000061814 001__ 61814
000061814 005__ 20170713115235.0
000061814 0247_ $$2doi$$a10.1186/1471-2164-14-316
000061814 0248_ $$2sideral$$a81745
000061814 037__ $$aART-2013-81745
000061814 041__ $$aeng
000061814 100__ $$0(orcid)0000-0002-3268-8730$$aEspinosa Angarica, V.
000061814 245__ $$aDiscovering putative prion sequences in complete proteomes using probabilistic representations of Q/N-rich domains
000061814 260__ $$c2013
000061814 5060_ $$aAccess copy available to the general public$$fUnrestricted
000061814 5203_ $$aBackground:
Prion proteins conform a special class among amyloids due to their ability to transmit aggregative folds. Prions are known to act as infectious agents in neurodegenerative diseases in animals, or as key elements in transcription and translation processes in yeast. It has been suggested that prions contain specific sequential domains with distinctive amino acid composition and physicochemical properties that allow them to control the switch between soluble and ß-sheet aggregated states. Those prion-forming domains are low complexity segments enriched in glutamine/asparagine and depleted in charged residues and prolines. Different predictive methods have been developed to discover novel prions by either assessing the compositional bias of these stretches or estimating the propensity of protein sequences to form amyloid aggregates. However, the available algorithms hitherto lack a thorough statistical calibration against large sequence databases, which makes them unable to accurately predict prions without retrieving a large number of false positives.
Results:
Here we present a computational strategy to predict putative prion-forming proteins in complete proteomes using probabilistic representations of prionogenic glutamine/asparagine rich regions. After benchmarking our predictive model against large sets of non-prionic sequences, we were able to filter out known prions with high precision and accuracy, generating prediction sets with few false positives. The algorithm was used to scan all the proteomes annotated in public databases for the presence of putative prion proteins. We analyzed the presence of putative prion proteins in all taxa, from viruses and archaea to plants and higher eukaryotes, and found that most organisms encode evolutionarily unrelated proteins with susceptibility to behave as prions.
Conclusions:
To our knowledge, this is the first wide-ranging study aiming to predict prion domains in complete proteomes. Approaches of this kind could be of great importance to identify potential targets for further experimental testing and to try to reach a deeper understanding of prions’ functional and regulatory mechanisms.
000061814 536__ $$9info:eu-repo/grantAgreement/ES/DGA/CTPR02-09$$9info:eu-repo/grantAgreement/ES/DGA/PI078-08$$9info:eu-repo/grantAgreement/ES/MICINN/BFU2010-16297
000061814 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000061814 590__ $$a4.041$$b2013
000061814 591__ $$aGENETICS & HEREDITY$$b40 / 164 = 0.244$$c2013$$dQ1$$eT1
000061814 591__ $$aBIOTECHNOLOGY & APPLIED MICROBIOLOGY$$b29 / 161 = 0.18$$c2013$$dQ1$$eT1
000061814 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000061814 700__ $$aVentura, S.
000061814 700__ $$0(orcid)0000-0002-2879-9200$$aSancho, J.$$uUniversidad de Zaragoza
000061814 7102_ $$11002$$2060$$aUniversidad de Zaragoza$$bDepartamento de Bioquímica y Biología Molecular y Celular$$cBioquímica y Biología Molecular
000061814 773__ $$g14, 1 (2013), 316 [17 pp]$$pBMC genomics$$tBMC Genomics$$x1471-2164
000061814 8564_ $$s666758$$uhttps://zaguan.unizar.es/record/61814/files/texto_completo.pdf$$yVersión publicada
000061814 8564_ $$s109456$$uhttps://zaguan.unizar.es/record/61814/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000061814 909CO $$ooai:zaguan.unizar.es:61814$$particulos$$pdriver
000061814 951__ $$a2017-07-13-11:11:23
000061814 980__ $$aARTICLE