ORIGINAL RESEARCH published: 27 March 2019 doi: 10.3389/fphys.2019.00314 In silico Characterization of Human Prion-Like Proteins: Beyond Neurological Diseases Valentin Iglesias 1† , Lisanna Paladin 2† , Teresa Juan-Blanco 3 , Irantzu Pallarès 1 , Patrick Aloy 3,4 , Silvio C. E. Tosatto 2,5 and Salvador Ventura 1* 1 Institut de Biotecnologia i de Biomedicina, Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Barcelona, Spain, 2 Department of Biomedical Sciences, University of Padua, Padua, Italy, 3 Joint IRB-BSC-CRG Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain, 4 Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain, 5 CNR Institute of Neuroscience, Padua, Italy Prion-like behavior has been in the spotlight since it was first associated with the onset of mammalian neurodegenerative diseases. However, a growing body of evidence suggests that this mechanism could be behind the regulation of processes such as transcription and translation in multiple species. Here, we perform a stringent computational survey to identify prion-like proteins in the human proteome. We detected Edited by: 242 candidate polypeptides and computationally assessed their function, protein– Michele Vendruscolo, University of Cambridge, protein interaction networks, tissular expression, and their link to disease. Human United Kingdom prion-like proteins constitute a subset of modular polypeptides broadly expressed Reviewed by: across different cell types and tissues, significantly associated with disease, embedded Antonio Scialdone, in highly connected interaction networks, and involved in the flow of genetic information Helmholtz Center Munich – German Research Center for Environmental in the cell. Our analysis suggests that these proteins might play a relevant role not only Health, Germany in neurological disorders, but also in different types of cancer and viral infections. Isabelle Callebaut, Centre National de la Recherche Keywords: prion-like proteins, disease, protein–protein interaction, protein aggregation, amyloid, bioinformatics Scientifique (CNRS), France *Correspondence: Salvador Ventura INTRODUCTION Salvador.ventura@uab.es † These authors have contributed Prions were first reported in the context of mammalian neurodegenerative disorders (Prusiner, equally to this work 1982; van Rheede et al., 2003; Harrison et al., 2010; Sikorska and Liberski, 2012), but it is now clear that different organisms exploit prion conformational conversion for functional purposes Specialty section: (Halfmann and Lindquist, 2010). The most studied organism is Saccharomyces cerevisiae, with up This article was submitted to to 11 functional prions identified so far (Cascarina and Ross, 2014; Batlle et al., 2017c) Initially, Biophysics, these yeast prions were proposed to be pathological agents (Nakayashiki et al., 2005; McGlinchey a section of the journal et al., 2011), but nowadays they are widely recognized to provide beneficial advantages in Frontiers in Physiology changing environments, predominantly by regulating transcription, translation, or RNA processing Received: 05 October 2018 (Halfmann et al., 2012; Newby and Lindquist, 2013). Yeast prions switch from an initially soluble Accepted: 07 March 2019 state through a structural conversion toward an aggregated amyloid conformation. This conversion Published: 27 March 2019 is encoded in PrDs; long intrinsically disordered regions of low complexity. Citation: A significant number of proteins sharing most, but not all, prion characteristics have been Iglesias V, Paladin L, identified in different organisms, and generically named prion-like proteins (Pallares et al., 2015; Juan-Blanco T, Pallarès I, Aloy P, Tosatto SCE and Ventura S (2019) Si, 2015; Chakrabortee et al., 2016). In higher eukaryotes, prion-like structural conversion plays In silico Characterization of a central role in diverse functions such as viral response (Hou et al., 2011; Franklin et al., Human Prion-Like Proteins: Beyond 2014; Xu et al., 2014) or long-term memory acquisition and maintenance (Si et al., 2010; Neurological Diseases. Front. Physiol. 10:314. Abbreviations: GO, gene ontology; LCC, largest connected component; MSC, mean shortest distance; PPIs, protein–protein doi: 10.3389/fphys.2019.00314 interactions; PrD, prion domain; PrLD, prion-like domain. Frontiers in Physiology | www.frontiersin.org 1 March 2019 | Volume 10 | Article 314 Iglesias et al. Human Prion-Like Proteins Majumdar et al., 2012; Si and Kandel, 2016). Even though PLAAC using as background probability the frequency of human multiple beneficial functions have been assigned to prion-like proteome. From the initial 70,940 proteins in the proteome, mechanisms across all kingdoms of life, aggregated proteins 431 PrLD containing candidates were identified. Their predicted in human neurodegenerative diseases such as Alzheimer’s and PrLDs were further evaluated with pWALTZ applying a cutoff Parkinson’s diseases and amyotophic lateral sclerosis also share of 60.00, as in Batlle et al. (2017a), which resulted in 242 final certain prion-like properties (Aguzzi and Rajendran, 2009; Gitler positive predictions (Supplementary Table S1). and Shorter, 2011; Luk et al., 2012; Stohr et al., 2012; Kim et al., 2013; Nomura et al., 2014). Prion-Like Domain Localization Within The accumulated knowledge on the determinants of yeast the Protein Sequence prions conformational conversion has provided strong stimuli Each prion-like protein sequence was divided into three for the development of bioinformatics tools to uncover new segments, the N- and C- terminal, accounted for 25% of the PrLDs in other organisms (Michelitsch and Weissman, 2000; residues each, whereas the resting 50% of the sequence was Harrison and Gerstein, 2003; Toombs et al., 2012; Espinosa considered as internal. Each predicted PrLD was located in the Angarica et al., 2014; Lancaster et al., 2014; Afsar Minhas et al., sequence and the number of residues mapping in each of the 2017; Batlle et al., 2017c). Previous screenings for PrLDs in the segments counted. human proteome have targeted the characteristic compositional bias of these protein regions (An and Harrison, 2016). We have Functional Annotation recently proposed that, in addition to a distinctive amino The GO annotation of all proteins in the prion-like dataset acidic composition, PrLDs contain soft amyloidogenic sequence were collected, excluding the terms Inferred from Electronic stretches that would contribute to trigger the initial protein self- Annotation (IEA) and filtering through the Generic GO slim assembly reaction (Sabate et al., 2015a,b). These cryptic amyloids developed by GO Consortium (Gene Ontology Consortium, were not only shown to be present and promote conformational 2015). All UniProt human proteins were used as background set conversion in bona fide yeast prions (Sant’Anna et al., 2016), to infer enrichment. A Fisher’s exact test of GO term distributions but they also exist in human prion-like proteins (Batlle et al., was performed in the three ontologies separately, to calculate 2017a) and appear to play key role in the induction, propagation, the enrichment/depletion of dataset proteins with respect to and inheritance of the prion state in the mammalian cytosol the whole UniProt. The Bonferroni correction was applied in (Duernberger et al., 2018). The amyloid stretches embedded performing all the tests. The results are shown in Figure 3 within PrLDs can be identified computationally (Sabate et al., applying the formula: 2015b; Zambrano et al., 2015). Here we applied to the human proteome the same prediction GO freq. in PPR GO freq. in PBack E = log − log scheme that allowed us to uncover the first bona fide prion- Tot GO in PPR Tot GO in PBack like protein in a bacterial proteome (Pallares et al., 2015; Yuan and Hochschild, 2017). Human proteins were first analyzed for where GO is the GO term, PPR and PBack are the datasets of the presence of regions with compositional similitude to yeast prion-like proteins and the whole proteome, respectively. The PrDs using the prion-like compositional bias (PLAAC) algorithm abbreviations freq. and Tot stay for frequency and total. (Alberti et al., 2009; Lancaster et al., 2014) and afterward these protein domains were individually screened for the presence Pfam Domains of soft amyloidogenic sequences using the pWALTZ program Pfam (Finn et al., 2016) domains annotation in the dataset (Sabate et al., 2015b). Indeed, we have recently shown that proteins were collected and compared to the human proteome such a combination of compositional and sequential PrLDs (from UniProt). Fisher’s exact test was used to assess significance. prediction provides the best accuracy when forecasting the aggregation propensities of individual human prion-like proteins Tissue and Cellular Localization (Batlle et al., 2017b). Tissue and cellular localization data of human proteins were In the present work, we computationally characterized the retrieved from Human Protein Atlas (Uhlen et al., 2015). The function, location, expression, PPI networks, and the connection prion-like proteins identifiers were converted to Ensembl Gene to disease of the human prion-like subproteome. The picture Ids. Human Protein Atlas reports a textual ranking of protein that emerges from this analysis is that prion-like proteins expression of each coding gene. This ranking (“none,” “low,” are widespread expressed proteins that function in biological “medium,” “high”) was converted to numerical expressions, from processes tightly associated to disease. 0 to 3, and each gene value for each particular tissue was collected. The expression of the complete gene set for the tissue was then averaged. MATERIALS AND METHODS Association to Diseases Data Acquisition OMIM disease annotation was extracted from the field “diseases” The human reference proteome dataset was obtained of the UniProt description (Amberger et al., 2015). All from Uniprot (UniProt Consortium, 2015) (Proteome ID information regarding the associated diseases was collected UP000005640; release 2016_09) and scanned for PrLDs with from the OMIM FTP site. DisGeNET data were retrieved from Frontiers in Physiology | www.frontiersin.org 2 March 2019 | Volume 10 | Article 314 Iglesias et al. Human Prion-Like Proteins DisGeNET download section (Pinero et al., 2015). For both PrLDs located in any of the protein’s ends (Figures 1, 2 and databases, the number of proteins associated to at least one Supplementary Table S1). PrLDs were 1.67 times more frequent disease ID was divided by the total number of proteins, obtaining at the protein C-terminus. This was the case for 122 proteins, the fraction of disease-associated proteins. The results were while in 73 of them the PrLDs were located at the N-terminus. compared to 100 random sampling of sets with the same number This statistically significant imbalance between the presence of of proteins than the one in the database. PrLDs at C- and N- in human proteins (p-value < 0.005, Z-test), contrasts with that found in bona fide yeast PrDs. In SUP35, Human Network Analysis URE2, NEW1, MOT3, and SWI1 proteins, the PrD is placed The human prion-like protein dataset was curated for duplicities at the N-terminus, whereas only in RNQ1, it is located near and scanned for PPIs with Interactome3D (2017_06 version) the carboxyl end (Baxa et al., 2007; Zambrano et al., 2015). (Mosca et al., 2013). Out of the 121 unique identities, 100 The modular architecture of prion-like proteins would allow the had annotated physical binary interactions. The degree and self-assembly of the PrLDs without disturbing the structure and the number of interactions between prion-like proteins were productive associations of the adjacent globular moieties. This analyzed and compared to a random distribution by sampling is likely facilitated by the predicted disordered nature of these the complete human binary interactome in Interactome3D. protein segments (Supplementary Table S1). Moreover, the sizes of the LCC and the MSD were measured (Menche et al., 2015). The subnetwork of prion-like proteins and their interactors were functionally characterized with DAVID Human Prion-Like Proteins Play a Major database (Huang da et al., 2009) for GO and KEGG pathways Role in Nucleic Acid Binding enrichment (n = 1542). The significance of the differences was As a first step to gain insights into the biological role assessed by Wilcox p-value or empirical p-value. of the candidate human prion-like proteins, we used a GO term analysis. GO terms were collected for biological process, molecular function, and cellular component categories RESULTS and their enrichment with respect to the human proteome calculated (Figure 3). When we analyzed the “biological Human Prion-Like Proteins Prevalence process” category for the set of candidate proteins, we found and Modularity a statistically significantly enriched cluster of GO terms A combination of prion-like compositional bias (PLAAC) and related to RNA and DNA associated processes, including sequential amyloid propensity (pWALTZ) analysis was applied to positive regulation of transcription from RNA polymerase the complete human proteome. This resulted in the identification II promoter (p-value < 1.20E-16, 30 proteins), positive of a total of 242 polypeptides (unique UniProt entries) bearing regulation of transcription DNA-templated (p-value < 6.92E-14, PrLDs (Supplementary Table S1). Our list of candidates included 22 proteins), mRNA splicing (p-value < 2.27E-9, 13 proteins), all human prion-like proteins shown to behave as such both transcription DNA-templated (p-value < 5.26E-8, 36 proteins), in vitro and in vivo: FUS (Ju et al., 2011), TDP-43 (Wang et al., RNA processing (p-value < 7.5E-8, 10 proteins), and negative 2012), EWS (Couthouis et al., 2012), hnRNP A1 and hnRNP A2 regulation of transcription from RNA polymerase II promoter (Kim et al., 2013), TIA1 (Li et al., 2014), and TAF15 (Couthouis (p-value < 6.28E-4, 11 proteins) (Figure 3A). This result is et al., 2011) proteins, reinforcing the suitability of our dataset consistent with the observation that the prion-like subproteomes for the further evaluation of the global properties of human identified in organisms belonging to different taxonomic prion-like sequences. divisions are usually enriched in proteins associated to the According to our predictions, prion-like proteins account regulation of the flux of genetic information in the cell (Iglesias for a 0.34% of the human proteome. This is in line with two et al., 2015; Pallares et al., 2018). previous independent surveys for human prion-like proteins With respect to the “molecular function,” the most enriched that exploited compositional bias alone for their detection; both GO terms are all involved in essential activities related with studies predicting that the prevalence of these proteins is <1% nucleic acid binding and transcription processes, such as (An and Harrison, 2016). Despite the percentage of proteins transcription coactivator activity (p-value < 5.63E-17, 20 pro- with PrLDs in the proteomes of different organisms seems to teins), nucleotide binding (p-value < 4.96 E-17, 37 proteins), differ significantly (Michelitsch and Weissman, 2000; Espinosa poly(A)RNA-binding (p-value < 3.94E-15, 30 proteins), RNA- Angarica et al., 2013; Malinovska et al., 2015; Chakrabortee et al., binding (p-value < 2.99E-14, 31 proteins), chromatin binding 2016; Pallares et al., 2018), their presence in all evolutionary (p-value < 3.34E-14, 14 proteins), transcription factor activity- lineages analyzed so far suggests that these regions might play sequence-specific DNA binding (p-value < 9.79E-6, 29 proteins), conserved functional roles (Michelitsch and Weissman, 2000; and ATP binding (p-value < 1.14E-4, 13 proteins) (Figure 3B). Malinovska et al., 2015; Batlle et al., 2017c). The conformational plasticity of PrLDs has been shown to be Yeast prion proteins tend to be modular (Li and Lindquist, behind certain transcription factors ability to bind to many 2000; Alberti et al., 2009). PrDs being generally located near different targets and to play a role in the formation of the N- or C-terminal ends of the sequence (Baxa et al., 2007; chromatin regulatory complexes (Boulay et al., 2017; Kataoka Zambrano et al., 2015). In our dataset, 195 proteins; an 80.6% and Mochizuki, 2017; Cho et al., 2018). Moreover, it is of the putative human prion-like proteins, presented their becoming increasingly clear that PrLDs are crucial for the Frontiers in Physiology | www.frontiersin.org 3 March 2019 | Volume 10 | Article 314 Iglesias et al. Human Prion-Like Proteins FIGURE 1 | Prion-like proteins modularity. Well-characterized prion-like human proteins have their PrLD (as identified by PLAAC in blue) and soft amyloid core (as identified by pWALTZ in red) at the protein edges, separated from their respective globular domains (retrieved from Pfam database in violet). formation of membraneless organelles, since they enable RNA- We extended our analysis to look for the role of the binding proteins (RBPs) to undergo liquid–liquid transition, constituent functional domains in the collection of PrLDs confining their RNA cargos (Villarroya-Beltri et al., 2013; containing proteins. In agreement with the above presented Wang et al., 2018). results, Pfam domain clustering rendered DNA/RNA binding as When we analyzed the cellular components populated by the most enriched functional group (Figure 3E). Among them, our protein subset, the most enriched GO terms were the the canonical RNA recognition motif (RRM) is by far the most nucleoplasm, nucleus, and the intracellular ribonucleoprotein statistically enriched, with 14% of the detected proteins harboring complex (Figures 3C,D). As expected, all these compartments an RRM. This observation is line with previous studies (King correspond to locations were the binding between nucleic et al., 2012) and consistent with the fact that the RRM is the most acids and proteins occur frequently. Of particular interest abundant domain in RBPs, conserved from bacteria to higher is the so-called ribonucleoprotein complex which includes eukaryotes (Reddy et al., 2015). This set of RRM-bearing prion- cellular structures like the stress granules, or P-bodies, which like proteins includes FUS, TDP-43, TIA1, or hnRNP A1, all are sites for mRNA decay as well as for mRNA storage involved in the formation of dynamic membraneless intracellular and therefore act as important cell regulatory centers in compartments and associated to disease (Cascarina and Ross, determining levels of gene expression (Anderson et al., 2015). 2014; March et al., 2016; Wang et al., 2018). The RBPs associated to those membrane-less organelles are key The second most enriched domain in our data set is the determinants in the control of the organelle function and have FoxP coiled-coil (p-value < 2.95E-19, 10 proteins). It corresponds been implicated not only in adaptation to stress but also in to a coiled–coil domain involved in the modulation of the tumor biology and the pathogenesis of neurodegenerative, dimeric associations of the forkhead box family of transcription immunological, and infectious diseases (Loomis et al., factors FoxP. There are multiple lines of evidence suggesting the 1990; Villarroya-Beltri et al., 2013; Anderson et al., 2015; biological relevance of domain swapping in FoxP functionality Harrison and Shorter, 2017). being important not only for their function regulation but Frontiers in Physiology | www.frontiersin.org 4 March 2019 | Volume 10 | Article 314 Iglesias et al. Human Prion-Like Proteins conserved. Interestingly, RBPs with PrLDs such as FUS or EWS accommodate in their structure a Zn_RanBP domain in close proximity to an RRM domain. The Helicase conserved C-terminal domain is found at the C-terminus of DEAD-box helicases. Helicases function in the separation of double-stranded RNA, DNA, and RNA/DNA structures in an energy-dependent manner and therefore it is clear their role in RNA metabolism. Interestingly, the first prion-like protein identified in bacteria corresponds to the transcription terminator Rho, a helicase that can undergo a prion-state that results in genome-wide changes at the transcriptome level, contributing to rapid bacterial adaptation to fluctuating environments (Pallares et al., 2015; Yuan and Hochschild, 2017). The multitasking transcriptional regulators DDX5 and DDX17 included in our dataset contain an helicase domain in their structure reported to be associated with FIGURE 2 | PrLD distribution along the protein sequence. The relative cancer development and cell proliferation (Mazurek et al., 2012; position of PrLDs in the sequences of the complete protein dataset is plotted. Fuller-Pace, 2013). Protein sequences were divided into 20 bins corresponding to 5% of their length and the PrLDs start position represented in blue and the end in red. Prion-Like Proteins Are Widespread Among Tissues The histological localization of human prion-like proteins was also linked to disease onset (Hafner-Bratkovic et al., 2011; assayed by retrieving data from the Human Protein Atlas. Medina et al., 2016). To compare the expression levels, proteins were mapped to The other two enriched Pfam families include Zinc-fingers Ensemble gene annotations (121 genes). The expression data in Ran binding proteins (Zn_RanBP) (p-value < 1.14E-14, were collected for each cell type and averaged by tissue and 9 proteins) and the Helicase conserved C-terminal domain organ. The result illustrates that prion-like proteins are widely (p-value < 2.47E-05, 7 proteins). Zinc Finger domains are a very distributed in human tissues (Figure 4). Importantly, the data versatile group of small protein domains which are evolutionary indicate that, globally, the expression of these proteins in the FIGURE 3 | Human prion-like proteins GO enrichment analysis. The prion-like proteins GO enrichment was performed and separated into its three ontologies. (A) Biological process. (B) Molecular function. (C,D) Cellular component. Clusters were grouped by color and represented with the same color code in a mammalian cell in D. (E) Pfam structural domains enriched in prion-like proteins were computed against the human proteome background. Frontiers in Physiology | www.frontiersin.org 5 March 2019 | Volume 10 | Article 314 Iglesias et al. Human Prion-Like Proteins FIGURE 4 | Prion-like proteins expression in tissues. The average expression of prion-like proteins dataset is plotted for different tissues. The tissue bars are colored based on the corresponding organ/tissue. Values range from 0 to 3 corresponding to Human Protein Atlas annotation “not detected,” “low,” “medium,” and “high.” brain is not higher than in most organs or tissues, being more Their association to diseases was retrieved separately from the represented in endocrine tissues, in the gastrointestinal tract, the Online Mendelian Inheritance in Man (OMIM) (Amberger et al., kidney, or the lung. 2015) and the database of gene-disease association (DisGeNET) In order to identify interesting cases, we clustered the dataset (Pinero et al., 2017). The percentage of genes with disease by representing each gene as a vector of the difference of its annotations was calculated and compared with that in the expression with respect to the proteome-level tissue average complete human UniProt dataset, which was used as background. (Vg = [ ( E - Ē )1 . . . ( E - Ē )n ] where Vg : the vector of According to the OMIM database, 13.22% of the prion-like gene expressions; E: gene expression in tissue n, and Ē: average proteins encoding genes are disease-related against a 2.39% expression of all human proteome in tissue n). The clustering for the UniProt dataset, whereas values of 33.47 and 9.49% was performed through k-means algorithm implementation of were obtained in the case of DisGeNET (p-value < 1.0E-5 for scikit-learn Python module, which uses Euclidean distances by both databases, Z-test). Thus, the association with disease of default. We tested cluster numbers from 3 to 10 and chose 6 as prion-like proteins was threefold and fivefold higher than the the most discriminative one (Average silhouette, Supplementary one in the complete human proteome, according to DisGeNET Figure S1). Thus, the highest expression level cluster represents a and OMIM, respectively. To assess the significance of this group of prion-like proteins that are generally over-expressed and enrichment, 100 random samples with the same size that the remarkably includes most of the human prion-like proteins for prion-like proteins dataset were selected from the background, which it has been already demonstrated their direct involvement the percentage of proteins associated to a disease in each sample in disease: FUS, TDP-43, hnRNP A1, hnRNP A2/B1, hnRNP A3, was counted and the distribution of the percentages calculated hnRNP U, hnRNP H1, and EWS. Many of these proteins have (Figure 5). For both OMIM and DisGeNET, the prion-like already been described to be spread throughout most tissues and dataset proportion is clearly above the 95 percentile of the identified at different developmental stages (Bastian et al., 2008; distribution, which implies a significant over-representation of Uhlen et al., 2015). disease-associated proteins among human prion-like proteins. At this point, it is important to underline that the prion-like protein Prion-Like Proteins Are Disease Related identification pipeline is sequence-based and totally blind with Given the widespread tissue distribution of the prion-like respect to the protein annotation. proteins and the link to disease of proteins in the most Prion-like proteins have been associated to the onset of expressed cluster, we explored whether, globally, genes encoding neurological disorders (Harrison and Shorter, 2017). The 9% of for these polypeptides were connected to pathological processes. genes encoding for prion-like proteins, 11 out of 121, are linked Frontiers in Physiology | www.frontiersin.org 6 March 2019 | Volume 10 | Article 314 Iglesias et al. Human Prion-Like Proteins FIGURE 5 | Prion-like proteins disease association. Number of disease associations for prion-like proteins (dotted blue line) compared to 100 random sampling of the human UniProt from (A) OMIM and (B) DisGeNET databases. The median of the background sample is plotted as a black dotted line, while the red line refers to the 95 percentile of the distribution (p-value < 0.05). FIGURE 6 | Human prion-like interactome. (A) Degree distribution for the complete interactome in red and the prion-like proteins network (first neighbors) in blue. (B) Prion-like proteins average interaction degree (blue dotted line) compared to a random sampling of 1000 sets. (C) Number of PPIs between prion-like proteins (blue dotted line) compared to a random sampling of 1000 sets. to neurological diseases, according to OMIM (Supplementary to genes to obtain unique entities. Out of the 121 resulting Table S3). This constitutes a significant enrichment, relative genes, 100 had annotated physical binary interactions (physical to the complete proteome (p-value < 1.5 E-8). However, interactions between two individual proteins). Overall, prion-like it is important to note that, despite proteins connected with dataset and the proteins they interact with establish a subnetwork neurological disorders are over enriched by 1.4-fold within the of 1544 proteins with 2079 PPIs between them. Both the prion- disease associated prion-like protein subgroup, this enrichment like dataset and the complete subnetwork have higher average is not statistically significant (p-value > 0.11). It is clear from interaction degrees than the human interactome (Figure 6A). the results presented above that many of the detected proteins To uncover whether prion-like proteins interact more than are ubiquitous regulators involved in a wide range of signaling expected by chance, the average degree of interactions of the pathways; which suggests that perturbations affecting their prion-like protein set was compared with 1000 random sets of function may have a great impact in multiple disorders and not proteins of the same size (Figure 6B). This analysis confirms exclusively in neurological diseases, as it is usually assumed. that prion-like proteins exhibit a significant higher number of interactions than the average human interactome. Next, we assessed whether prion-like proteins interact more between them Prion-Like Proteins’ Role in Highly than expected by chance, by comparing the number of intra-set Interconnected Subnetworks interactions with that in 1000 random sets, as before. The results Proteins rarely perform their functions independently; but showed that prion-like proteins establish more interactions – mostly rely on complexes to carry them out. The connectivity of one order of magnitude higher – between them than expected human prion-like proteins and the properties of their interactors randomly (Figure 6C). To further describe the human prion- were analyzed. As above, prion-like proteins were first mapped like subnetwork, it was tested to what extent prion-like proteins Frontiers in Physiology | www.frontiersin.org 7 March 2019 | Volume 10 | Article 314 Iglesias et al. Human Prion-Like Proteins TABLE 1 | Prion-like proteins are located nearer in the network than as prion-like proteins. This accounts for less than 1% of the expected by chance. human proteins, which implies that, compared with organisms Prion-like Random like Plasmodium or Dictyostelium where 10–25% of their proteins protein set expectation Z-score P-value are predicted be prionogenic (Singh et al., 2004), the prionic load of the human proteome is low. The dataset included several LCC size 32 3.16 16.8 <1.10−5 widely studied proteins with prion-like behavior, such as FUS, MSD 1.64 2.2 −6.78 <1.10−5 TIA1, TDP-43, EWS, and several hnRNPs, but also previously undescribed proteins with very important cellular functions: members of the mediator complex, nucleoporins, chromatin cluster into specialized interactome neighborhoods. The size of remodeling proteins, and transcription factors. the LCC and the MSD was measured and compared to 1000 As their counterparts in yeast (Santoso et al., 2000; Alberti random sets (Table 1). The results clearly show that prion- et al., 2009), human prion-like proteins, locate their PrLDs mostly like proteins share a higher interactomic vicinity than expected at their ends; with a slight preference for the amino terminus. randomly, providing support to the concept that they exist well- This might imply that the position of the PrLD within the protein defined interaction networks for human prion-like proteins. sequence might be relevant for its function. Indeed, previous To functionally characterize this subnetwork of prion-like analyses on proteins containing low complexity regions already proteins and their interactors, the 1544 proteins were analyzed for suggested that these terminal positions would allow them to act GO and KEGG pathways enrichment. GO enrichment analysis as act as promiscuous interfaces for protein binding, without are consistent with the results obtained for the prion-like proteins steric interferences by the adjacent globular domains (Coletta dataset alone, as it highlights regulation of gene expression et al., 2010). In a similar manner, prion-like modularity and the through DNA and RNA binding as the main biological role preference for terminal regions are likely maintained in order to played by this protein subset (Supplementary Table S4). delimit a flexible region which can switch its conformation and When we examined the statistically enriched pathways assemble, modulating in this way the activity of folded domains obtained from KEGG analysis, we observed that they can be without impacting their native 3D structure. grouped into two main clusters. Remarkably, the largest cluster According to the GO terms analysis, a highly significant collects pathways involved in different types of cancer, such fraction of prion-like proteins are involved in functions related to as transcriptional misregulation in cancer (p-value < 9.86E-15, nucleic acid binding and transcription and translation activities. 53 proteins), pancreatic cancer (p-value < 2.01E-12, 29 proteins), This includes proteins of the Mediator complex, implicated prostate cancer (p-value < 1.31E-11, 33 proteins), or colorectal in the regulated transcription of nearly all RNA polymerase cancer (p-value < 1.88E-7, 22 proteins) among others; 12 prion- II-dependent genes (Zhu et al., 2015; Cho et al., 2018), proteins like proteins (10% of the total unique entries) and 122 recruited in chromatin-remodeling complexes (Boulay et al., (8.4%) of their interactors were found in these cancer related 2017; Kataoka and Mochizuki, 2017), and a significant number of pathways. These interactors include cornerstones in mitogenesis, transcription factors. The dataset also includes the large majority growth factor signaling, apoptotic attenuation, cell cycle of RBPs already described to behave as prion-like in humans, progression, angiogenesis, cell invasion, immune regulation, and such as FUS which is implicated in transcription, DNA repair, microenvironment alterations. and RNA biogenesis (Patel et al., 2015), TIA1 which functions The second group encompasses pathways associated with in mRNA turnover and regulation of translation (Li et al., viral infection, such as viral carcinogenesis (p-value < 1.42E-15, 2014), TDP-43 which is involved in transcriptional regulation 61 proteins), Epstein–Barr virus infection (p-value < 3.91E-14, and RNA processing (Buratti and Baralle, 2008; King et al., 56 proteins), herpes simplex infection (p-value < 6.6E-12, 2012), EWS which is implicated in RNA binding and processing, 51 proteins), or hepatitis C (p-value < 1.07E-6, 38 proteins). or diverse hnRNPs involved in the packaging of pre-mRNA This is consistent with the involvement of RBPs, helicases, and into RNP particles (He and Smith, 2009). Not surprisingly, splicing-related proteins in the control of viral assembly and we found that a high proportion of these proteins map into trafficking of the viral genomic RNA from the nucleus. Prion-like the nucleus and intracellular ribonucleoprotein complex. This candidates such as DDX17 (Moy et al., 2014), DDX5 (Cheng et al., last observation is consistent the extensive literature identifying 2018), and hnRNP A2B2 (Levesque et al., 2006) have been already prion-like sequences as drivers of liquid–liquid phase separation described to play key roles in these processes. in membrane-less cellular compartments (Patel et al., 2015; Banani et al., 2017). Our data reveal that human prion-like proteins are DISCUSSION multifunctional proteins involved in important regulatory processes. Indeed, 50% of the proteins in our dataset carry In the present work, we used a stringent computational approach at least two different Pfam domains. As expected from the that considers that PrLDs should not be only disordered and molecular functions in which these proteins are involved, the compositionally biased, but also encode for short sequences most statistically enriched domains correspond to RNA and with moderate, but significant, amyloid propensity (Sabate DNA binding domains such as the canonical RRM, the Zn finger et al., 2015b). We concluded that 242 polypeptides in the domain, the forkhead domain, or the helicase domain. All of human proteome fulfill the requirements to potentially behave them present in well-characterized transcription factors and Frontiers in Physiology | www.frontiersin.org 8 March 2019 | Volume 10 | Article 314 Iglesias et al. Human Prion-Like Proteins RNPs. These are evolutionary conserved domains in which, account for their strong link to human diseases. Importantly, because of their functional relevance, genetic mutations are often KEGG pathway enrichment analysis of the prion-like proteins linked to disease (King et al., 2012; Cascarina and Ross, 2014). interactome allowed us to uncover a highly significant association We assessed the expression of genes coding for prion-like with two previously undescribed set of devastating pathological proteins for each human tissue, to try to rationalize why, processes: cancer and viral infections. so far, these proteins have been mostly related to neurological Overall, despite the present study constitutes only a first diseases. Human prion-like protein expression was not restricted theoretical approach to the function of human prion-like to nervous tissue but ubiquitously spread among tissues; also, proteins, our results indicate that this subproteome exert they are not especially abundant in the brain, relative to other important regulatory functions in different biological pathways, organs of the human body. This suggests that they play a thanks to both their protein-protein and protein-nucleic acids physiological role in different cellular types, although it raises binding capabilities, two properties that seem to be favored by the question of why most prion-like proteins related diseases are their modular architecture. The analysis suggests that in the tissue-specific. This situation is not unique for prion-like proteins forthcoming years, we can expect the discovery of a connection but common to other proteins involved in neurodegenerative between prion-like proteins malfunction and other pathologies disorders, i.e., a-synuclein the protein responsible for Parkinson’s apart from neurological disorders. disease, is abundantly expressed in both the cerebral cortex and the bone marrow, but only aggregates in the brain (Spillantini et al., 1997; Barbour et al., 2008). The protein quality control DATA AVAILABILITY machinery has an active role in managing protein misfolding and aggregation. Cellular aging impacts cell homeostasis and All datasets generated for this study are included in the leads to proteostatic-compromised cells in which misfolding manuscript and/or the Supplementary Files. and aggregation events cannot be compensated (Aguzzi and Altmeyer, 2016). It has been proposed that the low efficacy of replacing dying neurons, relative to other cells types, could be AUTHOR CONTRIBUTIONS one of the underlying reasons why the malfunction of prion- like proteins is more often associated to neurological conditions. IP, PA, ST, and SV conceived the experiments and analyzed the One important finding here is that many of the human prion- results. VI, LP, and TJ-B conducted the experiments and prepared like proteins that have been convincingly associated to disease are the figures. VI, IP, and SV wrote the main manuscript text. All among the most expressed polypeptides in the dataset. This fits authors reviewed the manuscript. very well with the so-called “life at the edge” hypothesis, which states that, because protein aggregation is extremely dependent on concentration, abundant proteins are, on the average, at FUNDING highest risk of misfolding and aggregation (Tartaglia et al., 2007). Independently of their tissue distribution, what becomes clear SV was supported by Ministerio de Economía y Competitividad from the analysis of the OMIM and DisGeNet databases is that (MINECO) (BIO2016-78310-R) and by ICREA, ICREA human prion-like proteins are strongly connected to disease. Two ACADEMIA 2015 to SV. PA was supported by MINECO complementary properties might explain, at least in part, this (BIO2016-77038-R) and the European Research Council strong association. First, the propensity of PrLDs to establish Consolidator grant, SysPharmAD (614944). TJ-B is a recipient intermolecular interactions together with the presence of regions of an FPI-SO fellowship. The funders had no role in study design, with significant amyloid propensity, exposed to solvent within data collection and analysis, decision to publish, or preparation large disordered regions, impose an inherent risk to aggregate of the manuscript. to these polypeptides. 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