The VMAA of a volatile spreads symmetrically across a microtiter plate

To quantify the vapour-phase-mediated activity in a straightforward manner, we developed the VMS assay and characterised the behaviour of volatiles in this assay using 96-well plates. We hypothesised that, under ideal conditions, a volatile added to the central four wells would spread symmetrically in a spherical manner, thus establishing a concentration gradient across the microtiter plate. A circle enclosing the four wells to which the volatile is added, was designated the volatility-centre (Fig. 1a upper left). Around this centre, concentric circles can be drawn that successively touch the nearest equidistant wells, with each set of wells making up a new distance category. These categories were defined to correct for the different number of wells in different categories and were ranked ordinally, with category one located closest to the volatility-centre (Fig. 1a,b). The distance between the circles and the volatility-centre is the minimum distance that a volatile needs to travel to possibly exert effects in the corresponding wells. Therefore, the content of all wells belonging to one category would be affected equally, due to radial symmetry and can be considered as technical repeats.

Figure 1 The VMAA of a volatile spreads symmetrically across a microtiter plate. (a) Illustrations of the spreading of a volatile in the VMS assay under ideal circumstances starting from the centre four wells (=volatility-centre which corresponds to category 0: upper-left); upper-middle to bottom-right: The first eight categories in which equidistant wells are affected (categories are indicated in red). (b) The number of equidistant wells and cumulative number of wells in successive categories with their distance to the volatility-centre. (c) Optical scans of the bottom of a 96-well microtiter plate illustrating the VMAA of Litsea citrata against C. albicans after 24 hours of incubation. Panels correspond to categories shown in Fig. 1a. (d) Graph illustrating the negative exponential distribution of both enantiomers of EOC citral over the microtiter plate in the VMS assay after one and 24 hours of incubation. Adjusted R² values represent goodness of fit. Each dot represents the relative peak area (extracted ion channel m/z 69) in HS-SPME-GC-MS analysis representing the concentration of pooled equidistant wells belonging to the same distance category as a function of their distance to the volatility-centre. Data from three independent experiments are shown and error bars represent standard deviation. The largest average absolute peak area over the different experiments was set as 100%, i.e. α-citral (24 h) at 0.9 mm. Full size image

Above theoretical model was illustrated by the growth inhibitory VMAA of the EO of Litsea citrata, rich in citral (71.80%; SI 1), on C. albicans in a VMS assay (Fig. 1c). As predicted, growth inhibition clearly increased the closer wells were located to the volatility-centre, and this visual impression was confirmed spectrophotometrically (SI 2). Headspace solid‐phase micro-extraction gas chromatography mass spectrometry (HS-SPME-GC-MS) on the content of the wells of the microtiter plates confirmed the presence of α-citral and β-citral in all wells, as quickly as one hour after addition of the EOC citral (≥95%) and this amount increased over the next hours (Fig. 1d). The largest inhibitory effects were observed in the wells located close to the volatility-centre (Fig. 1c), and they were associated with the highest concentration of citral measured (Fig. 1d).

We defined the inhibitory VMAA (iVMAA) as the categorised cumulative number of wells (Fig. 1a,b), determined by visual assessment and excluding the volatility-centre, in which growth was completely inhibited. When growth was only inhibited in some wells of one category, due to asymmetrical iVMAA patterns resulting from e.g. uncontrolled airflows, we assigned the intermediate value of 0.5. Only one intermediate categorical value was introduced between every two categories because the different categories can contain a different number of equidistant wells. Therefore, proportionally assigning the fraction of wells affected would result in an unequal number of intermediate values between every two categories.

A spectrophotometric determination of iVMAA termed iVMAA 90 and defined as the inhibitory VMAA resulting in a 90% reduction of growth as compared to control growth, showed a very high correlation (ρ = 0.991, p < 0.0001; SI 3) with iVMAA. This reflects a very high similarity between visual and spectrophotometric assessment and shows that both read-outs are equally valid.

The MIC of EO(C)s cannot be used to predict their iVMAA and vice versa

To characterise the vapour-phase-mediated growth inhibitory activity of EO(C)s, we determined the iVMAA of 175 chemically defined EOs (SI 1), and 37 of the most common EOCs (SI 4) against C. albicans and C. glabrata (Fig. 2a). As the VMS assay set-up is based on CLSI guidelines for the broth microdilution assay24,25, we also determined the MIC of our EO(C) collection against both Candida species (Fig. 2a). Despite the highly comparable experimental procedures used to determine the iVMAA and MIC, a comparison between these values for both species showed that the iVMAA of an EO(C) cannot be predicted from its MIC value and vice versa (Fig. 2b).

Figure 2 MIC of EO(C)s cannot be used to predict their iVMAA and vice versa. (a) Tukey boxplots representing MIC and iVMAA of EO(C) (n = 212) against C. albicans and C. glabrata. (b) Scatterplot of the correlations between MIC and iVMAA of EO(C)s (n = 212) against C. albicans (ρ = −0.0376, p = 0.59) and C. glabrata (ρ = −0.0555, p = 0.42). Red symbol indicates negative control DMSO. (c) Histogram with the relative frequency distribution of iVMAA of EO(C)s (n = 212) against C. albicans and C. glabrata. The relative frequency was calculated by dividing the number of EOC(s) in each category by the total number of EO(C)s. MIC = minimal inhibitory concentration; iVMAA = inhibitory vapour-phase-mediated antimicrobial activity. Full size image

Nine of the EOCs tested (24.3%) showed an iVMAA larger than 0.5 against both Candida species. The greatest activity was observed for EOC citronellal, followed by EOCs citral, thymol, trans-cinnamaldehyde, linalool, α-pinene, carvacrol, (-)-terpinen-4-ol and allo-ocimene. A comparable proportion of the EOs tested (25.7%; n = 45) showed an activity larger than 0.5 against both Candida species (Fig. 2c). Of these, 30 were rich in at least one of the previously mentioned EOCs, while 7 of the 15 remaining EOs primarily contained components that were not included in our collection. By contrast, the iVMAA was zero for representatives of all antifungal classes commonly used in clinical practice (i.e. amphotericin B, caspofungin, fluconazole, terbinafine and 5-flucytosine) when tested at five to ten times their MIC (data not shown). This lack of iVMAA was to be expected, considering the relatively high molecular weight and concomitant low vapour pressure at room temperature and/or high solubility in water of the tested molecules. Surprisingly, ethanol also failed to inhibit growth when tested in the VMS assay using the standard set-up despite its known antimicrobial activity and relatively high vapour pressure at room temperature. However, since it is known that relatively high concentrations of ethanol are needed to inhibit microbial growth29,30, we theorised that higher volumes were needed to observe iVMAA. Indeed, when testing ethanol at ten times the standard volume, i.e. 4 × 200 µL, an iVMAA of 3.5 to 4 was obtained (data not shown).

The major components present in an EO largely determine the presence or absence of iVMAA

To study the effect of the major individual EOCs in the EOs on their iVMAA, we categorised all EOs in 10 chemical classes. These classes were defined based on the number of carbon atoms and the presence of specific functional groups in the dominant EOCs (Fig. 3a and SI 1). Categorization occurred by the chemical class present at the highest concentration after combining all EOCs (>10% v/v) belonging to the same chemical class. This revealed that EO(C)s rich in aldehydes e.g. citronellal, citral and trans-cinnamaldehyde showed the highest iVMAA, followed by EO(C)s rich in phenols, e.g. carvacrol and thymol, monoterpenols, e.g. linalool and terpinen-4-ol, ethers, e.g. 1,8-cineol, and ketones such as carvone.

Figure 3 The major components present in an EO largely determine the presence or absence of iVMAA. (a) Tukey boxplots representing the iVMAA of EO(C)s (n = 209) categorised by the chemical class present at the highest concentration after combining all EOCs (>10%) belonging to the same chemical class. EOs for which one single major component could not be determined or for which this major component belonged to other chemical classes than defined in this paper were excluded (n = 3). (b) Correlations between the iVMAA of an EO(C) and its aldehyde concentration (>10%, n = 17) for C. albicans (top; ρ = 0.709, p = 0.0020) and for C. glabrata (bottom; ρ = 0.694, p = 0.0025). (c) Correlations between the iVMAA of an EO(C) and its monoterpenol concentration (>10%, n = 48) for C. albicans (top; ρ = 0.341, p = 0.018) and C. glabrata (bottom; ρ = 0.176, p = 0.23). (d) Correlations between the iVMAA of an EO(C) and its linalool concentration (>10%, n = 22) for C. albicans (top; ρ = 0.736, p < 0.0001) and C. glabrata (bottom; ρ = 0.6065, p = 0.0028). Full size image

While monoterpenol-rich EO(C)s were among the most active classes, EO(C)s rich in sesquiterpenols e.g. farnesol did not show iVMAA. Furthermore, an absence of iVMAA was shown for EOs that were mainly rich in sesquiterpenes such as β-caryophyllene, and iVMAA was very limited in EOs that were rich in phenol methyl ethers, e.g. methyleugenol. The high iVMAA observed for aldehyde-rich EOs was not only a result of the presence of aldehyde(s) but was also strongly correlated with the quantity of aldehyde(s) present in the EO (Fig. 3b). In contrast, for monoterpenol-rich EOs and the corresponding EOCs, the correlation between iVMAA and monoterpenol concentration was weak for C. albicans, while no correlation could be demonstrated for C. glabrata (Fig. 3c). While there was a moderate to strong correlation between the concentration of the tertiary monoterpenol linalool in an EO and its iVMAA (Fig. 3d), we did not observe a correlation between the concentration of geraniol, a primary monoterpenol, in an EO and its iVMAA (SI 5). Together this shows that while major components in EOs often determine the presence or absence of iVMAA, they are not always responsible for the observed biological effects. It is thus advisable to also be attentive to the contributions of minor components when performing this kind of analysis.

C. glabrata shows an average higher susceptibility to the iVMAA of EO(C)s than C. albicans

While the iVMAAs of the EO(C)s against the two Candida species tested correlated strongly (Fig. 4a), the overall susceptibility of the two species differed significantly (p < 0.0001). Despite the lower susceptibility of C. glabrata to antifungals in general8,25,31, it showed a higher average susceptibility to EO(C)s in the VMS assay compared to C. albicans. This higher susceptibility was evidenced by (i) more EO(C)s showing an iVMAA against C. glabrata (n = 113) than against C. albicans (n = 100) and (ii) on average a higher iVMAA of the EO(C)s (iVMAA > 0; n = 113) against C. glabrata (\(\bar{x}\) = 1.28 with a 95% CI between 1.13 and 1.44) than against C. albicans (\(\bar{x}\) = 0.916 with a 95% CI between 0.783 and 1.05). This resulted in more data points above the diagonal in the correlation analysis (Fig. 4a) and a clear contrast between the iVMAA of the two species visualised with a heat map (Fig. 4b). This indicates that EOs, and most likely specific EOCs within these EOs, can show a specific activity. To find those EO(C)s that showed the largest differential iVMAA against both species, the false discovery rate method was applied using a Q-value of 1%, i.e. accepting that 1% of the declared discoveries were false positives32. This resulted in four discovered EO(C)s i.e. organic EO Eucalyptus citriodora ct citronellal (t-ratio = 6.10; degrees of freedom (d.f.) = 452), EOC citronellal (t-ratio = 5.63; d.f. = 452), EO Cymbopogon winterianus (t-ratio = 4.22; d.f. = 452) and organic EO Cinnamomum cassia (t-ratio = 4.22; d.f. = 452) (Fig. 4b). Alternatively, when performing t-tests corrected for multiple comparisons (α = 0.05), the same EO(C)s were shown to have a differential iVMAA against both species. All EO(C)s found were aldehyde-rich i.e. the EOC citronellal, two EOs rich in citronellal and one EO rich in trans-cinnamaldehyde (Fig. 4b).

Figure 4 C. glabrata is on average more susceptible to the iVMAA of EO(C)s than C. albicans. (a) Scatterplot of the correlation (ρ = 0.930, p < 0.0001) between iVMAAs of EO(C)s (n = 212) against Candida albicans and C. glabrata. (b) Heat map of iVMAAs (>0 against at least one species) indicating the most differentially active of the EO(C)s (n = 113) against C. albicans and C. glabrata. # indicates that EO originates from an organic cultivar. (c) Graph showing iVMAA of citronellal in our VMS set-up against five C. albicans strains (SC5314 in black, and four clinical isolates) and five C. glabrata strains (ATCC2001 in grey, and four clinical isolates). Three independent experiments per strain are shown in the same colour and error bars represent standard error of the mean. iVMAA = inhibitory vapour-phase-mediated antimicrobial activity. ****p < 0.0001. Full size image

When a Q-value of 2% was applied, two additional EOs were shown to be differentially active including Leptospermum petersonii (t-ratio = 3.29; d.f. = 452), thereby finding all EO(C)s present in our collection that contain citronellal at more than 10% (SI 1). Together, this gives a very strong indication that the aldehyde citronellal is responsible for the higher iVMAA observed against C. glabrata. Although organic EO Cinnamomum cassia was also differentially active, its main component trans-cinnamaldehyde itself was not, and no other EOs rich in this EOC were found differentially active at the tested statistical cut-offs. Therefore, another component or a combination of components is most likely causing this differential activity. The other EO found with at a Q-value of 2% was Ammi visnage EO (t-ratio = 3.29; d.f. = 452), which contains linalool and two esters at more than 10% (SI 1).

The iVMAA of EOC citronellal was additionally determined against four clinical isolates of each species to exclude that the higher susceptibility to citronellal of C. glabrata compared to C. albicans was strain-dependent (Fig. 4c). An unpaired t-test with Welch’s correction (t = 8.90; d.f. = 18) corroborated that the species C. glabrata is more susceptible to EOC citronellal than C. albicans.