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Introduction: The deregulation of lncRNAs expression has been associated with neuronal damage in Alzheimer's disease (AD), but how or whether they can influence its onset is still unknown. We investigated 2 RNA-seq datasets consisting, respectively, of the hippocampal and fusiform gyrus transcriptomic profile of AD patients, matched with non-demented controls. Methods: We performed a differential expression analysis, a gene correlation network analysis (WGCNA) and a pathway enrichment analysis of two RNA-seq datasets. Results: We found deregulated lncRNAs in common between hippocampus and fusiform gyrus and deregulated gene groups associated to functional pathways related to neurotransmission and memory consolidation. lncRNAs, co-expressed with known AD-related coding genes, were identified from the prioritized modules of both brain regions. Discussion: We found common deregulated lncRNAs in the AD hippocampus and fusiform gyrus, that could be considered common signatures of AD pathogenesis, providing an important source of information for understanding the molecular changes of AD.
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BACKGROUND: The endometrium remains a difficult tissue for the analysis of microbiota, mainly due to the low bacterial presence and the sampling procedures. Among its pathologies, endometrial cancer has not yet been completely investigated for its relationship with microbiota composition. In this work, we report on possible correlations between endometrial microbiota dysbiosis and endometrial cancer. METHODS: Women with endometrial cancer at various stages of tumor progression were enrolled together with women with a benign polymyomatous uterus as the control. Analyses were performed using biopsies collected at two specific endometrial sites during the surgery. This study adopted two approaches: the absolute quantification of the bacterial load, using droplet digital PCR (ddPCR), and the analysis of the bacterial composition, using a deep metabarcoding NGS procedure. RESULTS: ddPCR provided the first-ever assessment of the absolute quantification of bacterial DNA in the endometrium, confirming a generally low microbial abundance. Metabarcoding analysis revealed a different microbiota distribution in the two endometrial sites, regardless of pathology, accompanied by an overall higher prevalence of pathogenic bacterial genera in cancerous tissues. CONCLUSIONS: These results pave the way for future studies aimed at identifying potential biomarkers and gaining a deeper understanding of the role of bacteria associated with tumors.
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To date several studies address the important role of gut microbiome and its interplay with the human host in the health and disease status. However, the selection of a universal sampling matrix representative of the microbial biodiversity associated with the gastrointestinal (GI) tract, is still challenging. Here we present a study in which, through a deep metabarcoding analysis of the 16S rRNA gene, we compared two sampling matrices, feces (F) and colon washing feces (CWF), in order to evaluate their relative effectiveness and accuracy in representing the complexity of the human gut microbiome. A cohort of 30 volunteers was recruited and paired F and CWF samples were collected from each subject. Alpha diversity analysis confirmed a slightly higher biodiversity of CWF compared to F matched samples. Likewise, beta diversity analysis proved that paired F and CWF microbiomes were quite similar in the same individual, but remarkable inter-individual variability occurred among the microbiomes of all participants. Taxonomic analysis in matched samples was carried out to investigate the intra and inter individual/s variability. Firmicutes, Bacteroidota, Proteobacteria and Actinobacteriota were the main phyla in both F and CWF samples. At genus level, Bacteirodetes was the most abundant in F and CWF samples, followed by Faecalibacterium, Blautia and Escherichia-Shigella. Our study highlights an inter-individual variability greater than intra-individual variability for paired F and CWF samples. Indeed, an overall higher similarity was observed across matched F and CWF samples, suggesting, as expected, a remarkable overlap between the microbiomes inferred using the matched F and CWF samples. Notably, absolute quantification of total 16S rDNA by droplet digital PCR (ddPCR) revealed comparable overall microbial load between paired F and CWF samples. We report here the first comparative study on fecal and colon washing fecal samples for investigating the human gut microbiome and show that both types of samples may be used equally for the study of the gut microbiome. The presented results suggest that the combined use of both types of sampling matrices could represent a suitable choice to obtain a more complete overview of the human gut microbiota for addressing different biological and clinical questions.