ARG, intI1, fecal indicator bacteria PCR data. This dataset is associated with the following publication: Keely, S., N. Brinkman, E. Wheaton, M. Jahne, S. Siefring, M. Varma, R. Hill, S. Leibowitz, R. Martin, J. Garland, and R. Haugland. Geospatial Patterns of Antimicrobial Resistance Genes in the US EPA National Rivers and Streams Assessment Survey. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 56(21): 14960–14971, (2022).

A table (DP_OTU.xlsx) contains rows as OTUs, columns as samples, and entries representing the abundance of each OTU. This dataset is associated with the following publication: Gomez-Alvarez, V., H. Liu, J. Pressman, and D. Wahman. Metagenomic Profile of Microbial Communities in a Drinking Water Storage Tank Sediment after Sequential Exposure to Monochloramine, Free Chlorine, and Monochloramine. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 1(5): 1283-1294, (2021).

Continuous monitoring of bacterial community structure in the ISS-Kibo. This data contains numerous sequence reads of 16S rRNA gene fragments.

This repository holds genome assemblies for Staphylococcus, Burkholderia, and Ralstonia bacterial isolates isolated from the ISS between the years of 2006-2015. Information on the overall microbial isolation effort is stored under NASA's Life Science Data Archive experiment 13823 (https://lsda.jsc.nasa.gov/Experiment/exper/13823). For the genomes presented here, isolates were received from NASA's Johnson Space Center and their genomes were sequenced and assembled thanks to NASA Space Biology awards to Michael D. Lee (NNH16ZTT001N-MOBE) and Aubrie O'Rourke (80NSSC17K0035).

Background PCR amplification of bacterial 16S rRNA genes provides the most comprehensive and flexible means of sampling bacterial communities. Sequence analysis of these cloned fragments can provide a qualitative and quantitative insight of the microbial population under scrutiny although this approach is not suited to large-scale screenings. Other methods, such as denaturing gradient gel electrophoresis, heteroduplex or terminal restriction fragment analysis are rapid and therefore amenable to field-scale experiments. A very recent addition to these analytical tools is represented by microarray technology. Results Here we present our results using a Universal DNA Microarray approach as an analytical tool for bacterial discrimination. The proposed procedure is based on the properties of the DNA ligation reaction and requires the design of two probes specific for each target sequence. One oligo carries a fluorescent label and the other a unique sequence (cZipCode or complementary ZipCode) which identifies a ligation product. Ligated fragments, obtained in presence of a proper template (a PCR amplified fragment of the 16s rRNA gene) contain either the fluorescent label or the unique sequence and therefore are addressed to the location on the microarray where the ZipCode sequence has been spotted. Such an array is therefore "Universal" being unrelated to a specific molecular analysis. Here we present the design of probes specific for some groups of bacteria and their application to bacterial diagnostics. Conclusions The combined use of selective probes, ligation reaction and the Universal Array approach yielded an analytical procedure with a good power of discrimination among bacteria.

This repository includes the raw data, analysis code, and results of a systematic analysis of natural transformation (i.e., horizontal gene transfer; HGT) of bacteria in a naturally occurring microbiome (human stool) following exposure to free extracellular DNA (eDNA) that coded for antibiotic resistance. A full description of this effort is available in the associated publication.

This repository includes the raw data, analysis code, and results of a systematic analysis of natural transformation (i.e., horizontal gene transfer; HGT) of bacteria in a naturally occurring microbiome (human stool) following exposure to free extracellular DNA (eDNA) that coded for antibiotic resistance. A full description of this effort is available in the associated publication.

Selected bacterial, and antibiotic resistance genes sul and INTI1 concentrations by qPCR assays, and ASV tables of bacterial communities growing in biofilms incubated in river -and wastewater treatment plant effluent amended -river water. This dataset is associated with the following publication: Eytcheson, S., S. Brown, H. Wu, C. Nietch, P. Weaver, J. Darling, E. Pilgrim, T. Purucker, and M. Molina. Assessment of Emerging Pathogens and Antibiotic Resistance Genes in the Biofilm of Microplastics Incubated Under a Wastewater Discharge Simulation. Environmental Microbiology. Wiley-Blackwell Publishing, Hoboken, NJ, USA, 27(5): e70103, (2025).

Dataset for a year long watershed study in southwestern Ohio to analyze antimicrobial resistant bacteria (E. coli, Enterococcus, and Salmonella) in surface waters and wastewater treatment plant effluent.

Data were collected in August and September 2015 for analysis of bacteria communities of the Grand Calumet River and associated shorelines. Water samples were collected on three occasions corresponding to one rain-related (wet) events and two non-rain (dry) events. Water samples were collected in the Grand Calumet River, at the mouth of the river, at offshore locations around the peninsular impoundment and at shoreline locations: Jeorse Park (East Chicago, Indiana), Whihala (Whiting, Indiana), and 63rd Street (Chicago, Illinois) beaches. Samples were collected in triplicate, and water was filtered at the USGS Lake Michigan Ecological Research Station. After DNA extraction, samples were analyzed using 16S rRNA sequencing using Illumina sequencing. Taxonomic identification was assigned for communities in each sample, at multiple taxonomic levels (Kingdom, Phylum, Class, Order, Family, Genus). Water was also analyzed for E. coli bacteria and turbidity, at the USGS laboratory. Hydrological conditions corresponding to the days of sample collection were obtained from publicly available USGS information (NWIS-National Water Information System). The coordinate file includes information regarding sampling locations and their corresponding latitude and longitudes. The Data file include E. coli densities, laboratory turbidity measurements, and NWIS hydrological data. The raw metagenomic data can be accessed at the NCBI repository under the biproject accession PRJNA541325: https://www.ncbi.nlm.nih.gov/sra/PRJNA541325