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Bioinformatic analysis of domain and motif architecture of cellulase enzymes in five CAZy families of Ascomycota | ||
| Mycologia Iranica | ||
| دوره 13، شماره 1، شهریور 2026، صفحه 25-38 اصل مقاله (2.18 M) | ||
| نوع مقاله: Data Analysis | ||
| شناسه دیجیتال (DOI): 10.22092/mi.2026.371792.1338 | ||
| نویسندگان | ||
| Abbas Rahimi1؛ Mohammad Ali Tajick Ghanbary* 1؛ Valiollah Babaeizad1؛ Mohammad Ali Barimani Varandi1؛ Samira Shahbazi2 | ||
| 1Department of Plant Protection. Faculty of Crop Sciences, Sari Agricultural Sciences and Natural Resources University (SANRU), Sari, Iran | ||
| 2Nuclear Agriculture Research School, Nuclear Science and Technology Research Institute (NSTRI), Karaj, Iran | ||
| چکیده | ||
| Cellulase enzymes degrade cellulose, the most abundant structural polysaccharide in plant biomass, thereby playing a central role in fungal ecology and biotechnology. Here, we conducted a bioinformatic analysis of cellulase enzymes across the phylum Ascomycota to examine their diversity, domain architecture, conserved motifs, and evolutionary relationships. We retrieved cellulase protein sequences from 69 representative Ascomycota species in the UniProtKB database, analyzed them using InterProScan, COBALT, and the MEME Suite, and conducted phylogenetic reconstruction in MEGA11. Our domain analysis identified five major CAZy families: glycoside hydrolase families GH5, GH7, GH10, GH11, and auxiliary activity family AA9, demonstrating the structural diversity found in ascomycete cellulases. Motif analysis revealed multiple conserved and family-specific motifs, indicating strong conservation of catalytic cores and variability in peripheral regions. Multiple sequence alignment and phylogenetic analyses showed that cellulase proteins clustered clearly within CAZy families, with high bootstrap support, suggesting that domain and motif architectures provide robust phylogenetic signals. Together, these results clarify the structural and evolutionary diversity of ascomycete cellulases and establish a foundation for future functional, ecological, and biotechnological studies of fungal cellulases. | ||
| کلیدواژه‌ها | ||
| COBALT؛ InterProScan؛ MEME Suite؛ NCBI؛ UniProtKB | ||
| مراجع | ||
|
Bailey TL, Johnson J, Grant CE, Noble WS. 2015. The MEME suite. Nucleic Acids Research. 43(W1): W39-W49. https://doi.org/10.1093/nar/gkv416.
Contato AG, Conte-Junior CA. 2025. Fungal lytic polysaccharide monooxygenases (LPMOs): Functional adaptation and biotechnological perspectives. Eng. 6(8): 177-177. https://doi.org/10.3390/eng6080177.
Coudert E, Gehant S, de Castro E, Pozzato M, Baratin D, Neto T, Sigrist CJA, Redaschi N, Bridge A. 2023. Annotation of biologically relevant ligands in UniProtKB using ChEBI. Bioinformatics. 39: btac803-btac803. https://doi.org/10.1093/bioinformatics/btac803.
de Vries RP, Visser J. 2001. Aspergillus enzymes involved in degradation of plant cell wall polysaccharides. Microbiology and Molecular Biology Reviews. 65(4): 497-522. https://doi.org/10.1128/MMBR.65.4.497-522.2001.
Eastwood DC, Floudas D, Binder M, Majcherczyk A, Schneider P, Aerts A, Watkinson SC, Hibbett DS. 2011. The plant cell wall–decomposing machinery underlies the functional diversity of forest fungi. Science. 333(6043): 762-765. https://doi.org/10.1126/science.1205411.
El Kaoutari A, Armougom F, Gordon JI, Raoult D, Henrissat B. 2013. The abundance and variety of carbohydrate-active enzymes in the human gut microbiota. Nature Reviews Microbiology. 11(7): 497-504. https://doi.org/10.1038/nrmicro3050.
Felsenstein J. 1985. Confidence limits on phylogenies: An approach using the bootstrap. Evolution. 39(4): 783-791. https://doi.org/10.2307/2408678.
Hage H, Rosso M-N. 2021. Evolution of fungal carbohydrate-active enzyme portfolios and adaptation to plant cell-wall polymers. Journal of Fungi. 7(3): 185-185. https://doi.org/10.3390/jof7030185.
Henrissat B, Davies G. 1997. Structural and sequence-based classification of glycoside hydrolases. Current Opinion in Structural Biology. 7(5): 637-644. https://doi.org/10.1016/S0959-440X(97)80072-3.
Himmel ME, Ding SY, Johnson DK, Adney WS, Nimlos MR, Brady JW, Foust TD. 2007. Biomass recalcitrance: Engineering plants and enzymes for biofuels production. Science. 315(5813): 804-807. https://doi.org/10.1126/science.1137016.
Horn SJ, Vaaje-Kolstad G, Westereng B, Eijsink VGH. 2012. Novel enzymes for the degradation of cellulose. Biotechnology for Biofuels. 5: 45-45. https://doi.org/10.1186/1754-6834-5-45.
Ipsen JØ, Hallas-Møller M, Brander S, Lo Leggio L, Johansen KS. 2021. Lytic polysaccharide monooxygenases and other histidine-brace copper proteins: Structure, oxygen activation and biotechnological applications. Biochemical Society Transactions. 49(1): 531-540. https://doi.org/10.1042/BST20201031.
Jones P, Binns D, Chang HY, Fraser M, Li W, McAnulla C, McWilliam H, Maslen J, Mitchell A, Nuka G, Hunter S. 2014. InterProScan 5: Genome-scale protein function classification. Bioinformatics. 30(9): 1236-1240. https://doi.org/10.1093/bioinformatics/btu031.
Lombard V, Golaconda Ramulu H, Drula E, Coutinho PM, Henrissat B. 2014. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Research. 42(D1): D490-D495. https://doi.org/10.1093/nar/gkt1178.
Lynd LR, Weimer PJ, van Zyl WH, Pretorius IS. 2002. Microbial cellulose utilization: Fundamentals and biotechnology. Microbiology and Molecular Biology Reviews. 66(3): 506-577. https://doi.org/10.1128/MMBR.66.3.506-577.2002.
Naumoff DG. 2011. Hierarchical classification of glycoside hydrolases. Biochemistry (Moscow). 76(6): 622-635. https://doi.org/10.1134/S0006297911060022.
Papadopoulos JS, Agarwala R. 2007. COBALT: A constraint-based alignment tool for multiple protein sequences. Bioinformatics. 23(9): 1073-1079. https://doi.org/10.1093/bioinformatics/btm076.
Payne CM, Knott BC, Mayes HB, Hansson H, Himmel ME, Sandgren M, Beckham GT. 2015. Fungal cellulases. Chemical Reviews. 115(3): 1308-1448. https://doi.org/10.1021/cr500351c.
Resl P, Bujold AR, Tagirdzhanova G, Meidl P, Freire Rallo S, Kono M, Spribille T. 2022. Large differences in carbohydrate degradation and transport potential among lichen fungal symbionts. Nature Communications. 13: 2634-2634. https://doi.org/10.1038/s41467-022-30218-6.
Somerville C. 2006. Cellulose synthesis in higher plants. Annual Review of Cell and Developmental Biology. 22: 53-78. https://doi.org/10.1146/annurev.cellbio.22.022206.160206.
Tamura K, Stecher G, Kumar S. 2021. MEGA11: Molecular evolutionary genetics analysis version 11. Molecular Biology and Evolution. 38(7): 3022-3027. https://doi.org/10.1093/molbev/msab120.
Wang Y, Wu J, Yan J, Guo M, Xu L, Hou L, Zou Q. 2022. Comparative genome analysis of plant ascomycete fungal pathogens with different lifestyles reveals distinctive virulence strategies. BMC Genomics. 23(1): 34-34. https://doi.org/10.1186/s12864-021-08165-1. | ||
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