Atomic force microscopy 3D structural reconstruction of individual particles in the study of amyloid protein assemblies.

Recent developments in atomic force microscopy (AFM) image analysis have made three-dimensional (3D) structural reconstruction of individual particles observed on 2D AFM height images a reality. Here, we review the emerging contact point reconstruction AFM (CPR-AFM) methodology and its application in 3D reconstruction of individual helical amyloid filaments in the context of the challenges presented by the structural analysis of highly polymorphous and heterogeneous amyloid protein structures. How individual particle-level structural analysis can contribute to resolving the amyloid polymorph structure-function relationships, the environmental triggers leading to protein misfolding and aggregation into amyloid species, the influences by the conditions or minor fluctuations in the initial monomeric protein structure on the speed of amyloid fibril formation, and the extent of the different types of amyloid species that can be formed, are discussed. Future perspectives in the capabilities of AFM-based 3D structural reconstruction methodology exploiting synergies with other recent AFM technology advances are also discussed to highlight the potential of AFM as an emergent general, accessible and multimodal structural biology tool for the analysis of individual biomolecules.

Geographical origin traceability of rice using a FTIR-based metabolomics approach.

Infrared spectroscopy is a crucial tool to achieve the origin traceability of rice, but it is constrained by data mining. In this study, a novel infrared spectroscopy-based metabolomics analytical method was proposed to discriminate rice products from 14 Chinese cities by seeking 'wave number markers'. Principal component analysis (PCA), cluster analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to separate all rice groups. The S-plot, permutation test and variable importance in projection (VIP) are used to screen eligible 'markers', which were further verified by a pairwise t-test. There are 55-265 'markers' picked out from 14 rice groups, with their characteristic wave number bands to be 2935.658-3238.482, 3851.846-4000.364, 3329.136-3518.160, 1062.778-1213.225, 1161.147-1386.819, 3348.425-3560.594, 3115.038-3624.245, 2567.254-2872.007, 3334.923-3560.594, 3282.845-3543.235, 3338.780-3518.160, 3197.977-3560.594, 3163.258-3267.414 and 3292.489-3477.655 cm-1, respectively. All but No. 5 rice groups show significantly low absorbance on their 'marker' bands. A mixed rice containing congenial No. 5 and No. 6 rice (80 : 20, m/m) was employed to test the validity of the method, and found that the 'marker' band of the mixed rice is the range of 1170.791-1338.598 cm-1, implying the existence of considerable discrepancy between the mixed rice and other rice. The results indicate that infrared spectroscopy coupled with metabolomics analysis is competent for origin traceability of rice; thus, it provides a novel and workable approach for the accurate and rapid discrimination of rice from different geographical origins, and a distinctive perspective of metabolomics to explore infrared spectroscopy and beyond, especially not confined in the field of origin traceability.

An Additive-Free Model for Tau Self-Assembly.

Tau is a natively unfolded protein that contributes to the stability of microtubules. Under pathological conditions such as Alzheimer's disease (AD), tau protein misfolds and self-assembles to form paired helical filaments (PHFs) and straight filaments (SFs). Full-length tau protein assembles poorly and its self-assembly is enhanced with polyanions such as heparin and RNA in vitro, but a role for heparin or other polyanions in vivo remains unclear. Recently, a truncated form of tau (297-391) has been shown to self-assemble in the absence of additives which provides an alternative in vitro PHF model system. Here we describe methods to prepare in vitro PHFs and SFs from tau (297-391) named dGAE. We also discuss the range of biophysical/biochemical techniques used to monitor tau filament assembly and structure.

Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize.

The metabolomics approach has proved to be promising in achieving non-targeted screening for those unknown and unexpected (U&U) contaminants in foods, but data analysis is often the bottleneck of the approach. In this study, a novel metabolomics analytical method via seeking marker compounds in 50 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked into lettuce and maize matrices was developed, based on ultrahigh-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) output results. Three concentration groups (20, 50 and 100 ng mL-1) to simulate the control and experimental groups applied in the traditional metabolomics analysis were designed to discover marker compounds, for which multivariate and univariate analysis were adopted. In multivariate analysis, each concentration group showed obvious separation from other two groups in principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) plots, providing the possibility to discern marker compounds among groups. Parameters including S-plot, permutation test and variable importance in projection (VIP) in OPLS-DA were used for screening and identification of marker compounds, which further underwent pairwise t-test and fold change judgement for univariate analysis. The results indicate that marker compounds on behalf of 50 PPCPs were all discovered in two plant matrices, proving the excellent practicability of the metabolomics approach on non-targeted screening of various U&U PPCPs in plant-derived foods. The limits of detection (LODs) for 50 PPCPs were calculated to be 0.4~2.0 µg kg-1 and 0.3~2.1 µg kg-1 in lettuce and maize matrices, respectively.

Comparative Analysis of the Relative Fragmentation Stabilities of Polymorphic Alpha-Synuclein Amyloid Fibrils.

The division of amyloid fibril particles through fragmentation is implicated in the progression of human neurodegenerative disorders such as Parkinson's disease. Fragmentation of amyloid fibrils plays a crucial role in the propagation of the amyloid state encoded in their three-dimensional structures and may have an important role in the spreading of potentially pathological properties and phenotypes in amyloid-associated diseases. However, despite the mechanistic importance of fibril fragmentation, the relative stabilities of different types or different polymorphs of amyloid fibrils toward fragmentation remain to be quantified. We have previously developed an approach to compare the relative stabilities of different types of amyloid fibrils toward fragmentation. In this study, we show that controlled sonication, a widely used method of mechanical perturbation for amyloid seed generation, can be used as a form of mechanical perturbation for rapid comparative assessment of the relative fragmentation stabilities of different amyloid fibril structures. This approach is applied to assess the relative fragmentation stabilities of amyloid formed in vitro from wild type (WT) α-synuclein and two familial mutant variants of α-synuclein (A30P and A53T) that generate morphologically different fibril structures. Our results demonstrate that the fibril fragmentation stabilities of these different α-synuclein fibril polymorphs are all highly length dependent but distinct, with both A30P and A53T α-synuclein fibrils displaying increased resistance towards sonication-induced fibril fragmentation compared with WT α-synuclein fibrils. These conclusions show that fragmentation stabilities of different amyloid fibril polymorph structures can be diverse and suggest that the approach we report here will be useful in comparing the relative stabilities of amyloid fibril types or fibril polymorphs toward fragmentation under different biological conditions.

Discrimination and Deaf Adolescents' Subjective Well-Being: The Role of Deaf Identity.

This study tested the influence of Deaf identity (cognitive identification and affective identification) on the association between perceived deaf discrimination and subjective well-being among Chinese adolescents who are deaf and hard-of-hearing (DHH), based on the rejection-identification model. Questionnaires on perceived deaf discrimination, subjective well-being, Deaf identity, and demographic information were completed by 246 DHH students (15-23 years old) from special residential schools in China. The results indicated that: (1) higher level of perceived deaf discrimination was significantly associated with lower level of subjective well-being (direct effect = -0.24, 95% confidence interval [CI] = [-0.37, -0.12], p < .001); (2) there was a significant indirect effect of perceived deaf discrimination on subjective well-being via cognitive identification (indirect effect = -0.07, 95% CI = [-0.12, -0.01], p < .05); and (3) positive affective identification due to increased cognitive identification with Deaf community may help counteract the negative impact of perceived deaf discrimination on subjective well-being (indirect effect = 0.06, 95% CI = [0.03, 0.10], p < .001). These findings further support the notion that the different components of group identification should be examined separately.

Structural Identification of Individual Helical Amyloid Filaments by Integration of Cryo-Electron Microscopy-Derived Maps in Comparative Morphometric Atomic Force Microscopy Image Analysis.

The presence of amyloid fibrils is a hallmark of more than 50 human disorders, including neurodegenerative diseases and systemic amyloidoses. A key unresolved challenge in understanding the involvement of amyloid in disease is to explain the relationship between individual structural polymorphs of amyloid fibrils, in potentially mixed populations, and the specific pathologies with which they are associated. Although cryo-electron microscopy (cryo-EM) and solid-state nuclear magnetic resonance (ssNMR) spectroscopy methods have been successfully employed in recent years to determine the structures of amyloid fibrils with high resolution detail, they rely on ensemble averaging of fibril structures in the entire sample or significant subpopulations. Here, we report a method for structural identification of individual fibril structures imaged by atomic force microscopy (AFM) by integration of high-resolution maps of amyloid fibrils determined by cryo-EM in comparative AFM image analysis. This approach was demonstrated using the hitherto structurally unresolved amyloid fibrils formed in vitro from a fragment of tau (297-391), termed 'dGAE'. Our approach established unequivocally that dGAE amyloid fibrils bear no structural relationship to heparin-induced tau fibrils formed in vitro. Furthermore, our comparative analysis resulted in the prediction that dGAE fibrils are structurally closely related to the paired helical filaments (PHFs) isolated from Alzheimer's disease (AD) brain tissue characterised by cryo-EM. These results show the utility of individual particle structural analysis using AFM, provide a workflow of how cryo-EM data can be incorporated into AFM image analysis and facilitate an integrated structural analysis of amyloid polymorphism.

Tuning dynamic DNA- and peptide-driven self-assembly in DNA-peptide conjugates.

DNA-peptide conjugates offer an opportunity to marry the benefits of both biomolecular classes, combining the high level of programmability found with DNA, with the chemical diversity of peptides. These hybrid systems offer potential in fields such as therapeutics, nanotechnology, and robotics. Using the first DNA-ß-turn peptide conjugate, we present three studies investigating the self-assembly of DNA-peptide conjugates over a period of 28 days. Time-course studies, such as these have not been previously conducted for DNA-peptide conjugates, although they are common in pure peptide assembly, for example in amyloid research. By using aging studies to assess the structures produced, we gain insights into the dynamic nature of these systems. The first study explores the influence varying amounts of DNA-peptide conjugates have on the self-assembly of our parent peptide. Study 2 explores how DNA and peptide can work together to change the structures observed during aging. Study 3 investigates the presence of orthogonality within our system by switching the DNA and peptide control on and off independently. These results show that two orthogonal self-assemblies can be combined and operated independently or in tandem within a single macromolecule, with both spatial and temporal effects upon the resultant nanostructures.

Metabolomics-based non-targeted screening analysis of 34 PPCPs in bovine and piscine muscles.

The metabolomics-based analytical strategy has showed superiority on the non-targeted screening of contaminants, especially for unknown and unexpected (U&U) contaminants in the field of food safety, but data analysis is often the bottleneck of the strategy. In this study, a novel metabolomics-based analytical method via searching for marker compounds was developed on the basis of ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) results to accurately, rapidly and comprehensively achieve the non-targeted screening of 34 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked in bovine and piscine muscle matrices. Three concentration groups (20, 50 and 100 ng mL-1) were intentionally designed to simulate the control and experimental groups for the discovery of marker compounds, for which multivariate and univariate analyses were adopted. In multivariate analysis, each concentration group was fully separated from the other two groups in PCA and OPLS-DA plots, laying a foundation to distinguish marker compounds among groups. The S-plot, permutation and variable importance in projection (VIP) in OPLS-DA were employed to screen and identify marker compounds, which were further verified by pairwise t-test and fold change judgement in univariate analysis. The results indicate that 34 PPCPs spiked in two muscle matrices were all identified as marker compounds, proving the validity and practicability of this novel metabolomics-based non-targeted screening method, which will exhibit great superiority and broad application prospects, especially in the face of massive PPCPs and various animal matrices in the field of food safety control. In addition, the limits of detection (LODs) for 34 PPCPs were calculated to be 0.2-2.6 µg kg-1 and 0.3-2.1 µg kg-1 in bovine and piscine muscle matrices, respectively.

Quantum chemical prediction of effects of temperature on hydrolysis rate of penicillin under weakly acidic condition.

Temperature and pH are important factors affecting the hydrolysis of ß-lactam antibiotics in water environments. However, the determination of hydrolysis kinetics and pathways is experimentally challenging, particularly in low temperature aqueous solutions because of time and cost constraints. In this study, an equation was employed to correct the Gibbs energy calculated in aqueous solutions by density functional theory methods to predict the effect of temperature on the hydrolysis kinetics and pathways of penicillin G. The results indicate that the most likely hydrolysis mechanism involves the opening of the ß-lactam ring of anionic penicillin G protonated at the ß-lactam oxygen atom with the participation of the carboxyl group and a water molecule. The results also suggest that the carboxyl group of ß-lactam antibiotics was crucial for the hydrogen transfer. The predicted rate constants were of the same order of magnitude as the experimental values obtained under comparable pH and temperature conditions. Therefore, the quantum chemical methodology described herein can be potentially employed to determine pH- and temperature-based two-dimensional hydrolysis rate models, which can enable the prediction of the ß-lactam antibiotics persistence in frigid waters.

Heterotypic Amyloid ß interactions facilitate amyloid assembly and modify amyloid structure.

It is still unclear why pathological amyloid deposition initiates in specific brain regions or why some cells or tissues are more susceptible than others. Amyloid deposition is determined by the self-assembly of short protein segments called aggregation-prone regions (APRs) that favour cross-ß structure. Here, we investigated whether Aß amyloid assembly can be modified by heterotypic interactions between Aß APRs and short homologous segments in otherwise unrelated human proteins. Mining existing proteomics data of Aß plaques from AD patients revealed an enrichment in proteins that harbour such homologous sequences to the Aß APRs, suggesting heterotypic amyloid interactions may occur in patients. We identified homologous APRs from such proteins and show that they can modify Aß assembly kinetics, fibril morphology and deposition pattern in vitro. Moreover, we found three of these proteins upon transient expression in an Aß reporter cell line promote Aß amyloid aggregation. Strikingly, we did not find a bias towards heterotypic interactions in plaques from AD mouse models where Aß self-aggregation is observed. Based on these data, we propose that heterotypic APR interactions may play a hitherto unrealized role in amyloid-deposition diseases.

Metabolomics-based screening analysis of PPCPs in water pretreated with five different SPE columns.

The selection of solid phase extraction (SPE) columns in the pretreatment process plays a decisive role in the screening and quantification of pharmaceutical and personal care products (PPCPs). As growing PPCPs have frequently been detected in the aquatic environment, it is a burdensome task through one-by-one recovery comparison to judge which column presents relatively ideal pretreatment results for PPCPs. In view of this, we developed a novel metabolomics-based screening method based on ultrahigh-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) results to accurately, rapidly and comprehensively choose a suitable column from 5 different kinds to handle 64 PPCPs in two water environments (50 µg L-1/pH ≅ 7.0/pure water and 1 µg L-1/pH ≅ 7.0/reservoir water) through seeking 'biomarkers', for which multivariate and univariate analyses were adopted. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) play a crucial role in multivariate analysis, and the pairwise t-test and fold change judgement in univariate analysis. Each column group was fully separated from the other 4 groups in PCA and OPLS-DA plots, laying a foundation to distinguish 'biomarkers' between groups. The S-Plot, permutation and variable importance in projection (VIP) in OPLS-DA were employed to screen and identify 'biomarkers', which were further verified by a pairwise t-test and fold change judgement. Eventually, the 64 PPCPs as 'biomarkers' were divided into 5 groups, which correspond to 5 column groups, consistent with the findings of traditional PPCP recovery comparison, proving the validity of the metabolomics-based screening method. This novel method will exhibit greater superiority in choosing suitable SPE columns to handle a growing and larger number of PPCPs in water environments and beyond.

Insights into the dynamic trajectories of protein filament division revealed by numerical investigation into the mathematical model of pure fragmentation.

The dynamics by which polymeric protein filaments divide in the presence of negligible growth, for example due to the depletion of free monomeric precursors, can be described by the universal mathematical equations of 'pure fragmentation'. The rates of fragmentation reactions reflect the stability of the protein filaments towards breakage, which is of importance in biology and biomedicine for instance in governing the creation of amyloid seeds and the propagation of prions. Here, we devised from mathematical theory inversion formulae to recover the division rates and division kernel information from time-dependent experimental measurements of filament size distribution. The numerical approach to systematically analyze the behaviour of pure fragmentation trajectories was also developed. We illustrate how these formulae can be used, provide some insights on their robustness, and show how they inform the design of experiments to measure fibril fragmentation dynamics. These advances are made possible by our central theoretical result on how the length distribution profile of the solution to the pure fragmentation equation aligns with a steady distribution profile for large times.

Amyloid particles facilitate surface-catalyzed cross-seeding by acting as promiscuous nanoparticles.

Amyloid seeds are nanometer-sized protein particles that accelerate amyloid assembly as well as propagate and transmit the amyloid protein conformation associated with a wide range of protein misfolding diseases. However, seeded amyloid growth through templated elongation at fibril ends cannot explain the full range of molecular behaviors observed during cross-seeded formation of amyloid by heterologous seeds. Here, we demonstrate that amyloid seeds can accelerate amyloid formation via a surface catalysis mechanism without propagating the specific amyloid conformation associated with the seeds. This type of seeding mechanism is demonstrated through quantitative characterization of the cross-seeded assembly reactions involving two nonhomologous and unrelated proteins: the human Aß42 peptide and the yeast prion-forming protein Sup35NM. Our results demonstrate experimental approaches to differentiate seeding by templated elongation from nontemplated amyloid seeding and rationalize the molecular mechanism of the cross-seeding phenomenon as a manifestation of the aberrant surface activities presented by amyloid seeds as nanoparticles.

On the Structural Diversity and Individuality of Polymorphic Amyloid Protein Assemblies.

The prediction of highly ordered three-dimensional structures of amyloid protein fibrils from the amino acid sequences of their monomeric self-assembly precursors constitutes a challenging and unresolved aspect of the classical protein folding problem. Because of the polymorphic nature of amyloid assembly whereby polypeptide chains of identical amino acid sequences under identical conditions are capable of self-assembly into a spectrum of different fibril structures, the prediction of amyloid structures from an amino acid sequence requires a detailed and holistic understanding of its assembly free energy landscape. The full extent of the structure space accessible to the cross-ß molecular architecture of amyloid must also be resolved. Here, we review the current understanding of the diversity and the individuality of amyloid structures, and how the polymorphic landscape of amyloid links to biology and disease phenotypes. We present a comprehensive review of structural models of amyloid fibrils derived by cryo-EM, ssNMR and AFM to date, and discuss the challenges ahead for resolving the structural basis and the biological consequences of polymorphic amyloid assemblies.

Thermodynamics of amyloid fibril formation from non-equilibrium experiments of growth and dissociation.

Amyloid fibrils are ordered, non-covalent polymers of proteins that are linked to a range of diseases, as well as biological functions. Amyloid fibrils are often considered thermodynamically so stable that they appear to be irreversible, explaining why very few quantitative thermodynamic studies have been performed on amyloid fibrils, compared to the very large body of kinetic studies. Here we explore the thermodynamics of amyloid fibril formation by the protein PI3K-SH3, which forms amyloid fibrils under acidic conditions. We use quartz crystal microbalance (QCM) and develop novel temperature perturbation experiments based on differential scanning fluorimetry (DSF) to measure the temperature dependence of the fibril growth and dissociation rates, allowing us to quantitatively describe the thermodynamic stability of PI3K-SH3 amyloid fibrils between 10 and 75°C.

The Division of Amyloid Fibrils: Systematic Comparison of Fibril Fragmentation Stability by Linking Theory with Experiments.

The division of amyloid protein fibrils is required for the propagation of the amyloid state and is an important contributor to their stability, pathogenicity, and normal function. Here, we combine kinetic nanoscale imaging experiments with analysis of a mathematical model to resolve and compare the division stability of amyloid fibrils. Our theoretical results show that the division of any type of filament results in self-similar length distributions distinct to each fibril type and the conditions applied. By applying these theoretical results to profile the dynamical stability toward breakage for four different amyloid types, we reveal particular differences in the division properties of disease-related amyloid formed from α-synuclein when compared with non-disease associated model amyloid, the former showing lowered intrinsic stability toward breakage and increased likelihood of shedding smaller particles. Our results enable the comparison of protein filaments' intrinsic dynamic stabilities, which are key to unraveling their toxic and infectious potentials.

Three-dimensional reconstruction of individual helical nano-filament structures from atomic force microscopy topographs.

Atomic force microscopy, AFM, is a powerful tool that can produce detailed topographical images of individual nano-structures with a high signal-to-noise ratio without the need for ensemble averaging. However, the application of AFM in structural biology has been hampered by the tip-sample convolution effect, which distorts images of nano-structures, particularly those that are of similar dimensions to the cantilever probe tips used in AFM. Here we show that the tip-sample convolution results in a feature-dependent and non-uniform distribution of image resolution on AFM topographs. We show how this effect can be utilised in structural studies of nano-sized upward convex objects such as spherical or filamentous molecular assemblies deposited on a flat surface, because it causes 'magnification' of such objects in AFM topographs. Subsequently, this enhancement effect is harnessed through contact-point based deconvolution of AFM topographs. Here, the application of this approach is demonstrated through the 3D reconstruction of the surface envelope of individual helical amyloid filaments without the need of cross-particle averaging using the contact-deconvoluted AFM topographs. Resolving the structural variations of individual macromolecular assemblies within inherently heterogeneous populations is paramount for mechanistic understanding of many biological phenomena such as amyloid toxicity and prion strains. The approach presented here will also facilitate the use of AFM for high-resolution structural studies and integrative structural biology analysis of single molecular assemblies.

Quantification of amyloid fibril polymorphism by nano-morphometry reveals the individuality of filament assembly.

Amyloid fibrils are highly polymorphic structures formed by many different proteins. They provide biological function but also abnormally accumulate in numerous human diseases. The physicochemical principles of amyloid polymorphism are not understood due to lack of structural insights at the single-fibril level. To identify and classify different fibril polymorphs and to quantify the level of heterogeneity is essential to decipher the precise links between amyloid structures and their functional and disease associated properties such as toxicity, strains, propagation and spreading. Employing gentle, force-distance curve-based AFM, we produce detailed images, from which the 3D reconstruction of individual filaments in heterogeneous amyloid samples is achieved. Distinctive fibril polymorphs are then classified by hierarchical clustering, and sample heterogeneity is objectively quantified. These data demonstrate the polymorphic nature of fibril populations, provide important information regarding the energy landscape of amyloid self-assembly, and offer quantitative insights into the structural basis of polymorphism in amyloid populations.