MicroRNAs (miRNAs) are small noncoding RNAs that act as master regulators in many biological processes. miRNAs function mainly by downregulating the expression of their gene targets. Thus, accurate prediction of miRNA targets is critical for characterization of miRNA functions. To this end, we have developed an online database, miRDB, for miRNA target prediction and functional annotations. Recently, we have performed major updates for miRDB. Specifically, by employing an improved algorithm for miRNA target prediction, we now present updated transcriptome-wide target prediction data in miRDB, including 3.5 million predicted targets regulated by 7000 miRNAs in five species. Further, we have implemented the new prediction algorithm into a web server, allowing custom target prediction with user-provided sequences. Another new database feature is the prediction of cell-specific miRNA targets. miRDB now hosts the expression profiles of over 1000 cell lines and presents target prediction data that are tailored for specific cell models. At last, a new web query interface has been added to miRDB for prediction of miRNA functions by integrative analysis of target prediction and Gene Ontology data. All data in miRDB are freely accessible at http://mirdb.org.

Supplementary data are available at Bioinformatics online.

GSD appears to be strongly associated with MetS, and the more the components of MetS, the higher the prevalence of GSD.

Klebsiella spp. are frequently enriched in the gut microbiota of preterm neonates, and overgrowth is associated with necrotizing enterocolitis (NEC), nosocomial infections and late-onset sepsis. Little is known about the genomic and phenotypic characteristics of preterm-associated Klebsiella , as previous studies have focused on the recovery of antimicrobial-resistant isolates or culture-independent molecular analyses. The aim of this study was to better characterize preterm-associated Klebsiella populations using phenotypic and genotypic approaches. Faecal samples from a UK cohort of healthy and sick preterm neonates (n=109) were screened on MacConkey agar to isolate lactose-positive Enterobacteriaceae . Whole-genome sequences were generated for Klebsiella spp., and virulence and antimicrobial resistance genes identified. Antibiotic susceptibility profiling and in vitro macrophage and iron assays were undertaken for the Klebsiella strains. Metapangenome analyses with a manually curated genome dataset were undertaken to examine the diversity of Klebsiella oxytoca and related bacteria in a publicly available shotgun metagenome dataset. Approximately one-tenth of faecal samples harboured Klebsiella spp. ( Klebsiella pneumoniae , 7.3 %; Klebsiella quasipneumoniae , 0.9 %; Klebsiella grimontii , 2.8 %; Klebsiella michiganensis , 1.8 %). Isolates recovered from NEC- and sepsis-affected infants and those showing no signs of clinical infection (i.e. ‘healthy’) encoded multiple β-lactamases. No difference was observed between isolates recovered from healthy and sick infants with respect to in vitro siderophore production (all encoded enterobactin in their genomes). All K. pneumoniae , K. quasipneumoniae , K. grimontii and K. michiganensis faecal isolates tested were able to reside and persist in macrophages, indicating their immune evasion abilities. Metapangenome analyses of published metagenomic data confirmed our findings regarding the presence of K. michiganensis in the preterm gut. There is little difference in the phenotypic and genomic characteristics of Klebsiella isolates recovered from healthy and sick infants. Identification of β-lactamases in all isolates may prove problematic when defining treatment regimens for NEC or sepsis, and suggests that healthy preterm infants contribute to the resistome. Refined analyses with curated sequence databases are required when studying closely related species present in metagenomic data.

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