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.     

Metapredict: a fast,accurate, and easy-to-use predictor of consensus disorder and structure

Intrinsically disordered proteins and protein regions make up a substantial fraction of many proteomes in which they play a wide variety of essential roles. A critical first step in understanding the role of disordered protein regions in biological function is to identify those disordered regions correctly. Computational methods for disorder prediction have emerged as a core set of tools to guide experiments, interpret results, and develop hypotheses. Given the multiple different predictors available, consensus scores have emerged as a popular approach to mitigate biases or limitations of any single method. Consensus scores integrate the outcome of multiple independent disorder predictors and provide a per-residue value that reflects the number of tools that predict a residue to be disordered. Although consensus scores help mitigate the inherent problems of using any single disorder predictor, they are computationally expensive to generate. They also necessitate the installation of multiple different software tools, which can be prohibitively difficult. To address this challenge, we developed a deep-learning-based predictor of consensus disorder scores. Our predictor, metapredict, utilizes a bidirectional recurrent neural network trained on the consensus disorder scores from 12 proteomes. By benchmarking metapredict using two orthogonal approaches, we found that metapredict is among the most accurate disorder predictors currently available. Metapredict is also remarkably fast, enabling proteome-scale disorder prediction in minutes. Importantly, metapredict is a fully open source and is distributed as a Python package, a collection of command-line tools, and a web server, maximizing the potential practical utility of the predictor. We believe metapredict offers a convenient, accessible, accurate, and high-performance predictor for single-proteins and proteomes alike.     

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.     

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.     

Orderly order in protein intrinsic disorder distribution: disorder in 3500 proteomes from viruses and the three domains of life

Intrinsically disordered proteins and intrinsically disordered protein regions are highly abundant in nature. However, the quantitative and qualitative measures of protein intrinsic disorder in species with known genomes are still not available. Furthermore, although the correlation between high fraction of disordered residues and advanced species has been reported, the details of this correlation and the connection between the disorder content and proteome complexity have not been reported as of yet. To fill this gap, we analysed entire proteomes of 3484 species from three domains of life (archaea, bacteria and eukaryotes) and from viruses. Our analysis revealed that the evolution process is characterized by distinctive patterns of changes in the protein intrinsic disorder content. We are showing here that viruses are characterized by the widest spread of the proteome disorder content (the percentage of disordered residues ranges from 7.3% in human coronavirus NL63 to 77.3% in Avian carcinoma virus). For several organisms, a clear correlation is seen between their disorder contents and habitats. In multicellular eukaryotes, there is a weak correlation between the complexity of an organism (evaluated as a number of different cell types) and its overall disorder content. For both the prokaryotes and eukaryotes, the disorder content is generally independent of the proteome size. However, disorder shows a sharp increase associated with the transition from prokaryotic to eukaryotic cells. This suggests that the increased disorder content in eukaryotic proteomes might be used by nature to deal with the increased cell complexity due to the appearance of the various cellular compartments.     

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.     

Structural disorder: a tool for housekeeping proteins performing tissue-specific interactions

An interaction between a pair of proteins unique for a particular tissue is denoted as a tissue-specific interaction (TSI). Tissue-specific (TS) proteins always perform TSIs with a limited number of interacting partners. However, it has been claimed that housekeeping (HK) proteins frequently take part in TSIs. This is actually an unusual phenomenon. How a single HK protein mediates TSIs – remains an interesting yet an unsolved question. We have hypothesized that HK proteins have attained a high degree of structural flexibility to modulate TSIs efficiently. We have observed that HK proteins are selected to be intrinsically disordered compared to TS proteins. Therefore, the purposeful adaptation of structural disorder brings out special advantages for HK proteins compared to TS proteins. We have demonstrated that TSIs may play vital roles in shaping the molecular adaptation of disordered regions within HK proteins. We also have noticed that HK proteins, mediating a huge number of TSIs, have a greater portion of their interacting interfaces overlapped with the adjacent disordered segment. Moreover, these HK proteins, mediating TSIs, preferably adapt single domain (SD). We have concluded that HK proteins adapt a high degree of structural flexibility to mediate TSIs. Besides, having a SD along with structural flexibility is more economic than maintaining multiple domains with a rigid structure. This assists them in attaining various structural conformations upon binding to their partners, thereby designing an economically optimum molecular system.     

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.     

Abundance and functional roles of intrinsic disorder in allergenic proteins and allergen representative peptides

The pathological process of allergies generally involves an initial activation of certain immune cells, tied to an ensuing inflammatory reaction on renewed contact with the allergen. In IgE-mediated hypersensitivity, this typically occurs in response to otherwise harmless food- or air-borne proteins. As some members of certain protein families carry special properties that make them allergenic, exploring protein allergens at the molecular level is instrumental to an improved understanding of the disease mechanisms, including the identification of relevant antigen features. For this purpose, we inspected a previously identified set of allergen representative peptides (ARPs) to scrutinize protein intrinsic disorder. The resulting study presented here focused on the association between these ARPs and protein intrinsic disorder. In addition, the connection between the disorder-enriched ARPs and UniProt functional keywords was considered. Our analysis revealed that ～ 20% of the allergen peptides are highly disordered, and that ～ 77% of ARPs are either located within disordered regions of corresponding allergenic proteins or show more disorder/flexibility than their neighbor regions. Furthermore, among the subset of allergenic proteins, ～ 70% of the predicted molecular recognition features (MoRFs that consist of short interactive disordered regions undergoing disorder-to-order transitions at interaction with binding partners) were identified as ARPs. These results suggest that intrinsic disorder and MoRFs may play functional roles in IgE-mediated allergy.     

Utilization of protein intrinsic disorder knowledge in structural proteomics

Intrinsically disordered proteins (IDPs) and proteins with long disordered regions are highly abundant in various proteomes. Despite their lack of well-defined ordered structure, these proteins and regions are frequently involved in crucial biological processes. Although in recent years these proteins have attracted the attention of many researchers, IDPs represent a significant challenge for structural characterization since these proteins can impact many of the processes in the structure determination pipeline. Here we investigate the effects of IDPs on the structure determination process and the utility of disorder prediction in selecting and improving proteins for structural characterization. Examination of the extent of intrinsic disorder in existing crystal structures found that relatively few protein crystal structures contain extensive regions of intrinsic disorder. Although intrinsic disorder is not the only cause of crystallization failures and many structured proteins cannot be crystallized, filtering out highly disordered proteins from structure-determination target lists is still likely to be cost effective. Therefore it is desirable to avoid highly disordered proteins from structure-determination target lists and we show that disorder prediction can be applied effectively to enrich structure determination pipelines with proteins more likely to yield crystal structures. For structural investigation of specific proteins, disorder prediction can be used to improve targets for structure determination. Finally, a framework for considering intrinsic disorder in the structure determination pipeline is proposed.     

Proteomic phenotyping of Novosphingobium nitrogenifigens reveals a robust capacity for simultaneous nitrogen fixation, polyhydroxyalkanoate production, and resistance to reactive oxygen species

Novosphingobium nitrogenifigens Y88(T) (Y88) is a free-living, diazotrophic Alphaproteobacterium, capable of producing 80% of its biomass as the biopolymer polyhydroxybutyrate (PHB). We explored the potential utility of this species as a polyhydroxybutyrate production strain, correlating the effects of glucose, nitrogen availability, dissolved oxygen concentration, and extracellular pH with polyhydroxybutyrate production and changes in the Y88 proteomic profile. Using two-dimensional differential in-gel electrophoresis and tandem mass spectrometry, we identified 217 unique proteins from six growth conditions. We observed reproducible, characteristic proteomic signatures for each of the physiological states we examined. We identified proteins that changed in abundance in correlation with either nitrogen fixation, dissolved oxygen concentration, or acidification of the growth medium. The proteins that correlated with nitrogen fixation were identified either as known nitrogen fixation proteins or as novel proteins that we predict play roles in aspects of nitrogen fixation based on their proteomic profiles. In contrast, the proteins involved in central carbon and polyhydroxybutyrate metabolism were constitutively abundant, consistent with the constitutive polyhydroxybutyrate production that we observed in this species. Three proteins with roles in detoxification of reactive oxygen species were identified in this obligate aerobe. The most abundant protein in all experiments was a polyhydroxyalkanoate granule-associated protein, phasin. The full-length isoform of this protein has a long, intrinsically disordered Ala/Pro/Lys-rich N-terminal segment, a feature that appears to be unique to sphingomonad phasins. The data suggest that Y88 has potential as a PHB production strain due to its aerobic tolerance and metabolic orientation toward polyhydroxybutyrate accumulation, even in low-nitrogen growth medium.     

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.     

A comprehensive overview of computational protein disorder prediction methods

Over the past decade there has been a growing acknowledgement that a large proportion of proteins within most proteomes contain disordered regions. Disordered regions are segments of the protein chain which do not adopt a stable structure. Recognition of disordered regions in a protein is of great importance for protein structure prediction, protein structure determination and function annotation as these regions have a close relationship with protein expression and functionality. As a result, a great many protein disorder prediction methods have been developed so far. Here, we present an overview of current protein disorder prediction methods including an analysis of their advantages and shortcomings. In order to help users to select alternative tools under different circumstances, we also evaluate 23 disorder predictors on the benchmark data of the most recent round of the Critical Assessment of protein Structure Prediction (CASP) and assess their accuracy using several complementary measures.     

Protein intrinsic disorder and human papillomaviruses: increased amount of disorder in E6 and E7 oncoproteins from high risk HPVs

It is recognized now that many functional proteins or their long segments are devoid of stable secondary and/or tertiary structure and exist instead as very dynamic ensembles of conformations. They are known by different names including natively unfolded, intrinsically disordered, intrinsically unstructured, rheomorphic, pliable, and different combinations thereof. Many important functions and activities have been associated with these intrinsically disordered proteins (IDPs), including molecular recognition, signaling, and regulation. It is also believed that disorder of these proteins allows function to be readily modified through phosphorylation, acetylation, ubiquitination, hydroxylation, and proteolysis. Bioinformatics analysis revealed that IDPs comprise a large fraction of different proteomes. Furthermore, it is established that the intrinsic disorder is relatively abundant among cancer-related and other disease-related proteins and IDPs play a number of key roles in oncogenesis. There are more than 100 different types of human papillomaviruses (HPVs), which are the causative agents of benign papillomas/warts, and cofactors in the development of carcinomas of the genital tract, head and neck, and epidermis. With respect to their association with cancer, HPVs are grouped into two classes, known as low (e.g., HPV-6 and HPV-11) and high-risk (e.g., HPV-16 and HPV-18) types. The entire proteome of HPV includes six nonstructural proteins [E1, E2, E4, E5, E6, and E7 (the latter two are known to function as oncoproteins in the high-risk HPVs)] and two structural proteins (L1 and L2). To understand whether intrinsic disorder plays a role in the oncogenic potential of different HPV types, we have performed a detailed bioinformatics analysis of proteomes of high-risk and low-risk HPVs with the major focus on E6 and E7 oncoproteins. The results of this analysis are consistent with the conclusion that high-risk HPVs are characterized by the increased amount of intrinsic disorder in transforming proteins E6 and E7.     

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.     

Large‐Scale Analysis of Redox‐Sensitive Conditionally Disordered Protein Regions Reveals Their Widespread Nature and Key Roles in High‐Level Eukaryotic Processes

Recently developed quantitative redox proteomic studies enable the direct identification of redox‐sensing cysteine residues that regulate the functional behavior of target proteins in response to changing levels of reactive oxygen species. At the molecular level, redox regulation can directly modify the active sites of enzymes, although a growing number of examples indicate the importance of an additional underlying mechanism that involves conditionally disordered proteins. These proteins alter their functional behavior by undergoing a disorder‐to‐order transition in response to changing redox conditions. However, the extent to which this mechanism is used in various proteomes is currently unknown. Here, a recently developed sequence‐based prediction tool incorporated into the IUPred2A web server is used to estimate redox‐sensitive conditionally disordered regions at a large scale. It is shown that redox‐sensitive conditional disorder is fairly widespread in various proteomes and that its presence strongly correlates with the expansion of specific domains in multicellular organisms that largely rely on extra stability provided by disulfide bonds or zinc ion binding. The analyses of yeast redox proteomes and human disease data further underlie the significance of this phenomenon in the regulation of a wide range of biological processes, as well as its biomedical importance.     

High‐throughput discovery of functional disordered regions

Partially or fully intrinsically disordered proteins are widespread in eukaryotic proteomes and play important biological functions. With the recognition that well defined protein structure is not a fundamental requirement for function come novel challenges, such as assigning function to disordered regions. In their recent work, Babu and colleagues (Ravarani et al, 2018 ) took on this challenge by developing IDR‐Screen, a robust high‐throughput approach for identifying functions of disordered regions.