Respiratory tract microbiome is closely related to respiratory tract infections, while characterization of oropharyngeal microbiome in recovered coronavirus disease 2019 (COVID-19) patients is not studied. Herein, oropharyngeal swabs are collected from confirmed cases (CCs) with COVID-19 (73 subjects), suspected cases (SCs) (36), confirmed cases who recovered (21), suspected cases who recovered (36), and healthy controls (Hs) (140) and then completed MiSeq sequencing. Oropharyngeal microbial 𝜶-diversity is markedly reduced in CCs versus Hs. Opportunistic pathogens are increased, while butyrate-producing genera are decreased in CCs versus Hs. The classifier based on eight optimal microbial markers is constructed through a random forest model and reached great diagnostic efficacy in both discovery and validation cohorts. Notably, the classifier successfully diagnosed SCs with positive IgG antibody as CCs and is demonstrated from the perspective of the microbiome. Importantly, several genera with significant differences gradually increase and decrease along with recovery from COVID-19. Forty-four oropharyngeal operational taxonomy units (OTUs) are closely correlated with 11 clinical indicators of SARS-CoV-2 infection and Hs based on Spearman correlation analysis. Together, this research is the first to characterize oropharyngeal microbiota in recovered COVID-19 cases and suspected cases, to successfully construct and validate the diagnostic model for COVID-19 and to depict the correlations between microbial OTUs and clinical indicators.
Cholangiocarcinoma (CCA) is the most common malignant tumor of the biliary system with a very poor prognosis. The human microbiome, which is the sum of the genetic information of human microorganisms, plays an important role in regulating the digestion, absorption, immune response, and metabolism of the host. Increasing evidence indicates a close relationship between CCA and the human microbiome. Specific alterations occur in the human microbiome of patients with CCA. Therefore, in this review, we aimed to summarize the recent evidence on dysbiosis in the human microbiome of CCA. Then, we generalized the effect of Helicobacter pylori on CCA. Additionally, the potential mechanism of human microbial dysbiosis promoted the progress of CCA, and its precancerous disease was also explored. Furthermore, the possibility of the human microbiome as a diagnostic and therapeutic target of CCA was discussed.
Objective: The gut microecosystem is the largest microecosystem in the human body and has been proven to be linked to neurological diseases. The main objective of this study was to characterize the fecal microbiome, investigate the differences between epilepsy patients and healthy controls, and evaluate the potential efficacy of the fecal microbiome as a diagnostic tool for epilepsy.Design: We collected 74 fecal samples from epilepsy patients (Eps, n = 24) and healthy controls (HCs, n = 50) in the First Affiliated Hospital of Zhengzhou University and subjected the samples to 16S rRNA MiSeq sequencing and analysis. We set up a train set and a test set, identified the optimal microbial markers for epilepsy after characterizing the gut microbiome in the former and built a diagnostic model, then validated it in the validation group.Results: There were significant differences in microbial communities between the two groups. The α-diversity of the HCs was higher than that of the epilepsy group, but the Venn diagram showed that there were more unique operational taxonomic unit (OTU) in the epilepsy group. At the phylum level, Proteobacteria and Actinobacteriota increased significantly in Eps, while the relative abundance of Bacteroidota increased in HCs. Compared with HCs, Eps were enriched in 23 genera, including Faecalibacterium, Escherichia-Shigella, Subdoligranulum and Enterobacteriaceae-unclassified. In contrast, 59 genera including Bacteroides, Megamonas, Prevotella, Lachnospiraceae-unclassified and Blautia increased in the HCs. In Spearman correlation analysis, age, WBC, RBC, PLT, ALB, CREA, TBIL, Hb and Urea were positively correlated with most of the different OTUs. Seizure-type, course and frequency are negatively correlated with most of the different OTUs. In addition, twenty-two optimal microbial markers were identified by a fivefold cross-validation of the random forest model. In the established train set and test set, the area under the curve was 0.9771 and 0.993, respectively.Conclusion: Our study was the first to characterize the gut microbiome of Eps and HCs in central China and demonstrate the potential efficacy of microbial markers as a noninvasive biological diagnostic tool for epilepsy.
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