Fungi form interkingdom microbial communities in the primordial human gut that develop with gestational age

Abstract

Fungal and bacterial commensal organisms play a complex role in the health of the human host. Expansion of commensal ecology after birth is a critical period in human immune development. However, the initial fungal colonization of the primordial gut remains undescribed. To investigate primordial fungal ecology, we performed amplicon sequencing and culture-based techniques of first-pass meconium, which forms in the intestine prior to birth, from a prospective observational cohort of term and preterm newborns. Here, we describe fungal ecologies in the primordial gut that develop complexity with advancing gestational age at birth. Our findings suggest homeostasis of fungal commensals may represent an important aspect of human biology present even before birth. Unlike bacterial communities that gradually develop complexity, the domination of the fungal communities of some preterm infants by Saccromycetes, specifically Candida, may suggest a pathologic association with preterm birth.-Willis, K. A., Purvis, J. H., Myers, E. D., Aziz, M. M., Karabayir, I., Gomes, C. K., Peters, B. M., Akbilgic, O., Talati, A. J., Pierre, J. F. Fungi form interkingdom microbial communities in the primordial human gut that develop with gestational age.

Keywords: Candida; meconium; microbiome; mycobiome; premature birth.

Conflict of interest statement

The authors thank the mothers and infants who contributed to the study, and also the research coordinators Gail Camp and Nancy Ruch (Division of Neonatology, Department of Pediatrics, College of Medicine, UTHSC) for assistance in identifying and recruiting patients. The authors declare no conflicts of interest.

Figures

Figure 1

Curation of clinical and microbial data. A) Schematic of patient allocation. VLBW, very low birth weight (preterm infants <1500 g). B) Schematic of data acquisition and analysis. Low biomass samples of meconium, an intralumenal material formed in the intestine prior to birth, were analyzed by culture-based techniques or Illumina MiSeq and quantitative PCR after high-fidelity DNA extraction. Sequence reads were subjected to exacting data processing to remove potential contaminants. Clinical demographics were used to perform ecological modeling of microbial communities and develop sequential rarified random forest classifier machine learning models.

Figure 2

Fungal ecologies in human meconium vary by the gestational age at birth. A) Sequencing rarefaction analysis of species richness. B) α diversity quantified by the Shannon index, ANOVA f = 4.5, P = 0.04. C) PCoA of Bray-Curtis dissimilarity matrices, PERMANOVA R2 = 0.308, P = 0.01. The subset displays a discriminant analysis of principal components. D) Network analysis developed using Pearson’s correlations. Positive correlations with FDR-adjusted values of P < 0.05 are presented as an edge. E) Heat map of differential distribution of taxa at the order level, ranked by gestation. Gold is set to a value of 0.5, representing equal distribution; red is set to a value >0.5, indicating a positive correlation; and blue is set to <0.5, indicating a negative correlation. F) Relative abundance of taxa at the phylum level. Sqrt(TSS), square root total sum normalization (Hellinger transformation). For route of delivery, black indicates cesarean delivery. For antibiotics, black indicates positive administration. For the CIRB-II, black indicates a critical score of >11. For sex, black indicates male. For gestational age, black indicates term length of gestation. For all analyses, n = 71. Preterm samples are displayed in red, and term samples are displayed in blue.

Figure 3

Fungal communities increase in complexity with advancing gestational age at birth. A) Relative abundance at the phylum level. Sqrt(TSS), square root total sum normalization (Hellinger transformation). B) Distribution of key taxa at the genus level. ANOVA, Bonferroni, *P < 0.05, **P < 0.01. C) Twenty most abundant interkingdom taxa at the order level. The size of box indicates relative abundance. D) Canonical correspondence analysis (CCA), χ2 = 0.71, f = 1.14, P = 0.004, and RDA, variance = 3.83, f = 1.22, P = 0.001. E) Core interkingdom OTUs and unique phyla between preterm and term infants. Data are median ± interquartile range (n = 71). Preterm samples are displayed in red and term samples are displayed in blue.

Figure 4

Fungal community structure is not determined by common perinatal factors. A) Host sex does not significantly alter fungal community composition. PCoA of Bray-Curtis dissimilarity matrices, PERMANOVA R2 = 0.0209, P = 0.529. RDA, variance = 3.19, f = 1.02, P = 0.348. The subset displays a discriminant analysis of principal components. B) Prenatal antibiotic exposure (PAE) does not significantly alter fungal community composition. PCoA of Bray-Curtis dissimilarity matrices, PERMANOVA R2 = 0.202, P = 0.598. RDA, variance = 3.51, f = 1.12, P = 0.083. C) Mode of delivery does not significantly alter fungal community composition. PCoA of Bray-Curtis dissimilarity matrices, PERMANOVA R2 = 0.202, P = 0.598. RDA, variance = 3.51, f = 1.12, P = 0.083. D) Illness severity does not significantly alter fungal community composition. PCoA of Bray-Curtis dissimilarity matrices, PERMANOVA R2 = 0.0251, P = 0.146. RDA, variance = 2.68, f = 0.85, P = 0.947. For all analyses n = 71.

Figure 5

Fungi and bacteria form complex interkingdom microbial communities in human meconium. A) Sequencing rarefaction analysis of species richness. B) α diversity quantified by the Shannon index, ANOVA f = 2.2, P = 0.14. C) PCoA of Bray-Curtis dissimilarity matrices, PERMANOVA with 999 permutations R2 = 0.103, P = 0.000333. The subset displays a discriminant analysis of principal components. D) Network analysis developed using Spearman’s correlations. Positive correlations with FDR-adjusted values of P <0.05 are presented as an edge. Nodes indicate specific bacterial or fungal taxa, with the relative number of significant connections indicated by the size of the node. E) Heat map of differential distribution of taxa at the order level, ranked by gestation. Gold is set to a value of 0.5, representing equal distribution; red is set to a value of >0.5, indicating a positive correlation; and blue is set to a value of <0.5, indicating a negative correlation. F) Relative abundance of taxa at the phylum level. Sqrt(TSS), square root total sum normalization (Hellinger transformation). For all analyses (n = 71), preterm samples are displayed in red and term samples in blue.

Figure 6

Interkingdom microbial community composition accurately classifies preterm infants. The precision of rarified random forest classifier machine learning models developed using microbial taxa from each level of the phylogenic tree increases as the phylogenic level decreases, highlighting the importance of key microbial taxa. Darker shading indicates a more important predictor to the machine learning model. Blue represents bacteria, red represents fungi, and black represents archaea and clinical demographics. Starting from the center and moving outward, concentric rings represent models developed utilizing taxa on the kingdom, phylum, class, order, family, and genus levels. For clarity, only the kingdom and phyla are annotated. The 10 most important predictors based on the genus-level model are highlighted in bold. AUC statistics for each level are reported in Supplemental Fig. S4B. *Represents significant predictors in the final model, which are listed in full in the Supplemental Data.