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The present study focused on production of mycelial chitosan from fungal mycelium by submerged fermentation with ecologically more balanced process. Different fungal strains were screened and
Absidia butleri
NCIM 977 was found to produce the highest mycelial chitosan. The one-factor-at-a-time method was adopted to investigate the effect of batch time, environmental factors (
i.e
. initial pH and temperature) and medium components (
i.e
. carbon and nitrogen) on the yield of mycelial chitosan. Among these variables, the optimal condition to increase in yield of mycelial chitosan was found to be batch time (72 h), pH (5.5), temperature (30
°C
), carbon source (glucose) and nitrogen source (tryptone and yeast extract). Subsequently, a three-level Box– Behnken factorial design was employed combining with response surface methodology (RSM) to maximise yield of mycelial chitosan by determining optimal concentrations and investigating the interactive effects of the most significant media components (i.e. carbon and nitrogen sources). The optimum value of parameters obtained through RSM was glucose (1.58%), tryptone (1.61%) and yeast extract (1.11%). There was an increase in mycelial chitosan yield after media optimization by one-factor-at-a-time and statistical analysis from 683 mg/L to 1 g/L. Mycelial chitosan was characterized for total glucosamine content (80.68%), degree of deacetylation (DD) (79.89%), molecular weight (8.07 × 10^{4} Da) and, viscosity (73.22 ml/g). The results of this study demonstrated that fungi are promising alternative sources of chitosan with high DD and high purity.

Chitosan is a natural amino polysaccharide comprising copolymers of D-glucosamine (GlcN) and N-acetyl- D-glucosamine (GlcNAc), and is a deacetylated derivative of chitin—the second most abundant natural polymer after cellulose [

Commercially available chitosan produced by chemical deacetylation of chitin has several disadvantages as isolation of chitin from crustacean shells and its conversion to chitosan requires strong alkali treatment, high temperature, and a long processing time, which make this process costly [

Recent advances in fermentation technology addressed that many of these problems can be overcome by culturing chitosan-producing fungi, particularly Zygomycetes species, which are known to contain chitosan as natural cell wall component [

Chitosan in cell walls produced through enzymatic deacetylation of chitin chain through the action of N-dea- cetylation is a common step in the modification of sugar chains [

Insight of the above advantages, the objective of present work is mainly focused to screen different fungal strains and to optimize culture conditions using one-factor-at-a-time and statistical analysis by response surface methodology (RSM) based on the Box-Behnken design for the highest production of mycelial chitosan by submerged fermentation. RSM was employed to build models, to evaluate the effective factors and their interaction and to select optimum conditions, with a minimum number of experiments. Furthermore, characterization of physical properties of produced mycelial chitosan was investigated.

Five different strains of Zygomycetes, namely, Absidia blakesleeana NCIM 889, Absidia butleri NCIM 977, Cunninghamella blakesleeana NCIM 687, Cunninghamella echinulata NCIM 691 and Rhizopus oryaze NCIM 1009 were purchased from National Collection of Industrial Microorganism (NCIM) Pune, India. For the screening, all the five strains were grown and maintained on potato dextrose agar (PDA) slants, grown at 30˚C for 10 days and stored at 4˚C and subcultured on a monthly basis. The chemicals and media components utilized in the present study were procured from Hi-Media (Mumbai, India). Concentrated NaOH solution was commercial grade and all chemicals were of analytical grade. Standards of chitosan were obtained from Sigma Chemical Co. (St. Louis, MO, USA).

The inoculum was prepared in Erlenmeyer flasks (250 ml) containing 100 ml of potato dextrose broth, inoculated with spore suspension (1.8 × 10^{8} spores/ml) and incubated at 30˚C for 16 h on a rotatory shaker (180 rpm). A 7.5% (v/v) of sixteen hr old inoculums was added aseptically to the 500 ml Erlenmeyer flasks, each containing 200 ml of the sterile production media of glucose 2%, peptone 1%, yeast extract 0.1%, (NH_{4})_{2}SO_{4} 0.5%, K_{2}HPO_{4} 0.1%, NaCl 0.1%, CaCl_{2} H_{2}O 0.01%, MgSO_{4}·7H_{2}O 0.05% [

To determine the optimum batch time for mycelial chitosan production, its production was carried out under the defined conditions, for different time periods ranging from 12 to 96 h. In order to investigate effect of initial pH of production media, fermentation runs were carried at initial pH varying from 3 to 6. The pH was adjusted using 0.1 N hydrochloric acid or 0.1 N sodium hydroxide. The effect of temperature on biomass and yield of mycelial chitosan was studied by incubating the production medium at varying temperature from 25˚C to 30˚C. In all three parameters after incubation, biomass was harvested, filtered through Whatman filter paper no. 1, washed with distilled water and dried them at 60˚C to a constant weight to determine the cell dry weight.

Several carbon sources were used to study the effect on mycelial chitosan production. To study the effect of various carbon sources on chitosan production, in the production medium, D (+) glucose was substituted with eight different carbon sources. All the carbon sources were used at 2% (w/v) concentration. Rests of the physicochemical parameters were constant.

To evaluate the effect of different nitrogen sources on mycelial chitosan production, combination of peptone (1% w/v), yeast extract (0.1% w/v) and ammonium sulphate (0.5% w/v) was replaced with different nitrogenous sources (both organic and inorganic) with concentration of 1.6% w/v. Mycelial chitosan yield and dry cell weight (DCW) were determined and rest of the physicochemical parameters were constant.

The most influential factors for mycelial chitosan production found by “one-factor-at-a-time” approach were further optimized with statistical approach. To describe the level of the significant parameters, interaction between variables, which influence the yield of mycelial chitosan and, the nature of the response surface in the optimum region, a Box-Behnken design [

In this study, the experimental plan consisted of 17 trials and the independent variables are studied at three different levels, low (−1), medium (0) and high (+1). The variables and their coded levels used for the study are shown in _{CY}). The second-order polynomial coefficients were calculated and analyzed using the Design Expert version 7.0.0 (STAT-EASE Inc., Minneapolis, MN, USA), statistical package.

The general form of the second degree polynomial Equation (1) is

where, Y_{CY} is the predicted response; β_{0} a constant; β_{i} the linear coefficient; β_{ii} the squared coefficient; and β_{ij} the cross-product coefficient, k is number of factors, x_{i} and x_{j} the level of the independent variables, subscripts i and j takes values from 1 to the number of variables.

In the present study, three variables are involved and hence n takes the value 3. Thus, by substituting the value 3 for n, and the coded variables for natural ones, Equation (1) becomes the following form: The yield of mycelial chitosan was taken as dependent variable or response Y_{CY}, and a multiple regression analysis of the data was carried out for obtaining an empirical model that relates the response measured to the independent variables.

Independent variables (%w/v) | Symbols | Coded values | ||
---|---|---|---|---|

−1 | 0 | +1 | ||

Glucose | A | 1.5 | 2 | 2.5 |

Tryptone | B | 1.1 | 1.6 | 2.1 |

Yeast extract | C | 1.1 | 1.6 | 2.1 |

The statistical and regression analyses of experimental data obtained from Box-Behnken design was done by using software Design Expert version 7.0.0 (STAT-EASE Inc., Minneapolis, MN, USA) to determine the significant differences (p ≤ 0.05) in response under different conditions. Three-dimensional surface plots were constructed for visualization of interaction between significant variables and their optimal values. The goodness of fit of the model was evaluated by the coefficient of determination (R^{2}) and the analysis of variance (ANOVA) and its statistical significance was checked by an F test quadratic polynomial equations were attained by holding one of the independent variances at a constant value and changing the level of the other variables.

The dried fungal cell mass was finely homogenized and subjected to alkali treatments to extract alkali soluble material like glucan and protein, present in fungal biomass. Dried mycelia homogenized dry cell mass were treated with 1 N sodium hydroxide solution (1:40, w/v) carried out by autoclaving biomass at 121˚C for 20 min. The alkali insoluble materials (AIM) were centrifuged (10,000 rpm, 15 min), washed with distilled water, until it completely gets neutralized and further treated with 2% acetic acid (1:40, w/v) at 95˚C for 6 h, closely following the method of [

Isolated mycelial chitosan obtained by submerged fermentation by evaluating some of the physical properties including glucosamine content, Fourier-transform infrared (FTIR) spectroscopy, degree of deacetylation (DD), viscosity and molecular weight (MW).

Determination of glucosamine content of mycelial chitosan was based on colorimetric measurement. Chitosan samples after extraction were hydrolyzed with 2 M hydrochloric acid at 110˚C for 2 h and the liberated D-glucosamine was deaminated with nitrous acid to yield 2,5-anhydromannose which react with 3-methyl-2- benzothiazolinone hydrazone hydrochloride (MBTH) to produce intense blue-colored complex measured at 650 nm [

The structure of extracted mycelial chitosan was confirmed by infra red spectroscopy using KBr pellet method in FTIR (Perkin Elmer Model 1600 Series, MA, USA). In FTIR spectra were recorded in the middle infrared (4000 cm^{−1} to 400 cm^{−1}) with a resolution of 4 cm^{−1} in the absorbance mode for 16 scans at room temperature. The mycelial chitosan samples were prepared by grinding the dry mycelial chitosan powder with powdered KBr, in the ratio of 1:5 (sample:KBr) and then compressed to form KBr pellet and subjected to FTIR analysis [

The degree of deacetylation (DD) was determined using the concept of baseline method [_{1655} and A_{3450} [^{−1} and the hydroxyl group absorption band at 3450 cm^{−1} were used as internal reference. An equation proposed by Baxter et al. for determination of degree of deacetylation is as follow:

Viscosity of mycelial chitosan was determined with an Ubbelohde-type capillary viscometer [_{in}]. The reduced viscosity (η_{red}), which is specific viscosity (η_{sp})/concentration (C), as tabulated, (η_{red} = η_{sp}/C) where (η_{sp} = η_{relative} − 1), and

Relative viscosity (η_{rel}) = specific viscosity (η_{sp}) = η_{rel} − 1

Reduced viscosity (η_{red}) vs. concentration of chitosan solution (g/dl, %) were plotted on a graph. The intrinsic viscosity ([η_{in}], dl/g) was obtained by extrapolating reduced viscosity vs. concentration data to zero concentration.

Using this value of the intrinsic viscosity ([η_{in}], dl/g) average molecular weight of mycelial chitosan (Mw) was determined. The viscosity-average molecular weight of mycelial chitosan solutions were calculated using the Mark Houwink equation which provides the relationship between intrinsic viscosity and molecular weight [

where, “K” and “a” are constants for given solute-solvent system and temperature.

A process of screening is necessary to determine the most influential factors affecting the cultivation process. In order to obtain the suitability of fermentation conditions the effect of various strains, incubation period, pH, temperature and various carbon and nitrogen sources on biomass and mycelial chitosan yield, was investigated.

Screening of fungal strains for mycelial chitosan producers are presented in

In order to determine the optimum batch time for mycelial chitosan production, fermentation process was carried out in 200 ml of sterile production media at 30˚C ± 2˚C on a rotary shaker at 160 rpm for different time level ranging from 12 h to 96 h. It was observed that 72 h time period resulted into maximum mycelial chitosan production of 585.33 mg/L with DCW 7.6 g/L (

culture enters the stationary growth phase, more of the chitosan is anchored to the cell wall of the Zygomycetes by binding to chitin and other polysaccharides and extraction becomes more difficult [

The pH of the medium always influences the physiology of a microorganism by affecting nutrient desirability, enzyme activity, oxidative-reductive reactions and most importantly cell membrane morphology. Among the various initial pH range studied (3 - 6), an initial pH 5.5 supported the maximum production of mycelial chitosan (669.16 mg/L) as well as biomass (

Temperature influences the metabolic activities and microbial growth which affects the production. In order to find out the effect of temperature on mycelial chitosan production, fermentation was carried out at different temperatures ranging from 20˚C to 35˚C. The yield increases from 20˚C till 30˚C and further decreased at 35˚C (

During microbial fermentations, the carbon source not only acts as a major constituent for building of cellular material, but also as an important energy source. All carbon sources with 2% (w/v) concentration showed different effects on mycelial chitosan production (

The nitrogen source is a critical factor which needs to be optimized for mycelial chitosan production. Chitosan is a nitrogen containing biopolymer, which is deacetylated form chitin. Fungi require an inorganic or organic nitrogen source as nutrient to synthesize the chitin and chitosan for their cell wall. Hence the nitrogen source is one of the important factors for the production of chitosan by fungi [

In this study, according to Box-Behnken design, all 17 designed experiments were conducted with different combinations of three independent parameters (glucose, tryptone and yeast extract) at three different levels, low (−1), medium (0) and, high (+1) to study the combined effects of these factors towards yield of mycelial chitosan. The variables and their coded levels used for the study are shown in

Run No. | Media concentration % (w/v) | Chitosan (g/L) | |||
---|---|---|---|---|---|

Glucose (A) | Tryptone (B) | Yeast extract (C) | Actual^{a} | Predicted | |

1 | 2.50 | 1.10 | 1.60 | 0.21 | 0.18 |

2 | 1.50 | 1.60 | 1.10 | 1 | 0.99 |

3 | 2.00 | 1.60 | 1.60 | 0.83 | 0.84 |

4 | 1.50 | 1.60 | 2.10 | 0.66 | 0.64 |

5 | 2.50 | 2.10 | 1.60 | 0.29 | 0.29 |

6 | 2.00 | 1.60 | 1.60 | 0.86 | 0.84 |

7 | 2.00 | 1.60 | 1.60 | 0.89 | 0.84 |

8 | 2.00 | 2.10 | 1.10 | 0.65 | 0.63 |

9 | 2.00 | 2.10 | 2.10 | 0.48 | 0.48 |

10 | 2.50 | 1.60 | 2.10 | 0.44 | 0.45 |

11 | 2.00 | 1.10 | 2.10 | 0.32 | 0.34 |

12 | 2.00 | 1.60 | 1.60 | 0.84 | 0.84 |

13 | 1.50 | 1.10 | 1.60 | 0.54 | 0.54 |

14 | 2.50 | 1.60 | 1.10 | 0.52 | 0.54 |

15 | 2.00 | 1.10 | 1.10 | 0.64 | 0.64 |

16 | 2.00 | 1.60 | 1.60 | 0.78 | 0.84 |

17 | 1.50 | 2.10 | 1.60 | 0.54 | 0.57 |

^{a}Values are mean ± SD of three determinations.

concentrations of glucose 1.5% (w/v), tryptone 1.6% (w/v), and yeast extract 1.1% (w/v). Consequently, the following second order polynomial equation for mycelial chitosan production was regressed and expressed in term of coded factors. It represents yield of mycelial chitosan (Y_{CY}) as a function of concentration of glucose (A), tryptone (B) and yeast extract (C).

In order to determine whether or not the quadratic model is significant, it is necessary to conduct analysis of variance (ANOVA). ANOVA for response surface quadratic model is presented in ^{2}, B^{2}) and one cross-product coefficients (AC) were significant. It implies that three parameters are very critical for the production of mycelial chitosan and there was strong interaction between concentrations of glucose and yeast extract. The statistical significance of the polynomial equation was carried by F-test. The model F-

Source | Sum of squares | df^{a} | Mean square | F-value | Prob > F |
---|---|---|---|---|---|

Model | 0.83 | 9 | 0.092 | 64.20 | <0.0001^{*} |

Lack of fit | 3.425E−003 | 3 | 1.142E−003 | 0.60 | 0.6031^{**} |

Residual | 0.010 | 7 | 1.432E−003 | ||

Pure error | 6.600E−003 | 4 | 1.650E−003 | ||

Correlation total | 0.84 | 16 |

^{a}Degree of freedom; ^{*}Significant; ^{**}Not significant.

Model term | Coefficient of estimate | df^{a} | Standard error | F-value | Prob > F |
---|---|---|---|---|---|

Intercept | 0.84 | 1 | 0.017 | - | - |

A | −0.16 | 1 | 0.013 | 143.00 | <0.0001 |

B | 0.031 | 1 | 0.013 | 5.46 | 0.0522 |

C | −0.11 | 1 | 0.013 | 72.28 | <0.0001 |

A^{2} | −0.16 | 1 | 0.018 | 71.78 | <0.0001 |

B^{2} | −0.29 | 1 | 0.018 | 245.13 | <0.0001 |

C^{2} | −0.029 | 1 | 0.018 | 2.43 | 0.1630 |

AB | 0.020 | 1 | 0.019 | 1.12 | 0.3256 |

AC | 0.065 | 1 | 0.019 | 11.80 | 0.0109 |

BC | 0.037 | 1 | 0.019 | 3.93 | 0.0879 |

A—Glucose; B—Tryptone; C—Yeast extract; ^{a}Degree of freedom; ^{*}Significant; ^{**}Not significant.

value of 64.20 (p < 0.0001) implies the model is significant and is calculated as ratio of mean square regression and mean square residual. The goodness of fit of the model was checked by coefficient of determination (R^{2}) and adjusted coefficient of determination (adjusted R^{2}). The R^{2} value varies from 0 to 1.0 and close to 1.0 implies better accuracy of the model. But in certain cases higher R^{2} value may be resulted in presence of large number of insignificant variables in the model and thereby predicts poor response. So the term adjusted R^{2 }was introduced which corrects R^{2} value accordingly to the sample size and number of terms in model. Ideally adjusted R^{2} should be close to R^{2} value. Larger difference between R^{2} and adjusted R^{2 }gives warning that model content too many insignificant terms [^{2} value (0.9880) indicates, good correlation between experimental and predicted values and 98.80% of the variability in the response could be explained by the model. The R^{2 }of 0.9880 is in reasonable agreement with the adjusted R^{2} of 0.9726 confirming the validity of the model. “Adequate Precision” measures the signal to noise ratio and its value can be predicted by statistical analysis. A ratio greater than 4 is desirable [

Perturbation graph shows the effect of each of the independent variables on response while keeping other variables at their respective zero level. From

Accordingly, 3-D response surface plot were generated for the pairwise combination of two independent variables where remaining variables are fixed at their respective zero level and described by the regression model which illustrate the interactive effect of this independent variables on the response variable and also determine optimum level of each variable [

range of glucose concentration from 1.5% (w/v) to 2.5% (w/v), the amplification of mycelial chitosan yield resulted in a linear increase in tryptone concentration, and then reduced. It can be inferred that yield of mycelial chitosan was markedly affected by the combination of glucose concentration and tryptone concentration. An increase of tryptone concentration increased the mycelial chitosan yield at a constant glucose concentration within a tryptone concentration of 1.6% (w/v). The appropriate maximal mycelial chitosan yield was determined at a glucose concentration of 1.5% (w/v).

In order to verify the predicted results, an experiment was performed using the optimized nutrient levels. The optimum conditions for these selected parameters were predicted using desirability function criteria available in design expert software. The maximum predicted mycelial chitosan production could be achieved with glucose concentration of 1.58% w/v (A), Tryptone concentration of 1.61% w/v (B), and yeast concentration of 1.11% w/v (C). Under these conditions experiments were carried out in triplicate. The mean value of the yield of mycelial chitosan was 1.002 mg/L, which agreed with the predicted value (1.0012 mg/L) well. As a result, the models developed were considered to be accurate and reliable for predicting the production of mycelial chitosan from A. butleri NCIM 977.

Chitosan are linear polysaccharides consisting of N-acetyl-D-glucosamine and D-glucosamine units present in different ratios in the polymers. The glucosamine content in chitosan isolated from fungal source A. butleri NCIM 977 was determined to be 80.68%, a little more than the report of Synowieki and Al-khateeb [

IR spectroscopy has been reported as a relatively quick, simple technique and commonly used for qualitative and quantitative evaluations of chitin and chitosan characteristics, mainly their functional groups, the degree of acetylation/deacetylation and impurities [^{−1}; the C-H stretching bands within 2870 - 2880 cm^{−1}; the skeletal vibrations involving the C-O-C stretching band at 1030 - 1070 cm^{−1}; the -CH_{2} bending centered at 1420 cm^{−1}; the anti-symmetric stretching of the C-O-C bridge around 1160 cm^{−1}; 1315 - 1320 cm^{−1} (amide III band); 1620 - 1630 cm^{−1} (-NH bending of NH_{2}); and 890 - 900 cm^{−1} (C-O-C bridge as well as glucosidic linkage) [^{−1}. Other functional group include hydroxyl stretching band at 3427 cm^{−1}, amide I band at 1655, primary amine band at 1638 - 1561 cm^{−1} amide II band at 1561 cm^{−1} and amide III band at 1320 cm^{−1}. The band at 897 cm^{−1} was referenced as glycosidic linkage of β-anomer. These absorption bands preliminary ascertained the product to be chitosan.

IR spectroscopic method was commonly used for determination of DD value of mycelial chitosan. It was initially

proposed by Moore and Roberts. It has a number of advantages like relatively fast method and does not require dissolution of the chitosan sample in an aqueous solvent. IR spectroscopy is primarily a solid-state method utilizing the concept of baseline for DD calculation. The baseline proposed by Baxter et al. [

The viscosity of mycelial chitosan obtained from the submerged fermentation of A. butleri NCIM 977 was 73.22 dl/g. The molecular weight of mycelial chitosan was depends and vary upon substrate, medium supplementation and fermentation mode. The viscosity average molecular weight of mycelial chitosan was calculated from Mark Houwink equation. In present study the molecular weight (MW) of mycelial chitosan was found to be 8.07 × 10^{4} Da and was lower compared to commercial chitosan. Previous research has reported the MW to be between 3 × 10^{4 }Da - 1.4 × 10^{5} Da [

In conclusion, the maximum yield of mycelial chitosan was obtained from A. Butleri NCIM 977 under the cultivation condition of pH 5.5 and temperature 30˚C with production batch time of 72 hrs. Subsequently, the culture media supplemented with glucose, yeast extract and tryptone produced the highest yield of mycelial chitosan. An increase in the yield of mycelial chitosan was dependent on the supplementation and interaction of nitrogen source with other media components. The results indicated that the choice of media and nitrogen supplements are critical factors in obtaining high yield of mycelial chitosan. The media composition also affected the glucosamine content, degree of deacetylation, viscosity and molecular weight of the mycelial chitosan and was found to be 80.68%, 79.89%, 73.22 ml/g and 8.07 × 10^{4} Da respectively. Interestingly, low molecular weight chitosan with desirable physico-chemical properties would be achieved under submerged fermentation and could be potentially applied to the food, cosmetic, chemical and pharmaceutical industries. In summary, fermentative production of mycelial chitosan can be a good alternative to lessen environmental pollution of strong alkali from traditional chitosan production and provides a new, simple and green technology for production of low-molecular-weight chitosan.