetic diversity within host cells by changing their locations in the genome. This review provides a comprehensive update on the versatility of MGEs as powerful genome engineering tools that offers efficient solutions to challenges associated with genome engineering. MGEs, including DNA transposons, retrotransposons, retrons, and CRISPR-associated transposons, offer various advantages, such as a broad host range, genome-wide mutagenesis, efficient large-size DNA integration, multiplexing capabilities, and in situ single-stranded DNA generation. We focused on the components, mechanisms, and features of each MGE-based tool to highlight their cellular applications. Finally, we discussed the current challenges of MGE-based genome engineering and provided insights into the evolving landscape of this transformative technology. In conclusion, the combination of genome engineering with MGE demonstrates remarkable potential for addressing various challenges and advancing the field of genetic manipulation, and promises to revolutionize our ability to engineer and understand the genomes of diverse organisms.

Establishing comprehensive quaternary structural proteomes from genome sequence

A critical body of knowledge has developed through advances in protein microscopy, protein-fold modeling, structural biology software, availability of sequenced bacterial genomes, large-scale mutation databases, and genome-scale models. Based on these recent advances, we develop a computational framework that; i) identifies the oligomeric structural proteome encoded by an organism's genome from available structural resources; ii) maps multi-strain alleleomic variation, resulting in the structural proteome for a species; and iii) calculates the 3D orientation of proteins across subcellular compartments with residue-level precision. Using the platform, we; iv) compute the quaternary E. coli K-12 MG1655 structural proteome; v) use a dataset of 12,000 mutations to build Random Forest classifiers that can predict the severity of mutations; and, in combination with a genome-scale model that computes proteome allocation, vi) obtain the spatial allocation of the E. coli proteome. Thus, in conjunction with relevant datasets and increasingly accurate computational models, we can now annotate quaternary structural proteomes, at genome-scale, to obtain a molecular-level understanding of whole-cell functions.

Significance

Advancements in experimental and computational methods have revealed the shapes of multi-subunit proteins. The absence of a unified platform that maps actionable datatypes onto these increasingly accurate structures creates a barrier to structural analyses, especially at the genome-scale. Here, we describe QSPACE, a computational annotation platform that evaluates existing resources to identify the best-available structure for each protein in a user's query, maps the 3D location of actionable datatypes ( e.g. , active sites, published mutations) onto the selected structures, and uses third-party APIs to determine the subcellular compartment of all amino acids of a protein. As proof-of-concept, we deployed QSPACE to generate the quaternary structural proteome of E. coli MG1655 and demonstrate two use-cases involving large-scale mutant analysis and genome-scale modelling.

Automated in vivo enzyme engineering accelerates biocatalyst optimization

Achieving cost-competitive bio-based processes requires development of stable and selective biocatalysts. Their realization through in vitro enzyme characterization and engineering is mostly low throughput and labor-intensive. Therefore, strategies for increasing throughput while diminishing manual labor are gaining momentum, such as in vivo screening and evolution campaigns. Computational tools like machine learning further support enzyme engineering efforts by widening the explorable design space. Here, we propose an integrated solution to enzyme engineering challenges whereby ML-guided, automated workflows (including library generation, implementation of hypermutation systems, adapted laboratory evolution, and in vivo growth-coupled selection) could be realized to accelerate pipelines towards superior biocatalysts.

Plasmid-free cheater cells commonly evolve during laboratory growth

It has been nearly a century since the isolation and use of penicillin, heralding the discovery of a wide range of different antibiotics. In addition to clinical applications, such antibiotics have been essential laboratory tools, allowing for selection and maintenance of laboratory plasmids that encode cognate resistance genes. However, antibiotic resistance mechanisms can additionally function as public goods. For example, extracellular beta-lactamases produced by resistant cells that subsequently degrade penicillin and related antibiotics allow neighboring plasmid-free susceptible bacteria to survive antibiotic treatment. How such cooperative mechanisms impact selection of plasmids during experiments in laboratory conditions is poorly understood. Here, we show in multiple bacterial species that the use of plasmid-encoded beta-lactamases leads to significant curing of plasmids in surface-grown bacteria. Furthermore, such curing was also evident for aminoglycoside phosphotransferase and tetracycline antiporter resistance mechanisms. Alternatively, antibiotic selection in liquid growth led to more robust plasmid maintenance, although plasmid loss was still observed. The net outcome of such plasmid loss is the generation of a heterogenous population of plasmid-containing and plasmid-free cells, leading to experimental confounds that are not widely appreciated.IMPORTANCEPlasmids are routinely used in microbiology as readouts of cell biology or tools to manipulate cell function. Central to these studies is the assumption that all cells in an experiment contain the plasmid. Plasmid maintenance in a host cell typically depends on a plasmid-encoded antibiotic resistance marker, which provides a selective advantage when the plasmid-containing cell is grown in the presence of antibiotic. Here, we find that growth of plasmid-containing bacteria on a surface and to a lesser extent in liquid culture in the presence of three distinct antibiotic families leads to the evolution of a significant number of plasmid-free cells, which rely on the resistance mechanisms of the plasmid-containing cells. This process generates a heterogenous population of plasmid-free and plasmid-containing bacteria, an outcome which could confound further experimentation.

Engineering Microorganisms for Cancer Immunotherapy

Cancer immunotherapy presents a promising approach to fight against cancer by utilizing the immune system. Recently, engineered microorganisms have emerged as a potential strategy in cancer immunotherapy. These microorganisms, including bacteria and viruses, can be designed and modified using synthetic biology and genetic engineering techniques to target cancer cells and modulate the immune system. This review delves into various microorganism-based therapies for cancer immunotherapy, encompassing strategies for enhancing efficacy while ensuring safety and ethical considerations. The development of these therapies holds immense potential in offering innovative personalized treatments for cancer.

Employing synthetic biology to expand antibiotic discovery

Antimicrobial-resistant (AMR) bacterial pathogens are a continually growing threat as our methods for combating these infections continue to be overcome by the evolution of resistance mechanisms. Recent therapeutic methods have not staved off the concern of AMR infections, so continued research focuses on new ways of identifying small molecules to treat AMR pathogens. While chemical modification of existing antibiotics is possible, there has been rapid development of resistance by pathogens that were initially susceptible to these compounds. Synthetic biology is becoming a key strategy in trying to predict and induce novel, natural antibiotics. Advances in cloning and mutagenesis techniques applied through a synthetic biology lens can help characterize the native regulation of antibiotic biosynthetic gene clusters (BGCs) to identify potential modifications leading to more potent antibiotic activity. Additionally, many cryptic antibiotic BGCs are derived from non-ribosomal peptide synthase (NRPS) and polyketide synthase (PKS) biosynthetic pathways; complex, clustered genetic sequences that give rise to amino acid-derived natural products. Synthetic biology can be applied to modify and metabolically engineer these enzyme-based systems to promote rapid and sustainable production of natural products and their variants. This review will focus on recent advances related to synthetic biology as applied to genetic pathway characterization and identification of antibiotics from naturally occurring BGCs. Specifically, we will summarize recent efforts to characterize BGCs via general genomic mutagenesis, endogenous gene expression, and heterologous gene expression.

Microbial production of branched chain amino acids: Advances and perspectives

Branched-chain amino acids (BCAAs) such as L-valine, L-leucine, and L-isoleucine are widely used in food and feed. To comply with sustainable development goals, commercial production of BCAAs has been completely replaced with microbial fermentation. However, the efficient production of BCAAs by microorganisms remains a serious challenge due to their staggered metabolic networks and cell growth. To overcome these difficulties, systemic metabolic engineering has emerged as an effective and feasible strategy for the biosynthesis of BCAA. This review firstly summarizes the research advances in the microbial synthesis of BCAAs and representative engineering strategies. Second, systematic methods, such as high-throughput screening, adaptive laboratory evolution, and omics analysis, can be used to analyses the synthesis of BCAAs at the whole-cell level and further improve the titer of target chemicals. Finally, new tools and engineering strategies that may increase the production output and development direction of the microbial production of BCAAs are discussed.

Mutagenesis techniques for evolutionary engineering of microbes - exploiting CRISPR-Cas, oligonucleotides, recombinases, and polymerases

The natural process of evolutionary adaptation is often exploited as a powerful tool to obtain microbes with desirable traits. For industrial microbes, evolutionary engineering is often used to generate variants that show increased yields or resistance to stressful industrial environments, thus obtaining superior microbial cell factories. However, even in large populations, the natural supply of beneficial mutations is typically low, which implies that obtaining improved microbes is often time-consuming and inefficient. To overcome this limitation, different techniques have been developed that boost mutation rates. While some of these methods simply increase the overall mutation rate across a genome, others use recent developments in DNA synthesis, synthetic biology, and CRISPR-Cas techniques to control the type and location of mutations. This review summarizes the most important recent developments and methods in the field of evolutionary engineering in model microorganisms. It discusses how both in vitro and in vivo approaches can increase the genetic diversity of the host, with a special emphasis on in vivo techniques for the optimization of metabolic pathways for precision fermentation.

Bacterial genome engineering using CRISPR-associated transposases

Clustered regularly interspaced short palindromic repeats (CRISPR)-associated transposases have the potential to transform the technology landscape for kilobase-scale genome engineering, by virtue of their ability to integrate large genetic payloads with high accuracy, easy programmability and no requirement for homologous recombination machinery. These transposons encode efficient, CRISPR RNA-guided transposases that execute genomic insertions in Escherichia coli at efficiencies approaching ~100%. Moreover, they generate multiplexed edits when programmed with multiple guides, and function robustly in diverse Gram-negative bacterial species. Here we present a detailed protocol for engineering bacterial genomes using CRISPR-associated transposase (CAST) systems, including guidelines on the available vectors, customization of guide RNAs and DNA payloads, selection of common delivery methods, and genotypic analysis of integration events. We further describe a computational CRISPR RNA design algorithm to avoid potential off-targets, and a CRISPR array cloning pipeline for performing multiplexed DNA insertions. The method presented here allows the isolation of clonal strains containing a novel genomic integration event of interest within 1-2 weeks using available plasmid constructs and standard molecular biology techniques.

The non-mevalonate pathway requires a delicate balance of intermediates to maximize terpene production

Terpenes are valuable industrial chemicals whose demands are increasingly being met by bioengineering microbes such as E. coli. Although the bioengineering efforts commonly involve installing the mevalonate (MVA) pathway in E. coli for terpene production, the less studied methylerythritol phosphate (MEP) pathway is a more attractive target due to its higher energy efficiency and theoretical yield, despite its tight regulation. In this study, we integrated an additional copy of the entire MEP pathway into the E. coli genome for stable, marker-free terpene production. The genomically integrated strain produced more monoterpene geraniol than a plasmid-based system. The pathway genes' transcription was modulated using different promoters to produce geraniol as the reporter of the pathway flux. Pathway genes, including dxs, idi, and ispDF, expressed from a medium-strength promoter, led to the highest geraniol production. Quantifying the MEP pathway intermediates revealed that the highest geraniol producers had high levels of isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP), but moderate levels of the pathway intermediates upstream of these two building blocks. A principal component analysis demonstrated that 1-deoxy-D-xylulose 5-phosphate (DXP), the product of the first enzyme of the pathway, was critical for determining the geraniol titer, whereas MEP, the product of DXP reductoisomerase (Dxr or IspC), was the least essential. This work shows that an intricate balance of the MEP pathway intermediates determines the terpene yield in engineered E. coli. The genetically stable and intermediate-balanced strains created in this study will serve as a chassis for producing various terpenes. KEY POINTS: • Genome-integrated MEP pathway afforded higher strain stability • Genome-integrated MEP pathway produced more terpene than the plasmid-based system • High monoterpene production requires a fine balance of MEP pathway intermediates.

Carbon recycling with synthetic CO2 fixation pathways

Carbon dioxide (CO2) is the node of alleviating global climate change and supporting living organisms on Earth. Currently, the warming climate and the growing population demand enhanced CO2 fixation for a sustainable future, which stimulates innovations in biotechnology to tackle these challenges. To this endeavor, synthetic biology and metabolic engineering are enabling a promising approach to engineer synthetic carbon fixation in heterotrophic organisms combining the advantages of both autotrophs and heterotrophs. Here, we review the current advances in constructing synthetic CO2 fixation pathways and discuss the underlying design principles with confronting challenges. Moreover, we highlight the application scenarios of these designs at different concentrations of CO2, and how sustainable bioproduction can be improved. We also foresee the future of engineering synthetic carbon fixation pathways for carbon recycling.

Competition-driven eco-evolutionary feedback reshapes bacteriophage lambda's fitness landscape and enables speciation

A major challenge in evolutionary biology is explaining how populations navigate rugged fitness landscapes without getting trapped on local optima. One idea illustrated by adaptive dynamics theory is that as populations adapt, their newly enhanced capacities to exploit resources alter fitness payoffs and restructure the landscape in ways that promote speciation by opening new adaptive pathways. While there have been indirect tests of this theory, to our knowledge none have measured how fitness landscapes deform during adaptation, or test whether these shifts promote diversification. Here, we achieve this by studying bacteriophage [Formula: see text], a virus that readily speciates into co-existing receptor specialists under controlled laboratory conditions. We use a high-throughput gene editing-phenotyping technology to measure [Formula: see text]'s fitness landscape in the presence of different evolved-[Formula: see text] competitors and find that the fitness effects of individual mutations, and their epistatic interactions, depend on the competitor. Using these empirical data, we simulate [Formula: see text]'s evolution on an unchanging landscape and one that recapitulates how the landscape deforms during evolution. [Formula: see text] heterogeneity only evolves in the shifting landscape regime. This study provides a test of adaptive dynamics, and, more broadly, shows how fitness landscapes dynamically change during adaptation, potentiating phenomena like speciation by opening new adaptive pathways.

Genome engineering of the human gut microbiome

The human gut microbiome, a complex ecosystem, significantly influences host health, impacting crucial aspects such as metabolism and immunity. To deepen our comprehension and control of the molecular mechanisms orchestrating the intricate interplay between gut commensal bacteria and human health, the exploration of genome engineering for gut microbes is a promising frontier. Nevertheless, the complexities and diversities inherent in the gut microbiome pose substantial challenges to the development of effective genome engineering tools for human gut microbes. In this comprehensive review, we provide an overview of the current progress and challenges in genome engineering of human gut commensal bacteria, whether executed in vitro or in situ. A specific focus is directed towards the advancements and prospects in cargo DNA delivery and high-throughput techniques. Additionally, we elucidate the immense potential of genome engineering methods to deepen our understanding of the human gut microbiome and engineer the microorganisms to enhance human health.

CRISPR-dCas13a system for programmable small RNAs and polycistronic mRNA repression in bacteria

Bacterial small RNAs (sRNAs) function in post-transcriptional regulatory responses to environmental changes. However, the lack of eukaryotic RNA interference-like machinery in bacteria has limited the systematic engineering of RNA repression. Here, we report the development of clustered regularly interspaced short palindromic repeats (CRISPR)-guided dead CRIPSR-associated protein 13a (dCas13a) ribonucleoprotein that utilizes programmable CRISPR RNAs (crRNAs) to repress trans-acting and cis-acting sRNA as the target, altering regulatory mechanisms and stress-related phenotypes. In addition, we implemented a modular loop engineering of the crRNA to promote modular repression of the target gene with 92% knockdown efficiency and a single base-pair mismatch specificity. With the engineered crRNAs, we achieved targetable single-gene repression in the polycistronic operon. For metabolic application, 102 crRNAs were constructed in the biofoundry and used for screening novel knockdown sRNA targets to improve lycopene (colored antioxidant) production in Escherichia coli. The CRISPR-dCas13a system will assist as a valuable systematic tool for the discovery of novel sRNAs and the fine-tuning of bacterial RNA repression in both scientific and industrial applications.

Transposons and CRISPR: Rewiring Gene Editing

CRISPR-Cas is driving a gene editing revolution because of its simple reprogramming. However, off-target effects and dependence on the double-strand break repair pathways impose important limitations. Because homology-directed repair acts primarily in actively dividing cells, many of the current gene correction/replacement approaches are restricted to a minority of cell types. Furthermore, current approaches display low efficiency upon insertion of large DNA cargos (e.g., sequences containing multiple gene circuits with tunable functionalities). Recent research has revealed new links between CRISPR-Cas systems and transposons providing new scaffolds that might overcome some of these limitations. Here, we comment on two new transposon-associated RNA-guided mechanisms considering their potential as new gene editing solutions. Initially, we focus on a group of small RNA-guided endonucleases of the IS200/IS605 family of transposons, which likely evolved into class 2 CRISPR effector nucleases (Cas9s and Cas12s). We explore the diversity of these nucleases (named OMEGA, obligate mobile element-guided activity) and analyze their similarities with class 2 gene editors. OMEGA nucleases can perform gene editing in human cells and constitute promising candidates for the design of new compact RNA-guided platforms. Then, we address the co-option of the RNA-guided activity of different CRISPR effector nucleases by a specialized group of Tn7-like transposons to target transposon integration. We describe the various mechanisms used by these RNA-guided transposons for target site selection and integration. Finally, we assess the potential of these new systems to circumvent some of the current gene editing challenges.

Metagenomics harvested genus-specific single-stranded DNA-annealing proteins improve and expand recombineering in Pseudomonas species

The widespread Pseudomonas genus comprises a collection of related species with remarkable abilities to degrade plastics and polluted wastes and to produce a broad set of valuable compounds, ranging from bulk chemicals to pharmaceuticals. Pseudomonas possess characteristics of tolerance and stress resistance making them valuable hosts for industrial and environmental biotechnology. However, efficient and high-throughput genetic engineering tools have limited metabolic engineering efforts and applications. To improve their genome editing capabilities, we first employed a computational biology workflow to generate a genus-specific library of potential single-stranded DNA-annealing proteins (SSAPs). Assessment of the library was performed in different Pseudomonas using a high-throughput pooled recombinase screen followed by Oxford Nanopore NGS analysis. Among different active variants with variable levels of allelic replacement frequency (ARF), efficient SSAPs were found and characterized for mediating recombineering in the four tested species. New variants yielded higher ARFs than existing ones in Pseudomonas putida and Pseudomonas aeruginosa, and expanded the field of recombineering in Pseudomonas taiwanensisand Pseudomonas fluorescens. These findings will enhance the mutagenesis capabilities of these members of the Pseudomonas genus, increasing the possibilities for biotransformation and enhancing their potential for synthetic biology applications.  .

Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments

Adaptive Laboratory Evolution (ALE) is a powerful tool for engineering and understanding microbial physiology. ALE relies on the selection and enrichment of mutations that enable survival or faster growth under a selective condition imposed by the experimental setup. Phenotypic fitness landscapes are often underpinned by complex genotypes involving multiple genes, with combinatorial positive and negative effects on fitness. Such genotype relationships result in mutational fitness landscapes with multiple local fitness maxima and valleys. Traversing local maxima to find a global maximum often requires an individual or sub-population of cells to traverse fitness valleys. Traversing involves gaining mutations that are not adaptive for a given local maximum but are necessary to 'peak shift' to another local maximum, or eventually a global maximum. Despite these relatively well understood evolutionary principles, and the combinatorial genotypes that underlie most metabolic phenotypes, the majority of applied ALE experiments are conducted using constant selection pressures. The use of constant pressure can result in populations becoming trapped within local maxima, and often precludes the attainment of optimum phenotypes associated with global maxima. Here, we argue that oscillating selection pressures is an easily accessible mechanism for traversing fitness landscapes in ALE experiments, and provide theoretical and practical frameworks for implementation.

Evolution and synthetic biology

Evolutionary observations have often served as an inspiration for biological design. Decoding of the central dogma of life at a molecular level and understanding of the cellular biochemistry have been elegantly used to engineer various synthetic biology applications, including building genetic circuits in vitro and in cells, building synthetic translational systems, and metabolic engineering in cells to biosynthesize and even bioproduce complex high-value molecules. Here, we review three broad areas of synthetic biology that are inspired by evolutionary observations: (i) combinatorial approaches toward cell-based biomolecular evolution, (ii) engineering interdependencies to establish microbial consortia, and (iii) synthetic immunology. In each of the areas, we will highlight the evolutionary premise that was central toward designing these platforms. These are only a subset of the examples where evolution and natural phenomena directly or indirectly serve as a powerful source of inspiration in shaping synthetic biology and biotechnology.

Microbial production of L-methionine and its precursors using systems metabolic engineering

L-methionine is an essential amino acid with versatile applications in food, feed, cosmetics and pharmaceuticals. At present, the production of L-methionine mainly relies on chemical synthesis, which conflicts with the concern over serious environmental problems and sustainable development goals. In recent years, microbial production of natural products has been amply rewarded with the emergence and rapid development of system metabolic engineering. However, efficient L-methionine production by microbial fermentation remains a great challenge due to its complicated biosynthetic pathway and strict regulatory mechanism. Additionally, the engineered production of L-methionine precursors, L-homoserine, O-succinyl-L-homoserine (OSH) and O-acetyl-L-homoserine (OAH), has also received widespread attention because they can be catalyzed to L-methionine via a high-efficiently enzymatic reaction in vitro, which is also a promising alternative to chemical route. This review provides a comprehensive overview on the recent advances in the microbial production of L-methionine and its precursors, highlighting the challenges and potential solutions for developing L-methionine microbial cell factories from the perspective of systems metabolic engineering, aiming to offer guidance for future engineering.

Physical Laboratory Automation in Synthetic Biology

Synthetic Biology has overcome many of the early challenges facing the field and is entering a systems era characterized by adoption of Design-Build-Test-Learn (DBTL) approaches. The need for automation and standardization to enable reproducible, scalable, and translatable research has become increasingly accepted in recent years, and many of the hardware and software tools needed to address these challenges are now in place or under development. However, the lack of connectivity between DBTL modules and barriers to access and adoption remain significant challenges to realizing the full potential of lab automation. In this review, we characterize and classify the state of automation in synthetic biology with a focus on the physical automation of experimental workflows. Though fully autonomous scientific discovery is likely a long way off, impressive progress has been made toward automating critical elements of experimentation by combining intelligent hardware and software tools. It is worth questioning whether total automation that removes humans entirely from the loop should be the ultimate goal, and considerations for appropriate automation versus total automation are discussed in this light while emphasizing areas where further development is needed in both contexts.

Rapid bacteria-phage coevolution drives the emergence of multiscale networks

Interactions between species catalyze the evolution of multiscale ecological networks, including both nested and modular elements that regulate the function of diverse communities. One common assumption is that such complex pattern formation requires spatial isolation or long evolutionary timescales. We show that multiscale network structure can evolve rapidly under simple ecological conditions without spatial structure. In just 21 days of laboratory coevolution, Escherichia coli and bacteriophage Φ21 coevolve and diversify to form elaborate cross-infection networks. By measuring ~10,000 phage-bacteria infections and testing the genetic basis of interactions, we identify the mechanisms that create each component of the multiscale pattern. Our results demonstrate how multiscale networks evolve in parasite-host systems, illustrating Darwin's idea that simple adaptive processes can generate entangled banks of ecological interactions.

Enhancing isoprenol production by systematically tuning metabolic pathways using CRISPR interference in E. coli

Regulation of metabolic gene expression is crucial for maximizing bioproduction titers. Recent engineering tools including CRISPR/Cas9, CRISPR interference (CRISPRi), and CRISPR activation (CRISPRa) have enabled effective knock-out, knock-down, and overexpression of endogenous pathway genes, respectively, for advanced strain engineering. CRISPRi in particular has emerged as a powerful tool for gene repression through the use of a deactivated Cas9 (dCas9) protein and target guide RNA (gRNA). By constructing gRNA arrays, CRISPRi has the capacity for multiplexed gene downregulation across multiple orthogonal pathways for enhanced bioproduction titers. In this study, we harnessed CRISPRi to downregulate 32 essential and non-essential genes in E. coli strains heterologously expressing either the original mevalonate pathway or isopentenyl diphosphate (IPP) bypass pathway for isoprenol biosynthesis. Isoprenol remains a candidate bioproduct both as a drop-in blend additive and as a precursor for the high-performance sustainable aviation fuel, 1,4-dimethylcyclooctane (DMCO). Of the 32 gRNAs targeting genes associated with isoprenol biosynthesis, a subset was found to vastly improve product titers. Construction of a multiplexed gRNA library based on single guide RNA (sgRNA) performance enabled simultaneous gene repression, yielding a 3 to 4.5-fold increase in isoprenol titer (1.82 ± 0.19 g/L) on M9-MOPS minimal medium. We then scaled the best performing CRISPRi strain to 2-L fed-batch cultivation and demonstrated translatable titer improvements, ultimately obtaining 12.4 ± 1.3 g/L isoprenol. Our strategy further establishes CRISPRi as a powerful tool for tuning metabolic flux in production hosts and that titer improvements are readily scalable with potential for applications in industrial bioproduction.

Molecular mechanism overview of metabolite biosynthesis in medicinal plants

Medicinal plants are essential and rich resources for plant-based medicines and new drugs. Increasing attentions are paid to the secondary metabolites of medicinal plants due to their unique biological activity, pharmacological action, and high utilization value. However, the development of medicinal plants is constrained by limited natural resources and an unclear understanding of the mechanisms underlying active medicinal ingredients, thereby rendering the utilization and exploration of secondary metabolites more challenging. Besides, with the advancement of research on biosynthesis and molecular metabolism of natural products from medicinal plants, the methods for studying the biological activity and pharmacological effects of these products are constantly evolving. In recent years, significant progress has been made in the biosynthetic pathways and related regulatory genes of secondary metabolites in medicinal plants, which has greatly advanced both basic research and the development of clinical applications for medicinal plants. In this review, we discuss the past two decades of international research on the development of medicinal plant resources, mainly focusing on the biosynthetic pathway of secondary metabolites, intracellular signal transduction processes, multi-omics applications, and the application of gene editing technology in related research progress. We also discuss future development trends to promote the deep mining and development of natural products from medicinal plants, providing a useful reference.

Large-scale pathway reconstruction and colorimetric screening accelerate cellular metabolism engineering

The capability to manipulate and analyze hard-wired metabolic pathways sets the pace at which we can engineer cellular metabolism. Here, we present a framework to extensively rewrite the central metabolic pathway for malonyl-CoA biosynthesis in yeast and readily assess malonyl-CoA output based on pathway-scale DNA reconstruction in combination with colorimetric screening (Pracs). We applied Pracs to generate and test millions of enzyme variants by introducing genetic mutations into the whole set of genes encoding the malonyl-CoA biosynthetic pathway and identified hundreds of beneficial enzyme mutants with increased malonyl-CoA output. Furthermore, the synthetic pathways reconstructed by randomly integrating these beneficial enzyme variants generated vast phenotypic diversity, with some displaying higher production of malonyl-CoA as well as other metabolites, such as carotenoids and betaxanthin, thus demonstrating the generic utility of Pracs to efficiently orchestrate central metabolism to optimize the production of different chemicals in various metabolic pathways. Pracs will be broadly useful to advance our ability to understand and engineer cellular metabolism.

Engineering the Maize Root Microbiome: A Rapid MoClo Toolkit and Identification of Potential Bacterial Chassis for Studying Plant-Microbe Interactions

Sustainably enhancing crop production is a global necessity to meet the escalating demand for staple crops while sustainably managing their associated carbon/nitrogen inputs. Leveraging plant-associated microbiomes is a promising avenue for addressing this demand. However, studying these communities and engineering them for sustainable enhancement of crop production have remained a challenge due to limited genetic tools and methods. In this work, we detail the development of the Maize Root Microbiome ToolKit (MRMTK), a rapid Modular Cloning (MoClo) toolkit that only takes 2.5 h to generate desired constructs (5400 potential plasmids) that replicate and express heterologous genes in Enterobacter ludwigii strain AA4 (Elu), Pseudomonas putida strain AA7 (Ppu), Herbaspirillum robiniae strain AA6 (Hro), Stenotrophomonas maltophilia strain AA1 (Sma), and Brucella pituitosa strain AA2 (Bpi), which comprise a model maize root synthetic community (SynCom). In addition to these genetic tools, we describe a highly efficient transformation protocol (107-109 transformants/μg of DNA) 1 for each of these strains. Utilizing this highly efficient transformation protocol, we identified endogenous Expression Sequences (ES; promoter and ribosomal binding sites) for each strain via genomic promoter trapping. Overall, MRMTK is a scalable and adaptable platform that expands the genetic engineering toolbox while providing a standardized, high-efficiency transformation method across a diverse group of root commensals. These results unlock the ability to elucidate and engineer plant-microbe interactions promoting plant growth for each of the 5 bacterial strains in this study.

Strategies to identify and edit improvements in synthetic genome segments episomally

Genome engineering projects often utilize bacterial artificial chromosomes (BACs) to carry multi-kilobase DNA segments at low copy number. However, all stages of whole-genome engineering have the potential to impose mutations on the synthetic genome that can reduce or eliminate the fitness of the final strain. Here, we describe improvements to a multiplex automated genome engineering (MAGE) protocol to improve recombineering frequency and multiplexability. This protocol was applied to recoding an Escherichia coli strain to replace seven codons with synonymous alternatives genome wide. Ten 44 402-47 179 bp de novo synthesized DNA segments contained in a BAC from the recoded strain were unable to complement deletion of the corresponding 33-61 wild-type genes using a single antibiotic resistance marker. Next-generation sequencing (NGS) was used to identify 1-7 non-recoding mutations in essential genes per segment, and MAGE in turn proved a useful strategy to repair these mutations on the recoded segment contained in the BAC when both the recoded and wild-type copies of the mutated genes had to exist by necessity during the repair process. Finally, two web-based tools were used to predict the impact of a subset of non-recoding missense mutations on strain fitness using protein structure and function calls.

High-resolution landscape of an antibiotic binding site

Antibiotic binding sites are located in important domains of essential enzymes and have been extensively studied in the context of resistance mutations; however, their study is limited by positive selection. Using multiplex genome engineering1 to overcome this constraint, we generate and characterize a collection of 760 single-residue mutants encompassing the entire rifampicin binding site of Escherichia coli RNA polymerase (RNAP). By genetically mapping drug-enzyme interactions, we identify an alpha helix where mutations considerably enhance or disrupt rifampicin binding. We find mutations in this region that prolong antibiotic binding, converting rifampicin from a bacteriostatic to bactericidal drug by inducing lethal DNA breaks. The latter are replication dependent, indicating that rifampicin kills by causing detrimental transcription-replication conflicts at promoters. We also identify additional binding site mutations that greatly increase the speed of RNAP.Fast RNAP depletes the cell of nucleotides, alters cell sensitivity to different antibiotics and provides a cold growth advantage. Finally, by mapping natural rpoB sequence diversity, we discover that functional rifampicin binding site mutations that alter RNAP properties or confer drug resistance occur frequently in nature.

From Saccharomyces cerevisiae to Ethanol: Unlocking the Power of Evolutionary Engineering in Metabolic Engineering Applications

Increased human population and the rapid decline of fossil fuels resulted in a global tendency to look for alternative fuel sources. Environmental concerns about fossil fuel combustion led to a sharp move towards renewable and environmentally friendly biofuels. Ethanol has been the primary fossil fuel alternative due to its low carbon emission rates, high octane content and comparatively facile microbial production processes. In parallel to the increased use of bioethanol in various fields such as transportation, heating and power generation, improvements in ethanol production processes turned out to be a global hot topic. Ethanol is by far the leading yeast output amongst a broad spectrum of bio-based industries. Thus, as a well-known platform microorganism and native ethanol producer, baker's yeast Saccharomyces cerevisiae has been the primary subject of interest for both academic and industrial perspectives in terms of enhanced ethanol production processes. Metabolic engineering strategies have been primarily adopted for direct manipulation of genes of interest responsible in mainstreams of ethanol metabolism. To overcome limitations of rational metabolic engineering, an alternative bottom-up strategy called inverse metabolic engineering has been widely used. In this context, evolutionary engineering, also known as adaptive laboratory evolution (ALE), which is based on random mutagenesis and systematic selection, is a powerful strategy to improve bioethanol production of S. cerevisiae. In this review, we focus on key examples of metabolic and evolutionary engineering for improved first- and second-generation S. cerevisiae bioethanol production processes. We delve into the current state of the field and show that metabolic and evolutionary engineering strategies are intertwined and many metabolically engineered strains for bioethanol production can be further improved by powerful evolutionary engineering strategies. We also discuss potential future directions that involve recent advancements in directed genome evolution, including CRISPR-Cas9 technology.

Enhanced absorbance detection system for online bacterial monitoring in digital microfluidics

We report a fully integrated digital microfluidic absorbance detection system with an enhanced sensitivity for online bacterial monitoring. Through a 100 μm gap in the chip, our optical detection system has a detection sensitivity for a BCA protein concentration of 0.1 mg mL-1. The absorbance detection limit of our system is 1.4 × 10-3 OD units, which is one order of magnitude better than that of the existing studies. The system's linear region is 0.1-7 mg mL-1, and the dynamic range is 0-25 mg mL-1. We measured the growth curves of wild-type and E. coli transformed with resistance plasmids and mixed at different ratios on chip. We sorted out the bacterial species including highly viable single cells based on the difference in absorbance data of growth curves. We explored the changes in the growth curves of E. coli under different concentrations of resistant media. In addition, we successfully screened for the optimal growth environment of the bacteria, in which the growth rate of PET30a-DH5α (in a medium with 33 μg mL-1 kanamycin resistance) was significantly higher than that of a 1 mg mL-1 resistance medium. In conclusion, the enhanced digital microfluidic absorbance detection system exhibits exceptional sensitivity, enabling precise bacterial monitoring and growth curve analysis, while also laying the foundation for DMF-based automated bioresearch platforms, thus advancing research in the life sciences.

Genomic characterization of rare earth binding by Shewanella oneidensis

Rare earth elements (REE) are essential ingredients of sustainable energy technologies, but separation of individual REE is one of the hardest problems in chemistry today. Biosorption, where molecules adsorb to the surface of biological materials, offers a sustainable alternative to environmentally harmful solvent extractions currently used for separation of rare earth elements (REE). The REE-biosorption capability of some microorganisms allows for REE separations that, under specialized conditions, are already competitive with solvent extractions, suggesting that genetic engineering could allow it to leapfrog existing technologies. To identify targets for genomic improvement we screened 3,373 mutants from the whole genome knockout collection of the known REE-biosorbing microorganism Shewanella oneidensis MR-1. We found 130 genes that increased biosorption of the middle REE europium, and 112 that reduced it. We verified biosorption changes from the screen for a mixed solution of three REE (La, Eu, Yb) using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) in solution conditions with a range of ionic strengths and REE concentrations. We identified 18 gene ontologies and 13 gene operons that make up key systems that affect biosorption. We found, among other things, that disruptions of a key regulatory component of the arc system (hptA), which regulates cellular response to anoxic environments and polysaccharide biosynthesis related genes (wbpQ, wbnJ, SO_3183) consistently increase biosorption across all our solution conditions. Our largest total biosorption change comes from our SO_4685, a capsular polysaccharide (CPS) synthesis gene, disruption of which results in an up to 79% increase in biosorption; and nusA, a transcriptional termination/anti-termination protein, disruption of which results in an up to 35% decrease in biosorption. Knockouts of glnA, pyrD, and SO_3183 produce small but significant increases (≈ 1%) in relative biosorption affinity for ytterbium over lanthanum in multiple solution conditions tested, while many other genes we explored have more complex binding affinity changes. Modeling suggests that while these changes to lanthanide biosorption selectivity are small, they could already reduce the length of repeated enrichment process by up to 27%. This broad exploratory study begins to elucidate how genetics affect REE-biosorption by S. oneidensis, suggests new areas of investigation for better mechanistic understanding of the membrane chemistry involved in REE binding, and offer potential targets for improving biosorption and separation of REE by genetic engineering.

Retron-mediated multiplex genome editing and continuous evolution in Escherichia coli

While there are several genome editing techniques available, few are suitable for dynamic and simultaneous mutagenesis of arbitrary targeted sequences in prokaryotes. Here, to address these limitations, we present a versatile and multiplex retron-mediated genome editing system (REGES). First, through systematic optimization of REGES, we achieve efficiency of ∼100%, 85 ± 3%, 69 ± 14% and 25 ± 14% for single-, double-, triple- and quadruple-locus genome editing, respectively. In addition, we employ REGES to generate pooled and barcoded variant libraries with degenerate RBS sequences to fine-tune the expression level of endogenous and exogenous genes, such as transcriptional factors to improve ethanol tolerance and biotin biosynthesis. Finally, we demonstrate REGES-mediated continuous in vivo protein evolution, by combining retron, polymerase-mediated base editing and error-prone transcription. By these case studies, we demonstrate REGES as a powerful multiplex genome editing and continuous evolution tool with broad applications in synthetic biology and metabolic engineering.

Competition-driven eco-evolutionary feedback reshapes bacteriophage lambda's fitness landscape and enables speciation

A major challenge in evolutionary biology is explaining how populations navigate rugged fitness landscapes without getting trapped on local optima. One idea illustrated by adaptive dynamics theory is that as populations adapt, their newly enhanced capacities to exploit resources alter fitness payoffs and restructure the landscape in ways that promote speciation by opening new adaptive pathways. While there have been indirect tests of this theory, none have measured how fitness landscapes deform during adaptation, or test whether these shifts promote diversification. Here, we achieve this by studying bacteriophage λ, a virus that readily speciates into co-existing receptor specialists under controlled laboratory conditions. We used a high-throughput gene editing-phenotyping technology to measure λ's fitness landscape in the presence of different evolved-λ competitors and found that the fitness effects of individual mutations, and their epistatic interactions, depend on the competitor. Using these empirical data, we simulated λ's evolution on an unchanging landscape and one that recapitulates how the landscape deforms during evolution. λ heterogeneity only evolved in the shifting landscape regime. This study provides a test of adaptive dynamics, and, more broadly, shows how fitness landscapes dynamically change during adaptation, potentiating phenomena like speciation by opening new adaptive pathways.

Simultaneous multi-site editing of individual genomes using retron arrays

Our understanding of genomics is limited by the scale of our genomic technologies. While libraries of genomic manipulations scaffolded on CRISPR gRNAs have been transformative, these existing approaches are typically multiplexed across genomes. Yet much of the complexity of real genomes is encoded within a genome across sites. Unfortunately, building cells with multiple, non-adjacent precise mutations remains a laborious cycle of editing, isolating an edited cell, and editing again. Here, we describe a technology for precisely modifying multiple sites on a single genome simultaneously. This technology - termed a multitron - is built from a heavily modified retron, in which multiple donor-encoding msds are produced from a single transcript. The multitron architecture is compatible with both recombineering in prokaryotic cells and CRISPR editing in eukaryotic cells. We demonstrate applications for this approach in molecular recording, genetic element minimization, and metabolic engineering.

Biosynthesis pathways of expanding carbon chains for producing advanced biofuels

Because the thermodynamic property is closer to gasoline, advanced biofuels (C ≥ 6) are appealing for replacing non-renewable fossil fuels using biosynthesis method that has presented a promising approach. Synthesizing advanced biofuels (C ≥ 6), in general, requires the expansion of carbon chains from three carbon atoms to more than six carbon atoms. Despite some specific biosynthesis pathways that have been developed in recent years, adequate summary is still lacking on how to obtain an effective metabolic pathway. Review of biosynthesis pathways for expanding carbon chains will be conducive to selecting, optimizing and discovering novel synthetic route to obtain new advanced biofuels. Herein, we first highlighted challenges on expanding carbon chains, followed by presentation of two biosynthesis strategies and review of three different types of biosynthesis pathways of carbon chain expansion for synthesizing advanced biofuels. Finally, we provided an outlook for the introduction of gene-editing technology in the development of new biosynthesis pathways of carbon chain expansion.

A robotic system for automated genetic manipulation and analysis of Caenorhabditis elegans

The nematode Caenorhabditis elegans is one of the most widely studied organisms in biology due to its small size, rapid life cycle, and manipulable genetics. Research with C. elegans depends on labor-intensive and time-consuming manual procedures, imposing a major bottleneck for many studies, especially for those involving large numbers of animals. Here, we describe a general-purpose tool, WormPicker, a robotic system capable of performing complex genetic manipulations and other tasks by imaging, phenotyping, and transferring C. elegans on standard agar media. Our system uses a motorized stage to move an imaging system and a robotic arm over an array of agar plates. Machine vision tools identify animals and assay developmental stage, morphology, sex, expression of fluorescent reporters, and other phenotypes. Based on the results of these assays, the robotic arm selectively transfers individual animals using an electrically self-sterilized wire loop, with the aid of machine vision and electrical capacitance sensing. Automated C. elegans manipulation shows reliability and throughput comparable with standard manual methods. We developed software to enable the system to autonomously carry out complex protocols. To validate the effectiveness and versatility of our methods, we used the system to perform a collection of common C. elegans procedures, including genetic crossing, genetic mapping, and genomic integration of a transgene. Our robotic system will accelerate C. elegans research and open possibilities for performing genetic and pharmacological screens that would be impractical using manual methods.

Production of hydroxytyrosol through whole-cell bioconversion from L-DOPA using engineered Escherichia coli

Hydroxytyrosol (HT), a polyphenolic molecule of high value, is used in the nutraceutical, cosmetic, food, and livestock nutrition industries. As a natural product, HT is chemically manufactured or extracted from olives; nevertheless, the increasing demand mandates the exploration and development of alternative sources, such as heterologous production by recombinant bacteria. In order to achieve this purpose, we have molecularly modified Escherichia coli to carry two plasmids. For conversion of L-DOPA (Levodopa) into HT efficiently, it is necessary to enhance the expression of DODC (DOPA decarboxylase), ADH (alcohol dehydrogenases), MAO (Monoamine oxidase) and GDH (glucose dehydrogenases). The step that significantly affects the rate of ht biosynthesis is likely to be associated with the reaction facilitated by DODC enzymatic activity, as suggested by the result of in vitro catalytic experiment and HPLC. Then Pseudomonas putida, Sus scrofa, Homo sapiens and Levilactobacillus brevis DODC were taken into comparsion. The DODC from H. sapiens is superior to that of P. putida, S. scrofa or L. brevis for HT production. Seven promoters were introduced to increase the expression levels of catalase (CAT) to remove the byproduct H₂O₂ and optimized coexpression strains were obtained after screening. After the 10-hour operation, the optimized whole-cell biocatalyst produced HT at a maximum titer of 4.84 g/L with over 77.5% molar substrate conversion rate.

A Cas3-base editing tool for targetable in vivo mutagenesis

The generation of genetic diversity via mutagenesis is routinely used for protein engineering and pathway optimization. Current technologies for random mutagenesis often target either the whole genome or relatively narrow windows. To bridge this gap, we developed CoMuTER (Confined Mutagenesis using a Type I-E CRISPR-Cas system), a tool that allows inducible and targetable, in vivo mutagenesis of genomic loci of up to 55 kilobases. CoMuTER employs the targetable helicase Cas3, signature enzyme of the class 1 type I-E CRISPR-Cas system, fused to a cytidine deaminase to unwind and mutate large stretches of DNA at once, including complete metabolic pathways. The tool increases the number of mutations in the target region 350-fold compared to the rest of the genome, with an average of 0.3 mutations per kilobase. We demonstrate the suitability of CoMuTER for pathway optimization by doubling the production of lycopene in Saccharomyces cerevisiae after a single round of mutagenesis.

Automating the design-build-test-learn cycle towards next-generation bacterial cell factories

Automation is playing an increasingly significant role in synthetic biology. Groundbreaking technologies, developed over the past 20 years, have enormously accelerated the construction of efficient microbial cell factories. Integrating state-of-the-art tools (e.g. for genome engineering and analytical techniques) into the design-build-test-learn cycle (DBTLc) will shift the metabolic engineering paradigm from an almost artisanal labor towards a fully automated workflow. Here, we provide a perspective on how a fully automated DBTLc could be harnessed to construct the next-generation bacterial cell factories in a fast, high-throughput fashion. Innovative toolsets and approaches that pushed the boundaries in each segment of the cycle are reviewed to this end. We also present the most recent efforts on automation of the DBTLc, which heralds a fully autonomous pipeline for synthetic biology in the near future.

Plasmid-free cheater cells commonly evolve during laboratory growth

It has been nearly a century since the isolation and use of penicillin, heralding the discovery of a wide range of different antibiotics. In addition to clinical applications, such antibiotics have been essential laboratory tools, allowing for selection and maintenance of laboratory plasmids that encode cognate resistance genes. However, antibiotic resistance mechanisms can additionally function as public goods. For example, secretion of beta-lactamase from resistant cells, and subsequent degradation of nearby penicillin and related antibiotics, allows neighboring plasmid-free susceptible bacteria to survive antibiotic treatment. How such cooperative mechanisms impact selection of plasmids during experiments in laboratory conditions is poorly understood. Here, we show that the use of plasmid-encoded beta-lactamases leads to significant curing of plasmids in surface grown bacteria. Furthermore, such curing was also evident for aminoglycoside phosphotransferase and tetracycline antiporter resistance mechanisms. Alternatively, antibiotic selection in liquid growth led to more robust plasmid maintenance, although plasmid loss still occurred. The net outcome of such plasmid loss is the generation of a heterogenous population of plasmid-containing and plasmid-free cells, leading to experimental confounds that are not widely appreciated.

Sugarcane wastes as microbial feedstocks: A review of the biorefinery framework from resource recovery to production of value-added products

Sugarcane industry is a major agricultural sector capable of producing sugars with byproducts including straw, bagasse, and molasses. Sugarcane byproducts are no longer wastes since they can be converted into carbon-rich resources for biorefinery if pretreatment of these is well established. Considerable efforts have been devoted to effective pretreatment techniques for each sugarcane byproduct to supply feedstocks in microbial fermentation to produce value-added fuels, chemicals, and polymers. These value-added chains, which start with low-value industrial wastes and end with high-value products, can make sugarcane-based biorefinery a more viable option for the modern chemical industry. In this review, recent advances in sugarcane valorization techniques are presented, ranging from sugarcane processing, pretreatment, and microbial production of value-added products. Three lucrative products, ethanol, 2,3-butanediol, and polyhydroxyalkanoates, whose production from sugarcane wastes has been widely researched, are being explored. Future studies and development in sugarcane waste biorefinery are discussed to overcome the challenges remaining.

Fast and efficient template-mediated synthesis of genetic variants

Efficient methods for the generation of specific mutations enable the study of functional variations in natural populations and lead to advances in genetic engineering applications. Here, we present a new approach, mutagenesis by template-guided amplicon assembly (MEGAA), for the rapid construction of kilobase-sized DNA variants. With this method, many mutations can be generated at a time to a DNA template at more than 90% efficiency per target in a predictable manner. We devised a robust and iterative protocol for an open-source laboratory automation robot that enables desktop production and long-read sequencing validation of variants. Using this system, we demonstrated the construction of 31 natural SARS-CoV2 spike gene variants and 10 recoded Escherichia coli genome fragments, with each 4 kb region containing up to 150 mutations. Furthermore, 125 defined combinatorial adeno-associated virus-2 cap gene variants were easily built using the system, which exhibited viral packaging enhancements of up to 10-fold compared with wild type. Thus, the MEGAA platform enables generation of multi-site sequence variants quickly, cheaply, and in a scalable manner for diverse applications in biotechnology.

Mapping the in vivo fitness landscape of a tethered ribosome

Fitness landscapes are models of the sequence space of a genetic element that map how each sequence corresponds to its activity and can be used to guide laboratory evolution. The ribosome is a macromolecular machine that is essential for protein synthesis in all organisms. Because of the prevalence of dominant lethal mutations, a comprehensive fitness landscape of the ribosomal peptidyl transfer center (PTC) has not yet been attained. Here, we develop a method to functionally map an orthogonal tethered ribosome (oRiboT), which permits complete mutagenesis of nucleotides located in the PTC and the resulting epistatic interactions. We found that most nucleotides studied showed flexibility to mutation, and identified epistatic interactions between them, which compensate for deleterious mutations. This work provides a basis for a deeper understanding of ribosome function and malleability and could be used to inform design of engineered ribosomes with applications to synthesize next-generation biomaterials and therapeutics.

In the business of base editors: Evolution from bench to bedside

With the advent of recombinant DNA technology in the 1970s, the idea of using gene therapies to treat human genetic diseases captured the interest and imagination of scientists around the world. Years later, enabled largely by the development of CRISPR-based genome editing tools, the field has exploded, with academic labs, startup biotechnology companies, and large pharmaceutical corporations working in concert to develop life-changing therapeutics. In this Essay, we highlight base editing technologies and their development from bench to bedside. Base editing, first reported in 2016, is capable of installing C•G to T•A and A•T to G•C point mutations, while largely circumventing some of the pitfalls of traditional CRISPR/Cas9 gene editing. Despite their youth, these technologies have been widely used by both academic labs and therapeutics-based companies. Here, we provide an overview of the mechanics of base editing and its use in clinical trials.