BackgroundPreterm birth is one of the leading causes of perinatal morbidity and mortality. Gut microbiome dysbiosis is closely related to adverse pregnancy outcomes. However, the role of the gut microbiome in the pathogenesis of preterm birth remains poorly studied.MethodWe collected fecal samples from 41 women (cases presenting with threatened preterm labor =19, 11 of which delivered preterm; gestational age-matched no-labor controls, all of which delivered at term = 22) were recruited for the study. We performed 16S rRNA amplicon sequencing to compare the composition of the gut microbiome in threatened preterm labor cases and controls and among women who delivered preterm and at term. By annotating taxonomic biomarkers with the Human Oral Microbiome Database, we observed an increased abundance of potential oral-to-gut bacteria in preterm patients.ResultsPatients with preterm birth showed a distinct gut microbiome dysbiosis compared with those who delivered at term. Opportunistic pathogens, particularly Porphyromonas, Streptococcus, Fusobacterium, and Veillonella, were enriched, whereas Coprococcus and Gemmiger were markedly depleted in the preterm group. Most of the enriched bacteria were annotated oral bacteria using the Human Oral Microbiome Database. These potential oral-to-gut bacteria were correlated with clinical parameters that reflected maternal and fetal status.ConclusionsThis study suggests that patients who deliver preterm demonstrate altered gut microbiome that may contain higher common oral bacteria.
Streptococcus agalactiae is a major pathogenic bacterium causing perinatal infections in humans. In the present study, a novel real-time fluorescence loop-mediated isothermal amplification technology was successfully developed and evaluated for the detection of S. agalactiae in a single reaction. Six specific primers were designed to amplify the corresponding six regions of fbs B gene of S. agalactiae, using Bst DNA polymerase with DNA strand displacement activity at a constant temperature for 60 min. The presence of S. agalactiae was indicated by the fluorescence in real-time. Amplification of the targeted gene fragment was optimized with the primer 1 in the current setup. Positive result was only obtained for Sa by Real-LAMP among 10 tested relevant bacterial strains, with the detection sensitivity of 300 pg/µl. Real-LAMP was demonstrated to be a simple and rapid detection tool for S. agalactiae with high specificity and stability, which ensures its wide application and broad prospective utilization in clinical practice for the rapid detection of S. agalactiae.
Background Cervical cancer (CC) is one of the most common malignancies affecting female worldwide. Long non-coding RNAs (lncRNAs) are increasingly indicated as crucial participants and promising therapeutic targets in human cancers. The main objective of this study was to explore the functions and mechanism of LINC00885 in CC. Methods RT-qPCR and western blot were used to detect RNA and protein levels. Functional and mechanism assays were respectively done for the analysis of cell behaviors and molecular interplays. Results Long intergenic non-coding RNA 885 (LINC00885) was discovered to be upregulated in CC tissues and cell lines through bioinformatics analysis and RT-qPCR. Overexpression of LINC00885 promoted proliferation and inhibited apoptosis, whereas its silence exerted opposite effects. The cytoplasmic localization of LINC00885 was ascertained and furthermore, LINC00885 competitively bound with miR-3150b-3p to upregulate BAZ2A expression in CC cells. Rescue assays confirmed that LINC00885 regulated CC proliferation and apoptosis through miR-3150b-3p/BAZ2A axis. Finally, we confirmed that LINC00885 aggravated tumor growth through animal experiments. Conclusions LINC00885 exerted oncogenic function in CC via regulating miR-3150b-3p/BAZ2A axis. These findings suggested LINC00885 might serve as a potential promising therapeutic target for CC patients.
Dengue fever virus (DENV) is a global health threat that is becoming increasingly critical. However, the pathogenesis of dengue has not yet been fully elucidated. In this study, we employed bioinformatics analysis to identify potential biomarkers related to dengue fever and clarify their underlying mechanisms. The results showed that there were 668, 1901, and 8283 differentially expressed genes between the dengue-infected samples and normal samples in the GSE28405, GSE38246, and GSE51808 datasets, respectively. Through overlapping, a total of 69 differentially expressed genes (DEGs) were identified, of which 51 were upregulated and 18 were downregulated. We identified twelve hub genes, including MX1, IFI44L, IFI44, IFI27, ISG15, STAT1, IFI35, OAS3, OAS2, OAS1, IFI6, and USP18. Except for IFI44 and STAT1, the others were statistically significant after validation. We predicted the related microRNAs (miRNAs) of these 12 target genes through the database miRTarBase, and finally obtained one important miRNA: has-mir-146a-5p. In addition, gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were carried out, and a protein–protein interaction (PPI) network was constructed to gain insight into the actions of DEGs. In conclusion, our study displayed the effectiveness of bioinformatics analysis methods in screening potential pathogenic genes in dengue fever and their underlying mechanisms. Further, we successfully predicted IFI44L and IFI6, as potential biomarkers with DENV infection, providing promising targets for the treatment of dengue fever to a certain extent.
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