Peptide Aggregation Induced Immunogenic Rupture (PAIIR)

Under the influence of stress and membrane damage, cells undergo immunogenic cell death (ICD), which involves the release of damage associated molecular patterns (DAMPs), natural adjuvants for enhancing an immune response. In the presence of an antigen, released DAMPs can determine the type and magnitude of the immune response, and therefore the longevity and efficacy of an antigen-specific immunity. In the last decade, the immune response effect of ICD has been shown, yet there is no tool that can induce controlled ICD with predictable results, regardless of the cell type. We designed a peptide-based tool, called [II], for controlled damage to cell membrane to induce ICD and DAMPs release. Herein we describe a series of experiments that determine that the mechanism of action of [II] includes a caspase-dependent ICD and subsequent release of immune stimulating DAMPs, on various cell types. Moreover, we tested the hypothesis that controlled DAMP release via [II] in vivo was associated with enhancement of antigen-specific adaptive immunity with influenza hemagglutinin (HA) subunit vaccine. HA and [II] showed significantly higher HA specific IgG1 and IgG2a antibodies, compared to HA-only immunized mice, while the peptide itself did not elicit antibodies. In this paper, we demonstrate the first peptide-aggregation induced immunogenic rupture (PAIIR) approach as vaccine adjuvants for increasing both humoral and cellular immunity. In consideration of its ability to enhance IgG2a responses that are associated with heterosubtypic influenza virus protection, PAIIR is a promising adjuvant to promote universal protection upon influenza HA vaccination.

A Binary Matrix Method to Enumerate, Hierarchically Order and Structurally Classify Peptide Aggregation

Protein aggregation is a common and complex phenomenon in biological processes, yet a robust analysis of this aggregation process remains elusive. The commonly used methods such as centre-of-mass to centre-of-mass (COM-COM) distance, the radius of gyration (Rg), hydrogen bonding (HB) and solvent accessible surface area (SASA) do not quantify the aggregation accurately. Herein, a new and robust method that uses an aggregation matrix (AM) approach to investigate peptide aggregation in a MD simulation trajectory is presented. A nxn two-dimensional aggregation matrix (AM) is created by using the inter-peptide CA-CA cut-off distances which are binarily encoded (0 or 1). These aggregation matrices are analysed to enumerate, hierarchically order and structurally classify the aggregates. Moreover, the comparison between the present AM method and the conventional Rg, COM-COM and HB methods shows that the conventional methods grossly underestimate the aggregation propensity. Additionally, the conventional methods do not address the hierarchy and structural ordering of the aggregates, which the present AM method does. Finally, the present AM method utilises only nxn two-dimensional matrices to analyse aggregates consisting of several peptide units. To the best of our knowledge, this is a maiden approach to enumerate, hierarchically order and structurally classify peptide aggregation.

Size Matters: A Mechanistic Model of Nanoparticle Curvature Effects on Amyloid Fibril Formation

The aggregation of peptides into amyloid fibrils is linked to ageing-related diseases, such as Alzheimer's disease and type 2 diabetes. Interfaces, particularly those with large nanostructured surface areas, can affect the kinetics of peptide aggregation, ranging from a complete inhibition to strong acceleration. While a number of physiochemical parameters determine interface effects, we here focus on the role of nanoparticle curvature for the aggregation of the amyloidogenic peptides Aβ40, NNFGAIL, GNNQQNY and VQIYVK. Nanoparticles (NPs) provided a surface for peptide monomers to adsorb, enabling the nucleation into oligomers and fibril formation. High surface curvature, however, destabilized prefibrillar structures, providing an explanation for inhibitory effects on fibril growth. Thioflavin T (ThT) fluorescence assays as well as dynamic light scattering (DLS), atomic force microscopy (AFM) and electron microscopy experiments revealed NP size-dependent effects on amyloid fibril formation, with differences between the peptides. While 5 nm gold NPs (AuNP-5) retarded or inhibited the aggregation of most peptides, larger 20 nm gold NPs (AuNP-20) tended to accelerate peptide aggregation. Molecular dynamics (MD) studies demonstrated that NPs' ability to catalyze or inhibit oligomer formation was influenced by the oligomer stability at curved interfaces which was lower at more highly curved surfaces. Differences in the NP effects for the peptides resulted from the peptide properties (size, aggregation propensity) and concomitant surface binding affinities. The results can be applied to the design of future nanostructured materials for defined applications.