Systematic and scalable genome-wide essentiality mapping to identify nonessential genes in phages.

Phages are one of the key ecological drivers of microbial community dynamics, function, and evolution. Despite their importance in bacterial ecology and evolutionary processes, phage genes are poorly characterized, hampering their usage in a variety of biotechnological applications. Methods to characterize such genes, even those critical to the phage life cycle, are labor intensive and are generally phage specific. Here, we develop a systematic gene essentiality mapping method scalable to new phage-host combinations that facilitate the identification of nonessential genes. As a proof of concept, we use an arrayed genome-wide CRISPR interference (CRISPRi) assay to map gene essentiality landscape in the canonical coliphages λ and P1. Results from a single panel of CRISPRi probes largely recapitulate the essential gene roster determined from decades of genetic analysis for lambda and provide new insights into essential and nonessential loci in P1. We present evidence of how CRISPRi polarity can lead to false positive gene essentiality assignments and recommend caution towards interpreting CRISPRi data on gene essentiality when applied to less studied phages. Finally, we show that we can engineer phages by inserting DNA barcodes into newly identified inessential regions, which will empower processes of identification, quantification, and tracking of phages in diverse applications.

Geochemical constraints on bacteriophage infectivity in terrestrial environments.

Lytic phages can be potent and selective inhibitors of microbial growth and can have profound impacts on microbiome composition and function. However, there is uncertainty about the biogeochemical conditions under which phage predation modulates microbial ecosystem function, particularly in terrestrial systems. Ionic strength is critical for infection of bacteria by many phages, but quantitative data is limited on the ion thresholds for phage infection that can be compared with environmental ion concentrations. Similarly, while carbon composition varies in the environment, we do not know how this variability influences the impact of phage predation on microbiome function. Here, we measured the half-maximal effective concentrations (EC50) of 80 different inorganic ions for the infection of E. coli with two canonical dsDNA and ssRNA phages, T4 and MS2, respectively. Many alkaline earth metals and alkali metals enabled lytic infection but the ionic strength thresholds varied for different ions between phages. Additionally, using a freshwater nitrate-reducing microbiome, we found that the ability of lytic phages to influence nitrate reduction end-products depended upon the carbon source as well as ionic strength. For all phage:host pairs, the ion EC50s for phage infection exceeded the ion concentrations found in many terrestrial freshwater systems. Thus, our findings support a model where phages most influence terrestrial microbial functional ecology in hot spots and hot moments such as metazoan guts, drought influenced soils, or biofilms where ion concentration is locally or transiently elevated and nutrients are available to support the growth of specific phage hosts.

Multicopy suppressor screens reveal convergent evolution of single-gene lysis proteins.

Single-strand RNA (ssRNA) Fiersviridae phages cause host lysis with a product of single gene (sgl for single-gene lysis; product Sgl) that induces autolysis. Many different Sgls have been discovered, but the molecular targets of only a few have been identified. In this study, we used a high-throughput genetic screen to uncover genome-wide host suppressors of diverse Sgls. In addition to validating known molecular mechanisms, we discovered that the Sgl of PP7, an ssRNA phage of Pseudomonas aeruginosa, targets MurJ, the flippase responsible for lipid II export, previously shown to be the target of the Sgl of coliphage M. These two Sgls, which are unrelated and predicted to have opposite membrane topology, thus represent a case of convergent evolution. We extended the genetic screens to other uncharacterized Sgls and uncovered a common set of multicopy suppressors, suggesting that these Sgls act by the same or similar mechanism.

Phage therapy: From biological mechanisms to future directions.

Increasing antimicrobial resistance rates have revitalized bacteriophage (phage) research, the natural predators of bacteria discovered over 100 years ago. In order to use phages therapeutically, they should (1) preferably be lytic, (2) kill the bacterial host efficiently, and (3) be fully characterized to exclude side effects. Developing therapeutic phages takes a coordinated effort of multiple stakeholders. Herein, we review the state of the art in phage therapy, covering biological mechanisms, clinical applications, remaining challenges, and future directions involving naturally occurring and genetically modified or synthetic phages.

Broad-spectrum CRISPR-Cas13a enables efficient phage genome editing.

CRISPR-Cas13 proteins are RNA-guided RNA nucleases that defend against incoming RNA and DNA phages by binding to complementary target phage transcripts followed by general, non-specific RNA degradation. Here we analysed the defensive capabilities of LbuCas13a from Leptotrichia buccalis and found it to have robust antiviral activity unaffected by target phage gene essentiality, gene expression timing or target sequence location. Furthermore, we find LbuCas13a antiviral activity to be broadly effective against a wide range of phages by challenging LbuCas13a against nine E. coli phages from diverse phylogenetic groups. Leveraging the versatility and potency enabled by LbuCas13a targeting, we applied LbuCas13a towards broad-spectrum phage editing. Using a two-step phage-editing and enrichment method, we achieved seven markerless genome edits in three diverse phages with 100% efficiency, including edits as large as multi-gene deletions and as small as replacing a single codon. Cas13a can be applied as a generalizable tool for editing the most abundant and diverse biological entities on Earth.

A Phage Foundry Framework to Systematically Develop Viral Countermeasures to Combat Antibiotic-Resistant Bacterial Pathogens.

At its current rate, the rise of antimicrobial-resistant (AMR) infections is predicted to paralyze our industries and healthcare facilities while becoming the leading global cause of loss of human life. With limited new antibiotics on the horizon, we need to invest in alternative solutions. Bacteriophages (phages)-viruses targeting bacteria-offer a powerful alternative approach to tackle bacterial infections. Despite recent advances in using phages to treat recalcitrant AMR infections, the field lacks systematic development of phage therapies scalable to different applications. We propose a Phage Foundry framework to establish metrics for phage characterization and to fill the knowledge and technological gaps in phage therapeutics. Coordinated investment in AMR surveillance, sampling, characterization, and data sharing procedures will enable rational exploitation of phages for treatments. A fully realized Phage Foundry will enhance the sharing of knowledge, technology, and viral reagents in an equitable manner and will accelerate the biobased economy.

The genetic basis of phage susceptibility, cross-resistance and host-range in Salmonella.

Though bacteriophages (phages) are known to play a crucial role in bacterial fitness and virulence, our knowledge about the genetic basis of their interaction, cross-resistance and host-range is sparse. Here, we employed genome-wide screens in Salmonella enterica serovar Typhimurium to discover host determinants involved in resistance to eleven diverse lytic phages including four new phages isolated from a therapeutic phage cocktail. We uncovered 301 diverse host factors essential in phage infection, many of which are shared between multiple phages demonstrating potential cross-resistance mechanisms. We validate many of these novel findings and uncover the intricate interplay between RpoS, the virulence-associated general stress response sigma factor and RpoN, the nitrogen starvation sigma factor in phage cross-resistance. Finally, the infectivity pattern of eleven phages across a panel of 23 genome sequenced Salmonella strains indicates that additional constraints and interactions beyond the host factors uncovered here define the phage host range.

Systematic discovery of pseudomonad genetic factors involved in sensitivity to tailocins.

Tailocins are bactericidal protein complexes produced by a wide variety of bacteria that kill closely related strains and may play a role in microbial community structure. Thanks to their high specificity, tailocins have been proposed as precision antibacterial agents for therapeutic applications. Compared to tailed phages, with whom they share an evolutionary and morphological relationship, bacterially produced tailocins kill their host upon production but producing strains display resistance to self-intoxication. Though lipopolysaccharide (LPS) has been shown to act as a receptor for tailocins, the breadth of factors involved in tailocin sensitivity, and the mechanisms behind resistance to self-intoxication, remain unclear. Here, we employed genome-wide screens in four non-model pseudomonads to identify mutants with altered fitness in the presence of tailocins produced by closely related pseudomonads. Our mutant screens identified O-antigen composition and display as most important in defining sensitivity to our tailocins. In addition, the screens suggest LPS thinning as a mechanism by which resistant strains can become more sensitive to tailocins. We validate many of these novel findings, and extend these observations of tailocin sensitivity to 130 genome-sequenced pseudomonads. This work offers insights into tailocin-bacteria interactions, informing the potential use of tailocins in microbiome manipulation and antibacterial therapy.

High-throughput mapping of the phage resistance landscape in E. coli.

Bacteriophages (phages) are critical players in the dynamics and function of microbial communities and drive processes as diverse as global biogeochemical cycles and human health. Phages tend to be predators finely tuned to attack specific hosts, even down to the strain level, which in turn defend themselves using an array of mechanisms. However, to date, efforts to rapidly and comprehensively identify bacterial host factors important in phage infection and resistance have yet to be fully realized. Here, we globally map the host genetic determinants involved in resistance to 14 phylogenetically diverse double-stranded DNA phages using two model Escherichia coli strains (K-12 and BL21) with known sequence divergence to demonstrate strain-specific differences. Using genome-wide loss-of-function and gain-of-function genetic technologies, we are able to confirm previously described phage receptors as well as uncover a number of previously unknown host factors that confer resistance to one or more of these phages. We uncover differences in resistance factors that strongly align with the susceptibility of K-12 and BL21 to specific phage. We also identify both phage-specific mechanisms, such as the unexpected role of cyclic-di-GMP in host sensitivity to phage N4, and more generic defenses, such as the overproduction of colanic acid capsular polysaccharide that defends against a wide array of phages. Our results indicate that host responses to phages can occur via diverse cellular mechanisms. Our systematic and high-throughput genetic workflow to characterize phage-host interaction determinants can be extended to diverse bacteria to generate datasets that allow predictive models of how phage-mediated selection will shape bacterial phenotype and evolution. The results of this study and future efforts to map the phage resistance landscape will lead to new insights into the coevolution of hosts and their phage, which can ultimately be used to design better phage therapeutic treatments and tools for precision microbiome engineering.

Dual-barcoded shotgun expression library sequencing for high-throughput characterization of functional traits in bacteria.

A major challenge in genomics is the knowledge gap between sequence and its encoded function. Gain-of-function methods based on gene overexpression are attractive avenues for phenotype-based functional screens, but are not easily applied in high-throughput across many experimental conditions. Here, we present Dual Barcoded Shotgun Expression Library Sequencing (Dub-seq), a method that uses random DNA barcodes to greatly increase experimental throughput. As a demonstration of this approach, we construct a Dub-seq library with Escherichia coli genomic DNA, performed 155 genome-wide fitness assays in 52 experimental conditions, and identified overexpression phenotypes for 813 genes. We show that Dub-seq data is reproducible, accurately recapitulates known biology, and identifies hundreds of novel gain-of-function phenotypes for E. coli genes, a subset of which we verified with assays of individual strains. Dub-seq provides complementary information to loss-of-function approaches and will facilitate rapid and systematic functional characterization of microbial genomes.

Author Correction: Jungle Express is a versatile repressor system for tight transcriptional control.

In the original version of this Article, an incorrect URL was provided in the Data Availability Statement regarding the deposition of plasmids listed in Supplementary Table 4. The correct URL is https://public-registry.jbei.org/folders/378 . This error has been corrected in both the PDF and HTML versions of the Article.

Jungle Express is a versatile repressor system for tight transcriptional control.

Tightly regulated promoters are essential for numerous biological applications, where strong inducibility, portability, and scalability are desirable. Current systems are often incompatible with large-scale fermentations due to high inducer costs and strict media requirements. Here, we describe the bottom-up engineering of 'Jungle Express', an expression system that enables efficient gene regulation in diverse proteobacteria. This system is guided by EilR, a multidrug-binding repressor with high affinity to its optimized operator and cationic dyes that act as powerful inducers at negligible costs. In E. coli, the engineered promoters exhibit minimal basal transcription and are inducible over four orders of magnitude by 1 µM crystal violet, reaching expression levels exceeding those of the strongest current bacterial systems. Further, we provide molecular insights into specific interactions of EilR with its operator and with two inducers. The versatility of Jungle Express opens the way for tightly controlled and efficient gene expression that is not restricted to host organism, substrate, or scale.

Rapid and Efficient One-Step Metabolic Pathway Integration in E. coli.

Methods for importing heterologous genes into genetically tractable hosts are among the most desired tools of synthetic biology. Easy plug-and-play construction methods to rapidly test genes and pathways stably in the host genome would expedite synthetic biology and metabolic engineering applications. Here, we describe a CRISPR-based strategy that allows highly efficient, single step integration of large pathways in Escherichia coli. This strategy allows high efficiency integration in a broad range of homology arm sizes and genomic positions, with efficiencies ranging from 70 to 100% in 7 distinct loci. To demonstrate the large size capability, we integrated a 10 kb construct to implement isobutanol production in a single day. The ability to efficiently integrate entire metabolic pathways in a rapid and markerless manner will facilitate testing and engineering of novel pathways using the E. coli genome as a stable testing platform.

Investigation of Proposed Ladderane Biosynthetic Genes from Anammox Bacteria by Heterologous Expression in E. coli.

Ladderanes are hydrocarbon chains with three or five linearly concatenated cyclobutane rings that are uniquely produced as membrane lipid components by anammox (anaerobic ammonia-oxidizing) bacteria. By virtue of their angle and torsional strain, ladderanes are unusually energetic compounds, and if produced biochemically by engineered microbes, could serve as renewable, high-energy-density jet fuel components. The biochemistry and genetics underlying the ladderane biosynthetic pathway are unknown, however, previous studies have identified a pool of 34 candidate genes from the anammox bacterium, Kuenenia stuttgartiensis, some or all of which may be involved with ladderane fatty acid biosynthesis. The goal of the present study was to establish a systematic means of testing the candidate genes from K. stuttgartiensis for involvement in ladderane biosynthesis through heterologous expression in E. coli under anaerobic conditions. This study describes an efficient means of assembly of synthesized, codon-optimized candidate ladderane biosynthesis genes in synthetic operons that allows for changes to regulatory element sequences, as well as modular assembly of multiple operons for simultaneous heterologous expression in E. coli (or potentially other microbial hosts). We also describe in vivo functional tests of putative anammox homologs of the phytoene desaturase CrtI, which plays an important role in the hypothesized ladderane pathway, and a method for soluble purification of one of these enzymes. This study is, to our knowledge, the first experimental effort focusing on the role of specific anammox genes in the production of ladderanes, and lays the foundation for future efforts toward determination of the ladderane biosynthetic pathway. Our substantial, but far from comprehensive, efforts at elucidating the ladderane biosynthetic pathway were not successful. We invite the scientific community to take advantage of the considerable synthetic biology resources and experimental results developed in this study to elucidate the biosynthetic pathway that produces unique and intriguing ladderane lipids.

Genome-Wide Tuning of Protein Expression Levels to Rapidly Engineer Microbial Traits.

The reliable engineering of biological systems requires quantitative mapping of predictable and context-independent expression over a broad range of protein expression levels. However, current techniques for modifying expression levels are cumbersome and are not amenable to high-throughput approaches. Here we present major improvements to current techniques through the design and construction of E. coli genome-wide libraries using synthetic DNA cassettes that can tune expression over a ∼10(4) range. The cassettes also contain molecular barcodes that are optimized for next-generation sequencing, enabling rapid and quantitative tracking of alleles that have the highest fitness advantage. We show these libraries can be used to determine which genes and expression levels confer greater fitness to E. coli under different growth conditions.

Composability of regulatory sequences controlling transcription and translation in Escherichia coli.

The inability to predict heterologous gene expression levels precisely hinders our ability to engineer biological systems. Using well-characterized regulatory elements offers a potential solution only if such elements behave predictably when combined. We synthesized 12,563 combinations of common promoters and ribosome binding sites and simultaneously measured DNA, RNA, and protein levels from the entire library. Using a simple model, we found that RNA and protein expression were within twofold of expected levels 80% and 64% of the time, respectively. The large dataset allowed quantitation of global effects, such as translation rate on mRNA stability and mRNA secondary structure on translation rate. However, the worst 5% of constructs deviated from prediction by 13-fold on average, which could hinder large-scale genetic engineering projects. The ease and scale this of approach indicates that rather than relying on prediction or standardization, we can screen synthetic libraries for desired behavior.

Precise and reliable gene expression via standard transcription and translation initiation elements.

An inability to reliably predict quantitative behaviors for novel combinations of genetic elements limits the rational engineering of biological systems. We developed an expression cassette architecture for genetic elements controlling transcription and translation initiation in Escherichia coli: transcription elements encode a common mRNA start, and translation elements use an overlapping genetic motif found in many natural systems. We engineered libraries of constitutive and repressor-regulated promoters along with translation initiation elements following these definitions. We measured activity distributions for each library and selected elements that collectively resulted in expression across a 1,000-fold observed dynamic range. We studied all combinations of curated elements, demonstrating that arbitrary genes are reliably expressed to within twofold relative target expression windows with ∼93% reliability. We expect the genetic element definitions validated here can be collectively expanded to create collections of public-domain standard biological parts that support reliable forward engineering of gene expression at genome scales.

Quantitative estimation of activity and quality for collections of functional genetic elements.

The practice of engineering biology now depends on the ad hoc reuse of genetic elements whose precise activities vary across changing contexts. Methods are lacking for researchers to affordably coordinate the quantification and analysis of part performance across varied environments, as needed to identify, evaluate and improve problematic part types. We developed an easy-to-use analysis of variance (ANOVA) framework for quantifying the performance of genetic elements. For proof of concept, we assembled and analyzed combinations of prokaryotic transcription and translation initiation elements in Escherichia coli. We determined how estimation of part activity relates to the number of unique element combinations tested, and we show how to estimate expected ensemble-wide part activity from just one or two measurements. We propose a new statistic, biomolecular part 'quality', for tracking quantitative variation in part performance across changing contexts.

Measurement and modeling of intrinsic transcription terminators.

The reliable forward engineering of genetic systems remains limited by the ad hoc reuse of many types of basic genetic elements. Although a few intrinsic prokaryotic transcription terminators are used routinely, termination efficiencies have not been studied systematically. Here, we developed and validated a genetic architecture that enables reliable measurement of termination efficiencies. We then assembled a collection of 61 natural and synthetic terminators that collectively encode termination efficiencies across an ∼800-fold dynamic range within Escherichia coli. We simulated co-transcriptional RNA folding dynamics to identify competing secondary structures that might interfere with terminator folding kinetics or impact termination activity. We found that structures extending beyond the core terminator stem are likely to increase terminator activity. By excluding terminators encoding such context-confounding elements, we were able to develop a linear sequence-function model that can be used to estimate termination efficiencies (r = 0.9, n = 31) better than models trained on all terminators (r = 0.67, n = 54). The resulting systematically measured collection of terminators should improve the engineering of synthetic genetic systems and also advance quantitative modeling of transcription termination.