Microbial signatures in amniotic fluid at preterm birth and association with bronchopulmonary dysplasia

Birte Staude1,2, Silvia Gschwendtner3, Tina Frodermann1

  • 1Department of General Pediatrics and Neonatology, Justus Liebig University and Universities of Giessen and Marburg Lung Center, Giessen, Germany.

Respiratory Research
|October 16, 2023
PubMed

Insights

Prenatal amniotic fluid bacterial signatures differ in preterm infants, potentially identifying those at risk for bronchopulmonary dysplasia (BPD). These distinct microbial patterns highlight the prenatal origins of BPD.

Area of Science:

  • Microbiology
  • Neonatalogy
  • Genetics

Background:

  • Microbiome dysbiosis is linked to various diseases, including bronchopulmonary dysplasia (BPD).
  • Intra-amniotic infection is a key risk factor for BPD, a multifactorial disease.
  • Recent studies associate lung microbiota colonization with BPD development.

Purpose of the Study:

  • To compare bacterial signatures in amniotic fluid (AF) from intact pregnancies versus preterm deliveries.
  • To analyze variations in AF bacterial signatures across different BPD severity stages.

Main Methods:

  • Prospective observational cohort study.
  • Collected AF samples from intact pregnancies (n=17) and preterm deliveries (<32 weeks, n=126).
  • Utilized 16S rRNA gene metabarcoding to assess bacterial community structure.

Main Results:

  • Preterm delivery AF showed increased 16S rRNA genes, reduced alpha diversity, and altered beta diversity.
  • Lactobacillus and Acetobacter were less abundant, while Fusobacterium, Pseudomonas, Ureaplasma, and Staphylococcus were more prevalent.
  • Moderate/severe BPD AF had Escherichia-Shigella, mild BPD AF had Ureaplasma and Enterococcus enrichment.

Conclusions:

  • Distinct intrauterine bacterial 16S rRNA gene patterns were identified in preterm infants.
  • These prenatal microbial signatures differ from those in intact pregnancies.
  • The findings emphasize the prenatal impact on BPD origins and identify potential risk indicators.
Abstract