Aggregation Kinetics Data Research Articles

Polyamines putrescine and spermidine as modulators of protein aggregation rate: The effect on DTT-induced aggregation of α-lactalbumin

Protein aggregation is undesirable for cells due to its possible toxicity, and is also undesirable in biotechnology and pharmaceuticals. Polyamines are known to be capable of both suppressing and stimulating protein aggregation. In the present work polyamines (spermidine, putrescine) have been shown to alter the pathway of α-lactalbumin aggregation induced by dithiothreitol, leading to the formation of larger protein particles during the initial stages of aggregation and promoting the later stage of sticking of aggregates. According to the aggregation kinetics data, polyamines accelerate protein aggregation in a concentration-dependent manner, with a maximum at 50 mM spermidine and 100 mM putrescine. With a further increase in polyamines concentration the effect of aggregation acceleration decreased, thus, the modulation of the aggregation rate by polyamines was shown. A comparison of the aggregation kinetics and hydrodynamic radii growth data registered by dynamic light scattering with the data obtained by asymmetric flow field-flow fractionation and analytical ultracentrifugation allowed us to describe the early stages of aggregation and formation of initial α-lactalbumin clusters. Our results provide a deeper insight into the mechanism of amorphous aggregation of α-lactalbumin and polyamines action on protein aggregation and protein-protein interaction in general.

C1 Inhibits Liquid-Liquid Phase Separation and Oligomerization of Tau and Protects Neuroblastoma Cells against Toxic Tau Oligomers.

The pathological aggregation of tau is one of the major contributing factors for several neurodegenerative tauopathies, including Alzheimer's disease. Here, we report that C1, a synthetic derivative of curcumin, strongly inhibited both the aggregation and filament formation of purified tau and protected neuroblastoma cells from the deleterious effects of the tau oligomers. Using confocal microscopy, C1 was found to reduce both the size and number of the tau droplets and increased the critical concentration of tau required for the droplet formation in vitro indicating that C1 suppressed the liquid-liquid phase separation of tau. C1 inhibited the aggregation of tau with a half-maximal inhibitory concentration of 1.5 ± 0.1 μM. An analysis of the aggregation kinetics data indicated that C1 strongly reduced the initial rate of the aggregation of tau. A dot blot analysis using tau-oligomer-specific antibody indicated that C1 inhibited the oligomerization of tau. Furthermore, dynamic light scattering experiments suggested that C1 strongly reduced the mean diameter of the tau oligomers. Atomic force microscopy experiments showed that C1 treatment reduced both the size and number of tau oligomers, suppressed the transition of tau oligomers into filaments, and also disintegrated preformed tau filaments. Also, the binding interaction of C1 with tau was monitored using absorbance and fluorescence spectroscopy. C1 bound to Y310W-tau with a dissociation constant of 2.0 ± 0.5 μM. The findings suggested that C1 is a potent inhibitor of tau aggregation and provided insights into the inhibitory mechanism of C1 on the oligomerization and fibril formation of tau.

Exploring the occurrence of thioflavin-T-positive insulin amyloid aggregation intermediates.

The aggregation of proteins is considered to be the main cause of several neurodegenerative diseases. Despite much progress in amyloid research, the process of fibrillization is still not fully understood, which is one of the main reasons why there are still very few effective treatments available. When the aggregation of insulin, a model amyloidogenic protein, is tracked using thioflavin-T (ThT), an amyloid specific dye, there is an anomalous occurrence of double-sigmoidal aggregation kinetics. Such an event is likely related to the formation of ThT-positive intermediates, which may affect the outcome of both aggregation kinetic data, as well as final fibril structure. In this work we explore insulin fibrillization under conditions, where both normal and double-sigmoidal kinetics are observed and show that, despite their dye-binding properties and random occurrence, the ThT-positive intermediates do not significantly alter the overall aggregation process.

Nucleation-dependent Aggregation Kinetics of Yeast Sup35 Fragment GNNQQNY

An N-terminal hepta-peptide sequence of yeast prion protein Sup35 with the sequence GNNQQNY is widely used as a model system for amyloid fibril formation. In this study, we used a reproducible solubilisation protocol that allows the generation of a homogenous monomeric solution of GNNQQNY to uncover the molecular details of its self-assembly mechanism. The aggregation kinetics data show that the GNNQQNY sequence follows nucleation-dependent aggregation kinetics with a critical nucleus of size ~7 monomers and that the efficiency of nucleation were found to be inversely related to the reaction temperature. The nucleus reduces the thermodynamic energy barrier by acting as a template for further self-assembly and results in highly ordered amyloid fibrils. The fibers grown at different temperatures showed similar Thioflavin T fluorescence, Congo-red binding and β-sheet rich structures displaying a characteristic cross-β diffraction pattern. These aggregates also share morphological and structural identity with those reported earlier. The mature GNNQQNY fibers did not exert significant oxidative stress or cytotoxicity upon incubating with differentiated SHSY5Y cells. To our knowledge, this is the first study to experimentally validate previous nucleus size predictions based on theoretical and molecular dynamics simulations. These findings provide the basis for understanding the kinetics and thermodynamics of amyloid nucleation and elongation of amyloidogenic proteins/peptides associated with many systemic and neurodegenerative diseases.

Capreomycin inhibits the initiation of amyloid fibrillation and suppresses amyloid induced cell toxicity

Protein aggregation and amyloid fibrillation are responsible for several serious pathological conditions (like type II diabetes, Alzheimer's and Parkinson's diseases etc.) and protein drugs ineffectiveness. Therefore, a molecule that can inhibit the amyloid fibrillation and potentially clear amyloid fibrils is of great therapeutic value. In this manuscript, we investigated the antiamyloidogenic, fibril disaggregating, as well as cell protective effect of an anti-tuberculosis drug, Capreomycin (CN). Aggregation kinetics data, as monitored by ThT fluorescence, inferred that CN retards the insulin amyloid fibrillation by primarily targeting the fibril elongation step with little effect on lag time. Increasing the dose of CN boosted its inhibitory potency. Strikingly, CN arrested the growth of fibrils when added during the elongation phase, and disaggregated mature insulin fibrils. Our Circular Dichroism (CD) results showed that, although CN is not able to maintain the alpha helical structure of protein during fibrillation, reduces the formation of beta sheet rich structure. Furthermore, Dynamic Light Scattering (DLS) and Transmission Electronic Microscopy (TEM) analysis confirmed that CN treated samples exhibited different size distribution and morphology, respectively. In addition, molecular docking results revealed that CN interacts with insulin through hydrophobic interactions as well as hydrogen bonding, and the Hemolytic assay confirmed the non-hemolytic activity of CN on human RBCs. For future research, this study may assist in the rational designing of molecules against amyloid formation.

Multistability in a prion replication interconnected cell reaction network

Aggregation of misfolded proteins has been implicated in a number of neurodegenerative disorders including prion disease. In spite of intensive research, the detailed mechanisms of protein misfolding leading to protein aggregation remain unsolved. Here, we explore the capacity for bistability of several classes of mechanisms proposed in the literature and compatible with protein aggregation kinetic data sets (it has been shown that bistability explains thresholds phenomena observed in protein aggregation in vitro and in vivo). Using a novel method for bistability detection we find a plausible scenario for which the so called subsequent monomer addition model leads to bistability.

Kfits: a software framework for fitting and cleaning outliers in kinetic measurements.

Kinetic measurements have played an important role in elucidating biochemical and biophysical phenomena for over a century. While many tools for analysing kinetic measurements exist, most require low noise levels in the data, leaving outlier measurements to be cleaned manually. This is particularly true for protein misfolding and aggregation processes, which are extremely noisy and hence difficult to model. Understanding these processes is paramount, as they are associated with diverse physiological processes and disorders, most notably neurodegenerative diseases. Therefore, a better tool for analysing and cleaning protein aggregation traces is required. Here we introduce Kfits, an intuitive graphical tool for detecting and removing noise caused by outliers in protein aggregation kinetics data. Following its workflow allows the user to quickly and easily clean large quantities of data and receive kinetic parameters for assessment of the results. With minor adjustments, the software can be applied to any type of kinetic measurements, not restricted to protein aggregation. Kfits is implemented in Python and available online at http://kfits.reichmannlab.com, in source at https://github.com/odedrim/kfits/, or by direct installation from PyPI (`pip install kfits`). danare@mail.huji.ac.il. Supplementary data are available at Bioinformatics online.

Model-based optimization of parameters for degradation reaction of an organophosphorus pesticide, paraoxon, using CeO2 nanoparticles in water media

Degradation and body surface decontamination is vital to prevent the skin penetration of paraoxon (POX), an organophosphorus pesticide, and victims poisoning. CeO2 demonstrated a good efficacy for the degradation of POX. The aim of the study was to develop a model which includes the impact of weight of CeO2, POX and diluent volumes on the degradation kinetics. The modelling was realized with rapid and simple experiments carried out in tubes, in aqueous diluent which contained ions in order to be in accordance with in vitro skin decontamination conditions. CeO2 had degraded from 5% (in case of 7.5mmol of POX per gram of CeO2) to 100% (0.002mmol of POX per gram of CeO2) of POX. Different kinetic models were tested. Using the particle aggregation kinetic model, the simulated and experimental data were in a good accordance. It highlighted the importance of particles aggregation due to salts and consistency of the mix on the degradation efficiency of CeO2. The model worked also really well to predict the degradation efficiency of CeO2 powders during in vitro skin experiments. However, it did not correctly forecast with an aqueous decontaminant, containing CeO2.

Aggregation Kinetics of Diesel Soot Nanoparticles in Wet Environments.

Soot produced during incomplete combustion consists mainly of carbonaceous nanoparticles (NPs) with severe adverse environmental and health effects, and its environmental fate and transport are largely controlled by aggregation. In this study, we examined the aggregation behavior for diesel soot NPs under aqueous condition in an effort to elucidate the fundamental processes that govern soot particle-particle interactions in wet environments such as rain droplets or surface aquatic systems. The influence of electrolytes and aqueous pH on colloidal stability of these NPs was investigated by measuring their aggregation kinetics in different aqueous solution chemistries. The results showed that the NPs had negatively charged surfaces and exhibited both reaction- and diffusion-limited aggregation regimes with rates depended upon solution chemistry. The aggregation kinetics data were in good agreement with the classic Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. The critical coagulation concentrations (CCC) were quantified and the Hamaker constant was derived for the soot (1.4 × 10-20 J) using the colloidal chemistry approach. The study indicated that, depending upon local aqueous chemistry, single soot NPs could remain stable against self-aggregation in typical freshwater environments and in neutral cloud droplets but are likely to aggregate under salty (e.g., estuaries) or acidic (e.g., acid rain droplets) aquatic conditions or both.

Pre-study and in-study validation of a size-exclusion chromatography method with different detection modes for the analysis of monoclonal antibody aggregates.

Size exclusion chromatography (SEC) with different detection modes was assessed as a means to characterize the type of bevacizumab aggregate that forms under thermal stress, quantitatively monitoring the aggregation kinetics. The combination of SEC with light-scattering (SEC/LS) detection was validated using in-study validation process. This was performed by applying a strategy based on a control chart to monitor the process parameters and by inserting quality control samples in routine runs. The SEC coupled with a differential refractive-index detector (SEC/RI) was validated using a pre-study validation process in accordance with the ICH-Q2 (R1) guidelines and in-study monitoring in accordance with the Analytical Target Profile (ATP) criteria. The total error and β-expectation tolerance interval rules were used to assess method suitability and control the risk of incorrectly accepting unsuitable analytical methods. The aggregation kinetics data were interpreted using a modified Lumry-Eyring model. The true order of the reaction was determined using the initial-rate approach. All the kinetic data show a linear Arrhenius dependence within the studied temperature range. The Arrhenius approach over-predicted the aggregation rate for 5°C, but provides an idea of the aggregation process and amount of aggregate formed. In any case, real-time stability data are necessary to establish the product shelf-life.

Fitting bevacizumab aggregation kinetic data with the Finke–Watzky two-step model: Effect of thermal and mechanical stress

Size exclusion chromatography with light scattering detection (SEC-MALLS) was assessed as a means to characterize the type of bevacizumab aggregates that form under mechanical and thermal stress, quantitatively monitoring the aggregation kinetics. The analytical method was monitored and verified during routine use at two levels: (1) the “pre-study” validation shows that the method is specific, linear, accurate, precise, robust and stability indicating; (2) the “in-study” validation was verified by inserting quality control samples and the use of control charts, indicating that the analytical method is in statistical control and stable.The aggregation kinetics data were interpreted using a modified Lumry–Eyring model, but the quality of the fit can be considered poor (R2>0.96), especially at higher temperatures. This indicates that the order of the reaction could not be reliably determined, suggesting a different degradation mechanism. The kinetic data set also fit the minimalistic Finke–Watzky (F–W) 2-step model, with an excellent quality of fit (R2>0.99), yielding the first quantitative rate constant for the steps of nucleation and growth in bevacizumab aggregation. The bevacizumab pharmaceutical preparation contains (initially) dimers, approximately 1.6% of bevacizumab total concentration, and the effect on aggregation kinetics of seeding was analyzed using the F–W 2-step model assuming [B]0≠0 (for the seeded case). The results suggested that the seeding had no impact on aggregation kinetics. Furthermore, the Arrhenius equation cannot be used to extrapolate the shelf-life since no linear temperature dependence of the rate constant was found within the temperature range. Although the real-time stability data provides the basis for determining the product shelf-life, predictive methodologies such as Vogel–Tammann–Fulcher (VFT) or the Arrhenius approach can be misleading and result in overestimates of the product shelf-life. However, they can be successfully applied to fixing the lower and upper limits of the aggregation rate, i.e. the best and worst-case scenarios regarding the aggregation potential of the product.In conclusion, the present study evaluates the first application of the F–W 2-step model to fitting and interpretation of experimental aggregation data for bevacizumab pharmaceutical preparations, using SEC-MALLS in this context.

Stability and sedimentation of silver nanoparticles in the presence of monovalent, divalent and trivalent electrolyte solutions.

The present study seeks to elucidate the effect of different electrolytes on the stability of citrate-coated silver nanoparticles synthesized by the reduction of the Ag(NH3)(2)(+) complex via Tollens' method. Time-resolved dynamic light scattering technique was used to measure the aggregation behavior of the nanoparticles over a range of electrolyte (NaCl, CaCl₂, and AlCl₃) concentrations. From the aggregation kinetic data, the critical coagulation concentration values were calculated as 0.11, 1.7 × 10⁻³, and 5.06 × 10⁻⁶ M for NaCl, CaCl₂, and AlCl₃, respectively. Supernatant of the nanoparticle suspension in presence of the three electrolytes was collected and measured using inductively coupled plasma mass spectrometry to quantify the sedimentation. It was found that the silver nanoparticle aggregates settled rapidly in the slow aggregation and fast aggregation regimes. Their sedimentation followed a nanoparticle size-dependent manner.

Biophysical Underpinnings of the Repeat Length Dependence of Polyglutamine Amyloid Formation

There are now 10 expanded CAG repeat diseases in which both disease risk and age of onset are strongly dependent on the repeat length of the polyglutamine (polyQ) sequence in the disease protein. Large, polyQ-rich inclusions in patient brains and in cell and animal models are consistent with the involvement of polyQ aggregation in the disease mechanism. This possibility is reinforced by studies showing strong repeat length dependence to the aggregation process, qualitatively mirroring the repeat length dependence of disease risk. Our understanding of the underlying biophysical principles that mediate the repeat length dependence of aggregation, however, is far from complete. A previous study of simple polyQ peptides showed that N*, the size of the critical nucleus that controls onset of aggregation, decreases from unfavorable tetramer to favorable monomer over the range Q23 to Q26. These data, however, do not explain why, for all peptides exhibiting N* ∼ 1, spontaneous aggregation rates continue to increase with increasing repeat length. Here we describe a novel kinetics analyses that maps out the nonlinear dependence with repeat length of a nucleation efficiency term that is likely related to aspects of nucleus structure. This trend accounts for why nucleus size increases to tetrameric at repeat lengths of Q23 or below. Intriguingly, both aggregation and age of onset trend with repeat length in similar ways, exhibiting large changes per added Gln at low repeat lengths and small changes per added Gln at relatively long repeat lengths. Fibril stability also increases with repeat length in a nonlinear fashion.

The effect of electrolytes on the aggregation kinetics of titanium dioxide nanoparticle aggregates

Metal oxide nanoparticles (NPs) are receiving increasing attention due to their increased industrial production and potential hazardous effect. The process of aggregation plays a key role in the fate of NPs in the environment and the resultant health risk. The aggregation of commercial titanium dioxide NP powder (25 nm) was investigated with various environmentally relevant solution chemistries containing different concentrations of monovalent (Na+, K+) and divalent (Ca2+) electrolytes. Titanium dioxide particle size increased with the increase in ion concentration. The stability of titanium dioxide also depended on the ionic composition. Titanium dioxide aggregated to a higher degree in the presence of divalent cations than monovalent ones. The attachment efficiency of NPs was constructed through aggregation kinetics data, from which the critical coagulation concentrations for the various electrolytes are determined (80, 19, and 1 meq/L for Na+, K+, and Ca2+, respectively). Our results suggest that titanium dioxide NP powders are relatively unstable in water and could easily be removed by adding multivalent cations so hazardous potentials decrease in aquatic environment.

Study of colloidal particle Brownian aggregation by low-coherence fiber optic dynamic light scattering

The aggregation kinetics of particles in dense polystyrene latex suspensions is studied by low-coherence fiber optic dynamic light scattering. Low-coherence fiber optic dynamic light scattering is used to measure the hydrodynamic radius of the aggregates. The aggregation kinetics data obtained can be fitted into a single exponential function, which is the characteristic of slow aggregation. It is found that the aggregation rate of particles increased with higher electrolyte levels and with larger particle concentrations. The experimental results can be explained by use of the Derjaruin–Landau–Verwey–Overbeer (DLVO) theory.

α-Synuclein aggregation variable temperature and variable pH kinetic data: A re-analysis using the Finke–Watzky 2-step model of nucleation and autocatalytic growth

The aggregation of proteins is believed to be intimately connected to many neurodegenerative disorders. We recently reported an “Ockham's razor”/minimalistic approach to analyze the kinetic data of protein aggregation using the Finke–Watzky (F–W) 2-step model of nucleation (A → B, rate constant k 1) and autocatalytic growth (A + B → 2B, rate constant k 2). With that kinetic model we have analyzed 41 representative protein aggregation data sets in two recent publications, including amyloid β, α-synuclein, polyglutamine, and prion proteins (Morris, A. M., et al. (2008) Biochemistry 47, 2413-2427; Watzky, M. A., et al. (2008) Biochemistry 47, 10790–10800). Herein we use the F–W model to reanalyze protein aggregation kinetic data obtained under the experimental conditions of variable temperature or pH 2.0 to 8.5. We provide the average nucleation ( k 1) and growth ( k 2) rate constants and correlations with variable temperature or varying pH for the protein α-synuclein. From the variable temperature data, activation parameters Δ G ‡, Δ H ‡, and Δ S ‡ are provided for nucleation and growth, and those values are compared to the available parameters reported in the previous literature determined using an empirical method. Our activation parameters suggest that nucleation and growth are energetically similar for α-synuclein aggregation (Δ G ‡ nucleation = 23(3) kcal/mol; Δ G ‡ growth = 22(1) kcal/mol at 37 °C). From the variable pH data, the F–W analyses show a maximal k 1 value at pH ~ 3, as well as minimal k 1 near the isoelectric point (pI) of α-synuclein. Since solubility and net charge are minimized at the pI, either or both of these factors may be important in determining the kinetics of the nucleation step. On the other hand, the k 2 values increase with decreasing pH (i.e., do not appear to have a minimum or maximum near the pI) which, when combined with the k 1 vs. pH (and pI) data, suggest that solubility and charge are less important factors for growth, and that charge is important in the k 1, nucleation step of α-synuclein. The chemically well-defined nucleation ( k 1) rate constants obtained from the F–W analysis are, as expected, different than the 1/lag-time empirical constants previously obtained. However, k 2 × [ A] 0 (where k 2 is the rate constant for autocatalytic growth and [ A] 0 is the initial protein concentration) is related to the empirical constant, k app obtained previously. Overall, the average nucleation and average growth rate constants for α-synuclein aggregation as a function of pH and variable temperature have been quantitated. Those values support the previously suggested formation of a partially folded intermediate that promotes aggregation under high temperature or acidic conditions.

Fitting Yeast and Mammalian Prion Aggregation Kinetic Data with the Finke−Watzky Two-Step Model of Nucleation and Autocatalytic Growth

Recently, we reported 14 amyloid protein aggregation kinetic data sets that were fit using the "Ockham's razor"/minimalistic Finke-Watzky (F-W) two-step model of slow nucleation (A --> B, rate constant k 1) and fast autocatalytic growth (A + B --> 2B, rate constant k 2), yielding quantitative (average) rate constants for nucleation ( k 1) and growth ( k 2), where A is the monomeric protein and B is the polymeric protein [Morris, A. M., et al. (2008) Biochemistry 47, 2413-2427]. Herein, we apply the F-W model to 27 representative prion aggregation kinetic data sets obtained from the literature. Each prion data set was successfully fit with the F-W model, including three different yeast prion proteins (Sup35p, Ure2p, and Rnq1p) as well as mouse and human prions. These fits yield the first quantitative rate constants for the steps of nucleation and growth in prion aggregation. Examination of a Sup35p system shows that the same rate constants are obtained for nucleation and for growth within experimental error, regardless of which of six physical methods was used, a unique set of important control experiments in the protein aggregation literature. Also provided herein are analyses of several factors influencing the aggregation of prions such as glutamine/asparagine rich regions and the number of oligopeptide repeats in the prion domain. Where possible, verification or refutation of previous correlations to glutamine/asparagine regions, or the number of repeat sequences, in literature aggregation kinetics is given in light of the quantitative rate constants obtained herein for nucleation and growth during prion aggregation. The F-W model is then contrasted to four literature mechanisms that address the molecular picture of prion transmission and propagation. Key limitations of the F-W model are listed to prevent overinterpretation of the data being analyzed, limitations that derive ultimately from the model's simplicity. Finally, possible avenues of future research are suggested.

Fitting Neurological Protein Aggregation Kinetic Data via a 2-Step, Minimal/“Ockham's Razor” Model: The Finke−Watzky Mechanism of Nucleation Followed by Autocatalytic Surface Growth

The aggregation of proteins has been hypothesized to be an underlying cause of many neurological disorders including Alzheimer's, Parkinson's, and Huntington's diseases; protein aggregation is also important to normal life function in cases such as G to F-actin, glutamate dehydrogenase, and tubulin and flagella formation. For this reason, the underlying mechanism of protein aggregation, and accompanying kinetic models for protein nucleation and growth (growth also being called elongation, polymerization, or fibrillation in the literature), have been investigated for more than 50 years. As a way to concisely present the key prior literature in the protein aggregation area, Table 1 in the main text summarizes 23 papers by 10 groups of authors that provide 5 basic classes of mechanisms for protein aggregation over the period from 1959 to 2007. However, and despite this major prior effort, still lacking are both (i) anything approaching a consensus mechanism (or mechanisms), and (ii) a generally useful, and thus widely used, simplest/"Ockham's razor" kinetic model and associated equations that can be routinely employed to analyze a broader range of protein aggregation kinetic data. Herein we demonstrate that the 1997 Finke-Watzky (F-W) 2-step mechanism of slow continuous nucleation, A --> B (rate constant k1), followed by typically fast, autocatalytic surface growth, A + B --> 2B (rate constant k2), is able to quantitatively account for the kinetic curves from all 14 representative data sets of neurological protein aggregation found by a literature search (the prion literature was largely excluded for the purposes of this study in order provide some limit to the resultant literature that was covered). The F-W model is able to deconvolute the desired nucleation, k1, and growth, k2, rate constants from those 14 data sets obtained by four different physical methods, for three different proteins, and in nine different labs. The fits are generally good, and in many cases excellent, with R2 values >or=0.98 in all cases. As such, this contribution is the current record of the widest set of protein aggregation data best fit by what is also the simplest model offered to date. Also provided is the mathematical connection between the 1997 F-W 2-step mechanism and the 2000 3-step mechanism proposed by Saitô and co-workers. In particular, the kinetic equation for Saitô's 3-step mechanism is shown to be mathematically identical to the earlier, 1997 2-step F-W mechanism under the 3 simplifying assumptions Saitô and co-workers used to derive their kinetic equation. A list of the 3 main caveats/limitations of the F-W kinetic model is provided, followed by the main conclusions from this study as well as some needed future experiments.

DNA induces folding in α-synuclein: Understanding the mechanism using chaperone property of osmolytes

α-Synuclein conformational modulation leading to fibrillation has been centrally implicated in Parkinson’s disease. Previously, we have shown that α-synuclein has DNA binding property. In the present study, we have characterized the effect of DNA binding on the conformation and fibrillation kinetics of α-synuclein. It was observed that single-stranded circular DNA induce α-helix conformation in α-synuclein while plasmid supercoiled DNA has dual effect inducing a partially folded conformation and α-helix under different experimental conditions. Interestingly, α-synuclein showed a specificity for GC* nucleotide sequence in its binding ability to DNA. The aggregation kinetics data showed that DNA which induced partially folded conformation in α-synuclein promoted the fibrillation while DNA which induced α-helix delayed the fibrillation, indicating that the partially folded intermediate conformation is critical in the aggregation process. Further, the mechanism of DNA-induced folding/aggregation of α-synuclein was studied using effect of osmolytes on α-synuclein as a model system. Among the five osmolytes used, Glycerol, trimethylamine- N-oxide, Betaine, and Taurine induced partially folded conformation and in turn enhanced the aggregation of α-synuclein. The ability of DNA and osmolytes in inducing conformational transition in α-synuclein, indicates that two factors are critical in modulating α-synuclein folding: (i) electrostatic interaction as in the case of DNA, and (ii) hydrophobic interactions as in the case of osmolytes. The property of DNA inducing α-helical conformation in α-synuclein and inhibiting the fibrillation may be of significance in engineering DNA-chip based therapeutic approaches to PD and other amyloid disorders.

Aggregation kinetics of latex microspheres in alcohol–water media

We report zeta potential and aggregation kinetics data on colloidal latex particles immersed in water–alcohol media. Zeta potential values show absolute maxima for volume fractions of alcohol of 0.10 and 0.05 for ethanol and 1-propanol, respectively. For methanol, no maximum of the absolute value of the zeta potential was found. Aggregation kinetics was studied by means of a single-cluster optical sizing equipment and for alcohol volume fractions ranging from 0 to 0.1. The aggregation processes are induced by adding different potassium bromide concentrations to the samples. We expected to find a slowdown of the overall aggregation kinetics for ethanol and 1-propanol, and no significant effect for methanol, as compared with pure water data. That is, we expected the zeta potential to govern the overall aggregation rate. However, we obtained a general enhancement of the aggregation kinetics for methanol and 1-propanol and a general slowdown of the aggregation rate for ethanol. In addition, aggregation data under ethanol show a slower kinetics for large electrolyte concentration than that obtained for intermediate electrolyte concentration. We think that these anomalous behaviors are linked to layering, changes in hydrophobicity of particle surfaces due to alcohol adsorption, complex ion–water–alcohol–surface structuring, and competition between alcohol–surface adsorption and alcohol–alcohol clustering.