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Novel, Synergistic Antifungal Combinations that Target Translation Fidelity.

ABSTRACT: There is an unmet need for new antifungal or fungicide treatments, as resistance to existing treatments grows. Combination treatments help to combat resistance. Here we develop a novel, effective target for combination antifungal therapy. Different aminoglycoside antibiotics combined with different sulphate-transport inhibitors produced strong, synergistic growth-inhibition of several fungi. Combinations decreased the respective MICs by ?8-fold. Synergy was suppressed in yeast mutants resistant to effects of sulphate-mimetics (like chromate or molybdate) on sulphate transport. By different mechanisms, aminoglycosides and inhibition of sulphate transport cause errors in mRNA translation. The mistranslation rate was stimulated up to 10-fold when the agents were used in combination, consistent with this being the mode of synergistic action. A range of undesirable fungi were susceptible to synergistic inhibition by the combinations, including the human pathogens Candida albicans, C. glabrata and Cryptococcus neoformans, the food spoilage organism Zygosaccharomyces bailii and the phytopathogens Rhizoctonia solani and Zymoseptoria tritici. There was some specificity as certain fungi were unaffected. There was no synergy against bacterial or mammalian cells. The results indicate that translation fidelity is a promising new target for combinatorial treatment of undesirable fungi, the combinations requiring substantially decreased doses of active components compared to each agent alone.

SUBMITTER: Moreno-Martinez E

PROVIDER: S-EPMC4648087 | biostudies-other | 2015 Nov

REPOSITORIES: biostudies-other

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Novel, Synergistic Antifungal Combinations that Target Translation Fidelity.

Moreno-Martinez Elena E Vallieres Cindy C Holland Sara L SL Avery Simon V SV

Scientific reports 20151117

There is an unmet need for new antifungal or fungicide treatments, as resistance to existing treatments grows. Combination treatments help to combat resistance. Here we develop a novel, effective target for combination antifungal therapy. Different aminoglycoside antibiotics combined with different sulphate-transport inhibitors produced strong, synergistic growth-inhibition of several fungi. Combinations decreased the respective MICs by ≥8-fold. Synergy was suppressed in yeast mutants resistant ...[more]

PMID: 26573415

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Project description:A range of fungicides or antifungals are currently deployed to control fungi in agriculture or medicine, but resistance to current agents is growing so new approaches and molecular targets are urgently needed. Recently, different aminoglycoside antibiotics combined with particular transport inhibitors were found to produce strong, synergistic growth-inhibition of fungi, by synergistically increasing the error rate of mRNA translation. Here, focusing on translation fidelity as a novel target for combinatorial antifungal treatment, we tested the hypothesis that alternative combinations of agents known to affect the availability of functional amino acids would synergistically inhibit growth of major fungal pathogens. We screened 172 novel combinations against three phytopathogens (Rhizoctonia solani, Zymoseptoria tritici, and Botrytis cinerea) and three human pathogens (Cryptococcus neoformans, Candida albicans, and Aspergillus fumigatus), showing that 48 combinations inhibited strongly the growth of the pathogens; the growth inhibition effect was significantly greater with the agents combined than by a simple product of their individual effects at the same doses. Of these, 23 combinations were effective against more than one pathogen, including combinations comprising food-and-drug approved compounds, e.g., quinine with bicarbonate, and quinine with hygromycin. These combinations [fractional inhibitory combination (FIC) index ≤0.5] gave up to 100% reduction of fungal growth yield at concentrations of agents which, individually, had negligible effect. No synergy was evident against bacterial, plant or mammalian cells, indicating specificity for fungi. Mode-of-action analyses for quinine + hygromycin indicated that synergistic mistranslation was the antifungal mechanism. That mechanism was not universal as bicarbonate exacerbated quinine action by increasing drug uptake. The study unveils chemical combinations and a target process with potential for control of diverse fungal pathogens, and suggests repurposing possibilities for several current therapeutics.

Project description:The parasite Plasmodium falciparum is the most lethal species of Plasmodium to cause serious malaria infection in humans, and with resistance developing rapidly novel treatment modalities are currently being sought, one of which being combinations of existing compounds. The discovery of combinations of antimalarial drugs that act synergistically with one another is hence of great importance; however an exhaustive experimental screen of large drug space in a pairwise manner is not an option. In this study we apply our machine learning approach, Combination Synergy Estimation (CoSynE), which can predict novel synergistic drug interactions using only prior experimental combination screening data and knowledge of compound molecular structures, to a dataset of 1,540 antimalarial drug combinations in which 22.2% were synergistic. Cross validation of our model showed that synergistic CoSynE predictions are enriched 2.74 × compared to random selection when both compounds in a predicted combination are known from other combinations among the training data, 2.36 × when only one compound is known from the training data, and 1.5 × for entirely novel combinations. We prospectively validated our model by making predictions for 185 combinations of 23 entirely novel compounds. CoSynE predicted 20 combinations to be synergistic, which was experimentally validated for nine of them (45%), corresponding to an enrichment of 1.70 × compared to random selection from this prospective data set. Such enrichment corresponds to a 41% reduction in experimental effort. Interestingly, we found that pairwise screening of the compounds CoSynE individually predicted to be synergistic would result in an enrichment of 1.36 × compared to random selection, indicating that synergy among compound combinations is not a random event. The nine novel and correctly predicted synergistic compound combinations mainly (where sufficient bioactivity information is available) consist of efflux or transporter inhibitors (such as hydroxyzine), combined with compounds exhibiting antimalarial activity alone (such as sorafenib, apicidin, or dihydroergotamine). However, not all compound synergies could be rationalized easily in this way. Overall, this study highlights the potential for predictive modeling to expedite the discovery of novel drug combinations in fight against antimalarial resistance, while the underlying approach is also generally applicable.

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Novel, Synergistic Antifungal Combinations that Target Translation Fidelity.

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Novel, Synergistic Antifungal Combinations that Target Translation Fidelity.

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