PrionHome: A Database of Prions and Other Sequences Relevant to Prion Phenomena

Prions are units of propagation of an altered state of a protein or proteins; prions can propagate from organism to organism, through cooption of other protein copies. Prions contain no necessary nucleic acids, and are important both as both pathogenic agents, and as a potential force in epigenetic phenomena. The original prions were derived from a misfolded form of the mammalian Prion Protein PrP. Infection by these prions causes neurodegenerative diseases. Other prions cause non-Mendelian inheritance in budding yeast, and sometimes act as diseases of yeast. We report the bioinformatic construction of the PrionHome, a database of >2000 prion-related sequences. The data was collated from various public and private resources and filtered for redundancy. The data was then processed according to a transparent classification system of prionogenic sequences (i.e., sequences that can make prions), prionoids (i.e., proteins that propagate like prions between individual cells), and other prion-related phenomena. There are eight PrionHome classifications for sequences. The first four classifications are derived from experimental observations: prionogenic sequences, prionoids, other prion-related phenomena, and prion interactors. The second four classifications are derived from sequence analysis: orthologs, paralogs, pseudogenes, and candidate-prionogenic sequences. Database entries list: supporting information for PrionHome classifications, prion-determinant areas (where relevant), and disordered and compositionally-biased regions. Also included are literature references for the PrionHome classifications, transcripts and genomic coordinates, and structural data (including comparative models made for the PrionHome from manually curated alignments). We provide database usage examples for both vertebrate and fungal prion contexts. Using the database data, we have performed a detailed analysis of the compositional biases in known budding-yeast prionogenic sequences, showing that the only abundant bias pattern is for asparagine bias with subsidiary serine bias. We anticipate that this database will be a useful experimental aid and reference resource. It is freely available at: http://libaio.biol.mcgill.ca/prion

Interaction Networks of Prion, Prionogenic and Prion-Like Proteins in Budding Yeast, and Their Role in Gene Regulation

<div><p>Prions are transmissible, propagating alternative states of proteins. Prions in budding yeast propagate heritable phenotypes and can function in large-scale gene regulation, or in some cases occur as diseases of yeast. Other ‘prionogenic’ proteins are likely prions that have been determined experimentally to form amyloid <i>in vivo</i>, and to have prion-like domains that are able to propagate heritable states. Furthermore, there are over 300 additional ‘prion-like’ yeast proteins that have similar amino-acid composition to prions (primarily a bias for asparagines and glutamines). Here, we examine the protein functional and interaction networks that involve prion, prionogenic and prion-like proteins. Set against a marked overall preference for N/Q-rich prion-like proteins not to interact with each other, we observe a significant tendency of prion/prionogenic proteins to interact with other, N/Q-rich prion-like proteins. This tendency is mostly due to a small number of networks involving the proteins NUP100p, LSM4p and PUB1p. In general, different data analyses of functional and interaction networks converge to indicate a strong linkage of prionogenic and prion-like proteins, to stress-granule assembly and related biological processes. These results further elucidate how prions may impact gene regulation, and reveal a broader horizon for the functional relevance of N/Q-rich prion-like domains.</p></div

Disorder content of known prions (KPs), experimental prionogenic domains (EPDs) and prion negatives (EPNs).

<p>Monte Carlo samples (n = 10000) of the same total protein length as each of the three data sets were made and the total amount of disorder (from the DISOPRED2 program <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100615#pone.0100615-Ward1" target="_blank">[25]</a>) was annotated. A fractional piece of one protein was used to make up the exact residue count for the sample size. The plot shows the distribution of disorder content for these samples for the KP set. The actual observed value is indicated by an arrow. The % of samples that have greater disorder than the observed value for each data set is indicated in the table below the histogram.</p

Schematic representation of the relationship between the four data sets KPs, EPDs, EPNs and NQPs.

<p>Schematic representation of the relationship between the four data sets KPs, EPDs, EPNs and NQPs.</p

The protein interaction network for the EPD data set.

<p>We drew this original picture using the publicly distributed Cytoscape tool that can be used for depicting networks <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100615#pone.0100615-Shannon1" target="_blank">[49]</a>, with the data sets of protein interactions that we derived (as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100615#s2" target="_blank"><i>Methods</i></a>) as input. We have coloured the nodes as follows: --- known prions (KP)  =  <b>BLACK</b>; --- other proteins in the EPD data set  =  <b>GREY</b>; --- EPN data set  =  <b>YELLOW</b>; --- NQPs that are also prion predictions made using the PrionScan algorithm  =  <b>CYAN</b>; --- any other NQP  =  <b>DARK BLUE</b>; --- other interactors  =  <b>BROWN</b>. The non-amyloid prion accessory protein STD1 that underlies the [GAR+] prion <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100615#pone.0100615-Brown1" target="_blank">[50]</a> (Q02794) is part of the NQP data set that we derived, since it has an N/Q-rich domain. We have coloured its node at the lower right of the network, <b>ORANGE</b>. The prion/prionogenic proteins are labelled with their UniProt accessions and standard gene names. The three EPD hubs are pointed out with red arrows. A red box surrounds common interactors between the LSM4 and PUB1 proteins.</p

Enrichments of proteins with and without protein-binding domains (PBDs), in the interactor lists of the EPDs^*.

<p>*As for <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100615#pone-0100615-t001" target="_blank">Table 1</a>.</p><p>**Proteins containing PBDs are those containing predicted coiled-coil regions or protein-binding domains defined specifically as such, in InterPro (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100615#s2" target="_blank"><i>Methods</i></a> for details). The enrichment of proteins containing PBDs in the list of their own interactors is very highly significant (P = 4e−52).</p>†<p>As for <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100615#pone-0100615-t001" target="_blank">Table 1</a>.</p

Enrichments for different sets of sequences in the interactor lists for prion, prionogenic and prion-like proteins in budding yeast^*.

<p>*The interactor lists are in the rows of the table, and the sets that are tested as enriched/depleted or not, are in the columns. These sets are explained in the main text. At the head of each column is given the total number of proteins of each set type, and the total number of interactions involving them. In each cell, is given the number of interactors that are members of the sets tested as enriching/depleted, expressed as a fraction of the total number of interactors. In brackets is given the hypergeometric probability for this enrichment/depletion, with NS for non-significant (P-value threshold  = 0.05). Values that are significant enrichments after Holm-Bonferroni correction are in bold, significant depletions in italics.</p>†<p>These P-values become non-significant after a Holm-Bonferroni correction over all tests performed (totalling 72).</p

Detailed analysis of compositional biases in budding yeast amyloid-type Prionogenic sequences.

<p>*The biases are in the following format: start point/end point/binomial P-value/bias signature. Residues contributing significantly to the bias are sorted in decreasing order of precedence, <i>i.e.</i>, for the bias signature <b>NS</b>HIT, N is the main bias, S is the most important subsidiary bias, and so on. NS biases are in bold text. All biases with P-value< = 10⁻⁶ are listed.</p