Distinct vaginal microbiome and metabolome profiles in women with preterm delivery following cervical cerclage

Preterm birth (PTB) is a major cause of infant morbidity and mortality. The aim of this study was to investigate the effect of vaginal microbiota and metabolites on the outcome of pregnant women. In this study, a total of 127 pregnant women provided written informed consent prior to enrollment in accordance with the approved institutional guidelines, but only 45 pregnancies met the experimental requirements, and then blood and cervical vaginal fluid (CVF) samples were collected before delivery (at the second week after cervical cerclage). Pregnant women with PTB exhibited high white blood cell and neutrophil contents, high neutrophil-to-lymphocyte ratio (NLR), and high systemic inflammation response index (SIRI) in the blood. Vaginal microbiome revealed that the proportion of beneficial bacteria (including Lactobacillus, [Ruminococcus] gnavus group, and Megamonas) significantly decreased in the PTB group, and the proportion of harmful bacteria (including Desulfovibrionaceae, Helicobacter, and Gardnerella) significantly increased, which is strongly related to the biochemical parameters of blood (white blood cells, neutrophils, NLR, and SIRI). In addition, vaginal metabolomics-based liquid chromatography-Orbitrap-tandem mass spectrometry (LC-Orbitrap-MS/MS) found that the alteration in vaginal metabolites in pregnant women with PTB is involved in starch and sucrose metabolism; arginine and praline metabolism; galactose metabolism; purine metabolism; arginine metabolism; tryptophan metabolism and N-glycan biosynthesis; cysteine and methionine metabolism; taurine and hypotaurine metabolism; amino acid metabolism; propanoate metabolism; valine, leucine, and isoleucine biosynthesis; glycine, serine, and threonine metabolism; and steroid hormone biosynthesis. These results elaborated that distinct vaginal microbiome and metabolome profiles in women with preterm delivery following cervical cerclage provide valuable information for establishing the prediction models for PTB.