Principles of self-organization in biological pathways: a hypothesis on the autogenous association of alpha-synuclein

Function of serine/arginine-rich splicing factors in hematopoiesis and hematopoietic malignancies

The serine/arginine-rich splicing factors (SRSFs) play an important role in regulating the alternative splicing of precursor RNA (pre-RNA). During this procedure, introns are removed from the pre-RNA, while the exons are accurately joined together to produce mature mRNA. In addition, SRSFs also involved in DNA replication and transcription, mRNA stability and nuclear export, and protein translation. It is reported that SRSFs participate in hematopoiesis, development, and other important biological process. They are also associated with the development of several diseases, particularly cancers. While the basic physiological functions and the important roles of SRSFs in solid cancer have been extensively reviewed, a comprehensive summary of their significant functions in normal hematopoiesis and hematopoietic malignancies is currently absent. Hence, this review presents a summary of their roles in normal hematopoiesis and hematopoietic malignancies.

(Dys)functional insights into nucleic acids and RNA-binding proteins modulation of the prion protein and α-synuclein phase separation

Prion diseases are prototype of infectious diseases transmitted by a protein, the prion protein (PrP), and are still not understandable at the molecular level. Heterogenous species of aggregated PrP can be generated from its monomer. α-synuclein (αSyn), related to Parkinson's disease, has also shown a prion-like pathogenic character, and likewise PrP interacts with nucleic acids (NAs), which in turn modulate their aggregation. Recently, our group and others have characterized that NAs and/or RNA-binding proteins (RBPs) modulate recombinant PrP and/or αSyn condensates formation, and uncontrolled condensation might precede pathological aggregation. Tackling abnormal phase separation of neurodegenerative disease-related proteins has been proposed as a promising therapeutic target. Therefore, understanding the mechanism by which polyanions, like NAs, modulate phase transitions intracellularly, is key to assess their role on toxicity promotion and neuronal death. Herein we discuss data on the nucleic acids binding properties and phase separation ability of PrP and αSyn with a special focus on their modulation by NAs and RBPs. Furthermore, we provide insights into condensation of PrP and/or αSyn in the light of non-trivial subcellular locations such as the nuclear and cytosolic environments.

Alpha-Synuclein mRNA Level Found Dependent on L444P Variant in Carriers and Gaucher Disease Patients on Enzyme Replacement Therapy

Gaucher disease (GD) is the most frequent sphingolipidosis, caused by biallelic pathogenic variants in the GBA1 gene encoding for β-glucocerebrosidase (GCase, E.C. 3.2.1.45). The condition is characterized by hepatosplenomegaly, hematological abnormalities, and bone disease in both non-neuronopathic type 1 (GD1) and neuronopathic type 3 (GD3). Interestingly, GBA1 variants were found to be one of the most important risk factors for the development of Parkinson's disease (PD) in GD1 patients. We performed a comprehensive study regarding the two most disease-specific biomarkers, glucosylsphingosine (Lyso-Gb1) and α-synuclein for GD and PD, respectively. A total of 65 patients with GD treated with ERT (47 GD1 patients and 18 GD3 patients), 19 GBA1 pathogenic variant carriers (including 10 L444P carriers), and 16 healthy subjects were involved in the study. Lyso-Gb1 was assessed by dried blood spot testing. The level of α-synuclein as an mRNA transcript, total, and oligomer protein concentration were measured with real-time PCR and ELISA, respectively. α-synuclein mRNA level was found significantly elevated in GD3 patients and L444P carriers. GD1 patients, along with GBA1 carriers of an unknown or unconfirmed variant, as well as healthy controls, have the same low level of α-synuclein mRNA. There was no correlation found between the level of α-synuclein mRNA and age in GD patients treated with ERT, whereas there was a positive correlation in L444P carriers.

Could Amyloid-β 1-42 or α-Synuclein Interact Directly with Mitochondrial DNA? A Hypothesis

The amyloid β (Aβ) and the α-synuclein (α-syn) are shown to be translocated into mitochondria. Even though their roles are widely investigated in pathological conditions, information on the presence and functions of Aβ and α-syn in mitochondria in endogenous levels is somewhat limited. We hypothesized that endogenous Aβ fragments or α-syn could interact with mitochondrial DNA (mtDNA) directly or influence RNAs or transcription factors in mitochondria and change the mtDNA transcription profile. In this review, we summarized clues of these possible interactions.

Widespread autogenous mRNA-protein interactions detected by CLIP-seq

Autogenous interactions between mRNAs and the proteins they encode are implicated in cellular feedback-loop regulation, but their extent and mechanistic foundation are unclear. It was recently hypothesized that such interactions may be common, reflecting the role of intrinsic nucleobase-amino acid affinities in shaping the genetic code's structure. Here we analyze a comprehensive set of CLIP-seq experiments involving multiple protocols and report on widespread autogenous interactions across different organisms. Specifically, 230 of 341 (67%) studied RNA-binding proteins (RBPs) interact with their own mRNAs, with a heavy enrichment among high-confidence hits and a preference for coding sequence binding. We account for different confounding variables, including physical (overexpression and proximity during translation), methodological (difference in CLIP protocols, peak callers and cell types) and statistical (treatment of null backgrounds). In particular, we demonstrate a high statistical significance of autogenous interactions by sampling null distributions of fixed-margin interaction matrices. Furthermore, we study the dependence of autogenous binding on the presence of RNA-binding motifs and structured domains in RBPs. Finally, we show that intrinsic nucleobase-amino acid affinities favor co-aligned binding between mRNA coding regions and the proteins they encode. Our results suggest a central role for autogenous interactions in RBP regulation and support the possibility of a fundamental connection between coding and binding.

Alpha synuclein processing by MMP-3 - implications for synucleinopathies

α-Synuclein (aSyn) is a protein implicated in physiological functions such as neurotransmitter release at the synapse and the regulation of gene expression in the nucleus. In addition, pathological aSyn assemblies are characteristic for a class of protein aggregation disorders referred to as synucleinopathies, where aSyn aggregates appear as Lewy bodies and Lewy neurites. We recently discovered a novel post-translational pyroglutamate (pGlu) modification at Gln79 of N-truncated aSyn that promotes oligomer formation and neurotoxicity in human synucleinopathies. A priori, the appearance of pGlu79-aSyn in vivo involves a two-step process of free N-terminal Gln79 residue generation and subsequent cyclization of Gln79 into pGlu79. Prime candidate enzymes for these processes are matrix metalloproteinase-3 (MMP-3) and glutaminyl cyclase (QC). Here, we analyzed the expression of aSyn, MMP-3, QC and pGlu79-aSyn in brains of two transgenic mouse models for synucleinopathies (BAC-SNCA and ASO) by triple immunofluorescent labellings and confocal laser scanning microscopy. We report a co-localization of these proteins in brain structures typically affected by aSyn pathology, namely hippocampus in BAC-SNCA mice and substantia nigra in ASO mice. In addition, Western blot analyses revealed a high abundance of QC, MMP-3 and transgenic human aSyn in brain stem and thalamus but lower levels in cortex/hippocampus, whereas endogenous mouse aSyn was found to be most abundant in cortex/hippocampus, followed by thalamus and brain stem. During aging of ASO mice, we observed no differences between controls and transgenic mice in MMP-3 levels but higher QC content in thalamus of 6-month-old transgenic mice. Transgenic human aSyn abundance transiently increased and then showed decrease in oldest ASO mice analyzed. Immunohistochemistry revealed a successive increase in intraneuronal and extracellular formation of pGlu79-aSyn in substantia nigra during aging of ASO mice. Together, our data are supportive for a role of MMP-3 and QC in the generation of pGlu79-aSyn in brains affected by aSyn pathology.

Alpha-synuclein negatively controls cell proliferation in dopaminergic neurons

As researchers grapple with the mechanisms and implications of alpha-synuclein (α-syn) in neuropathology, it is often forgotten that the function(s) of α-syn in healthy cells remain largely elusive. Previous work has relied on observing α-syn localization in the cell or using knockout mouse models. Here, we address the specific role of α-syn in human dopaminergic neurons by disrupting its gene (SNCA) in the human dopaminergic neuron cell line, LUHMES. SNCA-null cells were able to differentiate grossly normally and showed modest effects on gene expression. The effects on gene expression were monodirectional, resulting primarily in the significant decrease of expression for 401 genes, implicating them as direct, or indirect positive targets of α-syn. Gene ontological analysis of these genes showed enrichment in terms associated with proliferation, differentiation, and synapse activity. These results add to the tapestry of α-syn biological functions. SIGNIFICANCE STATEMENT: The normal functions of α-syn have remained controversial, despite its clear importance in Parkinson's Disease pathology, where it accumulates in Lewy bodies and contributes to neurodegeneration. Its name implies synaptic and nuclear functions, but how it participates at these locations has not been resolved. Via knock-out experiments in dopaminergic neurons, we implicate α-syn as a functional participant in synapse activity and in proliferation/differentiation, the latter being novel and provide insight into α-syn's role in neuronal development.

RNA modulates physiological and neuropathological protein phase transitions

Aggregation of RNA-binding proteins (RBPs) is a pathological hallmark of neurodegenerative disorders like amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). In these diseases, TDP-43 and FUS RBPs are depleted from the nuclear compartment, where they are normally localized, and found within cytoplasmic inclusions in degenerating regions of affected individuals' postmortem tissue. The mechanisms responsible for aggregation of these proteins has remained elusive, but recent studies suggest liquid-liquid phase separation (LLPS) might serve as a critical nucleation step in formation of pathological inclusions. The process of phase separation also underlies the formation and maintenance of several functional membraneless organelles (MLOs) throughout the cell, some of which contain TDP-43, FUS, and other disease-linked RBPs. One common ligand of disease-linked RBPs, RNA, is a major component of MLOs containing RBPs and has been demonstrated to be a strong modulator of RBP phase transitions. Although early evidence suggested a largely synergistic effect of RNA on RBP phase separation and MLO assembly, recent work indicates that RNA can also antagonize RBP phase behavior under certain physiological and pathological conditions. In this review, we describe the mechanisms underlying RNA-mediated phase transitions of RBPs and examine the molecular properties of these interactions, such as RNA length, sequence, and secondary structure, that mediate physiological or pathological LLPS.

Roles for α-Synuclein in Gene Expression

α-Synuclein (α-Syn) is a small cytosolic protein associated with a range of cellular compartments, including synaptic vesicles, the nucleus, mitochondria, endoplasmic reticulum, Golgi apparatus, and lysosomes. In addition to its physiological role in regulating presynaptic function, the protein plays a central role in both sporadic and familial Parkinson’s disease (PD) via a gain-of-function mechanism. Because of this, several recent strategies propose to decrease α-Syn levels in PD patients. While these therapies may offer breakthroughs in PD management, the normal functions of α-Syn and potential side effects of its depletion require careful evaluation. Here, we review recent evidence on physiological and pathological roles of α-Syn in regulating activity-dependent signal transduction and gene expression pathways that play fundamental role in synaptic plasticity.

RNA-protein interactions: Central players in coordination of regulatory networks

Changes in the abundance of protein and RNA molecules can impair the formation of complexes in the cell leading to toxicity and death. Here we exploit the information contained in protein, RNA and DNA interaction networks to provide a comprehensive view of the regulation layers controlling the concentration-dependent formation of assemblies in the cell. We present the emerging concept that RNAs can act as scaffolds to promote the formation ribonucleoprotein complexes and coordinate the post-transcriptional layer of gene regulation. We describe the structural and interaction network properties that characterize the ability of protein and RNA molecules to interact and phase separate in liquid-like compartments. Finally, we show that presence of structurally disordered regions in proteins correlate with the propensity to undergo liquid-to-solid phase transitions and cause human diseases. Also see the video abstract here https://youtu.be/kfpqibsNfS0.

Auto-regulatory feedback by RNA-binding proteins

RNA-binding proteins (RBPs) are key regulators in post-transcriptional control of gene expression. Mutations that alter their activity or abundance have been implicated in numerous diseases such as neurodegenerative disorders and various types of cancer. This highlights the importance of RBP proteostasis and the necessity to tightly control the expression levels and activities of RBPs. In many cases, RBPs engage in an auto-regulatory feedback by directly binding to and influencing the fate of their own mRNAs, exerting control over their own expression. For this feedback control, RBPs employ a variety of mechanisms operating at all levels of post-transcriptional regulation of gene expression. Here we review RBP-mediated autogenous feedback regulation that either serves to maintain protein abundance within a physiological range (by negative feedback) or generates binary, genetic on/off switches important for e.g. cell fate decisions (by positive feedback).

RNA structure drives interaction with proteins

The combination of high-throughput sequencing and in vivo crosslinking approaches leads to the progressive uncovering of the complex interdependence between cellular transcriptome and proteome. Yet, the molecular determinants governing interactions in protein-RNA networks are not well understood. Here we investigated the relationship between the structure of an RNA and its ability to interact with proteins. Analysing in silico, in vitro and in vivo experiments, we find that the amount of double-stranded regions in an RNA correlates with the number of protein contacts. This relationship -which we call structure-driven protein interactivity- allows classification of RNA types, plays a role in gene regulation and could have implications for the formation of phase-separated ribonucleoprotein assemblies. We validate our hypothesis by showing that a highly structured RNA can rearrange the composition of a protein aggregate. We report that the tendency of proteins to phase-separate is reduced by interactions with specific RNAs.

Post-transcriptional regulatory patterns revealed by protein-RNA interactions

The coordination of the synthesis of functionally-related proteins can be achieved at the post-transcriptional level by the action of common regulatory molecules, such as RNA–binding proteins (RBPs). Despite advances in the genome-wide identification of RBPs and their binding transcripts, the protein–RNA interaction space is still largely unexplored, thus hindering a broader understanding of the extent of the post-transcriptional regulation of related coding RNAs. Here, we propose a computational approach that combines protein–mRNA interaction networks and statistical analyses to provide an inferred regulatory landscape for more than 800 human RBPs and identify the cellular processes that can be regulated at the post-transcriptional level. We show that 10% of the tested sets of functionally-related mRNAs can be post-transcriptionally regulated. Moreover, we propose a classification of (i) the RBPs and (ii) the functionally-related mRNAs, based on their distinct behaviors in the functional landscape, hinting towards mechanistic regulatory hypotheses. In addition, we demonstrate the usefulness of the inferred functional landscape to investigate the cellular role of both well-characterized and novel RBPs in the context of human diseases.

RNA as a key factor in driving or preventing self-assembly of the TAR DNA-binding protein 43

Amyotrophic lateral sclerosis and frontotemporal lobar degeneration are incurable motor neuron diseases associated with muscle weakness, paralysis and respiratory failure. Accumulation of TAR DNA-binding protein 43 (TDP-43) as toxic cytoplasmic inclusions is one of the hallmarks of these pathologies. TDP-43 is an RNA-binding protein responsible for regulating RNA transcription, splicing, transport and translation. Aggregated TDP-43 does not retain its physiological function.

Here, we exploit the ability of TDP-43 to bind specific RNA sequences to validate our hypothesis that the native partners of a protein can be used to interfere with its ability to self-assemble into aggregates. We propose that binding of TDP-43 to specific RNA can compete with protein aggregation. This study provides a solid proof of concept to the hypothesis that natural interactions can be exploited to increase protein solubility and could be adopted as a more general rational therapeutic strategy.

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We found that binding of the RRM domains of TDP-43 to specific RNA competes with protein aggregation.

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This study provides a solid proof of concept to the hypothesis that natural interactions can be exploited to increase protein solubility.

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The concept could be adopted as a more general rationale for protein-specific drug design.

Protein complex scaffolding predicted as a prevalent function of long non-coding RNAs

The human transcriptome contains thousands of long non-coding RNAs (lncRNAs). Characterizing their function is a current challenge. An emerging concept is that lncRNAs serve as protein scaffolds, forming ribonucleoproteins and bringing proteins in proximity. However, only few scaffolding lncRNAs have been characterized and the prevalence of this function is unknown. Here, we propose the first computational approach aimed at predicting scaffolding lncRNAs at large scale. We predicted the largest human lncRNA-protein interaction network to date using the catRAPID omics algorithm. In combination with tissue expression and statistical approaches, we identified 847 lncRNAs (∼5% of the long non-coding transcriptome) predicted to scaffold half of the known protein complexes and network modules. Lastly, we show that the association of certain lncRNAs to disease may involve their scaffolding ability. Overall, our results suggest for the first time that RNA-mediated scaffolding of protein complexes and modules may be a common mechanism in human cells.

Discovering the 3' UTR-mediated regulation of alpha-synuclein

Recent evidence indicates a link between Parkinson's Disease (PD) and the expression of a-synuclein (SNCA) isoforms with different 3′ untranslated regions (3′UTRs). Yet, the post-transcriptional mechanisms regulating SNCA expression are unknown. Using a large-scale in vitro /in silico screening we identified RNA-binding proteins (RBPs) that interact with SNCA 3′ UTRs. We identified two RBPs, ELAVL1 and TIAR, that bind with high affinity to the most abundant and translationally active 3′ UTR isoform (575 nt). Knockdown and overexpression experiments indicate that both ELAVL1 and TIAR positively regulate endogenous SNCA in vivo. The mechanism of regulation implies mRNA stabilization as well as enhancement of translation in the case of TIAR. We observed significant alteration of both TIAR and ELAVL1 expression in motor cortex of post-mortem brain donors and primary cultured fibroblast from patients affected by PD and Multiple System Atrophy (MSA). Moreover, trans expression quantitative trait loci (trans-eQTLs) analysis revealed that a group of single nucleotide polymorphisms (SNPs) in TIAR genomic locus influences SNCA expression in two different brain areas, nucleus accumbens and hippocampus. Our study sheds light on the 3′ UTR-mediated regulation of SNCA and its link with PD pathogenesis, thus opening up new avenues for investigation of post-transcriptional mechanisms in neurodegeneration.

Handshakes and Fights: The Regulatory Interplay of RNA-Binding Proteins

What drives the flow of signals controlling the outcome of post-transcriptional regulation of gene expression? This regulatory layer, presiding to processes ranging from splicing to mRNA stability and localization, is a key determinant of protein levels and thus cell phenotypes. RNA-binding proteins (RBPs) form a remarkable army of post-transcriptional regulators, strong of more than 1,500 genes implementing this expression fine-tuning plan and implicated in both cell physiology and pathology. RBPs can bind and control a wide array of RNA targets. This sheer amount of interactions form complex regulatory networks (PTRNs) where the action of individual RBPs cannot be easily untangled from each other. While past studies have mostly focused on the action of individual RBPs on their targets, we are now observing an increasing amount of evidence describing the occurrence of interactions between RBPs, defining how common target RNAs are regulated. This suggests that the flow of signals in PTRNs is driven by the intertwined contribution of multiple RBPs, concurrently acting on each of their targets. Understanding how RBPs cooperate and compete is thus of paramount importance to chart the wiring of PTRNs and their impact on cell phenotypes. Here we review the current knowledge about patterns of RBP interaction and attempt at describing their general principles. We also discuss future directions which should be taken to reach a comprehensive understanding of this fundamental aspect of gene expression regulation.

Synucleins and Gene Expression: Ramblers in a Crowd or Cops Regulating Traffic?

Synuclein family consists of three members, α, β, and γ-synuclein. Due to their involvement in human diseases, they have been thoroughly investigated for the last 30 years. Since the first synuclein identification and description, members of this family are found in all vertebrates. Sequencing of their genes indicates high evolutionary conservation suggesting important function(s) of these proteins. They are small naturally unfolded proteins prone to aggregate, easily change their conformation, and bind to the membranes. The genes for α, β, and γ-synuclein have different chromosomal localization and a well preserved general organization composed of five coding exons of similar size. Three genes encoding synucleins are present in the majority of vertebrates, however, a variable number of synuclein genes are described in fishes of different species. An important question concerns their normal function in cells and tissues. α-Synuclein is implicated in the regulation of synaptic activity through regulation of synaptic vesicle release, while the physiological functions of two other members of the family is understood less clearly. Here we discuss recent results describing their role in the regulation of gene expression.

A synthetic gene circuit for measuring autoregulatory feedback control

Autoregulatory feedback loops occur in the regulation of molecules ranging from ATP to MAP kinases to zinc. Negative feedback loops can increase a system's robustness, while positive feedback loops can mediate transitions between cell states. Recent genome-wide experimental and computational studies predict hundreds of novel feedback loops. However, not all physical interactions are regulatory, and many experimental methods cannot detect self-interactions. Our understanding of regulatory feedback loops is therefore hampered by the lack of high-throughput methods to experimentally quantify the presence, strength and temporal dynamics of autoregulatory feedback loops. Here we present a mathematical and experimental framework for high-throughput quantification of feedback regulation and apply it to RNA binding proteins (RBPs) in yeast. Our method is able to determine the existence of both direct and indirect positive and negative feedback loops, and to quantify the strength of these loops. We experimentally validate our model using two RBPs which lack native feedback loops and by the introduction of synthetic feedback loops. We find that RBP Puf3 does not natively participate in any direct or indirect feedback regulation, but that replacing the native 3'UTR with that of COX17 generates an auto-regulatory negative feedback loop which reduces gene expression noise. Likewise, RBP Pub1 does not natively participate in any feedback loops, but a synthetic positive feedback loop involving Pub1 results in increased expression noise. Our results demonstrate a synthetic experimental system for quantifying the existence and strength of feedback loops using a combination of high-throughput experiments and mathematical modeling. This system will be of great use in measuring auto-regulatory feedback by RNA binding proteins, a regulatory motif that is difficult to quantify using existing high-throughput methods.

A Computational Approach for the Discovery of Protein-RNA Networks

Protein-RNA interactions play important roles in a wide variety of cellular processes, ranging from transcriptional and posttranscriptional regulation of genes to host defense against pathogens. In this chapter we present the computational approach catRAPID to predict protein-RNA interactions and discuss how it could be used to find trends in ribonucleoprotein networks. We envisage that the combination of computational and experimental approaches will be crucial to unravel the role of coding and noncoding RNAs in protein networks.

Protein aggregation, structural disorder and RNA-binding ability: a new approach for physico-chemical and gene ontology classification of multiple datasets

Background

Comparison between multiple protein datasets requires the choice of an appropriate reference system and a number of variables to describe their differences. Here we introduce an innovative approach to discriminate multiple protein datasets (multiCM) and to measure enrichments in gene ontology terms (cleverGO) using semantic similarities.

Results

We illustrate the powerfulness of our approach by investigating the links between RNA-binding ability and other protein features, such as structural disorder and aggregation, in S. cerevisiae, C. elegans, M. musculus and H. sapiens. Our results are in striking agreement with available experimental evidence and unravel features that are key to understand the mechanisms regulating cellular homeostasis.

Conclusions

In an intuitive way, multiCM and cleverGO provide accurate classifications of physico-chemical features and annotations of biological processes, molecular functions and cellular components, which is extremely useful for the discovery and characterization of new trends in protein datasets. The multiCM and cleverGO can be freely accessed on the Web at http://www.tartaglialab.com/cs_multi/submission and http://www.tartaglialab.com/GO_analyser/universal. Each of the pages contains links to the corresponding documentation and tutorial.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2280-z) contains supplementary material, which is available to authorized users.

Digested disorder, Quarterly intrinsic disorder digest (October-November-December, 2013)

This is the 4th issue of the Digested Disorder series that represents reader's digest of the scientific literature on intrinsically disordered proteins. The only 2 criteria for inclusion in this digest are the publication date (a paper should be published within the covered time frame) and topic (a paper should be dedicated to any aspect of protein intrinsic disorder). The current digest issue covers papers published during the fourth quarter of 2013; i.e. during the period of October, November, and December of 2013. Similar to previous issues, the papers are grouped hierarchically by topics they cover, and for each of the included paper a short description is given on its major findings.

Malleable nature of mRNA-protein compositional complementarity and its functional significance

It has recently been demonstrated that nucleobase-density profiles of typical mRNA coding sequences exhibit a complementary relationship with nucleobase-interaction propensity profiles of their cognate protein sequences. This finding supports the idea that the genetic code developed in response to direct binding interactions between amino acids and appropriate nucleobases, but also suggests that present-day mRNAs and their cognate proteins may be physicochemically complementary to each other and bind. Here, we computationally recode complete Methanocaldococcus jannaschii, Escherichia coli and Homo sapiens mRNA transcriptomes and analyze how much complementary matching of synonymous mRNAs can vary, while keeping protein sequences fixed. We show that for most proteins there exist cognate mRNAs that improve, but also significantly worsen the level of native matching (e.g. by 1.8 viz. 7.6 standard deviations on average for H. sapiens, respectively), with the least malleable proteins in this sense being strongly enriched in nuclear localization and DNA-binding functions. Even so, we show that the majority of recodings for most proteins result in pronounced complementarity. Our results suggest that the genetic code was designed for favorable, yet tunable compositional complementarity between mRNAs and their cognate proteins, supporting the hypothesis that the interactions between the two were an important defining element behind the code's origin.

The aggregation of mutant p53 produces prion-like properties in cancer

The tumor suppressor protein p53 loses its function in more than 50% of human malignant tumors. Recent studies have suggested that mutant p53 can form aggregates that are related to loss-of-function effects, negative dominance and gain-of-function effects and cancers with a worsened prognosis. In recent years, several degenerative diseases have been shown to have prion-like properties similar to mammalian prion proteins (PrPs). However, whereas prion diseases are rare, the incidence of these neurodegenerative pathologies is high. Malignant tumors involving mutated forms of the tumor suppressor p53 protein seem to have similar substrata. The aggregation of the entire p53 protein and three functional domains of p53 into amyloid oligomers and fibrils has been demonstrated. Amyloid aggregates of mutant p53 have been detected in breast cancer and malignant skin tumors. Most p53 mutations related to cancer development are found in the DNA-binding domain (p53C), which has been experimentally shown to form amyloid oligomers and fibrils. Several computation programs have corroborated the predicted propensity of p53C to form aggregates, and some of these programs suggest that p53C is more likely to form aggregates than the globular domain of PrP. Overall, studies imply that mutant p53 exerts a dominant-negative regulatory effect on wild-type (WT) p53 and exerts gain-of-function effects when co-aggregating with other proteins such as p63, p73 and acetyltransferase p300. We review here the prion-like behavior of oncogenic p53 mutants that provides an explanation for their dominant-negative and gain-of-function properties and for the high metastatic potential of cancers bearing p53 mutations. The inhibition of the aggregation of p53 into oligomeric and fibrillar amyloids appears to be a promising target for therapeutic intervention in malignant tumor diseases.

Absolute binding-free energies between standard RNA/DNA nucleobases and amino-acid sidechain analogs in different environments

Despite the great importance of nucleic acid-protein interactions in the cell, our understanding of their physico-chemical basis remains incomplete. In order to address this challenge, we have for the first time determined potentials of mean force and the associated absolute binding free energies between all standard RNA/DNA nucleobases and amino-acid sidechain analogs in high- and low-dielectric environments using molecular dynamics simulations and umbrella sampling. A comparison against a limited set of available experimental values for analogous systems attests to the quality of the computational approach and the force field used. Overall, our analysis provides a microscopic picture behind nucleobase/sidechain interaction preferences and creates a unified framework for understanding and sculpting nucleic acid-protein interactions in different contexts. Here, we use this framework to demonstrate a strong relationship between nucleobase density profiles of mRNAs and nucleobase affinity profiles of their cognate proteins and critically analyze a recent hypothesis that the two may be capable of direct, complementary interactions.

The H50Q mutation induces a 10-fold decrease in the solubility of α-synuclein

The conversion of α-synuclein from its intrinsically disordered monomeric state into the fibrillar cross-β aggregates characteristically present in Lewy bodies is largely unknown. The investigation of α-synuclein variants causative of familial forms of Parkinson disease can provide unique insights into the conditions that promote or inhibit aggregate formation. It has been shown recently that a newly identified pathogenic mutation of α-synuclein, H50Q, aggregates faster than the wild-type. We investigate here its aggregation propensity by using a sequence-based prediction algorithm, NMR chemical shift analysis of secondary structure populations in the monomeric state, and determination of thermodynamic stability of the fibrils. Our data show that the H50Q mutation induces only a small increment in polyproline II structure around the site of the mutation and a slight increase in the overall aggregation propensity. We also find, however, that the H50Q mutation strongly stabilizes α-synuclein fibrils by 5.0 ± 1.0 kJ mol⁻¹, thus increasing the supersaturation of monomeric α-synuclein within the cell, and strongly favors its aggregation process. We further show that wild-type α-synuclein can decelerate the aggregation kinetics of the H50Q variant in a dose-dependent manner when coaggregating with it. These last findings suggest that the precise balance of α-synuclein synthesized from the wild-type and mutant alleles may influence the natural history and heterogeneous clinical phenotype of Parkinson disease.

Computational analysis of amino acids and their sidechain analogs in crowded solutions of RNA nucleobases with implications for the mRNA-protein complementarity hypothesis

Many critical processes in the cell involve direct binding between RNAs and proteins, making it imperative to fully understand the physicochemical principles behind such interactions at the atomistic level. Here, we use molecular dynamics simulations and 15 μs of sampling to study the behavior of amino acids and amino acid sidechain analogs in high-concentration aqueous solutions of standard RNA nucleobases. Structural and energetic analysis of simulated systems allows us to derive interaction propensity scales for different amino acid/nucleobase combinations. The derived scales closely match and greatly extend the available experimental data, providing a comprehensive foundation for studying RNA-protein interactions in different contexts. By using these scales, we demonstrate a statistically significant connection between nucleobase composition of human mRNA coding sequences and nucleobase interaction propensities of their cognate protein sequences. For example, pyrimidine density profiles of mRNAs match uracil-propensity profiles of their cognate proteins with a median Pearson correlation coefficient of R = -0.70. Our results provide support for the recently proposed hypotheses that mRNAs and their cognate proteins may be physicochemically complementary to each other and bind, especially if unstructured, with the complementarity level being negatively influenced by mRNA adenine content. Finally, we utilize the derived scales to refine the complementarity hypothesis and closely examine its physicochemical underpinnings.

ccSOL omics: a webserver for solubility prediction of endogenous and heterologous expression in Escherichia coli

Summary: Here we introduce ccSOL omics, a webserver for large-scale calculations of protein solubility. Our method allows (i) proteome-wide predictions; (ii) identification of soluble fragments within each sequences; (iii) exhaustive single-point mutation analysis.

Results: Using coil/disorder, hydrophobicity, hydrophilicity, β-sheet and α-helix propensities, we built a predictor of protein solubility. Our approach shows an accuracy of 79% on the training set (36 990 Target Track entries). Validation on three independent sets indicates that ccSOL omics discriminates soluble and insoluble proteins with an accuracy of 74% on 31 760 proteins sharing <30% sequence similarity.

Availability and implementation:ccSOL omics can be freely accessed on the web at http://s.tartaglialab.com/page/ccsol_group. Documentation and tutorial are available at http://s.tartaglialab.com/static_files/shared/tutorial_ccsol_omics.html.

Contact:gian.tartaglia@crg.es

Supplementary information:Supplementary data are available at Bioinformatics online.

α-Synuclein oligomers distinctively permeabilize complex model membranes

α-Synuclein oligomers are increasingly considered to be responsible for the death of dopaminergic neurons in Parkinson's disease. The toxicity mechanism of α-synuclein oligomers likely involves membrane permeabilization. Even though it is well established that α-synuclein oligomers bind and permeabilize vesicles composed of negatively-charged lipids, little attention has been given to the interaction of oligomers with bilayers of physiologically relevant lipid compositions. We investigated the interaction of α-synuclein with bilayers composed of lipid mixtures that mimic the composition of plasma and mitochondrial membranes. In the present study, we show that monomeric and oligomeric α-synuclein bind to these membranes. The resulting membrane leakage differs from that observed for simple artificial model bilayers. Although the addition of oligomers to negatively-charged lipid vesicles displays fast content release in a bulk permeabilization assay, adding oligomers to vesicles with compositions mimicking mitochondrial membranes shows a much slower loss of content. Oligomers are unable to induce leakage in the artificial plasma membranes, even after long-term incubation. CD experiments indicate that binding to lipid bilayers initially induces conformational changes in both oligomeric and monomeric α-synuclein, which show little change upon long-term incubation of oligomers with membranes. The results of the present study demonstrate that the mitochondrial model membranes are more vulnerable to permeabilization by oligomers than model plasma membranes reconstituted from brain-derived lipids; this preference may imply that increasingly complex membrane components, such as those in the plasma membrane mimic used in the present study, are less vulnerable to damage by oligomers.

The cleverSuite approach for protein characterization: predictions of structural properties, solubility, chaperone requirements and RNA-binding abilities

Motivation: The recent shift towards high-throughput screening is posing new challenges for the interpretation of experimental results. Here we propose the cleverSuite approach for large-scale characterization of protein groups.

Description: The central part of the cleverSuite is the cleverMachine (CM), an algorithm that performs statistics on protein sequences by comparing their physico-chemical propensities. The second element is called cleverClassifier and builds on top of the models generated by the CM to allow classification of new datasets.

Results: We applied the cleverSuite to predict secondary structure properties, solubility, chaperone requirements and RNA-binding abilities. Using cross-validation and independent datasets, the cleverSuite reproduces experimental findings with great accuracy and provides models that can be used for future investigations.

Availability: The intuitive interface for dataset exploration, analysis and prediction is available at http://s.tartaglialab.com/clever_suite.

Contact:gian.tartaglia@crg.es

Supplementary information:Supplementary data are available at Bioinformatics online.

Constitutive patterns of gene expression regulated by RNA-binding proteins

Background

RNA-binding proteins regulate a number of cellular processes, including synthesis, folding, translocation, assembly and clearance of RNAs. Recent studies have reported that an unexpectedly large number of proteins are able to interact with RNA, but the partners of many RNA-binding proteins are still uncharacterized.

Results

We combined prediction of ribonucleoprotein interactions, based on catRAPID calculations, with analysis of protein and RNA expression profiles from human tissues. We found strong interaction propensities for both positively and negatively correlated expression patterns. Our integration of in silico and ex vivo data unraveled two major types of protein–RNA interactions, with positively correlated patterns related to cell cycle control and negatively correlated patterns related to survival, growth and differentiation. To facilitate the investigation of protein–RNA interactions and expression networks, we developed the catRAPID express web server.

Conclusions

Our analysis sheds light on the role of RNA-binding proteins in regulating proliferation and differentiation processes, and we provide a data exploration tool to aid future experimental studies.

Discovery of protein–RNA networks

We review the latest advances and future challenges in experimental and computational investigation of protein–RNA networks.

catRAPID omics: a web server for large-scale prediction of protein-RNA interactions

Summary: Here we introduce catRAPID omics, a server for large-scale calculations of protein–RNA interactions. Our web server allows (i) predictions at proteomic and transcriptomic level; (ii) use of protein and RNA sequences without size restriction; (iii) analysis of nucleic acid binding regions in proteins; and (iv) detection of RNA motifs involved in protein recognition.

Results: We developed a web server to allow fast calculation of ribonucleoprotein associations in Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, Homo sapiens, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae and Xenopus tropicalis (custom libraries can be also generated). The catRAPID omics was benchmarked on the recently published RNA interactomes of Serine/arginine-rich splicing factor 1 (SRSF1), Histone-lysine N-methyltransferase EZH2 (EZH2), TAR DNA-binding protein 43 (TDP43) and RNA-binding protein FUS (FUS) as well as on the protein interactomes of U1/U2 small nucleolar RNAs, X inactive specific transcript (Xist) repeat A region (RepA) and Crumbs homolog 3 (CRB3) 3′-untranslated region RNAs. Our predictions are highly significant (P < 0.05) and will help the experimentalist to identify candidates for further validation.

Availability:catRAPID omics can be freely accessed on the Web at http://s.tartaglialab.com/catrapid/omics. Documentation, tutorial and FAQs are available at http://s.tartaglialab.com/page/catrapid_group.

Contact:gian.tartaglia@crg.eu