Intranuclear inclusions of polyQ-expanded ATXN1 sequester RNA molecules.

Spinocerebellar ataxia type 1 (SCA1) is an autosomal dominant neurodegenerative disease caused by a trinucleotide (CAG) repeat expansion in the ATXN1 gene. It is characterized by the presence of polyglutamine (polyQ) intranuclear inclusion bodies (IIBs) within affected neurons. In order to investigate the impact of polyQ IIBs in SCA1 pathogenesis, we generated a novel protein aggregation model by inducible overexpression of the mutant ATXN1(Q82) isoform in human neuroblastoma SH-SY5Y cells. Moreover, we developed a simple and reproducible protocol for the efficient isolation of insoluble IIBs. Biophysical characterization showed that polyQ IIBs are enriched in RNA molecules which were further identified by next-generation sequencing. Finally, a protein interaction network analysis indicated that sequestration of essential RNA transcripts within ATXN1(Q82) IIBs may affect the ribosome resulting in error-prone protein synthesis and global proteome instability. These findings provide novel insights into the molecular pathogenesis of SCA1, highlighting the role of polyQ IIBs and their impact on critical cellular processes.

The importance of planning CT-based imaging features for machine learning-based prediction of pain response.

Patients suffering from painful spinal bone metastases (PSBMs) often undergo palliative radiation therapy (RT), with an efficacy of approximately two thirds of patients. In this exploratory investigation, we assessed the effectiveness of machine learning (ML) models trained on radiomics, semantic and clinical features to estimate complete pain response. Gross tumour volumes (GTV) and clinical target volumes (CTV) of 261 PSBMs were segmented on planning computed tomography (CT) scans. Radiomics, semantic and clinical features were collected for all patients. Random forest (RFC) and support vector machine (SVM) classifiers were compared using repeated nested cross-validation. The best radiomics classifier was trained on CTV with an area under the receiver-operator curve (AUROC) of 0.62 ± 0.01 (RFC; 95% confidence interval). The semantic model achieved a comparable AUROC of 0.63 ± 0.01 (RFC), significantly below the clinical model (SVM, AUROC: 0.80 ± 0.01); and slightly lower than the spinal instability neoplastic score (SINS; LR, AUROC: 0.65 ± 0.01). A combined model did not improve performance (AUROC: 0,74 ± 0,01). We could demonstrate that radiomics and semantic analyses of planning CTs allowed for limited prediction of therapy response to palliative RT. ML predictions based on established clinical parameters achieved the best results.

Development and Evaluation of MR-Based Radiogenomic Models to Differentiate Atypical Lipomatous Tumors from Lipomas.

BACKGROUND: The aim of this study was to develop and validate radiogenomic models to predict the MDM2 gene amplification status and differentiate between ALTs and lipomas on preoperative MR images. METHODS: MR images were obtained in 257 patients diagnosed with ALTs (n = 65) or lipomas (n = 192) using histology and the MDM2 gene analysis as a reference standard. The protocols included T2-, T1-, and fat-suppressed contrast-enhanced T1-weighted sequences. Additionally, 50 patients were obtained from a different hospital for external testing. Radiomic features were selected using mRMR. Using repeated nested cross-validation, the machine-learning models were trained on radiomic features and demographic information. For comparison, the external test set was evaluated by three radiology residents and one attending radiologist. RESULTS: A LASSO classifier trained on radiomic features from all sequences performed best, with an AUC of 0.88, 70% sensitivity, 81% specificity, and 76% accuracy. In comparison, the radiology residents achieved 60-70% accuracy, 55-80% sensitivity, and 63-77% specificity, while the attending radiologist achieved 90% accuracy, 96% sensitivity, and 87% specificity. CONCLUSION: A radiogenomic model combining features from multiple MR sequences showed the best performance in predicting the MDM2 gene amplification status. The model showed a higher accuracy compared to the radiology residents, though lower compared to the attending radiologist.

The transcriptional co-activator Yap1 promotes adult hippocampal neural stem cell activation.

Most adult hippocampal neural stem cells (NSCs) remain quiescent, with only a minor portion undergoing active proliferation and neurogenesis. The molecular mechanisms that trigger the transition from quiescence to activation are still poorly understood. Here, we found the activity of the transcriptional co-activator Yap1 to be enriched in active NSCs. Genetic deletion of Yap1 led to a significant reduction in the relative proportion of active NSCs, supporting a physiological role of Yap1 in regulating the transition from quiescence to activation. Overexpression of wild-type Yap1 in adult NSCs did not induce NSC activation, suggesting tight upstream control mechanisms, but overexpression of a gain-of-function mutant (Yap1-5SA) elicited cell cycle entry in NSCs and hilar astrocytes. Consistent with a role of Yap1 in NSC activation, single cell RNA sequencing revealed a partial induction of an activated NSC gene expression program. Furthermore, Yap1-5SA expression also induced expression of Taz and other key components of the Yap/Taz regulon that were previously identified in glioblastoma stem cell-like cells. Consequently, dysregulated Yap1 activity led to repression of hippocampal neurogenesis, aberrant cell differentiation, and partial acquisition of a glioblastoma stem cell-like signature.

DNA methylation and cardiovascular disease in humans: a systematic review and database of known CpG methylation sites.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death worldwide and considered one of the most environmentally driven diseases. The role of DNA methylation in response to the individual exposure for the development and progression of CVD is still poorly understood and a synthesis of the evidence is lacking. RESULTS: A systematic review of articles examining measurements of DNA cytosine methylation in CVD was conducted in accordance with PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines. The search yielded 5,563 articles from PubMed and CENTRAL databases. From 99 studies with a total of 87,827 individuals eligible for analysis, a database was created combining all CpG-, gene- and study-related information. It contains 74,580 unique CpG sites, of which 1452 CpG sites were mentioned in ≥ 2, and 441 CpG sites in ≥ 3 publications. Two sites were referenced in ≥ 6 publications: cg01656216 (near ZNF438) related to vascular disease and epigenetic age, and cg03636183 (near F2RL3) related to coronary heart disease, myocardial infarction, smoking and air pollution. Of 19,127 mapped genes, 5,807 were reported in ≥ 2 studies. Most frequently reported were TEAD1 (TEA Domain Transcription Factor 1) and PTPRN2 (Protein Tyrosine Phosphatase Receptor Type N2) in association with outcomes ranging from vascular to cardiac disease. Gene set enrichment analysis of 4,532 overlapping genes revealed enrichment for Gene Ontology molecular function "DNA-binding transcription activator activity" (q = 1.65 × 10-11) and biological processes "skeletal system development" (q = 1.89 × 10-23). Gene enrichment demonstrated that general CVD-related terms are shared, while "heart" and "vasculature" specific genes have more disease-specific terms as PR interval for "heart" or platelet distribution width for "vasculature." STRING analysis revealed significant protein-protein interactions between the products of the differentially methylated genes (p = 0.003) suggesting that dysregulation of the protein interaction network could contribute to CVD. Overlaps with curated gene sets from the Molecular Signatures Database showed enrichment of genes in hemostasis (p = 2.9 × 10-6) and atherosclerosis (p = 4.9 × 10-4). CONCLUSION: This review highlights the current state of knowledge on significant relationship between DNA methylation and CVD in humans. An open-access database has been compiled of reported CpG methylation sites, genes and pathways that may play an important role in this relationship.

The sequence context in poly-alanine regions: structure, function and conservation.

MOTIVATION: Poly-alanine (polyA) regions are protein stretches mostly composed of alanines. Despite their abundance in eukaryotic proteomes and their association to nine inherited human diseases, the structural and functional roles exerted by polyA stretches remain poorly understood. In this work we study how the amino acid context in which polyA regions are settled in proteins influences their structure and function. RESULTS: We identified glycine and proline as the most abundant amino acids within polyA and in the flanking regions of polyA tracts, in human proteins as well as in 17 additional eukaryotic species. Our analyses indicate that the non-structuring nature of these two amino acids influences the α-helical conformations predicted for polyA, suggesting a relevant role in reducing the inherent aggregation propensity of long polyA. Then, we show how polyA position in protein N-termini relates with their function as transit peptides. PolyA placed just after the initial methionine is often predicted as part of mitochondrial transit peptides, whereas when placed in downstream positions, polyA are part of signal peptides. A few examples from known structures suggest that short polyA can emerge by alanine substitutions in α-helices; but evolution by insertion is observed for longer polyA. Our results showcase the importance of studying the sequence context of homorepeats as a mechanism to shape their structure-function relationships. AVAILABILITY AND IMPLEMENTATION: The datasets used and/or analyzed during the current study are available from the corresponding author onreasonable request. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DNMT1 Deficiency Impacts on Plasmacytoid Dendritic Cells in Homeostasis and Autoimmune Disease.

Dendritic cells (DCs) are heterogeneous immune regulators involved in autoimmune diseases. Epigenomic mechanisms orchestrating DC development and DC subset diversification remain insufficiently understood but could be important to modulate DC fate for clinical purposes. By combining whole-genome methylation assessment with the analysis of mice expressing reduced DNA methyltransferase 1 levels, we show that distinct DNA methylation levels and patterns are required for the development of plasmacytoid DC and conventional DC subsets. We provide clonal in vivo evidence for DC lineage establishment at the stem cell level, and we show that a high DNA methylation threshold level is essential for Flt3-dependent survival of DC precursors. Importantly, reducing methylation predominantly depletes plasmacytoid DC and alleviates systemic lupus erythematosus in an autoimmunity mouse model. This study shows how DNA methylation regulates the production of DC subsets and provides a potential rationale for targeting autoimmune disease using hypomethylating agents.

Between Interactions and Aggregates: The PolyQ Balance.

Polyglutamine (polyQ) regions are highly abundant consecutive runs of glutamine residues. They have been generally studied in relation to the so-called polyQ-associated diseases, characterized by protein aggregation caused by the expansion of the polyQ tract via a CAG-slippage mechanism. However, more than 4,800 human proteins contain a polyQ, and only nine of these regions are known to be associated with disease. Computational sequence studies and experimental structure determinations are completing a more interesting picture in which polyQ emerge as a motif for modulation of protein-protein interactions. But long polyQ regions may lead to an excess of interactions, and produce aggregates. Within this mechanistic perspective of polyQ function and malfunction, we discuss polyQ definition and properties such as variable codon usage, sequence and context structure imposition, functional relevance, evolutionary patterns in species-centered analyses, and open resources.

DiseaseLinc: Disease Enrichment Analysis of Sets of Differentially Expressed LincRNAs.

Long intergenic non-coding RNAs (LincRNAs) are long RNAs that do not encode proteins. Functional evidence is lacking for most of them. Their biogenesis is not well-known, but it is thought that many lincRNAs originate from genomic duplication of coding material, resulting in pseudogenes, gene copies that lose their original function and can accumulate mutations. While most pseudogenes eventually stop producing a transcript and become erased by mutations, many of these pseudogene-based lincRNAs keep similarity to the parental gene from which they originated, possibly for functional reasons. For example, they can act as decoys for miRNAs targeting the parental gene. Enrichment analysis of function is a powerful tool to discover the functional effects of a treatment producing differential expression of transcripts. However, in the case of lincRNAs, since their function is not easy to define experimentally, such a tool is lacking. To address this problem, we have developed an enrichment analysis tool that focuses on lincRNAs exploiting their functional association, using as a proxy function that of the parental genes and has a focus on human diseases.

Protein expression profiling suggests relevance of noncanonical pathways in isolated pulmonary embolism.

Patients with isolated pulmonary embolism (PE) have a distinct clinical profile from those with deep vein thrombosis (DVT)-associated PE, with more pulmonary conditions and atherosclerosis. These findings suggest a distinct molecular pathophysiology and the potential involvement of alternative pathways in isolated PE. To test this hypothesis, data from 532 individuals from the Genotyping and Molecular Phenotyping of Venous ThromboEmbolism Project, a multicenter prospective cohort study with extensive biobanking, were analyzed. Targeted, high-throughput proteomics, machine learning, and bioinformatic methods were applied to contrast the acute-phase plasma proteomes of isolated PE patients (n = 96) against those of patients with DVT-associated PE (n = 276) or isolated DVT (n = 160). This resulted in the identification of shared molecular processes between PE phenotypes, as well as an isolated PE-specific protein signature. Shared processes included upregulation of inflammation, response to oxidative stress, and the loss of pulmonary surfactant. The isolated PE-specific signature consisted of 5 proteins: interferon-γ, glial cell line-derived neurotrophic growth factor, polypeptide N-acetylgalactosaminyltransferase 3, peptidyl arginine deiminase type-2, and interleukin-15 receptor subunit α. These proteins were orthogonally validated using cis protein quantitative trait loci. External replication in an independent population-based cohort (n = 5778) further validated the proteomic results and showed that they were prognostic for incident primary isolated PE in individuals without history of VTE (median time to event: 2.9 years; interquartile range: 1.6-4.2 years), supporting their possible involvement in the early pathogenesis. This study has identified molecular overlaps and differences between VTE phenotypes. In particular, the results implicate noncanonical pathways more commonly associated with respiratory and atherosclerotic disease in the acute pathophysiology of isolated PE.

Missing value imputation in proximity extension assay-based targeted proteomics data.

Targeted proteomics utilizing antibody-based proximity extension assays provides sensitive and highly specific quantifications of plasma protein levels. Multivariate analysis of this data is hampered by frequent missing values (random or left censored), calling for imputation approaches. While appropriate missing-value imputation methods exist, benchmarks of their performance in targeted proteomics data are lacking. Here, we assessed the performance of two methods for imputation of values missing completely at random, the previously top-benchmarked 'missForest' and the recently published 'GSimp' method. Evaluation was accomplished by comparing imputed with remeasured relative concentrations of 91 inflammation related circulating proteins in 86 samples from a cohort of 645 patients with venous thromboembolism. The median Pearson correlation between imputed and remeasured protein expression values was 69.0% for missForest and 71.6% for GSimp (p = 5.8e-4). Imputation with missForest resulted in stronger reduction of variance compared to GSimp (median relative variance of 25.3% vs. 68.6%, p = 2.4e-16) and undesired larger bias in downstream analyses. Irrespective of the imputation method used, the 91 imputed proteins revealed large variations in imputation accuracy, driven by differences in signal to noise ratio and information overlap between proteins. In summary, GSimp outperformed missForest, while both methods show good overall imputation accuracy with large variations between proteins.

Dynamics of a Protein Interaction Network Associated to the Aggregation of polyQ-Expanded Ataxin-1.

BACKGROUND: Several experimental models of polyglutamine (polyQ) diseases have been previously developed that are useful for studying disease progression in the primarily affected central nervous system. However, there is a missing link between cellular and animal models that would indicate the molecular defects occurring in neurons and are responsible for the disease phenotype in vivo. METHODS: Here, we used a computational approach to identify dysregulated pathways shared by an in vitro and an in vivo model of ATXN1(Q82) protein aggregation, the mutant protein that causes the neurodegenerative polyQ disease spinocerebellar ataxia type-1 (SCA1). RESULTS: A set of common dysregulated pathways were identified, which were utilized to construct cerebellum-specific protein-protein interaction (PPI) networks at various time-points of protein aggregation. Analysis of a SCA1 network indicated important nodes which regulate its function and might represent potential pharmacological targets. Furthermore, a set of drugs interacting with these nodes and predicted to enter the blood-brain barrier (BBB) was identified. CONCLUSIONS: Our study points to molecular mechanisms of SCA1 linked from both cellular and animal models and suggests drugs that could be tested to determine whether they affect the aggregation of pathogenic ATXN1 and SCA1 disease progression.

The 18S ribosomal RNA m6 A methyltransferase Mettl5 is required for normal walking behavior in Drosophila.

RNA modifications have recently emerged as an important layer of gene regulation. N6-methyladenosine (m6 A) is the most prominent modification on eukaryotic messenger RNA and has also been found on noncoding RNA, including ribosomal and small nuclear RNA. Recently, several m6 A methyltransferases were identified, uncovering the specificity of m6 A deposition by structurally distinct enzymes. In order to discover additional m6 A enzymes, we performed an RNAi screen to deplete annotated orthologs of human methyltransferase-like proteins (METTLs) in Drosophila cells and identified CG9666, the ortholog of human METTL5. We show that CG9666 is required for specific deposition of m6 A on 18S ribosomal RNA via direct interaction with the Drosophila ortholog of human TRMT112, CG12975. Depletion of CG9666 yields a subsequent loss of the 18S rRNA m6 A modification, which lies in the vicinity of the ribosome decoding center; however, this does not compromise rRNA maturation. Instead, a loss of CG9666-mediated m6 A impacts fly behavior, providing an underlying molecular mechanism for the reported human phenotype in intellectual disability. Thus, our work expands the repertoire of m6 A methyltransferases, demonstrates the specialization of these enzymes, and further addresses the significance of ribosomal RNA modifications in gene expression and animal behavior.

The features of polyglutamine regions depend on their evolutionary stability.

BACKGROUND: Polyglutamine regions (polyQ) are one of the most studied and prevalent homorepeats in eukaryotes. They have a particular length-dependent codon usage, which relates to a characteristic CAG-slippage mechanism. Pathologically expanded tracts of polyQ are known to form aggregates and are involved in the development of several human neurodegenerative diseases. The non-pathogenic function of polyQ is to mediate protein-protein interactions via a coiled-coil pairing with an interactor. They are usually located in a helical context. RESULTS: Here we study the stability of polyQ regions in evolution, using a set of 60 proteomes from four distinct taxonomic groups (Insecta, Teleostei, Sauria and Mammalia). The polyQ regions can be distinctly grouped in three categories based on their evolutionary stability: stable, unstable by length variation (inserted), and unstable by mutations (mutated). PolyQ regions in these categories can be significantly distinguished by their glutamine codon usage, and we show that the CAG-slippage mechanism is predominant in inserted polyQ of Sauria and Mammalia. The polyQ amino acid context is also influenced by the polyQ stability, with a higher proportion of proline residues around inserted polyQ. By studying the secondary structure of the sequences surrounding polyQ regions, we found that regarding the structural conformation around a polyQ, its stability category is more relevant than its taxonomic information. The protein-protein interaction capacity of a polyQ is also affected by its stability, as stable polyQ have more interactors than unstable polyQ. CONCLUSIONS: Our results show that apart from the sequence of a polyQ, information about its orthologous sequences is needed to assess its function. Codon usage, amino acid context, structural conformation and the protein-protein interaction capacity of polyQ from all studied taxa critically depend on the region stability. There are however some taxa-specific polyQ features that override this importance. We conclude that a taxa-driven evolutionary analysis is of the highest importance for the comprehensive study of any feature of polyglutamine regions.

Computational identification of cell-specific variable regions in ChIP-seq data.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is used to identify genome-wide DNA regions bound by proteins. Given one ChIP-seq experiment with replicates, binding sites not observed in all the replicates will usually be interpreted as noise and discarded. However, the recent discovery of high-occupancy target (HOT) regions suggests that there are regions where binding of multiple transcription factors can be identified. To investigate ChIP-seq variability, we developed a reproducibility score and a method that identifies cell-specific variable regions in ChIP-seq data by integrating replicated ChIP-seq experiments for multiple protein targets on a particular cell type. Using our method, we found variable regions in human cell lines K562, GM12878, HepG2, MCF-7 and in mouse embryonic stem cells (mESCs). These variable-occupancy target regions (VOTs) are CG dinucleotide rich, and show enrichment at promoters and R-loops. They overlap significantly with HOT regions, but are not blacklisted regions producing non-specific binding ChIP-seq peaks. Furthermore, in mESCs, VOTs are conserved among placental species suggesting that they could have a function important for this taxon. Our method can be useful to point to such regions along the genome in a given cell type of interest, to improve the downstream interpretative analysis before follow-up experiments.

NHC-gold compounds mediate immune suppression through induction of AHR-TGFß1 signalling in vitro and in scurfy mice.

Gold compounds have a long history of use as immunosuppressants, but their precise mechanism of action is not completely understood. Using our recently developed liver-on-a-chip platform we now show that gold compounds containing planar N-heterocyclic carbene (NHC) ligands are potent ligands for the aryl hydrocarbon receptor (AHR). Further studies showed that the lead compound (MC3) activates TGFß1 signaling and suppresses CD4+ T-cell activation in vitro, in human and mouse T cells. Conversely, genetic knockdown or chemical inhibition of AHR activity or of TGFß1-SMAD-mediated signaling offsets the MC3-mediated immunosuppression. In scurfy mice, a mouse model of human immunodysregulation polyendocrinopathy enteropathy X-linked syndrome, MC3 treatment reduced autoimmune phenotypes and extended lifespan from 24 to 58 days. Our findings suggest that the immunosuppressive activity of gold compounds can be improved by introducing planar NHC ligands to activate the AHR-associated immunosuppressive pathway, thus expanding their potential clinical application for autoimmune diseases.

Drivers of topoisomerase II poisoning mimic and complement cytotoxicity in AML cells.

Recently approved cancer drugs remain out-of-reach to most patients due to prohibitive costs and only few produce clinically meaningful benefits. An untapped alternative is to enhance the efficacy and safety of existing cancer drugs. We hypothesized that the response to topoisomerase II poisons, a very successful group of cancer drugs, can be improved by considering treatment-associated transcript levels. To this end, we analyzed transcriptomes from Acute Myeloid Leukemia (AML) cell lines treated with the topoisomerase II poison etoposide. Using complementary criteria of co-regulation within networks and of essentiality for cell survival, we identified and functionally confirmed 11 druggable drivers of etoposide cytotoxicity. Drivers with pre-treatment expression predicting etoposide response (e.g., PARP9) generally synergized with etoposide. Drivers repressed by etoposide (e.g., PLK1) displayed standalone cytotoxicity. Drivers, whose modulation evoked etoposide-like gene expression changes (e.g., mTOR), were cytotoxic both alone and in combination with etoposide. In summary, both pre-treatment gene expression and treatment-driven changes contribute to the cell killing effect of etoposide. Such targets can be tweaked to enhance the efficacy of etoposide. This strategy can be used to identify combination partners or even replacements for other classical anticancer drugs, especially those interfering with DNA integrity and transcription.

Evolutionary stability of topologically associating domains is associated with conserved gene regulation.

BACKGROUND: The human genome is highly organized in the three-dimensional nucleus. Chromosomes fold locally into topologically associating domains (TADs) defined by increased intra-domain chromatin contacts. TADs contribute to gene regulation by restricting chromatin interactions of regulatory sequences, such as enhancers, with their target genes. Disruption of TADs can result in altered gene expression and is associated to genetic diseases and cancers. However, it is not clear to which extent TAD regions are conserved in evolution and whether disruption of TADs by evolutionary rearrangements can alter gene expression. RESULTS: Here, we hypothesize that TADs represent essential functional units of genomes, which are stable against rearrangements during evolution. We investigate this using whole-genome alignments to identify evolutionary rearrangement breakpoints of different vertebrate species. Rearrangement breakpoints are strongly enriched at TAD boundaries and depleted within TADs across species. Furthermore, using gene expression data across many tissues in mouse and human, we show that genes within TADs have more conserved expression patterns. Disruption of TADs by evolutionary rearrangements is associated with changes in gene expression profiles, consistent with a functional role of TADs in gene expression regulation. CONCLUSIONS: Together, these results indicate that TADs are conserved building blocks of genomes with regulatory functions that are often reshuffled as a whole instead of being disrupted by rearrangements.

Glutamine Codon Usage and polyQ Evolution in Primates Depend on the Q Stretch Length.

Amino acid usage in a proteome depends mostly on its taxonomy, as it does the codon usage in transcriptomes. Here, we explore the level of variation in the codon usage of a specific amino acid, glutamine, in relation to the number of consecutive glutamine residues. We show that CAG triplets are consistently more abundant in short glutamine homorepeats (polyQ, four to eight residues) than in shorter glutamine stretches (one to three residues), leading to the evolutionary growth of the repeat region in a CAG-dependent manner. The length of orthologous polyQ regions is mostly stable in primates, particularly the short ones. Interestingly, given a short polyQ the CAG usage is higher in unstable-in-length orthologous polyQ regions. This indicates that CAG triplets produce the necessary instability for a glutamine stretch to grow. Proteins related to polyQ-associated diseases behave in a more extreme way, with longer glutamine stretches in human and evolutionarily closer nonhuman primates, and an overall higher CAG usage. In the light of our results, we suggest an evolutionary model to explain the glutamine codon usage in polyQ regions.