This dataset contains operational taxonomic units for epilithon eukaryotes (water samples): Approximate location of sampling sites was determined from maps to provide good spatial coverage of the Wolf River through to the Tamar River. Exact sites were determined in the field, considering accessibility and other logistics. The exact location of each sample site was determined using a Garmin GPS12. Three stones were taken from each of the 20 locations and epilithon removed from a defined area. Samples were kept in the cold and removed to the laboratory for analyses. DNA was extracted from all soil and epilithon samples using the MOBIO Powersoil 96 well DNA extraction kit. DNA was quality checked for purity and yield prior to submission for 454 pyrosequencing to assess both bacterial and eukaryotic biodiversity within each sample. Following bioinformatic sequence processing, sequencing were clustered into operational taxonomic units (OTU) and the data tables display the percentage of each OTU within each sample. Full details about this dataset can be found at https://doi.org/10.5285/18023db5-25d8-44f7-b291-61869f937367

In this mesocosm study, three types of wet wipes (plastic containing, and home and commercially compostable) colonised with E. coli were buried in beach sand and their degradation, tensile strength, and concentration of E. coli was quantified over 15 weeks. Wipes were firstly passed through a series of treatments to simulate their journey from the bathroom to the beach. Water characteristics (pH, salinity) of these water types were measured. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/19a8083b-afa4-40b9-91bf-7a529eea870d

This dataset contains operational taxonomic units for soil bacteria collected from various land use categories in the Wolf and Tamar catchments in South west England. A range of soils were targeted from the Tamar region comprising a range of land uses. Approximate location of sampling sites was determined from maps to provide good spatial coverage of the catchment. Exact sites were determined in the field, considering accessibility and other logistic, and soils taken. Full details about this dataset can be found at https://doi.org/10.5285/296ded8e-2c80-4a01-98cc-e71e3fa3fa1b

This dataset contains features detected by untargeted metabolomics analysis of paired cultures of 4 interacting Streptomyces bacteria. The bacteria were originally isolated from a nature reserve in Minnesota USA. Daily samples of spot cultures grown in adjacent pairs on solid ISP2 medium were taken from day 2 to 6 in triplicate. Metabolites were obtained by cold methanol extraction, and liquid chromatography-mass spectrometry data was collected in both positive and negative ionisation modes. This dataset contains the mass-to-charge (m/z) and retention time of identified peaks, and their ion intensity in each sample. The relative abundance of these identified features was later compared between pairs of interacting strains to gain insight into changes in their metabolism. This work was funded by NERC (NE/T010959/1) and National Science Foundation (USA, 1935458). Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/4921f306-5efa-4bf7-a15e-a157c2665889

This dataset contains operational taxonomic units for soil eukaryotes from the Wolf and Tamar catchments . A range of soils were targeted from the Tamar region comprising a range of land uses. Approximate location of sampling sites was determined from maps to provide good spatial coverage of the catchment. Exact sites were determined in the field, considering accessibility and other logistic, and soils taken. The exact location of each sample site was determined using a Garmin GPS12. Soil samples were kept in the cold and removed to the laboratory for analyses. Full details about this dataset can be found at https://doi.org/10.5285/4bf6228f-ce3d-449e-9438-c4b5c8291256

Antibiotic susceptibility tests are presented as the zone of inhibition using the disc-diffusion method, and categorized as resistant, intermediate or susceptible. DNA samples from antibiotic-resistant bacteria were analysed for the presence or absence of resistance genes using polymerase chain reaction (PCR). Laboratory analyses were conducted by trained staff at the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b). The aim of the study was to identify the antibiotic-susceptibility profiles and resistance genes of bacteria (Escherichia coli) obtained from humans, poultry and the environment. Bacterial isolates previously identified with resistance to third-generation cephalosporins or carbapenems were included in the analysis. Bacterial samples originated from rural households and poultry farms (broiler chickens) in Mirzapur, Tangail district; and urban food markets in Dhaka city, Bangladesh. Environmental samples included surface water, water supply, wastewater, soil, animal faeces (poultry and cattle) and solid waste. The survey was part of a wider research project, Spatial and Temporal Dynamics of Antimicrobial Resistance Transmission from the Outdoor Environment to Humans in Urban and Rural Bangladesh. The research was funded by NERC/BBSRC/MRC on behalf of the Antimicrobial Resistance Cross-Council Initiative award NE/N019555/1. Full details about this dataset can be found at https://doi.org/10.5285/dda6dd55-f955-4dd5-bc03-b07cc8548a3d

This dataset contains information about water quality based on faecal indicators at 15 lakes in the Greater Glasgow conurbation, Scotland. Lakes were sampled in winter (2016/17) and summer (2017) with faecal indicators being quantified at high spatial resolution (up to 60 points per lake depending on water body size) in sediment and water from each lake. Faecal indicators were quantified based on standard dilution, membrane filtration and incubation for water, and incubation in bacteria-specific broth, followed by plating and incubation for sediment extracts. Contextual information about water quality, water bird densities, and land cover in different buffer sizes is also provided for each lake. The data were collected to investigate how connectivity and stressors interact to determine biodiversity and ecosystem function in freshwaters. The work was supported by the Natural Environment Research Council grant NE/N006437/1 (Hydroscape: connectivity x stressor interactions in freshwater habitats) Full details about this dataset can be found at https://doi.org/10.5285/34df30f2-3163-4c11-8743-3732e49220fb

This dataset contains untargeted metabolomic profiles of paired cultures of 4 interacting Streptomyces bacteria. The bacteria were originally isolated from a nature reserve in Minnesota USA. Daily samples of spot cultures grown in adjacent pairs on solid ISP2 medium were taken from day 2 to 6 in triplicate. Metabolites were obtained by cold methanol extraction, and liquid chromatography-mass spectrometry data was collected in both positive and negative ionisation modes. This dataset contains raw LC-MS (liquid chromatography mass spectrometry) data converted to the open-source .mzML format, of each sample run in both positive and negative ionisation modes. This includes, mass-to-charge measurements, elution time, and ion count intensity. These data were collected to investigate how the metabolism of the interacting strains changes in response to neighbouring bacterial cultures. This work was funded by NERC (NE/T010959/1) and National Science Foundation (USA, 1935458). Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/475d6c02-45bb-4ac4-a31a-4a23c7c9cb2e

This dataset contains information about water quality based on faecal indicators at eighteen lakes in each of three lake districts: - Greater Glasgow conurbation, Scotland - Cumbria, NW England - Norfolk, E England. Lakes were sampled once in each of three seasons (spring, summer and autumn) in either 2016 (Norfolk) or 2017 (Cumbria and Greater Glasgow) with faecal indicators being quantified at three discrete sampling stations in each lake (>50m apart) and at three points at each station (i.e. nine samples per lake per sampling date). Faecal indicators were quantified based on standard dilution, membrane filtration and incubation, followed by colony counting. The data were collected to investigate the fine scale connectivity between Faecal Indicator Organisms (FIO) densities within water bodies and diffuse and point source inputs from the adjacent catchment and from biological vectors. They also provide an indication of the relative sources of variation in reported concentrations that is relevant for environmental regulatory purposes. The work was supported by the Natural Environment Research Council grant NE/N006437/1 (Hydroscape: connectivity x stressor interactions in freshwater habitats). Full details about this dataset can be found at https://doi.org/10.5285/5f988cd4-479d-4e35-8835-42f80ebc1698

The data comprises both compositional data and growth assay data from an experiment of wild bacterial communities in Wytham Woods, Oxford. The communities live in puddles of water in tree-holes formed by the roots of beech trees. We manipulated the pH of tree-holes during the experiment for comparison with control tree-holes that were unmanipulated. Compositional data comprises the frequency of different Amplicon Sequencing Variants and derived measures of species diversity for samples taken over time (up to 12 weeks from the start of the experiment). The growth assay data comprises measurements of growth rates of community samples and isolates back in the laboratory, when grown on beech tea media manipulated to have different pHs. Full details about this dataset can be found at https://doi.org/10.5285/9d64f2bd-2918-416f-b08c-3369edbc1b30