Premature neonatal gut microbial community patterns supporting an epithelial TLR-mediated pathway for necrotizing enterocolitis

Abstract

Background: Necrotising enterocolitis (NEC) is a devastating bowel disease, primarily affecting premature infants, with a poorly understood aetiology. Prior studies have found associations in different cases with an overabundance of particular elements of the faecal microbiota (in particular Enterobacteriaceae or Clostridium perfringens), but there has been no explanation for the different results found in different cohorts. Immunological studies have indicated that stimulation of the TLR4 receptor is involved in development of NEC, with TLR4 signalling being antagonised by the activated TLR9 receptor. We speculated that differential stimulation of these two components of the signalling pathway by different microbiota might explain the dichotomous findings of microbiota-centered NEC studies. Here we used shotgun metagenomic sequencing and qPCR to characterise the faecal microbiota community of infants prior to NEC onset and in a set of matched controls. Bayesian regression was used to segregate cases from control samples using both microbial and clinical data.

Results: We found that the infants suffering from NEC fell into two groups based on their microbiota; one with low levels of CpG DNA in bacterial genomes and the other with high abundances of organisms expressing LPS. The identification of these characteristic communities was reproduced using an external metagenomic validation dataset. We propose that these two patterns represent the stimulation of a common pathway at extremes; the LPS-enriched microbiome suggesting overstimulation of TLR4, whilst a microbial community with low levels of CpG DNA suggests reduction of the counterbalance to TLR4 overstimulation.

Conclusions: The identified microbial community patterns support the concept of NEC resulting from TLR-mediated pathways. Identification of these signals suggests characteristics of the gastrointestinal microbial community to be avoided to prevent NEC. Potential pre- or pro-biotic treatments may be designed to optimise TLR signalling.

Keywords: Metagenome; Microbiome; Necrotising enterocolitis; Premature infant; TLR4; TLR9.

Fig. 1

Canonical correlation analysis plot showing the similarity of the processed samples. Analysis was performed using data quantifying the most abundant taxonomic groups comprising 95% of the sequencing reads (n = 24; 11 NEC samples (black), 11 control samples (white), 1 technical repeat (white, C12R)). Taxonomic names indicate the major bacterial groups associated with nearby samples which drive the separation

Fig. 2

Samples clustered by taxonomic assignment of sequencing reads. Y axis indicates proportion of reads assigned to each taxonomic category as coded in the colour key. The categories are spread over multiple taxonomic levels, with reads binned according to highest resolution possible. X axis indicates the samples, clustered by similarity (n = 22; 11 NEC samples, 11 control samples)

Fig. 3

CpG motif frequency in premature infant gut colonisers. Binned bacterial reads for the taxonomic groups making up the top 95% of classifications are stratified according to the number of CpG motifs per megabase of DNA

Fig. 4

Stratification of samples by bacterial load and A CpG DNA content or B Gram-negative bacteria. Control and NEC samples are stratified by bacteria per gram of faeces (x axis) and A the occurrences of CpG DNA per gram of faeces (y axis) and B number of Gram-negative bacteria per gram of faeces (y axis). The solid diagonal lines indicate the relationship established between each pair of factors for control infants using linear regression. The interquartile range (IQR) of the deviation of control samples from the regression line is indicated by dashed lines. Stars indicate NEC cases identified as either having particularly low CpG DNA per gram of faeces or particularly high abundances of Gram-negative bacteria compared to control infants, as defined by being outside the IQR of the control samples

Fig. 5

Predicted probabilities from the Bayesian regression models for training and validation datasets. Predicted probabilities for the CpG-related NEC and Gram-negative-related NEC models are shown for 11 control infants, 11 NEC cases and for the validation dataset. Dashed lines indicate the 90% quantile of predicted probability for the eleven control samples along each axis. “NEC” samples are the closest available samples to an infant’s NEC diagnosis for each dataset and “Pre-NEC” refers to any prior samples from these infants. NEC cases that received no antibiotics prior to samples being taken are marked with stars. The points for samples “N1” and “N8” are overlaid