Saproxylic fungi of fine woody debris studied by metabarcoding-based MycoPins method in Oulanka, Finland, 2022-2023

Study Extent

Sampling

Quality Control

Method steps

1. MycoPin placement Three 10 m wires (transects) were prepared with pin sets (MycoPins) attached to each one of them at every meter. Each MycoPin set consisted of 6 pins (a sextet): a pair of pine pins (softwood), a pair of birch pins (hardwood), and a pair of spruce pins (softwood). Each sextet was labeled with a sample number (six numbers and a letter: A and B for pine, C and D for birch, E and F for spruce). Each transect was attached to a tree and then placed on the top soil with the pin sets buried under the top leaf and soil matter. One transect was placed at three different sampling sites: (A) An area of a boreal forest unprotected from reindeers. (B) An area of a boreal forest located next to A, but protected from grazing by reindeers. (C) An area of a mixed broadleaf forest, accessed by random visitors.
2. Extraction and storage. One MycoPin sextet from each transect was located using the wire transect as a guide and collected every two weeks with exceptions for weather conditions. The collected sextets were dried in separate waxed paper bags for 2-3 hours at 45°C and stored dry at room temperature.
3. DNA isolation. The core of each pin from each sexted was drilled using a 2 mm fire-sterilized drill bit. The resultant sawdust was collected in a sterile centrifuge tube. The sawdust was then used to isolate genomic DNA using PowerSoil DNA Isolation kit from Qiagen (USA) according to the manufacturer instructions. Homogenization was performed using BeadBug homogenizers (BenchMark Scientific). DNA concentration was measured using NanoDrop (ThermoFisher). Genomic DNA was stored at −80°C.
4. PCR. Tagged primers for the ITS2 fungal region were used to perform PCR according to Clemmensen (2016). Forward and reverse primers were ITS7 andITS4, . Using this F/R primer sequence, a set of 40 tagged primer pairs was generated to individualize each PCR procedure. 10-nucleotide long unique tags were added to primers during oligonucleotide synthesis. Each DNA extracted from each MycoPin was subjected to PCR with a uniquely tagged primer pair. The amplification was verified via agarose gel electrophoresis. The amplified DNA was purified and stored at −20°C. E.Z.N.A® Cycle Pure Kit (Omega Bio-tek) was used for the amplicons purification. Positive control was used to verify the PCR and subsequent NGS in a form of mock fungal community made of 12 plasmids (Palmer, 2018), negative control (water) was used to exclude false-positive results. Tagging of PCR fragments allowed for mixing them into a single multiplex for a subsequent Next Generation Sequencing; the resultant sequence file can be sorted into clusters by tags, allowing to segregate individual amplicons.
5. Next-Generation Sequencing. The amplified tagged DNA samples were combined at equal amounts of 100 ng to create a multiplex for next-generation sequencing. The multiplex was sequenced using AmpliconEZ service at Genewiz (Azenta Life Sciences, New Jersey, USA).
6. Bioinformatics.

   Two paired FASTQ files for each multiplex were analyzed using SCATA (https://scata.mykopat.slu.se/), a bioinformatic tool designed for analyzing sequenced tagged amplicons. The FASTQ files were uploaded and verified as SCATA datasets. Low quality sequences were excluded, similar sequences were clustered, and abundance data for each cluster was calculated.

   The sequence quality was based on several criteria using SCATA default parameters, they include (1) a 90% primer match on tag identification, (2) a minimum sequence length of 200, (3) a minimum base quality of 10, and (4) a minimum mean base quality of 20. The FASTQ files were overlapped and merged. Kmer size for overlap search was set to 7. The minimum number of adjacent kmers to form high-scoring segment pairs during overlap search was set to 5. The minimum number of shared kmers to merge a read pair was set to 10.

   SCATA uses the USEARCH algorithm for clustering. Using the SCATA clustering criteria defaults, the clustering distance was set to 0.015, the minimum proportion of the longest sequence in a sequence pair to consider for clustering was set to 0.85, the penalty for mismatch was set to 1, and no penalty was set on an introduction of an open gap. However, a penalty of 1 is incurred for each succeeding gap. No weights were used for end gaps. Homopolymers longer than 3 before clustering were collapsed. No downsampling and no removal of low frequency genotypes were performed during clustering. Up to 3 representative sequences were reported for each cluster. Singletons, double clusters and clusters present in positive and negative controls were excluded.

   Each set of representative sequences is matched to a species found in the UNITE v. 9.0 (2023-07-18) fungi database. For each of the clusters without a match, a BLASTn search against the NCBI database was performed. The search result with the lowest e-value and the highest percent identity was considered the best match species for the cluster. The BLASTn match results with a score less than 200 were excluded. If there are multiple best matches, the first match in the best match list is selected.

   The abundance data (DNA sequence reads) of the same species were amalgamated.

   Each species identification was aligned with the taxonomy of GBIF Backbone using statistical software R and rgbif package v. 3.7.9. Non-fungal species were rejected. Fungal species not identified on the phylum-level, at the minimum, were also discarded. Fungal traits were assigned according to FungalTraits database (from an Excel sheet, supplementary data of Põlme, 2020). Historical weather data for each transect were gathered from Weatherstack (www.weatherstack.com).

   Note:The abundance data is used as the Organism Quantity in the GBIF occurrence dataset with “DNA sequence reads” as the Organism Quantity Type. The value is used to pertain to the abundance of a species relative to other species present for a particular event (date-transect-substrate).

1. Leucosporidiales
   rank: order
2. Phaeomoniellales
   rank: order
3. Agaricostilbales
   rank: order
4. Filobasidiales
   rank: order
5. Trichosphaeriales
   rank: order
6. Wallemiales
   rank: order
7. Auriculariales
   rank: order
8. Sordariales
   rank: order
9. Pucciniales
   rank: order
10. Wallemiomycetes
    rank: class
11. Tremellomycetes
    rank: class
12. Orbiliales
    rank: order
13. Fungi
    rank: kingdom
14. Mucoromycota
    rank: phylum
15. Malasseziales
    rank: order
16. Tremellodendropsidales
    rank: order
17. Microascales
    rank: order
18. Mortierellomycetes
    rank: class
19. Cystofilobasidiales
    rank: order
20. Trichosporonales
    rank: order
21. Sebacinales
    rank: order
22. Microbotryales
    rank: order
23. Microbotryomycetes
    rank: class
24. Erythrobasidiales
    rank: order
25. Corticiales
    rank: order
26. Mortierellales
    rank: order
27. Rhytismatales
    rank: order
28. Helotiales
    rank: order
29. Mucorales
    rank: order
30. Malasseziomycetes
    rank: class
31. Agaricales
    rank: order
32. Sistotremastrales
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33. Endogonales
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34. Atheliales
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35. Trechisporales
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36. Dothideomycetes
    rank: class
37. Pleosporales
    rank: order
38. Umbelopsidales
    rank: order
39. Eurotiomycetes
    rank: class
40. Pezizales
    rank: order
41. Phallales
    rank: order
42. Kriegeriales
    rank: order
43. Lecanoromycetes
    rank: class
44. Polyporales
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45. Umbelopsidomycetes
    rank: class
46. Sporidiobolales
    rank: order
47. Eurotiales
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48. Capnodiales
    rank: order
49. Sordariomycetes
    rank: class
50. Saccharomycetes
    rank: class
51. Ascomycota
    rank: phylum
52. Ophiostomatales
    rank: order
53. Hymenochaetales
    rank: order
54. Xylariales
    rank: order
55. Lecanorales
    rank: order
56. Russulales
    rank: order
57. Mucoromycetes
    rank: class
58. Hypocreales
    rank: order
59. Pucciniomycetes
    rank: class
60. Botryosphaeriales
    rank: order
61. Chaetothyriales
    rank: order
62. Tremellales
    rank: order
63. Venturiales
    rank: order
64. Archaeorhizomycetes
    rank: class
65. Agaricomycetes
    rank: class
66. Cystobasidiomycetes
    rank: class
67. Thelebolales
    rank: order
68. Magnaporthales
    rank: order
69. Endogonomycetes
    rank: class
70. Leotiales
    rank: order
71. Basidiomycota
    rank: phylum
72. Saccharomycetales
    rank: order
73. Boletales
    rank: order
74. Archaeorhizomycetales
    rank: order
75. Pezizomycetes
    rank: class
76. Coniochaetales
    rank: order
77. Amylocorticiales
    rank: order
78. Cantharellales
    rank: order
79. Phacidiales
    rank: order
80. Cystobasidiales
    rank: order
81. Baeomycetales
    rank: order
82. Leotiomycetes
    rank: class
83. Orbiliomycetes
    rank: class
84. Dothideales
    rank: order
85. Diaporthales
    rank: order
86. Agaricostilbomycetes
    rank: class
87. Amphisphaeriales
    rank: order