Issue 16, 2018

An electrochemical biosensor for rapid detection of anti-dsDNA antibodies in absolute scale

Abstract

Autoimmune diseases are chronic inflammatory pathologies that are characterized by the presence of antibodies against the body's own epitopes in serum (autoantibodies). Systemic lupus erythematosus (SLE) is a common autoimmune pathology characterized by the presence of antinuclear antibodies (ANAs). These include anti-dsDNA (α-dsDNA) antibodies, which are widely used for diagnosis and disease monitoring. Their determination is carried out using traditional techniques such as Indirect Immunofluorescence (IFI) or Enzyme-Linked Immunosorbent Assay (ELISA), which are time consuming, require qualified technicians, and are not compatible with decentralized analysis outside a laboratory facility. Here, we show a sandwich-format electrochemical biosensor-based method for α-dsDNA determination in a rapid and simple manner. The total assay time is only 30 minutes, and the sensor is capable of detecting 16 ng (8 μg mL−1) of α-dsDNA antibodies. Using the current derived from the detection limit of the method as a cut-off, we could discriminate positive from negative serum samples with 90% sensitivity and 100% specificity. Using monoclonal antibodies for calibration curves, our results are presented in absolute scale (i.e., concentration instead of serum titer) which will help us to perform comparisons between methods and carry out further improvements of this protocol. In an effort to render the sensor compatible with automation, we minimized the manipulation steps without compromising the analytical performance, even in complex samples such as serum.

Graphical abstract: An electrochemical biosensor for rapid detection of anti-dsDNA antibodies in absolute scale

Supplementary files

Article information

Article type
Paper
Submitted
04 Jan 2018
Accepted
06 Jun 2018
First published
03 Jul 2018

Analyst, 2018,143, 3874-3882

An electrochemical biosensor for rapid detection of anti-dsDNA antibodies in absolute scale

P. Fagúndez, G. Brañas, E. Cairoli, J. Laíz and J. P. Tosar, Analyst, 2018, 143, 3874 DOI: 10.1039/C8AN00020D

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