Strain Dependent Genetic Networks for Antibiotic-Sensitivity in a Bacterial Pathogen with a Large Pan-Genome

Transposon-sequencing across multiple Mycobacterium abscessus isolates reveals significant functional genomic diversity among strains

Mycobacterium abscessus (Mab) is a clinically significant pathogen and a highly genetically diverse species due to its large accessory genome. The functional consequence of this diversity remains unknown mainly because, to date, functional genomic studies in Mab have been primarily performed on reference strains. Given the growing public health threat of Mab infections, understanding the functional genomic differences among Mab clinical isolates can provide more insight into how its genetic diversity influences gene essentiality, clinically relevant phenotypes, and importantly, potential drug targets. To determine the functional genomic diversity among Mab strains, we conducted transposon-sequencing (TnSeq) on 21 genetically diverse clinical isolates, including 15 M. abscessus subsp. abscessus isolates and 6 M. abscessus subsp. massiliense isolates, cataloging all the essential and non-essential genes in each strain. Pan-genome analysis revealed a core set of 3,845 genes and a large accessory genome of 11,507. We identified 259 core essential genes across the 21 clinical isolates and 425 differentially required genes, representing ~10% of the Mab core genome. We also identified genes whose requirements were subspecies, lineage, and isolate-specific. Finally, by correlating TnSeq profiles, we identified 19 previously uncharacterized genetic networks in Mab. Altogether, we find that Mab clinical isolates are not only genetically diverse but functionally diverse as well.

IMPORTANCE

This study investigates the genetic diversity of Mycobacterium abscessus (Mab), a bacteria known for causing difficult-to-treat infections. Researchers performed transposon-sequencing (TnSeq) on 21 different clinical isolates of Mab to identify essential and non-essential genes in each strain. Through this analysis, they identified core genes required for growth across all strains. Interestingly, they also identified genes whose requirement for growth or "essentiality" were subspecies, lineage, and isolate-specific. This study reveals that Mab's genetic diversity translates into significant functional differences among clinical isolates. Insights from this paper lay essential groundwork for future studies exploring the biological and clinical implications of genetic diversity in Mab clinical isolates. Understanding this diversity could guide targeted therapies and offer new insights into managing infections caused by Mab, a growing public health concern.

History shapes regulatory and evolutionary responses to tigecycline in strains of Acinetobacter baumannii from the pre- and post-antibiotic eras

Evolutionary history encompasses genetic and phenotypic bacterial differences, but the extent to which history influences drug response and antimicrobial resistance (AMR) adaptation is unclear. Historical contingencies arise when elements from an organism's past leave lasting effects on the genome, altering the paths available for adaptation. We utilize strains isolated before and after widespread antibiotic use to study the impact of deep historical differences shaped by decades of evolution in varying antibiotic and host pressures. We evaluated these effects by comparing immediate and adaptive responses of two strains of Acinetobacter baumannii to the last-resort antibiotic, tigecycline (TGC). When grown in subinhibitory TGC, the two strains demonstrated divergent transcriptional responses suggesting that baseline transcript levels may dictate global responses to drug and their subsequent evolutionary trajectories. Experimental evolution in TGC revealed clear differences in population-genetic dynamics - with hard sweeps in populations founded by one strain and no mutations reaching fixation in the other strain. Transcriptomes of evolved populations no longer showed signatures of drug response, as was seen in the ancestors, suggesting that genetic adaptation may outweigh preexisting differences in transcriptional networks. Genetically, AMR was acquired through predictable mechanisms of increased efflux and drug target modification; however, the two strains adapted by mutations in different efflux regulators. Fitness tradeoffs of AMR were only observed in lineages evolved from the pre-antibiotic era strain, suggesting that decades of adaptation to antibiotics resulted in preexisting compensatory mechanisms in the more contemporary isolate, an important example of a beneficial effect of historical contingencies.

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.

Saturation transposon mutagenesis enables genome-wide identification of genes required for growth and fluconazole resistance in the human fungal pathogen Cryptococcus neoformans

Fungi can cause devastating invasive infections, typically in immunocompromised patients. Treatment is complicated both by the evolutionary similarity between humans and fungi and by the frequent emergence of drug resistance. Studies in fungal pathogens have long been slowed by a lack of high-throughput tools and community resources that are common in model organisms. Here we demonstrate a high-throughput transposon mutagenesis and sequencing (TN-seq) system in Cryptococcus neoformans that enables genome-wide determination of gene essentiality. We employed a random forest machine learning approach to classify the Cryptococcus neoformans genome as essential or nonessential, predicting 1,465 essential genes, including 302 that lack human orthologs. These genes are ideal targets for new antifungal drug development. TN-seq also enables genome-wide measurement of the fitness contribution of genes to phenotypes of interest. As proof of principle, we demonstrate the genome-wide contribution of genes to growth in fluconazole, a clinically used antifungal. We show a novel role for the well-studied RIM101 pathway in fluconazole susceptibility. We also show that 5' insertions of transposons can drive sensitization of essential genes, enabling screenlike assays of both essential and nonessential components of the genome. Using this approach, we demonstrate a role for mitochondrial function in fluconazole sensitivity, such that tuning down many essential mitochondrial genes via 5' insertions can drive resistance to fluconazole. Our assay system will be valuable in future studies of C. neoformans, particularly in examining the consequences of genotypic diversity.

Floria: fast and accurate strain haplotyping in metagenomes

SUMMARY

Shotgun metagenomics allows for direct analysis of microbial community genetics, but scalable computational methods for the recovery of bacterial strain genomes from microbiomes remains a key challenge. We introduce Floria, a novel method designed for rapid and accurate recovery of strain haplotypes from short and long-read metagenome sequencing data, based on minimum error correction (MEC) read clustering and a strain-preserving network flow model. Floria can function as a standalone haplotyping method, outputting alleles and reads that co-occur on the same strain, as well as an end-to-end read-to-assembly pipeline (Floria-PL) for strain-level assembly. Benchmarking evaluations on synthetic metagenomes show that Floria is  > 3× faster and recovers 21% more strain content than base-level assembly methods (Strainberry) while being over an order of magnitude faster when only phasing is required. Applying Floria to a set of 109 deeply sequenced nanopore metagenomes took <20 min on average per sample and identified several species that have consistent strain heterogeneity. Applying Floria's short-read haplotyping to a longitudinal gut metagenomics dataset revealed a dynamic multi-strain Anaerostipes hadrus community with frequent strain loss and emergence events over 636 days. With Floria, accurate haplotyping of metagenomic datasets takes mere minutes on standard workstations, paving the way for extensive strain-level metagenomic analyses.

AVAILABILITY AND IMPLEMENTATION

Floria is available at https://github.com/bluenote-1577/floria, and the Floria-PL pipeline is available at https://github.com/jsgounot/Floria_analysis_workflow along with code for reproducing the benchmarks.

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.

Antiparasitic nitazoxanide potentiates colistin against colistin-resistant Acinetobacter baumannii and Escherichia coli in vitro and in vivo

IMPORTANCE

Colistin is used as a last resort in many infections caused by multidrug-resistant Gram-negative bacteria; however, colistin-resistant (COL-R) is on the rise. Hence, it is critical to develop new antimicrobial strategies to overcome COL-R. We found that nitazoxanide (NTZ) combined with colistin showed notable synergetic antibacterial activity. These findings suggest that the NTZ/colistin combination may provide an effective alternative route to combat COL-R A. baumannii and COL-R Escherichia coli infections.

Identification of Streptococcus pneumoniae genes associated with hypothiocyanous acid tolerance through genome-wide screening

Streptococcus pneumoniae is a commensal bacterium and invasive pathogen that causes millions of deaths worldwide. The pneumococcal vaccine offers limited protection, and the rise of antimicrobial resistance will make treatment increasingly challenging, emphasizing the need for new antipneumococcal strategies. One possibility is to target antioxidant defenses to render S. pneumoniae more susceptible to oxidants produced by the immune system. Human peroxidase enzymes will convert bacterial-derived hydrogen peroxide to hypothiocyanous acid (HOSCN) at sites of colonization and infection. Here, we used saturation transposon mutagenesis and deep sequencing to identify genes that enable S. pneumoniae to tolerate HOSCN. We identified 37 genes associated with S. pneumoniae HOSCN tolerance, including genes involved in metabolism, membrane transport, DNA repair, and oxidant detoxification. Single-gene deletion mutants of the identified antioxidant defense genes sodA, spxB, trxA, and ahpD were generated and their ability to survive HOSCN was assessed. With the exception of ΔahpD, all deletion mutants showed significantly greater sensitivity to HOSCN, validating the result of the genome-wide screen. The activity of hypothiocyanous acid reductase or glutathione reductase, known to be important for S. pneumoniae tolerance of HOSCN, was increased in three of the mutants, highlighting the compensatory potential of antioxidant systems. Double deletion of the gene encoding glutathione reductase and sodA sensitized the bacteria significantly more than single deletion. The HOSCN defense systems identified in this study may be viable targets for novel therapeutics against this deadly pathogen. IMPORTANCE Streptococcus pneumoniae is a human pathogen that causes pneumonia, bacteremia, and meningitis. Vaccination provides protection only against a quarter of the known S. pneumoniae serotypes, and the bacterium is rapidly becoming resistant to antibiotics. As such, new treatments are required. One strategy is to sensitize the bacteria to killing by the immune system. In this study, we performed a genome-wide screen to identify genes that help this bacterium resist oxidative stress exerted by the host at sites of colonization and infection. By identifying a number of critical pneumococcal defense mechanisms, our work provides novel targets for antimicrobial 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.

Occurrence of Multidrug-Resistant Bacteria Resulting from the Selective Pressure of Antibiotics: A Comprehensive Analysis of ESBL K. pneumoniae and MRSP Isolated in a Dog with Rhinorrhea

Because of public health concerns, much greater scrutiny is now placed on antibiotic use in pets, especially for antimicrobial agents that have human analogs. Therefore, this study aimed to characterize the phenotypic and genotypic profiles of multidrug-resistant bacteria isolated from nasal swabs samples taken from a one-year-old male Serra da Estrela dog with rhinorrhea that was treated with amikacin. An extended-spectrum β-lactamases (ESBL) Klebsiella pneumoniae was isolated in the first sample taken from the left nasal cavity of the dog. Seven days later, methicillin-resistant (MRSP) Staphylococcus pseudintermedius was also isolated. Nevertheless, no alterations to the therapeutic protocol were performed. Once the inhibitory action of the antibiotic disappeared, the competitive advantage of the amikacin-resistant MRSP was lost, and only commensal flora was observed on both nasal cavities. The genotypic profile of extended-spectrum β-lactamase (ESBL)-producing Klebsiella pneumoniae revealed the same characteristics and close relation to other strains, mainly from Estonia, Slovakia and Romania. Regarding MRSP isolates, although resistance to aminoglycosides was present in the first MRSP, the second isolate carried aac(6')-aph(2″), which enhanced its resistance to amikacin. However, the veterinary action was focused on the treatment of the primary agent (ESBL K. pneumoniae), and the antibiotic applied was according to its phenotypic profile, which may have led to the resolution of the infectious process. Therefore, this study highlights the importance of targeted therapy, proper clinical practice and laboratory-hospital communication to safeguard animal, human and environmental health.

Compendium-Wide Analysis of Pseudomonas aeruginosa Core and Accessory Genes Reveals Transcriptional Patterns across Strains PAO1 and PA14

Pseudomonas aeruginosa is an opportunistic pathogen that causes difficult-to-treat infections. Two well-studied divergent P. aeruginosa strain types, PAO1 and PA14, have significant genomic heterogeneity, including diverse accessory genes present in only some strains. Genome content comparisons find core genes that are conserved across both PAO1 and PA14 strains and accessory genes that are present in only a subset of PAO1 and PA14 strains. Here, we use recently assembled transcriptome compendia of publicly available P. aeruginosa RNA sequencing (RNA-seq) samples to create two smaller compendia consisting of only strain PAO1 or strain PA14 samples with each aligned to their cognate reference genome. We confirmed strain annotations and identified other samples for inclusion by assessing each sample's median expression of PAO1-only or PA14-only accessory genes. We then compared the patterns of core gene expression in each strain. To do so, we developed a method by which we analyzed genes in terms of which genes showed similar expression patterns across strain types. We found that some core genes had consistent correlated expression patterns across both compendia, while others were less stable in an interstrain comparison. For each accessory gene, we also determined core genes with correlated expression patterns. We found that stable core genes had fewer coexpressed neighbors that were accessory genes. Overall, this approach for analyzing expression patterns across strain types can be extended to other groups of genes, like phage genes, or applied for analyzing patterns beyond groups of strains, such as samples with different traits, to reveal a deeper understanding of regulation. IMPORTANCE Pseudomonas aeruginosa is a ubiquitous pathogen. There is much diversity among P. aeruginosa strains, including two divergent but well-studied strains, PAO1 and PA14. Understanding how these different strain-level traits manifest is important for identifying targets that regulate different traits of interest. With the availability of thousands of PAO1 and PA14 samples, we created two strain-specific RNA-seq compendia where each one contains hundreds of samples from PAO1 or PA14 strains and used them to compare the expression patterns of core genes that are conserved in both strain types and to determine which core genes have expression patterns that are similar to those of accessory genes that are unique to one strain or the other using an approach that we developed. We found a subset of core genes with different transcriptional patterns across PAO1 and PA14 strains and identified those core genes with expression patterns similar to those of strain-specific accessory genes.

Transposon mutagenesis in oral streptococcus

Oral streptococci are gram-positive facultative anaerobic bacteria that are normal inhabitants of the human oral cavity and play an important role in maintaining oral microecological balance and pathogenesis. Transposon mutagenesis is an effective genetic manipulation strategy for studying the function of genomic features. In order to study cariogenic related genes and crucial biological element genes of oral Streptococcus, transposon mutagenesis was widely used to identify functional genes. With the advent of next-generation sequencing (NGS) technology and the development of transposon random mutation library construction methods, transposon insertion sequencing (TIS) came into being. Benefiting from high-throughput advances in NGS, TIS was able to evaluate the fitness contribution and essentiality of genetic features in the bacterial genome. The application of transposon mutagenesis, including TIS, to oral streptococci provided a massive amount of valuable detailed linkage data between genetic fitness and genetic backgrounds, further clarify the processes of colonization, virulence, and persistence and provides a more reliable basis for investigating relationships with host ecology and disease status. This review focuses on transposon mutagenesis, including TIS, and its applicability in oral streptococci.

Genome-wide association studies reveal distinct genetic correlates and increased heritability of antimicrobial resistance in Vibrio cholerae under anaerobic conditions

The antibiotic formulary is threatened by high rates of antimicrobial resistance (AMR) among enteropathogens. Enteric bacteria are exposed to anaerobic conditions within the gastrointestinal tract, yet little is known about how oxygen exposure influences AMR. The facultative anaerobe Vibrio cholerae was chosen as a model to address this knowledge gap. We obtained V. cholerae isolates from 66 cholera patients, sequenced their genomes, and grew them under anaerobic and aerobic conditions with and without three clinically relevant antibiotics (ciprofloxacin, azithromycin, doxycycline). For ciprofloxacin and azithromycin, the minimum inhibitory concentration (MIC) increased under anaerobic conditions compared to aerobic conditions. Using standard resistance breakpoints, the odds of classifying isolates as resistant increased over 10 times for ciprofloxacin and 100 times for azithromycin under anaerobic conditions compared to aerobic conditions. For doxycycline, nearly all isolates were sensitive under both conditions. Using genome-wide association studies, we found associations between genetic elements and AMR phenotypes that varied by oxygen exposure and antibiotic concentrations. These AMR phenotypes were more heritable, and the AMR-associated genetic elements were more often discovered, under anaerobic conditions. These AMR-associated genetic elements are promising targets for future mechanistic research. Our findings provide a rationale to determine whether increased MICs under anaerobic conditions are associated with therapeutic failures and/or microbial escape in cholera patients. If so, there may be a need to determine new AMR breakpoints for anaerobic conditions.

A bacterial pan-genome makes gene essentiality strain-dependent and evolvable

Many bacterial species are represented by a pan-genome, whose genetic repertoire far outstrips that of any single bacterial genome. Here we investigate how a bacterial pan-genome might influence gene essentiality and whether essential genes that are initially critical for the survival of an organism can evolve to become non-essential. By using Transposon insertion sequencing (Tn-seq), whole-genome sequencing and RNA-seq on a set of 36 clinical Streptococcus pneumoniae strains representative of >68% of the species' pan-genome, we identify a species-wide 'essentialome' that can be subdivided into universal, core strain-specific and accessory essential genes. By employing 'forced-evolution experiments', we show that specific genetic changes allow bacteria to bypass essentiality. Moreover, by untangling several genetic mechanisms, we show that gene essentiality can be highly influenced by and/or be dependent on: (1) the composition of the accessory genome, (2) the accumulation of toxic intermediates, (3) functional redundancy, (4) efficient recycling of critical metabolites and (5) pathway rewiring. While this functional characterization underscores the evolvability potential of many essential genes, we also show that genes with differential essentiality remain important antimicrobial drug target candidates, as their inactivation almost always has a severe fitness cost in vivo.

Using genome-wide expression compendia to study microorganisms

A gene expression compendium is a heterogeneous collection of gene expression experiments assembled from data collected for diverse purposes. The widely varied experimental conditions and genetic backgrounds across samples creates a tremendous opportunity for gaining a systems level understanding of the transcriptional responses that influence phenotypes. Variety in experimental design is particularly important for studying microbes, where the transcriptional responses integrate many signals and demonstrate plasticity across strains including response to what nutrients are available and what microbes are present. Advances in high-throughput measurement technology have made it feasible to construct compendia for many microbes. In this review we discuss how these compendia are constructed and analyzed to reveal transcriptional patterns.

Antimicrobial tolerance and its role in the development of resistance: Lessons from enterococci

Bacteria have developed resistance against every antimicrobial in clinical use at an alarming rate. There is a critical need for more effective use of antimicrobials to both extend their shelf life and prevent resistance from arising. Significantly, antimicrobial tolerance, i.e., the ability to survive but not proliferate during antimicrobial exposure, has been shown to precede the development of bona fide antimicrobial resistance (AMR), sparking a renewed and rapidly increasing interest in this field. As a consequence, problematic infections for the first time are now being investigated for antimicrobial tolerance, with increasing reports demonstrating in-host evolution of antimicrobial tolerance. Tolerance has been identified in a wide array of bacterial species to all bactericidal antimicrobials. Of particular interest are enterococci, which contain the opportunistic bacterial pathogens Enterococcus faecalis and Enterococcus faecium. Enterococci are one of the leading causes of hospital-acquired infection and possess intrinsic tolerance to a number of antimicrobial classes. Persistence of these infections in the clinic is of growing concern, particularly for the immunocompromised. Here, we review current known mechanisms of antimicrobial tolerance, and include an in-depth analysis of those identified in enterococci with implications for both the development and prevention of AMR.

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

Detailed knowledge on how bacteria evade antibiotics and eventually develop resistance could open avenues for novel therapeutics and diagnostics. It is thereby key to develop a comprehensive genome-wide understanding of how bacteria process antibiotic stress, and how modulation of the involved processes affects their ability to overcome said stress. Here we undertake a comprehensive genetic analysis of how the human pathogen Streptococcus pneumoniae responds to 20 antibiotics. We build a genome-wide atlas of drug susceptibility determinants and generated a genetic interaction network that connects cellular processes and genes of unknown function, which we show can be used as therapeutic targets. Pathway analysis reveals a genome-wide atlas of cellular processes that can make a bacterium less susceptible, and often tolerant, in an antibiotic specific manner. Importantly, modulation of these processes confers fitness benefits during active infections under antibiotic selection. Moreover, screening of sequenced clinical isolates demonstrates that mutations in genes that decrease antibiotic sensitivity and increase tolerance readily evolve and are frequently associated with resistant strains, indicating such mutations could be harbingers for the emergence of antibiotic resistance.

Inhibition of Streptococcus pneumoniae growth by masarimycin

Despite renewed interest, development of chemical biology methods to study peptidoglycan metabolism has lagged in comparison to the glycobiology field in general. To address this, a panel of diamides were screened against the Gram-positive bacterium Streptococcus pneumoniae to identify inhibitors of bacterial growth. The screen identified the diamide masarimycin as a bacteriostatic inhibitor of S. pneumoniae growth with an MIC of 8 µM. The diamide inhibited detergent-induced autolysis in a concentration-dependent manner, indicating perturbation of peptidoglycan degradation as the mode-of-action. Cell based screening of masarimycin against a panel of autolysin mutants, identified a higher MIC against a ΔlytB strain lacking an endo-N-acetylglucosaminidase involved in cell division. Subsequent biochemical and phenotypic analyses suggested that the higher MIC was due to an indirect interaction with LytB. Further analysis of changes to the cell surface in masarimycin treated cells identified the overexpression of several moonlighting proteins, including elongation factor Tu which is implicated in regulating cell shape. Checkerboard assays using masarimycin in concert with additional antibiotics identified an antagonistic relationship with the cell wall targeting antibiotic fosfomycin, which further supports a cell wall mode-of-action.

Multiplexed Strain Phenotyping Defines Consequences of Genetic Diversity in Mycobacterium tuberculosis for Infection and Vaccination Outcomes

There is growing evidence that genetic diversity in Mycobacterium tuberculosis, the causative agent of tuberculosis, contributes to the outcomes of infection and public health interventions, such as vaccination. Epidemiological studies suggest that among the phylogeographic lineages of M. tuberculosis, strains belonging to a sublineage of Lineage 2 (mL2) are associated with concerning clinical features, including hypervirulence, treatment failure, and vaccine escape. The global expansion and increasing prevalence of this sublineage has been attributed to the selective advantage conferred by these characteristics, yet confounding host and environmental factors make it difficult to identify the bacterial determinants driving these associations in human studies. Here, we developed a molecular barcoding strategy to facilitate high-throughput, experimental phenotyping of M. tuberculosis clinical isolates. This approach allowed us to characterize growth dynamics for a panel of genetically diverse M. tuberculosis strains during infection and after vaccination in the mouse model. We found that mL2 strains exhibit distinct growth dynamics in vivo and are resistant to the immune protection conferred by Bacillus Calmette-Guerin (BCG) vaccination. The latter finding corroborates epidemiological observations and demonstrates that mycobacterial features contribute to vaccine efficacy. To investigate the genetic and biological basis of mL2 strains’ distinctive phenotypes, we performed variant analysis, transcriptional studies, and genome-wide transposon sequencing. We identified functional genetic changes across multiple stress and host response pathways in a representative mL2 strain that are associated with variants in regulatory genes. These adaptive changes may underlie the distinct clinical characteristics and epidemiological success of this lineage.

IMPORTANCE Tuberculosis, caused by the bacterium Mycobacterium tuberculosis, is a remarkably heterogeneous disease, a feature that complicates clinical care and public health interventions. The contributions of pathogen genetic diversity to this heterogeneity are uncertain, in part due to the challenges of experimentally manipulating M. tuberculosis, a slow-growing, biosafety level 3 organism. To overcome these challenges, we applied a molecular barcoding strategy to a panel of M. tuberculosis clinical isolates. This novel application of barcoding permitted the high-throughput characterization of M. tuberculosis strain growth dynamics and vaccine resistance in the mouse model of infection. Integrating these results with genomic analyses, we uncover bacterial pathways that contribute to infection outcomes, suggesting targets for improved therapeutics and vaccines.

Functional Mapping of Phenotypic Plasticity of Staphylococcus aureus Under Vancomycin Pressure

Phenotypic plasticity is the exhibition of various phenotypic traits produced by a single genotype in response to environmental changes, enabling organisms to adapt to environmental changes by maintaining growth and reproduction. Despite its significance in evolutionary studies, we still know little about the genetic control of phenotypic plasticity. In this study, we designed and conducted a genome-wide association study (GWAS) to reveal genetic architecture of how Staphylococcus aureus strains respond to increasing concentrations of vancomycin (0, 2, 4, and 6 μg/mL) in a time course. We implemented functional mapping, a dynamic model for genetic mapping using longitudinal data, to map specific loci that mediate the growth trajectories of abundance of vancomycin-exposed S. aureus strains. 78 significant single nucleotide polymorphisms were identified following analysis of the whole growth and development process, and seven genes might play a pivotal role in governing phenotypic plasticity to the pressure of vancomycin. These seven genes, SAOUHSC_00020 (walR), SAOUHSC_00176, SAOUHSC_00544 (sdrC), SAOUHSC_02998, SAOUHSC_00025, SAOUHSC_00169, and SAOUHSC_02023, were found to help S. aureus regulate antibiotic pressure. Our dynamic gene mapping technique provides a tool for dissecting the phenotypic plasticity mechanisms of S. aureus under vancomycin pressure, emphasizing the feasibility and potential of functional mapping in the study of bacterial phenotypic plasticity.

Next-generation microbiology: from comparative genomics to gene function

Microbiology is at a turning point in its 120-year history. Widespread next-generation sequencing has revealed genetic complexity among bacteria that could hardly have been imagined by pioneers such as Pasteur, Escherich and Koch. This data cascade brings enormous potential to improve our understanding of individual bacterial cells and the genetic basis of phenotype variation. However, this revolution in data science cannot replace established microbiology practices, presenting the challenge of how to integrate these new techniques. Contrasting comparative and functional genomic approaches, we evoke molecular microbiology theory and established practice to present a conceptual framework and practical roadmap for next-generation microbiology.

Antibacterial Titanium Implants Biofunctionalized by Plasma Electrolytic Oxidation with Silver, Zinc, and Copper: A Systematic Review

Patients receiving orthopedic implants are at risk of implant-associated infections (IAI). A growing number of antibiotic-resistant bacteria threaten to hamper the treatment of IAI. The focus has, therefore, shifted towards the development of implants with intrinsic antibacterial activity to prevent the occurrence of infection. The use of Ag, Cu, and Zn has gained momentum as these elements display strong antibacterial behavior and target a wide spectrum of bacteria. In order to incorporate these elements into the surface of titanium-based bone implants, plasma electrolytic oxidation (PEO) has been widely investigated as a single-step process that can biofunctionalize these (highly porous) implant surfaces. Here, we present a systematic review of the studies published between 2009 until 2020 on the biomaterial properties, antibacterial behavior, and biocompatibility of titanium implants biofunctionalized by PEO using Ag, Cu, and Zn. We observed that 100% of surfaces bearing Ag (Ag-surfaces), 93% of surfaces bearing Cu (Cu-surfaces), 73% of surfaces bearing Zn (Zn-surfaces), and 100% of surfaces combining Ag, Cu, and Zn resulted in a significant (i.e., >50%) reduction of bacterial load, while 13% of Ag-surfaces, 10% of Cu-surfaces, and none of Zn or combined Ag, Cu, and Zn surfaces reported cytotoxicity against osteoblasts, stem cells, and immune cells. A majority of the studies investigated the antibacterial activity against S. aureus. Important areas for future research include the biofunctionalization of additively manufactured porous implants and surfaces combining Ag, Cu, and Zn. Furthermore, the antibacterial activity of such implants should be determined in assays focused on prevention, rather than the treatment of IAIs. These implants should be tested using appropriate in vivo bone infection models capable of assessing whether titanium implants biofunctionalized by PEO with Ag, Cu, and Zn can contribute to protect patients against IAI.

The impact of genetic diversity on gene essentiality within the Escherichia coli species

Bacteria from the same species can differ widely in their gene content. In Escherichia coli, the set of genes shared by all strains, known as the core genome, represents about half the number of genes present in any strain. Although recent advances in bacterial genomics have unravelled genes required for fitness in various experimental conditions, most studies have focused on single model strains. As a result, the impact of the species' genetic diversity on core processes of the bacterial cell remains largely under-investigated. Here, we have developed a CRISPR interference platform for high-throughput gene repression that is compatible with most E. coli isolates and closely related species. We have applied it to assess the importance of ~3,400 nearly ubiquitous genes in three growth conditions in 18 representative E. coli strains spanning most common phylogroups and lifestyles of the species. Our screens revealed extensive variations in gene essentiality between strains and conditions. Investigation of the genetic determinants for these variations highlighted the importance of epistatic interactions with mobile genetic elements. In particular, we have shown how prophage-encoded defence systems against phage infection can trigger the essentiality of persistent genes that are usually non-essential. This study provides broad insights into the evolvability of gene essentiality and argues for the importance of studying various isolates from the same species under diverse conditions.

Transposon Insertion Sequencing, a Global Measure of Gene Function

The goal of genomics and systems biology is to understand how complex systems of factors assemble into pathways and structures that combine to form living organisms. Great advances in understanding biological processes result from determining the function of individual genes, a process that has classically relied on characterizing single mutations. Advances in DNA sequencing has made available the complete set of genetic instructions for an astonishing and growing number of species. To understand the function of this ever-increasing number of genes, a high-throughput method was developed that in a single experiment can measure the function of genes across the genome of an organism. This occurred approximately 10 years ago, when high-throughput DNA sequencing was combined with advances in transposon-mediated mutagenesis in a method termed transposon insertion sequencing (TIS). In the subsequent years, TIS succeeded in addressing fundamental questions regarding the genes of bacteria, many of which have been shown to play central roles in bacterial infections that result in major human diseases. The field of TIS has matured and resulted in studies of hundreds of species that include significant innovations with a number of transposons. Here, we summarize a number of TIS experiments to provide an understanding of the method and explanation of approaches that are instructive when designing a study. Importantly, we emphasize critical aspects of a TIS experiment and highlight the extension and applicability of TIS into nonbacterial species such as yeast.

Entropy of a bacterial stress response is a generalizable predictor for fitness and antibiotic sensitivity

Current approaches explore bacterial genes that change transcriptionally upon stress exposure as diagnostics to predict antibiotic sensitivity. However, transcriptional changes are often specific to a species or antibiotic, limiting implementation to known settings only. While a generalizable approach, predicting bacterial fitness independent of strain, species or type of stress, would eliminate such limitations, it is unclear whether a stress-response can be universally captured. By generating a multi-stress and species RNA-Seq and experimental evolution dataset, we highlight the strengths and limitations of existing gene-panel based methods. Subsequently, we build a generalizable method around the observation that global transcriptional disorder seems to be a common, low-fitness, stress response. We quantify this disorder using entropy, which is a specific measure of randomness, and find that in low fitness cases increasing entropy and transcriptional disorder results from a loss of regulatory gene-dependencies. Using entropy as a single feature, we show that fitness and quantitative antibiotic sensitivity predictions can be made that generalize well beyond training data. Furthermore, we validate entropy-based predictions in 7 species under antibiotic and non-antibiotic conditions. By demonstrating the feasibility of universal predictions of bacterial fitness, this work establishes the fundamentals for potentially new approaches in infectious disease diagnostics.

Genomic Profiling Reveals Distinct Routes To Complement Resistance in Klebsiella pneumoniae

The serum complement system is a first line of defense against bacterial invaders. Resistance to killing by serum enhances the capacity of Klebsiella pneumoniae to cause infection, but it is an incompletely understood virulence trait. Identifying and characterizing the factors responsible for preventing activation of, and killing by, serum complement could inform new approaches to treatment of K. pneumoniae infections. Here, we used functional genomic profiling to define the genetic basis of complement resistance in four diverse serum-resistant K. pneumoniae strains (NTUH-K2044, B5055, ATCC 43816, and RH201207), and explored their recognition by key complement components.

The serum complement system is a first line of defense against bacterial invaders. Resistance to killing by serum enhances the capacity of Klebsiella pneumoniae to cause infection, but it is an incompletely understood virulence trait. Identifying and characterizing the factors responsible for preventing activation of, and killing by, serum complement could inform new approaches to treatment of K. pneumoniae infections. Here, we used functional genomic profiling to define the genetic basis of complement resistance in four diverse serum-resistant K. pneumoniae strains (NTUH-K2044, B5055, ATCC 43816, and RH201207), and explored their recognition by key complement components. More than 90 genes contributed to resistance in one or more strains, but only three, rfaH, lpp, and arnD, were common to all four strains. Deletion of the antiterminator rfaH, which controls the expression of capsule and O side chains, resulted in dramatic complement resistance reductions in all strains. The murein lipoprotein gene lpp promoted capsule retention through a mechanism dependent on its C-terminal lysine residue; its deletion led to modest reductions in complement resistance. Binding experiments with the complement components C3b and C5b-9 showed that the underlying mechanism of evasion varied in the four strains: B5055 and NTUH-K2044 appeared to bypass recognition by complement entirely, while ATCC 43816 and RH201207 were able to resist killing despite being associated with substantial levels of C5b-9. All rfaH and lpp mutants bound C3b and C5b-9 in large quantities. Our findings show that, even among this small selection of isolates, K. pneumoniae adopts differing mechanisms and utilizes distinct gene sets to avoid complement attack.

Regulation of virulence and antibiotic resistance in Gram-positive microbes in response to cell wall-active antibiotics

PURPOSE OF REVIEW

Antibiotic stress can evoke considerable genotypic and phenotypic changes in Gram-positive bacteria. Here, we review recent studies describing altered virulence expression in response to cell wall-acting antibiotics and discuss mechanisms that coordinate regulation of the antibiotic response.

RECENT FINDINGS

Pleiotropic effects induced by antibiotic exposure include alterations to bacterial metabolism, cell wall structure and antibiotic resistance. In addition, subinhibitory concentrations of cell wall-active (CWA) antibiotics have increasingly been shown to induce the production of exotoxins and biofilm formation that may influence virulence. Remarkably, phenotypes associated with comparable antibiotic stresses can vary considerably, emphasizing the need to better understand the response to CWA antibiotics. Recent studies support both direct antibiotic recognition and recognition of antibiotic-induced stress to the bacterial cell wall. Specifically, bacterial two-component systems, penicillin-binding protein and serine/threonine kinase-associated kinases and conserved oxidative-stress sensors each contribute to modulating the antibiotic stress response.

SUMMARY

Bacterial sensory systems and global regulators coordinate signaling in response to CWA antibiotics. Regulation of the antibiotic response is complex and involves integration of signals from multiple response pathways. A better definition of the antibiotic stress response among Gram-positive pathogens may yield novel therapeutic targets to counter antibiotic resistance and virulence factor expression.

A decade of advances in transposon-insertion sequencing

It has been 10 years since the introduction of modern transposon-insertion sequencing (TIS) methods, which combine genome-wide transposon mutagenesis with high-throughput sequencing to estimate the fitness contribution or essentiality of each genetic component in a bacterial genome. Four TIS variations were published in 2009: transposon sequencing (Tn-Seq), transposon-directed insertion site sequencing (TraDIS), insertion sequencing (INSeq) and high-throughput insertion tracking by deep sequencing (HITS). TIS has since become an important tool for molecular microbiologists, being one of the few genome-wide techniques that directly links phenotype to genotype and ultimately can assign gene function. In this Review, we discuss the recent applications of TIS to answer overarching biological questions. We explore emerging and multidisciplinary methods that build on TIS, with an eye towards future applications.

In this Review, several experts discuss progress in the decade since the development of transposon-based approaches for bacterial genetic screens. They describe how advances in both experimental technologies and analytical strategies are resulting in insights into diverse biological processes.

ShinyOmics: collaborative exploration of omics-data

BACKGROUND

Omics-profiling is a collection of increasingly prominent approaches that result in large-scale biological datasets, for instance capturing an organism's behavior and response in an environment. It can be daunting to manually analyze and interpret such large datasets without some programming experience. Additionally, with increasing amounts of data; management, storage and sharing challenges arise.

RESULTS

Here, we present ShinyOmics, a web-based application that allows rapid collaborative exploration of omics-data. By using Tn-Seq, RNA-Seq, microarray and proteomics datasets from two human pathogens, we exemplify several conclusions that can be drawn from a rich dataset. We identify a protease and several chaperone proteins upregulated under aminoglycoside stress, show that antibiotics with the same mechanism of action trigger similar transcriptomic responses, point out the dissimilarity in different omics-profiles, and overlay the transcriptional response on a metabolic network.

CONCLUSIONS

ShinyOmics is easy to set up and customize, and can utilize user supplied metadata. It offers several visualization and comparison options that are designed to assist in novel hypothesis generation, as well as data management, online sharing and exploration. Moreover, ShinyOmics can be used as an interactive supplement accompanying research articles or presentations.

Multi-strain Tn-Seq reveals common daptomycin resistance determinants in Staphylococcus aureus

Antibiotic-resistant Staphylococcus aureus remains a leading cause of antibiotic resistance-associated mortality in the United States. Given the reality of multi-drug resistant infections, it is imperative that we establish and maintain a pipeline of new compounds to replace or supplement our current antibiotics. A first step towards this goal is to prioritize targets by identifying the genes most consistently required for survival across the S. aureus phylogeny. Here we report the first direct comparison of multiple strains of S. aureus via transposon sequencing. We show that mutant fitness varies by strain in key pathways, underscoring the importance of using more than one strain to differentiate between core and strain-dependent essential genes. We treated the libraries with daptomycin to assess whether the strain-dependent differences impact pathways important for survival. Despite baseline differences in gene importance, several pathways, including the lipoteichoic acid pathway, consistently promote survival under daptomycin exposure, suggesting core vulnerabilities that can be exploited to resensitize daptomycin-nonsusceptible isolates. We also demonstrate the merit of using transposons with outward-facing promoters capable of overexpressing nearby genes for identifying clinically-relevant gain-of-function resistance mechanisms. Together, the daptomycin vulnerabilities and resistance mechanisms support a mode of action with wide-ranging effects on the cell envelope and cell division. This work adds to a growing body of literature demonstrating the nuanced insights gained by comparing Tn-Seq results across multiple bacterial strains.

Antibiotic-resistant Staphylococcus aureus kills thousands of people every year in the United States alone. To stay ahead of the looming threat of multidrug-resistant infections, we must continue to develop new antibiotics and find ways to make our current repertoire of antibiotics more effective, including by finding pairs of compounds that perform best when administered together. In the age of next-generation sequencing, we can now use transposon sequencing to find potential targets for new antibiotics on a genome-wide scale, identified as either essential genes or genes that positively influence survival in the presence of an antibiotic. In this work, we created a compendium of genes that are essential across a range of S. aureus strains, as well as those that are important for growth in the presence of the antibiotic daptomycin. The results will be a resource for researchers working to develop the next generation of antibiotic therapies.

Genetic interaction networks mediate individual statin drug response in Saccharomyces cerevisiae

Eukaryotic genetic interaction networks (GINs) are extensively described in the Saccharomyces cerevisiae S288C model using deletion libraries, yet being limited to this one genetic background, not informative to individual drug response. Here we created deletion libraries in three additional genetic backgrounds. Statin response was probed with five queries against four genetic backgrounds. The 20 resultant GINs representing drug-gene and gene-gene interactions were not conserved by functional enrichment, hierarchical clustering, and topology-based community partitioning. An unfolded protein response (UPR) community exhibited genetic background variation including different betweenness genes that were network bottlenecks, and we experimentally validated this UPR community via measurements of the UPR that were differentially activated and regulated in statin-resistant strains relative to the statin-sensitive S288C background. These network analyses by topology and function provide insight into the complexity of drug response influenced by genetic background.

Antimicrobial resistance in mollicutes: known and newly emerging mechanisms

This review is devoted to the mechanisms of antibiotic resistance in mollicutes (class Bacilli, subclass Mollicutes), the smallest self-replicating bacteria, that can cause diseases in plants, animals and humans, and also contaminate cell cultures and vaccine preparations. Research in this area has been mainly based on the ubiquitous mollicute and the main contaminant of cell cultures, Acholeplasma laidlawii. The omics technologies applied to this and other bacteria have yielded a complex picture of responses to antimicrobials, including their removal from the cell, the acquisition of antibiotic resistance genes and mutations that potentially allow global reprogramming of many cellular processes. This review provides a brief summary of well-known resistance mechanisms that have been demonstrated in several mollicutes species and, in more detail, novel mechanisms revealed in A. laidlawii, including the least explored vesicle-mediated transfer of short RNAs with a regulatory potency. We hope that this review highlights new avenues for further studies on antimicrobial resistance in these bacteria for both a basic science and an application perspective of infection control and management in clinical and research/production settings.

The Landscape of Phenotypic and Transcriptional Responses to Ciprofloxacin in Acinetobacter baumannii: Acquired Resistance Alleles Modulate Drug-Induced SOS Response and Prophage Replication

The emergence of fluoroquinolone resistance in nosocomial pathogens has restricted the clinical efficacy of this antibiotic class. In Acinetobacter baumannii, the majority of clinical isolates now show high-level resistance due to mutations in gyrA (DNA gyrase) and parC (topoisomerase IV [topo IV]). To investigate the molecular basis for fluoroquinolone resistance, an exhaustive mutation analysis was performed in both drug-sensitive and -resistant strains to identify loci that alter ciprofloxacin sensitivity. To this end, parallel fitness tests of over 60,000 unique insertion mutations were performed in strains with various alleles in genes encoding the drug targets. The spectra of mutations that altered drug sensitivity were found to be similar in the drug-sensitive and gyrA parC double-mutant backgrounds, having resistance alleles in both genes. In contrast, the introduction of a single gyrA resistance allele, resulting in preferential poisoning of topo IV by ciprofloxacin, led to extreme alterations in the insertion mutation fitness landscape. The distinguishing feature of preferential topo IV poisoning was enhanced induction of DNA synthesis in the region of two endogenous prophages, with DNA synthesis associated with excision and circularization of the phages. Induction of the selective DNA synthesis in the gyrA background was also linked to heightened prophage gene transcription and enhanced activation of the mutagenic SOS response relative to that observed in either the wild-type (WT) or gyrA parC double mutant. Therefore, the accumulation of mutations that result in the stepwise evolution of high ciprofloxacin resistance is tightly connected to modulation of the SOS response and endogenous prophage DNA synthesis.IMPORTANCE Fluoroquinolones have been extremely successful antibiotics due to their ability to target multiple bacterial enzymes critical to DNA replication, the topoisomerases DNA gyrase and topo IV. Unfortunately, mutations lowering drug affinity for both enzymes are now widespread, rendering these drugs ineffective for many pathogens. To undermine this form of resistance, we examined how bacteria with target alterations differentially cope with fluoroquinolone exposures. We studied this problem in the nosocomial pathogen A. baumannii, which causes drug-resistant life-threatening infections. Employing genome-wide approaches, we uncovered numerous pathways that could be exploited to raise fluoroquinolone sensitivity independently of target alteration. Remarkably, fluoroquinolone targeting of topo IV in specific mutants caused dramatic hyperinduction of prophage replication and enhanced the mutagenic DNA damage response, but these responses were muted in strains with DNA gyrase as the primary target. This work demonstrates that resistance evolution via target modification can profoundly modulate the antibiotic stress response, revealing potential resistance-associated liabilities.

Bacterial Factors Required for Transmission of Streptococcus pneumoniae in Mammalian Hosts

The capacity of Streptococcus pneumoniae to successfully transmit and colonize new human hosts is a critical aspect of pneumococcal population biology and a prerequisite for invasive disease. However, the bacterial mechanisms underlying this process remain largely unknown. To identify bacterial factors required for transmission, we conducted a high-throughput genetic screen with a transposon sequencing (Tn-seq) library of a pneumococcal strain in a ferret transmission model. Key players in both metabolism and transcriptional regulation were identified as required for efficient bacterial transmission. Targeted deletion of the putative C3-degrading protease CppA, iron transporter PiaA, or competence regulatory histidine kinase ComD significantly decreased transmissibility in a mouse model, further validating the screen. Maternal vaccination with recombinant surface-exposed PiaA and CppA alone or in combination blocked transmission in offspring and were more effective than capsule-based vaccines. These data underscore the possibility of targeting pneumococcal transmission as a means of eliminating invasive disease in the population.

Phenotypic Plasticity of Staphylococcus aureus in Liquid Medium Containing Vancomycin

Phenotypic plasticity enables individuals to develop different phenotypes in a changing environment and promotes adaptive evolution. Genome-wide association study (GWAS) facilitates the study of the genetic basis of bacterial phenotypes, and provides a new opportunity for bacterial phenotypic plasticity research. To investigate the relationship between growth plasticity and genotype in bacteria, 41 Staphylococcus aureus strains, including 29 vancomycin-intermediate S. aureus (VISA) strains, were inoculated in the absence or presence of vancomycin for 48 h. Growth curves and maximum growth rates revealed that strains with the same minimum inhibitory concentration (MIC) showed different levels of plasticity in response to vancomycin. A bivariate GWAS was performed to map single-nucleotide polymorphisms (SNPs) associated with growth plasticity. In total, 227 SNPs were identified from 14 time points, while 15 high-frequency SNPs were mapped to different annotated genes. The P-values and growth variations between the two cultures suggest that non-coding region (SNP 738836), ebh (SNP 1394043), drug transporter (SNP 264897), and pepV (SNP 1775112) play important roles in the growth plasticity of S. aureus. Our study provides an alternative strategy for dissecting the adaptive growth of S. aureus in vancomycin and highlights the feasibility of bivariate GWAS in bacterial phenotypic plasticity research.

The bare necessities: Uncovering essential and condition-critical genes with transposon sequencing

Querying gene function in bacteria has been greatly accelerated by the advent of transposon sequencing (Tn-seq) technologies (related Tn-seq strategies are known as TraDIS, INSeq, RB-TnSeq, and HITS). Pooled populations of transposon mutants are cultured in an environment and next-generation sequencing tools are used to determine areas of the genome that are important for bacterial fitness. In this review we provide an overview of Tn-seq methodologies and discuss how Tn-seq has been applied, or could be applied, to the study of oral microbiology. These applications include studying the essential genome as a means to rationally design therapeutic agents. Tn-seq has also contributed to our understanding of well-studied biological processes in oral bacteria. Other important applications include in vivo pathogenesis studies and use of Tn-seq to probe the molecular basis of microbial interactions. We also highlight recent advancements in techniques that act in synergy with Tn-seq such as clustered regularly interspaced short palindromic repeats (CRISPR) interference and microfluidic chip platforms.

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.

Mutant phenotypes for thousands of bacterial genes of unknown function

One-third of all protein-coding genes from bacterial genomes cannot be annotated with a function. Here, to investigate the functions of these genes, we present genome-wide mutant fitness data from 32 diverse bacteria across dozens of growth conditions. We identified mutant phenotypes for 11,779 protein-coding genes that had not been annotated with a specific function. Many genes could be associated with a specific condition because the gene affected fitness only in that condition, or with another gene in the same bacterium because they had similar mutant phenotypes. Of the poorly annotated genes, 2,316 had associations that have high confidence because they are conserved in other bacteria. By combining these conserved associations with comparative genomics, we identified putative DNA repair proteins; in addition, we propose specific functions for poorly annotated enzymes and transporters and for uncharacterized protein families. Our study demonstrates the scalability of microbial genetics and its utility for improving gene annotations.

Identifying and exploiting genes that potentiate the evolution of antibiotic resistance

There is an urgent need to develop novel approaches for predicting and preventing the evolution of antibiotic resistance. Here we show that the ability to evolve de novo resistance to a clinically important β-lactam antibiotic, ceftazidime, varies drastically across the genus Pseudomonas. This variation arises because strains possessing the ampR global transcriptional regulator evolve resistance at a high rate. This does not arise because of mutations in ampR. Instead, this regulator potentiates evolution by allowing mutations in conserved peptidoglycan biosynthesis genes to induce high levels of β-lactamase expression. Crucially, blocking this evolutionary pathway by co-administering ceftazidime with the β-lactamase inhibitor avibactam can be used to eliminate pathogenic P. aeruginosa populations before they can evolve resistance. In summary, our study shows that identifying potentiator genes that act as evolutionary catalysts can be used to both predict and prevent the evolution of antibiotic resistance.

Comparative genomics of a drug-resistant Pseudomonas aeruginosa panel and the challenges of antimicrobial resistance prediction from genomes

Antimicrobial resistance (AMR) is now recognized as a global threat to human health. The accessibility of microbial whole-genome sequencing offers an invaluable opportunity for resistance surveillance via the resistome, i.e. the genes and mutations underlying AMR. Unfortunately, AMR prediction from genomic data remains extremely challenging, especially for species with a large pan-genome. One such organism, for which multidrug-resistant (MDR) isolates are frequently encountered in the clinic, is Pseudomonas aeruginosa. This study focuses on a commercially available panel of seven MDR P. aeruginosa strains. The main goals were to sequence and compare these strains' genomes, attempt to predict AMR from whole genomes using two different methods and determine whether this panel could be an informative complement to the international P. aeruginosa reference panel. As expected, the results highlight the complexity of associating genotype and AMR phenotype in P. aeruginosa, mainly due to the intricate regulation of resistance mechanisms. Our results also urge caution in the interpretation of predicted resistomes regarding the occurrence of gene identity discrepancies between strains. We envision that, in addition to accounting for the genomic diversity of P. aeruginosa, future development of predictive tools will need to incorporate a transcriptomic, proteomic and/or metabolomic component.

MAGenTA: a Galaxy implemented tool for complete Tn-Seq analysis and data visualization

Motivation

Transposon insertion sequencing (Tn-Seq) is a microbial systems-level tool, that can determine on a genome-wide scale and in high-throughput, whether a gene, or a specific genomic region, is important for fitness under a specific experimental condition.

Results

Here, we present MAGenTA, a suite of analysis tools which accurately calculate the growth rate for each disrupted gene in the genome to enable the discovery of: (i) new leads for gene function, (ii) non-coding RNAs; (iii) genes, pathways and ncRNAs that are involved in tolerating drugs or induce disease; (iv) higher order genome organization; and (v) host-factors that affect bacterial host susceptibility. MAGenTA is a complete Tn-Seq analysis pipeline making sensitive genome-wide fitness (i.e. growth rate) analysis available for most transposons and Tn-Seq associated approaches (e.g. TraDis, HiTS, IN-Seq) and includes fitness (growth rate) calculations, sliding window analysis, bottleneck calculations and corrections, statistics to compare experiments and strains and genome-wide fitness visualization.

Availability and implementation

MAGenTA is available at the Galaxy public ToolShed repository and all source code can be found and are freely available at https://vanopijnenlab.github.io/MAGenTA/ .

Contact

vanopijn@bc.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Achieving a Predictive Understanding of Antimicrobial Stress Physiology through Systems Biology

The dramatic spread and diversity of antibiotic-resistant pathogens has significantly reduced the efficacy of essentially all antibiotic classes, bringing us ever closer to a postantibiotic era. Exacerbating this issue, our understanding of the multiscale physiological impact of antimicrobial challenge on bacterial pathogens remains incomplete. Concerns over resistance and the need for new antibiotics have motivated the collection of omics measurements to provide systems-level insights into antimicrobial stress responses for nearly 20 years. Although technological advances have markedly improved the types and resolution of such measurements, continued development of mathematical frameworks aimed at providing a predictive understanding of complex antimicrobial-associated phenotypes is critical to maximize the utility of multiscale data. Here we highlight recent efforts utilizing systems biology to enhance our knowledge of antimicrobial stress physiology. We provide a brief historical perspective of antibiotic-focused omics measurements, highlight new measurement discoveries and trends, discuss examples and opportunities for integrating measurements with mathematical models, and describe future challenges for the field.

TnSeq of Mycobacterium tuberculosis clinical isolates reveals strain-specific antibiotic liabilities

Once considered a phenotypically monomorphic bacterium, there is a growing body of work demonstrating heterogeneity among Mycobacterium tuberculosis (Mtb) strains in clinically relevant characteristics, including virulence and response to antibiotics. However, the genetic and molecular basis for most phenotypic differences among Mtb strains remains unknown. To investigate the basis of strain variation in Mtb, we performed genome-wide transposon mutagenesis coupled with next-generation sequencing (TnSeq) for a panel of Mtb clinical isolates and the reference strain H37Rv to compare genetic requirements for in vitro growth across these strains. We developed an analytic approach to identify quantitative differences in genetic requirements between these genetically diverse strains, which vary in genomic structure and gene content. Using this methodology, we found differences between strains in their requirements for genes involved in fundamental cellular processes, including redox homeostasis and central carbon metabolism. Among the genes with differential requirements were katG, which encodes the activator of the first-line antitubercular agent isoniazid, and glcB, which encodes malate synthase, the target of a novel small-molecule inhibitor. Differences among strains in their requirement for katG and glcB predicted differences in their response to these antimicrobial agents. Importantly, these strain-specific differences in antibiotic response could not be predicted by genetic variants identified through whole genome sequencing or by gene expression analysis. Our results provide novel insight into the basis of variation among Mtb strains and demonstrate that TnSeq is a scalable method to predict clinically important phenotypic differences among Mtb strains.

Genomewide Identification of Essential Genes and Fitness Determinants of Streptococcus mutans UA159

Transposon mutagenesis coupled with next-generation DNA sequencing (Tn-seq) is a powerful tool for discovering regions of the genome that are required for the survival of bacteria in different environments. We adapted this technique to the dental caries pathogen Streptococcus mutans UA159 and identified 11% of the genome as essential, with many genes encoding products required for replication, translation, lipid metabolism, and cell wall biogenesis. Comparison of the essential genome of S. mutans UA159 with those of selected other streptococci for which such information is available revealed several metabolic pathways and genes that are required in S. mutans, but not in some Streptococcus spp. We further identified genes that are essential for sustained growth in rich or defined medium, as well as for persistence in vivo in a rodent model of oral infection. Collectively, our results provide a novel and comprehensive view of the genes required for essential processes of S. mutans, many of which could represent potential targets for therapeutics. IMPORTANCE Tooth decay (dental caries) is a common cause of pain, impaired quality of life, and tooth loss in children and adults. It begins because of a compositional change in the microorganisms that colonize the tooth surface driven by repeated and sustained carbohydrate intake. Although several bacterial species are associated with tooth decay, Streptococcus mutans is the most common cause. Therefore, it is important to identify biological processes that contribute to the survival of S. mutans in the human mouth, with the aim of disrupting the processes with antimicrobial agents. We successfully applied Tn-seq to S. mutans, discovering genes that are required for survival, growth, and persistence, both in laboratory environments and in a mouse model of tooth decay. This work highlights new avenues for the control of an important human pathogen.

Statistical analysis of co-occurrence patterns in microbial presence-absence datasets

Drawing on a long history in macroecology, correlation analysis of microbiome datasets is becoming a common practice for identifying relationships or shared ecological niches among bacterial taxa. However, many of the statistical issues that plague such analyses in macroscale communities remain unresolved for microbial communities. Here, we discuss problems in the analysis of microbial species correlations based on presence-absence data. We focus on presence-absence data because this information is more readily obtainable from sequencing studies, especially for whole-genome sequencing, where abundance estimation is still in its infancy. First, we show how Pearson's correlation coefficient (r) and Jaccard's index (J)-two of the most common metrics for correlation analysis of presence-absence data-can contradict each other when applied to a typical microbiome dataset. In our dataset, for example, 14% of species-pairs predicted to be significantly correlated by r were not predicted to be significantly correlated using J, while 37.4% of species-pairs predicted to be significantly correlated by J were not predicted to be significantly correlated using r. Mismatch was particularly common among species-pairs with at least one rare species (<10% prevalence), explaining why r and J might differ more strongly in microbiome datasets, where there are large numbers of rare taxa. Indeed 74% of all species-pairs in our study had at least one rare species. Next, we show how Pearson's correlation coefficient can result in artificial inflation of positive taxon relationships and how this is a particular problem for microbiome studies. We then illustrate how Jaccard's index of similarity (J) can yield improvements over Pearson's correlation coefficient. However, the standard null model for Jaccard's index is flawed, and thus introduces its own set of spurious conclusions. We thus identify a better null model based on a hypergeometric distribution, which appropriately corrects for species prevalence. This model is available from recent statistics literature, and can be used for evaluating the significance of any value of an empirically observed Jaccard's index. The resulting simple, yet effective method for handling correlation analysis of microbial presence-absence datasets provides a robust means of testing and finding relationships and/or shared environmental responses among microbial taxa.

Genome-wide discovery of novel M1T1 group A streptococcal determinants important for fitness and virulence during soft-tissue infection

The Group A Streptococcus remains a significant human pathogen causing a wide array of disease ranging from self-limiting to life-threatening invasive infections. Epithelium (skin or throat) colonization with progression to the subepithelial tissues is the common step in all GAS infections. Here, we used transposon-sequencing (Tn-seq) to define the GAS 5448 genetic requirements for in vivo fitness in subepithelial tissue. A near-saturation transposon library of the M1T1 GAS 5448 strain was injected subcutaneously into mice, producing suppurative inflammation at 24 h that progressed to prominent abscesses with tissue necrosis at 48 h. The library composition was monitored en masse by Tn-seq and ratios of mutant abundance comparing the output (12, 24 and 48 h) versus input (T₀) mutant pools were calculated for each gene. We identified a total of 273 subcutaneous fitness (scf) genes with 147 genes (55 of unknown function) critical for the M1T1 GAS 5448 fitness in vivo; and 126 genes (53 of unknown function) potentially linked to in vivo fitness advantage. Selected scf genes were validated in competitive subcutaneous infection with parental 5448. Two uncharacterized genes, scfA and scfB, encoding putative membrane-associated proteins and conserved among Gram-positive pathogens, were further characterized. Defined scfAB mutants in GAS were outcompeted by wild type 5448 in vivo, attenuated for lesion formation in the soft tissue infection model and dissemination to the bloodstream. We hypothesize that scfAB play an integral role in enhancing adaptation and fitness of GAS during localized skin infection, and potentially in propagation to other deeper host environments.

The WHO ranks the Group A Streptococcus (GAS) in the top 10 leading causes of morbidity and mortality from infectious diseases worldwide. GAS is a strict human pathogen causing both benign superficial infections as well as life-threatening invasive diseases. All GAS infections begin by colonization of an epithelium (throat or skin) followed by propagation into subepithelial tissues. The genetic requirements for M1T1 GAS 5448 within this niche were interrogated by in vivo transposon sequencing (Tn-seq), identifying 273 subcutaneous fitness (scf) genes with 108 of those previously of “unknown function”. Two yet uncharacterized genes, scfA and scfB, were shown to be critical during GAS 5448 soft tissue infection and dissemination into the bloodstream. Thus, this study improves the functional annotation of the GAS genome, providing new insights into GAS pathophysiology and enhancing the development of novel GAS therapeutics.

Antibiotics Disrupt Coordination between Transcriptional and Phenotypic Stress Responses in Pathogenic Bacteria

Bacterial genes that change in expression upon environmental disturbance have commonly been seen as those that must also phenotypically matter. However, several studies suggest that differentially expressed genes are rarely phenotypically important. We demonstrate, for Gram-positive and Gram-negative bacteria, that these seemingly uncoordinated gene sets are involved in responses that can be linked through topological network analysis. However, the level of coordination is stress dependent. While a well-coordinated response is triggered in response to nutrient stress, antibiotics trigger an uncoordinated response in which transcriptionally and phenotypically important genes are neither linked spatially nor in their magnitude. Moreover, a gene expression meta-analysis reveals that genes with large fitness changes during stress have low transcriptional variation across hundreds of other conditions, and vice versa. Our work suggests that cellular responses can be understood through network models that incorporate regulatory and genetic relationships, which could aid drug target predictions and genetic network engineering.

Defining Genetic Fitness Determinants and Creating Genomic Resources for an Oral Pathogen

Periodontitis is a microbial infection that destroys the structures that support the teeth. Although it is typically a chronic condition, rapidly progressing, aggressive forms are associated with the oral pathogen Aggregatibacter actinomycetemcomitans One of this bacterium's key virulence traits is its ability to attach to surfaces and form robust biofilms that resist killing by the host and antibiotics. Though much has been learned about A. actinomycetemcomitans since its initial discovery, we lack insight into a fundamental aspect of its basic biology, as we do not know the full set of genes that it requires for viability (the essential genome). Furthermore, research on A. actinomycetemcomitans is hampered by the field's lack of a mutant collection. To address these gaps, we used rapid transposon mutant sequencing (Tn-seq) to define the essential genomes of two strains of A. actinomycetemcomitans, revealing a core set of 319 genes. We then generated an arrayed mutant library comprising >1,500 unique insertions and used a sequencing-based approach to define each mutant's position (well and plate) in the library. To demonstrate its utility, we screened the library for mutants with weakened resistance to subinhibitory erythromycin, revealing the multidrug efflux pump AcrAB as a critical resistance factor. During the screen, we discovered that erythromycin induces A. actinomycetemcomitans to form biofilms. We therefore devised a novel Tn-seq-based screen to identify specific factors that mediate this phenotype and in follow-up experiments confirmed 4 mutants. Together, these studies present new insights and resources for investigating the basic biology and disease mechanisms of a human pathogen.IMPORTANCE Millions suffer from gum disease, which often is caused by Aggregatibacter actinomycetemcomitans, a bacterium that forms antibiotic-resistant biofilms. To fully understand any organism, we should be able to answer: what genes does it require for life? Here, we address this question for A. actinomycetemcomitans by determining the genes in its genome that cannot be mutated. As for the genes that can be mutated, we archived these mutants into a library, which we used to find genes that contribute to antibiotic resistance, leading us to discover that antibiotics cause A. actinomycetemcomitans to form biofilms. We then devised an approach to find genes that mediate this process and confirmed 4 genes. These results illuminate new fundamental traits of a human pathogen.

Antibiotic Capture by Bacterial Lipocalins Uncovers an Extracellular Mechanism of Intrinsic Antibiotic Resistance

The potential for microbes to overcome antibiotics of different classes before they reach bacterial cells is largely unexplored. Here we show that a soluble bacterial lipocalin produced by Burkholderia cenocepacia upon exposure to sublethal antibiotic concentrations increases resistance to diverse antibiotics in vitro and in vivo These phenotypes were recapitulated by heterologous expression in B. cenocepacia of lipocalin genes from Pseudomonas aeruginosa, Mycobacterium tuberculosis, and methicillin-resistant Staphylococcus aureus Purified lipocalin bound different classes of bactericidal antibiotics and contributed to bacterial survival in vivo Experimental and X-ray crystal structure-guided computational studies revealed that lipocalins counteract antibiotic action by capturing antibiotics in the extracellular space. We also demonstrated that fat-soluble vitamins prevent antibiotic capture by binding bacterial lipocalin with higher affinity than antibiotics. Therefore, bacterial lipocalins contribute to antimicrobial resistance by capturing diverse antibiotics in the extracellular space at the site of infection, which can be counteracted by known vitamins.IMPORTANCE Current research on antibiotic action and resistance focuses on targeting essential functions within bacterial cells. We discovered a previously unrecognized mode of general bacterial antibiotic resistance operating in the extracellular space, which depends on bacterial protein molecules called lipocalins. These molecules are highly conserved in most bacteria and have the ability to capture different classes of antibiotics outside bacterial cells. We also discovered that liposoluble vitamins, such as vitamin E, overcome in vitro and in vivo antibiotic resistance mediated by bacterial lipocalins, providing an unexpected new alternative to combat resistance by using this vitamin or its derivatives as antibiotic adjuvants.