English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Background  Since its discovery in 2007, the importance of the human gut bacterium  Prevotella copri  ( P. copri ) has been widely recognized with its links to diet and health status and potential as next generation probiotic. Therefore, precise, convenient and cost-effective diagnostic tools for the detection and quantification of  P. copri  from clinical and environmental samples are needed.    Results  In this study, a Sybr Green qPCR protocol for  P. copri  detection and quantification was developed and tested on  P. copri -spiked murine faeces samples targeting both the 16S rRNA gene and  P. copri  genome specific genes. The use of one 16S rRNA primer pair and 2 genome specific primer pairs resulted in at least 10x higher specificity and sensitivity than the primer-only PCR currently cited in the literature, reaching a sensitivity of 10 3  CFU/mL. Furthermore, we showed that the new 16S rRNA primer set provided the best balance of detection of a wide range of  P. copri  strains, while avoiding off-target detection of other  Prevotella  genus species. The quantification of  P. copri  in human stool samples using the new 16S rRNA primers also correlated well with 16S rRNA high throughput MiSeq sequencing data ( r  2  = 0.6604,  p  = 0.0074). The two genome specific primer pairs on the other hand uniquely detect the DSM18205 reference strain, allowing differential detection of indigenous and experimentally administered  P. copri  populations. Finally, it was shown that SYBR green qPCR mixes have an influence on sensitivity and specificity, with Biorad SsoAdvanced Universal SYBR Green Supermix performing the best under our test conditions of six commercially available SYBR green master mixes.    Conclusions  This improved qPCR-based method will allow accurate  P. copri  identification and quantification. Moreover, this methodology can also be applied to identify other bacterial species in complex samples.

Development of a real-time quantitative PCR method for detection and quantification of Prevotella copri