Inhibition of RNA Polymerase by Rifampicin and Rifamycin-Like Molecules

Recent advances in inhibitor development and metabolic targeting in tuberculosis therapy

Despite being a preventable and treatable disease, tuberculosis (TB) remained the second leading infectious cause of death globally in 2022, surpassed only by COVID-19. The death rate from TB is influenced by numerous factors that include antibiotic drug resistance, noncompliance with chemotherapy by patients, concurrent infection with the human immunodeficiency virus, delayed diagnosis, varying effectiveness of the Bacille-Calmette-Guerin vaccine, and other factors. Even with the recent advances in our knowledge of Mycobacterium tuberculosis and the accessibility of advanced genomic tools such as proteomics and microarrays, alongside modern methodologies, the pursuit of next-generation inhibitors targeting distinct or multiple molecular pathways remains essential to combat the increasing antimicrobial resistance. Hence, there is an urgent need to identify and develop new drug targets against TB that have unique mechanisms. Novel therapeutic targets might encompass gene products associated with various aspects of mycobacterial biology, such as transcription, metabolism, cell wall formation, persistence, and pathogenesis. This review focuses on the present state of our knowledge and comprehension regarding various inhibitors targeting key metabolic pathways of M. tuberculosis. The discussion encompasses small molecule, synthetic, peptide, natural product and microbial inhibitors and navigates through promising candidates in different phases of clinical development. Additionally, we explore the crucial enzymes and targets involved in metabolic pathways, highlighting their inhibitors. The metabolic pathways explored include nucleotide synthesis, mycolic acid synthesis, peptidoglycan biosynthesis, and energy metabolism. Furthermore, advancements in genetic approaches like CRISPRi and conditional expression systems are discussed, focusing on their role in elucidating gene essentiality and vulnerability in Mycobacteria.

Targeting Bacterial RNA Polymerase: Harnessing Simulations and Machine Learning to Design Inhibitors for Drug-Resistant Pathogens

The increase in antimicrobial resistance presents a major challenge in treating bacterial infections, underscoring the need for innovative drug discovery approaches and novel inhibitors. Bacterial RNA polymerase (RNAP) has emerged as a crucial target for antibiotic development due to its essential role in transcription. RNAP is a molecular motor, and its function relies heavily on the dynamic shifts between multiple conformational states. While biochemical and structural experimental methods offer crucial insights into static RNAP-drug interactions, they fall short in capturing the dynamics at a molecular level. By integrating experimental data with advanced computational techniques like Markov State Models (MSMs), Generalized Master Equation (GME) Models and other machine-learning models constructed from molecular dynamics (MD) simulations, researchers can elucidate novel cryptic pockets that open transiently for antibiotic compounds and gain a more nuanced and comprehensive understanding of RNAP-drug interactions. This integrated approach not only deepens our fundamental knowledge but also enables more targeted and efficient antibiotic design strategies. In this Perspective, we highlight how this synergy between experimental and computational methods has the potential to open new pathways for innovative drug design and combination therapies that may help turn the tide in the ongoing battle against antibiotic-resistant bacteria.

Advancements and challenges in tuberculosis drug discovery: A comprehensive overview

Tuberculosis continues to pose a health challenge causing the loss of millions of lives despite the existence of multiple drugs, for treatment. The emergence of drug-resistant strains has made the situation more complex making it increasingly difficult to fight against this disease. This review outlines the challenges associated with TB drug discovery, the nature of Mycobacterium tuberculosis shedding light on the mechanisms that lead to treatment failure and antibiotic resistance. We explore promising drug targets, encompassing inhibition of mycolyarabinogalactan peptidoglycan (MAGP) assembly, mycolic acid biosynthesis, DNA replication, transcription, translation, protein synthesis, and bioenergetics/metabolism pathways. A comprehensive overview of the global pipeline of anti-tuberculosis drugs at various stages of clinical trials, the diverse strategies being pursued to tackle this complex disease. By gaining an understanding of the mechanisms that contribute to resistance development and identifying suitable targets, we can pave the way for more effective treatments and contribute to global efforts to combat drug-resistant tuberculosis.

Decoding the role of mycobacterial lipid remodelling and membrane dynamics in antibiotic tolerance

Current treatments for tuberculosis primarily target Mycobacterium tuberculosis (Mtb) infections, often neglecting the emerging issue of latent tuberculosis infection (LTBI) which are characterized by reduced susceptibility to antibiotics. The bacterium undergoes multiple adaptations during dormancy within host granulomas, leading to the development of antibiotic-tolerant strains. The mycobacterial membrane plays a crucial role in drug permeability, and this study aims to characterize membrane lipid deviations during dormancy through extensive lipidomic analysis of bacteria cultivated in distinct media and growth stages. The results revealed that specific lipids localize in different regions of the membrane envelope, allowing the bacterium to adapt to granuloma conditions. These lipid modifications were then correlated with the biophysical properties of the mycomembrane, which may affect interactions with antibiotics. Overall, our findings offer a deeper understanding of the bacterial adaptations during dormancy, highlighting the role of lipids in modulating membrane behaviour and drug permeability, ultimately providing the groundwork for the development of more effective treatments tailored to combat latent infections.

Potentiality of Antibacterial Gels for the Prophylactic Coating of Hernia Repair Prosthetic Materials

Prosthetic mesh infection constitutes one of the major postsurgical complications following abdominal hernia repair. Antibacterial coatings represent a prophylactic strategy to reduce the risk of infection. This study assessed the in vitro response of two antibacterial gels made of 1% carboxymethylcellulose (CMC) functionalized with an antiseptic (chlorhexidine, CHX) or an antibiotic (rifampicin, RIF), developed for the coating of polypropylene (PP) meshes for hernia repair. Fragments of a lightweight PP mesh (1 cm2) presoaked in the unloaded or drug-loaded CMC (0.05% CHX; 0.13 mg/mL RIF) were challenged with 106 CFU/mL Staphylococcus aureus (Sa) and methicillin-resistant S. aureus (MRSA). Agar diffusion tests, sonication, turbidimetry, crystal violet staining, scanning electron microscopy and cell viability assays (fibroblasts, mesothelial cells) were performed to evaluate the response of the gels. Both compounds-especially the RIF-loaded gel-exerted a biocidal effect against gram-positive bacteria, developing wide inhibition halos, precluding adhesion to the mesh surface, and hampering bacterial survival in culture. The antibiotic gel proved innocuous, while lower viability was found in cells exposed to the antiseptic (p < 0.05). Together with their fast, affordable, convenient processing and easy application, the results suggest the potential effectiveness of these drug-loaded CMC gels in providing meshes with an antibacterial coating exhibiting great biocide performance.

A machine-learning based model for automated recommendation of individualized treatment of rifampicin-resistant tuberculosis

BACKGROUND

Rifampicin resistant tuberculosis remains a global health problem with almost half a million new cases annually. In high-income countries patients empirically start a standardized treatment regimen, followed by an individualized regimen guided by drug susceptibility test (DST) results. In most settings, DST information is not available or is limited to isoniazid and fluoroquinolones. Whole genome sequencing could more accurately guide individualized treatment as the full drug resistance profile is obtained with a single test. Whole genome sequencing has not reached its full potential for patient care, in part due to the complexity of translating a resistance profile into the most effective individualized regimen.

METHODS

We developed a treatment recommender clinical decision support system (CDSS) and an accompanying web application for user-friendly recommendation of the optimal individualized treatment regimen to a clinician.

RESULTS

Following expert stakeholder meetings and literature review, nine drug features and 14 treatment regimen features were identified and quantified. Using machine learning, a model was developed to predict the optimal treatment regimen based on a training set of 3895 treatment regimen-expert feedback pairs. The acceptability of the treatment recommender CDSS was assessed as part of a clinical trial and in a routine care setting. Within the clinical trial setting, all patients received the CDSS recommended treatment. In 8 of 20 cases, the initial recommendation was recomputed because of stock out, clinical contra-indication or toxicity. In routine care setting, physicians rejected the treatment recommendation in 7 out of 15 cases because it deviated from the national TB treatment guidelines. A survey indicated that the treatment recommender CDSS is easy to use and useful in clinical practice but requires digital infrastructure support and training.

CONCLUSIONS

Our findings suggest that global implementation of the novel treatment recommender CDSS holds the potential to improve treatment outcomes of patients with RR-TB, especially those with 'difficult-to-treat' forms of RR-TB.

Assessment of body mass-related covariates for rifampicin pharmacokinetics in healthy Caucasian volunteers

PURPOSE

Currently, body weight-based dosing of rifampicin is recommended. But lately, fat-free mass (FFM) was reported to be superior to body weight (BW). The present evaluation aimed to assess the influence of body mass-related covariates on rifampicin's pharmacokinetics (PK) parameters in more detail using non-linear mixed effects modeling (NLMEM).

METHODS

Twenty-four healthy Caucasian volunteers were enrolled in a bioequivalence study, each receiving a test and a reference tablet of 600 mg of rifampicin separated by a wash-out period of at least 9 days. Monolix version 2023R1 was used for NLMEM. Monte Carlo simulations (MCS) were performed to visualize the relationship of body size descriptors to the exposure to rifampicin.

RESULTS

A one-compartment model with nonlinear (Michaelis-Menten) elimination and zero-order absorption kinetics with a lag time best described the data. The covariate model including fat-free mass (FFM) on volume of distribution (V/F) and on maximum elimination rate (Vmax/F) lowered the objective function value (OFV) by 56.4. The second-best covariate model of sex on V/F and Vmax/F and BW on V/F reduced the OFV by 51.2. The decrease in unexplained inter-individual variability on Vmax/F in both covariate models was similar. For a given dose, MCS showed lower exposure to rifampicin with higher FFM and accordingly in males compared to females with the same BW and body height.

CONCLUSION

Our results indicate that beyond BW, body composition as reflected by FFM could also be relevant for optimized dosing of rifampicin. This assumption needs to be studied further in patients treated with rifampicin.

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 reconstructed genome-scale metabolic model of Helicobacter pylori for predicting putative drug targets in clarithromycin and rifampicin resistance conditions

BACKGROUND

Helicobacter pylori is considered a true human pathogen for which rising drug resistance constitutes a drastic concern globally. The present study aimed to reconstruct a genome-scale metabolic model (GSMM) to decipher the metabolic capability of H. pylori strains in response to clarithromycin and rifampicin along with identification of novel drug targets.

MATERIALS AND METHODS

The iIT341 model of H. pylori was updated based on genome annotation data, and biochemical knowledge from literature and databases. Context-specific models were generated by integrating the transcriptomic data of clarithromycin and rifampicin resistance into the model. Flux balance analysis was employed for identifying essential genes in each strain, which were further prioritized upon being nonhomologs to humans, virulence factor analysis, druggability, and broad-spectrum analysis. Additionally, metabolic differences between sensitive and resistant strains were also investigated based on flux variability analysis and pathway enrichment analysis of transcriptomic data.

RESULTS

The reconstructed GSMM was named as HpM485 model. Pathway enrichment and flux variability analyses demonstrated reduced activity in the ribosomal pathway in both clarithromycin- and rifampicin-resistant strains. Also, a significant decrease was detected in the activity of metabolic pathways of clarithromycin-resistant strain. Moreover, 23 and 16 essential genes were exclusively detected in clarithromycin- and rifampicin-resistant strains, respectively. Based on prioritization analysis, cyclopropane fatty acid synthase and phosphoenolpyruvate synthase were identified as putative drug targets in clarithromycin- and rifampicin-resistant strains, respectively.

CONCLUSIONS

We present a robust and reliable metabolic model of H. pylori. This model can predict novel drug targets to combat drug resistance and explore the metabolic capability of H. pylori in various conditions.

Identification of Novel Flavonoids and Ansa-Macrolides with Activities against Leishmania donovani through Natural Product Library Screening

The protozoan parasite Leishmania donovani is the causative agent of visceral leishmaniasis (VL), a potentially fatal disease if left untreated. Given the limitations of current therapies, there is an urgent need for new, safe, and effective drugs. To discover novel antileishmanial compounds from previously unexplored chemical spaces, we conducted a high-throughput screening (HTS) of 2562 natural compounds, assessing their activity against L. donovani promastigotes and intracellular amastigotes. Utilizing the criteria of ≥70% parasite growth inhibition and ≥70% host cell (THP-1) viability, we selected 100 inhibitors for half-maximal inhibitory concentration (IC50) value determination. Twenty-six compounds showed activities in both forms of Leishmania with a selectivity index of over 3. Clustering analysis resulted in four chemical clusters with scaffolds of lycorine (cluster 1), 5-hydroxy-9,10-dihydro-4H,8H-pyrano[2,3-f]chromene-4,8-dione (cluster 2), and semi-synthetic derivatives of ansamycin macrolide (cluster 4). The enantiomer of lycorine, BMD-NP-00820, showed the highest anti-amastigote activity with an IC50 value of 1.74 ± 0.27 μM and a selectivity index (SI) > 29. In cluster 3, the most potent compound had an IC50 value of 2.20 ± 0.29 μM with an SI > 23, whereas in cluster 4, with compounds structurally similar to the tuberculosis drug rifapentine, BMD-NP-02085 had an IC50 value of 1.76 ± 0.28 μM, but the SI value was 7.5. Taken together, the natural products identified from this study are a potential source for the discovery of antileishmanial chemotypes for further development.

Combined in vitro/in silico approaches, molecular dynamics simulations and safety assessment of the multifunctional properties of thymol and carvacrol: A comparative insight

Bioactive compounds derived from medicinal plants have acquired immense attentiveness in drug discovery and development. The present study investigated in vitro and predicted in silico the antibacterial, antifungal, and antiviral properties of thymol and carvacrol, and assessed their safety. The performed microbiological assays against Pseudomonas aeruginosa, Escherichia coli, Salmonella enterica Typhimurium revealed that the minimal inhibitory concentration values ranged from (0.078 to 0.312 mg/mL) and the minimal fungicidal concentration against Candida albicans was 0.625 mg/mL. Molecular docking simulations, stipulated that these compounds could inhibit bacterial replication and transcription functions by targeting DNA and RNA polymerases receptors with docking scores varying between (-5.1 to -6.9 kcal/mol). Studied hydroxylated monoterpenes could hinder C. albicans growth by impeding lanosterol 14α-demethylase enzyme and showed a (ΔG=-6.2 and -6.3 kcal/mol). Computational studies revealed that thymol and carvacrol could target the SARS-Cov-2 spike protein of the Omicron variant RBD domain. Molecular dynamics simulations disclosed that these compounds have a stable dynamic behavior over 100 ns as compared to remdesivir. Chemo-computational toxicity prediction using Protox II webserver indicated that thymol and carvacrol could be safely and effectively used as drug candidates to tackle bacterial, fungal, and viral infections as compared to chemical medication.

High-throughput, fluorescent-aptamer-based measurements of steady-state transcription rates for the Mycobacterium tuberculosis RNA polymerase

The first step in gene expression is the transcription of DNA sequences into RNA. Regulation at the level of transcription leads to changes in steady-state concentrations of RNA transcripts, affecting the flux of downstream functions and ultimately cellular phenotypes. Changes in transcript levels are routinely followed in cellular contexts via genome-wide sequencing techniques. However, in vitro mechanistic studies of transcription have lagged with respect to throughput. Here, we describe the use of a real-time, fluorescent-aptamer-based method to quantitate steady-state transcription rates of the Mycobacterium tuberculosis RNA polymerase. We present clear controls to show that the assay specifically reports on promoter-dependent, full-length RNA transcription rates that are in good agreement with the kinetics determined by gel-resolved, α-32P NTP incorporation experiments. We illustrate how the time-dependent changes in fluorescence can be used to measure regulatory effects of nucleotide concentrations and identity, RNAP and DNA concentrations, transcription factors, and antibiotics. Our data showcase the ability to easily perform hundreds of parallel steady-state measurements across varying conditions with high precision and reproducibility to facilitate the study of the molecular mechanisms of bacterial transcription.

Diversity of virulence and antibiotic resistance genes expressed in Class A biosolids and biosolids-amended soil as revealed by metatranscriptomic analysis

Class A biosolids is a treated sewage sludge, commonly applied to agricultural fields, home lawns/gardens, golf courses, forests, and remediation sites around the world. This practice is of public and agricultural concern due to the possibility that biosolids contain antibiotic-resistant bacteria and fungal pathogens that could persist for extended periods in soil. This possibility was determined by metatranscriptomic analysis of virulence, antibiotic resistance, and plasmid conjugation genes, a Class A biosolids, organically managed soil, and biosolids-amended soil under realistic conditions. Biosolids harbored numerous transcriptionally active pathogens, antibiotic resistance genes, and conjugative genes that annotated mostly to Gram-positive pathogens of animal hosts. Biosolids amendment to soil significantly increased the expression of virulence genes by numerous pathogens and antibiotic-resistant genes that were strongly associated with biosolids. Biosolids amendment also significantly increased the expression of virulence genes by native soil fungal pathogens of plant hosts, which suggests higher risks of crop damage by soil fungal pathogens in biosolids-amended soil. Although results are likely to be different in other soils, biosolids, and microbial growth conditions, they provide a more holistic, accurate view of potential health risks associated with biosolids and biosolids-amended soils than has been achievable with more selective cultivation and PCR-based techniques.

The Mycoplasma hyorhinis genome displays differential chromatin accessibility

Whilst the regulation of chromatin accessibility and its effect on gene expression have been well studied in eukaryotic species, the role of chromatin dynamics and 3D organisation in genome reduced bacteria remains poorly understood [1,2]. In this study we profiled the accessibility of the Mycoplasma hyorhinis genome, these data were collected fortuitously as part of an experiment where ATAC-Seq was conducted on mycoplasma, contaminated mammalian cells. We found a differential and highly reproducible chromatin accessibility landscape, with regions of increased accessibility corresponding to genes important for the bacteria's life cycle and infectivity. Furthermore, accessibility in general correlated with transcriptionally active genes as profiled by RNA-Seq, but peaks of high accessibility were also seen in non-coding and intergenic regions, which could contribute to the topological organisation of the genome. However, changes in transcription induced by starvation or application of the RNA polymerase inhibitor rifampicin did not themselves change the accessibility profile, which confirms that the differential accessibility is inherently a property of the genome, and not a consequence of its function. These results together show that differential chromatin accessibility is a key feature of the regulation of gene expression in bacteria.

Recent Advances in Strategies to Combat Bacterial Drug Resistance: Antimicrobial Materials and Drug Delivery Systems

Bacterial infection is a common clinical disease. Antibiotics have saved countless lives since their discovery and are a powerful weapon in the fight against bacteria. However, with the widespread use of antibiotics, the problem of drug resistance now poses a great threat to human health. In recent years, studies have investigated approaches to combat bacterial resistance. Several antimicrobial materials and drug delivery systems have emerged as promising strategies. Nano-drug delivery systems for antibiotics can reduce the resistance to antibiotics and extend the lifespan of novel antibiotics, and they allow targeting drug delivery compared to conventional antibiotics. This review highlights the mechanistic insights of using different strategies to combat drug-resistant bacteria and summarizes the recent advancements in antimicrobial materials and drug delivery systems for different carriers. Furthermore, the fundamental properties of combating antimicrobial resistance are discussed, and the current challenges and future perspectives in this field are proposed.

High-throughput, fluorescent-aptamer-based measurements of steady-state transcription rates for Mycobacterium tuberculosis RNA polymerase

The first step in gene expression is the transcription of DNA sequences into RNA. Regulation at the level of transcription leads to changes in steady-state concentrations of RNA transcripts, affecting the flux of downstream functions and ultimately cellular phenotypes. Changes in transcript levels are routinely followed in cellular contexts via genome-wide sequencing techniques. However, in vitro mechanistic studies of transcription have lagged with respect to throughput. Here, we describe the use of a real-time, fluorescent-aptamer-based method to quantitate steady-state transcription rates of the Mycobacterium tuberculosis RNA polymerase. We present clear controls to show that the assay specifically reports on promoter-dependent, full-length RNA transcription rates that are in good agreement with the kinetics determined by gel-resolved, α- 32 P NTP incorporation experiments. We illustrate how the time-dependent changes in fluorescence can be used to measure regulatory effects of nucleotide concentrations and identity, RNAP and DNA concentrations, transcription factors, and antibiotics. Our data showcase the ability to easily perform hundreds of parallel steady-state measurements across varying conditions with high precision and reproducibility to facilitate the study of the molecular mechanisms of bacterial transcription.

Significance Statement

RNA polymerase transcription mechanisms have largely been determined from in vitro kinetic and structural biology methods. In contrast to the limited throughput of these approaches, in vivo RNA sequencing provides genome-wide measurements but lacks the ability to dissect direct biochemical from indirect genetic mechanisms. Here, we present a method that bridges this gap, permitting high-throughput fluorescence-based measurements of in vitro steady-state transcription kinetics. We illustrate how an RNA-aptamer-based detection system can be used to generate quantitative information on direct mechanisms of transcriptional regulation and discuss the far-reaching implications for future applications.

Synergistic Effects of Bacteriophage vB_Eco4-M7 and Selected Antibiotics on the Biofilm Formed by Shiga Toxin-Producing Escherichia coli

Apart from antibiotic resistance of pathogenic bacteria, the formation of biofilms is a feature that makes bacterial infections especially difficulty to treat. Shiga toxin-producing Escherichia coli (STEC) strains are dangerous pathogens, causing severe infections in humans, and capable of biofilm production. We have reported previously the identification and characterization of the vB_Eco4-M7 bacteriophage, infecting various STEC strains. It was suggested that this phage might be potentially used in phage therapy against these bacteria. Here, we tested the effects of vB_Eco4-M7 alone or in a phage cocktail with another STEC-infecting phage, and/or in a combination with different antibiotics (ciprofloxacin and rifampicin) on biofilm formed by a model STEC strain, named E. coli O157:H7 (ST2-8624). The vB_Eco4-M7 phage appeared effective in anti-biofilm action in all these experimental conditions (2–3-fold reduction of the biofilm density, and 2–3 orders of magnitude reduction of the number of bacterial cells). However, the highest efficiency in reducing a biofilm’s density and number of bacterial cells was observed when phage infection preceded antibiotic treatment (6-fold reduction of the biofilm density, and 5–6 orders of magnitude reduction of the number of bacterial cells). Previous reports indicated that the use of antibiotics to treat STEC-caused infections might be dangerous due to the induction of Shiga toxin-converting prophages from bacterial genomes under stress conditions caused by antibacterial agents. We found that ciprofloxacin was almost as efficient in inducing prophages from the E. coli O15:H7 (ST2-8624) genome as a classical inducer, mitomycin C, while no detectable prophage induction could be observed in rifampicin-treated STEC cells. Therefore, we conclude the latter antibiotic or similarly acting compounds might be candidate(s) as effective and safe drug(s) when used in combination with phage therapy to combat STEC-mediated infections.

Cupressus sempervirens Essential Oil: Exploring the Antibacterial Multitarget Mechanisms, Chemcomputational Toxicity Prediction, and Safety Assessment in Zebrafish Embryos

Nowadays, increasing interest has recently been given to the exploration of new food preservatives to avoid foodborne outbreaks or food spoilage. Likewise, new compounds that substitute the commonly used synthetic food preservatives are required to restrain the rising problem of microbial resistance. Accordingly, the present study was conducted to examine the chemical composition and the mechanism(s) of action of the Cupressus sempervirens essential oil (CSEO) against Salmonella enterica Typhimuriumand Staphyloccocus aureus. The gas chromatography analysis revealed α-pinene (38.47%) and δ-3-carene (25.14%) are the major components of the CSEO. By using computational methods, such as quantitative structure-activity relationship (QSAR), we revealed that many CSEO components had no toxic effects. Moreover, findings indicated that α-pinene, δ-3-carene and borneol, a minor compound of CSEO, could inhibit the AcrB-TolC and MepR efflux pump activity of S. enterica Typhimurium and S. aureus, respectively. In addition, our molecular docking predictions indicated the high affinity of these three compounds with active sites of bacterial DNA and RNA polymerases, pointing to plausible impairments of the pathogenic bacteria cell replication processes. As well, the safety profile was developed through the zebrafish model. The in vivo toxicological evaluation of (CSEO) exhibited a concentration-dependent manner, with a lethal concentration (LC50) equal to 6.6 µg/mL.

Kanglemycin A Can Overcome Rifamycin Resistance Caused by ADP-Ribosylation by Arr Protein

Rifamycins, such as rifampicin (Rif), are potent inhibitors of bacterial RNA polymerase (RNAP) and are widely used antibiotics. Rifamycin resistance is usually associated with mutations in RNAP that preclude rifamycin binding. However, some bacteria have a type of ADP-ribosyl transferases, Arr, which ADP-ribosylate rifamycin molecules, thus inactivating their antimicrobial activity. Here, we directly show that ADP-ribosylation abolishes inhibition of transcription by rifampicin, the most widely used rifamycin antibiotic. We also show that a natural rifamycin, kanglemycin A (KglA), which has a unique sugar moiety at the ansa chain close to the Arr modification site, does not bind to Arr from Mycobacterium smegmatis and thus is not susceptible to inactivation. We, found, however, that kanglemycin A can still be ADP-ribosylated by the Arr of an emerging pathogen, Mycobacterium abscessus. Interestingly, the only part of Arr that exhibits no homology between the species is the part that sterically clashes with the sugar moiety of kanglemycin A in M. smegmatis Arr. This suggests that M. abscessus has encountered KglA or rifamycin with a similar sugar modification in the course of evolution. The results show that KglA could be an effective antimicrobial against some of the Arr-encoding bacteria.

Proximate and ultimate causes of the bactericidal action of antibiotics

During the past 85 years of antibiotic use, we have learned a great deal about how these 'miracle' drugs work. We know the molecular structures and interactions of these drugs and their targets and the effects on the structure, physiology and replication of bacteria. Collectively, we know a great deal about these proximate mechanisms of action for virtually all antibiotics in current use. What we do not know is the ultimate mechanism of action; that is, how these drugs irreversibly terminate the 'individuality' of bacterial cells by removing barriers to the external world (cell envelopes) or by destroying their genetic identity (DNA). Antibiotics have many different 'mechanisms of action' that converge to irreversible lethal effects. In this Perspective, we consider what our knowledge of the proximate mechanisms of action of antibiotics and the pharmacodynamics of their interaction with bacteria tell us about the ultimate mechanisms by which these antibiotics kill bacteria.

Ureidothiophene inhibits interaction of bacterial RNA polymerase with -10 promotor element

Bacterial RNA polymerase is a potent target for antibiotics, which utilize a plethora of different modes of action, some of which are still not fully understood. Ureidothiophene (Urd) was found in a screen of a library of chemical compounds for ability to inhibit bacterial transcription. The mechanism of Urd action is not known. Here, we show that Urd inhibits transcription at the early stage of closed complex formation by blocking interaction of RNA polymerase with the promoter -10 element, while not affecting interactions with -35 element or steps of transcription after promoter closed complex formation. We show that mutation in the region 1.2 of initiation factor σ decreases sensitivity to Urd. The results suggest that Urd may directly target σ region 1.2, which allosterically controls the recognition of -10 element by σ region 2. Alternatively, Urd may block conformational changes of the holoenzyme required for engagement with -10 promoter element, although by a mechanism distinct from that of antibiotic fidaxomycin (lipiarmycin). The results suggest a new mode of transcription inhibition involving the regulatory domain of σ subunit, and potentially pinpoint a novel target for development of new antibacterials.