7 research outputs found

    A MicroRNA Gene Panel Predicts the Vaginal Microbiota Composition

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    The vaginal microbiota plays an essential role in vaginal health. The vaginas of many reproductive-age women are dominated by one of the Lactobacillus species. However, the vaginas of a large number of women are characterized by the colonization of several other anaerobes. Notably, some women with the non-Lactobacillus-dominated vaginal microbiota develop bacterial vaginosis, which has been correlated with sexually transmitted infections and other adverse outcomes. However, interactions and mechanisms linking the vaginal microbiota to host response are still under investigation. There are studies suggesting a link between human microRNAs and gut microbiota, but limited analysis has been carried out on the interplay of microRNAs and vaginal microbiota. In this study, we performed a microRNA expression array profiling on 67 vaginal samples from young Swedish women. MicroRNAs were clustered into distinct groups according to vaginal microbiota composition. Interestingly, 182 microRNAs were significantly elevated in their expression in the non-Lactobacillus-dominated community, suggesting an antagonistic relationship between Lactobacillus and microRNAs. Of the elevated microRNAs, 10 microRNAs displayed excellent diagnostic potential, visualized by receiver operating characteristics analysis. We further validated our findings in 34 independent samples where expression of top microRNA candidates strongly separated the Lactobacillus-dominated community from the non-Lactobacillus-dominated community in the vaginal microbiota. Notably, the Lactobacillus crispatus-dominated community showed the most profound differential microRNA expression compared with the non-Lactobacillus-dominated community. In conclusion, we demonstrate a strong relationship between the vaginal microbiota and numerous genital microRNAs, which may facilitate a deeper mechanistic interplay in this biological niche. IMPORTANCE Vaginal microbiota is correlated with women's health, where a non-Lactobacillus-dominated community predisposes women to a higher risk of disease, including human papillomavirus (HPV). However, the molecular relationship between the vaginal microbiota and host is largely unexplored. In this study, we investigated a link between the vaginal microbiota and host microRNAs in a group of young women. We uncovered an inverse correlation of the expression of microRNAs with the abundance of Lactobacillus species in the vaginal microbiota. Particularly, the expression of microRNA miR-23a-3p and miR-130a-3p, displaying significantly elevated levels in non-Lactobacillus-dominated communities, predicted the bacterial composition of the vaginal microbiota in an independent validation group. Since targeting of microRNAs is explored in the clinical setting, our results warrant investigation of whether microRNA modulation could be used for treating vaginosis recurrence and vaginosis-related diseases. Conversely, commensal bacteria could be used for treating diseases with microRNA aberrations

    Tonsillar microbiota : A cross-sectional study of patients with chronic tonsillitis or tonsillar hypertrophy

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    Chronic tonsillitis (CT) and tonsillar hypertrophy (TH) are common tonsillar diseases that are related to infection and inflammation. Little is known about tonsillar microbiota and its role in CT and TH. This study aims to identify palatine tonsillar microbiota both on the surface and in the core tissues of CT and TH patients. In total, 22 palatine tonsils were removed and collected from CT and TH patients who underwent surgery. The surface and core microbiota in the tonsils of CT and TH patients were compared using 16S rRNA gene sequencing of V3-V4 regions. Differential tonsillar microbiotas were found in the CT versus TH patients and surface versus core tissues. Further, a higher relative abundance of bacterial genera, including Haemophilus, Streptococcus, Neisseria, Capnocytophaga, Kingella, Moraxella, and Lachnospiraceae [G-2] in patients with TH and Dialister, Parvimonas, Bacteroidales [G-2], Aggregatibacter, and Atopobium in patients with CT, was observed. Of these, the differential genera of Dialister, Parvimonas, and Neisseria served as key factors in the tonsillar microbiota network. Notably, four representable tonsillar microbial types were identified, with one, consisting of a higher abundance of Haemophilus and Neisseria, exclusively detected in the TH patients. This study analyzed the different tonsillar microbiota from the surface and core tissues of CT and TH patients. Several bacteria and various microbial types related to CT and TH were identified, along with potential bacterial networks and related immune pathways. IMPORTANCE: The human microbiota has been shown to be functionally connected to infectious and inflammation-related diseases. So far, only limited studies had been performed on tonsillar microbiota, although tonsils play an essential role in the human immune defense system and encountered numerous microorganisms. Our work presented different tonsillar microbiota from surface and core tissues of chronic tonsillitis (CT) and tonsillar hypertrophy (TH) patients. Notably, one tonsillar microbiota type, which contains a higher abundance of Haemophilus and Neisseria, was only detected in the TH patients. Furthermore, certain bacteria, such as Haemophilus, Neisseria, Dialister, and Parvimonas, may serve as microbial biomarkers to discriminate CT patients from TH patients. These data provide important microbiota data in the tonsillar research area and are highly useful for researchers both in the oral microbiome field and clinical field

    Cohort profile : the Swedish Maternal Microbiome project (SweMaMi) - assessing the dynamic associations between the microbiome and maternal and neonatal adverse events

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    Purpose The Swedish Maternal Microbiome (SweMaMi) project was initiated to better understand the dynamics of the microbiome in pregnancy, with longitudinal microbiome sampling, shotgun metagenomics, extensive questionnaires and health registry linkage. Participants Pregnant women were recruited before the 20th gestational week during 2017-2021 in Sweden. In total, 5439 pregnancies (5193 unique women) were included. For 3973 pregnancies (73%), samples were provided at baseline, and for 3141 (58%) at all three timepoints (second and third trimester and postpartum). In total, 38 591 maternal microbiome samples (vaginal, faecal and saliva) and 3109 infant faecal samples were collected. Questionnaires were used to collect information on general, reproductive and mental health, diet and lifestyle, complemented by linkage to the nationwide health registries, also used to follow up the health of the offspring (up to age 10). Findings to date The cohort is fairly representative for the total Swedish pregnant population (data from 2019), with 41% first-time mothers. Women with university level education, born in Sweden, with normal body mass index, not using tobacco-products and aged 30-34 years were slightly over-represented. Future plans The sample and data collection were finalised in November 2021. The next steps are the characterisation of the microbial DNA and linkage to the health and demographic information from the questionnaires and registries. The role of the microbiome on maternal and neonatal outcomes and early-childhood diseases will be explored (including preterm birth, miscarriage) and the role and interaction of other risk factors and confounders (including endometriosis, polycystic ovarian syndrome, diet, drug use). This is currently among the largest pregnancy cohorts in the world with longitudinal design and detailed and standardised microbiome sampling enabling follow-up of both mothers and children. The findings are expected to contribute greatly to the field of reproductive health focusing on pregnancy and neonatal outcomes

    Assessment of In Vitro and In Silico Protocols for Sequence-Based Characterization of the Human Vaginal Microbiome

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    The vaginal microbiome has been connected to a wide range of health outcomes. This has led to a thriving research environment but also to the use of conflicting methodologies to study its microbial composition. Here, we systematically assessed best practices for the sequencing-based characterization of the human vaginal microbiome. As far as 16S rRNA gene sequencing is concerned, the V1-V3 region performed best in silico, but limitations of current sequencing technologies meant that the V3-V4 region performed equally well. Both approaches presented very good agreement with qPCR quantification of key taxa, provided that an appropriate bioinformatic pipeline was used. Shotgun metagenomic sequencing presents an interesting alternative to 16S rRNA gene amplification and sequencing but requires deeper sequencing and more bioinformatic expertise and infrastructure. We assessed different tools for the removal of host reads and the taxonomic annotation of metagenomic reads, including a new, easy-to-build and -use reference database of vaginal taxa. This curated database performed as well as the best-performing previously published strategies. Despite the many advantages of shotgun sequencing, none of the shotgun approaches assessed here agreed with the qPCR data as well as the 16S rRNA gene sequencing. IMPORTANCE The vaginal microbiome has been connected to various aspects of host health, including susceptibility to sexually transmitted infections as well as gynecological cancers and pregnancy outcomes. This has led to a thriving research environment but also to conflicting available methodologies, including many studies that do not report their molecular biological and bioinformatic methods in sufficient detail to be considered reproducible. This can lead to conflicting messages and delay progress from descriptive to intervention studies. By systematically assessing best practices for the characterization of the human vaginal microbiome, this study will enable past studies to be assessed more critically and assist future studies in the selection of appropriate methods for their specific research questions.Correction in: MSPHERE, Volume:5, Issue:6, Article Number:e01253-20, DOI:10.1128/mSphere.01253-20</p

    Vaginal microbiota and human papillomavirus infection among young Swedish women

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    Human papillomavirus (HPV) infection is one of the most common sexually transmitted diseases. To define the HPV-associated microbial community among a high vaccination coverage population, we carried out a cross-sectional study with 345 young Swedish women. The microbial composition and its association with HPV infection, including 27 HPV types, were analyzed. Microbial alpha-diversity was found significantly higher in the HPV-infected group (especially with oncogenic HPV types and multiple HPV types), compared with the HPV negative group. The vaginal microbiota among HPV-infected women was characterized by a larger number of bacterial vaginosis-associated bacteria (BVAB), Sneathia, Prevotella, and Megasphaera. In addition, the correlation analysis demonstrated that twice as many women with non-Lactobacillus-dominant vaginal microbiota were infected with oncogenic HPV types, compared with L. crispatus-dominated vaginal microbiota. The data suggest that HPV infection, especially oncogenic HPV types, is strongly associated with a non-Lactobacillus-dominant vaginal microbiota, regardless of age and vaccination status.De tre första författarna delar förstaförfattarskapet</p

    Tissue-based map of the human proteome

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    Protein expression across human tissues Sequencing the human genome gave new insights into human biology and disease. However, the ultimate goal is to understand the dynamic expression of each of the approximately 20,000 protein-coding genes and the function of each protein. Uhlén et al. now present a map of protein expression across 32 human tissues. They not only measured expression at an RNA level, but also used antibody profiling to precisely localize the corresponding proteins. An interactive website allows exploration of expression patterns across the human body. Science , this issue 10.1126/science.1260419 </jats:p
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