Opposing effects of target overexpression reveal drug mechanisms

Integrating bacterial molecular genetics with chemical biology for renewed antibacterial drug discovery

The application of dyes to understanding the aetiology of infection inspired antimicrobial chemotherapy and the first wave of antibacterial drugs. The second wave of antibacterial drug discovery was driven by rapid discovery of natural products, now making up 69% of current antibacterial drugs. But now with the most prevalent natural products already discovered, ∼107 new soil-dwelling bacterial species must be screened to discover one new class of natural product. Therefore, instead of a third wave of antibacterial drug discovery, there is now a discovery bottleneck. Unlike natural products which are curated by billions of years of microbial antagonism, the vast synthetic chemical space still requires artificial curation through the therapeutics science of antibacterial drugs - a systematic understanding of how small molecules interact with bacterial physiology, effect desired phenotypes, and benefit the host. Bacterial molecular genetics can elucidate pathogen biology relevant to therapeutics development, but it can also be applied directly to understanding mechanisms and liabilities of new chemical agents with new mechanisms of action. Therefore, the next phase of antibacterial drug discovery could be enabled by integrating chemical expertise with systematic dissection of bacterial infection biology. Facing the ambitious endeavour to find new molecules from nature or new-to-nature which cure bacterial infections, the capabilities furnished by modern chemical biology and molecular genetics can be applied to prospecting for chemical modulators of new targets which circumvent prevalent resistance mechanisms.

Investigating Antiprotozoal Chemotherapies with Novel Proteomic Tools-Chances and Limitations: A Critical Review

Identification of drug targets and biochemical investigations on mechanisms of action are major issues in modern drug development. The present article is a critical review of the classical "one drug"-"one target" paradigm. In fact, novel methods for target deconvolution and for investigation of resistant strains based on protein mass spectrometry have shown that multiple gene products and adaptation mechanisms are involved in the responses of pathogens to xenobiotics rather than one single gene or gene product. Resistance to drugs may be linked to differential expression of other proteins than those interacting with the drug in protein binding studies and result in complex cell physiological adaptation. Consequently, the unraveling of mechanisms of action needs approaches beyond proteomics. This review is focused on protozoan pathogens. The conclusions can, however, be extended to chemotherapies against other pathogens or cancer.

Distinguishing mutants that resist drugs via different mechanisms by examining fitness tradeoffs

There is growing interest in designing multidrug therapies that leverage tradeoffs to combat resistance. Tradeoffs are common in evolution and occur when, for example, resistance to one drug results in sensitivity to another. Major questions remain about the extent to which tradeoffs are reliable, specifically, whether the mutants that provide resistance to a given drug all suffer similar tradeoffs. This question is difficult because the drug-resistant mutants observed in the clinic, and even those evolved in controlled laboratory settings, are often biased towards those that provide large fitness benefits. Thus, the mutations (and mechanisms) that provide drug resistance may be more diverse than current data suggests. Here, we perform evolution experiments utilizing lineage-tracking to capture a fuller spectrum of mutations that give yeast cells a fitness advantage in fluconazole, a common antifungal drug. We then quantify fitness tradeoffs for each of 774 evolved mutants across 12 environments, finding these mutants group into 6 classes with characteristically different tradeoffs. Their unique tradeoffs may imply that each group of mutants affects fitness through different underlying mechanisms. Some of the groupings we find are surprising. For example, we find some mutants that resist single drugs do not resist their combination, while others do. And some mutants to the same gene have different tradeoffs than others. These findings, on one hand, demonstrate the difficulty in relying on consistent or intuitive tradeoffs when designing multidrug treatments. On the other hand, by demonstrating that hundreds of adaptive mutations can be reduced to a few groups with characteristic tradeoffs, our findings may yet empower multidrug strategies that leverage tradeoffs to combat resistance. More generally speaking, by grouping mutants that likely affect fitness through similar underlying mechanisms, our work guides efforts to map the phenotypic effects of mutation.

Perturbation-Specific Transcriptional Mapping for unbiased target elucidation of antibiotics

The rising prevalence of antibiotic resistance threatens human health. While more sophisticated strategies for antibiotic discovery are being developed, target elucidation of new chemical entities remains challenging. In the post-genomic era, expression profiling can play an important role in mechanism-of-action (MOA) prediction by reporting on the cellular response to perturbation. However, the broad application of transcriptomics has yet to fulfill its promise of transforming target elucidation due to challenges in identifying the most relevant, direct responses to target inhibition. We developed an unbiased strategy for MOA prediction, called Perturbation-Specific Transcriptional Mapping (PerSpecTM), in which large-throughput expression profiling of wildtype or hypomorphic mutants, depleted for essential targets, enables a computational strategy to address this challenge. We applied PerSpecTM to perform reference-based MOA prediction based on the principle that similar perturbations, whether chemical or genetic, will elicit similar transcriptional responses. Using this approach, we elucidated the MOAs of three new molecules with activity against Pseudomonas aeruginosa by comparing their expression profiles to those of a reference set of antimicrobial compounds with known MOAs. We also show that transcriptional responses to small molecule inhibition resemble those resulting from genetic depletion of essential targets by CRISPRi by PerSpecTM, demonstrating proof-of-concept that correlations between expression profiles of small molecule and genetic perturbations can facilitate MOA prediction when no chemical entities exist to serve as a reference. Empowered by PerSpecTM, this work lays the foundation for an unbiased, readily scalable, systematic reference-based strategy for MOA elucidation that could transform antibiotic discovery efforts.

Dynamic microfluidic single-cell screening identifies pheno-tuning compounds to potentiate tuberculosis therapy

Drug-recalcitrant infections are a leading global-health concern. Bacterial cells benefit from phenotypic variation, which can suggest effective antimicrobial strategies. However, probing phenotypic variation entails spatiotemporal analysis of individual cells that is technically challenging, and hard to integrate into drug discovery. In this work, we develop a multi-condition microfluidic platform suitable for imaging two-dimensional growth of bacterial cells during transitions between separate environmental conditions. With this platform, we implement a dynamic single-cell screening for pheno-tuning compounds, which induce a phenotypic change and decrease cell-to-cell variation, aiming to undermine the entire bacterial population and make it more vulnerable to other drugs. We apply this strategy to mycobacteria, as tuberculosis poses a major public-health threat. Our lead compound impairs Mycobacterium tuberculosis via a peculiar mode of action and enhances other anti-tubercular drugs. This work proves that harnessing phenotypic variation represents a successful approach to tackle pathogens that are increasingly difficult to treat.

Evaluation of Fusobacterium nucleatum Enoyl-ACP Reductase (FabK) as a Narrow-Spectrum Drug Target

Fusobacterium nucleatum, a pathobiont inhabiting the oral cavity, contributes to opportunistic diseases, such as periodontal diseases and gastrointestinal cancers, which involve microbiota imbalance. Broad-spectrum antimicrobial agents, while effective against F. nucleatum infections, can exacerbate dysbiosis. This necessitates the discovery of more targeted narrow-spectrum antimicrobial agents. We therefore investigated the potential for the fusobacterial enoyl-ACP reductase II (ENR II) isoenzyme FnFabK (C4N14_ 04250) as a narrow-spectrum drug target. ENRs catalyze the rate-limiting step in the bacterial fatty acid synthesis pathway. Bioinformatics revealed that of the four distinct bacterial ENR isoforms, F. nucleatum specifically encodes FnFabK. Genetic studies revealed that fabK was indispensable for F. nucleatum growth, as the gene could not be deleted, and silencing of its mRNA inhibited growth under the test conditions. Remarkably, exogenous fatty acids failed to rescue growth inhibition caused by the silencing of fabK. Screening of synthetic phenylimidazole analogues of a known FabK inhibitor identified an inhibitor (i.e., 681) of FnFabK enzymatic activity and F. nucleatum growth, with an IC50 of 2.1 μM (1.0 μg/mL) and a MIC of 0.4 μg/mL, respectively. Exogenous fatty acids did not attenuate the activity of 681 against F. nucleatum. Furthermore, FnFabK was confirmed as the intracellular target of 681 based on the overexpression of FnFabK shifting MICs and 681-resistant mutants having amino acid substitutions in FnFabK or mutations in other genetic loci affecting fatty acid biosynthesis. 681 had minimal activity against a range of commensal flora, and it was less active against streptococci in physiologic fatty acids. Taken together, FnFabK is an essential enzyme that is amenable to drug targeting for the discovery and development of narrow-spectrum antimicrobial agents.

Discovery of a nitroaromatic nannocystin with potent in vivo anticancer activity against colorectal cancer by targeting AKT1

The development of targeted chemotherapeutic agents against colorectal cancer (CRC), one of the most common cancers with a high mortality rate, is in a constant need. Nannocystins are a family of myxobacterial secondary metabolites featuring a 21-membered depsipeptide ring. The in vitro anti-CRC activity of natural and synthetic nannocystins was well documented, but little is known about their in vivo efficacy and if positive, the underlying mechanism of action. In this study we synthesized a nitroaromatic nannocystin through improved preparation of a key fragment, and characterized its in vitro activity and in vivo efficacy against CRC. We first described the total synthesis of compounds 2-4 featuring Heck macrocyclization to forge their 21-membered macrocycle. In a panel of 7 cancer cell lines from different tissues, compound 4 inhibited the cell viability with IC values of 1-6 nM. In particular, compound 4 (1, 2, 4 nM) inhibited the proliferation of CRC cell lines (HCT8, HCT116 and LoVo) in both concentration and time dependent manners. Furthermore, compound 4 concentration-dependently inhibited the colony formation and migration of CRC cell lines. Moreover, compound 4 induced cell cycle arrest at sub-G1 phase, apoptosis and cellular senescence in CRC cell lines. In three patient-derived CRC organoids, compound 4 inhibited the PDO with IC values of 3.68, 28.93 and 11.81 nM, respectively. In a patient-derived xenograft mouse model, injection of compound 4 (4, 8 mg/kg, i.p.) every other day for 12 times dose-dependently inhibited the tumor growth without significant change in body weight. We conducted RNA-sequencing, molecular docking and cellular thermal shift assay to elucidate the anti-CRC mechanisms of compound 4, and revealed that it exerted its anti-CRC effect at least in part by targeting AKT1.

A dose-response model for statistical analysis of chemical genetic interactions in CRISPRi screens

An important application of CRISPR interference (CRISPRi) technology is for identifying chemical-genetic interactions (CGIs). Discovery of genes that interact with exposure to antibiotics can yield insights to drug targets and mechanisms of action or resistance. The objective is to identify CRISPRi mutants whose relative abundance is suppressed (or enriched) in the presence of a drug when the target protein is depleted, reflecting synergistic behavior. Different sgRNAs for a given target can induce a wide range of protein depletion and differential effects on growth rate. The effect of sgRNA strength can be partially predicted based on sequence features. However, the actual growth phenotype depends on the sensitivity of cells to depletion of the target protein. For essential genes, sgRNA efficiency can be empirically measured by quantifying effects on growth rate. We observe that the most efficient sgRNAs are not always optimal for detecting synergies with drugs. sgRNA efficiency interacts in a non-linear way with drug sensitivity, producing an effect where the concentration-dependence is maximized for sgRNAs of intermediate strength (and less so for sgRNAs that induce too much or too little target depletion). To capture this interaction, we propose a novel statistical method called CRISPRi-DR (for Dose-Response model) that incorporates both sgRNA efficiencies and drug concentrations in a modified dose-response equation. We use CRISPRi-DR to re-analyze data from a recent CGI experiment in Mycobacterium tuberculosis to identify genes that interact with antibiotics. This approach can be generalized to non-CGI datasets, which we show via an CRISPRi dataset for E. coli growth on different carbon sources. The performance is competitive with the best of several related analytical methods. However, for noisier datasets, some of these methods generate far more significant interactions, likely including many false positives, whereas CRISPRi-DR maintains higher precision, which we observed in both empirical and simulated data.

Bacteriophages as a potential substitute for antibiotics: A comprehensive review

Over the years, the administration of antibiotics for the purpose of addressing bacterial infections has become increasingly challenging due to the increased prevalence of antimicrobial resistance exhibited by various strains of bacteria. Multidrug-resistant (MDR) bacterial species are rising due to the unavailability of novel antibiotics, leading to higher mortality rates. With these conditions, there is a need for alternatives in which phage therapy has made promising results. Phage-derived endolysins, phage cocktails, and bioengineered phages are effective and have antimicrobial properties against MDR and extensively drug-resistant strains. Despite these, it has been observed that phages can give antimicrobial activity to more than one bacterial species. Thus, phage cocktail against resistant strains provides broad spectrum treatment and magnitude of effectivity, which is many folds higher than antibiotics. Many commercially available endolysins such as Staphefekt SA.100, Exebacase (CF-301), and N-Rephasin®SAL200 are used in biofilm penetration and treating plant diseases. The role of CMP1 phage endolysin in transgenic tomato plants in preventing Clavibacter michiganensis infection and the effectiveness of phage in protecting Atlantic salmon from vibriosis have been reported. Furthermore, phage-derived endolysin therapy, such as TSPphg phage exogenous treatment, can aid in disrupting cell walls, leading to bacterial cell lysis. As animals in aquaculture and slaughterhouses are highly susceptible to bacterial infections, effective phage therapy instead of antibiotics can help treat poultry animals, preserve them, and facilitate disease-free trade. Using bioengineered phages and phage cocktails enhances the effectiveness by providing a broad spectrum of phages and target specificity. Research is currently being conducted on clinical trials to confirm the efficacy of engineered phages and phage cocktails in humans. Although obtaining commercial approval may be time-consuming, it will be beneficial in the postantibiotic era. This review provides an overview of the significance of phage therapy as a potential alternative to antibiotics in combating resistant bacterial strains and its application to various fields and emphasizes the importance of safeguarding and ensuring treatment efficacy.

Antimicrobial Action Mechanisms of Natural Compounds Isolated from Endophytic Microorganisms

Infectious diseases are a significant challenge to global healthcare, especially in the face of increasing antibiotic resistance. This urgent issue requires the continuous exploration and development of new antimicrobial drugs. In this regard, the secondary metabolites derived from endophytic microorganisms stand out as promising sources for finding antimicrobials. Endophytic microorganisms, residing within the internal tissues of plants, have demonstrated the capacity to produce diverse bioactive compounds with substantial pharmacological potential. Therefore, numerous new antimicrobial compounds have been isolated from endophytes, particularly from endophytic fungi and actinomycetes. However, only a limited number of these compounds have been subjected to comprehensive studies regarding their mechanisms of action against bacterial cells. Furthermore, the investigation of their effects on antibiotic-resistant bacteria and the identification of biosynthetic gene clusters responsible for synthesizing these secondary metabolites have been conducted for only a subset of these promising compounds. Through a comprehensive analysis of current research findings, this review describes the mechanisms of action of antimicrobial drugs and secondary metabolites isolated from endophytes, antibacterial activities of the natural compounds derived from endophytes against antibiotic-resistant bacteria, and biosynthetic gene clusters of endophytic fungi responsible for the synthesis of bioactive secondary metabolites.

A Targeted Genome-scale Overexpression Platform for Proteobacteria

Targeted, genome-scale gene perturbation screens using Clustered Regularly Interspaced Short Palindromic Repeats interference (CRISPRi) and activation (CRISPRa) have revolutionized eukaryotic genetics, advancing medical, industrial, and basic research. Although CRISPRi knockdowns have been broadly applied in bacteria, options for genome-scale overexpression face key limitations. Here, we develop a facile approach for genome-scale gene overexpression in bacteria we call, "CRISPRtOE" (CRISPR transposition and OverExpression). We create a platform for comprehensive gene targeting using CRISPR-associated transposition (CAST) and show that transposition occurs at a higher frequency in non-transcribed DNA. We then demonstrate that CRISPRtOE can upregulate gene expression in Proteobacteria with medical and industrial relevance by integrating synthetic promoters of varying strength upstream of target genes. Finally, we employ CRISPRtOE screening at the genome-scale in Escherichia coli, recovering known antibiotic targets and genes with unexplored roles in antibiotic function. We envision that CRISPRtOE will be a valuable overexpression tool for antibiotic mode of action, industrial strain optimization, and gene function discovery in bacteria.

Vacuolar Proton-Translocating ATPase May Take Part in the Drug Resistance Phenotype of Glioma Stem Cells

The vacuolar proton-translocating ATPase (V-ATPase) is a transmembrane multi-protein complex fundamental in maintaining a normal intracellular pH. In the tumoral contest, its role is crucial since the metabolism underlying carcinogenesis is mainly based on anaerobic glycolytic reactions. Moreover, neoplastic cells use the V-ATPase to extrude chemotherapy drugs into the extra-cellular compartment as a drug resistance mechanism. In glioblastoma (GBM), the most malignant and incurable primary brain tumor, the expression of this pump is upregulated, making it a new possible therapeutic target. In this work, the bafilomycin A1-induced inhibition of V-ATPase in patient-derived glioma stem cell (GSC) lines was evaluated together with temozolomide, the first-line therapy against GBM. In contrast with previous published data, the proposed treatment did not overcome resistance to the standard therapy. In addition, our data showed that nanomolar dosages of bafilomycin A1 led to the blockage of the autophagy process and cellular necrosis, making the drug unusable in models which are more complex. Nevertheless, the increased expression of V-ATPase following bafilomycin A1 suggests a critical role of the proton pump in GBM stem components, encouraging the search for novel strategies to limit its activity in order to circumvent resistance to conventional therapy.

Comparative chemical genomics in Babesia species identifies the alkaline phosphatase PhoD as a determinant of antiparasitic resistance

Babesiosis is an emerging zoonosis and widely distributed veterinary infection caused by 100+ species of Babesia parasites. The diversity of Babesia parasites and the lack of specific drugs necessitate the discovery of broadly effective antibabesials. Here, we describe a comparative chemogenomics (CCG) pipeline for the identification of conserved targets. CCG relies on parallel in vitro evolution of resistance in independent populations of Babesia spp. (B. bovis and B. divergens). We identified a potent antibabesial, MMV019266, from the Malaria Box, and selected for resistance in two species of Babesia. After sequencing of multiple independently derived lines in the two species, we identified mutations in a membrane-bound metallodependent phosphatase (phoD). In both species, the mutations were found in the phoD-like phosphatase domain. Using reverse genetics, we validated that mutations in bdphoD confer resistance to MMV019266 in B. divergens. We have also demonstrated that BdPhoD localizes to the endomembrane system and partially with the apicoplast. Finally, conditional knockdown and constitutive overexpression of BdPhoD alter the sensitivity to MMV019266 in the parasite. Overexpression of BdPhoD results in increased sensitivity to the compound, while knockdown increases resistance, suggesting BdPhoD is a pro-susceptibility factor. Together, we have generated a robust pipeline for identification of resistance loci and identified BdPhoD as a resistance mechanism in Babesia species.

A dose-response model for statistical analysis of chemical genetic interactions in CRISPRi screens

An important application of CRISPR interference (CRISPRi) technology is for identifying chemical-genetic interactions (CGIs). Discovery of genes that interact with exposure to antibiotics can yield insights to drug targets and mechanisms of action or resistance. The objective is to identify CRISPRi mutants whose relative abundance is suppressed (or enriched) in the presence of a drug when the target protein is depleted, reflecting synergistic behavior. Different sgRNAs for a given target can induce a wide range of protein depletion and differential effects on growth rate. The effect of sgRNA strength can be partially predicted based on sequence features. However, the actual growth phenotype depends on the sensitivity of cells to depletion of the target protein. For essential genes, sgRNA efficiency can be empirically measured by quantifying effects on growth rate. We observe that the most efficient sgRNAs are not always optimal for detecting synergies with drugs. sgRNA efficiency interacts in a non-linear way with drug sensitivity, producing an effect where the concentration-dependence is maximized for sgRNAs of intermediate strength (and less so for sgRNAs that induce too much or too little target depletion). To capture this interaction, we propose a novel statistical method called CRISPRi-DR (for Dose-Response model) that incorporates both sgRNA efficiencies and drug concentrations in a modified dose-response equation. We use CRISPRi-DR to re-analyze data from a recent CGI experiment in Mycobacterium tuberculosis to identify genes that interact with antibiotics. This approach can be generalized to non-CGI datasets, which we show via an CRISPRi dataset for E. coli growth on different carbon sources. The performance is competitive with the best of several related analytical methods. However, for noisier datasets, some of these methods generate far more significant interactions, likely including many false positives, whereas CRISPRi-DR maintains higher precision, which we observed in both empirical and simulated data.

Homoharringtonine as a PHGDH inhibitor: Unraveling metabolic dependencies and developing a potent therapeutic strategy for high-risk neuroblastoma

Neuroblastoma, a childhood cancer affecting the sympathetic nervous system, continues to challenge the development of potent treatments due to the limited availability of druggable targets for this aggressive illness. Recent investigations have uncovered that phosphoglycerate dehydrogenase (PHGDH), an essential enzyme for de novo serine synthesis, serves as a non-oncogene dependency in high-risk neuroblastoma. In this study, we show that homoharringtonine (HHT) acts as a PHGDH inhibitor, inducing intricate alterations in cellular metabolism, and thus providing an efficient treatment for neuroblastoma. We have experimentally verified the reliance of neuroblastoma on PHGDH and employed molecular docking, thermodynamic evaluations, and X-ray crystallography techniques to determine the bond interactions between HHT and PHGDH. Administering HHT to treat neuroblastoma resulted in effective cell elimination in vitro and tumor reduction in vivo. Metabolite and functional assessments additionally disclosed that HHT treatment suppressed de novo serine synthesis, initiating intricate metabolic reconfiguration and oxidative stress in neuroblastoma. Collectively, these discoveries highlight the potential of targeting PHGDH using HHT as a potent approach for managing high-risk neuroblastoma.

Comparative chemical genomics in Babesia species identifies the alkaline phosphatase phoD as a novel determinant of resistance

Babesiosis is an emerging zoonosis and widely distributed veterinary infection caused by 100+ species of Babesia parasites. The diversity of Babesia parasites, coupled with the lack of potent inhibitors necessitates the discovery of novel conserved druggable targets for the generation of broadly effective antibabesials. Here, we describe a comparative chemogenomics (CCG) pipeline for the identification of novel and conserved targets. CCG relies on parallel in vitro evolution of resistance in independent populations of evolutionarily-related Babesia spp. ( B. bovis and B. divergens ). We identified a potent antibabesial inhibitor from the Malaria Box, MMV019266. We were able to select for resistance to this compound in two species of Babesia, achieving 10-fold or greater resistance after ten weeks of intermittent selection. After sequencing of multiple independently derived lines in the two species, we identified mutations in a single conserved gene in both species: a membrane-bound metallodependent phosphatase (putatively named PhoD). In both species, the mutations were found in the phoD-like phosphatase domain, proximal to the predicted ligand binding site. Using reverse genetics, we validated that mutations in PhoD confer resistance to MMV019266. We have also demonstrated that PhoD localizes to the endomembrane system and partially with the apicoplast. Finally, conditional knockdown and constitutive overexpression of PhoD alter the sensitivity to MMV019266 in the parasite: overexpression of PhoD results in increased sensitivity to the compound, while knockdown increases resistance, suggesting PhoD is a resistance mechanism. Together, we have generated a robust pipeline for identification of resistance loci, and identified PhoD as a novel determinant of resistance in Babesia species.

Highlights

Use of two species for in vitro evolution identifies a high confidence locus associated with resistance Resistance mutation in phoD was validated using reverse genetics in B. divergens Perturbation of phoD using function genetics results in changes in the level of resistance to MMV019266Epitope tagging reveals localization to the ER/apicoplast, a conserved localization with a similar protein in diatoms Together, phoD is a novel resistance determinant in multiple Babesia spp .

Plasmodium falciparum Eukaryotic Translation Initiation Factor 3 is Stabilized by Quinazoline-Quinoline Bisubstrate Inhibitors

Malaria drug resistance is hampering the fight against the deadliest parasitic disease affecting over 200 million people worldwide. We recently developed quinoline-quinazoline-based inhibitors (as compound 70) as promising new antimalarials. Here, we aimed to investigate their mode of action by using thermal proteome profiling (TPP). The eukaryotic translation initiation factor 3 (EIF3i) subunit I was identified as the main target protein stabilized by compound 70 in Plasmodium falciparum. This protein has never been characterized in malaria parasites. P. falciparum parasite lines were generated expressing either a HA tag or an inducible knockdown of the PfEIF3i gene to further characterize the target protein. PfEIF3i was stabilized in the presence of compound 70 in a cellular thermal shift Western blot assay, pointing that PfEIF3i indeed interacts with quinoline-quinazoline-based inhibitors. In addition, PfEIF3i-inducible knockdown blocks intra-erythrocytic development in the trophozoite stage, indicating that it has a vital function. We show that PfEIF3i is mostly expressed in late intra-erythrocytic stages and localizes in the cytoplasm. Previous mass spectrometry reports show that PfEIF3i is expressed in all parasite life cycle stages. Further studies will explore the potential of PfEIF3i as a target for the design of new antimalarial drugs active all along the life cycle of the parasite.

Drug repositioning targeting glutaminase reveals drug candidates for the treatment of Alzheimer's disease patients

BACKGROUND

Despite numerous clinical trials and decades of endeavour, there is still no effective cure for Alzheimer's disease. Computational drug repositioning approaches may be employed for the development of new treatment strategies for Alzheimer's patients since an extensive amount of omics data has been generated during pre-clinical and clinical studies. However, targeting the most critical pathophysiological mechanisms and determining drugs with proper pharmacodynamics and good efficacy are equally crucial in drug repurposing and often imbalanced in Alzheimer's studies.

METHODS

Here, we investigated central co-expressed genes upregulated in Alzheimer's disease to determine a proper therapeutic target. We backed our reasoning by checking the target gene's estimated non-essentiality for survival in multiple human tissues. We screened transcriptome profiles of various human cell lines perturbed by drug induction (for 6798 compounds) and gene knockout using data available in the Connectivity Map database. Then, we applied a profile-based drug repositioning approach to discover drugs targeting the target gene based on the correlations between these transcriptome profiles. We evaluated the bioavailability, functional enrichment profiles and drug-protein interactions of these repurposed agents and evidenced their cellular viability and efficacy in glial cell culture by experimental assays and Western blotting. Finally, we evaluated their pharmacokinetics to anticipate to which degree their efficacy can be improved.

RESULTS

We identified glutaminase as a promising drug target. Glutaminase overexpression may fuel the glutamate excitotoxicity in neurons, leading to mitochondrial dysfunction and other neurodegeneration hallmark processes. The computational drug repurposing revealed eight drugs: mitoxantrone, bortezomib, parbendazole, crizotinib, withaferin-a, SA-25547 and two unstudied compounds. We demonstrated that the proposed drugs could effectively suppress glutaminase and reduce glutamate production in the diseased brain through multiple neurodegeneration-associated mechanisms, including cytoskeleton and proteostasis. We also estimated the human blood-brain barrier permeability of parbendazole and SA-25547 using the SwissADME tool.

CONCLUSIONS

This study method effectively identified an Alzheimer's disease marker and compounds targeting the marker and interconnected biological processes by use of multiple computational approaches. Our results highlight the importance of synaptic glutamate signalling in Alzheimer's disease progression. We suggest repurposable drugs (like parbendazole) with well-evidenced activities that we linked to glutamate synthesis hereby and novel molecules (SA-25547) with estimated mechanisms for the treatment of Alzheimer's patients.

Fungal Drug Response and Antimicrobial Resistance

Antifungal resistance is a growing concern as it poses a significant threat to public health. Fungal infections are a significant cause of morbidity and mortality, especially in immunocompromised individuals. The limited number of antifungal agents and the emergence of resistance have led to a critical need to understand the mechanisms of antifungal drug resistance. This review provides an overview of the importance of antifungal resistance, the classes of antifungal agents, and their mode of action. It highlights the molecular mechanisms of antifungal drug resistance, including alterations in drug modification, activation, and availability. In addition, the review discusses the response to drugs via the regulation of multidrug efflux systems and antifungal drug-target interactions. We emphasize the importance of understanding the molecular mechanisms of antifungal drug resistance to develop effective strategies to combat the emergence of resistance and highlight the need for continued research to identify new targets for antifungal drug development and explore alternative therapeutic options to overcome resistance. Overall, an understanding of antifungal drug resistance and its mechanisms will be indispensable for the field of antifungal drug development and clinical management of fungal infections.

Overexpression profiling reveals cellular requirements in the context of genetic backgrounds and environments

Overexpression can help life adapt to stressful environments, making an examination of overexpressed genes valuable for understanding stress tolerance mechanisms. However, a systematic study of genes whose overexpression is functionally adaptive (GOFAs) under stress has yet to be conducted. We developed a new overexpression profiling method and systematically identified GOFAs in Saccharomyces cerevisiae under stress (heat, salt, and oxidative). Our results show that adaptive overexpression compensates for deficiencies and increases fitness under stress, like calcium under salt stress. We also investigated the impact of different genetic backgrounds on GOFAs, which varied among three S. cerevisiae strains reflecting differing calcium and potassium requirements for salt stress tolerance. Our study of a knockout collection also suggested that calcium prevents mitochondrial outbursts under salt stress. Mitochondria-enhancing GOFAs were only adaptive when adequate calcium was available and non-adaptive when calcium was deficient, supporting this idea. Our findings indicate that adaptive overexpression meets the cell's needs for maximizing the organism's adaptive capacity in the given environment and genetic context.

Growth-mediated negative feedback shapes quantitative antibiotic response

Dose–response relationships are a general concept for quantitatively describing biological systems across multiple scales, from the molecular to the whole‐cell level. A clinically relevant example is the bacterial growth response to antibiotics, which is routinely characterized by dose–response curves. The shape of the dose–response curve varies drastically between antibiotics and plays a key role in treatment, drug interactions, and resistance evolution. However, the mechanisms shaping the dose–response curve remain largely unclear. Here, we show in Escherichia coli that the distinctively shallow dose–response curve of the antibiotic trimethoprim is caused by a negative growth‐mediated feedback loop: Trimethoprim slows growth, which in turn weakens the effect of this antibiotic. At the molecular level, this feedback is caused by the upregulation of the drug target dihydrofolate reductase (FolA/DHFR). We show that this upregulation is not a specific response to trimethoprim but follows a universal trend line that depends primarily on the growth rate, irrespective of its cause. Rewiring the feedback loop alters the dose–response curve in a predictable manner, which we corroborate using a mathematical model of cellular resource allocation and growth. Our results indicate that growth‐mediated feedback loops may shape drug responses more generally and could be exploited to design evolutionary traps that enable selection against drug resistance.

Mechanisms of antibiotic action shape the fitness landscapes of resistance mutations

Antibiotic-resistant pathogens are a major public health threat. A deeper understanding of how an antibiotic's mechanism of action influences the emergence of resistance would aid in the design of new drugs and help to preserve the effectiveness of existing ones. To this end, we developed a model that links bacterial population dynamics with antibiotic-target binding kinetics. Our approach allows us to derive mechanistic insights on drug activity from population-scale experimental data and to quantify the interplay between drug mechanism and resistance selection. We find that both bacteriostatic and bactericidal agents can be equally effective at suppressing the selection of resistant mutants, but that key determinants of resistance selection are the relationships between the number of drug-inactivated targets within a cell and the rates of cellular growth and death. We also show that heterogeneous drug-target binding within a population enables resistant bacteria to evolve fitness-improving secondary mutations even when drug doses remain above the resistant strain's minimum inhibitory concentration. Our work suggests that antibiotic doses beyond this "secondary mutation selection window" could safeguard against the emergence of high-fitness resistant strains during treatment.

Low-cost anti-mycobacterial drug discovery using engineered E. coli

Whole-cell screening for Mycobacterium tuberculosis (Mtb) inhibitors is complicated by the pathogen's slow growth and biocontainment requirements. Here we present a synthetic biology framework for assaying Mtb drug targets in engineered E. coli. We construct Target Essential Surrogate E. coli (TESEC) in which an essential metabolic enzyme is deleted and replaced with an Mtb-derived functional analog, linking bacterial growth to the activity of the target enzyme. High throughput screening of a TESEC model for Mtb alanine racemase (Alr) revealed benazepril as a targeted inhibitor, a result validated in whole-cell Mtb. In vitro biochemical assays indicated a noncompetitive mechanism unlike that of clinical Alr inhibitors. We establish the scalability of TESEC for drug discovery by characterizing TESEC strains for four additional targets.

Novel potential NOX2 inhibitors, Dudleya brittonii water extract and polygalatenoside A inhibit intracellular ROS generation and growth of melanoma

Reactive oxygen species (ROS) are key regulators of the proliferation, metastasis, and drug resistance of melanoma, which accounts for 60% of skin cancer deaths. In a previous study, we developed Dudleya brittonii water extract (DBWE) with antioxidant activity, but the mechanism of action and bioactive substances of DBWE have not been fully identified. This study showed altered NADPH oxidase 2 (NOX2) expression and selective inhibition of cytosolic ROS but not mitochondrial ROS in B16-F10 melanoma cells, suggesting the NOX2 inhibitory potential of DBWE. In addition, DBWE inhibited mitochondrial activity, lipid metabolism, and cell cycle in B16-F10 cells. The anti-melanoma effect of DBWE was abrogated by the addition of ROS, and there was no significant change in the melanogenesis pathway. Polygalatenoside A was identified as a candidate bioactive substance in the DBWE aqueous fraction through mass spectrometry, and the DBWE-like anti-melanoma effect was confirmed. These data suggest that DBWE and polygalatenoside A have the potential to prevent and treat melanoma.

Expanding the search for small-molecule antibacterials by multidimensional profiling

New techniques for systematic profiling of small-molecule effects can enhance traditional growth inhibition screens for antibiotic discovery and change how we search for new antibacterial agents. Computational models that integrate physicochemical compound properties with their phenotypic and molecular downstream effects can not only predict efficacy of molecules yet to be tested, but also reveal unprecedented insights on compound modes of action (MoAs). The unbiased characterization of compounds that themselves are not growth inhibitory but exhibit diverse MoAs, can expand antibacterial strategies beyond direct inhibition of core essential functions. Early and systematic functional annotation of compound libraries thus paves the way to new models in the selection of lead antimicrobial compounds. In this Review, we discuss how multidimensional small-molecule profiling and the ever-increasing computing power are accelerating the discovery of unconventional antibacterials capable of bypassing resistance and exploiting synergies with established antibacterial treatments and with protective host mechanisms.

Integrated genomics and chemical biology herald an era of sophisticated antibacterial discovery, from defining essential genes to target elucidation

The golden age of antibiotic discovery in the 1940s-1960s saw the development and deployment of many different classes of antibiotics, revolutionizing the field of medicine. Since that time, our ability to discover antibiotics of novel structural classes or mechanisms has not kept pace with the ever-growing threat of antibiotic resistance. Recently, advances at the intersection of genomics and chemical biology have enabled efforts to better define the vulnerabilities of essential gene targets, to develop sophisticated whole-cell chemical screening methods that reveal target biology early, and to elucidate small molecule targets and modes of action more effectively. These new technologies have the potential to expand the chemical diversity of antibiotic candidates, as well as the breadth of targets. We illustrate how the latest tools of genomics and chemical biology are being integrated to better understand pathogen vulnerabilities and antibiotic mechanisms in order to inform a new era of antibiotic discovery.

Gradients in gene essentiality reshape antibacterial research

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

Dynamic gene expression and growth underlie cell-to-cell heterogeneity in Escherichia coli stress response

Individual bacteria that share identical genomes and growth environments can display substantial cell-to-cell differences in expression of stress-response genes and single-cell growth rates. This phenotypic heterogeneity can impact the survival of single cells facing sudden stress. However, the windows of time that cells spend in vulnerable or tolerant states are often unknown. We quantify the temporal expression of a suite of stress-response reporters, while simultaneously monitoring growth. We observe pulsatile expression across genes with a range of stress-response functions, finding that single-cell growth rates are often anticorrelated with reporter levels. These dynamic phenotypic differences have a concrete link to function, in which individual cells undergoing a pulse of elevated expression and slow growth are predisposed to survive antibiotic exposure.

Cell-to-cell heterogeneity in gene expression and growth can have critical functional consequences, such as determining whether individual bacteria survive or die following stress. Although phenotypic variability is well documented, the dynamics that underlie it are often unknown. This information is important because dramatically different outcomes can arise from gradual versus rapid changes in expression and growth. Using single-cell time-lapse microscopy, we measured the temporal expression of a suite of stress-response reporters in Escherichia coli, while simultaneously monitoring growth rate. In conditions without stress, we found several examples of pulsatile expression. Single-cell growth rates were often anticorrelated with reporter levels, with changes in growth preceding changes in expression. These dynamics have functional consequences, which we demonstrate by measuring survival after challenging cells with the antibiotic ciprofloxacin. Our results suggest that fluctuations in both gene expression and growth dynamics in stress-response networks have direct consequences on survival.

The physiology and genetics of bacterial responses to antibiotic combinations

Several promising strategies based on combining or cycling different antibiotics have been proposed to increase efficacy and counteract resistance evolution, but we still lack a deep understanding of the physiological responses and genetic mechanisms that underlie antibiotic interactions and the clinical applicability of these strategies. In antibiotic-exposed bacteria, the combined effects of physiological stress responses and emerging resistance mutations (occurring at different time scales) generate complex and often unpredictable dynamics. In this Review, we present our current understanding of bacterial cell physiology and genetics of responses to antibiotics. We emphasize recently discovered mechanisms of synergistic and antagonistic drug interactions, hysteresis in temporal interactions between antibiotics that arise from microbial physiology and interactions between antibiotics and resistance mutations that can cause collateral sensitivity or cross-resistance. We discuss possible connections between the different phenomena and indicate relevant research directions. A better and more unified understanding of drug and genetic interactions is likely to advance antibiotic therapy.

Chemical biology-whole genome engineering datasets predict new antibacterial combinations

Trimethoprim and sulfamethoxazole are used commonly together as cotrimoxazole for the treatment of urinary tract and other infections. The evolution of resistance to these and other antibacterials threatens therapeutic options for clinicians. We generated and analysed a chemical-biology-whole-genome data set to predict new targets for antibacterial combinations with trimethoprim and sulfamethoxazole. For this we used a large transposon mutant library in Escherichia coli BW25113 where an outward-transcribing inducible promoter was engineered into one end of the transposon. This approach allows regulated expression of adjacent genes in addition to gene inactivation at transposon insertion sites, a methodology that has been called TraDIS-Xpress. These chemical genomic data sets identified mechanisms for both reduced and increased susceptibility to trimethoprim and sulfamethoxazole. The data identified that over-expression of FolA reduced trimethoprim susceptibility, a known mechanism for reduced susceptibility. In addition, transposon insertions into the genes tdk, deoR, ybbC, hha, ldcA, wbbK and waaS increased susceptibility to trimethoprim and likewise for rsmH, fadR, ddlB, nlpI and prc with sulfamethoxazole, while insertions in ispD, uspC, minC, minD, yebK, truD and umpG increased susceptibility to both these antibiotics. Two of these genes’ products, Tdk and IspD, are inhibited by AZT and fosmidomycin respectively, antibiotics that are known to synergise with trimethoprim. Thus, the data identified two known targets and several new target candidates for the development of co-drugs that synergise with trimethoprim, sulfamethoxazole or cotrimoxazole. We demonstrate that the TraDIS-Xpress technology can be used to generate information-rich chemical-genomic data sets that can be used for antibacterial development.

Gene Amplification Uncovers Large Previously Unrecognized Cryptic Antibiotic Resistance Potential in E. coli

The activation of unrecognized antibiotic resistance genes in the bacterial cell can give rise to antibiotic resistance without the need for major mutations or horizontal gene transfer. We hypothesize that bacteria harbor an extensive array of diverse cryptic genes that can be activated in response to antibiotics via adaptive resistance. To test this hypothesis, we developed a plasmid assay to randomly manipulate gene copy numbers in Escherichia coli cells and identify genes that conferred resistance when amplified. We then tested for cryptic resistance to 18 antibiotics and identified genes conferring resistance. E. coli could become resistant to 50% of the antibiotics tested, including chloramphenicol, d-cycloserine, polymyxin B, and 6 beta-lactam antibiotics, following this manipulation. Known antibiotic resistance genes comprised 13% of the total identified genes, where 87% were unclassified (cryptic) antibiotic resistance genes. These unclassified genes encoded cell membrane proteins, stress response/DNA repair proteins, transporters, and miscellaneous or hypothetical proteins. Stress response/DNA repair genes have a broad antibiotic resistance potential, as this gene class, in aggregate, conferred cryptic resistance to nearly all resistance-positive antibiotics. We found that antibiotics that are hydrophilic, those that are amphipathic, and those that inhibit the cytoplasmic membrane or cell wall biosynthesis were more likely to induce cryptic resistance in E. coli. This study reveals a diversity of cryptic genes that confer an antibiotic resistance phenotype when present in high copy number. Thus, our assay can identify potential novel resistance genes while also describing which antibiotics are prone to induce cryptic antibiotic resistance in E. coli. IMPORTANCE Predicting where new antibiotic resistance genes will rise is a challenge and is especially important when new antibiotics are developed. Adaptive resistance allows sensitive bacterial cells to become transiently resistant to antibiotics. This provides an opportune time for cells to develop more efficient resistance mechanisms, such as tolerance and permanent resistance to higher antibiotic concentrations. The biochemical diversity harbored within bacterial genomes may lead to the presence of genes that could confer resistance when timely activated. Therefore, it is crucial to understand adaptive resistance to identify potential resistance genes and prolong antibiotics. Here, we investigate cryptic resistance, an adaptive resistance mechanism, and identify unknown (cryptic) antibiotic resistance genes that confer resistance when amplified in a laboratory strain of E. coli. We also pinpoint antibiotic characteristics that are likely to induce cryptic resistance. This study may help detect novel antibiotic resistance genes and provide the foundation to help develop more effective antibiotics.

Union is strength: target-based and whole-cell high throughput screens in antibacterial discovery

Antimicrobial resistance is one of the greatest global health challenges today. For over three decades antibacterial discovery research and development has been focused on cell-based and target-based high throughput assays. Target-based screens use diagnostic enzymatic reactions to look for molecules that can bind directly and inhibit the target. Target-based screens are only applied to proteins that can be successfully expressed, purified and the activity of which can be effectively measured using a biochemical assay. Often times the molecules found in these in vitro screens are not active in cells due to poor permeability or efflux. On the other hand, cell-based screens use whole cells and look for growth inhibition. These screens give higher number of hits than target-based assays and can simultaneously test many targets of one process or pathway in their physiological context. Both strategies have pros and cons when used separately. In the past decade and a half our increasing knowledge of bacterial physiology has led to the development of innovative and sophisticated technologies to perform high throughput screening combining these two strategies and thus minimizing their disadvantages. In this review we discuss recent examples of high throughput approaches that used both target-based and whole-cell screening to find new antibacterials, the new insights they have provided and how this knowledge can be applied to other in vivo validated targets to develop new antimicrobials.

Abd El-Hack M. Using essential oils to overcome bacterial biofilm formation and their antimicrobial resistance

The increase of resistant bacteria puts a huge pressure on the antimicrobials in current use. Antimicrobial resistance (AMR) results from antibiotic misuse and abuse over many years and is a global financial burden. New polices must be developed for the use of antimicrobials and to continue research efforts to mitigate AMR. It is essential to target the most harmful bacteria and concentrate on their mechanisms of resistance to develop successful antimicrobials. Essential oils (EOs) are occur naturally in plants and have long been used as antimicrobials, but most have not been researched. This review explores EOs as alternative antimicrobials, investigating their ability to decrease or inhibit biofilm formation, and assess their ability to contribute to AMR control. Low concentrations of EOs can inhibit Gram-positive and Gram-negative pathogenic bacteria. Some EOs have demonstrated strong anti-biofilm activities. If EOs are successful against biofilm formation, particularly in bacteria developing AMR, they could be incorporated into new antimicrobials. Therefore, there is a need to investigate these EOs' potential, particularly for surface disinfection, and against bacteria from food, clinical and non-clinical environments.

Entamoeba histolytica Adaption to Auranofin: A Phenotypic and Multi-Omics Characterization

Auranofin (AF), an antirheumatic agent, targets mammalian thioredoxin reductase (TrxR), an important enzyme controlling redox homeostasis. AF is also highly effective against a diversity of pathogenic bacteria and protozoan parasites. Here, we report on the resistance of the parasite Entamoeba histolytica to 2 µM of AF that was acquired by gradual exposure of the parasite to an increasing amount of the drug. AF-adapted E. histolytica trophozoites (AFAT) have impaired growth and cytopathic activity, and are more sensitive to oxidative stress (OS), nitrosative stress (NS), and metronidazole (MNZ) than wild type (WT) trophozoites. Integrated transcriptomics and redoxomics analyses showed that many upregulated genes in AFAT, including genes encoding for dehydrogenase and cytoskeletal proteins, have their product oxidized in wild type trophozoites exposed to AF (acute AF trophozoites) but not in AFAT. We also showed that the level of reactive oxygen species (ROS) and oxidized proteins (OXs) in AFAT is lower than that in acute AF trophozoites. Overexpression of E. histolytica TrxR (EhTrxR) did not protect the parasite against AF, which suggests that EhTrxR is not central to the mechanism of adaptation to AF.

MgrB Inactivation Confers Trimethoprim Resistance in Escherichia coli

After several decades of use, trimethoprim (TMP) remains one of the key access antimicrobial drugs listed by the World Health Organization. To circumvent the problem of trimethoprim resistance worldwide, a better understanding of drug-resistance mechanisms is required. In this study, we screened the single-gene knockout library of Escherichia coli, and identified mgrB and other several genes involved in trimethoprim resistance. Subsequent comparative transcriptional analysis between ΔmgrB and the wild-type strain showed that expression levels of phoP, phoQ, and folA were significantly upregulated in ΔmgrB. Further deleting phoP or phoQ could partially restore trimethoprim sensitivity to ΔmgrB, and co-overexpression of phoP/Q caused TMP resistance, suggesting the involvement of PhoP/Q in trimethoprim resistance. Correspondingly, MgrB and PhoP were shown to be able to modulated folA expression in vivo. After that, efforts were made to test if PhoP could directly modulate the expression of folA. Though phosphorylated PhoP could bind to the promotor region of folA in vitro, the former only provided a weak protection on the latter as shown by the DNA footprinting assay. In addition, deleting the deduced PhoP box in ΔmgrB could only slightly reverse the TMP resistance phenotype, suggesting that it is less likely for PhoP to directly modulate the transcription of folA. Taken together, our data suggested that, in E. coli, MgrB affects susceptibility to trimethoprim by modulating the expression of folA with the involvement of PhoP/Q. This work broadens our understanding of the regulation of folate metabolism and the mechanisms of TMP resistance in bacteria.

Inhibition of Escherichia coli Lipoprotein Diacylglyceryl Transferase Is Insensitive to Resistance Caused by Deletion of Braun's Lipoprotein

Lipoprotein diacylglyceryl transferase (Lgt) catalyzes the first step in the biogenesis of Gram-negative bacterial lipoproteins which play crucial roles in bacterial growth and pathogenesis. We demonstrate that Lgt depletion in a clinical uropathogenic Escherichia coli strain leads to permeabilization of the outer membrane and increased sensitivity to serum killing and antibiotics. Importantly, we identify G2824 as the first-described Lgt inhibitor that potently inhibits Lgt biochemical activity in vitro and is bactericidal against wild-type Acinetobacter baumannii and E. coli strains. While deletion of a gene encoding a major outer membrane lipoprotein, lpp, leads to rescue of bacterial growth after genetic depletion or pharmacologic inhibition of the downstream type II signal peptidase, LspA, no such rescue of growth is detected after Lgt depletion or treatment with G2824. Inhibition of Lgt does not lead to significant accumulation of peptidoglycan-linked Lpp in the inner membrane. Our data validate Lgt as a novel antibacterial target and suggest that, unlike downstream steps in lipoprotein biosynthesis and transport, inhibition of Lgt may not be sensitive to one of the most common resistance mechanisms that invalidate inhibitors of bacterial lipoprotein biosynthesis and transport.

IMPORTANCE As the emerging threat of multidrug-resistant (MDR) bacteria continues to increase, no new classes of antibiotics have been discovered in the last 50 years. While previous attempts to inhibit the lipoprotein biosynthetic (LspA) or transport (LolCDE) pathways have been made, most efforts have been hindered by the emergence of a common mechanism leading to resistance, namely, the deletion of the gene encoding a major Gram-negative outer membrane lipoprotein lpp. Our unexpected finding that inhibition of Lgt is not susceptible to lpp deletion-mediated resistance uncovers the complexity of bacterial lipoprotein biogenesis and the corresponding enzymes involved in this essential outer membrane biogenesis pathway and potentially points to new antibacterial targets in this pathway.

Single-molecule nanopore sequencing reveals extreme target copy number heterogeneity in arylomycin-resistant mutants

Genetic heterogeneity is a significant driver of antibiotic resistance in bacteria. Understanding copy number (CN) heterogeneity is important because minority subclones with increased CN can drive resistance during antibiotic exposure, but revert and escape detection during clinical susceptibility testing. Despite its clinical relevance, CN variation has eluded quantification at single-molecule resolution. Here, we report nanopore sequencing of arylomycin-resistant mutants carrying tandem repeats ranging in size from 4.8 to 50.0 kb and encompassing the arylomycin target gene lepB. Reads spanning individual repeat arrays show vast differences in CN, underscoring the importance of amplifications in driving the emergence of genetic heterogeneity. This is a direct observation of cell-to-cell CN differences in an antibiotic-resistant bacterial population.

Tandem gene amplification is a frequent and dynamic source of antibiotic resistance in bacteria. Ongoing expansions and contractions of repeat arrays during population growth are expected to manifest as cell-to-cell differences in copy number (CN). As a result, a clonal bacterial culture could comprise subpopulations of cells with different levels of antibiotic sensitivity that result from variable gene dosage. Despite the high potential for misclassification of heterogenous cell populations as either antibiotic-susceptible or fully resistant in clinical settings, and the concomitant risk of inappropriate treatment, CN distribution among cells has defied analysis. Here, we use the MinION single-molecule nanopore sequencer to uncover CN heterogeneity in clonal populations of Escherichia coli and Acinetobacter baumannii grown from single cells isolated while selecting for resistance to an optimized arylomycin, a member of a recently discovered class of Gram-negative antibiotic. We found that gene amplification of the arylomycin target, bacterial type I signal peptidase LepB, is a mechanism of unstable arylomycin resistance and demonstrate in E. coli that amplification instability is independent of RecA. This instability drives the emergence of a nonuniform distribution of lepB CN among cells with a range of 1 to at least 50 copies of lepB identified in a single clonal population. In sum, this remarkable heterogeneity, and the evolutionary plasticity it fuels, illustrates how gene amplification can enable bacterial populations to respond rapidly to novel antibiotics. This study establishes a rationale for further nanopore-sequencing studies of heterogeneous cell populations to uncover CN variability at single-molecule resolution.

High-throughput laboratory evolution reveals evolutionary constraints in Escherichia coli

Understanding the constraints that shape the evolution of antibiotic resistance is critical for predicting and controlling drug resistance. Despite its importance, however, a systematic investigation of evolutionary constraints is lacking. Here, we perform a high-throughput laboratory evolution of Escherichia coli under the addition of 95 antibacterial chemicals and quantified the transcriptome, resistance, and genomic profiles for the evolved strains. Utilizing machine learning techniques, we analyze the phenotype-genotype data and identified low dimensional phenotypic states among the evolved strains. Further analysis reveals the underlying biological processes responsible for these distinct states, leading to the identification of trade-off relationships associated with drug resistance. We also report a decelerated evolution of β-lactam resistance, a phenomenon experienced by certain strains under various stresses resulting in higher acquired resistance to β-lactams compared to strains directly selected by β-lactams. These findings bridge the genotypic, gene expression, and drug resistance gap, while contributing to a better understanding of evolutionary constraints for antibiotic resistance.

Exploration into the origins and mobilization of di-hydrofolate reductase genes and the emergence of clinical resistance to trimethoprim

Trimethoprim is a synthetic antibacterial agent that targets folate biosynthesis by competitively binding to the di-hydrofolate reductase enzyme (DHFR). Trimethoprim is often administered synergistically with sulfonamide, another chemotherapeutic agent targeting the di-hydropteroate synthase (DHPS) enzyme in the same pathway. Clinical resistance to both drugs is widespread and mediated by enzyme variants capable of performing their biological function without binding to these drugs. These mutant enzymes were assumed to have arisen after the discovery of these synthetic drugs, but recent work has shown that genes conferring resistance to sulfonamide were present in the bacterial pangenome millions of years ago. Here, we apply phylogenetics and comparative genomics methods to study the largest family of mobile trimethoprim-resistance genes (dfrA). We show that most of the dfrA genes identified to date map to two large clades that likely arose from independent mobilization events. In contrast to sulfonamide resistance (sul) genes, we find evidence of recurrent mobilization in dfrA genes. Phylogenetic evidence allows us to identify novel dfrA genes in the emerging pathogen Acinetobacter baumannii, and we confirm their resistance phenotype in vitro. We also identify a cluster of dfrA homologues in cryptic plasmid and phage genomes, but we show that these enzymes do not confer resistance to trimethoprim. Our methods also allow us to pinpoint the chromosomal origin of previously reported dfrA genes, and we show that many of these ancient chromosomal genes also confer resistance to trimethoprim. Our work reveals that trimethoprim resistance predated the clinical use of this chemotherapeutic agent, but that novel mutations have likely also arisen and become mobilized following its widespread use within and outside the clinic. Hence, this work confirms that resistance to novel drugs may already be present in the bacterial pangenome, and stresses the importance of rapid mobilization as a fundamental element in the emergence and global spread of resistance determinants.

Potentiating aminoglycoside antibiotics to reduce their toxic side effects

The lack of new antibiotics necessitates the improvement of existing ones, many of which are limited by toxic side effects. Aminoglycosides, antibiotics with excellent activity and low bacterial resistance, are hampered by dose-dependent toxic effects in patients (nephrotoxicity, ototoxicity). High antibiotic concentrations are often required to treat dormant, non-dividing bacteria, though previous studies show that aminoglycosides can be activated against such bacteria by specific metabolites. Here, we employed this mechanism to greatly boost the activity of low concentrations of aminoglycosides against prevalent Gram-negative pathogens (Escherichia coli, Salmonella enterica, and Klebsiella pneumoniae), suggesting that less toxic drug concentrations might be used effectively in patients. We go on to show that this effect improved treatment of biofilms, did not increase aminoglycoside resistance, and was due to the generation of proton-motive force (PMF). By single-cell microscopy, we demonstrate that stationary-phase cells, while non-dividing, actively maintain a growth-arrested state that is not reversed by metabolite addition. Surprisingly, within starved populations, we observed rare cells (3%) that divided without added nutrients. Additionally, we discovered that mannitol could directly protect human kidney cells from aminoglycoside cytotoxicity, independent of the metabolite's effect on bacteria. This work forwards a mechanism-based strategy to improve existing antibiotics by mitigating their toxic side effects.

Organoarsenicals inhibit bacterial peptidoglycan biosynthesis by targeting the essential enzyme MurA

Trivalent organoarsenicals such as methylarsenite (MAs(III)) are considerably more toxic than inorganic arsenate (As(V)) or arsenite (As(III)). In microbial communities MAs(III) exhibits significant antimicrobial activity. Although MAs(III) and other organoarsenicals contribute to the global arsenic biogeocycle, how they exert antibiotic-like properties is largely unknown. To identify possible targets of MAs(III), a genomic library of the gram-negative bacterium, Shewanella putrefaciens 200, was expressed in Escherichia coli with selection for MAs(III) resistance. One clone contained the S. putrefaciens murA gene (SpmurA), which catalyzes the first committed step in peptidoglycan biosynthesis. Overexpression of SpmurA conferred MAs(III) resistance to E. coli. Purified SpMurA was inhibited by MAs(III), phenylarsenite (PhAs(III)) or the phosphonate antibiotic fosfomycin but not by inorganic As(III). Fosfomycin inhibits MurA by binding to a conserved residue that corresponds to Cys117 in SpMurA. A C117D mutant was resistant to fosfomycin but remained sensitive to MAs(III), indicating that the two compounds have different mechanisms of action. New inhibitors of peptidoglycan biosynthesis are highly sought after as antimicrobial drugs, and organoarsenicals represent a new area for the development of novel compounds for combating the threat of antibiotic resistance.

Drug-target binding quantitatively predicts optimal antibiotic dose levels in quinolones

Antibiotic resistance is rising and we urgently need to gain a better quantitative understanding of how antibiotics act, which in turn would also speed up the development of new antibiotics. Here, we describe a computational model (COMBAT-COmputational Model of Bacterial Antibiotic Target-binding) that can quantitatively predict antibiotic dose-response relationships. Our goal is dual: We address a fundamental biological question and investigate how drug-target binding shapes antibiotic action. We also create a tool that can predict antibiotic efficacy a priori. COMBAT requires measurable biochemical parameters of drug-target interaction and can be directly fitted to time-kill curves. As a proof-of-concept, we first investigate the utility of COMBAT with antibiotics belonging to the widely used quinolone class. COMBAT can predict antibiotic efficacy in clinical isolates for quinolones from drug affinity (R2>0.9). To further challenge our approach, we also do the reverse: estimate the magnitude of changes in drug-target binding based on antibiotic dose-response curves. We overexpress target molecules to infer changes in antibiotic-target binding from changes in antimicrobial efficacy of ciprofloxacin with 92-94% accuracy. To test the generality of our approach, we use the beta-lactam ampicillin to predict target molecule occupancy at MIC from antimicrobial action with 90% accuracy. Finally, we apply COMBAT to predict antibiotic concentrations that can select for resistance due to novel resistance mutations. Using ciprofloxacin and ampicillin as well defined test cases, our work demonstrates that drug-target binding is a major predictor of bacterial responses to antibiotics. This is surprising because antibiotic action involves many additional effects downstream of drug-target binding. In addition, COMBAT provides a framework to inform optimal antibiotic dose levels that maximize efficacy and minimize the rise of resistant mutants.

Mechanisms of drug interactions between translation-inhibiting antibiotics

Antibiotics that interfere with translation, when combined, interact in diverse and difficult-to-predict ways. Here, we explain these interactions by "translation bottlenecks": points in the translation cycle where antibiotics block ribosomal progression. To elucidate the underlying mechanisms of drug interactions between translation inhibitors, we generate translation bottlenecks genetically using inducible control of translation factors that regulate well-defined translation cycle steps. These perturbations accurately mimic antibiotic action and drug interactions, supporting that the interplay of different translation bottlenecks causes these interactions. We further show that growth laws, combined with drug uptake and binding kinetics, enable the direct prediction of a large fraction of observed interactions, yet fail to predict suppression. However, varying two translation bottlenecks simultaneously supports that dense traffic of ribosomes and competition for translation factors account for the previously unexplained suppression. These results highlight the importance of "continuous epistasis" in bacterial physiology.

Genetic dominance governs the evolution and spread of mobile genetic elements in bacteria

Mobile genetic elements (MGEs), such as plasmids, promote bacterial evolution through horizontal gene transfer (HGT). However, the rules governing the repertoire of traits encoded on MGEs remain unclear. In this study, we uncovered the central role of genetic dominance shaping genetic cargo in MGEs, using antibiotic resistance as a model system. MGEs are typically present in more than one copy per host bacterium, and as a consequence, genetic dominance favors the fixation of dominant mutations over recessive ones. In addition, genetic dominance also determines the phenotypic effects of horizontally acquired MGE-encoded genes, silencing recessive alleles if the recipient bacterium already carries a wild-type copy of the gene. The combination of these two effects governs the catalog of genes encoded on MGEs. Our results help to understand how MGEs evolve and spread, uncovering the neglected influence of genetic dominance on bacterial evolution. Moreover, our findings offer a framework to forecast the spread and evolvability of MGE-encoded genes, which encode traits of key human interest, such as virulence or antibiotic resistance.

The Antitumor Agent Ansamitocin P-3 Binds to Cell Division Protein FtsZ in Actinosynnema pretiosum

Ansamitocin P-3 (AP-3) is an important antitumor agent. The antitumor activity of AP-3 is a result of its affinity towards β-tubulin in eukaryotic cells. In this study, in order to improve AP-3 production, the reason for severe growth inhibition of the AP-3 producing strain Actinosynnema pretiosum WXR-24 under high concentrations of exogenous AP-3 was investigated. The cell division protein FtsZ, which is the analogue of β-tubulin in bacteria, was discovered to be the AP-3 target through structural comparison followed by a SPR biosensor assay. AP-3 was trapped into a less hydrophilic groove near the GTPase pocket on FtsZ by hydrogen bounding and hydrophobic interactions, as revealed by docking analysis. After overexpression of the APASM_5716 gene coding for FtsZ in WXR-30, the resistance to AP-3 was significantly improved. Moreover, AP-3 yield was increased from 250.66 mg/L to 327.37 mg/L. After increasing the concentration of supplemented yeast extract, the final yield of AP-3 reached 371.16 mg/L. In summary, we demonstrate that the cell division protein FtsZ is newly identified as the bacterial target of AP-3, and improving resistance is an effective strategy to enhance AP-3 production.

Molecular and cellular dissection of the oxysterol-binding protein cycle through a fluorescent inhibitor

ORPphilins are bioactive natural products that strongly and selectively inhibit the growth of some cancer cell lines and are proposed to target intracellular lipid-transfer proteins of the oxysterol-binding protein (OSBP) family. These conserved proteins exchange key lipids, such as cholesterol and phosphatidylinositol 4-phosphate (PI(4)P), between organelle membranes. Among ORPphilins, molecules of the schweinfurthin family interfere with intracellular lipid distribution and metabolism, but their functioning at the molecular level is poorly understood. We report here that cell line sensitivity to schweinfurthin G (SWG) is inversely proportional to cellular OSBP levels. By taking advantage of the intrinsic fluorescence of SWG, we followed its fate in cell cultures and show that its incorporation at the trans-Golgi network depends on cellular abundance of OSBP. Using in vitro membrane reconstitution systems and cellular imaging approaches, we also report that SWG inhibits specifically the lipid transfer activity of OSBP. As a consequence, post-Golgi trafficking, membrane cholesterol levels, and PI(4)P turnover were affected. Finally, using intermolecular FRET analysis, we demonstrate that SWG directly binds to the lipid-binding cavity of OSBP. Collectively these results describe SWG as a specific and intrinsically fluorescent pharmacological tool for dissecting OSBP properties at the cellular and molecular levels. Our findings indicate that SWG binds OSBP with nanomolar affinity, that this binding is sensitive to the membrane environment, and that SWG inhibits the OSBP-catalyzed lipid exchange cycle.

TRPV1 Tunes Optic Nerve Axon Excitability in Glaucoma

The transient receptor potential vanilloid member 1 (TRPV1) in the central nervous system may contribute to homeostatic plasticity by regulating intracellular Ca²⁺, which becomes unbalanced in age-related neurodegenerative diseases, including Alzheimer’s and Huntington’s. Glaucomatous optic neuropathy – the world’s leading cause of irreversible blindness – involves progressive degeneration of retinal ganglion cell (RGC) axons in the optic nerve through sensitivity to stress related to intraocular pressure (IOP). In models of glaucoma, genetic deletion of TRPV1 (Trpv1^–/–) accelerates RGC axonopathy in the optic projection, whereas TRPV1 activation modulates RGC membrane polarization. In continuation of these studies, here, we found that Trpv1^–/– increases the compound action potential (CAP) of optic nerves subjected to short-term elevations in IOP. This IOP-induced increase in CAP was not directly due to TRPV1 channels in the optic nerve, because the TRPV1-selective antagonist iodoresiniferatoxin had no effect on the CAP for wild-type optic nerve. Rather, the enhanced CAP in Trpv1^–/– optic nerve was associated with increased expression of the voltage-gated sodium channel subunit 1.6 (NaV1.6) in longer nodes of Ranvier within RGC axons, rendering Trpv1^–/– optic nerve relatively insensitive to NaV1.6 antagonism via 4,9-anhydrotetrodotoxin. These results indicate that with short-term elevations in IOP, Trpv1^–/– increases axon excitability through greater NaV1.6 localization within longer nodes. In neurodegenerative disease, native TRPV1 may tune NaV expression in neurons under stress to match excitability to available metabolic resources.

Discovery and Characterization of the Antimetabolite Action of Thioacetamide-Linked 1,2,3-Triazoles as Disruptors of Cysteine Biosynthesis in Gram-Negative Bacteria

Increasing rates of drug-resistant Gram-negative (GN) infections, combined with a lack of new GN-effective antibiotic classes, are driving the need for the discovery of new agents. Bacterial metabolism represents an underutilized mechanism of action in current antimicrobial therapies. Therefore, we sought to identify novel antimetabolites that disrupt key metabolic pathways and explore the specific impacts of these agents on bacterial metabolism. This study describes the successful application of this approach to discover a new series of chemical probes, N-(phenyl)thioacetamide-linked 1,2,3-triazoles (TAT), that target cysteine synthase A (CysK), an enzyme unique to bacteria that is positioned at a key juncture between several fundamental pathways. The TAT class was identified using a high-throughput screen against Escherichia coli designed to identify modulators of pathways related to folate biosynthesis. TAT analog synthesis demonstrated a clear structure-activity relationship, and activity was confirmed against GN antifolate-resistant clinical isolates. Spontaneous TAT resistance mutations were tracked to CysK, and mode of action studies led to the identification of a false product formation mechanism between the CysK substrate O-acetyl-l-serine and the TATs. Global transcriptional responses to TAT treatment revealed that these antimetabolites impose substantial disruption of key metabolic networks beyond cysteine biosynthesis. This study highlights the potential of antimetabolite drug discovery as a promising approach to the discovery of novel GN antibiotics and the pharmacological promise of TAT CysK probes.

The intriguing biology and chemistry of fosfomycin: the only marketed phosphonate antibiotic

Recently infectious diseases caused by the increased emergence and rapid spread of drug-resistant bacterial isolates have been one of the main threats to global public health because of a marked surge in both morbidity and mortality. The only phosphonate antibiotic in the clinic, fosfomycin, is a small broad-spectrum molecule that effectively inhibits the initial step in peptidoglycan biosynthesis by blocking the enzyme, MurA in both Gram-positive and Gram-negative bacteria. As fosfomycin has a novel mechanism of action, low toxicity, a broad spectrum of antibacterial activity, excellent pharmacodynamic/pharmacokinetic properties, and good bioavailability, it has been approved for clinical use in the treatment of urinary tract bacterial infections in many countries for several decades. Furthermore, its potential use for difficult-to-treat bacterial infections has become promising, and fosfomycin has become an ideal candidate for the effective treatment of bacterial infections caused by multidrug-resistant isolates, especially in combination with other therapeutic drugs. Here we aim to present an overview of the biology and chemistry of fosfomycin including isolation and characterization, pharmacology, biosynthesis and chemical synthesis since its discovery in order to not only help scientists reassess the role of this exciting drug in fighting antibiotic resistance but also build the stage for discovering more novel phosphonate antibiotics in the future.

ProTargetMiner as a proteome signature library of anticancer molecules for functional discovery

Deconvolution of targets and action mechanisms of anticancer compounds is fundamental in drug development. Here, we report on ProTargetMiner as a publicly available expandable proteome signature library of anticancer molecules in cancer cell lines. Based on 287 A549 adenocarcinoma proteomes affected by 56 compounds, the main dataset contains 7,328 proteins and 1,307,859 refined protein-drug pairs. These proteomic signatures cluster by compound targets and action mechanisms. The targets and mechanistic proteins are deconvoluted by partial least square modeling, provided through the website http://protargetminer.genexplain.com. For 9 molecules representing the most diverse mechanisms and the common cancer cell lines MCF-7, RKO and A549, deep proteome datasets are obtained. Combining data from the three cell lines highlights common drug targets and cell-specific differences. The database can be easily extended and merged with new compound signatures. ProTargetMiner serves as a chemical proteomics resource for the cancer research community, and can become a valuable tool in drug discovery.

Anticancer drugs often have widespread effects on the cellular proteome. Here, the authors generate a proteome signature library of drug-treated cancer cell lines and develop a software tool to deconvolute drug targets and gain insights into their mechanisms of action.