bluuebunny/crossref_metadata_2025 huggingface dataset:
Posterior reversible encephalopathy syndrome
Authors: Liman Thomas G. , Siebert Eberhard , Endres Matthias
Published: December 2018

Purpose of review

Posterior reversible encephalopathy syndrome (PRES) is a clinicoradiological syndrome characterized by acute cerebral endotheliopathy with consecutive disruption of the blood–brain barrier and vasogenic edema. Since its first description in 1996, PRES is increasingly recognized. However, many aspects of this syndrome with its wide spectrum of clinical and radiological features are still incompletely understood. In this review, possible pathophysiological mechanisms, approaches to diagnosis, recent study results on outcome, and future directions of research are described.

Recent findings

Clinical manifestations of PRES include seizures, headache, visual disturbances, altered mental state, and more rarely hemiparesis or aphasia. Vasogenic edema predominantly occurs in the parieto-occipital region, but lesions affecting formerly called ‘atypical’ regions such as frontal lobe, cerebellum, or basal ganglia are common. If treated early and adequately, that is by removal of the underlying cause, PRES has a favorable prognosis, but neurological residual symptoms and even mortality can occur, particularly in patients with complications such as intracranial hemorrhage.

In summary, validated diagnostic criteria and algorithms are warranted to standardize the diagnosis of PRES. This is essential for further research and future prospective studies that should investigate risk factors for unfavorable outcome and identify the roles of imaging features, clinical symptoms, and other biomarkers in predicting outcome.
NeoPredPipe: High-Throughput Neoantigen Prediction and Recognition Potential Pipeline
Authors: Schenck Ryan O. , Lakatos Eszter , Gatenbee Chandler , Graham Trevor A. , Anderson Alexander R.A.
Published: December 2018

Next generation sequencing has yielded an unparalleled means of quickly determining the molecular make-up of patient tumors. In conjunction with emerging, effective immunotherapeutics for a number of cancers, this rapid data generation requires a paired high-throughput means of predicting neoantigens that may stimulate immune response. Here we offer NeoPredPipe as a contiguous means of predicting putative neoantigens and their corresponding recognition potentials for both single and multi-region tumor samples. NeoPredPipe is able to quickly provide summary information for researchers, and clinicians alike, on neoantigen burdens while providing high-level insights into tumor heterogeneity given somatic mutation calls and, optionally, patient HLA haplotypes.
In-depth proteomic characterization of Schistosoma haematobium: towards the development of new tools for elimination
Authors: Sotillo Javier , Pearson Mark S. , Becker Luke , Mekonnen Gebeyaw G. , Amoah Abena S. , van Dam Govert , Corstjens Paul L.A.M. , Mduluza Takafira , Mutapi Francisca , Loukas Alex
Published: December 2018

Background

Schistosomiasis is a neglected disease affecting hundreds of millions worldwide. Of the three main species affecting humans, Schistosoma haematobium is the most common, and is the leading cause of urogenital schistosomiasis. S. haematobium infection can cause different urogential clinical complications, particularly in the bladder, and furthermore, this parasite has been strongly linked with squamous cell carcinoma. A comprehensive analysis of the molecular composition of its different proteomes will contribute to developing new tools against this devastating disease.

Methods and Findings

By combining a comprehensive protein fractionation approach consisting of OFFGEL electrophoresis with high-throughput mass spectrometry, we have performed the first in-depth characterisation of the different discrete proteomes of S. haematobium that are predicted to interact with human host tissues, including the secreted and tegumental proteomes of adult flukes and secreted and soluble egg proteomes. A total of 662, 239, 210 and 138 proteins were found in the adult tegument, adult secreted, soluble egg and secreted egg proteomes, respectively. In addition, we probed these distinct proteomes with urine to assess urinary antibody responses from naturally infected human subjects with different infection intensities, and identified adult fluke secreted and tegument extracts as being the best predictors of infection.

Conclusion

We provide a comprehensive dataset of proteins from the adult and egg stages of S. haematobium and highlight their utility as diagnostic markers of infection intensity for the development of novel tools to control this important neglected tropical disease.

Author Summary

Schistosomiasis is a neglected tropical disease affecting millions of people worldwide. Of the main three species affecting humans, Schistosoma haematobium is the most common, and is the leading cause of urogenital schistosomiasis. This parasite can cause a range of clinical complications associated with bladder pathogenesis, including squamous cell carcinoma as well as genital malignancy in women. Herein, we have performed the first comprehensive characterisation of the proteins implicated in host-parasite interactions (secreted and surface proteins from the adult flukes and secreted and soluble egg proteins) in order to advance our understanding of the parasite’s biology. Furthermore, we have characterised the different antibody responses in urine from infected human subjects from an endemic area presenting different infection intensities. The data obtained in this study can be used as a first step towards the development of novel tools for the control of urogenital schistosomiasis.
Expansion, Exploitation and Extinction: Niche Construction in Ephemeral Landscapes
Authors: Wetherington Miles T. , Keymer Juan E.
Published: December 2018

We developed an interacting particle system (IPS) to study the effect of niche construction on metapopulation dynamics in ephemeral landscapes. Using finite scaling theory, we find a divergence in the qualitative behavior at the extinction threshold between analytic (mean field) and numerical (IPS) results when niche construction is confined to a small area in the spatial model. While increasing the area of niche construction leads to a faster rate of range expansion, it also causes a shift from a continuous to discontinuous phase transition, thus returning to the mean field prediction. Furthermore, in the discontinuous regime of the IPS, spatial clustering prior to a critical transition disappears. This is a significant finding as spatial clustering has been considered to be an early warning signal before ecosystems reach their ‘tipping point’. In addition to maintaining stability, we find this local niche construction strategy has an advantage when in competition with an exploiter because of their ability to monopolize the constructed niche due to spatial adjacency. However, as the niche construction neighborhood expands this advantage disappears and the exploiter strategy out-competes the niche constructor. In some cases the exploiter pushes the niche constructor to extinction, thus a tragedy of the commons ensues leading to ecological suicide and a collapse of the niche.

Significance Statement

Many populations do not exist passively in their environment. Niche construction theory tells us the co-regulatory feedback between a population and its localized environment can have significant impacts on the evolutionary trajectory and ecological stability of the population and broader community. However, if this feedback is not tightly coupled to the niche construction strategy it is left susceptible to exploitation. In some instances this can lead to ecological suicide, where both constructor and exploiter are driven to extinction. This study emphasizes the importance of being spatial when considering the ecological implications of niche construction. Along with adding to the development of niche construction theory, this work has implications for our understanding of critical transitions in vulnerable ecosystems.
Silent crickets reveal the genomic footprint of recent adaptive trait loss
Authors: Pascoal Sonia , Risse Judith E. , Zhang Xiao , Blaxter Mark , Cezard Timothee , Challis Richard J. , Gharbi Karim , Hunt John , Kumar Sujai , Langan Emma , Liu Xuan , Rayner Jack G. , Ritchie Michael G. , Snoek Basten L. , Trivedi Urmi , Bailey Nathan
Published: December 2018

Secondary trait loss is widespread and has profound consequences, from generating diversity to driving adaptation. Sexual trait loss is particularly common. Its genomic impact is challenging to reconstruct because most reversals occurred in the distant evolutionary past and must be inferred indirectly, and questions remain about the extent of disruption caused by pleiotropy, altered gene expression and loss of homeostasis. We tested the genomic signature of recent sexual signal loss in Hawaiian field crickets, Teleogryllus oceanicus. Song loss is controlled by a sex-linked Mendelian locus, flatwing, which feminises male wings by erasing sound-producing veins. This variant spread rapidly under pressure from an eavesdropping parasitoid fly. We sequenced, assembled and annotated the T. oceanicus genome, produced a high-density linkage map, and localised flatwing on the X chromosome. We characterised pleiotropic effects of flatwing, including changes in embryonic gene expression and alteration of another sexual signal, chemical pheromones. Song loss is associated with pleiotropy, hitchhiking and genome-wide regulatory disruption which feminises flatwing male pheromones. The footprint of recent adaptive trait loss illustrates R. A. Fisher's influential prediction that variants with large mutational effect sizes can invade genomes during the earliest stages of adaptation to extreme pressures, despite having severely disruptive genomic consequences.
Norovirus infection results in assembly of virus-specific G3BP1 granules and evasion of eIF2α signaling
Authors: Brocard Michèle , Iadevaia Valentina , Klein Philipp , Hall Belinda , Lewis Glenys , Lu Jia , Burke James , Parker Roy , Ruggieri Alessia , Goodfellow Ian G. , Locker Nicolas
Published: December 2018

During viral infection, the accumulation of RNA replication intermediates or viral proteins imposes major stress on the host cell. In response, cellular stress pathways can rapidly impose defence mechanisms by shutting off the protein synthesis machinery, which viruses depend on, and triggering the accumulation of mRNAs into stress granules to limit the use of energy and nutrients. Because this threatens viral gene expression, viruses need to evade these pathways to propagate. Human norovirus is responsible for gastroenteritis outbreaks worldwide. Previously we showed that murine norovirus (MNV) regulates the activity of eukaryotic initiation factors (eIFs). Here we examined how MNV interacts with the eIF2α signaling axis controlling translation and stress granules accumulation. We show that while MNV infection represses host cell translation, it results in the assembly of virus-specific granules rather than stress granules. Further mechanistic analyses revealed that eIF2α signaling is uncoupled from translational stalling. Moreover the interaction of the RNA-binding protein G3BP1 with viral factors together with a redistribution of its cellular interacting partners could explain norovirus evasion of stress granules assembly. These results identify novel strategies by which norovirus ensure efficient replication propagation by manipulating the host stress response.
Rapid functional divergence of grass duplicate genes
Authors: Jiang Xueyuan , Assis Raquel
Published: December 2018

Gene duplication has played an important role in the evolution and domestication of flowering plants. Yet little is known about how plant duplicate genes evolve and are retained over long timescales, particularly those arising from small-scale duplication (SSD) rather than whole-genome duplication (WGD) events. Here we address this question in the Poaceae (grass) family by analyzing gene expression data from nine tissues ofBrachypodium distachyon,Oryza sativa japonica(rice), andSorghum bicolor(sorghum). Consistent with theoretical predictions, expression profiles of most grass genes are conserved after SSD, suggesting that functional conservation is the primary outcome of SSD in grasses. However, we also uncover support for widespread functional divergence, much of which occurs asymmetrically via the process of neofunctionalization. Moreover, neofunctionalization preferentially targets younger (child) duplicate gene copies, is associated with RNA-mediated duplication, and occurs quickly after duplication. Further analysis reveals that functional divergence of SSD-derived genes is positively correlated with both sequence divergence and tissue specificity in all three grass species, and particularly with anther expression inB. distachyon. Therefore, as found in many animal species, SSD-derived grass genes often undergo rapid functional divergence that may be driven by natural selection on male-specific phenotypes.
Exploration of the immune cell landscape in brain cancer utilizing gene expression and copy number data
Authors: Gusev Yuriy , Bhuvaneshwar Krithika , Madhavan Subha
Published: December 2018

Brain cancer is a common cancer that affects more than 700,000 people in the US every year. We explore the dynamic changes in the abundance of immune cells based on RNA and DNA samples extracted from a large cohort of brain cancer patients. We used gene expression data and copy number data from a large brain cancer collections - the REMBRANDT project (REpository for Molecular BRAin Neoplasia DaTa) that includes 671 patients.
We applied virtual flow cytometry tools CIBERSORT and xCell to estimate the abundance of the immune cells in the RNA of these samples. The immune cell landscape in this dataset is compared with that of the TCGA brain cancer collection, that includes 511 patients with Lower Grade Glioma (TCGA-LGG) and 156 patients with Glioblastoma (TCGA-GBM).
We also discuss how well the results align with published literature, and how this computational analysis can help better understand how immune cells affect clinical outcome and survival in brain cancer patients.
Toxicity of JUUL Fluids and Aerosols Correlates Strongly with Nicotine and Some Flavor Chemical Concentrations
Authors: Omaiye Esther E. , McWhirter Kevin J. , Luo Wentai , Pankow James F. , Talbot Prue
Published: December 2018

While JUUL electronic cigarettes (ECs) have captured the majority of the EC market with a large fraction of their sales going to adolescents, little is known about their cytotoxicity and potential effects on health. The purpose of this study was to determine flavor chemical and nicotine concentrations in the eight currently marketed pre-filled JUUL EC cartridges (“pods”) and to evaluate the cytotoxicity of the different variants (e.g., “Cool Mint” and “Crème Brulee”) using in vitro assays. Nicotine and flavor chemicals were analyzed using gas chromatography/mass spectrometry in pod fluid before and after vaping and in the corresponding aerosols. 59 flavor chemicals were identified in JUUL pod fluids, and three were >1 mg/mL. Duplicate pods were similar in flavor chemical composition and concentration. Nicotine concentrations (average 60.9 mg/mL) were significantly higher than any EC products we have analyzed previously. Transfer efficiency of individual flavor chemicals that were >1mg/mL and nicotine from the pod fluid into aerosols was generally 35 - 80%. All pod fluids were cytotoxic at a 1:10 dilution (10%) in the MTT and neutral red uptake assays when tested with BEAS-2B lung epithelial cells. Most aerosols were cytotoxic in these assays at concentrations >1%. The cytotoxicity of aerosols was highly correlated with nicotine and ethyl maltol concentrations and moderately to weakly correlated with total flavor chemical concentration and menthol concentration. Our study demonstrates that: (1) some JUUL flavor pods have high concentrations of flavor chemicals that may make them attractive to youth, and (2) the concentrations of nicotine and some flavor chemicals (e.g. ethyl maltol) are high enough to be cytotoxic in acute in vitro assays, emphasizing the need to determine if JUUL products will lead to adverse health effects with chronic use.
The conflict between adaptation and dispersal for maintaining biodiversity in changing environments
Authors: Thompson Patrick L. , Fronhofer Emanuel A.
Published: December 2018

Dispersal and adaptation both allow species to persist in changing environments. Yet, we have limited understanding of how these processes interact to affect species persistence, especially in diverse communities where biotic interactions greatly complicate responses to environmental change. Here we use a stochastic metacommunity model to demonstrate how dispersal and adaptation to environmental change independently and interactively contribute to biodiversity maintenance. Dispersal provides spatial insurance, whereby species persist on the landscape by shifting their distributions to track favourable conditions. In contrast, adaptation allows species to persist by allowing for evolutionary rescue. But, when species both adapt and disperse, dispersal and adaptation do not combine positively to affect biodiversity maintenance, even if they do increase the persistence of individual species. This occurs because faster adapting species evolve to hold onto their initial ranges (i.e. monopolization effects), thus impeding slower adapting species from shifting their ranges and thereby causing extinctions. Importantly, these differences in adaptation speed emerge as the result of competition, which alters population sizes and colonization success. By demonstrating how dispersal and adaptation each independently and interactively contribute to the maintenance of biodiversity, we provide a framework that links the theories of spatial insurance, evolutionary rescue, and monopolization. This highlights the expectation that the maintenance of biodiversity in changing environments depends jointly on rates of dispersal and adaptation, and, critically, the interaction between these processes.

Significance Statement

Species can persist when the environment changes by shifting their ranges through dispersal or by adapting to the new conditions that they experience. Thus, we might expect that dispersal and adaptation in combination would increase persistence. Using a simulation model, we show that this may not be the case. Instead, species competition causes dispersal and adaptation to have conflicting contributions to biodiversity maintenance. Dispersal and adaptation each independently increase biodiversity maintenance. But when species both disperse and evolve, faster adapting species persist in their current ranges, preventing others from shifting their ranges to track environmental change. These findings highlight the need to consider ecological and evolutionary processes together, or we risk underestimating how global change will impact biodiversity.
Inferring Processes of Coevolutionary Diversification in a Community of Panamanian Strangler Figs and Associated Pollinating Wasps
Authors: Satler Jordan D. , Herre Edward Allen , Jandér K. Charlotte , Eaton Deren A. R. , Machado Carlos A. , Heath Tracy A. , Nason John D.
Published: December 2018

1

The fig and pollinator wasp obligate mutualism is diverse (~750 described species), ecologically important, and ancient (~80-90 Ma), providing model systems for generating and testing many questions in evolution and ecology. Once thought to be a prime example of strict one-to-one cospeciation, current thinking suggests that genera of pollinator wasps co-evolve with corresponding subsections of figs, but the degree to which cospeciation or other processes contributes to the association at finer scales is unclear. Here we use genome-wide sequence data from a community of Panamanian strangler figs (Ficus subgenus Urostigma, section Americana) and associated fig wasp pollinators (Pegoscapus spp.) to infer the process of coevolutionary diversification in this obligate mutualism. Using a model-based approach adapted from the study of gene family evolution, our results indicate pervasive and ongoing host switching of pollinator wasps at this fine phylogenetic and regional scale. Although the model estimates a modest amount of cospeciation, simulations reveal this signal to be consistent with levels of co-association expected under a model of free host switching. Our findings provide an outline for testing how ecological and evolutionary processes can be modeled to evaluate the history of association of interacting lineages in a phylogenetic framework.
Basal Role for Nrf2-transgne on transcriptional (mRNA/miRNA) regulation in the mouse myocardium
Authors: Jyothidasan Arun , Shanmugam Gobinath , Zhang John , Dally Brain , Crossman David , Namakkal Soorappan Rajasekaran
Published: December 2018

Background: NFE2L2 (nuclear factor, erythroid 2 like 2; Nrf2), is a stress responsive transcription factor that regulates cellular redox homeostasis. The action mechanism of Nrf2 occurs through sensing oxidative stress in the cellular environment in responses to various stresses including altered metabolism, toxic insult and xenobiotic stresses. However, under the basal condition, the role of excess Nrf2 on global miRNA and mRNA interactions in the myocardium is unknown. Here, we tested a hypothesis that excess Nrf2 (transgene) will promote the transcription of antioxidants, which then might escalate the basal defense mechanisms in the heart. Furthermore, we investigated whether changes in the miRNA profile might have a strong role on the transcriptome in TG hearts. Methods: Non transgenic (NTG), and Cardiac specific Nrf2 transgenic (Nrf2 TG) mice in the C57/BL6 background at the age of 6 to 8 months were used to examine transcriptional and posttranscriptional signatures (mRNA and miRNA expressions) by performing next generation sequencing (NGS) for RNA (RNAseq) and small RNA (sRNAseq) for miRNA expressions in the heart (n=3 to 6/group). Validation of the NGS data was performed by quantitative real time PCR (qRT PCR) using specific primers targeting selected miRNAs or mRNAs. Finally, in silico analyses were performed to determine the miRNA and mRNA interactome networks and the pathways that are potentially regulated by these networks. Results: NGS analysis for mRNA indicated that there were 5727 differently expressed genes DEGs) in the Nrf2 TG vs. NTG myocardium. Of which, 3552 were upregulated and 2175 were downregulated significantly. Small RNAseq analysis revealed that 112 miRNAs were significantly altered in Nrf2TG versus NTG hearts. Among these miRNAs, 68 were upregulated and 44 were downregulated significantly. Validation of key targets for mRNA and miRNA by qPCR confirmed the NGS results. In silico analysis (IPA) revealed that the majority of the miRNAs and mRNAs that are significantly altered in response to transgene expression are potentially involved in Nrf2 mediated oxidative stress response, ILK Signaling, hypoxia signaling in the cardiovascular system and glutathione mediated detoxification etc. Conclusion: These high throughput sequencing data sets from cardiac specific Nrf2TG mice revealed the transcriptome wide effects of Nrf2 in the myocardium. Furthermore, our comprehensive analysis indicates that Nrf2 may directly or indirectly regulates these sub sets of cardiac miRNA and mRNA interactome networks under basal physiological setting.
Predictive validity of effective shunt fraction in critically ill patients
Authors: Chang Emma M , Bretherick Andrew , Drummond Gordon B , Baillie J Kenneth
Published: December 2018

Accurate measurement of pulmonary oxygenation is important for classification of disease severity and quantification of outcomes in clinical studies. We compared predictive validity of established tension-based methods with two new measures of shunt fraction: (1) a non-invasive effective shunt (ES); and (2) inferred values from an integrated mathematical model of gas exchange (DB). Median absolute error (MAE) values for the four measures considered were: alveolar-arterial difference, 7.30kPa; PaO2/FIO2 ratio, 2.41kPa; DB, 2.13kPa; ES: 1.88kPa. ES performed significantly better than other measures (p<10−10 in all comparisons). While the simplicity of P/F is suitable for routine use, the superior predictive validity of ES should make this measure the preferred choice where physiological accuracy is important, such as for use as surrogate outcome in clinical research.
GeTallele: a method for integrative analysis and visualization of DNA and RNA allele frequencies
Authors: Słowiński Piotr , Li Muzi , Restrepo Paula , Alomran Nawaf , Spurr Liam F. , Miller Christian , Tsaneva-Atanasova Krasimira , Horvath Anelia
Published: December 2018

Background

Asymmetric allele expression typically indicates functional and/or structural features associated with the underlying genetic variants. When integrated, RNA and DNA allele frequencies can reveal patterns characteristic of a wide-range of biological traits, including ploidy changes, genome admixture, allele-specific expression and gene-dosage transcriptional response.

Results

To assess RNA and DNA allele frequencies from matched sequencing datasets, we introduce a method for generating model distributions of variant allele frequencies (VAF) with a given variant read probability. In contrast to other methods, based on whole sequences or single SNV, proposed methodology uses continuous multi-SNV genomic regions. The methodology is implemented in a GeTallele toolbox that provides a suite of functions for integrative analysis, statistical assessment and visualization ofGenome andTranscriptomeallelefrequencies. Using model VAF probabilities, GeTallele allows estimation and comparison of variant read probabilities (VAF distributions) in a sequencing dataset. We demonstrate this functionality across cancer DNA and RNA sequencing datasets.

Conclusion

Based on our evaluation, variant read probabilities can serve as a dependable indicator to assess gene and chromosomal allele asymmetries and to aid calls of genomic events in matched sequencing RNA and DNA datasets.

Contact

P.M.Slowinski@exeter.ac.uk
Uncovering the role of admixture in disease and drug response: Association of hepatocyte gene expression and DNA methylation with African Ancestry in African Americans
Authors: Park CS , De T , Xu Y , Zhong Y , Gamazon ER , Smithberger E , Alarcon C , Perera MA
Published: December 2018

Background

African Americans (AAs) are an admixed population with portions of their genome derived from West Africans and Europeans. In AAs, the proportion of West African ancestry (WAA) can vary widely and may explain the genetic drivers of disease, specifically those that disproportionately affect this understudied population. To examine the relationship between the proportion of WAA and gene expression, we used high dimensional data obtained from AA primary hepatocytes, a tissue important in disease and drug response.

Methods

RNA sequencing (Illumina HiSeq Platform) was conducted on 60 AA-derived primary hepatocytes, with methylation profiling (Illumina MethylationEPIC BeadChip) of 44 overlapping samples. WAA for each sample was calculated using fastSTRUCTURE and correlated to both gene expression and DNA methylation. The GTEx consortium (n = 15) was used for replication and a second cohort (n = 206) was using used for validation using differential gene expression between AAs and European-Americans.

Results

We identified 131 genes associated with WAA (FDR< 0.1), of which 28 gene expression traits were replicated (FDR<0.1) and enriched in angiogenesis and inflammatory pathways (FDR<0.1). These 28 replicated gene expression traits represented 257 GWAS catalog phenotypes. Among the PharmGKB pharmacogenes, VDR, PTGIS, ALDH1A1, CYP2C19 and P2RY1 were associated with WAA (p < 0.05) with replication of CYP2C19 and VDR in GTEx. Association of DNA methylation with WAA identified 1037 differentially methylated regions (FDR<0.05), with hypomethylated genes enriched in drug response pathways. Overlapping of differentially methylated regions with the 131 significantly correlated gene expression traits identified 5 genes with concordant directions of effect: COL26A1, HIC1, MKNK2, RNF135, SNAI1 and TRIM39.

Conclusions

We conclude that WAA contributes to variability in hepatic gene expression and DNA methylation with identified genes indicative of diseases disproportionately affecting AAs. Specifically, WAA-associated genes were linked to previously identified loci in cardiovascular disease (PTGIS, PLAT), renal disease (APOL1) and drug response (CYP2C19).
A Mechanism of Real-Time Noise Modulation in Neurons
Authors: Venugopal Sharmila , Seki Soju , Terman David H , Pantazis Antonios , Olcese Riccardo , Wiedau-Pazos Martina , Chandler Scott H
Published: December 2018

Uncertainties pose an ongoing challenge for information processing in the nervous system. It is not entirely clear how neurons maintain dynamic stability of information, encoded in the temporal features of spike trains, notwithstanding stochastic influences. Here we examined the contribution of subclasses of membrane sodium currents in real-time noise modulation in sensory neurons. Fast sodium (Na+) currents are essential for spike generation, and a persistent Na+ current can entrain preferred input frequencies via membrane resonance. Using mathematical modeling, theory and experiments, we show that a resurgent Na+ current can stabilize the temporal features of burst discharge and confer noise tolerance. These novel insights reckon the role of biophysical properties of Na+ currents beyond mere spike generation. Instead, these mechanisms might be how neurons perform real-time signal processing to maintain order and entropy in neural discharge. Our model analysis further predicts a negative feedback loop in the molecular machinery of an underlying Nav1.6-type Na+ channel gating considered in this study.
Predicting Methylation from Sequence and Gene Expression Using Deep Learning with Attention
Authors: Levy-Jurgenson Alona , Tekpli Xavier , Kristensen Vessela N. , Yakhini Zohar
Published: December 2018

DNA methylation has been extensively linked to alterations in gene expression, playing a key role in the manifestation of multiple diseases, most notably cancer. For this reason, researchers have long been measuring DNA methylation in living organisms. The relationship between methylation and expression, and between methylation in different genomic regions is of great theoretical interest from a molecular biology perspective. Therefore, several models have been suggested to support the prediction of methylation status in samples. These models, however, have two main limitations: (a) they heavily rely on partially measured methylation levels as input, somewhat defeating the object as one is required to collect measurements from the sample of interest before applying the model; and (b) they are largely based on human mediated feature engineering, thus preventing the model from unveiling its own representations. To address these limitations we used deep learning, with an attention mechanism, to produce a general model that predicts DNA methylation for a given sample in any CpG position based solely on the sample's gene expression profile and the sequence surrounding the CpG.

We show that our model is capable of generalizing to a completely separate test set of CpG positions and subjects. Depending on gene-CpG proximity conditions, our model can attain a Spearman correlation of up to 0.8 and MAE of 0.14 for thousands of CpG sites in the test data. We also identify and analyze several motifs and genes that our model suggests may be linked to methylation activity, such as Nodal and Hand1. Moreover, our approach, and most notably the use of attention mechanisms, offers a novel framework with which to extract valuable insights from gene expression data when combined with sequence information.

The code and trained models are available at:https://github.com/YakhiniGroup/Methylation
DEEPScreen: High Performance Drug-Target Interaction Prediction with Convolutional Neural Networks Using 2-D Structural Compound Representations
Authors: Rifaioglu Ahmet Sureyya , Atalay Volkan , Martin Maria Jesus , Cetin-Atalay Rengul , Dogan Tunca
Published: December 2018

The identification of physical interactions between drug candidate chemical substances and target biomolecules is an important step in the process of drug discovery, where the standard procedure is the systematic screening of chemical compounds against pre-selected target proteins. However, experimental screening procedures are expensive and time consuming, therefore, it is not possible to carry out comprehensive tests. Within the last decade, computational approaches have been developed with the objective of aiding experimental studies by predicting novel drug-target interactions (DTI), via the construction and application of statistical models. In this study, we propose a large-scale DTI interaction prediction system, DEEPScreen, for early stage drug discovery, using convolutional deep neural networks. One of the main advantages of DEEPScreen is employing readily available simple 2-D images of compounds at the input level instead of engineered complex feature vectors that displayed limited performance in DTI prediction tasks previously. DEEPScreen learns complex features inherently from the 2-D molecular representations, thus producing highly accurate predictions. DEEPScreen system was trained for 704 target proteins (using ChEMBL curated bioactivity data) and finalized with rigorous hyper-parameter optimization tests. We compared the performance of DEEPScreen against shallow classifiers such as the random forest, logistic regression and support vector machines, to indicate the effectiveness of the proposed deep learning approach. Additionally, we compared DEEPScreen with other deep learning based state-of-the-art DTI predictors on widely used benchmark datasets and showed that DEEPScreen produces better or comparable results to the top performers. The method proposed here can be employed to computationally scan a large portion of the recorded drug candidate compound and protein spaces to aid the experimentalists working in the field of drug discovery and repurposing by providing a preselection of interesting novel DTIs.
Proteomic and Genomic Signatures of Repeat-instability in Cancer and Adjacent Normal Tissues
Authors: Persi Erez , Prandi Davide , Wolf Yuri I. , Pozniak Yair , Barbieri Christopher , Gasperini Paola , Beltran Himisha , Faltas Bishoy M. , Rubin Mark A. , Geiger Tamar , Koonin Eugene V. , Demichelis Francesca , Horn David
Published: December 2018

Repetitive sequences are hotspots of evolution at multiple levels. However, due to technical difficulties involved in their assembly and analysis, the role of repeats in tumor evolution is poorly understood. We developed a rigorous motif-based methodology to quantify variations in the repeat content of proteomes and genomes, directly from proteomic and genomic raw sequence data, and applied it to analyze a wide range of tumors and normal tissues. We identify high similarity between the repeat-instability in tumors and their patient-matched normal tissues, but also tumor-specific signatures, both in protein expression and in the genome, that strongly correlate with cancer progression and robustly predict the tumorigenic state. In a patient, the hierarchy of genomic repeat instability signatures accurately reconstructs tumor evolution, with primary tumors differentiated from metastases. We find an inverse relationship between repeat-instability and point mutation load, within and across patients, and independently of other somatic aberrations. Thus, repeat-instability is a distinct, transient and compensatory adaptive mechanism in tumor evolution.
Novel algorithms for efficient subsequence searching and mapping in nanopore raw signals towards targeted sequencing
Authors: Han Renmin , Wang Sheng , Gao Xin
Published: December 2018

Genome diagnostics have gradually become a prevailing routine for human healthcare. With the advances in understanding the causal genes for many human diseases, targeted sequencing provides a rapid, cost-efficient and focused option for clinical applications, such as SNP detection and haplotype classification, in a specific genomic region. Although nanopore sequencing offers a perfect tool for targeted sequencing because of its mobility, PCR-freeness, and long read properties, it poses a challenging computational problem of how to efficiently and accurately search and map genomic subsequences of interest in a pool of nanopore reads (or raw signals). Due to its relatively low sequencing accuracy, there is no reliable solution to this problem, especially at low sequencing coverage.

Here, we propose a brand new signal-based subsequence inquiry pipeline as well as two novel algorithms to tackle this problem. The proposed algorithms follow the principle of subsequence dynamic time warping and directly operate on the electrical current signals, without loss of information in base-calling. Therefore, the proposed algorithms can serve as a tool for sequence inquiry in targeted sequencing. Two novel criteria are offered for the consequent signal quality analysis and data classification. Comprehensive experiments on real-world nanopore datasets show the efficiency and effectiveness of the proposed algorithms. We further demonstrate the potential applications of the proposed algorithms in two typical tasks in nanopore-based targeted sequencing: SNP detection under low sequencing coverage, and haplotype classification under low sequencing accuracy.
L-Norvaline, a New Therapeutic Agent against Alzheimer’s disease
Authors: Polis Baruh , Srikanth Kolluru D , Gurevich Vyacheslav , Gil-Henn Hava , Samson Abraham O.
Published: December 2018

Alzheimer’s disease (AD) is a slowly progressive neurodegenerative disorder with an insidious onset. The disease is characterized by cognitive impairment and a distinct pathology with neuritic plaques and neurofibrillary tangles.

Growing evidence highlights the role of arginase activity in the manifestation of AD. Upregulation of arginase was shown to contribute to endothelial dysfunction, atherosclerosis, diabetes, and neurodegeneration. Regulation of arginase activity appears to be a promising approach for interfering with the pathogenesis of AD and other metabolic disorders. Therefore, the enzyme represents a novel therapeutic target.

Here, we administer an arginase inhibitor L-norvaline to a mouse model of AD. Then, we evaluate the neuroprotective effect of L-norvaline using immunohistochemistry, proteomics, and quantitative polymerase chain reaction assays. Finally, we identify the biological pathways activated by the treatment.

Remarkably, we find that L-norvaline treatment reverses the cognitive decline in AD mice. We show the treatment is neuroprotective as indicated by reduced beta-amyloidosis, alleviated microgliosis, and TNFα transcription levels. Moreover, elevated levels of neuroplasticity related protein PSD-95 were detected in the hippocampi of mice treated with L-norvaline. Furthermore, we disclose several biological pathways, which are involved in cell survival and neuroplasticity and are activated by the treatment.

Through these modes of action, L-norvaline has the potential to improve the symptoms of AD and even interfere with its pathogenesis. As such, L-norvaline is a promising neuroprotective molecule that might be tailored for the treatment of a range of neurodegenerative disorders.
Selective roles of vertebrate PCF11 in premature and full-length transcript termination
Authors: Kamieniarz-Gdula Kinga , Gdula Michal R , Panser Karin , Nojima Takayuki , Monks Joan , Wiśniewski Jacek R , Riepsaame Joey , Brockdorff Neil , Pauli Andrea , Proudfoot Nick J
Published: December 2018

The pervasive nature of RNA polymerase II (Pol II) transcription requires efficient termination. A key player in this process is the cleavage and polyadenylation (CPA) factor PCF11, which directly binds to the Pol II C-terminal domain and dismantles elongating Pol II from DNA in vitro. We demonstrate that PCF11-mediated termination is essential for vertebrate development. A range of genomic analyses, including: mNET-seq, 3' mRNA-seq, chromatin RNA-seq and ChIP-seq, reveals that PCF11 enhances transcription termination and stimulates early polyadenylation genome-wide. PCF11 binds preferentially between closely spaced genes, where it prevents transcriptional interference and downstream gene silencing. Notably, PCF11 is sub-stoichiometric to the CPA complex. Low levels of PCF11 are maintained by an auto-regulatory mechanism involving premature termination of its own transcript, and are important for normal development. Both in human cell culture and during zebrafish development, PCF11 selectively attenuates the expression of other transcriptional regulators by premature CPA and termination.
A practical method for efficient and optimal production of selenomethionine-labeled recombinant protein complexes in the insect cells
Authors: Wenzel Sabine , Imasaki Tsuyoshi , Takagi Yuichiro
Published: December 2018

The use of Selenomethionine (SeMet) incorporated protein crystals for single or multiwavelength anomalous diffraction (SAD or MAD) to facilitate phasing has become almost synonymous with modern X-ray crystallography. The anomalous signals from SeMets can be used for phasing as well as sequence markers for subsequent model building. The production of large quantities of SeMet incorporated recombinant proteins is relatively straightforward when expressed inE. coli. In contrast, production of SeMet substituted recombinant proteins expressed in the insect cells is not as robust due to the toxicity of SeMet in eukaryotic systems. Previous protocols for SeMet-incorporation in the insect cells are laborious, and more suited for secreted proteins. In addition, these protocols have generally not addressed the SeMet toxicity issue, and typically result in low recovery of the labeled proteins. Here we report that SeMet toxicity can be circumvented by fully infecting insect cells with baculovirus. Quantitatively controlling infection levels using our Titer Estimation of Quality Control (TEQC) method allows for incorporation of substantial amounts of SeMet, resulting in an efficient and optimal production of labeled recombinant protein complexes. With the method described here, we were able to consistently reach incorporation levels of about 75% and protein yield of 60-90% compared to native protein expression.
A Systems Mechanism for KRAS Mutant Allele Specific Responses to Targeted Therapy
Authors: McFall Thomas , Diedrich Jolene K , Mengistu Meron , Littlechild Stacy L , Paskvan Kendra V , Sisk-Hackworth Laura , Moresco James J , Shaw Andrey S , Stites Edward C
Published: December 2018

A well-established genotype to phenotype relationship in genomic medicine is that activating KRAS mutations indicate resistance to anti-EGFR agents. We used a computational model of Ras signaling to investigate a confusing exception to this relationship whereby colorectal cancers with one specific, constitutively-active, mutant, KRAS G13D, respond to anti-EGFR agents. Our computational simulations of the biochemical processes that regulate Ras suggest EGFR inhibition reduces wild-type Ras activation in KRAS G13D mutant cancer cells more than in other KRAS mutant cancer cells. The model also reveals a non-intuitive, mutant-specific, dependency of wild-type Ras activation on EGFR. This dependency is determined by the interaction strength between a KRAS mutant and tumor suppressor neurofibromin. Our prospective experiments confirm this mechanism that arises from the systems-level regulation of Ras pathway signaling. Overall, our work demonstrates how systems approaches enable mechanism-based inference in genomic medicine.
Dense geographic and genomic sampling reveals paraphyly and a cryptic lineage in a classic sibling species complex
Authors: Linck Ethan , Epperly Kevin , van Els Paul , Spellman Garth M. , Bryson Robert W. , Canales-del-Castillo Ricardo , McCormack John E. , Klicka John
Published: December 2018

Incomplete or geographically biased sampling poses significant problems for research in phylogeography, population genetics, phylogenetics, and species delimitation. Despite the power of using genome-wide genetic markers in systematics and related fields, approaches such as the multispecies coalescent remain unable to easily account for unsampled lineages. The Empidonax difficilis / E. occidentalis complex of small tyrannid flycatchers (Aves: Tyrannidae) is a classic example of a widely distributed species with limited phenotypic geographic variation that was broken into two largely cryptic (or sibling) lineages following extensive study. Though the group is well-characterized north of the U.S. Mexico border, the evolutionary distinctiveness and phylogenetic relationships of southern populations remain obscure. In this paper, we use dense genomic and geographic sampling across the majority of the range of the E. difficilis / E . occidentalis complex to assess whether current taxonomy and species limits reflect underlying evolutionary patterns, or whether they are an artifact of historically biased or incomplete sampling. We find that additional samples from Mexico render the widely recognized species-level lineage E. occidentalis paraphyletic, though it retains support in the best-fit species delimitation model from clustering analyses. We further identify a highly divergent unrecognized lineage in a previously unsampled portion of the group's range, which a cline analysis suggests is more reproductively isolated than the currently recognized species E. difficilis and E. occidentalis. Our phylogeny supports a southern origin of these taxa. Our results highlight the pervasive impacts of biased geographic sampling, even in well-studied vertebrate groups like birds, and illustrate what is a common problem when attempting to define species in the face of recent divergence and reticulate evolution.
BOLD signal variability and complexity in children and adolescents with and without autism spectrum disorder
Authors: Easson Amanda K , McIntosh Anthony R
Published: December 2018

Variability of neural signaling is an important index of healthy brain functioning, as is signal complexity, which relates to information processing capacity. It is thought that alterations in variability and complexity may underlie certain brain dysfunctions. Here, resting-state fMRI was used to examine brain signal variability and complexity in male children and adolescents with and without autism spectrum disorder (ASD), a highly heterogeneous neurodevelopmental disorder. Variability was measured using the mean square successive difference (MSSD) of the time series, and complexity of these time series was assessed using sample entropy. A categorical approach was implemented to determine if the brain measures differed between diagnostic groups (ASD and typically developing (TD) groups). A dimensional approach was used to examine the continuum of relationships between each brain measure and behavioural severity, age, IQ, and the global efficiency (GE) of each participant's structural connectome, a metric that reflects the structural capacity for information processing. Using the categorical approach, no significant group differences were found for neither MSSD nor entropy. However, the dimensional approach revealed significant positive correlations between each brain measure, GE, and age. Further, negative correlations were observed between each brain measure and behavioural severity across all participants, whereby lower MSSD and entropy were associated with more severe ASD behaviours. These results reveal the nature of variability and complexity of fMRI signals in children and adolescents with and without ASD, and highlight the importance of taking a dimensional approach when analyzing brain function in ASD.