Discrimination of Metalloproteins by a Mini Sensor Array Based on Bispyrene Fluorophore/Surfactant Aggregate Ensembles

Abstract

Fluorescent sensor arrays with pattern recognition ability have been widely used to detect and identify multiple chemically similar analytes. In the present work, two particular bispyrene fluorophores containing hydrophilic oligo(oxyethylene) spacer, 6 and 4, were synthesized, but one is with and the other is without cholesterol unit. Their ensembles with cationic surfactant (CTAB) assemblies realize multiple fluorescence responses to different metalloproteins, including hemoglobin, myoglobin, ferritin, cytochrome c, and alcohol dehydrogenase. The combination of fluorescence variation at monomer and excimer emission of the two binary sensor ensembles enables the mini sensor array to provide a specific fingerprint pattern to each metalloprotein. Linear discriminant analysis shows that the two-ensemble-sensor-based array could well discriminate the five tested metalloproteins. The present work realizes using a mini sensor array to accomplish discrimination of complex analytes like proteins. They also display a very high sensitivity to the tested metalloproteins with detection limits in the range of picomolar concentration.

Discrimination of saturated alkanes and relevant volatile compounds via the utilization of a conceptual fluorescent sensor array based on organoboron-containing polymers

“…MATLAB R2012 software is generally used to conduct the PCA-based data processing. 46 In the present work, the PCA score plot as generated is depicted in Fig. 5 , which shows clear clustering of the data using only the first two PCs (representing 57.7% of variance), the first principle component (PC1) of which carries about 40.25% of the variance, while the second one (PC2) carries ∼17.45%.…”

Self-Assembly of Europium-Containing Polyoxometalates/Tetra-n-alkyl Ammonium with Enhanced Emission for Cu2+ Detection

“…0.15 μM for Cu 2+ through the 3σ method, which was much lower than the EPA-defined safety level of Cu 2+ in drinking water (20 μM). 54 Moreover, the 1/( I 0 – I ) value as a function of 1/[Cu 2+ ] displayed a wonderful linear fit ( R = 0.998) based on the emission intensity changes, and the binding constant ( K ) calculated according to the Benesi–Hildebrand equation was close to 4.65 × 10 3 M –1 (Figure S5). 55…”

Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting

“…Adding fluorophores to samples proved to be an efficient way of improving the discrimination performance using fluorescent fingerprinting when the samples are not intensely fluorescent or are not well discriminated by their intrinsic fluorescence [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ]. The discrimination performance should be quantitatively characterized.…”

“…Most fluorimetric fingerprinting classification methods use intrinsic fluorescence of samples [ 1 , 2 ]. A less developed approach is based on adding fluorophores to samples [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ], which promises their better discrimination because of the interaction of fluorophore(s) with non-fluorescent components of the sample and corresponding changes in the spectrum. If more than one fluorophore is added to samples, we can talk about fluorescent sensor arrays [ 4 , 5 , 8 , 10 , 11 , 15 , 17 , 20 ].…”