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Refreshable Nanobiosensor Based on Organosilica Encapsulation of Biorecognition Elements.

Rohit GuptaJingyi LuanShantanu ChakrabarttyErica L SchellerJeremiah J MorrisseySrikanth Singamaneni
Published in: ACS applied materials & interfaces (2020)
Implantable and wearable biosensors that enable monitoring of biophysical and biochemical parameters over long durations are highly attractive for early and presymptomatic diagnosis of pathological conditions and timely clinical intervention. Poor stability of antibodies used as biorecognition elements and the lack of effective methods to refresh the biosensors upon demand without severely compromising the functionality of the biosensor remain significant challenges in realizing protein biosensors for long-term monitoring. Here, we introduce a novel method involving organosilica encapsulation of antibodies for preserving their biorecognition capability under harsh conditions, typically encountered during the sensor refreshing process, and elevated temperature. Specifically, a simple aqueous rinsing step using sodium dodecyl sulfate (SDS) solution refreshes the biosensor by dissociating the antibody-antigen interactions. Encapsulation of the antibodies with an organosilica layer is shown to preserve the biorecognition capability of otherwise unstable antibodies during the SDS treatment, thus ultimately facilitating the refreshability of the biosensor over multiple cycles. Harnessing this method, we demonstrate the refreshability of plasmonic biosensors for anti-IgG (model bioanalyte) and neutrophil gelatinase-associated lipocalin (NGAL) (a biomarker for acute and chronic kidney injury). The novel encapsulation approach demonstrated can be easily extended to other transduction platforms to realize refreshable biosensors for monitoring of protein biomarkers over long durations.
Keyphrases
  • label free
  • sensitive detection
  • gold nanoparticles
  • randomized controlled trial
  • protein protein
  • drug induced
  • small molecule
  • intensive care unit
  • heart rate
  • blood pressure
  • hepatitis b virus
  • deep learning