Detection of live and antibiotic-killed bacteria by quantitative real-time PCR of specific fragments of rRNA.

Assessing bacterial viability by molecular markers might help accelerate the measurement of antibiotic-induced killing. This study investigated whether rRNA could be suitable for this purpose. Cultures of penicillin-susceptible and penicillin-tolerant (Tol1 mutant) Streptococcus gordonii were exposed to mechanistically different penicillin and levofloxacin. Bacterial survival was assessed by viable counts and compared to quantitative real-time PCR amplification of either the 16S rRNA genes or the 16S rRNA, following reverse transcription. Penicillin-susceptible S. gordonii lost > or =4 log(10) CFU/ml of viability over 48 h of penicillin treatment. In comparison, the Tol1 mutant lost < or =1 log(10) CFU/ml. Amplification of a 427-bp fragment of 16S rRNA genes yielded amplicons that increased proportionally to viable counts during bacterial growth but did not decrease during drug-induced killing. In contrast, the same 427-bp fragment amplified from 16S rRNA paralleled both bacterial growth and drug-induced killing. It also differentiated between penicillin-induced killing of the parent and the Tol1 mutant (> or =4 log(10) CFU/ml and < or =1 log(10) CFU/ml, respectively) and detected killing by mechanistically unrelated levofloxacin. Since large fragments of polynucleotides might be degraded faster than smaller fragments, the experiments were repeated by amplifying a 119-bp region internal to the original 427-bp fragment. The amount of 119-bp amplicons increased proportionally to viability during growth but remained stable during drug treatment. Thus, 16S rRNA was a marker of antibiotic-induced killing, but the size of the amplified fragment was critical for differentiation between live and dead bacteria.

Semiquantitative RT-PCR measurement of gene expression in rat tissues including a correction for varying cell size and number

Background: Current methodology of gene expression analysis limits the possibilities of comparison between cells/tissues of organs in which cell size and/or number changes as a consequence of the study (e.g. starvation). A method relating the abundance of specific mRNA copies per cell may allow direct comparison or different organs and/or changing physiological conditions. Methods: With a number of selected genes, we analysed the relationship of the number of bases and the fluorescence recorded at a present level using cDNA standards. A lineal relationship was found between the final number of bases and the length of the transcript. The constants of this equation and those of the relationship between fluorescence and number of bases in cDNA were determined and a general equation linking the length of the transcript and the initial number of copies of mRNA was deduced for a given pre-established fluorescence setting. This allowed the calculation of the concentration of the corresponding mRNAs per g of tissue. The inclusion of tissue RNA and the DNA content per cell, allowed the calculation of the mRNA copies per cell. Results: The application of this procedure to six genes: Arbp, cyclophilin, ChREBP, T4 deiodinase 2, acetyl-CoA carboxylase 1 and IRS-1, in liver and retroperitoneal adipose tissue of food-restricted rats allowed precise measures of their changes irrespective of the shrinking of the tissue, the loss of cells or changes in cell size, factors that deeply complicate the comparison between changing tissue conditions. The percentage results obtained with the present methods were essentially the same obtained with the delta-delta procedure and with individual cDNA standard curve quantitative RT-PCR estimation. Conclusion: The method presented allows the comparison (i.e. as copies of mRNA per cell) between different genes and tissues, establishing the degree of abundance of the different molecular species tested.