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12 results for “bacterioplankton”
Shifts in Bacterioplankton During Cyanobacterial Blooms Reflect Bloom Toxicity and lake Trophic State, OR 2019-2020
Harmful cyanobacterial blooms (cyanoHABs) typically occur in human-impacted eutrophic lakes suffering from nutrient pollution, but they also occur in lakes spanning the trophic and disturbance gradients. CyanoHABs change the bacterioplankton community structure with increases in specific cyanobacteria strains, as well as shifts in heterotrophic taxa. Bacterioplankton community shifts during cyanoHABs can be somewhat predictable but have been only studied in a limited number of lakes, most highly productive and in developed watersheds. The Cascade Mountains (USA) offer an unique area to study cyanotoxin variation and shifts in bacterioplankton composition across a productivity gradient in lakes with documented cyanoHABs but removed from most development. We explored associations of bacterioplankton communities with cyanoHABs and toxins within a season, as well as across lakes and years via physicochemical metrics, passive toxin samplers and 16S rRNA gene sequencing. The data set is a compilation of physicochemical, meteorological, biological as well as physical lake characteristics and sampling information. Water temperature was tracked continuously within a season for the three lakes while single point measurements of water temperature were taken for the other lakes in the spatial (n= 29) and intra-annual subset (n =12). Daily air temperature, precipitation and aerosol optical depth were extracted from the PRISM Gridded Climate data. Nutrient concentrations were measured for all lakes and analyzed for nitrogen and phosphorus via colorimetry in a flow analyzer. Chlorophyll-a concentrations were measured from filter samples via fluorimetry. Microcystin concentrations from grab and SPATT samples were analyzed via an ELISA kit for Microcystin-LR. Bacterioplankton diversity metrics were calculated from the processed 16S rRNA sequences along with the relative abundance of potentially toxigenic cyanobacteria. Bacterioplankton composition was and can be derived from the raw
Crossing Treeline: Bacterioplankton community composition in alpine and subalpine lakes of the Rocky Mountain southern ecoregion and associated physical and chemical characteristics
This dataset includes lake water samples collected in the summer of 2016 from 16 different mountain lakes in the Rocky mountains in both Rocky Mountain National Park and the Snowy Range of southern Wyoming. Each lake was sampled twice: once in the early summer when hydrologic connections with the surrounding terrestrial environment were high and again in the late summer when hydrologic connections were low. The main goal of the study was to compare communities of bacterioplankton in alpine and subalpine lakes to determine if communities differed across treeline as soil microbes in the surrounding terrestrial environment were. To do so, we collected water samples from the deepest point of each lake, mixed it with a surface water sample and characterized bacterioplankton communities with 16S sequencing technology. Additionally, we wanted to identify abiotic factors that may correlate with community dissimilarity and characterized a suite of chemical attributes for each lake. Lake characteristics reported included surface temperature, soluble reactive phosphorous (SRP), ammonia (NH3+), pH, total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), and total dissolved organic carbon (DOC), and chlorophyll a (chl-a).
Genome-scale community modelling reveals key metabolic cross-feedings in epipelagic bacterioplankton communities (Supplementary Materials)
<p>A comprehensive catalog of 19,791 marine prokaryotic isolates (WGS), single-amplified genomes (SAGs) and metagenomic-assembled genomes (MAGs) compiled from MarRef v4.0 (N=943, mostly high-quality WGS), MarDB v4.0 (N=12,963), and the aquatic representative genomes from the ProGenomes database v1.0 (N=566). This collection of well-documented genomes was complemented by 5,319 MAGs assembled from four distinct studies, namely: Parks et al. 2017 (<a href="https://doi.org/10.1038/s41564-017-0012-7">DOI</a>; N=1,765; downloaded from EBI), Tully et al. 2017/2018 (<a href="https://doi.org/10.7717/peerj.3558">DOI</a> and <a href="https://10.1038/sdata.2017.203">DOI</a>; N=2,597; downloaded from EBI), and Delmont et al. 2018 (<a href="https://doi.org/10.1038/s41564-018-0176-9">DOI</a>; N=957; downloaded from FIGSHARE). The Parks et al. study contained genomes reconstructed from non-marine biomes. Thus, a selection of 1,765 genomes was extracted by searching for specific keywords: “tara|marine|sea|ocean|mediterranean” (case insensitive). Note that depending on their study of origin, included MAGs may have been reconstructed using different assembling and binning methods.</p> <p>The archive includes:</p> <ul> <li>a metadata file describing the quality and redundancy of the genomes named `EcoSysMic_metadata.tsv`</li> <li>sequences of the 19,791 (redundant) genomes in `All/WGS`</li> <li>companion files in `All/Data` and `dRep95/Data` (see Methods in the associated paper), including <ul> <li>predicted CDS and EggNOG functional annotations</li> <li>predicted GTDB taxonomy</li> <li>CarveMe reconstructed metabolic models and their MEMOTE quality</li> </ul> </li> </ul> <p>The 7,658 non-redundant species-level genomes (delineated by a 95% ANI threshold over 60% of genome length) that were used in the associated paper are defined by the column `is_drep95` in the metadata file.</p>
Dataset: Bacterioplankton metabolism of phytoplankton lysates across a cyclone-anticyclone eddy dipole impacts the cycling of semi-labile organic matter in the photic zone
<p>This dataset contains both field data and the results of dilution batch-culture bioassay experiments characterizing bacterioplankton usage of ambient and added dissolved organic matter across a cyclone to anticyclone spatial transect in the North Pacific Subtropical Gyre. Field data include total organic carbon, total nitrogen, bacterioplankton cell abundances, ammonia monooxygenase subunit A gene concentrations, and 16S rRNA gene amplicons. Experimental data include time-resolved changes in total organic carbon, nitrogen species, and bacterioplankton cell abundances.</p>
Data for "Excess labile carbon promotes the expression of virulence factors in coral reef bacterioplankton"
<p>This publication contains 27 coral reef bacterioplankton metagenome-assembled genomes (MAGs) from the following paper: </p> <p>Cárdenas, A., Neave, M. J., Haroon, M. F., Pogoreutz, C., Rädecker, N., Wild, C., Gärdes, A., & Voolstra, C. R. (2018). Excess labile carbon promotes the expression of virulence factors in coral reef bacterioplankton. <em>The ISME Journal</em>, <em>12</em>(1), 59–76. https://doi.org/10.1038/ismej.2017.142</p> <p> </p>
Data from: Particle-associated bacterioplankton communities across the Red Sea
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Genetic survey of bacterioplankton communities of aquatic habitats in Green Lakes Valley, 2014 - 2017
Previous work has shown high-elevation ecosystems are especially susceptible to the effects of climate change, but little work has been done on microbial communities in high-elevation aquatic systems. Therefore, my research aimed to improve our understanding of the composition, stability, and factors controlling microbial communities in high-elevation lakes in the Front Range of the Colorado Rocky Mountains. I studied seasonal and inter-annual variations in bacterial (16S rDNA) and eukaryotic (18S rDNA) microbial communities at multiple locations (inlet, outlet, three depths in the water column) within alpine lakes over four years (2014-2017). Communities significantly differed between lake inlets and the lakes as a whole across sampling dates. The most significant variable controlling 16S and 18S community composition was lake discharge rate, indicating that water residence times play a strong role in structuring communities.
Dataset: Coral high molecular weight carbohydrates support opportunistic microbes in bacterioplankton from an algae-dominated reef
<p>This dataset contains raw data for figures 5 (genus-level microbial community compositions) and 6 (predicted metabolic functions, pathway types), R code for PERMANOVAs (Table 3), DESeq2 and random forest (rfpermute) analyses, and R code to generate figures 5, 6b, S5 & S6.</p> <p>Overview of .txt files:</p> <table> <tbody> <tr> <td> <p>Genus_16S_Counts.txt</p> </td> <td> <p>Counts data used for DESeq2 analysis (Fig. 5c).</p> </td> </tr> <tr> <td> <p>Genus_16S_relAbund.txt</p> </td> <td> <p>Relative abundance data used for Fig. 5a, b & d.</p> </td> </tr> <tr> <td> <p>MicFunPred_MetaCyc_types_all</p> </td> <td> <p>Predicted pathway abundance data for all pathway types used for DESeq2 (Fig. 6b), PERMANOVA (Table 3) and column clustering of Fig. 6b.</p> </td> </tr> <tr> <td> <p>MicFunPred_MetaCyc_AA_types.txt</p> </td> <td> <p>Amino acids (Fig. 6b)</p> </td> </tr> <tr> <td> <p>MicFunPred_MetaCyc_CH_types.txt</p> </td> <td> <p>Carbohydrates (Fig. 6b)</p> </td> </tr> <tr> <td> <p>MicFunPred_MetaCyc_EM _types.txt</p> </td> <td> <p>Energy metabolism (Fig. 6b)</p> </td> </tr> <tr> <td> <p>MicFunPred_MetaCyc_FAL _types.txt</p> </td> <td> <p>Fatty acids and lipids (Fig. 6b)</p> </td> </tr> <tr> <td> <p>MicFunPred_MetaCyc_SM _types.txt</p> </td> <td> <p>Secondary metabolism (Fig. 6b)</p> </td> </tr> <tr> <td> <p>MicFunPred_MetaCyc_OBiosyn _types.txt</p> </td> <td> <p>Other biosynthesis (Fig. S6)</p> </td> </tr> <tr> <td> <p>MicFunPred_MetaCyc_ODeg _types.txt</p> </td> <td> <p>Other degradation (Fig. S6)</p> </td> </tr> </tbody> </table>
Dissolved storage glycans shaped the community composition of abundant bacterioplankton clades during a North Sea spring phytoplankton bloom
<p>In 2020 we sampled a complete spring bloom in the German Bight over a 90-day period. Bacterioplankton metagenomes from 30 time-points allowed reconstruction of 251 metagenome-assembled genomes (MAGs). Corresponding metatranscriptomes highlighted 50 particularly active MAGs of the most abundant clades. Saccharide measurements together with bacterial polysaccharide utilization loci (PUL) expression data identified β-glucans (diatom laminarin) and α-glucans as the most prominent dissolved polysaccharide substrates metabolized by the bacterioplankton. Here we are depositing all supporting environmental data for the analyzed 2020 Helgoland spring algal bloom. This includes physicochemical data, data on algal abundances and biovolumes, data on copepod and flagellate abundances, data on monosaccharide and antibody-based polysaccharide measurements, and 16S rRNA-based bacterial diversity data. The corresponding metagenome, metatranscriptome and MAG sequence data of this project are available from the European Nucleotide Archive (accession PRJEB52999).</p>
Dataset: A methodological framework to analyse determinants of host-microbiota networks, with an application to the relationships between Daphnia magna's gut microbiota and bacterioplankton
<p>Dataset and R codes for the publication "A methodological framework to analyse determinants of host-microbiota networks, with an application to the relationships between <em>Daphnia magna</em>’s gut microbiota and bacterioplankton"</p>
Data from: Influence of salinity on bacterioplankton communities from the Brazilian rain forest to the coastal Atlantic Ocean
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The supplementary material (dataset S1 and dataset S2) of article with the title of "Bacterioplankton community variation in Bohai Bay (China) is explained by joint effects of environmental and spatial factors"
<p>Dataset S1 Geochemical and physical variables of the sampling sites in this study</p> <p>Dataset S2 The relative baundance of 36 OTUs (with relative abundance > 1%) </p>
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