Real-Time Analysis of Specific Binding between Apolipoprotein E Isoforms and Amyloid β-Peptide by Dual Polarization Interferometry

Real-time analysis of the biomolecular interaction between gelsolin and Aβ1-42 monomer and its implication for Alzheimer's disease

Biomolecular interaction acts a pivotal part in understanding the mechanisms underlying the development of Alzheimer's disease (AD). Herein, we built a biosensing platform to explore the interaction between gelsolin (GSN) and different β-amyloid protein 1-42 (Aβ1-42) species, including Aβ1-42 monomer (m-Aβ), Aβ1-42 oligomers with both low and high levels of aggregation (LLo-Aβ and HLo-Aβ) via dual polarization interferometry (DPI). Real-time molecular interaction process and kinetic analysis showed that m-Aβ had the strongest affinity and specificity with GSN compared with LLo-Aβ and HLo-Aβ. The impact of GSN on inhibiting aggregation of Aβ1-42 and solubilizing Aβ1-42 aggregates was evaluated by circular dichroism (CD) spectroscopy. The maintenance of random coil structure of m-Aβ and the reversal of β-sheet structure in HLo-Aβ were observed, demonstrating the beneficial effects of GSN on preventing Aβ from aggregation. In addition, the structure of m-Aβ/GSN complex was analyzed in detail by molecular dynamics (MD) simulation and molecular docking. The specific binding sites and crucial intermolecular forces were identified, which are believed to stabilize m-Aβ in its soluble state and to inhibit the fibrilization of Aβ1-42. Combined theoretical simulations and experiment results, we speculate that the success of GSN sequestration mechanism and the balance of GSN levels in cerebrospinal fluid and plasma of AD subjects may contribute to a delay in AD progression. This research not only unveils the molecular basis of the interaction between GSN and Aβ1-42, but also provides clues to understanding the crucial functions of GSN in AD and drives the development of AD drugs and therapeutic approaches.

Insights into Zwitterionic Surfactant Interactions at the Oil-Water Interface by Interferometry Experiments and MDS Calculations

In this work, the interaction performance of zwitterionic surfactant [dodecyl dimethyl sulfopropyl betaine (DSB-12) and hexadecyl dimethyl sulfopropyl betaine (DSB-16)] at the n-octadecane oil surface is investigated from experimental and simulation insights. For a macroscopic experiment, interfacial interferometry technology was developed for real-time monitor interaction performances and to obtain the quantitative interfacial thickness and mass results. The Langmuir model was characterized by thermodynamic analysis, deducing the aggregation spontaneity of DSB-16 > DSB-12 with ΔGagg(DSB-16) = -5.94 kJ mol-1 < ΔGagg(DSB-12) = 24.08 kJ mol-1. A three-step dynamic model (adsorption, arrangement, and aggregation) was characterized by kinetic analysis, indicating arrangement process as slow-limiting step with k2(arr) < k1(ads), k3(agg). For microscopic simulation, and molecular dynamic (MD) method was utilized to theoretically investigate interaction performances and obtain the interfacial configuration and energy results. The interaction stability and interaction strength were indicated to be DSB-16 > DSB-12 with differences of final energy ΔEfin = 48-88 kcal mol-1. The interaction mechanism was explained by proposing the model of "response enhancement" and "deposition activity" for DSB-16 interactions, and "response decrease" and "elution activity" for DSB-12 interactions. The different performances can be attributed to the different interaction forms and forces of surfactants. This work provided a platform for performance and mechanism investigation between the surfactant molecule and oil surface, which is of great significance in reservoir exploitation and enhanced oil recovery (EOR).

Protein conformation characterization via a silicon resonator-based optical sensor based on the combination of wavelength interrogation and dual polarization detection

Protein conformational abnormality causes cell malfunction. Conformational change of amyloid protein causes neuron malfunction, which renders "protein conformational disease" Alzheimer's disease. Dual polarization interferometry enables to provide one-dimensional structure of a protein biolayer via deconvolution of interference patterns, which in turn is interpreted as the protein molecule conformation. However, it is still challenging to avoid interference patterns becoming faint and obscure sometimes. Resonance wavelength response to the biolayer structure can achieve a very low detection limit due to inherent high Q factor of an optical resonator. Here, we introduce the concept of combining dual polarization detection with wavelength interrogation via a simple and compact resonator-based optical biosensor. Biolayer were probed by the wave of dual polarization and its opto-geometrical parameters were resolved into resonance wavelength shift. Because protein molecule with distinct conformation produced a biolayer with unique thickness and mass density. Amyloid proteins in monomeric and dimeric morphology were respectively characterized. This concept enables protein conformation characterization in an easy and direct paradigm and provides a desirable sensing performance due to sensitive resonance response in the form of the sharp resonance profile occurring in a nonoverlapping spectrum.

Continuous monitoring of molecular biomarkers in microfluidic devices

The ability to monitor molecular targets is crucial in fields ranging from healthcare to industrial processing to environmental protection. Devices employing biomolecules to achieve this goal are called biosensors. Over the last half century researchers have developed dozens of different biosensor approaches. In this chapter we analyze recent advances in the biosensing field aiming at adapting these to the problem of continuous molecular monitoring in complex sample streams, and how the merging of these sensors with lab-on-a-chip technologies would be beneficial to both. To do so we discuss (1) the components that comprise a biosensor, (2) the challenges associated with continuous molecular monitoring in complex sample streams, (3) how different sensing strategies deal with (or fail to deal with) these challenges, and (4) the implementation of these technologies into lab-on-a-chip architectures.