<i>Prevotella</i>are major contributors of sialidases in the human vaginal microbiome

Pelayo, Paula; Hussain, Fatima A.; Werlang, Caroline A.; Wu, Chloe; Woolston, Benjamin M.; Ribbeck, Katharina; Kwon, Douglas S.; Balskus, Emily P.

doi:10.1101/2024.01.09.574895

Cited by 5 publications

References 46 publications

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Prevotella are major contributors of sialidases in the human vaginal microbiome

Pelayo,

Hussain,

Werlang

et al. 2024

Proc. Natl. Acad. Sci. U.S.A.

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Elevated bacterial sialidase activity in the female genital tract is strongly associated with poor health outcomes including preterm birth and bacterial vaginosis (BV). These negative effects may arise from sialidase-mediated degradation of the protective mucus layer in the cervicovaginal environment. Prior biochemical studies of vaginal bacterial sialidases have focused solely on the BV-associated organism Gardnerella vaginalis . Despite their implications for sexual and reproductive health, sialidases from other vaginal bacteria have not been characterized. Here, we show that vaginal Prevotella species produce sialidases that possess variable activity toward mucin substrates. The sequences of sialidase genes and their presence are largely conserved across clades of Prevotella from different geographies, hinting at their importance globally. Finally, we find that Prevotella sialidase genes and transcripts, including those encoding mucin-degrading sialidases from Prevotella timonensis , are highly prevalent and abundant in human vaginal genomes and transcriptomes. Together, our results identify Prevotella as a critical source of sialidases in the vaginal microbiome, improving our understanding of this detrimental bacterial activity.

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Prevotella are major contributors of sialidases in the human vaginal microbiome

Pelayo,

Hussain,

Werlang

et al. 2024

Proc. Natl. Acad. Sci. U.S.A.

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Glycoengineering with neuraminic acid analogs to label lipooligosaccharides and detect native sialyltransferase activity in Gram-negative bacteria

Alvarado Melendez,

de Jong,

Hartman

et al. 2024

Preprint

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Lipooligosaccharides (LOS) are the most abundant cell surface glycoconjugates on the outer membrane of Gram-negative bacteria. They play important roles in host-microbe interactions. Certain Gram-negative pathogenic bacteria cap their LOS with the sialic acid,N-acetylneuraminic acid (Neu5Ac), to mimic host glycans that among others protects these bacteria from recognition by the hosts immune system. This process of molecular mimicry is not fully understood and remains under investigated. To explore the functional role of sialic acid-capped lipooligosaccharides (LOS) at the molecular level, it is important to have tools readily available for the detection and manipulation of both Neu5Ac on glycoconjugates and the involved sialyltransferases, preferably in live bacteria. We and others have shown that the native sialyltransferases of some Gram-negative bacteria can incorporate extracellular unnatural sialic acid nucleotides onto their LOS. We here report on the expanded use of native bacterial sialyltransferases to incorporate neuraminic acids analogs with a reporter group into the LOS of a variety of Gram-negative bacteria. We show that this approach offers a quick strategy to screen bacteria for the expression of functional sialyltransferases and the ability to use exogenous CMP-Neu5Ac to decorate their glycoconjugates. For selected bacteria we also show this strategy complements two other glycoengineering techniques, Metabolic Oligosaccharide Engineering (MOE) and Selective Exo-Enzymatic Labelling (SEEL), and that together they provide tools to modify, label, detect and visualize sialylation of bacterial LOS.

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Early prediction of preeclampsia using the first trimester vaginal microbiome

Kindschuh,

Austin,

Meydan

et al. 2024

Preprint

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Preeclampsia is a severe obstetrical syndrome which contributes to 10-15% of all maternal deaths. Although the mechanisms underlying systemic damage in preeclampsia--such as impaired placentation, endothelial dysfunction, and immune dysregulation--are well studied, the initial triggers of the condition remain largely unknown. Furthermore, although the pathogenesis of preeclampsia begins early in pregnancy, there are no early diagnostics for this life-threatening syndrome, which is typically diagnosed much later, after systemic damage has already manifested. Here, we performed deep metagenomic sequencing and multiplex immunoassays of vaginal samples collected during the first trimester from 124 pregnant individuals, including 62 who developed preeclampsia with severe features. We identified multiple significant associations between vaginal immune factors, microbes, clinical factors, and the early pathogenesis of preeclampsia. These associations vary with BMI, and stratification revealed strong associations between preeclampsia and Bifidobacterium spp., Prevotella timonensis, and Sneathia vaginalis. Finally, we developed machine learning models that predict the development of preeclampsia using this first trimester data, collected ~5.7 months prior to clinical diagnosis, with an auROC of 0.78. We validated our models using data from an independent cohort (MOMS-PI), achieving an auROC of 0.80. Our findings highlight robust associations among the vaginal microbiome, local host immunity, and early pathogenic processes of preeclampsia, paving the way for early detection, prevention and intervention for this devastating condition.

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Prevotellaare major contributors of sialidases in the human vaginal microbiome

Cited by 5 publications

References 46 publications

Prevotella are major contributors of sialidases in the human vaginal microbiome

Prevotella are major contributors of sialidases in the human vaginal microbiome

Glycoengineering with neuraminic acid analogs to label lipooligosaccharides and detect native sialyltransferase activity in Gram-negative bacteria

Early prediction of preeclampsia using the first trimester vaginal microbiome

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