Project description:The spring bloom in the North Atlantic develops over a few weeks in response to the physical stabilization of the nutrient replete water column and is one of the biggest biological signals on earth. The composition of the phytoplankton assemblage during the spring bloom of 2008 was evaluated, using a microarray, on the basis of functional genes that encode key enzymes in nitrogen and carbon assimilation in eukaryotic and prokaryotic phytoplankton. Oligonucleotide archetype probes representing RuBisCO, nitrate reductase and nitrate transporter genes from major phytoplankton classes detected a diverse assemblage. For RuBisCO, the archetypes with strongest signals represented known phytoplankton groups, but for the nitrate related genes, the major signals were not closely related to any known phytoplankton sequences. Most of the assemblage's components exhibited consistent temporal/spatial patterns. Yet, the strongest archetype signals often showed quite different patterns, indicating different ecological responses by the main players. The most abundant phytoplankton genera identified previously by microscopy, however, were not well represented on the microarray. The lack of sequence data for well-studied species, and the inability to identify organisms associated with functional gene sequences in the environment, still limits our understanding of phytoplankton ecology even in this relatively well-studied system.
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 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: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.
Project description:The evolutional trajectory of gut microbial colonization from birth has been shown to prime for health later in life. Here, we combined cultivation-independent 16S rRNA gene sequencing and metaproteomics to investigate the functional maturation of gut microbiota in faecal samples from full-term healthy infants collected at 6 and 18 months of age. Phylogenetic analysis of the metaproteomes showed that Bifidobacterium provided the highest number of distinct protein groups. Considerable divergences between taxa abundance and protein phylogeny were observed at all taxonomic ranks. Age had a profound effect on early microbiota where compositional and functional complexity of less dissimilar communities increased with time. Comparisons of the relative abundances of proteins revealed the transition of taxon-associated saccharolytic and carbon metabolism strategies from catabolic pathways of milk and mucin-derived monosaccharides feeding acetate/propanoate synthesis to complex food sugars fuelling butyrate production. Furthermore, co-occurrence network analysis uncovered two anti-correlated modules of functional taxa. A low-connected Bifidobacteriaceae-centred guild of facultative anaerobes was succeeded by a rich club of obligate anaerobes densely interconnected around Lachnospiraceae, underpinning their pivotal roles in microbial ecosystem assemblies. Our findings establish a framework to visualize whole microbial community metabolism and ecosystem succession dynamics, proposing opportunities for microbiota-targeted health-promoting strategies early in life.
Project description:Land cover change has long been recognized that marked effect the amount of soil organic carbon. However, little is known about microbial-mediated effect processes and mechanism on soil organic carbon. In this study, the soil samples in a degenerated succession from alpine meadow to alpine steppe meadow in Qinghai-Tibetan Plateau degenerated, were analyzed by using GeoChip functional gene arrays.