Amyloid Formation in Nanoliter Droplets.

amyloid formation atomic force microscopy fluorescence assay lysozyme nanoliter droplet polymorphism

Journal

International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791

Informations de publication

Date de publication:
13 May 2022
Historique:
received: 30 03 2022
revised: 11 05 2022
accepted: 12 05 2022
entrez: 28 5 2022
pubmed: 29 5 2022
medline: 1 6 2022
Statut: epublish

Résumé

Processes that monitor the nucleation of amyloids and characterize the formation of amyloid fibrils are vital to medicine and pharmacology. In this study, we observe the nucleation and formation of lysozyme amyloid fibrils using a facile microfluidic system to generate nanoliter droplets that can control the flow rate and movement of monomer-in-oil emulsion droplets in a T-junction microchannel. Using a fluorescence assay, we monitor the nucleation and growth process of amyloids based on the volume of droplets. Using the microfluidic system, we demonstrate that the lag phase, which is vital to amyloid nucleation and growth, is reduced at a lower droplet volume. Furthermore, we report a peculiar phenomenon of high amyloid formation at the edge of a bullet-shaped droplet, which is likely due to the high local monomer concentration. Moreover, we discovered that amyloid fibrils synthesized in the nanoliter droplets are shorter and thicker than fibrils synthesized from a bulk solution via the conventional heating method. Herein, a facile procedure to observe and characterize the nucleation and growth of amyloid fibrils using nanoliter droplets is presented, which is beneficial for investigating new features of amyloid fibril formation as an unconventional synthetic method for amyloid fibrils.

Identifiants

pubmed: 35628295
pii: ijms23105480
doi: 10.3390/ijms23105480
pmc: PMC9143811
pii:
doi:

Substances chimiques

Amyloid 0
Amyloidogenic Proteins 0
Emulsions 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Research Foundation of Korea
ID : NRF-2020R1A2C2102262
Organisme : National Research Foundation of Korea
ID : KMDF_PR_20200901_0127-01
Organisme : National Research Foundation of Korea
ID : 2021R1A4A1028969
Organisme : Korea University
ID : BK21 FOUR

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Auteurs

Da Yeon Cheong (DY)

Department of Biotechnology and Bioinformatics, Korea University, Sejong 30019, Korea.
Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University, Sejong 30019, Korea.

Wonseok Lee (W)

Department of Electrical Engineering, Korea National University of Transportation, Chungju 27469, Korea.

Insu Park (I)

Nick Holonyak Jr. Micro and Nanotechnology Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.

Jinsung Park (J)

Department of Biomechatronic Engineering, College of Biotechnology and Bioengineering, Sungkyunkwan University, Suwon 16419, Korea.

Gyudo Lee (G)

Department of Biotechnology and Bioinformatics, Korea University, Sejong 30019, Korea.
Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University, Sejong 30019, Korea.

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Classifications MeSH