tymczasowa.bib

@article{evans_curli_2014-2,
  series = {Protein trafficking and secretion in bacteria},
  title = {Curli Biogenesis: {{Order}} out of Disorder},
  volume = {1843},
  issn = {0167-4889},
  shorttitle = {Curli Biogenesis},
  doi = {10.1016/j.bbamcr.2013.09.010},
  abstract = {Many bacteria assemble extracellular amyloid fibers on their cell surface. Secretion of proteins across membranes and the assembly of complex macromolecular structures must be highly coordinated to avoid the accumulation of potentially toxic intracellular protein aggregates. Extracellular amyloid fiber assembly poses an even greater threat to cellular health due to the highly aggregative nature of amyloids and the inherent toxicity of amyloid assembly intermediates. Therefore, temporal and spatial control of amyloid protein secretion is paramount. The biogenesis and assembly of the extracellular bacterial amyloid curli is an ideal system for studying how bacteria cope with the many challenges of controlled and ordered amyloid assembly. Here, we review the recent progress in the curli field that has made curli biogenesis one of the best-understood functional amyloid assembly pathways. This article is part of a Special Issue entitled: Protein trafficking and secretion in bacteria. Guest Editors: Anastassios Economou and Ross Dalbey.},
  number = {8},
  journal = {Biochimica et Biophysica Acta (BBA) - Molecular Cell Research},
  author = {Evans, Margery L. and Chapman, Matthew R.},
  month = aug,
  year = {2014},
  keywords = {Aggregate,Biofilm,Curli,Functional amyloid,Nucleation–precipitation,Type VIII secretion},
  pages = {1551-1558},
  file = {/home/jarek/Zotero/storage/M4YQZN42/Evans i Chapman - 2014 - Curli biogenesis Order out of disorder.pdf;/home/jarek/Zotero/storage/UUPIVAH5/S0167488913003327.html}
}

@article{burdukiewicz_amyloidogenic_2017-1,
  title = {Amyloidogenic Motifs Revealed by N-Gram Analysis},
  volume = {7},
  issn = {2045-2322},
  doi = {10.1038/s41598-017-13210-9},
  abstract = {Amyloids are proteins associated with several clinical disorders, including Alzheimer's, and Creutzfeldt-Jakob's. Despite their diversity, all amyloid proteins can undergo aggregation initiated by short segments called hot spots. To find the patterns defining the hot spots, we trained predictors of amyloidogenicity, using n-grams and random forest classifiers. Since the amyloidogenicity may not depend on the exact sequence of amino acids but on their more general properties, we tested 524,284 reduced amino acid alphabets of different lengths (three to six letters) to find the alphabet providing the best performance in cross-validation. The predictor based on this alphabet, called AmyloGram, was benchmarked against the most popular tools for the detection of amyloid peptides using an external data set and obtained the highest values of performance measures (AUC: 0.90, MCC: 0.63). Our results showed sequential patterns in the amyloids which are strongly correlated with hydrophobicity, a tendency to form $\beta$-sheets, and lower flexibility of amino acid residues. Among the most informative n-grams of AmyloGram we identified 15 that were previously confirmed experimentally. AmyloGram is available as the web-server: http://smorfland.uni.wroc.pl/shiny/AmyloGram/ and as the R package AmyloGram. R scripts and data used to produce the results of this manuscript are available at http://github.com/michbur/AmyloGramAnalysis.},
  journal = {Scientific Reports},
  author = {Burdukiewicz, Micha\l{} and Sobczyk, Piotr and R\"odiger, Stefan and {Duda-Madej}, Anna and Mackiewicz, Pawe\l{} and Kotulska, Ma\l{}gorzata},
  month = oct,
  year = {2017},
  file = {/home/jarek/Zotero/storage/6C3VB3GJ/Burdukiewicz i in. - 2017 - Amyloidogenic motifs revealed by n-gram analysis.pdf},
  pmid = {29021608},
  pmcid = {PMC5636826}
}