High-Throughput Screening of Natural Plant Extracts for Antibacterial Effectiveness Compared to Commercial Disinfectants

All bacterial strains will be identity-verified by 16S rRNA PCR and sequencing prior to use. Extract concentrations will be verified by spectrophotometric measurement and HPLC prior to screening. All 96-well plates will include internal positive and negative controls in duplicate to flag plate-level failures. OD600 readings will be background-subtracted using sterility controls. Flow cytometer will be calibrated daily with reference beads. Confocal microscope settings will be standardized across imaging sessions. HPLC column performance will be validated with standard compounds before extract profiling. All reagents will be prepared fresh or from validated frozen aliquots. Laboratory notebooks will document all batch numbers, preparation dates, and instrument calibration records. Replicate experiments will be performed on separate days with independently prepared bacterial cultures.

Positive controls: wells containing commercial disinfectants (10% bleach, 70% isopropanol, Lysol) at effective concentrations known to kill bacteria; wells containing 100% bacteria kill confirmed by no OD600 change vs. sterility control. Negative controls: bacteria-only wells with equivalent solvent (≤1% DMSO) to measure uninhibited growth. Sterility controls: medium + highest extract concentration without bacteria to detect extract auto-fluorescence or color interference with OD600. Solvent toxicity controls: bacteria + 1% DMSO only to confirm solvent has no significant antibacterial effect. LIVE/DEAD assay controls: 100% live bacteria (untreated) and 100% dead bacteria (heat-killed at 80°C for 10 min) for flow cytometry gating calibration.

We expect to identify at least 3–5 plant extracts with MIC values below 10 mg/mL against at least one bacterial strain. Tea tree oil, oregano oil, and thyme extract are anticipated to show the strongest antibacterial activity, potentially approaching the efficacy of isopropanol at lower concentrations. S. aureus may show greater susceptibility to certain plant extracts than E. coli due to its gram-positive cell wall structure. The most effective extracts are expected to cause membrane disruption as visualized by confocal microscopy and confirmed by increased propidium iodide uptake in flow cytometry. HPLC/MS profiling is expected to identify phenolic compounds (e.g., thymol, carvacrol, allicin) as the primary active moieties. NGS data may reveal upregulation of membrane stress and oxidative stress response genes in bacteria treated with the most effective extracts.

• Natural plant extracts: tea tree oil, garlic extract, oregano essential oil, thyme extract, neem extract, eucalyptus oil, clove extract, cinnamon bark extract, rosemary extract, ginger extract (sourced from commercial botanical suppliers or freshly prepared)
• Bacterial strains: E. coli ATCC 25922, S. aureus ATCC 25923
• Commercial disinfectants: 10% bleach solution, 70% isopropanol, Lysol concentrate
• LB broth and LB agar (bacteriological grade)
• 96-well flat-bottom microplates (sterile)
• Sterile 1X PBS
• DMSO (solvent for extract dilutions)
• LIVE/DEAD BacLight Bacterial Viability Kit (fluorescent staining)
• 96-well plate reader (OD600 capable)
• Flow cytometer with appropriate filters for SYTO9/propidium iodide
• Confocal microscope with fluorescence capability
• HPLC system with C18 reverse-phase column
• Mass spectrometer (LC-MS compatible)
• Western blot reagents (SDS-PAGE gels, transfer membranes, antibodies for stress response proteins)
• ELISA reader
• NGS sequencer and library preparation kit
• PCR machine and reagents (for gene expression validation)
• Centrifuge
• Spectrophotometer
• Multichannel pipettes and reservoirs
• Microcentrifuge tubes
• Sterile filter units (0.22 µm)
• Ethanol for extract sterilization
• Biosafety cabinet (BSL-2 appropriate)
• Personal protective equipment (gloves, lab coat, eye protection)
• Statistical software (R or GraphPad Prism, free version)

To systematically evaluate and compare the antibacterial efficacy of multiple natural plant extracts against representative bacterial strains using high-throughput screening methods, benchmarking performance against commercially available disinfectants.

1. Prepare bacterial overnight cultures of E. coli ATCC 25922 and S. aureus ATCC 25923 in LB broth at 37°C with shaking (200 rpm) for 16 hours.
2. Dilute overnight cultures to OD600 = 0.05 (~5×10^6 CFU/mL) in fresh LB broth to prepare working inocula.
3. Prepare stock solutions of each plant extract at 100 mg/mL in DMSO (or appropriate solvent); filter-sterilize using 0.22 µm syringe filters. Prepare stock solutions of commercial disinfectants at standardized concentrations.
4. Perform 2-fold serial dilutions of each extract and disinfectant across 8 columns of a 96-well plate in LB broth (final DMSO concentration ≤1% in all wells), covering concentration range from 0.78 mg/mL to 100 mg/mL for extracts.
5. Add 100 µL of bacterial inoculum to each well containing 100 µL of diluted extract or disinfectant, achieving a final volume of 200 µL per well. Set up negative controls (bacteria + solvent only) and sterility controls (medium + extract, no bacteria).
6. Incubate plates at 37°C for 18–24 hours without shaking to enable growth assessment.
7. Measure OD600 of all wells using the plate reader. Calculate percent growth inhibition relative to the negative control wells. Determine MIC as the lowest concentration showing ≥90% growth inhibition.
8. Select the top 5 most effective plant extracts based on MIC values. Prepare bacterial cultures treated with extracts at MIC and 2× MIC concentrations for downstream assays.
9. Stain treated bacterial samples with LIVE/DEAD BacLight kit (SYTO9 and propidium iodide) according to manufacturer protocol. Analyze samples by flow cytometry to quantify proportions of live vs. dead cells. Analyze aliquots by confocal microscopy to visualize membrane integrity and morphological changes.
10. Characterize chemical profiles of the top 5 plant extracts using HPLC (C18 reverse-phase column, gradient elution with water/acetonitrile + 0.1% formic acid) and LC-MS to identify major bioactive compounds.
11. Extract RNA from bacteria treated with the most effective extract at MIC for 4 hours and from untreated controls. Prepare NGS libraries using a low-input RNA-seq library prep kit and sequence on available sequencer to assess transcriptomic stress response changes.
12. Validate NGS findings by RT-PCR using the PCR machine, targeting key stress response and antibiotic resistance genes (e.g., marA, soxS, norA).
13. Perform Western blot analysis on protein lysates from treated and untreated bacteria using antibodies against selected stress response proteins (e.g., GroEL as loading control, OmpA for membrane integrity) to confirm protein-level changes.
14. Conduct ELISA-based quantification (using ELISA reader) of any secreted virulence factors or stress markers if relevant antibody kits are available within budget.
15. Repeat the full 96-well plate screen in biological triplicates on three separate days to ensure reproducibility. Compile all OD600, flow cytometry, and microscopy data for statistical analysis.
16. Perform colony-forming unit (CFU) counting by plating serial dilutions of selected treated samples on LB agar to validate plate reader results and confirm bactericidal vs. bacteriostatic activity.
17. Compile all data, calculate MIC values, IC50 values (using dose-response curve fitting), and statistical comparisons. Generate summary tables and graphs for all extracts vs. commercial disinfectants.

Selected natural plant extracts (e.g., tea tree oil, garlic extract, oregano oil, thyme extract) will exhibit comparable or superior antibacterial activity against model bacterial strains (E. coli and S. aureus) relative to commercial disinfectants at equivalent or lower concentrations, as measured by bacterial viability, minimum inhibitory concentration (MIC), and growth inhibition metrics.

• If plant extracts are turbid or colored and interfere with OD600 readings, use resazurin (alamar blue) viability assay as an alternative fluorometric readout on the plate reader.
• If DMSO concentration exceeds 1% due to solubility requirements, test each extract's maximum non-toxic DMSO concentration first and adjust stock concentrations accordingly.
• If bacterial growth is insufficient in 18 hours (low OD600 in negative controls), extend incubation to 24 hours or verify inoculum density before plating.
• If HPLC peaks overlap or are unresolved, optimize gradient elution conditions (adjust acetonitrile gradient slope or add ion-pairing reagents) or increase column temperature to 40°C.
• If flow cytometer clogs due to bacterial aggregation from certain extracts, filter samples through a 35 µm cell strainer or dilute 1:5 in PBS before running.
• If confocal imaging shows high background fluorescence from plant extracts, wash bacteria 3× in PBS before staining and image in PBS rather than LB medium.
• If NGS library yield is insufficient, pool all treated samples of the same condition before library prep or use a low-input kit optimized for bacterial RNA.
• If Western blot bands are faint, increase protein loading (use up to 30 µg per lane), optimize blocking buffer, or extend primary antibody incubation to overnight at 4°C.
• If MIC values are inconsistent between replicates, verify inoculum standardization, ensure uniform mixing before plate sealing, and check for evaporation by using plate sealers during incubation.
• If budget constraints are exceeded, prioritize OD600 plate reader assay and HPLC profiling; defer NGS, Western blot, and ELISA to a subsequent study or seek collaborator instrument access.

MIC values will be determined from dose-response curves fitted using a four-parameter logistic (4PL) model in GraphPad Prism (free trial) or R (drc package, free). IC50 values will be calculated from fitted curves. Percent inhibition data will be analyzed using two-way ANOVA with Tukey's post-hoc test to compare all extract/disinfectant combinations across concentrations and bacterial strains. Flow cytometry live/dead ratios will be compared using one-way ANOVA with Dunnett's test (vs. negative control). Pearson correlation will be used to assess agreement between OD600-based MIC and CFU-based results. All experiments will be conducted in biological triplicates (n=3); data presented as mean ± SEM. Statistical significance threshold: p < 0.05. Heatmaps of inhibition across all extracts and concentrations will be generated using R (ggplot2 or pheatmap). NGS differential expression analysis will use DESeq2 in R with FDR correction (Benjamini-Hochberg, adjusted p < 0.05).