Multicopy suppressors for novel antibacterial compounds reveal targets and drug efflux susceptibility

High-Throughput Screening of Natural Product and Synthetic Molecule Libraries for Antibacterial Drug Discovery

Due to the continued emergence of resistance and a lack of new and promising antibiotics, bacterial infection has become a major public threat. High-throughput screening (HTS) allows rapid screening of a large collection of molecules for bioactivity testing and holds promise in antibacterial drug discovery. More than 50% of the antibiotics that are currently available on the market are derived from natural products. However, with the easily discoverable antibiotics being found, finding new antibiotics from natural sources has seen limited success. Finding new natural sources for antibacterial activity testing has also proven to be challenging. In addition to exploring new sources of natural products and synthetic biology, omics technology helped to study the biosynthetic machinery of existing natural sources enabling the construction of unnatural synthesizers of bioactive molecules and the identification of molecular targets of antibacterial agents. On the other hand, newer and smarter strategies have been continuously pursued to screen synthetic molecule libraries for new antibiotics and new druggable targets. Biomimetic conditions are explored to mimic the real infection model to better study the ligand-target interaction to enable the designing of more effective antibacterial drugs. This narrative review describes various traditional and contemporaneous approaches of high-throughput screening of natural products and synthetic molecule libraries for antibacterial drug discovery. It further discusses critical factors for HTS assay design, makes a general recommendation, and discusses possible alternatives to traditional HTS of natural products and synthetic molecule libraries for antibacterial drug discovery.

Development and applications of a CRISPR activation system for facile genetic overexpression in Candida albicans

For the fungal pathogen Candida albicans, genetic overexpression readily occurs via a diversity of genomic alterations, such as aneuploidy and gain-of-function mutations, with important consequences for host adaptation, virulence, and evolution of antifungal drug resistance. Given the important role of overexpression on C. albicans biology, it is critical to develop and harness tools that enable the analysis of genes expressed at high levels in the fungal cell. Here, we describe the development, optimization, and application of a novel, single-plasmid-based CRISPR activation (CRISPRa) platform for targeted genetic overexpression in C. albicans, which employs a guide RNA to target an activator complex to the promoter region of a gene of interest, thus driving transcriptional expression of that gene. Using this system, we demonstrate the ability of CRISPRa to drive high levels of gene expression in C. albicans, and we assess optimal guide RNA targeting for robust and constitutive overexpression. We further demonstrate the specificity of the system via RNA sequencing. We highlight the application of CRISPR activation to overexpress genes involved in pathogenesis and drug susceptibility, and contribute toward the identification of novel phenotypes. Consequently, this tool will facilitate a broad range of applications for the study of C. albicans genetic overexpression.

The mechanism of resistance in Escherichia coli to ridinilazole and other antibacterial head-to-head bis-benzimidazole compounds

The appY gene has been characterised as conferring resistance to a novel series of antimicrobial benzimidazole derivatives in E. coli MC1061 cells when expressed in high copy-number. A microarray approach was used to identify genes involved in the mechanism of appY-mediated antibacterial resistance, that were up- or down-regulated following induction of the gene in the appY knockout strain JW0553. In total, expression of 90 genes was induced and 48 repressed greater than 2.5-fold (P < 0.05), 45 min after appY induction. Over half the genes up-regulated following appY expression had confirmed or putative roles in acid resistance (AR) and response to oxidative and antibiotic stresses. These included the genes for MdtE and MdtF, which form a multi-drug transporter with TolC and have been implicated in resistance to several antibiotics including erythromycin. Amongst the acid resistance genes were gadAB and adiAC encoding the glutamate-dependant (AR2) and arginine-dependant (AR3) acid resistance systems respectively, in addition to the transcriptional activators of these systems gadE and gadX. In agreement with earlier studies, appA, appCB and hyaA-F were also up-regulated following induction of appY. This study has also confirmed that over-expression of mdtEF confers resistance to these antibacterial benzimidazoles, indicating that the observation of appY conferring resistance to these compounds, proceeds through an appY-mediated up-regulation of this efflux transporter. To assess the importance of the AppY enzyme to acid stress responses, the percentage survival of bacteria in acidified media (pH ≤ 2) was measured. From an initial input of 1 × 106 CFU/ml, the wild-type strain MG1655 showed 7.29% and 0.46% survival after 2 and 4 h, respectively. In contrast, strain JW0553 in which appY is deleted was completely killed by the treatment. Transformation of JW0553 with a plasmid carrying appY returned survival to wild-type levels (7.85% and 1.03% survival at 2 and 4 h). Further dissection of the response by prior induction of each of the three AR systems has revealed that AR1 and AR3 were most affected by the absence of appY. This work highlights an important and previously unidentified role for the AppY enzyme in mediating the responses to several stress conditions. It is likely that the appY gene fits into a complex transcriptional regulatory network involving σS and gadE and gadX. Further work to pinpoint its position in such a hierarchy and to assess the contribution of appY to oxidative stress responses should help determine its full significance. This work is also consistent with recent studies in C. difficile showing that the mechanism of action of ridinilazole involves AT-rich DNA minor groove binding.

Elucidating the Mechanisms of Action of Antimicrobial Agents

Despite the ever-growing antibiotic resistance crisis, the rate at which new antimicrobials are being discovered and approved for human use has rapidly declined over the past 75 years. A barrier for advancing newly identified antibiotics beyond discovery is elucidating their mechanism(s) of action.

A machine learning approach-based array sensor for rapidly predicting the mechanisms of action of antibacterial compounds

Rapid and accurate identification of the mechanisms of action (MoAs) of antibacterial compounds remains a challenge for the development of antibacterial compounds. Computational inference methods for determining the MoAs of antibacterial compounds have been developed in recent years. In particular, approaches combining machine learning technology enable precisely recognizing the MoA of antibacterial compounds. However, these methods heavily rely on the big data resulting from multiplexed experiments. As such, these approaches tend to produce minimal throughput and are not comprehensive enough to be adapted to widespread industrial applications. Here, we present a machine learning approach based on a customized array sensor for directly identifying the MoAs of antibacterial compounds. The array sensor consists of different two-dimensional nanomaterial fluorescence quenchers with different fluorescence-labeled single-stranded DNAs (ssDNAs). By mapping the subtle difference of the physicochemical properties on the bacterial surface treated with different antibacterial compound stimuli, the array sensor ensures visualizing the recognition process. Moreover, the customized array sensor produces a high volume of the MoA database, overcoming the dependence on big data. We further use the array sensor to build a chemical-response unique "fingerprint" database of MoAs. By combining a neural network-based genetic algorithm (NNGA), we rapidly discriminate the MoAs of four antibiotics with an overall accuracy of 100%. Furthermore, a new screening antibacterial peptide has been discovered and evaluated by our approach for determining the MoA with high accuracy proven by other techniques.

Technologies for High-Throughput Identification of Antibiotic Mechanism of Action

There are two main strategies for antibiotic discovery: target-based and phenotypic screening. The latter has been much more successful in delivering first-in-class antibiotics, despite the major bottleneck of delayed Mechanism-of-Action (MOA) identification. Although finding new antimicrobial compounds is a very challenging task, identifying their MOA has proven equally challenging. MOA identification is important because it is a great facilitator of lead optimization and improves the chances of commercialization. Moreover, the ability to rapidly detect MOA could enable a shift from an activity-based discovery paradigm towards a mechanism-based approach. This would allow to probe the grey chemical matter, an underexplored source of structural novelty. In this study we review techniques with throughput suitable to screen large libraries and sufficient sensitivity to distinguish MOA. In particular, the techniques used in chemical genetics (e.g., based on overexpression and knockout/knockdown collections), promoter-reporter libraries, transcriptomics (e.g., using microarrays and RNA sequencing), proteomics (e.g., either gel-based or gel-free techniques), metabolomics (e.g., resourcing to nuclear magnetic resonance or mass spectrometry techniques), bacterial cytological profiling, and vibrational spectroscopy (e.g., Fourier-transform infrared or Raman scattering spectroscopy) were discussed. Ultimately, new and reinvigorated phenotypic assays bring renewed hope in the discovery of a new generation of antibiotics.

Construction of a multicopy genomic DNA library and its application for suppression analysis

Suppression analysis is used for the identification of new genes and genetic interactions when there is a notable phenotype available for genetic selection or screening. A random genomic DNA library constructed on a multi-copy plasmid is a useful tool for suppression analysis when one expects that an overdose of a few genes will suppress the phenotype. These libraries have been successfully used to determine the function of a gene by revealing genes whose functions are related to the gene of interest. They have also been used to identify the targets of chemical or biological agents by increasing the number of unaffected target gene products in a cell. In this article, I will discuss important considerations for constructing multicopy genomic DNA libraries. The protocol provided in this paper should be a useful guide for constructing genomic DNA libraries in many bacterial species for which multi-copy plasmids are available.

Nonoptimal Gene Expression Creates Latent Potential for Antibiotic Resistance

Bacteria regulate genes to survive antibiotic stress, but regulation can be far from perfect. When regulation is not optimal, mutations that change gene expression can contribute to antibiotic resistance. It is not systematically understood to what extent natural gene regulation is or is not optimal for distinct antibiotics, and how changes in expression of specific genes quantitatively affect antibiotic resistance. Here we discover a simple quantitative relation between fitness, gene expression, and antibiotic potency, which rationalizes our observation that a multitude of genes and even innate antibiotic defense mechanisms have expression that is critically nonoptimal under antibiotic treatment. First, we developed a pooled-strain drug-diffusion assay and screened Escherichia coli overexpression and knockout libraries, finding that resistance to a range of 31 antibiotics could result from changing expression of a large and functionally diverse set of genes, in a primarily but not exclusively drug-specific manner. Second, by synthetically controlling the expression of single-drug and multidrug resistance genes, we observed that their fitness–expression functions changed dramatically under antibiotic treatment in accordance with a log-sensitivity relation. Thus, because many genes are nonoptimally expressed under antibiotic treatment, many regulatory mutations can contribute to resistance by altering expression and by activating latent defenses.

Gain- and Loss-of-Function Screens Coupled to Next-Generation Sequencing for Antibiotic Mode of Action and Resistance Studies in Streptococcus pneumoniae

Two whole-genome screening approaches are described for studying the mode of action and the mechanisms of resistance to trimethoprim (TMP) in the Gram-positive Streptococcus pneumoniae The gain-of-function approach (Int-Seq) relies on a genomic library of DNA fragments integrated into a fucose-inducible cassette. The second approach, leading to both gain- and loss-of-function mutation, is based on chemical mutagenesis coupled to next-generation sequencing (Mut-Seq). Both approaches pointed at the drug target dihydrofolate reductase (DHFR) as a major resistance mechanism to TMP. Resistance was achieved by dhfr overexpression either through the addition of fucose (Int-Seq) or by mutations upstream of the gene (Mut-Seq). Three types of mutations increased expression by disrupting a predicted Rho-independent terminator upstream of dhfr Known and novel DHFR mutations were also detected by Mut-Seq, and these were functionally validated for TMP resistance. The two approaches also suggested that an increase in the metabolic flux from purine synthesis to GTP and then to folate can modulate the susceptibility to TMP. Finally, we provide evidence for a novel role of the ABC transporter PatAB in TMP susceptibility. Our genomic screens highlighted novel aspects on the mode of action and mechanisms of resistance to antibiotics.

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

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

Gain of function methods based on gene overexpression are not easily applied to high-throughput screening across different experimental conditions. Here, the authors present Dub-seq, which separates overexpression library characterization from functional screening and uses random DNA barcodes to increase the experimental throughput.

Genome-wide mutant profiling predicts the mechanism of a Lipid II binding antibiotic

Identifying targets of antibacterial compounds remains a challenging step in antibiotic development. We have developed a two-pronged functional genomics approach to predict mechanism of action that uses mutant fitness data from antibiotic-treated transposon libraries containing both upregulation and inactivation mutants. We treated a Staphylococcus aureus transposon library containing 690,000 unique insertions with 32 antibiotics. Upregulation signatures, identified from directional biases in insertions, revealed known molecular targets and resistance mechanisms for the majority of these. Because single gene upregulation does not always confer resistance, we used a complementary machine learning approach to predict mechanism from inactivation mutant fitness profiles. This approach suggested the cell wall precursor Lipid II as the molecular target of the lysocins, a mechanism we have confirmed. We conclude that docking to membrane-anchored Lipid II precedes the selective bacteriolysis that distinguishes these lytic natural products, showing the utility of our approach for nominating antibiotic mechanism of action.

Coupling next-generation sequencing to dominant positive screens for finding antibiotic cellular targets and resistance mechanisms in Escherichia coli

In order to expedite the discovery of genes coding for either drug targets or antibiotic resistance, we have developed a functional genomic strategy termed Plas-Seq. This technique involves coupling a multicopy suppressor library to next-generation sequencing. We generated an Escherichia coli plasmid genomic library that was transformed into E. coli. These transformants were selected step by step using 0.25× to 2× minimum inhibitory concentrations for ceftriaxone, gentamicin, levofloxacin, tetracycline or trimethoprim. Plasmids were isolated at each selection step and subjected to Illumina sequencing. By searching for genomic loci whose sequencing coverage increased with antibiotic pressure we were able to detect 48 different genomic loci that were enriched by at least one antibiotic. Fifteen of these loci were studied functionally, and we showed that 13 can decrease the susceptibility of E. coli to antibiotics when overexpressed. These genes coded for drug targets, transcription factors, membrane proteins and resistance factors. The technique of Plas-Seq is expediting the discovery of genes associated with the mode of action or resistance to antibiotics and led to the isolation of a novel gene influencing drug susceptibility. It has the potential for being applied to novel molecules and to other microbial species.

Molecular Modeling of Multidrug Properties of Resistance Nodulation Division (RND) Transporters

Efflux pumps of the resistance nodulation division (RND) superfamily are among the major contributors to intrinsic and acquired multidrug resistance in Gram-negative bacteria. Structural information on AcrAB-TolC and MexAB-OprM, major efflux pumps of Escherichia coli and Pseudomonas aeruginosa respectively, boosted intensive research aimed at understanding the molecular mechanisms ruling the active extrusion processes. In particular, several studies were devoted to the understanding of the determinants behind the extraordinary broad specificity of the RND transporters AcrB and MexB. In this chapter, we discuss the ever-growing role computational methods have been playing in deciphering key structural and dynamical features of these transporters and of their interaction with substrates and inhibitors. We further discuss and illustrate examples from our lab of how molecular docking, homology modeling, all-atom molecular dynamics simulations and in silico free energy estimations can all together give precious insights into the processes of recognition and extrusion of substrates, as well as on the possible inhibition strategies.

Chemical genetics in drug discovery

Chemical-genetic approaches are based on measuring the cellular outcome of combining genetic and chemical perturbations in large-numbers in tandem. In these approaches the contribution of every gene to the fitness of an organism is measured upon exposure to different chemicals. Current technological advances enable the application of chemical genetics to almost any organism and at an unprecedented throughput. Here we review the underlying concepts behind chemical genetics, present its different vignettes and illustrate how such approaches can propel drug discovery.

Targeting quinolone- and aminocoumarin-resistant bacteria with new gyramide analogs that inhibit DNA gyrase

Bacterial DNA gyrase is an essential type II topoisomerase that enables cells to overcome topological barriers encountered during replication, transcription, recombination, and repair. This enzyme is ubiquitous in bacteria and represents an important clinical target for antibacterial therapy. In this paper we report the characterization of three exciting new gyramide analogs-from a library of 183 derivatives-that are potent inhibitors of DNA gyrase and are active against clinical strains of gram-negative bacteria (Escherichia coli, Shigella flexneri, and Salmonella enterica; 3 of 10 wild-type strains tested) and gram-positive bacteria (Bacillus spp., Enterococcus spp., Staphylococcus spp., and Streptococcus spp.; all 9 of the wild-type strains tested). E. coli strains resistant to the DNA gyrase inhibitors ciprofloxacin and novobiocin display very little cross-resistance to these new gyramides. In vitro studies demonstrate that the new analogs are potent inhibitors of the DNA supercoiling activity of DNA gyrase (IC50s of 47-170 nM) but do not alter the enzyme's ATPase activity. Although mutations that confer bacterial cells resistant to these new gyramides map to the genes encoding the subunits of the DNA gyrase (gyrA and gyrB genes), overexpression of GyrA, GyrB, or GyrA and GyrB together does not suppress the inhibitory effect of the gyramides. These observations support the hypothesis that the gyramides inhibit DNA gyrase using a mechanism that is unique from other known inhibitors.

The Complex Relationship between Virulence and Antibiotic Resistance

Antibiotic resistance, prompted by the overuse of antimicrobial agents, may arise from a variety of mechanisms, particularly horizontal gene transfer of virulence and antibiotic resistance genes, which is often facilitated by biofilm formation. The importance of phenotypic changes seen in a biofilm, which lead to genotypic alterations, cannot be overstated. Irrespective of if the biofilm is single microbe or polymicrobial, bacteria, protected within a biofilm from the external environment, communicate through signal transduction pathways (e.g., quorum sensing or two-component systems), leading to global changes in gene expression, enhancing virulence, and expediting the acquisition of antibiotic resistance. Thus, one must examine a genetic change in virulence and resistance not only in the context of the biofilm but also as inextricably linked pathologies. Observationally, it is clear that increased virulence and the advent of antibiotic resistance often arise almost simultaneously; however, their genetic connection has been relatively ignored. Although the complexities of genetic regulation in a multispecies community may obscure a causative relationship, uncovering key genetic interactions between virulence and resistance in biofilm bacteria is essential to identifying new druggable targets, ultimately providing a drug discovery and development pathway to improve treatment options for chronic and recurring infection.

Strategies for target identification of antimicrobial natural products

Despite a pervasive decline in natural product research at many pharmaceutical companies over the last two decades, natural products have undeniably been a prolific and unsurpassed source for new lead antibacterial compounds.

Whole Cell Target Engagement Identifies Novel Inhibitors of Mycobacterium tuberculosis Decaprenylphosphoryl-β-d-ribose Oxidase

We have targeted the Mycobacterium tuberculosis decaprenylphosphoryl-β-d-ribose oxidase (Mt-DprE1) for potential chemotherapeutic intervention of tuberculosis. A multicopy suppression strategy that overexpressed Mt-DprE1 in M. bovis BCG was used to profile the publically available GlaxoSmithKline antimycobacterial compound set, and one compound (GSK710) was identified that showed an 8-fold higher minimum inhibitory concentration relative to the control strain. Analogues of GSK710 show a clear relationship between whole cell potency and in vitro activity using an enzymatic assay employing recombinant Mt-DprE1, with binding affinity measured by fluorescence quenching of the flavin cofactor of the enzyme. M. bovis BCG spontaneous resistant mutants to GSK710 and a closely related analogue were isolated and sequencing of ten such mutants revealed a single point mutation at two sites, E221Q or G248S within DprE1, providing further evidence that DprE1 is the main target of these compounds. Finally, time-lapse microscopy experiments showed that exposure of M. tuberculosis to a compound of this series arrests bacterial growth rapidly followed by a slower cytolysis phase.

Application of bacterial cytological profiling to crude natural product extracts reveals the antibacterial arsenal of Bacillus subtilis

Although most clinically used antibiotics are derived from natural products, identifying new antibacterial molecules from natural product extracts is difficult due to the complexity of these extracts and the limited tools to correlate biological activity with specific molecules. Here, we show that bacterial cytological profiling (BCP) provides a rapid method for mechanism of action determination on plates and in complex natural product extracts and for activity-guided purification. We prepared an extract from Bacillus subtilis 3610 that killed the Escherichia coli lptD mutant and used BCP to observe two types of bioactivities in the unfractionated extract: inhibition of translation and permeablization of the cytoplasmic membrane. We used BCP to guide purification of the molecules responsible for each activity, identifying the translation inhibitors bacillaene and bacillaene B (glycosylated bacillaene) and demonstrating that two molecules contribute to cell permeabilitization, the bacteriocin subtilosin and the cyclic peptide sporulation killing factor. Our results suggest that bacillaene mediates translational arrest, and show that bacillaene B has a minimum inhibitory concentration 10 × higher than unmodified bacillaene. Finally, we show that BCP can be used to screen strains on an agar plate without the need for extract preparation, greatly saving time and improving throughput. Thus, BCP simplifies the isolation of novel natural products, by identifying strains, crude extracts and fractions with interesting bioactivities even when multiple activities are present, allowing investigators to focus labor-intensive steps on those with desired activities.

Determination of antibiotic EC50 using a zero-flow microfluidic chip based growth phenotype assay

Current existing assay systems for evaluating antimicrobial activity suffer from several limitations including excess reagent consumption and inaccurate concentration gradient preparation. Recently, microfluidic systems have been developed to provide miniaturized platforms for antimicrobial susceptibility assays. However, some of current microfluidic based assays require continuous flows of reagents or elaborate preparation steps during concentration preparation. In this study, we introduce a novel microfluidic chip based growth phenotype assay that automatically generates a logarithmic concentration gradient and allows observing the growth of pathogenic bacteria under different concentrations of antibiotics in nanoliter batch culture reactors. We chose pathogen bacterium Pseudomonas aeruginosa as a model strain and evaluated the inhibitory effects of gentamicin and ciprofloxacin. We determined the EC50 values and confirmed the validity of the present system by comparing the EC50 values obtained through conventional test tube method. We demonstrated that the EC50 values acquired from present assay are comparable to those obtained from conventional test tube cultures. The potential application of present assay system for investigating combinatorial effects of antibiotics on multidrug resistant pathogenic bacteria is discussed and it can be further used for systematic evaluation of antifungal or antiviral agents.

A Pipeline for Screening Small Molecules with Growth Inhibitory Activity against Burkholderia cenocepacia

Infections with the bacteria Burkholderia cepacia complex (Bcc) are very difficult to eradicate in cystic fibrosis patients due the intrinsic resistance of Bcc to most available antibiotics and the emergence of multiple antibiotic resistant strains during antibiotic treatment. In this work, we used a whole-cell based assay to screen a diverse collection of small molecules for growth inhibitors of a relevant strain of Bcc, B. cenocepacia K56-2. The primary screen used bacterial growth in 96-well plate format and identified 206 primary actives among 30,259 compounds. From 100 compounds with no previous record of antibacterial activity secondary screening and data mining selected a total of Bce bioactives that were further analyzed. An experimental pipeline, evaluating in vitro antibacterial and antibiofilm activity, toxicity and in vivo antibacterial activity using C. elegans was used for prioritizing compounds with better chances to be further investigated as potential Bcc antibacterial drugs. This high throughput screen, along with the in vitro and in vivo analysis highlights the utility of this experimental method to quickly identify bioactives as a starting point of antibacterial drug discovery.

A disk-diffusion-based target identification platform for antibacterials (TIPA): an inducible assay for profiling MOAs of antibacterial compounds

One of the challenges in antibiotic lead discovery is the difficulty and time-consuming task of determining the mechanism of action (MOA) of antibacterial compounds. In this report, we describe the development and validation of a facile and inexpensive assay system utilizing disk diffusion of inhibitors on solid agar medium embedded with mixed pools of a comprehensive collection of Escherichia coli clones each containing a plasmid-borne inducible essential gene from E. coli. From individual clones, pilot small-scale (48 or 50 clones) assays, to full-scale target identification platform for antibacterials (TIPA) system, involving a variety of assay formats (liquid vs solid media, individual vs mix clones), we demonstrate that elevated resistance phenotypes of relevant cell clones were highly specific. In particular, the TIPA system was able to reveal cellular targets of several known antibacterial inhibitors: cerulenin, diazaborine, indolmycin, phosphomycin, and triclosan. Complementary to several existing MOA profiling schemes, the TIPA system offers a simple and low-cost method for elucidating the target proteins of antibacterial inhibitors, thus will facilitate discovery and development of novel antibacterial compounds to combat multidrug-resistant bacterial pathogens.

Metabolic suppression identifies new antibacterial inhibitors under nutrient limitation

Characterizing new drugs and chemical probes of biological systems is hindered by difficulties in identifying the mechanism of action (MOA) of biologically active molecules. Here we present a metabolite suppression approach to explore the MOA of antibacterial compounds under nutrient restriction. We assembled an array of metabolites that can be screened for suppressors of inhibitory molecules. Further, we identified inhibitors of Escherichia coli growth under nutrient limitation and charted their interactions with our metabolite array. This strategy led to the discovery and characterization of three new antibacterial compounds, MAC168425, MAC173979 and MAC13772. We showed that MAC168425 interferes with glycine metabolism, MAC173979 is a time-dependent inhibitor of p-aminobenzoic acid biosynthesis and MAC13772 inhibits biotin biosynthesis. We conclude that metabolite suppression profiling is an effective approach to focus MOA studies on compounds impairing metabolic capabilities. Such bioactives can serve as chemical probes of bacterial physiology and as leads for antibacterial drug development.

Bacterial cytological profiling rapidly identifies the cellular pathways targeted by antibacterial molecules

Identifying the mechanism of action for antibacterial compounds is essential for understanding how bacteria interact with one another and with other cell types and for antibiotic discovery efforts, but determining a compound's mechanism of action remains a serious challenge that limits both basic research and antibacterial discovery programs. Here, we show that bacterial cytological profiling (BCP) is a rapid and powerful approach for identifying the cellular pathway affected by antibacterial molecules. BCP can distinguish between inhibitors that affect different cellular pathways as well as different targets within the same pathway. We use BCP to demonstrate that spirohexenolide A, a spirotetronate that is active against methicillin-resistant Staphylococcus aureus, rapidly collapses the proton motive force. BCP offers a simple, one-step assay that can be broadly applied, solving the longstanding problem of how to rapidly determine the cellular target of thousands of compounds.

Resistance-Nodulation-Division Multidrug Efflux Pumps in Gram-Negative Bacteria: Role in Virulence

Resistance-Nodulation-Division (RND) efflux pumps are one of the most important determinants of multidrug resistance (MDR) in Gram-negative bacteria. With an ever increasing number of Gram-negative clinical isolates exhibiting MDR phenotypes as a result of the activity of RND pumps, it is clear that the design of novel effective clinical strategies against such pathogens must be grounded in a better understanding of these pumps, including their physiological roles. To this end, recent evidence suggests that RND pumps play an important role in the virulence of Gram-negative pathogens. In this review, we discuss the important role RND efflux pumps play in different facets of virulence including colonization, evasion of host defense mechanisms, and biofilm formation. These studies provide key insights that may ultimately be applied towards strategies used in the design of effective therapeutics against MDR Gram negative bacterial pathogens.

Degradation of MAC13243 and studies of the interaction of resulting thiourea compounds with the lipoprotein targeting chaperone LolA

The discovery of novel small molecules that function as antibacterial agents or cellular probes of biology is hindered by our limited understanding of bacterial physiology and our ability to assign mechanism of action. We previously employed a chemical genomic strategy to identify a novel small molecule, MAC13243, as a likely inhibitor of the bacterial lipoprotein targeting chaperone, LolA. Here, we report on the degradation of MAC13243 into the active species, S-(4-chlorobenzyl)isothiourea. Analogs of this compound (e.g., A22) have previously been characterized as inhibitors of the bacterial actin-like protein, MreB. Herein, we demonstrate that the antibacterial activity of MAC13243 and the thiourea compounds are similar; these activities are suppressed or sensitized in response to increases or decreases of LolA copy number, respectively. We provide STD NMR data which confirms a physical interaction between LolA and the thiourea degradation product of MAC13243, with a Kd of ~150 μM. Taken together, we conclude that the thiourea series of compounds share a similar cellular mechanism that includes interaction with LolA in addition to the well-characterized target MreB.

Antisense RNA regulation and application in the development of novel antibiotics to combat multidrug resistant bacteria

Despite the availability of antibiotics and vaccines, infectious diseases remain one of most dangerous threats to humans and animals. The overuse and misuse of antibacterial agents have led to the emergence of multidrug resistant bacterial pathogens. Bacterial cells are often resilient enough to survive in even the most extreme environments. To do so, the organisms have evolved different mechanisms, including a variety of two-component signal transduction systems, which allow the bacteria to sense the surrounding environment and regulate gene expression in order to adapt and respond to environmental stimuli. In addition, some bacteria evolve resistance to antibacterial agents while many bacterial cells are able to acquire resistance genes from other bacterial species to enable them to survive in the presence of toxic antimicrobial agents. The crisis of antimicrobial resistance is an unremitting menace to human health and a burden on public health. The rapid increase in antimicrobial resistant organisms and limited options for development of new classes of antibiotics heighten the urgent need to develop novel potent antibacterial therapeutics in order to combat multidrug resistant infections. In this review, we introduce the regulatory mechanisms of antisense RNA and significant applications of regulated antisense RNA interference technology in early drug discovery. This includes the identification and evaluation of drug targets in vitro and in vivo, the determination of mode of action for antibiotics and new antibacterial agents, as well as the development of peptide-nucleic acid conjugates as novel antibacterials.

Dual targeting antibacterial peptide inhibitor of early lipid A biosynthesis

UDP-3-O-(R-3-hydroxyacyl)GlcN N-acyltransferase (LpxD) has been shown to be essential to survival of lipid A producing Gram-negative bacteria. In this study, LpxD-binding peptides 12 amino acids in length were identified from a phage-bound random peptide library screen. Three peptides displayed antibacterial activity when expressed intracellularly, one of which (RJPXD33) represented 15% of the total hits. RJPXD33 binds to E. coli LpxD with a K(d) of 6 μM and is competitive with R-3-hydroxymyristoyl-ACP binding. RJPXD33 can be C-terminally fused in vivo with thioredoxin or N-terminally modified in vitro with β-alanyl-fluorescein and maintain LpxD binding. The latter was used to develop an LpxD fluorescent binding assay used to evaluate unlabeled ligands and is amenable to small molecule library screening. Furthermore, RJPXD33 also binds to and inhibits E. coli UDP-N-acetylglucosamine acyltransferase (LpxA) with a K(d) of 20 μM, unearthing the possibility for the development of small molecule, dual-binding LpxA/LpxD inhibitors as novel antimicrobials.

Understanding efflux in Gram-negative bacteria: opportunities for drug discovery

INTRODUCTION

Bacteria evolved an arsenal of mechanisms to deal with toxic compounds and metabolic stresses, including antimicrobial agents. Efflux pumps are major players in the multidrug resistance of Gram-negative bacteria and pose major hurdles in the drug discovery process. However, recent advances in our understanding of efflux in these bacteria provide opportunities and assets for drug discovery.

AREAS COVERED

This review provides an overview of drug efflux in Gram-negative bacteria and its role in antimicrobial resistance, stress responses and other biological processes such as biofilm formation, and virulence. The discussion includes comments on the significance of synergy between a low-permeability outer membrane and efflux, notably the role of porins and lipopolysaccharide. The author then summarizes efforts aimed at inhibiting efflux pumps as a means to extend the utility of clinically useful antibiotics. This includes highlights of identification and characterization of small molecule efflux pump inhibitors (EPIs) from natural and synthetic sources, as well as novel strategies such as gene silencing and inhibitory antibodies.

EXPERT OPINION

Options for treating infections caused by multidrug-resistant bacteria are limited. Given the attractiveness of the therapeutic potential of efflux pump inhibition, further studies exploring novel strategies to interfere with efflux pump expression and function are warranted. This includes rational EPI design facilitated by pump structure information, exploitation of genetically defined efflux-proficient and efflux-compromised strain panels and non-traditional approaches such as pump inhibition by gene silencing, antibodies and perhaps even phage.

Compound prioritization methods increase rates of chemical probe discovery in model organisms

Preselection of compounds that are more likely to induce a phenotype can increase the efficiency and reduce the costs for model organism screening. To identify such molecules, we screened ~81,000 compounds in Saccharomyces cerevisiae and identified ~7500 that inhibit cell growth. Screening these growth-inhibitory molecules across a diverse panel of model organisms resulted in an increased phenotypic hit-rate. These data were used to build a model to predict compounds that inhibit yeast growth. Empirical and in silico application of the model enriched the discovery of bioactive compounds in diverse model organisms. To demonstrate the potential of these molecules as lead chemical probes, we used chemogenomic profiling in yeast and identified specific inhibitors of lanosterol synthase and of stearoyl-CoA 9-desaturase. As community resources, the ~7500 growth-inhibitory molecules have been made commercially available and the computational model and filter used are provided.

Classifying compound mechanism of action for linking whole cell phenotypes to molecular targets

Drug development programs have proven successful when performed at a whole cell level, thus incorporating solubility and permeability into the primary screen. However, linking those results to the target within the cell has been a major setback. The Phenotype Microarray system, marketed and sold by Biolog, seeks to address this need by assessing the phenotype in combination with a variety of chemicals with known mechanism of action (MOA). We have evaluated this system for usefulness in deducing the MOA for three test compounds. To achieve this, we constructed a database with 21 known antimicrobials, which served as a comparison for grouping our unknown MOA compounds. Pearson correlation and Ward linkage calculations were used to generate a dendrogram that produced clustering largely by known MOA, although there were exceptions. Of the three unknown compounds, one was definitively placed as an antifolate. The second and third compounds' MOA were not clearly identified, likely because the unique MOA was not represented within the database. The availability of the database generated in this report for Staphylococcus aureus ATCC 29213 will increase the accessibility of this technique to other investigators. From our analysis, the Phenotype Microarray system can group compounds with clear MOA, but the distinction of unique or broadly acting MOA at this time is less clear.

Maximizing the therapeutic window of an antimicrobial drug by imparting mitochondrial sequestration in human cells

The number of antimicrobial agents available for use in humans is limited by the difficulty of discovering chemical agents with selective toxicity to bacterial targets. Numerous small molecule inhibitors have potential as antimicrobial agents, yet their use has been prevented by high levels of toxic cross-reactivity in human cells. For example, methotrexate (Mtx) is an effective antimetabolite that exerts its effects by inhibiting DHFR. It is a potent antibacterial when accumulated intracellularly, but toxicity in human cells limits clinical utility in infectious disease treatment. Here, we describe peptide conjugates of Mtx that are sequestered into the mitochondria of human cells (mt-Mtx). This alteration in localization of Mtx, which directs it away from its enzyme target, decreases its toxicity in human cells by a factor of 10(3). Mt-Mtx, however, maintains activity against a variety of pathogenic gram-positive organisms, including methicillin-resistant Staphylococcus aureus (MRSA). The results from this proof-of-principle study describe a novel methodology for augmenting the antibacterial efficacy of drugs amenable to peptide conjugation while simultaneously decreasing their toxicity to the host organism.

Challenges of antibacterial discovery

The discovery of novel small-molecule antibacterial drugs has been stalled for many years. The purpose of this review is to underscore and illustrate those scientific problems unique to the discovery and optimization of novel antibacterial agents that have adversely affected the output of the effort. The major challenges fall into two areas: (i) proper target selection, particularly the necessity of pursuing molecular targets that are not prone to rapid resistance development, and (ii) improvement of chemical libraries to overcome limitations of diversity, especially that which is necessary to overcome barriers to bacterial entry and proclivity to be effluxed, especially in Gram-negative organisms. Failure to address these problems has led to a great deal of misdirected effort.

Staphylococcus aureus TargetArray: comprehensive differential essential gene expression as a mechanistic tool to profile antibacterials

The widespread emergence of antibiotic-resistant bacteria and a lack of new pharmaceutical development have catalyzed a need for new and innovative approaches for antibiotic drug discovery. One bottleneck in antibiotic discovery is the lack of a rapid and comprehensive method to identify compound mode of action (MOA). Since a hallmark of antibiotic action is as an inhibitor of essential cellular targets and processes, we identify a set of 308 essential genes in the clinically important pathogen Staphylococcus aureus. A total of 446 strains differentially expressing these genes were constructed in a comprehensive platform of sensitized and resistant strains. A subset of strains allows either target underexpression or target overexpression by heterologous promoter replacements with a suite of tetracycline-regulatable promoters. A further subset of 236 antisense RNA-expressing clones allows knockdown expression of cognate targets. Knockdown expression confers selective antibiotic hypersensitivity, while target overexpression confers resistance. The antisense strains were configured into a TargetArray in which pools of sensitized strains were challenged in fitness tests. A rapid detection method measures strain responses toward antibiotics. The TargetArray antibiotic fitness test results show mechanistically informative biological fingerprints that allow MOA elucidation.

A survey of yeast genomic assays for drug and target discovery

Over the past decade, the development and application of chemical genomic assays using the model organism Saccharomyces cerevisiae has provided powerful methods to identify the mechanism of action of known drugs and novel small molecules in vivo. These assays identify drug target candidates, genes involved in buffering drug target pathways and also help to define the general cellular response to small molecules. In this review, we examine current yeast chemical genomic assays and summarize the potential applications of each approach.

Chemical tools for dissecting bacterial physiology and virulence

Increasingly, chemical biology is being used in the context of bacterial virulence and the host-pathogen interaction, as small molecule inhibitors provide a number of unique advantages for the study of bacterial pathogens that complement powerful, existing classical genetic approaches. Small molecules have the potential to inhibit targets rapidly and reversibly, with a high degree of specificity. They are therefore well suited for studying the role of essential genes in bacterial physiology and virulence in both genetically tractable and intractable organisms, with the capacity to reveal novel phenotypes and insights into the function of essential factors during infection. The use of small molecule inhibitors during infection is also deepening our understanding of the role that host factors play in bacterial pathogenesis. In the future, the utility of chemical biology will grow as technologies for rapid identification of targets of interesting bioactive small molecules are developed. In this review, we highlight recent work in which small molecule inhibitors are used to study essential genes and genetically intractable organisms, to reveal novel phenotypes related to bacterial physiology, and to probe the role of bacterial and host factors during infection. In addition, we review recent advances in biochemical, genetic, and genomic techniques for target identification.

Chemical genomics in Escherichia coli identifies an inhibitor of bacterial lipoprotein targeting

One of the most significant hurdles to developing new chemical probes of biological systems and new drugs to treat disease is that of understanding the mechanism of action of small molecules discovered with cell-based small-molecule screening. Here we have assembled an ordered, high-expression clone set of all of the essential genes from Escherichia coli and used it to systematically screen for suppressors of growth inhibitory compounds. Using this chemical genomic approach, we demonstrate that the targets of well-known antibiotics can be identified as high copy suppressors of chemical lethality. This approach led to the discovery of MAC13243, a molecule that belongs to a new chemical class and that has a unique mechanism and promising activity against multidrug-resistant Pseudomonas aeruginosa. We show that MAC13243 inhibits the function of the LolA protein and represents a new chemical probe of lipoprotein targeting in bacteria with promise as an antibacterial lead with Gram-negative selectivity.

Small and lethal: searching for new antibacterial compounds with novel modes of action

The discovery of drugs used to combat infectious diseases is in the process of constant change to address the ever-worsening problem of antibiotic resistance in pathogens and a lack of recent success in discovering new antibacterial drugs. In the past 2 decades, research in both academia and industry has made use of molecular biology, genetics, and comparative genomics, which has led to the development of key technologies for the discovery of novel antibacterial agents. Genome-scale efforts have led to the identification of numerous molecular targets. Chemical diversity from synthetic combinatorial libraries and natural products is being used to screen for new molecules. A wide variety of approaches are being used in the search for novel antibiotics, and these can be categorized as being either biochemically focused or cell based. The over-riding goal of all methods in use today is to discover new chemical matter with novel mechanisms of action against drug-resistant pathogens.

A multicopy suppressor screening approach as a means to identify antibiotic resistance determinant candidates in Yersinia pestis

Background

Yersinia pestis is the causative agent of plague and a potential agent of bioterrorism and biowarfare. The plague biothreat and the emergence of multidrug-resistant plague underscore the need to increase our understanding of the intrinsic potential of Y. pestis for developing antimicrobial resistance and to anticipate the mechanisms of resistance that may emerge in Y. pestis. Identification of Y. pestis genes that, when overexpressed, are capable of reducing antibiotic susceptibility is a useful strategy to expose genes that this pathogen may rely upon to evolve antibiotic resistance via a vertical modality. In this study, we explored the use of a multicopy suppressor, Escherichia coli host-based screening approach as a means to expose antibiotic resistance determinant candidates in Y. pestis.

Results

We constructed a multicopy plasmid-based, Y. pestis genome-wide expression library of nearly 16,000 clones in E. coli and screened the library for suppressors of the antimicrobial activity of ofloxacin, a fluoroquinolone antibiotic. The screen permitted the identification of a transcriptional regulator-encoding gene (robA_Yp) that increased the MIC₉₉ of ofloxacin by 23-fold when overexpressed from a multicopy plasmid in Y. pestis. Additionally, we found that robA_Yp overexpression in Y. pestis conferred low-level resistance to many other antibiotics and increased organic solvent tolerance. Overexpression of robA_Yp also upregulated the expression of several efflux pumps in Y. pestis.

Conclusion

Our study provides proof of principle for the use of multicopy suppressor screening based on the tractable and easy-to-manipulate E. coli host as a means to identify antibiotic resistance determinant candidates of Y. pestis.

An integrated platform of genomic assays reveals small-molecule bioactivities

Bioactive compounds are widely used to modulate protein function and can serve as important leads for drug development. Identifying the in vivo targets of these compounds remains a challenge. Using yeast, we integrated three genome-wide gene-dosage assays to measure the effect of small molecules in vivo. A single TAG microarray was used to resolve the fitness of strains derived from pools of (i) homozygous deletion mutants, (ii) heterozygous deletion mutants and (iii) genomic library transformants. We demonstrated, with eight diverse reference compounds, that integration of these three chemogenomic profiles improves the sensitivity and specificity of small-molecule target identification. We further dissected the mechanism of action of two protein phosphatase inhibitors and in the process developed a framework for the rational design of multidrug combinations to sensitize cells with specific genotypes more effectively. Finally, we applied this platform to 188 novel synthetic chemical compounds and identified both potential targets and structure-activity relationships.

Target-based antimicrobial drug discovery

The continued increase in antibiotic resistance among bacterial pathogens, coupled with a decrease in infectious disease research among pharmaceutical companies, has escalated the need for novel and effective antibacterial chemotherapies. While current agents have emerged almost exclusively from whole-cell screening of natural products and small molecules that cause microbial death, recent advances in target identification and assay development have resulted in a flood of target-driven drug discovery methods. Whether genome-based methodologies will yield new classes of agents that conventional methods have been unable to is yet to be seen. At the end of the day, perhaps a synergy between old and new approaches will harvest the next generation of antibacterial treatments.