Cannabis detection with solid sensors and paper-based immunoassays by conjugating antibodies to nanocellulose

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Abstract

Highly sensitive and specific diagnostics for cannabis usage are essential for rapid on-site screening for illicit drug usage. To improve the sensitivity of THC immunoassays, a proper immobilization of the sensing elements on the sensor substrate is critical. In this work, we demonstrated the utilization of EDC/NHS coupling chemistry with nanocellulose to obtain efficient anchor layers for the immobilization of anti-immune complex antibodies on surfaces. In our approach, the high surface-to-volume ratio, OH-group-rich surface, and high hygroscopicity of TOCNF enable efficient surface functionalization and enhance water permeation inside the nanocellulose network structure, offering a hydrophilic spacer for the sensing antibodies. THC detection was shown in both SPR (surface plasmon resonance technique) and paper-based sensing systems. In SPR, antibody immobilization and the related interactions with the target molecule complex with 1–10 μg/mL THC were followed in-situ in aqueous environment, revealing robust attachment of the antibody to the nanocellulose layer and preserved bioactivity. Additionally, quantitative THC detection was enabled on paper substrate by colorimetric means by employing labeled anti-THC Fab antibody fragments as detection antibodies. THC detection efficiency of covalently linked biointerface was superior compared to the performance of physically linked biointerface. The chemical conjugation of anti-IC to nanocellulose allowed efficient binding, whereas supramolecular conjugation led to insufficient binding, highlighting the relevance of the developed nanocellulose-based anchor layer.
Original languageEnglish
Article number120517
JournalCarbohydrate Polymers
Volume304
DOIs
Publication statusPublished - 15 Mar 2023
MoE publication typeA1 Journal article-refereed

Keywords

  • Antibody immobilization
  • Immunoassays
  • Paper-based diagnostics
  • Surface plasmon resonance
  • THC detection

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