Cargando…

MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Lin, Chen, Likai, Yu, Xiaoqian (Annie), Duvallet, Claire, Isazadeh, Siavash, Dai, Chengzhen, Park, Shinkyu, Frois-Moniz, Katya, Duarte, Fabio, Ratti, Carlo, Alm, Eric J., Ling, Fangqiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9534451/
https://www.ncbi.nlm.nih.gov/pubmed/36149894
http://dx.doi.org/10.1371/journal.pcbi.1010472
_version_ 1784802544607821824
author Zhang, Lin
Chen, Likai
Yu, Xiaoqian (Annie)
Duvallet, Claire
Isazadeh, Siavash
Dai, Chengzhen
Park, Shinkyu
Frois-Moniz, Katya
Duarte, Fabio
Ratti, Carlo
Alm, Eric J.
Ling, Fangqiong
author_facet Zhang, Lin
Chen, Likai
Yu, Xiaoqian (Annie)
Duvallet, Claire
Isazadeh, Siavash
Dai, Chengzhen
Park, Shinkyu
Frois-Moniz, Katya
Duarte, Fabio
Ratti, Carlo
Alm, Eric J.
Ling, Fangqiong
author_sort Zhang, Lin
collection PubMed
description The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa’s relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.
format Online
Article
Text
id pubmed-9534451
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-95344512022-10-06 MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes Zhang, Lin Chen, Likai Yu, Xiaoqian (Annie) Duvallet, Claire Isazadeh, Siavash Dai, Chengzhen Park, Shinkyu Frois-Moniz, Katya Duarte, Fabio Ratti, Carlo Alm, Eric J. Ling, Fangqiong PLoS Comput Biol Research Article The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa’s relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome. Public Library of Science 2022-09-23 /pmc/articles/PMC9534451/ /pubmed/36149894 http://dx.doi.org/10.1371/journal.pcbi.1010472 Text en © 2022 Zhang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Zhang, Lin
Chen, Likai
Yu, Xiaoqian (Annie)
Duvallet, Claire
Isazadeh, Siavash
Dai, Chengzhen
Park, Shinkyu
Frois-Moniz, Katya
Duarte, Fabio
Ratti, Carlo
Alm, Eric J.
Ling, Fangqiong
MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes
title MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes
title_full MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes
title_fullStr MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes
title_full_unstemmed MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes
title_short MicrobiomeCensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes
title_sort microbiomecensus estimates human population sizes from wastewater samples based on inter-individual variability in gut microbiomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9534451/
https://www.ncbi.nlm.nih.gov/pubmed/36149894
http://dx.doi.org/10.1371/journal.pcbi.1010472
work_keys_str_mv AT zhanglin microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes
AT chenlikai microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes
AT yuxiaoqianannie microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes
AT duvalletclaire microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes
AT isazadehsiavash microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes
AT daichengzhen microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes
AT parkshinkyu microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes
AT froismonizkatya microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes
AT duartefabio microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes
AT ratticarlo microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes
AT almericj microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes
AT lingfangqiong microbiomecensusestimateshumanpopulationsizesfromwastewatersamplesbasedoninterindividualvariabilityingutmicrobiomes