Research Article | Volume: 9, Issue: 10, October, 2019

Optimization of camptothecin production and biomass yield from endophytic fungus Fusarium solani strain ATLOY-8

Prince Clarance Ameer Khusro Jebalsy Lalitha Jerin Sales Agastian Paul   

Open Access   

Published:  Oct 04, 2019

DOI: 10.7324/JAPS.2019.91005
Abstract

Fusarium solani strain ATLOY-8, a fungus that produces camptothecin (CPT) was isolated from Chonemorpha fragrans (Moon) Alston. The process of optimization of the camptothecin yield was optimized by means of the traditional methods and analytical tools. Using the Box–Behnken design (BBD) matrix at N = 17, three independent variables were optimized designated using one factor at a time (OFAT) method, for improved CPT and biomass production. The BBD exhibited 1.4- and 1.2-fold increase of CPT production and biomass yield, respectively, compared to OFAT approach in the basal medium containing absolute ethanol (5%), glucose (1%), and precursors (a combination of tryptophan, geraniol, and tryptamine; 0.03%). Analysis of variance showed the elevated coefficient of determination (R2 ) of 0.9751 and 0.9980, respectively, for CPT and biomass yielding at a significant level (p > 0.05). Three dimensional graphs revealed dependent synergy between two variables to improve the CPT and biomass yield.


Keyword:     Biomass Box–Behnken design camptothecin Fusarium solani optimization.


Citation:

Clarance P, Khusro A, Lalitha J, Sales J, Paul A. Optimization of camptothecin production and biomass yield from endophytic fungus Fusarium solani strain ATLOY-8. J Appl Pharm Sci, 2019; 9(10):035–046.

Copyright: © The Author(s). This is an open-access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

HTML Full Text

INTRODUCTION

Camptothecin (CPT) is a naturally occurring alkaloid. This alkaloid has the ability to prohibit the topoisomerase I; thus, it is an anticancer compound (Hsiang et al., 1988; Kjeldsen et al., 1992; Thomas et al., 2004). CPT has derivatives such as topotecan and irinotecan which are used in the medication of colon and ovarian cancers (Demain and Vaishnav, 2011). The demand for CPT per year is approximately 3,000 kg in the international market and the annual production throughout the globe is only 600 kg which cannot meet the demand (Raveendran, 2015).

The first isolation of camptothecin is owed to the elicitation of Camptotheca acuminata in China and Nothapodytes foetida in India (Lorence and Nessler, 2004). CPT has been spotted in species of plants from unrelated classes of Asterids and Rosids, families, such as Icacinaceae (Pyrenacantha klaineana and Merrilliodendron megacarapum), Gelsemiaceae (Mostuea brunonis), Apocynaceae (Ervatamia heyneana), Rubiaceae (Ophiorrhiza pumila), and Nyssaceae (C. acuminata) (Backlund et al., 2000; Hilu et al., 2003). Recently, the demand for CPT caused massive harvest of those trees in Asia (Shwetha et al., 2013). Under such a critical situation, there is an immediate need for finding new plant sources and alternative methods for the consistent supply of important compounds like CPT.

In this study, the authors isolated Fusarium solani from the root of the host plant Chonemorpha fragrans (Apocynaceae), which is marked as endangered in Karnataka state and vulnerable in Kerala state of India (Khan et al., 2005). The fungus is known to produce CPT in distinct media under shake flask culture. The optimum manufacture of CPT in a profitable manner can be achieved by applying alternative methods. Hence, further exploration is required to enhance extraction through varied techniques (Khusro and Aarti, 2015; Khusro et al., 2016). The optimization for dependent variables is proportionate to medium diverse factors such as carbon source, nitrogen source, pH, temperature, agitation speed, and incubation period. One factor at a time (OFAT) based optimization is a tedious method with less accuracy. To raise the accuracy level and yield, Response Surface Methodology (RSM) is implied nowadays with high accuracy (Bocchini et al., 2002). Considering this, the contemporary context was scrutinized to augment the CPT production and biomass yield from a new strain of endophytic fungus segregated from C. fragrans using RSM tool.


MATERIALS AND METHODS

Plant material

Chonemorpha fragrans, a stout spreading laticiferous shrub was gathered from the Western Ghats of the southern region of Kerala. The mature plant part of roots was collected in a clean and dry plastic bag. The roots showed dark brown in color at the epidermal layer. The roots collected were brought to the laboratory for processing. Prof. Dr. G. Jeyajothi, Taxonomist, Loyola College, Chennai, India, identified and verified the plant. The voucher specimen (No: 314) has been retained in the Department herbarium.

Isolation of endophytic fungus

The plant parts collected were cleaned using deionized water. Surface sterilization of explants was carried out as per the methodology of Hallmann et al. (2006) with minor modifications. The root selected were washed in 0.1% Tween 20 for 30 seconds, followed by 0.1% Bevistin for 2–3 minutes to prohibit the existence of external fungi. After that, samples were saturated in 0.1% sodium hypochlorite for 30 seconds and finally in 70% v/v ethanol for 3–5 minutes. After specific treatment, samples were rinsed thrice in sterile distilled water. After the surface sterilization process, the plant parts were finally desiccated in the laminar airflow chamber. Once the samples were dried, they were aseptically dissected to project the cortex region and placed on to aqueous agar (1.5%, HiMedia, Mumbai) medium and incubated for 4–5 days at 28°C ± 2oC in dark. The isolation medium was complemented with streptomycin (250 mg/l) for the prevention and growth of bacteria. A negative control was placed using the explants without the sterilization process to check the surface contaminated fungi.

Morphological and molecular characterization of fungus

The fungal species isolated was subjected for morphological assessment according to Barnett (1998). Further, the species was characterized using molecular techniques. Primers (ITS1 and ITS 4) were used for the amplification process (White et al., 1990). The fungus was grown in PDA plate and incubated at 28°C ± 2oC for 6 days. Within 6 days, white thick cottony mycelium was formed in the plate. The mycelium was taken apart from the culture. Approximately 25 mg of the tissue/mycelium was macerated using liquid nitrogen. In a microcentrifuge tube, the granulated tissue was collected. Using this powdered tissue, DNA isolation is performed using NucleoSpin® Plant II Kit (Macherey-Nagel). Amplification of the Polymerase chain reaction (PCR) products was implemented by making use of PCR thermal cycler (GeneAmp PCR System 9700, Applied Biosystems) and universal primers. UV transilluminator (Genei) was instrumental in visualization and imaging of the PCR products and the image was photographed beneath the UV light using Gel documentation system (Bio-Rad). Total score and highest homology were noted using BLAST. The fungal sequences were deposited to Genbank, NCBI, with accession number KY497951. MEGA (Molecular Evolution Genetic Analysis) software version 4 was used to create a phylogenetic tree.

Extraction of CPT

The fungal strain was cultured in 50 ml of pre-sterilized YESD (Yeast extract, Soy peptone, and Dextrose) broth (VanderMolen et al., 2013). Flasks were agitated at 180 rpm at 28°C ± 2oC for 10 days. Camptothecin was extracted from fungal mycelia using the methodology of Shweta et al. (2010) with minor adaptations. The mycelium was isolated from the culture by a cheese cloth and desiccated to moisture level (5%) at 60oC for 96 hours. The desiccated mat was finely pulverized using a sterilized mortar and pestle. 0.1 g of powder was taken in 15 ml vial, 10 ml of 61% ethanol was added and incubated overnight. After 12 hours, it was sonicated and placed at 60oC in shaking water bath for 3 hours. Then the essence was cooled to the room temperature, and further, the essence was subjected to centrifugation at 10,000 rpm (Remi, Mumbai) for 10 minutes at 10oC. The supernatant was filtered using 0.2 μ filter (Thermo fisher) and checked for CPT.

Reversed-phase high-performance liquid chromatography (RP-HPLC) analysis

Camptothecin was analyzed by RP-HPLC (LC-20AD, Shimadzu, Japan). The preparation of the typical CPT was (95% HPLC grade Sigma Aldrich Inc USA) performed using methanol and DMSO at 3:1 (v/v) ratio (1 mg/ml). Preparation of the working solution (20 μl) was done (0.1 to 0.5 mg/ml) from the stock solution and the working solution was introduced to the HPLC system to acquire the standard curve. It took 15 minutes of run time in the column. The availability of CPT was confirmed by matching with the retention time of standard. The standard CPT regression curve is noted and further quantified the CPT in the sample extract.

Quadruple time-of-flight mass spectrum analysis (ESI–Q-TOF MS) analysis

Mass spectrometry analysis was done by ESI–Q-TOF MS (Waters Micromass Q-Tof Premier Mass Spectrometer, USA) fortified with an electrospray ionization source. A syringe pump was instrumental in injecting the samples to the system at a flow rate of 10 ml/min and spray voltage was set to 1.5 kV in positive mode.

Biomass determination

Utilizing the methodology of Khusro et al. (2017), the fungal biomass estimation was carried out.

Medium optimization using OFAT method-standardization of basal medium

Standardization of the basal medium for the optimum growth of fungi and CPT production consists of various media as given below:

Czapek Dox broth (CDB; g/l):NaNO3 3.0, K2HPO4 1.0, MgSO4 0.5, KCl 0.5, FeSO4 0.01, and Sucrose 30.0

Potato dextrose broth (PDB; g/l):Potato 200.0 and Dextrose 20.0

Sabouraud dextrose broth

(SDB; g/l):Dextrose 40.0 and Peptone 10.0

YESD broth (g/l):Yeast extract 5, Soy peptone 20.0, and Dextrose 20.0

Malt Extract broth (MEB; g/l):Malt extract 5.0

YPSS (g/l):Yeast 4.0, Starch 11.4, KHPO4 1.0, and MgSO4.7H2O 0.5

Peptone Yeast extract

Glucose broth (PYG; g/l):Soy peptone 1.25, yeast extract 1.25, and D-glucose 5

The CPT yield and biomass produce were assessed based on the earlier described method.

Effect of incubation period

The fungal strain was inoculated into the optimum basal medium up to 14 days in shake flask condition. The CPT and biomass output were quantified according to the procedure as described earlier.

Effect of ethanol concentration

Addition of absolute ethanol is known to increase the production of CPT (Venugopalan et al., 2015). Varying ranges (0% to 10%) of pure ethanol were administered to the suspension cultures of fungi for the estimation of CPT and biomass production as per the methodology as discussed earlier.

Effect of carbon and nitrogen sources

Dextrose, mannose, galactose, sucrose, glucose, fructose, lactose, and maltose were used for estimating CPT and biomass. These carbon sources (1% w/v) were supplemented into the basal medium. Effect of various nitrogen sources was examined for the biomass and CPT production of the fungi. The basal medium was individually supplemented with ammonium phosphate, ammonium sulfate, ammonium nitrate, soy peptone, beef extract, and yeast extract (1% w/v). The CPT production and biomass yield were assessed according to the methodology as described earlier.

Effect of pH

To determine the impact of varying pH on CPT and biomass yield, pH of basal media was adjusted up to 12.0 prior to sterilization. The CPT production and biomass yield were estimated according to the methodology as discussed earlier.

Effect of temperature

To determine the impact of temperature on the maximum yield of CPT and biomass, basal medium containing optimum medium components was incubated at different temperatures (25°C–50°C) for 9 days. As per the methodology described earlier, the CPT production and biomass yield were estimated.

Determination of agitation speed

In shake flask culture, aeration is a central influence for the fermentation. The experiments were planned and executed by varying agitation speed ranging from 80 to 160 rpm for seeking the optimal level following all the other standardized parameters. As per the methodology described earlier, the estimation of CPT production and biomass yield were done.

Effect of precursors and elicitors

The precursors and elicitors were supplemented to the culture on the 6th day of the cultivation and harvested on the 9th day. The biosynthetic precursors added were (mM): tryptophan 1.0, tryptamine 0.5, and monoterpenoid alcohol geraniol 1.0. The elicitors added were (mM): jasmonic acid 0.25, methyl jasmonate 0.25, manganese chloride 0.5, BSA 0.075, and silicone oil 1.0. The estimation of CPT production and biomass yield were done according to the previously described methodology.

Optimization of independent variables using RSM

Based upon the results of the OFAT conventional methodology, Box–Behnken Design (BBD) matrix was instrumental in optimizing the most significant independent variables (ethanol, glucose, and precursors) to maximize CPT and biomass yield by keeping other variables constant. Independent variables are very important in this system. Each one of them in the design matrix was subjected for thorough study at three different levels (-1, 0, +1). BBD is a method of optimization of best-fit parameters using a small number of the quadratic models.

Validation of model and software used

The validation of the design was carried out by running the experiments in triplicates. Optimum values were selected. The prominent independent variables were optimized using Design Expert Version 11.0.0 (Stat-Ease Inc., Minneapolis, MN). Statistical parameters were validated by analysis of variance (ANOVA).


RESULTS

Isolation of fungus

The fungus was isolated from the root portion and showed a white cottony growth on PDA medium. The hyphae initially hyaline and mycelium turned white to yellowish; and to bluish-gray after 2 weeks. The mycelium produced copious microconidia appeared to be cylindrical to oval. Macroconidia were fusiform, 3–5 septate, cylindrical, and slightly curved (Fig. 1). An amplicon of 476 bp size (Fig. 2) was observed after amplification.

Identification of fungus

The ITS rDNA data of the fungus showed 100% similarity with the existing fungal strains and identified as F. solani strain ATLOY-8. The sequence was submitted to GenBank, NCBI (Accession No.: KY497951). Fig. 3 shows the phylogenetic tree of strain ATLOY-8 constructed using bioinformatics software MEGA 4.

Figure 1. Septate hypha showing macroconidia and microconidia observed under Olympus 40×.

[Click here to view]

Figure 2. ITS rDNA sequence (476 bp) of strain ATLOY-8.

[Click here to view]

Figure 3. Neighbor-joining tree of strain ATLOY-8 showing a relationship with other F. solani strains based on ITS rDNA sequence data.

[Click here to view]

HPLC and ESI-Q-TOF MS analysis for detection of CPT

The crude extract of strain ATLOY-8 was analyzed using HPLC. The analysis exhibited a peak eluting at a retention time of 4.6 minutes corresponding to the standard CPT. Most of the CPT was estimated in the broth. To further confirm the presence of CPT, the partially purified extract of strain ATLOY-8 was subjected to ESI–Q-TOF MS analysis. The spectrum showed a peak at m/z [M+H]+ 349 and m/z [M+H]+ 379 corresponding to the protonated molecule ions of CPT and 9-methoxycamptothecin, respectively.

Effect of media

Different media were prepared to grow and ferment strain ATLOY-8 for CPT and biomass production. The production of CPT on YESD was higher than that of PDB. The CPT content in YPSS was slightly lower than that of PDB. The CPT production was substantially reduced in CDB and MEB, respectively (Fig. 4a).

Effect of incubation period

Maximum CPT yield was obtained at 8th day of incubation while the biomass yield was increased at 9th day of incubation. The productivity of CPT and biomass yield reduced afterward (Fig. 4b).

Effect of ethanol

Addition of absolute ethanol increased the production of CPT. 5% absolute alcohol exhibited maximum CPT production (6.1 ± 0.183 μg/ml) and biomass (14 ± 0.42 g/l) (Fig. 4c).

Effect of carbon and nitrogen sources

Among varied carbon sources, glucose was observed to be the best inducer (1% w/v), followed by sucrose. Other carbon sources resulted in a reduced level of productivity (Fig. 4d).

Supplementing beef extract showed the maximum CPT yield (7.1 ± 0.213 μg/ml). On the other hand, ammonium nitrate gave maximum biomass yield (16 ± 0.48 g/l) (Fig. 4e).

Effect of pH

The pH 5.5 showed a maximum yield of CPT (8 ± 0.24 μg/ml). However, pH 6 gave maximum biomass yield (15 ± 0.45 g/l). Further, acidic pH reduced the growth of mycelia significantly and at alkaline pH, the growth of mycelia was very slow and subsequently reduced the yield of both the CPT and biomass (Fig. 4f).

Effect of temperature and agitation speed

Temperature is an important physical factor for the growth of mycelia in a medium. Strain ATLOY-8 showed maximum biomass production at 25°C (17 ± 0.51 g/l). As the temperature increased, the growth of the mycelia drastically reduced. At 28°C, the strain yielded maximum CPT (8.5 ± 0.25 μg/ml) (Fig. 4g). The highest CPT (9 ± 0.39 μg/ml) production and biomass yield (16.5 ± 0.49 g/l) were obtained at 120 rpm (Fig. 4h).

Figure 4a. Graphs showing optimization of (a) media (b) days (c) ethanol (d) carbon source (e) nitrogen source (f) pH (g) temperature (h) rpm (i) precursors and elicitors using OFAT method.

[Click here to view]

Effect of precursors and elicitors

CPT yield increased substantially by the addition of precursors and elicitors, particularly using the combination of tryptophan, geraniol, and tryptamine (0.03%). This combination showed 10.9 ± 0.32 μg/ml of CPT and 19 ± 0.57 g/l of biomass (Fig. 4i).

Optimization of independent variables using RSM

Ethanol, glucose, and precursors were selected as independent variables (Table 1). Study of parameters was done at three levels and a total of 17 experiments were carried out as per the variables ranges combinations mentioned in Table 2.

Table 1. Experimental range, level, and code of variables for BBD.



[Click here to view]

The CPT yield was obtained as per the model equation given below:

Y (μg/ml) = +11.86 - 0.0625Ethanol - 0.0875Glucose + 0.525Precursors + 0.275Ethanol × Glucose + 0.05Ethanol × Precursors - 0.3Glucose × Precursors + 0.2825Ethanol2 + 0.4825Glucose2 + 0.8075Precursors2

The biomass yield was determined as per the model equation given below:

Z (mg/l) = +21.02 + 0.6125Ethanol + 0.5875Glucose + 0.475Precursor + 0.15Ethanol × Glucose + 0.575Ethanol × Precursor + 0.375Glucose × Precursor - 1.51Ethanol2 - 0.41Glucose2 + 0.015Precursor2

The highest CPT production was obtained from Run no.14 which consisted of ethanol (5% v/v), glucose (0.5% w/v), and precursors (0.05% w/v). Likewise, the highest biomass production was obtained from run no.5 which consisted of ethanol (5% v/v), glucose (1.5% w/v), and precursors (0.05% w/v)

ANOVA for the quadratic model of CPT is shown in Table 3. F value (30.42) is the base of the significance of the model. Chances of occurrence of large F-value due to noise are only 0.01%. The validity of the significance of model terms is indicated by p values which are less than 0.05. Here, C, AB, BC, A2, B2, and C2 come under significant model terms. “Lack of Fit F value” of 0.33 specifies a good model. There is an 80.61% probability that a "Lack of Fit F value" this large could occur due to noise. The multiple correlation coefficient (R2) was found to be close to 1 (0.9751). Coefficient of variation (CV) of 1.31% represents that the experiments are dependable and accurate. Predicted R2 of 0.8898 is close to Adjusted R2 of 0.9430.

ANOVA of the quadratic model of fungal biomass is exhibited in Table 4. A, B, C, AB, AC, BC, A2, and B2 are significant model terms. The Model F-value of 387.74 implies the model is significant. Highly reliable and precise experiment performances are verified and denoted here by a low CV of 0.37%. Predicted R2 of 0.9737 is close to Adjusted R2 of 0.9954

The dots close to the diagonal line observed (Fig. 5) indicate the actual values and predicted of CPT. The interdependent interactions between glucose and ethanol, precursors and ethanol, and precursors and glucose for enhanced CPT production are shown in Figure 6a–c. Three-dimensional graphs results showed a significant effect of precursors on CPT production. The actual and predicted values of biomass production were observed to be close to the diagonal line (Fig. 7). The interdependent interactions between glucose and ethanol, precursors and ethanol, and precursors and glucose for enhanced biomass yield are shown in Figure 8a–c. Three-dimensional graphs results showed a significant effect of glucose, precursors, and ethanol on biomass yield. Further, the CPT production and biomass yield were compared with the theoretical values by carrying out the experiments under optimized conditions. Experimental values were found close with the theoretical values.

Table 2. BBD showing experimental and predicted values of the variable for CPT and biomass yield



[Click here to view]

Table 3. ANOVA for CPT production.



[Click here to view]

Table 4. ANOVA for biomass production.



[Click here to view]


DISCUSSION

Over the last few decades, endophytic fungi have created immense attention among worldwide researchers for distinct secondary metabolites of plants (Musavi et al., 2015). In this regard, several diversified bioactive components have been isolated and characterized as therapeutics (Shweta et al., 2010). However, studies revealing the potential of endophytic fungi as promising resources of such valuable constituents are scarce. In view of this, in the present investigation, we had undertaken a significant attempt not only to isolate endophytic fungus from C. fragrans but also optimizing the varied parameters to enhance the production of CPT from it. In this study, the endophytic fungus F. solani strain ATLOY-8 was successfully isolated from C. fragrans using morphological and molecular characterization tools. However, similar endophytic fungus from the different plant was isolated earlier from Venugopalan et al. (2016) too. The potentiality of many endophytic fungi has been explored and subjected for the synthesis of CPT outside their plant hosts. The reports of methods for augmentation of CPT are on record already (Musavi et al., 2015; Rehman et al., 2009). But still, economic viability and better yield of CPT by endophytic fungi is a matter of great concern and challenge.

Methods of conventional optimization techniques for monocultures and techniques and procedures of mixed fermentation gave adequate knowledge of the highly prompting parameters and their optimum values (Bhalkar et al., 2016). Medium constituents and culture parameters in optimization play an important role in the enhancement of metabolite productivity as well as microbial biomass yield in submerged fermentation. Among various media tested, strain ATLOY-8 showed maximum production of CPT and biomass yield in YESD medium. Likewise, the incubation period affected the production and biomass significantly. Maximum CPT production and biomass yield were estimated on day 9, while the production and yield decreased gradually afterward. The adding of absolute ethanol at varied concentrations affected the CPT and biomass yield from strain ATLOY-8. Maximum production of CPT and biomass was estimated in the presence of 5% (v/v) of ethanol. This might be due to the elicitor as well as energy source role of ethanol for this isolate, thereby exhibiting high CPT and biomass production. Similar observation was reported by Venugopalan and Srivastava (2015) who estimated the significant increment in the production of CPT due to the incorporation of absolute ethanol into the medium. Among different carbon sources tested, strain ATLOY-8 showed a maximum yield of CPT and biomass in the presence of glucose (1% w/v), followed by galactose, maltose, sucrose, fructose, and xylose. In like manner, the incorporation of beef extract (1% w/v) into the basal medium revealed a high yield of CPT and biomass.

Figure 5. Actual values vs predicted values for biomass yield residing close to the diagonal line.

[Click here to view]

Figure 6. 3D response plot for CPT production showing the interaction between (a) glucose and ethanol (b) precursors and ethanol, and (c) precursors and glucose.

[Click here to view]

The pH of the medium is one of the crucial factors affecting the growth and metabolite production from the microorganisms. In the present study, strain ATLOY-8 showed maximum CPT and biomass production at pH 6.0. Acidic pH reduced the growth of mycelia significantly, while in the alkaline pH, the growth of mycelia was very slow. The report agrees slightly with the findings of Venugopalan et al. (2016) who determined the enhanced yield of CPT at pH 6.0. Temperature is a very important physical factor for the growth of mycelia in the specific medium. In this study, strain ATLOY-8 showed maximum biomass production at 25°C. Further increment in the incubation temperature reduced the growth and metabolite production drastically. This might be due to the reason that the enzyme synthesizing CPT in this very strain would be the most active at this temperature. Surprisingly, the findings of our study do not favor the outcome of Venugopalan et al. (2016) who depicted gradual improvement in CPT yield with an increase in temperature. Likewise, the trend in the enhancement of CPT yield from endophytic fungus with increased temperature was observed by Pu et al. (2013) too.

Agitation speed is another critical factor affecting the metabolite production and growth of microbes. In this context, strain ATLOY-8 demonstrated a maximum yield of CPT and biomass at 120 rpm. Further increased agitation speed reduced productivity. This might be because of the shear stress causing a loss in cellular viability, thereby affecting the metabolite production. However, the lower production of CPT and biomass yield from the very strain at low agitation speed might be because of the limitations in mass transfer (Venugopalan et al., 2016). The exogenous addition of precursors and elicitors, particularly the combination of tryptophan, geraniol, and tryptamine exhibited the maximum productivity of CPT and biomass. The reduction in CPT and biomass production upon the incorporation of other precursors and elicitors could be because of the cellular toxicity at the particular doses provided. More or less similar outcomes of the positive influence of elicitor and precursor addition on CPT production from endophytic fungus have been reported by Pu et al. (2013).

Figure 7. Actual values vs predicted values for biomass yield residing close to the diagonal line.

[Click here to view]

Figure 8. 3D response plot for biomass production showing the interaction between (a) ethanol and glucose (b) precursors and ethanol, and (c) precursors and glucose.

[Click here to view]

The traditional tools of optimization, i.e., OFAT method is being avoided nowadays because of its time consuming and low accuracy approach (Aarti et al., 2018; Khusro et al., 2017). Response surface methodology is a technique that combines mathematical as well as statistical methods and it can undoubtedly be a promising alternative to the OFAT method. As a matter of fact, RSM analyzes the interdependent relationships between the dependent and independent variable and help carrying out a minimum number of experiments with high accuracy (Aarti et al., 2017). In the present context, the BBD of RSM led to the enhanced CPT production (14.1 μg/g) and biomass yield (22.2 g/l) in the medium containing ethanol (5% v/v), glucose (0.5% w/v), and precursor (0.05% w/v). ANOVA, as well as 3D graphs of CPT production and biomass yield, clearly showed the significant (p < 0.05) effect of precursors in order to enhance the responses.

Contour plots demonstrate insignificant interaction between two controlled variables. The slight variations between experimental and predicted response values were because of the determination coefficients (Khusro et al., 2018). Previously, Bhalkar et al. (2016) successfully enhanced CPT yield from endophytic fungus using statistical tools, suggesting the pivotal role of statistical tools based optimization of metabolites from endophytes.


CONCLUSION

In brief, the CPT producing endophytic fungus F. solani strain ATLOY-8 was isolated from C. fragrans using morphological and molecular characterization tools. HPLC and ESI-Q-TOF MS analysis showed the notable production of CPT from strain ATLOY-8. The promising factors selected through OFAT method were further optimized using BBD which showed enhanced CPT (14.1 μg/g) and biomass (22.0 g/l) yield in the production medium containing ethanol (5% v/v), glucose (0.5% w/v), and precursor (0.05% w/v). ANOVA, as well as 3D graphs of CPT production and biomass yield, showed the significant (p < 0.05) effect of precursors toward the enhancement of responses. Experimental data of response showed closeness with the predicted data.


CONFLICT OF INTEREST

None declared.


REFERENCES

Aarti C, Khusro A, Agastian P. Goat dung as a feedstock for hyper-production of amylase from Glutamicibacter arilaitensis strain ALA4. Bioresour Bioprocess, 2017; 4:43.

Aarti C, Khusro A, Agastian P. Carboxymethyl cellulase production optimization from Glutamicibacter arilaitensis strain ALA4 and its application in lignocellulosic waste biomass saccharification. Prep Biochem Biotechnol, 2018; 48:853–66.

Backlund M, Oxelman B, Bremer B. Phylogenetic relationships within the Gentianales based on ndhF and rbcL sequences, with particular reference to the Loganiaceae. Am J Bot, 2000; 87:1029–43.

Bhalkar BN, Patil SM, Govindwar SP. Camptothecine production by mixed fermentation of two endophytic fungi from Nothapodytes nimmoniana. Fungal Biol, 2016; 120:873–83.

Barnett HL, Hunter BB. Illustrated General of Imperfect fungi. 4h edition, The American Phytopathological Society, Minnesota, 1998.

Bocchini DA, Alves-Prado HF, Baida LC, Roberto IC, Gomes E, Da Silva R. Optimization of Xylanase production by Bacillus circulans D1 in submerged fermentation using response surface methodology. Process Biochem, 2002; 38:727–31.

Demain AL, Vaishnav P. Natural products for cancer chemotherapy. Microb Biotechnol, 2011; 4:687–99.

Hallmann J, Berg, G, Schulz B. Isolation procedure for endophytic microorganisms. In: Boyle, Ch JC, Sieber TN, Schulz BJE (eds.). Microbial root endophytes, Springer, Berlin, Heidelberg, pp 299–305, 2006.

Hilu KW, Borsch T, Müller K, Soltis DE, Soltis PS, Savolainen V, Chase MW, Powell MP, Alice LA, Evans R, Sauquet H, Neinhuis C, Slotta TA, Rohwer JG, Campbell CS, Chatrou LW. Angiosperm phylogeny based on matK sequence information. Am J Bot, 2003; 90:1758–76.

Hsiang YH, Liu LF. Identification of mammalian DNA Topoisomerase I as an intracellular target of the anticancer drug camptothecin. Cancer Res, 1988; 48:1722–6.

Khan S, Karnat NM, Darshan S. India’s foundation for revitalization of local health traditions, pioneering In situ conservation strategies for medicinal plants and local cultures. Herbalgram, 2005; 68:34–45.

Khusro A, Aarti C, Dusthackeer A, Agastian P. Enhancement of anti-tubercular activity and biomass of fermented food associated Staphylococcus hominis strain MANF2 using Taguchi orthogonal array and Box-Behnken design. Microb Pathog, 2018; 120:8–18.

Khusro A, Aarti C. Molecular identification of newly isolated Bacillus strains from poultry farm and optimization of process parameters for enhanced production of extracellular amylase using OFAT method. Res J Microbiol, 2015; 10:393–420

Khusro A, Barathikannan K, Aarti C, Agastian P. Optimization of thermo-alkali stable amylase production and biomass yield from Bacillus sp. under submerged cultivation. Fermentation, 2017; 3:1–19.

Khusro A, Kaliyan B, Al-Dhabi NA, Arasu MV, Agastian P. Statistical optimization of thermo- alkali stable xylansae production from Bacillus tequilensis strain ARMATI. Electron J Biotechnol, 2016; 22:16–25.

Kjeldsen E, Sevjestrup JQ, Gromova II, Alsner J, Westergaard O. Camptothecin inhibits both the cleavage and religation reactions of eukaryotic DNA Topoisomerase I. J Mol Biol, 1992; 228:1025–30.

Lorence, A, Nessler C L. Molecules of interest camptothecin, over four decades of surprising findings. Phytochemistry, 2004; 65:2735–49.

Musavi SF, Dhavale A, Balakrishnan RM, 2015. Optimization and kinetic modeling of cell500 associated camptothecin production from an endophytic Fusarium oxysporum NFX06. Prep Biochem Biotechnol, 2015; 45:158–72.

Pu X, Qu X, Chen F, Bao J, Zhang G, Luo Y. Camptothecin-producing endophytic fungus Trichoderma atroviride LY357: isolation, identification, and fermentation conditions optimization for camptothecin production. Appl Microbiol Biotechnol, 2013; 97:9365–75.

Raveendran VV. Camptothecin-discovery, clinical perspectives and biotechnology. Nat Prod Chem Res, 2015; 3:175.

Rehman S, Shawl AS, Kour A, Sultan P, Ahmad K, Khajuria R, Qazi GN. Comparative studies and identification of camptothecin produced by an endophyte at shake flask and bioreactor. Nat Prod Res, 2009; 23:1050–7.

Shweta S, Zuehlke BT, Ramesha V, Priti P, Mohana Kumar G, Ravikanth M, Spiteller R, Vasudeva R, Uma Shaanker R. Endophytic fungal strains of Fusarium solani, from Apodytes dimidiata E. Mey. ex Arn (Icacinaceae) produce camptothecin, 10-hydroxycamptothecin and 9-methoxycamptothecin. Phytochemistry, 2010; 71:117–22.

Shwetha S. Gurumurthy B, Ravikanth G, Ramanan U, Shivanna M. Endophytic fungi from Miquelia dentata Bedd, produce the anti-cancer alkaloid, camptothecine. Phytomedicine, 2013; 20:337–42.

Thomas CJ, Rahier NJ, Hecht SM. Camptothecin: current perspectives. Bioorgan Med Chem, 2004; 12: 1585–604.

VanderMolen KM, Raja HA, El-Elimat T, Oberlies NH. Evaluation of culture media for the production of secondary metabolites in a natural products screening program. AMB Express, 2013; 3:1–7.

Venugopalan A, Srivastava S. Enhanced camptothecin production by ethanol addition in the suspension culture of the endophyte, Fusarium solani. Bioresour Technol, 2015; 188:251–7.

Venugopalan A, Potunuru UR, Dixit M, Srivastava S. Effect of fermentation parameters, elicitors and precursors on camptothecin production from the endophyte Fusarium solani. Bioresour Technol, 2016; 213:311–8.

White T, Bruns T, Lee S, Taylor J. Amplification and direct sequencing of fungal ribosomal RNA Genes for phylogenetics. In: Innis, M, Gelfand D, Sanisky J, White T (eds.). PCR protocols: a guide to methods and applications, Academic Press, San Diego, pp 315–22, 1990.

Reference

ADR. 2018. Available via https://www.alz.co.uk/research/ world-report-2018 (Accessed 26 June 2019).

Akiba Y, Sasaki H, Huerta PT, Estevez AG, Baker H, Cave JW. Gamma-Aminobutyric acid-mediated regulation of the activity-dependent olfactory bulb dopaminergic phenotype. J Neurosci Res, 2009; 10:2211-21.https://doi.org/10.1002/jnr.22055

Claeysen S, Bockaert J, Giannoni P. Serotonin: a new hope in Alzheimer's disease? ACS Chem Neurosci, 2015; 7:940-3.https://doi.org/10.1021/acschemneuro.5b00135

Cullen WK, Suh YH, Anwyl R, Rowan MJ. Block of LTP in rat hippocampus in vivo by β-amyloid precursor protein fragments. Neuroreport,1997; 8:3213-7.https://doi.org/10.1097/00001756-199710200-00006

Devanand DP, Tabert MH, Cuasay K, Manly J, Schupf N, Brickman AM, Andrews H, Brown TR, DeCarli C, Mayeux R. Olfactory identification deficits and MCI in a multi-ethnic elderly community sample. Neurobiol Aging, 2010; 9:1593-600.https://doi.org/10.1016/j.neurobiolaging.2008.09.008

Djordjevic J, Jones-Gotman M, De Sousa K, Chertkow H. Olfaction in patients with mild cognitive impairment and Alzheimer's disease. Neurobiol Aging, 2008; 5:693-706.https://doi.org/10.1016/j.neurobiolaging.2006.11.014

Dong S, Duan Y, Hu Y, Zhao Z. Advances in the pathogenesis of Alzheimer's disease: a re-evaluation of amyloid cascade hypothesis. Transl Neurodegener, 2012; 1:18.https://doi.org/10.1186/2047-9158-1-18

Doty RL. The olfactory vector hypothesis of neurodegenerative disease: is it viable? Ann Neurol, 2008; 63:7-15.https://doi.org/10.1002/ana.21327

Dragicevic N, Mamcarz M, Zhu Y, Buzzeo R, Tan J, Arendash GW, Bradshaw PC. Mitochondrial amyloid-beta levels are associated with the extent of mitochondrial dysfunction in different brain regions and the degree of cognitive impairment in Alzheimer's transgenic mice. J Alzheimers Dis, 2010; Suppl 2:S535-50.https://doi.org/10.3233/JAD-2010-100342

Gaudry Q. Serotonergic modulation of olfaction in rodents and insects. Yale J Biol Med, 2018; 1:23-32.

Grimaldi M, Marino SD, Florenzano F, Ciotta MT, Nori SL, Rodriquez M, Sorrentino G, D'Ursi AM, Scrima M. β-Amyloid-acetylcholine molecular interaction: new role of cholinergic mediators in anti-Alzheimer therapy? Future Med Chem, 2016; 11:1179-89.https://doi.org/10.4155/fmc-2016-0006

Harvey JD, Heinbockel T. Neuromodulation of synaptic transmission in the main olfactory bulb. Int J Environ Res Public Health, 2018; 15:2194.https://doi.org/10.3390/ijerph15102194

Iuliana N-A. Olfactory dysfunctions in Alzheimer's disease, the clinical spectrum of Alzheimer's disease. In: De La Monte S (ed.). The charge toward comprehensive diagnostic and therapeutic strategies. IntechOpen, Europe, pp 127-44, 2011.

Kim HY, Lee DK, Chung BR., Kim HV, Kim Y. Intracerebroventricular injection of amyloid-β peptides in normal mice to acutely induces Alzheimer-like cognitive deficits. JoVE, 2016; 109:1-6.https://doi.org/10.3791/53308

Klafki HW, Staufenbiel M, Kornhuber J, Wiltfang J. Therapeutic approaches to Alzheimer's disease. Brain, 2006; 11:2840-55.https://doi.org/10.1093/brain/awl280

Li Y, Sun H, Chen Z, Xu H, Bu G, Zheng H. Implications of GABAergic neurotransmission in Alzheimer's disease. Front Aging Neurosci, 2016; 8:1-12.https://doi.org/10.3389/fnagi.2016.00031

Maheswari DU, Anand T, Manu TM, Khanum F, Sharma RK. Motion sickness induces physiological and neuronal alterations in a mouse model. IJPSR, 2019; 10:1650-9.

Monge-Acuña AA, Fornaguera-Trías J. A high-performance liquid chromatography method with electrochemical detection of gamma-aminobutyric acid, glutamate and glutamine in rat brain homogenates. J Neurosci Methods, 2009; 2:176-81.https://doi.org/10.1016/j.jneumeth.2009.06.042

Morrison AMS, Lyketsos CG. The pathophysiology of Alzheimer's disease and directions in treatment. ANS, 2005; 8:256-70.

Ogg MC, Ross JM, Bendahmane M, Fletcher ML. Olfactory bulb acetylcholine release dishabituates odour responses and reinstates odour investigation. Nat. Commun, 2018; 9:1868.https://doi.org/10.1038/s41467-018-04371-w

Palit P, Mukherjee D, Mandal SC. Reconstituted mother tinctures of Gelsemium sempervirens L. improve memory and cognitive impairment in mice scopolamine-induced dementia model. J Ethnopharmacol, 2015; 159:274-84.https://doi.org/10.1016/j.jep.2014.09.008

Quillfeldt JA. Behavioral methods to study learning and memory in rats. In: Andersen ML, Tufik S (ed.). Rodent model as tools in ethical biomedical research. Springer International Publishing, Cham, Switzerland, pp 271-311, 2006.https://doi.org/10.1007/978-3-319-11578-8_17

Revett TJ, Baker GB, Jhamandas J, Kar S. Glutamate system, amyloid ß peptides and tau protein: functional interrelationships and relevance to Alzheimer disease pathology. J Psychiatry Neurosci, 2013; 1:6-23.https://doi.org/10.1503/jpn.110190

Sadigh-Eteghad S, Sabermarouf B, Majdi A, Talebi M, Farhoudi M, Mahmoudi J. Amyloid-beta: a crucial factor in Alzheimer's disease. Med Princ Pract, 2015; 1:1-10.https://doi.org/10.1159/000369101

Scahill RI, Frost C, Jenkins R, Whitwell JL, Rossor MN, Fox NC. A longitudinal study of brain volume changes in normal aging using serial registered magnetic resonance imaging. Arch Neurol, 2003; 7:989-94.https://doi.org/10.1001/archneur.60.7.989

Schiavone S, Tucci P, Mhillaj E, Bove M, Trabace L, Morgese MG. Antidepressant drugs for beta amyloid-induced depression: a new standpoint? Prog Neuropsychopharmacol Biol Psychiatry, 2017; 78:114-22.https://doi.org/10.1016/j.pnpbp.2017.05.004

Souza LC, Jesse CR, Antunes MS, Ruff JR, de Oliveira Espinosa D, Gomes NS, Donato F, Giacomeli R, Boeira SP. Indoleamine- 2,3-dioxygenase mediates neurobehavioral alterations induced by an intracerebroventricular injection of amyloid-β1-42 peptide in mice. Brain Behav Immun, 2016; 56:363-77.https://doi.org/10.1016/j.bbi.2016.03.002

Tang J, Yuan Y, Wei C, Liao X, Yuan J, Nanberg E, Zhang Y, Bornehag, CG, Yang X. Neurobehavioral changes induced by di (2-ethylhexyl) phthalate and the protective effects of vitamin E in Kunming mice. Toxicology Res, 2015; 4:1006-15.https://doi.org/10.1039/C4TX00250D

Vina J, Lloret A. Why women have more Alzheimer's disease than men: gender and mitochondrial toxicity of amyloid-β peptide. JAD, 2010; 20:S527-33.https://doi.org/10.3233/JAD-2010-100501

Wang Y, Wang B, Zhu M-T, Li M, Wang HJ, Wang M, Ouyang H, Chai ZF, Feng WY, Zhao YL. Microglial activation, recruitment and phagocytosis as linked phenomena in ferric oxide nanoparticle exposure.

Toxicol Lett, 2011; 205:26-37.https://doi.org/10.2306/scienceasia1513-1874.2011.37.205

Wu N, Rao X, Gao Y, Wang J, Xu F. Amyloid-β deposition and olfactory dysfunction in an Alzheimer's disease model. J Alzheimers Dis, 2013; 37:699-712.https://doi.org/10.3233/JAD-122443

Yang M, Crawley JN. Simple behavioural assessment of mouse olfaction. Curr Protoc Neurosci, 2009; 48:8-24.https://doi.org/10.1002/0471142301.ns0824s48

Article Metrics
751 Views 142 Downloads 893 Total

Year

Month

Related Search

By author names