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MIRRAGGE – Minimum Information Required for Reproducible AGGregation Experiments

Authors :
Pedro M. Martins
Susanna Navarro
Alexandra Silva
Maria F. Pinto
Zsuzsa Sárkány
Francisco Figueiredo
Pedro José Barbosa Pereira
Francisca Pinheiro
Zuzana Bednarikova
Michał Burdukiewicz
Oxana V. Galzitskaya
Zuzana Gazova
Cláudio M. Gomes
Annalisa Pastore
Louise C. Serpell
Rostislav Skrabana
Vytautas Smirnovas
Mantas Ziaunys
Daniel E. Otzen
Salvador Ventura
Sandra Macedo-Ribeiro
Source :
Frontiers in Molecular Neuroscience, Vol 13 (2020)
Publication Year :
2020
Publisher :
Frontiers Media S.A., 2020.

Abstract

Reports on phase separation and amyloid formation for multiple proteins and aggregation-prone peptides are recurrently used to explore the molecular mechanisms associated with several human diseases. The information conveyed by these reports can be used directly in translational investigation, e.g., for the design of better drug screening strategies, or be compiled in databases for benchmarking novel aggregation-predicting algorithms. Given that minute protocol variations determine different outcomes of protein aggregation assays, there is a strong urge for standardized descriptions of the different types of aggregates and the detailed methods used in their production. In an attempt to address this need, we assembled the Minimum Information Required for Reproducible Aggregation Experiments (MIRRAGGE) guidelines, considering first-principles and the established literature on protein self-assembly and aggregation. This consensus information aims to cover the major and subtle determinants of experimental reproducibility while avoiding excessive technical details that are of limited practical interest for non-specialized users. The MIRRAGGE table (template available in Supplementary Information) is useful as a guide for the design of new studies and as a checklist during submission of experimental reports for publication. Full disclosure of relevant information also enables other researchers to reproduce results correctly and facilitates systematic data deposition into curated databases.

Details

Language :
English
ISSN :
16625099
Volume :
13
Database :
Directory of Open Access Journals
Journal :
Frontiers in Molecular Neuroscience
Publication Type :
Academic Journal
Accession number :
edsdoj.fc44793c97ba412084f310dcf7f683f9
Document Type :
article
Full Text :
https://doi.org/10.3389/fnmol.2020.582488