title: Sewage reflects the microbiomes of human populations.
abstract: 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.S. cities. On average, only 15% of sewage sample sequence reads were attributed to human fecal origin, but sewage recaptured most (97%) human fecal oligotypes. The most common oligotypes in stool matched the most common and abundant in sewage. After informatically separating sequences of human fecal origin, sewage samples exhibited ~3× greater diversity than stool samples. Comparisons among municipal sewage communities revealed the ubiquitous and abundant occurrence of 27 human fecal oligotypes, representing an apparent core set of organisms in U.S. populations. The fecal community variability among U.S. populations was significantly lower than among individuals. It clustered into three primary community structures distinguished by oligotypes from either: Bacteroidaceae, Prevotellaceae, or Lachnospiraceae/Ruminococcaceae. These distribution patterns reflected human population variation and predicted whether samples represented lean or obese populations with 81 to 89% accuracy. Our findings demonstrate that sewage represents the fecal microbial community of human populations and captures population-level traits of the human microbiome.
  
  
  OBJECTIVE
  The gut microbiota serves important functions in healthy humans. Numerous projects aim to define a healthy gut microbiome and its association with health states. However, financial considerations and privacy concerns limit the number of individuals who can be screened. By analyzing sewage from 71 cities, we demonstrate that geographically distributed U.S. populations share a small set of bacteria whose members represent various common community states within U.S. adults. Cities were differentiated by their sewage bacterial communities, and the community structures were good predictors of a city's estimated level of obesity. Our approach demonstrates the use of sewage as a means to sample the fecal microbiota from millions of people and its potential to elucidate microbiome patterns associated with human demographics.
authors.affiliation: School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA.
authors.forename: Ryan J
authors.initials: RJ
authors.lastname: Newton
authors.affiliation: School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA.
authors.forename: Sandra L
authors.initials: SL
authors.lastname: McLellan
authors.affiliation: School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA.
authors.forename: Deborah K
authors.initials: DK
authors.lastname: Dila
authors.affiliation: Josephine Bay Paul Center, Marine Biological Laboratory, Woods Hole, Massachusetts, USA.
authors.forename: Joseph H
authors.initials: JH
authors.lastname: Vineis
authors.affiliation: Josephine Bay Paul Center, Marine Biological Laboratory, Woods Hole, Massachusetts, USA.
authors.forename: Hilary G
authors.initials: HG
authors.lastname: Morrison
authors.affiliation: Josephine Bay Paul Center, Marine Biological Laboratory, Woods Hole, Massachusetts, USA.
authors.forename: A Murat
authors.initials: AM
authors.lastname: Eren
authors.affiliation: Josephine Bay Paul Center, Marine Biological Laboratory, Woods Hole, Massachusetts, USA mitchellsogin@gmail.com.
authors.forename: Mitchell L
authors.initials: ML
authors.lastname: Sogin
mesh_terms: D058448:Biota; D002947:Cities; D016000:Cluster Analysis; D004269:DNA, Bacterial / Q000737:chemistry / Q000235:genetics; D004275:DNA, Ribosomal / Q000737:chemistry / Q000235:genetics; D006801:Humans; D008969:Molecular Sequence Data; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D017422:Sequence Analysis, DNA; D012722:Sewage / Q000382:microbiology*; D014481:United States
chemical_list: D004269:DNA, Bacterial; D004275:DNA, Ribosomal; D012336:RNA, Ribosomal, 16S; D012722:Sewage