P3-44 The Step-by-Step RT-quality Assurance Procedure for Reverse Transcription Quantitative PCR: Illustration with the Bacillus weihenstephanensis Acid-resistance Biomarkers

Wednesday, July 31, 2013
Exhibit Hall (Charlotte Convention Center)
Noemie Desriac, ADRIA Development, Quimper, France
Florence Postollec, ADRIA Development, Quimper, France
Louis Coroller, LUBEM-UMT 08.3 PHYSI'Opt, Quimper, France
Daniele Sohier, ADRIA, Quimper, France
Introduction: Gene expression levels are recognized as relevant biomarkers to describe bacterial behavior and fitness. The use of reverse transcription quantitative PCR (RT-qPCR) enables accurate, sensitive, quantitative and fast measurements of RNAs. However, numerous critical points may arise throughout the entire RT-qPCR workflow, strongly influencing the robustness of the method, and thus the reliability of the results.

Purpose: This study describes appropriate step-by-step RT-qPCR quality controls implied for the selection and quantification of B. weihenstephanensisresistance biomarkers.

Methods: The robustness of the developed RT-qPCR method was assessed from the experimental design to the sample extraction, reverse transcription and quality controls.

Results: Primers and probes of 36 genes showed qPCR efficiency from 92% to 104%, r2 at least of 0.980 and closed intercept of 43.72 ± 0.98. The linearity and the repeatability of the RNA extraction was assessed from 3 log of CFU.ml-1 to 8 log CFU.ml-1. The linear correlation coefficient was equal to 0.99, with a slope of 1.01 and the intercept close to 0, with estimated bacterial concentrations ranging from 2.8 ± 0.2 to 7.8 ± 0.03 log CFU.ml-1. RNA extracted from bacterial cells upon sub-lethal conditions gave RQI value greater than 5. For cells submitted to lethal conditions, a repeatable RQI close to 3 was estimated. Efficient removal of contaminating genomic DNAs was estimated over 100 bacterial samples and. No significant variation in the estimated copy numbers (P < 0.05) of RNA samples was found underlying the absence of both reverse transcription and qPCR inhibitors. Using 51 bacterial samples, the calculated M value of 3 reference genes (tuf,16S, 23S) were lower than 1.5 underlining satisfying expression stability to perform RT-qPCR data normalization.

Significance: Provided appropriate controls, RT-qPCR enables relevant gene expression quantification to select acid resistance biomarkers that will further be used to increment bacterial physiology in behavior prediction.