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Flaviviruses pose significant global health threats, infecting over 300 million people annually. Among their evasion strategies, the production of subgenomic flaviviral RNAs (sfRNAs) from the 3′ UTR of viral genomes is particularly notable. Utilizing a comprehensive in silico approach with the catRAPID algorithm, we analyzed over 300,000 interactions between sfRNAs and human proteins derived from more than 8000 flavivirus genomes, including Dengue, Zika, Yellow Fever, West Nile, and Japanese Encephalitis viruses. By providing the first extensive atlas of sfRNA interactions, we offer new insights into how flaviviruses can manipulate host cellular machinery to facilitate viral survival and persistence. Our study not only validated known interactions but also revealed novel human proteins that could be involved in sfRNA-mediated host defense evasion, including helicases, splicing factors, and chemokines. These findings significantly expand the known interactome of sfRNAs with human proteins, underscoring their role in modulating host cellular pathways. Intriguingly, we predict interaction with stress granules, a critical component of the cellular response to viral infection, suggesting a mechanism by which flaviviruses inhibit their formation to evade host defenses. Moreover, a set of highly-interacting proteins in common among the sfRNAs showed predictive power to identify sfRNA-forming regions, highlighting how protein signatures could be used to annotate viruses. This atlas not only serves as a resource for exploring therapeutic targets but also aids in the identification of sfRNA biomarkers for improved flavivirus diagnostics.

Enhanced stabilization of protein structures via the presence of inert osmolytes is a key mechanism adopted both by physiological systems and in biotechnological applications. While the intrinsic stability of proteins is ultimately fixed by their amino acid composition and organization, the interactions between osmolytes and proteins together with their concentrations introduce an additional layer of complexity and in turn, a method of modulating protein stability. Here, we combined experimental measurements with molecular dynamics simulations and graph-theory-based analyses to predict the stabilizing/destabilizing effects of different kinds of osmolytes on proteins during heat-mediated denaturation. We found that (i) proteins in solution with stability-enhancing osmolytes tend to have more compact interaction networks than those assumed in the presence of destabilizing osmolytes; (ii) a strong negative correlation (R = -0.85) characterizes the relationship between the melting temperature Tm and the preferential interaction coefficient defined by the radial distribution functions of osmolytes and water around the protein and (iii) a positive correlation exists between osmolyte-osmolyte clustering and the extent of preferential exclusion from the local domain of the protein, suggesting that exclusion may be driven by enhanced steric hindrance of aggregated osmolytes.

Abstract Background The Pharyngeal Endoderm (PE) is an extremely relevant developmental tissue, serving as the progenitor for the esophagus, parathyroids, thyroids, lungs, and thymus. While several studies have highlighted the importance of PE cells, a detailed transcriptional and epigenetic characterization of this important developmental stage is still missing, especially in humans, due to technical and ethical constraints pertaining to its early formation. Results Here we fill this knowledge gap by developing an in vitro protocol for the derivation of PE-like cells from human Embryonic Stem Cells (hESCs) and by providing an integrated multi-omics characterization. Our PE-like cells robustly express PE markers and are transcriptionally homogenous and similar to in vivo mouse PE cells. In addition, we define their epigenetic landscape and dynamic changes in response to Retinoic Acid by combining ATAC-Seq and ChIP-Seq of histone modifications. The integration of multiple high-throughput datasets leads to the identification of new putative regulatory regions and to the inference of a Retinoic Acid-centered transcription factor network orchestrating the development of PE-like cells. Conclusions By combining hESCs differentiation with computational genomics, our work reveals the epigenetic dynamics that occur during human PE differentiation, providing a solid resource and foundation for research focused on the development of PE derivatives and the modeling of their developmental defects in genetic syndromes.

RNA modifications play a crucial role in regulating gene expression by altering RNA structure and modulating interactions with RNA-binding proteins (RBPs). In this study, we explore the impact of specific RNA chemical modifications—N6-methyladenosine (m⁶A), A-to-I editing, and pseudouridine (Ψ)—on RNA secondary structure and protein-RNA interactions. Utilizing genome-wide data, including RNA secondary structure predictions and protein-RNA interaction datasets, we classify proteins into distinct categories based on their binding behaviors: modification specific and structure independent, or modification unspecific and structure dependent. For instance, m⁶A readers such as YTHDF2 exhibit modification-specific and structure-independent binding, consistently recognizing m⁶A regardless of structural changes. Conversely, proteins such as U2AF2 display modification-unspecific and structure-dependent behavior, altering their binding preferences in response to structural changes induced by different modifications. A-to-I editing, which causes significant structural changes, typically reduces protein interactions, while Ψ enhances RNA structural stability, albeit with variable effects on protein binding. To predict these interactions, we developed the catRAPID 2.2 RNA modifications algorithm, which computes the effects of RNA modifications on protein-RNA binding propensities. This algorithm enables the prediction and analysis of RNA modifications’ impact on protein interactions, offering new insights into RNA biology and engineering.

Abstract RNA-binding proteins are central for many biological processes and their characterization has demonstrated a broad range of functions as well as a wide spectrum of target structures. RNA G-quadruplexes are important regulatory elements occurring in both coding and non-coding transcripts, yet our knowledge of their structure-based interactions is at present limited. Here, using theoretical predictions and experimental approaches, we show that many chromatin-binding proteins bind to RNA G-quadruplexes, and we classify them based on their RNA G-quadruplex-binding potential. Combining experimental identification of nuclear RNA G-quadruplex-binding proteins with computational approaches, we build a prediction tool that assigns probability score for a nuclear protein to bind RNA G-quadruplexes. We show that predicted G-quadruplex RNA-binding proteins exhibit a high degree of protein disorder and hydrophilicity and suggest involvement in both transcription and phase-separation into membrane-less organelles. Finally, we present the G4-Folded/UNfolded Nuclear Interaction Explorer System (G4-FUNNIES) for estimating RNA G4-binding propensities at http://service.tartaglialab.com/new_submission/G4FUNNIES .

Summary: Epitranscriptomics represents a further layer of gene expression regulation. Specifically, N6-methyladenosine (m6A) regulates RNA maturation, stability, degradation, and translation. Regarding microRNAs (miRNAs), while it has been reported that m6A impacts their biogenesis, the functional effects on mature miRNAs remain unclear. Here, we show that m6A modification on specific miRNAs weakens their coupling to AGO2, impairs their function on target mRNAs, determines their delivery into extracellular vesicles (EVs), and provides functional information to receiving cells. Mechanistically, the intracellular functional impairment is caused by m6A-mediated inhibition of AGO2/miRNA interaction, the EV loading is favored by m6A-mediated recognition by the RNA-binding protein (RBP) hnRNPA2B1, and the EV-miRNA function in the receiving cell requires their FTO-mediated demethylation. Consequently, cells express specific miRNAs that do not impact endogenous transcripts but provide regulatory information for cell-to-cell communication. This highlights that a further level of complexity should be considered when relating cellular dynamics to specific miRNAs.

Abstract We introduce Promoter-Enhancer-Guided Interaction Networks (PENGUIN), a method for studying protein-protein interaction (PPI) networks within enhancer-promoter interactions. PENGUIN integrates H3K27ac-HiChIP data with tissue-specific PPIs to define enhancer-promoter PPI networks (EPINs). We validated PENGUIN using cancer (LNCaP) and benign (LHSAR) prostate cell lines. Our analysis detected EPIN clusters enriched with the architectural protein CTCF, a regulator of enhancer-promoter interactions. CTCF presence was coupled with the prevalence of prostate cancer (PrCa) single nucleotide polymorphisms (SNPs) within the same EPIN clusters, suggesting functional implications in PrCa. Within the EPINs displaying enrichments in both CTCF and PrCa SNPs, we also show enrichment in oncogenes. We substantiated our identified SNPs through CRISPR/Cas9 knockout and RNAi screens experiments. Here we show that PENGUIN provides insights into the intricate interplay between enhancer-promoter interactions and PPI networks, which are crucial for identifying key genes and potential intervention targets. A dedicated server is available at https://penguin.life.bsc.es/ .

Abstract Biomolecular condensates serve as membrane-less compartments within cells, concentrating proteins and nucleic acids to facilitate precise spatial and temporal orchestration of various biological processes. The diversity of these processes and the substantial variability in condensate characteristics present a formidable challenge for quantifying their molecular dynamics, surpassing the capabilities of conventional microscopy. Here, we show that our single-photon microscope provides a comprehensive live-cell spectroscopy and imaging framework for investigating biomolecular condensation. Leveraging a single-photon detector array, single-photon microscopy enhances the potential of quantitative confocal microscopy by providing access to fluorescence signals at the single-photon level. Our platform incorporates photon spatiotemporal tagging, which allowed us to perform time-lapse super-resolved imaging for molecular sub-diffraction environment organization with simultaneous monitoring of molecular mobility, interactions, and nano-environment properties through fluorescence lifetime fluctuation spectroscopy. This integrated correlative study reveals the dynamics and interactions of RNA-binding proteins involved in forming stress granules, a specific type of biomolecular condensates, across a wide range of spatial and temporal scales. Our versatile framework opens up avenues for exploring a broad spectrum of biomolecular processes beyond the formation of membrane-less organelles.

Abstract Long Interspersed Nuclear Elements-1s (L1s) are transposable elements that constitute most of the genome’s transcriptional output yet have still largely unknown functions. Here we show that L1s are required for proper mouse brain corticogenesis operating as regulatory long non-coding RNAs. They contribute to the regulation of the balance between neuronal progenitors and differentiation, the migration of post-mitotic neurons and the proportions of different cell types. In cortical cultured neurons, L1 RNAs are mainly associated to chromatin and interact with the Polycomb Repressive Complex 2 (PRC2) protein subunits enhancer of Zeste homolog 2 (Ezh2) and suppressor of zeste 12 (Suz12). L1 RNA silencing influences PRC2’s ability to bind a portion of its targets and the deposition of tri-methylated histone H3 (H3K27me3) marks. Our results position L1 RNAs as crucial signalling hubs for genome-wide chromatin remodelling, enabling the fine-tuning of gene expression during brain development and evolution.

Annexin A11 (ANXA11) is a calcium-dependent phospholipid-binding protein belonging to the annexin protein family and implicated in the neurodegenerative amyotrophic lateral sclerosis. Structurally, ANXA11 contains a conserved calcium-binding C-terminal domain common to all annexins and a putative intrinsically unfolded N-terminus specific for ANXA11. Little is known about the structure and functions of this region of the protein. By analogy with annexin A1, it was suggested that residues 38 to 59 within the ANXA11 N-terminus could form a helical region that would be involved in interactions. Interestingly, this region contains residues that, when mutated, may lead to clinical manifestations. In the present study, we have studied the structural features of the full-length protein with special attention to the N-terminal region using a combination of biophysical techniques which include nuclear magnetic resonance and small angle X-ray scattering. We show that the N-terminus is intrinsically disordered and that the overall features of the protein are not markedly affected by the presence of calcium. We also analyzed the 38–59 helix hypothesis using synthetic peptides spanning both the wild-type sequence and clinically relevant mutations. We show that the peptides have a remarkable character typical of a native helix and that mutations do not alter the behaviour suggesting that they are required for interactions rather than being structurally important. Our work paves the way to a more thorough understanding of the ANXA11 functions.

Pathogenic variants in the GNAO1 gene, encoding the alpha subunit of an inhibitory heterotrimeric guanine nucleotide-binding protein (Go) highly expressed in the mammalian brain, have been linked to encephalopathy characterized by different combinations of neurological symptoms, including developmental delay, hypotonia, epilepsy and hyperkinetic movement disorder with life-threatening paroxysmal exacerbations. Currently, there are only symptomatic treatments, and little is known about the pathophysiology of GNAO1-related disorders. Here, we report the characterization of a new in vitro model system based on patient-derived induced pluripotent stem cells (hiPSCs) carrying the recurrent p.G203R amino acid substitution in Gαo, and a CRISPR-Cas9-genetically corrected isogenic control line. RNA-Seq analysis highlighted aberrant cell fate commitment in neuronal progenitor cells carrying the p.G203R pathogenic variant. Upon differentiation into cortical neurons, patients’ cells showed reduced expression of early neural genes and increased expression of astrocyte markers, as well as premature and defective differentiation processes leading to aberrant formation of neuronal rosettes. Of note, comparable defects in gene expression and in the morphology of neural rosettes were observed in hiPSCs from an unrelated individual harboring the same GNAO1 variant. Functional characterization showed lower basal intracellular free calcium concentration ([Ca2+]i), reduced frequency of spontaneous activity, and a smaller response to several neurotransmitters in 40- and 50-days differentiated p.G203R neurons compared to control cells. These findings suggest that the GNAO1 pathogenic variant causes a neurodevelopmental phenotype characterized by aberrant differentiation of both neuronal and glial populations leading to a significant alteration of neuronal communication and signal transduction.

Abstract Cells must coordinate the activation of thousands of replication origins dispersed throughout their genome. Active transcription is known to favor the formation of mammalian origins, although the role that RNA plays in this process remains unclear. We show that the ORC1 subunit of the human Origin Recognition Complex interacts with RNAs transcribed from genes with origins in their transcription start sites (TSSs), displaying a positive correlation between RNA binding and origin activity. RNA depletion, or the use of ORC1 RNA-binding mutant, result in inefficient activation of proximal origins, linked to impaired ORC1 chromatin release. ORC1 RNA binding activity resides in its intrinsically disordered region, involved in intra- and inter-molecular interactions, regulation by phosphorylation, and phase-separation. We show that RNA binding favors ORC1 chromatin release, by regulating its phosphorylation and subsequent degradation. Our results unveil a non-coding function of RNA as a dynamic component of the chromatin, orchestrating the activation of replication origins.

The development of methods able to modulate the binding affinity between proteins and peptides is of paramount biotechnological interest in view of a vast range of applications that imply designed polypeptides capable to impair or favour Protein-Protein Interactions. Here, we applied a peptide design algorithm based on shape complementarity optimization and electrostatic compatibility and provided the first experimental in vitro proof of the efficacy of the design algorithm. Focusing on the interaction between the SARS-CoV-2 Spike Receptor-Binding Domain (RBD) and the human angiotensin-converting enzyme 2 (ACE2) receptor, we extracted a 23-residues long peptide that structurally mimics the major interacting portion of the ACE2 receptor and designed in silico five mutants of such a peptide with a modulated affinity. Remarkably, experimental KD measurements, conducted using biolayer interferometry, matched the in silico predictions. Moreover, we investigated the molecular determinants that govern the variation in binding affinity through molecular dynamics simulation, by identifying the mechanisms driving the different values of binding affinity at a single residue level. Finally, the peptide sequence with the highest affinity, in comparison with the wild type peptide, was expressed as a fusion protein with human H ferritin (HFt) 24-mer. Solution measurements performed on the latter constructs confirmed that peptides still exhibited the expected trend, thereby enhancing their efficacy in RBD binding. Altogether, these results indicate the high potentiality of this general method in developing potent high-affinity vectors for hindering/enhancing protein-protein associations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a positive single-stranded RNA virus, engages in complex interactions with host cell proteins throughout its life cycle. While these interactions enable the host to recognize and inhibit viral replication, they also facilitate essential viral processes such as transcription, translation, and replication. Many aspects of these virus-host interactions remain poorly understood. Here, we employed the catRAPID algorithm and utilized the RNA-protein interaction detection coupled with mass spectrometry technology to predict and validate the host proteins that specifically bind to the highly structured 5′ and 3′ terminal regions of the SARS-CoV-2 RNA. Among the interactions identified, we prioritized pseudouridine synthase PUS7, which binds to both ends of the viral RNA. Using nanopore direct RNA sequencing, we discovered that the viral RNA undergoes extensive post-transcriptional modifications. Modified consensus regions for PUS7 were identified at both terminal regions of the SARS-CoV-2 RNA, including one in the viral transcription regulatory sequence leader. Collectively, our findings offer insights into host protein interactions with the SARS-CoV-2 UTRs and highlight the likely significance of pseudouridine synthases and other post-transcriptional modifications in the viral life cycle. This new knowledge enhances our understanding of virus-host dynamics and could inform the development of targeted therapeutic strategies.

Here, the authors generated an artificial RNA molecule, or aptamer, specific for the Amyotrophic Lateral Sclerosis protein TDP-43. By interacting avidly with its target, the aptamer can be exploited to track TDP-43 phase transition in vitro and in cells.

SINEUPs are a novel class of natural and synthetic non-coding antisense RNA molecules able to increase the translation of a target mRNA. They present a modular organization comprising an unstructured antisense target-specific domain, which sets the specificity of each individual SINEUP, and a structured effector domain, which is responsible for the translation enhancement. In order to design a fully functional in vitro transcribed SINEUP for therapeutics applications, SINEUP RNAs were synthesized in vitro with a variety of chemical modifications and screened for their activity on endogenous target mRNA upon transfection. Three combinations of modified ribonucleotides—2′O methyl-ATP (Am), N6 methyl-ATP (m6A), and pseudo-UTP (ψ)—conferred SINEUP activity to naked RNA. The best combination tested in this study was fully modified with m6A and ψ. Aside from functionality, this combination conferred improved stability upon transfection and higher thermal stability. Common structural determinants of activity were identified by circular dichroisms, defining a core functional structure that is achieved with different combinations of modifications.

Identifying human proteins that interact with SARS-CoV-2 genome is important to understand its replication and to identify therapeutic strategies. Recent studies have unveiled protein interactions of SARS-COV-2 in different cell lines and through a number of high-throughput approaches. Here, we carried out a comparative analysis of four experimental and one computational studies to characterize the interactions of SARS-CoV-2 genomic RNA. Although hundreds of interactors have been identified, only twenty-one appear in all the experiments and show a strong propensity to bind. This set of interactors includes stress granule forming proteins, pre-mRNA regulators and elements involved in the replication process. Our calculations indicate that DDX3X and several editases bind the 5′ end of SARS-CoV-2, a regulatory region previously reported to attract a large number of proteins. The small overlap among experimental datasets suggests that SARS-CoV-2 genome establishes stable interactions only with few interactors, while many proteins bind less tightly. In analogy to what has been previously reported for Xist non-coding RNA, we propose a mechanism of phase separation through which SARS-CoV-2 progressively sequesters human proteins hijacking the host immune response.

Human serine hydroxymethyltransferase (SHMT) regulates the serine-glycine one carbon metabolism and plays a role in cancer metabolic reprogramming. Two SHMT isozymes are acting in the cell: SHMT1 encoding the cytoplasmic isozyme, and SHMT2 encoding the mitochondrial one. Here we present a molecular model built on experimental data reporting the interaction between SHMT1 protein and SHMT2 mRNA, recently discovered in lung cancer cells. Using a stochastic dynamic model, we show that RNA moieties dynamically regulate serine and glycine concentration, shaping the system behaviour. For the first time we observe an active functional role of the RNA in the regulation of the serine-glycine metabolism and availability, which unravels a complex layer of regulation that cancer cells exploit to fine tune amino acids availability according to their metabolic needs. The quantitative model, complemented by an experimental validation in the lung adenocarcinoma cell line H1299, exploits RNA molecules as metabolic switches of the SHMT1 activity. Our results pave the way for the development of RNA-based molecules able to unbalance serine metabolism in cancer cells.

Since the beginning of the Covid19 pandemic, many efforts have been devoted to identifying approaches to neutralize SARS-CoV-2 replication within the host cell. A promising strategy to block the infection consists of using a mutant of the human receptor angiotensin-converting enzyme 2 (ACE2) as a decoy to compete with endogenous ACE2 for the binding to the SARS-CoV-2 Spike protein, which decreases the ability of the virus to enter the host cell. Here, using a computational framework based on the 2D Zernike formalism we investigate details of the molecular binding and evaluate the changes in ACE2-Spike binding compatibility upon mutations occurring in the ACE2 side of the molecular interface. We demonstrate the efficacy of our method by comparing our results with experimental binding affinities changes upon ACE2 mutations, separating ones that increase or decrease binding affinity with an Area Under the ROC curve ranging from 0.66 to 0.93, depending on the magnitude of the effects analyzed. Importantly, the iteration of our approach leads to the identification of a set of ACE2 mutants characterized by an increased shape complementarity with Spike. We investigated the physico-chemical properties of these ACE2 mutants and propose them as bona fide candidates for Spike recognition.

Abstract Protein aggregation is a pathological feature of neurodegenerative disorders. We previously demonstrated that protein inclusions in the brain are composed of supersaturated proteins, which are abundant and aggregation-prone, and form a metastable subproteome. It is not yet clear, however, whether this phenomenon is also associated with non-neuronal protein conformational disorders. To respond to this question, we analyzed proteomic datasets from biopsies of patients with genetic and acquired protein aggregate myopathy (PAM) by quantifying the changes in composition, concentration and aggregation propensity of proteins in the fibers containing inclusions and those surrounding them. We found that a metastable subproteome is present in skeletal muscle from healthy patients. The expression of this subproteome escalate as proteomic samples are taken more proximal to the pathologic inclusion, eventually exceeding its solubility limits and aggregating. While most supersaturated proteins decrease or maintain steady abundance across healthy fibers and inclusion-containing fibers, proteins within the metastable subproteome rise in abundance, suggesting that they escape regulation. Taken together, our results show in the context of a human conformational disorder that the supersaturation of a metastable subproteome underlies widespread aggregation and correlates with the histopathological state of the tissue.

TDP43 aggregates are a hallmark of amyotrophic lateral sclerosis. By using deep mutagenesis to measure the toxicity of more than 50,000 mutations in the prion domain of TDP43, the authors conclude that mutations that increase toxicity promote formation of liquid-like condensates, while aggregation of TDP43 is protective for the cell.

Interactions between protein and RNA occur on a large scale, and are often studied from a proteincentric point of view. Here the authors show that the number and strength of RNA-protein interactions correlate with the amount of RNA structure, which impacts the biological activity of the transcript.

Solubility is a requirement for many cellular processes. Loss of solubility and aggregation can lead to the partial or complete abrogation of protein function. Thus, understanding the relationship between protein evolution and aggregation is an important goal. Here, we analysed two deep mutational scanning experiments to investigate the role of protein aggregation in molecular evolution. In one data set, mutants of a protein involved in RNA biogenesis and processing, human TAR DNA binding protein 43 (TDP-43), were expressed in S. cerevisiae. In the other data set, mutants of a bacterial enzyme that controls resistance to penicillins and cephalosporins, TEM-1 beta-lactamase, were expressed in E. coli under the selective pressure of an antibiotic treatment. We found that aggregation differentiates the effects of mutations in the two different cellular contexts. Specifically, aggregation was found to be associated with increased cell fitness in the case of TDP-43 mutations, as it protects the host from aberrant interactions. By contrast, in the case of TEM-1 beta-lactamase mutations, aggregation is linked to a decreased cell fitness due to inactivation of protein function. Our study shows that aggregation is an important context-dependent constraint of molecular evolution and opens up new avenues to investigate the role of aggregation in the cell.

The interaction between polycomb-repressive complexes 1/2 (PRC1/2) and long non-coding RNA (lncRNA), such as the X inactive specific transcript Xist and the HOX transcript antisense RNA (HOTAIR), has been the subject of intense debate. While cross-linking, immuno-precipitation and super-resolution microscopy argue against direct interaction of Polycomb with some lncRNAs, there is increasing evidence supporting the ability of both PRC1 and PRC2 to functionally associate with RNA. Recent data indicate that these interactions are in most cases spurious, but nonetheless crucial for a number of cellular activities. In this review, we suggest that while PRC1/2 recruitment by HOTAIR might be direct, in the case of Xist, it might occur indirectly and, at least in part, through the process of liquid–liquid phase separation. We present recent models of lncRNA-mediated PRC1/2 recruitment to their targets and describe potential RNA-mediated roles in the three-dimensional organization of the nucleus.

Fragile X-associated tremor/ataxia syndrome (FXTAS) is a late-onset neurodegenerative monogenetic disorder affecting carriers of premutation (PM) forms of the FMR1 gene, resulting in a progressive development of tremors, ataxia, and neuropsychological problems. This highly disabling disease is quite common in the general population with an estimation of about 20 million PM carriers worldwide. The chances of developing FXTAS increase dramatically with age, with about 45% of male carriers over the age of 50 being affected. Both the gene and pathogenic trigger, a mutant expansion of CGG RNA, causing FXTAS are known. This makes it an interesting disease to develop targeted therapeutic interventions for. Yet, no such interventions are available at this moment. Here we discuss in silico, in vitro, and in vivo approaches and how they have been used to identify the molecular determinants of FXTAS pathology. These approaches have yielded substantial information about FXTAS pathology and, consequently, many markers have emerged to play a key role in understanding the disease mechanism. Integration of the different approaches is expected to provide crucial information about the value of these markers as either therapeutic target or biomarker, essential to monitor therapeutic interventions in the future.

Methods for time series prediction and classification of gene regulatory networks (GRNs) from gene expression data have been treated separately so far. The recent emergence of attention-based recurrent neural network (RNN) models boosted the interpretability of RNN parameters, making them appealing for the understanding of gene interactions. In this work, we generated synthetic time series gene expression data from a range of archetypal GRNs and we relied on a dual attention RNN to predict the gene temporal dynamics. We show that the prediction is extremely accurate for GRNs with different architectures. Next, we focused on the attention mechanism of the RNN and, using tools from graph theory, we found that its graph properties allow one to hierarchically distinguish different architectures of the GRN. We show that the GRN responded differently to the addition of noise in the prediction by the RNN and we related the noise response to the analysis of the attention mechanism. In conclusion, this work provides a way to understand and exploit the attention mechanism of RNNs and it paves the way to RNN-based methods for time series prediction and inference of GRNs from gene expression data.

Many of the molecular mechanisms underlying the pathological aggregation of proteins observed in neurodegenerative diseases are still not fully understood. Among the aggregate-associated diseases, Amyotrophic Lateral Sclerosis (ALS) is of relevant importance. In fact, although understanding the processes that cause the disease is still an open challenge, its relationship with protein aggregation is widely known. In particular, human TDP-43, an RNA/DNA binding protein, is a major component of the pathological cytoplasmic inclusions observed in ALS patients. Indeed, the deposition of the phosphorylated full-length TDP-43 in spinal cord cells has been widely studied. Moreover, it has also been shown that the brain cortex presents an accumulation of phosphorylated C-terminal fragments (CTFs). Even if it is debated whether the aggregation of CTFs represents a primary cause of ALS, it is a hallmark of TDP-43 related neurodegeneration in the brain. Here, we investigate the CTFs aggregation process, providing a computational model of interaction based on the evaluation of shape complementarity at the molecular interfaces. To this end, extensive Molecular Dynamics (MD) simulations were conducted for different types of protein fragments, with the aim of exploring the equilibrium conformations. Adopting a newly developed approach based on Zernike polynomials, able to find complementary regions in the molecular surface, we sampled a large set of solvent-exposed portions of CTFs structures as obtained from MD simulations. Our analysis proposes and assesses a set of possible association mechanisms between the CTFs, which could drive the aggregation process of the CTFs. To further evaluate the structural details of such associations, we perform molecular docking and additional MD simulations to propose possible complexes and assess their stability, focusing on complexes whose interacting regions are both characterized by a high shape complementarity and involve β3 and β5 strands at their interfaces.

Multiple human diseases are associated with a liquid-to-solid phase transition resulting in the formation of amyloid fibers or protein aggregates. Here, we present an alternative mechanism for cellular toxicity based on a concentration-dependent liquid-liquid demixing. Analyzing proteins that are toxic when their concentration is increased in yeast reveals that they share physicochemical properties with proteins that participate in physiological liquid-liquid demixing in the cell. Increasing the concentration of one of these proteins indeed results in the formation of cytoplasmic foci with liquid properties. Demixing occurs at the onset of toxicity and titrates proteins and mRNAs from the cytoplasm. Focus formation is reversible, and resumption of growth occurs as the foci dissolve as protein concentration falls. Preventing demixing abolishes the dosage sensitivity of the protein. We propose that triggering inappropriate liquid phase separation may be an important cause of dosage sensitivity and a determinant of human disease.

Summary: Recent evidence indicates that specific RNAs promote the formation of ribonucleoprotein condensates by acting as scaffolds for RNA-binding proteins (RBPs). We systematically investigated RNA-RBP interaction networks to understand ribonucleoprotein assembly. We found that highly contacted RNAs are structured, have long UTRs, and contain nucleotide repeat expansions. Among the RNAs with such properties, we identified the FMR1 3′ UTR that harbors CGG expansions implicated in fragile X-associated tremor/ataxia syndrome (FXTAS). We studied FMR1 binding partners in silico and in vitro and prioritized the splicing regulator TRA2A for further characterization. In a FXTAS cellular model, we validated the TRA2A-FMR1 interaction and investigated implications of its sequestration at both transcriptomic and post-transcriptomic levels. We found that TRA2A co-aggregates with FMR1 in a FXTAS mouse model and in post-mortem human samples. Our integrative study identifies key components of ribonucleoprotein aggregates, providing links to neurodegenerative disease and allowing the discovery of therapeutic targets. : Cid-Samper et al. analyze protein-RNA networks and identify properties of RNA scaffolds within biological condensates. They find that CGG repeats in the 3′ UTR of FMR1 attract several proteins, including the splicing factor TRA2A that co-aggregates in fragile X-associated tremor/ataxia syndrome (FXTAS). Keywords: phase separation, scaffolding RNA, CGG repeat expansion, FMR1 premutation, fragile X-associated tremor/ataxia syndrome, FXTAS, RNA aggregates, RNA binding proteins, RBP, TRA2A splicing regulator, neurodegeneration

To compare the secondary structure profiles of RNA molecules we developed the CROSSalign method. CROSSalign is based on the combination of the Computational Recognition Of Secondary Structure (CROSS) algorithm to predict the RNA secondary structure profile at single-nucleotide resolution and the Dynamic Time Warping (DTW) method to align profiles of different lengths. We applied CROSSalign to investigate the structural conservation of long non-coding RNAs such as XIST and HOTAIR as well as ssRNA viruses including HIV. CROSSalign performs pair-wise comparisons and is able to find homologs between thousands of matches identifying the exact regions of similarity between profiles of different lengths. In a pool of sequences with the same secondary structure CROSSalign accurately recognizes repeat A of XIST and domain D2 of HOTAIR and outperforms other methods based on covariance modeling. The algorithm is freely available at the webpage http://service.tartaglialab.com//new_submission/crossalign.

The maintenance of protein solubility is a fundamental aspect of cellular homeostasis because protein aggregation is associated with a wide variety of human diseases. Numerous proteins unrelated in sequence and structure, however, can misfold and aggregate, and widespread aggregation can occur in living systems under stress or aging. A crucial question in this context is why only certain proteins appear to aggregate readily in vivo, whereas others do not. We identify here the proteins most vulnerable to aggregation as those whose cellular concentrations are high relative to their solubilities. We find that these supersaturated proteins represent a metastable subproteome involved in pathological aggregation during stress and aging and are overrepresented in biochemical processes associated with neurodegenerative disorders. Consequently, such cellular processes become dysfunctional when the ability to keep intrinsically supersaturated proteins soluble is compromised. Thus, the simultaneous analysis of abundance and solubility can rationalize the diverse cellular pathologies linked to neurodegenerative diseases and aging.

Cellular chaperone networks prevent potentially toxic protein aggregation and ensure proteome integrity. Here, we used Escherichia coli as a model to understand the organization of these networks, focusing on the cooperation of the DnaK system with the upstream chaperone Trigger factor (TF) and the downstream GroEL. Quantitative proteomics revealed that DnaK interacts with at least ∼700 mostly cytosolic proteins, including ∼180 relatively aggregation-prone proteins that utilize DnaK extensively during and after initial folding. Upon deletion of TF, DnaK interacts increasingly with ribosomal and other small, basic proteins, while its association with large multidomain proteins is reduced. DnaK also functions prominently in stabilizing proteins for subsequent folding by GroEL. These proteins accumulate on DnaK upon GroEL depletion and are then degraded, thus defining DnaK as a central organizer of the chaperone network. Combined loss of DnaK and TF causes proteostasis collapse with disruption of GroEL function, defective ribosomal biogenesis, and extensive aggregation of large proteins.

BACKGROUND:The conversion of soluble peptides and proteins into polymeric amyloid structures is a hallmark of many age-related degenerative disorders, including Alzheimer's disease, type II diabetes and a variety of systemic amyloidoses. We report here that amyloid formation is linked to another major age-related phenomenon--prostate tissue remodelling in middle-aged and elderly men. METHODOLOGY/PRINCIPAL FINDINGS:By using multidisciplinary analysis of corpora amylacea inclusions in prostate glands of patients diagnosed with prostate cancer we have revealed that their major components are the amyloid forms of S100A8 and S100A9 proteins associated with numerous inflammatory conditions and types of cancer. In prostate protease rich environment the amyloids are stabilized by dystrophic calcification and lateral thickening. We have demonstrated that material closely resembling CA can be produced from S100A8/A9 in vitro under native and acidic conditions and shows the characters of amyloids. This process is facilitated by calcium or zinc, both of which are abundant in ex vivo inclusions. These observations were supported by computational analysis of the S100A8/A9 calcium-dependent aggregation propensity profiles. We found DNA and proteins from Escherichia coli in CA bodies, suggesting that their formation is likely to be associated with bacterial infection. CA inclusions were also accompanied by the activation of macrophages and by an increase in the concentration of S100A8/A9 in the surrounding tissues, indicating inflammatory reactions. CONCLUSIONS/SIGNIFICANCE:These findings, taken together, suggest a link between bacterial infection, inflammation and amyloid deposition of pro-inflammatory proteins S100A8/A9 in the prostate gland, such that a self-perpetuating cycle can be triggered and may increase the risk of malignancy in the ageing prostate. The results provide strong support for the prediction that the generic ability of polypeptide chains to convert into amyloids could lead to their involvement in an increasing number of otherwise apparently unrelated diseases, particularly those associated with ageing.

Protein aggregation into amyloid fibrils and protofibrillar aggregates is associated with a number of the most common neurodegenerative diseases. We have established, using a computational approach, that knowledge of the primary sequences of proteins is sufficient to predict their in vitro aggregation propensities. Here we demonstrate, using rational mutagenesis of the Abeta42 peptide based on such computational predictions of aggregation propensity, the existence of a strong correlation between the propensity of Abeta42 to form protofibrils and its effect on neuronal dysfunction and degeneration in a Drosophila model of Alzheimer disease. Our findings provide a quantitative description of the molecular basis for the pathogenicity of Abeta and link directly and systematically the intrinsic properties of biomolecules, predicted in silico and confirmed in vitro, to pathogenic events taking place in a living organism.