Project description:Vietnam is one of the top shrimp producing and exporting countries in the world [1]. However, viral and bacterial epidemic diseases cause severe damages to shrimp farming, resulting in millions of US dollars losses annually [2]. Furthermore, inappropriate use of antibiotics in shrimp rearing lead to increased emergence of drug resistant pathogens [3]. Current practices for water quality control, mostly based on chemical and physical parameters; neglected biological criteria necessary for maintaining pond health. Ninh Thuan is a region situated in the South Central Coast of Vietnam. Due to its geographic location, a large part of this region is dedicated to shrimp (Litopenaeus vannamei) post-larvae production and rearing. This article presents a microbiome dataset from two water samples collected in a shrimp rearing pond in Ninh Thuan. We used Oxford Nanopore Technologies (ONT) for metagenomic sequencing of the samples to characterize microbial communities and antibiotic resistance profiles. The metagenome dataset generated will provide an understanding and comparison framework of the microbial diversity and functionality among shrimp ponds with potential application in health management and shrimp rearing industry.

| S-EPMC7264489 | biostudies-literature

Shotgun metagenomic dataset of early-onset preeclampsia study

Project description:Preeclampsia metagenome dataset

| PRJEB52189 | ENA

diagnostic metagenomics proficiency test dataset

Project description:Proficiency testing of metagenomics-based detection of food-borne pathogens using a complex artificial sequencing dataset

| PRJEB37463 | ENA

Shotgun metagenomics dataset of <i>Striga hermonthica</i>-infested maize (<i>Zea mays</i> L.) rhizospheric soil microbiome.

Project description:This dataset includes shotgun metagenomics sequencing of the rhizosphere microbiome of maize infested with Striga hermonthica from Mbuzini, South Africa, and Eruwa, Nigeria. The sequences were used for microbial taxonomic classification and functional categories in the infested maize rhizosphere. High throughput sequencing of the complete microbial community's DNA was performed using the Illumina NovaSeq 6000 technology. The average base pair count of the sequences were 5,353,206 bp with G+C content of 67%. The raw sequence data used for analysis is available in NCBI under the BioProject accession numbers PRJNA888840 and PRJNA889583. The taxonomic analysis was performed using Metagenomic Rapid Annotations using Subsystems Technology (MG-RAST). Bacteria had the highest taxonomic representation (98.8%), followed by eukaryotes (0.56%), and archaea (0.45%). This metagenome dataset provide valuable information on microbial communities associated with Striga-infested maize rhizosphere and their functionality. It can also be used for further studies on application of microbial resources for sustainable crop production in this region.

| S-EPMC10293916 | biostudies-literature

Microbial community of drinking water distribution system

Project description:Microbial community of drinking water distribution system Metagenome

| PRJNA522050 | ENA