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Draft genome sequence of Trichoderma asperellum MLT1J1, isolated from coconut husk in Maluku, Indonesia
Korean J. Microbiol. 2022;58(3):208-210
Published online September 30, 2022
© 2022 The Microbiological Society of Korea.

Ika Octariyani Safitri1, Dian Anggraini Suroto1, Sardjono Sardjono1, Muhammad Nur Cahyanto1, and Jaka Widada2*

1Department of Food and Agricultural Product Technology, Faculty of Agricultural Technology, Gadjah Mada University, Jl. Flora, Bulaksumur, Yogyakarta 55281, Indonesia
2Department of Agricultural Microbiology, Faculty of Agriculture, Gadjah Mada University, Jl. Flora, Bulaksumur, Yogyakarta 55281, Indonesia
Correspondence to: *E-mail: jwidada@ugm.ac.id; Tel.: +62-818-265-654; Fax: +62-274-563-062
Received June 13, 2022; Revised September 3, 2022; Accepted September 13, 2022.
Abstract
A whole genome sequence was performed on Trichoderma asperellum MLT1J1 isolated from coconut husk in Maluku, Indonesia. This strain is a white fungus that has glucose- resistant properties in the production of alpha-amylase and glucoamylase. In this study, the genome sequence of Trichoderma asperellum MLT1J1 was sequenced using Illumina NovaSeq PE150. The genome assembly has a length of 48.66 Mb with a GC content of 52.32%, 471 scaffolds and 14,103 protein-coding genes. Based on additional analyses, the number of genes encoding carbohydrate-active enzymes and secondary metabolites gene clusters were revealed. The result of this study will provide useful genomic information that can be compared with other Trichoderma species.
Keywords : Trichoderma asperellum, genome sequence, glucose resistant
Body

Trichoderma is a thread fungi taxon commonly found in natural habitats (Li et al., 2017). Trichoderma is also widely reported to play an essential role in producing enzymes, especially cellulases. In this study, Trichoderma asperellum MLT1J1 was isolated from coconut husk in Maluku, Indonesia. The T. asperellum MLT1J1 has glucose-resistant properties in the production of alpha-amylase and glucoamylase (Safitri et al., 2022). This condition is closely related to carbon catabolite repression, which is generally owned by fungi and inhibits enzyme production.

The genomic DNA of Trichoderma asperellum MLT1J1 was extracted using the SDS method (Lim et al., 2016). Beijing Novogene Bioinformatics Technology Co., Ltd performed the whole genome sequencing. The library for sequencing was generated using NEBNext UltraTM DNA preparation kit according to the manufacturer’s instructions and sequenced on Illumina NovaSeq PE150 with coverage of 100x. The assembly was first performed using SOAPdenovo (version 2.04) (Luo et al., 2012), SPAdes (Bankevich et al., 2012), AbySS assembling software, and finally using CISA (Lin and Liao, 2013) software for integration. The genome size of Trichoderma asperellum MLT1J1 is 48.66 Mb with a total length of 18,073,466 bp with a gene length/genome value of 37.09%. The genome contains 471 scaffolds with a maximum scaffold size of 3,214,281 bp with an N50 value of 996,985 and N90 value of 84,280 and a GC content of 52.32% (Table 1). Among the 14 species of Trichoderma reported, this species has the largest genome size (Table 2).

Draft genome features of <italic>Trichoderma asperellum</italic> MLT1J1
Genome properties Value
Genome size (bp) 48,664,938
Total length (bp) 18,073,466
GC content (%) 52.32
Scaffolds 471
CDS 14,103
COG-categorized CDS 2,636
N50 996,985
N90 84,280
tRNA 346
rRNA 54


Comparative genomics of the most common <italic>Trichoderma</italic> species (<span class="xref"><a href="#B10">Kubicek <italic>et al</italic>., 2019</a></span>)
No. Species Strain Genome size (Mb) Gene number
1 Trichoderma reseei QM6a 32.7 9,877
2 RUT C30 34.2 10,877
3 Trichoderma longibrachiatum ATCC18648 31.74 10,938
4 Trichoderma citrinoviride TUCIM 6016 33.2 9,737
5 Trichoderma parareesei CBS125925 32.07 9,292
6 Trichoderma harzianum CBS 226.95 40.9 14,095
7 TR257 39.4 13,932
8 Trichoderma afoharzianum T6776 39.7 11,297
9 Trichoderma guizhouense NJAU4742 38.8 11,297
10 Trichoderma virens Gv29-8 40.52 12,427
11 Trichoderma atroviride IMI 206040 36.4 11,863
12 Trichoderma gamsii T6085 37.9 10,709
13 Trichoderma asperellum CBS433.97 37.66 12,586
14 Trichoderma hamatum GD12 38.43 10,520


The genome prediction was performed by using GeneMarks (Besemer et al., 2001). 22.4% of repetitive sequences were masked by RepeatMasker (Saha et al., 2008) and TRF (Tandem Repeats Finder) (Benson, 1999). Transfer RNA (tRNA) genes were predicted by the tRNAscan-SE (Lowe and Eddy, 1997). Ribosome RNA (rRNA) genes were analyzed by the rRNAmmer (Lagesen et al., 2007). Small nuclear RNAs (snRNA) were predicted by BLAST against the Rfam (Gardner et al., 2009). A total of 14,103 gene numbers were used for making 51,459 valid annotations by carrying out sequence similarity searches against the GO (Ashburner et al., 2000), KEGG (Kanehisa et al., 2004), COG (Galperin et al., 2015), Swissprot (Bairoch and Apweiler, 2000), and CAZyme databases (Cantarel et al., 2008).

The CaZy analysis showed that this strain has 395 enzymes involved in CAZymes (229 glycoside hydrolases, 128 glycosyl transferase, 23 carbohydrate bindings modules, 9 carbohydrate esterase, and 5 polysaccharide lyases). This strain produced the gene of alpha-amylase (shared 81.9% identity with Trichoderma asperellum CBS 433.97) and glucoamylase (shared 84.8% identity with Trichoderma atroviride IMI 206040). 11 secondary metabolites gene clusters (with 30 biosynthetic enzymes and 17 smCOGs) were found by using antiSMASH (Medema et al., 2011) consisting of NRPS-Like, T1PKS, terpene, beta lactone, ectoine, NRPS, NAPAA, lasso peptide, resorcinol, aryl polyene, phosphonate, and RiPP-like.

Nucleotide sequence accession number

The draft sequence of Trichoderma asperellum MLT1J1 (FNCC 6189) has been deposited at GenBank under the accession JAGJIL000000000 (BioProject; PRJNA699103). The version described in this paper is version JAGJIL000000000.

Acknowledgments

We are grateful to Purwito. Biotechnology Laboratory Staff. Faculty of Agricultural Technology. Gadjah Mada University for generously provides the fungal strain. This research was funded by a PMDSU scholarship from The Ministry of Research and Higher Education of the Republic of Indonesia with grant number 3191/UN1.DITLIT/DIT-LIT/PT/2020.

Conflict of Interest

The authors have no conflict of interest to report.

References
  1. Ashburner M, Ball CA, Blake JA, Botstein D, Butler J, Cherry M, Davis AP, Dolinski K, Dwight SS, and Eppig JTEppig JT, et al. 2000. Gene Ontology: tool for the unification of biology. Nat. Genet. 25, 25-29.
    Pubmed KoreaMed CrossRef
  2. Bairoch A and Apweiler R. 2000. The SWISS-PROT protein sequence database and its supplement TrEMBL in. Nucleic Acids Res. 28, 45-48.
    Pubmed KoreaMed CrossRef
  3. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, and Prjibelski ADPrjibelski AD, et al. 2012. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455-477.
    Pubmed KoreaMed CrossRef
  4. Benson G. 1999. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res. 27, 573-580.
    Pubmed KoreaMed CrossRef
  5. Besemer J, Lomsadze A, and Borodovsky M. 2001. GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions. Nucleic Acids Res. 29, 2607-2618.
    Pubmed KoreaMed CrossRef
  6. Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, and Henrissat B. 2008. The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics. Nucleic Acids Res. 37, D233-D238.
    Pubmed KoreaMed CrossRef
  7. Galperin MY, Makarova KS, Wolf YI, and Koonin EV. 2015. Expanded microbial genome coverage and improved protein family annotation in the COG database. Nucleic Acids Res. 43, 261-269.
    Pubmed KoreaMed CrossRef
  8. Gardner PP, Daub J, Tate JG, Nawrocki EP, Kolbe DL, Lindgreen S, Wilkinson AC, Finn RD, Jones SG, and Eddy SREddy SR, et al. 2009. Rfam: updates to the RNA families database. Nucleic Acids Res. 37, D136-D140.
    Pubmed KoreaMed CrossRef
  9. Kanehisa M, Goto S, Kawashima S, Okuno Y, and Hattori M. 2004. The KEGG resource for deciphering the genome. Nucleic Acids Res. 32, D277-D280.
    Pubmed KoreaMed CrossRef
  10. Kubicek CP, Steindorff AS, Chenthamara K, Manganiello G, Henrissat B, Zhang J, Cai F, Kopchinskiy AG, Kubicek EM, and Kuo AKuo A, et al. 2019. Evolution and comparative genomics of the most common Trichoderma species. BMC Genomics. 20, 485.
    Pubmed KoreaMed CrossRef
  11. Lagesen K, Hallin P, Rødland EA, Staerfeldt H, Rognes T, and Ussery DW. 2007. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res. 35, 3100-3108.
    Pubmed KoreaMed CrossRef
  12. Li WC, Huang CH, Chen CL, Chuang YC, Tung SY, and Wang TF. 2017. Trichoderma reesei complete genome sequence. repeat-induced point mutation. and partitioning of CAZyme gene clusters. Biotechnol. Biofuels 10, 170.
    Pubmed KoreaMed CrossRef
  13. Lim HJ, Lee EH, Yoon Y, Chua B, and Son A. 2016. Portable lysis apparatus for rapid single-step DNA extraction of Bacillus subtilis. J. Appl. Microbiol. 120, 379-387.
    Pubmed CrossRef
  14. Lin SH and Liao YC. 2013. CISA: contig integrator for sequence assembly of bacterial genomes. PLoS ONE 8, e60843.
    Pubmed KoreaMed CrossRef
  15. Lowe TM and Eddy SR. 1997. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 25, 955-964.
    Pubmed KoreaMed CrossRef
  16. Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, He G, Chen Y, Pan Q, and Liu YLiu Y, et al. 2012. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. GigaScience 4, 18.
    Pubmed KoreaMed CrossRef
  17. Medema HM, Blin K, Cimermancic P, de Jager V, Zakrzewski P, Fischbach MA, Weber T, Takano E, and Breiting R. 2011. antiSMASH: rapid identification. annotation. and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences. Nucleic Acids Res. 39, W339-W346.
    Pubmed KoreaMed CrossRef
  18. Safitri IO, Suroto DA, Widada J, Sardjono S, and Cahyanto MN. 2022. Effects of glucose as carbon catabolite repressor on alpha-amylase and glucoamylase production in Indonesian indigenous fungi. Malays. J. Microbiol. 18, 322-330.
    CrossRef
  19. Saha S, Bridges S, Magbanua ZV, and Peterson DG. 2008. Empirical comparison of ab initio repeat finding programs. Nucleic Acids Res. 36, 2284-2294.
    Pubmed KoreaMed CrossRef


September 2022, 58 (3)
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