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. 2018 Dec;24(12):1809-1814.
doi: 10.1038/s41591-018-0202-8. Epub 2018 Oct 15.

Precision identification of diverse bloodstream pathogens in the gut microbiome

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Precision identification of diverse bloodstream pathogens in the gut microbiome

Fiona B Tamburini et al. Nat Med. 2018 Dec.

Abstract

A comprehensive evaluation of every patient with a bloodstream infection includes an attempt to identify the infectious source. Pathogens can originate from various places, such as the gut microbiota, skin and the external environment. Identifying the definitive origin of an infection would enable precise interventions focused on management of the source1,2. Unfortunately, hospital infection control practices are often informed by assumptions about the source of various specific pathogens; if these assumptions are incorrect, they lead to interventions that do not decrease pathogen exposure3. Here, we develop and apply a streamlined bioinformatic tool, named StrainSifter, to match bloodstream pathogens precisely to a candidate source. We then leverage this approach to interrogate the gut microbiota as a potential reservoir of bloodstream pathogens in a cohort of hematopoietic cell transplantation recipients. We find that patients with Escherichia coli and Klebsiella pneumoniae bloodstream infections have concomitant gut colonization with these organisms, suggesting that the gut may be a source of these infections. We also find cases where typically nonenteric pathogens, such as Pseudomonas aeruginosa and Staphylococcus epidermidis, are found in the gut microbiota, thereby challenging the existing informal dogma of these infections originating from environmental or skin sources. Thus, we present an approach to distinguish the source of various bloodstream infections, which may facilitate more accurate tracking and prevention of hospital-acquired infections.

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Conflict of interest statement

Competing financial interests

None noted.

Figures

Figure 1.
Figure 1.. BSI pathogens are present in the gut microbiome at varying relative abundance prior to bloodstream infection.
Relative abundance of microbial reads classified at the species level. Plots show species present at 1.5% relative abundance or greater and thus stacked bars do not necessarily add up to 100%. The BSI causing organism is outlined in black in the bar plot and figure legend for each panel. Timing of BSI and engraftment relative to HCT are available in Table S1. Domination by Escherichia coli (a) and Enterococcus faecium (b) occurs prior to bacteremia. Klebsiella pneumoniae (c) and Staphylococcus epidermidis (d) are present in the gut microbiome prior to BSI at relatively low abundance.
Figure 2.
Figure 2.. Gut and BSI strains from the same patient are more closely related than strains from different patients.
Phylogenetic relatedness between bacterial strains as assessed by StrainSifter. Branch tip colors indicate stool (brown) and bloodstream infection (BSI) (red) samples. Samples from the same patient are more closely phylogenetically related to each other (blue highlight) than to samples from other patients. Days given are relative to BSI. Phylogenetic trees for P. aeruginosa and E. cloacae are not shown, as these species are not observed with sufficient abundance in more than one gut metagenome. Of note, although patient 20’s BSI is classified as S. epidermidis, this strain does not meet the coverage requirements for inclusion in the S. epidermidis phylogenetic tree.
Figure 3.
Figure 3.. Antibiotic resistance gene predictions in bloodstream isolate genomes
Antibiotic resistance genes predicted in bloodstream isolate draft genomes. Antibiotic resistance profiles are similar for different isolates of a given species. Of note, the Staphylococcus epidermidis isolate that was found to be concordant with a strain in the matching gut sample13, S. epidermidis BSI) has a larger number of predicted antibiotic resistance genes compared to the remaining S. epidermidis isolates.

Comment in

References

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Methods references

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