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| Content Provider | PubMed Central |
|---|---|
| Author | Wang, Xinhui Li, Xinran Liu, Shiwei Ren, Hang Yang, Mingjuan Ke, Yuehua Huang, Liuyu Liu, Chao Liu, Bo Chen, Zeliang |
| Copyright Year | 2016 |
| Abstract | Molecular detection assays are increasingly becoming routine diagnostic techniques for bacterial infection; however, their sensitivities are restricted by the low concentrations of bacteria in clinical samples. Here, we report a new paradigm for ultrasensitive detection of bacteria. The principle of this approach is that by choosing highly transcribed genes as signature sequences and detecting both DNA and its RNA transcripts, assay sensitivity can be greatly improved. First, signature genes with abundant transcripts were screened by RNA-Seq. We confirmed that RT-PCR efficiently amplifies both DNA and RNA, while PCR amplifies only DNA. Unexpectedly, we found that the RNA extraction efficiency is relatively low, while simplified denaturation was more appropriate for transcript detection. For highly transcribed genes, RT-PCR consistently generated lower cycle threshold (Ct) values than those of PCR. The sensitivity of RT-PCR targeting abundant transcripts could detect quantities as low as one bacterium, which was not possible using PCR. Amplification of different genes among several other common bacteria also confirmed that transcript detection by RT-PCR is more sensitive than is DNA detection by PCR. Therefore, abundant transcript detection represents a universal strategy for ultrasensitive detection of bacteria. |
| Related Links | http://dx.doi.org/10.1038/srep20393 |
| Starting Page | 20393 |
| File Format | |
| ISSN | 20452322 |
| e-ISSN | 20452322 |
| Journal | Scientific Reports |
| Volume Number | 6 |
| Language | English |
| Publisher | Nature Publishing Group |
| Publisher Date | 2016-02-01 |
| Access Restriction | Open |
| Rights Holder | Nature Publishing Group |
| Subject Keyword | Science and technology Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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