Evidence map›Paper›PMID 23475306›Full record

ArticleMicrobial ecology2013

A microbial signature approach to identify fecal pollution in the waters off an urbanized coast of Lake Michigan.

Ryan J Newton, Melinda J Bootsma, Hilary G Morrison, Mitchell L Sogin, Sandra L McLellan

Abstract read
In one paragraph

Article in Microbial ecology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed, 1 pooled it
7.8field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

77 citing papers in PubMed, 1 synthesis or guideline pooled it, 230 citations in OpenAlex.

  1. Pooled it
  2. Dynamics and virulence ofApplied and environmental microbiology · 2026
    Article
  3. Review
  4. Article
  5. Article
  6. An Urban Stormwater Contaminant Signature: Defining Priority Contaminants for Urban Stormwater Research.Water environment research : a research publication of the Water Environment Federation · 2025
    Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. The Prevalence ofPathogens (Basel, Switzerland) · 2022
    Review
  17. Article
  18. Article
  19. Article
  20. Article

17 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Ryan J NewtonGreat Lakes WATER Institute, School of Freshwater Sciences, University of Wisconsin-Milwaukee, 600 E. Greenfield Ave, Milwaukee, WI 53204, USA.
Melinda J Bootsma
Hilary G Morrison
Mitchell L Sogin
Sandra L McLellan
University of Wisconsin–Milwaukee · USMarine Biological Laboratory · US

Funding

Microbial Community Profiles Identify New Indicators of Waterborne PathogensR01AI091829 · NIAID · UNIVERSITY OF WISCONSIN MILWAUKEE · PI MCLELLAN, SANDRA L. · 2011 to 2019
$3.1M
NIAID NIH HHS 1R01AI091829-01A1NIAID NIH HHS R01 AI091829
6 · The paper itself

Abstract

Urban coasts receive watershed drainage from ecosystems that include highly developed lands with sewer and stormwater infrastructure. In these complex ecosystems, coastal waters are often contaminated with fecal pollution, where multiple delivery mechanisms that often contain multiple fecal sources make it difficult to mitigate the pollution. Here, we exploit bacterial community sequencing of the V6 and V6V4 hypervariable regions of the bacterial 16S rRNA gene to identify bacterial distributions that signal the presence of sewer, fecal, and human fecal pollution. The sequences classified to three sewer infrastructure-associated bacterial genera, Acinetobacter, Arcobacter, and Trichococcus, and five fecal-associated bacterial families, Bacteroidaceae, Porphyromonadaceae, Clostridiaceae, Lachnospiraceae, and Ruminococcaceae, served as signatures of sewer and fecal contamination, respectively. The human fecal signature was determined with the Bayesian source estimation program SourceTracker, which we applied to a set of 40 sewage influent samples collected in Milwaukee, WI, USA to identify operational taxonomic units (≥ 97 % identity) that were most likely of human fecal origin. During periods of dry weather, the magnitudes of all three signatures were relatively low in Milwaukee's urban rivers and harbor and nearly zero in Lake Michigan. However, the relative contribution of the sewer and fecal signature frequently increased to > 2 % of the measured surface water communities following sewer overflows. Also during combined sewer overflows, the ratio of the human fecal pollution signature to the fecal pollution signature in surface waters was generally close to that of sewage, but this ratio decreased dramatically during dry weather and rain events, suggesting that nonhuman fecal pollution was the dominant source during these weather-driven scenarios. The qPCR detection of two human fecal indicators, human Bacteroides and Lachno2, confirmed the urban fecal footprint in this ecosystem extends to at least 8 km offshore.

Indexed as

BacteriaDNA, BacterialEcosystemEnvironmental MonitoringFecesHumansLakesMichiganRNA, Ribosomal, 16SSewageUrbanizationWater PollutionDNA, BacterialRNA, Ribosomal, 16SSewage

Identifiers

PMID23475306
PMCPMC4084971
OpenAlexW2038023694

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.