Integrating gas-chromatographical analyses with nuclear-magnetic-resonance spectroscopy to elucidate anti-microbial profile of oleoresins isolated from Rauvolfia serpentina seeds by supercritical–(CO₂)–fluid extraction

Abstract

Rauvolfia serpentina (L.) Benth. Ex Kurz is a greatly appreciated medicinal plant, well-known for its therapeutic benefits in traditional medicine, particularly in Ayurveda, where the roots and whole plant are used to treat a variety of ailments. However, studies focusing on R. serpentina seeds are relatively scarce. Hence, the present study provides a novel approach by analysing the seed oil of R. serpentina extracted using the supercritical-carbon dioxide-fluid-extraction (SCFE) technique. The research employed advanced analytical methods including gas-chromatography with flame ionization detector (GC-FID), gas-chromatography-tandem mass spectrometry (GC-MS/MS), and high performance thin layer chromatography (HPTLC) to characterise the chemical composition of the extracted oil. Functional moieties were evaluated by Fourier transform infrared spectroscopy (FT-IR), while proton nuclear-magnetic-resonance (¹H NMR) spectroscopy was utilised to identify the phytometabolites as well as to assess the physico-chemical parameters. The anti-microbial potential of the supercritically extracted oil was demonstrated through its activity against Klebsiella pneumoniae. The inhibitory effects on K. pneumoniae were quantified using the broth microdilution method, showing activity at both minimum inhibitory concentrations (MIC₅₀ and MIC₉₀). Furthermore, the oil was found to be non-genotoxic, as demonstrated by the Ames assay, which showed no mutagenic effects against S. typhimurium and E. coli WP2 uvrA. Since previous reports on R. serpentina seeds and their novel contribution in the field of pharmaceutics are rather limited, the present study is of utmost importance. The study may pave the way for future investigations into the therapeutic potentials of R. serpentina seeds.

Graphical abstract

Highlights

• •Pioneer supercritical (CO₂) extraction was done on seeds of Rauvolfia serpentina L.
• •Utilised GC-FID and GC-MS/MS platforms for the identification of active biomarkers
• •Quantified phytometabolites using HPTLC, and validated by IR, and NMR techniques
• •Revealed strong bactericidal effects with non-genotoxic properties on various strains
• •Foremost studies on Rauvolfia serpentina seeds highlights its novel therapeutic role

1. Introduction

Rauvolfia serpentina (L.) Benth. ex Kurz, commonly known as Sarpagandha or Indian Snakeroot, is an ancient plant mentioned in the writings of Charaka, dating back to between 1000 and 800 B.C. The plant earned its Sanskrit name, Sarpagandha, due to the belief that its aroma could attract snakes. In India, it has long been a key element of Ayurveda and traditional medicine, where it is used to treat a variety of ailments, including as a neuroprotective agent [1]. In Ayurveda, R. serpentina is used to treat mental illnesses like schizophrenia, psychosis, and neuropsychiatric disorders, as well as for the treatment of high blood pressure, sleeplessness, asthma, acute stomachaches, and painful deliveries. Moreover, it is used to treat piles, lipoma, paraplegia, paratyphoid, tonsillitis, traumatic wounds, pneumonia, splenomegaly, insect stings, mental illnesses, gastric tumors, general weakness, goiter, hysteria, insomnia, insanity, and vertigo [2]. Alkaloids, flavonoids, glycosides, fatty acid esters, phenols and saponins present in the plant were known to treat a variety of illnesses [[3], [4], [5]]. Due to the significant anti-hypertensive effects of an indole alkaloid, reserpine found in the roots, R. serpentina is highly valued in the pharmaceutical industry [6]. Among the identified phytoconstituents, therapeutically active indole alkaloids including reserpine, serpentine, sarpagine, serpenticine, ajmaline, rauwolscine, rawolfinine, ajmalinine, rescinamine, isoajmaline, tetraphyllicine, renoxycine, and reserpilline received more importance because of their applications in the cure of intestinal problems, cancer, fever, hypertension, uterine contractions, pneumonia, asthma, sleeplessness, wounds, malaria, and splenic conditions [[6], [7], [8], [9], [10]].

Klebsiella pneumoniae (K. pneumoniae) is an infamous opportunistic pathogen widely associated with multiple organ infections, including pneumonia, urinary tract infections, bacteremia and liver abscesses. However, these infections have been the primary cause of concern for the immunocompromised individuals [11]. The emergence of resistance to carbapenems, a class of antibiotics regarded as the last line of defense against infections, along with the evolution of hypervirulent strains in the mid-1980s, poses a significant threat, leading to severe infections not only in immunocompromised individuals but also in young and healthy populations [12]. This calls for a critical need to develop therapeutic interventions that could act on K. pneumoniae via multiple mechanisms. Fatty acids have recently emerged as potential alternatives to conventional antibiotics [13]. In the current study, we have used supercritical–carbon dioxide–fluid extraction (SCFE) of seeds of R. serpentina. SCFE is considered as an efficient, non-destructive, cost effective, environmentally viable, and selective method for the extraction of oils from seeds using non-toxic carbon dioxide in the supercritical form. The execution of SCF extraction at low temperature preserves natural compounds from degradation without altering their contents and properties [14].

The roots, aerial parts, and leaves of R. serpentina have been extensively studied for their phytochemical diversity and pharmaceutical vigor. However, the seeds have been primarily explored for their roles in the cultivation of R. serpentina plants, with limited scientific investigation into their chemical composition and biological properties. Hence our study aims to address this gap by elucidating the phytochemical diversity as well as the anti-microbial properties of bioactive compounds from R. serpentina seed oil, extracted using supercritical carbon dioxide technology. To achieve this, diverse advanced analytical techniques, including gas chromatography with flame ionization detector (GC-FID), gas chromatography-tandem mass spectrometry (GC-MS/MS), and high performance thin layer chromatography (HPTLC) and various spectroscopic methods viz., Fourier transform infrared (FT-IR) and proton nuclear-magnetic-resonance (¹H NMR) were employed to identify and characterize the bioactive compounds. Subsequently, anti-microbial evaluation was conducted to assess their potential biological activity. Moreover, in the present study, we have conducted the classical bacterial mutagenicity test (Ames assay), a widely used primary method for assessing genotoxicity [15]. The assay utilized test strains of Salmonella typhimurium (S. typhimurium) and Escherichia coli (E. coli), both of which are auxotrophic for histidine (his-) and tryptophan (trp-), respectively [16]. In this setup, S. typhimurium strains cannot grow in minimal media lacking histidine, while E. coli strains cannot grow in media deficient in tryptophan. The colonies that do grow under these conditions are known as revertant colonies or prototrophs, indicating that they have undergone genetic mutations, such as base pair substitutions or frameshift mutations, which restore their ability to synthesise the missing amino acid [17].

2. Materials and methods

2.1. Chemicals, reagents and plant material used for the study

Sodium chloride (Cat #S0180), sodium sulphate (Cat #S0410), methanol (Cat #M0276), and sodium hydroxide (Cat # S0601) were procured from Rankem (Gurugram, India). Ethyl acetate (Cat # 73106), and boron trifluoride in methanol (14%) solution (Cat #48847) were obtained from SRL (Mumbai, India). n-Heptane (Cat #25383) was purchased from SDFCL (Mumbai, India). Maltol (Cat #M0673), squalene (Cat # H0097), and lupeol (Cat #L0321) were procured from Tokyo Chemical Industry (Tokyo, Japan). Vanillic acid (Cat #68654), vanillin (Cat #61860301001730), and β-sitosterol (Cat #85451) were obtained from Sigma-Aldrich (St. Louis, MA, USA). Trans-ferulaldehyde (Cat #H973078) was procured from Toronto Research Chemicals (North York, Canada); dimethyl sulphoxide (Cat #GRM5856) from Himedia laboratories (Thane, India); phenobarbital/5 6 benzoflavone induced S9 fraction from Sprague-Dawley rat liver (Cat #11–105.1), lyophilized NADPH REGENSYS (Cat #60–201.5L), and NADPH REGENSYS 'A' (Cat #60–200.5) from Molecular Toxicology Inc. (Boone, NC, USA) were also purchased. All standard mutagens were procured from E. Merck (Mumbai, India) and all other bacteriological media were purchased from Himedia Laboratories (Thane, India).

Seeds of R. serpentina (5 kg) were collected from an authenticated medicinal plant vendor in Haridwar, India and were identified by an experienced taxonomist at the Patanjali Research Foundation, Haridwar, Uttarakhand, India (Voucher specimen number: 2955). The collected seeds were cleaned thoroughly, dried and kept in polythene bags at 10 °C for further use.

2.2. SCF extraction of R. serpentina seeds

For the current study, supercritical fluid extractor (SFE 5000 Bio-Botanical Extraction system, Water Corporation, Milford, MA, USA) was used to facilitate the extraction. 2 kg grounded seeds of R. serpentina were loaded and carbon dioxide gas was simultaneously introduced. The extraction system consists of a CO₂ recycler and an extractor operated at temperatures of 45 and 75 °C, maintained backflow pressures of 55 bars and 400 bars, respectively. For a duration of 19 h, a constant flow rate of carbon dioxide gas at 80 g/min was maintained. The extracted oil was centrifuged at 5000 rpm (Sorvall ST8 R Centrifuge, Thermo Scientific, Waltham, MA, USA) for 15 min and analysis was done using the collected upper layer of oil (RsSO) [18].

2.3. GC-FID technique for the identification and quantification of fatty acids from R. serpentina seeds SCFE oil (RsSO)

2.3.1. Standard mix preparation for the fatty acid analysis using GC-FID

0.05 mL Supelco 37 component fatty acid methyl ester (FAME) mixed reference standard (Cat #CRM47885, Sigma Aldrich (Burlington, MA, USA)) was transferred in a GC vial and diluted to 1 mL with n-heptane. Further, 1 μL of the diluted standard sample was injected into GC-FID for the analysis.

2.3.2. Preparation of RsSO sample solution for the analysis of fatty acids using GC-FID formation of FAME

For the analysis of RsSO for fatty acids, 100 mg of RsSO was transferred to a 50 mL conical flask fitted with a suitable water cooled reflux condenser and a magnetic stirrer. 4 mL of 0.5 N methanolic sodium hydroxide solution was added and refluxed for 10 min. Solution was refluxed again for 2 min and 4 mL of n-heptane was added through the condenser and refluxed for additional 1 min. 5 mL methanolic boron trifluoride solution (14%) was added and swirled to mix at 37 °C. The solution was then cooled at room temperature followed by adding 15 mL of saturated sodium chloride solution and mixed well. Upon standing at room temperature, n-heptane layer was separated. The obtained n-heptane layer was collected and dried over anhydrous sodium sulphate. The layer was then filtered through a 0.45 μm nylon filter and 1 μL of the filtered layer was injected into the GC-FID instrument for the analysis [19].

2.3.3. Instrument conditions for the analysis of fatty acids through GC-FID method

Analysis was performed on GC-FID (8860 GC system, Agilent, Santa Clara, CA, USA) equipped with an Open Lab software. Separation was carried out using Agilent HP-88 capillary column (60 m × 0.25 mm, 0.20 μm). Nitrogen was used as carrier gas at a constant pressure of 20 psi. The temperature of the split injector was set at 240 °C. The column temperature was set at 70 °C (held for 2 min) and then changed with the rate of 20 °C/min to 160 °C (held for 2 min) followed by 2.5 °C/min to 230 °C (held for 4 min). The detector heater temperature was set at 280 °C and the flow rate of hydrogen and zero air were set 40 and 400 mL/min, respectively.

2.4. Identification of non-polar phytometabolites from RsSO using GC-MS/MS analytical technique

2.4.1. Sample preparation of RsSO for GC-MS/MS analysis

The sample solution was prepared by dissolving 250 mg of RsSO in 5 mL of ethyl acetate and mixed well using a vortex mixer. After mixing, sample solution was centrifuged for 5 min at 8000 rpm (Sorvall ST 8R Centrifuge, Thermo Scientific) and then filtered through 0.45 μm nylon filter prior to inject into the instrument.

2.4.2. Instrument conditions for the analysis of RsSO using GC-MS/MS method

Analysis was performed on GC-MS/MS (7000D GC/MS triple quad with 7890B GC system, Agilent) with mass hunter software. Separation was carried out using Agilent HP-5 MS capillary column (30 m × 0.25 mm, 0.25 μm). Helium was used as a carrier gas at a flow rate of 1 mL/min. The temperature of the split injector was set up at 280 °C and the split ratio was set 20:1. 1 μL of sample was injected and the column temperature was set at 80 °C (held for 1 min) which was then changed at 4 °C/min to 150 °C (held for 1 min), then to 6 °C/min to 240 °C (held for 1 min) followed by 4 °C/min to 300 °C (held for 1 min). The GC-MS ion source temperature was 230 °C and ionization potential was set 70 eV.

2.4.3. Quantification of vanillin and squalene in RsSO using GC-MS/MS analytical technique

2.4.3.1. Preparation of standard and sample solutions for the quantification of vanillin and squalene in RsSO

Standard stock solutions of vanillin and squalene reference standards were prepared separately by dissolving accurately weighed reference standards in ethyl acetate to achieve a concentration of 1000 ppm. These stock solutions were further diluted with ethyl acetate to obtain working standard solutions at a final concentration of 100 ppm. Sample solution was prepared as per the procedure described in Section 2.4.1.

2.4.3.2. Instrument conditions used for the quantification of vanillin and squalene in RsSO

The same instrumental conditions described in Section 2.4.2 were used for the quantification of vanillin and squalene in RsSO by GC-MS/MS method.

2.5. Identification of unsaponifiable constituents present in RsSO–A GC-MS/MS approach

2.5.1. Preparation of sample solution

To check the unsaponified matter in RsSO, 5 g of RsSO was placed in a 250 mL round-bottom flask. An alcoholic solution made with potassium hydroxide (25 mL, 4%) was added to it, and the mixture was left to reflux for an hour. An hour later, white foam was seen in the round-bottom flask, indicating that the reflux process was finished. Hot ethanol (10 mL) was used to clean the condenser and removed any leftover refluxed material. The solution collected was concentrated using a rotary evaporator at 60 °C. Afterwards, 5 mg of the resulting sample was dissolved in 5 mL of hexane and analysed by GC-MS/MS to identify the unsaponifiable constituents present [20].

2.5.2. Instrument conditions for the identification of unsaponifiable constituents of RsSO using GC-MS/MS method

Similarly, phytometabolites from the unsaponified matter of RsSO were also identified under the same instrument conditions (Section 2.4.2). However, the column temperature was set at 60 °C (held for 1 min) changed at 8 °C/min to 200 °C (held for 1 min) then to 4 °C/min to 300 °C (held for 16 min), followed 10 °C/min to 290 °C (held for 1 min). The ion source temperature was controlled at 230 °C, and ionization potential was maintained at 70 eV.

2.6. High performance thin layer chromatography (HPTLC) fingerprinting of active biomarkers from RsSO

2.6.1. Preparation of reference standard solutions

10 mg of each reference standards, maltol (MA), vanillic acid (VA), trans-ferulaldehyde (TF), vanillin (VN), squalene (SQ), and lupeol (LP) were dissolved in 10 mL methanol. Similarly, for preparation of reference standard solution of β-sitosterol (BS), the biomarker (10 mg) was dissolved in methanol:chloroform (1:1, v/v). The reference standards were further diluted to prepare MA, and VN in 40 μg/mL concentration, TF, and VA in 100 μg/mL concentration, and SQ, BS, and LP in 200 μg/mL concentration.

2.6.2. Preparation of sample solution

10 g RsSO was dissolved in 30 mL chloroform:methanol (2:1, v/v), and was sonicated for 10 min. The sample was then transferred to a separating funnel, and 60 mL of Milli-Q water was added to it. After proper mixing, the sample was allowed to separate into two layers, the aqueous layer was collected separately, and the organic layer was again extracted with 60 mL Milli-Q water. Both aqueous layer, and organic layer were collected separately. The aqueous layer was distilled out using rotary evaporator, and the residue was re-dissolved in 2 mL methanol for the analysis of phytometabolites. The organic layer (lipid fraction) was distilled out, and further used for lipid fingerprinting. The lipid fraction was further treated with alcoholic potassium hydroxide solution followed by separation using petroleum ether and water. The petroleum ether layer collected was used for the fingerprinting of phytosterols.

2.6.3. Instrument conditions for the analysis of phytometabolites using HPTLC method

A CAMAG HPTLC (CAMAG, Sonnenmattstrasse, Muttenz, Switzerland) system equipped with an automatic TLC sampler (ATS4), TLC scanner 4, TLC Visualizer, and integrated software WinCATS (Version 1.4.10) was used for the analysis. HPTLC was performed on a pre-coated silica gel 60 F₂₅₄ (Cat #1.05554.0007) aluminium backed TLC plate. For fingerprint analysis, 10 μL of each standard, and 10 μL of RsSO were applied as 8 mm band using spray-on technique on TLC plate. Plate was then developed using CAMAG twin trough chamber pre-saturated (for 15 min) with mobile phase toluene:ethyl acetate:formic acid (10:8:1, v/v/v) for MA, VA, and TF, toluene:acetone (6:4, v/v) for VN, and diethyl ether:toluene (8:2, v/v) for SQ, BS, and LP. For profiling of lipids, diethyl ether was used as a mobile phase. TLC plate was developed up to 70 mm, and then the developed TLC plate was dried under warm air and visualized. For MA, VA, TF and VN, the TLC plate was imaged, and scanned at 254 nm. For SQ, BS and LP, the TLC plate was imaged under white light (after derivatisation with anisaldehyde-sulphuric acid solution) and chromatogram was recorded at 520 nm. For general profiling of lipids, the TLC plate was visualized at 366 nm and scanned on UV scanner. The developed TLC plate was then, derivatised with iodine vapours and scanned after visualizing at 254 nm. The same TLC plate was again visualized under white light and then scanned at 520 nm.

2.6.4. Quantification of phytometabolites through HPTLC approach

Different concentrations of reference standards and samples were applied for the quantification of phytometabolites. A linearity plot was prepared and concentration of individual marker compounds were calculated under the same analytical conditions. For quantification, the developed TLC plate was scanned at 280 nm (for MA, and VA), 320 nm (for TF), and at 520 nm (for VN, BS, LP, and SQ).

2.7. FT-IR spectroscopic analysis of RsSO

FT-IR spectrometer (Cary 630 from Agilent Technologies, Bayan Lepas, Malaysia) equipped with diamond attenuated total reflectance (ATR), was used during FT-IR spectra acquisition. A few drops of RsSO was positioned in contact with ATR, and FT-IR spectra was recorded from 600 to 4000 cm⁻¹. The instrument underwent baseline correction and was maintained with a spectral resolution of 16 cm⁻¹.

2.8. ¹H NMR spectroscopic analysis of RsSO

¹H NMR evaluation of RsSO was performed on Bruker India Scientific Avance Neo 600 MHz (Bruker Switzerland AG, Industriestrasse, Faellanden, Switzerland) instrument. The sample, weighed 35 mg, was dissolved in 1 mL of deuterated chloroform (CDCl₃) with a small amount of tetramethyl silane (TMS) as internal standard and the resulting mixture was placed into a 5 mm diameter ultra-precision NMR sample tube (analysis conducted at SATHI-Banaras Hindu University, Varanasi, India). Chemical shifts (δ) were recorded in parts per million (ppm). The area of the signals was determined by using the equipment software Topspin 4.1. The interpreted and integrated peaks obtained from the ¹H NMR spectrum were used to determine the phytometabolites and physico-chemical characteristics of the oil (Refer to Supplementary data). International Organization for Standardization (ISO) protocol was followed for the wet lab physico-chemical analyses of RsSO. Specifically, the analyses included the determination of free fatty acids (ISO 660), iodine value (ISO 3961), and saponification value (ISO 3657).

2.9. Anti-microbial efficacy evaluation of RsSO

2.9.1. Bacterial strains and growth conditions

The bacterial strain, K. pneumoniae (MCC 3094) was procured from the National Repository of Microbial Cultures, namely, National Centre for Microbial Resource (NCMR) located in Pune, India. The culture was propagated in nutrient broth. The bacterial strain was stored in sterile glycerol stock (20% v/v) at −80 °C.

2.9.2. Anti-microbial activity using the broth microdilution method

2.9.2.1. Minimum inhibitory concentration (MIC)

The anti-microbial potency of RsSO against K. pneumoniae was evaluated by measuring the minimum inhibitory concentration (MIC) values, which followed the standard guidelines of the Clinical and Laboratory Standards Institute (CLSI) for broth microdilution method [21]. Bacterial suspension of 1 × 10⁸ CFU/mL was treated with RsSO for 24 h at 37 °C. Post-incubation, the absorbance of these cultures was measured at 600 nm using a microplate reader (Envision, PerkinElmer, Shelton, CT, USA). Percent bacterial growth inhibition by RsSO was calculated with reference to bacterial cultures that were untreated. Dose-response curve was generated from the obtained values using GraphPad Prism software (GraphPad Prism 8.0.2), to determine the RsSO concentrations that inhibited 50% (MIC₅₀) and 90% (MIC₉₀) of K. pneumoniae growth.

2.9.2.2. Minimum bactericidal concentration (MBC)

For minimum bactericidal concentration (MBC) determination, bacterial inoculum from the wells corresponding to 0.25× MIC₉₀, 0.5× MIC₉₀, 1.0× MIC₉₀, 2.0× MIC₉₀, 4.0× MIC₉₀ and 8.0× MIC₉₀ were serially diluted and plated on non-selective agar plates [22]. Colony-forming units (CFU/mL) were enumerated after 24 h of incubation at 37 °C. The data points were then plotted as a line graph using GraphPad Prism software (GraphPad Prism 8.02), and a non-linear curve was fitted to the values to calculate the MBC₅₀. All experiments were performed in triplicate.

2.9.3. Biofilm inhibition and eradication assay

K. pneumoniae biofilms were allowed to form on sterile coverslips in 6-well plates for 72 h at 37 °C in the presence or absence of RsSO at respective doses of 0.5× MIC₉₀, 1.0× MIC₉₀, 2.0× MIC₉₀, and 4.0× MIC₉₀. Following a thorough removal of planktonic cells with sterile phosphate-buffered saline, biofilms were stained with 1% crystal violet as described elsewhere [23]. For biofilm eradication assay, mature biofilms were treated with RsSO at indicated doses for additional 24 h. Images of the biofilms were captured using a brightfield microscope (Nikon, Melville, NY, USA) at 400× magnification. Image J software was used to determine the surface area covered by the blue region, indicating biofilm [24].

2.9.4. Bacterial mutagenicity assay (Ames assay)

S. typhimurium tester strains, namely, TA 98 (BAA 2720), TA 100 (BAA 2721), TA 1537 (29630), TA1535 (29629) and E. coli tester strain WP2 uvrA (49979) were procured from American Type Culture Collection (ATCC). The regenerating system for S9 mix was prepared as per the manufacturer's protocol.

The test strains were grown overnight at 37 °C by inoculating the freshly thawed frozen strains in nutrient broth media. Mutagenicity was assayed by the plate incorporation method in the absence of metabolic activation, while the pre-incubation method was followed in the presence of metabolic activation as per the previously published protocols [[12], [13], [14]]. The reverse mutation was assessed in three strains of S. typhimurium in addition to E. coli WP2 uvrA. The S9 metabolic activation mixture (S9 mix) was prepared according to the Organization for Economic Co-operation and Development (OECD) guidelines [25]. Briefly, 100 μL of test bacterial cultures (1-2 × 10⁹ cells/mL) was incubated at 37 °C with different concentrations of RsSO or standard mutagen in dimethyl sulphoxide (DMSO) (100 μL/plate) in the absence or presence of S9 mix (10% S9 fraction, regenerating system comprising of glucose-6-phosphate, NADPH, MgCl₂/KCl, and 0.1 M phosphate buffer at pH 7.4 per tube) for 30 min, without shaking. Subsequently, 2 mL of soft agar (0.6% bacto-agar, 0.5% NaCl, 50 μM biotin, and 50 μM histidine for S. typhimurium strains or 50 μM tryptophan for E. coli strain) was added to the above tube and poured immediately onto a plate of minimal agar (1.5% bacto-agar, Vogel-Bonner E medium, containing 0.4% glucose). The standard mutagen for TA 1535, TA 98, TA 100, TA 1537, and WP2 uvrA without S9 metabolic activation was sodium azide (0.5 μg/plate), 2-nitrofluorene (1 μg/plate), 9-aminoacridine (50 μg/plate), and 2-aminoanthracene (20 μg/plate), respectively. The standard mutagen for TA 100 with S9 metabolic activation was benzo(a)pyrene (5 μg/plate). All standard mutagens including RsSO were prepared in DMSO, except sodium azide, that was prepared in sterile deionised water.

The mutagenic effect of RsSO was assessed at 5 μL/plate and subsequent concentrations with a half-log fold difference, i.e., 5.0, 1.5, 0.5, 0.15, 0.05 μL/plate. Different doses of RsSO, vehicle control (DMSO (100 μL/plate)), and positive controls were tested in triplicates as per the OECD guidelines [25].

Following 64 to 72-h incubation period, the number of revertant colonies was counted. A positive result for genotoxicity was determined based on a significant increase in revertant colonies (mutagenicity ratio (MR) > 2.0) in at least one of the tester strains compared to the vehicle control. MR was calculated by dividing the number of revertant colonies in RsSO or the standard mutagen by the number of revertants in the vehicle control (DMSO), in accordance with established guidelines [25,26]. Revertant colonies are those that have undergone permanent mutations, restoring their ability to grow and become visible to the naked eye. To assess statistical significance, analysis of variance (ANOVA) followed by Dunnett's multiple comparison tests was applied, with P < 0.05 considered significant and P > 0.05 considered non-significant.

2.10. Data acquisition and processing

For GC-MS/MS analysis, compounds were confirmed by Standard Reference Data Program of the National Institute of Standards and Technology (NIST) Mass Spectral Library, version 2.2 (Gaithersburg, MD, USA). PubChem (https://pubchem.ncbi.nlm.nih.gov/) was used to confirm the structures of identified phytometabolites. WinCATS software (Version 1.4.10) was used for the identification and quantification of active biomarkers using HPTLC method. Results were presented as mean values with the standard error of the mean (SEM) based on at least three independent determinations. FT-IR and NMR spectral analysis were performed using Microlab (Agilent Technologies) and Bruker TopSpin 4.4.1 software, respectively. A non-linear regression model was applied, incorporating standard error of the mean (SEM) and a 95% confidence interval using GraphPad Prism Software Version 8.0.2 (2019) for Windows . Statistical analysis involved one-way ANOVA followed by Dunnett's multiple comparisons test was performed using GraphPad Prism software (Version 8.0.2 (2019)). Differences were deemed statistically significant at P < 0.05.

3. Results and discussion

3.1. GC-FID analysis for the identification and quantitation of fatty acids in RsSO

SCF extraction of R. serpentina seeds yielded 4.70% oil (RsSO), which was found to be higher than the yield obtained for Putranjiva roxburghii (3%) [18] and Petroselinum crispum (0.40%) [27] seeds, whilst Vitis vinifera seeds on SCF extraction yielded 150.80 mg/g seeds (15.08%) oil [28]. In the present study, gas chromatographic techniques including GC-FID and GC-MS/MS were used for the analysis of RsSO. GC-FID is primarily meant for the analysis of fatty acids in the form of FAME against reference standards. For the purpose, the non-volatile fatty acids were converted into volatile FAMEs [19]. However, GC-MS/MS analysis is intended for detecting the non-polar constituents of the oil.

GC-FID chromatogram of RsSO as shown in Fig. 1A depicted four distinct peaks corresponding to bioactive compounds, which were identified and quantified in RsSO, with reference to FAME standards, as detailed in Table 1. The chromatographic analysis revealed the presence of palmitic acid, stearic acid, oleic acid, and linoleic acid. Palmitic acid was detected at a retention time (RT) of 18.59 min and quantified as 11.92% (w/w). Stearic acid appeared at RT 22.27 min and was quantified as 3.42% (w/w). Oleic acid was detected at RT 23.41 min and quantified as 20.01% (w/w). The major peak of linoleic acid was observed at RT 25.17 min, and it was quantified as 28.02% (w/w), making it the most abundant fatty acid in RsSO. The results indicated that RsSO is rich in unsaturated fatty acids, which constitute 48.03% of the total composition and are well-known for their biological potential. A previous report on the GC-FID analysis of SCFE-processed Withania somnifera seeds also identified four major fatty acids, including palmitic acid, stearic acid, oleic acid, and linoleic acid, in addition to minor fatty acids, namely 11,14,17-eicosatetranoic acid, and nervonic acid [29]. Specifically, oleic acid, a monounsaturated fatty acid, has been reported to possess vasoprotective effects, and support the immune system [30] in addition to anti-microbial potential [31]. Linoleic acid, a polyunsaturated fatty acid, has demonstrated anti-bacterial activity against Staphylococcus aureus and Bacillus subtilis [32]. These findings highlight the significant therapeutic potential of RsSO, particularly due to its rich profile of unsaturated fatty acids, which could be further explored for their pharmacological applications, including immune support activity.

Fig. 1.

Gas chromatography-flame ionization detector (GC-FID) and gas chromatography-tandem mass spectrometry (GC-MS/MS) analyses of Rauvolfia serpentina seeds supercritical–carbon dioxide–fluid extraction (SCFE) oil (RsSO) for the identification and quantification of fatty acids and non-polar compounds. (A) GC-FID analysis of the fatty acid constituents of RsSO (in pink line) revealed the presence of both saturated and unsaturated fatty acids in comparison with fatty acid methyl ester (FAME) reference standard (in blue line), including palmitic acid (18.59 min), stearic acid (22.27 min), oleic acid (23.41 min), and linoleic acid (25.17 min). Linoleic acid was identified as the major unsaturated fatty acid, accounting for 28.02% (w/w) of the total content, as shown in Table 1. (B) GC-MS/MS analysis of RsSO, which identifies seven biomarkers: vanillin (16.17 min), 14-methylpentadecanoate (28.90 min), palmitic acid ethyl ester (30.08 min), linolelaidic acid methyl ester (31.71 min), 17-octadecynoic acid (32.75 min), oleic acid (32.84 min), and squalene (43.23 min), as detailed in Table 1. (C) GC-MS/MS analysis of phytometabolites in the unsaponifiable fraction of RsSO, which revealed six major compounds: squalene (36.80 min), campesterol (43.10 min), stigmasterol (43.60 min), γ-sitosterol (44.52 min), β-amyrin (44.97 min), and lupeol (45.72 min). These compounds are listed in Table 1. The structures of the identified phytometabolites were accessed from PubChem (https://pubchem.ncbi.nlm.nih.gov/) (accessed on 24/October/2024).

Table 1.

Fatty acids (by gas chromatography-flame ionization detector (GC-FID)), phytometabolites (by GC-MS/MS), and Unsaponified phytometabolites (by gas-chromatography-tandem mass spectrometry (GC-MS/MS)) quantified in Rauvolfia serpentina seeds supercritical–carbon dioxide–fluid extraction (SCFE) oil (RsSO).

Compounds	Retention time (min)	Content (%, w/w)
Fatty acids
Palmitic acid (C16:0)	18.59	11.92
Stearic acid (C18:0)	22.27	3.42
Oleic acid (C18:1)	23.41	20.01
Linoleic acid (C18:2)	25.17	28.02
Total saturated fatty acids		15.34
Total unsaturated fatty acids		48.03
Phytometabolites		Relative area (%)
Vanillin	16.17	3.87
14-Methylpentadecanoate	28.90	2.71
Palmitic acid ethyl ester	30.08	6.38
Linolelaidic acid methyl ester	31.71	4.39
17-Octadecynoic acid	32.75	10.54
Oleic Acid	32.84	8.39
Squalene	43.23	20.24
Unsaponified phytometabolites		Relative area (%)
Squalene	36.80	7.05
Campesterol	43.10	13.54
Stigmasterol	43.60	11.44
γ-Sitosterol	44.52	22.07
β-Amyrin	44.97	12.51
Lupeol	45.72	24.20

3.2. GC-MS/MS analysis of non-polar components and unsaponified phytometabolites present in RsSO

GC-MS/MS analysis was conducted to assess the overall composition of RsSO extracted using the SCFE technique. The GC-MS/MS chromatogram, shown in Fig. 1B and detailed in Table 1, identified a total of seven non-polar phytometabolites in RsSO. The identified components included vanillin, which appeared at a RT of 16.17 min, followed by 14-methylpentadecanoate at RT 28.90 min. Palmitic acid ethyl ester was detected at RT 30.08 min, and linolelaidic acid methyl ester was observed at RT 31.71 min. Other notable phytometabolites included 17-octadecynoic acid (RT 32.75 min), oleic acid (RT 32.84 min), and squalene (RT 43.23 min). Among the identified non-polar compounds, vanillin and squalene were quantified against reference standards also, which yielded concentrations of 0.11% (w/w) and 0.15 % (w/w), respectively.

Vanillin is widely used as a food additive in various formulations and has demonstrated several pharmacological properties, including anticancer [33], antibacterial [34], and anti-inflammatory effects [35]. Additionally, studies have shown that palmitic acid, when encapsulated in poly(D, L-lactic-co-glycolic acid) (PLGA) nanoparticles, can be employed for breast cancer therapy, either alone or in combination with doxorubicin [36]. Squalene, another identified phytometabolite, has been reported to exert hypolipidemic [37], antitumor [38], and antibacterial [39] effects.

A typical GC-MS/MS chromatogram of the unsaponifiable matter from RsSO obtained by SCFE was shown in Fig. 1C. The composition of the unsaponifiable matter was analysed, revealed the presence of several bioactive phytometabolites, including squalene, campesterol, stigmasterol, γ-sitosterol, β-amyrin, and lupeol. These compounds were detected within the retention time range of 35–46 min. Specifically, squalene was observed at a RT of 36.80 min, campesterol at RT 43.10 min, stigmasterol at RT 43.60 min, and γ-sitosterol at RT 44.52 min. The phytometabolites, β-amyrin was detected at RT 44.97 min, followed by lupeol at RT 45.72 min. Among the six identified active biomarkers, lupeol was observed as the most abundant, with a relative area percentage of 24.20 % (Table 1).

Fatty acids such as palmitic acid, oleic acid, stearic acid, and linoleic acid, along with sterols and triterpenoids like campesterol, stigmasterol, β-amyrin, β-sitosterol, and lupeol, have been previously identified from the methanol extract of R. serpentina leaves using the GC-MS/MS method and were found to contribute to the anticancer activity of the crude extract [40]. A literature review of the biological activities associated with these compounds highlights their diverse therapeutic potential. For example, campesterol has been reported to exhibit anti-bacterial activity against multidrug-resistant bacteria [41]. β-Amyrin, on the other hand, has been investigated for its anti-fibrotic effects in dimethylnitrosamine (DMN)-induced hepatic fibrosis in male rats, where it also demonstrated notable anti-inflammatory properties [42]. Lupeol has garnered attention for its anticancer activity, particularly against human non-small cell lung cancer, by inhibiting the phosphorylation of the epithelial growth factor receptor [43]. These analyses highlight the presence of bioactive non-polar compounds in RsSO, further supporting its potential therapeutic applications.

3.3. HPTLC fingerprinting of active biomarkers from RsSO

HPTLC is a crucial analytical technique for the separation, detection, and quantification of various classes of natural products, as well as for assessing the variation of chemical compounds in pharmaceutical formulations [44]. In this study, HPTLC fingerprinting was performed on RsSO extracted using the SCFE technique. An optimized method was developed for the identification of bioactive constituents present in RsSO. Therefore, for optimizing the solvent systems in HPTLC, different ratio of solvents was tried such as hexane:ethyl acetate:acetic acid in the ratio 9:10:2 (v/v/v), toluene:acetone in the ratio 8:2 (v/v), diethyl ether:hexane:acetic acid in the ratio 5:1:2 (v/v/v), and toluene:ethyl acetate:formic acid in the ratio 8:2:1 (v/v/v).

The results revealed the presence of several bioactive constituents in the extracted oil, including maltol, vanillic acid, trans-ferulaldehyde, vanillin, β-sitosterol, lupeol, and squalene. Chromatographic fingerprinting was carried out by comparing same concentration of duplicate RsSO samples with their respective reference standards, allowing for the identification and confirmation of these compounds in the oil. Fig. 2A(i) illustrates HPTLC fingerprint of active markers MA, VA, TF at 254 nm with reference standards. The TLC plate was developed in mobile phase toluene:ethyl acetate:formic acid (10:8:1, v/v/v) and scanned at 254 nm to generate the chromatogram (Fig. 2A(ii)). The chromatogram showed the similar retention factor (Rf) of the biomarkers in RsSO and of standards. MA was observed at Rf 0.28, which matched with the Rf of compound in RsSO. Similarly, Rf 0.45 and 0.54 showed the presence of VA and TF in RsSO, respectively. Fig. 2A(iii) depicts another identified biomarker, VN was developed on TLC plate using mobile phase toluene:acetone (6:4, v/v) and was visualized under UV light at 254 nm. The TLC plate confirmed the presence of VN in RsSO with Rf 0.47. The TLC plate was scanned and the chromatogram was generated at the same wavelength (Fig. 2A(iv)). Fig. 2A(v) represents the TLC profiling and associated chromatogram of biomarkers SQ, BS, and LP. The TLC plate was developed in diethyl ether:toluene (8:2, v/v) which confirmed the presence of BS at Rf 0.57. The compound observed at Rf 0.68 in RsSO corresponded to LP which was confirmed by comparing the Rf value with the standard LP. SQ was observed at Rf 0.87, and its presence was confirmed in the sample after derivatisation in white light at 520 nm as shown in Fig. 2A(vi).

Fig. 2.

High performance thin layer chromatography (HPTLC) analysis of Rauvolfia serpentina seeds supercritical–carbon dioxide–fluid extraction (SCFE) oil (RsSO). (A) the presence of active markers in different wavelengths. (i) Maltol (MA), vanillic acid (VA), and trans-ferulaldehyde (TF) at 254 nm; (ii) their respective 3D chromatogram at 254 nm. The HPTLC fingerprints revealed bands for the marker compounds at 254 nm with corresponding retention factor (Rf) values of 0.28, 0.45, and 0.54, respectively, when compared to the reference standards; (iii) HPTLC fingerprint of the active marker vanillin (VN) at 254 nm; (iv) Its respective 3D chromatogram at 254 nm. The vanillin band was observed at an Rf value of 0.47, which is comparable to the reference standard; (v) HPTLC fingerprint of active markers squalene (SQ), β-sitosterol (BS), and lupeol (LP) under white light after derivatization; and (vi) Their respective 3D chromatogram at 520 nm. The HPTLC fingerprints displayed bands for the markers SQ, BS, and LP under white light, with Rf values of 0.87, 0.57, and 0.68, respectively, with respect to the reference standards. (B) HPTLC fingerprinting of lipids present in RsSO. (i), (ii), and (iii) represent the HPTLC fingerprinting of lipids at 366, 254, and 520 nm, respectively; (iv), (v), and (vi) show their corresponding 3D chromatograms. The structures of the identified phytometabolites were accessed from PubChem (https://pubchem.ncbi.nlm.nih.gov/) (accessed on 24/October/2024).

The versatile technique, HPTLC is particularly valuable for profiling complex lipid mixtures, enabling the identification and quantification of individual lipid components, as well as providing a distinctive chromatographic fingerprint that can be used for quality control and authentication of lipid-containing products [45]. In order to support the existence of lipids in the sample, Fig. 2B showed a general profiling of lipids in RsSO. The developed TLC plate visualized at 366 nm and the corresponding 3D chromatogram were displayed in Fig. 2B(i) and 2B(iv), respectively. Lipids were present in the chromatogram between Rf 0.40 and 0.60 and between 0.75 and 0.85. Following derivatisation with iodine vapours, the TLC plate was examined (Fig. 2B(ii) and scanned (Fig. 2B(v)) at 254 nm. At 520 nm, the same TLC was analysed and lipids were observed which were then scanned and their generated chromatogram were analysed (Fig. 2B(vi)) after visualized at white light (Fig. 2B(iii)).

The quantitative analysis of the identified phytometabolites was shown in Fig. 3, where the chromatogram was plotted with absorbance (in absorption unit) on the y-axis and Rf on the x-axis. Reference standards were used at varying concentrations, and triplicate samples of RsSO were spotted (n = 3) to ensure reproducibility and accuracy of the measurements. This method allowed for precise quantification of the phytometabolites present in RsSO by comparing the sample's chromatographic data with that of the reference standards. Fig. 3A–C represent chromatograms of varying concentrations MA (40–800 μg/mL), and VA (100–1,200 μg/mL) at 280 nm; TF (100–800 μg/mL) at 320 nm; and VN (80–600 μg/mL), BS (400–2,500 μg/mL), LP (200–1,600 μg/mL), and SQ (200–1,200 μg/mL) at 520 nm. In the illustrated chromatograms, the straighten peaks depicted the standard biomarkers and the inverted peak correspond to RsSO.

Fig. 3.

Quantitative analysis of identified phytometabolites, i.e., maltol (MA), vanillic acid (VA), trans-ferulaldehyde (TF), vanillin (VN), β-sitosterol (BS), lupeol (LP), and squalene (SQ) in Rauvolfia serpentina seeds supercritical–carbon dioxide–fluid extraction (SCFE) oil (RsSO) by high performance thin layer chromatography (HPTLC) method (n = 3). (A) Chromatogram for MA (40–800 μg/mL), VA (100–1200 μg/mL), and TF (100–800 μg/mL) at varying concentrations. (B) Chromatogram for VN ( 80–600 μg/mL) at different concentrations. (C) Chromatogram for BS (400–2500 μg/mL), LP (200–1600 μg/mL), and SQ (200–1200 μg/mL) at different concentrations. In the chromatograms, the straightened peaks represent the standard biomarkers, while the inverted peaks correspond to the sample (RsSO). (D) The quantitative analysis of the identified phytometabolites, with results expressed as mean ± standard deviation (SD) (n = 3), as tabulated in Table S1. Rf: retention factor.

Based on the linearity plot, a regression equation was generated, and the biomarkers present in RsSO were quantified using HPTLC. The quantified values of these biomarkers were presented in Fig. 3D, which depicts a bar graph illustrating the quantity of each biomarker identified in RsSO. Among the quantified phytometabolites, LP was found to be the most abundant compound, with a value of 1938.77 ± 3.11, while MA was the least abundant, quantified at 1.62 ± 2.15. BS was the second most abundant compound, with a value of 1198.90 ± 12.03 (Table S1). Maltol has been recently reported for its ameliorating effect on intervertebral disc generation by increased the expression of anabolic proteins and decreased the expression of catabolic proteins. The work also studied the decreased secretion of inflammatory mediators [46]. Previous experimental evidences showed the alleviating potential of vanillic acid in acute myocardial hypoxia by inhibiting oxidative stress [47], and reported as a promising cardioprotective agent against methamphetamine-induced cardiotoxicity, resulted through antioxidant and mitochondrial protection studies [48].

3.4. FT-IR spectral analysis of active phytometabolites present in RsSO

ATR-FT-IR spectroscopy was used to analyse the structural bonds of RsSO. The spectra displayed in Fig. 4 provide a summary of the bands at various frequencies and intensities, which represented the functional groups found in the oil. The spectra showed a peak at 3006.1 cm⁻¹ indicated the stretching of carbon and hydrogen bond where carbon is doubly bonded (=C–H). The peak indicated the presence of β-sitosterol, fatty acids and their esters. The presence of lupeol, phytol, fatty acids, campesterol, fatty acid esters and β-sitosterol were acknowledged by the peak at 2916.6 cm⁻¹ which showed the presence of carbon and hydrogen stretching where carbon is singly bonded. The aldehyde group (–C–H) stretch was observed at 2849.5 cm⁻¹ which indicated the presence of vanillin in RsSO. Carbonyl groups (–C O) of aldehyde, and ester linkage were observed at 1740.7 cm⁻¹ and 1707.1 cm⁻¹ which indicated the presence of vanillin and fatty acids with their esters respectively. The C–C stretching in the phytometabolites was observed at 1463.0 cm⁻¹. The bending of carbon doubly bonded to carbon (C C) was observed at 939.3 cm⁻¹ which corresponds to unsaturated fatty acids in RsSO. The peak observed at 721.2 cm⁻¹ showed the presence of β-sitosterol, campesterol, lupeol, fatty acids, and their ester form, and phytol in RsSO which signified the bending of carbon and hydrogen. To comprehend the presence of active phytometabolites in RsSO, the FT-IR analysis was employed, which contributed in the preliminary analysis of RsSO active constituents on the structural basis of molecules.

Fig. 4.

Fourier transform-infrared (FT-IR) spectroscopic analysis of Rauvolfia serpentina seeds supercritical–carbon dioxide–fluid extraction (SCFE) oil (RsSO). The spectrum revealed various functional groups based on their peak positions, vibrations (stretching and bending), and corresponding phytometabolites. The major peaks observed correspond to the following functional groups (from left to right): =C–H stretch, –C–H stretch, –C–H aldehyde stretch, –C O stretch, –C O ester group stretch, C–C stretch, C C bend, and C–H bend.

3.5. ¹H NMR approach for the identification of phytometabolites present in RsSO

NMR spectral analysis of RsSO revealed characteristic proton signals correspond to various metabolites present in the oil. In the ¹H NMR spectrum (Fig. 5), peaks observed in the range of δ 0.85–0.88 ppm indicated the presence of aliphatic protons in the terminal methyl groups of fatty acids, their esters, squalene, and sterols. Methylene protons, found in fatty acids, fatty acid esters, sterols, and vanillin, were observed at δ 1.24 ppm, while methine protons, characteristic of compounds like vanillin, vanillic acid, and maltol, appeared between δ 1.59–2.04 ppm. The methoxy group in vanillin showed a signal at δ 4.10–4.29 ppm, while protons attached to oxygen were detected in the region of δ 5.30–5.37 ppm (Table 2). These NMR signals provided valuable insight into the chemical composition of RsSO.

Fig. 5.

Proton nuclear magnetic resonance (¹H NMR) spectrum of Rauvolfia serpentina seeds supercritical–carbon dioxide–fluid extraction (SCFE) oil (RsSO). The spectrum was recorded at 600 MHz using deuterated chloroform as the solvent. The chemical shift values, assigned to specific functional groups and their associated compounds, have been provided in Table 2. Additionally, the physico-chemical parameters calculated for RsSO using ¹H NMR spectroscopy have been tabulated in Table S2.

Table 2.

Observed ¹H chemical shift values of possible phytometabolites present in RsSO as shown in Fig. 5.

S. No.	Elucidated chemical shift values (δ) in 1H NMR spectrum (ppm)	Corresponding groups	Phytometabolites
1.	δ 0.85–0.88	Terminal –CH3	Fatty acids methyl esters, oleic acid, squalene, sterols
2.	δ 1.24	–CH2	Fatty acids, fatty acid esters, sterols, vanillin
3.	δ 1.59–2.04	–CH	Vanillin, vanillic acid, maltol
4.	δ 4.10–4.29	–OCH3	Vanillin
5.	δ 5.30–5.37	Proton attached to oxygen	Fatty acids, vanillin, maltol

NMR: nuclear magnetic resonance.

In the present study, ¹H NMR spectroscopy was also utilized to assess the physico-chemical parameters of RsSO (Fig. 5, and Table S2). The iodine value, calculated based on the number of olefinic protons was found to be 86.45 g iodine/100 g in RsSO suggested the significant presence of unsaturated fatty acids. The free fatty acid content, primarily resulting from the hydrolysis of triacylglycerides (TAGs) in RsSO, was found to be 12.66 mg/100 g. The saponification value (566.99 g KOH/kg), measures the alkali-reactive groups in fats and oils, was also determined. This value helped to predict the types of triacylglycerols present in RsSO. Overall, the physico-chemical parameters, including iodine value, free fatty acid content, and saponification value, derived from the NMR data, were consistent with the fatty acid profile of the oil and aligned well with the values obtained from conventional titration methods as per Indian Standards (Table S2). This confirms the reliability of the NMR-based approach for evaluating the quality and composition of RsSO.

3.6. RsSO inhibits the growth and viability of K. pneumoniae

The anti-microbial efficacy of RsSO against K. pneumoniae was assessed using the broth microdilution method. The MIC₅₀ and MIC₉₀ values of RsSO, indicating 50% and 90% inhibition of bacterial growth, were determined to be 3.03 mg/mL and 6.28 mg/mL, respectively (Fig. 6A). The results indicate that RsSO is bactericidal against K. pneumoniae. To assess whether the MIC concentrations also affect bacterial viability, the lowest concentration of RsSO required to eliminate 90% of the initial bacterial inoculum was determined as the MBC₉₀. Serially diluted RsSO-treated K. pneumoniae cultures plated on non-selective nutrient agar showed a significant inhibitory effect of RsSO on bacterial viability (Fig. 6B). CFU/mL was quantified by counting the CFUs (Fig. 6C) and percent viability determined MBC₅₀ value of RsSO to be 5.4 mg/mL (Fig. 6D). The data indicated that RsSO dose-dependently inhibited the viability of K. pneumoniae (Fig. 6D).

Fig. 6.

Rauvolfia serpentina seeds supercritical–carbon dioxide–fluid extraction (SCFE) oil (RsSO) inhibits the growth and viability of Klebsiella pneumonia (K. pneumoniae). (A) The dose-response curve, indicating the minimum inhibitory concentrations (MIC₅₀ and MIC₉₀) of RsSO against K. pneumoniae, was generated through a non-linear regression analysis of the values obtained from the broth microdilution method. (B) Representative digital images show the colony-forming units (CFUs) of K. pneumoniae on nutrient agar plates, with cultures treated with RsSO at concentrations corresponding to 0.25× MIC₉₀, 0.5× MIC₉₀, 1.0× MIC₉₀, 2.0× MIC₉₀, 4.0× MIC₉₀, and 8.0× MIC₉₀. (C, D) The CFU/mL (C) and (D) Percent viability in K. pneumoniae have been plotted against RsSO concentrations. Non-linear regression curves were used to evaluate the minimum bactericidal concentrations (MBC₅₀ and MBC₉₀). The data reflect results from more than three independent experiments, with error bars representing the mean ± standard error of the mean (SEM).

To examine the impact of these concentrations on bacterial viability, the minimum bactericidal concentration required to eliminate 90% of the initial bacterial inoculum (MBC₉₀) was determined. RsSO-treated K. pneumoniae cultures, serially diluted and plated on non-selective nutrient agar, demonstrated a significant reduction in bacterial viability (Fig. 6B). Colony-forming Units per milliliter

(CFU/mL) were quantified by counting CFUs (Fig. 6C), and the MBC₅₀ value of RsSO was determined to be 5.4 mg/mL (Fig. 6D). However, MBC₉₀ is still higher than MIC₉₀ indicating a bactericidal effect up to a certain concentration of RsSO. The observed inhibitory effect of RsSO could be attributed to the fatty acids present in notable amounts. Fatty acids have recently gained attention due to their microbial inhibitory mechanism that act via non-specific targets, unlike antibiotics [13,49]. It would be worth exploring the mechanistic aspects of the inhibitory action of RsSO on K. pneumoniae.

3.7. RsSO demonstrates significant biofilm inhibition and eradication in K. pneumoniae

Biofilms are complex communities of bacterial cells that exhibit enhanced resistance to anti-microbial agents [26,50]. We investigated the biofilm inhibition and eradication potential of RsSO against K. pneumoniae. To evaluate the inhibitory effects against K. pneumoniae, RsSO was applied to cultures at the stage of biofilm initiation. The biofilm eradication potential was subsequently assessed on mature biofilms that had been established 72 h post-inoculation. RsSO treatment was administered to the mature biofilms of K. pneumoniae for a duration of 24 h (Fig. 7A). RsSO inhibited the biofilm formation by K. pneumoniae, as visualized in brightfield microscopic images of biofilms stained with crystal violet (Fig. 7B). Image J semi-automated tool was employed to quantify the area covered by the biofilms formed. RsSO demonstrated a significant dose-dependent inhibitory effect on biofilm formation in K. pneumoniae, reducing the biofilm-covered area by 85% at a concentration of 4.0× MIC₉₀ (Fig. 7C). Mature biofilms of K. pneumoniae, when treated with RsSO resulted in a significant reduction of nearly 50% in the biofilm-covered area (Fig. 7D). We conclude that RsSO could not only inhibit the process of biofilm formation but could even disrupt the mature biofilms formed by K. pneumoniae. Further exploration of the combinatorial effect of RsSO with conventional antibiotics would be insightful as disrupting biofilms may even enhance the existing antibiotic efficacy.

Fig. 7.

Rauvolfia serpentina seeds supercritical–carbon dioxide–fluid extraction (SCFE) oil (RsSO) demonstrates significant biofilm inhibition and eradication in Klebsiella pneumonia (K. pneumoniae). (A) A schematic representation outlines the experimental approach used to assess the biofilm inhibition and eradication potential of RsSO. (B) Biofilms formed by K. pneumoniae were stained with crystal violet and subsequently imaged under a bright field microscope (Nikon) at 400× magnification using a 40× objective. (C, D) The ImageJ semi-automated tool was employed to calculate the percentage of the surface area covered by the biofilm. Biofilm inhibition (C), and biofilm eradication (D). Bar graphs were generated to represent the area covered by biofilm under the indicated RsSO treatments. The data reflect results from three independent images, with error bars representing the mean ± standard error of the mean (SEM). Statistical significance was determined using one-way analysis of variance (ANOVA), ^∗∗P < 0.005, and ^∗∗∗P < 0.0001, respectively.

3.8. RsSO isnon-mutagenic in nature

We performed the classical bacterial mutagenicity test, also referred as Ames assay which is readily used as a primary test to assess the genotoxic effects. The assay uses test strains of S. typhimurium and E. coli that are auxotrophic for histidine (his^-) and tryptophan (trp), respectively [11]. The strains of S. typhimurium are unable to grow in minimal media devoid of histidine, while E. coli strains are unable to grow in minimal media devoid of tryptophan. The colonies under these conditions that grow are called revertant colonies or prototrophs that have undergone base pair substitutions or frameshift mutations [11]. Revertant colony numbers and their mutagenicity ratio (MR) > 2 with respect to the vehicle (DMSO ) is considered as an indicator of genotoxicity. Revertant bacteria are those which are permanently converted to the prototrophic state, continue to grow and will become visible to the naked eye. The experiment was performed with vehicle control, positive control and with five concentrations of RsSO with and without S9 metabolic activation. All the five tester strains were subjected to RsSO from 0.05 to 5 μL/plate (Table 3, Table 4). MR > 2 was not observed in any of the tester strain, at any test concentration of RsSO.

Table 3.

Bacterial mutagenicity analysis of Rauvolfia serpentina seeds supercritical–carbon dioxide–fluid extraction (SCFE) oil (RsSO) showing the average number of revertants per plate in Salmonella typhimurium (S. typhimurium) TA 1535, TA 1537, TA 98, TA 100 and Escherichia coli (E. coli) WP2 uvrA strains in the absence of metabolic activation (–S9).

RsSO dose (μL/plate)	Bacterial strains
	TA 1535		TA 1537		TA 98		TA 100		E. coli WP2 uvrA
	Mean ± SDa	MRa	Mean ± SDa	MR	Mean ± SDa	MRa	Mean ± SDa	MRa	Mean ± SDa	MRa
0.00 (DMSO)	7.0 ± 2.6	1.0	3.6 ± 1.5	1.0	40.3 ± 12.5	1.0	103.3 ± 6.1	1.0	41.0 ± 7.0	1.0
0.05	2.0 ± 0.0	0.2	2.0 ± 0.0	0.5	56.3 ± 1.5	1.3	85.3 ± 8.7	0.8	38.0 ± 3.0	0.9
0.15	2.3 ± 0.5	0.3	3.3 ± 1.5	0.9	46.3 ± 3.7	1.1	101.3 ± 3.0	0.9	32.3 ± 3.5	0.7
0.50	3.0 ± 1.7	0.4	3.3 ± 1.1	0.9	49.3 ± 5.0	1.2	84.3 ± 3.5	0.8	33.0 ± 4.5	0.8
1.50	3.0 ± 1.0	0.4	3.3 ± 0.5	0.9	43.3 ± 8.0	1.0	88.6 ± 3.5	0.8	37.0 ± 2.0	0.9
5.00	3.0 ± 1.0	0.4	2.6 ± 0.5	0.7	23.3 ± 10.2	0.5	82.6 ± 13.3	0.8	43.6 ± 1.5	1.0
Standard mutagenb	278.6 ± 18.1	39.8c	99.6 ± 12.8	27.1c	110.6 ± 5.0	2.7c	474.6 ± 21.0	4.5c	124.0 ± 10.5	3.0c

^aMean of revertant colonies per plate (n = 3). SD: standard deviation; MR: mutagenicity ratio = Number of revertant colonies in RsSO or Mutagen/number of revertant colonies in Vehicle (dimethyl sulphoxide (DMSO)).

^bStandard mutagen: 2-Nitrofluorene (1 μg/plate) in TA 98; Sodium azide (0.5 μg/plate) in TA 100 and TA1535, 9-aminoacridine (50 μg/plate) in TA 1537 and 2-aminoanthracene (20 μg/plate) in E. coli WP2 uvrA.

^cIndicates the values are significant (P < 0.05) as compared to vehicle (DMSO).

Table 4.

Bacterial mutagenicity analysis of Rauvolfia serpentina seeds supercritical–carbon dioxide–fluid extraction (SCFE) oil (RsSO) showing the average number of revertants per plate in Salmonella typhimurium (S. typhimurium) TA 100 strain in the presence of metabolic activation (+S9).

RsSO dose (μL/plate)	Bacterial strain
	TA100
	Mean ± SDa	MRa
0.00 (DMSO)	106.6 ± 5.0	1.0
0.05	85.6 ± 2.0	0.8
0.15	83.6 ± 5.5	0.7
0.50	72.0 ± 10.0	0.6
1.50	74.0 ± 4.5	0.6
5.00	57.6 ± 3.5	0.5
Standard mutagenb	520 ± 13.2c	4.8c

^aMean of revertant colonies per plate (n = 3). SD: standard deviation; MR: Mutagenicity ratio = Number of revertant colonies in RsSO or Mutagen/number of revertant colonies in Vehicle (dimethyl sulphoxide (DMSO)).

^bStandard mutagen: Benzo(a)pyrene (5 μg/plate) in TA 100.

^cIndicate the values are significant (P < 0.05) compared to vehicle (DMSO).

The spontaneous reversion for strains TA 98, TA 100, TA 1535, TA 1537 and E. coli WP2 uvrA in vehicle and with standard mutagens (positive controls) align with the previous reports. ANOVA followed by Dunnett's multiple comparison tests indicated that no significant increase in the number of revertant colonies in tester strains with and without metabolic activation treatment of RsSO at concentrations of 5.0, 1.5, 0.5, 0.15 and 0.05 μL/plate was observed. On the contrary, respective to positive control, a significant (P < 0.05) increase in MR in the absence or presence of S9 metabolic activation was observed. Collectively, we demonstrate that RsSO did not induce any frameshift or point mutations by base substitutions in any of the tester strains of S. typhimurium or E. coli WP2 uvrA. RsSO was found to be non-mutagenic up to the tested concentration of 5.0 μL/plate with and without metabolic activation system under the tested experimental conditions. Collectively, the data provide insights into the safe use of RsSO, as it demonstrates a non-mutagenic in all bacterial strains.

4. Conclusions

In the current study, the investigation on the chemical composition of RsSO extracted via SCF extraction, identified a variety of bioactive compounds using several analytical techniques. Fatty acids, including palmitic acid, stearic acid, oleic acid, and linoleic acid, were characterized using GC-FID. GC-MS/MS analysis further revealed active biomarkers such as vanillin, 14-methylpentadecanoate, palmitic acid ethyl ester, linolelaidic acid methyl ester, and squalene. Additional examination of the unsaponifiable matter identified compounds like squalene, campesterol, stigmasterol, γ-sitosterol, β-amyrin, and lupeol. HPTLC fingerprinting confirmed the presence of key lipids and phytometabolites, including MA, VA, TF, VN, SQ, BS and LP. FT-IR and ¹H NMR spectroscopy were employed to analyse the functional groups and chemical shifts, providing deeper insights into the oil composition. The anti-microbial activity of RsSO was demonstrated by dose-dependent inhibition of bacterial viability, reflected in its MIC₅₀ and MIC₉₀ values. Additionally, RsSO exhibited significant biofilm inhibition and bacterial cell wall disruption. Notably, the oil showed no genotoxic effects in the Ames assay, indicating its safety profile. Despite the extensive biological activities linked to these compounds, there is a lack of comparable studies in the literature connecting these biomarkers to R. serpentina seeds. The identification of these bioactive compounds in RsSO lays a significant foundation for future pharmacological research and underscores its potential as a source of novel therapeutic agent.

CRediT authorship contribution statement

Acharya Balkrishna: Resources, Project administration, Funding acquisition, Conceptualization. Monali Joshi: Visualization, Software, Methodology, Formal analysis. Yash Varshney: Visualization, Software, Methodology, Formal analysis. Manisha Kabdwal: Visualization, Software, Methodology, Formal analysis. Himanshu Jangid: Visualization, Software, Methodology, Formal analysis. M. Priya Rani: Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Data curation. Pardeep Nain: Writing – review & editing, Investigation. Savita Lochab: Writing – original draft, Methodology, Investigation, Formal analysis, Data curation. Anurag Varshney: Writing – review & editing, Supervision, Project administration, Conceptualization.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Declaration of competing interest

The authors declare that there are no conflicts of interest.

Appendix A. Supplementary data

The following are the Supplementary data to this article.