Vaginal microbiome topic modeling of laboring Ugandan women with and without fever

Abstract The composition of the maternal vaginal microbiome influences the duration of pregnancy, onset of labor, and even neonatal outcomes. Maternal microbiome research in sub-Saharan Africa has focused on non-pregnant and postpartum composition of the vaginal microbiome. Here we aimed to illustra...

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Autores principales: Mercedeh Movassagh, Lisa M. Bebell, Kathy Burgoine, Christine Hehnly, Lijun Zhang, Kim Moran, Kathryn Sheldon, Shamim A. Sinnar, Edith Mbabazi-Kabachelor, Elias Kumbakumba, Joel Bazira, Moses Ochora, Ronnie Mulondo, Brian Kaaya Nsubuga, Andrew D. Weeks, Melissa Gladstone, Peter Olupot-Olupot, Joseph Ngonzi, Drucilla J. Roberts, Frederick A. Meier, Rafael A. Irizarry, James R. Broach, Steven J. Schiff, Joseph N. Paulson
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Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/aec5a945eb0b423e9ee84dede5fe278d
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spelling oai:doaj.org-article:aec5a945eb0b423e9ee84dede5fe278d2021-12-02T17:41:18ZVaginal microbiome topic modeling of laboring Ugandan women with and without fever10.1038/s41522-021-00244-12055-5008https://doaj.org/article/aec5a945eb0b423e9ee84dede5fe278d2021-09-01T00:00:00Zhttps://doi.org/10.1038/s41522-021-00244-1https://doaj.org/toc/2055-5008Abstract The composition of the maternal vaginal microbiome influences the duration of pregnancy, onset of labor, and even neonatal outcomes. Maternal microbiome research in sub-Saharan Africa has focused on non-pregnant and postpartum composition of the vaginal microbiome. Here we aimed to illustrate the relationship between the vaginal microbiome of 99 laboring Ugandan women and intrapartum fever using routine microbiology and 16S ribosomal RNA gene sequencing from two hypervariable regions (V1–V2 and V3–V4). To describe the vaginal microbes associated with vaginal microbial communities, we pursued two approaches: hierarchical clustering methods and a novel Grades of Membership (GoM) modeling approach for vaginal microbiome characterization. Leveraging GoM models, we created a basis composed of a preassigned number of microbial topics whose linear combination optimally represents each patient yielding more comprehensive associations and characterization between maternal clinical features and the microbial communities. Using a random forest model, we showed that by including microbial topic models we improved upon clinical variables to predict maternal fever. Overall, we found a higher prevalence of Granulicatella, Streptococcus, Fusobacterium, Anaerococcus, Sneathia, Clostridium, Gemella, Mobiluncus, and Veillonella genera in febrile mothers, and higher prevalence of Lactobacillus genera (in particular L. crispatus and L. jensenii), Acinobacter, Aerococcus, and Prevotella species in afebrile mothers. By including clinical variables with microbial topics in this model, we observed young maternal age, fever reported earlier in the pregnancy, longer labor duration, and microbial communities with reduced Lactobacillus diversity were associated with intrapartum fever. These results better defined relationships between the presence or absence of intrapartum fever, demographics, peripartum course, and vaginal microbial topics, and expanded our understanding of the impact of the microbiome on maternal and potentially neonatal outcome risk.Mercedeh MovassaghLisa M. BebellKathy BurgoineChristine HehnlyLijun ZhangKim MoranKathryn SheldonShamim A. SinnarEdith Mbabazi-KabachelorElias KumbakumbaJoel BaziraMoses OchoraRonnie MulondoBrian Kaaya NsubugaAndrew D. WeeksMelissa GladstonePeter Olupot-OlupotJoseph NgonziDrucilla J. RobertsFrederick A. MeierRafael A. IrizarryJames R. BroachSteven J. SchiffJoseph N. PaulsonNature PortfolioarticleMicrobial ecologyQR100-130ENnpj Biofilms and Microbiomes, Vol 7, Iss 1, Pp 1-10 (2021)
institution DOAJ
collection DOAJ
language EN
topic Microbial ecology
QR100-130
spellingShingle Microbial ecology
QR100-130
Mercedeh Movassagh
Lisa M. Bebell
Kathy Burgoine
Christine Hehnly
Lijun Zhang
Kim Moran
Kathryn Sheldon
Shamim A. Sinnar
Edith Mbabazi-Kabachelor
Elias Kumbakumba
Joel Bazira
Moses Ochora
Ronnie Mulondo
Brian Kaaya Nsubuga
Andrew D. Weeks
Melissa Gladstone
Peter Olupot-Olupot
Joseph Ngonzi
Drucilla J. Roberts
Frederick A. Meier
Rafael A. Irizarry
James R. Broach
Steven J. Schiff
Joseph N. Paulson
Vaginal microbiome topic modeling of laboring Ugandan women with and without fever
description Abstract The composition of the maternal vaginal microbiome influences the duration of pregnancy, onset of labor, and even neonatal outcomes. Maternal microbiome research in sub-Saharan Africa has focused on non-pregnant and postpartum composition of the vaginal microbiome. Here we aimed to illustrate the relationship between the vaginal microbiome of 99 laboring Ugandan women and intrapartum fever using routine microbiology and 16S ribosomal RNA gene sequencing from two hypervariable regions (V1–V2 and V3–V4). To describe the vaginal microbes associated with vaginal microbial communities, we pursued two approaches: hierarchical clustering methods and a novel Grades of Membership (GoM) modeling approach for vaginal microbiome characterization. Leveraging GoM models, we created a basis composed of a preassigned number of microbial topics whose linear combination optimally represents each patient yielding more comprehensive associations and characterization between maternal clinical features and the microbial communities. Using a random forest model, we showed that by including microbial topic models we improved upon clinical variables to predict maternal fever. Overall, we found a higher prevalence of Granulicatella, Streptococcus, Fusobacterium, Anaerococcus, Sneathia, Clostridium, Gemella, Mobiluncus, and Veillonella genera in febrile mothers, and higher prevalence of Lactobacillus genera (in particular L. crispatus and L. jensenii), Acinobacter, Aerococcus, and Prevotella species in afebrile mothers. By including clinical variables with microbial topics in this model, we observed young maternal age, fever reported earlier in the pregnancy, longer labor duration, and microbial communities with reduced Lactobacillus diversity were associated with intrapartum fever. These results better defined relationships between the presence or absence of intrapartum fever, demographics, peripartum course, and vaginal microbial topics, and expanded our understanding of the impact of the microbiome on maternal and potentially neonatal outcome risk.
format article
author Mercedeh Movassagh
Lisa M. Bebell
Kathy Burgoine
Christine Hehnly
Lijun Zhang
Kim Moran
Kathryn Sheldon
Shamim A. Sinnar
Edith Mbabazi-Kabachelor
Elias Kumbakumba
Joel Bazira
Moses Ochora
Ronnie Mulondo
Brian Kaaya Nsubuga
Andrew D. Weeks
Melissa Gladstone
Peter Olupot-Olupot
Joseph Ngonzi
Drucilla J. Roberts
Frederick A. Meier
Rafael A. Irizarry
James R. Broach
Steven J. Schiff
Joseph N. Paulson
author_facet Mercedeh Movassagh
Lisa M. Bebell
Kathy Burgoine
Christine Hehnly
Lijun Zhang
Kim Moran
Kathryn Sheldon
Shamim A. Sinnar
Edith Mbabazi-Kabachelor
Elias Kumbakumba
Joel Bazira
Moses Ochora
Ronnie Mulondo
Brian Kaaya Nsubuga
Andrew D. Weeks
Melissa Gladstone
Peter Olupot-Olupot
Joseph Ngonzi
Drucilla J. Roberts
Frederick A. Meier
Rafael A. Irizarry
James R. Broach
Steven J. Schiff
Joseph N. Paulson
author_sort Mercedeh Movassagh
title Vaginal microbiome topic modeling of laboring Ugandan women with and without fever
title_short Vaginal microbiome topic modeling of laboring Ugandan women with and without fever
title_full Vaginal microbiome topic modeling of laboring Ugandan women with and without fever
title_fullStr Vaginal microbiome topic modeling of laboring Ugandan women with and without fever
title_full_unstemmed Vaginal microbiome topic modeling of laboring Ugandan women with and without fever
title_sort vaginal microbiome topic modeling of laboring ugandan women with and without fever
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/aec5a945eb0b423e9ee84dede5fe278d
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