Fig. 4: A ratiometric luminescent assay can sense nitazenes specifically in relevant diagnostic scenarios. | Nature Communications

Fig. 4: A ratiometric luminescent assay can sense nitazenes specifically in relevant diagnostic scenarios.

From: Computational design of dynamic biosensors for emerging synthetic opioids

Fig. 4: A ratiometric luminescent assay can sense nitazenes specifically in relevant diagnostic scenarios.

A Cartoon of the luminescence assay. A mNeonGreen-NanoBiT “calibrator” protein enables ratiometric detection of samples, fluorescing at a wavelength of 520 nm independent of ligand concentration. PYR1 to ΔN-HAB1T+ dimerization results in an increased ratio of the relative luminescence units per second (RLU/s) at 450 nm versus the RLU/s at 520 nm. B Ratiometric assay of PYR1nitav2.1 in buffer or in urine using the indicated ligands. EC50 measurements and limit of detection (LOD) for the sensor are colored for the appropriate condition. 200 nM SmBiT-ΔNHAB1, 10 nM LgBiT-PYR1, and 512 pM calibrator are used. Benzylfentanyl, codeine, and heroin were tested in buffer. The nitazene-specific EC50 was 5.7 nM (95% c.i. 4.0– 8.3 nM) in the urine matrix and 2.8 nM (95% c.i. 2.3–3.4 nM) in buffer. C Luminescence assay results using PANnita.1 show sensitivity against a panel of nitazene variants and synthetic opioids across multiple concentrations. Analysis of variance was calculated using an ordinary 2-way ANOVA and Dunnett’s multiple comparison test, with a single pooled variance (****p < 0.0001, **p < 0.01, ns not statistically significant). 4 nM SmBit-ΔNHAB1 and 4 nM LgBiT-PYR1 are used. Data is shown as the average of n = 3 (B) or n = 4 (C) replicates. Error bars represent the standard error of the mean and in some cases are smaller than the symbols. EC50s were calculated by fitting the data to a four-parameter logistical sigmoidal model with nonlinear least-squares regression. LODs were calculated using the 3σ method, which is equivalent to the drug concentration that yields a signal equal to 3 times the standard deviation of the blank after subtraction. Source Data are provided with this paper as Source Data.

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