Kinetics of spherulite formation and growth: Salt and protein concentration dependence on proteins β-lactoglobulin and insulin

Domike, Kristin R.; Donald, Athene M.

doi:10.1016/j.ijbiomac.2008.12.014

Cited by 26 publications

(32 citation statements)

References 35 publications

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“…1(a)). [48,49] Successful amyloid fiber formation was confirmed with AFM of the fibers adsorbed onto Si surfaces ( Fig. 1(b),1(c)).…”

Section: Preparation and Identification Of Fibers And Spherulitesmentioning

confidence: 67%

“…At the center of the insulin spherulites, a dark region is observed in the structures, for which an associated large amorphous core has been suggested. [43][44][45]48] For β-LG spherulites, the corresponding dark region at the center is small, which implies a small or non-existent amorphous core. Finally, UV-Vis absorption spectra were captured and the expected absorption of the ring-structures in the proteins at about 278 nm was detected for all samples ( Fig.…”

Section: Preparation and Identification Of Fibers And Spherulitesmentioning

confidence: 99%

“…The assembly process depends on several factors, such as the protein concentration, temperature, pH and ion concentrations, and has been described elsewhere. [43][44][45][46][47][48][49][50][51] The microscopy efforts in this work focused on spherulites prepared from these proteins and the intrinsic optical properties of these amyloid structures were utilized in label-free imaging applications.…”

Section: Introductionmentioning

confidence: 99%

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Label-free imaging of amyloids using their intrinsic linear and nonlinear optical properties

Johansson¹,

Koelsch²

2017

Biomed. Opt. Express

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The optical properties of amyloid fibers are often distinct from those of the source protein in its non-fibrillar form. These differences can be utilized for label-free imaging or characterization of such structures, which is particularly important for understanding amyloid fiber related diseases such as Alzheimer's and Parkinson's disease. We demonstrate that two amyloid forming proteins, insulin and β-lactoglobulin (β-LG), show intrinsic fluorescence with emission spectra that are dependent on the excitation wavelength. Additionally, a new fluorescence peak at about 430 nm emerges for β-LG in its amyloid state. The shift in emission wavelength is related to the red edge excitation shift (REES), whereas the additional fluorescence peak is likely associated with charge delocalization along the fiber backbone. Furthermore, the spherulitic amyloid plaque-like superstructures formed from the respective proteins were imaged label-free with confocal fluorescence, multiphoton excitation fluorescence (MPEF), and second-harmonic generation (SHG) microscopy. The latter two techniques in particular yield images with a high contrast between the amyloid fiber regions and the core of amorphously structured protein. Strong multiphoton absorption (MPA) for the amyloid fibers is a likely contributor to the observed contrast in the MPEF images. The crystalline fibrillar region provides even higher contrast in the SHG images, due to the inherently ordered non-centrosymmetric structure of the fibers together with their non-isotropic arrangement. Finally, we show that MPEF from the insulin spherulites exhibits a spectral dependence on the excitation wavelength. This behavior is consistent with the REES phenomenon, which we hypothesize is the origin of this observation. The presented results suggest that amyloid deposits can be identified and structurally characterized based on their intrinsic optical properties, which is important for probe-less and label-free identification and characterization of amyloid fibers in vitro and in complex biological samples. A. 82(12), 4245-4249 (1985). 8. L. C. Serpell, "Alzheimer's amyloid fibrils: structure and assembly," Biochim. Biophys. Acta 1502(1), 16-30 (2000

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“…1(a)). [48,49] Successful amyloid fiber formation was confirmed with AFM of the fibers adsorbed onto Si surfaces ( Fig. 1(b),1(c)).…”

Section: Preparation and Identification Of Fibers And Spherulitesmentioning

confidence: 67%

Section: Preparation and Identification Of Fibers And Spherulitesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Label-free imaging of amyloids using their intrinsic linear and nonlinear optical properties

Johansson¹,

Koelsch²

2017

Biomed. Opt. Express

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“…[93][94][95][96] Spherulitic structures were also implicated in various human diseases such as Alzheimer's, type II diabetes, and other protein aggregation diseases. [97][98][99] Two main categories of the spherulitic morphologies are usually distinguished. Category 1 spherulites grow radially from their center, maintaining a space-filling character via dense branching.…”

Section: Disordered (''Dizzy'') Dendrites: Particles Vs M Hmentioning

confidence: 99%

Phase-Field Modeling of Polycrystalline Solidification: From Needle Crystals to Spherulites—A Review

Gránásy

Rátkai

Szàllàs

et al. 2013

Metall Mater Trans A

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LÁ SZLÓ GRÁ NÁ SY, LÁ SZLÓ RÁ TKAI, ATTILA SZÁ LLÁ S, BÁ LINT KORBULY, GYULA I. TÓ TH, LÁ SZLÓ KÖ RNYEI, and TAMÁ S PUSZTAI Advances in the orientation-field-based phase-field (PF) models made in the past are reviewed. The models applied incorporate homogeneous and heterogeneous nucleation of growth centers and several mechanisms to form new grains at the perimeter of growing crystals, a phenomenon termed growth front nucleation. Examples for PF modeling of such complex polycrystalline structures are shown as impinging symmetric dendrites, polycrystalline growth forms (ranging from disordered dendrites to spherulitic patterns), and various eutectic structures, including spiraling two-phase dendrites. Simulations exploring possible control of solidification patterns in thin films via external fields, confined geometry, particle additives, scratching/piercing the films, etc. are also displayed. Advantages, problems, and possible solutions associated with quantitative PF simulations are discussed briefly.

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“…These are ubiquitous structures, observed in a diverse range of materials, including pure Se (Ryschenkow and Faivre 1988;Bisault et al 1991), oxide and metallic glasses (James 1982;Köster and Herold 1981), minerals, volcanic rocks , polymers (Magill 2001;Sperling 1992), liquid crystals (Hutter and Bechhoefer 1999), and simple organic liquids (Magill and Plazek 1967), and diverse biological molecules (Phillips 1993;Lomas et al 1992 Jin et al 2003). These structures are particularly implicated in many human and animal diseases such as Alzheimer's, type II diabetes, and many other protein aggregation diseases (Lomas et al 1992;Koo et al 1999;Jin et al 2003;Krebs et al 2004;Rogers et al 2006;Domike and Donald 2009;Exley et al 2010). (One can argue about the ultimate cause of the toxicity associated with these aggregates, but having insoluble protein spherulites forming in brain and other tissues cannot be good for health.…”

Section: Phase-field Simulating Of Spherulitic Growthmentioning

confidence: 99%

Insights into Polymer Crystallization from Phase-Field Theory

Gránásy

Pusztai

Douglas

2013

Encyclopedia of Polymers and Composites

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Kinetics of spherulite formation and growth: Salt and protein concentration dependence on proteins β-lactoglobulin and insulin

Cited by 26 publications

References 35 publications

Label-free imaging of amyloids using their intrinsic linear and nonlinear optical properties

Label-free imaging of amyloids using their intrinsic linear and nonlinear optical properties

Phase-Field Modeling of Polycrystalline Solidification: From Needle Crystals to Spherulites—A Review

Insights into Polymer Crystallization from Phase-Field Theory

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