Whole Genome Analysis of a Non-O1, Non-O139 Vibrio cholerae Detected from Human Blood in China

Non-O1, non-O139 Vibrio cholerae (NOVC) can cause cholera-like diarrhea, but it rarely causes extraintestinal infection, so it is easily overlooked. In this report, we present a case of NOVC detected through blood culture in a 58-year-old male patient with cirrhosis, resulting in severe infection. The patient had been diagnosed with cirrhosis seven years prior and was admitted to the hospital due to abdominal distension and gastrointestinal bleeding. Gram-negative bacilli were isolated from blood cultures and identified as V. cholerae using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and average nucleotide identity (ANI). Moreover, the serum agglutination test showed that the strain was non-O1/non-O139. Further whole genome sequencing and analysis of the strain showed that the strain mainly carried virulence genes tox R, RTX, hly A, T3SS/T6SS, but no resistant genes such as sulII, dfrA1, strB were detected. It provides information for the study of the pathogenic mechanism and drug resistance mechanism of V. cholerae. The patient had severe symptoms and a poor prognosis, indicating that although the NOVC strain infected in this patient had few virulence genes, it was not weak in pathogenicity. It may be caused by the effect of some virulence genes, which should be paid attention to.

Identification of serum prognostic marker miRNAs and construction of microRNA-mRNA networks of esophageal cancer

Esophageal cancer is a common tumor of the digestive system with poor prognosis. This study was to gain a better understanding of the mechanisms involved in esophageal cancer and to identify new prognostic markers. We downloaded the esophageal cancer miRNA expression profile microarray data (GSE113740, GSE112264, GSE122497, GSE113486, and GSE106817) from the GEO database, extracted the esophageal cancer miRNA sequencing data from The Cancer Genome Atlas (TCGA) database, and then used a bioinformatics approach to select common differentially expressed miRNAs (DEMs). Differentially expressed genes (DEGs) were selected by predicting DEM target genes using the miRWalk database and intersecting with differential genes obtained from TCGA database for esophageal cancer. The STRING database was used to obtain protein-protein interaction (PPI) relationships to construct the DEM-DEG network. Furthermore, we selected core genes and core miRNAs associated with esophageal cancer prognosis by performing survival and univariate/multivariate COX analysis on DEMs and DEGs in the network and performed GSEA analysis on core genes alone, and finally the expression of the markers was verified by qPCR in esophageal cancer cell lines Eca109, SKGT-4 and normal esophageal epithelial cells HEEC. Nine DEMs were obtained, of which three were upregulated and six were downregulated, and 326 DEGs were obtained, of which 105 were upregulated and 221 were downregulated. Survival univariate/multivariate COX analysis revealed that five genes, ZBTB16, AQP4, ADCYAP1R1, PDGFD, and VIPR2, and two microRNAs, miR-99a-5p, and miR-508-5p, were related to esophageal cancer prognosis. GSEA analysis showed that the following genes may be involved in esophageal cancer prognosis: ZBTB16 may through the MTOR signaling pathway, AQP4 through the GNRH signaling pathway, ADCYAP1R1 through the PPAR signaling pathway, VIPR2 through the P53 signaling pathway and PDGFD through the PENTOSE-PHOSPHATE signaling pathway.