A multi-marker assessment of sewage contamination in streams using human-associated indicator bacteria, human-specific viruses, and pharmaceuticals.

Human sewage contaminates waterways, delivering excess nutrients, pathogens, chemicals, and other toxic contaminants. Contaminants and various sewage indicators are measured to monitor and assess water quality, but these analytes vary in their representation of sewage contamination and the inferences about water quality they support. We measured the occurrence and concentration of multiple microbiological (n = 21) and chemical (n = 106) markers at two urban stream locations in Milwaukee, Wisconsin, USA over two years.

Anthropogenic particle concentrations and fluxes in an urban river are temporally variable and impacted by storm events.

Anthropogenic particles (AP), which include microplastics and other synthetic, semisynthetic, and anthropogenically modified materials, are pollutants of concern in aquatic ecosystems worldwide. Rivers are important conduits and retention sites for AP, and time series data on the movement of these particles in lotic ecosystems are needed to assess the role of rivers in the global AP cycle. Much research assessing AP pollution extrapolates stream loads based on single time point measurements, but lotic ecosystems are highly variable over time (e.

Patterns of Host-Associated Fecal Indicators Driven by Hydrology, Precipitation, and Land Use Attributes in Great Lakes Watersheds.

Fecal contamination from sewage and agricultural runoff is a pervasive problem in Great Lakes watersheds. Most work examining fecal pollution loads relies on discrete samples of fecal indicators and modeling land use. In this study, we made empirical measurements of human and ruminant-associated fecal indicator bacteria and combined these with hydrological measurements in eight watersheds ranging from predominantly forested to highly urbanized.

High levels of sewage contamination released from urban areas after storm events: A quantitative survey with sewage specific bacterial indicators.

Background: Past studies have demonstrated an association between waterborne disease and heavy precipitation, and climate change is predicted to increase the frequency of these types of intense storm events in some parts of the United States. In this study, we examined the linkage between rainfall and sewage contamination of urban waterways and quantified the amount of sewage released from a major urban area under different hydrologic conditions to identify conditions that increase human risk of exposure to sewage.

Methods And Findings: Rain events and low-flow periods were intensively sampled to quantify loads of sewage based on two genetic markers for human-associated indicator bacteria (human Bacteroides and Lachnospiraceae).

EcoBLMcrX, a classical modification-dependent restriction enzyme in Escherichia coli B: Characterization in vivo and in vitro with a new approach to cleavage site determination.

Here we characterize the modification-dependent restriction enzyme (MDE) EcoBLMcrX in vivo, in vitro and in its genomic environment. MDE cleavage of modified DNAs protects prokaryote populations from lethal infection by bacteriophage with highly modified DNA, and also stabilizes lineages by reducing gene import when sparse modification occurs in the wrong context. The function and distribution of MDE families are thus important.

Quantification of human-associated fecal indicators reveal sewage from urban watersheds as a source of pollution to Lake Michigan.

Sewage contamination of urban waterways from sewer overflows and failing infrastructure is a major environmental and public health concern. Fecal coliforms (FC) are commonly employed as fecal indicator bacteria, but do not distinguish between human and non-human sources of fecal contamination. Human Bacteroides and human Lachnospiraceae, two genetic markers for human-associated indicator bacteria, were used to identify sewage signals in two urban rivers and the estuary that drains to Lake Michigan.

Urban microbial ecology of a freshwater estuary of Lake Michigan.

Freshwater estuaries throughout the Great Lakes region receive stormwater runoff and riverine inputs from heavily urbanized population centers. While human and animal feces contained in this runoff are often the focus of source tracking investigations, non-fecal bacterial loads from soil, aerosols, urban infrastructure, and other sources are also transported to estuaries and lakes. We quantified and characterized this non-fecal urban microbial component using bacterial 16S rRNA gene sequences from sewage, stormwater, rivers, harbor/estuary, and the lake surrounding Milwaukee, WI, USA.

Systematically variable planktonic carbon metabolism along a land-to-lake gradient in a Great Lakes coastal zone.

During the summers of 2002-2013, we measured rates of carbon metabolism in surface waters of six sites across a land-to-lake gradient from the upstream end of drowned river-mouth Muskegon Lake (ML) (freshwater estuary) to 19 km offshore in Lake Michigan (LM) (a Great Lake). Despite considerable inter-year variability, the average rates of gross production (GP), respiration (R) and net production (NP) across ML (604 ± 58, 222 ± 22 and 381 ± 52 µg C L day, respectively) decreased steeply in the furthest offshore LM site (22 ± 3, 55 ± 17 and -33 ± 15 µg C Lday, respectively). Along this land-to-lake gradient, GP decreased by 96 ± 1%, whereas R only decreased by 75 ± 9%, variably influencing the carbon balance along this coastal zone.

Sewage reflects the microbiomes of human populations.

Unlabelled: Molecular characterizations of the gut microbiome from individual human stool samples have identified community patterns that correlate with age, disease, diet, and other human characteristics, but resources for marker gene studies that consider microbiome trends among human populations scale with the number of individuals sampled from each population. As an alternative strategy for sampling populations, we examined whether sewage accurately reflects the microbial community of a mixture of stool samples. We used oligotyping of high-throughput 16S rRNA gene sequence data to compare the bacterial distribution in a stool data set to a sewage influent data set from 71 U.