State-of-the-Art Fluorescence Fluctuation-Based Spectroscopic Techniques for the Study of Protein Aggregation

International Journal of Molecular Sciences

Masataka Kinjo¹  Akira Kitamura¹ 

[1] Laboratory of Molecular Cell Dynamics, Faculty of Advanced Life Science, Hokkaido University, N21W11, Kita-ku, Sapporo, Hokkaido 001-0021, Japan;

关键词: fluorescence correlation spectroscopy (FCS);    image correlation spectroscopy (ICS);    number and brightness analysis;    super-resolution optical fluctuation imaging (SOFI);    transient state (TRAST) monitoring spectroscopy;    protein aggregate;    neurodegenerative disorder;    TDP-43;    polyQ;    amyloid;   

DOI  :  10.3390/ijms19040964

来源: DOAJ

【 摘 要 】

Neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease, are devastating proteinopathies with misfolded protein aggregates accumulating in neuronal cells. Inclusion bodies of protein aggregates are frequently observed in the neuronal cells of patients. Investigation of the underlying causes of neurodegeneration requires the establishment and selection of appropriate methodologies for detailed investigation of the state and conformation of protein aggregates. In the current review, we present an overview of the principles and application of several methodologies used for the elucidation of protein aggregation, specifically ones based on determination of fluctuations of fluorescence. The discussed methods include fluorescence correlation spectroscopy (FCS), imaging FCS, image correlation spectroscopy (ICS), photobleaching ICS (pbICS), number and brightness (N&B) analysis, super-resolution optical fluctuation imaging (SOFI), and transient state (TRAST) monitoring spectroscopy. Some of these methodologies are classical protein aggregation analyses, while others are not yet widely used. Collectively, the methods presented here should help the future development of research not only into protein aggregation but also neurodegenerative diseases.

【 授权许可】

Unknown