ABSTRACT
The ascomycete Truncatella angustata has a worldwide distribution. Commonly, it is associated with plants as an endophyte, pathogen, or saprotroph. The genome assembly comprises 44.9 Mbp, a G+C content of 49.2%, and 12,353 predicted genes, among them 12 unspecific peroxygenases (EC 1.11.2.1).
ANNOUNCEMENT
Truncatella angustata (Pers.) S. Hughes 1958 (1) belongs to the Sporocadaceae, a family of coelomycetous fungi with appendage-bearing conidia within the ascomycetous order Xylariales (2). It is common as an endophyte or pathogen of vascular plants in both temperate and tropical regions (3, 4). It infects stems (Vitis [5, 6], Vaccinium [7]), leaves (Rosa [8], Parthenocissus [3], Populus [9]), fruits (Malus [10], Olea [11]), and roots (Vitis [12]) and is also a candidate for biological control of plant diseases (9, 12). In addition to plants, this fungus was also isolated from marine sponges (13), humans (4), and as a pathogen from insects (14). T. angustata cultures showed several secondary metabolites with potential for application in biotechnology or medicine, e.g., α-pyrone-based analogs (15), phenazine-1-carboxylic acid with antifungal activity (6), ramulosin derivates with a broad range of biological activities (14, 16), and truncateols, isoprenylated cyclohexanols with antiviral activity (15, 17). In culture supernatants, isolate S358 showed activities of several oxidoreductases, including those of unspecific peroxygenase and laccase. Its genome will be useful for identifying biotechnologically relevant enzymes or biosynthetic clusters.
T. angustata isolate S358 (rRNA genes and internal transcribed spacer [ITS], GenBank accession number OL604502) was collected from a fruiting body of the basidiomycetous species Psathyrella conopilus, which was growing on soil mulched with Robinia pseudoacacia wood chips (Bernsdorf, Germany; 51°23′51.1″N, 14°01′42.2″E). The fungus was cultured at 24°C and 120 rpm for 3 days in a synthetic medium (18) inoculated with a conidiospore suspension. Mycelium was harvested by vacuum filtration, washed twice, and lyophilized. Genomic DNA was extracted using the FastDNA Spin kit for soil (MP Biomedicals, Germany) from 30 mg of the harvested material. Sequencing libraries were prepared using the NEBNext Ultra II DNA library prep kit (New England Biolabs, Frankfurt, Germany), and genome sequencing was performed using an Illumina NextSeq 500 instrument in 2 × 150-bp paired-end read mode. After quality and adapter filtering using BBDuk v38.84, a total of 26 million reads were used for de novo assembly using SPAdes v3.15.2 (19) with default parameters. The assembly consists of 853 contigs with a total length of 44.9 Mbp. The assembly was verified using QUAST v5.0.2 (20) and has an N50 value of 102,256 bp and a G+C content of 49.2%; the largest contig has a size of 376,640 bp. The completeness of the assembly was verified using BUSCO v5 (data set, ascomycota_odb10) and determined to be 93.8% (21). Gene prediction was performed using AUGUSTUS v3.4 (22) (predictor: Fusarium graminearum, both strands, only complete genes, without in-frame stop codons) and resulted in 12,353 protein-coding genes. The genes were annotated using OmicsBox v2.0.36 (23) (BioBam, Valencia, Spain) following a pipeline of blastp-fast search (E value, 1.0E-3; word size, 6), InterProScan (all member databases), and GO mapping (Goa v2021.11). Carbohydrate-active enzymes (CAZymes) were identified using dbCAN2 (HMMdb v10; E value, <1e-15; coverage, >0.35) (24). Altogether, 366 glycoside hydrolases, 65 carbohydrate esterases, 29 polysaccharide lyases, 102 glycosyltransferases, 183 enzymes with auxiliary activities, and 15 carbohydrate-binding modules (CBM) were identified (Table 1).
TABLE 1.
CAZyme classes, unspecific peroxygenases, and multicopper oxidases detected in the genome of Truncatella angustata S358
| Enzyme or domain group | No. of proteins | GenPept accession no. |
|---|---|---|
| Glycoside hydrolases | 366 | |
| Glycosyl transferases | 102 | |
| Polysaccharide lyases | 29 | |
| Carbohydrate esterases | 65 | |
| Enzymes with auxiliary activity | 183 | |
| Associated modules | ||
| Carbohydrate-binding modules | 15 | |
| Cellulose-binding domain CBM1 | 0 | |
| Enzymes of interest | ||
| Multicopper oxidase | 19 | KAH8193788, KAH8193910, KAH8196607, KAH8197187, KAH8197370, KAH8199586, KAH8199725, KAH8199806, KAH8200567, KAH8200848, KAH8201626, KAH8201963, KAH8202890, KAH8203692, KAH8204301, KAH8204821, KAH8204968, KAH8205436, KAH8205682 |
| Unspecific peroxygenase | 12 | KAH8195642, KAH8196030, KAH8197040, KAH8199887, KAH8200077, KAH8200361, KAH8201371, KAH8202439, KAH8203164, KAH8203310, KAH8203546, KAH8204654 |
Using the unspecific peroxygenase (UPO; EC 1.11.2.1) reference sequence from Cyclocybe (Agrocybe) aegerita (GenPept accession number CBJ94532), 12 putative UPO genes were detected in T. angustata. Further, 19 multicopper oxidases were identified, among them 12 laccases. Moreover, 82 secondary metabolite biosynthetic gene clusters (BGCs) were predicted using antiSMASH v6 (25) (using contigs; detection strictness, relaxed), among them 40 related to the synthesis of polyketides, 35 to nonribosomal peptides, and 11 to terpenes.
Data availability.
This whole-genome shotgun project has been deposited at DDBJ/ENA/GenBank under the accession number JAJJMK000000000. The version described in this paper is version JAJJMK010000000. The Sequence Read Archive (SRA) accession number is SRR16694223.
ACKNOWLEDGMENTS
We thank Marina Schramm for help with lab work and Andreas Dahl of the Deep Sequencing Facility of the TU Dresden for sequencing of the strain.
The work was financially and scientifically supported by the European Union’s Horizon 2020 research and innovation program under grant agreement number 792063 (SUSBIND), by the DFG Priority Program 1374, “Infrastructure-Biodiversity-Exploratories” (project numbers HO 1961/6-3 and KE 1742/2-3), and by the Bundesministerium für Bildung und Forschung (BMBF) (CEFOX 031B0831). We thank all the managers and initiators of these joint projects.
Contributor Information
Harald Kellner, Email: harald.kellner@tu-dresden.de.
Jason E. Stajich, University of California, Riverside
REFERENCES
- 1.Sutton BC. 1980. The Coelomycetes. Fungi imperfecti with pycnidia, acervuli and stromata. CMI, Kew, England. [Google Scholar]
- 2.Liu F, Bonthond G, Groenewald JZ, Cai L, Crous PW. 2019. Sporocadaceae, a family of coelomycetous fungi with appendagebearing conidia. Stud Mycol 92:287–415. doi: 10.1016/j.simyco.2018.11.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Andrianova TV. 2014. New data on Discosia, Robillarda and Truncatella species (Xylariales, Ascomycota) in Ukraine. Ukr Bot J 71:352–356. doi: 10.15407/ukrbotj71.03.352. [DOI] [Google Scholar]
- 4.Jagielski T, Żak I, Tyrak J, Bryk A. 2015. First probable case of subcutaneous infection due to Truncatella angustata: a new fungal pathogen of humans? J Clin Microbiol 53:1961–1964. doi: 10.1128/JCM.00400-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Úrbez-Torres JR, Adams P, Kamas J, Gubler WD. 2009. Identification, incidence, and pathogenicity of fungal species associated with grapevine dieback in Texas. Am J Enol Vitic 60:4. [Google Scholar]
- 6.Cimmino A, Bahmani Z, Castaldi S, Masi M, Isticato R, Abdollahzadeh J, Amini J, Evidente A. 2021. Phenazine-1-carboxylic acid (PCA), produced for the first time as an antifungal metabolite by Truncatella angustata, a causal agent of grapevine trunk diseases (GTDs) in Iran. J Agric Food Chem 69:12143–12147. doi: 10.1080/14786419.2021.1979544. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Espinoza JG, Briceño EX, Keith LM, Latorre BA. 2008. Canker and twig dieback of blueberry caused by Pestalotiopsis spp. and a Truncatella sp. in Chile. Plant Dis 92:1407–1414. doi: 10.1094/PDIS-92-10-1407. [DOI] [PubMed] [Google Scholar]
- 8.Eken C, Spanbayev A, Tulegenova Z, Abiev S. 2009. First report of Truncatella angustata causing leaf spot on Rosa canina in Kazakhstan. Australas Plant Dis Notes 4:44–45. doi: 10.1071/DN09018. [DOI] [Google Scholar]
- 9.Raghavendra AKH, Newcombe G. 2013. The contribution of foliar endophytes to quantitative resistance to Melampsora rust. New Phytol 197:909–918. doi: 10.1111/nph.12066. [DOI] [PubMed] [Google Scholar]
- 10.Wenneker M, Pham KTK, Boekhoudt LC, de Boer FA, van Leeuwen PJ, Hollinger TC, Thomma BPHJ. 2017. First report of Truncatella angustata causing postharvest rot on ‘Topaz’ apples in the Netherlands. Plant Dis 101:508–508. doi: 10.1094/PDIS-09-16-1374-PDN. [DOI] [Google Scholar]
- 11.Arzanlou M, Torbati M, Jafary H. 2012. Fruit rot of olive (Olea europaea) caused by Truncatella angustata. Plant Pathol Quar 2:117–123. doi: 10.5943/ppq/2/2/4. [DOI] [Google Scholar]
- 12.de Almeida AB, Concas J, Campos MD, Materatski P, Varanda C, Patanita M, Murolo S, Romanazzi G, do Rosario Félix M. 2020. Endophytic fungi as potential biological control agents against grapevine trunk diseases in Alentejo Region. Biology (Basel) 9:420. doi: 10.3390/biology9120420. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Zhao Y, Liu D, Proksch P, Yu S, Lin W. 2017. Angupyrones A–E, α-pyrone analogues with ARE-activation from a sponge-associated fungus Truncatella angustata. Chem Biodivers 14:e1700236. doi: 10.1002/cbdv.201700236. [DOI] [PubMed] [Google Scholar]
- 14.Chen S, Zhang Z, Li L, Liu X, Ren F. 2015. Two new ramulosin derivatives from the entomogenous fungus Truncatella angustata. Nat Prod Commun 10:341–344. [PubMed] [Google Scholar]
- 15.Zhao Y, Liu D, Proksch P, Zhou D, Lin W. 2018. Truncateols O–V, further isoprenylated cyclohexanols from the sponge-associated fungus Truncatella angustata with antiviral activities. Phytochemistry 155:61–68. doi: 10.1016/j.phytochem.2018.07.017. [DOI] [PubMed] [Google Scholar]
- 16.Cimmino A, Bahmani Z, Masi M, Abdollahzadeh J, Amini J, Tuzi A, Evidente A. 20 October 2021. Phytotoxins produced by Didymella glomerata and Truncatella angustata, associated with grapevine trunk diseases (GTDs) in Iran. Nat Prod Res doi: 10.1080/14786419.2021.1979544. [DOI] [PubMed] [Google Scholar]
- 17.Takahashi JA, Barbosa BVR, Lima MTNS, Cardoso PG, Contigli C, Pimenta LPS. 2021. Antiviral fungal metabolites and some insights into their contribution to the current COVID-19 pandemic. Bioorg Med Chem 46:116366. doi: 10.1016/j.bmc.2021.116366. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Keen NT. 1975. Specific elicitors of plant phytoalexin production: determinants of race specificity in pathogens? Science 187:74–75. doi: 10.1126/science.187.4171.74. [DOI] [PubMed] [Google Scholar]
- 19.Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA. 2012. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455–477. doi: 10.1089/cmb.2012.0021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Gurevich A, Saveliev V, Vyahhi N, Tesler G. 2013. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29:1072–1075. doi: 10.1093/bioinformatics/btt086. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Seppey M, Manni M, Zdobnov EM. 2019. BUSCO: assessing genome assembly and annotation completeness. Methods Mol Biol 1962:227–245. doi: 10.1007/978-1-4939-9173-0_14. [DOI] [PubMed] [Google Scholar]
- 22.Hoff KJ, Stanke M. 2019. Predicting genes in single genomes with AUGUSTUS. Curr Protoc Bioinformatics 65:e57. doi: 10.1002/cpbi.57. [DOI] [PubMed] [Google Scholar]
- 23.Götz S, García-Gómez JM, Terol J, Williams TD, Nagaraj SH, Nueda MJ, Robles M, Talón M, Dopazo J, Conesa A. 2008. High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res 36:3420–3435. doi: 10.1093/nar/gkn176. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Zhang H, Yohe T, Huang L, Entwistle S, Wu P, Yang Z, Busk PK, Xu Y, Yin Y. 2018. dbCAN2: a meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res 46:W95–W101. doi: 10.1093/nar/gky418. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Blin K, Shaw S, Kloosterman AM, Charlop-Powers Z, van Wezel GP, Medema MH, Weber T. 2021. antiSMASH 6.0: improving cluster detection and comparison capabilities. Nucleic Acids Res 49:W29–W35. doi: 10.1093/nar/gkab335. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
This whole-genome shotgun project has been deposited at DDBJ/ENA/GenBank under the accession number JAJJMK000000000. The version described in this paper is version JAJJMK010000000. The Sequence Read Archive (SRA) accession number is SRR16694223.