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      Discovering Putative Prion-Like Proteins in Plasmodium falciparum: A Computational and Experimental Analysis

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          Abstract

          Prions are a singular subset of proteins able to switch between a soluble conformation and a self-perpetuating amyloid state. Traditionally associated with neurodegenerative diseases, increasing evidence indicates that organisms exploit prion-like mechanisms for beneficial purposes. The ability to transit between conformations is encoded in the so-called prion domains, long disordered regions usually enriched in glutamine/asparagine residues. Interestingly, Plasmodium falciparum, the parasite that causes the most virulent form of malaria, is exceptionally rich in proteins bearing long Q/N-rich sequence stretches, accounting for roughly 30% of the proteome. This biased composition suggests that these protein regions might correspond to prion-like domains (PrLDs) and potentially form amyloid assemblies. To investigate this possibility, we performed a stringent computational survey for Q/N-rich PrLDs on P. falciparum. Our data indicate that ∼10% of P. falciparum protein sequences have prionic signatures, and that this subproteome is enriched in regulatory proteins, such as transcription factors and RNA-binding proteins. Furthermore, we experimentally demonstrate for several of the identified PrLDs that, despite their disordered nature, they contain inner short sequences able to spontaneously self-assemble into amyloid-like structures. Although the ability of these sequences to nucleate the conformational conversion of the respective full-length proteins should still be demonstrated, our analysis suggests that, as previously described for other organisms, prion-like proteins might also play a functional role in P. falciparum.

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          Most cited references 90

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          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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            The Pfam protein families database: towards a more sustainable future

            In the last two years the Pfam database (http://pfam.xfam.org) has undergone a substantial reorganisation to reduce the effort involved in making a release, thereby permitting more frequent releases. Arguably the most significant of these changes is that Pfam is now primarily based on the UniProtKB reference proteomes, with the counts of matched sequences and species reported on the website restricted to this smaller set. Building families on reference proteomes sequences brings greater stability, which decreases the amount of manual curation required to maintain them. It also reduces the number of sequences displayed on the website, whilst still providing access to many important model organisms. Matches to the full UniProtKB database are, however, still available and Pfam annotations for individual UniProtKB sequences can still be retrieved. Some Pfam entries (1.6%) which have no matches to reference proteomes remain; we are working with UniProt to see if sequences from them can be incorporated into reference proteomes. Pfam-B, the automatically-generated supplement to Pfam, has been removed. The current release (Pfam 29.0) includes 16 295 entries and 559 clans. The facility to view the relationship between families within a clan has been improved by the introduction of a new tool.
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              UniProt: a hub for protein information

              UniProt is an important collection of protein sequences and their annotations, which has doubled in size to 80 million sequences during the past year. This growth in sequences has prompted an extension of UniProt accession number space from 6 to 10 characters. An increasing fraction of new sequences are identical to a sequence that already exists in the database with the majority of sequences coming from genome sequencing projects. We have created a new proteome identifier that uniquely identifies a particular assembly of a species and strain or subspecies to help users track the provenance of sequences. We present a new website that has been designed using a user-experience design process. We have introduced an annotation score for all entries in UniProt to represent the relative amount of knowledge known about each protein. These scores will be helpful in identifying which proteins are the best characterized and most informative for comparative analysis. All UniProt data is provided freely and is available on the web at http://www.uniprot.org/.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                07 August 2018
                2018
                : 9
                Affiliations
                1Institut de Biotecnologia i de Biomedicina, Universitat Autònoma de Barcelona , Barcelona, Spain
                2Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona , Barcelona, Spain
                3Centre for Genomic Regulation, The Barcelona Institute of Science and Technology , Barcelona, Spain
                4Universitat Pompeu Fabra , Barcelona, Spain
                5Nanomalaria Group, Institute for Bioengineering of Catalonia, The Barcelona Institute of Science and Technology , Barcelona, Spain
                6Barcelona Institute for Global Health, Barcelona Centre for International Health Research (Hospital Clínic – Universitat de Barcelona) , Barcelona, Spain
                7Institute of Nanoscience and Nanotechnology, University of Barcelona , Barcelona, Spain
                Author notes

                Edited by: Rustam Aminov, University of Aberdeen, United Kingdom

                Reviewed by: Nyssa Drinkwater, Monash University, Australia; Thomas Dandekar, Universität Würzburg, Germany

                *Correspondence: Salvador Ventura, salvador.ventura@ 123456uab.es

                These authors have contributed equally to this work.

                This article was submitted to Infectious Diseases, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2018.01737
                6090025
                Copyright © 2018 Pallarès, de Groot, Iglesias, Sant’Anna, Biosca, Fernàndez-Busquets and Ventura.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Counts
                Figures: 6, Tables: 1, Equations: 0, References: 90, Pages: 13, Words: 0
                Funding
                Funded by: Ministerio de Economía y Competitividad 10.13039/501100003329
                Award ID: BIO2016-783-78310-R
                Funded by: Institució Catalana de Recerca i Estudis Avançats 10.13039/501100003741
                Award ID: ICREA ACADEMIA 2015
                Categories
                Microbiology
                Original Research

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