Abstract
ABSTRACTBacterial vaginosis (BV) is a dysbiosis of the vaginal microbiome, characterised by low levels of lacto-bacilli and overgrowth of a diverse group of bacteria, and associated with higher risk of a variety of infections, surgical complications, cancer and spontaneous preterm birth (PTB). Despite the lack of a consistently applicable aetiology, Prevotella spp. are often associated with both BV and PTB and P. bivia has known symbiotic relationships with both Peptostreptococcus anaerobius and Gardnerella vaginalis. Higher risk of PTB can also be predicted by a composite of metabolites linked to bacterial metabolism but their specific bacterial source remains poorly understood. Here we characterise diversity of metabolic strategies among BV associated bacteria and lactobacilli and the symbiotic metabolic relationships between P. bivia and its partners and show how these influence the availability of metabolites associated with BV/PTB and/or pro- or anti-inflammatory immune responses. We confirm a commensal relationship between Pe. anaerobius and P. bivia, refining its mechanism; P. bivia supplies tyrosine, phenylalanine, methionine, uracil and proline, the last of which leads to a substantial increase in overall acetate production. In contrast, our data indicate the relationship between P. bivia and G. vaginalis strains, with sequence variant G2, is mutualistic with outcome dependent on the metabolic strategy of the G. vaginalis strain. Seven G. vaginalis strains could be separated according to whether they performed mixed acid fermentation (MAF) or bifid shunt (BS). In co-culture, P. bivia supplies all G. vaginalis strains with uracil and received substantial amounts of asparagine in return. Acetate production, which is lower in BS strains, then matched that of MAF strains while production of aspartate increased for the latter. Taken together, our data show how knowledge of inter- and intra-species metabolic diversity and the effects of symbiosis may refine our understanding of the mechanism and approach to risk prediction in BV and/or PTB.
Publisher
Cold Spring Harbor Laboratory