Inhibiting fatty acid synthesis overcomes colistin resistance.

Treating multidrug-resistant infections has increasingly relied on last-resort antibiotics, including polymyxins, for example colistin. As polymyxins are given routinely, the prevalence of their resistance is on the rise and increases mortality rates of sepsis patients. The global dissemination of plasmid-borne colistin resistance, driven by the emergence of mcr-1, threatens to diminish the therapeutic utility of polymyxins from an already shrinking antibiotic arsenal. Restoring sensitivity to polymyxins using combination therapy with sensitizing drugs is a promising approach to reviving its clinical utility. Here we describe the ability of the biotin biosynthesis inhibitor, MAC13772, to synergize with colistin exclusively against colistin-resistant bacteria. MAC13772 indirectly disrupts fatty acid synthesis (FAS) and restores sensitivity to the last-resort antibiotic, colistin. Accordingly, we found that combinations of colistin and other FAS inhibitors, cerulenin, triclosan and Debio1452-NH3, had broad potential against both chromosomal and plasmid-mediated colistin resistance in chequerboard and lysis assays. Furthermore, combination therapy with colistin and the clinically relevant FabI inhibitor, Debio1452-NH3, showed efficacy against mcr-1 positive Klebsiella pneumoniae and colistin-resistant Escherichia coli systemic infections in mice. Using chemical genomics, lipidomics and transcriptomics, we explored the mechanism of the interaction. We propose that inhibiting FAS restores colistin sensitivity by depleting lipid synthesis, leading to changes in phospholipid composition. In all, this work reveals a surprising link between FAS and colistin resistance.

Nutrient stress is a target for new antibiotics.

Novel approaches are required to address the looming threat of pan-resistant Gram-negative pathogens and forestall the rise of untreatable infections. Unconventional targets that are uniquely important during infection and tractable to high-throughput drug discovery methods hold high potential for innovation in antibiotic discovery programs. In this context, inhibitors of bacterial nutrient stress are particularly exciting candidates for future antibiotic development. Amino acid, nucleotide, and vitamin biosynthesis pathways are critical for bacterial growth in nutrient-limiting conditions in the laboratory and the host. Although historically dismissed as dispensable for pathogens, a wealth of transposon mutagenesis and single-mutant studies have emerged which demonstrate that several such pathways are critical for infection. Indeed, high-throughput screens of diverse synthetic compounds and natural products have uncovered inhibitors of nutrient biosynthesis. Herein, we review bacterial nutrient biosynthesis and its role during host infection. Further, we explore screening platforms developed to search for inhibitors of these targets and highlight successes among these. Finally, we feature important and sometimes surprising connections between bacterial nutrient biosynthesis, antibiotic activity, and antibiotic resistance.

CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database.

The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 AMR detection models that can be used by the accompanying Resistance Gene Identifier (RGI) software to annotate genomic or metagenomic sequences. Focused curation enhancements since 2020 include expanded ß-lactamase curation, incorporation of likelihood-based AMR mutations for Mycobacterium tuberculosis, addition of disinfectants and antiseptics plus their associated ARGs, and systematic curation of resistance-modifying agents. This expanded curation includes 180 new AMR gene families, 15 new drug classes, 1 new resistance mechanism, and two new ontological relationships: evolutionary_variant_of and is_small_molecule_inhibitor. In silico prediction of resistomes and prevalence statistics of ARGs has been expanded to 377 pathogens, 21,079 chromosomes, 2,662 genomic islands, 41,828 plasmids and 155,606 whole-genome shotgun assemblies, resulting in collation of 322,710 unique ARG allele sequences. New features include the CARD:Live collection of community submitted isolate resistome data and the introduction of standardized 15 character CARD Short Names for ARGs to support machine learning efforts.

Preclinical Development of Pentamidine Analogs Identifies a Potent and Nontoxic Antibiotic Adjuvant.

The difficulty in treating Gram-negative bacteria can largely be attributed to their highly impermeable outer membrane (OM), which serves as a barrier to many otherwise active antibiotics. This can be overcome with the use of perturbant molecules, which disrupt OM integrity and sensitize Gram-negative bacteria to many clinically available Gram-positive-active antibiotics. Although many new perturbants have been identified in recent years, most of these molecules are impeded by toxicity due to the similarities between pathogen and host cell membranes. For example, our group recently reported the cryptic OM-perturbing activity of the antiprotozoal drug pentamidine. Its development as an antibiotic adjuvant is limited, however, by toxicity concerns. Herein, we took a medicinal chemistry approach to develop novel analogs of pentamidine, aiming to improve its OM activity while reducing its off-target toxicity. We identified the compound P35, which induces OM disruption and potentiates Gram-positive-active antibiotics in Acinetobacter baumannii and Klebsiella pneumoniae. Relative to pentamidine, P35 has reduced mammalian cell cytotoxicity and hERG trafficking inhibition. Additionally, P35 outperforms pentamidine in a murine model of A. baumannii bacteremia. Together, this preclinical analysis supports P35 as a promising lead for further development as an OM perturbant.

Overcoming Acquired and Native Macrolide Resistance with Bicarbonate.

The growing challenge of microbial resistance emphasizes the importance of new antibiotics or reviving strategies for the use of old ones. Macrolide antibiotics are potent bacterial protein synthesis inhibitors with a formidable capacity to treat life-threatening bacterial infections; however, acquired and intrinsic resistance limits their clinical application. In the work presented here, we reveal that bicarbonate is a potent enhancer of the activity of macrolide antibiotics that overcomes both acquired and intrinsic resistance mechanisms. With a focus on azithromycin, a highly prescribed macrolide antibiotic, and using clinically relevant pathogens, we show that physiological concentrations of bicarbonate overcome drug resistance by increasing the intracellular concentration of azithromycin. We demonstrate the potential of bicarbonate as a formulation additive for topical use of azithromycin in treating a murine wound infection caused by Pseudomonas aeruginosa. Further, using a systemic murine model of methicillin-resistant Staphylococcus aureus (MRSA) infection, we demonstrate the potential role of physiological bicarbonate, naturally abundant in the host, to enhance the activity of azithromycin against macrolide-resistant MRSA. In all, our findings suggest that macrolide resistance, observed in the clinical microbiology laboratory using standard culturing techniques, is a poor predictor of efficacy in the clinic and that observed resistance should not necessarily hamper the use of macrolides. Whether as a formulation additive for topical use or as a natural component of host tissues, bicarbonate is a powerful potentiator of macrolides with the capacity to overcome drug resistance in life-threatening bacterial infections.

Uncovering the Hidden Antibiotic Potential of Cannabis.

The spread of antimicrobial resistance continues to be a priority health concern worldwide, necessitating the exploration of alternative therapies. Cannabis sativa has long been known to contain antibacterial cannabinoids, but their potential to address antibiotic resistance has only been superficially investigated. Here, we show that cannabinoids exhibit antibacterial activity against methicillin-resistant Staphylococcus aureus (MRSA), inhibit its ability to form biofilms, and eradicate preformed biofilms and stationary phase cells persistent to antibiotics. We show that the mechanism of action of cannabigerol is through targeting the cytoplasmic membrane of Gram-positive bacteria and demonstrate in vivo efficacy of cannabigerol in a murine systemic infection model caused by MRSA. We also show that cannabinoids are effective against Gram-negative organisms whose outer membrane is permeabilized, where cannabigerol acts on the inner membrane. Finally, we demonstrate that cannabinoids work in combination with polymyxin B against multidrug resistant Gram-negative pathogens, revealing the broad-spectrum therapeutic potential for cannabinoids.

A Deep Learning Approach to Antibiotic Discovery.

Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we trained a deep neural network capable of predicting molecules with antibacterial activity. We performed predictions on multiple chemical libraries and discovered a molecule from the Drug Repurposing Hub-halicin-that is structurally divergent from conventional antibiotics and displays bactericidal activity against a wide phylogenetic spectrum of pathogens including Mycobacterium tuberculosis and carbapenem-resistant Enterobacteriaceae. Halicin also effectively treated Clostridioides difficile and pan-resistant Acinetobacter baumannii infections in murine models. Additionally, from a discrete set of 23 empirically tested predictions from >107 million molecules curated from the ZINC15 database, our model identified eight antibacterial compounds that are structurally distant from known antibiotics. This work highlights the utility of deep learning approaches to expand our antibiotic arsenal through the discovery of structurally distinct antibacterial molecules.

Mimicking the human environment in mice reveals that inhibiting biotin biosynthesis is effective against antibiotic-resistant pathogens.

To revitalize the antibiotic pipeline, it is critical to identify and validate new antimicrobial targets1. In Mycobacteria tuberculosis and Francisella tularensis, biotin biosynthesis is a key fitness determinant during infection2-5, making it a high-priority target. However, biotin biosynthesis has been overlooked for priority pathogens such as Acinetobacter baumannii, Klebsiella pneumoniae and Pseudomonas aeruginosa. This can be attributed to the lack of attenuation observed for biotin biosynthesis genes during transposon mutagenesis studies in mouse infection models6-9. Previous studies did not consider the 40-fold higher concentration of biotin in mouse plasma compared to human plasma. Here, we leveraged the unique affinity of streptavidin to develop a mouse infection model with human levels of biotin. Our model suggests that biotin biosynthesis is essential during infection with A. baumannii, K. pneumoniae and P. aeruginosa. Encouragingly, we establish the capacity of our model to uncover in vivo activity for the biotin biosynthesis inhibitor MAC13772. Our model addresses the disconnect in biotin levels between humans and mice, and explains the failure of potent biotin biosynthesis inhibitors in standard mouse infection models.

Overcoming mcr-1 mediated colistin resistance with colistin in combination with other antibiotics.

Plasmid-borne colistin resistance mediated by mcr-1 may contribute to the dissemination of pan-resistant Gram-negative bacteria. Here, we show that mcr-1 confers resistance to colistin-induced lysis and bacterial cell death, but provides minimal protection from the ability of colistin to disrupt the Gram-negative outer membrane. Indeed, for colistin-resistant strains of Enterobacteriaceae expressing plasmid-borne mcr-1, clinically relevant concentrations of colistin potentiate the action of antibiotics that, by themselves, are not active against Gram-negative bacteria. The result is that several antibiotics, in combination with colistin, display growth-inhibition at levels below their corresponding clinical breakpoints. Furthermore, colistin and clarithromycin combination therapy displays efficacy against mcr-1-positive Klebsiella pneumoniae in murine thigh and bacteremia infection models at clinically relevant doses. Altogether, these data suggest that the use of colistin in combination with antibiotics that are typically active against Gram-positive bacteria poses a viable therapeutic alternative for highly drug-resistant Gram-negative pathogens expressing mcr-1.

Silent but deadly: IS200 promotes pathogenicity in Salmonella Typhimurium.

Bacterial transposons were long thought of as selfish mobile genetic elements that propagate at the expense of 'host' bacterium fitness. However, limited transposition can benefit the host organism by promoting DNA rearrangements and facilitating horizontal gene transfer. Here we discuss and provide context for our recently published work which reported the surprising finding that an otherwise dormant transposon, IS200, encodes a regulatory RNA in Salmonella Typhimurium. This previous work identified a trans-acting sRNA that is encoded in the 5'UTR of IS200 transposase mRNA (tnpA). This sRNA represses expression of genes encoded within Salmonella Pathogenicity Island 1 (SPI-1), and accordingly limits invasion into non-phagocytic cells in vitro. We present new data here that shows IS200 elements are important for colonization of the mouse gastrointestinal tract. We discuss our previous and current findings in the context of transposon biology and suggest that otherwise 'silent' transposons may in fact play an important role in controlling host gene expression.