Multi-Compartment Profiling of Bacterial and Host Metabolites Identifies Intestinal Dysbiosis and Its Functional Consequences in the Critically Ill Child

Abstract

Objectives: Adverse physiology and antibiotic exposure devastate the intestinal microbiome in critical illness. Time and cost implications limit the immediate clinical potential of microbial sequencing to identify or treat intestinal dysbiosis. Here, we examined whether metabolic profiling is a feasible method of monitoring intestinal dysbiosis in critically ill children.

Design: Prospective multicenter cohort study.

Setting: Three U.K.-based PICUs.

Patients: Mechanically ventilated critically ill (n = 60) and age-matched healthy children (n = 55).

Interventions: Collection of urine and fecal samples in children admitted to the PICU. A single fecal and urine sample was collected in healthy controls.

Measurements and main results: Untargeted and targeted metabolic profiling using 1H-nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry or urine and fecal samples. This was integrated with analysis of fecal bacterial 16S ribosomal RNA profiles and clinical disease severity indicators. We observed separation of global urinary and fecal metabolic profiles in critically ill compared with healthy children. Urinary excretion of mammalian-microbial co-metabolites hippurate, 4-cresol sulphate, and formate were reduced in critical illness compared with healthy children. Reduced fecal excretion of short-chain fatty acids (including butyrate, propionate, and acetate) were observed in the patient cohort, demonstrating that these metabolites also distinguished between critical illness and health. Dysregulation of intestinal bile metabolism was evidenced by increased primary and reduced secondary fecal bile acid excretion. Fecal butyrate correlated with days free of intensive care at 30 days (r = 0.38; p = 0.03), while urinary formate correlated inversely with vasopressor requirement (r = -0.2; p = 0.037).

Conclusions: Disruption to the functional activity of the intestinal microbiome may result in worsening organ failure in the critically ill child. Profiling of bacterial metabolites in fecal and urine samples may support identification and treatment of intestinal dysbiosis in critical illness.

Figures

Figure 1.

Urinary and fecal 1H-nuclear magnetic resonance (1H-NMR) global metabolic profiles of critically ill and healthy children. A, Unsupervised principal components analysis (PCA) scores plot of admission urine samples from age-matched critically ill (red) and healthy (blue) children. R2 = 0.16, Q2 = 0.09. B, Supervised Orthogonal Projections to Latent Structures Discriminant Analysis (O-PLS-DA) loadings line plot. Urinary metabolites higher in critically ill children (up) compared with age-matched healthy children (down). The color bar indicates the correlation coefficient (R2) (i.e., the redder the peak, the higher the correlation). R2Y = 0.89, Q2Y = 0.80. C, Unsupervised PCA scores plot of fecal samples from age-matched critically ill (red, n = 27) and healthy control (blue, n = 41) samples. R2 = 0.23, Q2 = 0.08. D, Supervised O-PLS-DA loadings line plot. Fecal metabolites higher in critically ill children (up) compared with age-matched healthy children (down). R2Y = 0.96, Q2Y = 0.85. R2Y = variance explained, Q2Y= predictive ability. a.u = arbitrary units, N-AG = n-acetylglucosamine, NMNA = n-nethylnicotinamide.

Figure 2.

Fecal liquid chromatography-mass spectrometry bile acid (BA) profiles of critically ill and healthy children. A, Unsupervised principal components analysis scores plot of critically ill (red) and healthy control (blue) samples. R2 = 0.47, Q2 = 0.16. B, Changes in the metabolism of BAs in critically ill (in red) compared with healthy children (in blue) illustrate accumulation of primary BAs and a reduction in lithocholic acid in critically ill children. 5β-CA-3β, 12a-diol = 5β-cholanic acid-3β, 12a-diol, FDR 2.952E-6, 23 nor 5β- CA-3α, 12a-diol = 23-nor-5b-cholanic acid-3a, 12a-diol, FDR 1.664E-7, 3KCA = 3 ketocholanic acid, FDR 3.505E-7, 3a-H-12 KLCA = 3a-hydroxy-12 ketolithocholic acid, FDR 4.174E-6, CA = cholic acid, FDR 2.142E-7, DCA = deoxycholic acid, FDR 0.004, FDR = false discovery rate, ILCA = isolithocholic acid, FDR 1.596E-10, LCA = lithocholic acid, FDR 6.157E-10, PC = principal component, TCA = taurocholic acid, FDR 0.001.

Figure 3.

Bacterial composition in age-matched critically ill and healthy children. Nonmetric multidimensional scaling (NMDS) plot of fecal microbial composition at genus level. High variability is seen in samples from critically ill children (red) compared with healthy controls (orange). PERmutational Multivariate ANalysis Of Variance (PERMANOVA) p = 0.0001, F = 3.314. Samples from healthy children were tightly clustered together, suggesting greater similarity in composition, while those from patients were scattered widely across the plot and statistically separated from the healthy profiles (PERMANOVA test: F = 9.78; p < 0.001).