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Application of genetically modified microorganisms for potential human amyloids search. / Ryabinina, Marina ; Zelinsky, Andrew ; Rubel, Aleksandr.

в: Ecological Genetics, Том 20, № S, 08.12.2022, стр. 52.

Результаты исследований: Научные публикации в периодических изданияхтезисыРецензирование

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@article{495298b630694e5bb0a91eb42b65365d,
title = "Application of genetically modified microorganisms for potential human amyloids search",
abstract = "Amyloids are fibrous protein structures often found in patients with severe diseases, such as Alzheimer{\textquoteright}s, Parkinson{\textquoteright}s diseases etc. A number of studies have shown that the production of heterologous amyloidogenic proteins in Saccharomyces cerevisiae strains results in formation of amyloid aggregates with properties similar to those found in mammals.Amyloid aggregates formed in yeasts usually do not have their own phenotypic manifestation. To assess amyloidogenic potential of individual proteins a yeast test-system was developed under supervision of Prof. Y.O. Chernoff. The system is based on usage of genetically modified S. cerevisiae cells auxotrophic for certain growth factors, allowing effective phenotypic selection to search for amyloidogenic proteins within proteomes of various organisms [1]. Using this test-system, our laboratory evaluated amyloid potential of a spectrum of human proteins, the amyloidogenicity of which was previously predicted by bioinformatics algorithms. The proteins that have shown amyloidogenic potential in yeast-based model are being currently tested in vitro and in vivo. Some mutant Escherichia coli strains can be applied for studying propensity of heterologous proteins to form amyloids in vitro. Thus, application of genetically modified microorganisms makes it possible to identify new human amyloidogenic proteins and to improve predictive ability of bioinformatics algorithms.The research is supported by RSF grant №20-14-00148 and by St. Petersburg State University (project No. 93025998). Authors acknowledge SPbSU Resource Centers “Chromas”, “Molecular and Cell Technologies” and “Biobank”.",
author = "Marina Ryabinina and Andrew Zelinsky and Aleksandr Rubel",
year = "2022",
month = dec,
day = "8",
doi = "10.17816/ecogen112346",
language = "English",
volume = "20",
pages = "52",
journal = "ЭКОЛОГИЧЕСКАЯ ГЕНЕТИКА",
issn = "1811-0932",
publisher = "Эко-Вектор",
number = "S",
note = "null ; Conference date: 06-12-2022 Through 08-12-2022",

}

RIS

TY - JOUR

T1 - Application of genetically modified microorganisms for potential human amyloids search

AU - Ryabinina, Marina

AU - Zelinsky, Andrew

AU - Rubel, Aleksandr

PY - 2022/12/8

Y1 - 2022/12/8

N2 - Amyloids are fibrous protein structures often found in patients with severe diseases, such as Alzheimer’s, Parkinson’s diseases etc. A number of studies have shown that the production of heterologous amyloidogenic proteins in Saccharomyces cerevisiae strains results in formation of amyloid aggregates with properties similar to those found in mammals.Amyloid aggregates formed in yeasts usually do not have their own phenotypic manifestation. To assess amyloidogenic potential of individual proteins a yeast test-system was developed under supervision of Prof. Y.O. Chernoff. The system is based on usage of genetically modified S. cerevisiae cells auxotrophic for certain growth factors, allowing effective phenotypic selection to search for amyloidogenic proteins within proteomes of various organisms [1]. Using this test-system, our laboratory evaluated amyloid potential of a spectrum of human proteins, the amyloidogenicity of which was previously predicted by bioinformatics algorithms. The proteins that have shown amyloidogenic potential in yeast-based model are being currently tested in vitro and in vivo. Some mutant Escherichia coli strains can be applied for studying propensity of heterologous proteins to form amyloids in vitro. Thus, application of genetically modified microorganisms makes it possible to identify new human amyloidogenic proteins and to improve predictive ability of bioinformatics algorithms.The research is supported by RSF grant №20-14-00148 and by St. Petersburg State University (project No. 93025998). Authors acknowledge SPbSU Resource Centers “Chromas”, “Molecular and Cell Technologies” and “Biobank”.

AB - Amyloids are fibrous protein structures often found in patients with severe diseases, such as Alzheimer’s, Parkinson’s diseases etc. A number of studies have shown that the production of heterologous amyloidogenic proteins in Saccharomyces cerevisiae strains results in formation of amyloid aggregates with properties similar to those found in mammals.Amyloid aggregates formed in yeasts usually do not have their own phenotypic manifestation. To assess amyloidogenic potential of individual proteins a yeast test-system was developed under supervision of Prof. Y.O. Chernoff. The system is based on usage of genetically modified S. cerevisiae cells auxotrophic for certain growth factors, allowing effective phenotypic selection to search for amyloidogenic proteins within proteomes of various organisms [1]. Using this test-system, our laboratory evaluated amyloid potential of a spectrum of human proteins, the amyloidogenicity of which was previously predicted by bioinformatics algorithms. The proteins that have shown amyloidogenic potential in yeast-based model are being currently tested in vitro and in vivo. Some mutant Escherichia coli strains can be applied for studying propensity of heterologous proteins to form amyloids in vitro. Thus, application of genetically modified microorganisms makes it possible to identify new human amyloidogenic proteins and to improve predictive ability of bioinformatics algorithms.The research is supported by RSF grant №20-14-00148 and by St. Petersburg State University (project No. 93025998). Authors acknowledge SPbSU Resource Centers “Chromas”, “Molecular and Cell Technologies” and “Biobank”.

UR - https://elibrary.ru/item.asp?id=49914917

UR - https://www.webofscience.com/wos/author/record/GYU-6558-2022

U2 - 10.17816/ecogen112346

DO - 10.17816/ecogen112346

M3 - Meeting Abstract

VL - 20

SP - 52

JO - ЭКОЛОГИЧЕСКАЯ ГЕНЕТИКА

JF - ЭКОЛОГИЧЕСКАЯ ГЕНЕТИКА

SN - 1811-0932

IS - S

Y2 - 6 December 2022 through 8 December 2022

ER -

ID: 102462264