Layer-by-layer electrochemical biosensors configuring xanthine oxidase and carbon nanotubes/graphene complexes for hypoxanthine and uric acid in human serum solutions.

A selective biosensing platform for the determination of hypoxanthine (Hx) and uric acid (UA) concentrations in both buffer and human serum sample solutions was developed. The biosensor features the layer-by-layer (LbL) self-assembly of negatively charged xanthine oxidase (XOD) and positively charged poly(diallyldimethyl ammonium chloride) (PDDA) wrapped oxidized multi-walled carbon nanotubes and graphene (CNTs-G) complexes (PDDA-CNTs-G) on screen printed carbon electrode (SPCE) surfaces. Catalytic responses of the XOD modified biosensor with the chosen optimum number of layers for LbL assembly on SPCE towards Hx in buffer solutions were first investigated using both cyclic and square wave voltammetries. The peak current at around 0.08 V (vs. Ag/AgCl) associated with the production of UA increased as a function of the Hx concentration due to the surface selective catalytic reaction of XOD and Hx. A linear dynamic range of 5-50 µM Hx with a detection limit of 4.40 µM was obtained and the sensor was further applied to the analysis of Hx in normal human serum solutions in addition to myocardial infarction (MI) patient serum sample solutions from a local hospital. Since untreated serum solutions contain a certain amount of UA, a XOD free SPCE biosensor consisted of only PDDA-CNTs-G was also employed to evaluate the native concentration of UA in the serum and further assist the determination of Hx concentration when using the developed LbL biosensor. Our sensing results for the real biological fluidic solutions were finally validated by comparing to those using liquid chromatography-mass spectrometry(LC-MS).

• Publication year

  2018

• Venue

  Biosensors & bioelectronics

• Publication date

  2018-12-01

• Fields of study

  Medicine, Materials Science, Chemistry, Engineering

• Identifiers
  DOI 10.1016/j.bios.2018.08.074PMID 30223102
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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