Improvement of LOD in Fluorescence Detection with Spectrally Nonuniform Background by Optimization of Emission Filtering

The limit-of-detection (LOD) in analytical instruments with fluorescence detection can be improved by reducing noise of optical background. Efficiently reducing optical background noise in systems with spectrally nonuniform background requires complex optimization of an emission filter–the main element of spectral filtration. Here, we introduce a filter-optimization method, which utilizes an expression for the signal-to-noise ratio (SNR) as a function of (i) all noise components (dark, shot, and flicker), (ii) emission spectrum of the analyte, (iii) emission spectrum of the optical background, and (iv) transmittance spectrum of the emission filter. In essence, the noise components and the emission spectra are determined experimentally and substituted into the expression. This leaves a single variable–the transmittance spectrum of the filter–which is optimized numerically by maximizing SNR. Maximizing SNR provides an accurate way of filter optimization, while a previously used approach based on maximizing a signal-to-background ratio (SBR) is the approximation that can lead to much poorer LOD specifically in detection of fluorescently labeled biomolecules. The proposed filter-optimization method will be an indispensable tool for developing new and improving existing fluorescence-detection systems aiming at ultimately low LOD

Photosensitized Singlet Oxygen Luminescence from the Protein Matrix of Zn-Substituted Myoglobin

A nanosecond laser near-infrared spectrometer was used to study singlet oxygen (¹O₂) emission in a protein matrix. Myoglobin in which the intact heme is substituted by Zn-protoporphyrin IX (ZnPP) was employed. Every collision of ground state molecular oxygen with ZnPP in the excited triplet state results in ¹O₂ generation within the protein matrix. The quantum yield of ¹O₂ generation was found to be equal to 0.9 ± 0.1. On the average, six from every 10 ¹O₂ molecules succeed in escaping from the protein matrix into the solvent. A kinetic model for ¹O₂ generation within the protein matrix and for a subsequent ¹O₂ deactivation was introduced and discussed. Rate constants for radiative and nonradiative ¹O₂ deactivation within the protein were determined. The first-order radiative rate constant for ¹O₂ deactivation within the protein was found to be 8.1 ± 1.3 times larger than the one in aqueous solutions, indicating the strong influence of the protein matrix on the radiative ¹O₂ deactivation. Collisions of singlet oxygen with each protein amino acid and ZnPP were assumed to contribute independently to the observed radiative as well as nonradiative rate constants

Accurate MicroRNA Analysis in Crude Cell Lysate by Capillary Electrophoresis-Based Hybridization Assay in Comparison with Quantitative Reverse Transcription-Polymerase Chain Reaction

Accurate quantitation of microRNA (miRNA) in tissue samples is required for validation and clinical use of miRNA-based disease biomarkers. Since sample processing, such as RNA extraction, introduces undesirable biases, it is advantageous to measure miRNA in a crude cell lysate. Here, we report on accurate miRNA quantitation in crude cell lysate by a CE-based hybridization assay termed direct quantitative analysis of multiple miRNAs (DQAMmiR). Accuracy and precision of miRNA quantitation were determined for miRNA samples in a crude cell lysate, RNA extract from the lysate, and a pure buffer. The results showed that the measurements were matrix-independent with inaccuracies of below 13% from true values and relative standard deviations of below 11% from the mean values in a miRNA concentration range of 2 orders of magnitude. We compared DQAMmiR-derived results with those obtained by a benchmark miRNA-quantitation method–quantitative reverse transcription-polymerase chain reaction (qRT-PCR). qRT-PCR-based measurements revealed multifold inaccuracies and relative standard deviations of up to 70% in crude cell lysate. Robustness of DQAMmiR to changes in sample matrix makes it a perfect candidate for validation and clinical use of miRNA-based disease biomarkers