Temporal development and potential interactions between the gut microbiome and resistome in early childhood

ABSTRACT Antimicrobial resistance-associated infections have become a major threat to global health. The gut microbiome serves as a major reservoir of bacteria with antibiotic resistance genes; whereas, the temporal development of gut resistome during early childhood and the factors influencing it remain unclear. Moreover, the potential interactions between gut microbiome and resistome still need to be further explored. In this study, we found that antibiotic treatment led to destabilization of the gut microbiome and resistome structural communities, exhibiting a greater impact on the resistome than on the microbiome. The composition of the gut resistome at various developmental stages was influenced by the abundance and richness of different core microbes. First exposure to antibiotics led to a dramatic increase in the number of opportunistic pathogens carrying multidrug efflux pump encoding genes. Multiple factors could influence the gut microbiome and resistome formation. The data may provide new insights into early-life research. IMPORTANCE In recent years, the irrational or inappropriate use of antibiotics, an important life-saving medical intervention, has led to the emergence and increase of drug-resistant and even multidrug-resistant bacteria. It remains unclear how antibiotic exposure affects various developmental stages of early childhood and how gut core microbes under antibiotic exposure affect the structural composition of the gut resistome. In this study, we focused on early antibiotic exposure and analyzed these questions in detail using samples from infants at various developmental stages. The significance of our research is to elucidate the impact of early antibiotic exposure on the dynamic patterns of the gut resistome in children and to provide new insights for early-life studies.


Figure S3
The estimated variance in stability index per child in gut microbiome and resistome.
The estimated variance of (a) gut microbiota and (d) gut resistome for children of "With Antibiotics" and "Without Antibiotics" (mean ± SE) with at least two samples per child.The estimated variance of (b) gut microbiota and (e) gut resistome for children of "With Antibiotics" and "Without Antibiotics" (mean ± SE) with at least three samples in different age groups per child.The estimated variance of (c) gut microbiota and (f) gut resistome for children of "With Antibiotics" and "Without Antibiotics" (mean ± SE) with at least three samples in different age groups per child and number of antibiotic treatments no less than six in "With Antibiotics" children.
Table S3 Mediation result with acem value greater than zero and p value less than 0.05.

Figure S2
Figure S2In vitro experiments to investigate the proportion of antibiotic-resistant bacteria in E. coli flora under ampicillin pressure.

Figure S5
Figure S5 Development of ARGs belonging to antibiotic inactivation of children in the "With Antibiotics" group.Longitudinal changes (a) and proportion at age three (b) of ARGs belonging to antibiotic inactivation in the "With Antibiotics" children.

Figure S6
Figure S6 Average composition of gut microbiome of "With Antibiotics"(a) and "Without Antibiotics" (b) children during the first three years of age.

Figure S7
Figure S7 The realstionship of ARGs mechanism and species.(a) The mechanism of ARGs and the corresponding species were displayed; (b) A map showing antibiotic efflux pump genes from E. coli and other species;(c) The proportion of E. coli with efflux genes in different age groups.

Figure
Figure S9 ARG, species, and average phylum-level composition profiles of individual (E022960).(a) Abundance of ARG (TPM: Transcripts Per Kilobase Million) over time, together with the timing of individual antibiotic courses (colored dots) and diseases (colored triangles).(b) Relative abundance of species that most correlated with the ARG profiles.(c) Average phylum-level composition.

Figure S11
Figure S11ARG richness among bacterial species and phyla in 3-6 months.

Figure S12
Figure S12 ARG richness among bacterial species and phyla in 6-12 months.

Figure S13
Figure S13 ARG richness among bacterial species and phyla in 12-18 months.

Figure S14
Figure S14ARG richness among bacterial species and phyla in 18-36 months.

Figure S15
Figure S15Average phylum-level ARGs richness during five age groups.

Figure S16
Figure S16Log-transformed total ARG abundance among bacterial species and phyla in 0-3 months.

Figure S17
Figure S17Log-transformed total ARG abundance among bacterial species and phyla in 3-6 months.

Figure S18
Figure S18 Log-transformed total ARG abundance among bacterial species and phyla in 6-12 months.

Figure S19
Figure S19 Log-transformed total ARG abundance among bacterial species and phyla in 12-18 months.

Figure S20
Figure S20Log-transformed total ARG abundance among bacterial species and phyla in 18-36 months.

Figure S21
Figure S21Log-transformed total ARG abundance among bacterial species and phyla.

Figure S22
Figure S22Average phylum-level ARGs abundance during five age groups.

Figure S23
Figure S23 Ecological network of bacteria and ARGs.Correlations between ARGs and (a) E. coli or (b) Klebsiella were calculated through Spearman's rank correlation analysis.Only statistically significant correlations (P < 0.05) with r > 0.5 were plotted.The color of the node represents the ARGs of different antibiotic resistance mechanisms or species.a b

Table S4
The Procrustes analysis result of correlation between the gut microbiome and resistome for each age group.