Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Surveying what’s flushed away

This month’s Genome Watch highlights the use of metagenomics to survey urban waste waters as a proxy for studying the gut microbiota in the local population and discusses how predictive models based on this data could inform public health.

The development of global-scale initiatives to characterize the human gut microbiome, like the Human Microbiome Project1 or the Metagenomics of the Human Intestinal Tract (MetaHIT) consortium2, is enabling us to better understand associations between its compositional variability and the development of diseases such as cancer, obesity and inflammatory bowel diseases. Most efforts to characterize the gut microbiota use faecal samples as the starting material, however, the increasing awareness of the microbiota in the built environment is expanding our potential to understand human health from a holistic perspective by acquiring samples from our environment.

Credit: Philip Patenall/Macmillan Publishers Limited

Today, more than a half of the human population live in cities, so studying microbial dynamics in urban environments is being considered for public health. Indeed, the MetaSUB consortium3 have performed extensive metagenomic surveys of public transport systems to analyse the spread of pathogens and antibiotic resistance.

Tons of human waste that pass through municipal sewage systems each day could be used to gain a broad overview of the gut microbiota of large populations living in urban areas. In a recent study, Newton et al.4 analyzed the waste waters of 71 cities in the United States using 16S ribosomal RNA (rRNA) amplicon sequencing and concluded that sewage can be used as a proxy for studying microbiomes in human populations. After filtering out reads belonging to non-faecal bacteria, the authors recaptured most (97%) of the oligotypes (taxonomic units of organisms that are classified according to primary DNA sequence) that are present in individual stool samples and found that the relative abundances of species correlated between sewage-derived and individual stool samples. Also, sewage bacteria were found to be a good predictor of the incidence of obesity. Specifically, higher Bacteroides spp. and lower Faecalibacterium spp. abundances were observed in cities with a higher percentage of individuals with obesity. These results suggest that gut bacteria present in sewage can be used as population-level biomarkers for demographics and public health.

Amplicon sequencing is useful for studying the diversity of microbial communities, but shotgun metagenomics enables their functions to be investigated. Hence, the strategy used by Newton et al.4 may be enhanced by integrating functional profiles inferred from shotgun metagenomics or whole-genome sequencing data, providing more information about virulence, antibiotic resistance or metabolic traits in the gut microbiota of human populations. Indeed, a recent study by Garza et al.5 reconstructed genome-scale metabolic models from over 1,500 human-associated bacteria and then integrated metagenomics data from different body sites to predict metabolomes. Using this approach, the authors recapitulated the observed differences between the oral, skin, faecal and vaginal microbiota from the relative counts of predicted metabolites. Additionally, consistent correlations were observed after comparing predicted and measured metabolomes, supporting the application of metagenome-guided modeling to infer phenotypic traits from diverse environments.

In summary, the development of methods to investigate gut bacteria in waste water using multiomics data could be useful for public health initiatives. The routine application of these approaches brings us closer to the concept of smart cities, which could detect environmental changes in real time, like the production of enterotoxins or antibiotic metabolites. Also, these tools could inform us of dietary habits, the use of drugs or any measurable parameter just from the composition and functional patterns of the environmental, human-associated microbiota.


  1. 1.

    Turnbaugh, P. J. et al. The human Microbiome Project. Nature 449, 804–810 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. 2.

    Li, J. et al. An integrated catalog of reference genes in the human gut microbiome. Nat. Biotechnol. 32, 834–841 (2014).

    Article  PubMed  CAS  Google Scholar 

  3. 3.

    Consortium, T. M. I. The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) International Consortium inaugural meeting report. Microbiome 4, 24 (2016).

    Article  Google Scholar 

  4. 4.

    Newton, R. J. et al. Sewage Reflects the Microbiomes of Human Populations. mBio 6, e02574–14 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. 5.

    Garza, D. R., Verk, M. C., Huynen, M. A. & Dutilh, B. E. Towards predicting the environmental metabolome from metagenomics with a mechanistic model. Nat. Microbiol. 3, 456–460 (2018).

    Article  PubMed  CAS  Google Scholar 

Download references

Author information



Corresponding authors

Correspondence to Gregorio Iraola or Nitin Kumar.

Ethics declarations

Competing interests

The authors declare no competing interests.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Iraola, G., Kumar, N. Surveying what’s flushed away. Nat Rev Microbiol 16, 456 (2018).

Download citation

Further reading


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing