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Streptococcus mutans (S. mutans) is the major clinical pathogen responsible for dental caries. Its acid tolerance has been identified as a significant virulence factor for its survival and cariogenicity in acidic conditions. Small RNAs (sRNAs) are recognized as key regulators of virulence and stress adaptation. Here, we constructed three libraries of sRNAs with small size exposed to acidic conditions for the first time, followed by verification using qRT-PCR. The levels of two sRNAs and target genes predicted to be bioinformatically related to acid tolerance were further evaluated under different acid stress conditions (pH 7.5, 6.5, 5.5, and 4.5) at three time points (0.5, 1, and 2 h). Meanwhile, bacterial growth characteristics and vitality were assessed. We obtained 1879 sRNAs with read counts of at least 100. One hundred and ten sRNAs were perfectly mapped to reported msRNAs in S. mutans. Ten out of 18 sRNAs were validated by qRT-PCR. The survival of bacteria declined as the acid was increased from pH 7.5 to 4.5 at each time point. The bacteria can proliferate under each pH except pH 4.5 with time. The levels of sRNAs gradually decreased from pH 7.5 to 5.5, and slightly increased in pH 4.5; however, the expression levels of target mRNAs were up-regulated in acidic conditions than in pH 7.5. These results indicate that some sRNAs are specially induced at acid stress conditions, involving acid adaptation, and provide a new insight into exploring the complex acid tolerance for S. mutans.
Pubmed ID: 27649155 RIS Download
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The Rfam database is a collection of RNA families, each represented by multiple sequence alignments, consensus secondary structures and covariance models (CMs). The families in Rfam break down into three broad functional classes: Non-coding RNA genes, structured cis-regulatory elements and self-splicing RNAs. Typically these functional RNAs often have a conserved secondary structure which may be better preserved than the RNA sequence. The CMs used to describe each family are a slightly more complicated relative of the profile hidden Markov models (HMMs) used by Pfam. CMs can simultaneously model RNA sequence and the structure in an elegant and accurate fashion. Rfam is also available via FTP. You can find data in Rfam in various ways... * Analyze your RNA sequence for Rfam matches * View Rfam family annotation and alignments * View Rfam clan details * Query Rfam by keywords * Fetch families or sequences by NCBI taxonomy * Enter any type of accession or ID to jump to the page for a Rfam family, sequence or genome
View all literature mentionsSoftware for aligning sequencing reads against large reference genome. Consists of three algorithms: BWA-backtrack, BWA-SW and BWA-MEM. First for sequence reads up to 100bp, and other two for longer sequences ranged from 70bp to 1Mbp.
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