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. 2023 Sep 15;11:207. doi: 10.1186/s40168-023-01636-5

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 1 — Conceptual diagram of study design. This study included a survey of the participants to gather information on the children/infants and observational data about each household. Household soil/dust and drinking water were collected from each house. Drinking water quality was tested on site. Fecal samples were collected from children, infants, and chickens. Household soil/dust was further analyzed via quantification of microbial source tracking (MST) and pathogenic marker genes. Chickens and a subset of household soil/dust samples were sent for 16S rRNA gene sequencing for microbial community analysis. Long-read metagenomic sequencing was completed for child/infant fecal samples. All inputs described were used in the final statistical analyses of the factors influencing the child/infant gut microbiomes and resistome