Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 19  |  Issue : 4  |  Page : 321-329

Optimization and molecular characterization of novel Aspergillus spp. producing invertase enzyme


Department of Microbial Genetics, National Research Centre, Dokki, Giza, Egypt

Date of Submission18-Jun-2020
Date of Decision20-Jul-2020
Date of Acceptance23-Jul-2020
Date of Web Publication04-Jan-2021

Correspondence Address:
PhD Rasha G Salim
Department of Microbial Genetics, National Research Centre, Dokki, Giza, 12622
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/epj.epj_34_20

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  Abstract 


Background and objective Invertase, one of the most important enzymes used in industrial and pharmaceutical applications, has been produced from different Aspergillus spp. Statistical and mathematical tools [response surface methodology (RSM)] have been carried out to optimize culture conditions to facilitate maximum enzyme production. This investigation aims to screen the ability of some Aspergillus spp. to produce invertase enzyme, to optimize the culture parameters, and to detect the genetic diversity between them.
Materials and methods A total of five fungal strains were tested for the production of invertase. The most promising strain was selected for optimization. Optimization experiments were carried out to obtain maximum enzyme production, and a molecular marker (RAPD-PCR) was used to differentiate between these strains.
Results and conclusion Some Aspergillus spp. were examined to produced invertase enzyme after 2 days of cultivation. Aspergillus niger recorded the highest enzyme production (6.8 U/ml). Ten RAPD-PCR primers were used to differentiate between Aspergillus spp. A total of 131 bands were amplified in the five strains of Aspergillus spp. Based on RAPD-PCR analysis, the highest similarities obtained between A. parasiticus and A. niger showed 75%. Moreover, the RAPD-PCR technique is a good tool for differentiation between the Aspergillus spp. To optimize culture condition, RSM was used to increase invertase production by A. niger. Temperature, pH, and incubation time dramatically affect invertase yield. A combination of these factors (pH 5, 35°C, and incubation for 72 h) was optimum for maximum production of invertase (8.2 U/ml). Our results employed RSM to elucidate the combination of effective factors such as temperature, pH, and incubation time to obtain a high yield of an important enzyme, invertase, from A. niger, used as a promising candidate for industrial applications.

Keywords: Aspergillus spp, invertase, optimization and molecular characterization, RAPD-PCR, response surface methodology


How to cite this article:
Salim RG, Abo-Sereh NA, Khalil BE. Optimization and molecular characterization of novel Aspergillus spp. producing invertase enzyme. Egypt Pharmaceut J 2020;19:321-9

How to cite this URL:
Salim RG, Abo-Sereh NA, Khalil BE. Optimization and molecular characterization of novel Aspergillus spp. producing invertase enzyme. Egypt Pharmaceut J [serial online] 2020 [cited 2021 Jun 20];19:321-9. Available from: http://www.epj.eg.net/text.asp?2020/19/4/321/306141




  Introduction Top


β-Fructofuranosidase (EC.3.2.1.26) is the official name for invertase, which implies that the hydrolysis of the terminal non-reducing β-fructofuranoside residues in the β-fructofuranosides reaction is catalyzed by this enzyme [1]. Invertase is considered the most important enzyme that is produced from different organisms, such as yeast, bacteria, and filamentous fungi as good producers for invertase enzyme, which is used in various industrial applications with potential effects. It is used in fondants, soft-centered sweets, lactic acid, alcoholic drinks, and artificial honey industries owing to its sweetening effects. The production of inverted sugar is one of invertase’s numerous applications owing to its sweetening effects, which are more than sucrose [2]. Other applications of this enzyme are seen in drug and pharmaceutical industries; moreover, the enzyme acts as an antioxidant, an immune booster, and used in treating some cases of cancer such as stomach and bone [3],[4].

The optimization of the enzyme production in general and invertase production in particular includes fermentation conditions to obtain high enzyme yield and high microbial growth. Classical optimization methods involve identifying the various factors that may influence enzyme yield, and then, varying one of the factors at the same time keeping the rest constant. This methodology is a single-dimensional inquiry procedure, which though simple, does not achieve optimized conditions as it fails to consider interactions between factors. Therefore, in finding solutions to these obvious challenges, scientists designed statistical and mathematical procedures that circumvent these shortcomings. One of such statistical and mathematical procedure is response surface methodology (RSM). RSM is an experimental approach that efficiently runs ideal conditions for multivariable strategy [5]. According to Ting et al. [6], RSM is an assemblage of mathematical and analytical procedures that design experiments, build models, measure responses, evaluate effects and relationship between groups of controlled factors under experimental conditions, and search for the optimum conditions in bioprocess optimization. In this study, RSM has been applied to optimize cultural conditions for the overproduction of invertase by Aspergillus niger grown on PDP. Molecular markers provide additional tools for characterization, differentiation, assessment of genetic relatedness, and diversity in collections. Among all molecular markers, RAPD-PCR technique of DNA fingerprinting has been used in this work, which is widely used in conservation biology because of its quick results, cost-effectiveness, easy analyzed results, and reproducibility [7].


  Materials and methods Top


Fungal strains and culture conditions

Five isolates of Aspergillus spp. were used in this study: A. niger, A. terreus, A. flavus, A. ochraceus, and A. parasiticus. These strains were cultivated in potato dextrose agar (Merck KGaA, Germany) at 28°C for 4 days and kept at 4°C. Three isolates were previously identified in microbial genetic department, NRC, by Salim et al. [8] as A. ochraceus Egy2 LC360803, A. flavus Egy3 under accession number LC368455, and A. niger Egy4 LC368456, and two isolates were friendly provided from the toxin department NRC. The experiments were performed using a production medium according to Dinarvand et al. [9]. It was slightly modified by adding sucrose 30 g/l, yeast extract 2.0 g/l, NaNO3 2 g/l, MgSO4 0.05 g/l, and K2HPO4 0.5 g/l, before sterilization at 121°C for 15 min. Erlenmeyer flasks (250 ml) containing 50 ml of the production medium were inoculated with stock culture and incubated at 30°C with 150 rpm shaking for 48 h.

Invertase assay

Invertase activity was assayed according to Miller [10] after 10 min of incubation of 0.2 ml enzyme solution with 1.8 ml of 1% sucrose in 0.2 M sodium acetate buffer (pH 5) at 50°C. Reducing sugars were quantified by addition of 1 ml of dinitrosalicylic acid to stop the reaction; 1 ml of dinitrosalicylic acid was added in boiling water for 10 min. Finally, absorbance was read at 540 nm in spectrophotometer (JASCOV-730; Jasco, Tokyo, Japan). One unit of invertase was defined as the amount of enzyme that catalyzed 1 μmol of reducing sugar/min.

Experimental design for response surface methodology and statistical analysis

In this study, three autonomous factors (temperature, pH, and incubation time) were represented at two levels, high concentration (+1) and low concentration −1), in twenty runs, as shown in [Table 2]. Each row represents a trial run, and each column represents an independent variable concentration. With the insignificant ones eliminated, a smaller and more fitting collection of factors was obtained and analyzed.
Table 2 Design of different trials of the RSM for independent variables and responses by Aspergillus niger

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The design of 20 experiments and the coded and un-coded levels of the three investigated independent variables are listed in [Table 2]. The second-order observed model can be achieved from the experimental data, and the relationship between the response yield (invertase activity) and the variables through polynomial regression analysis. The form of the second-order polynomial model is as follows:



where YActivity is the predicted production of invertase (U/ml) and X1, X2, and X3 are the independent variables corresponding to the chosen affecting factors. ß0 is the intercept; ß1, ß2, and ß3 are linear coefficients; ß11, ß22 and ß33 are quadratic coefficients; and ß 12, ß13 and ß23are cross-product coefficients [11].

Statistical analysis

The statistical analysis of the model was performed to assess the analysis of variance. Statistical significance of the model equation was determined by Fisher’s test value, and the proportion of variance explained by the model was given by the assessment of multiple coefficients for each variable. The quadratic models were showed as contour plots (3D), and the response surface curves were generated by using STATISTICA (0.6) (STATSOFT).

Molecular characterization of fungal strains

Extraction of genomic DNA

Using the DNeasy plant mini kit (Qiagen Sciences, Maryland, USA), extraction of genomic DNA was performed by following the manufacturer’s instruction manual cat No.69104.

Differentiation of Aspergillus spp. using RAPD-PCR analysis

A total of 10 RAPD primers were used in the detection of polymorphism among the Aspergillus spp. These primers were synthesized by Metabion Corp. (Planegg-steinkirchen, Germany). The nucleotide sequences and primers code are presented in [Table 1]. The amplification reactions of PCR were carried out as mentioned by Adawy et al. [12]. Reactions were performed in 25-μl volume composed of 1x reaction buffer, 0.2 mmol/l of dNTPs, 1.5 mmol/l MgCl2, 0.2 μmol/l of primer, 0.5 unit of Taq polymerase (Qiagen Ltd, Germany), and 50 ng of template DNA, in sterile distilled water. PCR amplification of the DNA was performed in a Perkin Elmer thermal cycler 2400 programmed to fulfill 40 cycles. The temperature profile in the different cycles was as follows: an initial strand separation cycle at 94°C for 5 min followed by 40 cycles comprised of a denaturation step at 94°C for 1min, an annealing step at 36°C for 1 min, and an extension step at 72°C for 2 min. The final cycle was a polymerization cycle for 7 min at 72°C. PCR products were mixed with 2-μl gel loading dye and resolved by electrophoresis in a 1.5% agarose gel containing ethidium bromide (0.5 mg/ml) in 1× TBE buffer at 120 volts. A 100-bp DNA ladder (promega) was used as a molecular size standard. PCR products were visualized under UV light and documented using a XR+ Gel Documentation System (Bio-Rad, Hercules, California, USA).
Table 1 The RAPD-PCR primer name and sequence

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Data analysis

The amplified fragments were scored as present (1) or absent (0). Ladder 100-bp DNA was used to identify the molecular weights of fragments. Among the fungal isolates, the similarity matrix was calculated according to Coelho [13] and Rohlf [14], Unweighted Pair-Group Method with Arithmetical average was used to design the dendrogram for similarity coefficient.


  Results Top


Screening of some Aspergillus spp. for invertase enzyme production

Among five Aspergillus spp., A. niger presented the highest invertase production (6.9 U/ml) after 48 h of cultivation, whereas A. parasiticus presented the lowest invertase production (0.8 U/ml) after 48 h of cultivation; invertase production of A. terreus, A. flavus, and A. ochraceus was 4.5, 6.6, and 4 U/ml, respectively ([Figure 1]).
Figure 1 Invertase activity for Aspergillus strains.

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Optimization by response surface methodology for extracellular invertase production produced by A. niger using RSM

Statistical and mathematical analysis of multivariable data obtained from RSM is one of the most important tools to improve and optimize invertase production by A. niger. In the RSM, a central composite model was selected for invertase production using a 20-run experimental design with important factors such as temperature, PH, and incubation time. 20 trials matrix with three factors and three levels (−1, 0, and +1) including three replicates at the central point, [Table 2] illustrated the independent variables with coded matrix, responses furthermore experimental and predicted values for invertase activity. The modification in the enzyme activity was observed during the twenty runs of the experiments

The alteration within the enzyme activity was owing to the different conditions in the experiment in each run, reflecting the importance of statistical optimization of fermentation condition over the traditional fermentation methodology. The maximum invertase activity was obtained after an optimized culture condition at 5 pH, 35°C-incubation temperature for 72 h with activity of 8.2 U/ml (Run11).

The determination coefficient (R2) showed the accuracy of the model. R2 was 0.9858, explaining 98.5% of the variability in the response could be accounted for the model, and was considered as a significant correlation. Therefore, the present value of R2 confirms the reliability of the current model for invertase production and also exhibited a good correlation between the experiment and theoretical values.

A second-order final equation in terms of actual factors is as follows:



where Y represents response or invertase yield and X1, X2, and X3 is temperature, pH, and incubation time, respectively.

The model validation

The validity of the proposed model was estimated by prediction of A. niger invertase production for each trail of the matrix. The experimental results in [Table 2] showed that the maximum observed invertase production (8.2) was very close to the predicted value (8.3) run11.

The results obtained by analysis of variance analysis for the production of invertase by A. niger is given in [Table 3]. It showed that the model was highly significant with an F value of 77.33 for invertase production and showed that it was a significant model which is evident from Fisher’s ‘F’ test along with a very low probability value (P model > F=0.0001). Values of ‘Prob>F’ that are less than 0.05 signify significant model, and at the same time, a relatively lower coefficient of variation (CV=7.28%) was indicated, implicating a better precision and reliability of the experiments carried out. The results obtained from this study revealed that agreement between the actual values and the predicted values and all factors have a significant response on the invertase production data, as presented in [Table 3]. The statistical optimization increased the biosynthesis of invertase about 1-fold of that of the basal medium (U/ml). The influence on the yield of invertase imposed by the factors and reciprocity between them is represented in [Figure 2]a–c. The response surface curves were designed to reveal the interaction between different variable factors and determine the optimum level of each variable for maximum response. Each figure indicated the effect of two factors, whereas the other factors were fixed at zero levels; the highest response value was detected at the result points 25°C and pH 5 for 72 h.
Table 3 Analysis of variance for invertase production by Aspergillus niger

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Figure 2 Response surface plot of the interaction effect of (A) temp, pH (B) temp, incubation time, and (C) pH and incubation time on invertase production by Aspergillus niger.

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RAPD-PCR analysis

To study the genetic difference among the five Aspergillus spp., DNA samples were subjected to RAPD-PCR analysis using 10 primers. The pattern of these primers shows instructive and clear profile for each strain ([Figure 3]) [Table 4] revealed that the ten primers produced a total of 131 bands detected among the five strains. Only 70 of them were polymorphic. The percentage of polymorphism ranged from 75 to 100%. Primer OPA-08 produced the highest percentage of polymorphism, whereas primers OPB17 and OPC-03 produced the lowest percentage of polymorphism (75%). The RAPD-PCR profiles were generated by these primers and have multiple bands varying from 10 to 16. These primers OPA-05, OPA-06, and OPC-03 produced the maximum number of bands (16 bands), whereas the lowest two were 10 bands and generated with primers OPB-07 and OPB-09. A dendrogram was constructed after numerical analysis of RAPD-PCR data ([Figure 4]), based on the similarity matrix. The results also showed the closest relationship between them. In this study, RAPD-PCR is a powerful tool to differentiate between Aspergillus spp.
Figure 3 RAPD-PCR pattern produced with 10 primers. M ladder 100-bp lane (1–5) Aspergillus spp.

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Table 4 RAPD-PCR primers names and statistical analysis

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Figure 4 Dendrogram showing the relationships and polymorphism between fungal strains based on RAPD-PCR analysis.

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The similarity matrix between fungal strains revealed that isolates A. parasiticus and A. niger showed a 75% similarity in [Table 5]. Results also showed that both A. terreus and A. niger had a similarity of 67%, followed by A. flavus and A. niger with a similarity of 52%. Lower similarities were recorded between A. flavus and A. ochraceus (45%) and between A. flavus and A. terreus (52%).
Table 5 Similarity matrix of fungal strains based on RAPD-PCR analysis

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Cluster analysis

The dendrogram was constructed using Unweighted Pair-Group Method with Arithmetical average cluster analysis to reveal the genetic relationships among five fungal isolates based on the similarity matrix between isolates. [Figure 4] shows three major clusters: the first cluster included A. flavus isolate separate group; the second cluster (interposed group) contained A. terreus, divided at two subcluster A. parasiticus and A. niger isolates; and the third group contained A. ochraceus.


  Discussion Top


Numerous microorganisms, especially the genus Aspergillus that possesses fructosyltransferases (invertase) with high transfructosylating activity, have been regarded as the most efficient producers of fructooligosaccharides. A. niger proved to be the most appropriate strain for invertase production. The productivity of the enzyme from A. niger was extremely high. Nguyen et al. [15] previously reported the production of fructooligosaccharides using β-fructofuranosidase from A. niger IMI303386. Mao et al. [16] isolated novel invertase from A. niger TCCC41686. Our results agree with Oyedeji et al. [17], who also reported that there was appreciable invertase production after 72 h (15.29±0.60 U/ml) incubation of Aspergillus niger. Furthermore, Veana et al. [18] reported that only A. niger GH1 among eight strains evaluated produced 8.6 U/ml invertase in less time under submerged cultivation after 48 h. The effect of improvement parameters under examination was assessed to acquire the most extreme yield of enzyme production. There are many reports for evaluation of the perfect culture conditions for production from A. niger using RSM method; these results agree with Ire et al. [19], who also used this methodology to optimize the invertase production from A. niger grown on low-cost agricultural wastes. Ben Mefteh et al. [20] used the RSM method to optimize an acidic protease produced by Penicillium bilaiae. RSM is gaining attention owing to its suitability in effectively aggregating optimal conditions for multivariable schemes [5]. This technique was utilized in the optimization of environmental conditions necessary for the production of invertase. Applying RSM, at the same time, the determination of the main and interaction effects of different environmental factors on invertase production was permitted. Sivakumar et al. [21] used the RSM technique to optimize keratinase production by Bacillus cereus and concluded that RSM can improve yield as well as the cost of enzyme production. The use of RSM in optimizing bioprocess techniques has been heralded as an effective way of determining the most suitable parameters for the production process. Senthivelan et al. [12] also used RSM to improve and optimize the activity of laccase enzyme. The maximum activity (7.9 U/ml) was detected after optimization for 5 days and in cultivation at 32°C by the potential white-rot fungus Penicillium chrysogenum. This technique was more accurate than the classical method (6.0 U/ml). RAPD-PCR technique was used to study the genetic diversity and relationships between Aspergillus strains. RAPD-PCR has been successfully employed in phylogenetic and genetic diversity studies, as it is simple, inexpensive, and has high reproducible profiles. These results are in agreement with Hashoosh et al. [22] who also used RAPD-PCR to differentiate between twenty-four isolates of A. niger isolated from different sources (soil, seeds, powdered milk, and factory wastewater). Similar observations were reported by Adss et al. [23], who used RAPD and ISSR to differentiate between seven isolates of A. solani and their pathogenic capability.


  Conclusion Top


In the current investigation, some filamentous fungi were screened for invertase production. A. niger was the most promising strain for enzyme production. RSM seems to the prospective technique for optimization of microbial enzymes. The current study points to the successful optimization of invertase production after a combination between various factors such as 35°C temperature, pH 5, and incubation time for 72 h. The obtained data from this investigation have demonstrated a significant increase in extracellular invertase production by A. niger through RSM. Invertase production was the result of a synergistic combination of effective parameter interactions. The optimized conditions for the production of invertase enzyme as reported in this study can be of several advantages, with a wide range of industrial applications such as the food industry. The use of fungi for the invertase production seems to be a promising candidate, with a eukaryotic origin. RAPD markers have the potential technique for differentiation between Aspergillus spp.

Acknowledgements

This research was done in the laboratories of National Research Center.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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