Saproxylic Fungal Communities in Boreal Forest, Finland, Oulanka, 2022-2023

Study Extent

The sampling event was performed in a boreal forest at the Oulanka Biological Station, Finland from July 1, 2022 to October 6, 2023. Sterilized wooden pins of pine, birch, and spruce were placed in four different sampling sites. They were collected every 2 weeks during summer and fall seasons.

Sampling

Sterilized wooden pins of softwood (pine and spruce) and hardwood (birch), each in a duplicate, were placed on the top soil of four different sampling sites: transect A - conifer forest with reindeer access, transect B - conifer forest without reindeer access, transect C - broadleaf forest with access to tourists, transect D - swamp. The pins were collected approximately every 2 weeks during summer and fall seasons between July 1, 2022 and October 6, 2023. Upon collection, the pins were dried for 2 hours at 45°C and stored at room temperature. Sawdust then was extracted by drilling and DNA was isolated from it. A set of 40 tagged primers for ITS fungal region (Clemmensen, 2016) were used to perform PCR with each DNA sample. The tagged amplicons were then mixed into a multiplex which was used for Next Generation Sequencing. The resultant sequence files were processed in SCATA pipeline (https://scata.mykopat.slu.se/). Species were identified using a curated fungi database UNITE Fungi v 9.0 (https://unite.ut.ee/) in SCATA using USEARCH algorithm, and then those that were not identified in it were identified using BLAST algorithm and Nucleotide database of NCBI (https://www.ncbi.nlm.nih.gov/) . Taxonomic IDs were aligned with the GBIF backbone taxonomy database, and fungal traits were assigned using the FungalTraits database (Põlme, 2020).

Quality Control

Paired FASTQ files of NGS of multiplexes were submitted to SCATA to ensure the quality of reads. Tag identification was based on a 90% primer match. Only sequences with a minimum of 200 in length were considered. Minimum base quality was 10. UNITE Fungi v 9.0 (2023-07-18) database was used for species identification. For species where no match exists from the UNITE Fungi database, a BLAST search was performed. The search result with a minimum bit score of 200, had the lowest e-value, and had the highest percent identity is considered the best match species. Species taxonomy was referenced from GBIF backbone taxonomy. Only species of the Fungi kingdom were included in the species list. Species without a known genus were excluded.

Method steps

1. MycoPin placement Four 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 an individual number. 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 four different sampling sites: (A) An area of a boreal forest protected from grazing by reindeers. (B) An area of a boreal forest located next to A, but unprotected by reindeers. (C) An area of a mixed broadleaf forest, accessed by random visitors. (D) An area of a swamp protected from 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 ITS2 fungal region were used to perform PCR according to Clemmensen (2016). While the forward and reverse primers were always the same, a pair of primers with a unique nucleotide tag was used to perform PCR for each DNA extracted from each MycoPin. 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 was used to exclude false-positive results in a form of water.
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 the following procedure:
   1. The FASTQ files were uploaded to SCATA pipeline (https://scata.mykopat.slu.se/) .
   2. A SCATA pipeline was used to exclude sequences of low quality, clustering of similar sequences, and identification of species using UNITE v. 9.0 (2023-07-18) fungi database. Clusters present in positive and negative controls were excluded.
      1. Sequence quality was parameterized to include only the following: (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. Pipeline was configured to overlap and merge the FASTQ files. 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.
      2. SCATA uses the USEARCH algorithm for clustering. 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. Penalty for mismatch was set to 1. 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 down sampling and no removal of low frequency genotypes were performed during clustering. Up to 3 representative sequences were reported for each cluster.
   3. Double clusters and clusters present in positive and negative controls were excluded.
   4. For each of the clusters without a match from the UNITE database, a BLAST search against 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 BLAST 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.
   5. The abundance of the same species were amalgamated.
   6. Each species ID 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 genus-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).

Saproxylic fungi from Ascomycetes and Basidiomycetes were identified from DNA extracted from saw dust of wooden pins (pine, spruce, birch) using MycoPins method (Shumskaya, 2023).

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

Oulanka Research Station https://eu-interact.org/field-sites/oulanka-research-station/ 25 km south of the Arctic Circle Sub-Arctic (Boreal zone) No permafrost