New methods for quantification and analysis of quantitative real-time polymerase chain reaction data

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^

Absolute quantitative real-time polymerase chain reaction for the measurement of human papillomavirus E7 mRNA in cervical cytobrush specimens.

BACKGROUND: Few reports of the utilization of an accurate, cost-effective means for measuring HPV oncogene transcripts have been published. Several papers have reported the use of relative quantitation or more expensive Taqman methods. Here, we report a method of absolute quantitative real-time PCR utilizing SYBR-green fluorescence for the measurement of HPV E7 expression in cervical cytobrush specimens. RESULTS: The construction of a standard curve based on the serial dilution of an E7-containing plasmid was the key for being able to accurately compare measurements between cervical samples. The assay was highly reproducible with an overall coefficient of variation of 10.4%. CONCLUSION: The use of highly reproducible and accurate SYBR-based real-time polymerase chain reaction (PCR) assays instead of performing Taqman-type assays allows low-cost, high-throughput analysis of viral mRNA expression. The development of such assays will help in refining the current screening programs for HPV-related carcinomas.

Impact of real time polymerase chain reaction technology on the therapeutic approach to treatment of staphylococcal infections

Can the early identification of the species of staphylococcus responsible for infection by the use of Real Time PCR technology influence the approach to the treatment of these infections? ^ This study was a retrospective cohort study in which two groups of patients were compared. The first group, ‘Physician Aware’ consisted of patients in whom physicians were informed of specific staphylococcal species and antibiotic sensitivity (using RT-PCR) at the time of notification of the gram stain. The second group, ‘Physician Unaware’ consisted of patients in whom treating physicians received the same information 24–72 hours later as a result of blood culture and antibiotic sensitivity determination. ^ The approach to treatment was compared between ‘Physician Aware’ and ‘Physician Unaware’ groups for three different microbiological diagnoses—namely MRSA, MSSA and no-SA (or coagulase negative Staphylococcus). ^ For a diagnosis of MRSA, the mean time interval to the initiation of Vancomycin therapy was 1.08 hours in the ‘Physician Aware’ group as compared to 5.84 hours in the ‘Physician Unaware’ group (p=0.34). ^ For a diagnosis of MSSA, the mean time interval to the initiation of specific anti-MSSA therapy with Nafcillin was 5.18 hours in the ‘Physician Aware’ group as compared to 49.8 hours in the ‘Physician Unaware’ group (p=0.007). Also, for the same diagnosis, the mean duration of empiric therapy in the ‘Physician Aware’ group was 19.68 hours as compared to 80.75 hours in the ‘Physician Unaware’ group (p=0.003) ^ For a diagnosis of no-SA or coagulase negative staphylococcus, the mean duration of empiric therapy was 35.65 hours in the ‘Physician Aware’ group as compared to 44.38 hours in the ‘Physician Unaware’ group (p=0.07). However, when treatment was considered a categorical variable and after exclusion of all cases where anti-MRS therapy was used for unrelated conditions, only 20 of 72 cases in the ‘Physician Aware’ group received treatment as compared to 48 of 106 cases in the ‘Physician Unaware’ group. ^ Conclusions. Earlier diagnosis of MRSA may not alter final treatment outcomes. However, earlier identification may lead to the earlier institution of measures to limit the spread of infection. The early diagnosis of MSSA infection, does lead to treatment with specific antibiotic therapy at an earlier stage of treatment. Also, the duration of empiric therapy is greatly reduced by early diagnosis. The early diagnosis of coagulase negative staphylococcal infection leads to a lower rate of unnecessary treatment for these infections as they are commonly considered contaminants. ^

Molecular mechanisms of signal transducer and activator of transcription (STAT) protein function in hematopoiesis

Hematopoietic growth factors play important roles in regulating blood cell growth and development in vivo. In this work, we investigated the signaling mechanisms of two growth factors with clinical significance, erythropoietin (Epo) and granulocyte colony-stimulating factor (G-CSF). Epo is essential for the survival, proliferation and differentiation of red blood cell progenitors, while G-CSF plays an important role in controlling mature neutrophil production. To identify which amino acid(s) and/or motif in EpoR is responsible for cell survival, wild type or mutant EpoR isoforms were transfected into the growth factor-dependent 32D cell line. Proliferation and apoptosis assays demonstrated that an EpoR isoform that lacks intracellular tyrosine residues and is truncated after 321 amino acids in the cytoplasmic tail (EpoR 1-321) mediates Epo-dependent cell survival. Furthermore, in absence of fetal calf serum (FCS), Epo signaling through wild type or mutant receptors supported anti-apoptosis, but not proliferation during 72 hours in response to Epo. To investigate the signaling pathway by which EpoR regulates cell survival, a dominant negative Stat5b (dnStat5b) isoform was generated and coexpressed with EpoR in stable cell lines. Expression of dnStat5b causes a significant induction of apoptosis in the presence of Epo in cells expressing EpoR 1-321, indicating that Stat5 is essential for survival signaling through tyrosine independent sequences in the EpoR. In a second project to investigate G-CSF signaling, we studied mechanisms by which G-CSF regulates the expression of PU.1, an important transcription factor in myeloid and B cell development. We demonstrated, by immunoblot and real time RT-PCR, that PU.1 is induced by G-CSF ex vivo as well as in vivo. To test whether G-CSF signaling through Stat3 is required for PU.1 regulation, the upstream region of the PU.1 gene was analyzed for potential Stat3 binding motifs. Four potential sites were identified; chromatin immunoprecipitations demonstrated that G-CSF activated Stat3 binds to 3 of the 4 binding motifs. In addition, PU.1 induction by G-CSF was completely abrogated in bone marrow from hematopoietic conditional Stat3 knockout mice. These results indicate an important role for Stat3 in G-CSF-dependent PU.1 gene regulation. Collectively, our works demonstrate that Stat protein play important and diverse roles in hematopoietic growth factor signaling. ^