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Comparative Genomics Uncovers the Genetic Diversity and Synthetic Biology of Secondary Metabolite Production of Trametes

  • Zhang, Yan (School of Life Sciences, Hefei Normal University) ;
  • Wang, Jingjing (School of Life Sciences, Hefei Normal University) ;
  • Yajun, Chen (School of Life Sciences, Hefei Normal University) ;
  • Zhou, Minghui (School of Life Sciences, Hefei Normal University) ;
  • Wang, Wei (School of Life Sciences, Hefei Normal University) ;
  • Geng, Ming (School of Life Sciences, Hefei Normal University) ;
  • Xu, Decong (School of Life Sciences, Hefei Normal University) ;
  • Xu, Zhongdong (School of Life Sciences, Hefei Normal University)
  • Received : 2019.10.05
  • Accepted : 2020.01.22
  • Published : 2020.04.30

Abstract

The carbohydrate-active enzyme (CAZyme) genes of Trametes contribute to polysaccharide degradation. However, the comprehensive analysis of the composition of CAZymes and the biosynthetic gene clusters (BGCs) of Trametes remain unclear. Here, we conducted comparative analysis, detected the CAZyme genes, and predicted the BGCs for nine Trametes strains. Among the 82,053 homologous clusters obtained for Trametes, we identified 8518 core genes, 60,441 accessory genes, and 13,094 specific genes. A large proportion of CAZyme genes were cataloged into glycoside hydrolases, glycosyltransferases, and carbohydrate esterases. The predicted BGCs of Trametes were divided into six strategies, and the nine Trametes strains harbored 47.78 BGCs on average. Our study revealed that Trametes exhibits an open pan-genome structure. These findings provide insights into the genetic diversity and explored the synthetic biology of secondary metabolite production for Trametes.

Keywords

References

  1. Cho KS, Ryu HW. Biodecolorization and biodegradation of dye by fungi: a review. KSBB J. 2015;30:203-222. https://doi.org/10.7841/ksbbj.2015.30.5.203
  2. Ryu H, Ryu HW, Cho KS. Characterization of dye decolorization in cell-free culture broth of Trametes versicolor CBR43. J Microbiol Biotechnol. 2017;27:155-160. https://doi.org/10.4014/jmb.1608.08008
  3. Justo A, Miettinen O, Floudas D, et al. A revised family-level classification of the Polyporales (Basidiomycota). Fungal Biol. 2017;121:798-824. https://doi.org/10.1016/j.funbio.2017.05.010
  4. Ferreira DSS, Kato RB, Miranda FM, et al. Draft genome sequence of Trametes villosa (Sw.) Kreisel CCMB561, a tropical white-rot Basidiomycota from the semiarid region of Brazil. Data Brief. 2018;18:1581-1587. https://doi.org/10.1016/j.dib.2018.04.074
  5. Knezevic A, Stajic M, Sofrenic I, et al. Antioxidative, antifungal, cytotoxic and antineurodegenerative activity of selected Trametes species from Serbia. PLoS One. 2018;13:e0203064. https://doi.org/10.1371/journal.pone.0203064
  6. Yang XQ, Zhao XX, Liu CY, et al. Decolorization of azo, triphenylmethane and anthraquinone dyes by a newly isolated Trametes sp. SQ01 and its laccase. Process Biochem. 2009;44:1185-1189. https://doi.org/10.1016/j.procbio.2009.06.015
  7. Levin L, Herrmann C, Papinutti VL. Optimization of lignocellulolytic enzyme production by the white-rot fungus Trametes trogii in solid-state fermentation using response surface methodology. Biochem Eng J. 2008;39:207-214. https://doi.org/10.1016/j.bej.2007.09.004
  8. Neves M, Baseia I, Drechsler-Santos E, et al. Guide to the common fungi of the semiarid region of Brazil. Florianopolis: TECC Editora; 2013.
  9. Milton RD, Giroud F, Thumser AE, et al. Hydrogen peroxide produced by glucose oxidase affects the performance of laccase cathodes in glucose/oxygen fuel cells: FAD-dependent glucose dehydrogenase as a replacement. Phys Chem Chem Phys. 2013;15:19371-19379. https://doi.org/10.1039/c3cp53351d
  10. Salaj-Kosla U, P€oller S, Schuhmann W, et al. Direct electron transfer of Trametes hirsuta laccase adsorbed at unmodified nanoporous gold electrodes. Bioelectrochemistry. 2013;91:15-20. https://doi.org/10.1016/j.bioelechem.2012.11.001
  11. Davies GJ, Williams SJ. Carbohydrate-active enzymes: sequences, shapes, contortions and cells. Biochem Soc Trans. 2016;44:79-87. https://doi.org/10.1042/BST20150186
  12. Sista Kameshwar AK, Qin W. Comparative study of genome-wide plant biomass-degrading CAZymes in white rot, brown rot and soft rot fungi. Mycology. 2018;9:93-105. https://doi.org/10.1080/21501203.2017.1419296
  13. Zhao Z, Liu H, Wang C, et al. Comparative analysis of fungal genomes reveals different plant cell wall degrading capacity in fungi. BMC Genomics. 2013;14:274. https://doi.org/10.1186/1471-2164-14-274
  14. Dai W, Chen X, Wang X, et al. The Algicidal Fungus Trametes versicolor F21a eliminating blue algae via genes encoding degradation enzymes and metabolic pathways revealed by transcriptomic analysis. Front Microbiol. 2018;9:826. https://doi.org/10.3389/fmicb.2018.00826
  15. Newman DJ, Cragg GM. Natural products as sources of new drugs over the 30 years from 1981 to 2010. J Nat Prod. 2012;75:311-335. https://doi.org/10.1021/np200906s
  16. Blin K, Wolf T, Chevrette MG, et al. antiSMASH 4.0-improvements in chemistry prediction and gene cluster boundary identification. Nucleic Acids Res. 2017;45:W36-W41. https://doi.org/10.1093/nar/gkx319
  17. Pusztahelyi T, Holb IJ, Pocsi I. Secondary metabolites in fungus-plant interactions. Front Plant Sci. 2015;6:573. https://doi.org/10.3389/fpls.2015.00573
  18. Keller NP. Fungal secondary metabolism: regulation, function and drug discovery. Nat Rev Microbiol. 2018; 17(3):167-180. https://doi.org/10.1038/s41579-018-0121-1
  19. Collemare J, Billard A, B€ohnert HU, et al. Biosynthesis of secondary metabolites in the rice blast fungus Magnaporthe grisea: the role of hybrid PKS-NRPS in pathogenicity. Mycol Res. 2008;112:207-215. https://doi.org/10.1016/j.mycres.2007.08.003
  20. Cimermancic P, Medema MH, Claesen J, et al. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell. 2014;158:412-421. https://doi.org/10.1016/j.cell.2014.06.034
  21. Clevenger KD, Bok JW, Ye R, et al. A scalable platform to identify fungal secondary metabolites and their gene clusters. Nat Chem Biol. 2017;13:895-901. https://doi.org/10.1038/nchembio.2408
  22. Nielsen JC, Grijseels S, Prigent S, et al. Global analysis of biosynthetic gene clusters reveals vast potential of secondary metabolite production in Penicillium species. Nat Microbiol. 2017;2:17044. https://doi.org/10.1038/nmicrobiol.2017.44
  23. Hyatt D, Chen GL, Locascio PF, et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11:119. https://doi.org/10.1186/1471-2105-11-119
  24. Aherfi S, Andreani J, Baptiste E, et al. A large open pangenome and a small core genome for giant pandoraviruses. Front Microbiol. 2018;9:1486. https://doi.org/10.3389/fmicb.2018.01486
  25. Li L, Stoeckert CJ Jr, Roos DS. OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res. 2003;13:2178-2189. https://doi.org/10.1101/gr.1224503
  26. Schoch CL, Seifert KA, Huhndorf S, et al.; Fungal Barcoding Consortium. Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi. Proc Natl Acad Sci USA. 2012;109:6241-6246. https://doi.org/10.1073/pnas.1117018109
  27. Blaalid R, Kumar S, Nilsson RH, et al. ITS1 versus ITS2 as DNA metabarcodes for fungi. Mol Ecol Resour. 2013;13:218-224. https://doi.org/10.1111/1755-0998.12065
  28. Bengtsson-Palme J, Ryberg M, Hartmann M, et al. Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data. Methods Ecol Evol. 2013;4:914-919.
  29. Lesage-Meessen L, Haon M, Uzan E, et al. Phylogeographic relationships in the polypore fungus Pycnoporus inferred from molecular data. FEMS Microbiol Lett. 2011;325:37-48. https://doi.org/10.1111/j.1574-6968.2011.02412.x
  30. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32:1792-1797. https://doi.org/10.1093/nar/gkh340
  31. Talavera G, Castresana J. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst Biol. 2007;56:564-577. https://doi.org/10.1080/10635150701472164
  32. Retief JD. Phylogenetic analysis using PHYLIP. Methods Mol Biol. 1999;132:243-258.
  33. Tamura K, Peterson D, Peterson N, et al. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011;28:2731-2739. https://doi.org/10.1093/molbev/msr121
  34. Tatusov RL, Fedorova ND, Jackson JD, et al. The COG database: an updated version includes eukaryotes. BMC Bioinformatics. 2003;4:41. https://doi.org/10.1186/1471-2105-4-41
  35. Huerta-Cepas J, Szklarczyk D, Forslund K, et al. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res. 2016;44:D286-D293. https://doi.org/10.1093/nar/gkv1248
  36. Lombard V, Golaconda Ramulu H, Drula E, et al. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 2014;42:D490-D495. https://doi.org/10.1093/nar/gkt1178
  37. Cantarel BL, Coutinho PM, Rancurel C, et al. The Carbohydrate-Active EnZymes database (CAZy): an expert resource for glycogenomics. Nucleic Acids Res. 2009;37:D233-D238. https://doi.org/10.1093/nar/gkn663
  38. M€akel€a M, DiFalco M, McDonnell E, et al. Genomic and exoproteomic diversity in plant biomass degradation approaches among Aspergilli. Stud Mycol. 2018;91:79-99. https://doi.org/10.1016/j.simyco.2018.09.001
  39. Lomascolo A, Cayol JL, Roche M, et al. Molecular clustering of Pycnoporus strains from various geographic origins and isolation of monokaryotic strains for laccase hyperproduction. Mycol Res. 2002;106:1193-1203. https://doi.org/10.1017/S0953756202006494
  40. Levasseur A, Lomascolo A, Chabrol O, et al. The genome of the white-rot fungus Pycnoporus cinnabarinus: a basidiomycete model with a versatile arsenal for lignocellulosic biomass breakdown. BMC Genomics. 2014;15:486. https://doi.org/10.1186/1471-2164-15-486
  41. Busk PK, Lange M, Pilgaard B, et al. Several genes encoding enzymes with the same activity are necessary for aerobic fungal degradation of cellulose in nature. PLoS One. 2014;9:e114138. https://doi.org/10.1371/journal.pone.0114138
  42. Couturier M, Navarro D, Chevret D, et al. Enhanced degradation of softwood versus hardwood by the white-rot fungus Pycnoporus coccineus. Biotechnol Biofuels. 2015;8:216. https://doi.org/10.1186/s13068-015-0407-8
  43. Pavlov AR, Tyazhelova TV, Moiseenko KV, et al. Draft genome sequence of the fungus Trametes hirsuta 072. Genome Announc. 2015;3:e01287-01215.
  44. Cerron LM, Romero-Suarez D, Vera N, et al. Decolorization of textile reactive dyes and effluents by biofilms of Trametes polyzona LMB-TM5 and Ceriporia sp. LMB-TM1 isolated from the Peruvian Rainforest. Water Air Soil Pollut. 2015;226:235. https://doi.org/10.1007/s11270-015-2505-4
  45. Granchi Z, Peng M, Chi-A-Woeng T, et al. Genome sequence of the basidiomycete white-rot fungus Trametes pubescens FBCC735. Genome Announc. 2017;5:e0164301616.
  46. Wang J, Zhang Y, Xu Y, et al. Genome sequence of a laccase producing fungus Trametes sp. AH28-2. J Biotechnol. 2015;216:167-168. https://doi.org/10.1016/j.jbiotec.2015.11.001
  47. Floudas D, Binder M, Riley R, et al. The Paleozoic origin of enzymatic mechanisms for decay of lignin reconstructed using 31 fungal genomes. Science. 2012;336:1715-1719. https://doi.org/10.1126/science.1221748
  48. de Oliveira Carneiro RT, Lopes MA, Silva MLC, et al. Trametes villosa lignin peroxidase (TvLiP): genetic and molecular characterization. J Microbiol Biotechnol. 2017;27:179-188. https://doi.org/10.4014/jmb.1606.06055
  49. Rytioja J, Hilden K, Yuzon J, et al. Plant-polysaccharide-degrading enzymes from basidiomycetes. Microbiol Mol Biol Rev. 2014;78:614-649. https://doi.org/10.1128/MMBR.00035-14
  50. Berrin JG, Navarro D, Couturier M, et al. Exploring the natural fungal biodiversity of tropical and temperate forests toward improvement of biomass conversion. Appl Environ Microbiol. 2012;78:6483-6490. https://doi.org/10.1128/AEM.01651-12
  51. Yin Y, Mao X, Yang J, et al. dbCAN: a web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 2012;40:W445-W451. https://doi.org/10.1093/nar/gks479
  52. Murphy C, Powlowski J, Wu M, et al. Curation of characterized glycoside hydrolases of fungal origin. Database (Oxford). 2011;2011:bar020. https://doi.org/10.1093/database/bar020
  53. Viborg AH, Terrapon N, Lombard V, et al. A subfamily roadmap of the evolutionarily diverse glycoside hydrolase family 16 (GH16). J Biol Chem. 2019;294:15973-15986. https://doi.org/10.1074/jbc.RA119.010619