The vaginal microbiome and preterm birth

Fettweis, Jennifer M.; Serrano, Myrna G.; Brooks, J. Paul; Edwards, D.J.; Girerd, Philippe H.; Parikh, Hardik I.; Huang, Bernice; Arodz, Tom; Edupuganti, Laahirie; Glascock, Abigail; Xu, Jie; Jimenez, Nicole R.; Vivadelli, Stephany C.; Fong, Stephen S.; Sheth, Nihar U.; Jean, Sophonie; Lee, Vladimir; Bokhari, Yahya; Lara, Ana; Mistry, Shreni; Duckworth, Robert A.; Bradley, Steven; Kopardé, Vishal N.; Orenda, X. Valentine; Milton, Sarah; Rozycki, Sarah K.; Matveyev, Andrey V.; Wright, Michelle L.; Huzurbazar, Snehalata; Jackson, Eugenie M.; Smirnova, Ekaterina; Korlach, Jonas; Tsai, Yu‐Chih; Dickinson, Molly R.; Brooks, Jamie L.; Drake, Jennifer I.; Chaffin, Donald O.; Sexton, Amber L.; Gravett, Michael G.; Rubens, Craig E.; Wijesooriya, N. Romesh; Hendricks‐Muñoz, Karen D.; Jefferson, Kimberly K.; Strauss, Jerome F.; Buck, Gregory A.

doi:10.1038/s41591-019-0450-2

Cited by 671 publications

(917 citation statements)

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“…Recent publications from iHMP (integrative Human Microbiome Project) provided longitudinal data during pregnancy and showed relatively more L. iners compared to non-pregnant individuals even in women of African American history (DiGiulio et al, 2015; Fettweis et al, 2019; Petricevic et al, 2014; Serrano et al, 2019). In our data, the L. iners versus L. crispatus shift was apparent in women with past pregnancy, and L. iners interestingly showed a negative association with number of spontaneous abortions (Figure 7).…”

Section: Discussionmentioning

confidence: 99%

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The vagino-cervical microbiome as a woman’s life history

Jie

Liang

et al. 2019

Preprint

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The vagina contains at least a billion microbial cells, which are dominated byLactobacilli. Here we perform metagenomic shotgun sequencing on cervical samples from 1148 women. Factors such as pregnancy, delivery histories and breast-feeding were all more important than menstrual cycle in shaping the microbiome. Bifidobacterium breve was seen with older age at sexual debut;Lactobacillus crispatus negatively correlated with pregnancy history; potential markers for lack of menstrual regularity, heavy flow, dysmenorrhea, contraceptives were also identified. Other features such as mood fluctuations and facial speckles could potentially be deduced from the vagino-cervical microbiome. Gut and oral microbiome, plasma vitamins, metals, amino acids and hormones showed associations with the vagino-cervical microbiome. Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact. Highlights:Shotgun sequencing of 1148 vagino-cervical samples reveal subtypes; 1Other omics such as moods and skin features could be predicted by the vagino-cervical 2 bacteria; 3Factors such as delivery mode and breast-feeding associate with the vagino-cervical 4 microbiome; 5With dwindled Lactobacilli, postmenopausal samples are relatively enriched for viruses. 6 7 3 4 vulvovaginal candidiasis (Bradford and Ravel, 2017). The over 90% of human 30 sequences in female reproductive tract samples, in contrast to 1% in feces (Li et al., 31 2018; Methé et al., 2012; Wang and Jia, 2016), has made metagenomic shotgun 32 sequencing more expensive. Most studies of the vaginal microbiota used 16S rRNA 33 gene amplicon sequencing, which lacked a view of the overall microorganism 34 communities including bacteria, archaea, viruses and fungi (Byrd et al., 2018), as well 35 as the functional capacity encoded. Besides infection, studies on current sexual activity 36 and the menstrual cycle occurred naturally to the vaginal microbiota field (Gajer et al., 37 2012; Ravel et al., 2010). However, lasting impacts from other potentially important 38 factors such as sexual debut, pregnancy and breast-feeding have not been looked at in 39 a reasonably large cohort. 40 41 As a sizable reservoir of microbes instead of a transient entity, the female reproductive 42 tract microbiota might also reflect conditions in other body sites. It is however not clear 43 whether other omics in circulation or in the intestine cross-talks with the vagino-cervical 44 microbiome. Intersecting with hormones, metabolic and immune functions, we find it 45intriguing to explore the potential link of the vagino-cervical microbiome to the brain and 46 the face. 47 5 data, immune indices, physical fitness test, facial skin imaging, as well as female life 53 history questionnaire, lifestyle questionnaire, and psychological questionnaire (Figure 1). 54Our work pinpoints other metadata or omics that can predict or be predicted from the 55 microbiota in the female reproductive tr...

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Section: Discussionmentioning

confidence: 99%

“…Interestingly, our cohort generally lacked bacteria known for BV (e.g. (Fettweis et al, 2019; Serrano et al, 2019). ) and also contained less Prevotella compared to some of the surgically sampled individuals.…”

Section: Discussionmentioning

confidence: 99%

The vagino-cervical microbiome as a woman’s life history

Jie

Liang

et al. 2019

Preprint

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“…As such, microbiota diversity is neither good nor bad. The point is easily demonstrated by the human vaginal microbiota, where increased microbial diversity is clearly associated with detrimental effects (bacterial vaginosis, in Afro-American women even associated with compromised birth outcomes; Fettweis et al, 2019). The host genetic background dependency for microbiotahealth associations is well demonstrated in vaginal microbiota studies from Afro-American and White US women (Callahan et al, 2017).…”

Section: The Issue Of Diversitymentioning

confidence: 99%

Problems with the concept of gut microbiota dysbiosis

Brüssow

2019

Microbial Biotechnology

173

137

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Summary The human microbiome research is with the notable exception of fecal transplantation still mostly in a descriptive phase. Part of the difficulty for translating research into medical interventions is due to the large compositional complexity of the microbiome resulting in datasets that need sophisticated statistical methods for their analysis and do not lend to industrial applications. Another part of the difficulty might be due to logical flaws in terminology particularly concerning ‘dysbiosis’ that avoids circular conclusions and is based on sound ecological and evolutionary reasoning. Many case–control studies are underpowered necessitating more meta‐analyses that sort out consistent from spurious dysbiosis–disease associations. We also need for the microbiome a transition from statistical associations to causal relationships with diseases that fulfil a set of modified Koch's postulates for commensals. Disturbingly, the most sophisticated statistical analyses explain only a small percentage of the variance in the microbiome. Microbe–microbe interactions irrelevant to the host and stochastic processes might play a greater role than anticipated. To satisfy the concept of Karl Popper about conjectures and refutations in the scientific process, we should also conduct more experiments that try to refute the role of the commensal gut microbiota for human health and disease.

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“…Microbiomes have been implicated in the development of diseases of nearly all types, both acute and chronic, infectious and systemic. The vaginal microbiome has been implicated in preterm birth (1), the skin microbiome in acne (2) and eczema (3), and the gut microbiome in a spectrum of diseases including inflammatory bowel disease (IBD) (4-6,6-9), anxiety (10)(11)(12), major depressive disorder (13)(14)(15), autism (16)(17)(18)(19)(20), and Parkinson's Disease (21)(22)(23).…”

Section: Microbial Survey Studiesmentioning

confidence: 99%

Decoding the Language of Microbiomes: Leveraging Patterns in 16S Public Data using Word-Embedding Techniques and Applications in Inflammatory Bowel Disease

Tataru

David

2019

Preprint

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Microbiomes are complex ecological systems that play crucial roles in understanding natural phenomena from human disease to climate change. Especially in human gut microbiome studies, where collecting clinical samples can be arduous, the number of taxa considered in any one study often exceeds the number of samples ten to one hundred-fold. This discrepancy decreases the power of studies to identify meaningful differences between samples, increases the likelihood of false positive results, and subsequently limits reproducibility. Despite the vast collections of microbiome data already available, biome-specific patterns of microbial structure are not currently leveraged to inform studies. Instead, most microbiome survey studies focus on differential abundance testing per taxa in pursuit of specific biomarkers for a given phenotype. This methodology assumes differences in individual species, genera, or families can be used to distinguish between microbial communities and ignores community-level response. In this paper, we propose to leverage public microbiome databases to shift the analysis paradigm from a focus on taxonomic counts to a focus on comprehensive properties that more completely characterize microbial community members' function and environmental relationships. We learn these properties by applying an embedding algorithm to quantify taxa co-occurrence patterns in over 18,000 samples from the American Gut Project (AGP) microbiome crowdsourcing effort. The resulting set of embeddings transforms human gut microbiome data from thousands of taxa counts to a latent variable landscape of only one hundred "properties", or contextual relationships. We then compare the predictive power of models trained using properties, normalized taxonomic count 1 data, and another commonly used dimensionality reduction method, Principal Component Analysis in categorizing samples from individuals with inflammatory bowel disease (IBD) and healthy controls. We show that predictive models trained using property data are the most accurate, robust, and generalizable, and that property-based models can be trained on one dataset and deployed on another with positive results. Furthermore, we find that these properties can be interpreted in the context of current knowledge; properties correlate significantly with known metabolic pathways, and distances between taxa in "property space" roughly correlate with their phylogenetic distances. Using these properties, we are able to extract known and new bacterial metabolic pathways associated with inflammatory bowel disease across two completely independent studies.More broadly, this paper explores a reframing of the microbiome analysis mindset, from taxonomic counts to comprehensive community-level properties. By providing a set of pre-trained embeddings, we allow any V4 16S amplicon study to leverage and apply the publicly informed properties presented to increase the statistical power, reproducibility, and generalizability of analysis. References

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The vaginal microbiome and preterm birth

Cited by 671 publications

References 76 publications

The vagino-cervical microbiome as a woman’s life history

The vagino-cervical microbiome as a woman’s life history

Problems with the concept of gut microbiota dysbiosis

Decoding the Language of Microbiomes: Leveraging Patterns in 16S Public Data using Word-Embedding Techniques and Applications in Inflammatory Bowel Disease

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