Project description:Particle-attached bacterioplankton and eukaryote composition of surface seawater during the spring bloom at Helgoland in the year 2018
Project description:The dataset represents the proteome analysis of 7 sampling dates during the phytoplankton bloom in the Helgoland Roads in the North Sea at the long-term research station ‘Kabeltonne’ (54°11'N 7°54'E, DEIMS.ID https://deims.org/1e96ef9b-0915-4661-849f-b3a72f5aa9b1) in 2018.
Project description:Marine microalgae (phytoplankton) mediate almost half of the worldwide photosynthetic carbon dioxide fixation and therefore play a pivotal role in global carbon cycling, most prominently during massive phytoplankton blooms. Phytoplankton biomass consists of considerable proportions of polysaccharides, substantial parts of which are rapidly remineralized by heterotrophic bacteria. We analyzed the diversity, activity and functional potential of such polysaccharide-degrading bacteria in different size fractions during a diverse spring phytoplankton bloom at Helgoland Roads (southern North Sea) at high temporal resolution using microscopic, physicochemical, biodiversity, metagenome and metaproteome analyses.
Project description:Marine snow plays a central role in carbon cycling. It consists of organic particles and particle-associated (PA) microbMarine snow plays a central role in carbon cycling. It consists of organic particles and particle-associated (PA) microbial communities that are embedded in a sugary matrix. Metaproteomic analysis offers the unique opportunity to gain unprecedented insight into the microbial community composition and biomolecular activity of environmental samples. In order to realize this potential for marine PA microbial communities, new methods of protein extraction must be developed. In this study, we used 1D-SDS-PAGEs and LC-MS/MS to compare the efficiency of six established protein extraction protocols for their applicability of metaproteomic analyses of the PA microbial community in the North Sea. A combination of SDS-buffer extraction and bead beating resulted in the greatest number of identified protein groups. As expected, a metagenomic database of the same environmental sample increased the number of protein identification by approximately 50%. To demonstrate the application of our established protocol, particulate bacterioplankton samples collected during spring phytoplankton bloom in 2009 near the island Helgoland, were analysed by a GeLC-MS/MS-based metaproteomic approach. Our results indicated that there are only slight differences in the taxonomical distribution between free-living (FL) and PA bacteria but that the abundance of protein groups involved in polysaccharide degradation, motility and particle specific stress (oxygen limitation, nutrient limitation, heavy metal stress) is higher in the PA fractions. ial communities that are embedded in a sugary matrix. Metaproteomic analysis offers the unique opportunity to gain unprecedented insight into the microbial community composition and biomolecular activity of environmental samples. In order to realize this potential for marine PA microbial communities, new methods of protein extraction must be developed. In this study, we used 1D-SDS-PAGEs and LC-MS/MS to compare the efficiency of six established protein extraction protocols for the their applicability of metaproteomic analyses of the PA microbial community in the North Sea. A combination of SDS-buffer extraction and bead beating resulted in the greatest number of identified protein groups. As expected, a metagenomic database of the same environmental sample increased the number of protein identification by approximately 50%. To demonstrate the application of our established protocol, particulate bacterioplankton samples collected during spring phytoplankton bloom in 2009 near the island Helgoland, were analysed by a GeLC-MS/MS-based metaproteomic approach. Our results indicated that there are only slight differences in the taxonomical distribution between free-living (FL) and PA bacteria but that the abundance of protein groups involved in polysaccharide degradation, motility and particle specific stress (oxygen limitation, nutrient limitation, heavy metal stress) is higher in the PA fractions.
Project description:The dataset represents the proteome analysis of six sampling dates during the phytoplankton bloom at the island of Helgoland in the North Sea at the long term research station ‘Kabeltonne’ (54° 11' 17.88'' N, 7° 54' 0'' E) in 2016.
Project description:The dataset represents the proteome analysis of 15 sampling dates during the phytoplankton bloom in the Helgoland Roads in the North Sea at the long-term research station ‘Kabeltonne’ (54°11'N 7°54'E, DEIMS.ID https://deims.org/1e96ef9b-0915-4661-849f-b3a72f5aa9b1) in 2020.