Persistent metagenomic signatures of early-life hospitalization and antibiotic treatment in the infant gut microbiota and resistome

Abstract

Hospitalized preterm infants receive frequent and often prolonged exposures to antibiotics because they are vulnerable to infection. It is not known whether the short-term effects of antibiotics on the preterm infant gut microbiota and resistome persist after discharge from neonatal intensive care units. Here, we use complementary metagenomic, culture-based and machine learning techniques to study the gut microbiota and resistome of antibiotic-exposed preterm infants during and after hospitalization, and we compare these readouts to antibiotic-naive healthy infants sampled synchronously. We find a persistently enriched gastrointestinal antibiotic resistome, prolonged carriage of multidrug-resistant Enterobacteriaceae and distinct antibiotic-driven patterns of microbiota and resistome assembly in extremely preterm infants that received early-life antibiotics. The collateral damage of early-life antibiotic treatment and hospitalization in preterm infants is long lasting. We urge the development of strategies to reduce these consequences in highly vulnerable neonatal populations.

Figure 1 |. Clinical variables predict microbiota diversity and composition.

a, Shannon diversity of all near-term (n=17) and preterm (n=41) infants in this study, by month of life. Box plots represent the first quartile, median, and third quartile of the data with whiskers extending to the last data point within 1.5× the interquartile range. b, Microbiota species and functional compositions inferred by MetaPhlAn2 of all near-term (n=17) and preterm (n=41) infants in this study. c, Microbiota species and functional compositions inferred by HUMAnN2 of all near-term (n=17) and preterm (n=41) infants in this study. d, Day of life is significantly associated with an increase in microbiota Shannon diversity, while vancomycin, ampicillin, meropenem, or cefepime treatment within the month prior to sampling is associated with significantly decreased species richness (***, p<0.001, ** p<0.01, * p<0.05; generalized linear mixed model with subject as random effect using 437 infant gut metagenomes.) Oxacillin was included in the model but was not significant after correction for multiple comparisons. Error bars indicate s.e. e, Shannon diversity is significantly lower in infants who have received >1 course of antibiotic treatment in the past month compared to infants who had not received antibiotic treatment during that time span (**** p<0.0001, ***, p<0.001, ** p<0.01, * p<0.05; two-sided Wilcoxon with Benjamini-Hochberg correction, n=212 samples). Box plots represent the first quartile, median, and third quartile of the data with whiskers extending to the last data point within 1.5× the interquartile range.

Figure 2 |. Partial architectural recovery of preterm infant gut microbiota following discharge from NICU.

a, Microbiota composition is distinct between near-term infants, preterm infants with early only antibiotic treatment, and preterm infants with early and subsequent antibiotic treatment (Bray-Curtis, p<0.001, Adonis, n=437 samples), but chronological day of life (DOL) is a major driver of microbiota composition. b, Fivefold cross-validation indicates that 50 variables are sufficient for random forests prediction of chronological age of near-term infants based on microbiota composition. Inset details vertex. Points indicate mean and error bars indicate s.e. computed over 100 iterations. c, The 50 most informative predictors to the random forests model. These species were included in a sparse model. Points indicate mean and error bars indicate s.e. computed over 100 iterations. d, The sparse random forests model accurately predicts near-term infant chronological age, but preterm infant chronological age is predicted to be less than actual age across numerous stages of development. Curves are loess regression fit to each group and shading depicts 95% confidence interval, n=437 samples. e, Preterm infant microbiota for age Z-score (MAZ) is significantly lower than that of near-term infants in the first month of life, indicating early microbiota immaturity (** p<0.01, **** p<0.0001, two-sided Wilcoxon, n=140 samples). f, Preterm infant MAZ is statistically indistinguishable from near-term infant by 12–15 months of life, indicating resolution of microbiota immaturity by this time point (p>0.05, two-sided Wilcoxon, n=65 samples). Box plots represent the first quartile, median, and third quartile of the data with whiskers extending to the last data point within 1.5× the interquartile range.

Figure 3 |. Preterm infants harbor an enriched gut resistome.

a, Amino acid identity between all functionally-selected ARGs and their top hit in CARD vs their top hit in the NCBI nr protein database, colored by class of antibiotic used for selection. Notably, ARGs recovered by fluoroquinolone and polymyxin selection have very low median identity to CARD. Box plots represent the first quartile, median, and third quartile of the data with whiskers extending to the last data point within 1.5× the interquartile range, n=879 ARGs. b, The most commonly predicted hosts of functionally-selected ARGs based on highest identity BLAST hit in the NCBI nr protein database. c, Gut resistome composition is distinct between near-term infants, preterm infants with early only antibiotic treatment, and preterm infants with early and subsequent antibiotic treatment (Bray-Curtis, p<0.001, Adonis, n=437 samples). d, Preterm infants had fewer unique ARGs encoded in their gut metagenomes than near-term infants. (* p<0.05, ** p<0.01 two-sided Wilcoxon, n=437 samples). Box plots represent the first quartile, median, and third quartile of the data with whiskers extending to the last data point within 1.5× the interquartile range. e, The cumulative resistome relative abundance was significantly higher in the gut microbiota of preterm infants with early and subsequent antibiotic treatment compared to both preterm infants with only early antibiotic treatment and near-term infants (* p<0.05, two-sided Wilcoxon, n=437 samples). Box plots represent the first quartile, median, and third quartile of the data with whiskers extending to the last data point within 1.5× the interquartile range. f, A random forests model trained on preterm infant gut resistome poorly predicts chronological age of near-term infants. Black line is linear regression line of day of life as predicted by the random forests model against the actual day of life (R²=0.62, n=437 samples) g, Relative abundance of 50 most informative resistance genes over the first months of life in near-term (left heatmap) and preterm (right heatmap) infants. Resistance genes are hierarchically clustered and listed to the right of the heatmaps. Colored bars above heatmaps correspond to colors in panels c-e. For canonical resistance genes, the CARD accession is displayed and for resistance genes functionally-selected in this study, the relevant selection information is listed.

Figure 4 |. Multidrug resistant Enterobacteriaceae lineages persist in infant gut microbiota.

Maximum likelihood core genome phylogenies of E. coli (a), Klebsiella spp. (c), and E. cloacae (e) isolated from infant stool. Annotations to the right of metadata indicate timepoints of isolation and sequence type (determined by in silico MLST) for E. coli and E. cloacae or species for Klebsiella. Persistent isolates are highlighted in red. Average nucleotide identity heat maps for E. coli (b), Klebsiella spp. (d), and E. cloacae (f) indicate that persistent isolates are isogenic, i.e., they share >99.997% nucleotide identity. Persistent isolate pairs are highlighted in red. g, Timeline of isolation of persistent Enterobacteriaceae from infant stool. Vertical bar indicates the day at which infants were discharged from the hospital. The first two infants displayed are preterm infants, while the third is a near-term infant.

Figure 5 |. Enduring damage to the preterm infant gut microbiota.

a, Support vector machine confusion matrix for classification of gestational age based on the species and ARGs present in the microbiota following discharge from the NICU or at matched timepoints in unhospitalized near-term infants. b, Twenty predictors most important to classification. A sparse model trained using only these twenty predictors was highly accurate (96.4% classification accuracy), a persistent metagenomic signature of preterm birth and associated hospitalization and antibiotic treatment.