Dataset Information

Quantification of bacterial transcripts during infection using competitive reverse transcription-PCR (RT-PCR) and LightCycler RT-PCR.

ABSTRACT: Bacteria have evolved sophisticated regulatory circuits to modulate their gene expression in response to disparate environments. In order to monitor bacterial gene expression and regulation in the host, methods for direct transcript analysis from clinical specimens are needed. For most bacterial infections, amplification of the mRNAs of interest is necessary due to the low numbers of cells present and the low levels of specific transcripts. Here we compare two methods of quantitative reverse transcription-PCR (RT-PCR)-competitive RT-PCR using a one-tube system followed by standard gel analysis and the real-time detection of PCR product formation by fluorescence resonance energy transfer technology using the LightCycler unit. We isolated Staphylococcus aureus RNA directly from clinical specimens obtained from cystic fibrosis patients with chronic S. aureus lung infection and from an animal model of foreign-body infection with no further cultivation of the bacteria. Competitive RT-PCR and LightCycler RT-PCR were tested for their ability to quantify the transcription of a constitutively expressed gyrase gene (gyr) and a highly regulated alpha-toxin gene (hla) of S. aureus. Reproducible results were obtained with both methods. A sensitivity of 10(4) (gyr) and 10(3) (hla) copies, respectively, was reached, which was sufficient for the quantification of transcripts during bacterial infection. Overall, the competitive RT-PCR is a robust technique which does not need special RNA purification. On the negative side, it is labor intensive and time consuming, thus limiting the numbers of samples which can be analyzed at a given time. LightCycler RT-PCR is very susceptible to even traces of inhibitors, but it allows high-throughput processing of samples.

SUBMITTER: Goerke C

PROVIDER: S-EPMC96049 | biostudies-literature | 2001 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantification of bacterial transcripts during infection using competitive reverse transcription-PCR (RT-PCR) and LightCycler RT-PCR.

Goerke C C Bayer M G MG Wolz C C

Clinical and diagnostic laboratory immunology 20010301 2

Bacteria have evolved sophisticated regulatory circuits to modulate their gene expression in response to disparate environments. In order to monitor bacterial gene expression and regulation in the host, methods for direct transcript analysis from clinical specimens are needed. For most bacterial infections, amplification of the mRNAs of interest is necessary due to the low numbers of cells present and the low levels of specific transcripts. Here we compare two methods of quantitative reverse tra ...[more]

PMID: 11238208

Similar Datasets

Project description:Most individuals acutely infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibit mild symptoms. However, 10 to 20% of those infected develop long-term symptoms, referred to as post-coronavirus disease 2019 (COVID-19) condition (PCC). One hypothesis is that PCC might be exacerbated by viral persistence in tissue sanctuaries. Therefore, the accurate detection and quantification of SARS-CoV-2 are not only necessary for viral load monitoring but also crucial for detecting long-term viral persistence and determining whether viral replication is occurring in tissue reservoirs. In this study, the sensitivity and robustness of reverse transcription (RT)-droplet digital PCR (ddPCR) and RT-quantitative PCR (qPCR) techniques have been compared for the detection and quantification of SARS-CoV-2 genomic and subgenomic RNAs from oropharyngeal swabs taken from confirmed SARS-CoV-2-positive, SARS-CoV-2-exposed, and nonexposed individuals as well as from samples from mice infected with SARS-CoV-2. Our data demonstrated that both techniques presented equivalent results in the mid- and high-viral-load ranges. Additionally, RT-ddPCR was more sensitive than RT-qPCR in the low-viral-load range, allowing the accurate detection of positive results in individuals exposed to the virus. Overall, these data suggest that RT-ddPCR might be an alternative to RT-qPCR for detecting low viral loads in samples and for assessing viral persistence in samples from individuals with PCC. IMPORTANCE We developed one-step reverse transcription (RT)-droplet digital PCR (ddPCR) protocols to detect SARS-CoV-2 RNA and compared them to the gold-standard RT-quantitative PCR (RT-qPCR) method. RT-ddPCR was more sensitive than RT-qPCR in the low-viral-load range, while both techniques were equivalent in the mid- and high-viral-load ranges. Overall, these results suggest that RT-ddPCR might be a viable alternative to RT-qPCR when it comes to detecting low viral loads in samples, which is a highly relevant issue for determining viral persistence in as-yet-unknown tissue reservoirs in individuals suffering from post-COVID conditions or long COVID.

Dataset Information

Quantification of bacterial transcripts during infection using competitive reverse transcription-PCR (RT-PCR) and LightCycler RT-PCR.

Publications

Quantification of bacterial transcripts during infection using competitive reverse transcription-PCR (RT-PCR) and LightCycler RT-PCR.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets