Resilience of death: intrinsic disorder in proteins involved in the programmed cell death

It is recognized now that intrinsically disordered proteins (IDPs), which do not have unique 3D structures as a whole or in noticeable parts, constitute a significant fraction of any given proteome. IDPs are characterized by an astonishing structural and functional diversity that defines their ability to be universal regulators of various cellular pathways. Programmed cell death (PCD) is one of the most intricate cellular processes where the cell uses specialized cellular machinery and intracellular programs to kill itself. This cell-suicide mechanism enables metazoans to control cell numbers and to eliminate cells that threaten the animal''s survival. PCD includes several specific modules, such as apoptosis, autophagy, and programmed necrosis (necroptosis). These modules are not only tightly regulated but also intimately interconnected and are jointly controlled via a complex set of protein–protein interactions. To understand the role of the intrinsic disorder in controlling and regulating the PCD, several large sets of PCD-related proteins across 28 species were analyzed using a wide array of modern bioinformatics tools. This study indicates that the intrinsic disorder phenomenon has to be taken into consideration to generate a complete picture of the interconnected processes, pathways, and modules that determine the essence of the PCD. We demonstrate that proteins involved in regulation and execution of PCD possess substantial amount of intrinsic disorder. We annotate functional roles of disorder across and within apoptosis, autophagy, and necroptosis processes. Disordered regions are shown to be implemented in a number of crucial functions, such as protein–protein interactions, interactions with other partners including nucleic acids and other ligands, are enriched in post-translational modification sites, and are characterized by specific evolutionary patterns. We mapped the disorder into an integrated network of PCD pathways and into the interactomes of selected proteins that are involved in the p53-mediated apoptotic signaling pathway.     

Recent developments of sequence-based prediction of protein–protein interactions

The identification of protein–protein interactions (PPIs) can lead to a better understanding of cellular functions and biological processes of proteins and contribute to the design of drugs to target disease-causing PPIs. In addition, targeting host–pathogen PPIs is useful for elucidating infection mechanisms. Although several experimental methods have been used to identify PPIs, these methods can yet to draw complete PPI networks. Hence, computational techniques are increasingly required for the prediction of potential PPIs, which have never been seen experimentally. Recent high-performance sequence-based methods have contributed to the construction of PPI networks and the elucidation of pathogenetic mechanisms in specific diseases. However, the usefulness of these methods depends on the quality and quantity of training data of PPIs. In this brief review, we introduce currently available PPI databases and recent sequence-based methods for predicting PPIs. Also, we discuss key issues in this field and present future perspectives of the sequence-based PPI predictions.     

Enhanced immunoprecipitation techniques for the identification of RNA-binding protein partners: IGF2BP1 interactions in mammary epithelial cells

RNA-binding proteins (RBPs) regulate the expression of large cohorts of RNA species to produce programmatic changes in cellular phenotypes. To describe the function of RBPs within a cell, it is key to identify their mRNA-binding partners. This is often done by crosslinking nucleic acids to RBPs, followed by chemical release of the nucleic acid fragments for analysis. However, this methodology is lengthy, which involves complex processing with attendant sample losses, thus large amounts of starting materials and prone to artifacts. To evaluate potential alternative technologies, we tested “exclusion-based” purification of immunoprecipitates (IFAST or SLIDE) and report here that these methods can efficiently, rapidly, and specifically isolate RBP–RNA complexes. The analysis requires less than 1% of the starting material required for techniques that include crosslinking. Depending on the antibody used, 50% to 100% starting protein can be retrieved, facilitating the assay of endogenous levels of RBPs; the isolated ribonucleoproteins are subsequently analyzed using standard techniques, to provide a comprehensive portrait of RBP complexes. Using exclusion-based techniques, we show that the mRNA-binding partners for RBP IGF2BP1 in cultured mammary epithelial cells are enriched in mRNAs important for detoxifying superoxides (specifically glutathione peroxidase [GPX]-1 and GPX-2) and mRNAs encoding mitochondrial proteins. We show that these interactions are functionally significant, as loss of function of IGF2BP1 leads to destabilization of GPX mRNAs and reduces mitochondrial membrane potential and oxygen consumption. We speculate that this underlies a consistent requirement for IGF2BP1 for the expression of clonogenic activity in vitro.     

Inherent dynamics within the Crimean-Congo Hemorrhagic fever virus protease are localized to the same region as substrate interactions

Crimean-Congo Hemorrhagic fever virus (CCHFV) is one of several lethal viruses that encodes for a viral ovarian tumor domain (vOTU), which serves to cleave and remove ubiquitin (Ub) and interferon stimulated gene product 15 (ISG15) from numerous proteins involved in cellular signaling. Such manipulation of the host cell machinery serves to downregulate the host response and, therefore, complete characterization of these proteases is important. While several structures of the CCHFV vOTU protease have been solved, both free and bound to Ub and ISG15, few structural differences have been found and little insight has been gained as to the structural plasticity of this protease. Therefore, we have used NMR relaxation experiments to probe the dynamics of CCHFV vOTU, both alone and in complex with Ub, discovering a highly dynamic protease that exhibits conformational exchange within the same regions found to engage its Ub substrate. These experiments reveal a structural plasticity around the N-terminal regions of CCHFV vOTU, which are unique to vOTUs, and provide a rationale for engaging multiple substrates with the same binding site.     

Beta turn propensity and a model polymer scaling exponent identify intrinsically disordered phase-separating proteins

The complex cellular milieu can spontaneously demix, or phase separate, in a process controlled in part by intrinsically disordered (ID) proteins. A protein''s propensity to phase separate is thought to be driven by a preference for protein–protein over protein–solvent interactions. The hydrodynamic size of monomeric proteins, as quantified by the polymer scaling exponent (v), is driven by a similar balance. We hypothesized that mean v, as predicted by protein sequence, would be smaller for proteins with a strong propensity to phase separate. To test this hypothesis, we analyzed protein databases containing subsets of proteins that are folded, disordered, or disordered and known to spontaneously phase separate. We find that the phase-separating disordered proteins, on average, had lower calculated values of v compared with their non-phase-separating counterparts. Moreover, these proteins had a higher sequence-predicted propensity for β-turns. Using a simple, surface area-based model, we propose a physical mechanism for this difference: transient β-turn structures reduce the desolvation penalty of forming a protein-rich phase and increase exposure of atoms involved in π/sp² valence electron interactions. By this mechanism, β-turns could act as energetically favored nucleation points, which may explain the increased propensity for turns in ID regions (IDRs) utilized biologically for phase separation. Phase-separating IDRs, non-phase-separating IDRs, and folded regions could be distinguished by combining v and β-turn propensity. Finally, we propose a new algorithm, ParSe (partition sequence), for predicting phase-separating protein regions, and which is able to accurately identify folded, disordered, and phase-separating protein regions based on the primary sequence.     

The CCN2/CTGF interactome: an approach to understanding the versatility of CCN2/CTGF molecular activities

Cellular communication network 2 (CCN2), also known as connective tissue growth factor (CTGF) regulates diverse cellular processes, some at odds with others, including adhesion, proliferation, apoptosis, and extracellular matrix (ECM) protein synthesis. Although a cause-and-effect relationship between CCN2/CTGF expression and local fibrotic reactions has initially been established, CCN2/CTGF manifests cell-, tissue-, and context-specific functions and differentially affects developmental and pathological processes ranging from progenitor cell fate decisions and angiogenesis to inflammation and tumorigenesis. CCN2/CTGF multimodular structure, binding to and activation or inhibition of multiple cell surface receptors, growth factors and ECM proteins, and susceptibility for proteolytic cleavage highlight the complexity to CCN2/CTGF biochemical attributes. CCN2/CTGF expression and dosage in the local environment affects a defined community of its interacting partners, and this results in sequestration of growth factors, interference with or potentiation of ligand-receptor binding, cellular internalization of CCN2/CTGF, inhibition or activation of proteases, and generation of CCN2/CTGF degradome products that add molecular diversity and expand the repertoire of functional modules in the cells and their microenvironment. Through these interactions, different intracellular signals and cellular responses are elicited culminating into physiological or pathological reactions. Thus, the CCN2/CTGF interactome is a defining factor of its tissue- and context-specific effects. Mapping of new CCN2/CTGF binding partners might shed light on yet unknown roles of CCN2/CTGF and provide a solid basis for tissue-specific targeting this molecule or its interacting partners in a therapeutic context.     

Interactome Analysis of KIN (Kin17) Shows New Functions of This Protein

KIN (Kin17) protein is overexpressed in a number of cancerous cell lines, and is therefore considered a possible cancer biomarker. It is a well-conserved protein across eukaryotes and is ubiquitously expressed in all cell types studied, suggesting an important role in the maintenance of basic cellular function which is yet to be well determined. Early studies on KIN suggested that this nuclear protein plays a role in cellular mechanisms such as DNA replication and/or repair; however, its association with chromatin depends on its methylation state. In order to provide a better understanding of the cellular role of this protein, we investigated its interactome by proximity-dependent biotin identification coupled to mass spectrometry (BioID-MS), used for identification of protein–protein interactions. Our analyses detected interaction with a novel set of proteins and reinforced previous observations linking KIN to factors involved in RNA processing, notably pre-mRNA splicing and ribosome biogenesis. However, little evidence supports that this protein is directly coupled to DNA replication and/or repair processes, as previously suggested. Furthermore, a novel interaction was observed with PRMT7 (protein arginine methyltransferase 7) and we demonstrated that KIN is modified by this enzyme. This interactome analysis indicates that KIN is associated with several cell metabolism functions, and shows for the first time an association with ribosome biogenesis, suggesting that KIN is likely a moonlight protein.     

Host pathogen protein interactions predicted by comparative modeling

Pathogens have evolved numerous strategies to infect their hosts, while hosts have evolved immune responses and other defenses to these foreign challenges. The vast majority of host-pathogen interactions involve protein-protein recognition, yet our current understanding of these interactions is limited. Here, we present and apply a computational whole-genome protocol that generates testable predictions of host-pathogen protein interactions. The protocol first scans the host and pathogen genomes for proteins with similarity to known protein complexes, then assesses these putative interactions, using structure if available, and, finally, filters the remaining interactions using biological context, such as the stage-specific expression of pathogen proteins and tissue expression of host proteins. The technique was applied to 10 pathogens, including species of Mycobacterium, apicomplexa, and kinetoplastida, responsible for "neglected" human diseases. The method was assessed by (1) comparison to a set of known host-pathogen interactions, (2) comparison to gene expression and essentiality data describing host and pathogen genes involved in infection, and (3) analysis of the functional properties of the human proteins predicted to interact with pathogen proteins, demonstrating an enrichment for functionally relevant host-pathogen interactions. We present several specific predictions that warrant experimental follow-up, including interactions from previously characterized mechanisms, such as cytoadhesion and protease inhibition, as well as suspected interactions in hypothesized networks, such as apoptotic pathways. Our computational method provides a means to mine whole-genome data and is complementary to experimental efforts in elucidating networks of host-pathogen protein interactions.     

Macromolecular interactions of the bacterial division FtsZ protein: from quantitative biochemistry and crowding to reconstructing minimal divisomes in the test tube

The division of Escherichia coli is an essential process strictly regulated in time and space. It requires the association of FtsZ with other proteins to assemble a dynamic ring during septation, forming part of the functionally active division machinery, the divisome. FtsZ reversibly interacts with FtsA and ZipA at the cytoplasmic membrane to form a proto-ring, the first molecular assembly of the divisome, which is ultimately joined by the rest of the division-specific proteins. In this review we summarize the quantitative approaches used to study the activity, interactions, and assembly properties of FtsZ under well-defined solution conditions, with the aim of furthering our understanding of how the behavior of FtsZ is controlled by nucleotides and physiological ligands. The modulation of the association and assembly properties of FtsZ by excluded-volume effects, reproducing in part the natural crowded environment in which this protein has evolved to function, will be described. The subsequent studies on the reactivity of FtsZ in membrane-like systems using biochemical, biophysical, and imaging technologies are reported. Finally, we discuss the experimental challenges to be met to achieve construction of the minimum protein set needed to initiate bacterial division, without cells, in a cell-like compartment. This integrated approach, combining quantitative and synthetic strategies, will help to support (or dismiss) conclusions already derived from cellular and molecular analysis and to complete our understanding on how bacterial division works.     

ATP regulates RNA‐driven cold inducible RNA binding protein phase separation

Intrinsically disordered proteins and proteins containing intrinsically disordered regions are highly abundant in the proteome of eukaryotes and are extensively involved in essential biological functions. More recently, their role in the organization of biomolecular condensates has become evident and along with their misregulation in several neurologic disorders. Currently, most studies involving these proteins are carried out in vitro and using purified proteins. Given that in cells, condensate‐forming proteins are exposed to high, millimolar concentrations of cellular metabolites, we aimed to reveal the interactions of cellular metabolites and a representative condensate‐forming protein. Here, using the arginine–glycine/arginine–glycine–glycine (RG/RGG)‐rich cold inducible RNA binding protein (CIRBP) as paradigm, we studied binding of the cellular metabolome to CIRBP. We found that most of the highly abundant cellular metabolites, except nucleotides, do not directly bind to CIRBP. ATP, ADP, and AMP as well as NAD⁺, NADH, NADP⁺, and NADPH directly interact with CIRBP, involving both the folded RNA‐recognition motif and the disordered RG/RGG region. ATP binding inhibited RNA‐driven phase separation of CIRBP. Thus, it might be beneficial to include cellular metabolites in in vitro liquid–liquid phase separation studies of RG/RGG and other condensate‐forming proteins in order to better mimic the cellular environment in the future.     

Detritivores ameliorate the enhancing effect of plant-based trophic cascades on nitrogen cycling in an old-field system

Nitrogen (N) cycling is a fundamental process central to numerous ecosystem functions and services. Accumulating evidence suggests that species within detritus- and plant-based food chains can play an instrumental role in regulating this process. However, the effects of each food chain are usually examined in isolation of each other, so it remains uncertain if their effects are equally important or if one chain exerts predominant control. We experimentally manipulated the species composition of detritus-based (isopods and spiders) and plant-based (grasshoppers and spiders) food chains individually and in combination within mesocosms containing plants and microbes from an old-field ecosystem. We tested: (i) their relative impact on N cycling, and (ii) whether interactions between them moderated the influence of one group or the other. We found that spiders in plant-based food chains exerted the only positive effect on N cycling. Detritus-based food chains had no net effects on N cycling but, when combined with plant-based food chains, ameliorated the positive effects of plant-based species. Our results suggest that detritus-based food chains may ultimately limit rates of N cycling by eroding the enhancing effects of plant-based food chains when antagonistic interactions between detritus- and plant-based species exist.     

Vultures acquire information on carcass location from scavenging eagles

Vultures are recognized as the scroungers of the natural world, owing to their ecological role as obligate scavengers. While it is well known that vultures use intraspecific social information as they forage, the possibility of inter-guild social information transfer and the resulting multi-species social dilemmas has not been explored. Here, we use data on arrival times at carcasses to show that such social information transfer occurs, with raptors acting as producers of information and vultures acting as scroungers of information. We develop a game-theoretic model to show that competitive asymmetry, whereby vultures dominate raptors at carcasses, predicts this evolutionary outcome. We support this theoretical prediction using empirical data from competitive interactions at carcasses. Finally, we use an individual-based model to show that these producer–scrounger dynamics lead to vultures being vulnerable to declines in raptor populations. Our results show that social information transfer can lead to important non-trophic interactions among species and highlight important potential links among social evolution, community ecology and conservation biology. With vulture populations suffering global declines, our study underscores the importance of ecosystem-based management for these endangered keystone species.     

Solution structure and backbone dynamics of an N-terminal ubiquitin-like domain in the GLUT4-regulating protein, TUG

The GLUT4-regulating protein, TUG, functions to retain GLUT4-containing membrane vesicles intracellularly and, in response to insulin stimulation, releases these vesicles to the cellular exocytic machinery for translocation to the plasma membrane. As part of our on going effort to describe the molecular basis for TUG function, we have determined the tertiary structure and characterized the backbone dynamics for an N-terminal ubiquitin-like domain (TUG-UBL1) using NMR spectroscopy. A well-ordered conformation is observed for residues 10-83 of full-length TUG, and confirms a beta-grasp or ubiquitin-like topology. Although not required for in vitro association with GLUT4, the functional role of the TUG-UBL1 domain has not yet been described. We undertook a limited literature review of similar N-terminal UBL domains and noted that a majority participate in protein-protein interactions, generally functioning as adaptor modules to physically associate the over all activity of the protein with a specific cellular process, such as the ubiquitin-proteasome pathway. In consistent fashion, TUG-UBL1 is not expected to participate in a covalent protein modification reaction as it lacks the characteristic C-terminal diglycine ("GG") motif required for conjugation to an acceptor lysine, and also lacks the three most common acceptor lysine residues involved in polyubiquitination. Additionally, analysis of the TUG-UBL1 molecular surface reveals a lack of conservation of the "Ile-44 hydrophobic face" typically involved in ubiquitin recognition. Instead, we speculate on the possible significance of a concentrated area of negative electrostatic potential with increased backbone mobility, both of which are features suggestive of a potential protein-protein interaction site.     

Mass spectrometry‐based protein–protein interaction networks for the study of human diseases

A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein–protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)‐based approaches have allowed unbiased mapping of these disease‐mediated changes in protein–protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein–protein interactions at a system‐level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS‐based protein–protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications.     

Impacts of predator-mediated interactions along a climatic gradient on the population dynamics of an alpine bird

According to classic theory, species'' population dynamics and distributions are less influenced by species interactions under harsh climatic conditions compared to under more benign climatic conditions. In alpine and boreal ecosystems in Fennoscandia, the cyclic dynamics of rodents strongly affect many other species, including ground-nesting birds such as ptarmigan. According to the ‘alternative prey hypothesis’ (APH), the densities of ground-nesting birds and rodents are positively associated due to predator–prey dynamics and prey-switching. However, it remains unclear how the strength of these predator-mediated interactions change along a climatic harshness gradient in comparison with the effects of climatic variation. We built a hierarchical Bayesian model to estimate the sensitivity of ptarmigan populations to interannual variation in climate and rodent occurrence across Norway during 2007–2017. Ptarmigan abundance was positively linked with rodent occurrence, consistent with the APH. Moreover, we found that the link between ptarmigan abundance and rodent dynamics was strongest in colder regions. Our study highlights how species interactions play an important role in population dynamics of species at high latitudes and suggests that they can become even more important in the most climatically harsh regions.     

The interactions of molecular chaperones with client proteins: why are they so weak?

The major classes of molecular chaperones have highly variable sequences, sizes, and shapes, yet they all bind to unfolded proteins, limit their aggregation, and assist in their folding. Despite the central importance of this process to protein homeostasis, it has not been clear exactly how chaperones guide this process or whether the diverse families of chaperones use similar mechanisms. For the first time, recent advances in NMR spectroscopy have enabled detailed studies of how unfolded, “client” proteins interact with both ATP-dependent and ATP-independent classes of chaperones. Here, we review examples from four distinct chaperones, Spy, Trigger Factor, DnaK, and HscA-HscB, highlighting the similarities and differences between their mechanisms. One striking similarity is that the chaperones all bind weakly to their clients, such that the chaperone–client interactions are readily outcompeted by stronger, intra- and intermolecular contacts in the folded state. Thus, the relatively weak affinity of these interactions seems to provide directionality to the folding process. However, there are also key differences, especially in the details of how the chaperones release clients and how ATP cycling impacts that process. For example, Spy releases clients in a largely folded state, while clients seem to be unfolded upon release from Trigger Factor or DnaK. Together, these studies are beginning to uncover the similarities and differences in how chaperones use weak interactions to guide protein folding.