Process parameters optimization for biosynthesis of gibberellic acid using orange waste as an alternative substrate

Gibberellic acid (GA 3 ) is the most important gibberellin that affects various plant developmental processes. As such, it has an international market value of $106 million dollars. However, it is costly in the market because of high downstream processing cost that is linked to its current mode of production via submerged fermentation. Solid-state fermentation, in contrast, minimizes this limitation of cost when optimal process parameters are used. Hence, this study utilized orange waste as a cheap substrate in the bio-production of gibberellic acid through the optimization of three process parameters (incubation temperature, pH and substrate concentration). The study also investigated the interactive effects of these parameters on the yield of gibberellic acid. Using Design Expert ® software, a 19-run experiment, varied at five levels, was generated. Accordingly, each fermentation reaction that had been supplemented with 0.03% FeSO 4 .7H 2 O and 0.01% (NH 4 ) 2 SO 4 was inoculated with a constant fungal inoculum. The highest yield of gibberellic acid was with a combination of 19.5 g of substrate set at 30 °C incubation temperature with a pH of 5.5. The interaction between the three factors was a linear relationship. The bio-production of gibberellic acid using orange waste as an alternative substrate suggests the possibility of a further reduction in cost of production of high-end value metabolites when proper optimization is carried out.


INTRODUCTION
Plant hormones, are small signaling molecules that affect plant growth and development (Bilkay et al., 2010;Shani et al., 2013;Sleem, 2013), and include auxins, cytokinins, gibberellins, abscisic acid, and ethylene.Gibberellins are a large family of structurally related diterpenoid carboxylic acids that occur in green plants and some microorganisms, which serve as plant growth regulators (Machado et al., 2002;Urbanová et al., 2011;Rangaswamy, 2012).Gibberellic acid (GA3) is the most important gibberellin.It has an impact on various plant developmental processes, including stem elongation, seed germination, dormancy break and mobilization of endosperm reserves, enzyme induction, flowering, crop yield, sex expression, leaf and fruit senescence (Rodrigues et al., 2009;Luís et al., 2013;da Silva et al., 2013;Camara et al., 2018).Similarly, GA3 has diverse applications in agriculture, brewery industry, biotechnology, tissue culture and viticulture (Ohlsson and Berglund, 2001;Marzouk and Kassem, 2011;Ferrara et al., 2014;Archana and Sivachandiran, 2015;Beerappa et al., 2019;Demes et al., 2021;Ghimire et al., 2021;Yadav et al., 2022) and is gaining attention all over the world with an international market value of 106.53 million USD in 2021 (HNY Research Limited, 2022).Furthermore, GA3 can be obtained by either microbial fermentation as secondary metabolite, extraction from plants or chemical synthesis, though economically not feasible by plant extraction and chemical synthesis (Pandey et al., 2008;Luís et al., 2013).GA3 has been synthesized using Gibberella fujikuroi, Aspergillus niger, Rhizobium phaseoli, Azospirillum brasilense, Pseudomonas spp, and Phaeosphaeria spp.(Rademacher, 1994;Escamilla et al., 2000;Karakoc and Aksoz, 2006;Bilkay et al., 2010;Sleem, 2013;Li et al., 2022).GA3 production by submerged fermentation (SmF) is affected by different physical factors such as pH, incubation time and temperature and also gives a low yield with high production costs, which result into a higher sales price (Qian et al., 1994;Camara et al., 2018;Ben Rhouma et al., 2020).This high cost is due to the poor yield generated and its presence in dilute form, which results in higher downstream processing and waste water disposal expenses, as well as a high cost of importation for developing countries (Machado et al., 2002;Rangaswamy, 2012).These have restricted its use to preclude application for plant growth promotion, except for certain high value plants (Machado et al., 2002).
Several studies aimed at decreasing the production costs of GA3 through different approaches have been reported.Some evaluated different fermentation processes (Machado et al., 2002;Pandey et al., 2008;Rodrigues et al., 2009) and optimized culture conditions (Escamilla et al., 2000;Karakoc and Aksoz, 2006;Siddikee et al., 2010;Ben Rhouma et al., 2020).Others studied the potential of genetic modification of fermentation microbe (Li et al., 2022), and utilized cheaper agro-wastes (Machado et al., 2002;Rangaswamy, 2012;da Silva et al., 2013;Kobomoje et al., 2013).In their review, Camara et al (2018) summarised different substrates and fermentation strategies used for the production of GA3 using Fusarium spp such as Wheat bran (1.2g/kg; 6.8g/kg; 3g/kg (Kumar and Lonsane (1990); Agosin et al (1997); Bandelier et al (1997), respectively) and Cassava (250mg/kg (Tomasini and Fajardo, 1997)) for solid-state fermentation (SSF).For SmF, Glucose and lactose yielded 25mg/L (Tomasini and Fajardo, 1997); Glucose and rice flour yielded 3,900mg/L and 1,175mg/L (Escamilla et al., 2000 andUthandi et al., 2010, respectively) and Glucose alone yielded 15g/L and 216mg/L (Rangaswamy, 2012 andAlbermann et al., 2013, respectively).Similarly, de Oliviera et al (2017) compared the effect of different fermentation systems with citric pulp as the substrate and recorded highest GA3 production via SSF (7.6g/kg; 946mg/L) than via SmF (2.74g/kg; 236ml/L).The authors also tried a semi solid-state fermentation (SSSF) with the citric pulp and recorded 7.69g/kg; 331mg/L of GA3 suggesting a possible paradigm shift to the system in the future.In this locality, orange waste is a cheap and readily available agro residue that is locally generated throughout the season and is relatively not utilized for any process, but thrown into dump areas.SSF as an alternative cost effective method could make use of agroindustrial residues as substrates towards GA3 production, and for the production of high-value products such as secondary metabolites (Rangaswamy, 2012;Kobomoje et al., 2013;Luís et al., 2013;Ja'afar and Shitu, 2022).SSF system not only minimizes production and extraction costs, but also increases yield of the required end product (Pandey et al., 2008;Admassu et al., 2015;Sindhu et al., 2015).However, its scale-up is difficult due to variances in fermentation process parameters (Camara et al., 2018) amongst which are temperature, pH, agitation, aeration, humidity and moisture (Karakoc and Aksoz, 2006;Singhania et al., 2009).
Therefore, this study investigated the potential of orange waste as an alternative substrate, and identified the optimimal process parameters conditions (pH of media, incubation temperature and substrate concentration) for GA3 biosynthesis by employing a statistical approach.

Aspergillus niger strain
Aspergillus niger (A.niger) was a kind donation from the Department of Microbiology, Modibbo Adama University, Yola.It was stored on PDA slants until the time of use.

Substrate collection and processing
Orange waste (orange peel and left over pulp) was obtained from local orange sellers.It was washed with clean water and then air-dried.Finely ground powder was stored in airtight container for further use.

Solid-state fermentation optimization
To determine the optimum process parameters for GA3 production, a mathematical approach using Design Expert ® (version 6) was employed to design the experiment.Independent factors; pH of media, incubation temperature and substrate concentrations, varied at five levels generated 19 experiments (Table 1).To each experiment, 3.5 ml of the inoculum was added.

Media preparation
Media was prepared according to the method described by Machado et al. (2002).Briefly, to a specific gram of the processed substrate as designed by the software, it was dissolved in an equivalent mineral solution containing 0.03% FeSO4.7H2O and 0.01% (NH4)2SO4 in a ratio of 1:4 v/w (mineral solution: substrate concentration).The pH of the final media was adjusted as provided (Table 1) and it was sterilized by autoclaving at 121 °C for 15 mins.This was subsequently inoculated with 3.5 ml of the inoculum.Media was mixed thoroughly and incubated at specific temperatures generated by the software (Table 1) for 5 days.

Extraction of GA3
The extraction of GA3 was done as described by Rangaswamy (2012).Briefly, distilled water was added to the fermented product in each flask in a ratio of 10:1 v/w (distilled water: initial substrate concentration) of the substrate initial concentration.The mixture was shaken vigorously.The slurry from each flask was filtered through muslin cloth and then through a filter paper.The filtrate was centrifuged at 10,000 rpm for 10 min and supernatant was collected.

Purification and quantification of GA3
Purification of GA3 was done as described by Ergün et al. (2002) with little modifications of solvent final volumes.Briefly, to 5 ml of the extracted supernatant, 20 ml of solvent consisting of methanol, chloroform and ammonium hydroxide (12:5:3 v/v) was added.Additional 10 ml of distilled water was added to the mixture and shaken well.In a separating funnel, the bottom layer chloroform was removed and the methanol in the upper aqueous phase was evaporated.The pH of the remaining solution was adjusted to 2.5 and extracted with ethyl acetate.The ethyl acetate phase was collected and evaporated to dryness in a water bath at 50 °C.The dried material was dissolved with ethanol and GA3 concentration was estimated spectrophotometrically by comparing with a standard of pure GA3 at 254 nm.

RESULT AND DISCUSSION
In an effort to determine the optimum process parameters for the production of GA3 by the fungus A. niger, three process parameters (incubation temperature, pH of media and substrate concentration) were investigated through response surface methodology.For this purpose, a 19-run experiment based on face-centered central composite design (FCCCD) was generated by Design Expert ® , and the result is presented in Table 1 while Table 2 shows the statistical variance analysis.Figure 1 shows pictorial representation of extraction and purification of GA3.The statistical model representing the predicted concentration of GA3 as a function of the independent variables within the region under investigation is expressed in coded form (Equation 1): 3  = (0.6202 + 1.5078 × 10 −0.03  − 0.0137 + 0.0488) (1) where A, B and C are the coded variables for temperature, pH and substrate concentrations, respectively.
Furthermore, the model evaluation was performed through analysis of variance (ANOVA) and coefficient of determination (R 2 ) that measures the goodness of fit of the regression model (Table 2).The good agreement between the adjusted R 2 and predicted R 2 showed how fit the model was in predicting the best combination of three process parameters.
The relationship between the response and experimental levels of variables in the study were expressed in the form of a graphical plot (Fig. 2). Figure 2 shows that there is no statistically significant interaction between the variables, rather a linear expression of individual parameter.An increase in substrate concentration resulted to a higher increase in GA3 concentration, whereas, changes in pH and temperature showed no any significance effect on the yield.Gibberellic acid can also be synthesized from the substrate only without any supplement, but it produces lower result when compared to same treatment with supplement (Ben Rhouma et al., 2020).A preliminary fermentation was performed to ascertain the requirement of supplement in the media.Hence, a result of 186mg and 116mg of GA3/g of substrate was observed with and without supplement, respectively.As such, all optimization experiments conducted in this study had 0.01% (NH4)2SO4 and 0.03% FeSO4.7H2O as supplement in the final media composition.GA3 is synthesized when the fungus is brought to stationary phase by nitrogen diminishing with an abundant carbon source (glucose) in the medium (Pandey et al., 2008).Utilization of substrate was observed to be slow during the first 24 hours, however, the whole substrate was relatively consumed by day five of the fermentation period (media was relatively dark with the fungus covering all over it).This study did not consider inoculation time to production of GA3 because previous study had shown its minimal effect on GA3 production (Li et al., 2022).However, Karakoc and Aksoz (2006) reported an initial increase of GA3 production by 12 hours of incubation and reached its peak by 72 hours.This was speculated to be because of the microbe used since bacterium normally has a shorter doubling time (Pirt 1967;Reischke et al., 2014).In fact, for GA3 production, the fungi Fusarium moniliforme and Gibberella fujikuroi, and the bacteria belonging to the genus Azotobacter and Azospirillum are the microbes of choice (Rademacher, 1994).
Although not statistically significant, it was observed that GA3 production decreased at low temperatures even at high substrate concentrations.The best results were obtained at 30 °C, which correlates with most reports from literatures (Karakoc and Aksoz, 2006;Rodrigues et al., 2009;Bilkay et al., 2010;Rangaswamy, 2012). However, Li et al. (2022) reported a range of 26 -28 ℃, but significantly decreased when it was higher than 32 ℃.Similarly, Machado et al. (2002) maintained a temperature of 29 ℃ in their GA3 production when they noticed insignificant effects between 28 -30 ℃.Furthermore, a slight increase in temperature had no any significant effect on the yield of GA3 in this study.Similarly, the pH of the medium has no any significant effect on the yield, which also correlates with results of other literatures (Rodrigues et al., 2009;Rangaswamy, 2012).However, a pH of 5.5 seems to be the optimum as earlier reported (Escamilla et al., 2000;Bilkay et al., 2010).In contrast, Li et al. (2022) reported an optimal pH of 4, while Karakoc andAksoz (2006) andSiddikee et al. (2010) reported an optimal pH of 7 for Pseudomonas and Methylobacterium spp., respectively.When studying the kinetics of GA3 production, Machado et al. (2002) observed that irrespective of how high the initial pH of media was, it comes down to a range of 5.3 -5.6 within the first 24 hours of fermentation and maintains that until the end of the fermentation process.In this study, the yield of GA3 was observed to be dependent on the amount of substrate concentration; the yield increased with an increase in substrate concentration (Fig. 2).Similar studies with such claims have been reported (Escamilla et al., 2000;Ben Rhouma et al., 2020).This high utilization of the substrate is, perhaps, associated with the high lignocellulose content of orange peels and the cellulolytic nature of cellulases in Aspergillus niger.Cellulases from A. niger and Trichoderma reesei have been shown to be of choice during biomass pretreatment processes because of their high cellulolytic potential (Rangaswamy, 2012).Thus, with a substrate concentration of 19.5 g and a pH of 5.5 at 30 °C, the highest amount of GA3 was obtained.The yield of GA3 (2.74g/19.5g(~140mg/g) of orange waste (w/w)) obtained in this study is somewhat higher than that obtained from previous studies, (105mg/g of Jatropha seed cake, Rangaswamy, 2012; 0.925mg/g of Coffee husk, Machado et al., 2002;19.3mg/g of Corn flour, Qian et al., 1994).Optimization studies have traditionally been based on individual parameter variation while keeping other parameters constant (Karakoc and Aksoz, 2006;Siddikee et al., 2010;Camara et al., 2018).Mathematical models that take into account all individual variables have been reported previously (Escamilla et al., 2000;Machado et al., 2002;Ja'afar et al., 2018;Ben Rhouma et al., 2020;Li et al., 2022).Other designs used for GA3 optimization include Plackett Burman (Li et al., 2022) and Taguchi (Ben Rhouma et al., 2020).

CONCLUSION
Optimization of process parameters in SSF has increased the yield of GA3 production.Similarly, the bioavailability of orange waste towards the improved synthesis of GA3 through mathematical optimization suggests the economic significance of this abundant and cheap agricultural residue that has not been harnessed.Utilization of this agro-residue would reduce the cost of GA3 and other important byproducts hitherto were costly and not readily available and affordable.Nonetheless, further research is required to upscale the production of this hormone.

Table 1 :
Solid-state fermentation experimental runs and yield of GA3

Table 2 :
ANOVA results for response surface linear model of GA3 production