Optimizing the Chemical Recognition Process of a Fluorescent Chemosensor for α-Ketoglutarate

Ye He, Zhiqian Guo, Pengwei Jin, Changhong Jiao, He Tian, Weihong Zhu

Industrial & Engineering Chemistry Research · 2015 · 13 citations · 51 references

Concepts

Abstract

α-Ketoglutarate (α-KA) can convert to 2-hydroxyglutarate (2-HG), which is confirmed to be associated with many diseases, especially with acute myeloid leukemia (AML). In this paper, a novel reaction-based chemosensor DT based on the typical Schiff-base reaction was designed for sensing the biomarker of α-KA, in which a diazanyl group as the recognition group was linked with a benzothiadiazole unit as the fluorophore moiety. Considering the typical Schiff-base reaction to generate hydrazones suffering from slow kinetics, particularly under neutral conditions, a series of parallel experiments was conducted for optimizing the chemical recognition process, including varying the solvent, reaction temperature, reactant concentration, and reaction rate. The optimum condition was established as a pH value, temperature, α-KA concentration, and response time of 5.7, 30 °C, 100 μM, and 20 min, respectively. Notably, in contrast with the initial 6.3-fold fluorescence enhancement, the remarkable 75-fold fluorescence enhancement (( I – I 0 )/ I 0 at 560 nm) was observed by optimizing the chemical recognition process of DT and α-KA. Finally, DT was carried out for the chemical recognition processing of α-KA in serum. We demonstrated that DT is selective for α-KA over other potential biologically interferences with similar structures and thus is suitable for detecting α-KA in serum. On the basis of the optimized chemical recognition process, DT shows high potential application for sensing α-KA with remarkable fluorescence enhancement. This work provided a potential method that is quick and convenient for sensing biomarker α-KA in serum. It is worth noting that without complicated pretreatment, utilizing a novel reaction-based fluorescent chemosensor may establish a new promising platform for clinical diagnosis biomarker.

References

51