A genome-wide atlas of antibiotic susceptibility targets and pathways to tolerance

Functional genomic analysis of genes important for Candida albicans fitness in diverse environmental conditions

Fungal pathogens such as Candida albicans pose a significant threat to human health with limited treatment options available. One strategy to expand the therapeutic target space is to identify genes important for pathogen growth in host-relevant environments. Here, we leverage a pooled functional genomic screening strategy to identify genes important for fitness of C. albicans in diverse conditions. We identify an essential gene with no known Saccharomyces cerevisiae homolog, C1_09670C, and demonstrate that it encodes subunit 3 of replication factor A (Rfa3). Furthermore, we apply computational analyses to identify functionally coherent gene clusters and predict gene function. Through this approach, we predict the cell-cycle-associated function of C3_06880W, a previously uncharacterized gene required for fitness specifically at elevated temperatures, and follow-up assays confirm that C3_06880W encodes Iml3, a component of the C. albicans kinetochore with roles in virulence in vivo. Overall, this work reveals insights into the vulnerabilities of C. albicans.

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.

CRISPRi functional genomics in bacteria and its application to medical and industrial research

SUMMARYFunctional genomics is the use of systematic gene perturbation approaches to determine the contributions of genes under conditions of interest. Although functional genomic strategies have been used in bacteria for decades, recent studies have taken advantage of CRISPR (clustered regularly interspaced short palindromic repeats) technologies, such as CRISPRi (CRISPR interference), that are capable of precisely modulating expression of all genes in the genome. Here, we discuss and review the use of CRISPRi and related technologies for bacterial functional genomics. We discuss the strengths and weaknesses of CRISPRi as well as design considerations for CRISPRi genetic screens. We also review examples of how CRISPRi screens have defined relevant genetic targets for medical and industrial applications. Finally, we outline a few of the many possible directions that could be pursued using CRISPR-based functional genomics in bacteria. Our view is that the most exciting screens and discoveries are yet to come.

The function of CozE proteins is linked to lipoteichoic acid biosynthesis in Staphylococcus aureus

Coordinated membrane and cell wall synthesis is vital for maintaining cell integrity and facilitating cell division in bacteria. However, the molecular mechanisms that underpin such coordination are poorly understood. Here we uncover the pivotal roles of the staphylococcal proteins CozEa and CozEb, members of a conserved family of membrane proteins previously implicated in bacterial cell division, in the biosynthesis of lipoteichoic acids (LTA) and maintenance of membrane homeostasis in Staphylococcus aureus. We establish that there is a synthetic lethal relationship between CozE and UgtP, the enzyme synthesizing the LTA glycolipid anchor Glc2DAG. By contrast, in cells lacking LtaA, the flippase of Glc2DAG, the essentiality of CozE proteins was alleviated, suggesting that the function of CozE proteins is linked to the synthesis and flipping of the glycolipid anchor. CozE proteins were indeed found to modulate the flipping activity of LtaA in vitro. Furthermore, CozEb was shown to control LTA polymer length and stability. Together, these findings establish CozE proteins as novel players in membrane homeostasis and LTA biosynthesis in S. aureus.IMPORTANCELipoteichoic acids are major constituents of the cell wall of Gram-positive bacteria. These anionic polymers are important virulence factors and modulators of antibiotic susceptibility in the important pathogen Staphylococcus aureus. They are also critical for maintaining cell integrity and facilitating proper cell division. In this work, we discover that a family of membrane proteins named CozE is involved in the biosynthesis of lipoteichoic acids (LTAs) in S. aureus. CozE proteins have previously been shown to affect bacterial cell division, but we here show that these proteins affect LTA length and stability, as well as the flipping of glycolipids between membrane leaflets. This new mechanism of LTA control may thus have implications for the virulence and antibiotic susceptibility of S. aureus.

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

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

High-throughput fitness experiments reveal specific vulnerabilities of human-adapted Salmonella during stress and infection

Salmonella enterica is comprised of genetically distinct 'serovars' that together provide an intriguing model for exploring the genetic basis of pathogen evolution. Although the genomes of numerous Salmonella isolates with broad variations in host range and human disease manifestations have been sequenced, the functional links between genetic and phenotypic differences among these serovars remain poorly understood. Here, we conduct high-throughput functional genomics on both generalist (Typhimurium) and human-restricted (Typhi and Paratyphi A) Salmonella at unprecedented scale in the study of this enteric pathogen. Using a comprehensive systems biology approach, we identify gene networks with serovar-specific fitness effects across 25 host-associated stresses encountered at key stages of human infection. By experimentally perturbing these networks, we characterize previously undescribed pseudogenes in human-adapted Salmonella. Overall, this work highlights specific vulnerabilities encoded within human-restricted Salmonella that are linked to the degradation of their genomes, shedding light into the evolution of this enteric pathogen.

A method to correct for local alterations in DNA copy number that bias functional genomics assays applied to antibiotic-treated bacteria

Functional genomics techniques, such as transposon insertion sequencing and RNA-sequencing, are key to studying relative differences in bacterial mutant fitness or gene expression under selective conditions. However, certain stress conditions, mutations, or antibiotics can directly interfere with DNA synthesis, resulting in systematic changes in local DNA copy numbers along the chromosome. This can lead to artifacts in sequencing-based functional genomics data when comparing antibiotic treatment to an unstressed control. Further, relative differences in gene-wise read counts may result from alterations in chromosomal replication dynamics, rather than selection or direct gene regulation. We term this artifact "chromosomal location bias" and implement a principled statistical approach to correct it by calculating local normalization factors along the chromosome. These normalization factors are then directly incorporated into statistical analyses using standard RNA-sequencing analysis methods without modifying the read counts themselves, preserving important information about the mean-variance relationship in the data. We illustrate the utility of this approach by generating and analyzing a ciprofloxacin-treated transposon insertion sequencing data set in Escherichia coli as a case study. We show that ciprofloxacin treatment generates chromosomal location bias in the resulting data, and we further demonstrate that failing to correct for this bias leads to false predictions of mutant drug sensitivity as measured by minimum inhibitory concentrations. We have developed an R package and user-friendly graphical Shiny application, ChromoCorrect, that detects and corrects for chromosomal bias in read count data, enabling the application of functional genomics technologies to the study of antibiotic stress.IMPORTANCEAltered gene dosage due to changes in DNA replication has been observed under a variety of stresses with a variety of experimental techniques. However, the implications of changes in gene dosage for sequencing-based functional genomics assays are rarely considered. We present a statistically principled approach to correcting for the effect of changes in gene dosage, enabling testing for differences in the fitness effects or regulation of individual genes in the presence of confounding differences in DNA copy number. We show that failing to correct for these effects can lead to incorrect predictions of resistance phenotype when applying functional genomics assays to investigate antibiotic stress, and we provide a user-friendly application to detect and correct for changes in DNA copy number.

Streptococcus pneumoniae favors tolerance via metabolic adaptation over resistance to circumvent fluoroquinolones

Streptococcus pneumoniae is a major human pathogen of global health concern and the rapid emergence of antibiotic resistance poses a serious public health problem worldwide. Fluoroquinolone resistance in S. pneumoniae is an intriguing case because the prevalence of fluoroquinolone resistance does not correlate with increasing usage and has remained rare. Our data indicate that deleterious fitness costs in the mammalian host constrain the emergence of fluoroquinolone resistance both by de novo mutation and recombination. S. pneumoniae was able to circumvent such deleterious fitness costs via the development of antibiotic tolerance through metabolic adaptation that reduced the production of reactive oxygen species, resulting in a fitness benefit during infection of mice treated with fluoroquinolones. These data suggest that the emergence of fluoroquinolone resistance is tightly constrained in S. pneumoniae by fitness tradeoffs and that mutational pathways involving metabolic networks to enable tolerance phenotypes are an important contributor to the evasion of antibiotic-mediated killing.IMPORTANCEThe increasing prevalence of antibiotic resistant bacteria is a major global health concern. While many species have the potential to develop antibiotic resistance, understanding the barriers to resistance emergence in the clinic remains poorly understood. A prime example of this is fluroquinolone resistance in Streptococcus pneumoniae, whereby, despite continued utilization, resistance to this class of antibiotic remains rare. In this study, we found that the predominant pathways for developing resistance to this antibiotic class severely compromised the infectious capacity of the pneumococcus, providing a key impediment for the emergence of resistance. Using in vivo models of experimental evolution, we found that S. pneumoniae responds to repeated fluoroquinolone exposure by modulating key metabolic pathways involved in the generation of redox molecules, which leads to antibiotic treatment failure in the absence of appreciable shifts in resistance levels. These data underscore the complex pathways available to pathogens to evade antibiotic mediating killing via antibiotic tolerance.

Randomly barcoded transposon mutant libraries for gut commensals II: Applying libraries for functional genetics

The critical role of the intestinal microbiota in human health and disease is well recognized. Nevertheless, there are still large gaps in our understanding of the functions and mechanisms encoded in the genomes of most members of the gut microbiota. Genome-scale libraries of transposon mutants are a powerful tool to help us address this gap. Recent advances in barcoded transposon mutagenesis have dramatically lowered the cost of mutant fitness determination in hundreds of in vitro and in vivo experimental conditions. In an accompanying review, we discuss recent advances and caveats for the construction of pooled and arrayed barcoded transposon mutant libraries in human gut commensals. In this review, we discuss how these libraries can be used across a wide range of applications, the technical aspects involved, and expectations for such screens.

Mutualism reduces the severity of gene disruptions in predictable ways across microbial communities

Predicting evolution in microbial communities is critical for problems from human health to global nutrient cycling. Understanding how species interactions impact the distribution of fitness effects for a focal population would enhance our ability to predict evolution. Specifically, does the type of ecological interaction, such as mutualism or competition, change the average effect of a mutation (i.e., the mean of the distribution of fitness effects)? Furthermore, how often does increasing community complexity alter the impact of species interactions on mutant fitness? To address these questions, we created a transposon mutant library in Salmonella enterica and measured the fitness of loss of function mutations in 3,550 genes when grown alone versus competitive co-culture or mutualistic co-culture with Escherichia coli and Methylorubrum extorquens. We found that mutualism reduces the average impact of mutations, while competition had no effect. Additionally, mutant fitness in the 3-species communities can be predicted by averaging the fitness in each 2-species community. Finally, we discovered that in the mutualism S. enterica obtained vitamins and more amino acids than previously known. Our results suggest that species interactions can predictably impact fitness effect distributions, in turn suggesting that evolution may ultimately be predictable in multi-species communities.

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.

Inhalable GSH-Triggered Nanoparticles to Treat Commensal Bacterial Infection in In Situ Lung Tumors

Bacterial infection has been considered one of the primary reasons for low survival rate of lung cancer patients. Herein, we demonstrated that a kind of mesoporous silica nanoparticles loaded with anticancer drug doxorubicin (DOX) and antimicrobial peptide HHC36 (AMP) (MSN@DOX-AMP) can kill both commensal bacteria and tumor cells under GSH-triggering, modulating the immunosuppressive tumor microenvironment, significantly treating commensal bacterial infection, and eliminating in situ lung tumors in a commensal model. Meanwhile, MSN@DOX-AMP encapsulated DOX and AMP highly efficiently via a combined strategy of physical adsorption and click chemistry and exhibited excellent hemocompatibility and biocompatibility. Importantly, MSN@DOX-AMP could be inhaled and accumulate in lung by a needle-free nebulization, achieving a better therapeutic effect. This system is expected to serve as a straightforward platform to treat commensal bacterial infections in tumors and promote the translation of such inhaled GSH-triggered MSN@DOX-AMP to clinical treatments of lung cancer.

Microbial Genomics: Innovative Targets and Mechanisms

Multidrug resistance (MDR) has become an increasing threat to global health because bacteria can develop resistance to antibiotics over time. Scientists worldwide are searching for new approaches that go beyond traditional antibiotic discovery and development pipelines. Advances in genomics, however, opened up an unexplored therapeutic opportunity for the discovery of new antibacterial agents. Genomic approaches have been used to discover several novel antibiotics that target critical processes for bacterial growth and survival, including histidine kinases (HKs), LpxC, FabI, peptide deformylase (PDF), and aminoacyl-tRNA synthetases (AaRS). In this review, we will discuss the use of microbial genomics in the search for innovative and promising drug targets as well as the mechanisms of action for novel antimicrobial agents. We will also discuss future directions on how the utilization of the microbial genomics approach could improve the odds of antibiotic development having a more successful outcome.

Overview on Strategies and Assays for Antibiotic Discovery

The increase in antibiotic resistance poses a major threat to global health. Actinomycetes, the Gram-positive bacteria of the order Actinomycetales, are fertile producers of bioactive secondary metabolites, including antibiotics. Nearly two-thirds of antibiotics that are used for the treatment of bacterial infections were originally isolated from actinomycetes strains belonging to the genus Streptomyces. This emphasizes the importance of actinomycetes in antibiotic discovery. However, the identification of a new antimicrobial compound and the exploration of its mode of action are very challenging tasks. Therefore, different approaches that enable the "detection" of an antibiotic and the characterization of the mechanisms leading to the biological activity are indispensable. Beyond bioinformatics tools facilitating the identification of biosynthetic gene clusters (BGCs), whole cell-screenings-in which cells are exposed to actinomycete-derived compounds-are a common strategy applied at the very early stage in antibiotic drug development. More recently, target-based approaches have been established. In this case, the drug candidates were tested for interactions with usually validated targets. This review focuses on the bioactivity-based screening methods and provides the readers with an overview on the most relevant assays for the identification of antibiotic activity and investigation of mechanisms of action. Moreover, the article includes examples of the successful application of these methods and suggestions for improvement.