Design of high-order antibiotic combinations against M. tuberculosis by ranking and exclusion

Isoniazid potentiates tigecycline to kill methicillin-resistant Staphylococcus aureus

Therapeutic option for treating methicillin-resistant Staphylococcus aureus (MRSA) infection is urgently required since its resistance to a broad spectrum of currently available antibiotics. Here, we report that isoniazid is able to potentiate the killing efficacy of tigecycline to MRSA. The combination of isoniazid and tigecycline reduces the minimal inhibitory concentration of clinic MRSA strains to tigecycline. The killing activity of tigecycline is further confirmed by killing experiments and murine infection model. We further demonstrate the mechanism that isoniazid increases intracellular accumulation of tigecycline by promoting the influx but limiting the efflux of tigecycline through proton motive force. We also show that isoniazid and tigecycline synergize to increase the abundance of isoniazid-NAD adduct, which in turn damage cell membrane, possibly contributing to the disruption of PMF. Whereas phosphatidylethanolamine and cardiolipin are able to abrogate the synergistic effect of isoniazid plus tigecycline. Thus our study provides a new perspective that antibiotics, e.g. isoniazid, once recognized only to target Mycobacterium tuberculosis, can be repurposed as antibiotic adjuvant to tigecycline, expanding our choice of antibiotic-antibiotic combinations in treating bacterial infectious diseases.

Identification of gene targets that potentiate the action of rifampicin on Mycobacterium bovis BCG

Tuberculosis (TB) caused by bacteria of the Mycobacterium tuberculosis complex remains one of the most important infectious diseases of mankind. Rifampicin is a first line drug used in multi-drug treatment of TB, however, the necessary duration of treatment with these drugs is long and development of resistance is an increasing impediment to treatment programmes. As a result, there is a requirement for research and development of new TB drugs, which can form the basis of new drug combinations, either due to their own anti-mycobacterial activity or by augmenting the activity of existing drugs such as rifampicin. This study describes a TnSeq analysis to identify mutants with enhanced sensitivity to sub-minimum inhibitory concentrations (MIC) of rifampicin. The rifampicin-sensitive mutants were disrupted in genes of a variety of functions and the majority fitted into three thematic groups: firstly, genes that were involved in DNA/RNA metabolism, secondly, genes involved in sensing and regulating mycobacterial cellular systems, and thirdly, genes involved in the synthesis and maintenance of the cell wall. Selection at two concentrations of rifampicin (1/250 and 1/62 MIC) demonstrated a dose response for mutants with statistically significant sensitivity to rifampicin. The dataset reveals mechanisms of how mycobacteria are innately tolerant to and initiate an adaptive response to rifampicin; providing putative targets for the development of adjunctive therapies that potentiate the action of rifampicin.

Morpholinium-based Ionic Liquids as Potent Antibiofilm and Sensitizing Agents for the Control of Pseudomonas aeruginosa

Rising antimicrobial resistance is a critical threat to worldwide public health. To address the increasing antibiotic tolerance, diverse antimicrobial agents are examined for their ability to decrease bacterial resistance. One of the most relevant and persistent human pathogens is Pseudomonas aeruginosa. Our study investigates the anti-biofilm and sensitizing activity of 12 morpholinium-based ionic liquids with herbicidal anions on four clinically relevant P. aeruginosa strains. Among all tested compounds, four ionic liquids prevented biofilm formation at sub-minimum inhibitory concentrations for all investigated strains. For the first time, we established a hormetic effect on biofilm formation for P. aeruginosa strains subjected to an ionic liquid treatment. Interestingly, while ionic liquids with 4,4-didecylmorpholinium [Dec2Mor]+ are more efficient against planktonic bacteria, 4-decyl-4-ethylmorpholinium [DecEtMor]+ showed more potent inhibition of biofilm formation. Ionic liquids with 4,4-didecylmorpholinium ([Dec2Mor]+) cations even induced biofilm formation by strain 39016 at high concentrations due to flocculation. Morpholinium-based ionic liquids were also shown to enhance the efficacy of commonly used antibiotics from different chemical groups. We demonstrate that this synergy is associated with the mode of action of the antibiotics.

A host-directed oxadiazole compound potentiates antituberculosis treatment via zinc poisoning in human macrophages and in a mouse model of infection

Antituberculosis drugs, mostly developed over 60 years ago, combined with a poorly effective vaccine, have failed to eradicate tuberculosis. More worryingly, multiresistant strains of Mycobacterium tuberculosis (MTB) are constantly emerging. Innovative strategies are thus urgently needed to improve tuberculosis treatment. Recently, host-directed therapy has emerged as a promising strategy to be used in adjunct with existing or future antibiotics, by improving innate immunity or limiting immunopathology. Here, using high-content imaging, we identified novel 1,2,4-oxadiazole-based compounds, which allow human macrophages to control MTB replication. Genome-wide gene expression analysis revealed that these molecules induced zinc remobilization inside cells, resulting in bacterial zinc intoxication. More importantly, we also demonstrated that, upon treatment with these novel compounds, MTB became even more sensitive to antituberculosis drugs, in vitro and in vivo, in a mouse model of tuberculosis. Manipulation of heavy metal homeostasis holds thus great promise to be exploited to develop host-directed therapeutic interventions.

Spermine enhances the activity of anti-tuberculosis drugs

IMPORTANCE

This is the first study that attempted to demonstrate the mechanisms of reactive oxygen species (ROS) generation by spermine (Spm) in Mycobacterium tuberculosis (M.tb). Furthermore, this is the first study to demonstrate that it is able to enhance the activity of currently available and World Health Organization (WHO)-approved tuberculosis (TB) drugs. Spermine can easily be obtained since it is already found in our diet. Moreover, as opposed to conventional antibiotics, it is less toxic to humans since it is found in millimolar concentrations in the body. Finally, with the difficulty of curing TB with conventional antibiotics, this study suggests that less toxic molecules, such as Spm, could in a long-term perspective be incorporated in a TB regimen to boost the treatment.

Developing synergistic drug combinations to restore antibiotic sensitivity in drug-resistant Mycobacterium tuberculosis

Tuberculosis (TB) is a leading global cause of mortality owing to an infectious agent, accounting for almost one-third of antimicrobial resistance (AMR) deaths annually. We aimed to identify synergistic anti-TB drug combinations with the capacity to restore therapeutic efficacy against drug-resistant mutants of the causative agent, Mycobacterium tuberculosis We investigated combinations containing the known translational inhibitors, spectinomycin (SPT) and fusidic acid (FA), or the phenothiazine, chlorpromazine (CPZ), which disrupts mycobacterial energy metabolism. Potentiation of whole-cell drug efficacy was observed in SPT-CPZ combinations. This effect was lost against an M. tuberculosis mutant lacking the major facilitator superfamily (MFS) efflux pump, Rv1258c. Notably, the SPT-CPZ combination partially restored SPT efficacy against an SPT-resistant mutant carrying a g1379t point mutation in rrs, encoding the mycobacterial 16S ribosomal RNA. Combinations of SPT with FA, which targets the mycobacterial elongation factor G, exhibited potentiating activity against wild-type M. tuberculosis Moreover, this combination produced a modest potentiating effect against both FA-monoresistant and SPT-monoresistant mutants. Finally, combining SPT with the frontline anti-TB agents, rifampicin (RIF) and isoniazid, resulted in enhanced activity in vitro and ex vivo against both drug-susceptible M. tuberculosis and a RIF-monoresistant rpoB S531L mutant.These results support the utility of novel potentiating drug combinations in restoring antibiotic susceptibility of M. tuberculosis strains carrying genetic resistance to any one of the partner compounds.

Antibiotic combinations reduce Staphylococcus aureus clearance

The spread of antibiotic resistance is attracting increased attention to combination-based treatments. Although drug combinations have been studied extensively for their effects on bacterial growth^1–11, much less is known about their effects on bacterial long-term clearance, especially at cidal, clinically relevant concentrations^12–14. Here, using en masse microplating and automated image analysis, we systematically quantify Staphylococcus aureus survival during prolonged exposure to pairwise and higher-order cidal drug combinations. By quantifying growth inhibition, early killing and longer-term population clearance by all pairs of 14 antibiotics, we find that clearance interactions are qualitatively different, often showing reciprocal suppression whereby the efficacy of the drug mixture is weaker than any of the individual drugs alone. Furthermore, in contrast to growth inhibition^6–10 and early killing, clearance efficacy decreases rather than increases as more drugs are added. However, specific drugs targeting non-growing persisters^15–17 circumvent these suppressive effects. Competition experiments show that reciprocal suppressive drug combinations select against resistance to any of the individual drugs, even counteracting methicillin-resistant Staphylococcus aureus both in vitro and in a Galleria mellonella larva model. As a consequence, adding a β-lactamase inhibitor that is commonly used to potentiate treatment against β-lactam-resistant strains can reduce rather than increase treatment efficacy. Together, these results underscore the importance of systematic mapping the long-term clearance efficacy of drug combinations for designing more-effective, resistance-proof multidrug regimes.

Different pairs of antibiotics show qualitatively different bacterial clearance interactions—some pairs show reciprocal suppression whereby the drug mixture efficacy is weaker than the individual drugs alone, and the clearance efficacy decreases as more drugs are added.

Identification of Drug Combination Therapies for SARS-CoV-2: A Molecular Dynamics Simulations Approach

Purpose

The development of effective treatments for coronavirus infectious disease 19 (COVID-19) caused by SARS-Coronavirus-2 was hindered by the little data available about this virus at the start of the pandemic. Drug repurposing provides a good strategy to explore approved drugs' possible SARS-CoV-2 antiviral activity. Moreover, drug synergism is essential in antiviral treatment due to improved efficacy and reduced toxicity. In this work, we studied the effect of approved and investigational drugs on one of SARS-CoV-2 essential proteins, the main protease (Mpro), in search of antiviral treatments and/or drug combinations.

Methods

Different possible druggable sites of Mpro were identified and screened against an in-house library of more than 4000 chemical compounds. Molecular dynamics simulations were carried out to explore conformational changes induced by different ligands' binding. Subsequently, the inhibitory effect of the identified compounds and the suggested drug combinations on the Mpro were established using a 3CL protease (SARS-CoV-2) assay kit.

Results

Three potential inhibitors in three different binding sites were identified; favipiravir, cefixime, and carvedilol. Molecular dynamics simulations predicted the synergistic effect of two drug combinations: favipiravir/cefixime, and favipiravir/carvedilol. The in vitro inhibitory effect of the predicted drug combinations was established on this enzyme.

Conclusion

In this work, we could study one of the promising SARS-CoV-2 viral protein targets in searching for treatments for COVID-19. The inhibitory effect of several drugs on Mpro was established in silico and in vitro assays. Molecular dynamics simulations showed promising results in predicting the synergistic effect of drug combinations.

Sample-efficient identification of high-dimensional antibiotic synergy with a normalized diagonal sampling design

Antibiotic resistance is an important public health problem. One potential solution is the development of synergistic antibiotic combinations, in which the combination is more effective than the component drugs. However, experimental progress in this direction is severely limited by the number of samples required to exhaustively test for synergy, which grows exponentially with the number of drugs combined. We introduce a new metric for antibiotic synergy, motivated by the popular Fractional Inhibitory Concentration Index and the Highest Single Agent model. We also propose a new experimental design that samples along all appropriately normalized diagonals in concentration space, and prove that this design identifies all synergies among a set of drugs while only sampling a small fraction of the possible combinations. We applied our method to screen two- through eight-way combinations of eight antibiotics at 10 concentrations each, which requires sampling only 2,560 unique combinations of antibiotic concentrations.

Antibiotic resistance is a growing public health concern, and there is an increasing need for methods to combat it. One potential approach is the development of synergistic antibiotic combinations, in which a mixture of drugs is more effective than any individual component. Unfortunately, the search for clinically beneficial drug combinations is severely restricted by the pace at which drugs can be screened. To date, most studies of combination therapies have been limited to testing only pairs or triples of drugs. These studies have identified primarily antagonistic drug interactions, in which the combination is less effective than the individual components. There is an acute need for methodologies that enable screening of higher-order drug combinations, both to identify synergies among many drugs and to understand the behavior of higher-order combinations. In this work we introduce a new paradigm for combination testing, the normalized diagonal sampling design, that makes identifying interactions among eight or more drugs feasible for the first time. Screening d drugs at m different combinations requires m ⋅ 2^d samples under our design as opposed to m^d under exhaustive screening, while provably identifying all synergies under mild assumptions about antibiotic behavior. Scientists can use our design to quickly screen for antibiotic interactions, accelerating the pace of combination therapy development.

Pre-Clinical Tools for Predicting Drug Efficacy in Treatment of Tuberculosis

Combination therapy has, to some extent, been successful in limiting the emergence of drug-resistant tuberculosis. Drug combinations achieve this advantage by simultaneously acting on different targets and metabolic pathways. Additionally, drug combination therapies are shown to shorten the duration of therapy for tuberculosis. As new drugs are being developed, to overcome the challenge of finding new and effective drug combinations, systems biology commonly uses approaches that analyse mycobacterial cellular processes. These approaches identify the regulatory networks, metabolic pathways, and signaling programs associated with M. tuberculosis infection and survival. Different preclinical models that assess anti-tuberculosis drug activity are available, but the combination of models that is most predictive of clinical treatment efficacy remains unclear. In this structured literature review, we appraise the options to accelerate the TB drug development pipeline through the evaluation of preclinical testing assays of drug combinations.

Impact of Simulated Intestinal Fluids on Dissolution, Solution Chemistry, and Membrane Transport of Amorphous Multidrug Formulations

The solution behavior and membrane transport of multidrug formulations were herein investigated in a biorelevant medium simulating fasted conditions. Amorphous multidrug formulations were prepared by the solvent evaporation method. Combinations of atazanavir (ATV) and ritonavir (RTV) and felodipine (FDN) and indapamide (IPM) were prepared and stabilized by a polymer for studying their dissolution (under non-sink conditions) and membrane transport in fasted state simulated intestinal fluid (FaSSIF). The micellar solubilization by FaSSIF enhanced the amorphous solubility of the drugs to different extents. Similar to buffer, the maximum achievable concentration of drugs in combination was reduced in FaSSIF, but the extent of reduction was affected by the degree of FaSSIF solubilization. Dissolution studies of ATV and IPM revealed that the amorphous solubility of these two drugs was not affected by FaSSIF solubilization. In contrast, RTV was significantly affected by FaSSIF solubilization with a 30% reduction in the maximum achievable concentration upon combination to ATV, compared to 50% reduction in buffer. This positive deviation by FaSSIF solubilization was not reflected in the mass transport–time profiles. Interestingly, FDN concentrations remain constant until the amount of IPM added was over 1000 μg/mL. No decrease in the membrane transport of FDN was observed for a 1:1 M ratio of FDN-IPM combination. This study demonstrates the importance of studying amorphous multidrug formulations under physiologically relevant conditions to obtain insights into the performance of these formulations after oral administration.

[Mechanisms underlying chronic fatigue, a symptom too often overlooked]

Acute fatigue after exertion, like acute inflammation after injury, is useful for our body. On the contrary, both chronic fatigue and chronic inflammation are deleterious, and they are associated in many diseases. In this first part, we will analyze different immune phenomena (bystander activation, memory of the innate immune system, link with the intestinal microbiota) involved in triggering chronic inflammation. This review aims at looking for links between different signs and symptoms associated with chronic fatigue, as well as between different diseases in which severe chronic fatigue can manifest. Possible underlying mechanisms for these phenomena are discussed. This is a proposal made by a researcher, with no clinical experience, to doctors confronted with an entity that is still largely mysterious. The link between chronic inflammation, neuroinflammation and fatigue will be examined in a second part.

Deep learning identifies synergistic drug combinations for treating COVID-19

Effective treatments for COVID-19 are urgently needed. However, discovering single-agent therapies with activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been challenging. Combination therapies play an important role in antiviral therapies, due to their improved efficacy and reduced toxicity. Recent approaches have applied deep learning to identify synergistic drug combinations for diseases with vast preexisting datasets, but these are not applicable to new diseases with limited combination data, such as COVID-19. Given that drug synergy often occurs through inhibition of discrete biological targets, here we propose a neural network architecture that jointly learns drug-target interaction and drug-drug synergy. The model consists of two parts: a drug-target interaction module and a target-disease association module. This design enables the model to utilize drug-target interaction data and single-agent antiviral activity data, in addition to available drug-drug combination datasets, which may be small in nature. By incorporating additional biological information, our model performs significantly better in synergy prediction accuracy than previous methods with limited drug combination training data. We empirically validated our model predictions and discovered two drug combinations, remdesivir and reserpine as well as remdesivir and IQ-1S, which display strong antiviral SARS-CoV-2 synergy in vitro. Our approach, which was applied here to address the urgent threat of COVID-19, can be readily extended to other diseases for which a dearth of chemical-chemical combination data exists.

A novel, multitargeted endogenous metabolic modulator composition impacts metabolism, inflammation, and fibrosis in nonalcoholic steatohepatitis-relevant primary human cell models

Nonalcoholic steatohepatitis (NASH) is a complex metabolic disease of heterogeneous and multifactorial pathogenesis that may benefit from coordinated multitargeted interventions. Endogenous metabolic modulators (EMMs) encompass a broad set of molecular families, including amino acids and related metabolites and precursors. EMMs often serve as master regulators and signaling agents for metabolic pathways throughout the body and hold the potential to impact a complex metabolic disease like NASH by targeting a multitude of pathologically relevant biologies. Here, we describe a study of a novel EMM composition comprising five amino acids and an amino acid derivative (Leucine, Isoleucine, Valine, Arginine, Glutamine, and N-acetylcysteine [LIVRQNac]) and its systematic evaluation across multiple NASH-relevant primary human cell model systems, including hepatocytes, macrophages, and stellate cells. In these model systems, LIVRQNac consistently and simultaneously impacted biology associated with all three core pathophysiological features of NASH—metabolic, inflammatory, and fibrotic. Importantly, it was observed that while the individual constituent amino acids in LIVRQNac can impact specific NASH-related phenotypes in select cell systems, the complete combination was necessary to impact the range of disease-associated drivers examined. These findings highlight the potential of specific and potent multitargeted amino acid combinations for the treatment of NASH.

Perspectives for systems biology in the management of tuberculosis

Standardised management of tuberculosis may soon be replaced by individualised, precision medicine-guided therapies informed with knowledge provided by the field of systems biology. Systems biology is a rapidly expanding field of computational and mathematical analysis and modelling of complex biological systems that can provide insights into mechanisms underlying tuberculosis, identify novel biomarkers, and help to optimise prevention, diagnosis and treatment of disease. These advances are critically important in the context of the evolving epidemic of drug-resistant tuberculosis. Here, we review the available evidence on the role of systems biology approaches - human and mycobacterial genomics and transcriptomics, proteomics, lipidomics/metabolomics, immunophenotyping, systems pharmacology and gut microbiomes - in the management of tuberculosis including prediction of risk for disease progression, severity of mycobacterial virulence and drug resistance, adverse events, comorbidities, response to therapy and treatment outcomes. Application of the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach demonstrated that at present most of the studies provide "very low" certainty of evidence for answering clinically relevant questions. Further studies in large prospective cohorts of patients, including randomised clinical trials, are necessary to assess the applicability of the findings in tuberculosis prevention and more efficient clinical management of patients.

Patient-tailored design for selective co-inhibition of leukemic cell subpopulations

The extensive drug resistance requires rational approaches to design personalized combinatorial treatments that exploit patient-specific therapeutic vulnerabilities to selectively target disease-driving cell subpopulations. To solve the combinatorial explosion challenge, we implemented an effective machine learning approach that prioritizes patient-customized drug combinations with a desired synergy-efficacy-toxicity balance by combining single-cell RNA sequencing with ex vivo single-agent testing in scarce patient-derived primary cells. When applied to two diagnostic and two refractory acute myeloid leukemia (AML) patient cases, each with a different genetic background, we accurately predicted patient-specific combinations that not only resulted in synergistic cancer cell co-inhibition but also were capable of targeting specific AML cell subpopulations that emerge in differing stages of disease pathogenesis or treatment regimens. Our functional precision oncology approach provides an unbiased means for systematic identification of personalized combinatorial regimens that selectively co-inhibit leukemic cells while avoiding inhibition of nonmalignant cells, thereby increasing their likelihood for clinical translation.

Insights into Dissolution and Solution Chemistry of Multidrug Formulations of Antihypertensive Drugs

Using fixed dose combinations of drugs instead of administering drugs separately can be beneficial for both patients and the health care system, but the current understanding of how multidrug formulations work at the molecular level is still in its infancy. Here, we explore dissolution, solubility, and supersaturation of various drug combinations in amorphous formulations. The effect of chemical structural similarity on combination behavior was investigated by using structurally related compounds of both drugs. The effect of polymer type on solution behavior was also evaluated using chemically diverse polymers. Indapamide (IPM) concentration decreased when combined with felodipine (FDN) or its analogues, which occurred even when the IPM solution was undersaturated. The extent of solubility decrease of FDN was less than that of IPM from the dissolution of an equimolar formulation of the drugs. No significant solubility decrease was observed for FDN at low contents of IPM which was also observed for other dihydropyridines, whereas FDN decreases at high contents of IPM. This was explained by the complex nature of the colloidal precipitates of the combinations which impacts the chemical potential of the drugs in solution at different levels. The maximum achievable concentration of FDN and IPM during dissolution of the polyvinylpyrrolidone-based amorphous solid dispersion was higher than the value measured with the hydroxypropyl methylcellulose acetate succinate-based formulation. This emphasizes the significance of molecular properties and chemical diversity of drugs and polymers on solution chemistry and solubility profiles. These findings may apply to drugs administered as a single dosage form or in separate dosage forms and hence need to be well controlled to assure effective treatments and patient safety.

Guided screen for synergistic three-drug combinations

Combinations of three or more drugs are routinely used in various medical fields such as clinical oncology and infectious diseases to prevent resistance or to achieve synergistic therapeutic benefits. The very large number of possible high-order drug combinations presents a formidable challenge for discovering synergistic drug combinations. Here, we establish a guided screen to discover synergistic three-drug combinations. Using traditional checkerboard and recently developed diagonal methods, we experimentally measured all pairwise interactions among eight compounds in Erwinia amylovora, the causative agent of fire blight. Showing that synergy measurements of these two methods agree, we predicted synergy/antagonism scores for all possible three-drug combinations by averaging the synergy scores of pairwise interactions. We validated these predictions by experimentally measuring 35 three-drug interactions. Therefore, our guided screen for discovering three-drug synergies is (i) experimental screen of all pairwise interactions using diagonal method, (ii) averaging pairwise scores among components to predict three-drug interaction scores, (iii) experimental testing of top predictions. In our study, this strategy resulted in a five-fold reduction in screen size to find the most synergistic three-drug combinations.

Functionalized Polymers Enhance Permeability of Antibiotics in Gram-negative MDR Bacteria and Biofilms for Synergistic Antimicrobial Therapy

The emergence of multi-drug resistant pathogenic bacteria constitutes a key threat to global health. Infections caused by multi-drug resistant Gram-negative bacteria are particularly challenging to treat due to the ability of pathogens to prevent antibiotic penetration inside the bacterial membrane. Antibiotic therapy is further rendered ineffective due to biofilm formation where the protective Extracellular Polymeric Substance (EPS) matrix limits the diffusion of antibiotics inside the biofilm. We hypothesized that careful engineering of chemical groups on polymer scaffolds could enable polymers to penetrate the barriers of Gram-negative bacterial membrane and biofilm matrix. Here, we present the use of engineered polymeric nanoparticles in combination with antibiotics for synergistic antimicrobial therapy. These polymeric nanoparticles enhance the accumulation of antibiotics inside Gram-negative bacteria and biofilm matrix, resulting in increased potency of antibiotics in combination therapy. Sub-lethal concentrations of engineered polymeric nanoparticles reduce the antibiotic dosage by 32-fold to treat MDR bacteria and biofilms. Tailoring of chemical groups on polymers demonstrate a strong-structure activity relationship in generating additive and synergistic combinations with antibiotics. This study demonstrates the ability of polymeric nanoparticles to 'rejuvenate' antibiotics rendered ineffective by resistant bacteria and provides a rationale to design novel compounds to achieve effective antimicrobial combination therapies.