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A Clinical Trial to Evaluate the Efficacy of α-Viniferin in Staphylococcus aureus – Specific Decolonization without Depleting the Normal Microbiota of Nares

MD ABDUR RAHIM
MD ABDUR RAHIM
, 
HOONHEE SEO
HOONHEE SEO
, 
SUKYUNG KIM
SUKYUNG KIM
, 
YOON KYOUNG JEONG
YOON KYOUNG JEONG
, 
HANIEH TAJDOZIAN
HANIEH TAJDOZIAN
, 
MIJUNG KIM
MIJUNG KIM
, 
SAEBIM LEE
SAEBIM LEE
 e 
HO-YEON SONG
HO-YEON SONG
   | 19 mar 2021
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Article Category: original-paper
Pubblicato online: 19 mar 2021
Pagine: 117 - 130
Ricevuto: 28 dic 2020
Accettato: 08 feb 2021
DOI: https://doi.org/10.33073/pjm-2021-011
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© 2021 Md Abdur Rahim et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Introduction

Staphylococcus aureus is one of the most common opportunistic pathogens carried by approximately 30–50% of humans and continues to be a leading cause of infection-related deaths, ranging from 6–40% around the globe (Frank et al. 2010; Islam et al. 2020). Although the axilla, throat, and perineum are essential reservoirs, the anterior nares are the primary niche for S. aureus and serve as a reservoir for the pathogen’s spread (Lowy 1998). S. aureus nasal colonization causes a range of mild infections to life-threatening conditions, including fatal endocarditis, pneumonia, bacteremia, or chronic osteomyelitis. Additionally, it is a risk factor for life-threatening surgical site infections and infections in dialysis (Mitchell and Howden 2005). So far, antibiotic therapy has been the best option for treating S. aureus. However, S. aureus infections have become a serious global challenge because of resistance to a wide range of clinically significant antibiotics and a limited number of new antibiotics. Previous studies showed that the rate of discovery of new antibiotics is slowing, while the occurrence of antibiotic-resistant infections is increasing sharply, therefore, the rate of antibiotic withdrawal from the healthcare system is higher than that of approvals (Kinch et al. 2014). In addition, the current antibiotic regimen reduces and changes the skin’s microbial composition and supports pathogen overgrowth (Chambers and Deleo 2009; Song et al. 2018), highlighting the need to develop new drugs that not only serve as effective alternatives to the current drug regimen but also preserve skin microbiota.

Natural products and secondary metabolites produced by living systems, mostly plants, have a wide range of pharmacological properties, including antimicrobial and anti-inflammatory ones, and a high potential for treating human diseases, such as coronary heart diseases, cancer, diabetes, and infectious diseases (Chabán et al. 2019). According to the World Health Organization, 65–80% of the world’s population depends on traditional medicine to treat many diseases (Chew et al. 2011). α-Viniferin is a phytochemical compound extracted from Carex humilis, a medicinal plant that grows in eastern Asian countries, such as Japan, China, and Korea (Seo et al. 2017). It was also identified from Iris clarkei, Caragana Sinica, and Caragana chamlagu (Chung et al. 2003). α-Viniferin isolated and identified as a stilbene oligomer has various biological activities, including antioxidant, anti-tumor, anti-cancer, and anti-arthritis. It has also been reported to inhibit cyclooxygenase, acetylcholinesterase, and prostaglandin H-2 synthase (Sim et al. 2014; Seo et al. 2017). Additionally, α-viniferin shows antibacterial activity against drug-susceptible and drug-resistant strains of Mycobacterium tuberculosis and excellent anti-Staphylococcus activity against three Staphylococcus species, including methicillin-susceptible S. aureus (MSSA), methicillin-resistant S. aureus (MRSA), and methicillin-resistant Staphylococcus epidermidis (MRSE) (Seo et al. 2017). Previous studies using animal models have demonstrated that α-viniferin improves general health in mammals and is rapidly absorbed in the blood stream (Baur et al. 2006; Fan et al. 2020). Although α-viniferin is assumed to be a potential S. aureus-specific drug, there were no clinical studies on its effects on S. aureus to the best of our knowledge. In this study, we investigated α-viniferin clinical efficacy in eradicating S. aureus from the nasal carriage. Additionally, we looked over the effectiveness of α-viniferin against nasal MRSA.

Experimental
Materials and Methods

α-Viniferin and its antimicrobial inhibition. We purchased the α-viniferin, pale brown powder (Cat No.: CFN97068) from Chem Faces (Wuhan, Hubei, China) and confirmed its specific toxicity against 20 bacterial strains obtained from the National Culture Collection for Pathogens (NCCP) (Chungbuk, Korea). The minimal inhibitory concentration (MIC) of α-viniferin against each bacterial strain was determined using cation-adjusted Mueller-Hinton broth according to the Clinical and Laboratory Standards Institute (CLSI). Each well of a 96-well plate was inoculated with 200 μl of the inoculum suspension (1 × 105 to 1 × 106 CFU/ml) and the plates were incubated for 24 h. The MIC values were determined as the lowest drug concentrations that showed complete inhibition of visible growth. The bacterial strains were as follows: Escherichia coli NCCP 14762, Proteus vulgaris NCCP 14765, Shigella boydii NCCP 14745, Shigella flexneri NCCP 14744, Shigella dysenteriae NCCP 14746, Staphylococcus aureus NCCP 14780, Staphylococcus epidermidis NCCP 14768, Staphylococcus aureus MRSA NCCP 14769, Corynebacterium diphtheriae NCCP 10353, Salmonella enteritidis NCCP 14771, Acinetobacter baumannii NCCP 14782, Streptococcus sangunis NCCP 14775, Streptococcus pyogenes NCCP 14783, Streptococcus pneumoniae NCCP 14774, Serratia marcescens NCCP 14770, Citrobacter freundii NCCP 14766, Enterobacter aerogenes NCCP 14761, Proteus mirabilis NCCP 14763, Klebsiella pneumoniae NCCP 14764, and Escherichia coli O157 NCCP 14541.

Study design and subjects. Our study enrolled 20 Korean adult females aged between 20 and 60 years following inclusion and exclusion criteria. The inclusion criteria comprised health and physical fitness, age > 18 years, and the willingness to avoid topical agent applied to the nares during the entire trial. The characteristics of the subjects are shown in Table SI. The Institutional Review Board approved this study of the Korea Dermatology Research Institute (IRB Number: KDRI-IRB-20231, Study Code: KDRI-2020-231). We obtained written informed consent from all participants before conducting the study. The study was carried out according to the 1964 declaration of Helsinki.

Clinical experiment. Following the randomization sequence, we sequentially numbered containers with the study drug, α-viniferin, and provided it to the numerical order participants. Nare’s specimens were collected on day 0 and at day ten by a professional. During the trial, each participant’s skin moisture content was measured on days 0, 4, and 8 using a corneometer CM 825 (Courage and Khazaka, Germany). Each time, the corneometer measurement was done five times at constant temperature and humidity (20–24°C, 40–60% RH), at the same site, in the same way, and the average value was recorded as an immediate value. The recorded value was then analyzed to observe our study drug’s moisturizing power because moisture content plays a key role in maintaining an intact skin barrier (Mojumdar et al. 2017). During and immediately after the test, a dermatologist examined the skin for irritation or allergic symptoms.

Skin irritation test. Before the clinical trials, a skin irritation test for three concentrations of α-viniferin (10 μg/ml, 100 μg/ml, 1,000 μg/ml) was done on 32 Korean adult females in a different place to rule out the possibility of skin irritation of the test drug. The characteristics of the participants are shown in Table SII. The drug solution was loaded into a clear patch chamber, and then the patches were applied onto the participants’ backs. All participants were advised to avoid water, heavy exercise, and scratching. The patch chambers were removed after 48 hours. After thirty minutes of patch removal (total 48 hours test), the reaction site was observed and observed again after 24 hours (total 72 hours of the test). The reactions were graded according to the recommendation of the International Contact Dermatitis Research Group (ICDRG), and Frosch and Kligman (Frosch and Kligman 1979; Lachapelle and Maibach 2020). This study was approved by the Institutional Review Board of the COREDERM Skin Research Center (IRB Number: CDIRB-QR-20-025, Study Code: CDS-2000-005-14). We obtained written informed consent from all participants before conducting this study.

Preparation and application of α-viniferin. We prepared α-viniferin suspension by mixing the powder with sterile distilled water at 100 mg/l. A sterile cotton swab (BD Difco, USA) was used to treat the nares; the swab was moistened with the drug suspension and then gently rubbed the anterior nares while rotating it for 15 seconds. The drug was applied three times daily for ten days in right and left nares. The participants themselves made the application of the drug solution.

Sample collection. An expert did the collection of nasal specimens at day zero (0) and the end of the trial (at day 10), by swabbing the anterior nares with sterile foam-tipped swabs moistened with a mixed solution of 0.15 M NaCl and 0.1% Tween 20 solution (Sigma-Aldrich, France) (You et al. 2019). Each region was swabbed for 15 seconds while rotating the swab and exerting gentle pressure. Each swab was then placed into the swab container without touching any objects and transported to the laboratory in a dry-ice bag container within two hours of collection.

Culture of microorganisms. Upon receiving the lab samples, we added 2 ml 0.15 M NaCl solution into the swab container, vortexed it enough, and transferred it into a fresh microcentrifuge tube. After doing a 10-fold serial dilution four times (10–1 to 10–4) in 0.15 M NaCl solution, we placed a 10-μl sample from each of the dilution-tube in duplicate onto the nutrient agar, a staphylococcus agar medium (BD Difco, USA), and a second staphylococcus agar medium containing methicillin antibiotic (50 μg/ml) for the culture-based quantification of nasal microbiota, S. aureus, and MRSA, respectively, using a spread plate method. After 48 hours of incubation at 37°C, plates were inspected for the growth of colonies with morphology characteristic of S. aureus. We distinguished S. aureus from other Staphylococcus species by its round and golden-yellow colonies. For each dilution, the average of the two duplicate plates was calculated. When two successive dilutions yielded 30 to 300 colonies, the average count of both dilutions was calculated. We stored the rest of the samples at –80°C for further molecular analysis.

DNA extraction. We extracted DNA for real-time quantitative PCR (qRT-PCR) and next-generation sequencing (NGS)-based 16S rRNA profiling by thawing samples and transferring them to Lysing Matrix B tubes aseptically (MP, Biomedicals, USA), followed by mechanical lysis through bead beading. After centrifuging enough, we collected supernatant without any visible particles. Next, we checked the quality of extracted DNA by agarose gel electrophoresis and visualized it using ethidium bromide (Bio-Rad, ChemiDoc, USA). We also quantified the isolated DNA by a Qubit Fluorometer using a dsDNA HS Assay kit (Invitrogen, USA). We used a 0.15 M NaCl solution as a negative control to ensure no DNA contamination occurred during the whole process (Rainer et al. 2020).

qRT-PCR. We did qRT-PCR (C1000 Thermal Cycler) to test for the presence and quantification of S. aureus and MRSA in the nasal swab samples separately, targeting organism-specific genes is a significant correlation between PCR cycle threshold (Ct) value and bacterial load (Dionne et al. 2013; Davies et al. 2018). We used the following primers in this study: SA1 (5’-AATCTTTGTCGGTACACGATATTCTTCACG-3’) and SA2 (5’-CGTAATGAGATTTCAGTAGATAATACA ACA-3’) specific for S. aureus (Pereira et al. 2010); and MRS1 (5’-TAGAAATGACTGAAC GTCCG-3’) and MRS2 (5’-TTGCGATCAATGTTACC GTAG-3’) specific for MRSA (Del Vecchio et al. 1995). We also used 16S rRNA universal primers to quantify resident nasal microbiota. We did the assay in a final volume of 20 μl consisting of a 5-μl extracted template DNA and 15 μl reaction mixtures: 4 μl nuclease-free water, 10 μl iQ SYBR Green Supermix (Bio-Rad Laboratories, USA), and 0.5 μl each of the forward and reverse primer (10 pmol/μl). We did amplification as follows: an initial DNA denaturation and enzyme activation at 95°C for 3 min, followed by 49 cycles of a 10-s denaturation step at 95°C, a 10-s annealing step at 55°C, and a 30-s extension step at 72°C.

Absolute quantification. To make a qRT-PCR standard curve (threshold cycle versus the number of CFU/ml curve), we cultivated an S. aureus stock culture (0.1% inoculation) in Mueller-Hinton broth (BD Difco, USA) for 6–8 hours at 37°C using a shaker incubator (BioFree, Korea). We then checked the optical density (OD at 600 nm) using a spectrophotometer (DR 1900, Hach, USA); it was 0.8 to 1.0. Next, we centrifuged the broth culture to get the bacterial pellet at 1,811.16 ×g for 10 mins employing a Hanil combi R515 (Hanil Scientific Inc., Korea) serially diluted the pellet 10-fold eight times using sterile distilled water. After that, we extracted DNA through mechanical lysis as described in the DNA Extraction section, amplified it by qRT-PCR, and used the data to create the standard curve in which each target CFU is plotted against the resulting Ct value.

16S rRNA-based amplicon sequencing. Following the DNA extraction, we amplified the V4 hyper-variable region of the 16S ribosomal RNA gene. We used the V4 region-specific primers with a locus-specific overhang sequence: 515F-5’ – TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG-GTGCCAGCMGCCGCGGTAA and 806R – 5’-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG-GGACTACHVGGGTWTCTAAT (overhang sequence-locus specific-sequence). We attached indexes and Illumina sequencing adapters through index PCR using a Nextera XT Index kit v2 (Illumina, USA). We used Agencourt AMPure XP (Beckman Coulter, USA) beads after every PCR step to purify the PCR products and quantified them using the Qubit dsDNA HS Assay kit (Invitrogen, USA). We then normalized the samples, pooled, mixed them with PhiX Control v3 (Illumina), and sequenced them using Illumina iSeq 100 platform (Illumina). Finally, we analyzed the sequence data using Ezcloud software that exhibits the entire microbial profile within the sample tested.

Gene expression profiling. Drug treatment, RNA extraction, and analysis. To understand how α-viniferin downregulate S. aureus gene expression, we treated an S. aureus broth culture with α-viniferin, extracted RNA, and sent it for the RNA sequencing. We cultivated S. aureus culture and measured optical density as described in the absolute quantification section. Then, we distributed the broth culture into three tubes; each tube contained 30 ml of broth. Afterward, we added a specific volume of α-viniferin stock solution to the tubes separately to make the drug concentration 1 × the MIC value (10 μg/ml) and 2× the MIC value (20 μg/ml). We also used drug-free 0.15 M NaCl solution in one of the tubes as a negative control. We then incubated the drug-treated and drug-free culture at 37°C for 6–8 hours on a shaker incubator. After the incubation, we extracted total RNA from the broth cultures of S. aureus using the RNA Protect Bacterial Reagent and RNeasy Mini kit (QIAGEN, Germany), according to the manufacturer’s instructions (RNeasy Mini Handbook). We also used an RNase-free DNase set (QIAGEN) for the degradation of the existing DNA. We assessed the quality of the isolated total RNA through 2% agarose gel electrophoresis since high-quality RNA is a prerequisite for ensuring all expressed genes’ representation. We sent RNA samples for RNA sequencing, which has become a standard tool for analyzing gene expression in bacterial infections (Saliba et al. 2017). We did an RNA sequencing assay using a commercial RNA sequencing service (Ebiogen, Seoul, Korea).

Library preparation, sequencing, and data analysis. We used a QuantSeq 3’mRNA-Seq Library Prep Kit (Lexogen, Inc., Austria) to construct an RNA library following the manufacturer’s instructions. In brief, we hybridized 500 ng of the total RNA with an oligo-dT primer containing an Illumina-compatible sequence at the 5’ end, followed by reverse transcription. We initiated the second-strand synthesis using a random primer containing an Illumina-compatible linker sequence at its 5’ end after the degradation of the RNA template. We used magnetic beads to remove all the reaction components and purify the double-stranded library. We then amplified the library to add the entire adapter sequences essential for cluster generation. Finally, we purified the complete library from PCR components, did a high throughput sequencing as single-end 75 sequencing using NextSeq 500 (Illumina). After the sequencing, we used Bowtie2 to align the QuantSeq 3’mRNA-Seq reads. We created Bowtie2 indices from either a representative transcript sequence or a genome assembly sequence for aligning with genome and transcriptome. We used alignment files for assembling transcripts, estimating their abundances, and detecting different expressions of genes. We used Bedtool coverage to find the differentially expressed genes based on counts from unique and multiple alignments. We processed the RT (Read Count) data based on Quantile normalization using EdgeR within R using Bioconductor. We based gene classification on searches done in the DAVID (http://david.abcc.ncifcrf.gov/) and Medline databases (http://www.ncbi.nlm.nih.gov/).

Statistical analysis. We analyzed the corneometer value, CFU, and qRT-PCR data using Prism 7.0 (GraphPad Software, Inc., La Jolla, USA). We used a two-tailed Student’s t-test to evaluate the statistical significance of the results of three independent experiments done in triplicate. In the graph, data are represented as mean ± standard deviation (SD). Means were considered to be significant at p < 0.05 (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001). We analyzed NGS-based 16S rRNA sequencing data using Ezcloud software. We also used the hypergeometric distribution to analyze the RNA sequencing data.

Results

Antimicrobial inhibition. Antibacterial inhibition of α-viniferin was tested against 20 bacterial isolates. The antibacterial activities of α-viniferin and two references antibiotics VAN and MET, expressed as MICs, are shown in Fig. 1, where MICs values were expressed up to 100 μg/ml. However, in this study, α-viniferin showed excellent anti-staphylococcus efficacy with the MIC value of 7.8 μg/ml against three Staphylococcus species including methicillin-susceptible S. aureus (MSSA), methicillin-resistant S. aureus (MRSA), and methicillin-resistant S. epidermidis (MRSE) with no toxicity to other bacterial strains (Fig. 1A). The reference drug VAN was also active against three Staphylococcus species, but it also showed toxicity against other bacterial strains (Fig. 1B), and MET was also tested as a second reference drug (Fig. 1C). These results indicate α-viniferin as a potential antibacterial agent with specific toxicity against Staphylococcus group.

Fig. 1.

Antimicrobial inhibition. Antibacterial activities, expressed as MICs, of α-viniferin (A), Vancomycin (B) and Methicillin (C) against 20 bacterial isolates. Bacterial suspensions (1 × 105 to 1×106 CFU/ml) were incubated with varying concentrations of α-viniferin, Vancomycin, Methicillin in Mueller Hinton Broth in a 96 well plate for 24 h at 37°C. In vitro MICs were determined by the broth dilution procedures described by the Clinical and Laboratory Standards Institute (CLSI).

Clinical experiment. We performed a 10-day clinical trial to investigate the antimicrobial efficiency of α-viniferin, in which 20 healthy Korean adult females participated. The drug was applied in the right and left anterior nares three times daily. We collected the nasal swab samples before (day 0) and after conducting the clinical trial (day 10), and we analyzed them through culture-based and molecular-based techniques (Fig. 2A). We also measured each participant’s skin surface’s hydration level using a corneometer at day 0, fourth, and eighth, respectively, and then the corneometer value, A.U, was analyzed. We observed that skin moisture content increased to a statistically significant level (p < 0.001) at day 4 (21.11%) and at day 8 (41.10%), compared to day 0, demonstrating the moisturizing power of α-viniferin (Fig. 2B).

Fig. 2.

Clinical experiment of α-viniferin. General overview of clinical experiment. α-Viniferin was treated three times daily both in the left and right nares using a sterile cotton swab stick for 10 days. Nasal specimens were collected at 0th day (drug-free) and 10th day (α-viniferin treated) and analyzed (A). Skin Moisture Content Measurement. Skin moisture content was also measured during the α-viniferin treatment at day 0, 4, and 8 respectively, using coreometer. After a 4-day and 8-day treatment, the skin moisture content of the area was increased dramatically (p < 0.001) to 21.11% and 41.10% respectively, compared to at day 0 (B). The experiments were performed in triplicate, and the data are represented as mean values and standard deviations. *Statistical significance vs. drug-free control using one-way ANOVA (*p < 0.05, **p < 0.01, ***p < 0.001).

Skin irritation test. A skin irritation test of α-viniferin was done in 32 healthy females in different locations before performing the clinical trial; with all participants, after the patch was attached for 48 hours, α-viniferin did not show skin irritation or allergic reactions at 30 mins and 24 hours after patch removal. The mean values with three different α-viniferin concentrations in both cases were 0.00 and were classified as having a low range (0.00–0.87) irritation potential according to the classification criteria (Table I). These results ensure the safety profile of α-viniferin as a topical agent.

Skin irritation test result.

Material’s nameNo. responder30 min. after patch removal (48 hrs.)24 hrs. after patch removal (72 hrs.)Meana
0.5+1+2+3+4+mean0.5+1+2+3+4+mean
1. α-viniferin 100–b––––0.00–––––0.000.00
2. α-viniferin 1000–––––0.00–––––0.000.00
3. α-viniferin 1,0000–––––0.00–––––0.000.00
4. Negative control0–––––0.00–––––0.000.00

– Mean: (mean value of skin reaction at 48 hrs. + mean value of skin reaction at 72 hrs.)/2. (Mean score: 0.00 ~ 0.87, low; 0.88 ~ 2.42, mild; 2.43 ~ 3.44, moderate; 3.45 <, severe)

– “-“: No reaction. (Reaction score: 0, –, no reaction; 0.5, ±, Barely perceptible erythema, Doubtful or questionable reaction; 1, +, Slight erythema, either spotty or diffuse; 2, ++, Moderate uniform erythema; 3, +++, Intense redness with edema; 4, ++++, Intense redness with edema and vesicles).

Culture-based quantification. To enumerate the culturable bacteria, S. aureus, and MRSA in the drug-free and α-viniferin-treated samples, we collected nasal specimens on day 0 and tenth. We assayed them on the nutrient agar, staphylococcus agar medium, and a staphylococcus agar medium containing methicillin (50 μg/ml) through spread-plate techniques. After incubation, we analyzed the resulting CFU data, which revealed that the samples’ bacterial content remained almost constant throughout the clinical trial period. The average number of commensal bacteria before and after the treatment was 1.7 × 107 CFU/ml and 1.2 × 107 CFU/ml, respectively, and the p was 0.616 (p>0.05) (Fig. 3A), indicating lack of significant change in bacterial content after α-viniferin treatment. On the other hand, the average number of S. aureus before and after the treatment was 3.8 × 105 CFU/ml and 8.3 × 103 CFU/ml, respectively, and the p was 0.002 (p<0.01) (Fig. 3B). The MRSA number was 7.8×104 CFU/ml and 2.9×103 CFU/ml, respectively, and the p was 0.008 (Fig. 3C), indicating a significant reduction in the number of S. aureus and MRSA during the clinical trial. Overall, the culture-based quantification results demonstrate α-viniferin as an antibacterial agent with specific activity against the staphylococcus group, including MRSA without affecting the nares’ resident normal microbiota.

Fig. 3.

Culture-based quantification. Nasal swab samples of 0 and 10th days were collected and incubated in nutrient agar, staphylococcus agar media 110, and staphylococcus agar media 110 containing methicillin antibiotic for 48 hours at 37°C by using spread plate technique. After this period, antimicrobial activity was determined by the colony forming unit (CFU) method against normal flora (A), S. aureus (B), and MRSA (C), respectively. The experiments were performed in triplicate, and the data are represented as mean values and standard deviations. *Statistical significance vs. drug-free control using unpaired two-tailed Students’s t-test (*p < 0.05, **p < 0.01, ***p < 0.001).

qRT-PCR-based quantification. We did qRT-PCR using S. aureus- and MRSA-specific primers to evaluate and quantify these organisms in the nares samples. We then analyzed the resulting Ct value and found that the Ct values for S. aureus and MRSA increased, which indicated the reduction of the organism populations. It is also noteworthy that there was no noticeable change in the Ctvalue of normal microbiota (p>0.05) (Fig. 4A). In Fig. 4B, the difference of the Ct value between the columns is four, which indicates that the S. aureus number was reduced 16-fold while the MRSA number decreased 32-fold (Fig. 4C). Since we know that in each amplification cycle, the target doubles exponentially, and the Ct value is inversely related to the content of starting material. To calculate the reduction of bacterial numbers in the samples, we generated a qRT-PCR standard curve (Fig. 4D). Comparing the analyzed data with this curve, the initial and final average Ct value of S. aureus was 31 and 35 (p < 0.01), which corresponded to 1.6×104 CFU/ml and 1 × 103 CFU/ml, respectively. Furthermore, MRSA’s initial and final average Ct value was 32 and 37 (p < 0.001), which corresponded to 1 × 104 CFU/ml and 3.2 × 102 CFU/ml, respectively. Based on the Ct values in this study, we can conclude that α-viniferin treatment did not significantly change the microbiota, but the prevalence of S. aureus, including MRSA, changed significantly. These findings demonstrated the specific antimicrobial effectiveness of α-viniferin against S. aureus and MRSA.

Fig. 4.

qRT-PCR-based quantification. Nares swab samples of 0 and 10th days were collected, following by DNA extraction and qRT-PCR was performed. Antimicrobial activity of α-viniferin (A, B, C) was determined by comparing the resulting Ct value with the standard curve (D) against normal flora, S. aureus, and MRSA, respectively. The experiments were carried out 3 times, and the data are given as mean values and standard deviations. * Statistical significance vs. drug-free control using unpaired two-tailed Students’ t-test (*p < 0.05, **p < 0.01, ***p < 0.001).

NGS-based 16s rRNA profiling. To determine the whole bacterial composition throughout the α-viniferin-treatment period, we did 16S rRNA amplicon sequencing. Based on the results, the Staphylococcaceae family and Staphylococcus genus were the most abundant in the nares, covering 51.04% and 51.03% of the whole microbial community. After α-viniferin treatment, we observed that the organisms decreased from 51.04% to 23.99% at the family level and 51.03% to 23.99% at the genus level (Fig. 5).

Fig. 5.

NGS-based 16S rRNA profiling. To know the whole bacterial composition throughout the α-viniferin treatment, we conducted 16S rRNA amplicon sequencing with 0th (α-viniferin-free) and 10th days (α-viniferin treated) nasal swab samples, and the resulting data was analyzed by Ezcloud software. Staphylococcaceae is the most dominant family, which decreased from 51.04% to 23.99% (A), and Staphylococcus is the most abundant among the genus level group that reduced from 51.03% to 23.99% (B) after the α-viniferin treatment.

Exploring α-viniferin-induced gene expression in S. aureus. We verified the integrity of extracted total RNA by the sharpness of the ribosomal RNA bands visualized on the 2% agarose gel using ethidium bromide. We observed distinct 23S and 16S rRNA bands without degradation in all samples tested (Fig. S1). Then, we did transcriptional profiling of S. aureus using 2,842 whole-genome RNA sequencing to measure the effects of α-viniferin relative to a sample of logarithmically growing S. aureus. Compared with the drug-free control group, 583 (1 × MIC, 8 h) and 1,057 (2 × MIC, 8 h) genes had expression levels altered 2-fold. When the FC cutoff was raised to 5-fold, we found that 94 (1 × MIC, 8 h) and 256 (2 × MIC, 8 h) genes had altered expression levels in the α-viniferin-treated group (Table II). To better understand the transcriptional response of S. aureus to α-viniferin, we adopted more specific functional classifications. We used a hypergeometric distribution to determine whether the enrichment of genes within a particular functional category in response to α-viniferin-treatment was significant. We observed that protein synthesis, transport, and binding proteins, protein fate, amino acid biosynthesis, cellular processes; transport and binding proteins, biosynthesis of cofactors, prosthetic group, and carriers, cellular processes, and DNA metabolism functional groups were significantly reduced five-fold when the bacteria were treated with a drug at a concentration equal to 2× MIC (Table III). These results demonstrated how α-viniferin inhibited the growth of the Staphylococcus group.

Number of genes (FC cutoff > 2 and 5) regulated in S. aureus by 1× and 2× MIC α-viniferin treatment for 8 hours at 37°C,

according to functional class.

Functional classificationTotal number of genes2-fold5-fold
1 × MIC2 × MIC1 × MIC2 × MIC
updownupdownupdownupdown
  1 DNA metabolism  92    9    2  20  11    2    0    2    0
  2 Energy metabolism126  10  17  22  31    1    5    5  11
  3 Protein synthesis  85    5    4a  12  15    0    0    1    1
  4 Transport and binding proteins195  29b  32b  42a  48b    4    4  16b  19
  5 Protein fate  77    5    4a  13  10    2    1    6    1
  6 Amino acid biosynthesis  62  13b    5  25    5a    3a    2  11    2
  7 Signal transduction  13    0    3    0    3    0    0    0    2
  8 Purines, pyrimidines, nucleosides, and nucleotides  37    1    5    2    7    1    0    1    2
  9 Regulatory functions; Signal transduction    9    0    2    1    4    0    1    0    1
10 Cellular processes  90    9  11  15  21    0    5    5    8
11 Biosynthesis of cofactors, prosthetic groups, and carriers; Transport and binding proteins    3    0    2    0    2    0    1    0    1
12 Central intermediary metabolism  21    1    4    6    7    0    2    1    3
13 Regulatory functions  55    3    8    6  11    1    1    1    3
14 DNA metabolism; Regulatory functions; Cellular processes    1    0    0    0    0    0    0    0    0
15 Cell envelope  50    4    4    8  11    0    0    1    1
16 Cellular processes; Transport and binding proteins  13    5b    2    5    1    2a    0    3a    0
17 Energy metabolism; Purines, pyrimidines, nucleosides, and nucleotides    2    0    0    0    1    0    0    0    0
18 Transcription  22    1    2    3    3    0    0    0    1
19 Biosynthesis of cofactors, prosthetic groups, and carriers  99    8    7a  25a  13a    1    3    6    2
20 Protein fate; Energy metabolism    4    0    1    1    1    0    0    0    1
21 Fatty acid and phospholipid metabolism  24    0    2    3    3    0    0    0    0
22 Transport and binding proteins; Signal transduction  10    0    2    2    3    0    0    0    1
23 Hypothetical proteins  26    3    3    5    4    1    1    3    3
24 Cell envelope; Central intermediary metabolism    1    0    0    0    0    0    0    0    0
25 DNA metabolism; Mobile and extrachromosomal element functions    3    1    0    1    0    0    0    1    0
26 Cellular processes; DNA metabolism    8    0    2    1    4a    0    0    0    0
27 Protein fate; Transport and binding proteins    1    0    0    0    0    0    0    0    0
28 Regulatory functions; Purines, pyrimidines, nucleosides, and nucleotides    1    0    0    0    0    0    0    0    0
29 Protein fate; Cellular processes    6    1    0    1    0    0    0    0    0
30 Energy metabolism; Central intermediary metabolism    1    0    0    0    0    0    0    0    0
31 Regulatory functions; Cellular processes    2    0    1    0    1    0    0    0    0
32 Signal transduction; Regulatory functions    1    0    0    0    0    0    0    0    0
33 DNA metabolism; Cellular processes    3    0    1    1    1    0    0    0    0
34 Biosynthesis of cofactors, prosthetic groups, and carriers; Central intermediary metabolism    1    0    0    1    0    0    0    0    0
35 Mobile and extrachromosomal element functions  32    1    1    5    1    0    0    0    0
36 Protein synthesis; Cellular processes; Regulatory functions    1    0    0    0    0    0    0    0    0
37 Cellular processes; Cell envelope    2    0    0    0    0    0    0    0    0
38 Transport and binding proteins; Cellular processes    2    0    0    0    0    0    0    0    0
39 Protein fate; Cell envelope    3    0    1    1    0    0    0    0    0
40 Cell envelope; Cellular processes    4    0    0    1    1    0    0    0    0
41 Cell envelope; Transport and binding proteins    4    1    0    1    0    0    0    0    0
42 Regulatory functions; Transport and binding proteins    2    0    0    0    1    0    0    0    0
43 DNA metabolism; Regulatory functions    3    0    0    0    0    0    0    0    0
44 Cellular processes; Protein fate    4    0    0    0    1    0    0    0    0
45 Mobile and extrachromosomal element functions; Regulatory functions    3    0    1    0    1    0    0    0    1
46 Mobile and extrachromosomal element functions; Hypothetical proteins    2    0    0    0    0    0    0    0    0
47 Protein fate; Signal transduction    3    0    1    1    1    0    0    0    0
48 Regulatory functions; Amino acid biosynthesis    2    0    1    0    0    0    0    0    0
49 Purines, pyrimidines, nucleosides, and nucleotides; Central intermediary metabolism    1    0    0    0    0    0    0    0    0
50 Protein synthesis; Biosynthesis of cofactors, prosthetic groups, and carriers    1    0    0    0    0    0    0    0    0
51 Regulatory functions; Central intermediary metabolism    2    0    1    0    1    0    0    0    0
52 Protein fate; Regulatory functions    3    0    0    2    0    0    0    0    0
53 Regulatory functions; Energy metabolism    1    0    1    0    0    0    0    0    0
54 Mobile and extrachromosomal element functions; Protein fate    1    0    0    1    0    0    0    0    0
55 Regulatory functions; Central intermediary metabolism; Signal transduction    1    0    1    0    1    0    1    0    1
56 Central intermediary metabolism; Cell envelope    1    0    0    0    0    0    0    0    0
57 Cellular processes; Mobile and extrachromosomal element functions    4    0    0    0    0    0    0    0    0
58 Protein fate; Purines, pyrimidines, nucleosides, and nucleotides    1    0    1    0    1    0    0    0    1

a – p < 0.05; b – p < 0.01; c – p < 0.001

Number of (FC cutoff > 2 and 5) specific regulated gene groups in S. aureus by 1 × and 2 × MIC α-viniferin treatment for 8 hours at 37°C,

according to functional classification.

Functional classificationTotal number of genes2-fold5-fold
1 × MIC2 × MIC1 × MIC2 × MIC
updownupdownupdownupdown
3 Protein synthesis
   a tRNA aminoacylation12  1  1  1  4  0  0  1  1
   b Ribosomal proteins: synthesis and modification25  2  3  5  4  0  0  0  0
   c tRNA and rRNA base modification37  2  0  6  4  0  0  0  0
   d Other85  9  81618  2  0  6  2
   e Translation factors  7  0  0  0  2  0  0  0  0
4 Transport and binding proteins
   a Amino acids, peptides and, amines32  5  2  7  4  0  1    4a  1
   b Cations and iron carrying compounds72  8  91210  1  0  2  3
   c Carbohydrates, organic alcohols, and acids27  4  6  7  8  1  1  3    5b
   d Anions18  4  2  510  0  1  2  5
   e Anions; Other  1  1  0  1  0  0  0    1a  0
   f Other85  9  81618  2  0  6  2
   g Nucleosides, purines and, pyrimidines  6  0  3  05b  0  1  0    3b
   h Unknown substrate20  3  6  6  6  0  0  1  2
   i Cations and iron carrying compounds; Anions  3  0  1  0  2  0  0  0  0
5 Protein fate
   a Protein and peptide secretion and trafficking27  2  2  3  5  0  0  2  0
   b Degradation of proteins, peptides, and glycopeptides18  1  0  5  0  0  0  2  0
   c Protein modification and repair20  0  0  0  3  0  0  0  0
   d Protein folding and stabilization  42a  1  2  12b  1    2a  1
   e Degradation of proteins, peptides, and glycopeptides; Protein folding and stabilization  6  0  0  3  0  0  0  0  0
   f Degradation of proteins, peptides, and glycopeptides; Protein modification and repair  1  0  0  0  0  0  0  0  0
   g Protein and peptide secretion and trafficking; Protein modification and repair  1  0  1  0  1  0  0  0  0
6 Amino acid biosynthesis
   a Aspartate family15  3  18b  0  1  0    3a  0
   b Serine family11  3  0  4  2  0  0  1  0
   c Glutamate family  7  03a  0  2  0  1  0  1
   d Pyruvate family125b  1  8  1  0  1  5  1
   e Histidine family  8  0  0  2  0  0  0  0  0
   f Aromatic amino acid family  9  2  0  3  02b  0  2  0
16 Cellular processes; Transport and binding proteins
   a Toxin production and resistance; Other13  3  1  4  12a  0    3a  0
   b Toxin production and resistance; Unknown substrate  32a  1  1  0  0  0  0  0
   c Detoxification; Other  1  0  0  0  0  0  0  0  0
19 Biosynthesis of cofactors, prosthetic groups, and carriers
   a Glutathione and analogs  4  0  0  1  1  0  0  0  0
   b Menaquinone and ubiquinone17  0  0  3  1  0  0  0  0
   c Other85  9  81618  2  0  6  2
   d Heme, porphyrin, and cobalamin19  3  27a  2  0  1  2  1
   e Folic acid  6  0  0  0  0  0  0  0  0
   f Pyridoxine  2  02a  02a  0  2  0  0
   g Riboflavin, FMN, and FAD  6  0  0  2  0  0  0  0  0
   h Thiamine  7  0  0  0  2  0  0  0  0
   i Lipoate  1  0  0  0  0  0  0  0  0
   j Other; Thiamine; Pyridoxine  2  0  0  0  0  0  0  0  0
   k Pantothenate and coenzyme A  6  0  1  1  1  0  0  0  0
   l Biotin  6  2  04a  0  1  02a  0
   m Pyridine nucleotides  2  0  0  0  0  0  0  0  0
   n Molybdopterin  4  1  0  2  0  0  0  0  0
26 Cellular processes; DNA metabolism
   a Cell division; Chromosome-associated proteins  8  0  2  14a  0  0  0  0

– p < 0.05; b – p < 0.01; c – p < 0.001

Discussion

In a 10-day clinical trial, we investigated the decolonization efficiency of α-viniferin as an S. aureus-specific drug candidate. Before the clinical trial, we checked the specific toxicity of α-viniferin and two other reference drugs against 20 bacterial isolates. α-Viniferin showed excellent antibacterial effectiveness against the Staphylococcus group. On the other hand, several reports showed VAN resulted in rapid depletion of intestinal microflora and significantly promoted the growth of vancomycin-resistant bacteria (Edlund et al. 1997; Isaac et al. 2016) highlighting the drawbacks of VAN even though it was the most effective anti-Staphylococcus reference drug in the present MIC study. We have also tested MET as another reference drug.

In this study, we analyzed the nasal swab samples through culture-based techniques to investigate the antimicrobial effectiveness of α-viniferin against the nares normal microflora, S. aureus, and MRSA. α-Viniferin was active against S. aureus and MRSA but showed no activity against nasal microflora. To further confirm this, we did qRT-PCR using S. aureus- and MRSA-specific primers since precise detection and quantification are achievable by using this technique. Expectedly, α-viniferin was active against S. aureus and MRSA while preserving the resident nasal microflora. Moreover, α-viniferin improved the skin moisture content, which is essential in maintaining skin plasticity and barrier integrity without toxicity.

In addition, we used NGS-based 16S rRNA profiling to investigate further the clinical efficiency of α-viniferin against the Staphylococcus group. We also evaluated the effect of α-viniferin against normal nasal microflora using NGS, where NGS upgrades DNA sequencing methodology to the next level through parallel sequencing processes that enable the simultaneous sequencing of different DNA fragments while providing precise identification results (Abayasekara et al. 2017). The NGS results demonstrated Staphylococcus as the most dominant group in the anterior nares, supporting similar published findings (Hogan et al. 2016; Warnke et al. 2016; Lu et al. 2018). α-Viniferin drastically reduced the number of Staphylococcus in the anterior nares, while the decrease in the number of other bacteria groups was statistically insignificant. The important thing is that α-viniferin significantly decreased the Staphylococcus group. This molecular approach provides evidence of the antimicrobial specificity of α-viniferin as a pathogen-specific potential drug, and the results were consistent with the culture and qRT-PCR-based findings. The results were also in agreement with a previous study finding that demonstrated the in vitro activity of α-viniferin against MRSA (Seo et al. 2017).

RNA sequencing technology is a powerful tool for studying the molecular basis of genetic interactions; it makes it possible to examine the relatively unbiased measurements of expression levels across the entire length of a transcript using high-throughput sequencing platforms (Pickrell et al. 2010). In the present study we did RNA sequencing to understand α-viniferin-induced gene expression in S. aureus. Our results showed that α-viniferin inhibits the growth of S. aureus, which may be attributed to its effects on some of the gene groups mentioned. Further research is required to elucidate this finding. In conclusion, we demonstrated the clinical efficiency of α-viniferin as a potential S. aureus-specific drug candidate for the first time through a clinical trial.

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Life Sciences, Microbiology and Virology
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