Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days
Abstract In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of a Rhizosolenia sp. bloom, the initiation and complete bloom cycle of Chaetoceros so...
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Nature Portfolio
2024-11-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-024-04013-5 |
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| author | Brook L. Nunn Emma Timmins-Schiffman Miranda C. Mudge Deanna L. Plubell Gabriella Chebli Julia Kubanek Michael Riffle William S. Noble Elizabeth Harvey Tasman A. Nunn Tatiana Rynearson Marcel Huntemann Kurt LaButti Brian Foster Bryce Foster Simon Roux Krishnaveni Palaniappan Supratim Mukherjee T. B. K. Reddy Chris Daum Alex Copeland I-Min A. Chen Natalia N. Ivanova Nikos C. Kyrpides Tijana Glavina del Rio Emiley A. Eloe-Fadrosh |
| author_facet | Brook L. Nunn Emma Timmins-Schiffman Miranda C. Mudge Deanna L. Plubell Gabriella Chebli Julia Kubanek Michael Riffle William S. Noble Elizabeth Harvey Tasman A. Nunn Tatiana Rynearson Marcel Huntemann Kurt LaButti Brian Foster Bryce Foster Simon Roux Krishnaveni Palaniappan Supratim Mukherjee T. B. K. Reddy Chris Daum Alex Copeland I-Min A. Chen Natalia N. Ivanova Nikos C. Kyrpides Tijana Glavina del Rio Emiley A. Eloe-Fadrosh |
| author_sort | Brook L. Nunn |
| collection | DOAJ |
| description | Abstract In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of a Rhizosolenia sp. bloom, the initiation and complete bloom cycle of Chaetoceros socialis (8 days), and the following bacterial bloom (2 days). Metagenomes were completed on the time series, and the dataset includes 128 size-fractionated microbial samples (0.22–1.2 µm), providing gene abundances for the dominant members of bacteria, archaea, and viruses. This dataset also has time-matched nutrient analyses, flow cytometry data, and physical parameters of the environment at a single point of sampling within a coastal ecosystem that experiences regular bloom events, facilitating a range of modeling efforts that can be leveraged to understand microbial community structure and their influences on the growth, maintenance, and senescence of phytoplankton blooms. |
| format | Article |
| id | doaj-art-8208ac76a20e4255af7934254cb67d6f |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-8208ac76a20e4255af7934254cb67d6f2025-01-26T12:14:25ZengNature PortfolioScientific Data2052-44632024-11-011111810.1038/s41597-024-04013-5Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 DaysBrook L. Nunn0Emma Timmins-Schiffman1Miranda C. Mudge2Deanna L. Plubell3Gabriella Chebli4Julia Kubanek5Michael Riffle6William S. Noble7Elizabeth Harvey8Tasman A. Nunn9Tatiana Rynearson10Marcel Huntemann11Kurt LaButti12Brian Foster13Bryce Foster14Simon Roux15Krishnaveni Palaniappan16Supratim Mukherjee17T. B. K. Reddy18Chris Daum19Alex Copeland20I-Min A. Chen21Natalia N. Ivanova22Nikos C. Kyrpides23Tijana Glavina del Rio24Emiley A. Eloe-Fadrosh25University of Washington, Department of Genome SciencesUniversity of Washington, Department of Genome SciencesUniversity of Washington, Department of Genome SciencesUniversity of Washington, Department of Genome SciencesGeorgia Institute of Technology, School of Biological Sciences and School of Chemistry & Biochemistry, Parker H. Petit Institute for Bioengineering and BioscienceGeorgia Institute of Technology, School of Biological Sciences and School of Chemistry & Biochemistry, Parker H. Petit Institute for Bioengineering and BioscienceUniversity of Washington, Department of Genome SciencesUniversity of Washington, Department of Genome SciencesDepartment of Biological Sciences, University of New HampshireUniversity of Washington, Department of Genome SciencesSchool of Oceanography, University of Rhode IslandDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryDOE Joint Genome Institute, Lawrence Berkeley National LaboratoryAbstract In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of a Rhizosolenia sp. bloom, the initiation and complete bloom cycle of Chaetoceros socialis (8 days), and the following bacterial bloom (2 days). Metagenomes were completed on the time series, and the dataset includes 128 size-fractionated microbial samples (0.22–1.2 µm), providing gene abundances for the dominant members of bacteria, archaea, and viruses. This dataset also has time-matched nutrient analyses, flow cytometry data, and physical parameters of the environment at a single point of sampling within a coastal ecosystem that experiences regular bloom events, facilitating a range of modeling efforts that can be leveraged to understand microbial community structure and their influences on the growth, maintenance, and senescence of phytoplankton blooms.https://doi.org/10.1038/s41597-024-04013-5 |
| spellingShingle | Brook L. Nunn Emma Timmins-Schiffman Miranda C. Mudge Deanna L. Plubell Gabriella Chebli Julia Kubanek Michael Riffle William S. Noble Elizabeth Harvey Tasman A. Nunn Tatiana Rynearson Marcel Huntemann Kurt LaButti Brian Foster Bryce Foster Simon Roux Krishnaveni Palaniappan Supratim Mukherjee T. B. K. Reddy Chris Daum Alex Copeland I-Min A. Chen Natalia N. Ivanova Nikos C. Kyrpides Tijana Glavina del Rio Emiley A. Eloe-Fadrosh Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days Scientific Data |
| title | Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days |
| title_full | Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days |
| title_fullStr | Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days |
| title_full_unstemmed | Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days |
| title_short | Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days |
| title_sort | microbial metagenomes across a complete phytoplankton bloom cycle high resolution sampling every 4 hours over 22 days |
| url | https://doi.org/10.1038/s41597-024-04013-5 |
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