1. bookVolume 70 (2021): Issue 4 (December 2021)
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2544-4646
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Chemical Components of Aqueous Extracts of Melia azedarach Fruits and Their Effects on The Transcriptome of Staphylococcus aureus

Published Online: 29 Oct 2021
Volume & Issue: Volume 70 (2021) - Issue 4 (December 2021)
Page range: 447 - 459
Received: 20 Jun 2021
Accepted: 15 Sep 2021
Journal Details
License
Format
Journal
eISSN
2544-4646
First Published
04 Mar 1952
Publication timeframe
4 times per year
Languages
English
Abstract

Staphylococcus aureus is the causative agent of numerous and varied clinical infections. Crude aqueous extracts of Melia azedarach fruits inhibit the planktonic growth and initial biofilm formation of S. aureus in a dose-dependent manner. Moreover, the biofilm topologies became sparse and decreased as the concentration of the aqueous extracts increased. RNA-Seq analyses revealed 532 differentially expressed genes (DEGs) after S. aureus exposure to 0.25 g/ml extracts; 319 of them were upregulated, and 213 were downregulated. The majority of DEGs were categorized into abundant sub-groups in the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Finally, untargeted UHPLC-MS/MS analyses of the aqueous extracts of M. azedarach fruits demonstrated a highly complex profile in positive and negative electrospray ionization modes. The extracts primarily consisted of lipids and lipid-like molecules, organic acids and their derivatives, phenylpropanoids, polyketides, organoheterocyclic compounds, and benzenoids annotated by abundant lipid maps and KEGG pathways. Overall, this study provides evidences that the aqueous extracts of M. azedarach fruits can control S. aureus infections and sought to understand the mode of action of these extracts on S. aureus.

Keywords

The planktonic growth (A) and biofilm formation (B) of Staphylococcus aureus can be inhibited by aqueous extracts of Melia azedarach fruits in a dose-dependent manner

Introduction

Melia azedarach (chinaberry) tolerates a wide range of adverse environmental settings so that it is commonly found in tropical, subtropical, and warm temperate areas as an ornamental plant, shade tree, and a source of fuel (Khan et al. 2011). In the past decades, various components have been extracted from chinaberry leaves, bark, fruits, and roots with different approaches. The active ingredients exhibited antimicrobial activities, which might be affected by the solvents used in the extraction and the parts of this plant that the extracts were from (Khan et al. 2011; Zahoor et al. 2015). Chinaberry leaves, roots, and bark extracted with methanol, petrol, dichloromethane, and ethyl acetate exhibited a broad spectrum of antibacterial activity, but the dichloromethane fraction of the bark was the most effective (Khan et al. 2001). A methanol extract of chinaberry flowers demonstrated potential antibacterial effects on Staphylococcus aureus when evaluated with a rabbit skin infection model (Saleem et al. 2002).

The antibacterial activities of chinaberry leaves extract in aqueous or chloroform on two Gram-positive bacteria, Bacillus subtilis and S. aureus, and three Gram-negative bacteria, Escherichia coli, Pseudomonas aeruginosa, and Klebsiella pneumoniae, were assessed using the agar well diffusion method. The extracts exhibited a relatively higher zone of inhibition at 75 μl/ml than at concentrations of 25 and 50 μl/ml, and the aqueous extracts were more effective at inhibiting the bacteria than those extracted in chloroform at the specific concentrations tested. It suggests that the leaf extracts caused inhibition in a dose-dependent manner, and the solvents used in extraction also influenced the activities (Suresh et al. 2008).

However, another study found that the alcoholic extracts of chinaberry leaves were more potent than those extracted with methanol, petroleum ether, and water when tested against eight human pathogens, including E. coli, P. aeruginosa, B. cereus, S. aureus, Fusarium oxisporum, Aspergillus niger, Rhizopus stolonifera, and Aspergillus flavus (Sen and Batra 2012). Antibacterial activities of the crude methanolic extracts of chinaberry were measured using an agar well diffusion method, but E. coli was highly resistant to the extracts at all doses tested (Zulqarnain et al. 2015). It suggests that the antibacterial activity of crude extracts of chinaberry varies with the microorganisms’ species.

In addition, the antibacterial spectrum of the same chinaberry extracts was affected by the solvents used in the extraction process. The antimicrobial, antioxidant, and cytotoxic activities of chinaberry bark extracted with various solvents were assayed. The results showed that the chloroform extract was active against both Enterobacter aerogenes and Proteus mirabilis, while both n-hexane and butanol were the most effective at inhibiting E. aerogenes. Simultaneously, aqueous and methanolic extracts were the most effective against P. mirabilis, and ethyl acetate was the most effective against P. aeruginosa (Zahoor et al. 2015).

Bacterial biofilms are complex, multi-species bacterial communities that are usually highly resistant to antimicrobial agents (Mah 2012; Zhou et al. 2015). However, chinaberry extracts have been shown to have strong antimicrobial effects against the microorganisms producing recalcitrant biofilm, including Acinetobacter guillouiae, Alcaligenes faecalis, Bacillus pumilus, Bacillus safensis, Brevundimonas alba, Microbacterium lacticum, Staphylococcus equorum, and Staphylococcus saprophyticus, which were isolated from dental plaques (Khalid et al. 2017).

In addition to their antibacterial activities, the bioactive phytochemicals were also isolated and identified from chinaberry extracts. The human pathogens Enterococcus faecalis, E. coli, P. aeruginosa and Klebsiella oxytoca were susceptible to extracts from chinaberry leaves, particularly the petroleum ether fraction that consists of secondary metabolites, such as alkaloids, terpenes/sterols, saponins, tannins and anthocyanins (Rojas Sierra et al. 2012). A variety of compounds have been found in the methanolic extracts from chinaberry, including propanedioic acid, butanedioic acid, diethyl ester, 2-pyrrolidinyl-methylamine, 2-piperidimethanamine, and trichloromethane (Al-Marzoqi et al. 2015). In addition, a substantial number of different ingredients were also isolated and identified from chinaberry by different research groups, which repeatedly demonstrated that the components of extracts varied with the extracted parts, solvents, and methodology.

Taken together, the antimicrobial activities and bioactive agents of extracts of chinaberry have been widely studied by different laboratories. However, the underlying modes of action of these extracts on bacteria remain elusive. Thus, in this study, we tried to extract components from chinaberry fruits using simple boiling water methods, and the differentially expressed genes (DEGs) were detected with RNA-Seq using S. aureus as a model strain. The results demonstrated that various growth and metabolism-related genes and pathways were affected by the aqueous extracts of chinaberry fruits. Moreover, lipids and lipid-like molecules, organic acids, and derivatives were relatively abundant in these extracts.

Experimental
Materials and Methods

Bacterial strains and chemicals. The bacterial strain S. aureus ATCC 6538 was purchased from the American Type Culture Collection (ATCC) and was cultivated in Luria Bertani (LB) medium that consisted of 5 g/l yeast extract (Oxoid, Hampshire, England), 10 g/l NaCl (Sigma-Aldrich, St. Louis, MO, USA) and 10 g/l peptone (Oxoid) without any antibiotics at 37°C in a shaking incubator. All the chemicals used in this study were of analytical grade and supplied by Sigma-Aldrich (St. Louis, MO, USA) unless indicated otherwise.

Extractions of chinaberry fruits with water. The chinaberry fruits purchased in Sichuan (China) were first washed with pure water to remove dust, dried to a constant weight at 65°C, and then crushed into powders using a grinder (Tianchuang Powder Technology Co., Ltd., Changsha, China). An aliquot of 100 g of the ground powders was weighed and dissolved in 1,000 ml of distilled water, sonicated with an ultrasound instrument (Anpu Experimental Technology Co, Ltd., Shanghai, China) for 30 min at room temperature, heated, and boiled for 30 min, and sonicated again for another 30 min. The samples were filtered with 200-mesh gauze to obtain the crude extracts. The filter residues were subsequently added to 500 ml of distilled water, boiled for another 30 min, filtered with 200-mesh gauze, and the extracts obtained were combined with the previous extracts and centrifuged at 13,000 rpm for 10 min. The supernatants were then transferred into a new plastic tube, filtered through a 400-mesh nylon filter using a gas-liquid diaphragm vacuum pump (Huankai Microbiology Technology Co. Ltd., Guangzhou, China), and the filtered samples were re-filtered through a 0.45-μm membrane using the same vacuum pump. Finally, the samples that had been filtered twice were placed in a rotary evaporator (Ailang Instrument Co. Ltd., Shanghai, China) with a vacuum degree of –0.1 ~ –0.08 MPa to concentrate the liquid to 100 ml under reduced pressure to ensure that the final concentration of the bioactive reagents was approximately 1.00 g/ml. After sterilization at 121°C for 20 min, the concentrated extracts were stored in a refrigerator at 4°C for future use.

Semi-quantitative measurements of S. aureus biofilms. The biofilm biomass formed by S. aureus was measured using a crystal violet staining method in flat-bottomed polystyrene microtiter plates (Corning Inc., Corning, NY, USA), as previously described with minor modifications (Stepanović et al. 2000; Zhou et al. 2019). Briefly, each well of one column of a 96-well microtiter plate was inoculated with 150 μl of S. aureus suspensions with an optical density (OD600) of approximately 0.05 and 50 μl of aqueous extracts of chinaberry fruits to final concentrations of 0, 0.25, 0.33, 0.50, and 1.00 g/ml. Moreover, the negative controls contained only LB medium. The inoculated plates were then placed in a static incubator with a constant temperature at 37°C and cultured for 48 h. Before staining, the OD600 of planktonic cells was detected with a Multiskan GO plate reader (Thermo Fisher Scientific, Waltham, MA, USA). Next, the plates were gently washed three times with sterile water to remove all the planktonic cells. The biofilms formed on the inner wall of the plates were finally stained with 250 μl of crystal violet (0.1%, w/v; Shanghai Chemical Reagents Co. Ltd., Shanghai, China) for at least 30 min at room temperature. After removing the crystal violet, the stained biofilms in each well were finally dissolved in 260 μl of 95% ethanol (v/v; Shanghai Chemical Reagents Co. Ltd.), and the OD590 of each well was determined using the same Multiskan GO reader (Thermo Fisher Scientific). All the experiments were conducted with eight replicates and repeated at least three times on different days.

Confocal laser scanning microscopy (CLSM) observation of biofilm topographies. The biofilms of S. aureus that had formed on pre-sterilized glass cover slides were observed by CLSM as previously described with minor modifications (Shukla and Rao 2013; Zhou et al. 2013). Briefly, the wells of a 24-well polystyrene microtiter plate with glass coverslips inside were inoculated with 2 ml aliquots of S. aureus suspensions (final OD600 = 0.05), and different concentrations of water extracts of chinaberry fruits (final concentrations 0, 0.25, 0.33, 0.50, and 1.00 g/ml). The microtiter plates were then transferred to an incubator and incubated at static conditions at 37°C for 48 h. To assay the biomass and observe the topographies of the attached S. aureus biofilms, 5 μM of SYTO9 fluorescent dye (Invitrogen, Carlsbad, CA, USA) was used to dye the slips for 20 min in the dark, as previously reported (GrayMerod et al. 2005). Finally, the stained biofilms were visualized and photographed using a Zeiss LSM 710 (Jena, Germany), and the live bacteria encased in the biofilms were dyed fluorescent green. The CLSM images obtained under different conditions were analyzed in more detail using COMSAT 2.1 software to evaluate the biomass, maximum, and average height of the biofilms formed (Heydorn et al. 2000).

Transcriptomic sequencing (RNA-Seq) and data analyses.S. aureus was cultured statically in 96-well microtiter plates in the presence of 0.25 g/ml aqueous extracts of chinaberry fruits at 37°C. After 2 days of cultivation, the cultured planktonic cells of S. aureus were harvested from wells, the pellets were collected by centrifugation, and sent to the Guangzhou Meige Biotechnology Company (Guangzhou, China) for RNA extraction and RNA-Seq library preparation. The chinaberry fruits cultured without any water extracts were the control samples, and were simultaneously sent to the sequencing company. After cluster generation, the prepared RNA-Seq library was then sequenced on an Illumina NovaSeq platform (San Diego, CA, USA), and the paired-end reads of 150 bp were generated. Moreover, the clean data were acquired by removing low-quality reads and the reads that contained adapter and ploy-N from raw data. Differential expression analyses of the two conditions/groups were calculated using the DESeq R package (1.18.0). Moreover, the approach of Benjamini and Hochberg was used to adjust the resulting p-values to control the false discovery rate. DEGs were assigned with an adjusted value of p < 0.05 and |fold-change| > 1.5. Gene Ontology (GO) enrichment analyses of the DEGs were processed using the GOseq R package, in which the gene length bias was synchronously corrected. Moreover, GO terms with corrected p-values less than 0.05 were considered to be significantly enriched by DEGs. In addition, the KOBAS software was utilized to test the statistical enrichment of DEGs in KEGG pathways (https://www.kegg.jp/kegg/pathway.html). In addition, the clean transcriptomic sequencing data were deposited in the NCBI Sequence Read Archive (SRA) under BioProject ID PRJNA723959.

Chemical composition of the aqueous extracts from chinaberry fruits. The chemical composition of aqueous extracts from chinaberry fruits was analyzed as previously described (Liu et al. 2020; Wright Muelas et al. 2020; Grabowska et al. 2021). A Vanquish UHPLC system (Thermo Fisher Scientific) equipped with an Orbitrap Q Exactive series mass spectrometer (Thermo Fisher Scientific) was utilized to analyze the chemicals from the LC-MS/MS chinaberry fruit extracts. The treated and filtered samples were transferred into a Hypersil Gold column (100 × 2.1 mm, 1.9 μm; Thermo Fisher Scientific) operating at a column temperature of 50°C. The samples were eluted at 0.4 ml/min flow rate over 15 min with 0.1% formic acid in water (solvent A) and 0.1% formic acid in methanol (solvent B). Moreover, 5 mM ammonium acetate at pH 9.0 (solvent A) and methanol (solvent B) were used as eluents in the negative polarity mode. The solvent gradient was performed as follows: 2% B, 1.5 min; 2–100% B, 12.0 min; 100% B, 14.0 min; 100–2% B, 14.1 min; and 2% B, 17 min. The Q Exactive series mass spectrometer (Thermo Fisher Scientific) was operated in a positive or negative polarity mode with a capillary temperature of 320°C, a spray voltage of 3.2 kV, an auxiliary gas flow rate 10 arb, and a sheath gas flow rate of 35 arb. The raw data files obtained by UHPLC-MS/MS were then processed with Compound Discoverer CD3.1 software (Thermo Fisher Scientific) to align the peaks and picks and quantify each metabolite. The main parameters in the analyses were set as follows: retention time tolerance, 0.2 min; signal intensity tolerance, 30%; actual mass tolerance, 5 ppm; minimum intensity, 100,000 and signal/noise ratio, 3; respectively. Subsequently, the acquired peak intensities were then normalized to the total spectral intensity. The acquired normalized data were continuously used to predict the molecular formula based on the molecular ion peaks, additive ions, and fragment ions. Finally, the peaks were processed to match the mzVault 2.1, mzCloud (https://www.mzcloud.org/), and MassList databases to obtain accurate and relative quantitative results. Statistical analyses in this section were performed with the statistical software R (version: R-3.4.3), Python (version: 2.7.6), and CentOS (CentOS release 6.6). Furthermore, the HMDB (http://www.hmdb.ca/), LipidMaps (http://www.lipidmaps.org/), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases (http://www.genome.jp/kegg/) were utilized to conduct the annotation of all metabolites identified.

Statistical analysis. All the data obtained were expressed as the mean ± standard deviation (SD) and were then subjected to a one-way analysis of variance (ANOVA) followed by comparing multiple treatment levels with the control using the Fisher’s LSD test. Moreover, when p-value < 0.05 was considered as significant. The statistical analyses were calculated using the data processing system (DPS) software (Tang and Feng 2007).

Results

Aqueous extracts of chinaberry fruits exhibit inhibitory effects on both planktonic growth and biofilm formation of S. aureus. In this study, the active components were extracted from chinaberry fruits using a simple water boiling method. The aqueous extracts were then used to test their effects on planktonic growth and the initial S. aureus biofilm formation in a static condition in 96-well microtiter plates. As expected, the planktonic growth of S. aureus was inhibited by the aqueous extracts of chinaberry fruits in a dose-dependent manner (Fig. 1A). In the presence of 0.25, 0.33, 0.50, and 1.00 g/ml aqueous extracts, the planktonic growth of S. aureus was repressed by approximately 17.63%, 76.05%, 89.32%, and 97.27%, respectively, compared with the controls (Fig. 1A). Furthermore, the biofilm formation of S. aureus treated with the same concentrations of aqueous extracts of chinaberry fruits was assayed with the crystal violet staining method. The results demonstrated that the aqueous extracts also inhibited the biofilms of S. aureus in a dose-dependent manner (Fig. 1B), which is like the efficiencies of the inhibition of planktonic growth. When treated with 0.25, 0.33, 0.50, and 1.00 g/ml aqueous extracts, the biofilm formation of S. aureus was repressed by approximately 51.68%, 77.83%, 93.22%, and 98.30%, respectively, compared with the controls (Fig. 1B). These results revealed that aqueous extracts of chinaberry fruits can inhibit not only planktonic growth but also the S. aureus biofilm formation in a dose-dependent manner.

Fig. 1.

Effect of aqueous extracts of Melia azedarach fruits on planktonic growth (A) and biofilm formation (B) of Staphylococcus aureus ATCC 6538. S. aureus ATCC 6538 was cultured on LB media supplemented with different concentrations of aqueous extracts of chinaberry fruits at 37°C for 48 h. The S. aureus planktonic cells and biofilms stained with crystal violet were measured at OD600 and OD590, respectively, using a Multiskan GO plate reader.

Biofilm topographies of S. aureus can be influenced by the aqueous extracts of chinaberry fruits. As shown in Fig. 1B, since the initial biofilm of S. aureus formed on a polystyrene surface can be influenced by the aqueous extracts of chinaberry fruits, we sought to determine whether the biofilm topographies of this strain built on a glass surface could be affected by these extracts. Therefore, the initial S. aureus biofilm was first allowed to be formed on glass cover slips, and then stained with the fluorescent dye SYTO9, and finally observed under CLSM. The results demonstrated that when cultured for 2 days, a typical S. aureus biofilm could be formed on the surface of the glass slips (Fig. 2A). However, the biofilms on these slips decreased and became sparse with the increasing concentrations of the aqueous extracts (Fig. 2B-2E). Furthermore, the biofilms-related parameters were also calculated using the COMSTAT based on the images obtained from CLSM. The results showed that the average thickness and total biomass, with the exception of maximum thickness, of the formed biofilms that formed when cultured without aqueous extracts treatments were always higher than those harvested in the presence of various concentrations of aqueous extracts (Table I).

Fig. 2.

Representative CLSM images of Staphylococcus aureus ATCC 6538 biofilms grown in the presence of different concentrations of aqueous extracts of Melia azedarach fruits and stained with SYTO9. The biofilms were cultivated on the surface of glass coverslips for 48 h at 37°C. The constructed biofilms were stained with the fluorescent dye SYTO9 and then observed under a Zeiss LSM 710 CLSM. Scale bar = 50 μm. CLSM, confocal laser scanning microscopy.

Quantification of biofilm topologies in the presence of different concentrations of aqueous extracts of Melia azedarach fruits.

ParametersControl0.25 g/ml0.33 g/ml0.50 g/ml1.00 g/ml
Maximum thickness (μm)  10 ± 0.00a  10 ± 0.00a  10 ± 0.00a  10 ± 0.00a  10 ± 0.00a
Average thickness (μm)7.75 ± 0.10a6.68 ± 0.36b3.37 ± 0.17c2.11 ± 0.19d1.11 ± 0.03e
Total biomass (μm3/μm2)9.81 ± 1.78a6.97 ± 0.08b2.98 ± 0.25c1.40 ± 0.24cd0.22 ± 0.02d

Different letters marked in the same row represent the significant differences among different treatments (p < 0.05)

RNA-Seq results and DEGs. Since both bacterial growth and the initial biofilm formation of S. aureus could be inhibited by aqueous extracts of chinaberry fruits, our next goal was to elucidate the underlying modes of action of the aqueous extracts on S. aureus cells. Therefore, the samples of S. aureus planktonic cells treated with or without 0.25 g/ml aqueous extracts were harvested and subjected to RNA-Seq to acquire their transcriptome sequence data using an Illumina NovaSeq platform. The sequencing results identified 15,306,690; 16,228,122; 14,710,464; 15,424,438; 15,052,636; and 14,875,448 clean reads for the controls and treatments with three replicates, respectively. Moreover, the DEGs between controls and treatments were also analyzed with the DESeq R package (1.18.0). A total of 532 DEGs, of which 319 were activated, and 213 were inhibited, were identified when S. aureus planktonic cells were treated with 0.25 g/ml aqueous extracts of chinaberry fruits based on the following criteria identified: DESeq2 padj < 0.05 and |log2Fold-Change| > 1.5.

Various GO and KEGG pathways can be affected by the aqueous extracts of chinaberry fruits. In addition, GO analyses were also conducted to classify functions of the DEGs found in the RNA-Seq experiments. Based on the sequence homology, the DEGs were categorized into three classes that included biological process, cellular component, and molecular function, which have been shown as the first ten subgroups in each category (Fig. 3). Gene expression, membrane, and oxidoreductase activity were the largest subgroups enriched for the downregulated DEGs in biological process, cellular component, and molecular function, respectively (Fig. 3). Moreover, the oxidation-reduction process, membrane, and oxidoreductase activity were the most significant subgroups enriched for the up-regulated DEGs in biological process, cellular component, and molecular function, respectively (Fig. 3).

Fig. 3.

Histogram depiction of enriched Gene Ontology classification of the DEGs of Staphylococcus aureus ATCC 6538 treated with 0.25 g/ml aqueous extracts of Melia azedarach fruits. The results were categorized into three main categories of biological process, molecular function, and cellular component. The x-axis indicates the gene numbers in each subcategory. The top 10 subcategories in each main category are shown here.

To further elucidate these DEGs’ functions and explore the enriched metabolic or signal transduction pathways, the DEGs were also mapped to the terms from the KEGG pathway database (Fig. 4). Among the top 20 enriched KEGG pathways, the DEGs were significantly enriched for ribosome (KEGG pathway ID: pae03010) and valine, leucine, and isoleucine biosynthesis (pae00290).

Fig. 4.

Functional analysis of DEGs of Staphylococcus aureus ATCC 6538 treated with 0.25 g/ml aqueous extracts of Melia azedarach fruits based on the KEGG pathway. Among the top 20 pathways, the first two pathways, the ribosome (pae03010) and valine, leucine, and isoleucine biosynthesis (pae00290), were significantly enriched (padj < 0.05). The right y-axis represents the KEGG pathway. The x-axis exhibits the enrichment factor, which denotes the ratio of the DEG numbers to the annotated gene numbers enriched in a specific pathway. DEG, differentially expressed genes; KEGG, Kyoto Encyclopedia of Genes and Genomes.

Chemical components of the aqueous extracts of chinaberry fruits. Since S. aureus planktonic growth, biofilm formation, and the related GO and KEGG pathways could be influenced by the aqueous extracts of chinaberry fruits, we sought to determine the chemical components composed of these extracts. Thus, the chemical compositions of the aqueous extracts were characterized using a UHPLC-MS/MS-based non-targeted metabolomics approach to explain which active factors played roles in these biological processes. The results demonstrated that 681 and 339 metabolites were successfully identified under positive and negative ion modes, respectively. The basic characteristics of the top 25 metabolites in both the positive and negative ion modes are shown in Tables II and III, respectively. The detailed information, including the total ion intensity of the metabolites identified in chinaberry fruits’ aqueous extracts, is shown in supplementary Excel files S1 and S2.

Identification results of the top 25 metabolites from aqueous extracts of Melia azedarach fruits in a positive mode.

No.Compound_IDNameFormulaMolecular WeightRetention Time (min)
1Com_2_posD-Pyrrolidine-2-Carboxylic acidC5H9NO2115.06341.382
2Com_3_posDL-ArginineC6H14N4O2174.11151.425
3Com_6_posCholineC5H13NO103.09991.275
4Com_49_posL-Glutamic acidC5H9NO4147.05291.434
5Com_28_posNicotinic acidC6H5NO2123.03211.773
6Com_44_posPerillartineC10H15NO165.11527.342
7Com_30_pos6-Hydroxynicotinic acidC6H5NO3139.02681.988
8Com_59_posMaltolC6H6O3126.03185.271
9Com_21_posIsoamylamineC5H13N87.105174.875
10Com_75_pos5-oxoprolineC5H7NO3129.04261.45
11Com_71_posEthyl 4-amino-2-(methylsulfanyl)-1,3-thiazole-5-carboxylateC7H10N2O2S2218.0191.265
12Com_77_posDL-TryptophanC11H12N2O2204.08976.801
13Com_98_posEcgonine methyl esterC10H17NO3199.12068.349
14Com_103_posScopoletinC10H8O4192.04218.708
15Com_105_posGamma-Aminobutyric acidC4H9NO2103.06371.292
16Com_85_posKinetinC10H9N5O237.06352.048
17Com_104_posN-Acetyl-DL-serineC5H9NO4147.05291.284
18Com_116_posPipecolinic acidC6H11NO2129.0791.734
19Com_119_pos2-Methylenesuccinic acidC5H6O4130.02631.284
20Com_168_pos2-Picolinic acidC6H5NO2123.03211.523
21Com_165_pos6-O-(2-Methylbutanoyl)-α-D-glucopyranosyl α-D-glucopyranosideC17H30O12443.19978.133
22Com_135_pos(+/-)12(13)-DiHOMEC18H34O4296.234514.142
23Com_171_posCorylifol AC25H26O4390.182310.9
24Com_78_posOleoyl ethylamideC20H39NO309.302515.542
25Com_114_posCytidineC9H13N3O5243.08938.013

Identification results of the top 25 metabolites from aqueous extracts of Melia azedarach fruits in a negative mode.

No.Compound_IDNameFormulaMolecular WeightRetention Time (min)
1Com_2_negD-Saccharic acidC6H10O8210.03721.174
2Com_6_negPalmitic acidC16H32O2256.239714.6
3Com_4_negCitric acidC6H8O7192.02671.214
4Com_11_negN-Acetylneuraminic acidC11H19NO9309.10551.296
5Com_17_negElaidic acidC18H34O2282.255314.704
6Com_15_negSucroseC12H22O11402.1371.39
7Com_22_negD-(–)-LyxoseC5H10O5150.05261.268
8Com_21_negGluconic acidC6H12O7196.0581.256
9Com_29_negDL-Malic acidC4H6O5134.02141.186
10Com_23_neg4-OxoprolineC5H7NO383.037091.293
11Com_31_negPyruvic acidC3H4O388.015951.186
12Com_25_negD-(–)-FructoseC6H12O6180.06321.307
13Com_48_negGlutaconic acidC5H6O4130.02651.172
14Com_56_neg2-Furoic acidC5H4O3112.0161.155
15Com_47_negToosendaninC30H38O11574.241411.083
16Com_57_negα-Eleostearic acidC18H30O2278.224114.157
17Com_50_negα-LactoseC12H22O11388.12131.373
18Com_71_negNomilinC28H34O9514.219310.413
19Com_54_neg4-Acetamidobutanoic acidC6H11NO3145.07391.439
20Com_59_negD-(+)-GlucoseC6H12O6180.06321.484
21Com_70_neg6-SialyllactoseC23H39NO19633.21271.319
22Com_78_negPurineC5H4N4120.04221.274
23Com_77_neg2-C-methyl D-erythritol 4-phosphateC5H13O7P216.03991.27
24Com_72_negAzelaic acidC9H16O4188.10475.304
25Com_81_neg16-Hydroxyhexadecanoic acidC16H32O3254.224214.26

Functional annotation of the metabolites from aqueous extracts of chinaberry fruits. Three databases of HMDB, lipid maps, and KEGG pathways were used to annotate the functions of the metabolites from the aqueous extracts of chinaberry fruits. The annotation results demonstrated that a total of 242 and 148 metabolites under positive and negative ion modes were classified into 11 and 9 HMDB groups, respectively (Fig. 5). Among all the metabolites, 8.08% and 15.04% of the positive and negative ion modes referred to lipids and lipid-like molecules, respectively, following by organic acids and derivatives (6.46% and 8.26%, respectively), phenylpropanoids and polyketides (5.58% and 5.31%, respectively), organoheterocyclic compounds (5.43% and 4.72%, respectively), and benzenoids (3.52% and 3.83%, respectively; Fig. 5).

Fig. 5.

HMDB classification annotation of the components of aqueous extracts of Melia azedarach fruits in both positive and negative ion modes. The x-axis represents metabolite numbers, and the y-axis represents annotated HMDB entries.

Furthermore, based on the classification notes of LIPID MAP, fatty acyls, polyketides, prenol lipids, and sterol lipids were found in both the positive and negative ion modes (Fig. 6). However, there are different numbers of metabolites that are members of different groups from the positive and negative ion modes (Fig. 6).

Fig. 6.

Lipidmaps classification annotation of components of aqueous extracts of Melia azedarach fruits in both positive and negative ion modes. The x-axis represents metabolite numbers, and the y-axis represents annotated Lipidmaps entries.

In addition, the three main KEGG pathways of metabolism, genetic information processing, and environmental information processing were enriched for approximately 184 and 137 metabolites in the positive and negative ion modes, respectively (Fig. 7). In a positive mode, most metabolites take part in global and overview maps, biosynthesis of other secondary metabolites, and amino acid metabolism (Fig. 7). In contrast, in the negative mode, the pathways of global and overview maps, amino acid metabolism, and carbohydrate metabolism occupy most of the metabolites (Fig. 7).

Fig. 7.

KEGG enrichment chart of the components of aqueous extraction of Melia azedarach fruits in both positive and negative ion modes. The x-axis represents metabolite numbers, and the y-axis represents enriched KEGG pathways. KEGG, Kyoto Encyclopedia of Genes and Genomes.

Discussion

S. aureus is frequently found in the respiratory tract, human nose, and on the skin, so that it has been regarded as the most common cause of nosocomial infections (Archer 1998). However, it has been reported that the growth of S. aureus could be inhibited by the extracts of chinaberry leaves, barks, fruits, flowers, essential oils, and seeds (Kaneria et al. 2009; Liu et al. 2010; Kharkwal et al. 2015; Zulqarnain et al. 2015; Hadadi et al. 2020). Moreover, ordinary water was used as a solvent to extract active physiochemical ingredients from chinaberry. The antibacterial activity of chinaberry leaves was evaluated using an agar well diffusion method by measuring the inhibitory diameter of bacterial growth zones with 25, 50, and 75 μl of aqueous and solvent leaf extracts. The results indicated that the growth of S. aureus was inhibited by phytochemical compounds of aqueous extracts of chinaberry leaves, which is better than that extracted by chloroform in the three concentrations tested (Suresh et al. 2008).

In this study, we found that the crude aqueous extracts of chinaberry fruits inhibited S. aureus planktonic growth in a dose-dependent manner (Fig. 1A), although only water was used to extract the bioactive agents from the chinaberry fruits. Similar assays were also conducted by Sen and Batra (2012). However, they found that the antimicrobial activity of the aqueous extracts of chinaberry leaves to S. aureus exhibited comparatively lower efficiencies than those extracted by ethanol based on the agar well diffusion method or the minimum inhibitory concentrations. In addition, the petrol, benzene, ethyl acetate, methanol, and aqueous extractions of the mature seeds of chinaberry demonstrated inhibitory activities on S. aureus growth depending on the concentrations of the extracts, and it was also found that the most effective crude extract was not aqueous but ethyl acetate (Khan et al. 2011). The above findings, including ours, suggest that the anti-S. aureus efficiencies of extracts vary with the extracted parts of chinaberry. In other words, different parts of chinaberry may possess different bioactive agents that inhibit S. aureus.

Furthermore, S. aureus biofilms are cellular communities encased by self-produced three-dimensional polymers of hydrated extracellular polymeric substances (EPS) consisting primarily of water, polysaccharides, nucleic acids, proteins, and lipids (Flemming and Wingender 2010). It has been proven that biofilm-associated S. aureus is the pathogen of many human diseases, including osteomyelitis, endocarditis, and other infections (Götz 2002). Moreover, the construction of S. aureus biofilms increases its resistance to antimicrobial agents and poses a severe burden in healthcare settings (Suresh et al. 2019). Many studies have primarily focused on exploiting novel therapeutic strategies or approaches to eradicate infections associated with S. aureus biofilms (Lister and Horswill 2014; Bhattacharya et al. 2015; Abreu et al. 2016). In this study, we found that planktonic cells and the biofilms of S. aureus could be inhibited by aqueous extracts of chinaberry fruits (Fig. 1A and 2), which predicts a function for the aqueous extracts of these fruits to control S. aureus infections. Moreover, there is a consistent decrease in the trends of planktonic growth and biofilm formation of S. aureus in the presence of different concentrations of aqueous extracts of chinaberry fruits. Thus, we hypothesized that the decrease in S. aureus biofilm formation in the presence of aqueous extracts of chinaberry fruits might be induced by the decreases in planktonic growth (Fig. 1).

Subsequently, we sought to determine how the aqueous extracts of chinaberry fruits inhibit the growth of S. aureus. Therefore, the transcriptome of S. aureus exposed to aqueous extracts of chinaberry fruits was explored using the RNA-Seq method. The results indicated that the genes of the ribosome (pae03010), peptidoglycan biosynthesis (pae00550), DNA replication (pae03030), and phenylalanine, tyrosine, and tryptophan biosynthesis (pae00400), which are crucial for S. aureus protein synthesis, metabolism, and survival, were primarily inhibited by the aqueous extracts of chinaberry fruits (Fig. 3 and 4), which partially explained the mode of action of these extracts on the growth of S. aureus.

In addition, the crude extracts from chinaberry were evaluated for their antimicrobial efficiencies. A substantial number of active components were also separated and identified from different chinaberry parts, such as leaves, bark, fruit, and seeds. A substantial number of compounds extracted by methanol were found using GC-MS in chinaberry leaves, and the results demonstrated that the extracts contained trichloromethane, 2-pyrrolidinyl-methylamine, propanedioic acid, diethyl ester, and 2-piperidimethanamine, among others (Al-Marzoqi et al. 2015). The ethanol extracts of chinaberry leaves exhibited significant antimicrobial activity to several bacteria, including S. aureus. Further isolation and identification using TLC chromatograms and GC/MS demonstrated that the compound 5,6,7,8-tetrahydro-1,2,4-benzotriazine-3-amine might be responsible for the antimicrobial activity (Kathireshan et al. 2019). A GC-MS analysis of the hexane extracts of chinaberry leaves showed a highly complex profile that contained ketones, fatty acid derivatives, ethers, 1,3-dipalmitate, methyl esters, 7,8-dihydrocarpesterol, and 2-undecanol (Habib et al. 2017). The methanolic fraction of the aerial parts of chinaberry contained steroids, anthraquinones, phenolics, flavonoids, and tannins (Malar et al. 2020). The metabolites of chinaberry flowers included branched and n-hydrocarbons, fatty acids, aromatics, fatty acid methyl esters, polyisoprenoids, and fatty alcohols (Muhammad et al. 2015). Taken together, there are various compounds extracted from various parts of chinaberry with different solvents. The extracted methods and solvents also simultaneously influenced the constituents of chinaberry extracts.

Herein, we also sought to explore the bioactive agents in the aqueous extracts of chinaberry fruits extracted in this study. Using UHPLC-MS/MS analyses, we found that the aqueous extracts from chinaberry fruits contain lipids and lipid-like molecules, organic acids and derivatives, phenylpropanoids and polyketides, organoheterocyclic compounds, and benzenoids (Fig. 5), which play an important role in inhibiting planktonic growth and biofilm formation (Fig. 1 and 2). In particular, the water extractions of chinaberry fruits also contained a substantial proportion of toosendanin, which is a potential treatment for parasites in the digestive tract and agricultural insecticides (Shi and Li 2007). It also exhibited significant inhibitory effects on the growth of S. aureus (data not shown). In contrast, the major components extracted from chinaberry fruits with hexane were methyl palmitate (18.8%), methyl linolenate (16.1%), and methyl linoleate (9.8%) (Hadjiakhoondi et al. 2006). A sequential extraction from chinaberry fruits was performed in four steps with scCO2, a scCO2/ethanol mixture, ethanol, and an ethanol/water mixture. As a result, linoleic, palmitic, and myristic fatty acids were identified in the supercritical extracts; moreover, caffeic, and malic acid were found in other extracts (Bitencourt et al. 2014).

This study demonstrated that the active components from chinaberry fruits, which inhibited the planktonic growth and biofilm formations of S. aureus, could be extracted using water with ultrasonic and boiling methods that are environmentally friendly. The main active components in the aqueous extracts of chinaberry fruits are lipids and lipid-like molecules, organic acids and derivatives, phenylpropanoids, polyketides, organoheterocyclic compounds, and benzenoids, which affect the gene expression of protein synthesis, metabolism, and transcriptional regulation at various levels. The results obtained in this study may help clarify the mode of action of aqueous chinaberry extracts on the growth of S. aureus and facilitate the further development and utilization of these extracts.

The planktonic growth (A) and biofilm formation (B) of Staphylococcus aureus can be inhibited by aqueous extracts of Melia azedarach fruits in a dose-dependent manner
The planktonic growth (A) and biofilm formation (B) of Staphylococcus aureus can be inhibited by aqueous extracts of Melia azedarach fruits in a dose-dependent manner

Fig. 1.

Effect of aqueous extracts of Melia azedarach fruits on planktonic growth (A) and biofilm formation (B) of Staphylococcus aureus ATCC 6538. S. aureus ATCC 6538 was cultured on LB media supplemented with different concentrations of aqueous extracts of chinaberry fruits at 37°C for 48 h. The S. aureus planktonic cells and biofilms stained with crystal violet were measured at OD600 and OD590, respectively, using a Multiskan GO plate reader.
Effect of aqueous extracts of Melia azedarach fruits on planktonic growth (A) and biofilm formation (B) of Staphylococcus aureus ATCC 6538. S. aureus ATCC 6538 was cultured on LB media supplemented with different concentrations of aqueous extracts of chinaberry fruits at 37°C for 48 h. The S. aureus planktonic cells and biofilms stained with crystal violet were measured at OD600 and OD590, respectively, using a Multiskan GO plate reader.

Fig. 2.

Representative CLSM images of Staphylococcus aureus ATCC 6538 biofilms grown in the presence of different concentrations of aqueous extracts of Melia azedarach fruits and stained with SYTO9. The biofilms were cultivated on the surface of glass coverslips for 48 h at 37°C. The constructed biofilms were stained with the fluorescent dye SYTO9 and then observed under a Zeiss LSM 710 CLSM. Scale bar = 50 μm. CLSM, confocal laser scanning microscopy.
Representative CLSM images of Staphylococcus aureus ATCC 6538 biofilms grown in the presence of different concentrations of aqueous extracts of Melia azedarach fruits and stained with SYTO9. The biofilms were cultivated on the surface of glass coverslips for 48 h at 37°C. The constructed biofilms were stained with the fluorescent dye SYTO9 and then observed under a Zeiss LSM 710 CLSM. Scale bar = 50 μm. CLSM, confocal laser scanning microscopy.

Fig. 3.

Histogram depiction of enriched Gene Ontology classification of the DEGs of Staphylococcus aureus ATCC 6538 treated with 0.25 g/ml aqueous extracts of Melia azedarach fruits. The results were categorized into three main categories of biological process, molecular function, and cellular component. The x-axis indicates the gene numbers in each subcategory. The top 10 subcategories in each main category are shown here.
Histogram depiction of enriched Gene Ontology classification of the DEGs of Staphylococcus aureus ATCC 6538 treated with 0.25 g/ml aqueous extracts of Melia azedarach fruits. The results were categorized into three main categories of biological process, molecular function, and cellular component. The x-axis indicates the gene numbers in each subcategory. The top 10 subcategories in each main category are shown here.

Fig. 4.

Functional analysis of DEGs of Staphylococcus aureus ATCC 6538 treated with 0.25 g/ml aqueous extracts of Melia azedarach fruits based on the KEGG pathway. Among the top 20 pathways, the first two pathways, the ribosome (pae03010) and valine, leucine, and isoleucine biosynthesis (pae00290), were significantly enriched (padj < 0.05). The right y-axis represents the KEGG pathway. The x-axis exhibits the enrichment factor, which denotes the ratio of the DEG numbers to the annotated gene numbers enriched in a specific pathway. DEG, differentially expressed genes; KEGG, Kyoto Encyclopedia of Genes and Genomes.
Functional analysis of DEGs of Staphylococcus aureus ATCC 6538 treated with 0.25 g/ml aqueous extracts of Melia azedarach fruits based on the KEGG pathway. Among the top 20 pathways, the first two pathways, the ribosome (pae03010) and valine, leucine, and isoleucine biosynthesis (pae00290), were significantly enriched (padj < 0.05). The right y-axis represents the KEGG pathway. The x-axis exhibits the enrichment factor, which denotes the ratio of the DEG numbers to the annotated gene numbers enriched in a specific pathway. DEG, differentially expressed genes; KEGG, Kyoto Encyclopedia of Genes and Genomes.

Fig. 5.

HMDB classification annotation of the components of aqueous extracts of Melia azedarach fruits in both positive and negative ion modes. The x-axis represents metabolite numbers, and the y-axis represents annotated HMDB entries.
HMDB classification annotation of the components of aqueous extracts of Melia azedarach fruits in both positive and negative ion modes. The x-axis represents metabolite numbers, and the y-axis represents annotated HMDB entries.

Fig. 6.

Lipidmaps classification annotation of components of aqueous extracts of Melia azedarach fruits in both positive and negative ion modes. The x-axis represents metabolite numbers, and the y-axis represents annotated Lipidmaps entries.
Lipidmaps classification annotation of components of aqueous extracts of Melia azedarach fruits in both positive and negative ion modes. The x-axis represents metabolite numbers, and the y-axis represents annotated Lipidmaps entries.

Fig. 7.

KEGG enrichment chart of the components of aqueous extraction of Melia azedarach fruits in both positive and negative ion modes. The x-axis represents metabolite numbers, and the y-axis represents enriched KEGG pathways. KEGG, Kyoto Encyclopedia of Genes and Genomes.
KEGG enrichment chart of the components of aqueous extraction of Melia azedarach fruits in both positive and negative ion modes. The x-axis represents metabolite numbers, and the y-axis represents enriched KEGG pathways. KEGG, Kyoto Encyclopedia of Genes and Genomes.

Identification results of the top 25 metabolites from aqueous extracts of Melia azedarach fruits in a positive mode.

No.Compound_IDNameFormulaMolecular WeightRetention Time (min)
1Com_2_posD-Pyrrolidine-2-Carboxylic acidC5H9NO2115.06341.382
2Com_3_posDL-ArginineC6H14N4O2174.11151.425
3Com_6_posCholineC5H13NO103.09991.275
4Com_49_posL-Glutamic acidC5H9NO4147.05291.434
5Com_28_posNicotinic acidC6H5NO2123.03211.773
6Com_44_posPerillartineC10H15NO165.11527.342
7Com_30_pos6-Hydroxynicotinic acidC6H5NO3139.02681.988
8Com_59_posMaltolC6H6O3126.03185.271
9Com_21_posIsoamylamineC5H13N87.105174.875
10Com_75_pos5-oxoprolineC5H7NO3129.04261.45
11Com_71_posEthyl 4-amino-2-(methylsulfanyl)-1,3-thiazole-5-carboxylateC7H10N2O2S2218.0191.265
12Com_77_posDL-TryptophanC11H12N2O2204.08976.801
13Com_98_posEcgonine methyl esterC10H17NO3199.12068.349
14Com_103_posScopoletinC10H8O4192.04218.708
15Com_105_posGamma-Aminobutyric acidC4H9NO2103.06371.292
16Com_85_posKinetinC10H9N5O237.06352.048
17Com_104_posN-Acetyl-DL-serineC5H9NO4147.05291.284
18Com_116_posPipecolinic acidC6H11NO2129.0791.734
19Com_119_pos2-Methylenesuccinic acidC5H6O4130.02631.284
20Com_168_pos2-Picolinic acidC6H5NO2123.03211.523
21Com_165_pos6-O-(2-Methylbutanoyl)-α-D-glucopyranosyl α-D-glucopyranosideC17H30O12443.19978.133
22Com_135_pos(+/-)12(13)-DiHOMEC18H34O4296.234514.142
23Com_171_posCorylifol AC25H26O4390.182310.9
24Com_78_posOleoyl ethylamideC20H39NO309.302515.542
25Com_114_posCytidineC9H13N3O5243.08938.013

Quantification of biofilm topologies in the presence of different concentrations of aqueous extracts of Melia azedarach fruits.

ParametersControl0.25 g/ml0.33 g/ml0.50 g/ml1.00 g/ml
Maximum thickness (μm)  10 ± 0.00a  10 ± 0.00a  10 ± 0.00a  10 ± 0.00a  10 ± 0.00a
Average thickness (μm)7.75 ± 0.10a6.68 ± 0.36b3.37 ± 0.17c2.11 ± 0.19d1.11 ± 0.03e
Total biomass (μm3/μm2)9.81 ± 1.78a6.97 ± 0.08b2.98 ± 0.25c1.40 ± 0.24cd0.22 ± 0.02d

Identification results of the top 25 metabolites from aqueous extracts of Melia azedarach fruits in a negative mode.

No.Compound_IDNameFormulaMolecular WeightRetention Time (min)
1Com_2_negD-Saccharic acidC6H10O8210.03721.174
2Com_6_negPalmitic acidC16H32O2256.239714.6
3Com_4_negCitric acidC6H8O7192.02671.214
4Com_11_negN-Acetylneuraminic acidC11H19NO9309.10551.296
5Com_17_negElaidic acidC18H34O2282.255314.704
6Com_15_negSucroseC12H22O11402.1371.39
7Com_22_negD-(–)-LyxoseC5H10O5150.05261.268
8Com_21_negGluconic acidC6H12O7196.0581.256
9Com_29_negDL-Malic acidC4H6O5134.02141.186
10Com_23_neg4-OxoprolineC5H7NO383.037091.293
11Com_31_negPyruvic acidC3H4O388.015951.186
12Com_25_negD-(–)-FructoseC6H12O6180.06321.307
13Com_48_negGlutaconic acidC5H6O4130.02651.172
14Com_56_neg2-Furoic acidC5H4O3112.0161.155
15Com_47_negToosendaninC30H38O11574.241411.083
16Com_57_negα-Eleostearic acidC18H30O2278.224114.157
17Com_50_negα-LactoseC12H22O11388.12131.373
18Com_71_negNomilinC28H34O9514.219310.413
19Com_54_neg4-Acetamidobutanoic acidC6H11NO3145.07391.439
20Com_59_negD-(+)-GlucoseC6H12O6180.06321.484
21Com_70_neg6-SialyllactoseC23H39NO19633.21271.319
22Com_78_negPurineC5H4N4120.04221.274
23Com_77_neg2-C-methyl D-erythritol 4-phosphateC5H13O7P216.03991.27
24Com_72_negAzelaic acidC9H16O4188.10475.304
25Com_81_neg16-Hydroxyhexadecanoic acidC16H32O3254.224214.26

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