Phytochemical profiling and antimicrobial activity of ginger (Zingiber officinale) essential oils against important phytopathogens

2.1 Collection and preservation of plant sample

The plant materials used were the rhizomes of wild and domestic gingers. To reduce variations between samples, fresh ginger rhizomes raised in the same environmental and growth conditions were obtained in February 2019 from local producers in Bentong, Pahang (GPS coordinates: 3.8126°N, 103.3256°E). The matured rhizomes were divided into 3 kg of six experimental groups after which the ginger rhizomes were kept in an ice chest and transported to the laboratory for extracting EOs.

2.2 Extraction of the essential oils

The EOs were extracted from the ginger rhizomes using standard procedures. The rhizomes were washed with tap water to remove dirt followed by washing them with distilled water after which they were cut into pieces and ground using a blender. The extractions were performed using hydro-distillation (Clevenger-type apparatus). The device is a custom-sized machine coupled with an electric boiler as well as condenser and glass decanter to separate oil from water condensate. The ratio of 3:5 of pretreated ginger rhizomes with solvent (distilled water) was used. The process was maintained for five hours. The ground ginger rhizomes were put directly inside the 10 L flask and boiled. The hot steam enables the aromatic compounds (essential oils) in the plant parts to be released. Thereafter, the molecules of these volatile oils escaped from the plant material and evaporated into the vapor within the system. The steam temperature was carefully regulated. The sample was boiled at 100 °C for 20 min after which the temperature of the sample was reduced to 45 °C for 5 h. This was to ensure that the EOs were extracted. Afterwards, the samples with the EOs were condensed and separated (Mesomo et al., 2013). The yield OEs was computed using the below formula after which the samples were stored at − 20 °C in Bacteriology Laboratory, Faculty of Agriculture, Universiti Putra Malaysia, until when it was required for the antimicrobial bioassays. $$\mathrm{T}\mathrm{h}\mathrm{e}\mathrm{O}\mathrm{i}\mathrm{l}\mathrm{Y}\mathrm{i}\mathrm{e}\mathrm{l}\mathrm{d}(\%)=\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}\mathrm{o}\mathrm{f}\mathrm{O}\mathrm{i}\mathrm{l}(\mathrm{g})/\mathrm{W}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}\mathrm{o}\mathrm{f}\mathrm{s}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e}(\mathrm{g})\mathrm{X}100.$$

2.3 Analysis of the chemical contents of domestic and wild ginger essential oils using GCMS

The GCMS analysis was carried out at the Institute of Bioscience (IBS), Universiti Putra Malaysia. The analysis was conducted to determine the volatile compounds and their amounts in the ginger EOs. The approach used by Bhattarai et al. (2018) to analyze the volatile compounds was adopted using Shimadzu QP-2010 GCMS system that consists of gas chromatograph interfaced with a mass spectrometer and equipped with a Zebron ZB5-MS capillary fused silica column (30 m × 0.25 nm I.D. × 0.25 m film thickness). The initial temperature of the oven was set at 70 °C (isothermal for 3 min) with a 10 °C/min after which it was increased to 240 °C followed by increasing it to 300 °C for 10 min isothermal. A scan interval of 0.5 s and fragments of 45 to 480 Da were taken at 70 ev. Total GC running time was 45 mins for the domestic ginger and 51 mins for the wild ginger. Carrier gas, helium (99.999%) with a flow rate of 1 ml/min; injection volume 1 μl with a split ratio of 10:1 and injector temperature 250 °C were used in this present study. The mass spectrum of the obscured constituents of both gingers was identified by comparing their retention times (RT), similarity index (SI), and mass spectral data with those from FFNSC1.3.lib, NIST11.lib, and WILEY229. Lib mass spectral databases, as well as with related literature (Wei et al., 2010; Nagappan and Palaniveloo, 2012; Trimanto et al., 2018). The composition of EOs was expressed as a percentage of total peak area. The chemical compound’s names, percentages, retention time, and molecular formula were determined.

2.4 Analysis of the chemical contents of domestic and wild ginger by headspace

The analysis was carried out using the procedure of Yang et al., (2009). A 0.5 g amount of ginger rhizome particle was hermetically sealed in a 4 ml screw-top amber vial. The sealed vial was exposed to the extraction of the ginger component by immediately inserting it into the GC injector and the fiber thermally desorbed. A desorption time of 2 min at 250 °C was used in splitless mode with a valve oven temperature at 110 °C and transfer line temperature of 120 °C. Thereafter, the above stated GCMS condition was established using a Shimadzu QP-2010 GCMS system. The chemical compounds names, percentages, retention time, and molecular formula were recorded.

2.5 Description and retrieval of fungal and bacterial pathogens

The phytopathogenic bacteria and fungi were obtained from the Culture Collections Unit, Department of Plant Protection, Faculty of Agriculture, Universiti Putra Malaysia. Isolates of five plant pathogenic fungi and bacteria were Fusarium oxysporum, Pyricularia oryzae, Colletotrichum falcatum, Ganoderma boninense, and Rigidoporus microporus as well as Xanthomonas oryzae pv. oryzae- strain A, X. oryzae pv. oryzae- strain B, Ralstonia solanacearum, Bacillus sp. and Klebsiella sp. Confirmation of the identity of the resultant cultures was based on their morphological and molecular characteristics (Table 1).

2.6 Determination of antifungal activity of ginger essential oils

The ginger EOs were screened against the fungal pathogens using the food poison technique (Talibi et al., 2012). The test concentrations 1, 2, 3, 4, 5, and 6 µl/ml were prepared by adding an appropriate amount of ginger EOs containing 0.5% (v/v) of Tween 80 to the cooled molten PDA (45 °C) followed by manual rotation in a sterile Erlenmeyer flask to disperse the oil in the medium and thoroughly mixed before solidification. After the samples had solidified, 6 mm bits of fungus culture was cut from a seven day old culture with sterilized cork borer after which it then placed at the center of Petri dish plates with a sterilized inoculation needle in three replications of each treatment. All Petri dishes were sealed with sterile laboratory parafilm to prevent the EOs from evaporating. The Petri dish plates were incubated at 25 ± 2 °C. Negative control was maintained in the medium that was not mixed with anything but inoculated with the pathogen whereas the positive control was mixed with 60 µl/ml of Azoxystrobin/Difenoconazole. Data were collected when the control petri plates were fully grown with mycelium. The data of the radial growth of the fungal colony was measured in millimeters. The percentage inhibition over control was calculated by the below formula (Aman and Rai, 2015): $$\mathrm{P}\mathrm{e}\mathrm{r}\mathrm{c}\mathrm{e}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{n}\mathrm{h}\mathrm{i}\mathrm{b}\mathrm{i}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{o}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}=[(\mathrm{C}-\mathrm{T})/\mathrm{T}]\times 100$$

Where C = Growth of fungus in control T = Growth of fungus in treatment.

To determine whether the EOs have fungicidal effect on the test pathogens, a plug of 6 mm PDA from the plate with no growth or suppressed growth was transferred to un-amended PDA medium. The treatment in which the mycelial did not growth after additional seven days of incubation was considered fungicidal to the test pathogens (Talibi et al., 2012).

2.7 Determination of antibacterial activity of ginger essential oils

The analysis was done using the method of Rajip et al., (2016) but with modifications. A standard disc diffusion method was used to determine the antibacterial activity of the EOs against the bacterial pathogens in triplicate using 24–48 h grown bacterial species reseeded on nutrient media. The cultures were adjusted with saline water to obtain a suspension at concentration of 1 × 10⁶ CFU/ml using spectrophotometer, then 100 µl of the suspension was spread on Muller Hinton (MH) agar media plates to obtain uniform microbial growth using a sterile glass rod. Sterile filter paper discs (Whatman’s No. 6 mm in diameter) was impregnated with 10 µl of oils diluted in dimethyl sulfoxide (DMSO) and obtained different concentrations range from 50, 100, 200, 300, 400 and 500 µl/ml and finally placed on the surface of the agar test plate at intervals. The positive control discs were saturated with 10 µl of streptomycin (15 µg/ml/disc) and negative control was DMSO buffer. All Petri dishes were sealed with sterile laboratory parafilm to prevent the EOs from evaporating. The dishes were left for 30 min at room temperature to enable the oil to diffuse. Afterwards, the plates were incubated at 37 °C for 24 h. The appearance or absence of a zone of inhibition has been used as a means of identifying active or inactive concentrations of the EOs, they were determined by measuring the growth inhibition diameter in millimeter (mm).

2.8 Metabolomics’ Profiling of chemical constituents of ginger essential oils

After GCMS analysis of domestic (DMT) and wild (WLD) ginger EOs, the chromatographic and spectral data were properly processed and analyzed by multivariate data analysis (MDA). The metabolomic analysis started by obtaining the comma-separated values (CSV) file, which enables data to be saved in a tabular format. The deconvolution was done to convert these data into a data matrix suitable for multivariate data analysis (MDA) using Microsoft Excel 2010. After these procedures, a multivariate data matrix containing information about sample identities (sample code), ion identities (RT and m/z values), and normalized peak intensities were introduced into the analytical software called SIMCA (MKS Umetrics, version 14.1.0.2047 (32-bit) whereby the generated normalized metabolite peaks were transformed into variables. The data were mean centered and Pareto scaled. The PCA was then used to see the discrimination among the different observations from different ginger samples, (DMT and WLD). A model containing PCs (PC1 and PC2) were established representing a portion of examined data set. Results were visualized in the score plot of the two main components (DMT and WLD), in which each point was a representative of an individual sample spectrum. The analysis was checked and validated by default seven-fold internal cross validation based on the values R2X and Q2 which are the fitness and goodness of prediction respectively. The PCA, which is an unsupervised analysis that was performed to evaluate summary of the possible differences or similarities between sample groups based on the score plots observation. The corresponding loading plot were created to show the metabolites leading to group separation.

The supervised partial least square (PLS) was subsequently conducted to classify the metabolites associated with bioactivity addition via the score plot, that is, PLS model was used to find the correlation between the antimicrobial activities to the metabolites identified in each of the two different ginger EOs. There was validation by determining R2Y and Q2 through permutation test. Thereafter, the most significant metabolites (VIP > 1.0) were then identified with the bioactivity and subsequently, the bi-plot gave the correlation of bioactivity in a single plot.

2.9 Determination of antibacterial activity against Xanthomonas oryzae pv. oryzae- strainA

The potential antibacterial effects of EOs were evaluated using the electron microscopy (EM) methods. Scanning electron microscopy (SEM) for visual observation of the pathogen response to the in-situ antibacterial activity of the EOs. The test pathogen was treated with the MIC concentration (100 µl/ml), streptomycin (15 µg/ml/disc) and control with DMSO. The method as described by de Oliveira et al., (2011) was used for this analysis. The samples were then fixed with modified Karnovsky’s fixative (Karnivsky, 1965) containing 2% (v/v) glutaraldehyde and 2% (v/v) paraformaldehyde in 0.05 M sodium cacodylate buffer solution (pH 7.2) and left at 4 °C overnight. The samples were washed with 0.1 M sodium cacodylate buffer in three changes after 30 mins each, followed by post-fixation in 1% osmium tetroxide in 0.2 M PBS for 2 h, dehydrated through series of graded acetone (35, 50, 75, 95%) for 10 min each and 100% for 15 min. After completing the dehydration process, the samples were transferred into specimen basket and put into critical dryer for 30 min and observed with a scanning electron microscope (SEM: JSM − 5610LV, JOEL, Japan) at the IBS, Universiti Putra Malaysia.

2.10 Data analysis

The data in this present study were analyzed using PROC ANOVA by SAS 9.4 version and significant differences among the means were determined using least significant difference (LSD) at probability level of 0.05. The EPA probit analysis program version 1.5 was used to determine LC values among different concentrations of the essential oil and their overall antimicrobial activity.

3.1 The extracted oil and yield (%)

The volume of EOs for the domestic ginger was 8 ml per 3 kg fresh rhizome. The highest yield obtained was 2.46% and the lowest yield obtained was 0.41% per 3 kg whereas for that of wild ginger, the oil yield was poor, the volume of EOs was 0.3 ml per 3 kg. The highest yield obtained was 0.28% and the lowest yield was 0.046% per 3 kg fresh rhizome.

3.2 Chemical constituents of the domestic and wild ginger essential oils by GCMS

The essential oil's chemical constituents of the domestic and wild ginger were identified using GCMS analysis. In total, 82 (42 from domestic and 51 from wild) chemical components were identified, representing 99.0% and 98.9% of the total constituents detected in the EOs from both domestic and wild ginger, respectively. The volatile phytochemical composition of domestic ginger EOs with the most abundant compounds were α-zingiberene (18.56%), geranial (13.88%), neral (10.75%), Trans-caryophyllene (9.64%), Eucalyptol (5.05%), β-phellandrene (5.51%), camphene (5.34%), α-pinene (2.05%) and heptan-2-ol (1.05%). The detailed identification and concentrations of the compounds found in both domestic and wild ginger EOs are presented in Table 2. The chemical compounds in the wild ginger EOs were monoterpenes such as isoeugenol, camphene, geranial, geranyl acetate, anethole, fenchyl acetate and neral as well as sesquiterpene hydrocarbons mainly α-humulene, α-urcumene, β-bisabolene, β-sesquiphellandrene, thus the most abundant compounds were isoeugenol (42.17%), caryophyllene (6.72%), β-bisabolene (5.10%), anethole (4.60%), Eucalyptol (1.41%), β-isabolol (1.98%), (-)-globulol (1.90%), α-curcumene (1.54%), α-humulene (1.74%), fenchyl acetate (1.49%), β-pinene (1.85%), alloaromadendrene (1.49%) and geranial (1.15%).

3.3 Chemical constituents of domestic and wild ginger rhizomes by headspace

Using headspace analysis of the domestic and wild ginger rhizomes revealed 27 (24 from domestic and 10 from wild) constituents, representing 99.4% and 99.9%, respectively of the total constituents detected. The dominant constituents of the domestic ginger rhizome were camphene (16.93%), Bisacurone epoxide (16.35%), Eucalyptol (14.90%), β-phellandrene (11.60%), α-zingiberene (7.17%), α-pinene (5.18%), geranial (4.14%), myrcene (4.08%), neral (2.87%), α-farnesene (2.81%), heptan-2-ol (2.31%), β-sesquiphellandrene (2.26%) and β-bisabolene (1.09%). For the wild ginger were β-phellandrene (72.73%), isoeugenol (3.98%), β-pinene (17.21%), and α-pinene (4.21%) (Table 3).

However, monoterpenes were present in the constituents of the two ginger rhizomes. The constituents were monoterpenes alcohols (heptan-2-ol, 4-terpineol); bicyclic monoterpenes (phellandrenes, camphene, borneol, pinenes); acyclic monoterpenoids like myrcene, geranyl acetate, geranial, neral and citronellol. Even though present were several sesquiterpenes such as farnesenes, β-bisabolene, α-zingiberene, curcumenes, caryophyllene, globulol. Some compounds were present in the wild ginger but absent in the domestic ginger rhizomes Tables 2 and 3. Furthermore, the wild ginger oils have isoeugenol (42.17%) as the major component identified, whereas α-zingiberene (18.56%) is the major constituent in the domestic ginger oils.

3.4 Determination of antifungal activity of essential oils (in-vitro)

Findings of this study showed that the assayed EOs had different degrees of growth inhibition against the five fungal species. The antifungal activity of the EOs (Table 4) suggests that the ginger EOs has antifungal effect. Considerable variation in the concentrations of the EOs ranging from 1 to 6 µl/ml was observed to have effect on the fungal pathogens. The fungal pathogens exhibited considerable inhibition even at a lower concentration (1 µl/ml). Fusarium oxysporum exhibited the highest inhibition (50.38 ± 0.5) and the lowest was G. boninense (27.46 ± 0.5) at a concentration of 1 µl/ml. The order of the sensitivity (descending order) was F. oxysporum > C. falcatum > P. oryzae > R. microporus > G. boninense. Mycelial inhibition was dependent on the index of concentrations because the diameter of inhibition increased with the increasing concentration of the EOs. Mycelial growth inhibition was observed in F. oxysporum and C. falcatum to be the same at 2 µl/ml (57.19 ± 0.3).

However, mycelial growth inhibition was also observed in all the sampled fungi. The percentage range of the suppression was from 50% to 100%. The positive control (Azoxystrobin/Difenoconazole) was effective at lower concentration because it demonstrated higher inhibition zones against all the fungal strains. Inhibition zones were not observed with the negative control. The minimum fungicidal concentrations of the ginger EOs on the tested isolates were in the range of 5–6 µl/ml, suggesting the fungicidal effects on the five fungi at > 5 µl/ml (Table 5).

3.5 Determination of in-vitro antibacterial activity of the essential oils

The ginger EOs showed different degrees of growth inhibition of the assayed EOs against the five bacterial species. The growth of the tested pathogens was affected by the concentration EOs which ranged from 100 to 500 µl/ml. In this present study, X. oryzae pv. oryzae-strain-A was affectively controlled by the EOs at 400 µl/ml and 500 µl/ml. The mean diameters of inhibition zone for 400 µl/ml and 500 µl/ml were 20.66 and 22.66 mm, respectively. The inhibition areas of X. oryzae pv. oryzae-strain-B at similar concentration were 17.33 and 18.66 mm, respectively (Table 4). Bacillus sp. recorded the lowest effect in which the mean diameter of the inhibition zones at 400 µl/ml and 500 µl/ml were 13.00 and 17.66 mm, respectively. These findings suggest significant antibacterial activity against X. oryzae pv. oryzae-strain-A, X. oryzae pv, oryzae-strain-B, R. solanacearum, Klebseilla sp. and least effective against Bacillus sp. The EOs' minimum inhibitory concentration (MIC) was determined and reported in Table 5. The MIC value of ginger EOs was 100 µl/ml. The effectiveness of antibacterial activity varied depending on the species of pathogens.

3.6 Metabolomic analysis of chemical constituents of ginger essential oils

The results obtained from the multivariate analysis of GC-mass spectral data of EOs for the domestic (DMT) and wild (WLD) gingers are shown in the PCA model against X. oryzae pv. oryzae-strain-A. The validity of PCA model was measured by the relative values of R2X and Q2 respectively, which are the goodness of a model's fit and predictive performance. Model fitness and predictive capacity are considered good when the values Q2 and R2 are>0.5. R2X (cum) = 0.87 and Q2 = 0.69, indicating how well the model fit and good predictively, each point represented one sample in the score plot.

The PC1 explained 56.5% of the variation between the two different observations whereas PC2 explained 30.5% of the variability. Hence, the model explained a total of 87.0% of the data set variation. Fig. 3 shows the score plot of all the variables from the two EOs group (DMT and WLD) with good separation by PC1. Significant outliers were not observed. The respective loading plot shows a concentrated distribution of metabolites in the middle, suggesting that the two groups might share high similarity in metabolites (Fig. 1).

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Fig. 1

Score and scattered plot of the observation (PCA) showing all the variables from the two EOs groups (DMT and WLD) have good separation by PC1 suggesting that the two groups might share high similarity in metabolites from the scattered plot.

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In the loading column plot (Fig. 2), the elements of the PCA loading vector represent the weights that combine the X-variables (domestic (DMT) and wild (WLD) ginger) to form the score vector. They are also proportional to the correlations between the scores and each X-variable.

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Fig. 2

Metabolomic analysis of domestic and wild EOs. (A) Score and scattered plot of the observation (PLS) showing all the variables from the two EOs group (DMT and WLD) have good separation by PC1. Suggesting that the two groups might share high similarity in metabolites from the scattered plot and (B) Loading column plot (PLS model) of simplified relevant metabolites in a threshold of VIP > 1 representing a total of 13 discriminating metabolites.

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Fig. 3

The bi-plot of the simplified relevant metabolites in a threshold of VIP > 1 showing 13 metabolites with clear contribution from α-Zingiberene, (-)-β-Sesquiphellandrene and Eucalyptol in the bioassay activity.

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The PLS model carried out the detection and comparison of metabolites present in ginger EOs with respect to the bioactivity. The developed PLS model was efficient as shown by parameters R2Y = 0.986 and Q2 = 0.96, respectively. These values indicate the fit and predictability of goodness. The scores plot shows PCs and sample classification. Hence, the model explained 86.2% of the data set variation (Fig. 2A). Bioassay of related metabolites are conveniently defined in the loading plot by their correlation with the PCs that distinguish sample groups. Differential metabolites contributing to the correlation were identified using variable importance for the projection (VIP) value. In general, a threshold of VIP > 1 was considered as the relevant metabolites for interpreting the discrimination. Subsequently, accurate mass determination, elemental composition analysis, GCMS fragmentation and search of metabolite spectral databases establish the chemical identities of bioactive phytochemicals/reactive metabolites (putative compounds). The robustness of the model was also verified through further testing by a 100-permutation test which signifies a very good prediction. A total of 13 discriminating metabolites (Table 6) resulting from model group were obtained when compared with reported metabolites presented in Table 2.

The cross-validated PLS model showed a strong correlation between ginger EOs and Xoo-A bio-efficacy. The results indicate that 13 metabolites in the bioassay (Fig. 2B). This suggest clear activity by α-zingiberene, β-sesquiphellandrene and Eucalyptol (Fig. 3). Their functions in inhibiting X. oryzae pv. oryzae-strain-A growth were thoroughly ascertained. However, the PLS is a supervised calibration approach which enables the details of ginger components to be compared with the response data from the bioactivity instead of describing the variance of both gingers as PCA does. Conclusively, the results for multivariate analysis of GC-mass spectral data of both ginger EOs were considered with a good fitness and predictability of the constructed PCA and PLS models accordingly. It also showed that the metabolomics approach is an effective way of gaining insights into the metabolite responses to the X. oryzae pv. oryzae-strain-A bio-efficacy.

3.7 Scanning electron microscopy (SEM) observation on the mode of action of ginger EOs against Xanthomonas oryzae pv. oryzae-strain A

The examination of the changes on morphology and integrity of X. oryzae pv. oryzae-strain-A cells in response to ginger EOs treatment at MIC concentration (100 µl/ml), streptomycin (15 µg/ml/disc) and control with DMSO was carried out using scanning electron microscopy. The scanning electron micrograph revealed that normal untreated cells of X. oryzae pv. oryzae-strain-A was typically rod shaped with a normal, smooth and bright surface without any apparent cellular debris (Fig. 4A). However, the Xoo cells with ginger EOs demonstrated irregular shape with sunken surfaces and severely disruption of cells (Fig. 4B). Similarly, effects of the antibiotics on X. oryzae pv. oryzae-strain-A cells caused abnormal growth, lysis, shrinkage, disruption, and aggregation of cells (Fig. 4C). Thus, by electron microscopy (SEM), it can be inferred that the EOs interrupts the cell's structure with sunken surfaces and produces substantial damage that ultimately leads to X. oryzae pv. oryzae-strain-A growth inhibition.

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Fig. 4

Scanning electron micrograph of ginger EOs causes ultrastructural modifications in Xanthomonas oryzae pv. oryzae-strain A cells. (A) The Xoo cells treated with DMSO (control) showing Xoo cells with a normal rod shape, smooth and bright surface, (B) The Xoo cells treated with the ginger EOs showed irregular shape with sunken surfaces, severely disruption of the cells and (C) The Xoo cells treated with (Streptomycin (15 µg/ml) display abnormal growth, shrinkage, disruption and aggregation of the cells.

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