Skip to main content

Cindy H. Nakatsu

thumbnail
This dataset provides results of a targeted bacterial community metagenomic analysis of surface water, groundwater, and sand samples at Jeorse Park on Lake Michigan in East Chicago, Indiana. Seventy-two samples were collected from 6 sites in 2017. Samples were analyzed for the 16S ribosomal RNA (16S rRNA) gene (the S in 16S refers to the rate of sedimentation, in Svedberg units, of the RNA molecule in a centrifugal field), and one sample was excluded because it produced too few reads. The 16S rRNA gene is the most conserved of three rRNA genes (16S, 23S, and 5S) and is considered the most reliable for identification and taxonomic classification of bacterial species (Bouchet and others, 2008). Taxonomic analysis...
The data being released were part of a project funded by the Great Lakes Restoration Initiative (GLRI). This study sought to examine the influence of filter pore size (5.0 µm pre and 0.22 µm final filtration) on microbial communities and source-specific microbial source tracking (MST) markers at three locations along southern Lake Michigan: Racine, WI; Chicago, IL; and East Chicago, IN; between 2015 and 2017. In 2015, triplicate water samples were collected during three events, in 2016 individual water samples were collected during three events, and in 2017, individual water samples were collected one day a week for ten weeks between June and August. Samples were collected from twelve locations, two river, two river...
thumbnail
The data associated with the following data release were collected between 2016 and 2017 at three locations on Lake Michigan: Racine, WI; Chicago, IL; and East Chicago, IN. Individual water samples were collected one day a week for ten weeks between June and August. Samples were collected from eight specific sites made up of two river and six shoreline type environments. Sampling was completed at sites where various morphology (embayment, sand and sediment characteristics, size and shape) and hydrologic conditions (currents and waves) were present. Then samples were analyzed using microbial communities (metagenomic analysis), markers of contamination (microbial source tracking), and fecal indicator bacteria (E....
ScienceBase brings together the best information it can find about USGS researchers and offices to show connections to publications, projects, and data. We are still working to improve this process and information is by no means complete. If you don't see everything you know is associated with you, a colleague, or your office, please be patient while we work to connect the dots. Feel free to contact sciencebase@usgs.gov.