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Screening for amyloid proteins in the yeast proteome

Overview of attention for article published in Current Genetics, October 2017
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Title
Screening for amyloid proteins in the yeast proteome
Published in
Current Genetics, October 2017
DOI 10.1007/s00294-017-0759-7
Pubmed ID
Authors

Tatyana A. Ryzhova, Julia V. Sopova, Sergey P. Zadorsky, Vera A. Siniukova, Aleksandra V. Sergeeva, Svetlana A. Galkina, Anton A. Nizhnikov, Aleksandr A. Shenfeld, Kirill V. Volkov, Alexey P. Galkin

Abstract

The search for novel pathological and functional amyloids represents one of the most important tasks of contemporary biomedicine. Formation of pathological amyloid fibrils in the aging brain causes incurable neurodegenerative disorders such as Alzheimer's, Parkinson's Huntington's diseases. At the same time, a set of amyloids regulates vital processes in archaea, prokaryotes and eukaryotes. Our knowledge of the prevalence and biological significance of amyloids is limited due to the lack of universal methods for their identification. Here, using our original method of proteomic screening PSIA-LC-MALDI, we identified a number of proteins that form amyloid-like detergent-resistant aggregates in Saccharomyces cerevisiae. We revealed in yeast strains of different origin known yeast prions, prion-associated proteins, and a set of proteins whose amyloid properties were not shown before. A substantial number of the identified proteins are cell wall components, suggesting that amyloids may play important roles in the formation of this extracellular protective sheath. Two proteins identified in our screen, Gas1 and Ygp1, involved in biogenesis of the yeast cell wall, were selected for detailed analysis of amyloid properties. We show that Gas1 and Ygp1 demonstrate amyloid properties both in vivo in yeast cells and using the bacteria-based system C-DAG. Taken together, our data show that this proteomic approach is very useful for identification of novel amyloids.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 24%
Student > Bachelor 10 20%
Student > Ph. D. Student 8 16%
Student > Master 3 6%
Student > Doctoral Student 2 4%
Other 7 14%
Unknown 9 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 31%
Agricultural and Biological Sciences 16 31%
Psychology 2 4%
Neuroscience 2 4%
Nursing and Health Professions 1 2%
Other 5 10%
Unknown 9 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 August 2018.
All research outputs
#18,573,839
of 23,005,189 outputs
Outputs from Current Genetics
#973
of 1,203 outputs
Outputs of similar age
#248,713
of 324,711 outputs
Outputs of similar age from Current Genetics
#19
of 31 outputs
Altmetric has tracked 23,005,189 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,203 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.