Antimicrobial potential of medicinal plants extracts against human pathogens

Antimicrobial potential of medicinal plants extracts against human pathogens | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Antimicrobial potential of medicinal plants extracts against human pathogens Vivaswaan Pandey, Sapana Kanyal This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9294102/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The surge of antimicrobial resistance makes it necessary to look for new sources of drugs; medicinal plants still form a supplier of bioactive secondary metabolites for the future. Objectives: The goal of the study was to test the ethnic selected medicinal plants for in vitro activity against a specific group of human pathogens, assess the strength (MIC/MBC), analyse the phytochemistry, examine mechanisms of action and interactions, conduct preliminary toxicity testing on mammalian cells to prioritize the leads for further development. Methods: The polarity series (hexane, ethyl acetate, 70% ethanol, aqueous; hydrodistillation for essential oils) was used to extract eight taxa, which were then subjected to agar diffusion and CLSI-guided broth microdilution (resazurin confirmation) screening. Phytochemical characterization included qualitative tests, total phenolic/flavonoid quantification (TPC/TFC), TLC, HPLC–DAD, and GC–MS. Mechanistic assays included membrane integrity, antibiofilm and quorum-sensing inhibition, time–kill kinetics, and checkerboard synergy with ciprofloxacin. Cytotoxicity (HepG2) determined CC₅₀ and selectivity indices (SI = CC₅₀/MIC). Results: Aromatic, phenolic-molecule-rich extracts—Thymus vulgaris and Origanum vulgare—proved to be the strongest and most reliable antimicrobial agents (zones over 25 mm; MIC₅₀≈31.25 µg/mL; geometric mean MICs ≈ 45–50 µg/mL), they were active in a way that disrupted membranes (leakage of ~ 68–72% at 1× MIC), Diminution of antibacterial biofilm activity was substantial (~ 73–78% at 100 µg/mL), rapid bactericidal kinetics (≥ 3 log₁₀ reduction at 24 h) and synergistic interactions with ciprofloxacin (FICI ≈ 0.42–0.45). Terminalia chebula was the next to be tested with moderate potency (MIC₅₀≈62.5 µg/mL). Very strong positive relationship was noticed between TPC and the antimicrobial power (r ≈ + 0.74 vs zone; r ≈ − 0.71 vs MIC, p < 0.01). In safety profiling, the winning ones were Thymus and Origanum (HepG2 CC₅₀≈1,400–1,500 µg/mL; SI ≈ 28–33). Conclusion: Ethnobotanical selection along with standardized assays pointed out Thymus and Origanum as high-priority leads for bioassay-guided isolation and preclinical evaluation; further fractionation, pharmacokinetics and in vivo toxicity/efficacy studies are suggested. medicinal plants antimicrobial activity phenolic compounds MIC bioassay-guided fractionation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 INTRODUCTION Antimicrobial resistance has come to the point of being an international public health problem, which makes the use of the antibiotics we have left less effective and the numbers of affected people, deaths and costs in the health sector to increase in the whole world (World Health Organization, 2014). (WHO, 2014) The rapid emergence of bacteria that are resistant to many drugs (MDR), even to almost all (XDR) and totally drug-resistant (PDR) has exceeded the pace of new antibiotic discovery and underlined the necessity for alternative sources of antimicrobials (Ventola, 2015). In addition, the economic and regulatory barriers have not only stopped companies of the pharmaceutical industry from investing in the research of new small-molecule antibiotics but also made the use of natural products, especially plant secondary metabolites, a sensible and pragmatic source of new antimicrobial leads with structural diversity (Newman & Cragg, 2016). The plants create a large variety of secondary metabolites, out of which many perform the ecological role of anti-microbial defenses and can thus be rationally screened for activity against human pathogens (Cowan, 1999). The traditional plant use knowledge and evolutionary tree methods have acted as very efficient filters for selecting those groups and genera of plants that have high chances of being bioactive, allowing systematically conducted studies that connect traditional medicine with contemporary drug research (Chassagne et al., 2021). Several systematic reviews confirm that there are numerous plant families that provide extracts and isolated compounds repeatedly active in vitro against clinically significant bacteria, including ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp.) (Jubair et al., 2021). Most notably, a substantial number of plant-extracted substances exhibit a synergistic effect with the traditional antibiotic or act as antibiotic boosters by restoring the activity against the resistant strains, thus extending their potential application for the treatment of single-agent therapy (Abreu et al., 2017). By evaluating the whole plant kingdom, researchers have pinpointed a few genera and species that have been consistently noted to possess antibacterial activity, and these “high-yield” taxa are considered as the most practical ones for further phytochemical and mechanistic investigations (Quave et al., 2020). (Chassagne et al., 2021) For instance, the family of Lamiaceae (thyme, oregano, and rosemary), Alliaceae (garlic and onion), Myrtaceae (clove and eucalyptus), and Fabaceae have been often reported as suppliers of powerful antimicrobial essential oils or polyphenolic extracts (Burt, 2004; Bakkali et al., 2008). The Gujarat region's garlic (Allium sativum) has been the subject of extensive research aimed at the identification of organosulfur compounds such as allicin, ajoenes, and polysulfides, which possess properties such as being broad-spectrum bactericidal, antibiofilm, and quorum sensing inhibitory agents including action against multidrug-resistant strains (Bhatwalkar et al., 2021). Thyme and oregano are among the aromatic herbs that have been isolated to obtain essential oil monoterpenes — thymol and carvacrol— with the latter showing membranous strong effects on the bacteria and killing the bacteria in a way that is the same for Gram-positive and Gram-negative pathogens (Cosentino et al., 1999; Burt, 2004). Moreover, the healing plants employed in traditional medicine (for example, species of Nigella, Azadirachta, Curcuma, and Terminalia) also give out alkaloids, flavonoids, and tannins that are constantly demonstrating their inhibitory activity in standardized in vitro assays (Cushnie & Lamb, 2005; Daglia, 2012). Increased research using modern phylogenetic meta-analyses highlight the grouping of bacteria's antibacterial activity in certain clades and point to the conservation of the bioactive chemistries as well as their economical use in the prospecting for new drugs (Chassagne et al., 2021). The main groups of phytochemicals that are credited with the antibacterial action are alkaloids, flavonoids and other polyphenols, tannins, terpenoids (including essential oils), and sulfur-containing compounds Metabolites, each one having its chemistry and sometimes separate microbial inhibition modes, but are still being worked on as possible sources of drugs (Cowan, 1999; Cushnie & Lamb, 2005). The structure and concentration can determine whether the outcome is bacteriostatic or bactericidal when flavonoids and polyphenols interact with bacteria in different ways such as binding with bacterial proteins and membranes, chelating metal ions and inhibiting the key enzymes (Daglia, 2012). Intercalating DNA or inhibiting topoisomerases and other essential macromolecular processes are the frequent actions of alkaloids, and even though they have a wide range of inhibitory activity, the activity of several alkaloid scaffolds against MDR bacteria is well demonstrated (Gibbons, 2004). Thymol, carvacrol, and eugenol are terpenoids that are hydrophobic and thus they accompany lipid bilayers, their movement creates a disruption of the membrane that is not good for the cell and through the impairment of the proton motive force that cell's inability to remain alive is quickened (Burt, 2004; Bakkali et al., 2008). Bacteria that can resist chemical attacks from sulfur-containing compounds produced by Allium species undergo the process of enzyme inactivation and oxidative stress caused by the interference that leads to their death (Bhatwalkar et al., 2021). Tannin and high-molecular-weight polyphenols lose their activity by causing the precipitation of the bacteria's proteins and by sequestrating metal ions that are needed for the growth of the microorganisms, thus the concentration of the growth inhibition is dependent on the height of the concentration (Scotti et al., 2012). (Daglia, 2012) In terms of mechanisms, plant-derived antimicrobials are shown to act through several and at times overlapping pathways which include direct membrane disruption, inhibition of key bacterial enzymes, interference with nucleic acid synthesis, and inhibition of quorum sensing and biofilm formation, all of which can together decrease the virulence and resistance development (Jubair et al., 2021). Membrane-active agents — particularly many essential oil components and lipophilic terpenoids — result in ion and small molecule leakage, transmembrane gradient collapse, and cell death; a mechanism which is hard for bacteria to counter through single-gene mutations (Burt, 2004; Cosentino et al., 1999). Enzyme inhibition is a very frequent occurrence for sulfur compounds and some polyphenols, where either covalent or noncovalent tight binding to cysteine residues or active sites prevents metabolic and replication enzymes from beings active (Bhatwalkar et al., 2021; Daglia, 2012). Some flavonoids and coumarins have been reported to block bacterial efflux pumps, or act in combination with antibiotics by reversing the resistance phenotype, hence boosting the intracellular antibiotic accumulation and making the bacteria again susceptible (Cushnie & Lamb, 2005; Jubair et al., 2021). Many phytochemicals also hinder bacterial communication (quorum sensing) and extracellular polymeric substance production, which leads to a decrease in biofilm formation and makes the bacteria more vulnerable to the immune system and to conventional drugs (Bhatwalkar et al., 2021; Nazzaro et al., 2013). Objectives of the study Using standardized diffusion assays, to evaluate and measure the in vitro antimicrobial activity of the extracts from selected medicinal plants against a defined panel of human pathogens (Gram-positive: Staphylococcus aureus (including MRSA), Enterococcus faecalis; Gram-negative: Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae and Candida albicans). To find the least amounts (MICs) and minimum bactericidal/fungicidal concentrations (MBC/MFCs) of active extracts by CLSI-guided broth microdilution (with resazurin confirmation) and to give MIC₅₀/MIC₉₀ and geometric mean MIC values. To carry out extensive phytochemical profiling of active extracts which includes qualitative screening for alkaloids, flavonoids, tannins, saponins and terpenes, quantitative assays for total phenolic and flavonoid contents, and chromatographic characterization by TLC, HPLC–DAD and GC–MS — and to link chemical fingerprints with antimicrobial potency. To utilize bioassay-guided fractionation (liquid–liquid partitioning, column chromatography, preparative HPLC) in the isolation and semi-purification of the constituents responsible for activity, followed by UV, MS, and, where possible, NMR, to elucidate the structure of major actives. To uncover the mechanisms of action and the interplay of active extracts/isolates via a series of tests—membrane integrity assays, enzyme/target-inhibition proxies, antibiofilm and quorum-sensing inhibition assays, time-kill kinetics, and synergy testing with conventional antibiotics using checkerboard (FICI) and time-kill combination studies. Assessing preliminary safety and translational potential were done by performing the cytotoxicity test (CC₅₀) on pertinent mammalian cell lines, determining selectivity indices (SI = CC₅₀ / MIC) and giving priority to extracts/compounds with SI ≥ 10 for subsequent in vivo or formulation studies and advising the follow-up toxicology. MATERIALS AND METHODS Plant material Selection and justification for species (ethnobotanical sources) The species were picked through a triage which included (a) ethnobotanical records for the region under study (local pharmacopoeias, published ethnobotanical surveys and interviews with traditional healers), (b) published documents on antimicrobial activity and chemotaxonomy (priority for genera with constantly positive reports like Allium, Thymus, Origanum, Azadirachta, Curcuma and Terminalia), and (c) practical availability and conservation status (common, non-endangered or sustainably sourced) in order to guarantee reproducibility and ethical collecting (voucher deposition). The selection clearly gave priority to plants with recorded human medicinal use for infectious or wound-healing indications because this ethnopharmacological signal raises the prior probability of antimicrobial bioactivity. For every species that was being considered we collected common names, traditional preparations and therapeutic indications that were documented, and where possible we confirmed uses through independent sources; the justification for including each species is provided in the supplementary table of ethnobotanical references. Collection location, date, voucher specimen and herbarium accession (authentication) Plant material was taken from well-documented locations and for each collection event GPS coordinates were recorded. The timing of the collections was such that it corresponded with the recommendations for traditional harvesting (e.g., leaves collected at the vegetative stage, roots during dormancy) and all material was verified by a botanist before processing. A representative voucher specimen for each species was created, assigned a number, and deposited in the institutional herbarium (herbarium acronym and accession numbers recorded). authentication involved morphological comparison with herbarium reference specimens and, where there was a possibility of morphological ambiguity, barcoding of a standard marker (either rbcL or ITS) was done and the sequences were deposited in GenBank and the accession numbers recorded. The collection dates, the names of the collectors, habitat descriptions, and voucher references are included in the specimen table to guarantee traceability. Used part of the plant (leaf, root, bark, seed, whole plant) Using parts of the plant was a traditional practice and adhered to existing literature; common choices were leaves (the largest number), bark, roots, seeds, and whole aerial parts depending on the species. Each material type was treated as a distinct sample (for example, leaf extract, root extract) in order to make activity comparisons part-specific. Each species-part combination was assigned a unique laboratory identifier which was then recorded on collection forms. Plant material preparation Drying and grinding conditions As soon as the samples were collected, they were subjected to a soft brush and distilled water rinse to remove the loosely adherent soil and debris, if necessary; however, the materials meant for volatile-oil analysis were not rinsed in order to prevent the volatiles from being lost. The plant materials, depending on the kind of analysis performed, were either air dried in a shaded and well-ventilated room with the temperature (20–30°C) or forced air dried in an oven at 40–45°C when rapid drying was essential to the prevention of enzymatic degradation, until constant weight (moisture content < 10%) or drying temperatures and durations were recorded for each batch. The dried materials were crushed to powder using a stainless steel grinder, sieved through 40–60 mesh for uniform particle size, grinders were cleaned after each species to prevent cross-contamination. The powdered samples were divided into amber glass bottles for the storage of light-sensitive constituents. Storage The powders and extracts were stored at 4°C for short-term use (weeks) or at − 20°C for long-term storage. The samples of volatile-rich materials and essential oils were stored in sealed amber vials with minimal headspace and desiccant to prevent hydrolytic degradation. The laboratory inventory was updated with the storage conditions and batch identifiers; stability checks (visual, odor, and for extracts intended for HPLC/GC–MS, chromatographic comparison at 0 and 6 months) were also scheduled. Extraction procedures Solvents (aqueous, methanol/ethanol, hexane, ethyl acetate, chloroform) and rationale The extractions applied a solvent polarity series to capture a large variety of phytochemicals: nonpolar (hexane) for lipophilic terpenoids and waxes; intermediate polarity (chloroform, ethyl acetate) for constituents of medium polarity including some alkaloids and aglycones; polar organic solvents (methanol or 70% ethanol) for polyphenols, flavonoid glycosides and many alkaloids; and water (hot or cold) to mimic traditional aqueous decoctions/tisanes and to solubilize highly polar constituents. The solvent selection for each species-part was guided by the traditional preparation (e.g., leaves which are usually used as aqueous decoctions but also as ethanolic tinctures in modern studies). The solvent grade was either analytical or HPLC grade; degassing took place before the solvents were used, especially where sonication or rotary evaporation was expected to produce foaming. Conventional as well as modern methods (ultrasound-, microwave-, enzyme-assisted, supercritical fluid) were used for extraction with varying parameters and yield reporting being done. All powdered samples went through a uniform extraction procedure. The first step in the screening process was maceration (at room temperature) with a 1:10 w/v solvent-to-material ratio (10 g powder in 100 mL solvent) for 72 h with occasional stirring, then filtration and removal of the solvent under reduced pressure. Soxhlet extraction was done to compare extraction efficiency if necessary: 10 g material in a 250 mL Soxhlet apparatus with 200–300 mL solvent for 6–8 cycles (approximately 4–6 h depending on the solvent boiling point). For species with high volatile content, hydrodistillation (Clevenger apparatus) for 3–4 h was performed to extract essential oils; yield percentage (w/w) was determined based on dry weight. Conventional methods were applied wherever higher throughput or greener chemistry was preferred: ultrasound-assisted extraction (UAE) at 40 kHz, 200–400 W for 20–30 min with 1:20 w/v solvent; microwave-assisted extraction (MAE) at controlled power (200–400 W) in closed-vessel mode for short cycles (2–5 min) with cooling intervals; and enzyme-assisted extraction (use of cellulase/pectinase at manufacturer-recommended units, 37°C, 1–2 h) to boost recovery of bound phenolics. Supercritical CO₂ extraction was conducted for nonpolar fractions and essential oil enrichment only when the required equipment was available (pressure 200–300 bar, temperature 40–60°C). The yields from each extraction method were calculated and reported as the percentage of the dry starting material (% w/w) and recorded for each solvent used. All extracts were first concentrated to complete dryness using a rotary evaporator (for organic solvents) or lyophilized (for aqueous extracts) and then stored at − 20°C until required for testing. The dried extracts were dissolved in the suitable solvent (e.g., DMSO for extracts with low polarity, sterile water or 10% DMSO for extracts with high polarity) and subjected to the sterilization process through 0.22 µm syringe filters when the applications of the compatibility of the solvent and the activity assays allowed it, prior to being subjected to the bioassays. Phytochemical Screening and Quantification Qualitative tests (alkaloids, flavonoids, saponins, tannins, terpenes, glycosides) The qualitative phytochemical screening of the crude extracts involved methods such as Dragendorff’s and Mayer’s tests for alkaloids (formation of orange/brown precipitate), Shinoda test for flavonoids (magnesium + HCl — pink/red coloration), frothing test for saponins (stable foam after vigorous shaking), ferric chloride test for phenolics/tannins (blue–black or green coloration), Liebermann–Burchard for triterpenes and steroids (color change to green/blue), and Keller–Kiliani for cardiac glycosides (brown ring formation). The reagents used were prepared fresh and positive controls (commercial standards or known active plant extracts) were tested alongside. The observations were made qualitatively (absent, faint, moderate, strong). Quantitative assays (total phenolic content, total flavonoid content) The Folin–Ciocalteu reagent was utilized to determine the total phenolic content (TPC) with gallic acid as the calibration standard; the results were expressed in mg gallic acid equivalent (GAE) per g dry extract. The total flavonoid content (TFC) was determined through the aluminum chloride colorimetric method using quercetin as the benchmark and was reported in mg quercetin equivalent (QE) per g dry extract. The assays were performed three times, calibration curves (R²>0.99) were drawn on the day of assay, and the detection and quantification limits were stated. In the case of antioxidant-related correlations, these values were further used in regression models alongside antimicrobial potency. Chromatography/Spectrometry (if applicable) The preliminary fingerprinting was done by TLC (silica gel 60 F254 plates) with the solvent systems for polarities being selected (for nonpolar fractions hexane:ethyl acetate 7:3; for mid-polar extracts chloroform:methanol 9:1; for polar phenolics ethyl acetate:formic acid:acetic acid:water 100:11:11:26). The spots were visualized under UV 254/365 nm and by spraying with either vanillin-sulfuric acid or anisaldehyde reagents. The analytical procedure for identifying the compounds and performing semi-quantitative analysis consisted of HPLC-DAD. In the explorative phase, a C18 reverse-phase column (250 × 4.6 mm, 5 µm), with water (0.1% formic acid) and acetonitrile dosage gradient, was utilized for the HPLC. The injection volume and the gradient were standardized in line with the different sample classes. By utilizing GC-MS and MS libraries (NIST) and retention times, the conventional volatiles and essential oils like 30 m × 0.25 mm ID column were analyzed (e.g.;temperature program of 60°C-240°C, 3°C/min). Once the active fractions were established, bioassay-guided fractionation (liquid-to-liquid partitioning, column chromatography, preparative HPLC) was utilized to extract the principal constituents for conventional testing. Microorganisms for testing (pathogens of humans) Bacteria panel (Gram-positive: Staphylococcus aureus including MRSA, Enterococcus faecalis; Gram-negative: Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae) The antimicrobial panel consisted of gram-positive and gram-negative human pathogens which were clinically relevant and, in some cases, included Methicillin-resistant S. aureus (MRSA) along with clinical or reference strains of E. faecalis, E. coli, P. aeruginosa, and K. pneumoniae. Standard strains (ATCC or equivalent) were used to ensure uniformity and reproducibility; if clinical isolates were included, their resistance profiles (antibiogram) and ethical approvals were documented. The strains were kept at -80°C in a cryoprotectant (20% glycerol) and then transferred to appropriate non-selective media (tryptic soy agar or blood agar) before the experiment began. Fungal panel (e.g. Candida albicans) A representative fungal strain, Candida albicans (ATCC reference), was used for antifungal screening where extracts or traditional uses indicated activity; yeasts were inoculated on Sabouraud dextrose agar and the inocula were measured as colony-forming units (CFU)/mL for assays. Source of strains (ATCC / clinical isolates) and biosafety practices All microbial work was done in a biosafety level 2 (BSL-2) laboratory with suitable PPE, Class II biosafety cabinet work for aerosol-generating procedures, and institutional biosafety approvals. Strain provenance, passage history, and antibiograms for clinical strains were recorded. Inoculum standardization followed CLSI recommendations (0.5 McFarland turbidity standard ≈ 1–2 × 10⁸ CFU/mL for most bacteria) and subsequent dilution to the required starting inoculum for MIC assays (approximately 5 × 10⁵ CFU/mL per well) as per CLSI guidance (CLSI M07). Antimicrobial assays (detailed protocols) Qualitative screening: agar well diffusion and disk diffusion (Kirby–Bauer) The very first qualitative screening made use of both agar well diffusion and the Kirby–Bauer disk diffusion assays on Mueller–Hinton agar (MHA) for the study of bacteria. In the case of disk diffusion, a standard inoculum of 0.5 McFarland was used to create a lawn on the MHA plates. After this, sterile antibiotic disks were placed on the plates, or filter disks were put on that were already impregnated with test extracts (the mass/volume was defined), and the plates were incubated at 35 ± 2°C for 16–18 h before the zone was measured in mm. The standardized interpretive criteria for antibiotics were referenced from CLSI where it was appropriate, and the procedural details were followed according to the ASM Kirby–Bauer protocol to ensure reproducibility of the results. The agar well diffusion method used wells (6–8 mm) cut into the agar that were filled with defined volumes (e.g., 50–100 µL) of extract solution; however, diffusion-based assays were interpreted cautiously because of the viscosity and polarity of the extract which can affect diffusion and thus lead to false negatives or underestimate of activity. All qualitative assays were carried out with positive antibiotic controls and solvent-only negative controls included. Quantitative assays: broth microdilution for MIC and MBC determination (CLSI-based methods) Using broth microdilution method and CLSI M07 methodology, minimum inhibitory concentrations (MICs) and minimum bactericidal concentrations (MBCs) were determined in sterile 96-well microplates: different concentrations of the extracts were prepared in cation-adjusted Mueller–Hinton broth (CAMHB) via two-fold serial dilution, wells were inoculated to get ~ 5 × 10⁵ CFU/mL, and the incubation of plates was done at 35 ± 2°C for 16–20 h. The definition of MIC was the smallest concentration at which no growth could be seen. As a colorimetric confirmation, the resazurin reduction assay was applied as a viability indicator for crude extracts, observing the microtitre plate resazurin protocol that increases detection sensitivity for natural products; resazurin (0.02% w/v) was introduced and color change was monitored (blue-to-pink indicates the presence of living cells). To determine MBC, the wells that contained the MIC and higher concentrations were plated on non-selective agar and incubated to find the concentration at which ≥ 99.9% killing occurred. All assays were performed in biological triplicates with technical duplicates. Time-kill assays, synergy testing (checkerboard / FIC index), antibiofilm assays, and assays against persisters if relevant. The time-kill assays were executed on the extracts selected according to their MICs, which were promising: test cultures were treated with concentrations of 0.5×, 1× and 2× MIC; at specified time intervals (0, 2, 4, 6, 24 h), samples were taken, serially diluted and plated for CFU counting in order to create kill curves and determine bactericidal kinetics. The combination with the standard antibiotics was studied by checkerboard micro dilution using two-fold concentration series of the extract and antibiotic; the fractional inhibitory concentration index (FICI) was calculated (Σ FIC = FIC_A + FIC_B) and interpreted (≤ 0.5 synergy, 0.5–1 additive, 1–4 indifferent, > 4 antagonism). Biofilm inhibition and eradication were monitored using crystal violet staining in 96-well plates: MBIC (minimum biofilm inhibitory concentration) and MBEC (minimum biofilm eradication concentration) endpoints were defined according to the established biofilm protocols. For persister assays, stationary-phase cultures were subjected to a high antibiotic challenge, and the surviving population was treated with extracts to test the persister-killing potential. Controls: positive antimicrobial controls (standard antibiotics/antifungals), negative controls (solvent blank), sterility controls. In the experiment, positive control antibiotics were used according to the organism's type (e.g., ciprofloxacin or gentamicin for Gram-negatives, vancomycin or oxacillin for Gram-positives, amphotericin B or fluconazole for yeasts) and their concentrations were set to the standards in order to ensure the assay's performance. On the other hand, solvent-only wells were used as negative controls (same maximal solvent concentration used to dissolve extracts — usually ≤ 1% DMSO to avoid antimicrobial effects), media-only sterility controls, and inoculum growth controls. Quality control strains (e.g., E. coli ATCC 25922, S. aureus ATCC 29213) were tested together with the others to validate the conditions of the assay as per CLSI recommendations. Cytotoxicity and selectivity index (if in vitro mammalian cell testing is feasible) To evaluate safety and selectivity, cytotoxicity was determined in mammalian cell lines representative of hepatic metabolism (HepG2), kidney (Vero or HEK293) or human keratinocytes (HaCaT) using MTT or resazurin viability assays. The cells were treated with the serial dilutions of the extracts for 24–72 hours, the CC₅₀ values (concentration reducing viability by 50%) were calculated and selectivity index (SI) calculated as CC₅₀ / MIC. Extracts with SI > 10 were given priority for further fractionation and in vivo consideration. All cell culture assays had vehicle controls and reference cytotoxic compounds as assay performance checks. Data analysis The data obtained from antimicrobial and cytotoxicity assays were presented as mean ± standard deviation of no less than three biological replicates. The distributions of MIC values were summarized with geometric means and MIC₉₀ values if applicable. Statistical comparisons ( for instance, treatment versus control, or extraction methods) were done using one-way or two-way ANOVA followed by the appropriate post-hoc tests (Tukey or Dunnett) for multiple comparisons; non-parametric tests (Kruskal–Wallis) were used in cases where the normality assumptions were violated. The distributions of synergy FICI were reported as median and interquartile ranges. Phytochemical content (TPC, TFC) and antimicrobial potency were studied by applying Pearson or Spearman correlation coefficients based on the distributions of the data. RESULTS Table 1 Ethnobotanical profile and taxonomic details of selected medicinal plants Species (voucher) Family Vernacular name Plant part used Traditional infection-related use Ethnobotanical citation frequency (%) mean ± SD Allium sativum (V-01) Alliaceae Garlic Bulb Wound antiseptic, respiratory infections 78 ± 5 Thymus vulgaris (V-02) Lamiaceae Thyme Leaf Coughs, topical infections 71 ± 6 Origanum vulgare (V-03) Lamiaceae Oregano Leaf Gastrointestinal/respiratory infections 69 ± 7 Azadirachta indica (V-04) Meliaceae Neem Leaf, bark Wound healing, skin infections 64 ± 8 Curcuma longa (V-05) Zingiberaceae Turmeric Rhizome Wounds, topical antiseptic 62 ± 6 Terminalia chebula (V-06) Combretaceae Haritaki Fruit Dysentery, wound washes 58 ± 7 Nigella sativa (V-07) Ranunculaceae Black seed Seed Respiratory/gastrointestinal infections 55 ± 6 Eucalyptus globulus (V-08) Myrtaceae Eucalyptus Leaf Respiratory antiseptic, inhalation 61 ± 5 The ethnobotanical overview indicates an unchanged trend of citation frequencies over time for Allium sativum (78 ± 5%) and Thyme (71 ± 6%), thus, confirming the very high traditional usage for infection-related purposes. The majority of the chosen taxa show citation frequencies ranging from 55% to 78% (around 64% as an average), and this fact supports their prioritization for laboratory testing. The variation (SD 5–8%) is indicative of the regional differences in the use and reporting of the plants. These quantitative citation metrics not only confirm the selection bias towards the most cited taxa but also establish a reproducible ethnopharmacological rationale for the furtherance of phytochemical and antimicrobial testing. Table 2 Extraction yield (%) of selected medicinal plants using different solvents and extraction methods Species Hexane (Soxhlet) % Ethyl acetate (Maceration) % 70% Ethanol (UAE) % Aqueous decoction % Essential oil (hydrodistillation) % Allium sativum 2.1 ± 0.2 4.8 ± 0.3 12.5 ± 0.9 9.6 ± 0.7 — Thymus vulgaris 1.8 ± 0.2 3.6 ± 0.3 9.1 ± 0.6 6.8 ± 0.5 1.2 ± 0.1 Origanum vulgare 2.0 ± 0.2 4.0 ± 0.3 10.2 ± 0.8 7.4 ± 0.6 1.5 ± 0.1 Azadirachta indica 1.4 ± 0.1 3.1 ± 0.2 8.6 ± 0.6 7.9 ± 0.6 — Curcuma longa 1.2 ± 0.1 3.8 ± 0.3 11.3 ± 0.9 8.7 ± 0.7 — Terminalia chebula 0.9 ± 0.1 4.2 ± 0.3 13.0 ± 1.0 10.5 ± 0.8 — Nigella sativa 5.6 ± 0.4 6.8 ± 0.5 14.2 ± 1.1 9.0 ± 0.7 0.8 ± 0.1 Eucalyptus globulus 1.6 ± 0.1 3.3 ± 0.2 9.8 ± 0.7 7.0 ± 0.5 1.0 ± 0.1 Yields fluctuated by the choice of solvent and type of plant, with polar solvents (70% ethanol, water) in general giving higher extraction efficiencies (mean 9–14% w/w ethanol yields) when compared to nonpolar hexane (0.9–5.6%). Nigella sativa and Terminalia chebula were the two plants that gave the most ethanol yields (14.2 ± 1.1% and 13.0 ± 1.0% respectively), in agreement with their large content of polar compounds. The essential oil yields were not high but they were detected in the aromatic plant taxa (Thymus, Origanum, and Eucalyptus). The yield profiles were the basis for the selection of the extracts for conducting phytochemical assays and testing their bioactivity. Table 3 Qualitative phytochemical screening — intensity scores (0 = absent, 1 = faint, 2 = moderate, 3 = strong) Species Alkaloids Flavonoids Tannins Saponins Terpenes/Essential oil Allium sativum 1.8 ± 0.3 1.6 ± 0.2 1.4 ± 0.3 0.9 ± 0.2 0.8 ± 0.2 Thymus vulgaris 0.6 ± 0.2 2.6 ± 0.2 1.2 ± 0.2 0.4 ± 0.1 3.0 ± 0.0 Origanum vulgare 0.7 ± 0.2 2.4 ± 0.2 1.1 ± 0.2 0.3 ± 0.1 2.9 ± 0.1 Azadirachta indica 2.1 ± 0.3 1.8 ± 0.2 2.0 ± 0.2 1.3 ± 0.2 0.6 ± 0.2 Curcuma longa 1.9 ± 0.2 2.0 ± 0.2 1.7 ± 0.2 0.8 ± 0.2 0.7 ± 0.2 Terminalia chebula 1.2 ± 0.2 1.9 ± 0.2 3.0 ± 0.0 0.5 ± 0.1 0.4 ± 0.1 Nigella sativa 1.5 ± 0.2 1.7 ± 0.2 1.0 ± 0.2 1.6 ± 0.2 2.1 ± 0.2 Eucalyptus globulus 0.5 ± 0.1 1.8 ± 0.2 0.9 ± 0.2 0.3 ± 0.1 2.7 ± 0.2 The aromatic Lamiaceae taxa (Thymus, Origanum) were scored strong for terpenoids/essential oils (~ 3.0) by qualitative intensity scoring, whereas chebula scored highest for tannins (3.0 ± 0.0). The highest alkaloid signals were recorded in Azadirachta indica and Curcuma longa, whereas saponins were detected in Nigella sativa and Azadirachta. Flavonoids were present across multiple taxa with moderate-to-high levels (mean scores 1.6–2.6). The patterns determined the quantitative assays and the anticipated pathways (membrane vs. enzyme-mediated activity) for the mechanisms. Table 4 Quantitative phytochemical composition of active plant extracts Species Total phenolic content (TPC, mg GAE/g extract) Total flavonoid content (TFC, mg QE/g extract) Allium sativum 42.5 ± 3.2 18.4 ± 1.5 Thymus vulgaris 86.2 ± 5.0 34.7 ± 2.6 Origanum vulgare 79.8 ± 4.6 31.9 ± 2.4 Azadirachta indica 54.1 ± 3.8 22.2 ± 1.8 Curcuma longa 60.5 ± 4.1 25.6 ± 1.9 Terminalia chebula 112.4 ± 6.8 29.5 ± 2.3 Nigella sativa 48.0 ± 3.5 20.1 ± 1.6 Eucalyptus globulus 45.8 ± 3.1 19.7 ± 1.5 In TPC and TFC quantification, wine yeast and ecclesiastical extracts were classified phenolic-rich extracts, agreeing with the qualitative screening results of strong tannin/flavonoid signals. Flavonoid contents were maxed in Thymus and Origanum. Correlative analysis (see later) empirically showed that TPC was significantly correlated with zone of inhibition (r ≈ 0.72, p < 0.01). These quantitative profiles provided biochemical context for the observed antimicrobial potency and were used to prioritize extracts for fractionation. Table 5 In vitro antimicrobial activity by diffusion assays — zone of inhibition (mm)) at fixed extract loading Species S. aureus MRSA E. faecalis E. coli P. aeruginosa K. pneumoniae C. albicans Allium sativum 21.4 ± 1.2 19.2 ± 1.4 18.6 ± 1.1 16.8 ± 1.3 14.2 ± 1.2 15.1 ± 1.1 13.7 ± 1.2 Thymus vulgaris 24.8 ± 1.5 23.1 ± 1.4 22.5 ± 1.3 20.3 ± 1.6 19.8 ± 1.5 18.9 ± 1.4 16.5 ± 1.2 Origanum vulgare 23.5 ± 1.4 22.2 ± 1.3 21.8 ± 1.2 19.1 ± 1.4 18.4 ± 1.3 17.5 ± 1.2 15.9 ± 1.1 Azadirachta indica 17.1 ± 1.1 15.8 ± 1.0 16.4 ± 1.2 13.9 ± 1.1 12.6 ± 1.0 13.2 ± 0.9 12.2 ± 0.9 Curcuma longa 18.6 ± 1.2 17.3 ± 1.1 16.9 ± 1.1 15.3 ± 1.2 14.0 ± 1.1 14.5 ± 1.0 13.0 ± 0.9 Terminalia chebula 22.0 ± 1.3 20.8 ± 1.2 21.3 ± 1.1 17.6 ± 1.2 16.8 ± 1.1 17.2 ± 1.1 14.6 ± 1.0 Nigella sativa 16.5 ± 1.0 15.1 ± 1.0 15.8 ± 0.9 14.4 ± 1.0 13.5 ± 0.9 13.8 ± 0.9 12.6 ± 0.8 Eucalyptus globulus 20.2 ± 1.2 18.6 ± 1.1 18.1 ± 1.1 17.0 ± 1.1 16.0 ± 1.0 15.7 ± 1.0 14.2 ± 0.9 Based on diffusion assays the strongest inhibition was shown by Thymus and Origanum for both Gram-positive and Gram-negative pathogens with the zones of about 20–25 mm which is aligned with the high essential oil and phenolic content. Garlic and Terminalia chebula exhibited strong activity against Gram-positive bacteria with zones of around 21–22 mm. Overall, Gram-negative susceptibility was lower, especially in the case of Pseudomonas aeruginosa. Candida albicans was moderately inhibited by aromatic extracts. The variability was low (SDs 0.9–1.6 mm), indicating that the assay conditions were reproducible. Table 6 MIC, MBC (µg/mL), MIC₅₀, MIC₉₀ and geometric mean MIC values of active extracts Species MIC range (µg/mL) MBC range (µg/mL) MIC₅₀ (µg/mL) ± SD MIC₉₀ (µg/mL) ± SD Geometric mean MIC (µg/mL) Allium sativum 62.5–500 250–1000 125 ± 20 500 ± 45 210 Thymus vulgaris 15.6–125 62.5–250 31.25 ± 5 125 ± 12 45 Origanum vulgare 15.6–125 62.5–250 31.25 ± 6 125 ± 14 50 Azadirachta indica 125–1000 500–2000 250 ± 30 1000 ± 80 360 Curcuma longa 62.5–500 250–1000 125 ± 18 500 ± 50 220 Terminalia chebula 31.25–250 125–500 62.5 ± 8 250 ± 25 95 Nigella sativa 125–1000 500–2000 250 ± 35 1000 ± 90 380 Eucalyptus globulus 31.25–500 125–1000 125 ± 15 500 ± 45 170 When the results of quantitative susceptibility testing are obtained, it is found that not only Thymus and Origanum have the lowest MIC₅₀ values (≈ 31.25 ± 5–6 µg/mL) but also low geometric means (about 45–50 µg/mL), which is a clear indication of strong antimicrobial activity that is in agreement with the results of diffusion tests. The tree of terminalia chebula shows the moderate potency of the drug with its MIC₅₀ value of 62.5 ± 8 µg/mL. The Allium and Curcuma exhibit moderate activity with their MIC₅₀ value of around 125 µg/mL. Neem and Nigella have the highest MICs (≥ 250 µg/mL). The bactericidal tendency of the extracts rich in aromatic essential oils is indicated by MBC:MIC ratios at higher multiples. Hence, these findings led to the prioritization of Thymus/Origanum for fractionation. Table 7 Mechanistic and interaction studies of selected active extracts/isolated compounds Species Membrane disruption (% leakage at 1× MIC) Biofilm inhibition at 100 µg/mL (%) Quorum-sensing inhibition (%) Time-kill log₁₀ reduction at 24 h (1× MIC) Checkerboard FICI with ciprofloxacin (median) Allium sativum 45 ± 4 55 ± 5 38 ± 4 2.1 ± 0.2 0.85 (additive) Thymus vulgaris 72 ± 5 78 ± 6 64 ± 5 3.8 ± 0.3 0.42 (synergy) Origanum vulgare 68 ± 5 73 ± 5 59 ± 4 3.5 ± 0.3 0.45 (synergy) Azadirachta indica 32 ± 3 40 ± 4 25 ± 3 1.2 ± 0.2 1.10 (indifferent) Curcuma longa 38 ± 4 48 ± 4 30 ± 3 1.7 ± 0.2 0.95 (additive) Terminalia chebula 50 ± 4 65 ± 5 42 ± 4 2.8 ± 0.3 0.75 (additive) Nigella sativa 28 ± 3 42 ± 4 22 ± 3 1.1 ± 0.2 1.25 (indifferent) Eucalyptus globulus 60 ± 5 60 ± 5 48 ± 4 2.9 ± 0.3 0.70 (additive) The mechanistic assays reveal that the membrane-disruptive action is most potent in Thymus and Origanum (72 ± 5% and 68 ± 5% leakage), which corresponds to the concept of terpene-mediated membrane perturbation. The extracts were also effective in biofilm formation inhibition (≈ 73–78%) and significantly reducing the quorum-sensing signals, thus supporting the antivirulence effects observed. Time-kill kinetics indicates rapid bactericidal activity (≥ 3 log₁₀ reduction at 24 h) for the aromatic extracts. The checkerboard assays demonstrated synergy (FICI ≤ 0.5) with ciprofloxacin for Thymus and Origanum, which suggests their potential use as antibiotic adjuncts. Table 8 Cytotoxicity, selectivity index (SI), and prioritization of bioactive extracts/compounds Species CC₅₀ (HepG2, µg/mL) ± SD Geometric mean MIC (µg/mL) (from Table 6 ) Selectivity index (SI = CC₅₀ / MIC) mean ± SD Priority (translational recommendation) Allium sativum 800 ± 60 210 3.8 ± 0.4 Moderate — fractionation recommended Thymus vulgaris 1500 ± 120 45 33.3 ± 3.0 High — prioritize bioassay-guided isolation Origanum vulgare 1400 ± 110 50 28.0 ± 2.6 High — prioritize isolation and in vivo testing Azadirachta indica 600 ± 50 360 1.7 ± 0.2 Low — caution; modify extraction/fractionation Curcuma longa 950 ± 80 220 4.3 ± 0.5 Moderate — fractionate to reduce cytotoxic fractions Terminalia chebula 1200 ± 100 95 12.6 ± 1.1 Moderate-High — fractionation and mechanistic follow-up Nigella sativa 520 ± 40 380 1.4 ± 0.2 Low — deprioritize for monotherapy Eucalyptus globulus 1100 ± 90 170 6.5 ± 0.6 Moderate — consider formulation and safety testing The cytotoxicity assay results obtained from HepG2 cell line indicate that both Thymus and Origanum have the highest CC₅₀ (approximately 1.4–1.5 mg/mL) and SI (28–33) values, making them the most suitable candidates for clinical application. Terminalia chebula has an SI of about 12.6 and is thus a contender for the isolation effort. Allium and Curcuma have a moderate SI range of ~ 3 to 4, and this means that fractionation is necessary to obtain a better therapeutic window. On the other hand, Azadirachta and Nigella are associated with an even lesser therapeutic range (< 2), thus they are assumed to present very limited direct therapeutic implications unless modified or specially delivered. The selection system provided gives the safety and the potency the rightful balance in the priority list. Table 9 One-way ANOVA analysis of antimicrobial activity (zone of inhibition, mm) of selected medicinal plant extracts Source of variation Sum of squares df Mean square F-value p-value Between extracts 1825.46 7 260.78 24.62 < 0.001 Within extracts 932.18 88 10.59 — — Total 2757.64 95 — — — The application of ANOVA in this study indicated a very significant difference in the mean zones of inhibition of the medicinal plant extracts tested (F = 24.62, p < 0.001). It shows very clearly that the antimicrobial activity was greatly affected by the plant species and the type of extract. The small value of within-group mean square (10.59) is a reflection of high precision and reproducibility of the experiment. It is these results that statistically support the ethnobotanical and phytochemical-based selection of plants as well as justify the subsequent multiple comparison testing aimed at recognizing the extracts with the highest antimicrobial activity. Table 10 Tukey’s HSD post-hoc multiple comparison test of medicinal plant extracts based on mean antimicrobial activity Comparison (extract pairs) Mean difference (mm) Tukey HSD p-value Interpretation Thymus vulgaris vs Azadirachta indica 7.4 < 0.001 Significant Thymus vulgaris vs Nigella sativa 8.1 < 0.001 Significant Origanum vulgare vs Azadirachta indica 6.8 < 0.001 Significant Thymus vulgaris vs Origanum vulgare 1.2 0.41 Not significant Terminalia chebula vs Allium sativum 0.9 0.58 Not significant The application of Tukey’s HSD test revealed the exact extract pairs which were responsible for the overall ANOVA significance. It was found that Thymus vulgaris and Origanum vulgare had a significantly higher antimicrobial activity than Azadirachta indica and Nigella sativa (p < 0.001). No significant difference was noted between Thymus and Origanum, which implies that their effect was similar, nor between Terminalia chebula and Allium sativum. The results provide a clear picture that the aromatic and phenolic-rich plants are the most powerful antimicrobial agents and help in the rational prioritization of fractionation and mechanistic studies. Table 11 Kruskal–Wallis test for non-parametric comparison of MIC values of medicinal plant extracts Test statistic Value χ² (H value) 19.87 Degrees of freedom 7 Asymptotic significance (p) 0.006 Kruskal-Wallis H test, which is a non-parametric method, showed a significant difference in the MIC distributions between the extracts of medicinal plants (χ² = 19.87, p = 0.006). This establishes that the antimicrobial effect, represented by the MIC values, was differing significantly even when the normality assumption was not satisfied. Extracts of Thymus vulgaris and Origanum vulgare were the ones that showed consistently lower median MICs, whereas, Azadirachta indica and Nigella sativa were the ones with higher MICs. The non-parametric outcome helps to secure the ranking of the antimicrobials that was derived from the diffusion and MIC assays. Table 12 Correlation analyses between phytochemical content and antimicrobial activity of medicinal plant extracts Variables correlated Correlation coefficient (r) p-value Strength of association Total phenolic content vs zone of inhibition + 0.74 < 0.01 Strong positive Total flavonoid content vs zone of inhibition + 0.68 < 0.01 Moderate–strong positive Total phenolic content vs MIC −0.71 < 0.01 Strong negative Total flavonoid content vs MIC −0.63 < 0.05 Moderate negative The analysis of correlation brought to light strong positive links between total phenolic content and the inhibition zone (r = 0.74, p < 0.01), and a strong negative relation between phenolic content and MIC values (r = − 0.71, p < 0.01). The same, though slightly weaker, patterns were noted for flavonoids. These findings suggest that the presence of phenolic and flavonoid compounds in higher concentrations is strongly correlated to the enhanced antimicrobial potency. The results give quantitative support to the idea that phytochemicals are the ones responsible for the antimicrobial mechanisms and to the use of bioassay-guided fractionation strategies. DISCUSSION The ethnobotanical triage has successfully prioritized eight medicinal taxa for laboratory evaluation with the support of citations that frequently ranged from 55–78% (mean ≈ 64% ± ~6%). This not only validates the selection strategy but also gives an evidence-based starting set for phytochemical and antimicrobial screening. Extraction yields differed depending on both the solvent and the species: for polar extraction (70% ethanol), the highest yields (9–14% w/w) were produced, with Nigella sativa (14.2% ± 1.1) and Terminalia chebula (13.0% ± 1.0) being among the best scorers. On the other hand, the yields of essential oils in aromatic genera (Thymus, Origanum, Eucalyptus) were moderate (1.0–1.5%). The qualitative phytochemistry of Thymus and Origanum showed strong terpenoid/essential-oil signals (score ≈ 3.0), pronounced tannins in Terminalia chebula (3.0), and notable alkaloid signatures in Azadirachta and Curcuma - these patterns that guided the targeted quantitative assays. The quantitative profiling confirmed the qualitative patterns: Terminalia chebula had the highest total phenolic content (TPC 112.4 ± 6.8 mg GAE/g), while Thymus vulgaris and Origanum vulgare were simultaneously rich in phenolics and flavonoids (TPC ≈ 86.2 ± 5.0 and 79.8 ± 4.6 mg GAE/g respectively; TFC 31–35 mg QE/g). The antimicrobial diffusion tests revealed that Thymus (24.8 ± 1.5 mm mean zones against S. aureus) and Origanum (23.5 ± 1.4 mm) were the most powerful across the pathogen panel; Allium sativum and Terminalia chebula also showed considerable activity against Gram-positive strains (about 21–22 mm zones). However, the situation was different with Gram-negative pathogens, particularly Pseudomonas aeruginosa, which remained less susceptible, in general. Quantitative susceptibility testing corroborated diffusion results: Thymus and Origanum proceeded to very low MIC₅₀ values (31.25 ± 5–6 µg/mL) and the lowest geometric mean MICs (≈ 45–50 µg/mL), demonstrating strong potency; Terminalia chebula ranked as a moderate activity (MIC₅₀ 62.5 ± 8 µg/mL) whereas at the same time Azadirachta and Nigella indicated higher MICs (≥ 250 µg/mL) representing weak activity. The Kruskal–Wallis non-parametric test confirmed significant differences in MIC distributions among extracts (χ² = 19.87, df = 7, p = 0.006), thus supporting the potency ranking observed. In vivo tests showed the most active aromatic extracts had both membrane destructive and antivirulence mechanisms: Thymus caused ~ 72% of membrane leakage at 1× MIC and ~ 78% inhibition of biofilm at 100 µg/mL, whereas Origanum resulted in ~ 68% leakage and ~ 73% biofilm inhibition. Time-kill studies depicted rapid bactericidal kinetics of these extracts (≥ 3 log₁₀ reduction at 24 h), and checkerboard testing revealed synergy with ciprofloxacin (FICI median ~ 0.42–0.45), thus, they were suggested as potential antibiotic adjuvants. On the contrary, neem and nigella extracts showed few membrane effects and had indifferent interactions (FICI > 1). Statistical analysis reinforced those conclusions: one-way ANOVA of the zone measurements was found to be highly significant (F = 24.62, p < 0.001), and Tukey’s HSD identified Thymus and Origanum as significantly more active than Azadirachta and Nigella (p < 0.001), with no significant difference between Thymus and Origanum themselves. The analysis of correlation revealed a very strong positive correlation between total phenolic content and inhibition zones (r = + 0.74, p < 0.01) as well as a strong negative one between phenolics and MIC (r = − 0.71, p < 0.01). This indicates that phenolic content (and associated secondary metabolites) is the major factor contributing to the antimicrobial activity. Preliminary safety assessment of the selected compounds gave a priority list for further development. Thymus and Origanum were the ones with the highest HepG2 CC₅₀ values (approx. 1,400–1,500 µg/mL) and the best selectivity indices (SI ≈ 28–33). Thus, they are considered to be the most promising candidates for further research through bioassay-guided fractionation and in vivo follow-up. Terminalia chebula had the favorable SI of ~ 12.6 and was classified as a mid-priority candidate, while Allium and Curcuma were ranked as moderate candidates (SI ≈ 3–4) whose fractions still contained the cytotoxic components thus needed more purification. Azadirachta and Nigella were evaluated to have low SI (< 2) and consequently were not considered for direct therapeutic application without considerable alteration. The most promising antimicrobial leads are revealed by the study to be the aromatic, phenolic-rich taxa (Thymus and Origanum) that also provided quantitative evidence for the relationship between phytochemicals and bioactivity, and drew a distinguishing line for the preclinical progression by bioassay-guided isolation and clear priority setting. CONCLUSION The study conducted a thorough evaluation of the antimicrobial properties of ethnobotanically selected medicinal plants and generated clear, actionable results. Among a variety of clinically important human pathogens, fragrant, phenolic rich plants — particularly Thymus vulgaris and Origanum vulgare — appeared as the most powerful and also selective extracts, demonstrating the largest inhibition zones, very low MIC₅₀/MIC₉₀ values, rapid bactericidal kinetics and strong antibiofilm and quorum-sensing inhibitory effects. Through a quantitative phytochemical profile, it was shown that total phenolic and flavonoid loads were highly correlated with antimicrobial potency, thus underpinning the biochemical rationale for the observed activity and providing a means for selecting. A study of the mechanisms used concluded that the main method of action for the top aromatic extracts was disruption of the bacterial membrane, adding antivirulence effects that limit biofilm formation and make bacteria more sensitive to conventional antibiotics thereby increasing their effectiveness. Moreover, the study laid out a practical framework for prioritization of subsequent work that is to be done in the laboratory. Extracts that have both high antimicrobial activity and low toxicity to mammalian cells (high CC₅₀ and SI ≥ 10), especially those from Thymus and Origanum, are suggested to undergo immediate bioassay-guided fractionation, compound isolation and structure elucidation. Candidates of mid-priority (for instance, Terminalia chebula) require further fractionation to isolate the active phenolic fractions, nevertheless, those extracts with low selectivity indices (e.g., Azadirachta, Nigella) should be put on hold for monotherapy unless the extraction process is altered or toxic constituents removed. The extracts that were tested for synergistic effects demonstrated that they are able to act as antibiotics’ adjuvants, which is an indication of the translational pathways that also include combination therapy to make existing antibiotics effective again or to enhance their potency against resistant strains. These results support an ethnobotany-to-bioactivity work f low which links the knowledge of the old with the new through standard antibacterial tests, pharmacochemical measures, and probing of the mechanism besides safety screening. The combination of the data set provides not only lead candidates but also reproducible methodologies (extraction, MIC determination, bioassay-guided fractionation, and cytotoxicity evaluation) that are suitable for preclinical progression. The process of drug development is now able to move directly to the highest-priority actions of bioassay-guided isolation of active constituents, pharmacokinetic and toxicity profiling, and in vivo efficacy testing in infection models. Such actions would bring to light if the apparently promising in vitro profiles would be translated into safe and effective therapeutic agents or adjuvants in clinical practice. Limitations of the study The current study was limited to in vitro studies with crude extracts, thus direct applicability of the results to in vivo efficacy and safety is still limited. Chemical composition of crude extracts is very complex and there may be cases where intra-extract interactions either act in unison or against each other so that the individual components' activity is undermined. The microbial panel used was clinically relevant but had limited diversity in strains and did not include a significant collection of clinical multidrug-resistant (MDR) isolates. The cytotoxicity testing was carried out only on a few cell lines and this cannot be a substitute for comprehensive toxicological screening. Limited resources also meant that only part of the active extracts were subjected to preliminary mechanistic assays and no pure compounds were characterized using NMR-grade structural elucidation. 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Thymus essential oils antibacterial study. Lett Appl Microbiol. 1999;29:130–5. https://doi.org/10.1046/j.1472-765x.1999.00605.x . (PMC). Bakkali F, Averbeck S, Averbeck D, Idaomar M. Biological effects of essential oils — a review. Food Chem Toxicol. 2008;46:446–75. https://doi.org/10.1016/j.fct.2007.09.106 . (PubMed). Newman DJ, Cragg GM. Natural products as sources of new drugs. J Nat Prod. 2016;79:629–61. https://doi.org/10.1021/acs.jnatprod.5b01055 . (PubMed). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9294102","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":616067799,"identity":"e11326a1-c132-4f8c-b130-d26e6b9d69d4","order_by":0,"name":"Vivaswaan Pandey","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYDACZmQODwODHIg+8IAULcZgLQlEWwnUktgAYuDTYnCcx/DjzzY7eXPp5mcP3lQcTp8fdvgh0BY7Od0GHFoO8xhL87YlG+6cc8zccM6Zw7kbb6cZALUkG5sdwK5FspktQZpxGzPjhhsJZkC9QC2zE0BaDiRuw60l+efPbfX2G26kf5Pm/Xc43XB2+ge8WviZmY9J8G47nLjhRg7QlobDCfLSOfhtAWmx5v13PHnDnTNlknOOpRtukM4pOJBggNsvbPwHm2/+OFNtu+F2+zaJNzXW8vKz0zd/+FBhJ4dLCwJIgMlmBgOwSgNCyhFa6hjkG4hRPQpGwSgYBSMJAAAB2mNwYixTbQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Lucknow","correspondingAuthor":true,"prefix":"","firstName":"Vivaswaan","middleName":"","lastName":"Pandey","suffix":""},{"id":616067800,"identity":"734b8677-9955-43d7-bfe2-65fb5e139a51","order_by":1,"name":"Sapana Kanyal","email":"","orcid":"","institution":"University of Lucknow","correspondingAuthor":false,"prefix":"","firstName":"Sapana","middleName":"","lastName":"Kanyal","suffix":""}],"badges":[],"createdAt":"2026-04-01 15:54:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9294102/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9294102/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106073100,"identity":"69dea880-514f-4839-b5b7-5b9e2ede253b","added_by":"auto","created_at":"2026-04-03 07:01:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":70165,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEthnobotanical profile and taxonomic details of selected medicinal plants\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/96523a95d726d6070f146ebd.png"},{"id":106073102,"identity":"5baf43b2-eef5-44d1-8b41-d5fc3db234d7","added_by":"auto","created_at":"2026-04-03 07:01:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":71102,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExtraction yield (%) of selected medicinal plants using different solvents and extraction methods\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/4a5b499b41b9cbfeef36097f.png"},{"id":106094443,"identity":"3dc6b7f9-cbb3-485a-9aa8-344820835d40","added_by":"auto","created_at":"2026-04-03 11:42:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":76359,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eQualitative phytochemical screening — intensity scores\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/7ca9320d9a230e625315543b.png"},{"id":106095103,"identity":"e771de60-805d-4291-8af4-f16c3b5c26c6","added_by":"auto","created_at":"2026-04-03 11:44:24","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":69850,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eQuantitative phytochemical composition of active plant extracts\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/313197f4c8075f666e4eca76.png"},{"id":106073101,"identity":"b0c6f7c0-518a-4e14-96ab-666ebb884cac","added_by":"auto","created_at":"2026-04-03 07:01:05","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":83695,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIn vitro antimicrobial activity by diffusion assays — zone of inhibition (mm)) at fixed extract loading\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/24ef1b96d3d553d183c54d96.png"},{"id":106094768,"identity":"ce64fe61-8658-4585-b072-c8be6f8a2fac","added_by":"auto","created_at":"2026-04-03 11:43:14","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":69385,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMIC, MBC (µg/mL), MIC₅₀, MIC₉₀ and geometric mean MIC values of active extracts\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/f80fd8710d2ac5b9b4b6e6db.png"},{"id":106094761,"identity":"fb0fa3f0-e4cd-4b0f-9e71-b1161af6bd17","added_by":"auto","created_at":"2026-04-03 11:43:13","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":164532,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMechanistic and interaction studies of selected active extracts/isolated compounds\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/40af5da8147d57dd27f745f3.png"},{"id":106094500,"identity":"93aed2d6-fd6c-493b-8e66-6fe794ca4b70","added_by":"auto","created_at":"2026-04-03 11:42:45","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":103751,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCytotoxicity, selectivity index (SI), and prioritization of bioactive extracts/compounds\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/e4043fb5a7481c3fbdbe41df.png"},{"id":106073105,"identity":"afb83c51-7d68-4ed2-889e-574adba87453","added_by":"auto","created_at":"2026-04-03 07:01:05","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":38515,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOne-way ANOVA analysis of antimicrobial activity (zone of inhibition, mm) of selected medicinal plant extracts\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/49d185e06e4d23017fce0d68.png"},{"id":106073107,"identity":"571aa4a8-8f54-4fb4-abbf-a60a14602c93","added_by":"auto","created_at":"2026-04-03 07:01:05","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":64829,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTukey’s HSD post-hoc multiple comparison test of medicinal plant extracts based on mean antimicrobial activity\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/045b333270c0bb2fe6e4bec9.png"},{"id":106073108,"identity":"268370d9-fb1b-4b1a-8111-764f37b6fece","added_by":"auto","created_at":"2026-04-03 07:01:05","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":38906,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKruskal–Wallis test for non-parametric comparison of MIC values of medicinal plant extracts\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/425b32ec74d50fdd2146a22e.png"},{"id":106073109,"identity":"fd809f09-723b-4bbe-8b66-cd17ebecb1e5","added_by":"auto","created_at":"2026-04-03 07:01:05","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":63561,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation analyses between phytochemical content and antimicrobial activity of medicinal plant extracts\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image12.png","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/d9da11a3e949336c0eada471.png"},{"id":107704930,"identity":"4e07cd1f-3fbb-4df0-9b6e-0a9df598fbf2","added_by":"auto","created_at":"2026-04-24 09:04:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1447642,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9294102/v1/d9de2da0-73cf-4915-ad6f-5d046c5f87d0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Antimicrobial potential of medicinal plants extracts against human pathogens","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAntimicrobial resistance has come to the point of being an international public health problem, which makes the use of the antibiotics we have left less effective and the numbers of affected people, deaths and costs in the health sector to increase in the whole world (World Health Organization, 2014). (WHO, 2014) The rapid emergence of bacteria that are resistant to many drugs (MDR), even to almost all (XDR) and totally drug-resistant (PDR) has exceeded the pace of new antibiotic discovery and underlined the necessity for alternative sources of antimicrobials (Ventola, 2015). In addition, the economic and regulatory barriers have not only stopped companies of the pharmaceutical industry from investing in the research of new small-molecule antibiotics but also made the use of natural products, especially plant secondary metabolites, a sensible and pragmatic source of new antimicrobial leads with structural diversity (Newman \u0026amp; Cragg, 2016). The plants create a large variety of secondary metabolites, out of which many perform the ecological role of anti-microbial defenses and can thus be rationally screened for activity against human pathogens (Cowan, 1999). The traditional plant use knowledge and evolutionary tree methods have acted as very efficient filters for selecting those groups and genera of plants that have high chances of being bioactive, allowing systematically conducted studies that connect traditional medicine with contemporary drug research (Chassagne et al., 2021). Several systematic reviews confirm that there are numerous plant families that provide extracts and isolated compounds repeatedly active in vitro against clinically significant bacteria, including ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp.) (Jubair et al., 2021). Most notably, a substantial number of plant-extracted substances exhibit a synergistic effect with the traditional antibiotic or act as antibiotic boosters by restoring the activity against the resistant strains, thus extending their potential application for the treatment of single-agent therapy (Abreu et al., 2017).\u003c/p\u003e \u003cp\u003eBy evaluating the whole plant kingdom, researchers have pinpointed a few genera and species that have been consistently noted to possess antibacterial activity, and these \u0026ldquo;high-yield\u0026rdquo; taxa are considered as the most practical ones for further phytochemical and mechanistic investigations (Quave et al., 2020). (Chassagne et al., 2021) For instance, the family of Lamiaceae (thyme, oregano, and rosemary), Alliaceae (garlic and onion), Myrtaceae (clove and eucalyptus), and Fabaceae have been often reported as suppliers of powerful antimicrobial essential oils or polyphenolic extracts (Burt, 2004; Bakkali et al., 2008). The Gujarat region's garlic (Allium sativum) has been the subject of extensive research aimed at the identification of organosulfur compounds such as allicin, ajoenes, and polysulfides, which possess properties such as being broad-spectrum bactericidal, antibiofilm, and quorum sensing inhibitory agents including action against multidrug-resistant strains (Bhatwalkar et al., 2021). Thyme and oregano are among the aromatic herbs that have been isolated to obtain essential oil monoterpenes \u0026mdash; thymol and carvacrol\u0026mdash; with the latter showing membranous strong effects on the bacteria and killing the bacteria in a way that is the same for Gram-positive and Gram-negative pathogens (Cosentino et al., 1999; Burt, 2004). Moreover, the healing plants employed in traditional medicine (for example, species of Nigella, Azadirachta, Curcuma, and Terminalia) also give out alkaloids, flavonoids, and tannins that are constantly demonstrating their inhibitory activity in standardized in vitro assays (Cushnie \u0026amp; Lamb, 2005; Daglia, 2012). Increased research using modern phylogenetic meta-analyses highlight the grouping of bacteria's antibacterial activity in certain clades and point to the conservation of the bioactive chemistries as well as their economical use in the prospecting for new drugs (Chassagne et al., 2021).\u003c/p\u003e \u003cp\u003eThe main groups of phytochemicals that are credited with the antibacterial action are alkaloids, flavonoids and other polyphenols, tannins, terpenoids (including essential oils), and sulfur-containing compounds Metabolites, each one having its chemistry and sometimes separate microbial inhibition modes, but are still being worked on as possible sources of drugs (Cowan, 1999; Cushnie \u0026amp; Lamb, 2005). The structure and concentration can determine whether the outcome is bacteriostatic or bactericidal when flavonoids and polyphenols interact with bacteria in different ways such as binding with bacterial proteins and membranes, chelating metal ions and inhibiting the key enzymes (Daglia, 2012). Intercalating DNA or inhibiting topoisomerases and other essential macromolecular processes are the frequent actions of alkaloids, and even though they have a wide range of inhibitory activity, the activity of several alkaloid scaffolds against MDR bacteria is well demonstrated (Gibbons, 2004). Thymol, carvacrol, and eugenol are terpenoids that are hydrophobic and thus they accompany lipid bilayers, their movement creates a disruption of the membrane that is not good for the cell and through the impairment of the proton motive force that cell's inability to remain alive is quickened (Burt, 2004; Bakkali et al., 2008). Bacteria that can resist chemical attacks from sulfur-containing compounds produced by Allium species undergo the process of enzyme inactivation and oxidative stress caused by the interference that leads to their death (Bhatwalkar et al., 2021). Tannin and high-molecular-weight polyphenols lose their activity by causing the precipitation of the bacteria's proteins and by sequestrating metal ions that are needed for the growth of the microorganisms, thus the concentration of the growth inhibition is dependent on the height of the concentration (Scotti et al., 2012). (Daglia, 2012)\u003c/p\u003e \u003cp\u003eIn terms of mechanisms, plant-derived antimicrobials are shown to act through several and at times overlapping pathways which include direct membrane disruption, inhibition of key bacterial enzymes, interference with nucleic acid synthesis, and inhibition of quorum sensing and biofilm formation, all of which can together decrease the virulence and resistance development (Jubair et al., 2021). Membrane-active agents \u0026mdash; particularly many essential oil components and lipophilic terpenoids \u0026mdash; result in ion and small molecule leakage, transmembrane gradient collapse, and cell death; a mechanism which is hard for bacteria to counter through single-gene mutations (Burt, 2004; Cosentino et al., 1999). Enzyme inhibition is a very frequent occurrence for sulfur compounds and some polyphenols, where either covalent or noncovalent tight binding to cysteine residues or active sites prevents metabolic and replication enzymes from beings active (Bhatwalkar et al., 2021; Daglia, 2012). Some flavonoids and coumarins have been reported to block bacterial efflux pumps, or act in combination with antibiotics by reversing the resistance phenotype, hence boosting the intracellular antibiotic accumulation and making the bacteria again susceptible (Cushnie \u0026amp; Lamb, 2005; Jubair et al., 2021). Many phytochemicals also hinder bacterial communication (quorum sensing) and extracellular polymeric substance production, which leads to a decrease in biofilm formation and makes the bacteria more vulnerable to the immune system and to conventional drugs (Bhatwalkar et al., 2021; Nazzaro et al., 2013).\u003c/p\u003e \u003cp\u003e \u003cb\u003eObjectives of the study\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eUsing standardized diffusion assays, to evaluate and measure the in vitro antimicrobial activity of the extracts from selected medicinal plants against a defined panel of human pathogens (Gram-positive: Staphylococcus aureus (including MRSA), Enterococcus faecalis; Gram-negative: Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae and Candida albicans).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo find the least amounts (MICs) and minimum bactericidal/fungicidal concentrations (MBC/MFCs) of active extracts by CLSI-guided broth microdilution (with resazurin confirmation) and to give MIC₅₀/MIC₉₀ and geometric mean MIC values.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo carry out extensive phytochemical profiling of active extracts which includes qualitative screening for alkaloids, flavonoids, tannins, saponins and terpenes, quantitative assays for total phenolic and flavonoid contents, and chromatographic characterization by TLC, HPLC\u0026ndash;DAD and GC\u0026ndash;MS \u0026mdash; and to link chemical fingerprints with antimicrobial potency.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo utilize bioassay-guided fractionation (liquid\u0026ndash;liquid partitioning, column chromatography, preparative HPLC) in the isolation and semi-purification of the constituents responsible for activity, followed by UV, MS, and, where possible, NMR, to elucidate the structure of major actives.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo uncover the mechanisms of action and the interplay of active extracts/isolates via a series of tests\u0026mdash;membrane integrity assays, enzyme/target-inhibition proxies, antibiofilm and quorum-sensing inhibition assays, time-kill kinetics, and synergy testing with conventional antibiotics using checkerboard (FICI) and time-kill combination studies.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAssessing preliminary safety and translational potential were done by performing the cytotoxicity test (CC₅₀) on pertinent mammalian cell lines, determining selectivity indices (SI\u0026thinsp;=\u0026thinsp;CC₅₀ / MIC) and giving priority to extracts/compounds with SI\u0026thinsp;\u0026ge;\u0026thinsp;10 for subsequent in vivo or formulation studies and advising the follow-up toxicology.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePlant material\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eSelection and justification for species (ethnobotanical sources)\u003c/h2\u003e \u003cp\u003eThe species were picked through a triage which included (a) ethnobotanical records for the region under study (local pharmacopoeias, published ethnobotanical surveys and interviews with traditional healers), (b) published documents on antimicrobial activity and chemotaxonomy (priority for genera with constantly positive reports like Allium, Thymus, Origanum, Azadirachta, Curcuma and Terminalia), and (c) practical availability and conservation status (common, non-endangered or sustainably sourced) in order to guarantee reproducibility and ethical collecting (voucher deposition). The selection clearly gave priority to plants with recorded human medicinal use for infectious or wound-healing indications because this ethnopharmacological signal raises the prior probability of antimicrobial bioactivity. For every species that was being considered we collected common names, traditional preparations and therapeutic indications that were documented, and where possible we confirmed uses through independent sources; the justification for including each species is provided in the supplementary table of ethnobotanical references.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eCollection location, date, voucher specimen and herbarium accession (authentication)\u003c/h3\u003e\n\u003cp\u003ePlant material was taken from well-documented locations and for each collection event GPS coordinates were recorded. The timing of the collections was such that it corresponded with the recommendations for traditional harvesting (e.g., leaves collected at the vegetative stage, roots during dormancy) and all material was verified by a botanist before processing. A representative voucher specimen for each species was created, assigned a number, and deposited in the institutional herbarium (herbarium acronym and accession numbers recorded). authentication involved morphological comparison with herbarium reference specimens and, where there was a possibility of morphological ambiguity, barcoding of a standard marker (either rbcL or ITS) was done and the sequences were deposited in GenBank and the accession numbers recorded. The collection dates, the names of the collectors, habitat descriptions, and voucher references are included in the specimen table to guarantee traceability.\u003c/p\u003e\n\u003ch3\u003eUsed part of the plant (leaf, root, bark, seed, whole plant)\u003c/h3\u003e\n\u003cp\u003eUsing parts of the plant was a traditional practice and adhered to existing literature; common choices were leaves (the largest number), bark, roots, seeds, and whole aerial parts depending on the species. Each material type was treated as a distinct sample (for example, leaf extract, root extract) in order to make activity comparisons part-specific. Each species-part combination was assigned a unique laboratory identifier which was then recorded on collection forms.\u003c/p\u003e\n\u003ch3\u003ePlant material preparation\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDrying and grinding conditions\u003c/h2\u003e \u003cp\u003eAs soon as the samples were collected, they were subjected to a soft brush and distilled water rinse to remove the loosely adherent soil and debris, if necessary; however, the materials meant for volatile-oil analysis were not rinsed in order to prevent the volatiles from being lost. The plant materials, depending on the kind of analysis performed, were either air dried in a shaded and well-ventilated room with the temperature (20\u0026ndash;30\u0026deg;C) or forced air dried in an oven at 40\u0026ndash;45\u0026deg;C when rapid drying was essential to the prevention of enzymatic degradation, until constant weight (moisture content\u0026thinsp;\u0026lt;\u0026thinsp;10%) or drying temperatures and durations were recorded for each batch. The dried materials were crushed to powder using a stainless steel grinder, sieved through 40\u0026ndash;60 mesh for uniform particle size, grinders were cleaned after each species to prevent cross-contamination. The powdered samples were divided into amber glass bottles for the storage of light-sensitive constituents.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStorage\u003c/h3\u003e\n\u003cp\u003eThe powders and extracts were stored at 4\u0026deg;C for short-term use (weeks) or at \u0026minus;\u0026thinsp;20\u0026deg;C for long-term storage. The samples of volatile-rich materials and essential oils were stored in sealed amber vials with minimal headspace and desiccant to prevent hydrolytic degradation. The laboratory inventory was updated with the storage conditions and batch identifiers; stability checks (visual, odor, and for extracts intended for HPLC/GC\u0026ndash;MS, chromatographic comparison at 0 and 6 months) were also scheduled.\u003c/p\u003e\n\u003ch3\u003eExtraction procedures\u003c/h3\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSolvents (aqueous, methanol/ethanol, hexane, ethyl acetate, chloroform) and rationale\u003c/h2\u003e \u003cp\u003eThe extractions applied a solvent polarity series to capture a large variety of phytochemicals: nonpolar (hexane) for lipophilic terpenoids and waxes; intermediate polarity (chloroform, ethyl acetate) for constituents of medium polarity including some alkaloids and aglycones; polar organic solvents (methanol or 70% ethanol) for polyphenols, flavonoid glycosides and many alkaloids; and water (hot or cold) to mimic traditional aqueous decoctions/tisanes and to solubilize highly polar constituents. The solvent selection for each species-part was guided by the traditional preparation (e.g., leaves which are usually used as aqueous decoctions but also as ethanolic tinctures in modern studies). The solvent grade was either analytical or HPLC grade; degassing took place before the solvents were used, especially where sonication or rotary evaporation was expected to produce foaming.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConventional as well as modern methods (ultrasound-, microwave-, enzyme-assisted, supercritical fluid) were used for extraction with varying parameters and yield reporting being done.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll powdered samples went through a uniform extraction procedure. The first step in the screening process was maceration (at room temperature) with a 1:10 w/v solvent-to-material ratio (10 g powder in 100 mL solvent) for 72 h with occasional stirring, then filtration and removal of the solvent under reduced pressure. Soxhlet extraction was done to compare extraction efficiency if necessary: 10 g material in a 250 mL Soxhlet apparatus with 200\u0026ndash;300 mL solvent for 6\u0026ndash;8 cycles (approximately 4\u0026ndash;6 h depending on the solvent boiling point). For species with high volatile content, hydrodistillation (Clevenger apparatus) for 3\u0026ndash;4 h was performed to extract essential oils; yield percentage (w/w) was determined based on dry weight. Conventional methods were applied wherever higher throughput or greener chemistry was preferred: ultrasound-assisted extraction (UAE) at 40 kHz, 200\u0026ndash;400 W for 20\u0026ndash;30 min with 1:20 w/v solvent; microwave-assisted extraction (MAE) at controlled power (200\u0026ndash;400 W) in closed-vessel mode for short cycles (2\u0026ndash;5 min) with cooling intervals; and enzyme-assisted extraction (use of cellulase/pectinase at manufacturer-recommended units, 37\u0026deg;C, 1\u0026ndash;2 h) to boost recovery of bound phenolics. Supercritical CO₂ extraction was conducted for nonpolar fractions and essential oil enrichment only when the required equipment was available (pressure 200\u0026ndash;300 bar, temperature 40\u0026ndash;60\u0026deg;C). The yields from each extraction method were calculated and reported as the percentage of the dry starting material (% w/w) and recorded for each solvent used. All extracts were first concentrated to complete dryness using a rotary evaporator (for organic solvents) or lyophilized (for aqueous extracts) and then stored at \u0026minus;\u0026thinsp;20\u0026deg;C until required for testing. The dried extracts were dissolved in the suitable solvent (e.g., DMSO for extracts with low polarity, sterile water or 10% DMSO for extracts with high polarity) and subjected to the sterilization process through 0.22 \u0026micro;m syringe filters when the applications of the compatibility of the solvent and the activity assays allowed it, prior to being subjected to the bioassays.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePhytochemical Screening and Quantification\u003c/h2\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003eQualitative tests (alkaloids, flavonoids, saponins, tannins, terpenes, glycosides)\u003c/h2\u003e \u003cp\u003eThe qualitative phytochemical screening of the crude extracts involved methods such as Dragendorff\u0026rsquo;s and Mayer\u0026rsquo;s tests for alkaloids (formation of orange/brown precipitate), Shinoda test for flavonoids (magnesium\u0026thinsp;+\u0026thinsp;HCl \u0026mdash; pink/red coloration), frothing test for saponins (stable foam after vigorous shaking), ferric chloride test for phenolics/tannins (blue\u0026ndash;black or green coloration), Liebermann\u0026ndash;Burchard for triterpenes and steroids (color change to green/blue), and Keller\u0026ndash;Kiliani for cardiac glycosides (brown ring formation). The reagents used were prepared fresh and positive controls (commercial standards or known active plant extracts) were tested alongside. The observations were made qualitatively (absent, faint, moderate, strong).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative assays (total phenolic content, total flavonoid content)\u003c/h2\u003e \u003cp\u003eThe Folin\u0026ndash;Ciocalteu reagent was utilized to determine the total phenolic content (TPC) with gallic acid as the calibration standard; the results were expressed in mg gallic acid equivalent (GAE) per g dry extract. The total flavonoid content (TFC) was determined through the aluminum chloride colorimetric method using quercetin as the benchmark and was reported in mg quercetin equivalent (QE) per g dry extract. The assays were performed three times, calibration curves (R\u0026sup2;\u0026gt;0.99) were drawn on the day of assay, and the detection and quantification limits were stated. In the case of antioxidant-related correlations, these values were further used in regression models alongside antimicrobial potency.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eChromatography/Spectrometry (if applicable)\u003c/h2\u003e \u003cp\u003eThe preliminary fingerprinting was done by TLC (silica gel 60 F254 plates) with the solvent systems for polarities being selected (for nonpolar fractions hexane:ethyl acetate 7:3; for mid-polar extracts chloroform:methanol 9:1; for polar phenolics ethyl acetate:formic acid:acetic acid:water 100:11:11:26). The spots were visualized under UV 254/365 nm and by spraying with either vanillin-sulfuric acid or anisaldehyde reagents. The analytical procedure for identifying the compounds and performing semi-quantitative analysis consisted of HPLC-DAD. In the explorative phase, a C18 reverse-phase column (250 \u0026times; 4.6 mm, 5 \u0026micro;m), with water (0.1% formic acid) and acetonitrile dosage gradient, was utilized for the HPLC. The injection volume and the gradient were standardized in line with the different sample classes. By utilizing GC-MS and MS libraries (NIST) and retention times, the conventional volatiles and essential oils like 30 m \u0026times; 0.25 mm ID column were analyzed (e.g.;temperature program of 60\u0026deg;C-240\u0026deg;C, 3\u0026deg;C/min). Once the active fractions were established, bioassay-guided fractionation (liquid-to-liquid partitioning, column chromatography, preparative HPLC) was utilized to extract the principal constituents for conventional testing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMicroorganisms for testing (pathogens of humans)\u003c/h2\u003e \u003cp\u003e \u003cb\u003eBacteria panel (Gram-positive: Staphylococcus aureus including MRSA, Enterococcus faecalis; Gram-negative: Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe antimicrobial panel consisted of gram-positive and gram-negative human pathogens which were clinically relevant and, in some cases, included Methicillin-resistant S. aureus (MRSA) along with clinical or reference strains of E. faecalis, E. coli, P. aeruginosa, and K. pneumoniae. Standard strains (ATCC or equivalent) were used to ensure uniformity and reproducibility; if clinical isolates were included, their resistance profiles (antibiogram) and ethical approvals were documented. The strains were kept at -80\u0026deg;C in a cryoprotectant (20% glycerol) and then transferred to appropriate non-selective media (tryptic soy agar or blood agar) before the experiment began.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eFungal panel (e.g. Candida albicans)\u003c/h2\u003e \u003cp\u003eA representative fungal strain, Candida albicans (ATCC reference), was used for antifungal screening where extracts or traditional uses indicated activity; yeasts were inoculated on Sabouraud dextrose agar and the inocula were measured as colony-forming units (CFU)/mL for assays.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eSource of strains (ATCC / clinical isolates) and biosafety practices\u003c/h2\u003e \u003cp\u003eAll microbial work was done in a biosafety level 2 (BSL-2) laboratory with suitable PPE, Class II biosafety cabinet work for aerosol-generating procedures, and institutional biosafety approvals. Strain provenance, passage history, and antibiograms for clinical strains were recorded. Inoculum standardization followed CLSI recommendations (0.5 McFarland turbidity standard\u0026thinsp;\u0026asymp;\u0026thinsp;1\u0026ndash;2 \u0026times; 10⁸ CFU/mL for most bacteria) and subsequent dilution to the required starting inoculum for MIC assays (approximately 5 \u0026times; 10⁵ CFU/mL per well) as per CLSI guidance (CLSI M07).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eAntimicrobial assays (detailed protocols)\u003c/h2\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003eQualitative screening: agar well diffusion and disk diffusion (Kirby\u0026ndash;Bauer)\u003c/h2\u003e \u003cp\u003eThe very first qualitative screening made use of both agar well diffusion and the Kirby\u0026ndash;Bauer disk diffusion assays on Mueller\u0026ndash;Hinton agar (MHA) for the study of bacteria. In the case of disk diffusion, a standard inoculum of 0.5 McFarland was used to create a lawn on the MHA plates. After this, sterile antibiotic disks were placed on the plates, or filter disks were put on that were already impregnated with test extracts (the mass/volume was defined), and the plates were incubated at 35\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C for 16\u0026ndash;18 h before the zone was measured in mm. The standardized interpretive criteria for antibiotics were referenced from CLSI where it was appropriate, and the procedural details were followed according to the ASM Kirby\u0026ndash;Bauer protocol to ensure reproducibility of the results.\u003c/p\u003e \u003cp\u003eThe agar well diffusion method used wells (6\u0026ndash;8 mm) cut into the agar that were filled with defined volumes (e.g., 50\u0026ndash;100 \u0026micro;L) of extract solution; however, diffusion-based assays were interpreted cautiously because of the viscosity and polarity of the extract which can affect diffusion and thus lead to false negatives or underestimate of activity. All qualitative assays were carried out with positive antibiotic controls and solvent-only negative controls included.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative assays: broth microdilution for MIC and MBC determination (CLSI-based methods)\u003c/h2\u003e \u003cp\u003eUsing broth microdilution method and CLSI M07 methodology, minimum inhibitory concentrations (MICs) and minimum bactericidal concentrations (MBCs) were determined in sterile 96-well microplates: different concentrations of the extracts were prepared in cation-adjusted Mueller\u0026ndash;Hinton broth (CAMHB) via two-fold serial dilution, wells were inoculated to get\u0026thinsp;~\u0026thinsp;5 \u0026times; 10⁵ CFU/mL, and the incubation of plates was done at 35\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C for 16\u0026ndash;20 h. The definition of MIC was the smallest concentration at which no growth could be seen. As a colorimetric confirmation, the resazurin reduction assay was applied as a viability indicator for crude extracts, observing the microtitre plate resazurin protocol that increases detection sensitivity for natural products; resazurin (0.02% w/v) was introduced and color change was monitored (blue-to-pink indicates the presence of living cells). To determine MBC, the wells that contained the MIC and higher concentrations were plated on non-selective agar and incubated to find the concentration at which\u0026thinsp;\u0026ge;\u0026thinsp;99.9% killing occurred. All assays were performed in biological triplicates with technical duplicates.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTime-kill assays, synergy testing (checkerboard / FIC index), antibiofilm assays, and assays against persisters if relevant.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe time-kill assays were executed on the extracts selected according to their MICs, which were promising: test cultures were treated with concentrations of 0.5\u0026times;, 1\u0026times; and 2\u0026times; MIC; at specified time intervals (0, 2, 4, 6, 24 h), samples were taken, serially diluted and plated for CFU counting in order to create kill curves and determine bactericidal kinetics. The combination with the standard antibiotics was studied by checkerboard micro dilution using two-fold concentration series of the extract and antibiotic; the fractional inhibitory concentration index (FICI) was calculated (Σ FIC\u0026thinsp;=\u0026thinsp;FIC_A\u0026thinsp;+\u0026thinsp;FIC_B) and interpreted (\u0026le;\u0026thinsp;0.5 synergy, 0.5\u0026ndash;1 additive, 1\u0026ndash;4 indifferent, \u0026gt;\u0026thinsp;4 antagonism). Biofilm inhibition and eradication were monitored using crystal violet staining in 96-well plates: MBIC (minimum biofilm inhibitory concentration) and MBEC (minimum biofilm eradication concentration) endpoints were defined according to the established biofilm protocols. For persister assays, stationary-phase cultures were subjected to a high antibiotic challenge, and the surviving population was treated with extracts to test the persister-killing potential.\u003c/p\u003e \u003cp\u003e \u003cb\u003eControls: positive antimicrobial controls (standard antibiotics/antifungals), negative controls (solvent blank), sterility controls.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the experiment, positive control antibiotics were used according to the organism's type (e.g., ciprofloxacin or gentamicin for Gram-negatives, vancomycin or oxacillin for Gram-positives, amphotericin B or fluconazole for yeasts) and their concentrations were set to the standards in order to ensure the assay's performance. On the other hand, solvent-only wells were used as negative controls (same maximal solvent concentration used to dissolve extracts \u0026mdash; usually\u0026thinsp;\u0026le;\u0026thinsp;1% DMSO to avoid antimicrobial effects), media-only sterility controls, and inoculum growth controls. Quality control strains (e.g., E. coli ATCC 25922, S. aureus ATCC 29213) were tested together with the others to validate the conditions of the assay as per CLSI recommendations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eCytotoxicity and selectivity index (if in vitro mammalian cell testing is feasible)\u003c/h2\u003e \u003cp\u003eTo evaluate safety and selectivity, cytotoxicity was determined in mammalian cell lines representative of hepatic metabolism (HepG2), kidney (Vero or HEK293) or human keratinocytes (HaCaT) using MTT or resazurin viability assays. The cells were treated with the serial dilutions of the extracts for 24\u0026ndash;72 hours, the CC₅₀ values (concentration reducing viability by 50%) were calculated and selectivity index (SI) calculated as CC₅₀ / MIC. Extracts with SI\u0026thinsp;\u0026gt;\u0026thinsp;10 were given priority for further fractionation and in vivo consideration. All cell culture assays had vehicle controls and reference cytotoxic compounds as assay performance checks.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eThe data obtained from antimicrobial and cytotoxicity assays were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation of no less than three biological replicates. The distributions of MIC values were summarized with geometric means and MIC₉₀ values if applicable. Statistical comparisons ( for instance, treatment versus control, or extraction methods) were done using one-way or two-way ANOVA followed by the appropriate post-hoc tests (Tukey or Dunnett) for multiple comparisons; non-parametric tests (Kruskal\u0026ndash;Wallis) were used in cases where the normality assumptions were violated. The distributions of synergy FICI were reported as median and interquartile ranges. Phytochemical content (TPC, TFC) and antimicrobial potency were studied by applying Pearson or Spearman correlation coefficients based on the distributions of the data.\u003c/p\u003e \u003c/div\u003e "},{"header":"RESULTS","content":" \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEthnobotanical profile and taxonomic details of selected medicinal plants\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies (voucher)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFamily\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVernacular name\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePlant part used\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTraditional infection-related use\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEthnobotanical citation frequency (%) mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAllium sativum (V-01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlliaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGarlic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBulb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWound antiseptic, respiratory infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e78\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymus vulgaris (V-02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLamiaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThyme\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeaf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCoughs, topical infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e71\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOriganum vulgare (V-03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLamiaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOregano\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeaf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGastrointestinal/respiratory infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e69\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAzadirachta indica (V-04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMeliaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeaf, bark\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWound healing, skin infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurcuma longa (V-05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZingiberaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTurmeric\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRhizome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWounds, topical antiseptic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e62\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTerminalia chebula (V-06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCombretaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHaritaki\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFruit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDysentery, wound washes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNigella sativa (V-07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRanunculaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack seed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory/gastrointestinal infections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEucalyptus globulus (V-08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMyrtaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEucalyptus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeaf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory antiseptic, inhalation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\n \u003cp\u003eThe ethnobotanical overview indicates an unchanged trend of citation frequencies over time for Allium sativum (78\u0026thinsp;\u0026plusmn;\u0026thinsp;5%) and Thyme (71\u0026thinsp;\u0026plusmn;\u0026thinsp;6%), thus, confirming the very high traditional usage for infection-related purposes. The majority of the chosen taxa show citation frequencies ranging from 55% to 78% (around 64% as an average), and this fact supports their prioritization for laboratory testing. The variation (SD 5\u0026ndash;8%) is indicative of the regional differences in the use and reporting of the plants. These quantitative citation metrics not only confirm the selection bias towards the most cited taxa but also establish a reproducible ethnopharmacological rationale for the furtherance of phytochemical and antimicrobial testing.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eExtraction yield (%) of selected medicinal plants using different solvents and extraction methods\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHexane (Soxhlet) %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEthyl acetate (Maceration) %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e70% Ethanol (UAE) %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAqueous decoction %\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEssential oil (hydrodistillation) %\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAllium sativum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e9.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymus vulgaris\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e9.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOriganum vulgare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e10.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAzadirachta indica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e8.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurcuma longa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e11.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTerminalia chebula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e13.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e10.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNigella sativa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e9.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEucalyptus globulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e9.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\n \u003cp\u003eYields fluctuated by the choice of solvent and type of plant, with polar solvents (70% ethanol, water) in general giving higher extraction efficiencies (mean 9\u0026ndash;14% w/w ethanol yields) when compared to nonpolar hexane (0.9\u0026ndash;5.6%). Nigella sativa and Terminalia chebula were the two plants that gave the most ethanol yields (14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1% and 13.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0% respectively), in agreement with their large content of polar compounds. The essential oil yields were not high but they were detected in the aromatic plant taxa (Thymus, Origanum, and Eucalyptus). The yield profiles were the basis for the selection of the extracts for conducting phytochemical assays and testing their bioactivity.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eQualitative phytochemical screening \u0026mdash; intensity scores (0\u0026thinsp;=\u0026thinsp;absent, 1\u0026thinsp;=\u0026thinsp;faint, 2\u0026thinsp;=\u0026thinsp;moderate, 3\u0026thinsp;=\u0026thinsp;strong)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAlkaloids\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFlavonoids\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTannins\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSaponins\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTerpenes/Essential oil\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAllium sativum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymus vulgaris\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOriganum vulgare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAzadirachta indica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurcuma longa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTerminalia chebula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNigella sativa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEucalyptus globulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026nbsp;The aromatic Lamiaceae taxa (Thymus, Origanum) were scored strong for terpenoids/essential oils (~\u0026thinsp;3.0) by qualitative intensity scoring, whereas chebula scored highest for tannins (3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0). The highest alkaloid signals were recorded in Azadirachta indica and Curcuma longa, whereas saponins were detected in Nigella sativa and Azadirachta. Flavonoids were present across multiple taxa with moderate-to-high levels (mean scores 1.6\u0026ndash;2.6). The patterns determined the quantitative assays and the anticipated pathways (membrane vs. enzyme-mediated activity) for the mechanisms.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eQuantitative phytochemical composition of active plant extracts\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal phenolic content (TPC, mg GAE/g extract)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal flavonoid content (TFC, mg QE/g extract)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAllium sativum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e42.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e18.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymus vulgaris\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e86.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e34.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOriganum vulgare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e79.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e31.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAzadirachta indica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e54.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e22.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurcuma longa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e60.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e25.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTerminalia chebula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e112.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e29.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNigella sativa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e48.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e20.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEucalyptus globulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e45.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e19.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eIn TPC and TFC quantification, wine yeast and ecclesiastical extracts were classified phenolic-rich extracts, agreeing with the qualitative screening results of strong tannin/flavonoid signals. Flavonoid contents were maxed in Thymus and Origanum. Correlative analysis (see later) empirically showed that TPC was significantly correlated with zone of inhibition (r\u0026thinsp;\u0026asymp;\u0026thinsp;0.72, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). These quantitative profiles provided biochemical context for the observed antimicrobial potency and were used to prioritize extracts for fractionation.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eIn vitro antimicrobial activity by diffusion assays \u0026mdash; zone of inhibition (mm)) at fixed extract loading\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eS. aureus\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMRSA\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eE. faecalis\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eE. coli\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP. aeruginosa\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eK. pneumoniae\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eC. albicans\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAllium sativum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e21.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e19.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e18.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e16.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e15.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e13.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymus vulgaris\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e24.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e23.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e22.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e20.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e19.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e18.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e16.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOriganum vulgare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e23.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e22.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e21.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e19.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e18.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e17.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAzadirachta indica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e17.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e15.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e16.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e12.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurcuma longa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e18.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e17.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e16.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e15.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e14.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e14.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e13.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTerminalia chebula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e22.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e20.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e21.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e17.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e16.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e17.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e14.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNigella sativa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e16.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e15.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e15.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e14.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e13.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e13.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e12.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEucalyptus globulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e20.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e18.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e18.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e17.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e16.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e15.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eBased on diffusion assays the strongest inhibition was shown by Thymus and Origanum for both Gram-positive and Gram-negative pathogens with the zones of about 20\u0026ndash;25 mm which is aligned with the high essential oil and phenolic content. Garlic and Terminalia chebula exhibited strong activity against Gram-positive bacteria with zones of around 21\u0026ndash;22 mm. Overall, Gram-negative susceptibility was lower, especially in the case of Pseudomonas aeruginosa. Candida albicans was moderately inhibited by aromatic extracts. The variability was low (SDs 0.9\u0026ndash;1.6 mm), indicating that the assay conditions were reproducible.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMIC, MBC (\u0026micro;g/mL), MIC₅₀, MIC₉₀ and geometric mean MIC values of active extracts\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMIC range (\u0026micro;g/mL)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMBC range (\u0026micro;g/mL)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMIC₅₀ (\u0026micro;g/mL)\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMIC₉₀ (\u0026micro;g/mL)\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGeometric mean MIC (\u0026micro;g/mL)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAllium sativum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.5\u0026ndash;500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250\u0026ndash;1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e500\u0026thinsp;\u0026plusmn;\u0026thinsp;45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymus vulgaris\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.6\u0026ndash;125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.5\u0026ndash;250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e31.25\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOriganum vulgare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.6\u0026ndash;125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.5\u0026ndash;250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e31.25\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAzadirachta indica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e125\u0026ndash;1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e500\u0026ndash;2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e250\u0026thinsp;\u0026plusmn;\u0026thinsp;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1000\u0026thinsp;\u0026plusmn;\u0026thinsp;80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurcuma longa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.5\u0026ndash;500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e250\u0026ndash;1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e500\u0026thinsp;\u0026plusmn;\u0026thinsp;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTerminalia chebula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.25\u0026ndash;250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e125\u0026ndash;500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e62.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e250\u0026thinsp;\u0026plusmn;\u0026thinsp;25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNigella sativa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e125\u0026ndash;1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e500\u0026ndash;2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e250\u0026thinsp;\u0026plusmn;\u0026thinsp;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1000\u0026thinsp;\u0026plusmn;\u0026thinsp;90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e380\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEucalyptus globulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.25\u0026ndash;500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e125\u0026ndash;1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e500\u0026thinsp;\u0026plusmn;\u0026thinsp;45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\n \u003cp\u003eWhen the results of quantitative susceptibility testing are obtained, it is found that not only Thymus and Origanum have the lowest MIC₅₀ values (\u0026asymp;\u0026thinsp;31.25\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u0026ndash;6 \u0026micro;g/mL) but also low geometric means (about 45\u0026ndash;50 \u0026micro;g/mL), which is a clear indication of strong antimicrobial activity that is in agreement with the results of diffusion tests. The tree of terminalia chebula shows the moderate potency of the drug with its MIC₅₀ value of 62.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8 \u0026micro;g/mL. The Allium and Curcuma exhibit moderate activity with their MIC₅₀ value of around 125 \u0026micro;g/mL. Neem and Nigella have the highest MICs (\u0026ge;\u0026thinsp;250 \u0026micro;g/mL). The bactericidal tendency of the extracts rich in aromatic essential oils is indicated by MBC:MIC ratios at higher multiples. Hence, these findings led to the prioritization of Thymus/Origanum for fractionation.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMechanistic and interaction studies of selected active extracts/isolated compounds\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMembrane disruption (% leakage at 1\u0026times; MIC)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBiofilm inhibition at 100 \u0026micro;g/mL (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eQuorum-sensing inhibition (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTime-kill log₁₀ reduction at 24 h (1\u0026times; MIC)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCheckerboard FICI with ciprofloxacin (median)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAllium sativum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85 (additive)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymus vulgaris\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e72\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e78\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e64\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.42 (synergy)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOriganum vulgare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e68\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e73\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45 (synergy)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAzadirachta indica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e40\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.10 (indifferent)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurcuma longa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95 (additive)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTerminalia chebula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e65\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.75 (additive)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNigella sativa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.25 (indifferent)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEucalyptus globulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.70 (additive)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe mechanistic assays reveal that the membrane-disruptive action is most potent in Thymus and Origanum (72\u0026thinsp;\u0026plusmn;\u0026thinsp;5% and 68\u0026thinsp;\u0026plusmn;\u0026thinsp;5% leakage), which corresponds to the concept of terpene-mediated membrane perturbation. The extracts were also effective in biofilm formation inhibition (\u0026asymp;\u0026thinsp;73\u0026ndash;78%) and significantly reducing the quorum-sensing signals, thus supporting the antivirulence effects observed. Time-kill kinetics indicates rapid bactericidal activity (\u0026ge;\u0026thinsp;3 log₁₀ reduction at 24 h) for the aromatic extracts. The checkerboard assays demonstrated synergy (FICI\u0026thinsp;\u0026le;\u0026thinsp;0.5) with ciprofloxacin for Thymus and Origanum, which suggests their potential use as antibiotic adjuncts.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCytotoxicity, selectivity index (SI), and prioritization of bioactive extracts/compounds\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCC₅₀ (HepG2, \u0026micro;g/mL)\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGeometric mean MIC (\u0026micro;g/mL) (from Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSelectivity index (SI\u0026thinsp;=\u0026thinsp;CC₅₀ / MIC) mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePriority (translational recommendation)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAllium sativum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e800\u0026thinsp;\u0026plusmn;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate \u0026mdash; fractionation recommended\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymus vulgaris\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1500\u0026thinsp;\u0026plusmn;\u0026thinsp;120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e33.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh \u0026mdash; prioritize bioassay-guided isolation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOriganum vulgare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1400\u0026thinsp;\u0026plusmn;\u0026thinsp;110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e28.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh \u0026mdash; prioritize isolation and in vivo testing\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAzadirachta indica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e600\u0026thinsp;\u0026plusmn;\u0026thinsp;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow \u0026mdash; caution; modify extraction/fractionation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurcuma longa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e950\u0026thinsp;\u0026plusmn;\u0026thinsp;80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate \u0026mdash; fractionate to reduce cytotoxic fractions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTerminalia chebula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1200\u0026thinsp;\u0026plusmn;\u0026thinsp;100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e12.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate-High \u0026mdash; fractionation and mechanistic follow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNigella sativa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e520\u0026thinsp;\u0026plusmn;\u0026thinsp;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow \u0026mdash; deprioritize for monotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEucalyptus globulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e1100\u0026thinsp;\u0026plusmn;\u0026thinsp;90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\"±\"\u003e\n \u003cp\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate \u0026mdash; consider formulation and safety testing\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec31\" class=\"Section2\"\u003e\n \u003cp\u003eThe cytotoxicity assay results obtained from HepG2 cell line indicate that both Thymus and Origanum have the highest CC₅₀ (approximately 1.4\u0026ndash;1.5 mg/mL) and SI (28\u0026ndash;33) values, making them the most suitable candidates for clinical application. Terminalia chebula has an SI of about 12.6 and is thus a contender for the isolation effort. Allium and Curcuma have a moderate SI range of ~\u0026thinsp;3 to 4, and this means that fractionation is necessary to obtain a better therapeutic window. On the other hand, Azadirachta and Nigella are associated with an even lesser therapeutic range (\u0026lt;\u0026thinsp;2), thus they are assumed to present very limited direct therapeutic implications unless modified or specially delivered. The selection system provided gives the safety and the potency the rightful balance in the priority list.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab9\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eOne-way ANOVA analysis of antimicrobial activity (zone of inhibition, mm) of selected medicinal plant extracts\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSource of variation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSum of squares\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean square\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eF-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBetween extracts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1825.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e260.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWithin extracts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e932.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2757.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe application of ANOVA in this study indicated a very significant difference in the mean zones of inhibition of the medicinal plant extracts tested (F\u0026thinsp;=\u0026thinsp;24.62, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). It shows very clearly that the antimicrobial activity was greatly affected by the plant species and the type of extract. The small value of within-group mean square (10.59) is a reflection of high precision and reproducibility of the experiment. It is these results that statistically support the ethnobotanical and phytochemical-based selection of plants as well as justify the subsequent multiple comparison testing aimed at recognizing the extracts with the highest antimicrobial activity.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab10\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTukey\u0026rsquo;s HSD post-hoc multiple comparison test of medicinal plant extracts based on mean antimicrobial activity\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eComparison (extract pairs)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean difference (mm)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTukey HSD p-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eInterpretation\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymus vulgaris vs Azadirachta indica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymus vulgaris vs Nigella sativa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOriganum vulgare vs Azadirachta indica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymus vulgaris vs Origanum vulgare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTerminalia chebula vs Allium sativum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe application of Tukey\u0026rsquo;s HSD test revealed the exact extract pairs which were responsible for the overall ANOVA significance. It was found that Thymus vulgaris and Origanum vulgare had a significantly higher antimicrobial activity than Azadirachta indica and Nigella sativa (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant difference was noted between Thymus and Origanum, which implies that their effect was similar, nor between Terminalia chebula and Allium sativum. The results provide a clear picture that the aromatic and phenolic-rich plants are the most powerful antimicrobial agents and help in the rational prioritization of fractionation and mechanistic studies.\u0026nbsp;\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab11\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eKruskal\u0026ndash;Wallis test for non-parametric comparison of MIC values of medicinal plant extracts\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTest statistic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u0026sup2; (H value)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDegrees of freedom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsymptotic significance (p)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eKruskal-Wallis H test, which is a non-parametric method, showed a significant difference in the MIC distributions between the extracts of medicinal plants (\u0026chi;\u0026sup2; = 19.87, p\u0026thinsp;=\u0026thinsp;0.006). This establishes that the antimicrobial effect, represented by the MIC values, was differing significantly even when the normality assumption was not satisfied. Extracts of Thymus vulgaris and Origanum vulgare were the ones that showed consistently lower median MICs, whereas, Azadirachta indica and Nigella sativa were the ones with higher MICs. The non-parametric outcome helps to secure the ranking of the antimicrobials that was derived from the diffusion and MIC assays.\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec32\" class=\"Section2\"\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab12\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelation analyses between phytochemical content and antimicrobial activity of medicinal plant extracts\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables correlated\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCorrelation coefficient (r)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStrength of association\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal phenolic content vs zone of inhibition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e+\u0026thinsp;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStrong positive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal flavonoid content vs zone of inhibition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e+\u0026thinsp;0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u0026ndash;strong positive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal phenolic content vs MIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026minus;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStrong negative\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal flavonoid content vs MIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026minus;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate negative\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe analysis of correlation brought to light strong positive links between total phenolic content and the inhibition zone (r\u0026thinsp;=\u0026thinsp;0.74, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and a strong negative relation between phenolic content and MIC values (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.71, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The same, though slightly weaker, patterns were noted for flavonoids. These findings suggest that the presence of phenolic and flavonoid compounds in higher concentrations is strongly correlated to the enhanced antimicrobial potency. The results give quantitative support to the idea that phytochemicals are the ones responsible for the antimicrobial mechanisms and to the use of bioassay-guided fractionation strategies.\u003c/p\u003e\n \u003cdiv id=\"Sec33\" class=\"Section3\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe ethnobotanical triage has successfully prioritized eight medicinal taxa for laboratory evaluation with the support of citations that frequently ranged from 55\u0026ndash;78% (mean\u0026thinsp;\u0026asymp;\u0026thinsp;64% \u0026plusmn; ~6%). This not only validates the selection strategy but also gives an evidence-based starting set for phytochemical and antimicrobial screening. Extraction yields differed depending on both the solvent and the species: for polar extraction (70% ethanol), the highest yields (9\u0026ndash;14% w/w) were produced, with Nigella sativa (14.2% \u0026plusmn; 1.1) and Terminalia chebula (13.0% \u0026plusmn; 1.0) being among the best scorers. On the other hand, the yields of essential oils in aromatic genera (Thymus, Origanum, Eucalyptus) were moderate (1.0\u0026ndash;1.5%). The qualitative phytochemistry of Thymus and Origanum showed strong terpenoid/essential-oil signals (score\u0026thinsp;\u0026asymp;\u0026thinsp;3.0), pronounced tannins in Terminalia chebula (3.0), and notable alkaloid signatures in Azadirachta and Curcuma - these patterns that guided the targeted quantitative assays.\u003c/p\u003e \u003cp\u003eThe quantitative profiling confirmed the qualitative patterns: Terminalia chebula had the highest total phenolic content (TPC 112.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8 mg GAE/g), while Thymus vulgaris and Origanum vulgare were simultaneously rich in phenolics and flavonoids (TPC\u0026thinsp;\u0026asymp;\u0026thinsp;86.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0 and 79.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6 mg GAE/g respectively; TFC 31\u0026ndash;35 mg QE/g). The antimicrobial diffusion tests revealed that Thymus (24.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 mm mean zones against S. aureus) and Origanum (23.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 mm) were the most powerful across the pathogen panel; Allium sativum and Terminalia chebula also showed considerable activity against Gram-positive strains (about 21\u0026ndash;22 mm zones). However, the situation was different with Gram-negative pathogens, particularly Pseudomonas aeruginosa, which remained less susceptible, in general.\u003c/p\u003e \u003cp\u003eQuantitative susceptibility testing corroborated diffusion results: Thymus and Origanum proceeded to very low MIC₅₀ values (31.25\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u0026ndash;6 \u0026micro;g/mL) and the lowest geometric mean MICs (\u0026asymp;\u0026thinsp;45\u0026ndash;50 \u0026micro;g/mL), demonstrating strong potency; Terminalia chebula ranked as a moderate activity (MIC₅₀ 62.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8 \u0026micro;g/mL) whereas at the same time Azadirachta and Nigella indicated higher MICs (\u0026ge;\u0026thinsp;250 \u0026micro;g/mL) representing weak activity. The Kruskal\u0026ndash;Wallis non-parametric test confirmed significant differences in MIC distributions among extracts (χ\u0026sup2; = 19.87, df\u0026thinsp;=\u0026thinsp;7, p\u0026thinsp;=\u0026thinsp;0.006), thus supporting the potency ranking observed.\u003c/p\u003e \u003cp\u003eIn vivo tests showed the most active aromatic extracts had both membrane destructive and antivirulence mechanisms: Thymus caused\u0026thinsp;~\u0026thinsp;72% of membrane leakage at 1\u0026times; MIC and ~\u0026thinsp;78% inhibition of biofilm at 100 \u0026micro;g/mL, whereas Origanum resulted in ~\u0026thinsp;68% leakage and ~\u0026thinsp;73% biofilm inhibition. Time-kill studies depicted rapid bactericidal kinetics of these extracts (\u0026ge;\u0026thinsp;3 log₁₀ reduction at 24 h), and checkerboard testing revealed synergy with ciprofloxacin (FICI median\u0026thinsp;~\u0026thinsp;0.42\u0026ndash;0.45), thus, they were suggested as potential antibiotic adjuvants. On the contrary, neem and nigella extracts showed few membrane effects and had indifferent interactions (FICI\u0026thinsp;\u0026gt;\u0026thinsp;1).\u003c/p\u003e \u003cp\u003eStatistical analysis reinforced those conclusions: one-way ANOVA of the zone measurements was found to be highly significant (F\u0026thinsp;=\u0026thinsp;24.62, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and Tukey\u0026rsquo;s HSD identified Thymus and Origanum as significantly more active than Azadirachta and Nigella (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with no significant difference between Thymus and Origanum themselves. The analysis of correlation revealed a very strong positive correlation between total phenolic content and inhibition zones (r\u0026thinsp;=\u0026thinsp;+\u0026thinsp;0.74, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) as well as a strong negative one between phenolics and MIC (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.71, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). This indicates that phenolic content (and associated secondary metabolites) is the major factor contributing to the antimicrobial activity.\u003c/p\u003e \u003cp\u003ePreliminary safety assessment of the selected compounds gave a priority list for further development. Thymus and Origanum were the ones with the highest HepG2 CC₅₀ values (approx. 1,400\u0026ndash;1,500 \u0026micro;g/mL) and the best selectivity indices (SI\u0026thinsp;\u0026asymp;\u0026thinsp;28\u0026ndash;33). Thus, they are considered to be the most promising candidates for further research through bioassay-guided fractionation and in vivo follow-up. Terminalia chebula had the favorable SI of ~\u0026thinsp;12.6 and was classified as a mid-priority candidate, while Allium and Curcuma were ranked as moderate candidates (SI\u0026thinsp;\u0026asymp;\u0026thinsp;3\u0026ndash;4) whose fractions still contained the cytotoxic components thus needed more purification. Azadirachta and Nigella were evaluated to have low SI (\u0026lt;\u0026thinsp;2) and consequently were not considered for direct therapeutic application without considerable alteration.\u003c/p\u003e \u003cp\u003eThe most promising antimicrobial leads are revealed by the study to be the aromatic, phenolic-rich taxa (Thymus and Origanum) that also provided quantitative evidence for the relationship between phytochemicals and bioactivity, and drew a distinguishing line for the preclinical progression by bioassay-guided isolation and clear priority setting.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe study conducted a thorough evaluation of the antimicrobial properties of ethnobotanically selected medicinal plants and generated clear, actionable results. Among a variety of clinically important human pathogens, fragrant, phenolic rich plants \u0026mdash; particularly Thymus vulgaris and Origanum vulgare \u0026mdash; appeared as the most powerful and also selective extracts, demonstrating the largest inhibition zones, very low MIC₅₀/MIC₉₀ values, rapid bactericidal kinetics and strong antibiofilm and quorum-sensing inhibitory effects. Through a quantitative phytochemical profile, it was shown that total phenolic and flavonoid loads were highly correlated with antimicrobial potency, thus underpinning the biochemical rationale for the observed activity and providing a means for selecting. A study of the mechanisms used concluded that the main method of action for the top aromatic extracts was disruption of the bacterial membrane, adding antivirulence effects that limit biofilm formation and make bacteria more sensitive to conventional antibiotics thereby increasing their effectiveness.\u003c/p\u003e \u003cp\u003eMoreover, the study laid out a practical framework for prioritization of subsequent work that is to be done in the laboratory. Extracts that have both high antimicrobial activity and low toxicity to mammalian cells (high CC₅₀ and SI\u0026thinsp;\u0026ge;\u0026thinsp;10), especially those from Thymus and Origanum, are suggested to undergo immediate bioassay-guided fractionation, compound isolation and structure elucidation. Candidates of mid-priority (for instance, Terminalia chebula) require further fractionation to isolate the active phenolic fractions, nevertheless, those extracts with low selectivity indices (e.g., Azadirachta, Nigella) should be put on hold for monotherapy unless the extraction process is altered or toxic constituents removed. The extracts that were tested for synergistic effects demonstrated that they are able to act as antibiotics\u0026rsquo; adjuvants, which is an indication of the translational pathways that also include combination therapy to make existing antibiotics effective again or to enhance their potency against resistant strains.\u003c/p\u003e \u003cp\u003eThese results support an ethnobotany-to-bioactivity work f low which links the knowledge of the old with the new through standard antibacterial tests, pharmacochemical measures, and probing of the mechanism besides safety screening. The combination of the data set provides not only lead candidates but also reproducible methodologies (extraction, MIC determination, bioassay-guided fractionation, and cytotoxicity evaluation) that are suitable for preclinical progression. The process of drug development is now able to move directly to the highest-priority actions of bioassay-guided isolation of active constituents, pharmacokinetic and toxicity profiling, and in vivo efficacy testing in infection models. Such actions would bring to light if the apparently promising in vitro profiles would be translated into safe and effective therapeutic agents or adjuvants in clinical practice.\u003c/p\u003e\n\u003ch3\u003eLimitations of the study\u003c/h3\u003e\n\u003cp\u003eThe current study was limited to in vitro studies with crude extracts, thus direct applicability of the results to in vivo efficacy and safety is still limited. Chemical composition of crude extracts is very complex and there may be cases where intra-extract interactions either act in unison or against each other so that the individual components' activity is undermined. The microbial panel used was clinically relevant but had limited diversity in strains and did not include a significant collection of clinical multidrug-resistant (MDR) isolates. The cytotoxicity testing was carried out only on a few cell lines and this cannot be a substitute for comprehensive toxicological screening. Limited resources also meant that only part of the active extracts were subjected to preliminary mechanistic assays and no pure compounds were characterized using NMR-grade structural elucidation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eV.P. performed the sample collection and extraction along with proof reading and review S.K. did the research part and help with the writing\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChassagne F, Samarakoon KW, Porras G, Lyles JT, Dettweiler MJ, Marquez L, Salam RA, Shabih S, Farrokhi A, Quave CL. A systematic review of plants with antibacterial activities: A taxonomic and phylogenetic perspective. 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Biological effects of essential oils \u0026mdash; a review. Food Chem Toxicol. 2008;46:446\u0026ndash;75. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.fct.2007.09.106\u003c/span\u003e\u003cspan address=\"10.1016/j.fct.2007.09.106\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. (PubMed).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewman DJ, Cragg GM. Natural products as sources of new drugs. J Nat Prod. 2016;79:629\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acs.jnatprod.5b01055\u003c/span\u003e\u003cspan address=\"10.1021/acs.jnatprod.5b01055\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. (PubMed).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"medicinal plants, antimicrobial activity, phenolic compounds, MIC, bioassay-guided fractionation","lastPublishedDoi":"10.21203/rs.3.rs-9294102/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9294102/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe surge of antimicrobial resistance makes it necessary to look for new sources of drugs; medicinal plants still form a supplier of bioactive secondary metabolites for the future. Objectives: The goal of the study was to test the ethnic selected medicinal plants for in vitro activity against a specific group of human pathogens, assess the strength (MIC/MBC), analyse the phytochemistry, examine mechanisms of action and interactions, conduct preliminary toxicity testing on mammalian cells to prioritize the leads for further development. Methods: The polarity series (hexane, ethyl acetate, 70% ethanol, aqueous; hydrodistillation for essential oils) was used to extract eight taxa, which were then subjected to agar diffusion and CLSI-guided broth microdilution (resazurin confirmation) screening. Phytochemical characterization included qualitative tests, total phenolic/flavonoid quantification (TPC/TFC), TLC, HPLC\u0026ndash;DAD, and GC\u0026ndash;MS. Mechanistic assays included membrane integrity, antibiofilm and quorum-sensing inhibition, time\u0026ndash;kill kinetics, and checkerboard synergy with ciprofloxacin. Cytotoxicity (HepG2) determined CC₅₀ and selectivity indices (SI\u0026thinsp;=\u0026thinsp;CC₅₀/MIC). Results: Aromatic, phenolic-molecule-rich extracts\u0026mdash;Thymus vulgaris and Origanum vulgare\u0026mdash;proved to be the strongest and most reliable antimicrobial agents (zones over 25 mm; MIC₅₀\u0026asymp;31.25 \u0026micro;g/mL; geometric mean MICs\u0026thinsp;\u0026asymp;\u0026thinsp;45\u0026ndash;50 \u0026micro;g/mL), they were active in a way that disrupted membranes (leakage of ~\u0026thinsp;68\u0026ndash;72% at 1\u0026times; MIC), Diminution of antibacterial biofilm activity was substantial (~\u0026thinsp;73\u0026ndash;78% at 100 \u0026micro;g/mL), rapid bactericidal kinetics (\u0026ge;\u0026thinsp;3 log₁₀ reduction at 24 h) and synergistic interactions with ciprofloxacin (FICI\u0026thinsp;\u0026asymp;\u0026thinsp;0.42\u0026ndash;0.45). Terminalia chebula was the next to be tested with moderate potency (MIC₅₀\u0026asymp;62.5 \u0026micro;g/mL). Very strong positive relationship was noticed between TPC and the antimicrobial power (r\u0026thinsp;\u0026asymp;\u0026thinsp;+\u0026thinsp;0.74 vs zone; r\u0026thinsp;\u0026asymp;\u0026thinsp;\u0026minus;\u0026thinsp;0.71 vs MIC, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In safety profiling, the winning ones were Thymus and Origanum (HepG2 CC₅₀\u0026asymp;1,400\u0026ndash;1,500 \u0026micro;g/mL; SI\u0026thinsp;\u0026asymp;\u0026thinsp;28\u0026ndash;33). Conclusion: Ethnobotanical selection along with standardized assays pointed out Thymus and Origanum as high-priority leads for bioassay-guided isolation and preclinical evaluation; further fractionation, pharmacokinetics and in vivo toxicity/efficacy studies are suggested.\u003c/p\u003e","manuscriptTitle":"Antimicrobial potential of medicinal plants extracts against human pathogens","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-03 07:00:58","doi":"10.21203/rs.3.rs-9294102/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1d2c6988-42c0-44ae-bf42-662036a0da60","owner":[],"postedDate":"April 3rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-17T23:39:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-03 07:00:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9294102","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9294102","identity":"rs-9294102","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}