Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

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

Verbrugghe, Phebe LU ; Van Aken, Olivier LU ; Hållenius, Frida LU orcid and Nilsson, Anne LU orcid (2021) In BMC Microbiology 21(1).
Abstract

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... (More)

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 103 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 (r2 = 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.

(Less)
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Prevotella copri, qPCR, SYBR green
in
BMC Microbiology
volume
21
issue
1
article number
23
publisher
BioMed Central (BMC)
external identifiers
  • scopus:85099105350
  • pmid:33430782
ISSN
1471-2180
DOI
10.1186/s12866-020-02063-4
language
English
LU publication?
yes
id
e7fccf62-ea85-40e2-97ad-dd8dc1562645
date added to LUP
2021-01-19 08:01:38
date last changed
2024-06-13 05:38:14
@article{e7fccf62-ea85-40e2-97ad-dd8dc1562645,
  abstract     = {{<p>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<sup>3</sup> 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<sup>2</sup> = 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.</p>}},
  author       = {{Verbrugghe, Phebe and Van Aken, Olivier and Hållenius, Frida and Nilsson, Anne}},
  issn         = {{1471-2180}},
  keywords     = {{Prevotella copri; qPCR; SYBR green}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{BioMed Central (BMC)}},
  series       = {{BMC Microbiology}},
  title        = {{Development of a real-time quantitative PCR method for detection and quantification of Prevotella copri}},
  url          = {{http://dx.doi.org/10.1186/s12866-020-02063-4}},
  doi          = {{10.1186/s12866-020-02063-4}},
  volume       = {{21}},
  year         = {{2021}},
}