Comparative Analysis of α-Amylase Sequences in Selected Aspergillus Species and Analysis of Amylase Activity in Three Locally Isolated Aspergillus Species
Article Sidebar
Main Article Content
Abstract
Amylase is an important enzyme in industries where members of the Aspergillus genus are significant producers of industrial amylase enzymes; α- amylase is an endoamylase which plays a crucial role in starch hydrolysis. However, knowledge regarding the sequences and evolutionary relationship of α- amylase among sections Nigri, Flavi and Fumigati in the Aspergillus genus have remained unknown. The amylase activity of some previously isolated important Aspergillus species, namely A. niger, A. fumigatus and A. flavus, also requires further investigation. In this study, α- amylase sequences of species under three sections in the Aspergillus genus were retrieved from NCBI for sequence analysis and alignment for phylogenetic tree construction. The solid-based method was then applied to screen for amylase production and the Enzymatic Activity Index (EAI) was evaluated to analyze amylase activity. Similarities in enzyme sequences among the selected species were established through the presence of α- amylase domains and phylogenetic tree branching that rooted to a common ancestor. This study also found that the amylase activity of three selected species differed significantly, with A. flavus having the highest EAI of 1.03 ± 0.049, followed by A. niger (0.77 ± 0.049) and A. fumigatus (0.60 ± 0.103).
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Heckmann CM, Paradisi F. Looking back: A short history of the discovery of enzymes and how they became powerful chemical tools. Chem Cat Chem. 2020;12(24):6082-102.
Bhatia S. Introduction to enzymes and their applications. In: Bhatia S, editor. Introduction to pharmaceutical biotechnology, Volume 2. IOPPublishing; 2018:1-29.
May O. Industrial enzyme applications - Overview and historic perspective. In: Vogel A, May O, editors. Industrial enzyme applications. Chichester, UK: John Wiley & Sons, Ltd; 2019. p. 1-24.
Ivaldo Itabaiana Jr, Rodrigo O. M. A. De Souza. Biocatalysts at room temperature. In: Luque R, Lam FYL, editors. Sustainable catalysis: Energyefficient reactions and applications. Wiley; 2018. p. 89-134.
Rebello S, Aneesh EM, Sindhu R, et al. Enzyme catalysis: A workforce to productivity of textile industry. In: Saran S, Babu V, Chaubey A, editors. High value fermentation products. Wiley; 2019. p. 49-65.
Balakrishnan D, Kumar SS, Sugathan S. Amylases for food applications— Updated information. In: Parameswaran B, Varjani S, Raveendran S, editors. Energy, environment, and sustainability green bio-processes. Springer Singapore; 2018. p. 199-227.
Sharma A, Gupta G, Ahmad T, et al. Enzyme engineering: Current trends and future perspectives. Food Reviews International. 2021; 37(2): 121-54.
Sidar A, Albuquerque ED, Voshol GP, et al. Carbohydrate binding modules: Diversity of domain architecture in amylases and cellulases from filamentous microorganisms. Frontiers in Bioengineering and Biotechnology. 2020; 8:1-17.
Martinovičová M, Janeček Š. In silico analysis of the α-amylase family GH57: Eventual subfamilies reflecting enzyme specificities. 3 Biotech. 2018; 8: 307.
Janecek S. Sequence similarities and evolutionary relationships of microbial, plant and animal alphaamylases. European Journal of
Biochemistry. 1994; 224(2): 519-24.
Avwioroko OJ, Anigboro AA, Unachukwu NN, et al. Isolation, identification and in silico analysis of alpha-amylase gene of Aspergillus niger strain CSA35 obtained from cassava undergoing spoilage. Biochemistry and Biophysics Reports. 2018; 14: 35-42.
Janíčková Z, Janeček Š. Fungal αamylases from three GH13 subfamilies: their sequence-structural features and evolutionary relationships. International Journal of Biological Macromolecules. 2020; 159: 763-72.
Liu X, Kokare C. microbial enzymes of use in industry. In: Brahmacharin G, editor. Biotechnology of microbial enzymes. Elsevier; 2017. p. 267-98.
Arastehfar A, Carvalho A, Houbraken J, et al. Aspergillus fumigatus and aspergillosis: From basics to clinics. Studies in Mycology. 2021; 100(1): 100115.
Samson RA, Visagie CM, Houbraken J, et al. Phylogeny, identification and nomenclature of the genus Aspergillus. Studies in Mycology. 2014; 78(1): 141-73.
Vesth TC, Nybo JL, Theobald S, et al. Investigation of inter- and intraspecies variation through genome sequencing of Aspergillus section Nigri. Nature Genetics. 2018; 50(12): 1688-95.
Frisvad JC, Hubka V, Ezekiel CN, et al. Taxonomy of Aspergillus section Flavi and their production of aflatoxins, ochratoxins and other mycotoxins. Studies in Mycology. 2019; 93(1): 1-63.
Talbot JJ, Barrs VR. One-health pathogens in the Aspergillus viridinutans complex. Medical Mycology. 2018; 56(1): 1-12.
Varga J, Frisvad JC, Kocsubé S, et al. New and revisited species in Aspergillus section Nigri. Studies in Mycology. 2011; 69: 1-17.
Frisvad JC, Larsen TO. Extrolites of Aspergillus fumigatus and other pathogenic species in Aspergillus section Fumigati. Frontiers in
Microbiology. 2016; 6: 1-14.
Letunic I, Bork P. 20 years of the SMART protein domain annotation resource. Nucleic Acids Research.2018; 46: D493-6.
Nielsen H. Predicting secretory proteins with SignalP. In: Kihara D, editor. Protein function prediction. New York: Humana New York; 2017. p. 59-73.
Thumuluri V, Almagro Armenteros JJ, Johansen AR, et al. DeepLoc 2.0: Multi-label subcellular localization prediction using protein language models. Nucleic Acids Research. 2022; 50: W228-34.
Nuanpirom J, Sangket U. Improving identification of animal secretoryproteins. In: 7th International Conference on Biochemistry and Molecular Biology. 2021.
Madeira F, Pearce M, Tivey ARN, et al. Search and sequence analysis tools services from EMBL-EBI in 2022. Nucleic Acids Research. 2022; 50:W276-9.
Barton GJ. Sequence alignment for molecular replacement. Acta Crystallographica Section D Biological Crystallography. 2008; 64(1): 25-32.
Kumar S, Stecher G, Li M, et al. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Molecular Biology andEvolution. 2018; 35(6): 1547-9.
Gopinath SCB, Anbu P, ArshadMKM, et al. Biotechnological processes in microbial amylase production. BioMed Research International. 2017; 2017(1): 1-9.
Ugoh SC, Ijigbade B. Production and characterisation of amylase by fungi isolated from soil samples at Gwagwalada, FCT, Abuja - Nigeria. Report and Opinion. 2013;5(7):44-53.
Das S, Samanta P, Uday USP. Isolation and characterisation of amylase producing fungal strain. Journal of Environment and Sociobiology. 2020; 17(2): 1-7.
Goldbeck R, Andradel CCP, Pereira GAG, et al. Screening and identification of cellulase producing yeast-like microorganisms from Brazilian biomes. African Journal of Biotechnology. 2012;11(53):11595- 603.
Janecek S, Svensson B, Henrissat B. Domain evolution in the α-amylase family. Journal of Molecular Evolution. 1997; 45(3): 322-31.
Wang Y, Zhang H, Zhong H, et al. Protein domain identification methods and online resources. Computational and Structural Biotechnology Journal. 2021; 19: 1145-53.
Kumari B, Kumar R, Kumar M. Low complexity and disordered regions of proteins have different structural and amino acid preferences. Molecular Biosystems. 2015; 11(2): 585-94.
Mier P, Andrade-Navarro MA. Assessing the low complexity of protein sequences via the low complexity triangle. PLoS One. 2020;15: e0239154.
Paul JS, Gupta N, Beliya E, et al. Aspects and recent trends in microbial α-amylase: A review. Applied Biochemistry and Biotechnology. 2021; 193(8): 2649-98.
Da Lage J-L. An optional C-terminal domain is ancestral in α-amylases of bilaterian animals. Amylase. 2017; 1: 26-34.
Ren Z, Ren PX, Balusu R, et al. Transmembrane helices tilt, bend, slide, torque, and unwind between functional states of rhodopsin. Scientific Reports. 2016;6(1):34129.
Guna A, Hegde RS. Transmembrane domain recognition during membrane protein biogenesis and quality control. Current Biology. 2018;28:R498- R511.
Singh S, Mittal A. Transmembrane domain lengths serve as signatures of organismal complexity and viral transport mechanisms. Scientific Reports 2016;6(1):22352.
Teufel F, Almagro Armenteros JJ, Johansen AR, et al. SignalP 6.0 predicts all five types of signal peptides using protein language models. Nature Biotechnology. 2022;40(7):1023-5.
Grasso S, Dabene V, Hendriks MMWB, et al. Signal peptide efficiency: From high-throughput data to prediction and explanation. ACS Synthetic Biology. 2023;12(2):390- 404.
Pohlschroder M, Pfeiffer F, Schulze S, et al. Archaeal cell surface biogenesis. FEMS Microbiology Reviews. 2018; 42(5): 694-717.
Yao D, Su L, Li N, et al. Enhanced extracellular expression of Bacillus stearothermophilus α-amylase in Bacillus subtilis through signal peptide optimization, chaperone overexpression and α-amylase mutant selection. Microbial Cell Factories. 2019; 18(1): 69.
Rédei GP. Encyclopedia of genetics, genomics, proteomics and informatics. Dordrecht: Springer Netherlands; 2008.
Dalio RJD, Herlihy J, Oliveira TS, et al. Effector biology in focus: A primer for computational prediction and functional characterization. Molecular Plant-Microbe Interactions. 2018; 31(1):22-33.
Almagro Armenteros JJ, Sønderby CK, Sønderby SK, et al. DeepLoc: Prediction of protein subcellular localization using deep learning. Bioinformatics. 2017;33(21):3387-95.
Hallgren J, Tsirigos KD, Pedersen MD, et al. DeepTMHMM predicts alpha and beta transmembrane proteins using deep neural networks. bioRxiv 2022; 2022.04.08.487609.
Gautier M, Normand A-C, Ranque S. Previously unknown species of Aspergillus. Clinical Microbiology and Infection. 2016; 22(8): 662-9.
Chang PK, Ehrlich K, Fujii I. Cyclopiazonic acid biosynthesis of Aspergillus flavus and Aspergillus oryzae. Toxins (Basel). 2009;1:74-99.
Gibbons JG, Salichos L, Slot JC, et al. The evolutionary imprint of domestication on genome variation and function of the filamentous fungus Aspergillus oryzae. Current Biology. 2012; 22(15): 1403-9.
Campbell CK, Johnson EM, Warnock DW. Identification of pathogenic fungi. Wiley; 2013.
Gupta R, Gigras P, Mohapatra H, et al. Microbial α-amylases: A biotechnological perspective. Process Biochemistry. 2003; 38: 1599-616.
Brust H, Orzechowski S, Fettke J. Starch and glycogen analyses: Methods and techniques. Biomolecules. 2020; 10: 1020.
Seung D. Amylose in starch: Towards an understanding of biosynthesis, structure and function. New Phytologist. 2020; 228: 1490-504.
Fadahunsi IF, Garuba OE. Amylase production by Aspergillus flavus associated with the bio-deterioration of starch-based fermented foods. New York Science Journal. 2012;(1):13-8.
Mythii A, Singh YRB, Priya R, et al. In vitro and comparative study on the extracellular enzyme activity of molds isolated from keratomycosis and soil. International Journal of Ophthalmology. 2014; 7(5): 778-84.
El-Latif Hesham A, Saleh F, Al-Bedak O, et al. Molecular identification of naturally isolated Candida tropicalis AUN-H100 and optimization of their extracellular amylase production. International Journal of Agricultural Sciences and Veterinary Medicine. 2019; 7(4): 28-34.
Khokhar I, Mukhtar I, Mushtaq S. Comparative studies on the amylase and cellulase production of Aspergillus and Penicillium. Journal of Applied Sciences and Environmental Management. 2011; 15: 657-61.
Fifendy M, Indriati G, Osnita S, et al. Isolation and activity of amylase enzyme in isolates of fungi from black rice lemang (Oryza sativa Siarang). Advances in Biological Sciences Research. 2020; 10:46-50.
Tuppad DarshanS, Shishupala S. Endophytic mycobiota of medicinal plant Butea monosperma. International Journal of Current
Microbiology and Applied Sciences. 2013; 2(12): 615-27.
Pathak SS, Sandhu SS. Screening of glucoamylase producing fungi from the soils of Jabalpur region. International Journal of Recent Scientific Research. 2019;10:30470-6.
Saleem A, Ebrahim MKH. Production of amylase by fungi isolated from legume seeds collected in Almadinah Almunawwarah, Saudi Arabia. Journal of Taibah University for Science. 2014; 8: 90-7.
Aydoğdu H, Balkan B, Balkan S, et al. Amylolytic activities of fungi species on the screening medium adjusted to different pH. Erzincan University Journal of Science and Technology. 2012; 5: 1-12.
Mäkelä MR, DiFalco M, McDonnell E, et al. Genomic and exoproteomic diversity in plant biomass degradation approaches among Aspergilli. Studies in Mycology. 2018; 91: 79-99.
Mukunda S, Onkarappa R, Prashith Kekuda TR. Isolation and screening of industrially important fungi from the
soils of Western Ghats of Agumbe and Koppa, Karnataka, India. Science, Technology and Arts Research Journal. 2012; 1(4): 27-32.
Adeniran HA, Abiose SH, Ogunsua AO. production of fungal β-amylase and amyloglucosidase on some Nigerian agricultural residues. Food and Bioprocess Technology. 2010; 3(5): 693-8.
Omemu A, Bamigbade G, Obadina A, et al. Isolation and screening of amylase from moulds associated with the spoilage of some fermented cereal foods. British Microbiology Research Journal. 2015; 5(4): 359-67.
Al-Hindi RR, Al-Najada AR, Mohamed SA. Isolation and identification of some fruit spoilage fungi: Screening of plant cell wall degrading enzymes. African Journal of Microbiology Research. 2011; 5(4): 443-8.
Morya V, Yadav D. Isolation and screening of different isolates of Aspergillus for amylases production. The Internet Journal of Microbiology. 2008; 7(1): 1-8.
Huma T, Mustafa G, Sethi A, et al. Computational approach to study role of active site amino acids of alpha amylases in thermostability of Pyrococcus furiosus and Bacillus sp. Biochemistry & Molecular Biology Journal. 2021; 7(10): 1-9.
Singh S, Singh S, Bali V, et al. Production of fungal amylases using cheap, readily available agriresidues, for potential application in textile industry. Biomed Research International. 2014; 2014: 1-9.