Compositional analyses reveal correlations between taxon-level gut bacterial abundance and peripheral T cell marker expression in African infants

Capturing the dynamics of microbial interactions through individual-specific networks

Longitudinal analysis of multivariate individual-specific microbiome profiles over time or across conditions remains dauntin. Most statistical tools and methods that are available to study microbiomes are based on cross-sectional data. Over the past few years, several attempts have been made to model the dynamics of bacterial species over time or across conditions. However, the field needs novel views on handling microbial interactions in temporal analyses. This study proposes a novel data analysis framework, MNDA, that combines representation learning and individual-specific microbial co-occurrence networks to uncover taxon neighborhood dynamics. As a use case, we consider a cohort of newborns with microbiomes available at 6 and 9 months after birth, and extraneous data available on the mode of delivery and diet changes between the considered time points. Our results show that prediction models for these extraneous outcomes based on an MNDA measure of local neighborhood dynamics for each taxon outperform traditional prediction models solely based on individual-specific microbial abundances. Furthermore, our results show that unsupervised similarity analysis of newborns in the study, again using the notion of a taxon's dynamic neighborhood derived from time-matched individual-specific microbial networks, can reveal different subpopulations of individuals, compared to standard microbiome-based clustering, with potential relevance to clinical practice. This study highlights the complementarity of microbial interactions and abundances in downstream analyses and opens new avenues to personalized prediction or stratified medicine with temporal microbiome data.

Composition characteristics of the gut microbiota in infants and young children of under 6 years old between Beijing and Japan

BACKGROUND

The composition of intestinal flora in Chinese and Japanese has been reported in many studies but that in infants aged 0-6 years old has not been studied yet.

METHODS

The distribution characteristics of the fecal flora of infants in Beijing (n=84) and Japan (n=53) were analyzed using 16S rRNA gene sequencing analysis.

RESULTS

This study showed the higher relative abundance of Erysipelotrichaceae_ UCG-003 and Anaerostipes in male group that of Ruminiclostridium, Eubacterium, Senegalimassilia and Senegalimassilia in female group, especially Senegalimassilia, which was not detected in male group. Defecation trait groups indicated significantly higher relative abundance of Bifidobacterium in abnormal bowel trait group than that in the normal group (P<0.05). The feeding groups' analysis showed significantly higher relative abundance of Bifidobacterium and Enterococcus and lower abundance of Bacteroides and Lacetospirillaceae in the breast-feeding group than that in the formula feeding and mixed-feeding groups. The relative abundance of Parasutterella and Ruminococcaceae_UCG-003 in the halitosis group was significantly higher than that in the normal group. The comparison of cold and fever group and normal group indicated significantly higher relative abundance of Erysipelatoclostridium and lower relative abundance of Lachnospiraceae _UCG-001 in the fever and cold group than that in the normal group (P<0.05). The regional comparison of intestinal flora of Beijing and Japan showed significant increase in the relative abundance of Bacillus, Lactobacillus, Prevotella, megamonas and Veillonella in the intestinal flora of 0-6 years old infants in Beijing.

CONCLUSIONS

These findings improve the understanding of intestinal bacterial and viral communities of infants from the two Asian countries.

Prospective study reveals a microbiome signature that predicts the occurrence of post-operative enterocolitis in Hirschsprung disease (HSCR) patients

Hirschsprung disease (HSCR) is a birth defect with an approximate incidence of 1/5,000 live births, and up to one-third of HSCR patients develop Hirschsprung-associated enterocolitis (HAEC), the leading cause of HSCR-related death. Very little is known about the pathogenesis, prevention, and early diagnosis of HAEC. Here, we used a prospective study to investigate the enteric microbiome composition at the time of surgery as a predictor for developing postoperative HAEC. We identified a microbiome signature containing 21 operational taxonomic units (OTUs) that can potentially predict postoperative HAEC with ~85% accuracy. Furthermore, we identified exclusive breastfeeding as a novel protective factor for total HAEC (i.e., preoperative and postoperative HAEC combined). In addition, we discovered that breastfeeding was associated with a lowered risk for HAEC potentially mediated by modulating the gut microbiome composition characterized by a lower abundance of Gram-negative bacteria and lower LPS concentrations. In conclusion, modulating the gut microbiome by encouraging breastfeeding might prevent HAEC progression in HSCR patients.