Abstract
The growing prevalence of antifungal drug resistance coupled with the slow development of new, acceptable drugs and fungicides has raised interest in natural products (NPs) for their therapeutic potential and level of acceptability. However, a number of well-studied NPs are considered promiscuous molecules. In this study, the advantages of drug–drug synergy were exploited for the discovery of pairwise NP combinations with potentiated antifungal activity and, potentially, increased target specificity. A rational approach informed by previously known mechanisms of action of selected NPs did not yield novel antifungal synergies. In contrast, a high-throughput screening approach with yeast revealed 34 potential synergies from 800 combinations of a diverse NP library with four selected NPs of interest (eugenol, EUG; β-escin, ESC; curcumin, CUR; berberine hydrochloride, BER). Dedicated assays validated the most promising synergies, namely, EUG + BER, CUR + sclareol, and BER + pterostilbene (PTE) [fractional inhibitory concentrations (FIC) indices ≤ 0.5 in all cases], reduced to as low as 35 (BER) and 7.9 mg L–1 (PTE). These three combinations synergistically inhibited a range of fungi, including human or crop pathogens Candida albicans, Aspergillus fumigatus, Zymoseptoria tritici, and Botrytis cinerea, with synergy also against azole-resistant isolates and biofilms. Further investigation indicated roles for mitochondrial membrane depolarization and reactive oxygen species (ROS) formation in the synergistic mechanism of EUG + BER action. This study establishes proof-of-principle for utilizing high-throughput screening of pairwise NP interactions as a tool to find novel antifungal synergies. Such NP synergies, with the potential also for improved specificity, may help in the management of fungal pathogens.
Introduction
Fungi can have devastating socio-economic impacts through human disease, crop disease, and food spoilage (; ; ; ). As fungi share many conserved cellular functions with potential host eukaryotes (humans, plants), the discovery of effective antifungal drugs or fungicides is challenging while resistance is growing to existing agents, accentuating the need for discovery of novel measures for fungal control (; ). On top of this, tightening of regulations and shifting of public attitudes away from the use of traditional chemical actives calls for different approaches to fungal control. Natural products are one group of compounds that are more acceptable in this landscape (; ).
Natural products are increasingly reported in inhibitor discovery programs. Natural products in cancer and infectious disease therapeutics already form the backbone of >50% of drugs being used today, either directly or indirectly (; ). Antibiotics are a key example of NP use, including where the antibiotic chemical scaffold has been “copied” from NPs (Wright, 2019). Moreover, the use of NPs in their native form is not to be underestimated considering that they have been moulded throughout evolution to provide benefit to producing organisms, possessing underlying properties required for biological activity (Wright, 2019). Furthermore, regulatory hurdles are commonly lower for NPs. For example, in the application of essential-oil (EO) NPs for food preservation, the European Regulation No. 1334/2008 defines EOs and their active components as flavoring preparations and flavoring substances, respectively. This allows EOs with these properties or which are natural constituents of the product not to be labeled as a preservative, also satisfying “clean label” demand of consumers. Nonetheless, each NP should be judged by its own merits (; ). Despite the numerous advantages of NPs, in recent years several NPs have also been designated promiscuous molecules, having undesirable molecular properties (such as aggregation and membrane perturbation) (). Related to this, several NPs are very commonly identified as “hits” in high-throughput screens. These NPs have been referred to as pan-assay interference compounds (PAINS) and, in certain cases, invalid metabolic panaceas (IMPs), which are unlikely to progress to lead compounds (; ; ). Therefore, enhanced specificity of action is one consideration in the discovery of lead NPs of interest.
Another popular strategy for addressing current challenges of disease- (e.g., fungal) control is the use of drug combinations (). One advantage is that resistance to one drug within the combination may be compensated by the second agent, while rapid pathogen removal can theoretically slow resistance development, where additional mutations would be necessary to overcome the combinatorial inhibition (; ). Pairs of drug activities may produce additive, antagonistic, or synergistic interactions. Understanding such interactions is important and the potential risk of antagonism between antifungal drugs, for example, has been highlighted (). Conversely, with drug–drug synergy, the advantages include the use of lower drug doses for effect, so lowering costs and non-specific toxicity concerns (). These types of interaction can be distinguished by determination of fractional inhibitory concentration indices (FICIs) (). Combinations of certain non-antifungal agents, such as paromomycin and β-escin, were reported to produce marked antifungal synergy against the human pathogen Candida albicans, with up to a 64-fold reduction in minimum inhibitory concentrations (MICs) compared with either agent alone (). A few synergistic combinations of NPs such as EOs have been described, e.g., a eugenol and thymol combination inhibiting food-borne bacterial pathogens (). Despite the novel activities of interest that have already been uncovered by study of NPs, there remains a diversity of NPs yet to be investigated. In particular, there has yet been very little work dedicated to the discovery of NP–NP synergies. Moreover, the problem of promiscuous activities of some NPs (PAINS, IMPs), discussed above, could potentially be countered with the application of combinational synergy as this should encourage increased potency and specificity (through a common targeted function).
The application of mechanism of action (MOA) knowledge can aid the prediction and discovery of synergistic interactions, as done recently in helping to find novel anti-cancer treatments, for example (Yang et al., 2020). This targeted approach relies on prior knowledge sufficient to enable rational predictions; such as when two agents are known to target similar but not identical processes, which is one basis for synergy (). On the other hand, the availability of NPs in selective chemical libraries (e.g., libraries which maximize chemical diversity and/or interesting NP activities) facilitates non-targeted screening approaches, including for discovery of lead targets and novel antifungal compounds (). The use of high-throughput combinatorial screening of chemical-libraries, by combining these with selected compound(s)-of-interest, has recently proved an effective strategy for discovery of novel antifungal synergies (). The latter study used standard, non-NP chemical libraries and the approach has not been exploited previously to find NP synergies.
Considering the potential importance of NP discovery for healthcare, food, and agricultural applications, this study tested the hypothesis that either rational or screening-based approaches could be used to find novel, antifungal synergies between NPs. The rational approach capitalized on prior MOA knowledge for three NPs with cell membrane-targeting actions, while wider interrogation utilized an NP-specific chemical library in combination with selected NPs of interest. The study shows the effectiveness of this new screening strategy for finding potent, combinatorial activities among NPs, offering additional tools in the effort to control fungal pathogens.
Results
Selected Natural Products With Similar Mechanisms-of-Action Did Not Reveal Combinatorial Synergies
It was hypothesized that the natural products eugenol (EUG), β-escin, and curcumin (CUR) may act synergistically in combination. This was based on their related, reported mechanisms of action: in causing lipid peroxidation and disruption of cell membrane integrity (EUG), pore formation within the cell membrane (β-escin), and interactions with ABC drug transporters and ERG3 gene downregulation, leading to decreased membrane ergosterol and permeability (CUR) (; ; ). Checkerboard assays measuring growth of the model yeast Saccharomyces cerevisiae were used to assess synergy. These showed that pairwise combinations of EUG, β-escin, or CUR did not present any synergistic interaction: all three of the fractional inhibitory concentration (FIC) index values for these pairs of NPs were > 0.5 (Figure 1). In fact, both the EUG + β-escin and CUR + β-escin combinations exhibited antagonism (with FIC indices ≥ 2.5). The interaction between EUG and CUR was deemed additive (FIC index, 1.5). These observations were reproduced in two common laboratory strains of S. cerevisiae, W303 (Figure 1) and BY4743 (Supplementary Figure 1). The results did not support the starting hypothesis.
FIGURE 1
An organism’s microenvironment can be an important determinant of drug–drug interaction, with previous work reporting a shift from antagonism to synergism for certain antibiotic combinations when bacteria were incubated with glycerol or ethanol instead of glucose (
FIGURE 2

Effect of metabolic environment on the stability of combinatorial interactions. (A) Growth curves for S. cerevisiae W303 in YEP medium supplemented with either glucose, glycerol, or ethanol (all at 2% w/v). Each point represents the mean of three independent experiments ± SEM (error bars did not exceed the dimensions of the symbols). (B)S. cerevisiae W303 was treated in checkerboard format with combinations of eugenol, β-escin, and curcumin in YEP supplemented with 2% either glucose (black), glycerol (pink), or ethanol (green). Percentage growth was used to calculate FIC indices. Each bar represents the mean of three independent experiments ± SEM. The corresponding checkerboard data are presented in Supplementary Figure 2.
Screen of Natural Product Library in Combinations With Selected Natural Products Reveals Multiple Combinatorial Antifungal Candidates
To widen the net for enabling the discovery of novel NP antifungal synergies, the Puretitre NP compound library1 was screened in combinations with the NPs of interest EUG, CUR, and β-escin. The Puretitre library was selected as the 200 NP compounds it comprises mostly have described use in traditional medicine, possessing both high bioactivity and relatively low toxicity so enhancing translational potential. An additional screen of the library in combination with the NP berberine (BER) is described, as BER had been identified as a hit compound in an initial screen of the library with EUG (described later), and there are previous reports of antimicrobial BER actions (Xu et al., 2009;
FIGURE 3

A screen of library NPs in combinations with selected NPs of interest, against the growth of S. cerevisiae. Left: normalized growth of S. cerevisiae W303 was calculated from OD600 values after 24 h with and without NPs, for each of the library NPs both in the absence (x-axis) or in the presence (y-axis) of 750 μM eugenol (EUG), 12.5 μM β-escin (ESC), 50 μM curcumin (CUR), or 350 μM berberine (BER). Each point represents the mean ± SEM calculated from two independent experiments. Right: effect strengths were determined from [(% growth with library agent) - (% growth with library agent + second agent)] for the different combinations; color is used to highlight those with an effect strength > 50. The underlying data for each combination from the screen are listed in Supplementary Table 1.
Corroboration of Candidate Synergies and Activity Against Fungal Pathogens
To corroborate synergistic interactions from the most promising screen combinations, checkerboard analysis was performed initially in S. cerevisiae. The three combinations with the greatest effect strengths from each of the three screens that indicated synergies were selected (Figure 4A). Synergy was corroborated for all nine of these combinations by checkerboard analysis (Supplementary Figure 4). The most promising checkerboard result for each of eugenol, curcumin, and berberine is displayed in Figure 4B, with the corresponding library-compound structures in Figure 4C. The other tested combinations gave FIC index values between 0.25 and ≤0.5 (Supplementary Figure 4) but were not pursued further in this study. For eugenol, the EUG + BER combination reduced the MICs for both compounds by up to 8-fold (Figure 4B). Checkerboard analysis for CUR with sclareol also indicated strong synergy, with MICs reduced by up to 4- and 8-fold, respectively, while the combination of BER with pterostilbene reduced these agents’ MICs by up to 16- and 8-fold, respectively.
FIGURE 4

Corroboration of synergies in S. cerevisiae. (A) Mean effect strengths ± SEM from each screen (Figure 3) for selected combinations of interest (n = 2). (B) Checkerboard assays of combinatorial growth effects performed according to the EUCAST procedure in YPD broth with S. cerevisiae W303 at the indicated concentrations of eugenol, curcumin, berberine, sclareol, and pterostilbene. The growth values represent the mean of three independent experiments calculated as percentages of growth (OD600) with the natural products relative to the minus-NP control, after 24 h growth at 30°C. FICI, fractional inhibitory concentration index, calculated from the data and where growth < 5% of the control was assigned as no-growth (
To assess the wider efficacies of the three selected combinations, they were tested against fungi that are either important human pathogens, including drug-resistant isolates (Candida albicans, C. glabrata, A. fumigatus); phytopathogens (B. cinerea, Z. tritici); or a food spoilage organism (Zygosaccharomyces bailli). The combinatorial effects determined from checkerboard analysis with this wider range of fungi revealed synergy in all cases, with FIC index values ranging between 0.19 and 0.5, the lowest values suggesting the strongest synergy was with EUG + BER (Table 1). Synergies were also retained in drug- (azole-) resistant isolates of C. albicans and A. fumigatus. In addition, the EUG + BER combination retained synergistic activity against biofilms of C. albicans, showing a significantly greater observed effect of the combination than would be expected from an additive interaction of the observed individual-NP effects (Supplementary Figure 5A). This evidence supported our initial use of NP combinatorial screening (with S. cerevisiae) to find novel NP synergies that had broad antifungal spectra.
TABLE 1
| Organism | Eugenol + Berberine | Curcumin + Sclareol | Berberine + Pterostilbene |
| C. albicans | 0.50a | ≤0.50 | ≤0.38b |
| C. albicans (azoleR) | 0.50 | >0.50 | ≤0.50 |
| C. glabrata | 0.19 | ≤0.38 | ≤0.50 |
| Z. tritici | 0.19 | ≤0.25 | ≤0.38 |
| B. cinerea | 0.25 | ≤0.25 | 0.26 |
| A. fumigatus | 0.25 | ≤0.25 | 0.50 |
| A. fumigatus (azoleR) | 0.19 | ≤0.50 | 0.38 |
| Z. bailli | 0.31 | ≤0.50 | 0.38 |
Values for FIC index for selected NP combinations against diverse human-, plant-pathogenic, and spoilage fungi.
aFIC index values were determined by checkerboard analysis with the indicated fungi.
b≤symbol indicates that the calculated FICI represents the highest possible FIC value for the combination; as inhibitory concentrations were not achieved at the highest doses used in checkerboards, precluding absolute MIC definition for certain agents when supplied individually.
The Berberine + Eugenol Combination Causes Synergistic Depolarization of the Mitochondrial Membrane
As the BER + EUG combination gave the strongest overall synergy it was chosen for further investigation of the mechanism of synergistic action. We hypothesized that the synergy between these agents was centered on mitochondria as a target, as previous studies have indicated that each agent causes mitochondrial perturbation [and associated reactive oxygen species (ROS) production] as a mechanism of cell inhibition (
FIGURE 5

Mitochondrial membrane depolarization in eugenol- and berberine-treated yeast cells. (A) Checkerboard assays of combinatorial growth effects were performed as described in Figures 1, 4. Combination concentrations that were subsequently tested for mitochondrial membrane depolarization are circled. (B) Microscopic imaging of S. cerevisiae cells treated with or without 94 μM EUG and 188 μM BER for 24 h, stained with rhodamine-123. Images were captured using a ×40 objective lens, through a FITC-filter; scale bar, 20 μm. Images are representative of three biological replicates. (C) Flow cytometric histograms for cells incubated for 24 h without (control) or with the indicated concentrations of EUG and BER. Cells were then stained with rhodamine 123 before analysis of fluorescence; a.u., arbitrary units. (D) Observed effects of combinations were obtained experimentally from median fluorescence of rhodamine 123-stained cells exposed to the EUG + BER combination [derived from corresponding flow cytometric data as in panel (B)], normalized to the no drug control (100%). Expected effects were calculated by multiplication of the % median-fluorescence determinations obtained for the corresponding individual-compound effects. Values represent means ± SEM from four independent experiments: *p < 0.05 and **p < 0.01 according to paired t-tests. EUG, eugenol; BER, berberine.
Action of Mitochondrial Reactive Oxygen Species in the Synergy Between Eugenol and Berberine
To further elucidate the mechanism of EUG + BER synergy, we focused on the reported effects of ROS in the individual actions of both these agents (
FIGURE 6

Effect of antioxidants on the eugenol plus berberine synergy. Values plotted to represent mean FICI values from three independent checkerboard experiments performed with S. cerevisiae W303, as described in Figures 1, 4, with the inclusion of the antioxidants at the specified concentrations. Bar heights show means ± SEM. *p < 0.05 and **p < 0.05, according to unpaired t-tests. The relevant checkerboard data are presented in Supplementary Figure 6.
In keeping with the earlier depolarization results for mitochondrial membrane function, and the indication that (mitochondrial) ROS production is important for the synergy, next we focused specifically on the involvement of mitochondrial ROS in the EUG + BER interaction. Deletion mutants defective for three mitochondrial antioxidant functions were tested: Δsod2 cells lacking the mitochondrial superoxide dismutase that scavenges mitochondrial superoxide; Δogg1 cells lacking a DNA glycosylase that protects the mitochondrial genome from oxidative damage; and Δccp1 cells lacking the mitochondrial cytochrome C peroxidase. The Δogg1 and Δccp1 deletants exhibited FIC indices with EUG + BER that were not significantly different from that of the wild type (Figure 7). In contrast, synergy was accentuated in cells defective for Sod2p, reflected by an FIC index in the mutant that was ∼50% of that in the wild type (Figure 7). This evidence for partial suppression of the synergy by Sod2p (in wild-type cells) further suggests that ROS, more specifically, mitochondrial superoxide is important for the mechanism of synergistic eugenol–berberine action.
FIGURE 7

Eugenol plus berberine synergy in deletion strains defective for mitochondrial antioxidant proteins. (A) Checkerboard assays of combinatorial growth effects performed according to the EUCAST procedure in YPD broth within S. cerevisiae BY4743 (WT) and isogenic deletion mutants Δsod2, Δccp1, and Δogg1 at the indicated concentrations of eugenol and berberine. The growth values represent the mean of three independent experiments calculated as percentages of growth (OD600) with the natural products relative to the minus-NP control, after 24 h at 30°C. FICI, fractional inhibitory concentration index, calculated from the data and where growth < 5% of the control was assigned as no-growth (
Discussion
This study highlights the potential value of using NP combinations for fungal control, and how a high-throughput screening approach can enable the ready discovery of novel NP synergies. The high-throughput approach proved more successful here for that purpose, compared with a rational approach based on prior mechanism-of-action knowledge. NPs have been the focus of considerable recent attention for finding novel fungal inhibitors, as concern has grown over diminishing treatment options in the face of growing resistance to existing agents (
High-throughput screening of individual NPs has been historically important for identifying novel compounds of interest, including in the treatment of cancer, infectious disease, cardiovascular disease, and inflammation (Waltenberger et al., 2016;
Among the 34 candidate synergies identified here from 800 interactions tested, nine were chosen for validation and from these, three were taken further for additional investigation. It is encouraging that only a limited number of candidates were identified from the screen, as it supports the notion that assay for synergy should restrict the scope for promiscuity compared with individual-NP activities. The BER + pterostilbene (PTE) combination produced up to 16-fold (BER) and 8-fold (PTE) reductions in MICs for inhibition of S. cerevisiae and the synergy was retained against fungal pathogens. Individually, BER and PTE have previously reported activities against C. albicans, with reported MOAs linked to the Ras/cyclic AMP pathway (PTE) or membrane damage (BER) (
To test a synergistic MOA experimentally, here we concentrated on EUG + BER as this combination gave the lowest FIC index value (strongest synergy) against several of the fungal pathogens tested. Knowledge of previous indications of commonalities in fungus-inhibitory actions of EUG and BER (
Concerning the potential for application, one consideration is cost. Berberine and eugenol, for example, are relatively inexpensive. These are purchasable from research suppliers for less than ∼10 USD per gram, whereas the equivalent pricing for the common antifungal drug amphotericin B is ∼1,000 USD per gram. Regarding safety, eugenol is already used in pharmaceutical products (commonly as a local antiseptic and analgesic), as a food preservative, in agriculture (pest control) and in cosmetics and can be administered at 2.5 mg/kg body weight per day in humans (
Importantly, the lead combinations from this study synergistically inhibited a range of important pathogenic and spoilage ascomycete fungi, including activity against C. albicans biofilms (EUG + BER). Synergy was also retained in azole-resistant isolates of C. albicans and A. fumigatus, suggesting additional potential relevance for the clinical setting where azoles are key drugs for treating invasive infection (
Materials and Methods
Strains, Culture, and Maintenance
The principal yeast strain backgrounds were S. cerevisiae W303 (MATa/MATα leu2-3,112 trp1-1 can1-100 ura3-1 ade2-1 his3-11,15 [phi+]) and BY4743 (MATa/MATα his3-1/his3-1 leu2-0/leu2-0 met15-0/MET15 LYS2/lys2-0 ura3-0/ura3-0). A rho0 mutant was derived from S. cerevisiae BY4743 by sub-culturing three times on YPD agar supplemented with 40 μg mL–1 ethidium bromide. It was confirmed that the resultant mutant was defective for respiratory growth by a lack of growth on YPG agar (recipe as for YPD agar, below, but with glycerol replacing glucose). The sod2Δ, ogg1Δ, and ccp1Δ homozygous diploid deletants (obtained from Euroscarf, Germany), were in the BY4743 background. Other yeast species used in this study included Z. bailli strain NCYC1766, Candida glabrata BG2, Candida albicans SC5314, and an azole-resistant isolate, C. albicans J942148, kindly provided by Carol Munro and Donna MacCallum (University of Aberdeen, United Kingdom). Yeasts were maintained and grown at 30°C (S. cerevisiae) or 37°C (C. albicans and C. glabrata) in YPD broth [2% peptone (Oxoid, Basingstoke, United Kingdom), 1% yeast extract (Oxoid), 2% D-glucose]. For experimental purposes, the yeasts were streaked onto YPD agar [recipe as for YPD broth but with the inclusion of 1.5% agar] from −80°C glycerol stocks and cultured for at least 48 h before single colonies were picked for sub-culture to the broth as described below.
Filamentous fungi used in the study were A. fumigatus CBS 144.89 and an azole-resistant isolate A. fumigatus 3216 (kindly provided by Matthias Brock, University of Nottingham, United Kingdom), Z. tritici K4418 (kindly provided by Syngenta, United Kingdom) and B. cinerea SAR109940. The filamentous fungi were routinely maintained and grown either on Aspergillus complete medium (ACM) at 37°C for A. fumigatus, or Potato Dextrose Agar (PDA, Oxoid) or Potato Dextrose Broth (PDB, Sigma) at room temperature for Z. tritici and B. cinerea (
Natural Product and Antioxidant Chemicals
Eugenol, β-escin, curcumin, berberine hydrochloride, sclareol, capsaicin, parthenolide, ellagic acid, glutathione, L-ascorbic acid were from Sigma–Aldrich (United Kingdom); osthole and pterostilbene were from Stratech (United Kingdom) and mitoquinol from Cayman Chemical Company (United Kingdom); all other NPs were components of the Puretitre natural compound library from Caithness Biotechnologies (United Kingdom). All of the above except eugenol (70% ethanol), glutathione, and L-ascorbic acid (dH2O) were dissolved in dimethyl sulfoxide (DMSO, Sigma United Kingdom) and added to growth media from the following stock solutions prepared in those solvents: eugenol, 500 mM; glutathione, 375 mM, L-ascorbic acid, 500 mM; osthole, 200 mM; pterostilbene, 200 mM; β-escin, 50 mM; curcumin, 50 mM; berberine hydrochloride, 200 mM; sclareol, 130 mM; capsaicin, 200 mM; parthenolide, 130 mM; ellagic acid, 33.3 mM, mitoquinol, 2.94 mM.
Checkerboard Assays and Other Growth Inhibition Assays
All culturing and preparation for checkerboard assays adhered to EUCAST guidelines, except for the use of YPD broth, ACM, or PDB instead of RPMI as medium (
Biofilm Inhibition Assay
Biofilm metabolic activity was measured using the XTT (tetrazolium salt, 2,3-bis[2-methyloxy-4nitro-5-sulfophenyl]-2H-tetrazolium-5-carboxanilide) (Sigma, United Kingdom) reduction assay and performed as described previously (
Establishment of Sub-Inhibitory Concentrations
For the initial determination of sub-inhibitory concentrations (SIC) of selected test compounds (for subsequent use in the high throughput screen), experimental cell suspensions of S. cerevisiae W303 in YPD were prepared from overnight cultures as described above. Aliquots (50 μL at OD600 0.2) were mixed with 50 μL of YPD containing the relevant NP, from 2× solutions of the test compounds. In all conditions including solvent-matched controls, solvent concentrations were <1% of the final assay volume. Subsequent growth was measured by OD600 determination with a BioTek EL800 microplate spectrophotometer, after 24 h static incubation at 30°C.
High-Throughput Screening
For high-throughput screens, the four test compounds at their SIC (750 μM eugenol, 12.5 μM β-escin, 350 μM berberine, 50 μM curcumin) were assayed in pairwise combinations against the Puretitre natural compound library (Caithness Biotechnologies, United Kingdom), comprising 200 chemicals at 10 mM, dissolved in DMSO. For the screens, aliquots (1 μL) of each library compound were combined with 49 μL YPD and added to 96-well microtiter plates (Greiner Bio-One). Aliquots (50 μL) of yeast cell suspension (prepared as described above) containing one of the four test compounds (added at double the final desired SIC concentration, see above) were added to the 50 μL library-compound preparations in the microtiter plates. This gave final concentrations of 100 μM of each library compound in 100 μL total per well. Solvent-matched controls at 0.35% DMSO or 0.3% ethanol (70%) were used for control assays without added compounds. Subsequent growth was measured according to OD600 determinations with a BioTek EL800 microplate spectrophotometer after 12 h and 24 h static incubation at 30°C. OD600 from growth with added compounds was expressed as a percentage of control growth without the compounds. Effect strength [(% growth with library compound) - (% growth with library compound + test compound)] was calculated for each combination; screen “hits” were considered as those combinations showing an effect strength > 50, as described previously (
Mitochondrial-Membrane Depolarization Assay
Depolarization of the mitochondrial membrane in yeast cells was determined according to rhodamine 123 dye retention using a method adapted from previous reports (
Fluorescence Microscopy
Visualization of S. cerevisiae cells was performed after 24 h treatment with the EUG + BER combination, rhodamine-123 staining, and washing as described above. Cells were resuspended in 50 μL PBS before mounting. A GXML3201LED fluorescence microscope equipped with a GX-CAM controlled by GXCapture software (GX microscopes, Stansfield, United Kingdom) was used to collect images via the FITC filter (excitation, 495 nm; emission, 519 nm) using a ×40 objective lens.
Publisher’s Note
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Statements
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
Author contributions
CA designed and performed the experiments, carried out data analysis, and drafted the manuscript. SA conceived the project and contributed to data interpretation and manuscript preparation. Both authors contributed to the article and approved the submitted version.
Funding
This work was supported by the Biotechnology and Biological Sciences Research Council (grant number BB/M008770/1).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2022.866840/full#supplementary-material
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Summary
Keywords
drug combinations, fungicide combinations, crop pathogens, fungal pathogens, Zygosaccharomyces bailii, Saccharomyces cerevisiae
Citation
Augostine CR and Avery SV (2022) Discovery of Natural Products With Antifungal Potential Through Combinatorial Synergy. Front. Microbiol. 13:866840. doi: 10.3389/fmicb.2022.866840
Received
31 January 2022
Accepted
23 March 2022
Published
26 April 2022
Volume
13 - 2022
Edited by
Rafael Guerra Lund, Federal University of Pelotas, Brazil
Reviewed by
Siddharth Kaushal Tripathi, University of Mississippi, United States; Rebecca Anne Hall, University of Kent, United Kingdom
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© 2022 Augostine and Avery.
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*Correspondence: Simon V. Avery, simon.avery@nottingham.ac.uk
This article was submitted to Antimicrobials, Resistance and Chemotherapy, a section of the journal Frontiers in Microbiology
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