Quantitative analysis of triple-mutant genetic interactions

CRISPRi-TnSeq maps genome-wide interactions between essential and non-essential genes in bacteria

Genetic interactions identify functional connections between genes and pathways, establishing gene functions or druggable targets. Here we use CRISPRi-TnSeq, CRISPRi-mediated knockdown of essential genes alongside TnSeq-mediated knockout of non-essential genes, to map genome-wide interactions between essential and non-essential genes in Streptococcus pneumoniae. Transposon-mutant libraries constructed in 13 CRISPRi strains enabled screening of ~24,000 gene pairs. This identified 1,334 genetic interactions, including 754 negative and 580 positive interactions. Network analyses show that 17 non-essential genes pleiotropically interact with more than half the essential genes tested. Validation experiments confirmed that a 7-gene subset protects against perturbations. Furthermore, we reveal hidden redundancies that compensate for essential gene loss, relationships between cell wall synthesis, integrity and cell division, and show that CRISPRi-TnSeq identifies synthetic and suppressor-type relationships between both functionally linked and disparate genes and pathways. Importantly, in species where CRISPRi and Tn-Seq are established, CRISPRi-TnSeq should be straightforward to implement.

Tigecycline-Rifampicin Restrains Resistance Development in Carbapenem-Resistant Klebsiella pneumoniae

The goal of this study was to clarify the synergistic antibacterial activity of the combination of tigecycline (TGC) and rifampicin (RIF). Additionally, the study sought to investigate the impact of this combination on the development of mutational resistance and to assess its efficacy in an in vivo model using Galleria mellonella. Through a checkerboard test, we found that the combination of TGC and RIF showed synergistic antibacterial activity against carbapenem-resistant Klebsiella pneumoniae (CRKP). The fractional inhibition concentration index (FICI) was found to be ≤0.5, confirming the potency of the combination. Additionally, this synergistic effect was further validated in vivo using the G. mellonella infection model. TGC-RIF treatment had a lower mutant prevention concentration (MPC) than that of monotherapy, indicating its potential to reduce the development of mutational resistance. We observed a substantial variation in the MPCs of TGC and RIF when they were measured at different proportions in the combinations. Furthermore, during the resistant mutant selection window (MSW) test, we noticed a correlation between strains with low FICI and low MSW. The expression of efflux-pump-related genes, namely rarA and acrB, is significantly decreased in the combination therapy group. This indicates that altered expression levels of certain efflux pump regulator genes are associated with a combined decrease in bacterial mutation resistance. In conclusion, the combination of TGC and RIF effectively suppresses antibiotic resistance selection in CRKP. This study establishes a paradigm for evaluating drug-resistant mutant suppression in antimicrobial combination therapy.

CRISPRi-TnSeq: A genome-wide high-throughput tool for bacterial essential-nonessential genetic interaction mapping

Genetic interaction networks can help identify functional connections between genes and pathways, which can be leveraged to establish (new) gene function, drug targets, and fill pathway gaps. Since there is no optimal tool that can map genetic interactions across many different bacterial strains and species, we develop CRISPRi-TnSeq, a genome-wide tool that maps genetic interactions between essential genes and nonessential genes through the knockdown of a targeted essential gene (CRISPRi) and the simultaneous knockout of individual nonessential genes (Tn-Seq). CRISPRi-TnSeq thereby identifies, on a genome-wide scale, synthetic and suppressor-type relationships between essential and nonessential genes, enabling the construction of essential-nonessential genetic interaction networks. To develop and optimize CRISPRi-TnSeq, CRISPRi strains were obtained for 13 essential genes in Streptococcus pneumoniae, involved in different biological processes including metabolism, DNA replication, transcription, cell division and cell envelope synthesis. Transposon-mutant libraries were constructed in each strain enabling screening of ∼24,000 gene-gene pairs, which led to the identification of 1,334 genetic interactions, including 754 negative and 580 positive genetic interactions. Through extensive network analyses and validation experiments we identify a set of 17 pleiotropic genes, of which a subset tentatively functions as genetic capacitors, dampening phenotypic outcomes and protecting against perturbations. Furthermore, we focus on the relationships between cell wall synthesis, integrity and cell division and highlight: 1) how essential gene knockdown can be compensated by rerouting flux through nonessential genes in a pathway; 2) the existence of a delicate balance between Z-ring formation and localization, and septal and peripheral peptidoglycan (PG) synthesis to successfully accomplish cell division; 3) the control of c-di-AMP over intracellular K + and turgor, and thereby modulation of the cell wall synthesis machinery; 4) the dynamic nature of cell wall protein CozEb and its effect on PG synthesis, cell shape morphology and envelope integrity; 5) functional dependency between chromosome decatenation and segregation, and the critical link with cell division, and cell wall synthesis. Overall, we show that CRISPRi-TnSeq uncovers genetic interactions between closely functionally linked genes and pathways, as well as disparate genes and pathways, highlighting pathway dependencies and valuable leads for gene function. Importantly, since both CRISPRi and Tn-Seq are widely used tools, CRISPRi-TnSeq should be relatively easy to implement to construct genetic interaction networks across many different microbial strains and species.

Gradients in gene essentiality reshape antibacterial research

Essential genes encode the processes that are necessary for life. Until recently, commonly applied binary classifications left no space between essential and non-essential genes. In this review, we frame bacterial gene essentiality in the context of genetic networks. We explore how the quantitative properties of gene essentiality are influenced by the nature of the encoded process, environmental conditions and genetic background, including a strain's distinct evolutionary history. The covered topics have important consequences for antibacterials, which inhibit essential processes. We argue that the quantitative properties of essentiality can thus be used to prioritize antibacterial cellular targets and desired spectrum of activity in specific infection settings. We summarize our points with a case study on the core essential genome of the cystic fibrosis pathobiome and highlight avenues for targeted antibacterial development.

Mutation Edgotype Drives Fitness Effect in Human

Missense mutations are known to perturb protein-protein interaction networks (known as interactome networks) in different ways. However, it remains unknown how different interactome perturbation patterns (“edgotypes”) impact organismal fitness. Here, we estimate the fitness effect of missense mutations with different interactome perturbation patterns in human, by calculating the fractions of neutral and deleterious mutations that do not disrupt PPIs (“quasi-wild-type”), or disrupt PPIs either by disrupting the binding interface (“edgetic”) or by disrupting overall protein stability (“quasi-null”). We first map pathogenic mutations and common non-pathogenic mutations onto homology-based three-dimensional structural models of proteins and protein-protein interactions in human. Next, we perform structure-based calculations to classify each mutation as either quasi-wild-type, edgetic, or quasi-null. Using our predicted as well as experimentally determined interactome perturbation patterns, we estimate that >∼40% of quasi-wild-type mutations are effectively neutral and the remaining are mostly mildly deleterious, that >∼75% of edgetic mutations are only mildly deleterious, and that up to ∼75% of quasi-null mutations may be strongly detrimental. These estimates are the first such estimates of fitness effect for different network perturbation patterns in any interactome. Our results suggest that while mutations that do not disrupt the interactome tend to be effectively neutral, the majority of human PPIs are under strong purifying selection and the stability of most human proteins is essential to human life.

τ-SGA: synthetic genetic array analysis for systematically screening and quantifying trigenic interactions in yeast

Systematic complex genetic interaction studies have provided insight into high-order functional redundancies and genetic network wiring of the cell. Here, we describe a method for screening and quantifying trigenic interactions from ordered arrays of yeast strains grown on agar plates as individual colonies. The protocol instructs users on the trigenic synthetic genetic array analysis technique, τ-SGA, for high-throughput screens. The steps describe construction of the double-mutant query strains and the corresponding single-mutant control query strains, which are screened in parallel in two replicates. The screening experimental set-up consists of sequential replica-pinning steps that enable automated mating, meiotic recombination and successive haploid selection steps for the generation of triple mutants, which are scored for colony size as a proxy for fitness, which enables the calculation of trigenic interactions. The procedure described here was used to conduct 422 trigenic interaction screens, which generated ~460,000 yeast triple mutants for trigenic interaction analysis. Users should be familiar with robotic equipment required for high-throughput genetic interaction screens and be proficient at the command line to execute the scoring pipeline. Large-scale screen computational analysis is achieved by using MATLAB pipelines that score raw colony size data to produce τ-SGA interaction scores. Additional recommendations are included for optimizing experimental design and analysis of smaller-scale trigenic interaction screens by using a web-based analysis system, SGAtools. This protocol provides a resource for those who would like to gain a deeper, more practical understanding of trigenic interaction screening and quantification methodology.

Genetic interaction mapping informs integrative structure determination of protein complexes

Determining structures of protein complexes is crucial for understanding cellular functions. Here, we describe an integrative structure determination approach that relies on in vivo measurements of genetic interactions. We construct phenotypic profiles for point mutations crossed against gene deletions or exposed to environmental perturbations, followed by converting similarities between two profiles into an upper bound on the distance between the mutated residues. We determine the structure of the yeast histone H3-H4 complex based on ~500,000 genetic interactions of 350 mutants. We then apply the method to subunits Rpb1-Rpb2 of yeast RNA polymerase II and subunits RpoB-RpoC of bacterial RNA polymerase. The accuracy is comparable to that based on chemical cross-links; using restraints from both genetic interactions and cross-links further improves model accuracy and precision. The approach provides an efficient means to augment integrative structure determination with in vivo observations.

Genetic and Chemical-Genetic Interactions Map Biogenesis and Permeability Determinants of the Outer Membrane of Escherichia coli

Gram-negative bacteria are intrinsically resistant to many antibiotics due to their outer membrane barrier. Although the outer membrane has been studied for decades, there is much to uncover about the biology and permeability of this complex structure. Investigating synthetic genetic interactions can reveal a great deal of information about genetic function and pathway interconnectivity. Here, we performed synthetic genetic arrays (SGAs) in Escherichia coli by crossing a subset of gene deletion strains implicated in outer membrane permeability with nonessential gene and small RNA (sRNA) deletion collections. Some 155,400 double-deletion strains were grown on rich microbiological medium with and without subinhibitory concentrations of two antibiotics excluded by the outer membrane, vancomycin and rifampin, to probe both genetic interactions and permeability. The genetic interactions of interest were synthetic sick or lethal (SSL) gene deletions that were detrimental to the cell in combination but had a negligible impact on viability individually. On average, there were ∼30, ∼36, and ∼40 SSL interactions per gene under no-drug, rifampin, and vancomycin conditions, respectively; however, many of these involved frequent interactors. Our data sets have been compiled into an interactive database called the Outer Membrane Interaction (OMI) Explorer, where genetic interactions can be searched, visualized across the genome, compared between conditions, and enriched for gene ontology (GO) terms. A set of SSL interactions revealed connectivity and permeability links between enterobacterial common antigen (ECA) and lipopolysaccharide (LPS) of the outer membrane. This data set provides a novel platform to generate hypotheses about outer membrane biology and permeability.IMPORTANCE Gram-negative bacteria are a major concern for public health, particularly due to the rise of antibiotic resistance. It is important to understand the biology and permeability of the outer membrane of these bacteria in order to increase the efficacy of antibiotics that have difficulty penetrating this structure. Here, we studied the genetic interactions of a subset of outer membrane-related gene deletions in the model Gram-negative bacterium E. coli We systematically combined these mutants with 3,985 nonessential gene and small RNA deletion mutations in the genome. We examined the viability of these double-deletion strains and probed their permeability characteristics using two antibiotics that have difficulty crossing the outer membrane barrier. An understanding of the genetic basis for outer membrane integrity can assist in the development of new antibiotics with favorable permeability properties and the discovery of compounds capable of increasing outer membrane permeability to enhance the activity of existing antibiotics.

Use of genetic and chemical synthetic lethality as probes of complexity in bacterial cell systems

Different conditions and genomic contexts are known to have an impact on gene essentiality and interactions. Synthetic lethal interactions occur when a combination of perturbations, either genetic or chemical, result in a more profound fitness defect than expected based on the effect of each perturbation alone. Synthetic lethality in bacterial systems has long been studied; however, during the past decade, the emerging fields of genomics and chemical genomics have led to an increase in the scale and throughput of these studies. Here, we review the concepts of genomics and chemical genomics in the context of synthetic lethality and their revolutionary roles in uncovering novel biology such as the characterization of genes of unknown function and in antibacterial drug discovery. We provide an overview of the methodologies, examples and challenges of both genetic and chemical synthetic lethal screening platforms. Finally, we discuss how to apply genetic and chemical synthetic lethal approaches to rationalize the synergies of drugs, screen for new and improved antibacterial therapies and predict drug mechanism of action.

High-Throughput Quantitative Genetic Interaction Mapping in the Fission Yeast Schizosaccharomyces pombe

Epistasis mapping, in which the phenotype that emerges from combining pairs of mutations is measured quantitatively, is a powerful tool for unbiased study of gene function. When performed at a large scale, this approach has been used to assign function to previously uncharacterized genes, define functional modules and pathways, and study their cross talk. These experiments rely heavily on methods for rapid sampling of binary combinations of mutant alleles by systematic generation of a series of double mutants. Epistasis mapping technologies now exist in various model systems. Here we provide an overview of different epistasis mapping technologies, including the pombe epistasis mapper (PEM) system designed for the collection of quantitative genetic interaction data in fission yeast Schizosaccharomyces pombe Comprising a series of high-throughput selection steps for generation and characterization of double mutants, the PEM system has provided insight into a wide range of biological processes as well as facilitated evolutionary analysis of genetic interactomes across different species.

Systematic Gene-to-Phenotype Arrays: A High-Throughput Technique for Molecular Phenotyping

We have developed a highly parallel strategy, systematic gene-to-phenotype arrays (SGPAs), to comprehensively map the genetic landscape driving molecular phenotypes of interest. By this approach, a complete yeast genetic mutant array is crossed with fluorescent reporters and imaged on membranes at high density and contrast. Importantly, SGPA enables quantification of phenotypes that are not readily detectable in ordinary genetic analysis of cell fitness. We benchmark SGPA by examining two fundamental biological phenotypes: first, we explore glucose repression, in which SGPA identifies a requirement for the Mediator complex and a role for the CDK8/kinase module in regulating transcription. Second, we examine selective protein quality control, in which SGPA identifies most known quality control factors along with U34 tRNA modification, which acts independently of proteasomal degradation to limit misfolded protein production. Integration of SGPA with other fluorescent readouts will enable genetic dissection of a wide range of biological pathways and conditions.

Suppressive drug combinations and their potential to combat antibiotic resistance

Antibiotic effectiveness often changes when two or more such drugs are administered simultaneously and unearthing antibiotic combinations with enhanced efficacy (synergy) has been a longstanding clinical goal. However, antibiotic resistance, which undermines individual drugs, threatens such combined treatments. Remarkably, it has emerged that antibiotic combinations whose combined effect is lower than that of at least one of the individual drugs can slow or even reverse the evolution of resistance. We synthesize and review studies of such so-called 'suppressive interactions' in the literature. We examine why these interactions have been largely disregarded in the past, the strategies used to identify them, their mechanistic basis, demonstrations of their potential to reverse the evolution of resistance and arguments for and against using them in clinical treatment. We suggest future directions for research on these interactions, aiming to expand the basic body of knowledge on suppression and to determine the applicability of suppressive interactions in the clinic.

Genetic interactions and functional analyses of the fission yeast gsk3 and amk2 single and double mutants defective in TORC1-dependent processes

The Target of Rapamycin (TOR) signalling network plays important roles in aging and disease. The AMP-activated protein kinase (AMPK) and the Gsk3 kinase inhibit TOR during stress. We performed genetic interaction screens using synthetic genetic arrays (SGA) with gsk3 and amk2 as query mutants, the latter encoding the regulatory subunit of AMPK. We identified 69 negative and 82 positive common genetic interactors, with functions related to cellular growth and stress. The 120 gsk3-specific negative interactors included genes functioning in translation and ribosomes. The 215 amk2-specific negative interactors included genes functioning in chromatin silencing and DNA damage repair. Both amk2- and gsk3-specific interactors were enriched in phenotype categories related to abnormal cell size and shape. We also performed SGA screen with the amk2 gsk3 double mutant as a query. Mutants sensitive to 5-fluorouracil, an anticancer drug are under-represented within the 305 positive interactors specific for the amk2 gsk3 query. The triple-mutant SGA screen showed higher number of negative interactions than the double mutant SGA screens and uncovered additional genetic network information. These results reveal common and specialized roles of AMPK and Gsk3 in mediating TOR-dependent processes, indicating that AMPK and Gsk3 act in parallel to inhibit TOR function in fission yeast.

Hypermutation signature reveals a slippage and realignment model of translesion synthesis by Rev3 polymerase in cisplatin-treated yeast

Gene-gene or gene-drug interactions are typically quantified using fitness as a readout because the data are continuous and easily measured in high throughput. However, to what extent fitness captures the range of other phenotypes that show synergistic effects is usually unknown. Using Saccharomyces cerevisiae and focusing on a matrix of DNA repair mutants and genotoxic drugs, we quantify 76 gene-drug interactions based on both mutation rate and fitness and find that these parameters are not connected. Independent of fitness defects, we identified six cases of synthetic hypermutation, where the combined effect of the drug and mutant on mutation rate was greater than predicted. One example occurred when yeast lacking RAD1 were exposed to cisplatin, and we characterized this interaction using whole-genome sequencing. Our sequencing results indicate mutagenesis by cisplatin in rad1Δ cells appeared to depend almost entirely on interstrand cross-links at GpCpN motifs. Interestingly, our data suggest that the following base on the template strand dictates the addition of the mutated base. This result differs from cisplatin mutation signatures in XPF-deficient Caenorhabditis elegans and supports a model in which translesion synthesis polymerases perform a slippage and realignment extension across from the damaged base. Accordingly, DNA polymerase ζ activity was essential for mutagenesis in cisplatin-treated rad1Δ cells. Together these data reveal the potential to gain new mechanistic insights from nonfitness measures of gene-drug interactions and extend the use of mutation accumulation and whole-genome sequencing analysis to define DNA repair mechanisms.

Module-based construction of plasmids for chromosomal integration of the fission yeast Schizosaccharomyces pombe

Integration of an external gene into a fission yeast chromosome is useful to investigate the effect of the gene product. An easy way to knock-in a gene construct is use of an integration plasmid, which can be targeted and inserted to a chromosome through homologous recombination. Despite the advantage of integration, construction of integration plasmids is energy- and time-consuming, because there is no systematic library of integration plasmids with various promoters, fluorescent protein tags, terminators and selection markers; therefore, researchers are often forced to make appropriate ones through multiple rounds of cloning procedures. Here, we establish materials and methods to easily construct integration plasmids. We introduce a convenient cloning system based on Golden Gate DNA shuffling, which enables the connection of multiple DNA fragments at once: any kind of promoters and terminators, the gene of interest, in combination with any fluorescent protein tag genes and any selection markers. Each of those DNA fragments, called a ‘module’, can be tandemly ligated in the order we desire in a single reaction, which yields a circular plasmid in a one-step manner. The resulting plasmids can be integrated through standard methods for transformation. Thus, these materials and methods help easy construction of knock-in strains, and this will further increase the value of fission yeast as a model organism.