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Phytochemical Composition, Antibacterial, Antioxidant and Antidiabetic Potentials of Cydonia oblonga Bark

Cydonia oblonga is a medicinal plant that is used to treat a number of health complications in traditional medication systems. The objective of this study was to evaluate the phytochemical composition, and antibacterial, antioxidant, and ant-diabetic potentials of methanolic extracts of Cydonia oblonga bark. The Cydonia oblonga bark extraction was fractionated through HPLC and seven purified fractions labeled as F1, F2, F3, F4, F5, F6, and F7 were obtained. The HPLC-UV analysis of methanolic extract showed the presence of a number of possible compounds. The GC-MS and HPLC analysis confirmed the presence of the following bioactive compounds in the crude extract and purified fractions: malic acid, mandelic acid, quercetin, caffeic acid, catechin hydrate, as morin (HPLC analysis), BIS-(2-ethylhexyl)phthalate and diisooctyl phthalate (F1), carbamide (F2, used as fertilizer), octasiloxane and dimethylsiloxanecyclictrimer (F3), silicic acid and cyclotrisiloxane (F4), 6-AH-cAMP, 4H-cyclopropa[5′,6′]benz[1′,2′,7,8]azule, and 4-(4-chlorophenyl)-3-morpholinepyrol-2-yl)-butenedioic acid (F5), isopropyamine (F6), and 1-propylhydrazine (F7). The extract and purified fractions were then tested for biological activities. All the purified fractions and methanolic extract showed effective antibacterial activity; however, the highest activity was recorded for methanolic extract against Staphylococcus aureus and Streptococcus pneumonia. Antioxidant evaluation of methanolic extract and purified fractions against DPPH showed strong % inhibition of the synthetic free radical. The methanolic extract exhibited 87.41 ± 0.54% inhibition whereas fractions showed: F1, 85.45 ± 0.85; F2, 65.78 ± 0.68; F3, 58.61 ± 0.58; F4, 80.76 ± 0.59; F5, 571.29 ± 0.49; F6, 85.28 ± 0.94; and F7, 48.45 ± 0.62% inhibition. Ascorbic acid (standard) was used as a control with 94.88 ± 0.56% inhibition at a maximum concentration of 1000 µg/mL. The α-glucosidase inhibition assay of methanolic extract and purified fractions at a maximum concentration of 1000 µg/mL showed activities as: methanolic extract, 78.21 ± 0.67; F1, 55.01 ± 0.29; F2, 56.10 ± 0.24; F3, 62.44 ± 1.03; F4, 70.52 ± 0.15; F5, 62.18 ± 0.92; F6, 72.68 ± 0.2; and F7, 57.33 ± 0.05% inhibition. α-Amylase % inhibition of methanolic extract and purified fractions were noted as: methanolic extract, 77.98 ± 0.57; F1, 79.72 ± 0.02; F2, 79.72 ± 0.02; F3, 82.16 ± 0.48; F4, 77.37 ± 0.28; F5, 72.14 ± 0.30; F6, 74.24 ± 0.29; and F7, 56.58 ± 0.10 at the highest concentration of 1000 µg/mL. Acarbose (standard) showed 87.65 ± 0.71% inhibition of α-glucosidase and 85.99 ± 0.44% inhibition of α-amylase at the highest concentration of 1000 µg/mL. It was found that all biological activities of methanolic extract and purified fractions might be attributed to the fact that they are rich sources of phenolic and flavonoids along with other bioactive compounds. The total phenolic and flavonoid contents of methanolic extract were recorded higher as compared to purified fractions (TPC = 70% and TFC = 69%). Amongst the purified fractions, fraction 6 exhibited the highest TPC value (64%), and purified fraction 1 exhibited the highest value of TFC (58%). Recent research demonstrated that Cydonia oblonga may be considered an antibacterial medicinal plant. The result of the present study revealed that it might be utilized for the isolation of bioactive phytochemicals that can lead to new opportunities in the discovery of new antibiotics.

Introduction
Much work has been carried out on studying and isolating natural compounds with pharmacological, pesticidal, and dietary benefits. Natural products have attracted a lot of attention in research. Since the earliest days, natural products have been employed as therapeutic agents for curing diseases [1]. The WHO estimates that more than 80% of the world's population uses herbal medicines [2]. Herbal medicine is still incorporated into the basic healthcare system despite being replaced by conventional pharmaceuticals. The potential health and pharmacological benefits of phytochemicals have been highlighted, including their antioxidant, antibacterial, anti-cancer, cardioprotective, immune systemboosting, UV radiation-protective [3], and anti-inflammatory [3,4] properties. Additionally, medicinal plants are thought to be an important source in the development of new drugs. Synthetic medicines are constantly replacing effective pharmacological phytochemicals. However, the value of natural products cannot be emphasized enough, as herbal medicine offers a wide range of therapeutic benefits and may be used to treat a wide range of illnesses [5], including chronic diseases such as diabetes and related health complications of oxidative stress. Diabetes is considered to be the third most life-threatening health complication after cancer and heart attacks. Oxidative stress is caused by a number of causative agents and leads to number of health issues including diabetes. The most important causative agent of oxidative stress in the human body is the production of free radicals, also called reactive oxygen species, which cause the breaking of biologically important molecules such as protein and DNA, thus leading to a number of health issues. They are produced in normal oxidation processes in the body. Phenolic compounds, by virtue of a benzene ring, can stabilize these free radicals, which is why vegetables and fruits are important to be ingested in a person's diet [1][2][3][4][5].
Secondary metabolites are important components of the human diet as they are present in daily food products such as coffee, tea, soybean, fruits, and vegetables [6]. Due to their advantages in human health, including the treatment and prevention of many illnesses, phenolic compounds and flavonoids are well known as antioxidants and other significant bioactive agents. Various studies have revealed that the consumption of polyphenols has a protective effect against inflammation and cancer [7]. Because they are known to scavenge and stop the generation of reactive oxygen and nitrogen species, the anti-inflammatory actions of polyphenols have been attributed exclusively to their antioxidant activity [8]. Moreover, phenolic-rich plants have anti-tumor [9], anti-mutagenic, anti-HIV [10], and anti-diabetic [11] properties. Antimicrobial resistance has caused serious concern for both human health and the control of bacterial infectious illnesses [12]. Due to the intensive misuse of antibiotics to treat infections, bacterial resistance has increased in recent years [13]. A number of common pathogenic strains already bear antibiotic-resistant genes, and, presumably, more antibiotic-resistant pathogens will emerge in the future, if suitable measures are not taken to prevent this [14]. Antimicrobial resistance may be handled in two different ways, either by developing new active materials, which has growing bench-to-market costs and is time consuming [15], or by looking for ways to make existing antimicrobials more effective [16]. As phytochemicals have antibacterial potential [3], they may be potential candidates to counter antibacterial resistance. Diabetes mellitus is a metabolic illness with numerous etiologies marked by a lack of glucose homeostasis as well as abnormalities in carbohydrate, lipid, and protein metabolism as a result of deficiencies in insulin production and/or action [17]. Raised blood glucose is one of the most significant public health issues in the world; after high blood pressure and cigarette smoking, it is the third most significant risk factor for early mortality globally, according to a study by the International Diabetes Federation [18]. Well-known anti-inflammatory phytochemicals such as flavonoids, polyphenols, and tannins, which function as free radical scavengers, may have anti-diabetic effects [19,20]. These antioxidants are considered to have an insulin-mimetic impact on peripheral tissues, either by promoting tissue regeneration or by causing existing cells to secrete pancreatic insulin. The phytochemicals may also speed up filtration and renal excretion, improving metabolism, or integrating glucose into fat deposits, which improves the efficiency of the pancreas to make insulin [19].
Quince (Cydonia oblonga) belongs to the family Rosaceae, which is conventionally popular for medicinal, nutritional, and ornamental uses [21,22]. The name of the Cydonia genus is derived from the name of a region Kydonia on the northwestern Coast of Crete, Greece, where this tree has been cultivated since ancient times. In older Greek rituals, the fruit was offered at weddings as they symbolized fertility [23]. The fruits of quince are used in various countries for food, pharmaceutical, perfume, and agricultural purposes [24]. Therefore, this plant has garnered considerable attention due to its economic value. Secondary metabolites (phenolic compounds and essential oils), minerals, and vitamins are found in large amounts in quince fruits [25]. Various studies have revealed that the pulp of quince reduces the risk of diseases such as cardiovascular diseases [26], cancer [27], colon issues, and kidney problems [28]. Quince tannins are used as an antiseptic agent in pulmonary infections as they show activity against bacteria, fungi, and viruses [29]. Furthermore, the seed of quince is used for the treatment of cough, diarrhea, constipation, dysentery, and bronchitis. Numerous secondary metabolites have been identified in the phytochemical screening of quince fruits [30].
The bark of the Cydonia oblonga plant has not been studied to date. Therefore, the aim of the present work was to determine and characterize of the secondary metabolites of Cydonia oblonga bark using high-performance liquid chromatography, and to investigate the antioxidant, antibacterial, and anti-diabetic activity of the bark extract and the seven isolated fractions.

Phytochemical Evaluation
Preliminary phytochemical screening of Met + Ext of Cydonia oblonga showed positive results for major phytochemical constituents as given in Table 1.

TFC and TPC in the Met-Ext and Purified Fractions of Cydonia oblonga
The results of TPC and TFC are presented in Figure 1. Met-Ext has the highest TFC and TPC values of 69% and 70%, respectively, while purified fraction 6 has the highest TPC (64%) and purified F1 has the highest TFC (58%).

HPLC Analysis of Methanolic Extract of Cydonia oblonga
The human health benefits of phenolic compounds are widely documented. HPLC analysis was carried out to determine the phenolic content of the Met + Ext of Cydonia oblonga bark. Figure 2 displays the extract chromatogram and Table 2 displays the possible compounds. Although there are many peaks in the chromatogram, only a few were identified by comparing their retention times with that of available standards. Furthermore, it should be noted that they are only possible compounds as HPLC is not an absolute technique for compound identifications.

GC-MS Characterization of Methanolic Extract and Purified Fractions
The results of GC-MS analysis of the fractions are given in the Supporting Materials in Figures S1-S20 (Figures S1, S4, S7, S10, S13, S15 and S18 are the GC chromatograms, Figure S2, S5, S8, S11, S14, S16 and S19 represents structure of compounds identified whereas Figure S3, S6, S9, S12, S17 and S20 represents the mass fragmentation of individual compounds identified in each fraction) whereas Tables S1-S7 correspondingly summarizes the major compounds present in fractions F1 to F7. The identified compounds are depicted in Table 3. Table 3. List of the identified compounds in Cydonia oblonga bark fractions (F1-F7) determined through GC-MS analysis.

S. No
Fraction Compounds

Evaluation of Antibacterial Activity of Methanolic Extract and Fractions
Using the disc diffusion methodology, the antibacterial activities of the Met + Ext and purified fractions were assessed against several microbial strains. The zones of inhibition were noted and the results are presented in Table 4.

Antioxidant Activity of Crude and Purified Fractions of Cydonia oblonga
DPPH scavenging activity was investigated to find the antioxidant potential of the Met + Ext and the purified fractions and results are displayed in Table 5. The standard ascorbic acid caused scavenging up to 94.88 ± 0.96% with the lowest IC 50 value of 30 µg/mL at 1000 µg/mL against DPPH. Met + Ext exhibited 87.41 ± 0.54 with the lowest IC 50 value of 120, while among the fractions the highest % inhibition value was recorded for F1, as 85.45 ± 0.85, with the lowest IC 50 value of 115.  The IC 50 values of the purified fractions and Met + Ext were calculated at different concentrations as presented in Table 6. Met + Ext was the most potent inhibitor with the lowest IC 50 value. Acarbose (standard) at the maximum concentration 1000 µg/mL showed 87.65 ± 0.71 α-glucosidase inhibition with 30 µg/mL IC 50 value. The IC 50 values of the purified fractions and Met + Ext were calculated at different concentrations along with percent inhibition values and are depicted in Table 6. The crude extract was recorded to be the most potent α-amylase inhibitor l with the lowest IC 50 value. Standard acarbose at the maximum concentration 1000 µg/mL showed 85.99 ± 0.44 α-glucosidase inhibition with 32 µg/mL IC 50 values.

Discussion
The analysis of the present study indicated that Met-Ext had the highest TFC and TPC values of 69% and 70%, respectively. Purified fraction 6 had the highest TPC of 64% and purified fraction 1 had the highest TFC of 58%. According to Erdogan et al. [25], the leaves of Cydonia oblonga are a rich source of phenolic compounds, which confirms our observed results. Scientific interest in the standardization and characterization of herbal medications is ongoing in the herbal drug sector. Simple, rapid, practical, and affordable standardization approaches are becoming more and more desirable as sophisticated chromatographic techniques are introduced [27]. For the standardization of Met + Ext from plant bark, HPLC was used as it is a sensitive and accurate technique that is widely used for the evaluation of plant extracts and their derived products/formulations [31]. The HPLC-UV analysis of Met + Ext showed the presence of a number of possible compounds such as malic acid, mandelic acid, quercetin, morin, catechin hydrate, and caffeic acid, which were identified through comparison of the retention time of the respective peak in the chromatogram with that of the available standards. As mentioned in the Section 2, this is not a standard technique for the identification of compounds and thus must be used in conjunction with MS in the form of GC-MS or LC-MS and/or NMR investigations in order to fully identify the compounds present and comprehend their structure [32]. The GC-MS technique was successfully employed for Cydonia oblonga bark isolated fractions, and is one of the most extensively used techniques for separating phytoconstituents. About 25 phytochemical substances in the leaves and rhizome of Amomum nilgiricum species have been identified previously through GC-MS [33]. The GC-MS analysis of the purified fractions also confirmed the presence of certain valuable phytochemicals. Antibiotics are widely used to address a variety of infections brought on by bacteria, which can be multidrug resistant. These infections are common, which raises treatment resistance and impedes the research and development of new drugs [34]. Analysis has revealed that Gram-positive bacteria are more vulnerable than Gram-negative bacteria to the tested extract and fractions. Our research is consistent with the reported studies where it has been discovered that quince extract has a significant antibacterial effect against Grampositive bacteria but is less effective against Gram-negative bacteria [35,36]. The outer membranes of Gram-negative bacteria contain lipopolysaccharide, which keeps phenolics from adhering to the surface of the bacterial strain [37], which is why lower activity has been observed against each Gram-negative strain. In general, Gram-positive bacteria appear to be more sensitive to bactericidal polyphenols than Gram-negative species [38]. The DPPH scavenging activity of methanolic and the purified fractions were measured, and the results exhibited potential antioxidant activity. The leaf extract of quince has depicted a concentration-dependent antioxidant potential of 120 µg/mL [39] previously. In another study, methanolic extracts of edible peel and pulp of quince showed IC 50 values of 600 and 800 µg/mL, respectively, whereas seed extracts were reported to have a lower antioxidant potential [40]. The Cydonia obolonga extract and the isolated fractions showed effectiveness against α-glucosidase and α-amylase. A previous study showed that plant extracts (methanolic and n-hexane) display remarkable anti-diabetic activity against αglucosidase and α-amylase [41]. The antidiabetic activity of Cydonia oblonga leaves in hydro-ethanolic extract was studied in normal and streptozotocin-induced diabetic rats. There was no significant effect on normal rat glucose, while a significant reduction in blood glucose levels was recorded in diabetic rats at the time period of 0 to 3 h [42,43]. These reported findings confirm our observations on the selected plant.

Plant Sample Collection
The bark of Cydonia oblonga was collected from Allahdand Dheri (latitude. 34

Chemicals and Standards
Gallic acid and quercetin were purchased from Sigma-Aldrich France, and nutrient agar was obtained from Oxoid Ltd. England. 2,2-Diphenyle-1 picrylhydrazyl (DPPH) and Folin-Ciocalteu reagent (Sigma-Aldrich CHEMIE GmbH Burlington, MA, USA), aluminum chloride, methanol, iron chloride, sodium hydroxide, sodium nitrite, and ascorbic acid were purchased from Sigma-Aldrich, Germany. All the chemicals utilized in assays were of analytical grade, except HPLC-grade solvents, which were purchased from Dae-Jung, Korea. They were used as such without any further purification.

Extraction and Fractionation
The fresh bark of the Cydonia oblonga was washed and dried under a hood to avoid deterioration of bioactive active compounds due to sunlight. The dried sample was ground into a powder and mixed well with methanol. After three days, the extract was filtered through Whatman filter paper, and using a rotary evaporator (Rota Vapor R-200 Buchi, Switzerland) the solvent was evaporated from the filtrate under reduced pressure and at 40 • C. HPLC analysis of the crude was carried out using a reported protocol [44]. Then, 7 HPLC fractions were collected in vials which were labeled as F1, F2, F3, F4, F5, F6, and F7 and stored at 4 • C temperature till further analysis. The separated fractions and methanolic extract (Met + Ext) were screened for phytochemical evaluation (TPC and TFC etc.) and various biological activities. The purified fractions were also analyzed using GC-MS for the presence of bioactive compounds.

Phytochemical Analysis
Preliminary phytochemical screening was undertaken to determine the presence of various bioactive constituents such as alkaloids, flavonoids, glycosides, terpenoids, and tannins in Met + Ext of Cydonia oblonga bark using reported assays [45][46][47].

Analysis of Total Phenolic Content and Total Flavonoids Content
The content of phenolics was determined in Cydonia oblonga bark Met + Ext and purified fractions from F1 to F7 using Folin-Ciocalteu assay [45]. For the preparation of the required solution, 5 mg of sample extract was taken and dissolved in 5 mL of methanol. Then, 1 mL of Folin-Ciocalteu reagent was diluted with 10 mL of distilled water to prepare the Folin-Ciocalteu reagent solution. In a volumetric flask, 9 mL of distilled water was added to 1 mL of sample solution and 1 mL of the diluted solution of Folin-Ciocalteu reagent and allowed to stand for 6 min. After 6 min, 10 mL of 7% NaHCO 3 (sodium carbonate) solution was successively added to the mixture. The mixture was made up to 25 mL volume with distilled water and thoroughly mixed. After 90 min, the absorbance was measured at 760 nm using a UV spectrophotometer. Gallic acid solution curve (0 to 100 mg/mL) was used as a standard. Total phenolic content was expressed as gallic acid equivalents (mg GAE/g) per gram of dry sample, which is a common reference compound.
The total flavonoid content was determined using the aluminum chloride calorimetry method [46] with little modification. The plant extract was diluted with methanol. The methanolic solution of extract (100 µL) and 500 µL distilled water were added to 10 mL volumetric flasks followed by the addition of 100 µL NaNO 2 (5%), 150 µL AlCl 3 (10%), and 200 µL NaOH (1 M). A calibration curve was prepared by using the methanolic solution of quercetin in concentrations ranging from 0-100 µg/mL. The resulting mixture was incubated for 5 min; absorbance was measured spectrophotometrically at 510 nm. The total flavonoid content was expressed in terms of Quercetin equivalent to mg of QE/g of dry samples.

HPLC Characterization Sample Preparation for HPLC Analysis
HPLC analysis was performed according to a previously reported protocol [44] with some modifications. For analysis, a sample extract was prepared by dissolving 1 g of powder sample in a 10 mL mixture of water and methanol (5:5). The mixture was shaken thoroughly for 1 h at 60 • C and then subjected to filtration using a Whatman filter paper with 0.7 µm pore size. The filtrates were then centrifuged for 15 min at 4000 rpm. The sample extract was filtered twice and collected in a HPLC vial, marked with proper code.

HPLC-UV
The sample was analyzed in an Agilent 1260 infinity High-performance Liquid Chromatography (HPLC) instrument equipped with an autosampler, quaternary pump, degasser, and ultraviolet (UV) detector. An Agilent Zorbax Eclipse C18 column was used for separation. The mobile phase was solvent A (acetic acid, methanol, deionized water, 2.10.88, v/v) and solvent B (acetic acid, deionized water, methanol, 2.8.90, v/v). The system was conditioned with the mobile phase at least for 30-40 min. The gradient profile started with 100% solvent A at 0 min, 85% A at 5 min, 50% solvent A at 20 min, at 25 min solvent A decreased to 30%, and finally, 100% solvent B at 30-40 min. The solvents were delivered at 1 mL/min flow rate, and the absorbance of phytochemicals was measured at 280 nm wavelength, by using retention times (chromatographic comparisons), and UV spectra were recorded with the UV detector identification of different compounds. Seven active fractions were obtained (F1 to F7), which were further analyzed by GC-MS.

GC-MS Analysis for Characterization
Phytoconstituents in purified fractions were analyzed through GC-MS (Agilent Technological, Santa Clara, CA, USA) using a previously reported protocol [48]. The system was equipped with an FID detector to identify phytochemicals. Compounds were identified by comparing their mass spectra and retention times with pure compounds (standards) taken from Willy and NIST libraries software.

Antibacterial Activity
In vitro antibacterial activity was examined for Met + Ext and purified fractions of Cydonia oblonga against Gram-positive (Bacillus subtilis, Staphylococcus aureus, and Streptococcus pneumonia) and Gram-negative bacteria (Escherichia coli, Salmonella typhi, and Klebsiella pneumonia) using the disc diffusion method. Standard bacterial cultures were used in which the viable count in each culture was determined using a surface viable technique. The bacterial cultures (from 10 8 -10 9 colony forming units per mL) were swabbed uniformly on the surface of the prepared media using a separate sterile cotton swab each time. Sterilized filter paper discs (Whatman No. 2, Whatman plc, Little Chalfont, GB) impregnated with 20 µL of sample solution were placed individually at equal distances on the surface of seeded agar plates, followed by incubation of bacteria at 37 • C for 24 h in an incubator.
Respective solvents without plant extracts were taken as a negative control. After incubation, the results were observed, and we measured the zone diameter around each disc. The experiment was performed in triplicate and mean zone of inhibition values were calculated.

DPPH Radical Scavenging Activity
The stock solution was prepared by dissolving 20 mg DPPH in 100 mL of methanol; 3 mL of this solution was taken and its absorbance was measured spectrophotometrically at 517 nm and was considered as a negative control solution. For free radical formation, a stock solution was covered with aluminum foil and incubated at room temperature in dark conditions for 24 h. About 5 mg of extract and each purified fraction were dissolved in 5 mL methanol to obtain the stock solution. Then, the above solution was serially diluted in methanol at the following concentrations: 1000, 500, 250, 125, and 62.5 (µg/mL). Then, 2 mL of each sample solution was mixed with 2 mL solution of DPPH and after reaction for 15 min in dark, the absorbance values of the samples were measured. DPPH radical scavenging activity of plant extract and fractions were calculated by using the following equation: where A• is the absorbance of pure DPPH and B• is the absorbance of samples. IC 50 values were determined using ascorbic acid taken as a standard, prepared with a concentration of 5 mg/5 mL. Serial dilutions were performed with different concentrations of ascorbic acid in the samples at 1000, 500, 250, 125, and 62.5 µg/mL. All the experiments were performed in triplicate.

Inhibition of α-Amylase
The α-amylase solution was prepared by dissolving 10 mg enzyme in 100 mL distilled water. Then, 10 µL α-amylase enzyme solution was mixed with each test sample in the concentration range of 30 µL. As a negative control, 30 mL of sodium phosphate buffer was added to 10 µL enzyme solution and incubated at 37 • C for 10 min. Then, 40 mL of starch solution was added to each test tube. Incubation was carried out again at 37 • C for 30 min, then 20 µL of 1 M HCL was added and absorbance was measured at 540 nm using a spectrophotometer. The control samples were prepared without any plant samples. Equation (2) was used to estimate the percent inhibition of the enzyme.

α-Glucosidase Inhibition Activity
The reaction mixture was formulated by adding 100 µL of α-glucosidase enzyme (0.5 units/mL), 0.1 M phosphate buffer (600 µL) at pH 6.9 and 50 µL of each sample dilution (62.4, 125, 250, 500, and 1000 µg/mL). The mixture was incubated for 15 min at 37 • C. The enzymatic reaction began by adding 100 µL p-nitro-phenyl-α-D-glucopyranoside (5 Mm) solution in 0.1 M phosphate buffer at pH 6.9 followed by 15 min incubation at 37 • C. The absorbance of the final reaction mixture was recorded at 405 nm. The reaction mixture with no plant extract was used as positive control while the blank solution was prepared without the enzyme α-glucosidase. The α-glucosidase % inhibition was calculated using the formula: % α − glucosidase inhibition = control absorbance − sample absorbance control absorbance × 100 (2)

Statistical Analysis
To calculate IC 50 for % DPPH, α-amylase, and α-glucosidase inhibition, Excel 2007 was used. The standard deviation and means were estimated using Excel.

Conclusions
HPLC analysis revealed that the bark of Cydonia oblonga has numerous biologically active compounds such as polyphenols and flavonoids. The crude extract and fractions isolated through HPLC were subjected to GC-MS analysis. A total of twelve compounds were identified through HPLC and GC-MS analysis. The extract and various fractions exhibited potential biological activity such as antioxidant, antibacterial, and anti-diabetic activities. This bark can constitute an alternative therapeutic agent for bacterial infections, oxidative stress, and diabetes, which are major subjects for future research. Pharmacological and toxicological studies are also needed to confirm the hypothesis tested here, which will also further elaborate on the safety profile of the extract.
Supplementary Materials: The following supporting information can be downloaded at: https:// www.mdpi.com/article/10.3390/molecules27196360/s1. Figure S1. GC-MS chromatogram of fraction 1 of Cydonia oblonga, Figure S2. Major phytochemical compounds identified in Fraction 1 of Cydonia oblonga, Figure S3. Individual mass fragmentation of each compound, Figure S4. GC-MS chromatogram of Fraction 2 of Cydonia oblonga, Figure S5. Major phytochemical compounds identified in fraction 2 of Cydonia oblonga, Figure S6. Individual mass fragmentation of compound. (A) Carbamide, Figure S7. GC-MS chromatogram of Fraction 3 of Cydonia oblonga, Figure S8: Major phytochemical compounds identified in fraction 3 of Cydonia oblonga, Figure S9. Individual mass fragmentation of Each Compound, Figure S10. GC-MS chromatogram of Fraction 4 of Cydonia oblonga, Figure S11. Major phytochemical compounds identified in fraction 4 of Cydonia oblonga, Figure S12. Individual mass fragmentation of Each Compound, Figure S13. GC-MS chromatogram of Fraction 5 of Cydonia oblonga, Figure S14. Major phytochemical compounds identified in fraction 5 of Cydonia oblonga, Figure S15. GC-MS chromatogram of Fraction 6 of Cydonia oblonga, Figure S16. Major phytochemical compounds identified in fraction 6 of Cydonia oblonga, Figure S17. Individual mass fragmentation of the Compound. (A) Isopropylamine, Figure S18. GC-MS chromatogram of Fraction 7 of Cydonia oblonga, Figure S19. Major phytochemical compounds identified in fraction 7 of Cydonia oblonga, and Figure S20. Individual mass fragmentation of the Compound. (A) 1-Propylhydrazine. Table S1. List of major components and their parameters identified in fraction 1 of Cydonia oblonga, Table S2. List of major components and their parameters identified in Fraction 2 of Cydonia oblonga, Table S3. List of major components and their parameters identified in Fraction 3 of Cydonia oblonga, Table S4. List of major components and their parameters identified in Fraction 4 of Cydonia oblonga ,  Table S5. List of major components and their parameters identified in Fraction 6 of Cydonia oblonga, Table S6. List of major component and their parameters identified in Fraction 6 of Cydonia oblonga, and Table S7  Acknowledgments: The authors are thankful to the Chairman, department of Biochemistry, University of Malakand for providing access to equipment.

Conflicts of Interest:
The authors declare no conflict of interest.


provenance: AgriculturalAndFoodSciences,2022-2022-Agricultural And Food Sciences-2022.jsonl.gz.gz

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Identification of Key Pathways Associated With Residual Feed Intake of Beef Cattle Based on Whole Blood Transcriptome Data Analyzed Using Gene Set Enrichment Analysis

We applied whole blood transcriptome analysis and gene set enrichment analysis to identify pathways associated with divergent selection for low or high RFI in beef cattle. A group of 56 crossbred beef steers (average BW = 261 ± 18.5 kg) were adapted to a high-forage total mixed ration in a confinement dry lot equipped with GrowSafe intake nodes for period of 49 d to determine their residual feed intake (RFI). After RFI determination, whole blood samples were collected from beef steers with the lowest RFI (most efficient; low-RFI; n = 8) and highest RFI (least efficient; high-RFI; n = 8). Prior to RNA extraction, whole blood samples collected were composited for each steer. Sequencing was performed on an Illumina NextSeq2000 equipped with a P3 flow. Gene set enrichment analysis (GSEA) was used to analyze differentially expressed gene sets and pathways between the two groups of steers. Results of GSEA revealed pathways associated with metabolism of proteins, cellular responses to external stimuli, stress, and heat stress were differentially inhibited (false discovery rate (FDR) < 0.05) in high-RFI compared to low-RFI beef cattle, while pathways associated with binding and uptake of ligands by scavenger receptors, scavenging of heme from plasma, and erythrocytes release/take up oxygen were differentially enriched (FDR < 0.05) in high-RFI, relative to low-RFI beef cattle. Taken together, our results revealed that beef steers divergently selected for low or high RFI revealed differential expressions of genes related to protein metabolism and stress responsiveness.

INTRODUCTION
Residual feed intake (RFI), a measure of feed efficiency, continues to be of great economic importance due to increasing cost of animal feeds (1). Residual Feed Intake is the difference between an animal's actual feed intake and its predicted feed intake for a given level of maintenance and body weight gain (1). Feed efficient animals consume less than expected and have a low (negative) RFI, while inefficient animals consume more than expected and have a high (positive) RFI. Thus, beef cattle selected for low RFI have decreased feed costs because they consume less dry matter when compared with high-RFI beef cattle while maintaining similar growth performance.
Due to the great economic importance of RFI, the biological mechanisms underlying variation in this trait have always been of great interest; however, these mechanisms have not been fully understood. Difference in RFI has been suggested to be an indication of differences in metabolism rather than differences in growth performance because the trait is phenotypically independent of growth performance (1). Several studies have applied whole transcriptome analysis of several tissues such as liver and ruminal epithelium to further understand the biological mechanisms regulating feed efficiency traits including RFI in beef cattle (2)(3)(4). For instance, Kong et al. (3) analyzed the rumen epithelial transcriptome from low-RFI and high-RFI beef steers and observed increased tissue morphogenesis and greater expression of mitochondrial genes in low-RFI compared to high-RFI steers. Mukiibi et al. (4) analyzed liver tissue transcriptome profile and observed differential expressions of genes involved in nutrient metabolisms and cellular development in beef steers divergent for low and high RFI. However, these studies involve invasive sample collection procedures. Despite the convenience of collection and relatively non-invasive accessibility of blood in ruminants, very few attempts have been made to apply wholeblood transcriptome to understand the biological mechanisms associated with RFI in animals. Genes expressed in peripheral blood cells have been demonstrated to reflect physiological changes in different body tissues and can highlight biological processes related to overall metabolisms. Therefore, the objective of this study was to analyze the whole-blood transcriptome data of beef steers via gene-set enrichment analysis to identify key pathways associated with divergent selection for low or high RFI in beef cattle.

Animals and Sample Collection
A total of 56 crossbred growing beef steers with average BW of 261.3 ± 18.5 kg were fed a high-forage total mixed ration (TMR; primarily consisting of triticale silage; rye grass silage; and a ration balancing Supplementary Table 1) in five confinement dry lot pens (15 by 47 m 2 ), each served by three GrowSafe 8000 (GrowSafe Systems Ltd., Airdrie, Alberta, Canada) feeding nodes to measure individual feed intake and two In-Pen Weighing Positions (IPW Positions, Vytelle LLC) to measure daily BW for a total of 49 d after 15-d adjustment period to the feeding facilities. The use of IPW Positions has enabled the measurement of individual animal BW multiple times in a day (5). The IPW Positions measure the partial BW by weighing the front end of an animal (6). The IPW positions were positioned at a water trough in each pen such that an animal must place its front feet on the scale in order to drink (7). The partial BW of the animals was measured every second the animals stayed on the scale while drinking. More details on the accuracy, use and applicability of IPW positions have been described in previous studies (5,6). In this study, approximately 617 ± 92 daily BW data points (after filtering outliers) per animal were generated and were regressed on time to calculate beginning BW, mid-test BW, and average daily gain (ADG) of each animal. Animal ADG and metabolic mid-test BW (mid-test BW 0.75 ) were regressed against individual average daily intake, and RFI was calculated as the residual or the difference between the predicted value of the regression and the actual measured value based on the following equation: Y = β 0 + β 1 X 1 + β 2 X 2 + ε, where Y is the observed DMI (kg/d), β 0 is the regression intercept, β 1 and β 2 are the partial regression coefficients, X 1 is the mid-test metabolic BW (kg), X 2 is the ADG (kg/d), and ε indicates the RFI [kg/d; (8)]. After the determination of RFI values for all animals, the most-efficient with the lowest RFI (low-RFI; n = 8) and the least-efficient with the highest RFI (high-RFI; n = 8) beef steers were selected, kept separate from others, and kept on the same diet for additional 21 d (designated in this study as d 50-70). On d 56, 63, and 70, 10 mL of blood samples were collected before morning feeding into tubes containing sodium heparin. Immediately after collection, subsamples (500 µL each) were transferred into RNA-protect tubes (Cat. No. 76554; Qiagen) containing a reagent that lyses blood cells and stabilizes intracellular RNA and stored at −80 • C until later analysis.

RNA Extraction, Library Preparation, and Sequencing
Prior to RNA extraction, whole blood samples collected on d 56, 63, and 70 were composited for each steer. Total RNA was extracted from the composited samples using RNeasy Protect Animal Blood kit (Cat. No. 73224; Qiagen) following the manufacturer's instructions. RNA concentration was measured using a NanoDrop One C spectrophotometer with an A260:A280 ratio from 1.8 to 2.0 (Thermo Fisher Scientific, Waltham, MA, USA). All RNA samples had RNA integrity numbers >8.0. Dual indexed RNA Libraries were prepared from 100 to 250 ng of total RNA per sample using the KAPA RNA HyperPrep Kit with RiboErase (Human, Mouse, Rat) Globin Reduction method in the WVU Genomics Core according to the kit manufacturer's instructions. Library quality was assessed by electrophoretic analysis on the Agilent 4,200 TapeStation system with High Sensitivity D1000 screentape. RNA libraries were sequenced in a dual indexed 2 × 50 paired-end run on an Illumina NextSeq2000 equipped with a P3 flow.

Data and Statistical Analysis
For the RNA-seq data, reads were trimmed using Trimmomatic v 0.39 to remove low-quality base calls and adapter sequences (9), and then aligned to the Bovine reference genome ARS-UCD1.2 (10) using HISAT2 v 2.2.1 (11). Resulting files were sorted and indexed, and PCR and optical duplicate reads were marked using SamTools v1.12 (12). The numbers of reads mapping to each gene for each sample were counted using the R/Bioconductor package GenomicAlignments v 1.26.0 (13). Log 2 fold change values were computed using DESeq2 version 1.30.1 (14). We used gene set enrichment analysis (GSEA), a pathway enrichment method that utilizes predefined gene sets from the reactome pathways (15), to analyze differentially expressed gene sets using the R/Bioconductor package fgsea v 1.16.0. The GSEA was performed to determine the key pathways that were enriched or inhibited by considering the expression levels of sets of biologically related genes (16). Genes identified by DESeq2 as expressing over a minimal threshold were ranked by Log 2 fold change and analyzed by the GSEA algorithm (17). The altered pathways were filtered based on FDR ≤ 0.05 and were arranged in the order of their normalized enrichment scores.

RESULTS
The average RFI values of low-and high-RFI steers were−1.93 and 2.01, respectively. An average of 36 million reads per sample was generated (Supplementary Table 2). Results of GSEA revealed gene sets (pathways) associated with metabolism of proteins, cellular responses to external stimuli, stress, heat stress, and regulation of HSF-1-mediated heat shock response were differentially inhibited (FDR = 0.01) in high-RFI compared to low-RFI beef cattle (Table 1, Supplementary Figure 1). The gene set associated with metabolism of proteins consists of 248 genes, and 85 of which were leading edge genes (significantly enriched genes). Both cellular response to external stimuli and cellular response to stress shared the same nineteen leading edge genes including HSPA1A, HSPH1, BAG2, DNAJA1, DNAJB1, H3C13, H2BC7, H4C2, ELOC, JUN, and HSPA4. Five of the leading edge genes (HSPA1A, HSPH1, BAG2, HSPA4, and DNAJB1) associated with cellular response to external stimuli and stress were also leading edge genes in gene sets associated with response to heat stress and regulation of HSF-1-mediated heat shock response ( Table 1).
Gene sets associated with binding and uptake of ligands by scavenger receptors, scavenging of heme from plasma, erythrocytes take up/release carbon dioxide and release/take up oxygen share the same leading edge genes (HBB, HBA1, and HBA) and were all differentially enriched (FDR < 0.05) in high-RFI, relative to low-RFI beef cattle ( Table 1

DISCUSSION
Understanding the biological mechanisms regulating feed efficiency using easily accessible and non-invasive sample such as blood is essential to the future of livestock production systems in terms of profitability and animal welfare concern.
In this study, protein metabolism is the most enriched metabolic pathway based on the number of leading edge genes (such as LOC101907518, RPL39, LOC101902490, UBE2D1, FUCA2) in the gene set. In addition to the function of amino acids as the building blocks of proteins, amino acids regulate key metabolism essential for growth, performance, reproduction, and immunity (18). Research studies have shown that protein (amino acids) metabolism is essential for optimizing efficiency of nutrient absorption and metabolism to enhance immunity against diseases and stress, growth performance, and milk production of animals (18). Several published articles have identified protein metabolism as one of the most important metabolic processes associated with RFI in animals (19,20). In our previous study, we identified plasma amino acid metabolites as the most significant metabolic signatures associated with RFI in beef cattle (20). Elolimy et al. (21) reported differences in signaling mechanisms controlling protein turnover in ruminal epithelium of beef cattle divergent for low-or high-RFI. In a similar study, Kong et al. (3) reported increased expression of genes involved in protein and cell turnover in the ruminal epithelium of low-RFI beef cattle, compared with high-RFI beef cattle. 4 performed RNA-seq analysis of liver tissue in beef cattle divergent for low and high RFI and observed downregulation of genes involved in amino acid degradation and urea synthesis in low-RFI beef cattle. In fact, some studies have reported significant association of blood metabolites involved in urea cycle with RFI in beef cattle (22,23). Our results and those of others that utilized tissues with relatively more invasive collection methods suggest that amino acid metabolism plays a considerable role in regulating RFI of beef cattle and its enrichment in low-RFI beef steers probably explains their similar growth performance with high-RFI beef steers despite lower DMI.
Amino acids play a functional role in regulating stress response, including oxidative stress, in animals (24). Stress response has significant implication on health and production efficiency of animals (25). In fact, difference in stress responsiveness has been suggested to contribute to variation in feed efficiency of beef cattle (19,26). In this study, we observed downregulation of gene set including HSPA1A, HSPH1, BAG2, and DNAJA1 associated with cellular responses to external stimuli, stress, heat stress, and regulation of HSF-1-mediated heat shock response in high-RFI beef steers, which suggests that these steers are more susceptible to stress. When an animal can no longer cope with a stressor, level of blood cortisol increases via activation of hypothalamic-pituitary-adrenal axis (HPA) axis which causes a fight or flight response that increases energy expenditure. Thus, stress response in animals is often determined by blood cortisol level and activity of the HPA axis (27). In a study that determined the response of beef heifers to an exogenous adrenocorticotropic hormone (ACTH) challenge, there was a positive association of plasma cortisol level with RFI status and low-RFI had a lower cortisol response than high-RFI heifers indicating that low-RFI heifers coped better with the stress challenge (28). Richardson et al. (19) and Gomes et al. (29) reported lower blood levels of cortisol in low-RFI beef cattle when compared to high-RFI beef cattle. A similar result was observed in crossbred rams following ACTH challenge (26). Taken together, downregulation of genes associated with cellular responses to external stimuli, stress, heat stress, and regulation of HSF-1-mediated heat shock response in high-RFI beef steers suggests that low-RFI steers have better adaptive mechanisms to cope with environmental stressors, thereby, reducing energy expenditure and increasing energy availability for improved growth performance and better feed efficiency.
In this study, we observed enrichment of gene sets (HBB, HBA1, and HBA) associated with erythrocytes take up/release carbon dioxide, release/take up oxygen, scavenging of heme from plasma, and binding and uptake of ligands by scavenger receptors in high-RFI, relative to low-RFI beef cattle. Erythrocytes contain hemoglobins which carry oxygen to the body and are continuously exposed to high oxygen content which pre-disposes them to oxidative stress damage (30,31). Heme scavenger proteins, such as hemopexin and alpha-1-microglobulin, scavenge extracellular heme, a physiological ligand (32), synthesized from hemoglobin degradation via the activity of heme-oxygenase, an enzyme that is inducible by stressors such as oxygen free radicals (33,34). Previous investigations have shown that cellular expression of alpha-1-microglobulin is enriched during increased oxidative stress and heme exposure (30,34). In ruminants, oxidative stress has been implicated in many pathophysiological conditions that are relevant for growth performance, reproduction, and health (35). In fact, several studies have shown that oxidative damage of cell organelles and biomolecules is a source of energy drain and negatively affects several cellular processes including lipid and protein metabolism (36,37). The major source of intracellular reactive oxygen species production is the mitochondria (38) and previous studies have reported higher mitochondrial ROS production in less feed-efficient compared to high feed efficient animals (36,39,40). In addition, Casal et al. (41) reported increased hepatic abundance of protein carbonyls and thiobarbituric acid reactive species, which are products of protein and lipid oxidative damage, and reduced protein expression of antioxidant enzymes, including mitochondrial manganese superoxide dismutase, in high-RFI when compared with low-RFI beef steers. Similarly, Tizioto et al. (42) observed upregulation of oxidative stress-induced transcription factors in muscle of high-RFI beef steers. Therefore, it is reasonable to speculate that enrichment of genes associated with erythrocytes take up/release carbon dioxide, scavenging of heme from plasma, and binding and uptake of ligands by scavenger receptors in high-RFI compared to low-RFI beef steers suggests that they may be more prone to oxidative stress, thereby resulting in reduced efficiency of energy use for metabolic processes such as growth.
It is important to note that though whole blood transcriptome data might encompass gene activities of several body tissues and organs including liver, kidney, muscles, and rumen, the contribution of each tissue to the whole blood transcriptome is not known and should be determined in future studies. In addition, biological validation of the RNA-Seq data on selected genes by RT-qPCR is also needed to confirm the results of this study.

CONCLUSION
Results of GSEA of whole blood transcriptome data in beef steers divergently selected for low or high RFI revealed differential expression of genes related to protein metabolism, erythrocytes take up/release carbon dioxide and release/take up oxygen, and stress responsiveness. These results are similar to those of several studies that utilized other tissues including liver, muscle, and ruminal epithelium. Thus, this study demonstrates the suitability of whole blood transcriptome data for understanding the biological mechanisms regulating RFI in animals. Due to the small number of animals used in this study and the effect of different diets and breeds on RFI ranking, further validation using a larger cohort of beef cattle fed different diets is needed to confirm these findings.

DATA AVAILABILITY STATEMENT
All raw and processed sequencing data were submitted to the Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) and can be accessed via accession number GSE198068.

ETHICS STATEMENT
The animal study was reviewed and approved by the Institutional Animal Care and Use Committees of West Virginia University (protocol number 1608003693).

AUTHOR CONTRIBUTIONS
IO and APC designed the experiment. GT and MI conducted the experiment. JD analyzed the RNA-Seq data. IO, GT, and APC drafted the manuscript. All authors reviewed and approved the final manuscript.

FUNDING
This work was funded by West Virginia University Experimental Station (scientific article number 3430) in support of U.S. Department of Agriculture hatch multi-state regional project W-3010.


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Growth of probiotic Lactobacillus rhamnosus GR-1 using saccharified oil palm mesocarp fibre as affected by saccharification time and fermentation time

Mohd, N.H., *Maskat, M.Y., Mackeen, M.M., Zaini, N.A.M., Sahilah, A.M. and Sage, E.E. Department of Chemical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia Department of Food Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

Introduction
The World Health Organization defines a probiotic as ''live microorganisms that when administered in adequate amounts confer a health benefit on the host when ingested" (Williams and Hekmat, 2017;White and Hekmat, 2018). Examples of probiotic microorganisms include Lactobacillus rhamnosus, Lactobacillus plantarum (Asmariah et al., 2018), Lactobacillus salivarius, Lactobacillus reuteri (Shamsudin et al., 2019) as well as Bifidobacterium species (Williams and Hekmat, 2017). The growth and metabolic activity of probiotic bacteria such as lactobacilli can be selectively accelerated by various dietary carbohydrates that were not digested by the host (Leblanc et al., 2017). Prebiotics are defined as a selectively fermented ingredient that concedes specific changes, both in condition and/or activity in the gastrointestinal microflora, that bestow health benefits (White and Hekmat, 2018).
Nowadays, it is a great attraction to produce novel forms of prebiotic from readily available and renewable carbohydrate resources (Shi et al., 2018). Recently, there has been increased interest in the potential of oligosaccharides as prebiotics such as xylooligosaccharides, fructooligosaccharides (FOS), and several others (Dávila et al., 2019). An oligosaccharide is a molecule containing a low number of monosaccharide residues connected by glycosidic linkages (Nguyen and Haltrich, 2013). According to Patel and Goyal (2011), functional oligosaccharides are gaining outstanding popularity among the non-digestible carbohydrates, owing to their physiological benefits to the consumer. Moreover, they positively affect the composition and metabolic activity of the intestinal microflora and a daily moderate supplement of these non -digestible oligosaccharides stimulates mineral absorption especially Ca and Mg (Roberfroid et al., 2010;Kunova et al., 2012). Biomass (Gullon et al., 2009). Cellulose is a high molecular weight linear polymer composed of β-glucose (5000-10,000 units) and linked by β-1,4-glycosidic bonds (Srivastava et al., 2019). Enzymatic hydrolysis using cellulase from Trichoderma reesei, a mixture of endoglucanases, exoglucanases, and β-glucosidase, is widely used for the degradation of cellulose into soluble oligo glucan/ oligomers, cellobiose and glucose (Pasma et al., 2013). Cellulose from oil palm mesocarp fibre (OPMF) possibly can be depolymerised using enzymes to produce oligosaccharides through saccharification. About 80 million tonnes of oil palm biomass was produced in Malaysia in 2017. In addition, it was forecasted that the quantity of solid biomass from oil palm will reach 111 million tonnes a year by 2020 (MGCC, 2018). Moreover, approximately 11% of oil palm mesocarp fibre (OPMF) is generated from palm fruits after oil extraction. OPMF, also known as palm pressed fibre (PPF), is the biomass residue obtained after pressing the palm fruits for palm oil extraction (Nordin et al., 2013). Thus, it is a potential source of biomass that can be utilised for the production of valuable compounds . However, in order for the saccharified OPMF to function as a prebiotic, it has to be shown to be able to support the growth of probiotic microorganisms.
Lactobacillus rhamnosus GR-1 was chosen for this study since it was known as the second most scientifically documented L. rhamnosus probiotic. It was discovered in 1981 in Kingston, Ontario (Westerik et al., 2018). L. rhamnosus GR-1 is a probiotic strain that is bile and acid resistant and also can survive the passage through the gastrointestinal tract. These properties made L. rhamnosus GR-1 exert a number of human health benefits such as the prevention of urinary tract infections and oral intake of GR-1 also provide benefits to the urogenital tract, the gut as well as respiratory tract (Westerik et al., 2018;White and Hekmat 2018;Figueroa-Gonzalez et al., 2019). Due to its properties, L. rhamnosus GR-1 has been attributed as one of the main probiotic strains that are suitable for applications in the production of yoghurt and fermented foods in Africa (Wekstrik et al., 2018). Meanwhile, Zare et al. (2012) reported that L. rhamnosus has been the main species used as a probiotic over the years. Williams and Hekmat (2017) have described the addition of short-chain inulin, long-chain Inulin and oat have no adverse supplementation effects in the viability of L. rhamnosus GR-1, with 4% of short-chain inulin showing the highest viability. While, White and Hekmat (2018) were found that the fermentation of apple cider, grape and orange juice fortified with inulin fibre with L. rhamnosus GR-1 improved the viable bacterial counts that were greater than the minimum requirement of 10 6 CFU/mL, to be classified as prebiotics. Other than that, results from the sensory evaluation indicated may be potential for probiotic fruit juices in the commercial market. A study conducted by Dunkley and Hekmat (2019) has studied the growth and viability of L. rhamnosus GR-1 in carrot juice (CJ), carrot apple juice (CAJ), carrot orange juice (COJ) and carrot apple juice (CBJ) over 72 h of fermentation and 30 days storage at 4°C. The result showed a significant microbial growth only juices CJ and COJ with a significant decline in pH.
Due to its abundance, OPMF fibre has the potential to serve as a lower-cost cellulosic feedstock to produce oligosaccharides as an alternative source of prebiotic. As there is limited literature on the use of saccharified OPMF as feedstock for probiotics, this study was carried out to determine the ability of saccharified OPMF to support the growth of L. rhamnosus GR-1 which is a known probiotic as affected by saccharification time and also fermentation time.

Preparation of carbohydrate substrates
The mesocarp fibre was washed to remove foreign particles and dried in an oven at 80 o C overnight . Subsequently, the dried fibre was ground into approximately 0.25 mm particles, transferred into sealed plastic bags and stored at 4 o C until used. The ground OPMF was deconstructed as according to  with slight modifications which involved pre-treatment using steam and 15% NaOH solution.
Subsequently, the OPMF was subjected to enzymatic saccharification using a commercial enzyme cocktail (Celluclast 1.5 L) in an incubator shaker (Wisecube wis 20) at 50 o C, 120 rpm (Tang et al., 2018). The saccharification time was varied at 1, 3 and 6 hrs to produce samples at different degrees of polymerisation (DP) ranging between 2 and 4. The saccharified OPMF was extracted by centrifugation 2147×g, 15 mins (Thermo Scientific TM Sorvall TM model) and then dried using a rotary evaporator. The glucose units (GU) of saccharified OPMF was determined using highperformance liquid chromatography with fluorescence detection (HPLC-FD). Fluorescent labelling via chemical derivatisation with 2-aminobenzamide (2-AB) and the subsequent HPLC-FD analysis of saccharified OPMF samples were carried out as described previously (Woon et al., 2016;Jalaludin et al., 2017). The 2AB-labelled samples (10 μL of hydrolysate) were run on an HPLC instrument using an XBridge amide (4.6×250 mm, particle size 3.5 µm) column with a gradient elution system of ammonium acetate (pH 3.5) and acetonitrile as reported by Woon et al. (2016). The chromatography system consists of a Waters 600 pump, autosampler Waters 2707 with a Waters 2745 model fluorescent detector set at the wavelengths of 360 nm wavelength (excitation) and 426 nm (emission).

In vitro fermentation of saccharified OPMF using Lactobacillus rhamnosus
The fermentation of saccharified OPMF using L. rhamnosus GR-1 was carried out according to the methods by Shi et al. (2018) and Mueller et al. (2016) with slight modifications. A fresh overnight culture of L. rhamnosus GR-1 was prepared in MRS broth with carbohydrate source (Fluka Analytical) at 37 o C for 16 hrs at 180 rpm using an incubator shaker (Wisecube wis 20) in aerobic condition and cell density was determined based on turbidity measurement as indicated by an increased OD 600 value using UV-spectrophotometer (Spectronic 200, Thermo Scientific TM ). Subsequently, the cultured bacteria were collected by centrifugation at 6708×g for 5 mins (Gryozen Mini, Korea) and the bacteria were washed two times in phosphate buffered saline (PBS) supplemented with cysteine hydrochloride to remove MRS broth residue. The cell amount for a final starting OD 600 of 0.1 was determined. The bacteria (1% v/v) were resuspended in the MRS broth medium in the absence of any carbohydrate source. Subsequently, the fermentation was conducted in the presence of 1% (v/v) saccharide OPMF samples (1, 3 and 6 hrs) in a 100 mL Erlenmeyer flask with a final volume of 30 mL. Aerobic fermentation of the saccharified OPMF was carried out for 0, 12 and 24 hrs at 37°C at 180 rpm incubator shaker (Wisecube wis 20). The growth of L. rhamnosus GR-1 was measured based on OD 600 using a UV-spectrophotometer. The negative control was incubated without sugar and FOS was chosen as a positive control. All experiments were conducted in triplicates.

pH analysis
The pH of all saccharified OPMF samples (1, 3 and 6 hrs) was measured using Sartorius Basic PB-10 pH meter (Germany) after 0, 12 and 24 hrs of fermentation. An average of three replicates of each sample at each fermentation time was taken.

Statistical analysis
All data reported in this study was indicated as means ± SD. To determine if there were significant differences in the growth of L. rhamnosus GR-1 a twoway ANOVA and Tukey test were performed using the statistical software JASP. Comparison of pH data was carried out using one-way ANOVA and Tukey test. The confidence interval of 95% was used.

Results and discussion
The effects of saccharification and fermentation time of OPMF on the growth of probiotic L. rhamnosus GR-1 are as shown in Table 1. Based on the results, the individual effect of saccharification time on L. rhamnosus GR-1 growth showed a significant (p<0.05) increase in OD 600 from saccharification time of 1 to 3 hrs. However, further increase of saccharification time from 3 to 6 hrs did not show any significant change in the growth of L. rhamnosus GR-1. The significant increase in growth of L. rhamnosus GR-1 (p<0.05) showed that saccharified OPMF was able to support the growth of probiotic bacteria.
The increase in growth from 1 to 3 hrs of saccharification time may be due to the ease in using the substrate as the longer duration of saccharification will result in a lower degree of GU of the cellulose in OPMF (Meng et al., 2016). However, saccharification beyond 3 eISSN: 2550-2166 © 2022 The Authors. Published by Rynnye Lyan Resources FULL PAPER hrs may not have produced any further decrease in the GU of cellulose thus resulting in the insignificant growth measured. Results from Table 2 supported the mentioned possibility as it can be seen that the type of oligosaccharide after 3 and 6 hrs of saccharification (1, 2, 3 and 4 glucose units) were higher compared to 1 hr (1 and 2 glucose units). In addition, no increase in the type of oligosaccharide was observed between 3 and 6 hrs of saccharification.
A previous study reported that L. rhamnosus GR-1 grew on β-glucan oligosaccharides where it consistently consumed mono-and disaccharides and preferentially consumed tri-saccharides (degree of polymerisation (DP) 3) (Sims et al., 2014). Several studies have described that L. rhamnosus consumed both oligosaccharides (tri-and disaccharides) as well as glucose as reported in a study on the consumption of Oligomate 55 (galactooligosaccharide 55%) in fermentation media (Figueroa-Gonzalez et al., 2019). Table 1 also shows a significant individual effect (p<0.05) of fermentation time on the growth of L. rhamnosus GR-1. An increase in fermentation time from 0 to 12 hrs resulted in a significant increase (p<0.05) in the growth of L. rhamnosus GR-1. However, a further increase from 12 to 24 hrs showed a significant decrease (p<0.05) in the growth of the probiotic bacteria. In general, the longer the fermentation time, the higher the opportunity for the bacteria to consume the saccharified OPMF (Hawashi et al., 2017). Thus, this explained the significant increase (p<0.05) in growth when fermentation time was increased to 12 hrs. The decrease in growth when fermentation time was extended to 24 hrs may be due to the limitation of nutrients to support growth (Hawashi et al., 2017). The significant interaction between saccharification time and fermentation time as shown in Table 1 is elaborated in Table 3. The effect of increased saccharification time was dependent on fermentation time where at fermentation time of 12 hrs, growth of L. rhamnosus GR-1 increased significantly (p<0.05) from 1 to 3 hrs but not significantly different when further increased to 3 hrs. Similarly, the interactive effect between saccharification time and fermentation time can be observed for saccharification time of 6 hrs where the increase in fermentation time from 12 to 24 hrs resulted in a significant decrease (p<0.05) in bacterial growth. Table 3 also shows the combined effects of saccharification time and fermentation time compared to FOS. FOS samples showed a similar trend for growth to OPMF 1 and 3 hrs where there was a significant increase (p<0.05) when fermentation time was increased from 0 to 12 hrs. Increasing fermentation time from 12 to 24 hrs did not produce any significant difference in growth. Thus, OPMF samples showed similar growth compared to FOS suggesting the possible potential of OPMF as a prebiotic material. However, further studies need to be carried out to ascertain the potential.
The combined effect of saccharification time and fermentation time on pH during the growth of L. rhamnosus GR-1 using oil palm mesocarp fibre as carbon source was analysed as shown in Table 4. Comparison made among the samples showed that for saccharification time of 1, 3 and 6 hrs, fermentation up to 12 hrs showed a significant (p<0.05) decrease in pH. However, all OPMF samples (1, 3, and 6 hrs) did not show any significant changes (p>0.05) in pH after a further increase in fermentation time from 12 to 24 hrs. The trend showed for pH (   Table 3. According to Sims et al. (2014), an increase in OD 600 of the culture broth and a decrease in pH of the culture media is the result of shortchain fatty acid production and reflected the ability of the bacteria to grow on the substrates. It has also been reported that L. rhamnosus is able to increase the production of SCFAs such as acetate, propionate and butyrate (Leblanc et al., 2017). Thus, these observations further support the ability of the probiotic L. rhamnosus to grow on saccharified OPMF.
The results obtained (Table 4) also revealed that during fermentation for 12 hrs, an increase in saccharification time from 1 to 3 hrs, and subsequently to 6 hrs did not result in any significant (p>0.05) changes in pH for the growth of L. rhamnosus GR-1. However, when fermentation was extended for 24 hrs, OPMF saccharified for 3 hrs resulted in a significantly (p<0.05) decreased culture medium pH compared to OPMF 1 hr. Further increase in saccharification time from 3 to 6 hrs did not show any significant (p>0.05) difference in pH. The results suggested that an extended fermentation time was needed to realise the effects of increased saccharification time on pH.
Compared to FOS samples, the pH of all OPMF samples (1, 3 and 6 hrs) showed significantly lower (p<0.05) pH after fermentation for 12 and 24 hrs. As the lowering of pH may have been attributed to the production of short-chain fatty acids (Sim et al., 2014), the results suggested that saccharified OPMF may be able to produce more short-chain fatty acid by L. rhamnosus compared to FOS.

Conclusion
In our study, both saccharification time and fermentation time with 3 hrs and 12 hrs, respectively, showed a significant (p<0.05) effect on the growth of L. rhamnosus GR-1 using saccharified oil palm mesocarp fibre (OPMF) as carbon sources. The growth of L. rhamnosus GR-1 using OPMF was comparable to its growth when using FOS. In addition, the growth of L. rhamnosus GR-1 using OPMF saccharified for 3 hrs resulted in a significantly (p<0.05) decreased culture medium pH compared to FOS. Thus, this work suggested that saccharifying OPMF to oligosaccharides has the potential to be developed as a prebiotic for L. rhamnosus GR-1 probiotic.
Values with different superscript within the same row are significantly different (p<0.05).