REVERSE AGING IN SACCHAROMYCES CEREVISIAE THROUGH REDUCED TOR1 EXPRESSION AND REPLICATIVE LIFE SPAN MODELLING WITH CELL VIABILITY ASSESSMENT USING PHYTOCHEMICAL EXTRACTS ALPINIA GALANGAL, COMMIPHORA MUKUL, ACORUS CALAMUS AND MORSHELLA ESCULENTAHTML Full Text
REVERSE AGING IN SACCHAROMYCES CEREVISIAE THROUGH REDUCED TOR1 EXPRESSION AND REPLICATIVE LIFE SPAN MODELLING WITH CELL VIABILITY ASSESSMENT USING PHYTOCHEMICAL EXTRACTS ALPINIA GALANGAL, COMMIPHORA MUKUL, ACORUS CALAMUS AND MORSHELLA ESCULENTA
Nilanjana Prasad and Kashish Gupta *
Department of Biotechnology & Microbiology, Noida International University, Greater Noida, Uttar Pradesh, India.
ABSTRACT: To study reverse aging in Saccharomyces cerevisiae (S. cerevisiae) by gene expression analysis of target of rapamycin (TOR1) induced autophagy and replicative life span modelling (RLS) using Alpinia galangal (A. galangal), Commiphora mukul (C. mukul), Acorus calamus (A. calamus) and Morshella esculenta (M. esculenta). Methanolic extraction of plants was carried out using maceration. Activation of yeast was performed using the sugar fermentation method. Pharmacological anti-aging screens in yeast performed by RLS. Primers for Actin (ACT1) and TOR1 were designed using Primer-BLAST. Gene expression analysis (RNA isolation and quantification, reverse transcription, and real-time polymerase chain reaction) of TOR1 in S. cerevisiae was conducted using methanolic extracts. Phenolic and Flavonoid compounds were quantified using reversed-phase high-performance liquid chromatography (RP-HPLC). Cell counting and viability assessment of S. cerevisiae with trypan blueusing methanolic extracts was performed. Gene expression analysis results revealed under expression of TOR1 in S. cerevisiae with mean normalized expression ratios < 1 using all four methanolic extracts. Results from RLS showed increased absorbances due to decreased TOR1 activity. HPLC analysis showed the presence of antioxidants such as vanillic acid, caffeic acid, rutin, and quercetin in crude extracts. Cell viability assessment revealed nontoxicity effects of M. esculenta and A. galangal whereas toxicity effects of A. calamus and C. mukul on S. cerevisiae cells. Reverse aging in S. cerevisiae was studied by gene expression analysis of TOR1 and RLS. TOR1 gene role in the activation of autophagy was explored using real-time polymerase chain reaction.
Keywords: Reverse aging, Target of rapamycin, Replicative life span, S. cerevisiae, Cell viability
INTRODUCTION: Autophagy, an evolutionary conserved catabolic process, involves the degradation of aberrant biomolecules, organelles, etc., including the elimination of aging cells by replacement with new cells and proteins required for maintaining cellular homeostasis 1.
Aging has been characterized by the gradual failure over time in physiological functions, leading to an assemblage of molecular and cellular damage (autophagy decreases with age) with loss of physiological function 2.
The yeast, S. cerevisiae was chosen as a model organism to study reverse aging because it has been reported that there are several conserved hallmarks of aging between yeast and humans, remarkedly autophagy by a pharmacological screening method known as RLS, which provided a measure of several mitotic events an individual mother cell could undertake before senescence in many eukaryotes 3, 4. TOR proteins are highly evolutionary conserved proteins throughout eukaryotes activated in response to nutrient sensors; orthologous to human mTOR (mechanistic target of rapamycin kinase). TOR1, a phosphatidylinositol kinase homologue; part of TORC1 complex in S. cerevisiae is involved in several metabolic processes, remarkedly in inhibition of autophagy 5, 6. Rapamycin (Sirolimus) increased lifespan by activating autophagy through mTOR inhibition in various model organisms. Studies have reported that reduced signalling (inhibition /decreased expression) of the TOR pathway, achieved by either genetic or pharmacological means, resulted in increased lifespan by up-regulation of autophagy in many organisms including yeast 6, 7, 8, 9, 10. Several plant antioxidants, such as resveratrol have been extensively studied earlier for lifespan extension via the induction of autophagy 11, 12.
Amongst the various medicinal plants, we have chosen plants, viz., A. galangal, C. mukul, A. calamus and M. esculenta. A. galangal commonly known as kulanjan and greater galangal is found in Western Ghats, Malabar coasts and Gujrat in India. The rhizome of A. galangal has antioxidant and antiaging activities 13, 14, 15. C. mukul commonly known as guggul and Indian bdellium, is found in arid regions of India, Assam, Karnataka, etc. Oleo-gum resin secreted by C. mukul has antioxidant and anti-aging activities 16, 17. A. calamus, commonly known as vacha and sweet flag is found in areas of Jammu and Kashmir, Himachal Pradesh etc., in India. The rhizome of A. calamus exhibited antioxidant activity 18. M. esculenta is one of the costliest edible morels commonly known as gnocchi and morel found in the North-West Himalayas mainly, Kashmir renowned for their gastronomic quality and nutritional health benefits due to their anti-oxidative properties 19. Earlier, fungus such as Aspergillus niger has been studied using our selected plant A. galangal 20. It was reported that S. cerevisiae autophagy was induced by starvation 21. The present study evaluates gene expression of TOR1 in the absence of starvation and RLS with cell viability assessment in S. cerevisiae using methanolic extracts A. galangal, C. mukul, A. calamus, and M. esculenta. Pharmacological activation of autophagy through medicinal plants by under expression of TOR1 would cause depletion of damaged cells which will pave way for stem cell development and rejuvenation of new cells which might be a realistic and promising treatment for reverse aging.
MATERIALS AND METHODS:
Sample Collection: A. calamus rhizome was collected from Himachal Pradesh (India), M. esculenta mycelia were collected from Uttarakhand (India), A. galangal rhizome and C. mukul gum were collected from Karnataka (India).
Extract Preparation: Samples were thoroughly cleansed with distilled water and air dried to remove moisture and ground into a coarse powder. For methanolic extraction, 10g powder of all four plant samples was mixed with 40ml solvent to attain a minimum concentration of 250mg/ml, followed by maceration with occasional shaking for 5 days at room temperature with 100% methanol. The extracts were filtered and evaporated to obtain the crude extracts. All the extracts were preserved at 4°C for a further 22.
Growth of Yeast by Sugar Fermentation: Beaker was filled with distilled water (100ml) and microwaved until warmed. Sucrose (1g) was added to the prewarmed water, and the sugar solution was microwaved until boiled. The mixture was cooled at room temperature, followed by adding baker’s yeast (0.5g) and mixed properly for yeast activation.
RLS Modelling in S. Cerevisiae: Activated yeast was streaked on sterilized Potato Dextrose Agar media (PDA; 0.2g potato extract, 2g dextrose, and 0.4g agar in 50ml of distilled water) followed by an incubation of 48 -72 hours; pH 5.6 ± 0.2). Single colonies were inoculated into sterilized Potato Dextrose Broth media (PDB; 0.4g potato extract and 4g dextrose in 100ml of distilled water; pH 5.6 ± 0.2) followed by incubation at 36°C for 48 hours along with constant agitation using an orbital shaker incubator 23.
Forty-eight hours old yeast cultures (5ml) were distributed in five test tubes first test tube contained only yeast culture marked as a control sample. In contrast, the other four test tubes consisted of four methanolic extracts (1ml) and were incubated at 36°C with unvarying agitation for 20 days. Absorbance was recorded at 600 nm by spectrophotometer in triplicates 24.
RNA Isolation and Quantification: RNA was isolated from yeast previously incubated with four methanolic plant extracts and with a control sample (only yeast) using TriXtractTM RNA isolation method manufacturer’s instructions. Qualitative analysis of isolated RNA was performed using 1.5% (w/v) Tris-borate-EDTA (TBE) - agarose gel electrophoresis at 100°C.
The gel was visualized with UV transilluminator at 302nm to obtain the image. RNA concentration and purity were assessed by determining the absorbance of RNA in RNase-free water at 260nm and 280nm using spectrophotometer. RNA yield was evaluated based on absorbance at 260 nm (A260). The ratio A260/A280 was assessed to calculate RNA purity.
Reverse Transcription: RNA (288-336µg/ml) from each sample was retrotranscribed to complementary DNA (cDNA). Briefly, the assay was performed with total RNA (5µl), Oligo (dT)16 (2µl), and sterile RNase- free water to make a final volume of 14µl. The mixture was heated to 65°C for 5 minutes and immediately chilled on ice. It was followed by the addition of Moloney murine leukemia virus (MMLV) buffer (5X) (4µl), dNTPs (2µl), RNAsin (0.5µl), M-MLV (1µl) followed by incubation at 42°C for 60 minutes and successively heated up to 95°C for 15 minutes. Finally, the samples were chilled on ice for downstream experiments or stored at -20°C.
Primer Designing: ACT1 and TOR1 sequences were retrieved from NCBI data bank. Primers were designed and checked for specificity using Primer-BLAST software.
Polymerase Chain Reaction (PCR): To check the specificity of the designed primer pairs, conventional PCR amplification was carried out from cDNA template in a final volume (50µl) consisting of master mix (25μl), cDNA (5µl), each forward and reverse primer (1µl) (10mM) and nuclease-free water (18µl) in a thermal cycler.
The PCR thermal profile was 95°C for 3 minutes, 95°C for 20 seconds, 50°C (Act1) / 56°C (TOR1) for 20 seconds, 72°C for 40 seconds for 40x, 72°C for 3 minutes 4°C for 10 minutes.
Real-Time PCR (qPCR) Analysis: qPCR was conducted using a thermal cycler ABI PRISM 7000 sequence detection system. Amplifications were carried out in a final volume of 50μl, reaction solutions containing Kappa SYBR Fast Master Mix (25μl) (2X) with ROX reference dye, Primer F (2.0µl) (10mM), Primer R (2.0µl) (10mM), cDNA (5.0µl), nuclease-free water (16µl). The experiment was performed in triplicates for each test sample and control sample in a 96-well plate. qPCR conditions were used with an activation step of 2 minutes at 95°C followed by an initial denaturation step of 5 minutes at 95°C followed by 40 cycles of 95°C for 10 seconds, 52°C for 20 seconds, and 72°C for 10 seconds. Optimization of annealing temperatures and primer concentrations was done, and it confirmed that primer sets performed well as single plex. Standard curve assays were conducted to determine assay sensitivity, efficiency, and reproducibility of the assay at various concentrations of cDNA using initial concentration (N0) 1ng and five 1: 2 serial dilutions (0.5ng, 0.250ng, 0.0625ng, 0.015625ng, and 0.0009765625ng). Normal yeast cells were selected as a biological control in standard curve assay. Primers with amplification efficiency below 90% and above 110% were not considered. Gene expression variations were evaluated regarding fold induction concerning the normal yeast cells by 2-ΔΔCt comparative Ct method 25. The real-time data analysis was conducted with ABI Prism 7000 SDS software, Data analysis gene expression (DAGE), LinReg, and Excel.
HPLC Preparation of Standards: Commercial standard compounds consisting of four phenolics and two flavonoid compounds namely: gallic acid, vanillic acid, caffeic acid, resveratrol, quercetin, and rutin were purchased. Working standard solutions (30µg/ml) were prepared in HPLC-grade methanol from the standard stock solution (100µg/ml) and stored in HPLC vials until use.
HPLC Sample Preparation: Samples (1.5ml) were briefly vortexed and centrifuged at 10000g for 10 minutes to collect the supernatant. Subsequently, the supernatant was sonicated for 30 minutes at 30°C and successively filtered through a filter (pore size 0.45µm), pre-washed with 70% ethanol, and stored in HPLC vials before injection in the sample loop.
Chromatographic Conditions: HPLC analysis of methanolic crude extracts was performed on a reverse phase Zorbax Eclipse XDB-C18 column (4.6 × 150mm, 5μm particle). The injection volume of samples was 20μl. Methanol: phosphate buffer (pH 6.8) was used as mobile phase adjusted with orthophosphoric acid solution 0.5%, v/v) in MilliQ water (63:37%, v/v) and filtered through a 0.22μm nylon membrane and ultrasonically degassed before use at a flow rate of 1ml/min in an isocratic mode and the column temperature was thermostatically stable at 30°C. The total runtime was 4 minutes. Detection wavelengths of different standard compounds were as follows: 254nm for vanillic acid, 320nm for caffeic acid, 307nm for resveratrol, 350nm for quercetin, 278nm for gallic acid and 256nm for rutin, respectively 24, 25, 26. Identification of phenolic and flavonoid compounds was based on their respective retention times (RT) compared with commercial standards. Values for a limit of detection (LOD) and limit of quantification (LOQ) were calculated to identify and quantify phenolic, and flavonoid compounds in the extracts. The experiment was performed in independent triplicates. Data analysis was performed using MS Excel. The concentration of antioxidants was calculated from the concentration obtained by HPLC (µg/ml) divided by the weight of the plant sample (g), initially mixed with the volume of solvent (ml) for extraction.
Concentration (ug/g) = Concentration calculated (ug/ml)) / (weight of plant (g) / volume of solvent (ml)
Cell Counting and Viability Assessment of S. Cerevisiae: Aqueous plant extracts (0.2ml) were prepared and mixed with freshly activated yeast culture (0.5ml) for 20 days incubation. The resulting mixed aqueous extracts and freshly prepared control sample (S. cerevisiae) (0.1ml) were separately mixed with commercially available trypan blue dye (0.01ml) on a glass slide and immediately observed under a microscope. An appropriate amount of mixture (2µl) was then applied at the center of the hemocytometer using a micropipette. The mixture was drawn into the chamber by capillary action and left to sit for 2-3 minutes before counting. The cells in all 9 squares were counted in the order of “S.” according to the conventional counting principle wherein cells on the top and the left boundaries are counted, whereas, cells on the bottom and the right boundaries are not counted 27. Cells were manually counted using a 40× objective, and snapshot images were taken. With the supposition that dead cells retain stain while viable cells unretain stain, viable transparent (unstained), and dead blue (stained) cells were counted. Concentration was calculated, and cell viability, viable and dead cells were calculated using the following equations 28:
Cell Viability = (Number of viable cells) / (Number of dead cells)
Viable cells (%) = (Number of live cells) / (Total number of cells) ×100
Dead cells (%) = (Number of dead cells) / (Total number of cells) × 100
Statistical Analysis: Methods such as replicative life span modelling and RNA quantification were analyzed by one-way ANOVA: Single factor. For HPLC, a t-test: paired two samples for mean was used. Significance was set at P< 0.05 unless otherwise stated.
Growth of S. Cerevisiae: S. cerevisiae activated using sugar fermentation Fig. 1A. Single colonies appeared on PDA media Fig. 1B, and yeast culture obtained using PDB media Fig. 1C.
FIG. 1: S. CEREVISIAE GROWTH. (A) ACTIVATION OF YEAST IS CHARACTERIZED BY THE RELEASE OF ETHANOL AND FOAMING CAUSED BY CO2 BUBBLES. (B) SINGLE COLONY ISOLATION (C) YEAST CULTURE
RLS of S. Cerevisiae: Methanolic extracts with yeast cultures for studying RLS in yeast ae shown in Fig. 2 and Table 1.
FIG. 2: SAMPLES IN TRIPLICATES. (A) L-R: TEST TUBES (1-3): CONTROL (YEAST), (4-6): A. GALANGAL + YEAST, (7-9): C. MUKUL + YEAST (B) L-R: TEST TUBES (1-3): A. CALAMUS + YEAST, (4-6): M. ESCULENTA + YEAST
TABLE 1: REPLICATIVE LIFE SPAN
|Samples||Absorbance at 600nm|
|Control||0.012 ± 0.002|
|A. galangal||1.054 ± 0.001|
|C. mukul||0.335 ± 0.003|
|A. calamus||1.053 ± 0.002|
|M.esculenta||0.105 ± 0.024|
Values are represented as Mean ± S.D. (n=5) and analyzed by one-way ANOVA: Single factor statistical method (P 0.00028).
Qualitative and Quantitative Assessment of RNA: Fig. 3 shows an agarose image of isolated RNA from S. cerevisiae and a quantitative analysis of RNA Table 2.
FIG. 3: RNA QUALITATIVE ANALYSIS. DENATURING AGAROSE GEL ELECTROPHORESIS OF TOTAL EXTRACTED RNA (7ΜL) STAINED WITH ETHIDIUM BROMIDE. FOR THE POSITIVE CONTROL, TOTAL RNA WAS EXTRACTED FROM S. CEREVISIAE
TABLE 2: ANALYSIS OF RNA CONCENTRATION, YIELD AND PURITY
|Samples||Concentration of RNA sample (µg/ml ± S.D)||Total yield (µg ± S.D)||Purity (%)|
|Control||288 ± 13.063||20.16 ± 0.914||1.942 ± 0.212|
|A. galangal||336 ± 14.236||23.52 ± 0.996||2.120 ± 0.531|
|C.mukul||290.666 ± 11.469||20.346 ± 0.802||1.934 ± 0.187|
|A. calamus||292 ± 8.640||20.44 ± 0.604||2.050 ± 0.112|
|M.esculenta||332 ± 6.531||23.24 ± 0.457||2.166 ± 0.068|
Values are represented as Mean ± S.D. (n=5) and analyzed by one-way ANOVA: Single factor statistical method (P 0.0021).
Primer Designing: Primers for TOR 1 and ACT1 were designed as shown in Table 3. TOR1 showed significant homology only to S. cerevisiae, whereas ACT1 was not only specific to S. cerevisiae but also to Torulaspora delbrueckii and Scheffersomyces stipites.
TABLE 3: PRIMER PARAMETERS FOR ACT1 AND TOR1
|Name /Gene ID||Gene Description||Accession number
|Sequence (5'->3')||Tm (°C)||GC (%)||Amplicon length (bp)|
|TOR1||Phosphatidylinositol kinase-related protein kinase TOR1 [Saccharomyces cerevisiae S288C]||NM_001181724.1||F: TTACCACAC
|ACT1||Actin[Saccharomyces cerevisiae S288C]||NM_001179927.1||F:TCGTTCCAATTTACGCTGGTT
R: CGGCCAAATCG ATTCTCAA
TOR1: target of rapamycin, ACT1: actin, Tm: melting temperature, GC: guanine-cytosine, F: forward, R: reverse, bp: base pairs
Gene Expression Studies: Amplification plot and standard curves were generated from cDNA dilutions Fig. 4. Relative quantification of TOR1 among test samples shown in Table 4 and Fig. 5.
FIG. 4: REGRESSION CURVES (A) LOG AMPLIFICATION CURVE PLOTTED WITH FLUORESCENCE AGAINST CYCLE NUMBERS (B) STANDARD CURVES WITH CT PLOTTED AGAINST LOG OF STARTING QUANTITY OF CDNA. EQUATION FOR THE REGRESSION LINE AND COEFFICIENT OF DETERMINATION (R2) ARE SHOWN. PCR EFFICIENCY FOR ACT1 AND TOR1 94.31% AND 100.36%
TABLE 4: RELATIVE QUANTIFICATION OF TOR1 IN S. CEREVISIAE
|Parameters||Control||A. galangal||C. mukul||A. calamus||M. esculenta|
|Negative ∆∆ Ct||0||-8.2
|Normalized expression ratio (2-∆∆Ct)||1
|Mean (2-∆∆Ct)||1||0.003 ± 0.001||0.001 ± 0.001||0.005 ± 0.006||0.006 ± 0.001|
TOR1: target of rapamycin, ACT1: actin, CT: cycle threshold. Values expressed as Mean± S.D.
FIG. 5: RELATIVE COMPARISON OF TOR1 EXPRESSION AMONG SAMPLES. NORMALIZED EXPRESSION RATIO / FOLD DECREASE VALUES OF TOR1 IN S. CEREVISIAE IN THE PRESENCE OF TEST SAMPLES (METHANOLIC EXTRACTS)
HPLC of Standards and Crude Extracts: Chromatograms of standard antioxidants and samples are shown in Fig. 6 and Fig. 7. Standard parameters for phenolics and flavonoids are shown in Table 5. Antioxidants in plant extracts were identified, and their concentrations were calculated in Table 6.
FIG. 6: HPLC CHROMATOGRAMS OF STANDARD PHENOLICS AND FLAVONOIDS (A) CAFFEIC ACID (RT: 14.852 MIN) (B) GALLIC ACID (RT: 16.092 MIN) (C) VANILLIN (RT: 9.968 MIN) (D) RUTIN (RT: 13.728 MIN) (E) RESVERATROL (RT: 12.588 MIN) (F) QUERCETIN (RT: 7.92 MIN)
FIG. 7: HPLC CHROMATOGRAMS OF SAMPLES (A) A. GALANGAL EXTRACT (VANILLIC ACID AT 9.820 MIN) (B) C. MUKUL (VANILLIC ACID AT 9.968 MIN) (C) A. CALAMUS (QUERCETIN AND VANILLIC ACID AT 8.068 AND 9.864 MINS) (D) M. ESCULENTA (VANILLIC ACID, RUTIN, AND CAFFEIC ACID AT 9.988, 13.472 AND 15.064 MINS)
TABLE 5: ANALYTICAL PARAMETERS FOR HPLC ANALYSIS
|Standards||Detection wavelength (nm)||RT (min)||m||c||R2||LOD (µg/ml)||LOQ (µg/ml)|
|Gallic acid||278||16.001 ± 0.09||24.701||911.5||1||0.256||0.855|
|Vanillic acid||254||9.966 ± 0.001||2.475||584.49||1||0.296||0.988|
|Quercetin||254||7.92 ± 0.02||3.558||97.468||1||0.154||0.514|
RT: retention time, m: slope, c: intercept, R2: regression coefficient, LOD: limit of detection, LOQ: limit of quantification. Values expressed as Mean ± S.D.
TABLE 6: HPLC QUANTIFICATION OF STANDARD COMPOUNDS IDENTIFIED IN PLANTS
|Antioxidant standards||A. galangal||C.mukul||A. calamus||M. esculenta|
|Caffeic acid||nd||nd||nd||10.990 ± 0.001|
|Vanillic acid||17.652 ± 0.017||27.439 ± 0.0005||13.206 ± 0.0005||20.393 ± 0.001|
|Quercetin||nd||nd||150.017 ± 0.003||nd|
|Rutin||nd||nd||nd||9.720 ± 0.002|
n.d.: not detected. Values expressed as Mean ± S.D. in (µg/g)and analysed by t-test: paired two sample for means; significant at (P<0.05).
Cell Viability of S. Cerevisiae: S. cerevisiae live and dead cells were observed from trypan blue staining Fig. 8.
Concentration and cell viability values were obtained for control and test samples Table 7.
FIG. 8: IMAGES OF YEAST CELLS TAKEN FROM 9 SQUARES OF HEMOCYTOMETER IN WHICH DEAD CELLS ARE INDICATED BY BLUE COLOR AND LIVE CELLS ARE UNSTAINED. (A) YEAST AS CONTROL (B) YEAST+ A. GALANGAL (C) YEAST +C. MUKUL (C) YEAST +A. CALAMUS (D) YEAST +M. ESCULENTA
TABLE 7: CELL VIABILITY OF S. CEREVISIAE
|Samples||Concentration (cells/ml)||Viable cells (%)||Dead cells (%)||Cell viability|
DISCUSSION: S. cerevisiae has been proven to be an appropriate reverse aging model because we have provided evidence about reduced TOR1 activated autophagyon lifespan extension of yeast without starvation by all four methanolic plant extracts A. galangal, C. mukul, A. calamus and M. esculenta. Reverse aging was studied in two ways which are TOR1 gene expression analysis and RLS. Pharmacological anti-aging screens in yeast performed by RLS in S. cerevisiae in the presence of extracts showed an increase in absorbances (0.105 ± 0.024 - 1.054 ± 0.001) compared to the control yeast sample (0.012 ± 0.002) due to decrement of TOR1 activity. Gene expression studies revealed M. esculenta with the highest reverse aging effect with a mean normalized expression value of 0.006 and the lowest C. mukul with a value of 0.001.
Results from HPLC indicated the presence of vanillic acid as the major phenolic compound present in all four methanolic extracts. Only M. esculenta showed the presence of a maximum number of antioxidants consisting of vanillic acid (20.393 ± 0.001µg/g), rutin (9.720 ± 0.002µg/g), and caffeic acid (10.990 ± 0.001µg/g). Our result contradicts another study that reported the absence of vanillic acid, rutin, and caffeic acid in M. esculenta methanolic extract 29. Cell viability assay performed to check the effect of aqueous extracts on the longevity of S. cerevisiae cells showed the highest percentage of viable cells in the presence of M. esculenta extract with a value of 87.73% followed by A. galangal extract (86.67%) as compared to control yeast sample (87.05%).
These results suggested the strongest survival effect of S. cerevisiae cells conferred by M. esculenta whereas A. galangal was at the borderline. By contrast, the lowest percentage of viable cells was observed by A. calamus (28.60%) followed by C. mukul (46.51%). Cell viability studies have been reported earlier in A. calamus using methylene blue for anticancer study 30. A major controversy that the results of our study might raise is since it is proven from the results of gene expression studies that methanolic extracts of A. calamus and C. mukul elicit reverse aging effect in S. cerevisiae but results from cell viability assay are contradictory to the data that A. calamus and C. mukul are toxic to S. cerevisiae cells. Two main facts might resolve this controversy: the first is that plants make self - poisonous compounds and the second is heavy metal toxicity in plants due to their growth in contaminated areas. These two facts might be the reasons of death of S. cerevisiae cells by A. calamus and C. mukul extracts. Our study showed that M. esculenta might be a promising reverse aging herb based on gene expression studies, HPLC, and cell viability assay results. Results from HPLC showed the presence of specific phenols and flavonoids in plant extracts; however, other antioxidants might also contribute to the reverse aging property of these plants, which requires further research. Future directions for our study might be the development of natural drugs focused on improving the health of the aging population and the formulation of herbaceutical products for reverse aging using our proven extracts.
Furthermore, cultivating plants in a healthy environment free from heavy metal contamination might make the plants nontoxic to yeast cells. Alternatively, plants could be grown along the river bed so that heavy metals from plants get absorbed by water which can be treated by wastewater treatment. Moreover, the exact mechanisms by which plant antioxidants activate autophagy by reduced TOR1 remains obscure and requires further exploration. In conclusion, our bodies will be biologically younger for longer if the rate of aging could be modulated at a genetic level since aging is amenable to therapeutic manipulations, regardless of our chronological age.
ACKNOWLEDGEMENT: I cannot express enough thanks to the research lab, Allele Life Sciences, for providing the platform for conducting lab experiments and my university, Noida International University, for continued support and encouragement.
CONFLICTS OF INTEREST: The authors declare that the research was conducted without any commercial or financial assistance and declare no conflict of interest.
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How to cite this article:
Prasad N and Gupta K: Reverse aging in Saccharomyces cerevisiae through reduced tor1 expression and replicative life span modelling with cell viability assessment using phytochemical extracts Alpinia galangal, Commiphora mukul, Acorus calamus and Morshella esculenta. Int J Pharm Sci & Res 2023; 14(3): 1242-52. doi: 10.13040/IJPSR.0975-8232.14(3).1242-52.
All © 2023 are reserved by International Journal of Pharmaceutical Sciences and Research. This Journal licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
Nilanjana Prasad and Kashish Gupta *
Department of Biotechnology & Microbiology, Noida International University, Greater Noida, Uttar Pradesh, India.
03 July 2022
23 August 2022
01 September 2022
01 March 2023