LMO 16S rRNA metabarcoding dataset

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Este IPT archiva los datos y, por lo tanto, sirve como repositorio de datos. Los datos y los metadatos del recurso están disponibles para su descarga en la sección descargas. La tabla versiones enumera otras versiones del recurso que se han puesto a disposición del público y permite seguir los cambios realizados en el recurso a lo largo del tiempo.

Versiones

La siguiente tabla muestra sólo las versiones publicadas del recurso que son de acceso público.

¿Cómo referenciar?

Los usuarios deben citar este trabajo de la siguiente manera:

Bunse C, Pinhassi J, Lundin D, Farnelid H, Lindehoff E (2026). LMO 16S rRNA metabarcoding dataset. Version 1.0. Linnaeus University. Occurrence dataset. https://www.gbif.se/ipt/resource?r=lmo_2011-2023_16s&v=1.0

Derechos

Los usuarios deben respetar los siguientes derechos de uso:

El publicador y propietario de los derechos de este trabajo es Linnaeus University. Esta obra está bajo una licencia Creative Commons de Atribución/Reconocimiento (CC-BY 4.0).

Registro GBIF

Este recurso ha sido registrado en GBIF con el siguiente UUID: 604b1b36-37c1-498f-9e49-439831bff7a5.  Linnaeus University publica este recurso y está registrado en GBIF como un publicador de datos avalado por GBIF Sweden.

Palabras clave

Occurrence; Observation

Contactos

Cobertura geográfica

Lat: 56.9309 Long: 17.0607

Cobertura taxonómica

Archaea and Bacteria

Cobertura temporal

Datos del proyecto

Marine microbiomes exhibit seasonal dynamics in many ocean regions. While we can characterize the biodiversity and composition of ocean microbiomes, we lack a systematic understanding of how environmental drivers shape the seasonal succession of marine microbes. To leverage the pronounced temporal changes in growth conditions in the temperate waters of the Baltic Sea, we here report on dynamics in the prokaryoplankton community over 13 years at the Linnaeus Microbial Observatory (LMO), focusing on both free-living (FL; 0.2-3 µm fraction) and particle-associated (PA; >3 µm fraction) prokaryotes. As expected, our analysis showed a higher diversity in the PA compared to the FL fraction and that the grand majority of 16S rRNA gene amplicon sequence variants (ASVs) were consistently rare. Yet, to an unexpected degree also a majority of the abundant ASVs transitioned into the rare biosphere over extended periods of the year. Prokaryotes in both the PA and FL fractions showed pronounced seasonal dynamics, with notable differences between the fractions from phylum down to the ASV level. Abundant ASVs were strongly correlated to several environmental drivers, including nutrient concentrations, salinity and temperature. Intriguingly, at comparable temperatures in spring and autumn (e.g. at 12°C), the community composition was strikingly different. This highlighted that specific temperature values per se are informative, but that the trajectories of change in temperature and other environmental drivers (low to high, high to low) merit attention in ecological research. Our data suggest that the community composition of prokaryoplankton in temperate regions strongly depend on factors beyond temperature and photoperiod values, including the history of the community, the direction of environmental change, and qualitative and quantitative levels of (in)organic nutrients, as well as biotic interactions.

Personas asociadas al proyecto:

Métodos de muestreo

Seawater was collected at the Linnaeus Microbial Observatory (LMO, N 56° 55.8540', E 17° 3.6420'), situated in the Western Baltic Proper during 2011 to 2023. Seawater was sampled at 2 m depth using a Ruttner sampler and was transported back to the laboratory in Kalmar (Linnaeus University, Sweden) (~1 hour) where it was processed for various abiotic and biotic parameters as described in detail in (Lindh et al., 2015; Bunse et al., 2019; Fridolfsson et al., 2023). During 2011-2013, samples were collected approximately twice a week during the productive season, in 2014 samples were collected monthly, and from 2015 samples were collected bi-weekly when weather permitted sampling. Environmental data were gathered following the procedures described in (Lindh et al., 2015; Bunse et al., 2019; Fridolfsson et al., 2023). Prokaryotic cell counts via flow cytometry were analysed using Partec Cube8 (2013–2018) and CytoFlex, Beckman Coulter (2019-2024) instruments equipped with blue lasers (488nm) with protocols adapted from (Gasol and Morán, 2015). Raw data were subsequently analyzed using the software FCSalyser 0.9.22 and CytExpert and gates in SSC/FL1 and SSC/B525 were drawn to count prokaryotic cells across all years. DNA extraction and 16S rRNA gene processing For prokaryotic community composition estimates, 3-8 L seawater was filtered through 3.0 µm pore size, 47 mm diameter, polycarbonate filters (Pall life sciences), referred to as particle-associated (PA). Bacterioplankton biomass was subsequently collected on 0.2 µm Sterivex™ cartridge filters (Millipore) referred to as the 0.2-3 µm "free-living" fraction (FL), and filters were stored frozen at -80°C in TE-buffer. DNA was extracted using the phenol-chloroform protocol described by (Boström et al., 2004) and modified after (Bunse et al., 2016). We amplified the V3V4 region of the 16S rRNA gene using the primer pair 341f-805r (Herlemann et al., 2011) as described and validated in (Hugerth et al., 2014). The 16S rRNA gene and Illumina adapters were amplified using the Phusion Mastermix (ThermoScientific) in 20 cycles (98°C 30 sec, (98°C 10 s, 58°C 30 s, 72°C 15 s), 72°C 2 min). After cleaning the PCR1 product using AmpPureXP following the manufacturer’s instructions, the Miseq Step two PCR with standard Illumina handles and index primers included 12 cycles (98°C 30 s, (98°C 10 s, 62 °C 30 s, 72 °C 5 s), 72°C 2 min). PCR products were quantified using Qubit 2.0 Fluorometer (Invitrogen) and subsequent gel electrophoresis confirmed amplicon specificity. Sequencing was carried out at the Science for Life Laboratory, Sweden on the MiSeq platform (Illumina), producing 2 × 300 bp paired-end reads. At the time of analysis, ASV data were available until end of 2022 for PA and until end of 2023 for FL.

Descripción de la metodología paso a paso:

1. The samples from the LMO timeseries are continuously processed and were sequenced over the course of 13 years in different sequencing batches. Therefore, raw reads were processed with the nf-core/ampliseq pipeline (v2.11.0-g0473e15, Nextflow: 24.04.4 (Straub et al., 2020)) for each Illumina run separately. The nf-core/ampliseq pipeline is based on DADA2 (v. 1.30.0; (Callahan et al., 2016)) which uses an error correction algorithm for Illumina amplicon reads to produce amplicon sequence variants (ASVs). The pipeline was run with default settings except for forward and reverse trimming lengths which were set to 259 and 199 respectively. We taxonomically annotated the full dataset using SBDI-GTDB (v. R09-RS220; (Parks et al., 2018; Lundin and Andersson, 2024)) and SILVA (v. 138.2) (Quast et al., 2012) respectively.

Metadatos adicionales