Household environment and animal fecal contamination are critical modifiers of the gut microbiome and resistome in young children from rural Nicaragua

Study information

Reviewed Marked as Reviewed by Svetlana up on 2024-7-5

study design

cross-sectional observational, not case-control

Citation

PMID PubMed identifier for scientific articles.

37715296

DOI Digital object identifier for electronic documents.

10.1186/s40168-023-01636-5

URI

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503196/

Authors

Mills M, Lee S, Piperata BA, Garabed R, Choi B, Lee J

Journal

Microbiome

Year

2023

Keywords:

Animals, Breastfeeding duration, Dirt floor, E. coli as antibiotic resistance host, Microbial source tracking, Multi-drug resistance, One Health

BACKGROUND: Early life plays a vital role in the development of the gut microbiome and subsequent health. While many factors that shape the gut microbiome have been described, including delivery mode, breastfeeding, and antibiotic use, the role of household environments is still unclear. Furthermore, the development of the gut antimicrobial resistome and its role in health and disease is not well characterized, particularly in settings with water insecurity and less sanitation infrastructure. RESULTS: This study investigated the gut microbiome and resistome of infants and young children (ages 4 days-6 years) in rural Nicaragua using Oxford Nanopore Technology's MinION long-read sequencing. Differences in gut microbiome diversity and antibiotic resistance gene (ARG) abundance were examined for associations with host factors (age, sex, height for age z-score, weight for height z-score, delivery mode, breastfeeding habits) and household environmental factors (animals inside the home, coliforms in drinking water, enteric pathogens in household floors, fecal microbial source tracking markers in household floors). We identified anticipated associations of higher gut microbiome diversity with participant age and vaginal delivery. However, novel to this study were the significant, positive associations between ruminant and dog fecal contamination of household floors and gut microbiome diversity. We also identified greater abundance of potential pathogens in the gut microbiomes of participants with higher fecal contamination on their household floors. Path analysis revealed that water quality and household floor contamination independently and significantly influenced gut microbiome diversity when controlling for age. These gut microbiome contained diverse resistome, dominated by multidrug, tetracycline, macrolide/lincosamide/streptogramin, and beta-lactam resistance. We found that the abundance of ARGs in the gut decreased with age. The bacterial hosts of ARGs were mainly from the family Enterobacteriaceae, particularly Escherichia coli. CONCLUSIONS: This study identified the role of household environmental contamination in the developing gut microbiome and resistome of young children and infants with a One Health perspective. We found significant relationships between host age, gut microbiome diversity, and the resistome. Understanding the impact of the household environment on the development of the resistome and microbiome in early life is essential to optimize the relationship between environmental exposure and human health. Video Abstract.

Experiment 1

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Reviewed Marked as Reviewed by Svetlana up on 2024-7-5

Curated date: 2024/03/23

Curator: Aishat

Revision editor(s): Aishat, Scholastica

Subjects

Location of subjects: Nicaragua

Host species Species from which microbiome was sampled. Contact us to have more species added.: Homo sapiens

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: Gut microbiome measurement Gut microbiome measurement,gut microbiome measurement

Group 0 name Corresponds to the control (unexposed) group for case-control studies: Infants

Group 1 name Corresponds to the case (exposed) group for case-control studies: Children

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Participants between 2.0 – 6.0 years of age

Group 0 sample size Number of subjects in the control (unexposed) group: 26

Group 1 sample size Number of subjects in the case (exposed) group: 31

Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): None

Lab analysis

Sequencing type: WMS

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: Not specified

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Nanopore

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).: relative abundances

Statistical test: LEfSe

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.05

MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: Yes

LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool: 2

Alpha Diversity

Pielou Quantifies how equal the community is numerically: increased

Shannon Estimator of species richness and species evenness: more weight on species richness: increased

Signature 1

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Curated date: 2024/03/23

Curator: Aishat

Revision editor(s): Aishat, Scholastica

Source: Figure 2b

Description: Bacterial families with different abundances in children versus infants identified with linear discriminant analysis effect size (LEfSe)

Abundance in Group 1: increased abundance in Children

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Lachnospiraceae
Prevotellaceae
Spirochaetaceae
Oscillospiraceae

Revision editor(s): Aishat, Scholastica

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Source: Figure 2b

Description: Bacterial families with different abundances in children versus infants identified with linear discriminant analysis effect size (LEfSe)

Abundance in Group 1: decreased abundance in Children

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Bacteroidaceae
Bifidobacteriaceae
Enterobacteriaceae

Revision editor(s): Aishat, Scholastica

Experiment 2

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Curated date: 2024/07/05

Curator: Scholastica

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Differences from previous experiment shown

Subjects

Group 0 name Corresponds to the control (unexposed) group for case-control studies: No - antibiotics

Group 1 name Corresponds to the case (exposed) group for case-control studies: Yes - antibiotics

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Infants and young children (ages 4 days - 6 years) in rural Nicaragua who had ever received antibiotics

Group 0 sample size Number of subjects in the control (unexposed) group: 11

Group 1 sample size Number of subjects in the case (exposed) group: 11

Lab analysis

Statistical Analysis

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Source: Supplementary Figure S5

Description: Differentially abundant taxa identified in children and infants who had compared to those who had not received antibiotics using linear discriminant analysis effect size (LEfSe).

Abundance in Group 1: decreased abundance in Yes - antibiotics

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Parvimonas micra
Parvimonas
Weissella
Megamonas hypermegale

Revision editor(s): Scholastica