We present a study of the dynamics of protein aggregation using a Bloch surface wave (BSW) label-free sensing scheme. In a previous work, we demonstrated the ability to detect the early dynamic events of fibrillogenesis of amyloid betapeptides (Aβ), linked to Alzheimer’s Disease. Here, we demonstrate the efficacy of the BSW sensor by describing a simultaneous light scattering measurement, with the purpose of real-time monitoring the size change of the Aβ aggregates, throughout fibrillization.
The misfolding and aggregation of amyloid proteins has been associated with incurable diseases such as Alzheimer's or Parkinson's disease. In the specific case of Alzheimer's disease, recent studies have shown that cell toxicity is caused by soluble oligomeric forms of aggregates appearing in the early stages of aggregation, rather than by insoluble fibrils. Research on new strategies of diagnosis is imperative to detect the disease prior to the onset of clinical symptoms. Here, we propose the use of an optical method for protein aggregation dynamic studies using a Bloch surface wave based approach. A one dimension photonic crystal made of a periodic stack of silicon oxide and silicon nitride layers is used to excite a Bloch surface wave, which is sensitive to variation of the refractive index of an aqueous solution. The aim is to detect the early dynamic events of protein aggregation and fibrillogenesis of the amyloid-beta peptide Aβ42, which plays a central role in the onset of the Alzheimer’s disease. The detection principle relies on the refractive index changes caused by the depletion of the Aβ42 monomer concentration during oligomerization and fibrillization. We demonstrate the efficacy of the Bloch surface wave approach by monitoring in real-time the first crucial steps of Aβ42 oligomerization.
We present a study of the dynamics of protein aggregation using a common path heterodyne Bloch surface wave sensing
scheme. We demonstrate the ability to detect, during thermal incubation, the early events linked to the aggregation of
proteins related to conformational diseases. Alzheimer's amyloid-β 1-42 is used to demonstrate the efficiency of the
method. A model based on elementary interactions is shown to describe accurately the aggregation process. The
described sensing scheme is sensitive to the early events of the aggregation process. is hence proposed as a method for
the detection of early stages of the evolution of conformational diseases.