ABSTRACT
We report bacterial community 16S rRNA amplicon sequencing results to provide insights into the formation process of terrestrial microbial communities on Nishinoshima, which was covered by volcanic ash and pyroclastic deposits from successive eruptions in 2020.
KEYWORDS: bacterial community analysis, volcanic ash, pyroclastic deposit, Nishinoshima
ANNOUNCEMENT
The present Nishinoshima (140°52.5'E, 27°14.8'N), a volcanically active island surrounded by the sea, has been covered with fresh volcanic deposits by the 2020 huge eruption (1). The invasion and colonization of microbes play a crucial role in primary succession within volcanic deposits (2–4). The surface of volcanic ash and pyroclastic deposits (0–5 cm) was collected manually on-site using scoops in October 2016, May 2018, September 2019, and July 2022. In September 2021, the surface of deposits was collected using vacuum-equipped drones operated on the research vessel. Approximately 50 g of the collected samples were packed into sterilized plastic bags, respectively, and stored in a dark place.
Genomic DNA was extracted through a modified CTAB method (5, 6). The bacterial 16S rRNA gene region was amplified by using a 515F/806R primer pair [5′-GTGCCAGCMGGCCGCGGTAA-3′/5′-GGACTACHVGGGTWTCTAAT-3′; (7)]. All PCRs were carried out with 15 µL of Phusion High-Fidelity PCR Master Mix (New England Biolabs Inc., MA, USA), 2 µM of forward and reverse primers, and about 10 ng of template DNA. Thermal cycling consisted of an initial denaturation at 98°C for 1 min, followed by 30 cycles of denaturation at 98°C for 10 sec, annealing at 50°C for 30 sec, and elongation at 72°C for 30 sec. The final step was a 5 min extension at 72°C.
The sequencing was performed on the Illumina NovaSeq 6000 system (Illumina, CA, USA). Adapter-sequence removal was performed using Cutadapt v2.6 (8) (-overlap 3, -e 0.1) with default parameters. The processed sequences were subsequently analyzed using the mothur package v1.48.1 (9) following the standard operating procedure (10). Briefly, the 250 bp paired-end reads were merged (mothur command: make.contigs) and aligned (align.seqs) with the SILVA database v138 (https://www.arb-silva.de/) (11). Quality control was carried out (screen.seqs) and chimeric sequences were identified and removed using the VSEARCH algorithm (chimera.vsearch) (12). Taxonomic classification was performed using 16S rRNA reference (RDP) files v19 (https://sourceforge.net/projects/rdp-classifier/) (13) and sequences classified into non-bacterial taxa were removed (remove.lineage). Operational taxonomic units (OTUs) were clustered with 97.0% sequence identity and consensus classifications were obtained for each OTU (cutoff = 80). Then, taxonomic classification was performed again using RDP v19.
Table 1 shows the number of OTUs, ranging from 5,323 to 8,674, which were generated from 69,865 to 125,481 raw reads. According to the RDP analysis in the Nishinoshima volcanic deposits from 2016 to 2019, the dominant phyla were Pseudomonadota (20.8%), Deinococcota (18.9%), and Bacillota (16.6%) (Fig. 1A). In fresh volcanic ash deposits after the 2020 eruption, the phyla Pseudomonadota (27.8%), Bacillota (16.4%), and Actinomycetota (13.4%) became predominant (Fig. 1A). While the relative abundance within the phylum Pseudomonadota was dominated by Alphaproteobacteria (27.3%), Betaproteobacteria (26.7%), and Gammaproteobacteria (42.7%) in the volcanic deposits of former Nishinoshima, the relative abundances of these classes were 34.7%, 24.5%, and 40.3%, respectively, in fresh volcanic ash deposits (Fig. 1B).
TABLE 1.
Summary of sample features and 16S rRNA gene-based sequence data of Nishinoshima
| Sample features | ||||||
|---|---|---|---|---|---|---|
| Sampling date/Sample ID | Deposit type | Sampling location/East longitude, North latitude | No. of raw reads | Coverage (%) | No. of OTUs | SRA accession no. |
| October 2016 | ||||||
| 16OI_S0 | ash | 140°87.38', 27°24.57' | 111,542 | 99.3 | 6,180 | SRR32456516 |
| 16OI_S2 | ash | 140°87.38', 27°24.57' | 107,343 | 98.1 | 8,352 | SRR32456515 |
| 16OI_S5 | ash | 140°87.38', 27°24.57' | 69,865 | 99.0 | 6,649 | SRR32456504 |
| 16OI_L | pyroclastic | 140°87.22', 27°24.67' | 115,158 | 97.9 | 8,521 | SRR32456501 |
| 16NI_L | pyroclastic | 140°87.30', 27°24.61' | 110,203 | 98.1 | 7,755 | SRR32456500 |
| May 2018 | ||||||
| 18OI_A | pyroclastic | 140°87.31', 27°24.65' | 105,426 | 99.3 | 6,399 | SRR32456499 |
| 18NS_B | pyroclastic | 140°87.80', 27°24.40' | 103,765 | 97.9 | 8,144 | SRR32456498 |
| September 2019 | ||||||
| 19 Nl_Q1 | pyroclastic | 140°52.39', 27°14.72' | 113,449 | 98.5 | 7,095 | SRR32456497 |
| 19OI_Q2 | pyroclastic | 140°52.40', 27°14.75' | 82,200 | 98.7 | 7,120 | SRR32456496 |
| 19OI_Q3 | pyroclastic | 140°52.38', 27°14.77' | 103,694 | 99.5 | 6,249 | SRR32456495 |
| 19 Nl_Q4 | pyroclastic | 140°52.31', 27°14.88' | 114,111 | 97.8 | 8,674 | SRR32456514 |
| 19 Nl_Q5 | pyroclastic | 140°87.52', 27°14.49' | 125,481 | 97.9 | 8,170 | SRR32456513 |
| September 2021 | ||||||
| 21AE_L1 | ash | 140°88.17', 27°25.64' | 113,691 | 99.4 | 5,958 | SRR32456512 |
| 21AE_L3 | ash | 140°87.07', 27°24.62' | 114,259 | 99.6 | 5,774 | SRR32456511 |
| 21AE_L4 | ash | 140°88.80', 27°25.05' | 103,465 | 99.6 | 5,733 | SRR32456510 |
| 21AE_L6 | ash | 140°88.96', 27°24.87' | 102,746 | 99.8 | 5,323 | SRR32456509 |
| 21AE_D2 | ash with seabird nest | 140°87.13', 27°24.61' | 103,218 | 99.6 | 5,877 | SRR32456508 |
| 21AE_D3 | ash | 140°88.97', 27°24.88' | 102,391 | 99.4 | 6,057 | SRR32456507 |
| 21AE_D4 | ash | 140°87.19', 27°24.43' | 103,511 | 99.5 | 5,941 | SRR32456506 |
| July 2022 | ||||||
| 22AE_N1 | ash | 140°88.17', 27°25.64' | 111,044 | 99.7 | 5,664 | SRR32456505 |
| 22AE_N2 | ash | 140°88.21', 27°25.65' | 105,517 | 99.7 | 5,568 | SRR32456503 |
| 22AE_N3 | ash | 140°88.17', 27°25.64' | 78,091 | 99.8 | 5,616 | SRR32456502 |
Fig 1.

Relative abundance of bacterial phyla (A) and Pseudomonadota classes (B). The sample IDs are listed in the first column of Table 1. The reference to the phyla and class is shown on the right, respectively.
ACKNOWLEDGMENTS
We thank Yuika Sakashita in Nishizawa Lab for supporting the experimental procedures and The Earthquake Research Institute, The University of Tokyo for providing the 2016 specimens. Some of the samples were collected during environmental surveys conducted by the Ministry of the Environment.
This study was supported by a Japan Society for the Promotion of Science (JSPS) Grant-in-Aid (23K23945 and 25K02336).
Contributor Information
Tomoyasu Nishizawa, Email: tomoyasu.nishizawa.agr@vc.ibaraki.ac.jp.
Elinne Becket, California State University San Marcos, San Marcos, California, USA.
DATA AVAILABILITY
The 16S rRNA gene amplicon data sets are available through NCBI BioProject ID PRJNA1227021. Individual accessions for each sample are listed in Table 1.
REFERENCES
- 1. Maeno F, Yasuda A, Hokanishi N, Kaneko T, Tamura Y, Yoshimoto M, Nakano S, Takagi A, Takeo M, Nakada S. 2021. Intermittent growth of a newly-born volcanic island and its feeding system revealed by geological and geochemical monitoring 2013–2020, Nishinoshima, Ogasawara, Japan. Front Earth Sci 9:773819. doi: 10.3389/feart.2021.773819 [DOI] [Google Scholar]
- 2. Fierer N, Nemergut D, Knight R, Craine JM. 2010. Changes through time: integrating microorganisms into the study of succession. Res Microbiol 161:635–642. doi: 10.1016/j.resmic.2010.06.002 [DOI] [PubMed] [Google Scholar]
- 3. Dragone NB, Whittaker K, Lord OM, Burke EA, Dufel H, Hite E, Miller F, Page G, Slayback D, Fierer N. 2023. The early microbial colonizers of a short-lived volcanic Island in the kingdom of Tonga. mBio 14:e0331322. doi: 10.1128/mbio.03313-22 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Ni G, Lappan R, Hernández M, Santini T, Tomkins AG, Greening C. 2023. Functional basis of primary succession: traits of the pioneer microbes. Environ Microbiol 25:171–176. doi: 10.1111/1462-2920.16266 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Zhou J, Bruns MA, Tiedje JM. 1996. DNA recovery from soils of diverse composition. Appl Environ Microbiol 62:316–322. doi: 10.1128/aem.62.2.316-322.1996 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Fujimura R, Kim SW, Sato Y, Oshima K, Hattori M, Kamijo T, Ohta H. 2016. Unique pioneer microbial communities exposed to volcanic sulfur dioxide. Sci Rep 6:19687. doi: 10.1038/srep19687 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, Knight R. 2012. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6:1621–1624. doi: 10.1038/ismej.2012.8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Martin M. 2011. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 17:10. doi: 10.14806/ej.17.1.200 [DOI] [Google Scholar]
- 9. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF. 2009. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537–7541. doi: 10.1128/AEM.01541-09 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. 2013. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 79:5112–5120. doi: 10.1128/AEM.01043-13 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO. 2013. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:D590–6. doi: 10.1093/nar/gks1219 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Rognes T, Flouri T, Nichols B, Quince C, Mahé F. 2016. VSEARCH: a versatile open source tool for metagenomics. PeerJ 4:e2584. doi: 10.7717/peerj.2584 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Cole JR, Wang Q, Fish JA, Chai B, McGarrell DM, Sun Y, Brown CT, Porras-Alfaro A, Kuske CR, Tiedje JM. 2014. Ribosomal database project: data and tools for high throughput rRNA analysis. Nucl Acids Res 42:D633–D642. doi: 10.1093/nar/gkt1244 [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
The 16S rRNA gene amplicon data sets are available through NCBI BioProject ID PRJNA1227021. Individual accessions for each sample are listed in Table 1.
