Antibiotic-driven intestinal dysbiosis in pediatric short bowel syndrome is associated with persistently altered microbiome functions and gut-derived bloodstream infections

Robert Thänert, Anna Thänert, Jocelyn Ou, Adam Bajinting, Carey-Ann D Burnham, Holly J Engelstad, Maria E Tecos, I Malick Ndao, Carla Hall-Moore, Colleen Rouggly-Nickless, Mike A Carl, Deborah C Rubin, Nicholas O Davidson, Phillip I Tarr, Barbara B Warner, Gautam Dantas, Brad W Warner, Robert Thänert, Anna Thänert, Jocelyn Ou, Adam Bajinting, Carey-Ann D Burnham, Holly J Engelstad, Maria E Tecos, I Malick Ndao, Carla Hall-Moore, Colleen Rouggly-Nickless, Mike A Carl, Deborah C Rubin, Nicholas O Davidson, Phillip I Tarr, Barbara B Warner, Gautam Dantas, Brad W Warner

Abstract

Surgical removal of the intestine, lifesaving in catastrophic gastrointestinal disorders of infancy, can result in a form of intestinal failure known as short bowel syndrome (SBS). Bloodstream infections (BSIs) are a major challenge in pediatric SBS management. BSIs require frequent antibiotic therapy, with ill-defined consequences for the gut microbiome and childhood health. Here, we combine serial stool collection, shotgun metagenomic sequencing, multivariate statistics and genome-resolved strain-tracking in a cohort of 19 patients with surgically-induced SBS to show that antibiotic-driven intestinal dysbiosis in SBS enriches for persistent intestinal colonization with BSI causative pathogens in SBS. Comparing the gut microbiome composition of SBS patients over the first 4 years of life to 19 age-matched term and 18 preterm controls, we find that SBS gut microbiota diversity and composition was persistently altered compared to controls. Commensals including Ruminococcus, Bifidobacterium, Eubacterium, and Clostridium species were depleted in SBS, while pathobionts (Enterococcus) were enriched. Integrating clinical covariates with gut microbiome composition in pediatric SBS, we identified dietary and antibiotic exposures as the main drivers of these alterations. Moreover, antibiotic resistance genes, specifically broad-spectrum efflux pumps, were at a higher abundance in SBS, while putatively beneficial microbiota functions, including amino acid and vitamin biosynthesis, were depleted. Moreover, using strain-tracking we found that the SBS gut microbiome harbors BSI causing pathogens, which can persist intestinally throughout the first years of life. The association between antibiotic-driven gut dysbiosis and enrichment of intestinal pathobionts isolated from BSI suggests that antibiotic treatment may predispose SBS patients to infection. Persistence of pathobionts and depletion of beneficial microbiota and functionalities in SBS highlights the need for microbiota-targeted interventions to prevent infection and facilitate intestinal adaptation.

Keywords: Short bowel syndrome; antibiotics; bloodstream infections; functional profiling; intestinal dysbiosis; microbiota; shotgun metagenomics; strain-tracking.

Conflict of interest statement

No potential conflict of interest was reported by the author(s).

Figures

Figure 1.
Figure 1.
Taxonomic composition of the SBS microbiota compared to preterm and term controls. (a) Shannon diversity indices of the gut microbiota of SBS patients (salmon), preterm (purple) and term controls (teal) by year of life (n = 159). Loess regression lines with 95% confidence interval shading are drawn. All P-values are two-tailed, from longitudinal maximum-likelihood GLMMs Tukey-adjusted for multiple comparisons. (b) Boxplot of Shannon diversity of SBS gut microbiota with or without exposure to antibiotics in the month prior to sampling (n = 51, P = .042, longitudinal maximum-likelihood GLMM FDR corrected). (c) Principal Coordinate Analysis (PCoA) plot of species based on the Bray–Curtis dissimilarity index for all samples (n = 159), colored by day of life. (d) Species enriched (salmon) or depleted (teal) in SBS patients compared to term controls as determined via MaAsLin2. (Top) Number of species significantly depleted or enriched in SBS or term controls plotted against determined binned effect sizes. (Bottom) Top 20% of species depleted or enriched in SBS patients compared to term controls selected based on determined effect size
Figure 1.
Figure 1.
Taxonomic composition of the SBS microbiota compared to preterm and term controls. (a) Shannon diversity indices of the gut microbiota of SBS patients (salmon), preterm (purple) and term controls (teal) by year of life (n = 159). Loess regression lines with 95% confidence interval shading are drawn. All P-values are two-tailed, from longitudinal maximum-likelihood GLMMs Tukey-adjusted for multiple comparisons. (b) Boxplot of Shannon diversity of SBS gut microbiota with or without exposure to antibiotics in the month prior to sampling (n = 51, P = .042, longitudinal maximum-likelihood GLMM FDR corrected). (c) Principal Coordinate Analysis (PCoA) plot of species based on the Bray–Curtis dissimilarity index for all samples (n = 159), colored by day of life. (d) Species enriched (salmon) or depleted (teal) in SBS patients compared to term controls as determined via MaAsLin2. (Top) Number of species significantly depleted or enriched in SBS or term controls plotted against determined binned effect sizes. (Bottom) Top 20% of species depleted or enriched in SBS patients compared to term controls selected based on determined effect size
Figure 2.
Figure 2.
Functional composition of the SBS microbiota throughout the first years of life. (a) Principal Coordinate Analysis (PCoA) plot of functional pathway abundance based on the Bray–Curtis dissimilarity index for all samples (n = 159), colored by day of life. (b) Pathways significantly enriched (salmon) or depleted (teal) in SBS patients aggregated into functional categories based on MetaCyc hierarchy compared to term controls as determined via MaAsLin2. (Left and right) Number of pathways significantly depleted or enriched in SBS or term controls within each functional category plotted against determined binned effect sizes. (Middle) Sum of all depleted or enriched pathways within each functional category grouped by depletion and enrichment status in SBS patients compared to term controls. (c) Amino acid synthesis or degradation pathways significantly enriched (salmon) or depleted (teal) in SBS patients compared to term controls as determined via MaAsLin2
Figure 2.
Figure 2.
Functional composition of the SBS microbiota throughout the first years of life. (a) Principal Coordinate Analysis (PCoA) plot of functional pathway abundance based on the Bray–Curtis dissimilarity index for all samples (n = 159), colored by day of life. (b) Pathways significantly enriched (salmon) or depleted (teal) in SBS patients aggregated into functional categories based on MetaCyc hierarchy compared to term controls as determined via MaAsLin2. (Left and right) Number of pathways significantly depleted or enriched in SBS or term controls within each functional category plotted against determined binned effect sizes. (Middle) Sum of all depleted or enriched pathways within each functional category grouped by depletion and enrichment status in SBS patients compared to term controls. (c) Amino acid synthesis or degradation pathways significantly enriched (salmon) or depleted (teal) in SBS patients compared to term controls as determined via MaAsLin2
Figure 3.
Figure 3.
Resistome composition in SBS throughout the first years of life. (a) ARG abundance measured in RPKM within the microbiome of SBS patients (salmon), preterm (purple) and term controls (teal) by year of life (n = 159). Loess regression lines with 95% confidence interval shading are drawn. All P-values are two-tailed, from longitudinal maximum-likelihood GLMMs Tukey-adjusted for multiple comparisons. (b) Boxplot of ARG abundance measured in RPKM within the microbiome of SBS patients with or without exposure to enteral nutrition at sampling (n = 51, P = .011, longitudinal maximum-likelihood GLMM). (c) Principal Coordinate Analysis (PCoA) plot of ARG abundance profiles based on the Bray–Curtis dissimilarity index for all samples (n = 159), colored by day of life
Figure 3.
Figure 3.
Resistome composition in SBS throughout the first years of life. (a) ARG abundance measured in RPKM within the microbiome of SBS patients (salmon), preterm (purple) and term controls (teal) by year of life (n = 159). Loess regression lines with 95% confidence interval shading are drawn. All P-values are two-tailed, from longitudinal maximum-likelihood GLMMs Tukey-adjusted for multiple comparisons. (b) Boxplot of ARG abundance measured in RPKM within the microbiome of SBS patients with or without exposure to enteral nutrition at sampling (n = 51, P = .011, longitudinal maximum-likelihood GLMM). (c) Principal Coordinate Analysis (PCoA) plot of ARG abundance profiles based on the Bray–Curtis dissimilarity index for all samples (n = 159), colored by day of life
Figure 4.
Figure 4.
Gut-persisting pathobionts can cause repeated episodes of BSI in SBS. (a) E. faecalis persists in patient SBS 07 causing two BSI over 3 years of life. (Top) Relative abundance of E. faecalis in stools (red) by year of life. Other species are depicted in gray. Schematic of sample collection and BSI events is shown on top. (Bottom) Phylogenetic relatedness of BSI isolates and metagenomic strains based on core SNPs as assessed by StrainSifter. Branch tip colors indicate BSI isolates (red), SBS (brown) and preterm (peach), or term (teal) stools. (b) K. pneumoniae found in a stool of patient SBS 01 concurrently causes a BSI. (Top) Relative abundance of K. pneumoniae in stools (green) by year of life. Other species are depicted in gray. Schematic of sample collection and BSI events is shown on top. (Bottom) Phylogenetic relatedness of BSI isolates and metagenomic strains based on core SNPs as assessed by StrainSifter. Branch tip colors indicate BSI isolates (red), SBS (brown) and preterm (peach), or term (teal) stools
Figure 4.
Figure 4.
Gut-persisting pathobionts can cause repeated episodes of BSI in SBS. (a) E. faecalis persists in patient SBS 07 causing two BSI over 3 years of life. (Top) Relative abundance of E. faecalis in stools (red) by year of life. Other species are depicted in gray. Schematic of sample collection and BSI events is shown on top. (Bottom) Phylogenetic relatedness of BSI isolates and metagenomic strains based on core SNPs as assessed by StrainSifter. Branch tip colors indicate BSI isolates (red), SBS (brown) and preterm (peach), or term (teal) stools. (b) K. pneumoniae found in a stool of patient SBS 01 concurrently causes a BSI. (Top) Relative abundance of K. pneumoniae in stools (green) by year of life. Other species are depicted in gray. Schematic of sample collection and BSI events is shown on top. (Bottom) Phylogenetic relatedness of BSI isolates and metagenomic strains based on core SNPs as assessed by StrainSifter. Branch tip colors indicate BSI isolates (red), SBS (brown) and preterm (peach), or term (teal) stools

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