Microbial diversity among critically ill children differs significantly from healthy adults and children

We analyzed 16S rRNA gene pyrosequencing data from 71 tongue swabs, 50 skin swabs, and 77 GI samples (37 fecal samples, 40 rectal swabs) collected from 37 patients over 39 pediatric ICU (PICU) admissions [27]. Samples with below 200 reads following clustering were removed from downstream analysis. A single set of samples was analyzed for 23 subjects, whereas longitudinal series of samples were analyzed for the remaining 14 subjects (detailed metadata provided in Additional files 1 and 2). The average number of sequencing reads per sample was 2980 (463–41,180 reads). The mean age of the patients was 2.9 years (range 1–9). Of these patients, 86.5% were chronically ill and 45.9% had a PICU stay within the prior 6 months (mean number of days 19.8 days, range 2–64 days). Nearly all subjects received antibiotics (89.2%) and required mechanical ventilation (94.6%).

We compared our dataset to published 16S rRNA gene sequences obtained from the tongue dorsum, stool, and skin (antecubital fossa) of 227 healthy adult volunteers in the Human Microbiome Project [28]. Because age impacts the microbiota [29], we also sought comparisons of the PICU data with healthy age-matched children. To our knowledge, however, there are no analogous public datasets containing microbial sequencing data obtained simultaneously from multiple body sites from individual children. Therefore, we also analyzed GI, tongue, and skin samples collected from 13 children ages 1–9 (Additional file 2) admitted to our hospital for brief observation after minor trauma (mean age 4.6 years; average number of pyrosequencing reads per sample 2175; range 451–4784). These patients had not received antibiotics in the prior 6 months, and they received a regular diet during their hospitalization and thus were considered a valid reference group for comparison with PICU patients.

Alpha diversity is an ecological measure of how many taxonomic groups are present within each sample and whether the abundance of these groups is evenly distributed [30]. Compared to adult and pediatric samples, PICU GI and oral samples were significantly reduced in alpha diversity, using either the Chao1 diversity metric or the Shannon entropy metric (non-parametric test, all p values <0.003) (Fig. 1). PICU skin samples were significantly lower in diversity compared to pediatric samples, but not HMP samples (non-parametric test, all p values <0.003).

Fig. 1 Alpha diversity comparisons of microbial communities of PICU patients, healthy adults, and healthy children. Shown are a calculated Chao1 species richness indices for PICU, pediatric, and reference samples and b the calculated Shannon species evenness predictions for the same groups at each site Full size image

To characterize similarities and differences in the composition of microbial communities, we calculated two measures of beta diversity, weighted UniFrac distances and Jaccard indices (Fig. 2; see also supporting figures in Additional file 3). Community composition at each body location was significantly different between PICU populations and both reference sets (Jaccard distances, PERMANOVA p < 0.001).

Fig. 2 Beta diversity comparisons of microbial communities of PICU patients, healthy adults, and healthy children. Displayed are principal coordinate analyses (a gut; b skin; c tongue) of abundance Jaccard distances between samples from PICU patients, healthy children, and healthy adults. Axis labels indicate the proportion of variance explained by each principal coordinate axis Full size image

To further define the PICU-associated microbiota, LEfSe [31] was used to identify taxa at a given body site that were either enriched or depleted specifically in PICU samples (Additional file 4) (LEfSe p values <0.05 for all taxa listed as enriched or depleted). At the phylum level, PICU oral samples were enriched for Bacteroidetes, GI samples were enriched for Firmicutes, Actinobacteria, and Fusobacteria, and skin samples were enriched for Firmicutes and Bacteroidetes. At the genus level, PICU samples were enriched for two common ICU pathogens (Enterococcus and Staphylococcus) at all three body sites and enriched for Pseudomonas in GI and oral samples. Additional features of the PICU microbiome are displayed in Additional files 4 and 5, including the sharp enrichment of Capnocytophaga in oral and skin samples. Importantly, PICU samples were found to be depleted of several commensals identified in healthy adults and children. Depleted taxa within PICU GI samples included several anaerobes associated with gut health, e.g., Ruminococcus, Roseburia, and Faecalibacterium. PICU oral samples were depleted of commensals such as Rothia and Haemophilus, and PICU skin samples were also depleted of Haemophilus.

Phylogenetic analysis of OTUs corresponding to Pseudomonadaceae indicated that some of the observed OTUs could be assigned to a contaminant in control samples that most closely maps to either Pseudomonas putida or Pseudomonas fluorescens. However, most of the observed Pseudomonadaceae OTUs in patient samples mapped to a clade of Pseudomonas aeruginosa, a well-recognized human pathogen that was also isolated by the hospital clinical microbiology laboratory in tracheal aspirates obtained from several of the study subjects (Additional file 2). OTUs from the genus Capnocytophaga were most commonly from taxa previously observed in the human oral cavity: C. leadbetteri, C. sputigena, and C. gingivalis.

ICU samples are characterized by dominant pathogens and loss of site specificity

The presence of a “dominant” pathogen within fecal samples has been identified as a risk factor for subsequent infections caused by that same organism [5, 21]. To our knowledge, our recent study of critically ill adults was the first to quantify the number of samples in the Human Microbiome Project with dominant taxa [28]. We defined dominance as the presence of a single taxon with relative abundance exceeding 50%. Here, we found that the percentage of GI and tongue samples with dominant taxa was also higher among PICU samples than adult or pediatric samples (Fig. 3a). Although healthy adult samples did contain many dominant taxa, these taxa were typically normal commensals such as Propionibacterium (skin) and Bacteroides (gut). By contrast, dominant taxa in the PICU were more likely to be pathogenic, e.g., Enterococcus (GI), Staphylococcus (skin), Porphyromonas (tongue), Pseudomonas (tongue), Capnocytophaga ﻿(tongue), and Stenotrophomonas (tongue). Remarkably, the PICU population included many subjects in whom all examined body sites simultaneously harbored dominant organisms (most commonly with different dominant taxa at each location). This pattern was observed only rarely among healthy children and adults (Fig. 3b).

Fig. 3 Dominant pathogens and loss of site specificity in PICU samples. a Proportion of overall samples in which more than 50% of sequencing reads are derived from a single dominant bacterial taxon. Colored stacked bars indicate the identity of the dominant taxa. Many dominant genera in the adult and pediatric groups are known commensals, whereas many dominant taxa identified in PICU samples are pathogenic. b Proportion of subjects with any dominant genus present on three body sites simultaneously. Many PICU subjects harbored three distinct dominant pathogens simultaneously at the three body sites studied. c Boxplot of abundance Jaccard distances between samples collected on the same date from PICU, pediatric, and adult subjects. Shown are distances between GI and skin samples from the same individual, GI and tongue samples from the same individual, and skin and tongue samples from the same individual. In all comparisons except skin vs. tongue, we found the median distance between samples to be significantly reduced in PICU patients Full size image

Another well-described feature of the human microbiome is site specificity. It has been demonstrated repeatedly that microbial community membership typically varies significantly between body sites [32]. In our study of critically ill adults, we noted that pathogenic taxa were commonly present simultaneously at multiple body sites at relatively high abundance. Among PICU patients, we observed a similar phenomenon. The genus most commonly observed simultaneously at all three body sites in both PICU and adult datasets was Prevotella, but this phenomenon was also observed in the PICU with Staphylococcus, Stenotrophomonas, and Porphyromonas.

To better define the loss of site specificity in the ICU, we calculated abundance Jaccard distances between microbial communities for each pair of body locations (gut vs. skin, gut vs. tongue, and skin vs. tongue) from all individuals with complete sets of GI, skin, and oral sequencing data (Fig. 3c). Accounting for sequencing failures from one or more body sites, we identified 120 healthy adults, 33 PICU subjects, and five healthy children with at least one complete set of contemporaneous samples collected from three body sites on the same day. We found that the distance between body sites was significantly reduced in PICU patients relative to HMP subjects for all comparisons between sites (Welch’s two-sample t test, p values <0.05). The distances between GI vs. tongue and GI vs. skin samples from PICU patients were also reduced relative to healthy children, although the distance between tongue vs. skin samples was not reduced significantly. Interestingly, some paired distances of healthy children were reduced relative to HMP subjects, suggesting that age contributes partly to the development of site-specific microbial communities.

The microbiota often but not always changes radically during PICU admission

The mean alpha diversity of samples correlated inversely with days spent in the PICU (Shannon diversity index, GI r 2 = 0.115; skin r 2 = 0.173; oral r 2 = 0.122) (Fig. 4a). A corresponding finding was an increase in the prevalence of dominant taxa over time among the PICU samples (GI r 2 = 0.134; skin r 2 = 0.093; tongue r 2 = 0.056) (Fig. 4b). In some subjects but not all, alpha diversity recovered near the end of the ICU admission (see supplemental figure in Additional file 6).

Fig. 4 Temporal changes in the site-specific microbiota of PICU patients. a Temporal changes in the median Shannon diversity index of study subjects followed longitudinally during their PICU admission. All p values <0.05. b Temporal changes in relative abundance of most abundant taxa in PICU patients. With time in the ICU, dominant taxa become more prevalent at each body site. All p values <0.05. c Temporal and spatial variation of the microbiota in a single individual. Shown here are microbial profiles for a 2-year-old chronically ill child with enterococcal sepsis. With time and antibiotics, the dysbiosis seen on admission resolves. The enterococcal populations at all three body sites nearly disappear, and the skin and oral communities also adopt configurations more typical of healthy individuals (e.g., Staphylococcus on the skin and Streptococcus and Neisseria in the mouth) Full size image

To examine the taxonomic stability of the ICU microbiome over time, we calculated binary Jaccard distances for all samples collected at adjacent time points from the same individual and same body site, as well as binary Jaccard distances between samples collected on the same study date from unrelated individuals (see the figure in Additional file 7). Overall, samples from different individuals taken on the same date were significantly different from samples collected on adjacent dates from the same individuals (GI; Wilcoxon’s rank sum test; p value <2.2e−16; oral p value <2.2e−16; skin p value = 5.845e−09). Most samples were more similar to other samples from the same individual than samples from other individuals, as also shown in a similar analysis of gut microbiota in infants [33]. However, we observed a much broader range of values for intra-individual comparisons in the PICU than was observed in healthy children. This is evidence that dynamic temporal changes exist in the microbiota of ICU patients, as major differences were observed in a subset of samples collected at adjacent dates from the same patient.

The potential value of analyzing temporal and spatial variation in the microbiota is illustrated by time series analysis of patient 6 (Fig. 4c). This 2-year-old child was admitted to the ICU with sepsis. Blood cultures on admission were positive for growth of Enterococcus, Acinetobacter, and Staphylococcus (latter two organisms suspected to be skin contaminants from venipuncture). Interestingly, microbiota profiling demonstrated Enterococcus at two body sites shortly after admission (relative abundance GI 97.9%, skin 35.8%, and tongue 0%), and three body sites 3 days later (GI 90.6%, skin 26.9%, and tongue 0.005%). Early tongue samples were dominated by Porphyromonas. Over time, after the initiation of antibiotics and resolution of clinical symptoms, the dominant populations of Enterococcus and Porphyromonas disappeared and alpha diversity recovered.

Associations between clinical information and configuration of the microbiota

We sought to characterize associations between positive microbiology culture results and microbiota profiles. Of the 39 PICU admissions, 27 were marked by at least one positive culture (see metadata in Additional file 2). In contrast to the small group of blood, wound, and urine cultures, only the group of 31 positive tracheal aspirates (TAs) was large enough to assess for associations with the microbiota. The pathogen isolated most frequently in TAs was P. aeruginosa; S. aureus, Serratia marcescens, and Stenotrophomonas maltophilia were also observed frequently. We compared microbiota profiles of patients with positive TAs to profiles from patients without positive cultures from any body location. Interestingly, we found that patients with TAs positive for Serratia (1.5 vs. <1%, Wilcoxon’s rank sum test, p value = 0.01959) and Stenotrophomonas (3.3 vs. <1%, Wilcoxon’s rank sum test, p value = 0.03707) harbored skin swabs (collected within 2 days of the positive culture) with significantly higher abundance of these same organisms than patients without positive cultures; the same relationship did not hold for other genera, and it did not hold true for GI or tongue samples. These correlations between tracheal aspirate and skin colonization patterns may represent direct inoculation of the anterior chest wall via aerosolization. Pseudomonas was extremely common on PICU tongue swabs but was present at varying levels of abundance; a relative abundance of Pseudomonas greater than 0.5% on a tongue swab (collected within 2 days of the positive culture) was highly associated with the presence of a TA positive for P. aeruginosa, although this association did not reach statistical significance (25% of positive samples vs. 0% samples negative for Pseudomonas; χ 2 = 1.8863, df = 1, p value = 0.1696).