Title Science and Technology Indonesia e-ISSN:2580-4391 p-ISSN:2580-4405 Vol. 7, No. 2, April 2022 Research Paper Optimization of Antibacterial Production of Endophytic Fungi with Various Sources of C, N, and pH using The Response Surface Methodology Hary Widjajanti1*, Elisa Nurnawati1, Muharni1, Eca Desriana Zahwa1 1Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Sriwijaya, Palembang, 30662, Indonesia *Corresponding Author e-mail: hary_widjajanti@unsri.ac.id Abstract Secondary metabolites extract of McB1 endophytic fungi from gelam (Melaleuca cajuputi Powell.) leaves have a high potential antibacterialactivityagainstEscherichiacoliATCC8739andStaphylococcusaureusATCC6538withflavonoidsandphenolasbioactive compounds. Thelowproductionofsecondarymetabolitesextract inthecultivationstageandthehighpotentialantibacterialactivity of bioactive compounds produced by McB1 endophytic fungi require special treatment for optimizing the secondary metabolites product. This ispossiblyachievedbyoptimizingthecompositionofthecultivationmedia, wherevarioussourcesofcarbon, nitrogen, and pH produce different amounts and classes of secondary metabolites. The objectives of the research are to obtain the optimum interactionbetweensourcesofcarbon,nitrogen, andpHfortheproductionofsecondarymetaboliteextractusingResponseSurface Methodology (RSM). The results showed that the highest extract (0.250 g) with the composition of sucrose as carbon source, yeast extract as nitrogen source, and pH 6. The optimization of the cultivation medium with composition 4.500 g/L sucrose, 0.480 g/L yeast extract, and pH 6.1 yielded 0.340 g secondary metabolites extract of McB1 endophytic fungi. The chromatogram profile of the optimized secondary metabolite extract revealed the presence of flavonoids, phenols, terpenoids, and tannins. Keywords Endophytic Fungi, Antibacterial Compound, Response Surface Methodology (RSM) Received: 13 November 2021, Accepted: 8 February 2022 https://doi.org/10.26554/sti.2022.7.2.149-157 1. INTRODUCTION Endophytic fungi live in plant tissues at a certain time to form colonies and produce the same bioactive compounds as the host plants, due to the genetic transfer followed by the coevo- lution process (Je�rey et al., 2008). From the result of previ- ous research the McB1 endophytic fungi of gelam leaves pro- duced secondary metabolites as antibacterial against Escherichia coli with a Minimum Inhibitory Concentration (MIC) of 100 `g/mL, metabolite extract of 0.250 g, and fungal biomass of 2.340 g (Widjajanti et al., 2019). E�orts are required to increase the low production of secondary metabolites at the cultivation stage 0,250 g/L and the potential for the activity of bioactive compounds produced by modifying the cultiva- tion media composition. Meanwhile, the di�erences in the composition of the cultivation media lead to di�erent amounts of metabolites and their pro�les. Discovering the most op- timal conditions in the growth process and the formation of secondary metabolites from isolates is the basis for optimizing cultivation media (Goutam et al., 2014), which is achieved by modifying the carbon, nitrogen source, and pH (Septiana et al., 2017). Carbon source is an important basic nutrient for fungi which is used as the main structure in providing energy for cell growth in metabolic processes. Sucrose as a carbon source also greatly a�ects the formation of antimicrobial compounds in endophytic fungi from Moringa oleifera plants (Arora and Kaur, 2019). Previous studies used glucose as carbon sources and increased the production of secondary metabolites in the form of beauvericin in Fusarium oxysporum (Lee et al., 2008) and Fusarium rodolens (Xu et al., 2009). The highest biosynthesis of �avonoid compounds was found after the use of dextrose as a carbon source in isolates of the fungus Aspergillus tamarii (Bose et al., 2019). In some cases the growth of the source fungi and the nitro- gen concentration greatly a�ect the production of secondary metabolites, it is often carried out several related studies to �nd the best nitrogen source in the formation of secondary metabolites. In this case, the most commonly used nitrogen sources are yeast extract, peptone, and sodium nitrate which are added to fungal nutrition (Arora et al., 2012). The optimal growth of fungi in the pH range of 5-8 (Gupta et al., 2010). Secondary metabolite production in the fungal https://crossmark.crossref.org/dialog/?doi=10.26554/sti.2022.7.2.149-157&domain=pdf https://doi.org/10.26554/sti.2022.7.2.149-157 Widjajanti et. al. Science and Technology Indonesia, 7 (2022) 149-157 group that Fusarium incarnatum produces the most optimum pigment at pH 5 (Himalini and Razia, 2018), while secondary metabolites were produced at the most optimum in Geosmithia pallida (Deka and Jha, 2018) and Fusarium solani at pH 6 Mer- lin et al. (2013). The condition of pH 7 greatly a�ects the formation of antimicrobial compounds in endophytic fungi Moringa oleifera (Arora and Kaur, 2019) while at pH 8 greatly a�ects the formation of naphthoquinones pigments in Fusarium verticilioides (Boonyapranai et al., 2008). The cultivation media can be optimized using Response Surface Methodology (RSM) to obtain the optimum factors. It also analyzes the secondary metabolite formation response in�uenced by several independent variables to enhance the response examined (Qiu et al., 2012). The fungus Aspergillus niger KE1 produced the highest lipase enzyme with an opti- mum nutritional composition that had been analyzed using RSM, namely 2% peptone, 0.100% olive oil, 0.500% glucose and 0.075% MgSO4.7H2O (Ilmi , 2021). The endophytic fun- gus Dichotomopilus funicola Y3 isolated from pigeon pea (Cajanus cajan) produced 4.9 times higher vitexin of 78.890 mg/L with the optimum media composition determined by RSM, namely 0.060 g/L L-phenylalanine, 0.21 g/L salicylic acid, and 0.19 g/L CuSO4·5H2O (Gu et al., 2018). In this study, we will try to optimize the growth medium by experimenting with variations in carbon, nitrogen, and pH sources using RSM in the hope that higher metabolite products will be obtained. Acording to Bezerra et al. (2008) Response Surface Methodology (RSM) is a combination of mathematical and statistical techniques based on the compatibility of poly- nomial equations with experimental data that must describe a data set with the aim of predicting statistically. Because of its high e�ciency in fermentation, media composition, and pro- cess conditions, the RSM method was chosen. Furthermore, it can explain the interaction of variables, and its accuracy is high (Kiran et al., 2016; Palukurty and Somalanka, 2016; Karthikeyan et al., 2010). RSM can be applied if a response is in�uenced by several variables, the aim is to optimize the interaction of these variables so that the best results are ob- tained. The objectives of the research to obtain the optimum interaction between sources of carbon, nitrogen, and pH for the production of secondary metabolite extract using Response Surface Methodology (RSM). 2. EXPERIMENTAL SECTION 2.1 Materials Pure culture of McB1 endophytic fungi from the previous research that isolated from Melaleuca cajuputi leaves. 2.2 Methods 2.2.1 Propagation of Endophytic Fungi Pure culture of McB1 endophytic fungi were propagated on PDA medium in test tubes and petri dish for stock and working cultures. Subsequently, it was incubated at room temperature until the fungi grew for aproximately 5-7 days. 2.2.2 Selection of Carbon, Nitrogen Sources, and pH Potato Dextrose Broth medium with composition of potato 200 g/L, peptone 0.500 g/L, yeast extract 0.800 g/L, (NH4)2 SO4 3 g/L, KH2PO4 2 g/L, 0.500 g/L MgSO4, 0.010 g/L phenylalanine, and 4% (w/v) carbon source (Merlin et al., 2013) used in cultivation. In the selection of carbon sources, the medium was modi�ed by using carbon sources in the form of glucose, dextrose and sucrose. In the selection of nitrogen sources, the medium was modi�ed by using nitrogen sources in the form of peptone, yeast extract, and sodium nitrate. In the selection of pH, the medium was modi�ed by using variation pH 5, 6, 7, and 8. 2.2.3 OptimizationofCultivationMediumCompositionwith Response Surface Methodology (RSM) The composition of the cultivation medium is optimized using Response Surface Methodology, and it includes three selected variables: carbon, nitrogen, and pH. The data of the selection from the previous test was used to determine the upper and lower limits of the Central Composite Design (CCD). This is also useful in the RSM method with the Design-Expert 7.0 from Stat-Ease (Qiu et al., 2012). This stage consisted of 9 fractional factorial points 23 for a factorial design compiling from 3 variables, which is enlarged by 6 starting and 5 center points. The total of all experimental units in this stage was 19 and was optimized using the culti- vation medium composition of potato 200 g/L, yeast extract 0.800 g/L, (NH4)2SO4 3 g/L, KH2PO4 2 g/L, MgSO4 0.500 g/L, phenylalanine 0.010 g/L, sources of carbon, nitrogen, and pH determined by Central Composite Design (CCD). 2.2.4 Extraction of Endophytic Fungi Secondary Metabo- lite The biomass of endophytic fungi was separated from the op- timization medium using �lter paper. The liquid-liquid frac- tionation (partition) was carried out with ethyl acetate solvent in a ratio of 1:1 and the extract collected was concentrated with a rotary evaporator to obtain the ethyl acetate extract of endophytic fungi. Subsequently, the separated biomass was dried using an oven to obtain the dry weight (Bhardwaj et al., 2015). 2.2.5 Thin Layer Chromatography (TLC) The optimized extract from McB1 endophytic fungi was dis- solved with ethyl acetate, spotted with a capillary pipette on a TLC plate (TLC, silica gel 60 F254, Merck), and eluted in a chamber that contained eluent with a ratio of n-hexane: ethyl acetate 3:2. When the eluent reached the boundary line to form a TLC chromatogram pattern, the plate was removed and the stain formed was viewed using 366 nm UV light. For vi- sualization observations, it was sprayed with 5% H2SO4 reagent and heated on a hot plate at a temperature of 80°C. The stains formed were identi�ed through color spots and the Rf value (Retardation factor) was determined using the formula below (Bele and Khale, 2011): © 2022 The Authors. Page 150 of 157 Widjajanti et. al. Science and Technology Indonesia, 7 (2022) 149-157 Rf = Distance traveled by component Distance traveled by solven 2.2.6 Data Analysis Data was analyzed with Analysis of Variance (ANOVA) at U 0.050. 3. RESULT AND DISCUSSION 3.1 The Carbon Source for McB1 Endophytic Fungi McB1 endophytic fungi grew and produced secondary metabo- lites on all sources of sucrose, dextrose, or glucose. Meanwhile, the weight of the ethyl acetate extract and the mass of biomass produced were shown in Figure 1. After 30 days of cultivation, the highest extract yielded and biomass weight was 0.250 g and 2.450 g with a carbon source of dextrose and sucrose, respec- tively. Monosaccharides were found to be the most e�ective carbon source for fungal growth. This is also evidenced in a similar study in Bose et al. (2019) that, dextrose is a simple type of carbon that can be metabolized by fungi more easily compared to other carbon sources. The metabolism process of monosaccharide-type carbon sources is easily broken down by the fungus isolate used quickly, characterized by the highest fungal biomass weight, this causes the dextrose concentration to decrease in the cultivation media. After the dextrose carbon source is depleted, the fungus regulates the use of other carbon sources in the media to be used for the formation of secondary metabolites in the idiophase. This is explained in Stanbury and Whitaker (1987) that the limited carbon concentration will induce the formation of secondary metabolites, limited carbon is indicated due to fast metabolism for cell growth. Figure 1. Fungal Biomass and Extract Weight from Carbon Source Optimization Sucrose belongs to the disaccharide group which is broken down into glucose and fructose by enzymes before it is metab- olized by fungi. According to Mao et al. (2005), this occurs through the use of substrates with a slow metabolism by fungi due to the inability to hydrolyze, characterized by non-optimal cell growth. Meanwhile, the formation of secondary metabo- lites is induced by slow growth due to the depletion of the main carbon source. Figure 1 shows the biomass of McB1 endophytic fungi which is not directly proportional to the secondary metabolites production. The use of sucrose produced a lower weight of biomass than dextrose, however, this is not shown in the pro- duction of secondary metabolites. Furthermore, high biomass weight did not produce higher secondary metabolite weight because cell growth has no relationship with their formation. According to Sanchez et al. (2010), biomass is formed at the cell growth stage which is dominantly synthesized at the expo- nential phase, while secondary metabolites are at the stationary to the lag phases. 3.2 The Nitrogen Source for McB1 Endophytic Fungi McB1 endophytic fungi also grew and produced secondary metabolites on all nitrogen sources, namely peptone, yeast extract, and NaNO3. The weight of the ethyl acetate extract and biomass produced are shown in Figure 2. After 30 days of cultivation, the highest extract and biomass weight were 0.390 and 1.360 g with nitrogen sources in form of yeast extract and peptone, respectively. The highest metabolite production was obtained after the use of yeast extract, which did not produce maximum fungal biomass, however, there was high production of biomass from peptone. Merlin et al. (2013) stated that the highest secondary metabolites production by the endophytic fungi of Fusarium solani was observed after the use of yeast extract. According to Septiana and Simanjuntak (2017), yeast extract is the best nitrogen source in producing antioxidant compounds by iso- lates of endophytic fungi from turmeric roots. Described by Wang et al. (1979), the amino acids found in yeast extract and peptone contain glutamic acid, glutamine, cysteine, methion- ine, arginine, asparagine, proline, and phenylalanine. Besides containing amino acids, yeast extract also contains several min- erals such as sodium, chloride, calcium, magnesium, potassium phosphate, and sulfate as elements used in the growth process by fungi. Figure 2. Optimization of Nitrogen Source Yields Fungal Biomass and Extract Weight 3.3 pH Range for McB1 Endophytic Fungi The McB1 endophytic fungi were able to grow and produce secondary metabolites at all tested pH values, which include © 2022 The Authors. Page 151 of 157 Widjajanti et. al. Science and Technology Indonesia, 7 (2022) 149-157 6, 7, and 8. The extract weight of the ethyl acetate and fungi biomass produced with variations in pH are shown in Figure 3. After 30 days of cultivation, the highest extract was 0.560 g at pH 6, while the biomass weight was 2.270 g at pH 7. Since the most optimum secondary metabolite production was obtained at pH 6, therefore, the fungi produced maximally in acidic pH. It has been previously examined by Gazi and Kanda (2004) that cell growth and the formation of secondary metabolites in fungi tend to be produced at optimal pH with a range of 5-7. Research conducted by Merlin et al. (2013) also found that the isolates from the endophytic fungi of Fusarium solani formed the highest secondary metabolites at pH 6. Figure 3. Fungal Biomass and Extract Weight as a Result of pH Optimization Acording to Rousk et al. (2009) pH a�ects the growth of fungi, starting from the growth of mycelium or the growth of fruiting bodies. The pH will a�ect the permeability of the fun- gal membrane, therefore the fungus will be unable to absorb important nutrients when a certain pH is not suitable. Acord- ing to Arora and Chandra (2010) the inhibition of the nutrient uptake process will a�ect the metabolic rate of the fungus. pH also related to the permeability characteristics of the fungal membrane so that it a�ects the uptake and loss of ions in me- dia nutrient for their growth. The e�ect of pH on secondary metabolite production varies greatly depending on the fungus species. The production of quinidine increased considerably in Fusarium solani at an initial pH of 6.2, but not in Diaporthe sp. at an initial pH of 6.8 (Rahmawati et al., 2021). 3.4 Results of Cultivation Medium Optimization for McB1 Endophytic Fungi In McB1 endophytic fungi, three factors were used to a�ect the weight of secondary metabolite extract with sucrose as carbon source with a value ranging from 0.360 g/L to 0.680 g/L and yeast extract as nitrogen source with a value between 0.160 g/L to 0.830 g/L, while the pH ranges from 5.1 to 6.8. Meanwhile, the range and level of the factors used can be reviewed in Table 1. The extract weight of the ethyl acetate and biomass of endophytic fungi optimized using sucrose, yeast extract, and pH are presented in Table 2. The 19 treatment points of the design gave a response in form of the McB1 endophytic fungi extract weight, as presented Table 1. The Composition of Medium Optimization for The McB1 Endophytic Fungi and The Range of Factors Tested Optimization Factor Range and Level -1.680 -1 0 1 1.680 Sucrose (g/L) 0.630 2 4 6 7.360 Yeast Extract (g/L) 0.160 0.300 0.500 0.700 0.830 pH 5.1 5.5 6 6.5 6.8 in Table 2. The highest extract weight was obtained in the center point at the 17th standard with the metabolite extract weight of 0.390 g. Figure 4. 3D-Surface Graphics for Surface and Contour Responses The Surface of McB1 Endophytic Fungi Extract. (a) 3D-Surface Graphics for Response Surface (b) Contour Graph for Response Surface 3.5 Response Model of McB1 Endophytic Fungi The data model was selected based on the response from the weight of the secondary metabolite extract by reading the re- sults of the sequential analysis of the sum of squares in line with the smallest p-value (p>0.050). According to the analysis of the summary statistics and the sequential sum of the square, it was concluded that the appropriate model was selected by the pro- © 2022 The Authors. Page 152 of 157 Widjajanti et. al. Science and Technology Indonesia, 7 (2022) 149-157 Table 2. Weight of McB1 Endophytic Fungi Extract from Cultivation Medium Optimization with 3 Factors using RSM Standard Sucrose (X1, g/L) Yeast Extract (X2, g/L) pH (X3 ) Extract Weight (Y, g) 1 2 0.300 5.5 0.130 2 6 0.300 5.5 0.180 3 2 0.700 5.5 0.090 4 6 0.700 5.5 0.230 5 2 0.300 6.5 0.290 6 6 0.300 6.5 0.270 7 2 0.700 6.5 0.100 8 6 0.700 6.5 0.190 9 0.630 0.500 6 0.110 10 7.360 0.500 6 0.270 11 4 0.160 6 0.160 12 4 0.830 6 0.250 13 4 0.500 5.1 0.180 14 4 0.500 6.8 0.250 15 4 0.500 6 0.280 16 4 0.500 6 0.360 17 4 0.500 6 0.390 18 4 0.500 6 0.340 19 4 0.500 6 0.31 gram. This was conducted to determine the optimum response of the secondary metabolite of the McB1 endophytic fungi and explain the relationship between the three factors. Therefore, the quadratic model in the selection analysis represented the most appropriate model used in this research. 3.6 Results of Analysis of Variance (ANOVA) and Interac- tion Between Factors on The Response of McB1 Endo- phytic Fungi Based on the data processing using Design Expert 11.0.0 and Analysis of Variance (ANOVA), the yeast extract, pH, and the 2FI model (interaction between 2 factors) have insigni�cant values. As shown in the table, each p-value has 0.551, 0.086, 0.170, 0.394 and 0.067, respectively, where p>0.050. This indicated that the use of nitrogen sources such as yeast extract, variations in pH, and the relationship between the two factors did not a�ect the production of secondary metabolites. Accord- ing toBaş and Boyacı (2007), a signi�cant data model provides accurate data to explain the relationship between the depen- dent and independent variables in the response surface analysis method. The use of a carbon source in form of sucrose had a sig- ni�cant value of 0.015 where p <0.050, which a�ected the production of secondary metabolite extracts. Similarly, the use of sucrose a�ected on the formation of secondary metabolites of McB1 endophytic fungi. This is because sucrose is a disac- charide that is di�cult to synthesize and is not favored by fungi. Therefore, other carbon sources are used until the condition of the �rst preferred source is exhausted, which causes metabolic imbalance and physiological stress. Martin and Demain (1980) stated that in a medium, a carbon source such as sucrose is used Figure 5. Results of TLC on Secondary Metabolite Extract of McB1 Endophytic Fungi (a) TLC of McB1 Endophytic Fungi Extracts at 366 nm UV Light (b) Chromatogram of McB1 Endophytic Fungi Extract After Spraying H2S04 5% longer by fungi and after the preferred source, while the latter is used for the biosynthesis of secondary metabolites. The use of sucrose, yeast extract, and pH is shown in form of contour plots and response surface graphs in Figure 4. Based on the analysis, there is an increase in the concentration of sucrose from 0.680 g to 4 g and yeast extract from 0.160 to 0.500 g. Furthermore, the use of sucrose more than 4 g and yeast extracts more than 0.500 g can reduce the production of secondary metabolites. The optimum concentration to increase the production of metabolites were 4 g of sucrose and 0.500 g of yeast extract. This decrease in production was explained by Tudzynski (2014) which stated that some nitrogen and excess © 2022 The Authors. Page 153 of 157 Widjajanti et. al. Science and Technology Indonesia, 7 (2022) 149-157 Table 3. Composition Formula for Medium Optimization of McB1 Endophytic Fungi Isolate Sucrose Yeast Extract pH Secondary Metabolites Desirability Level 4.500 g/L 0.480 g/L 6.1 0.340 g 0.853 carbon sources used in the cultivation medium cause inhibition of secondary metabolite formation by the substrate. Since these conditions signi�cantly a�ect the speci�c growth process, the cell growth rate becomes constant and there is no physiological imbalance that induces the formation of secondary metabolites leading to inhibition by the substrate. Figure 6. The Mechanism for The Biosynthesis of Terpenoids through The Mevalonic Acid Pathway (Flynn and Schmidt-Dannert, 2018) Based on the ANOVA yeast extract, pH and the 2FI model (interaction between 2 factors) have nonsigni�cant values. Each p-value shown in the table is 0.551, 0.086, 0.170, 0.394 and 0.067 where p>0.050. This indicates that the use factor ni- trogen source in the form of yeast extract, variations in pH and the relationship between the two factors did not a�ect the production of secondary metabolites of McB1 fungal isolate. Based on Figure 4, as the pH value increases from 5.5 to 6.5, the production of secondary metabolites also increases, and the optimum value is obtained at pH 6. According to Arora and Chandra (2010), the appropriate pH is among the factors that determine growth, product formation, and enzymes used in metabolic processes. The optimum pH under within the acidity range was able to a�ect the work of the enzymes pro- duced. This showed that fungi can grow optimally and produce secondary metabolites at a pH within the acidic range. 3.7 The Formulation for Medium Optimization of McB1 Endophytic Fungi Figure 7 provides optimal point solutions for each factor sug- gested by Design Expert 11.0.0. Meanwhile, the production of secondary metabolites was increased with in�uencing factors, namely sucrose, yeast extract, and pH range using the Design Expert 11.0.0 program with the speci�ed limits to produce the optimum value. The criteria for optimizing the response to the production of secondary metabolites are adjusted to the limits in Table 3. The mathematical model for the secondary metabolite pro- duction of McB1 endophytic fungi obtained in the optimization was Y= -8.297 + 0.185X1 + 3.022X2 + 2.443X3 + 0.062X1X2 - 0.015X1X3 - 0.350X2X3 – 0.013X12 - 1.213X22 - 0.179 X32, where the variables with the most optimum response were sucrose (X1) of 4.500 g/L, yeast extract (X2) of 0.480 g/L and pH (X3) of 6.1. Moreover, the estimated response obtained was 0.340 g with a desirability of 0.853, which is approximately 1. According to Raissi and Farsani (2009), desirability is a value showing the program’s ability to ful�ll the desires based on the criteria set on the �nal product. Therefore, the most optimal formula accepted is that with the maximum desirability value in a range of 0 to 1. The desirability value closer to 1 indicates that the program’s ability to produce the desired product is getting more perfect. 3.8 TLC Secondary Metabolite Extract from Optimization of McB1 Endophytic Fungi Thin-Layer Chromatography was used to examine the opti- mized secondary metabolite extract (TLC). The fungi pro- duced secondary metabolites from several groups of com- pounds as the medium composition of the cultivation process changed, including phenols, �avonoids, terpenoids, and tannins (Figure 5). The bioactive compounds were identi�ed by examining the color spots formed on the TLC plate. Based on Figure 5, the secondary metabolite extract of the McB1 endophytic fungi in TLC obtained yellow phenol compounds and �avonoids with an orange color. According to Bungihan and Matias (2013), yellow-colored compounds are classi�ed as phenolic, while �avonoids have a brownish-yellow to red color. Furthermore, the two other spots observed were blackish-brown spot which was identi�ed as tannins, while purple spots were identi�ed as terpenoid. Bioactive compounds from the tannin group form green, brown to black spots, while terpenoid formed pink to purple or violet after being sprayed with 5% H2SO4 and heated. © 2022 The Authors. Page 154 of 157 Widjajanti et. al. Science and Technology Indonesia, 7 (2022) 149-157 Figure 7. The Mechanism of Tannin Biosynthesis through The Shikimic Acid Pathway (Tohge et al., 2013) Based on the results of TLC (Figure 5), two new groups of the compound were added, namely terpenoids and tannins were added to the secondary metabolite compounds of the McB1 endophytic fungi. In Widjajanti et al. (2019), the group of compounds produced by McB1 endophytic fungi was phe- nolic and �avonoids, due to changes in the composition of the cultivation medium used. In a previous study, cultivation used the PDB medium (200 g of potatoes and 20 g of glucose in 1 L of distilled water). In the optimization, a medium with a more complete composition was used (200 g potato, 4 g su- crose, 0.800 g yeast extract, 3 g (NH4)2SO4, 0.500 g MgSO4, 0.010 g phenylalanine in 1 L of aquadest). Abo-Elmagd (2014) also stated that the nutrient source can induce or eliminate a metabolite compound produced by fungi. The terpenoid group is formed due to di�erences in the composition of the carbon source. The formation of acetic acid in cellular processes is in�uenced by carbon metabolism. Hence, it was used as a substrate in primary metabolism to produce acetyl CoA as the main ingredient in the formation of terpenoid compounds during the biosynthesis of the mevalonic acid pathway (Figure 6). According to Agusta (2006) and Flynn and Schmidt-Dannert (2018), acetic acid was condensed to pro- duce acetyl coenzyme A, after activation, which is the reaction step of terpenoid biosynthetic. The reaction of acetyl coen- zyme A produced Isopentenyl Pyrophosphate (IPP), which is isomerized into Dimethyl Allyl Pyrophosphate (DMAPP) by the isomerase enzyme. Moreover, IPP is an active isoprene unit that combined head-to-tail with DMAPP, which is the �rst step of isoprene polymerization to produce terpenoids. Based on the chromatogram pro�le, blackish-brown spots formed were assumed to be tannin compounds, due to the use of L-phenylalanine in the composition of the medium optimization. Meanwhile, the use of L-phenylalanine as a precursor for the formation of tannins is presented in Figure 7. According to Tohge et al. (2013), the shikimic acid pathway is used in the synthesis of hydrolyzable tannin groups and compounds based on the amino acid phenylalanine. Since the amino acid phenylalanine is used in the formation of gallic acid, therefore, the tannins are formed through esteri�ed gallic acid derivatives. From fungus McB1 isolate tannin support as an antibacterial compound. 4. CONCLUSION The optimization of the cultivation medium with composi- tion 4.500 g/L sucrose, 0.480 g/L yeast extract, and pH 6.1 yielded 0.340 g secondary metabolites extract of McB1 endo- phytic fungi. The optimized secondary metabolite extract’s chromatogram pro�le revealed the presence of �avonoids, phe- nols, terpenoids, and tannins. The chromatogram pro�le of the optimized secondary metabolite extract showed the pres- ence of �avonoids, phenols, terpenoids, and tannins that as an antibacterial. © 2022 The Authors. Page 155 of 157 Widjajanti et. al. Science and Technology Indonesia, 7 (2022) 149-157 5. ACKNOWLEDGEMENT The DIPA of the Public Service Agency of Universitas Sriwi- jaya 2021 funded the research and publication of this article. 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Page 157 of 157 INTRODUCTION EXPERIMENTAL SECTION Materials Methods Propagation of Endophytic Fungi Selection of Carbon, Nitrogen Sources, and pH Optimization of Cultivation Medium Composition with Response Surface Methodology (RSM) Extraction of Endophytic Fungi Secondary Metabolite Thin Layer Chromatography (TLC) Data Analysis RESULT AND DISCUSSION The Carbon Source for McB1 Endophytic Fungi The Nitrogen Source for McB1 Endophytic Fungi pH Range for McB1 Endophytic Fungi Results of Cultivation Medium Optimization for McB1 Endophytic Fungi Response Model of McB1 Endophytic Fungi Results of Analysis of Variance (ANOVA) and Interaction Between Factors on The Response of McB1 Endophytic Fungi The Formulation for Medium Optimization of McB1 Endophytic Fungi TLC Secondary Metabolite Extract from Optimization of McB1 Endophytic Fungi CONCLUSION ACKNOWLEDGEMENT