Browsing by Author "Cheng, Yeong-Nan"

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miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions
(2018-01-04)
Chou, Chih-Hung
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Shrestha, Sirjana
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Yang, Chi-Dung
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Chang, Nai-Wen
;
Lin, Yu-Ling
MicroRNAs (miRNAs) are small non-coding RNAs of similar to 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased similar to 1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.
Vaginal microbiome variances in sample groups categorized by clinical criteria of bacterial vaginosis
(2018-12-31)
Chen, Hui-Mei
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Chang, Tzu-Hao
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Lin, Feng-Mao
;
Liang, Chao
;
Chiu, Chih-Min
BackgroundOne of the most common and recurrent vaginal infections is bacterial vaginosis (BV). The diagnosis is based on changes to the normal vaginal microbiome; however, the normal microbiome appears to differ according to reproductive status and ethnicity, and even among individuals within these groups. The Amsel criteria and Nugent score test are widely used for diagnosing BV; however, these tests are based on different criteria, and so may indicate distinct changes in the vaginal microbial community. Nevertheless, few studies have compared the results of these test against metagenomics analysis.MethodsVaginal flora samples from 77 participants were classified according to the Amsel criteria and Nugent score test. The microbiota composition was analyzed using 16S ribosome RNA gene amplicon sequencing. Bioinformatics analysis and multivariate statistical analysis were used to evaluate the microbial diversity and function.ResultsOnly 3 % of the participants diagnosed BV negative using the Amsel criteria (A-) were BV-positive according to the Nugent score test (N+), while over half of the BV-positive patients using the Amsel criteria (A+) were BV-negative according to the Nugent score test (N-). Thirteen genera showed significant differences in distribution among BV status defined by BV tests (e.g., A-N-, A+N- and A+N+). Variations in the four most abundant taxa, Lactobacillus, Gardnerella, Prevotella, and Escherichia, were responsible for most of this dissimilarity. Furthermore, vaginal microbial diversity differed significantly among the three groups classified by the Nugent score test (N-, N+, and intermediate flora), but not between the Amsel criteria groups. Numerous predictive microbial functions, such as bacterial chemotaxis and bacterial invasion of epithelial cells, differed significantly among multiple BV test, but not between the A- and A+ groups.ConclusionsMetagenomics analysis can greatly expand our current understanding of vaginal microbial diversity in health and disease. Metagenomics profiling may also provide more reliable diagnostic criteria for BV testing.