Intrinsic disorder in pathogenic and non-pathogenic microbes: discovering and analyzing the unfoldomes of early-branching eukaryotes

Parasitic protozoal infections have long been known to cause profound degrees of sickness and death in humans as well as animal populations. Despite the increase in the number of annotated genomes available for a large variety of protozoa, a great deal more has yet to be learned about them, from their fundamental physiology to mechanisms invoked during host-pathogen interactions. Most of these genomes share a common feature, namely a high prevalence of low complexity regions in their predicted proteins, which is believed to contribute to the uniqueness of the individual species within this diverse group of early-branching eukaryotes. In the case of Plasmodium species, which cause malaria, such regions have also been reported to hamper the identification of homologues, thus making functional genomics exceptionally challenging. One of the better accepted theories accounting for the high number of low complexity regions is the presence of intrinsic disorder in these microbes. In this study we compare the degree of disordered proteins that are predicted to be expressed in many such ancient eukaryotic cells. Our findings indicate an unusual bias in the amino acids comprising protozoal proteomes, and show that intrinsic disorder is remarkably abundant among their predicted proteins. Additionally, the intrinsically disordered regions tend to be considerably longer in the early-branching eukaryotes. An analysis of a Plasmodium falciparum interactome indicates that protein-protein interactions may be at least one function of the intrinsic disorder. This study provides a bioinfomatics basis for the discovery and analysis of unfoldomes (the complement of intrinsically disordered proteins in a given proteome) of early-branching eukaryotes. It also provides new insights into the evolution of intrinsic disorder in the context of adapting to a parasitic lifestyle and lays the foundation for further work on the subject.     

Trend of amino acid composition of proteins of different taxa

Archaea, bacteria and eukaryotes represent the main kingdoms of life. Is there any trend for amino acid compositions of proteins found in full genomes of species of different kingdoms? What is the percentage of totally unstructured proteins in various proteomes? We obtained amino acid frequencies for different taxa using 195 known proteomes and all annotated sequences from the Swiss-Prot data base. Investigation of the two data bases (proteomes and Swiss-Prot) shows that the amino acid compositions of proteins differ substantially for different kingdoms of life, and this difference is larger between different proteomes than between different kingdoms of life. Our data demonstrate that there is a surprisingly small selection for the amino acid composition of proteins for higher organisms (eukaryotes) and their viruses in comparison with the "random" frequency following from a uniform usage of codons of the universal genetic code. On the contrary, lower organisms (bacteria and especially archaea) demonstrate an enhanced selection of amino acids. Moreover, according to our estimates, 12%, 3% and 2% of the proteins in eukaryotic, bacterial and archaean proteomes are totally disordered, and long (> 41 residues) disordered segments are found to occur in 16% of arhaean, 20% of eubacterial and 43% of eukaryotic proteins for 19 archaean, 159 bacterial and 17 eukaryotic proteomes, respectively. A correlation between amino acid compositions of proteins of various taxa, show that the highest correlation is observed between eukaryotes and their viruses (the correlation coefficient is 0.98), and bacteria and their viruses (the correlation coefficient is 0.96), while correlation between eukaryotes and archaea is 0.85 only.     

Marked Variability in the Extent of Protein Disorder within and between Viral Families

Intrinsically disordered regions in eukaryotic proteomes contain key signaling and regulatory modules and mediate interactions with many proteins. Many viral proteomes encode disordered proteins and modulate host factors through the use of short linear motifs (SLiMs) embedded within disordered regions. However, the degree of viral protein disorder across different viruses is not well understood, so we set out to establish the constraints acting on viruses, in terms of their use of disordered protein regions. We surveyed predicted disorder across 2,278 available viral genomes in 41 families, and correlated the extent of disorder with genome size and other factors. Protein disorder varies strikingly between viral families (from 2.9% to 23.1% of residues), and also within families. However, this substantial variation did not follow the established trend among their hosts, with increasing disorder seen across eubacterial, archaebacterial, protists, and multicellular eukaryotes. For example, among large mammalian viruses, poxviruses and herpesviruses showed markedly differing disorder (5.6% and 17.9%, respectively). Viral families with smaller genome sizes have more disorder within each of five main viral types (ssDNA, dsDNA, ssRNA+, dsRNA, retroviruses), except for negative single-stranded RNA viruses, where disorder increased with genome size. However, surveying over all viruses, which compares tiny and enormous viruses over a much bigger range of genome sizes, there is no strong association of genome size with protein disorder. We conclude that there is extensive variation in the disorder content of viral proteomes. While a proportion of this may relate to base composition, to extent of gene overlap, and to genome size within viral types, there remain important additional family and virus-specific effects. Differing disorder strategies are likely to impact on how different viruses modulate host factors, and on how rapidly viruses can evolve novel instances of SLiMs subverting host functions, such as innate and acquired immunity.     

RAPID: Fast and accurate sequence-based prediction of intrinsic disorder content on proteomic scale

Recent research in the protein intrinsic disorder was stimulated by the availability of accurate computational predictors. However, most of these methods are relatively slow, especially considering proteome-scale applications, and were shown to produce relatively large errors when estimating disorder at the protein- (in contrast to residue-) level, which is defined by the fraction/content of disordered residues. To this end, we propose a novel support vector Regression-based Accurate Predictor of Intrinsic Disorder (RAPID). Key advantages of RAPID are speed (prediction of an average-size eukaryotic proteome takes < 1 h on a modern desktop computer); sophisticated design (multiple, complementary information sources that are aggregated over an input chain are combined using feature selection); and high-quality and robust predictive performance. Empirical tests on two diverse benchmark datasets reveal that RAPID's predictive performance compares favorably to a comprehensive set of state-of-the-art disorder and disorder content predictors. Drawing on high speed and good predictive quality, RAPID was used to perform large-scale characterization of disorder in 200 + fully sequenced eukaryotic proteomes. Our analysis reveals interesting relations of disorder with structural coverage and chain length, and unusual distribution of fully disordered chains. We also performed a comprehensive (using 56000+ annotated chains, which doubles the scope of previous studies) investigation of cellular functions and localizations that are enriched in the disorder in the human proteome. RAPID, which allows for batch (proteome-wide) predictions, is available as a web server at http://biomine.ece.ualberta.ca/RAPID/.     

Structural disorder in eukaryotes

Based on early bioinformatic studies on a handful of species, the frequency of structural disorder of proteins is generally thought to be much higher in eukaryotes than in prokaryotes. To refine this view, we present here a comparative prediction study and analysis of 194 fully described eukaryotic proteomes and 87 reference prokaryotes for structural disorder. We found that structural disorder does distinguish eukaryotes from prokaryotes, but its frequency spans a very wide range in the two superkingdoms that largely overlap. The number of disordered binding regions and different Pfam domain types also contribute to distinguish eukaryotes from prokaryotes. Unexpectedly, the highest levels--and highest variability--of predicted disorder is found in protists, i.e. single-celled eukaryotes, often surpassing more complex eukaryote organisms, plants and animals. This trend contrasts with that of the number of domain types, which increases rather monotonously toward more complex organisms. The level of structural disorder appears to be strongly correlated with lifestyle, because some obligate intracellular parasites and endosymbionts have the lowest levels, whereas host-changing parasites have the highest level of predicted disorder. We conclude that protists have been the evolutionary hot-bed of experimentation with structural disorder, in a period when structural disorder was actively invented and the major functional classes of disordered proteins established.     

Inferring function using patterns of native disorder in proteins

Natively unstructured regions are a common feature of eukaryotic proteomes. Between 30% and 60% of proteins are predicted to contain long stretches of disordered residues, and not only have many of these regions been confirmed experimentally, but they have also been found to be essential for protein function. In this study, we directly address the potential contribution of protein disorder in predicting protein function using standard Gene Ontology (GO) categories. Initially we analyse the occurrence of protein disorder in the human proteome and report ontology categories that are enriched in disordered proteins. Pattern analysis of the distributions of disordered regions in human sequences demonstrated that the functions of intrinsically disordered proteins are both length- and position-dependent. These dependencies were then encoded in feature vectors to quantify the contribution of disorder in human protein function prediction using Support Vector Machine classifiers. The prediction accuracies of 26 GO categories relating to signalling and molecular recognition are improved using the disorder features. The most significant improvements were observed for kinase, phosphorylation, growth factor, and helicase categories. Furthermore, we provide predicted GO term assignments using these classifiers for a set of unannotated and orphan human proteins. In this study, the importance of capturing protein disorder information and its value in function prediction is demonstrated. The GO category classifiers generated can be used to provide more reliable predictions and further insights into the behaviour of orphan and unannotated proteins.     

Occurrence of disordered patterns and homorepeats in eukaryotic and bacterial proteomes

Combining the motif discovery and disorder protein segment identification in PDB allows us to create the first and largest library of disordered patterns. At present the library includes 109 disordered patterns. Here we offer a comprehensive analysis of the occurrence of selected disordered patterns and 20 homorepeats of 6 residues long in 123 proteomes. 27 disordered patterns occur sparsely in all considered proteomes, but the patterns of low-complexity-homorepeats-appear more often in eukaryotic than in bacterial proteomes. A comparative analysis of the number of proteins containing homorepeats of 6 residues long and the disordered selected patterns in these proteomes has been performed. The matrices of correlation coefficients between numbers of proteins where at least once a homorepeat of six residues long for each of 20 types of amino acid residues and 109 disordered patterns from the library appears in 9 kingdoms of eukaryota and 5 phyla of bacteria have been calculated. As a rule, the correlation coefficients are higher inside the considered kingdom than between them. The largest fraction of homorepeats of 6 residues belongs to Amoebozoa proteomes (D. discoideum), 46%. Moreover, the longest uninterrupted repeats belong to S306 from D. discoideum (Amoebozoa). Homorepeats of some amino acids occur more frequently than others and the type of homorepeats varies across different proteomes, . For example, E6 appears most frequent for all considered proteomes for Chordata, Q6 for Arthropoda, S6 for Nematoda. The averaged occurrence of multiple long runs of 6 amino acids in a decreasing order for 97 eukaryotic proteomes is as follows: Q6, S6, A6, G6, N6, E6, P6, T6, D6, K6, L6, H6, R6, F6, V6, I6, Y6, C6, M6, W6, and for 26 bacterial proteomes it is A6, G6, P6, and the others occur seldom. This suggests that such short similar motifs are responsible for common functions for nonhomologous, unrelated proteins from different organisms.     

Intrinsic disorder of the extracellular matrix

The extracellular matrix is very well organized at the supramolecular and tissue levels and little is known on the potential role of intrinsic disorder in promoting its organization. We predicted the amount of disorder and identified disordered regions in the human extracellular proteome with established computational tools. The extracellular proteome is significantly enriched in proteins comprising more than 50% of disorder compared to the complete human proteome. The enrichment is mostly due to long disordered regions containing at least 100 consecutive disordered residues. The amount of intrinsic disorder is heterogeneous in the extracellular protein families, with the most disordered being collagens and the small integrin-binding ligand N-linked glycoproteins. Although most domains found in extracellular proteins are structured, the fibronectin III domains contain a variable amount of disordered residues (up to 92%). Binding sites for heparin and integrins are found in disordered sequences of extracellular proteins. Intrinsic disorder is evenly distributed in hubs and ends in the interaction network of extracellular proteins with their extracellular partners. In contrast, extracellular hubs are significantly enriched in disorder in the network of extracellular proteins with their extracellular, membrane and intracellular partners. Disorder could thus provide the structural plasticity required for the hubs to interact with membrane and intracellular proteins. Organization and assembly of the extracellular matrix, development of mineralized tissues and cell-matrix adhesion are the biological processes overrepresented in the most disordered extracellular proteins. Extracellular disorder is associated with binding to growth factors, glycosaminoglycans and integrins at the molecular level.     

Towards an understanding of the role of intrinsic protein disorder on plant adaptation to environmental challenges

Intrinsic protein disorder is an interesting structural feature where fully functional proteins lack a three-dimensional structure in solution. In this work, we estimated the relative content of intrinsic protein disorder in 96 plant proteomes including monocots and eudicots. In this analysis, we found variation in the relative abundance of intrinsic protein disorder among these major clades; the relative level of disorder is higher in monocots than eudicots. In turn, there is an inverse relationship between the degree of intrinsic protein disorder and protein length, with smaller proteins being more disordered. The relative abundance of amino acids depends on intrinsic disorder and also varies among clades. Within the nucleus, intrinsically disordered proteins are more abundant than ordered proteins. Intrinsically disordered proteins are specialized in regulatory functions, nucleic acid binding, RNA processing, and in response to environmental stimuli. The implications of this on plants’ responses to their environment are discussed.     

The importance of intrinsic disorder for protein phosphorylation

Reversible protein phosphorylation provides a major regulatory mechanism in eukaryotic cells. Due to the high variability of amino acid residues flanking a relatively limited number of experimentally identified phosphorylation sites, reliable prediction of such sites still remains an important issue. Here we report the development of a new web-based tool for the prediction of protein phosphorylation sites, DISPHOS (DISorder-enhanced PHOSphorylation predictor, http://www.ist.temple. edu/DISPHOS). We observed that amino acid compositions, sequence complexity, hydrophobicity, charge and other sequence attributes of regions adjacent to phosphorylation sites are very similar to those of intrinsically disordered protein regions. Thus, DISPHOS uses position-specific amino acid frequencies and disorder information to improve the discrimination between phosphorylation and non-phosphorylation sites. Based on the estimates of phosphorylation rates in various protein categories, the outputs of DISPHOS are adjusted in order to reduce the total number of misclassified residues. When tested on an equal number of phosphorylated and non-phosphorylated residues, the accuracy of DISPHOS reaches 76% for serine, 81% for threonine and 83% for tyrosine. The significant enrichment in disorder-promoting residues surrounding phosphorylation sites together with the results obtained by applying DISPHOS to various protein functional classes and proteomes, provide strong support for the hypothesis that protein phosphorylation predominantly occurs within intrinsically disordered protein regions.     

Conservation of intrinsic disorder in protein domains and families: II. functions of conserved disorder

Regions of conserved disorder prediction (CDP) were found in protein domains from all available InterPro member databases, although with varying frequency. These CDP regions were found in proteins from all kingdoms of life, including viruses. However, eukaryotes had 1 order of magnitude more proteins containing long disordered regions than did archaea and bacteria. Sequence conservation in CDP regions varied, but was on average slightly lower than in regions of conserved order. In some cases, disordered regions evolve faster than ordered regions, in others they evolve slower, and in the rest they evolve at roughly the same rate. A variety of functions were found to be associated with domains containing conserved disorder. The most common were DNA/RNA binding, and protein binding. Many ribosomal proteins also were found to contain conserved disordered regions. Other functions identified included membrane translocation and amino acid storage for germination. Due to limitations of current knowledge as well as the methodology used for this work, it was not determined whether these functions were directly associated with the predicted disordered region. However, the functions associated with conserved disorder in this work are in agreement with the functions found in other studies to correlate to disordered regions. We have established that intrinsic disorder may be more common in bacterial and archaeal proteins than previously thought, but this disorder is likely to be used for different purposes than in eukaryotic proteins, as well as occurring in shorter stretches of protein. Regions of predicted disorder were found to be conserved within a large number of protein families and domains. Although many think of such conserved domains as being ordered, in fact a significant number of them contain regions of disorder that are likely to be crucial to their functions.     

Natively Disordered Proteins

Proteins can exist in at least three forms: the ordered form (solid-like), the partially folded form (collapsed, molten globule-like or liquid-like) and the extended form (extended, random coil-like or gas-like). The protein trinity hypothesis has two components: (i) a given native protein can be in any one of the three forms, depending on the sequence and the environment; and (ii) function can arise from any one of the three forms or from transitions between them. In this study, bioinformatics and data mining were used to investigate intrinsic disorder in proteins and develop neural network-based predictors of natural disordered regions (PONDR) that can discriminate between ordered and disordered residues with up to 84% accuracy. Predictions of intrinsic disorder indicate that the three kingdoms follow the disorder ranking eubacteria < archaebacteria < eukaryotes, with approximately half of eukaryotic proteins predicted to contain substantial regions of intrinsic disorder. Many of the known disordered regions are involved in signalling, regulation or control. Involvement of highly flexible or disordered regions in signalling is logical: a flexible sensor more readily undergoes conformational change in response to environmental perturbations than does a rigid one. Thus, the increased disorder in the eukaryotes is likely the direct result of an increased need for signalling and regulation in nucleated organisms. PONDR can also be used to detect molecular recognition elements that are disordered in the unbound state and become structured when bound to a biologically meaningful partner. Application of disorder predictions to cell-signalling, cancer-associated and control protein databases supports the widespread occurrence of protein disorder in these processes.     

Abundance of intrinsic disorder in protein associated with cardiovascular disease

Evidence that many protein regions and even entire proteins lacking stable tertiary and/or secondary structure in solution (i.e., intrinsically disordered proteins) might be involved in protein-protein interactions, regulation, recognition, and signal transduction is rapidly accumulating. These signaling proteins play a crucial role in the development of several pathological conditions, including cancer. To test a hypothesis that intrinsic disorder is also abundant in cardiovascular disease (CVD), a data set of 487 CVD-related proteins was extracted from SWISS-PROT. CVD-related proteins are depleted in major order-promoting residues (Trp, Phe, Tyr, Ile, and Val) and enriched in some disorder-promoting residues (Arg, Gln, Ser, Pro, and Glu). The application of a neural network predictor of natural disordered regions (PONDR VL-XT) together with cumulative distribution function (CDF) analysis, charge-hydropathy plot (CH plot) analysis, and alpha-helical molecular recognition feature (alpha-MoRF) indicator revealed that CVD-related proteins are enriched in intrinsic disorder. In fact, the percentage of proteins with 30 or more consecutive residues predicted by PONDR VL-XT to be disordered was 57 +/- 4% for CVD-associated proteins. This value is close that described earlier for signaling proteins (66 +/- 6%) and is significantly larger than the content of intrinsic disorder in eukaryotic proteins from SWISS-PROT (47 +/- 4%) and in nonhomologous protein segments with a well-defined three-dimensional structure (13 +/- 4%). Furthermore, CDF and CH-plot analyses revealed that 120 and 36 CVD-related proteins, respectively, are wholly disordered. This high level of intrinsic disorder could be important for the function of CVD-related proteins and for the control and regulation of processes associated with cardiovascular disease. In agreement with this hypothesis, 198 alpha-MoRFs were predicted in 101 proteins from the CVD data set. A comparison of disorder predictions with the experimental structural and functional data for a subset of the CVD-associated proteins indicated good agreement between predictions and observations. Thus, our data suggest that intrinsically disordered proteins might play key roles in cardiovascular disease.     

Intrinsic structural disorder of DF31, a Drosophila protein of chromatin decondensation and remodeling activities

Protein disorder is predicted to be widespread in eukaryotic proteomes, although direct experimental evidence is rather limited so far. To fill this gap and to unveil the identity of novel intrinsically disordered proteins (IDPs), proteomic methods that combine 2D electrophoresis with mass spectrometry have been developed. Here, we applied the method developed in our laboratory [ Csizmok et al., Mol. Cell. Proteomics 2006, 5, 265- 273 ] to the proteome of Drosophila melanogaster. Protein Df31, earlier described as a histone chaperone involved in chromatin decondensation and stabilization, was among the IDPs identified. Despite some hints at the unusual structural behavior of Df31, this protein has not yet been structurally characterized. Here, we provide evidence by a variety of techniques such as CD, NMR, gel-filtration, limited proteolyzsis and bioinformatics that Df31 is intrinsically disordered along its entire length. Further, by chemical cross-linking, we provide evidence that it is a monomeric protein, and suggest that its function(s) may benefit from having an extended and highly flexible structural state. The potential functional advantages and the generality of protein disorder among chromatin organizing proteins are discussed in detail. Finally, we also would like to point out the utility of our 2DE/MS technique for discoveringor, as a matter of fact, rediscoveringIDPs even from the complicated proteome of an advanced eukaryote.     

Genome‐scale prediction of proteins with long intrinsically disordered regions

Proteins with long disordered regions (LDRs), defined as having 30 or more consecutive disordered residues, are abundant in eukaryotes, and these regions are recognized as a distinct class of biologically functional domains. LDRs facilitate various cellular functions and are important for target selection in structural genomics. Motivated by the lack of methods that directly predict proteins with LDRs, we designed Super‐fast predictor of proteins with Long Intrinsically DisordERed regions (SLIDER). SLIDER utilizes logistic regression that takes an empirically chosen set of numerical features, which consider selected physicochemical properties of amino acids, sequence complexity, and amino acid composition, as its inputs. Empirical tests show that SLIDER offers competitive predictive performance combined with low computational cost. It outperforms, by at least a modest margin, a comprehensive set of modern disorder predictors (that can indirectly predict LDRs) and is 16 times faster compared to the best currently available disorder predictor. Utilizing our time‐efficient predictor, we characterized abundance and functional roles of proteins with LDRs over 110 eukaryotic proteomes. Similar to related studies, we found that eukaryotes have many (on average 30.3%) proteins with LDRs with majority of proteomes having between 25 and 40%, where higher abundance is characteristic to proteomes that have larger proteins. Our first‐of‐its‐kind large‐scale functional analysis shows that these proteins are enriched in a number of cellular functions and processes including certain binding events, regulation of catalytic activities, cellular component organization, biogenesis, biological regulation, and some metabolic and developmental processes. A webserver that implements SLIDER is available at http://biomine.ece.ualberta.ca/SLIDER/ .Proteins 2014; 82:145–158. © 2013 Wiley Periodicals, Inc.     

Intrinsic disorder in the human spliceosomal proteome

The spliceosome is a molecular machine that performs the excision of introns from eukaryotic pre-mRNAs. This macromolecular complex comprises in human cells five RNAs and over one hundred proteins. In recent years, many spliceosomal proteins have been found to exhibit intrinsic disorder, that is to lack stable native three-dimensional structure in solution. Building on the previous body of proteomic, structural and functional data, we have carried out a systematic bioinformatics analysis of intrinsic disorder in the proteome of the human spliceosome. We discovered that almost a half of the combined sequence of proteins abundant in the spliceosome is predicted to be intrinsically disordered, at least when the individual proteins are considered in isolation. The distribution of intrinsic order and disorder throughout the spliceosome is uneven, and is related to the various functions performed by the intrinsic disorder of the spliceosomal proteins in the complex. In particular, proteins involved in the secondary functions of the spliceosome, such as mRNA recognition, intron/exon definition and spliceosomal assembly and dynamics, are more disordered than proteins directly involved in assisting splicing catalysis. Conserved disordered regions in spliceosomal proteins are evolutionarily younger and less widespread than ordered domains of essential spliceosomal proteins at the core of the spliceosome, suggesting that disordered regions were added to a preexistent ordered functional core. Finally, the spliceosomal proteome contains a much higher amount of intrinsic disorder predicted to lack secondary structure than the proteome of the ribosome, another large RNP machine. This result agrees with the currently recognized different functions of proteins in these two complexes.     

Prevalent structural disorder in E. coli and S. cerevisiae proteomes

Intrinsically unstructured proteins, which exist without a well-defined 3D structure, carry out essential functions and occur with high frequency, as predicted for genomes. The generality of this phenomenon, however, is questioned by the uncertainty of what fraction of genomes actually encodes for expressed proteins. Here, we used two independent bioinformatic predictors, PONDR VSL1, and IUPred, to demonstrate that disorder prevails in the recently characterized proteomes and essential proteins of E. coli and S. cerevisiae, at levels exceeding that estimated from the genomes. The S. cerevisiae proteome contains three times as much disorder as that of E. coli, with 50-60% of proteins containing at least one long (>30 residues) disordered segment. This evolutionary advance can be explained by the observation that disorder is much higher in Gene Ontology categories related to regulatory, as opposed to metabolic, functions, and also in categories unique to yeast. Thus, protein disorder is a widespread and functionally important phenomenon, which needs to be characterized in full detail for understanding complex organisms at the molecular level.     

Disordered nucleiome: Abundance of intrinsic disorder in the DNA‐ and RNA‐binding proteins in 1121 species from Eukaryota,Bacteria and Archaea

Intrinsically disordered proteins (IDPs) are abundant in various proteomes, where they play numerous important roles and complement biological activities of ordered proteins. Among functions assigned to IDPs are interactions with nucleic acids. However, often, such assignments are made based on the guilty‐by‐association principle. The validity of the extension of these correlations to all nucleic acid binding proteins has never been analyzed on a large scale across all domains of life. To fill this gap, we perform a comprehensive computational analysis of the abundance of intrinsic disorder and intrinsically disordered domains in nucleiomes (～548 000 nucleic acid binding proteins) of 1121 species from Archaea, Bacteria and Eukaryota. Nucleiome is a whole complement of proteins involved in interactions with nucleic acids. We show that relative to other proteins in the corresponding proteomes, the DNA‐binding proteins have significantly increased disorder content and are significantly enriched in disordered domains in Eukaryotes but not in Archaea and Bacteria. The RNA‐binding proteins are significantly enriched in the disordered domains in Bacteria, Archaea and Eukaryota, while the overall abundance of disorder in these proteins is significantly increased in Bacteria, Archaea, animals and fungi. The high abundance of disorder in nucleiomes supports the notion that the nucleic acid binding proteins often require intrinsic disorder for their functions and regulation.