Pathological gut microbiota dynamics associate with nosocomial infections in critically ill patients

We conducted a prospective, longitudinal, integrated multi-omics analysis of the fecal microbiota, systemic cellular immune and inflammatory responses in 51 critically ill adults in medical, surgical, trauma and neurological ICUs in Calgary (Table 1). We enrolled patients who were adults, newly admitted to the ICU and expected to require continuous mechanical ventilation and intensive care for at least 72 h, as judged by the treating specialists. To avoid known confounders of microbiota ecology or systemic immune function, we excluded patients who were in hospital more than 48 h before ICU admission (during the current admission or any time in the previous 3 months), received systemic antibiotics in the 3 months before admission, were immunocompromised (congenital or acquired), had inflammatory bowel disease or gastrointestinal (GI) malignancy, had a discontinuous GI tract or moribund patients not expected to survive >72 h at the time of admission (Methods and Supplementary Table 1 provide additional details).

Table 1 Demographic, clinical and treatment characteristics of study participants

Fecal bacterial microbiota composition was analyzed at the time of ICU admission and then serially on days 3 and 7 of ICU admission using 16s rRNA gene amplicon sequencing (Fig. 1a). Owing to the need for precise timing of sample collection and unpredictable timing of bowel movements in critically ill patients, rectal swabs were utilized as previously described in multiple studies of gut microbiota in ICU patients11,19,20,21. From the time of admission, critically ill patients harbored evidence of gut dysbiosis compared to healthy volunteers, including reduced taxonomic diversity, richness and significant shifts in community β-diversity (Fig. 1a–d). Serial analysis of the microbiota over the first week of critical illness demonstrated progressive erosion of biodiversity, taxonomic richness and compositional shifts (Fig. 1a–d, Extended Data Fig. 1 and Supplementary Tables 2 and 3). Consistent with previous reports10,11,12, the shifts in fecal microbial communities in critical illness were characterized by a loss of commensal anaerobic fermenters (Ruminococcaceaea and Lachnospiraceae) and emergence of pathobiont taxa (Enterococcaceae and Enterobacteriaceae) (Fig. 1a, Extended Data Fig. 1 and Supplementary Tables 2 and 3). To confirm that the observed microbiota differences were not due to the difference in median age between ICU and healthy cohorts, we also obtained publicly available datasets of 16s rRNA gene amplicon sequencing of rectal swabs from healthy volunteers with similar median age (62 years, range 42–80), sex and ethnicity distribution as our ICU patient cohort22. Again, the ICU microbiota displayed significantly different β-diversity, reduced α-diversity, as well as differential abundance and increased relative abundance of Enterobacteriaceae (Supplementary Fig. 1). Permutational multivariate analysis of variance (PERMANOVA) analysis identified that only biological sex and duration of antibiotic treatment before sampling were significantly associated with microbiota composition in the first week of critical illness, whereas age, ethnicity, burden of comorbidities (Charlson index), illness severity (sequential organ failure assessment (SOFA) score), duration of hospitalization before microbiota sampling and admission diagnosis (both subacute illnesses (sepsis) and hyperacute illnesses such as trauma, neurological injury and cardiac arrest) were not associated with microbiota composition (Extended Data Table 1 and Supplementary Fig. 2). All critically ill patients in this study were treated with enteral nutrition, none received stress-dose glucocorticoid therapy and one patient was treated with proton-pump inhibitor therapy during admission. Collectively, these data demonstrate that dysbiosis of the fecal bacterial microbiota is established at the time of ICU admission and exhibits dynamic and progressive changes during the acute phase of critical illness.

Fig. 1: Intestinal dysbiosis with progressive Enterobacteriaceae enrichment in critical illness is associated with nosocomial infections.

a, Taxonomic composition by relative abundance of bacterial families. b, Three-dimensional principal-coordinates analysis (Bray–Curtis dissimilarity distances, genus level) analyzed by PERMANOVA. c, Shannon index. d, Chao1 index in rectal swabs from critically ill patients on day 1 (n = 51) and again from survivors who remained in ICU on day 3 (n = 44) and day 7 (n = 15), compared to healthy volunteers (n = 15). Dots represent individual patients, central line indicates median, box shows interquartile range (IQR) and whiskers show range; analyzed by two-sided Kruskal–Wallis test (healthy versus ICU days) with pairwise comparisons of repeated measures across days using a mixed linear regression model with a post hoc Tukey’s test. e, MOFA of microbiota composition between healthy volunteers and ICU patients showing top ten taxonomic factors (families) and their relative contributions to explained microbiota variance (factor weight). f, Enterobacteriaceae relative abundance on days 1, 3 and 7 of ICU admission compared to healthy controls. Dots represent individual patients, central line shows median, box shows IQR and whiskers show range, analysis as per c and d. g, Correlation between Enterobacteriaceae relative abundance and Shannon index, analyzed using Spearman correlation test. Dots show individual patient samples, regression (line) and 95% confidence intervals (shaded area) are shown. h, Penalized ridge regression of the 15 most abundant bacterial families and their importance toward change in Shannon diversity from days 1–3 of ICU admission. i,j, Mean relative abundance († indicates Padj  < 0.1 by ANCOM-II differential abundance) (i) and correlation matrices (j) of the 15 most abundant bacterial families on ICU day 3. k, Longitudinal microbiota community stability index between patients with progressive Enterobacteriaceae enrichment (n = 18) or no enrichment (n = 26). Dots represent individual patients, central line shows the median, box shows IQR and whiskers show range; analyzed by two-sided Mann–Whitney U-test. l–n, The 30-d nosocomial infection-free survival analyzed by log-rank test (l), odds ratio of nosocomial infection caused by any pathogen or Enterobacteriaceae pathogen determined by two-sided Fisher’s exact test (m) and pathogens identified in nosocomial infections (n) (n = 30 infections in 28 patients). P values as shown in b; *P < 0.05, **P < 0.01.

Using multi-omics factor analysis (MOFA)23 we found that variance in microbiome composition between critically ill patients and healthy volunteers was overwhelmingly explained by members of the Enterobacteriaceae family, both on admission as well as across all time points during the first week in ICU (Fig. 1e and Extended Data Fig. 2a). Proteobacteria, and in particular Enterobacteriaceae, expansion has been consistently observed in previous studies of hospitalized and critically ill patients11,12,13,14,20,24. Median Enterobacteriaceae relative abundance was ~tenfold higher in rectal swab samples of critically ill patients compared to healthy controls, with individual patient variability that was dynamic over the first week of ICU admission (Fig. 1f). Enterobacteriaceae abundance was inversely correlated with total microbiota richness and diversity (Fig. 1g and Extended Data Fig. 2b) and penalized ridge regression analysis revealed that Enterobacteriaceae was the most important family associated with the change in microbiota diversity over time in ICU patients (Fig. 1h). Increased Enterobacteriaceae relative abundance coincided with early reduction of anaerobic fermenters including Ruminococcaceae and Lachnospiraceae (Extended Data Fig. 1b,c). Community network visualization and Spearman correlation analyses between bacterial families did not reveal significant pairwise correlations between Enterobacteriaceae and anaerobic fermenters such as Ruminococcaceae, Lachnospiraceae and Bifidobacteriaceae at individual points in time (Extended Data Fig. 2c–e and Supplementary Tables 4–7). In contrast, longitudinal analysis of the change of Enterobacteriaceae relative abundance between admission (day 1) and day 3 of ICU using penalized ridge regression identified Lachnospiraceae and Bifidobacteriaceae as the most important families associated with Enterobacteriaceae dynamics (Extended Data Fig. 2f), which aligns with their known role in colonization resistance against Enterobacteriaceae expansion in the gut25.

Further interrogation of the temporal changes of Enterobacteriaceae over the first week of ICU admission demonstrated that 41% of patients with serial sampling had greater than doubling of Enterobacteriaceae relative abundance between consecutive sampling time points, hereafter referred to as progressive Enterobacteriaceae enrichment (14 of 18 between days 1 and 3 and 4 of 18 between days 3 and 7; Extended Data Fig. 2g and Supplementary Table 1). Notably, both univariable and multivariable regression analysis found that the development of progressive Enterobacteriaceae enrichment was independent of age, sex, comorbidities, admission diagnosis, antibiotic treatment (spectrum or duration before microbiota sampling), duration of hospitalization before microbiota sampling or illness severity (Extended Data Table 2). Progressive Enterobacteriaceae enrichment was not associated with expansion of other pathobionts, but was instead linked to a reduction in overall bacterial community stability (Fig. 1i–k). Furthermore, quantification of total fecal bacterial density by qPCR as well as total Enterobacteriaceae abundance (quantified by total bacterial density multiplied by relative abundance of Enterobacteriaceae, as previously reported20,26) revealed that patients with progressive Enterobacteriaceae enrichment had both progressive increase in total bacterial density and total Enterobacteriaceae quantity, indicating that enrichment was mediated by Enterobacteriaceae expansion rather than contraction of other taxa (Extended Data Fig. 2h,i). Together, these findings reveal dynamic and progressive microbiota injury in acute critical illness dominated by Enterobacteriaceae enrichment.

Microbiota dysbiosis has been linked to adverse outcomes including nosocomial infections in hospitalized and critically ill patients11,14,16,20,24,27. Consistent with this, we found that patients with low microbiota Shannon diversity on admission (<3.59, cutoff determined by maximally selected rank statistics) had a significantly increased risk of nosocomial infection or death compared to patients with a high Shannon diversity (>3.59) on admission (Extended Data Fig. 3a,b). To explore whether this relationship between microbiota dysbiosis and nosocomial infection-free survival was associated with particular taxa (either quantity or temporal dynamics), we focused on bacterial families that were differentially abundant in ICU patients compared to healthy controls (Enterobacteriaceae, Ruminococcaceae and Lachnospiraceae; Extended Data Fig. 1). The relative abundance of these families at admission was not associated with nosocomial infection-free survival (Extended Data Fig. 3c–e). In contrast, patients who experienced any increase in Enterobacteriaceae relative abundance between time points were at significantly higher risk of infection or death compared to patients with decreased Enterobacteriaceae, whereas no association was observed for Ruminococcaceae or Lachnospiraceae dynamics (Extended Data Fig. 3f–h). Furthermore, patients with doubling or more of Enterobacteriaceae relative abundance between time points (which we define as progressive Enterobacteriaceae enrichment) were found to have significantly increased risk of the composite of nosocomial infection or death, as well as higher odds of nosocomial infection (OR 6.8, 95% CI 1.7–25.3) compared to patients without progressive Enterobacteriaceae enrichment (Fig. 1l,m). Members of the Enterobacteriaceae family are common causative pathogens in nosocomial infections and previous studies have suggested a direct link between gut overgrowth and infection via translocation and dissemination11,15,17,24. Clinical microbiology data identified Enterobacteriaceae organisms in 27% of nosocomial infections in this cohort of critically ill patients (Table 2); however, no significant association was found between progressive Enterobacteriaceae enrichment in the fecal microbiota and the odds of infection caused by Enterobacteriaceae pathogens (OR 0.97, 95% CI 0.2–4.7), although this analysis is likely underpowered due to the relatively small number of Enterobacteriaceae infections in this study (Fig. 1m). Instead, pathogens identified in nosocomial infections were diverse and not different between those with fecal Enterobacteriaceae enrichment and those without enrichment (Fig. 1n and Table 2). Therefore, microbiota dysbiosis and progressive Enterobacteriaceae enrichment are associated with an increased risk of nosocomial infections caused by a spectrum of bacterial and fungal pathogens, suggestive of a state of globally impaired host defense.

Table 2 Nosocomial infections in study participantsDysbiosis of a microbiota–immune metasystem in critical illness

We next performed a systems-level analysis of the cellular immune and inflammatory landscapes in the bloodstream of each patient to test the hypothesis that microbiota injury in critical illness is coupled with impaired systemic immunity. High-dimensional single-cell analysis of the circulating immune landscape using mass cytometry revealed profound shifts in innate and adaptive immunity in critically ill patients that were dynamic over the first week of admission (Fig. 2a,b and Extended Data Fig. 4). Consistent with previous reports3,4,28, the cellular immune response in acute critical illness was dominated by an early and sustained elevation of neutrophils, together with depletion of T and B lymphocytes as well as natural killer (NK) cells (Extended Data Fig. 4). Clustering of single-cell data using FlowSOM revealed that neutrophil expansion in critically ill patients was attributed largely to immature neutrophils (CD16lo/intCD11blo/int, clusters N1, N2 and N8) including a population resembling recently characterized dysfunctional CD123+ neutrophils (cluster N4)29, with reduction of mature (CD16hiCD11bhi, clusters N3, N5 and N7) and aged (CXCR4+CD62Llo, cluster N6) neutrophil populations (Fig. 2a, Extended Data Fig. 5a and Supplementary Table 8). Additional multi-lineage innate immune dysregulation was observed including monocyte dysregulation (early and sustained depletion of HLA-DR-expressing classical and intermediate monocyte clusters CM3, CM4, IM1 and IM2, as well as expansion of non-classical monocyte clusters NC2 and NC3), loss of HLA-DR+ dendritic cells (cluster DC3) and decreased activated interferon-γ+ NK cells (cluster NK2) (Extended Data Fig. 5b–d and Supplementary Table 8). Within the adaptive immune compartment, global T and B cell lymphopenia predominated in critically ill patients, with the remaining T cell pool enriched with PD-1+ CD4+ and CD8+ T cell clusters (CD4-2, CD4-3 and CD8-6) and regulatory T (Treg) cell (CD4+CD25+FoxP3+, CD4-4) clusters (Extended Data Fig. 6a,b and Supplementary Table 8). Quantification of circulating inflammatory mediators revealed acute and dynamic upregulation of pro-inflammatory (interleukin (IL)-6, tumor necrosis factor-α, IL-8, C-reactive protein and serum amyloid A) and anti-inflammatory (IL-10 and IL-4) responses (Fig. 2c,d and Supplementary Figs. 3 and 4) characteristic of a cytokine storm syndrome30. Collectively, these data reveal dynamic cellular immune and inflammatory responses in critically ill patients characterized by early innate immune dysregulation and systemic inflammation, followed by progressive innate and adaptive immune dysfunction.

Fig. 2: Dynamic microbiota–immune metasystem dysbiosis in critical illness.

a–d, The cellular immune landscape of blood (a,b) and plasma inflammatory mediators (c,d) were quantified by mass cytometry and multiplexed electrochemiluminescence assays, respectively, in blood samples from critically ill patients (n = 51) sampled on day 1 of admission (n = 49) and again from survivors who remined in ICU on day 3 (n = 43) and day 7 (n = 15), compared to healthy volunteer controls (n = 12). The abundance of all immune cell populations (shown as %CD45+) identified by FlowSOM clustering of single-cell mass cytometry data (Methods) (a) and t-SNE dimensionality reduction of the single-cell immune landscape between healthy volunteers and ICU patients (b). Concentrations (pg ml−1) of inflammatory mediators in the plasma (c) and log2 fold change (FC) (d) in concentrations of each mediator in ICU patients on days 1, 3 and 7 compared to healthy volunteers. CRP, C-reactive protein; TNF, tumor necrosis factor; IFN, interferon; SAA, serum amyloid A. e,f, Chord diagrams depicting the significant Spearman correlations (false discovery rate (FDR)-adjusted P < 0.1) between microbiota composition, immune cell landscape and systemic inflammatory mediators in healthy volunteers and ICU patients at each time point (e) and quantification of the number of significant Spearman’s correlations (FDR-adjusted P < 0.1) between metasystem compartments (f). g,h, Heat map of individual Spearman’s correlation coefficients between the 15 most abundant microbiota families (relative abundance) and immune cell clusters in blood (g) and plasma inflammatory mediators (h) across the first week of ICU admission. i,j, NMDS ordination of the single-cell immune landscape (i) and systemic inflammatory mediators (j) across the first 7 d of ICU admission in patients with (n = 18 patients) and without (n = 26 patients) progressive fecal Enterobacteriaceae enrichment. Statistical comparisons were performed using PERMANOVA (Supplementary Tables 15 and 16 show full model results) accounting for repeated measures, each point represents an individual patient-time point; P values as shown. t-SNE, t-distributed stochastic neighbor embedding.

Given the overlapping temporal dynamics of microbiota injury and systemic immune dysregulation during acute critical illness, we sought to determine whether microbiota and immune dynamics demonstrated metasystem-level connectivity. Using Chord diagram analysis and visualization of connectivity between microbial taxa and immune components, a higher number of significant interactions was observed in ICU patients at admission compared to the connectivity observed in healthy volunteers (Fig. 2e,f). Augmented microbiota–immune connectivity was sustained through the early phase of critical illness, remaining elevated on days 3 and 7 of admission (Fig. 2e,f). To identify whether this surge in microbiota–immune connectivity was linked to specific taxonomic changes in the microbiota, we quantified Spearman correlation coefficients between each of the 15 most abundant bacterial families and individual immune cell subsets (Fig. 2g and Supplementary Tables 9–11) and inflammatory mediators (Fig. 2h and Supplementary Table 12–14). Hierarchical analysis (indicated by the dendrogram) revealed that the associations between Enterobacteriaceae and both cellular and inflammatory mediators were unique compared to all other microbial families (Fig. 2g,h). Strong correlations were found between Enterobacteriaceae relative abundance and innate immune responses, with increased Enterobacteriaceae correlating with higher levels of immature neutrophils (clusters N1, N2 and N4) and classical monocytes (clusters CM5 and CM6) and reduced mature neutrophils (cluster N3) (Fig. 2g). Furthermore, increased Enterobacteriaceae positively correlated with prototypical systemic inflammatory mediators (IL-8, IL-15, tumor necrosis factor-α, MIP-1α and IL-10), whereas no correlations were found with acute phase reactants C-reactive protein and serum amyloid A (Fig. 2g and Supplementary Fig. 5a–d). Temporal analysis over the first week of critical illness revealed changes in the magnitude of correlations between Enterobacteriaceae and inflammatory and innate immune landscapes (Supplementary Figs. 5e,f and 6 and Supplementary Tables 9–14).

Consistent with these observations, dimensionality reduction of the single-cell immune landscape using non-metric multidimensional scaling (NMDS) revealed that patients with progressive Enterobacteriaceae enrichment (doubling or more of Enterobacteriaceae relative abundance during the first week in ICU) displayed cellular immune responses that differed significantly compared to those without progressive enrichment (Fig. 2i), even after controlling for patient covariables associated with immune cell composition including age, sex, admission diagnosis, ethnicity and illness severity (Supplementary Table 15). In contrast, no significant difference was observed in the circulating inflammatory mediator landscape between patients with and without progressive Enterobacteriaceae enrichment (Fig. 2j) as well as no association between the admission inflammatory mediator landscape and subsequent development of Enterobacteriaceae enrichment (Extended Data Fig. 7). Collectively, these data demonstrate that microbiota and cellular immune dynamics during acute critical illness function as an integrated metasystem and identify progressive Enterobacteriaceae enrichment as a possible driver of overall metasystem dysbiosis.

Metasystem dysbiosis leads to a breakdown of innate immune defense

Next, we investigated whether Enterobacteriaceae-associated metasystem dysbiosis was characterized by defects in specific immune defense programs that may contribute to the elevated risk of bacterial and fungal nosocomial infections. Dimensionality reduction analysis revealed that the adaptive immune cell compartment in patients with progressive Enterobacteriaceae enrichment was not significantly different from those without (Fig. 3a). Aside from a single naive B cell population (cluster B2), there was little impact on lymphocyte responses in patients with progressive Enterobacteriaceae enrichment during the first week of critical illness (Fig. 3a,b). In stark contrast, the innate immune cell landscape was significantly different in patients with progressive Enterobacteriaceae enrichment in the fecal microbiota compared to those without enrichment (Fig. 3c,d). Analysis of individual innate immune cell clusters revealed that this difference was characterized primarily by large shifts in neutrophil clusters, with more limited impact on monocytes, dendritic cells and innate lymphocytes (Fig. 3d,e).

Fig. 3: Enterobacteriaceae dysbiosis and impaired neutrophil host defense in critical illness.

a–d, NMDS ordinations (a,c) and comparisons of abundance (b,d) of adaptive immune cell (T and B cells) populations and innate immune cell populations (all neutrophils, monocytes, dendritic cells and innate lymphoid cell populations) (a,b) identified by clustering of mass cytometry data in the blood of ICU patients with (n = 18) or without (n = 26) progressive enrichment of Enterobacteriaceae in their fecal microbiota. Dots show individual patient-time points across the first 7 d of ICU admission, with statistical analysis by PERMANOVA accounting for repeated measures (a,c). e, t-SNE plots of neutrophils (left) and all other innate immune cells (right; monocytes, dendritic cells and NK cell clusters as indicated), with heat map overlay showing the log2FC in abundance of each cell cluster between ICU patients with (n = 18) or without (n = 26) progressive enrichment of Enterobacteriaceae in their fecal microbiota. f, Correlation between fecal Enterobacteriaceae relative abundance and the quantity of mature (left) and immature (right) neutrophils (shown as proportion of total neutrophils) in ICU patients across the first week of admission analyzed using Spearman’s ranked correlation test. Dots show individual patient samples, regression (line) and 95% confidence intervals (shaded area) are shown. g, Comparison of neutrophil clusters in blood of ICU patients with (n = 18) or without (n = 26) Enterobacteriaceae enrichment (shown as log2 fold difference of cluster abundance between groups). To determine the independent contribution of Enterobacteriaceae enrichment status (a–e,g), analyses controlled for clinical covariables that were independently associated with immune cell composition (Supplementary Table 15). i,j, Quantification of plasma NET markers (i) cell-free DNA and (j) MPO–DNA complexes on ICU day 3 in patients with (n = 18) or without (n = 26) Enterobacteriaceae enrichment. Dots represent individual patients, central line shows the median, box shows the IQR and whiskers show the range; statistical comparison was performed using a two-sided Mann–Whitney U-test. P values are shown.

Previous studies using mouse models have reported an important role for the gut microbiota in directing neutrophil-mediated host defense via regulation of granulopoiesis, maturation and aging of circulating neutrophils31,32,33,34. Strong correlations were observed in ICU patients between Enterobacteriaceae relative abundance and increased immature neutrophils (CD16lo/intCD11blo/int clusters N1, N2, N4 and N8) and decreased mature neutrophils (CD16hiCD11bhi clusters N3, N5, N7 and N9) (Fig. 3f). Despite similar total numbers of circulating neutrophils, ICU patients with progressive Enterobacteriaceae enrichment in their fecal microbiota had a notable shift in the landscape of neutrophils over time, including early and sustained increases in immature clusters (N1, N2 and N4) (Fig. 3g). Consistent with the temporal directionality between microbiota–immune metasystem dysbiosis and subsequent risk of nosocomial infections, we also compared the immune landscape between patients who developed nosocomial infections versus those who did not and again found that differences in the innate immune cell landscape, including expansion of immature neutrophils, preceded the development of infections (Extended Data Fig. 8). Recent studies have shown that immature neutrophil populations in humans display hypofunctional pathogen killing mechanisms, including impaired production of neutrophil extracellular traps (NETs)35. Patients with progressive Enterobacteriaceae enrichment (and associated immature neutrophil expansion) were found to have reduced quantities of circulating NET markers in their plasma (both cell-free DNA and myeloperoxidase (MPO)–DNA complexes) compared to those without enrichment (Fig. 3h,i). Overall, these findings reveal that increased susceptibility to nosocomial infections in the setting of progressive Enterobacteriaceae enrichment is coupled to dysregulated and hypofunctional neutrophil responses.