Systems-level antimicrobial drug and drug synergy discovery

Building a unified model for drug synergy analysis powered by large language models

Drug synergy prediction is a challenging and important task in the treatment of complex diseases including cancer. In this manuscript, we present a unified Model, known as BAITSAO, for tasks related to drug synergy prediction with a unified pipeline to handle different datasets. We construct the training datasets for BAITSAO based on the context-enriched embeddings from Large Language Models for the initial representation of drugs and cell lines. After demonstrating the relevance of these embeddings, we pre-train BAITSAO with a large-scale drug synergy database under a multi-task learning framework with rigorous selections of tasks. We demonstrate the superiority of the model architecture and the pre-trained strategies of BAITSAO over other methods through comprehensive benchmark analysis. Moreover, we investigate the sensitivity of BAITSAO and illustrate its promising functions including drug discoveries, drug combinations-gene interaction, and multi-drug synergy predictions.

Building A Unified Model for Drug Synergy Analysis Powered by Large Language Models

Drug synergy prediction is a challenging and important task in the treatment of complex diseases including cancer. In this manuscript, we present a novel unified Model, known as BAITSAO, for tasks related to drug synergy prediction with a unified pipeline to handle different datasets. We construct the training datasets for BAITSAO based on the context-enriched embeddings from Large Language Models for the initial representation of drugs and cell lines. After demonstrating the relevance of these embeddings, we pre-train BAITSAO with a large-scale drug synergy database under a multi-task learning framework with rigorous selections of tasks. We demonstrate the superiority of the model architecture and the pre-trained strategies of BAITSAO over other methods through comprehensive benchmark analysis. Moreover, we investigate the sensitivity of BAITSAO and illustrate its unique functions including new drug discoveries, drug combinations-gene interaction, and multi-drug synergy predictions.

Innovative perspectives on the discovery of small molecule antibiotics

Antibiotics are essential to modern medicine, but multidrug-resistant (MDR) bacterial infections threaten their efficacy. Resistance evolution shortens antibiotic lifespans, limiting investment returns and slowing new approvals. Consequently, the WHO defines four innovation criteria: new chemical class, target, mode of action (MoA), and lack of cross-resistance. This review explores innovative discovery approaches, including AI-driven screening, metagenomics, and target-based strategies, to develop novel antibiotics that meet these criteria and combat MDR infections.

Rationally designed pooled CRISPRi-seq uncovers an inhibitor of bacterial peptidyl-tRNA hydrolase

Bacterial mutant libraries with downregulated antibiotic targets are useful tools for elucidating the mechanisms of action of antibacterial compounds, a pivotal step in antibiotic discovery. However, achieving genomic coverage of antibacterial targets poses a challenge due to the uneven proliferation of knockdown mutants during pooled growth, leading to the unintended loss of important targets. To overcome this issue, we constructed an arrayed essential gene mutant library (EGML) in the antibiotic-resistant bacterium Burkholderia cenocepacia using CRISPR interference (CRISPRi). By modeling depletion levels and adjusting knockdown mutant inocula, we rationally designed and optimized a CRISPR interference-mediated pooled library of essential genes (CIMPLE) approaching coverage of the bacterial essential genome with mutant sensitization. We exposed CIMPLE to an uncharacterized bacterial growth inhibitor structurally different from antibiotics and discovered that it inhibits the essential peptidyl-tRNA hydrolase. Overall, CIMPLE leverages the advantages of arrayed and pooled CRISPRi libraries to uncover unexplored targets for antibiotic action.

Environment by environment interactions (ExE) differ across genetic backgrounds (ExExG)

While the terms "gene-by-gene interaction" (GxG) and "gene-by-environment interaction" (GxE) are widely recognized in the fields of quantitative and evolutionary genetics, "environment-byenvironment interaction" (ExE) is a term used less often. In this study, we find that environmentby-environment interactions are a meaningful driver of phenotypes, and moreover, that they differ across different genotypes (suggestive of ExExG). To support this conclusion, we analyzed a large dataset of roughly 1,000 mutant yeast strains with varying degrees of resistance to different antifungal drugs. Our findings reveal that the effectiveness of a drug combination, relative to single drugs, often differs across drug resistant mutants. Remarkably, even mutants that differ by only a single nucleotide change can have dramatically different drug × drug (ExE) interactions. We also introduce a new framework that more accurately predicts the direction and magnitude of ExE interactions for some mutants. Understanding how ExE interactions change across genotypes (ExExG) is crucial not only for modeling the evolution of pathogenic microbes, but also for enhancing our knowledge of the underlying cell biology and the sources of phenotypic variance within populations. While the significance of ExExG interactions has been overlooked in evolutionary and population genetics, these fields and others stand to benefit from understanding how these interactions shape the complex behavior of living systems.

Rationally Designed Pooled CRISPRi-Seq Uncovers an Inhibitor of Bacterial Peptidyl-tRNA Hydrolase

Pooled knockdown libraries of essential genes are useful tools for elucidating the mechanisms of action of antibacterial compounds, a pivotal step in antibiotic discovery. However, achieving genomic coverage of antibacterial targets poses a challenge due to the uneven proliferation of knockdown mutants during pooled growth, leading to the unintended loss of important targets. To overcome this issue, we describe the construction of CIMPLE ( C RISPR i - m ediated p ooled library of e ssential genes), a rationally designed pooled knockdown library built in a model antibiotic-resistant bacteria, Burkholderia cenocepacia. By analyzing growth parameters of clonal knockdown populations of an arrayed CRISPRi library, we predicted strain depletion levels during pooled growth and adjusted mutant relative abundance, approaching genomic coverage of antibacterial targets during antibiotic exposure. We first benchmarked CIMPLE by chemical-genetic profiling of known antibacterials, then applied it to an uncharacterized bacterial growth inhibitor from a new class. CRISPRi-Seq with CIMPLE, followed by biochemical validation, revealed that the novel compound targets the peptidyl-tRNA hydrolase (Pth). Overall, CIMPLE leverages the advantages of arrayed and pooled CRISPRi libraries to uncover unexplored targets for antibiotic action.

Summary

Bacterial mutant libraries in which antibiotic targets are downregulated are useful tools to functionally characterize novel antimicrobials. These libraries are used for chemical-genetic profiling as target-compound interactions can be inferred by differential fitness of mutants during pooled growth. Mutants that are functionally related to the antimicrobial mode of action are usually depleted from the pool upon exposure to the drug. Although powerful, this method can fail when the unequal proliferation of mutant strains before exposure causes mutants to fall below the detection level in the library pool. To address this issue, we constructed an arrayed essential gene mutant library (EGML) in the antibiotic-resistant bacterium Burkholderia cenocepacia using CRISPR interference (CRISPRi) and analyzed the growth parameters of individual mutant strains. We then modelled depletion levels during pooled growth and used the model to rationally design an optimized CRISPR interference-mediated pooled library of essential genes (CIMPLE). By adjusting the initial inoculum of the knockdown mutants, we achieved coverage of the bacterial essential genome with mutant sensitization. We exposed CIMPLE to a recently discovered antimicrobial of a novel class and discovered it inhibits the peptidyl-tRNA hydrolase, an essential bacterial enzyme. In summary, we demonstrate the utility of CIMPLE and CRISPRi-Seq to uncover the mechanism of action of novel antimicrobial compounds.

Graphical abstract

Functional mechanism study of the allelochemical myrigalone A identifies a group of ultrapotent inhibitors of ethylene biosynthesis in plants

Allelochemicals represent a class of natural products released by plants as root, leaf, and fruit exudates that interfere with the growth and survival of neighboring plants. Understanding how allelochemicals function to regulate plant responses may provide valuable new approaches to better control plant function. One such allelochemical, Myrigalone A (MyA) produced by Myrica gale, inhibits seed germination and seedling growth through an unknown mechanism. Here, we investigate MyA using the tractable model Dictyostelium discoideum and reveal that its activity depends on the conserved homolog of the plant ethylene synthesis protein 1-aminocyclopropane-1-carboxylic acid oxidase (ACO). Furthermore, in silico modeling predicts the direct binding of MyA to ACO within the catalytic pocket. In D. discoideum, ablation of ACO mimics the MyA-dependent developmental delay, which is partially restored by exogenous ethylene, and MyA reduces ethylene production. In Arabidopsis thaliana, MyA treatment delays seed germination, and this effect is rescued by exogenous ethylene. It also mimics the effect of established ACO inhibitors on root and hypocotyl extension, blocks ethylene-dependent root hair production, and reduces ethylene production. Finally, in silico binding analyses identify a range of highly potent ethylene inhibitors that block ethylene-dependent response and reduce ethylene production in Arabidopsis. Thus, we demonstrate a molecular mechanism by which the allelochemical MyA reduces ethylene biosynthesis and identify a range of ultrapotent inhibitors of ethylene-regulated responses.

Antibiofilm activity of mesoporous silica nanoparticles against the biofilm associated infections

In pharmaceutical industries, various chemical carriers are present which are used for drug delivery to the correct target sites. The most popular and upcoming drug delivery carriers are mesoporous silica nanoparticles (MSN). The main reason for its popularity is its ability to be specific and optimize the drug delivery process in a controlled manner. Nowadays, MSNs are widely used to eradicate various microbial infections, especially the ones related to biofilms. Biofilms are sessile groups of cells that live by forming a consortium and exhibit antibacterial resistance (AMR). They exhibit AMR by extracellular polymeric substances (EPS) and various quorum sensing (QS) signaling molecules. Usually, bacterial and fungal cells are capable of forming biofilms. These biofilms are pathogenic. In the majority of the cases, biofilms cause nosocomial diseases. This review will focus on the antibiofilm activities of MSN, its mechanism of target-specific drug delivery, and its ability to disrupt the bacterial biofilms inhibiting the infection. The review will also discuss various mechanisms for the delivery of pharmaceutical molecules by the MSNs to inhibit the bacterial biofilms, and lastly, we will talk about the different types of MSNs and their antibiofilm activities.

A FtsZ Inhibitor That Can Utilize Siderophore-Ferric Iron Uptake Transporter Systems for Activity against Gram-Negative Bacterial Pathogens

The global threat of multidrug-resistant Gram-negative bacterial pathogens necessitates the development of new and effective antibiotics. FtsZ is an essential and highly conserved cytoskeletal protein that is an appealing antibacterial target for new antimicrobial therapeutics. However, the effectiveness of FtsZ inhibitors against Gram-negative species has been limited due in part to poor intracellular accumulation. To address this limitation, we have designed a FtsZ inhibitor (RUP4) that incorporates a chlorocatechol siderophore functionality that can chelate ferric iron (Fe3+) and utilizes endogenous siderophore uptake pathways to facilitate entry into Gram-negative pathogens. We show that RUP4 is active against both Klebsiella pneumoniae and Acinetobacter baumannii, with this activity being dependent on direct Fe3+ chelation and enhanced under Fe3+-limiting conditions. Genetic deletion studies in K. pneumoniae reveal that RUP4 gains entry through the FepA and CirA outer membrane transporters and the FhuBC inner membrane transporter. We also show that RUP4 exhibits bactericidal synergy against K. pneumoniae when combined with select antibiotics, with the strongest synergy observed with PBP2-targeting β-lactams or MreB inhibitors. In the aggregate, our studies indicate that incorporation of Fe3+-chelating moieties into FtsZ inhibitors is an appealing design strategy for enhancing activity against Gram-negative pathogens of global clinical significance.

Elucidating the Mechanism of Action of the Gram-Negative-Pathogen-Selective Cyclic Antimicrobial Lipopeptide Brevicidine

Due to the accelerated appearance of antimicrobial-resistant (AMR) pathogens in clinical infections, new first-in-class antibiotics, operating via novel modes of action, are desperately needed. Brevicidine, a bacterial nonribosomally produced cyclic lipopeptide, has shown potent and selective antimicrobial activity against Gram-negative pathogens. However, before our investigations, little was known about how brevicidine exerts its potent bactericidal effect against Gram-negative pathogens. In this study, we find that brevicidine has potent antimicrobial activity against AMR Enterobacteriaceae pathogens, with MIC values ranging between 0.5 μM (0.8 mg/L) and 2 μM (3.0 mg/L). In addition, brevicidine showed potent antibiofilm activity against the Enterobacteriaceae pathogens, with the same 100% inhibition and 100% eradication concentration of 4 μM (6.1 mg/L). Further mechanistic studies showed that brevicidine exerts its potent bactericidal activity by interacting with lipopolysaccharide in the outer membrane, targeting phosphatidylglycerol and cardiolipin in the inner membrane, and dissipating the proton motive force of bacteria. This results in metabolic perturbation, including the inhibition of ATP synthesis; the inhibition of the dehydrogenation of NADH; the accumulation of reactive oxygen species in bacteria; and the inhibition of protein synthesis. Finally, brevicidine showed a good therapeutic effect in a mouse peritonitis-sepsis model. Our findings pave the way for further research on the clinical applications of brevicidine to combat prevalent infections caused by AMR Gram-negative pathogens worldwide.

Chimeric Peptidomimetic Antibiotic Efficiently Neutralizes Lipopolysaccharides (LPS) and Bacteria-Induced Activation of RAW Macrophages

Peptide antibiotics have gathered attention given the urgent need to discover antimicrobials with new mechanisms of action. Their extended role as immunomodulators makes them interesting candidates for the development of compounds with dual mode of action. The objective of this study was to test the anti-inflammatory capacity of a recently reported chimeric peptidomimetic antibiotic (CPA) composed of polymyxin B nonapeptide (PMBN) and a macrocyclic β-hairpin motif (MHM). We investigated the potential of CPA to inhibit lipopolysaccharide (LPS)-induced activation of RAW264.7 macrophages. In addition, we elucidated which structural motif was responsible for this activity by testing CPA, its building blocks, and their parent compounds separately. CPA showed excellent LPS neutralizing activity for both smooth and rough LPSs. At nanomolar concentrations, CPA completely inhibited LPS-induced nitric oxide, TNF-α, and IL-10 secretion. Murepavadin, MHM, and PMBN were incapable of neutralizing LPS in this assay, while PMB was less active compared to CPA. Isothermal titration calorimetry showed strong binding between the CPA and LPS with similar binding characteristics also found for the other compounds, indicating that binding does not necessarily correlate with neutralization of LPS. Finally, we showed that CPA-killed bacteria caused significantly less macrophage activation than bacteria killed with gentamicin, heat, or any of the other compounds. This indicates that the combined killing activity and LPS neutralization of CPA can prevent unwanted inflammation, which could be a major advantage over conventional antibiotics. Our data suggests that immunomodulatory activity can further strengthen the therapeutic potential of peptide antibiotics and should be included in the characterization of novel compounds.

Chemical-Genetic Approaches for Exploring Mode of Action of Antifungal Compounds in the Fungal Pathogen Candida albicans

Candida albicans is a prevalent fungal pathogen of humans that can cause both superficial and life-threatening disease, primarily in immunocompromised populations. Currently, antifungal drug classes available to treat fungal infections remain limited and the emergence of drug-resistant strains threatens antifungal efficacy, necessitating the discovery and development of additional therapeutics. The construction of the C. albicans double-barcoded heterozygous deletion collection (DBC) enables the rapid and systematic assessment of haploinsufficiency phenotypes in a pooled format. Specifically, this functional genomics resource can be used to identify heterozygous deletion mutants that are hypersensitive to compounds in order to define putative cellular targets and/or other modifiers of compound activity. Here, we describe protocols to characterize the mode of action of small molecules using the C. albicans DBC, including how to prepare compound-treated cultures, isolate genomic DNA, amplify strain-specific barcodes, and prepare DNA libraries for high-throughput sequencing. This technique provides a powerful approach to elucidate the compound mechanism of action in order to bolster the antifungal pipeline.

Synthetic Studies with Bacitracin A and Preparation of Analogues Containing Alternative Zinc Binding Groups

The growing threat of drug-resistant bacteria is a global concern, highlighting the urgent need for new antibiotics and antibacterial strategies. In this light, practical synthetic access to natural product antibiotics can provide important structure-activity insights while also opening avenues for the development of novel analogues with improved properties. To this end, we report an optimised synthetic route for the preparation of the clinically used macrocyclic peptide antibiotic bacitracin. Our combined solid- and solution-phase approach addresses the problematic, and previously unreported, formation of undesired epimers associated with the stereochemically fragile N-terminal thiazoline moiety. A number of bacitracin analogues were also prepared wherein the thiazoline motif was replaced by other known zinc-binding moieties and their antibacterial activities evaluated.

Therapeutic Approaches for Combating Aspergillus Associated Infection

Now-a-days fungal infection emerges as a significant problem to healthcare management systems due to high frequency of associated morbidity, mortality toxicity, drug-drug interactions, and resistance of the antifungal agents. Aspergillus is the most common mold that cause infection in immunocompromised hosts. It's a hyaline mold that is cosmopolitan and ubiquitous in nature. Aspergillus infects around 10 million population each year with a mortality rate of 30-90%. Clinically available antifungal formulations are restricted to four classes (i.e., polyene, triazole, echinocandin, and allylamine), and each of them have their own limitations associated with the activity spectrum, the emergence of resistance, and toxicity. Consequently, novel antifungal agents with modified and altered chemical structures are required to combat these invasive fungal infections. To overcome these limitations, there is an urgent need for new antifungal agents that can act as potent drugs in near future. Currently, some compounds have shown effective antifungal activity. In this review article, we have discussed all potential antifungal therapies that contain old antifungal drugs, combination therapies, and recent novel antifungal formulations, with a focus on the Aspergillus associated infections.

Library Screening for Synergistic Combinations of FDA-Approved Drugs and Metabolites with Vancomycin against VanA-Type Vancomycin-Resistant Enterococcus faecium

Antimicrobial resistance is a major public health threat, and there is an urgent need for new strategies to address this issue. In a recent study, a library screening strategy was developed in which an FDA-approved drug library was screened against methicillin-resistant Staphylococcus aureus (MRSA) in both its original (unmetabolized [UM]) and its human liver microsome metabolized (postmetabolized [PM]) forms and in the absence and presence of a resistant-to antibiotic. This allows the identification of agents with active metabolites and agents that can act synergistically with the resistant-to antibiotic. In this study, this strategy is applied to VanA-type vancomycin-resistant Enterococcus faecium (VREfm) in the absence and presence of vancomycin. Thirteen drugs with minimum MICs that were ≤12.5 μM under any tested condition (UM/PM vs. -/+vancomycin) were identified. Seven of these appeared to act synergistically with vancomycin, and follow-up checkerboard analyses confirmed synergy (∑FICmin ≤0.5) for six of these. Ultimately four rifamycins, two pleuromutilins, mupirocin, and linezolid were confirmed as synergistic. The most synergistic agent was rifabutin (∑FICmin = 0.19). Linezolid, a protein biosynthesis inhibitor, demonstrated relatively weak synergy (∑FICmin = 0.5). Only mupirocin showed significantly improved activity after microsomal metabolism, indicative of a more active metabolite, but efforts to identify an active metabolite were unsuccessful. Spectra of activity of several hits and related agents were also determined. Gemcitabine showed activity against a number vancomycin-resistant E. faecium and E. faecalis strains, but this activity was substantially weaker than previously observed in MRSA. IMPORTANCE Resistance to currently used antibiotics poses a serious threat to public health. This study reports a complete screen of 1,000 FDA-approved drugs and their metabolites against vancomycin-resistant Enterococcus faecium (VREfm) in both the absence and presence of vancomycin. This identified potentially synergistic combinations of FDA-approved drugs with vancomycin, and a number of these were confirmed in follow-up checkerboard assays. Among intrinsically active FDA-approved drugs, gemcitabine was identified as having activity against a panel of VRE strains.

Calcineurin Inhibitors Synergize with Manogepix to Kill Diverse Human Fungal Pathogens

Invasive fungal infections have mortality rates of 30–90%, depending on patient co-morbidities and the causative pathogen. The frequent emergence of drug resistance reduces the efficacy of currently approved treatment options, highlighting an urgent need for antifungals with new modes of action. Addressing this need, fosmanogepix (N-phosphonooxymethylene prodrug of manogepix; MGX) is the first in a new class of gepix drugs, and acts as a broad-spectrum, orally bioavailable inhibitor of the essential fungal glycosylphosphatidylinositol (GPI) acyltransferase Gwt1. MGX inhibits the growth of diverse fungal pathogens and causes accumulation of immature GPI-anchored proteins in the fungal endoplasmic reticulum. Relevant to the ongoing clinical development of fosmanogepix, we report a synergistic, fungicidal interaction between MGX and inhibitors of the protein phosphatase calcineurin against important human fungal pathogens. To investigate this synergy further, we evaluated a library of 124 conditional expression mutants covering 95% of the genes encoding proteins involved in GPI-anchor biosynthesis or proteins predicted to be GPI-anchored. Strong negative chemical-genetic interactions between the calcineurin inhibitor FK506 and eleven GPI-anchor biosynthesis genes were identified, indicating that calcineurin signalling is required for fungal tolerance to not only MGX, but to inhibition of the GPI-anchor biosynthesis pathway more broadly. Depletion of these GPI-anchor biosynthesis genes, like MGX treatment, also exposed fungal cell wall (1→3)-β-D-glucans. Taken together, these findings suggest the increased risk of invasive fungal infections associated with use of calcineurin inhibitors as immunosuppressants may be mitigated by their synergistic fungicidal interaction with (fos)manogepix and its ability to enhance exposure of immunostimulatory glucans.

BIONIC: biological network integration using convolutions

Biological networks constructed from varied data can be used to map cellular function, but each data type has limitations. Network integration promises to address these limitations by combining and automatically weighting input information to obtain a more accurate and comprehensive representation of the underlying biology. We developed a deep learning-based network integration algorithm that incorporates a graph convolutional network framework. Our method, BIONIC (Biological Network Integration using Convolutions), learns features that contain substantially more functional information compared to existing approaches. BIONIC has unsupervised and semisupervised learning modes, making use of available gene function annotations. BIONIC is scalable in both size and quantity of the input networks, making it feasible to integrate numerous networks on the scale of the human genome. To demonstrate the use of BIONIC in identifying new biology, we predicted and experimentally validated essential gene chemical-genetic interactions from nonessential gene profiles in yeast.

Genomic Approaches to Antifungal Drug Target Identification and Validation

The last several decades have witnessed a surge in drug-resistant fungal infections that pose a serious threat to human health. While there is a limited arsenal of drugs that can be used to treat systemic infections, scientific advances have provided renewed optimism for the discovery of novel antifungals. The development of chemical-genomic assays using Saccharomyces cerevisiae has provided powerful methods to identify the mechanism of action of molecules in a living cell. Advances in molecular biology techniques have enabled complementary assays to be developed in fungal pathogens, including Candida albicans and Cryptococcus neoformans. These approaches enable the identification of target genes for drug candidates, as well as genes involved in buffering drug target pathways. Here, we examine yeast chemical-genomic assays and highlight how such resources can be utilized to predict the mechanisms of action of compounds, to study virulence attributes of diverse fungal pathogens, and to bolster the antifungal pipeline.

A defect in cell wall recycling confers antibiotic resistance and sensitivity in Staphylococcus aureus

WalKR is a two-component system that is essential for viability in Gram-positive bacteria that regulates the all-important autolysins in cell wall homeostasis. Further investigation of this essential system is important for identifying ways to address antibiotic resistance. Here, we show that a T101M mutation in walR confers a defect in autolysis, a thickened cell wall, and decreased susceptibility to antibiotics that target lipid II cycle, a phenotype that is reminiscent of the clinical resistance form known as vancomycin intermediate-resistant Staphylococcus aureus. Importantly, this is accompanied by dramatic sensitization to tunicamycin. We demonstrate that this phenotype is due to partial collapse of a pathway consisting of autolysins, AtlA and Sle1, a transmembrane sugar permease, MurP, and GlcNAc recycling enzymes, MupG and MurQ. We suggest that this causes a shortage of substrate for the peptidoglycan biosynthesis enzyme MraY, causing it to be hypersensitive to competitive inhibition by tunicamycin. In conclusion, our results constitute a new molecular model for antibiotic sensitivity in S. aureus and a promising new route for antibiotic discovery.

Combination with a FtsZ inhibitor potentiates the in vivo efficacy of oxacillin against methicillin-resistant Staphylococcus aureus

Oxacillin is a first-line antibiotic for the treatment of methicillin-sensitive Staphylococcus aureus (MSSA) infections but is ineffective against methicillin-resistant S. aureus (MRSA) due to resistance. Here we present results showing that co-administering oxacillin with the FtsZ-targeting prodrug TXA709 renders oxacillin efficacious against MRSA. The combination of oxacillin and the active product of TXA709 (TXA707) is associated with synergistic bactericidal activity against clinical isolates of MRSA that are resistant to current standard-of-care antibiotics. We show that MRSA cells treated with oxacillin in combination with TXA707 exhibit morphological characteristics and PBP2 mislocalization behavior similar to that exhibited by MSSA cells treated with oxacillin alone. Co-administration with TXA709 renders oxacillin efficacious in mouse models of both systemic and tissue infection with MRSA, with this efficacy being observed at human-equivalent doses of oxacillin well below that recommended for daily adult use. Pharmacokinetic evaluations in mice reveal that co-administration with TXA709 also increases total exposure to oxacillin. Viewed as a whole, our results highlight the clinical potential of repurposing oxacillin to treat MRSA infections through combination with a FtsZ inhibitor.

Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision Dosing

In the era of “Bad Bugs, No Drugs,” optimizing antibiotic therapy against multi-drug resistant (MDR) pathogens is crucial. Mathematical modelling has been employed to further optimize dosing regimens. These models include mechanism-based PK/PD models, systems-based models, quantitative systems pharmacology (QSP) and population PK models. Quantitative systems pharmacology has significant potential in precision antimicrobial chemotherapy in the clinic. Population PK models have been employed in model-informed precision dosing (MIPD). Several antibiotics require close monitoring and dose adjustments in order to ensure optimal outcomes in patients with infectious diseases. Success or failure of antibiotic therapy is dependent on the patient, antibiotic and bacterium. For some drugs, treatment responses vary greatly between individuals due to genotype and disease characteristics. Thus, for these drugs, tailored dosing is required for successful therapy. With antibiotics, inappropriate dosing such as insufficient dosing may put patients at risk of therapeutic failure which could lead to mortality. Conversely, doses that are too high could lead to toxicities. Hence, precision dosing which customizes doses to individual patients is crucial for antibiotics especially those with a narrow therapeutic index. In this review, we discuss the various strategies in optimizing antimicrobial therapy to address the challenges in the management of infectious diseases and delivering personalized therapy.

Antisense Peptide Nucleic Acid-Diaminobutanoic Acid Dendron Conjugates with SbmA-Independent Antimicrobial Activity against Gram-Negative Bacteria

Precision antisense antibacterial agents may be developed into novel antibiotics in the fight against multidrug-resistant Gram-negative bacteria. In this study, a series of diaminobutanoic acid (DAB) dendrons are presented as novel carriers for the delivery of antisense antibacterial peptide nucleic acids (PNAs). The dendron-PNA conjugates targeting the essential acpP gene exhibit specific antisense antimicrobial bactericidal activity against Escherichia coli and Klebsiella pneumoniae at one-digit micromolar concentrations, while showing low toxicity to human cells. One compound selected from a structure-activity relationship series showed high stability in mouse and human serum (t_1/2 ≫ 24 h) as well as in vivo activity against a multidrug-resistant, extended spectrum beta-lactamase-producing E. coli in a murine peritonitis model. The compound was also well tolerated in mice upon i.v. administration up to a dose of 20 mg/kg, and in vivo fluorescence imaging indicated clearance via renal excretion with slight accumulation in the kidneys and liver. Thus, DAB-based dendrons constitute a promising new chemistry platform for development of effective delivery agents for antibacterial drugs with possible in vivo use.

SynLethDB 2.0: a web-based knowledge graph database on synthetic lethality for novel anticancer drug discovery

Two genes are synthetic lethal if mutations in both genes result in impaired cell viability, while mutation of either gene does not affect the cell survival. The potential usage of synthetic lethality (SL) in anticancer therapeutics has attracted many researchers to identify synthetic lethal gene pairs. To include newly identified SLs and more related knowledge, we present a new version of the SynLethDB database to facilitate the discovery of clinically relevant SLs. We extended the first version of SynLethDB database significantly by including new SLs identified through Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) screening, a knowledge graph about human SLs, a new web interface, etc. Over 16 000 new SLs and 26 types of other relationships have been added, encompassing relationships among 14 100 genes, 53 cancers, 1898 drugs, etc. Moreover, a brand-new web interface has been developed to include modules such as SL query by disease or compound, SL partner gene set enrichment analysis and knowledge graph browsing through a dynamic graph viewer. The data can be downloaded directly from the website or through the RESTful Application Programming Interfaces (APIs). Database URL:  https://synlethdb.sist.shanghaitech.edu.cn/v2.

Recent Molecular Tools for the Genetic Manipulation of Highly Industrially Important Mucoromycota Fungi

Mucorales is the largest and most well-studied order of the phylum Mucormycota and is known for its rapid growth rate and various industrial applications. The Mucorales fungi are a fascinating group of filamentous organisms with many uses in research and the industrial and medical fields. They are widely used biotechnological producers of various secondary metabolites and other value-added products. Certain members of Mucorales are extensively used as model organisms for genetic and molecular investigation and have extended our understanding of the metabolisms of other members of this order as well. Compared with other fungal species, our understanding of Mucoralean fungi is still in its infancy, which could be linked to their lack of effective genetic tools. However, recent advancements in molecular tools and approaches, such as the construction of recyclable markers, silencing vectors, and the CRISPR-Cas9-based gene-editing system, have helped us to modify the genomes of these model organisms. Multiple genetic modifications have been shown to generate valuable products on a large scale and helped us to understand the morphogenesis, basic biology, pathogenesis, and host–pathogen interactions of Mucoralean fungi. In this review, we discuss various conventional and modern genetic tools and approaches used for efficient gene modification in industrially important members of Mucorales.

Infection microenvironment-related antibacterial nanotherapeutic strategies

The emergence and spread of antibiotic resistance is one of the biggest challenges in public health. There is an urgent need to discover novel agents against the occurrence of multidrug-resistant bacteria, such as methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci. The drug-resistant pathogens are able to grow and persist in infected sites, including biofilms, phagosomes, or phagolysosomes, which are more difficult to eradicate than planktonic ones and also foster the development of drug resistance. For years, various nano-antibacterial agents have been developed in the forms of antibiotic nanocarriers. Inorganic nanoparticles with intrinsic antibacterial activity and inert nanoparticles assisted by external stimuli, including heat, photon, magnetism, or sound, have also been discovered. Many of these strategies are designed to target the unique microenvironment of bacterial infections, which have shown potent antibacterial effects in vitro and in vivo. This review summarizes ongoing efforts on antibacterial nanotherapeutic strategies related to bacterial infection microenvironments, including targeted antibacterial therapy and responsive antibiotic delivery systems. Several grand challenges and future directions for the development and translation of effective nano-antibacterial agents are also discussed. The development of innovative nano-antibacterial agents could provide powerful weapons against drug-resistant bacteria in systemic or local bacterial infections in the foreseeable future.

Leveraging machine learning essentiality predictions and chemogenomic interactions to identify antifungal targets

Fungal pathogens pose a global threat to human health, with Candida albicans among the leading killers. Systematic analysis of essential genes provides a powerful strategy to discover potential antifungal targets. Here, we build a machine learning model to generate genome-wide gene essentiality predictions for C. albicans and expand the largest functional genomics resource in this pathogen (the GRACE collection) by 866 genes. Using this model and chemogenomic analyses, we define the function of three uncharacterized essential genes with roles in kinetochore function, mitochondrial integrity, and translation, and identify the glutaminyl-tRNA synthetase Gln4 as the target of N-pyrimidinyl-β-thiophenylacrylamide (NP-BTA), an antifungal compound.

Antibiotic Biosynthesis Pathways from Endophytic Streptomyces SUK 48 through Metabolomics and Genomics Approaches

Streptomyces sp. has been known to be a major antibiotic producer since the 1940s. As the number of cases related to resistance pathogens infection increases yearly, discovering the biosynthesis pathways of antibiotic has become important. In this study, we present the streamline of a project report summary; the genome data and metabolome data of newly isolated Streptomyces SUK 48 strain are also analyzed. The antibacterial activity of its crude extract is also determined. To obtain genome data, the genomic DNA of SUK 48 was extracted using a commercial kit (Promega) and sent for sequencing (Pac Biosciences technology platform, Menlo Park, CA, USA). The raw data were assembled and polished using Hierarchical Genome Assembly Process 4.0 (HGAP 4.0). The assembled data were structurally predicted using tRNAscan-SE and rnammer. Then, the data were analyzed using Kyoto Encyclopedia of Genes and Genomes (KEGG) database and antiSMASH analysis. Meanwhile, the metabolite profile of SUK 48 was determined using liquid chromatography-mass spectrophotometry (LC-MS) for both negative and positive modes. The results showed that the presence of kanamycin and gentamicin, as well as the other 11 antibiotics. Nevertheless, the biosynthesis pathways of aurantioclavine were also found. The cytotoxicity activity showed IC50 value was at 0.35 ± 1.35 mg/mL on the cell viability of HEK 293. In conclusion, Streptomyces sp. SUK 48 has proven to be a non-toxic antibiotic producer such as auranticlavine and gentamicin.

Genetic interaction analysis in microbial pathogens: unravelling networks of pathogenesis, antimicrobial susceptibility and host interactions

Genetic interaction (GI) analysis is a powerful genetic strategy that analyzes the fitness and phenotypes of single- and double-gene mutant cells in order to dissect the epistatic interactions between genes, categorize genes into biological pathways, and characterize genes of unknown function. GI analysis has been extensively employed in model organisms for foundational, systems-level assessment of the epistatic interactions between genes. More recently, GI analysis has been applied to microbial pathogens and has been instrumental for the study of clinically important infectious organisms. Here, we review recent advances in systems-level GI analysis of diverse microbial pathogens, including bacterial and fungal species. We focus on important applications of GI analysis across pathogens, including GI analysis as a means to decipher complex genetic networks regulating microbial virulence, antimicrobial drug resistance and host-pathogen dynamics, and GI analysis as an approach to uncover novel targets for combination antimicrobial therapeutics. Together, this review bridges our understanding of GI analysis and complex genetic networks, with applications to diverse microbial pathogens, to further our understanding of virulence, the use of antimicrobial therapeutics and host-pathogen interactions. .

Recent Advances in Genome Editing Tools in Medical Mycology Research

Manipulating fungal genomes is an important tool to understand the function of target genes, pathobiology of fungal infections, virulence potential, and pathogenicity of medically important fungi, and to develop novel diagnostics and therapeutic targets. Here, we provide an overview of recent advances in genetic manipulation techniques used in the field of medical mycology. Fungi use several strategies to cope with stress and adapt themselves against environmental effectors. For instance, mutations in the 14 alpha-demethylase gene may result in azole resistance in Aspergillusfumigatus strains and shield them against fungicide's effects. Over the past few decades, several genome editing methods have been introduced for genetic manipulations in pathogenic fungi. Application of restriction enzymes to target and cut a double-stranded DNA in a pre-defined sequence was the first technique used for cloning in Aspergillus and Candida. Genome editing technologies, including zinc-finger nucleases (ZFNs) and transcriptional activator-like effector nucleases (TALENs), have been also used to engineer a double-stranded DNA molecule. As a result, TALENs were considered more practical to identify single nucleotide polymorphisms. Recently, Class 2 type II Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/Cas9 technology has emerged as a more useful tool for genome manipulation in fungal research.

β-Lactams against the Fortress of the Gram-Positive Staphylococcus aureus Bacterium

The biological diversity of the unicellular bacteria-whether assessed by shape, food, metabolism, or ecological niche-surely rivals (if not exceeds) that of the multicellular eukaryotes. The relationship between bacteria whose ecological niche is the eukaryote, and the eukaryote, is often symbiosis or stasis. Some bacteria, however, seek advantage in this relationship. One of the most successful-to the disadvantage of the eukaryote-is the small (less than 1 μm diameter) and nearly spherical Staphylococcus aureus bacterium. For decades, successful clinical control of its infection has been accomplished using β-lactam antibiotics such as the penicillins and the cephalosporins. Over these same decades S. aureus has perfected resistance mechanisms against these antibiotics, which are then countered by new generations of β-lactam structure. This review addresses the current breadth of biochemical and microbiological efforts to preserve the future of the β-lactam antibiotics through a better understanding of how S. aureus protects the enzyme targets of the β-lactams, the penicillin-binding proteins. The penicillin-binding proteins are essential enzyme catalysts for the biosynthesis of the cell wall, and understanding how this cell wall is integrated into the protective cell envelope of the bacterium may identify new antibacterials and new adjuvants that preserve the efficacy of the β-lactams.

Antifungal Drug Resistance: Molecular Mechanisms in Candida albicans and Beyond

Fungal infections are a major contributor to infectious disease-related deaths across the globe. Candida species are among the most common causes of invasive mycotic disease, with Candida albicans reigning as the leading cause of invasive candidiasis. Given that fungi are eukaryotes like their human host, the number of unique molecular targets that can be exploited for antifungal development remains limited. Currently, there are only three major classes of drugs approved for the treatment of invasive mycoses, and the efficacy of these agents is compromised by the development of drug resistance in pathogen populations. Notably, the emergence of additional drug-resistant species, such as Candida auris and Candida glabrata, further threatens the limited armamentarium of antifungals available to treat these serious infections. Here, we describe our current arsenal of antifungals and elaborate on the resistance mechanisms Candida species possess that render them recalcitrant to therapeutic intervention. Finally, we highlight some of the most promising therapeutic strategies that may help combat antifungal resistance, including combination therapy, targeting fungal-virulence traits, and modulating host immunity. Overall, a thorough understanding of the mechanistic principles governing antifungal drug resistance is fundamental for the development of novel therapeutics to combat current and emerging fungal threats.

Emerging peptide antibiotics with therapeutic potential

This review covers some of the recent progress in the field of peptide antibiotics with a focus on compounds with novel or established mode of action and with demonstrated efficacy in animal infection models. Novel drug discovery approaches, linear and macrocyclic peptide antibiotics, lipopeptides like the polymyxins as well as peptides addressing targets located in the plasma membrane or in the outer membrane of bacterial cells are discussed.

Unconventional Antibacterials and Adjuvants

The need for new classes of antibacterials is genuine in light of the dearth of clinical options for the treatment of bacterial infections. The prodigious discoveries of antibiotics during the 1940s to 1970s, a period wistfully referred to as the Golden Age of Antibiotics, have not kept up in the face of emergence of resistant bacteria in the past few decades. There has been a renewed interest in old drugs, the repurposing of the existing antibiotics and pairing of synergistic antibiotics or of an antibiotic with an adjuvant. Notwithstanding, discoveries of novel classes of these life-saving drugs have become increasingly difficult, calling for new paradigms. We describe, herein, three strategies from our laboratories toward discoveries of new antibacterials and adjuvants using computational and multidisciplinary experimental methods. One approach targets penicillin-binding proteins (PBPs), biosynthetic enzymes of cell-wall peptidoglycan, for discoveries of non-β-lactam inhibitors. Oxadiazoles and quinazolinones emerged as two structural classes out of these efforts. Several hundred analogs of these two classes of antibiotics have been synthesized and fully characterized in our laboratories. A second approach ventures into inhibition of allosteric regulation of cell-wall biosynthesis. The mechanistic details of allosteric regulation of PBP2a of Staphylococcus aureus, discovered in our laboratories, is outlined. The allosteric site in this protein is at 60 Å distance to the active site, whereby ligand binding at the former makes access to the latter by the substrate possible. We have documented that both quinazolinones and ceftaroline, a fifth-generation cephalosporin, bind to the allosteric site in manifestation of the antibacterial activity. Attempts at inhibition of the regulatory phosphorylation events identified three classes of antibacterial adjuvants and one class of antibacterials, the picolinamides. The chemical structures for these hits went through diversification by synthesis of hundreds of analogs. These analogs were characterized in various assays for identification of leads with adjuvant and antibacterial activities. Furthermore, we revisited the mechanism of bulgecins, a class of adjuvants discovered and abandoned in the 1980s. These compounds potentiate the activities of β-lactam antibiotics by the formation of bulges at the sites of septum formation during bacterial replication, which are points of structural weakness in the envelope. These bulges experience rupture, which leads to bacterial death. Bulgecin A inhibits the lytic transglycosylase Slt of Pseudomonas aeruginosa as a likely transition-state mimetic for its turnover of the cell-wall peptidoglycan. Once damage to cell wall is inflicted by a β-lactam antibiotic, the function of Slt is to repair the damage. When Slt is inhibited by bulgecin A, the organism cannot cope with it and would undergo rapid lysis. Bulgecin A is an effective adjuvant of β-lactam antibiotics. These discoveries of small-molecule classes of antibacterials or of adjuvants to antibacterials hold promise in strategies for treatment of bacterial infections.

Double Orthogonal Click Reactions for the Development of Antimicrobial Peptide Nanotubes

A new class of amphipathic cyclic peptides, which assemble in bacteria membranes to form polymeric supramolecular nanotubes giving them antimicrobial properties, is described. The method is based on the use of two orthogonal clickable transformations to incorporate different hydrophobic or hydrophilic moieties in a simple, regioselective, and divergent manner. The resulting cationic amphipathic cyclic peptides described in this article exhibit strong antimicrobial properties with a broad therapeutic window. Our studies suggest that the active form is the nanotube resulted from the parallel stacking of the cyclic peptide precursors. Several techniques, CD, FTIR, fluorescence, and STEM, among others, confirm the nanotube formation.

Crystal structures of human NSDHL and development of its novel inhibitor with the potential to suppress EGFR activity

NAD(P)-dependent steroid dehydrogenase-like (NSDHL), an essential enzyme in human cholesterol synthesis and a regulator of epidermal growth factor receptor (EGFR) trafficking pathways, has attracted interest as a therapeutic target due to its crucial relevance to cholesterol-related diseases and carcinomas. However, the development of pharmacological agents for targeting NSDHL has been hindered by the absence of the atomic details of NSDHL. In this study, we reported two X-ray crystal structures of human NSDHL, which revealed a detailed description of the coenzyme-binding site and the unique conformational change upon the binding of a coenzyme. A structure-based virtual screening and biochemical evaluation were performed and identified a novel inhibitor for NSDHL harboring suppressive activity towards EGFR. In EGFR-driven human cancer cells, treatment with the potent NSDHL inhibitor enhanced the antitumor effect of an EGFR kinase inhibitor. Overall, these findings could serve as good platforms for the development of therapeutic agents against NSDHL-related diseases.

Integrative omics analysis reveals relationships of genes with synthetic lethal interactions through a pan-cancer analysis

Synthetic lethality is thought to play an important role in anticancer therapies. Herein, to understand the potential distributions and relationships between synthetic lethal interactions between genes, especially for pairs deriving from different sources, we performed an integrative analysis of genes at multiple molecular levels. Based on inter-species phylogenetic conservation of synthetic lethal interactions, gene pairs from yeast and humans were analyzed; a total of 37,588 candidate gene pairs containing 7,816 genes were collected. Of these, 49.74% of genes had 2–10 interactions, 22.93% were involved in hallmarks of cancer, and 21.61% were identified as core essential genes. Many genes were shown to have important biological roles via functional enrichment analysis, and 65 were identified as potentially crucial in the pathophysiology of cancer. Gene pairs with dysregulated expression patterns had higher prognostic values. Further screening based on mutation and expression levels showed that remaining gene pairs were mainly derived from human predicted or validated pairs, while most predicted pairs from yeast were filtered from analysis. Genes with synthetic lethality were further analyzed with their interactive microRNAs (miRNAs) at the isomiR level which have been widely studied as negatively regulatory molecules. The miRNA–mRNA interaction network revealed that many synthetic lethal genes contributed to the cell cycle (seven of 12 genes), cancer pathways (five of 12 genes), oocyte meiosis, the p53 signaling pathway, and hallmarks of cancer. Our study contributes to the understanding of synthetic lethal interactions and promotes the application of genetic interactions in further cancer precision medicine.

Advances in fungal chemical genomics for the discovery of new antifungal agents

Invasive fungal infections have escalated from a rare curiosity to a major cause of human mortality around the globe. This is in part due to a scarcity in the number of antifungal drugs available to combat mycotic disease, making the discovery of novel bioactive compounds and determining their mode of action of utmost importance. The development and application of chemical genomic assays using the model yeast Saccharomyces cerevisiae has provided powerful methods to identify the mechanism of action of diverse molecules in a living cell. Furthermore, complementary assays are continually being developed in fungal pathogens, most notably Candida albicans and Cryptococcus neoformans, to elucidate compound mechanism of action directly in the pathogen of interest. Collectively, the suite of chemical genetic assays that have been developed in multiple fungal species enables the identification of candidate drug target genes, as well as genes involved in buffering drug target pathways, and genes involved in general cellular responses to small molecules. In this review, we examine current yeast chemical genomic assays and highlight how such resources provide powerful tools that can be utilized to bolster the antifungal pipeline.

Mimicry of a Non-ribosomally Produced Antimicrobial, Brevicidine, by Ribosomal Synthesis and Post-translational Modification

The group of bacterial non-ribosomally produced peptides (NRPs) forms a rich source of antibiotics, such as daptomycin, vancomycin, and teixobactin. The difficulty of functionally expressing and engineering the corresponding large biosynthetic complexes is a bottleneck in developing variants of such peptides. Here, we apply a strategy to synthesize mimics of the recently discovered antimicrobial NRP brevicidine. We mimicked the molecular structure of brevicidine by ribosomally synthesized, post-translationally modified peptide (RiPP) synthesis, introducing several relevant modifications, such as dehydration and thioether ring formation. Following this strategy, in two rounds peptides were engineered in vivo, which showed antibacterial activity against Gram-negative pathogenic bacteria susceptible to wild-type brevicidine. This study demonstrates the feasibility of a strategy to structurally and functionally mimic NRPs by employing the synthesis and post-translational modifications typical for RiPPs. This enables the future generation of large genetically encoded peptide libraries of NRP-mimicking structures to screen for antimicrobial activity against relevant pathogens.

Predicting drug synergy for precision medicine using network biology and machine learning

Identification of effective drug combinations for patients is an expensive and time-consuming procedure, especially for in vitro experiments. To accelerate the synergistic drug discovery process, we present a new classification model to identify more effective anti-cancer drug pairs using in silico network biology approach. Based on the hypotheses that the drug synergy comes from the collective effects on the biological network, therefore, we developed six network biology features, including overlap and distance of drug perturbation network, that were derived by using individual drug-perturbed transcriptome profiles and the relevant biological network analysis. Using publicly available drug synergy databases and three machine-learning (ML) methods, the model was trained to discriminate the positive (synergistic) and negative (nonsynergistic) drug combinations. The proposed models were evaluated on the test cases to predict the most promising network biology feature, which is the network degree activity, i.e. the synergistic effect between drug pairs is mainly accounted by the complementary signaling pathways or molecular networks from two drugs.

Supramolecular Assemblies of Heterogeneous Mesoporous Silica Nanoparticles to Co-deliver Antimicrobial Peptides and Antibiotics for Synergistic Eradication of Pathogenic Biofilms

Pathogenic biofilms protected by extracellular polymeric substances frequently compromise the efficiency of antibacterial drugs and severely threaten human health. In this study, we designed a multi-stimuli-responsive magnetic supramolecular nanoplatform to co-deliver large and low molecular weight drugs for synergistic eradication of pathogenic biofilms. This co-delivery platform was composed of mesoporous silica nanoparticles (MSNs) with large pores (MSNLP) capped by β-cyclodextrin (β-CD)-modified polyethylenimine (PEICD) and adamantane (ADA)-decorated MSNs containing a magnetic core (MagNP@MSNA) capped by cucurbit[6]uril (CB[6]). The host MSNs (H, MSNLP@PEICD) and the guest MSNs (G, MagNP@MSNA-CB[6]) spontaneously form coassemblies (H+G), based on the host-guest interactions between β-CD and ADA. Under the stimulus of pathogen cells together with heating by an alternating magnetic field (AMF), the supramolecular coassemblies released both the large molecular weight antimicrobial peptide melittin (MEL) and the low molecular weight antibiotic ofloxacin (OFL) with high efficiency. As compared to free drugs (MEL and OFL) or unattached MSNs (H or G), the drug-loading H+G coassemblies (H-MEL+G-OFL) exhibited much higher capacity for biofilm eradication, thoroughly removing biofilm biomass and killing the pathogenic cells, and displaying no obvious toxicity to mammalian cells. This strong antibiofilm capacity was severely decreased when the host and guest components were prevented from coassembling but administered simultaneously, revealing the critical role of the supramolecular assembly in biofilm removal. Moreover, an in vivo implantation model showed that the coassemblies eradicated the pathogenic biofilms from the implants, preventing host tissue damage and inflammation. Therefore, the co-delivering and multi-stimuli-responsive nanocarriers could overcome the anti-infection difficulties during treatment of infections because of protective biofilms.

L-lysine potentiates aminoglycosides against Acinetobacter baumannii via regulation of proton motive force and antibiotics uptake

Acinetobacter baumannii, a Gram-negative opportunistic pathogen, is a leading cause of hospital- and community-acquired infections. Acinetobacter baumannii can rapidly acquire diverse resistance mechanisms and undergo genetic modifications that confer resistance and persistence to all currently used clinical antibiotics. In this study, we found exogenous L-lysine sensitizes Acinetobacter baumannii, other Gram-negative bacteria (Escherichia coli and Klebsiella pneumoniae) and a Gram-positive bacterium (Mycobacterium smegmatis) to aminoglycosides. Importantly, the combination of L-lysine with aminoglycosides killed clinically isolated multidrug-resistant Acinetobacter baumannii and persister cells. The exogenous L-lysine can increase proton motive force via transmembrane chemical gradient, resulting in aminoglycoside acumination that further accounts for reactive oxygen species production. The combination of L-lysine and antibiotics highlights a promising strategy against bacterial infection.

Constructing and deconstructing the bacterial cell wall

The history of modern medicine cannot be written apart from the history of the antibiotics. Antibiotics are cytotoxic secondary metabolites that are isolated from Nature. The antibacterial antibiotics disproportionately target bacterial protein structure that is distinct from eukaryotic protein structure, notably within the ribosome and within the pathways for bacterial cell-wall biosynthesis (for which there is not a eukaryotic counterpart). This review focuses on a pre-eminent class of antibiotics-the β-lactams, exemplified by the penicillins and cephalosporins-from the perspective of the evolving mechanisms for bacterial resistance. The mechanism of action of the β-lactams is bacterial cell-wall destruction. In the monoderm (single membrane, Gram-positive staining) pathogen Staphylococcus aureus the dominant resistance mechanism is expression of a β-lactam-unreactive transpeptidase enzyme that functions in cell-wall construction. In the diderm (dual membrane, Gram-negative staining) pathogen Pseudomonas aeruginosa a dominant resistance mechanism (among several) is expression of a hydrolytic enzyme that destroys the critical β-lactam ring of the antibiotic. The key sensing mechanism used by P. aeruginosa is monitoring the molecular difference between cell-wall construction and cell-wall deconstruction. In both bacteria, the resistance pathways are manifested only when the bacteria detect the presence of β-lactams. This review summarizes how the β-lactams are sensed and how the resistance mechanisms are manifested, with the expectation that preventing these processes will be critical to future chemotherapeutic control of multidrug resistant bacteria.

Screening and identification of genes associated with cell proliferation in cholangiocarcinoma

Cholangiocarcinoma (CCA), an aggressive tumor with poor prognosis, is a malignant cancer with increasing incidence and mortality rates. It is important to survey crucial genes in CCA to find and design potential drug targets, especially for those genes associated with cell proliferation that is a key biological process in tumorgenesis. Herein, we surveyed genes associated with cell proliferation via a comprehensive pan-cancer analysis. Candidate genes were further analyzed using multiple approaches, including cross-analysis from diverse molecular levels, examination of potential function and interactions, and additional experimental validation. We primarily screened 15 potential genes based on 11 validated genes, and these 26 genes were further examined to delineate their biological functions and potential roles in cancer treatment. Several of them were involved synthetically lethal genetic interactions, especially for RECQL4, TOP2A, MKI67 and ASPM, indicating their potential roles in drug design and cancer treatment. Further experimental validation indicated that some genes were significantly upregulated in several cancer cell lines, implying their important roles in tumorigenesis. Our study identifies some genes associated with cell proliferation, which may be potential future targets in molecular targeted therapy.

In vitro activity of meropenem/piperacillin/tazobactam triple combination therapy against clinical isolates of Staphylococcus aureus, Staphylococcus epidermidis, Staphylococcus pseudintermedius and vancomycin-resistant Enterococcus spp

OBJECTIVES

To evaluate the activity of the reported synergistic and collaterally sensitive antibiotic combination, meropenem/piperacillin/tazobactam (ME/PI/TZ), against a panel of methicillin-resistant Staphylococcus aureus (MRSA) and other methicillin-resistant Staphylococcus species; and to investigate the relationship between ME/PI/TZ susceptibility and the genomic background of clinical isolates of MRSA.

METHODS

ME/PI/TZ combination and single drug minimum inhibitory concentrations (MICs) were determined for 207 strains (including 121 MRSA, 4 methicillin-sensitive S. aureus [MSSA], 37 vancomycin-intermediate S. aureus [VISA], 6 ceftaroline non-susceptible MRSA, 29 coagulase-negative staphylococci [CoNS], 5 S. pseudointermedius and 5 vancomycin-resistant Enterococci [VRE]) by broth microdilution. Whole genomes of 168 S. aureus strains were sequenced, assembled, and comparatively analysed.

RESULTS

USA300-SCCmec type IV isolates, clonal complex 8 (CC8)-MRSA isolates, including some VISA and ceftaroline (CPT)-intermediate strains, and all tested methicillin-resistant S. epidermidis isolates were highly susceptible to ME/PI/TZ. Isolates with elevated MICs (MICs of >16/16/16 mg/L) clustered with the USA100-SCCmec type II strain. Susceptibility of MRSA to ME/PI/TZ was correlated with susceptibility to ME. No obvious cross-resistance to CPT was observed among high-ME/PI/TZ MIC isolates.

CONCLUSIONS

The ME/PI/TZ combination is effective against a variety of clinical MRSA isolates, particularly of the USA300 lineage, which is expanding worldwide. ME/PI/TZ is also effective against drug-resistant CoNS and S. pseudintermedius clinical isolates.

Challenges and strategies in drug delivery systems for treatment of pulmonary infections

Inhalation therapy has been reported as the most effective treatment for respiratory bacterial infections due to the increasing relevance of drug bioavailability. Drug delivery systems (DDS) have the capacity to overcome pulmonary biological barriers limiting the bioavailability of inhaled anti-infectives. This is important to eradicate bacterial infections and to prevent the development of bacterial resistance. Despite substantial efforts in the field, the current state-of-the-art often fails to achieve those goals, and we still observe increasing bacterial resistance. We give a brief insight on benefits and challenges in pulmonary delivery of anti-infectives. In the context of drug delivery development for pulmonary infections, particularly focusing on Pseudomonas aeruginosa (PA) infections, this mini review will critically discuss the main requirements, as well as the recent strategies of drug delivery system synthesis and preparation. Finally, interaction of DDS with crucial pulmonary biological barriers will be of great importance for the success of future applications of the developed DDS.

Systems Pharmacology for Investigation of the Mechanisms of Action of Traditional Chinese Medicine in Drug Discovery

As a traditional medical intervention in Asia and a complementary and alternative medicine in western countries, traditional Chinese medicine (TCM) has attracted global attention in the life science field. TCM provides extensive natural resources for medicinal compounds, and these resources are generally regarded as effective and safe for use in drug discovery. However, owing to the complexity of compounds and their related multiple targets of TCM, it remains difficult to dissect the mechanisms of action of herbal medicines at a holistic level. To solve the issue, in the review, we proposed a novel approach of systems pharmacology to identify the bioactive compounds, predict their related targets, and illustrate the molecular mechanisms of action of TCM. With a predominant focus on the mechanisms of actions of TCM, we also highlighted the application of the systems pharmacology approach for the prediction of drug combination and dynamic analysis, the synergistic effects of TCMs, formula dissection, and theory analysis. In summary, the systems pharmacology method contributes to understand the complex interactions among biological systems, drugs, and complex diseases from a network perspective. Consequently, systems pharmacology provides a novel approach to promote drug discovery in a precise manner and a systems level, thus facilitating the modernization of TCM.

Prediction of drug synergy score using ensemble based differential evolution

Prediction of drug synergy score is an ill-posed problem. It plays an efficient role in the medical field for inhibiting specific cancer agents. An efficient regression-based machine learning technique has an ability to minimise the drug synergy prediction errors. Therefore, in this study, an efficient machine learning technique for drug synergy prediction technique is designed by using ensemble based differential evolution (DE) for optimising the support vector machine (SVM). Because the tuning of the attributes of SVM kernel regulates the prediction precision. The ensemble based DE employs two trial vector generation techniques and two control attributes settings. The initial generation technique has the best solution and the other is without the best solution. The proposed and existing competitive machine learning techniques are applied to drug synergy data. The extensive analysis demonstrates that the proposed technique outperforms others in terms of accuracy, root mean square error and coefficient of correlation.

Drug combinations: a strategy to extend the life of antibiotics in the 21st century

Antimicrobial resistance threatens a resurgence of life-threatening bacterial infections and the potential demise of many aspects of modern medicine. Despite intensive drug discovery efforts, no new classes of antibiotics have been developed into new medicines for decades, in large part owing to the stringent chemical, biological and pharmacological requisites for effective antibiotic drugs. Combinations of antibiotics and of antibiotics with non-antibiotic activity-enhancing compounds offer a productive strategy to address the widespread emergence of antibiotic-resistant strains. In this Review, we outline a theoretical and practical framework for the development of effective antibiotic combinations.

Use of genetic and chemical synthetic lethality as probes of complexity in bacterial cell systems

Different conditions and genomic contexts are known to have an impact on gene essentiality and interactions. Synthetic lethal interactions occur when a combination of perturbations, either genetic or chemical, result in a more profound fitness defect than expected based on the effect of each perturbation alone. Synthetic lethality in bacterial systems has long been studied; however, during the past decade, the emerging fields of genomics and chemical genomics have led to an increase in the scale and throughput of these studies. Here, we review the concepts of genomics and chemical genomics in the context of synthetic lethality and their revolutionary roles in uncovering novel biology such as the characterization of genes of unknown function and in antibacterial drug discovery. We provide an overview of the methodologies, examples and challenges of both genetic and chemical synthetic lethal screening platforms. Finally, we discuss how to apply genetic and chemical synthetic lethal approaches to rationalize the synergies of drugs, screen for new and improved antibacterial therapies and predict drug mechanism of action.