CRISPR/Cas9 recombineering-mediated deep mutational scanning of essential genes in Escherichia coli

Accelerated Metabolic Engineering for Industrial Strain Development via the Construction of a Large-Scale Genome Library

Production of chemicals via metabolic engineering of microbes is becoming highly important for sustainable bioeconomy. Conventional metabolic engineering methodologies typically involve labor-intensive and time-consuming processes of iterative genetic modifications, which are inefficient in identifying new genetic targets for the construction of robust industrial strains on a large scale. To accelerate the creation of efficient microbial cell factories and enhance our insights into cellular metabolism, diverse large-scale genome libraries are emerging as powerful tools, which can be established through multiplex or parallel genome editing, gene expression regulation, and incorporation of evolutionary strategies. In this review, we discuss the latest advancements in the construction of genome-scale libraries as well as their applications within the domain of metabolic engineering. We also address the limitations of various techniques and provide insights into future prospects for the field.

Enhancing glucaric acid production from myo-inositol in Escherichia coli by eliminating cell-to-cell variation

Glucaric acid (GA) is a value-added chemical and can be used to manufacture food additives, anticancer drugs, and polymers. The non-genetic cell-to-cell variations in GA biosynthesis are naturally inherent, indicating the presence of both high- and low-performance cells in culture. Low-performance cells can lead to nutrient waste and inefficient production. Furthermore, myo-inositol oxygenase (MIOX) is a key rate-limiting enzyme with the problem of low stability and activity in GA production. Therefore, eliminating cell-to-cell variations and increasing MIOX stability can select high-performance cells and improve GA production. In this study, an in vivo GA bioselector was constructed based on GA biosensor and tetracycline efflux pump protein TetA to continuously select GA-efficient production strains. Additionally, the upper limit of the GA biosensor was improved to 40 g/L based on ribosome-binding site optimization, achieving efficient enrichment of GA high-performance cells. A small ubiquitin-like modifier (SUMO) enhanced MIOX stability and activity. Overall, we used the GA bioselector and SUMO-MIOX fusion in fed-batch GA production and achieved a 5.52-g/L titer in Escherichia coli, which was 17-fold higher than that of the original strain.IMPORTANCEGlucaric acid is a non-toxic valuable product that was mainly synthesized by chemical methods. Due to the problems of non-selectivity, inefficiency, and environmental pollution, GA biosynthesis has attracted significant attention. The non-genetic cell-to-cell variations and MIOX stability were both critical factors for GA production. In addition, the high detection limit of the GA biosensor was a key condition for performing high-throughput screening of GA-efficient production strains. To increase GA titer, this work eliminated the cell-to-cell variations by GA bioselector constructed based on GA biosensor and TetA, and improved the stability and activity of MIOX in the GA biosynthetic pathway through fusing the SUMO to MIOX. Finally, these approaches improved the GA production by 17-fold to 5.52 g/L at 65 h. This study represents a significant step toward the industrial application of GA biosynthetic pathways in E. coli.

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.

CRISPR-Cas9-assisted genome editing in E. coli elevates the frequency of unintended mutations

Cas-assisted lambda Red recombineering techniques have rapidly become a mainstay of bacterial genome editing. Such techniques have been used to construct both individual mutants and massive libraries to assess the effects of genomic changes. We have found that a commonly used Cas9-assisted editing method results in unintended mutations elsewhere in the genome in 26% of edited clones. The unintended mutations are frequently found over 200 kb from the intended edit site and even over 10 kb from potential off-target sites. We attribute the high frequency of unintended mutations to error-prone polymerases expressed in response to dsDNA breaks introduced at the edit site. Most unintended mutations occur in regulatory or coding regions and thus may have phenotypic effects. Our findings highlight the risks associated with genome editing techniques involving dsDNA breaks in E. coli and likely other bacteria and emphasize the importance of sequencing the genomes of edited cells to ensure the absence of unintended mutations.

Recent advances in genome-scale engineering in Escherichia coli and their applications

Owing to the rapid advancement of genome engineering technologies, the scale of genome engineering has expanded dramatically. Genome editing has progressed from one genomic alteration at a time that could only be employed in few species, to the simultaneous generation of multiple modifications across many genomic loci in numerous species. The development and recent advances in multiplex automated genome engineering (MAGE)-associated technologies and clustered regularly interspaced short palindromic repeats and their associated protein (CRISPR-Cas)-based approaches, together with genome-scale synthesis technologies offer unprecedented opportunities for advancing genome-scale engineering in a broader range. These approaches provide new tools to generate strains with desired phenotypes, understand the complexity of biological systems, and directly evolve a genome with novel features. Here, we review the recent major advances in genome-scale engineering tools developed for Escherichia coli, focusing on their applications in identifying essential genes, genome reduction, recoding, and beyond.

Deep mutational scanning reveals the molecular determinants of RNA polymerase-mediated adaptation and tradeoffs

RNA polymerase (RNAP) is emblematic of complex biological systems that control multiple traits involving trade-offs such as growth versus maintenance. Laboratory evolution has revealed that mutations in RNAP subunits, including RpoB, are frequently selected. However, we lack a systems view of how mutations alter the RNAP molecular functions to promote adaptation. We, therefore, measured the fitness of thousands of mutations within a region of rpoB under multiple conditions and genetic backgrounds, to find that adaptive mutations cluster in two modules. Mutations in one module favor growth over maintenance through a partial loss of an interaction associated with faster elongation. Mutations in the other favor maintenance over growth through a destabilized RNAP-DNA complex. The two molecular handles capture the versatile RNAP-mediated adaptations. Combining both interaction losses simultaneously improved maintenance and growth, challenging the idea that growth-maintenance tradeoff resorts only from limited resources, and revealing how compensatory evolution operates within RNAP.

ShinyBioHEAT: an interactive shiny app to identify phenotype driver genes in E.coli and B.subtilis

SUMMARY

In any population under selective pressure, a central challenge is to distinguish the genes that drive adaptation from others which, subject to population variation, harbor many neutral mutations de novo. We recently showed that such genes could be identified by supplementing information on mutational frequency with an evolutionary analysis of the likely functional impact of coding variants. This approach improved the discovery of driver genes in both lab-evolved and environmental Escherichia coli strains. To facilitate general adoption, we now developed ShinyBioHEAT, an R Shiny web-based application that enables identification of phenotype driving gene in two commonly used model bacteria, E.coli and Bacillus subtilis, with no specific computational skill requirements. ShinyBioHEAT not only supports transparent and interactive analysis of lab evolution data in E.coli and B.subtilis, but it also creates dynamic visualizations of mutational impact on protein structures, which add orthogonal checks on predicted drivers.

AVAILABILITY AND IMPLEMENTATION

Code for ShinyBioHEAT is available at https://github.com/LichtargeLab/ShinyBioHEAT. The Shiny application is additionally hosted at http://bioheat.lichtargelab.org/.

Improved Dual Base Editor Systems (iACBEs) for Simultaneous Conversion of Adenine and Cytosine in the Bacterium Escherichia coli

Genome-editing (GE) techniques like base editing are ideal for introducing novel gain-of-function mutations and in situ protein evolution. Features of base editors (BEs) such as higher efficacy, relaxed protospacer adjacent motif (PAM), and a broader editing window enables diversification of user-defined targeted locus. Cytosine (CBE) or adenine (ABE) BEs alone can only alter C-to-T or A-to-G in target sites. In contrast, dual BEs (ACBEs) can concurrently generate C-to-T and A-to-G modifications. Although BE tools have recently been applied in microbes, there is no report of ACBE for microbial GE. In this study, we engineered four improved ACBEs (iACBEs) tethering highly active CBE and ABE variants that can introduce synchronized C-to-T and A-to-G mutations in targeted loci. iACBE4 generated by evoCDA1-ABE9e fusion demonstrated a broader editing window (positions -6 to 15) and is also compatible with the multiplex editing approach in Escherichia coli. We further show that the iACBE4-NG containing PAM-relaxed nCas9-NG expands the targeting scope beyond NGG (N-A/G/C/T) PAM. As a proof-of-concept, iACBE was effectively utilized to identify previously unknown mutations in the rpoB gene, conferring gain-of-function, i.e., rifampicin resistance. The iACBE tool would expand the CRISPR-GE toolkit for microbial genome engineering and synthetic biology. IMPORTANCE Dual base editors are DSB-free CRISPR tools applied in eukaryotes but not yet in bacteria. We developed an improved ACBE toolset for bacteria, combining highly processive deaminases. We believe that the bacterial optimized iACBE toolset is a significant advancement in CRISPR-based E. coli genome editing and adaptable to other microbes.

Mutational fitness landscape and drug resistance

Robust technology has been developed to systematically quantify fitness landscapes that provide valuable opportunities to improve our understanding of drug resistance and define new avenues to develop drugs with reduced resistance susceptibility. We outline the critical importance of drug resistance studies and the potential for fitness landscape approaches to contribute to this effort. We describe the major technical advancements in mutational scanning, which is the primary approach used to quantify protein fitness landscapes. There are many complex steps to consider in planning and executing mutational scanning projects including developing a selection scheme, generating mutant libraries, tracking the frequency of variants using next-generation sequencing, and processing and interpreting the data. Key experimental parameters impacting each of these steps are discussed to aid in planning fitness landscape studies. There is a strong need for improved understanding of drug resistance, and fitness landscapes provide a promising new approach.

Deep mutational scanning: A versatile tool in systematically mapping genotypes to phenotypes

Unveiling how genetic variations lead to phenotypic variations is one of the key questions in evolutionary biology, genetics, and biomedical research. Deep mutational scanning (DMS) technology has allowed the mapping of tens of thousands of genetic variations to phenotypic variations efficiently and economically. Since its first systematic introduction about a decade ago, we have witnessed the use of deep mutational scanning in many research areas leading to scientific breakthroughs. Also, the methods in each step of deep mutational scanning have become much more versatile thanks to the oligo-synthesizing technology, high-throughput phenotyping methods and deep sequencing technology. However, each specific possible step of deep mutational scanning has its pros and cons, and some limitations still await further technological development. Here, we discuss recent scientific accomplishments achieved through the deep mutational scanning and describe widely used methods in each step of deep mutational scanning. We also compare these different methods and analyze their advantages and disadvantages, providing insight into how to design a deep mutational scanning study that best suits the aims of the readers' projects.

CRISPR and Antisense RNA Technology: Exploiting Nature's Tool to Restrain Virulence in Tenacious Pathogens

Pathogenic bacteria constitute a significant threat to mankind and at the same time represent a huge reservoir of abeyant therapeutics to prevent and treat various diseases. The concept of virulence determinants has been a compelling tool in driving research in the field of bacterial pathogenesis and infectious diseases. In this review, we highlight a few virulence elements forged by the pathogens from the viewpoint of the damage-response scaffold, vandalizing the susceptible host. Seeking an alternative to target the virulence determinants heads a road map toward the exemplary molecular approach. Hence, here we explore some of the exceptional applications of the clustered regulatory interspaced short palindromic repeat (CRISPR)- based therapy and antisense RNA (asRNA) approach, which could be exploited to selectively dismantle adamant components of the pathogen's virulence machinery. To the best of our knowledge, this is the first review paper involving both CRISPR and antisense RNA technology, as an alternative strategy to evade virulence mechanisms in bacterial pathogens.

A Toolkit for Effective and Successive Genome Engineering of Escherichia coli

The bacterium Escherichia coli has been well-justified as an effective workhorse for industrial applications. In this study, we developed a toolkit for flexible genome engineering of this microorganism, including site-specific insertion of heterologous genes and inactivation of endogenous genes, such that bacterial hosts can be effectively engineered for biomanufacturing. We first constructed a base strain by genomic implementation of the cas9 and λRed recombineering genes. Then, we constructed plasmids for expressing gRNA, DNA cargo, and the Vibrio cholerae Tn6677 transposon and type I-F CRISPR-Cas machinery. Genomic insertion of a DNA cargo up to 5.5 kb was conducted using a transposon-associated CRISPR-Cas system, whereas gene inactivation was mediated by a classic CRISPR-Cas9 system coupled with λRed recombineering. With this toolkit, we can exploit the synergistic functions of CRISPR-Cas, λRed recombineering, and Tn6677 transposon for successive genomic manipulations. As a demonstration, we used the developed toolkit to derive a plasmid-free strain for heterologous production of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) by genomic knock-in and knockout of several key genes with high editing efficiencies.

CRISPR-based oligo recombineering prioritizes apicomplexan cysteines for drug discovery

Nucleophilic amino acids are important in covalent drug development yet underutilized as anti-microbial targets. Chemoproteomic technologies have been developed to mine chemically accessible residues via their intrinsic reactivity towards electrophilic probes but cannot discern which chemically reactive sites contribute to protein function and should therefore be prioritized for drug discovery. To address this, we have developed a CRISPR-based oligo recombineering (CORe) platform to support the rapid identification, functional prioritization and rational targeting of chemically reactive sites in haploid systems. Our approach couples protein sequence and function with biological fitness of live cells. Here we profile the electrophile sensitivity of proteinogenic cysteines in the eukaryotic pathogen Toxoplasma gondii and prioritize functional sites using CORe. Electrophile-sensitive cysteines decorating the ribosome were found to be critical for parasite growth, with target-based screening identifying a parasite-selective anti-malarial lead molecule and validating the apicomplexan translation machinery as a target for ongoing covalent ligand development.

Interpreting protein variant effects with computational predictors and deep mutational scanning

Computational predictors of genetic variant effect have advanced rapidly in recent years. These programs provide clinical and research laboratories with a rapid and scalable method to assess the likely impacts of novel variants. However, it can be difficult to know to what extent we can trust their results. To benchmark their performance, predictors are often tested against large datasets of known pathogenic and benign variants. These benchmarking data may overlap with the data used to train some supervised predictors, which leads to data re-use or circularity, resulting in inflated performance estimates for those predictors. Furthermore, new predictors are usually found by their authors to be superior to all previous predictors, which suggests some degree of computational bias in their benchmarking. Large-scale functional assays known as deep mutational scans provide one possible solution to this problem, providing independent datasets of variant effect measurements. In this Review, we discuss some of the key advances in predictor methodology, current benchmarking strategies and how data derived from deep mutational scans can be used to overcome the issue of data circularity. We also discuss the ability of such functional assays to directly predict clinical impacts of mutations and how this might affect the future need for variant effect predictors.

Recent advances in high-throughput metabolic engineering: Generation of oligonucleotide-mediated genetic libraries

The preparation of genetic libraries is an essential step to evolve microorganisms and study genotype-phenotype relationships by high-throughput screening/selection. As the large-scale synthesis of oligonucleotides becomes easy, cheap, and high-throughput, numerous novel strategies have been developed in recent years to construct high-quality oligo-mediated libraries, leveraging state-of-art molecular biology tools for genome editing and gene regulation. This review presents an overview of recent advances in creating and characterizing in vitro and in vivo genetic libraries, based on CRISPR/Cas, regulatory RNAs, and recombineering, primarily for Escherichia coli and Saccharomyces cerevisiae. These libraries' applications in high-throughput metabolic engineering, strain evolution and protein engineering are also discussed.

Rapid intraspecies evolution of fitness effects of yeast genes

Organisms within species have numerous genetic and phenotypic variations. Growing evidences show intraspecies variation of mutant phenotypes may be more complicated than expected. Current studies on intraspecies variations of mutant phenotypes are limited to just a few strains. This study investigated the intraspecies variation of fitness effects of 5,630 gene mutants in ten Saccharomyces cerevisiae strains using CRISPR–Cas9 screening. We found that the variability of fitness effects induced by gene disruptions is very large across different strains. Over 75% of genes affected cell fitness in a strain-specific manner to varying degrees. The strain specificity of the fitness effect of a gene is related to its evolutionary and functional properties. Subsequent analysis revealed that younger genes, especially those newly acquired in S. cerevisiae species, are more likely to be strongly strain-specific. Intriguingly, there seems to exist a ceiling of fitness effect size for strong strain-specific genes, and among them, the newly acquired genes are still evolving and have yet to reach this ceiling. Additionally, for a large proportion of protein complexes, the strain specificity profile is inconsistent among genes encoding the same complex. Taken together, these results offer a genome-wide map of intraspecies variation for fitness effect as a mutant phenotype and provide an updated insight on intraspecies phenotypic evolution.

[Research advances on the development and application of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein system]

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) protein system, as an emerging gene editing system, can be divided into class 1 and class 2 systems according to the number of Cas protein. The CRISPR/Cas9 in class 2 system can cleave target nucleic acid only with the help of Cas9 protein and single-stranded guide RNA, which is currently the most widely used CRISPR/Cas system. In addition to gene editing in the treatment of genetic diseases, a variety of CRISPR/Cas system derived technologies have vast application prospect in the fields of disease-related gene screening, gene expression regulation, and rapid detection, prevention, and control of pathogens. This article summarizes the discovery process of CRISPR/Cas system and applications of several major CRISPR/Cas derived technologies, aiming to provide a reference for researchers in the field of life science.

Genetic Diversity for Accelerating Microbial Adaptive Laboratory Evolution

Adaptive laboratory evolution (ALE) is a widely used and highly effective tool for improving microbial phenotypes and investigating the evolutionary roots of biological phenomena. Serving as the raw materials of evolution, mutations have been extensively utilized to increase the chances of engineering molecules or microbes with tailor-made functions. The generation of genetic diversity is therefore a core technology for accelerating ALE, and a high-quality mutant library is crucial to its success. Because of its importance, technologies for generating genetic diversity have undergone rapid development in recent years. Here, we review the existing techniques for the construction of mutant libraries, briefly introduce their mechanisms and applications, discuss ongoing and emerging efforts to apply engineering technologies in the construction of mutant libraries, and suggest future perspectives for library construction.

High-throughput functional variant screens via in vivo production of single-stranded DNA

Creating and characterizing individual genetic variants remains limited in scale, compared to the tremendous variation both existing in nature and envisioned by genome engineers. Here we introduce retron library recombineering (RLR), a methodology for high-throughput functional screens that surpasses the scale and specificity of CRISPR-Cas methods. We use the targeted reverse-transcription activity of retrons to produce single-stranded DNA (ssDNA) in vivo, incorporating edits at >90% efficiency and enabling multiplexed applications. RLR simultaneously introduces many genomic variants, producing pooled and barcoded variant libraries addressable by targeted deep sequencing. We use RLR for pooled phenotyping of synthesized antibiotic resistance alleles, demonstrating quantitative measurement of relative growth rates. We also perform RLR using the sheared genomic DNA of an evolved bacterium, experimentally querying millions of sequences for causal variants, demonstrating that RLR is uniquely suited to utilize large pools of natural variation. Using ssDNA produced in vivo for pooled experiments presents avenues for exploring variation across the genome.

Recombineering and MAGE

Recombination-mediated genetic engineering, also known as recombineering, is the genomic incorporation of homologous single-stranded or double-stranded DNA into bacterial genomes. Recombineering and its derivative methods have radically improved genome engineering capabilities, perhaps none more so than multiplex automated genome engineering (MAGE). MAGE is representative of a set of highly multiplexed single-stranded DNA-mediated technologies. First described in Escherichia coli, both MAGE and recombineering are being rapidly translated into diverse prokaryotes and even into eukaryotic cells. Together, this modern set of tools offers the promise of radically improving the scope and throughput of experimental biology by providing powerful new methods to ease the genetic manipulation of model and non-model organisms. In this Primer, we describe recombineering and MAGE, their optimal use, their diverse applications and methods for pairing them with other genetic editing tools. We then look forward to the future of genetic engineering.

High-Throughput Functional Genomics for Energy Production

Functional genomics remains a foundational field for establishing genotype-phenotype relationships that enable strain engineering. High-throughput (HTP) methods accelerate the Design-Build-Test-Learn cycle that currently drives synthetic biology towards a forward engineering future. Trackable mutagenesis techniques including transposon insertion sequencing and CRISPR-Cas-mediated genome editing allow for rapid fitness profiling of a collection, or library, of mutants to discover beneficial mutations. Due to the relative speed of these experiments compared to adaptive evolution experiments, iterative rounds of mutagenesis can be implemented for next-generation metabolic engineering efforts to design complex production and tolerance phenotypes. Additionally, the expansion of these mutagenesis techniques to novel bacteria are opening up industrial microbes that show promise for establishing a bio-based economy.

Activity- and reactivity-based proteomics: Recent technological advances and applications in drug discovery

Activity-based protein profiling (ABPP) is recognized as a powerful and versatile chemoproteomic technology in drug discovery. Central to ABPP is the use of activity-based probes to report the activity of specific enzymes or reactivity of amino acid types in complex biological systems. Over the last two decades, ABPP has facilitated the identification of new drug targets and discovery of lead compounds in human and infectious disease. Furthermore, as part of a sustained global effort to illuminate the druggable proteome, the repertoire of target classes addressable with activity-based probes has vastly expanded in recent years. Here, we provide an overview of ABPP and summarise the major technological advances with an emphasis on probe development.

Predicting Drug Resistance Using Deep Mutational Scanning

Drug resistance is a major healthcare challenge, resulting in a continuous need to develop new inhibitors. The development of these inhibitors requires an understanding of the mechanisms of resistance for a critical mass of occurrences. Recent genome editing technologies based on high-throughput DNA synthesis and sequencing may help to predict mutations resulting in resistance by testing large mutagenesis libraries. Here we describe the rationale of this approach, with examples and relevance to drug development and resistance in malaria.

CRISPR/Cas9 recombineering-mediated deep mutational scanning of essential genes in Escherichia coli

Deep mutational scanning can provide significant insights into the function of essential genes in bacteria. Here, we developed a high-throughput method for mutating essential genes of Escherichia coli in their native genetic context. We used Cas9-mediated recombineering to introduce a library of mutations, created by error-prone PCR, within a gene fragment on the genome using a single gRNA pre-validated for high efficiency. Tracking mutation frequency through deep sequencing revealed biases in the position and the number of the introduced mutations. We overcame these biases by increasing the homology arm length and blocking mismatch repair to achieve a mutation efficiency of 85% for non-essential genes and 55% for essential genes. These experiments also improved our understanding of poorly characterized recombineering process using dsDNA donors with single nucleotide changes. Finally, we applied our technology to target rpoB, the beta subunit of RNA polymerase, to study resistance against rifampicin. In a single experiment, we validate multiple biochemical and clinical observations made in the previous decades and provide insights into resistance compensation with the study of double mutants.