Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days.

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
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, Marcel Huntemann, Alicia Clum, 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
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引用次数: 0

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.

整个浮游植物繁殖周期的微生物元基因组:22 天内每 4 小时一次的高分辨率采样。
2021 年 5 月和 6 月,在美国华盛顿州东海湾(East Sound)采集了海洋微生物样本进行 DNA 测序,每 4 小时采集一次,持续 22 天。这种高时间分辨率的采样工作捕捉到了Rhizosolenia sp.绽放的最后3天、Chaetoceros socialis的开始和完整绽放周期(8天)以及随后的细菌绽放(2天)。时间序列上的元基因组已经完成,数据集包括 128 个尺寸分馏微生物样本(0.22-1.2 微米),提供了细菌、古菌和病毒主要成员的基因丰度。该数据集还具有与时间相匹配的营养分析、流式细胞仪数据和环境物理参数,取样点位于定期发生浮游植物藻华事件的沿岸生态系统中,有助于开展一系列建模工作,以了解微生物群落结构及其对浮游植物藻华的生长、维持和衰老的影响。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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