Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Metagenome of Eutrophic Lake

PROVIDER: PRJNA844179 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR19497811_1.fastq.gz	Fastqsanger.gz
	SRR19497811_2.fastq.gz	Fastqsanger.gz

Items per page:

1 - 2 of 2

Similar Datasets

Microbial consortia mediating lignocellulose turnover and denitrification in eutrophic lake sediment enrichments

Project description:Anthropogenic activities such as urbanization and agriculture can potentially pose a threat to neighboring freshwaters through nitrate and phosphorous contamination, which over time may lead to lake eutrophication. In such nitrogen-polluted environments, oxygen is depleted, and plants die and decompose. This enhances denitrifying microbes that respire under hypoxic/anoxic conditions by reducing nitrate instead of molecular oxygen and using plant remnants (lignocellulose) as carbon source. Microbial lignocellulose degradation has been well-studied for both aerobic- and anaerobic conditions; however, its degradation during denitrification remains largely unknown. Here we have applied a combination of gas kinetics and meta-omics techniques to enrich and analyze microbial communities from 10 eutrophic lakes to identify a set of core microbial metagenome-assembled genomes (MAGs) present in all the eutrophic lakes. We have further investigated their strategies and enzyme profiles for degrading lignocellulose under denitrifying conditions. We identified Pseudomonadota, Bacteroidota, Verrucomicrobiota, and Actinomycetota as the most abundant phyla and they were present in enrichments from all eutrophic lakes having a key role in denitrification and fermentation. Lignocellulose degradation was, however, dominated by species outside the core microbiome, i.e., there were differing key degraders between lakes, suggesting some level of lake-specialization. Among these we observed potential respiratory DNRA pathways, and they expressed a broad range of CAZymes targeting the various lignocellulose subfractions. Interestingly, many of the detected MAGs contained NO dismutases, enzymes postulated to convert NO to molecular oxygen and dinitrogen gas.

2026-04-30 | PXD069160 | Pride

Metaproteomics of phototrophic biomats from two soda lakes in the Canadian Rocky Mountains

Project description:This data is a case study done in the context of developing methods for assessing the taxonomic composition of microbial communities using metaproteomics. For this study with analyzed phototrophic biomats from two Soda Lakes in the Canadian Rocky Mountains using metaproteomics. For protein identification we generated a metagenome from which we predicted and annotated the protein sequences used to analyze the metaproteomes. The database is available in this PRIDE submission. Lake1 refers to Goodenough Lake (GEM, 51°19'47.64"N 121°38'28.90"W) and Lake2 referes to Last Chance Lake (LCM, 51°19'39.3" N 121°37'59.3"W).

2017-05-12 | PXD006343 | Pride

13C or 15N labeled metaproteome of phototrophic microbial mats from Goodenough soda lake in the Cariboo Plateau region of British Columbia, Canada

Project description:In this study, we used 13C and 15N labeled substrates to assess the carbon (C) and nitrogen (N) assimilation by detecting 13C and 15N in proteins from microorganisms in the phototrophic microbial mats in a soda lake on the Cariboo Plateau, British Columbia, Canada. Metagenomic database used for protein identification and metagenome assembled genome membership had been previousl generated in Zorz et.al. (2019).

2025-10-22 | PXD059992 | Pride

Project description:eutrophic lake and pond sediments

| PRJNA906637 | ENA

freshwater sediment metagenome

Project description:metagenomics in eutrophic lake Donghu

| PRJNA909471 | ENA

Diel cycles of gene expression in oligotrophic, dystrophic, and eutrophic lakes to identify new gene functions and dissect carbon cycling metabolisms

Project description:Aquatic microbial communities contain a vast amount of genetic diversity and we have much to learn about how this manifests to functional diversity. Existing long-term time series data includes 16S tags, metagenomes, single amplified genomes (SAGs), and genomes from metagenomes (GFMs). Information about functional diversity and metabolic capabilities is often unavailable. The study sites include three lakes that are the subject of intense study through the North Temperate Lakes Long Term Ecological Research site: Sparkling Lake (oligotrophic), Lake Mendota (eutrophic), and Trout Bog Lake (dystrophic). The work (proposal:https://doi.org/10.46936/10.25585/60000947) conducted by the U.S. Department of Energy Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science User Facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231.

2023-11-02 | MSV000093272 | MassIVE

lake water metagenome

Project description:Eutrophic lake water microbial communities from Lake Mendota, Wisconsin, USA - GEODES118 metaG metagenome

| PRJNA368374 | ENA

lake water metagenome

Project description:Eutrophic lake water microbial communities from Lake Mendota, Wisconsin, USA - GEODES117 metaG metagenome

| PRJNA368373 | ENA

Project description:water metagenomics in eutrophic lake Donghu

| PRJNA910294 | ENA

lake water metagenome

Project description:Metagenome of Eutrophic Water

| PRJNA973269 | ENA