Gut Dysbiosis With Bacilli Dominance and Accumulation of Fermentation Products Precedes Late-onset Sepsis in Preterm Infants

Authors:

Graspeutner S, Waschina S, Künzel S, Twisselmann N, Rausch TK, Cloppenburg-Schmidt K, Zimmermann J, Viemann D, Herting E, Göpel W, Baines JF, Kaleta C, Rupp J, Härtel C, Pagel J

Year of publication:

2019

Volume:

69

Issue:

2

ISSN:

1058-4838

Journal (long):

Clinical Infectious Diseases

Journal (short):

Clin. Infect. Dis.

Impact factor:

7.710

Abstract:

Background: Gut dysbiosis has been suggested as a major risk factor for the development of late-onset sepsis (LOS), a main cause of mortality and morbidity in preterm infants. We aimed to assess specific signatures of the gut microbiome, including metabolic profiles, in preterm infants <34 weeks of gestation preceding LOS. Methods: In a single-center cohort, fecal samples from preterm infants were prospectively collected during the period of highest vulnerability for LOS (days 7, 14, and 21 of life). Following 16S rRNA gene profiling, we assessed microbial community function using microbial metabolic network modeling. Data were adjusted for gestational age and use of probiotics. Results: We studied stool samples from 71 preterm infants with LOS and 164 unaffected controls (no LOS/necrotizing enterocolitis). In most cases, the bacteria isolated in diagnostic blood culture corresponded to the genera in the gut microbiome. LOS cases had a decelerated development of microbial diversity. Before onset of disease, LOS cases had specific gut microbiome signatures with higher abundance of Bacilli (specifically coagulase-negative Staphylococci) and a lack of anaerobic bacteria. In silico modeling of bacterial community metabolism suggested accumulation of the fermentation products ethanol and formic acid in LOS cases before the onset of disease. Conclusions: Intestinal dysbiosis preceding LOS is characterized by an accumulation of Bacilli and their fermentation products and a paucity of anaerobic bacteria. Early microbiome and metabolic patterns may become a valuable biomarker to guide individualized prevention strategies of LOS in highly vulnerable populations.

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