The HIF transcription network exerts innate antiviral activity in neurons and limits brain inflammation.

Pattern recognition receptors (PRRs) induce host defense but can also induce exacerbated inflammatory responses. This raises the question of whether other mechanisms are also involved in early host defense. Using transcriptome analysis of disrupted transcripts in herpes simplex virus (HSV)-infected cells, we find that HSV infection disrupts the hypoxia-inducible factor (HIF) transcription network in neurons and epithelial cells. Importantly, HIF activation leads to control of HSV replication. Mechanistically, HIF activation induces autophagy, which is essential for antiviral activity. HSV-2 infection in vivo leads to hypoxia in CNS neurons, and mice with neuron-specific HIF1/2α deficiency exhibit elevated viral load and augmented PRR signaling and inflammatory gene expression in the CNS after HSV-2 infection. Data from human stem cell-derived neuron and microglia cultures show that HIF also exerts antiviral and inflammation-restricting activity in human CNS cells. Collectively, the HIF transcription factor system senses virus-induced hypoxic stress to induce cell-intrinsic antiviral responses and limit inflammation.

Women With Turner Syndrome Are Both Estrogen and Androgen Deficient: The Impact of Hormone Replacement Therapy.

CONTEXT: Women with Turner syndrome (TS) suffer from hypergonadotropic hypogonadism, causing a deficit in gonadal hormone secretion. As a consequence, these women are treated with estrogen from the age of 12 years, and later in combination with progesterone. However, androgens have been given less attention. OBJECTIVE: To assess sex hormone levels in women with TS, both those treated and those nontreated with hormone replacement therapy (HRT), and investigate the impact of HRT on sex hormone levels. METHODS: At Aarhus University Hospital, 99 women with TS were followed 3 times from August 2003 to February 2010. Seventeen were lost during follow-up. Control group 1 consisted of 68 healthy age-matched control women seen once during this period. Control group 2 consisted of 28 young, eumenorrheic women sampled 9 times throughout the same menstrual cycle. Serum concentrations of follicle-stimulating hormone (FSH), luteinizing hormone (LH), 17ß-estradiol, estrone sulfate, DHEAS, testosterone, free androgen index, androstenedione, 17-OH progesterone, and sex hormone-binding globulin (SHBG) were analyzed. RESULTS: All androgens, 17-OH progesterone, and sex hormone-binding globulin (SHBG) were 30% to 50% lower in TS compared with controls (P < 0.01). FSH, LH, and estrone sulfate were more than doubled in women with TS compared with controls (P < 0.02). Using principal component analysis, we describe a positive correlation between women with TS receiving HRT, elevated levels of SHBG, and decreased levels of androgens. CONCLUSION: The sex hormone profile in TS reveals a picture of androgen deficiency, aggravated further by HRT. Conventional HRT does not normalize estradiol levels in TS.

SARS-CoV2-mediated suppression of NRF2-signaling reveals potent antiviral and anti-inflammatory activity of 4-octyl-itaconate and dimethyl fumarate.

Antiviral strategies to inhibit Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) and the pathogenic consequences of COVID-19 are urgently required. Here, we demonstrate that the NRF2 antioxidant gene expression pathway is suppressed in biopsies obtained from COVID-19 patients. Further, we uncover that NRF2 agonists 4-octyl-itaconate (4-OI) and the clinically approved dimethyl fumarate (DMF) induce a cellular antiviral program that potently inhibits replication of SARS-CoV2 across cell lines. The inhibitory effect of 4-OI and DMF extends to the replication of several other pathogenic viruses including Herpes Simplex Virus-1 and-2, Vaccinia virus, and Zika virus through a type I interferon (IFN)-independent mechanism. In addition, 4-OI and DMF limit host inflammatory responses to SARS-CoV2 infection associated with airway COVID-19 pathology. In conclusion, NRF2 agonists 4-OI and DMF induce a distinct IFN-independent antiviral program that is broadly effective in limiting virus replication and in suppressing the pro-inflammatory responses of human pathogenic viruses, including SARS-CoV2.

Author Correction: SARS-CoV2-mediated suppression of NRF2-signaling reveals potent antiviral and anti-inflammatory activity of 4-octyl-itaconate and dimethyl fumarate.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

STATegra, a comprehensive multi-omics dataset of B-cell differentiation in mouse.

Multi-omics approaches use a diversity of high-throughput technologies to profile the different molecular layers of living cells. Ideally, the integration of this information should result in comprehensive systems models of cellular physiology and regulation. However, most multi-omics projects still include a limited number of molecular assays and there have been very few multi-omic studies that evaluate dynamic processes such as cellular growth, development and adaptation. Hence, we lack formal analysis methods and comprehensive multi-omics datasets that can be leveraged to develop true multi-layered models for dynamic cellular systems. Here we present the STATegra multi-omics dataset that combines measurements from up to 10 different omics technologies applied to the same biological system, namely the well-studied mouse pre-B-cell differentiation. STATegra includes high-throughput measurements of chromatin structure, gene expression, proteomics and metabolomics, and it is complemented with single-cell data. To our knowledge, the STATegra collection is the most diverse multi-omics dataset describing a dynamic biological system.

Author Correction: H3K64 trimethylation marks heterochromatin and is dynamically remodeled during developmental reprogramming.

In this article, the Ponceau staining presented in Fig. 1b (right, bottom) does not follow best practices for figure preparation since itinadvertently included duplications from the Ponceau staining presented in Supplementary Fig. 1b (for which the same preparation ofnucleosomes from HeLa cells had been used). A new Fig. 1b is provided in the Author Correction.

Identifying peaks in *-seq data using shape information.

BACKGROUND: Peak calling is a fundamental step in the analysis of data generated by ChIP-seq or similar techniques to acquire epigenetics information. Current peak callers are often hard to parameterise and may therefore be difficult to use for non-bioinformaticians. In this paper, we present the ChIP-seq analysis tool available in CLC Genomics Workbench and CLC Genomics Server (version 7.5 and up), a user-friendly peak-caller designed to be not specific to a particular *-seq protocol. RESULTS: We illustrate the advantages of a shape-based approach and describe the algorithmic principles underlying the implementation. Thanks to the generality of the idea and the fact the algorithm is able to learn the peak shape from the data, the implementation requires only minimal user input, while still being applicable to a range of *-seq protocols. Using independently validated benchmark datasets, we compare our implementation to other state-of-the-art algorithms explicitly designed to analyse ChIP-seq data and provide an evaluation in terms of receiver-operator characteristic (ROC) plots. In order to show the applicability of the method to similar *-seq protocols, we also investigate algorithmic performances on DNase-seq data. CONCLUSIONS: The results show that CLC shape-based peak caller ranks well among popular state-of-the-art peak callers while providing flexibility and ease-of-use.

Tracing biogeochemical and microbial variability over a complete oil sand mining and recultivation process.

Recultivation of disturbed oil sand mining areas is an issue of increasing importance. Nevertheless only little is known about the fate of organic matter, cell abundances and microbial community structures during oil sand processing, tailings management and initial soil development on reclamation sites. Thus the focus of this work is on biogeochemical changes of mined oil sands through the entire process chain until its use as substratum for newly developing soils on reclamation sites. Therefore, oil sand, mature fine tailings (MFTs) from tailings ponds and drying cells and tailings sand covered with peat-mineral mix (PMM) as part of land reclamation were analyzed. The sample set was selected to address the question whether changes in the above-mentioned biogeochemical parameters can be related to oil sand processing or biological processes and how these changes influence microbial activities and soil development. GC-MS analyses of oil-derived biomarkers reveal that these compounds remain unaffected by oil sand processing and biological activity. In contrast, changes in polycyclic aromatic hydrocarbon (PAH) abundance and pattern can be observed along the process chain. Especially naphthalenes, phenanthrenes and chrysenes are altered or absent on reclamation sites. Furthermore, root-bearing horizons on reclamation sites exhibit cell abundances at least ten times higher (10(8) to 10(9) cells g(-1)) than in oil sand and MFT samples (10(7) cells g(-1)) and show a higher diversity in their microbial community structure. Nitrate in the pore water and roots derived from the PMM seem to be the most important stimulants for microbial growth. The combined data show that the observed compositional changes are mostly related to biological activity and the addition of exogenous organic components (PMM), whereas oil extraction, tailings dewatering and compaction do not have significant influences on the evaluated compounds. Microbial community composition remains relatively stable through the entire process chain.

Hsp90 inhibition differentially destabilises MAP kinase and TGF-beta signalling components in cancer cells revealed by kinase-targeted chemoproteomics.

BACKGROUND: The heat shock protein 90 (Hsp90) is required for the stability of many signalling kinases. As a target for cancer therapy it allows the simultaneous inhibition of several signalling pathways. However, its inhibition in healthy cells could also lead to severe side effects. This is the first comprehensive analysis of the response to Hsp90 inhibition at the kinome level. METHODS: We quantitatively profiled the effects of Hsp90 inhibition by geldanamycin on the kinome of one primary (Hs68) and three tumour cell lines (SW480, U2OS, A549) by affinity proteomics based on immobilized broad spectrum kinase inhibitors ("kinobeads"). To identify affected pathways we used the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway classification. We combined Hsp90 and proteasome inhibition to identify Hsp90 substrates in Hs68 and SW480 cells. The mutational status of kinases from the used cell lines was determined using next-generation sequencing. A mutation of Hsp90 candidate client RIPK2 was mapped onto its structure. RESULTS: We measured relative abundances of > 140 protein kinases from the four cell lines in response to geldanamycin treatment and identified many new potential Hsp90 substrates. These kinases represent diverse families and cellular functions, with a strong representation of pathways involved in tumour progression like the BMP, MAPK and TGF-beta signalling cascades. Co-treatment with the proteasome inhibitor MG132 enabled us to classify 64 kinases as true Hsp90 clients. Finally, mutations in 7 kinases correlate with an altered response to Hsp90 inhibition. Structural modelling of the candidate client RIPK2 suggests an impact of the mutation on a proposed Hsp90 binding domain. CONCLUSIONS: We propose a high confidence list of Hsp90 kinase clients, which provides new opportunities for targeted and combinatorial cancer treatment and diagnostic applications.

A cell extraction method for oily sediments.

Hydrocarbons can be found in many different habitats and represent an important carbon source for microbes. As fossil fuels, they are also an important economical resource and through natural seepage or accidental release they can be major pollutants. DNA-specific stains and molecular probes bind to hydrocarbons, causing massive background fluorescence, thereby hampering cell enumeration. The cell extraction procedure of Kallmeyer et al. (2008) separates the cells from the sediment matrix. In principle, this technique can also be used to separate cells from oily sediments, but it was not originally optimized for this application. Here we present a modified extraction method in which the hydrocarbons are removed prior to cell extraction. Due to the reduced background fluorescence the microscopic image becomes clearer, making cell identification, and enumeration much easier. Consequently, the resulting cell counts from oily samples treated according to our new protocol are significantly higher than those treated according to Kallmeyer et al. (2008). We tested different amounts of a variety of solvents for their ability to remove hydrocarbons and found that n-hexane and - in samples containing more mature oils - methanol, delivered the best results. However, as solvents also tend to lyse cells, it was important to find the optimum solvent to sample ratio, at which hydrocarbon extraction is maximized and cell lysis minimized. A volumetric ratio of 1:2-1:5 between a formalin-fixed sediment slurry and solvent delivered highest cell counts. Extraction efficiency was around 30-50% and was checked on both oily samples spiked with known amounts of E. coli cells and oil-free samples amended with fresh and biodegraded oil. The method provided reproducible results on samples containing very different kinds of oils with regard to their degree of biodegradation. For strongly biodegraded oil MeOH turned out to be the most appropriate solvent, whereas for less biodegraded samples n-hexane delivered best results.

The structural impact of cancer-associated missense mutations in oncogenes and tumor suppressors.

BACKGROUND: Current large-scale cancer sequencing projects have identified large numbers of somatic mutations covering an increasing number of different cancer tissues and patients. However, the characterization of these mutations at the structural and functional level remains a challenge. RESULTS: We present results from an analysis of the structural impact of frequent missense cancer mutations using an automated method. We find that inactivation of tumor suppressors in cancer correlates frequently with destabilizing mutations preferably in the core of the protein, while enhanced activity of oncogenes is often linked to specific mutations at functional sites. Furthermore, our results show that this alteration of oncogenic activity is often associated with mutations at ATP or GTP binding sites. CONCLUSIONS: With our findings we can confirm and statistically validate the hypotheses for the gain-of-function and loss-of-function mechanisms of oncogenes and tumor suppressors, respectively. We show that the distinct mutational patterns can potentially be used to pre-classify newly identified cancer-associated genes with yet unknown function.

CMView: interactive contact map visualization and analysis.

SUMMARY: Contact maps are a valuable visualization tool in structural biology. They are a convenient way to display proteins in two dimensions and to quickly identify structural features such as domain architecture, secondary structure and contact clusters. We developed a tool called CMView which integrates rich contact map analysis with 3D visualization using PyMol. Our tool provides functions for contact map calculation from structure, basic editing, visualization in contact map and 3D space and structural comparison with different built-in alignment methods. A unique feature is the interactive refinement of structural alignments based on user selected substructures. AVAILABILITY: CMView is freely available for Linux, Windows and MacOS. The software and a comprehensive manual can be downloaded from http://www.bioinformatics.org/cmview/. The source code is licensed under the GNU General Public License.

Crosstalk between phosphorylation and multi-site arginine/lysine methylation in C/EBPs.

C/EBPs are implied in an amazing number of cellular functions: C/EBPs regulate tissue and cell type specific gene expression, proliferation, and differentiation control. C/EBPs assist in energy metabolism, female reproduction, innate immunity, inflammation, senescence, and the development of neoplasms. How can C/EBPs fulfill so many functions? Here we discuss that C/EBPs are extensively modified by methylation of arginine and lysine side chains and that regulated methylation profoundly affects the activity of C/EBPs.

PDBWiki: added value through community annotation of the Protein Data Bank.

The success of community projects such as Wikipedia has recently prompted a discussion about the applicability of such tools in the life sciences. Currently, there are several such 'science-wikis' that aim to collect specialist knowledge from the community into centralized resources. However, there is no consensus about how to achieve this goal. For example, it is not clear how to best integrate data from established, centralized databases with that provided by 'community annotation'. We created PDBWiki, a scientific wiki for the community annotation of protein structures. The wiki consists of one structured page for each entry in the the Protein Data Bank (PDB) and allows the user to attach categorized comments to the entries. Additionally, each page includes a user editable list of cross-references to external resources. As in a database, it is possible to produce tabular reports and 'structure galleries' based on user-defined queries or lists of entries. PDBWiki runs in parallel to the PDB, separating original database content from user annotations. PDBWiki demonstrates how collaboration features can be integrated with primary data from a biological database. It can be used as a system for better understanding how to capture community knowledge in the biological sciences. For users of the PDB, PDBWiki provides a bug-tracker, discussion forum and community annotation system. To date, user participation has been modest, but is increasing. The user editable cross-references section has proven popular, with the number of linked resources more than doubling from 17 originally to 39 today. Database URL: http://www.pdbwiki.org.

Optimal contact definition for reconstruction of contact maps.

BACKGROUND: Contact maps have been extensively used as a simplified representation of protein structures. They capture most important features of a protein's fold, being preferred by a number of researchers for the description and study of protein structures. Inspired by the model's simplicity many groups have dedicated a considerable amount of effort towards contact prediction as a proxy for protein structure prediction. However a contact map's biological interest is subject to the availability of reliable methods for the 3-dimensional reconstruction of the structure. RESULTS: We use an implementation of the well-known distance geometry protocol to build realistic protein 3-dimensional models from contact maps, performing an extensive exploration of many of the parameters involved in the reconstruction process. We try to address the questions: a) to what accuracy does a contact map represent its corresponding 3D structure, b) what is the best contact map representation with regard to reconstructability and c) what is the effect of partial or inaccurate contact information on the 3D structure recovery. Our results suggest that contact maps derived from the application of a distance cutoff of 9 to 11A around the Cbeta atoms constitute the most accurate representation of the 3D structure. The reconstruction process does not provide a single solution to the problem but rather an ensemble of conformations that are within 2A RMSD of the crystal structure and with lower values for the pairwise average ensemble RMSD. Interestingly it is still possible to recover a structure with partial contact information, although wrong contacts can lead to dramatic loss in reconstruction fidelity. CONCLUSIONS: Thus contact maps represent a valid approximation to the structures with an accuracy comparable to that of experimental methods. The optimal contact definitions constitute key guidelines for methods based on contact maps such as structure prediction through contacts and structural alignments based on maximum contact map overlap.

Somatic mutation profiles of MSI and MSS colorectal cancer identified by whole exome next generation sequencing and bioinformatics analysis.

BACKGROUND: Colorectal cancer (CRC) is with approximately 1 million cases the third most common cancer worldwide. Extensive research is ongoing to decipher the underlying genetic patterns with the hope to improve early cancer diagnosis and treatment. In this direction, the recent progress in next generation sequencing technologies has revolutionized the field of cancer genomics. However, one caveat of these studies remains the large amount of genetic variations identified and their interpretation. METHODOLOGY/PRINCIPAL FINDINGS: Here we present the first work on whole exome NGS of primary colon cancers. We performed 454 whole exome pyrosequencing of tumor as well as adjacent not affected normal colonic tissue from microsatellite stable (MSS) and microsatellite instable (MSI) colon cancer patients and identified more than 50,000 small nucleotide variations for each tissue. According to predictions based on MSS and MSI pathomechanisms we identified eight times more somatic non-synonymous variations in MSI cancers than in MSS and we were able to reproduce the result in four additional CRCs. Our bioinformatics filtering approach narrowed down the rate of most significant mutations to 359 for MSI and 45 for MSS CRCs with predicted altered protein functions. In both CRCs, MSI and MSS, we found somatic mutations in the intracellular kinase domain of bone morphogenetic protein receptor 1A, BMPR1A, a gene where so far germline mutations are associated with juvenile polyposis syndrome, and show that the mutations functionally impair the protein function. CONCLUSIONS/SIGNIFICANCE: We conclude that with deep sequencing of tumor exomes one may be able to predict the microsatellite status of CRC and in addition identify potentially clinically relevant mutations.

Defining an essence of structure determining residue contacts in proteins.

The network of native non-covalent residue contacts determines the three-dimensional structure of a protein. However, not all contacts are of equal structural significance, and little knowledge exists about a minimal, yet sufficient, subset required to define the global features of a protein. Characterisation of this "structural essence" has remained elusive so far: no algorithmic strategy has been devised to-date that could outperform a random selection in terms of 3D reconstruction accuracy (measured as the Ca RMSD). It is not only of theoretical interest (i.e., for design of advanced statistical potentials) to identify the number and nature of essential native contacts-such a subset of spatial constraints is very useful in a number of novel experimental methods (like EPR) which rely heavily on constraint-based protein modelling. To derive accurate three-dimensional models from distance constraints, we implemented a reconstruction pipeline using distance geometry. We selected a test-set of 12 protein structures from the four major SCOP fold classes and performed our reconstruction analysis. As a reference set, series of random subsets (ranging from 10% to 90% of native contacts) are generated for each protein, and the reconstruction accuracy is computed for each subset. We have developed a rational strategy, termed "cone-peeling" that combines sequence features and network descriptors to select minimal subsets that outperform the reference sets. We present, for the first time, a rational strategy to derive a structural essence of residue contacts and provide an estimate of the size of this minimal subset. Our algorithm computes sparse subsets capable of determining the tertiary structure at approximately 4.8 A Ca RMSD with as little as 8% of the native contacts (Ca-Ca and Cb-Cb). At the same time, a randomly chosen subset of native contacts needs about twice as many contacts to reach the same level of accuracy. This "structural essence" opens new avenues in the fields of structure prediction, empirical potentials and docking.

Designing evolvable libraries using multi-body potentials.

Novel high-throughput technologies for directed evolution enable experimental coverage of an impressive number of sequences. Nevertheless, the success of such experiments hinges on the initial sequence libraries. Here we consider the computational design of smart focused libraries and review insights from experimental strategies and theoretic advances in modelling their energy landscapes. In library design as in structure prediction, the applied energy function is the key. Current knowledge-based potentials have proven more successful than purely physics-based ones. Here we summarize novel approaches that extend the classical pairwise treatment of residue contacts towards adaptive knowledge-based multi-body potentials. We suggest that minimal sets of probabilistic constraints will lead to much more efficient sampling of permissible conformations and sequence space.

Optimized null model for protein structure networks.

Much attention has recently been given to the statistical significance of topological features observed in biological networks. Here, we consider residue interaction graphs (RIGs) as network representations of protein structures with residues as nodes and inter-residue interactions as edges. Degree-preserving randomized models have been widely used for this purpose in biomolecular networks. However, such a single summary statistic of a network may not be detailed enough to capture the complex topological characteristics of protein structures and their network counterparts. Here, we investigate a variety of topological properties of RIGs to find a well fitting network null model for them. The RIGs are derived from a structurally diverse protein data set at various distance cut-offs and for different groups of interacting atoms. We compare the network structure of RIGs to several random graph models. We show that 3-dimensional geometric random graphs, that model spatial relationships between objects, provide the best fit to RIGs. We investigate the relationship between the strength of the fit and various protein structural features. We show that the fit depends on protein size, structural class, and thermostability, but not on quaternary structure. We apply our model to the identification of significantly over-represented structural building blocks, i.e., network motifs, in protein structure networks. As expected, choosing geometric graphs as a null model results in the most specific identification of motifs. Our geometric random graph model may facilitate further graph-based studies of protein conformation space and have important implications for protein structure comparison and prediction. The choice of a well-fitting null model is crucial for finding structural motifs that play an important role in protein folding, stability and function. To our knowledge, this is the first study that addresses the challenge of finding an optimized null model for RIGs, by comparing various RIG definitions against a series of network models.

H3K64 trimethylation marks heterochromatin and is dynamically remodeled during developmental reprogramming.

Histone modifications are central to the regulation of all DNA-dependent processes. Lys64 of histone H3 (H3K64) lies within the globular domain at a structurally important position. We identify trimethylation of H3K64 (H3K64me3) as a modification that is enriched at pericentric heterochromatin and associated with repeat sequences and transcriptionally inactive genomic regions. We show that this new mark is dynamic during the two main epigenetic reprogramming events in mammals. In primordial germ cells, H3K64me3 is present at the time of specification, but it disappears transiently during reprogramming. In early mouse embryos, it is inherited exclusively maternally; subsequently, the modification is rapidly removed, suggesting an important role for H3K64me3 turnover in development. Taken together, our findings establish H3K64me3 as a previously uncharacterized histone modification that is preferentially localized to repressive chromatin. We hypothesize that H3K64me3 helps to 'secure' nucleosomes, and perhaps the surrounding chromatin, in an appropriately repressed state during development.