Objectives:To enable interactive visualization of the vaginal microbiome across the pregnancy and facilitate discovery of novel insights and generation of new hypotheses. Material and Methods:Vaginal Microbiome Atlas during Pregnancy (VMAP) was created with R shiny to generate visualizations of structured vaginal microbiome data from multiple studies. Results:VMAP (http://vmapapp.org) visualizes 3880 vaginal microbiome samples of 1402 pregnant individuals from 11 studies, aggregated via open-source tool MaLiAmPi. Visualized features include diversity measures, VALENCIA community state types, and composition (phylotypes, taxonomy) that can be filtered by various categories. Discussion:This work represents one of the largest and most geographically diverse aggregations of the vaginal microbiome in pregnancy to date and serves as a user-friendly resource to further analyze vaginal microbiome data and better understand pregnancies and associated outcomes. Conclusion:VMAP can be obtained from https://github.com/msirota/vmap.git and is currently deployed as an online app for non-R users.

Mutations in the FUT2 gene that result in a lack of expression of histo-blood group antigens on secreted glycoproteins may shape the vaginal microbiota with consequences for birth outcome. To test this, we analysed the relationship between secretor status, vaginal microbiota and gestational length in an ethnically diverse cohort of 302 pregnant women, including 82 who delivered preterm. Lactobacillus gasseri and L. jensenii were found to have distinct co-occurrence patterns with other microbial taxa in non-secretors. Moreover, non-secretors with Lactobacillus spp. depleted high diversity vaginal microbiota in early pregnancy had significantly shorter gestational length than Lactobacillus spp. dominated non-secretors (mean of 241.54 days (sd=47.14) versus 266.21 (23.61); P-value=0.0251). Similar gestational length differences were observed between non-secretors with high vaginal diversity and secretors with Lactobacillus spp. dominance (mean of 262.52 days (SD=27.73); p-value=0.0439) or depletion (mean of 266.05 days (SD=20.81); p-value=0.0312). Our data highlight secretor status and blood-group antigen expression as being important mediators of vaginal microbiota-host interactions in the context of preterm birth risk.

Endometrial cancer is a multifactorial disease with inflammatory, metabolic and potentially microbial cues involved in disease pathogenesis. Here we sampled different regions of the reproductive tract (vagina, cervix, endometrium, fallopian tubes and ovaries) of 61 patients and showed that the upper genital tract of a subset of women with and without endometrial cancer harbour microbiota quantitatively and compositionally distinguishable from background contaminants. A microbial continuum, defined by detection of common bacterial species along the genital tract, was noted in most women without cancer while the continuum was less cohesive in endometrial cancer patients. Vaginal microbiota were poorly correlated with rectal microbiota in the studied cohorts. Endometrial cancer was associated with reduced cervicovaginal and rectal bacterial load together with depletion of Lactobacillus species relative abundance, including L. crispatus, increased bacterial diversity and enrichment of Porphyromonas, Prevotella, Peptoniphilus and Anaerococcus in the lower genital tract and endometrium. Treatment of benign and malignant endometrial organoids with L. crispatus conditioned media had minimal impact on cytokine and chemokine profiles. Our findings provide evidence that the upper female reproductive tract of some women contains detectable levels of bacteria, the composition of which is associated with endometrial cancer. Whether this is a cause or consequence of cancer pathophysiology remains to be elucidated.

The vaginal microbiome has been shown to be associated with pregnancy outcomes including preterm birth (PTB) risk. Here we present VMAP: Vaginal Microbiome Atlas during Pregnancy ( http://vmapapp.org ), an application to visualize features of 3,909 vaginal microbiome samples of 1,416 pregnant individuals from 11 studies, aggregated from raw public and newly generated sequences via an open-source tool, MaLiAmPi. Our visualization tool ( http://vmapapp.org ) includes microbial features such as various measures of diversity, VALENCIA community state types (CST), and composition (via phylotypes and taxonomy). This work serves as a resource for the research community to further analyze and visualize vaginal microbiome data in order to better understand both healthy term pregnancies and those associated with adverse outcomes.

Preterm infants are particularly susceptible to bacterial late-onset sepsis (LOS). Diagnosis by blood culture and inflammatory markers have sub-optimal sensitivity and specificity and prolonged reporting times. There is an urgent need for more rapid, accurate adjunctive diagnostics in LOS to improve management and minimise antibiotic exposure. We measured the diagnostic performance of secretory phospholipase A2 type IIA (sPLA2-IIA) in very preterm infants (<30 weeks gestational age) with suspected LOS. Plasma sPLA2-IIA levels were elevated in infants with LOS (n = 28) compared to those without LOS (n = 21; median 30,970 vs. 2534 pg/ml, p < 0.0001). The mean area under the curve was 0.884 (95% CI: 0.771, 0.977) with a sensitivity of 0.907 (95% CI: 0.667, 1.00) and specificity of 0.804 (95% CI: 0.600, 1.00). The positive and negative predictive values were 0.833 (95% CI: 0.664, 0.927) and 0.842 (95% CI: 0.624, 0.945), respectively. This pilot study suggests that sPLA2-IIA may have clinical utility for the early diagnosis of LOS in very preterm infants, potentially informing clinical management and antibiotic stewardship.

Vaginal microbiota-host interactions are linked to preterm birth (PTB), which continues to be the primary cause of global childhood mortality. Due to population size, the majority of PTB occurs in Asia, yet there have been few studies of the pregnancy vaginal microbiota in Asian populations. Here, we characterized the vaginal microbiome of 2689 pregnant Chinese women using metataxonomics and in a subset ( n = 819), the relationship between vaginal microbiota composition, sialidase activity and leukocyte presence and pregnancy outcomes. Vaginal microbiota were most frequently dominated by Lactobacillus crispatus or L. iners , with the latter associated with vaginal leukocyte presence. Women with high sialidase activity were enriched for bacterial vaginosis-associated genera including Gardnerella, Atopobium and Prevotella . Vaginal microbiota composition, high sialidase activity and/or leukocyte presence was not associated with PTB risk suggesting underlying differences in the vaginal microbiota and/or host immune responses of Chinese women, possibly accounting for low PTB rates in this population.

BACKGROUND:Host immune responses during late-onset sepsis (LOS) in very preterm infants are poorly characterised due to a complex and dynamic pathophysiology and challenges in working with small available blood volumes. We present here an unbiased transcriptomic analysis of whole peripheral blood from very preterm infants at the time of LOS.METHODS:RNA-Seq was performed on peripheral blood samples (6-29 days postnatal age) taken at the time of suspected LOS from very preterm infants <30 weeks gestational age. Infants were classified based on blood culture positivity and elevated C-reactive protein concentrations as having confirmed LOS (n = 5), possible LOS (n = 4) or no LOS (n = 9). Bioinformatics and statistical analyses performed included pathway over-representation and protein-protein interaction network analyses. Plasma cytokine immunoassays were performed to validate differentially expressed cytokine pathways.RESULTS:The blood leukocyte transcriptional responses of infants with confirmed LOS differed significantly from infants without LOS (1,317 differentially expressed genes). However, infants with possible LOS could not be distinguished from infants with no LOS or confirmed LOS. Transcriptional alterations associated with LOS included genes involved in pathogen recognition (mainly TLR pathways), cytokine signalling (both pro-inflammatory and inhibitory responses), immune and haematological regulation (including cell death pathways), and metabolism (altered cholesterol biosynthesis). At the transcriptional-level cytokine responses during LOS were characterised by over-representation of IFN-α/β, IFN-γ, IL-1 and IL-6 signalling pathways and up-regulation of genes for inflammatory responses. Infants with confirmed LOS had significantly higher levels of IL-1α and IL-6 in their plasma.CONCLUSIONS:Blood responses in very preterm infants with LOS are characterised by altered host immune responses that appear to reflect unbalanced immuno-metabolic homeostasis.

Objective: The pandemic 2019 Coronavirus disease (COVID-19) is the greatest concern globally. Here we analyzed the epidemiological features of China, South Korea, Italy and Spain to find out the relationship of major public health events and epidemiological curves. Study design: In this study we described and analyzed the epidemiological characteristics of COVID-19 in and outside China. We used GAM to generate the epidemiological curves and simulated infection curves with reported incubation period. Results: The epidemiological curves derived from the GAM suggested that the infection curve can reflect the public health measurements sensitively. Under the massive actions token in China, the infection curve flattened at 23rd of January. While surprisingly, even before Wuhan lockdown and first level response of public emergency in Guangdong and Shanghai, those infection curve came to the reflection point both at 21st of January, which indicated the mask wearing by the public before 21st Jan were the key measure to cut off the transmission. In the countries outside China, infection curves also changed in response to measures, but its rate of decline was much smaller than the curve of China's. Conclusion: The present analysis comparing the epidemiological curves in China, South Korea, Italy and Spain supports the importance of mask wearing by the public. Analysis of the infection curve helped to clarify the impact of important public health events, evaluate the efficiencies of prevention measures, and showed wearing masks in public resulted in significantly reduced daily infected cases.

Neonatal sepsis remains a significant cause of morbidity and mortality especially in the preterm infant population. The ability to promptly and accurately diagnose neonatal sepsis based on clinical evaluation and laboratory blood tests remains challenging. Advances in high-throughput molecular technologies have increased investigations into the utility of transcriptomic, proteomic and metabolomic approaches as diagnostic tools for neonatal sepsis. A systems-level understanding of neonatal sepsis, obtained by using omics-based technologies (at the transcriptome, proteome or metabolome level), may lead to new diagnostic tools for neonatal sepsis. In particular, recent omic-based studies have identified distinct transcriptional signatures and metabolic or proteomic biomarkers associated with sepsis. Despite the emerging need for a systems biology approach, future studies have to address the challenges of integrating multi-omic data with laboratory and clinical meta-data in order to translate outcomes into precision medicine for neonatal sepsis. Omics-based analytical approaches may advance diagnostic tools for neonatal sepsis. More research is needed to validate the recent systems biology findings in order to integrate multi-dimensional data (clinical, laboratory and multi-omic) for future translation into precision medicine for neonatal sepsis. This review will discuss the possible applications of omics-based analyses for identification of new biomarkers and diagnostic signatures for neonatal sepsis, focusing on the immune-compromised preterm infant and considerations for clinical translation.