ABSTRACT
We report the development of a new technology for simultaneous quantitative detection of multiple targets in a single sample. Scalable transcriptional analysis routine (STAR) represents a novel integration of reverse transcriptase-polymerase chain reaction and capillary electrophoresis that allows detection of dozens of gene transcripts in a multiplexed format using amplicon size as an identifier for each target. STAR demonstrated similar or better sensitivity and precision compared to two commonly used methods, SYBR Green-based and TaqMan probe-based real-time reverse transcriptase-polymerase chain reaction. STAR can be used as a flexible platform for building a variety of applications to monitor gene expression, from single gene assays to assays analyzing the expression level of multiple genes. Using severe acute respiratory syndrome (SARS) corona virus as a model system, STAR technology detected single copies of the viral genome in a two-gene multiplex. Blinded studies using RNA extracted from various tissues of a SARS-infected individual showed that STAR correctly identified all samples containing SARS virus and yielded negative results for non-SARS control samples. Using alternate priming strategies, STAR technology can be adapted to transcriptional profiling studies without requiring a priori sequence information. Thus, STAR technology offers a flexible platform for development of highly multiplexed assays in gene expression analysis and molecular diagnostics.
Subject(s)
Gene Expression Profiling/methods , Reverse Transcriptase Polymerase Chain Reaction/methods , Severe Acute Respiratory Syndrome/diagnosis , Transcription, Genetic/genetics , Animals , Brain/metabolism , Color , Fluorescent Dyes , Gene Expression Profiling/instrumentation , RNA, Viral/analysis , RNA, Viral/genetics , Rats , Reproducibility of Results , Reverse Transcriptase Polymerase Chain Reaction/instrumentation , Severe acute respiratory syndrome-related coronavirus/genetics , Severe acute respiratory syndrome-related coronavirus/isolation & purification , Sensitivity and Specificity , Severe Acute Respiratory Syndrome/virology , Taq Polymerase/metabolism , Time FactorsABSTRACT
Development of inhibitor compounds selective against undesirable targets is critical in drug discovery. Selectivity ratios for candidate compounds are evaluated by dividing potencies from two assays assessing the off-target and target. Because all potency measurements have underlying uncertainty, understanding error propagation is essential to interpreting selectivity data. Assay noise introduces ambiguity in the statistical significance of selectivity ratios, particularly at low replicate numbers when compounds are often prioritized for subsequent testing. The ability to differentiate potency results for any pair of compounds in one assay is evaluated using a metric called minimum significant ratio (MSR). Potency results of one compound tested in a pair of assays can be differentiated by the minimum significant selectivity ratio (MSSR). To differentiate selectivity ratios for any pair of compounds, we extend this concept by proposing two new parameters called the minimum significant ratio of selectivity ratios (MSRSR) and confidence in ratio of selectivity ratios (CRSR). Importantly, these tools can be used after a single selectivity measurement. We describe these methods and illustrate their usefulness using structure-activity relationship data from a Janus kinase inhibitor project, in which these tools informed a cogent retesting strategy and enabled rapid and objective decision making.