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Optimization of fungal chitosan production from Cunninghamella echinulata using statistical  designs

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Abstract

Fungal chitosan (FCH) is superior to crustacean chitosan (CH) sources and is of immense interest to the scientific community while having a high demand at the global market. Industrial scale fermentation technologies of FCH production are associated with considerable challenges that frequently restrict their economic production and feasibility. The production of high quality FCH using an underexplored fungal strain Cunninghamella echinulata NCIM 691 that is hoped to mitigate potential future large-scale production was investigated. The one-factor-at-a-time (OFAT) method was implemented to examine the effect of the medium components (i.e. carbon and nitrogen) on the FCH yield. Among these variables, the optimal condition for increased FCH yield was carbon (glucose) and nitrogen (yeast extract) source. A total of 11 factors affected FCH yield among which, the best factors were screened by Plackett–Burman design (PBD). The optimization process was carried out using the response surface methodology (RSM) via Box-Behnken design (BBD). The three-level Box– Behnken factorial design facilitated optimum values for 3 parameters—glucose (2% w/v), yeast extract (1.5% w/v) and magnesium sulphate (0.1% w/v) at 30˚C and pH of 4.5. The optimization resulted in a 2.2-fold higher FCH yield. The produced FCH was confirmed using XRD, 1H NMR, TGA and DSC techniques. The degree of deacetylation (DDA) of the extracted FCH was 88.3%. This optimization process provided a significant improvement of FCH yields and product quality for future potential scale-up processes. This research represents the first report on achieving high FCH yield using a reasonably unfamiliar fungus C. echinulata NCIM 691 through optimised submerged fermentation conditions.

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Data availability

The raw data supporting the conclusion of this article will be made available by the authors upon reasonable request.

Abbreviations

AIM:

Alkali insoluble materials

ANOVA:

Analysis of variance

BBD:

Box-Behnken design

CCD:

Central composite design

CH:

Chitosan

CHNPs:

Chitosan nanoparticles

CSL:

Corn steep liquor

CT:

Chitin

CW:

Cassava waste water

D2O:

Deuterium oxide

DCl:

Deuterium chloride

DCW:

Dry cell weight

DDA:

Degree of deacetylation

DLS:

Dynamic light scattering

DoE:

Design of experiment

DSC:

Differential scanning calorimetry

FCH:

Fungal chitosan

FT-IR:

Fourier transform infrared spectroscopy

LMWCH:

Low molecular weight chitosan

MGYP:

Malt extract glucose yeast extract peptone

MW :

Molecular weight

NCIM:

National collection of industrial microorganism

NMR:

Nuclear magnetic resonance spectroscopy

OFAT:

One-factor-at-a-time

PBD:

Plackett–Burman Design

PBS:

Phosphate Buffer Saline

PDB/PDA:

Potato dextrose broth/agar

RSM:

Response surface methodology

SEM:

Scanning electron microscopy

SmF:

Submerged fermentation

Tg:

Glass transition temperature

TGA:

Thermogravimetric analysis

VIF:

Variance Inflation Factor

XRD:

X-Ray diffraction

YPD:

Yeast extract peptone dextrose

ZP:

Zeta potential

References

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Acknowledgements

BMK, PAM and SKS are grateful to Savitribai Phule Pune University for providing financial support to complete the proposed research

Author information

Authors and Affiliations

  1. Department of Microbiology, Savitribai Phule Pune University, Ganeshkhind, Pune, 411007, Maharashtra, India

    Bhoomika M. Karamchandani, Priya A. Maurya & Surekha K. Satpute

  2. Department of Statistics, Savitribai Phule Pune University, Ganeshkhind, Pune, 411007, Maharashtra, India

    Manik Awale

  3. Tissue Culture Section, Vasantdada Sugar Institute, Pune, 412307, Maharashtra, India

    Sunil G. Dalvi

  4. School of Biomedical Sciences, University of Ulster, Coleraine, Northern Ireland, BT52 1SA, UK

    Ibrahim M. Banat

Authors
  1. Bhoomika M. Karamchandani
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  2. Priya A. Maurya
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  3. Manik Awale
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  4. Sunil G. Dalvi
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  5. Ibrahim M. Banat
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  6. Surekha K. Satpute
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Contributions

BMK performed all the experiments in the laboratory and wrote the paper- preliminary draft including entire data analysis. PAM assisted BMK to conduct the experiments and write the preliminary draft. MA analysed the statistical data and was also involved in editing the manuscript. SD and SKS contributed towards conceptualization, designing the methodology and editing the manuscript. IMB and SKS contributed in designing, studying, reviewing, analysing the entire data as well as editing the complete manuscript. All authors have carefully read and approved the final version of the manuscript.

Corresponding authors

Correspondence to Ibrahim M. Banat or Surekha K. Satpute.

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Conflict of interest

Authors have declared that they have no conflict of interest.

Ethical standards

This research does not involve any human participants and/or animals.

Supplementary Information

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Supplementary file1 (DOCX 48 KB)

Supplementary file2 (TIF 488 KB)

Fig. S1 Effect of different nitrogen sources at A: 1%, B: 1.5%, C: 2%, D: Merge plot depicting comparison between all nitrogen sources at varied concentrations (%), E: Effect of peptone (P) and yeast extract (Y) individually and in combination at varied concentrations on chitosan production (mg/l) by C. echinulata. The fungal suspension - 1.0 ×108 spores/ml was made in phosphate buffer saline (pH 7.0) and inoculated into fermentation medium supplemented with four nitrogen sources individually at three different concentrations - selected through One-factor-at-a-time (OFAT) approach. Culture was incubated at 29±1℃/100 rpm/6 days. Highest biomass and chitosan production were observed in yeast extract followed by peptone, soyameal and tryptone. Comparison between all four nitrogen sources depicted a positive effect on biomass and chitosan with gradual increase in the concentration of yeast extract

Supplementary file3 (TIF 338 KB)

Fig. S2 Thermogravimetric analysis (TGA) A: Commercial-Low molecular weight commercial chitosan (LMWCH) and B: Fungal chitosan (FCH) derived from C. echinulata. TGA provides thermal analysis under the influence of altered temperature conditions. The TGA was performed at 40–600°C in an inert environment of nitrogen (20°C/min). TGA curves denoted the thermal stability along with decomposition of samples. In LMWCH, first stage loss was 2.382% at 50-180°C; whereas, for FCH the weight loss was 4.151% which remained stable up to 240°C. The second decomposition resulted in weight loss of 53.875% (for LMWCH) and 53.854% (for FCH) which can be correlated with the pyrolytic decomposition of saccharide rings of the chitosan molecule at 200 and 450°C

Supplementary file4 (TIF 297 KB)

Fig. S3 Differential scanning calorimeter (DSC). A: Commercial - Low molecular weight commercial chitosan (LMWCH) and B: Fungal chitosan (FCH) derived from C. echinulata. DSC measures the difference in the amount of heat needed to raise the temperature of a sample. Both samples were upheld at 30-200°C in an inert nitrogen environment (10°C/min). The DSC curves of both samples displayed a typical polysaccharide with degradation profiles. The first endothermic peak for LMWCH at 28.19°C (348.9J/g) and for FCH at 40.59°C (450.5 J/g). The second endothermic peak initiated at 77.81°C (for LMWCH) and 87.94°C (for FCH) till 126.30°C. The elevation in the baseline corresponds to the degradation of chitosan samples due to its combustion

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Karamchandani, B.M., Maurya, P.A., Awale, M. et al. Optimization of fungal chitosan production from Cunninghamella echinulata using statistical  designs. 3 Biotech 14, 82 (2024). https://doi.org/10.1007/s13205-024-03919-6

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  • DOI: https://doi.org/10.1007/s13205-024-03919-6

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