bluuebunny/crossref_metadata_2025 huggingface dataset:
Chronic Active Epstein-Barr Virus Infection of T/NK-Cell Type Mimicking Classic Hodgkin Lymphoma
Authors: Chen Zihang , Liu Weiping , Zhang Wenyan , Ye Yunxia , Guan Pujun , Gao Limin , Zhao Sha
Published: July 2019

Chronic active Epstein-Barr virus (EBV) infection of T-cell and NK-cell type, systemic form (CAEBV-T/NK-S) is characterized by EBV+ T-cell and/or NK-cell proliferation with no changes suggesting malignancy. Therefore, when Hodgkin/Reed-Sternberg (HRS)-like cells are scattered in CAEBV-T/NK-S, it is more likely to be misdiagnosed as classic Hodgkin lymphoma. We encountered a case wherein the patient showed HRS-like cells with typical NK phenotype. Therefore, we further investigated 8 similar cases to provide clinicopathologic and genetic features and discuss their distinction from other related diseases. Clinically, all cases met the diagnostic criteria of CAEBV. Moreover, 4/8 patients had hemophagocytic lymphohistiocytosis. The median survival was 16 months (range, 5 to 35 mo). Pathologically, all lymph node samples had a remarkably similar morphology with scattered HRS-like cells surrounded by a mixture of small-sized lymphocytes, plasma cells, and macrophages that masqueraded classic Hodgkin lymphoma. Besides, erythrophagocytosis was detected in 4/11 samples. The HRS-like cells were positive for CD2, CD3p, CD30, CD56, GrB, and EBER-ISH, but negative for CD20, CD5, PAX-5, and LMP-1. The surrounding lymphocytes were mainly CD8+ cytotoxic T cells, without obvious aberrant expression. In addition, all patients were polyclonal in the T-cell receptor γ rearrangement test. The harbored mutations were mainly in epigenetic modifiers, JAK-STAT signaling pathway, and apoptosis/cell cycle pathway, including SOCS1, DDX3X, and KMT2D, similar to other EBV-associated T/NK-cell lymphoproliferative disorders. Therefore, the evidence indicates that “HRS-like cells of NK phenotype” is a variant of CAEBV-T/NK-S. This study may raise awareness of such confounding CAEBV-T/N-S cases in clinical practice to avoid misdiagnosis and treatment delay.
Tafenoquine: the new kid on the block
Authors: Chen Victor , Daily Johanna P.
Published: July 2019

Purpose of review

This is a review of tafenoquine, a new antimalarial drug. Here we examine the recent literature supporting the use of tafenoquine and summarize the opportunities and challenges for its well tolerated use worldwide.

Recent findings

Tafenoquine was recently approved by the US Food and Drug Administration for the treatment of dormant liver stage (hypnozoite) in Plasmodium vivax and for malaria prophylaxis. Single-dose tafenoquine provides equivalent efficacy to 14 days of primaquine for radical cure in P. vivax, and it can be dosed weekly to prevent malaria. However, tafenoquine can only be used in patients with normal G6PD activity and is contraindicated in children and during pregnancy or in lactating mothers with infants of deficient or unknown G6PD status.

Tafenoquine's long half-life allows a single dose to achieve radical cure, and weekly dosing for chemoprophylaxis to provide an exciting therapeutic option for patient care and as a new weapon for malaria control/eradication programs. Global implementation of tafenoquine will require the development and validation of a robust, low-cost diagnostic to reliably identify G6PD-deficient individuals. In addition, studies on tafenoquine safety in children are needed.
WHO's new rabies recommendations: implications for high incidence countries
Authors: Pattanaik Amrita , Mani Reeta S.
Published: July 2019

Purpose of review

Rabies is virtually always fatal; however, it is nearly 100% preventable with timely and appropriate prophylactic immunization. This review summarizes the recently revised WHO guidelines for rabies prophylaxis published in 2018, following a scientific review by a strategic advisory group of experts on immunization. The scientific basis for the major changes and its implications for countries with high disease burden are also discussed.

Recent findings

The key changes in the updated WHO 2018 guidelines for rabies prophylaxis include abbreviated vaccination regimens for pre and postexposure prophylaxis. These cost and dose-sparing regimens allow equitable sharing of vaccines, necessitate fewer clinic visits and thus can enhance patient compliance. The recommendations on rabies immunoglobulin administration permit prioritization and optimal use of this life-saving biologic, especially in areas with scarcity. However, there is a need for additional evidence to support the abridgment of some regimens and need for data on the safety and immunogenicity of these regimens in special groups such as infants and the immunocompromised.

National health authorities in high incidence countries need to develop consensus for effective implementation of simplified, cost-effective, and logistically feasible regimens for rabies prophylaxis, on the basis of the revised WHO guidelines.
Type 2 Diabetes Interacts With Alzheimer Disease Risk Factors to Predict Functional Decline
Authors: Thomas Kelsey R. , Bangen Katherine J. , Weigand Alexandra J. , Edmonds Emily C. , Sundermann Erin , Wong Christina G. , Eppig Joel , Werhane Madeleine L. , Delano-Wood Lisa , Bondi Mark W.
Published: July 2019

Objective:

The current study examined the interactive effect of type 2 diabetes and Alzheimer disease (AD) risk factors on the rate of functional decline in cognitively normal participants from the Alzheimer’s Disease Neuroimaging Initiative.

Methods:

Participants underwent annual assessments that included the Functional Activities Questionnaire, an informant-rated measure of everyday functioning. Multilevel modeling, controlling for demographic variables and ischemic risk, examined the interactive effects of diabetes status (diabetes, n=69; no diabetes, n=744) and AD risk factors in the prediction of 5-year longitudinal change in everyday functioning. One model was run for each AD risk factor, including: objectively-defined subtle cognitive decline (Obj-SCD), and genetic susceptibility [apolipoprotein E ε4 (APOE ε4) as well as cerebrospinal fluid β-amyloid (Aβ), total tau (tau), and hyperphosphorylated tau (p-tau).

Results:

The 3-way diabetes×AD risk factor×time interaction predicted increased rates of functional decline in models that examined Obj-SCD, APOE ε4, tau, and p-tau positivity, but not Aβ positivity.

Conclusions:

Participants with both diabetes and at least 1 AD risk factor (ie, Obj-SCD, APOE ε4, tau, and p-tau positivity) demonstrated faster functional decline compared with those without both risk factors (diabetes or AD). These findings have implications for early identification of, and perhaps earlier intervention for, diabetic individuals at risk for future functional difficulty.
P-hacking in clinical trials and how incentives shape the distribution of results across phases*
Authors: Adda Jérôme , Decker Christian , Ottaviani Marco
Published: July 2019

Clinical research should conform to high standards of ethical and scientific integrity, given that human lives are at stake. However, economic incentives can generate conflicts of interest for investigators, who may be inclined to withhold unfavorable results or even tamper with data in order to achieve desired outcomes. To shed light on the integrity of clinical trial results, this paper systematically analyzes the distribution of p-values of primary outcomes for phase II and phase III drug trials reported to theClinicalTrials.govregistry. First, we detect no bunching of results just above the classical 5% threshold for statistical significance. Second, a density discontinuity test reveals an upward jump at the 5% threshold for phase III results by small industry sponsors. Third, we document a larger fraction of significant results in phase III compared to phase II. Linking trials across phases, we find that early favorable results increase the likelihood of continuing into the next phase. Once we take into account this selective continuation, we can explain almost completely the excess of significant results in phase III for trials conducted by large industry sponsors. For small industry sponsors, instead, part of the excess remains unexplained.
High Resolution Tomographic Analysis of in vitro 3D Glioblastoma Tumor Model under Long-Term Drug Treatment
Authors: Ozturk Mehmet S. , Lee Vivian K. , Zou Hongyan , Friedel Roland H. , Dai Guohao , Intes Xavier
Published: July 2019

Glioblastoma multiforme (GBM) is an extremely lethal type of brain tumor as it frequently develops therapeutic resistance over months of chemotherapy cycles. Hence, there is a critical need to provide relevant biological systems to guide the development of new potent personalized drugs but also efficient methodologies that enable personalized prediction of various therapeutic regimens for enhanced patient prognosis. Towards this goal, we report on the development of i) an appropriate in vitro model that mimics the 3D tumor microenvironment and ii) a companion imaging modality that enables to assess this in vitro model in its entirety. More precisely, we developed an integrated platform of bio-printing in vitro 3D GBM models and mesoscopic imaging to monitor tumor growth and invasion along with long-term drug treatment. The newly-developed in vitro 3D model contains tumor spheroids made of patient-derived glioma stem cells with a fluorescent reporter and vascular channels for drug perfusion. The imaging of these thick tissue constructs was performed using our second-Generation Mesoscopic Fluorescence Molecular Tomography (2GMFMT) imaging system which delivered 3D reconstruction of the fluidic channels and the GBM spheroids over the course of pre- and post-drug treatment (up to 70 days). The 2D measurements collected via 2GMFMT was comparable to existing imaging modalities, but 2GMFMT enabled non-sacrificial volumetric monitoring that provided a unique insgiht into the GBM spheroid growth and drug response. Overall, our integrated platform provides customizable in vitro model systems combined with an efficient long-term non-sacrificial imaging for the volumetric change of tumor mass, thus has a great potential in profoundly affecting the drug pipeline for a vast array of pathologies as well as for guiding personalized therapeutic regimen.
Deep learning regression model for antimicrobial peptide design
Authors: Witten Jacob , Witten Zack
Published: July 2019

Antimicrobial peptides (AMPs) are naturally occurring or synthetic peptides that show promise for treating antibiotic-resistant pathogens. Machine learning techniques are increasingly used to identify naturally occurring AMPs, but there is a dearth of purely computational methods to design novel effective AMPs, which would speed AMP development. We collected a large database, Giant Repository of AMP Activities (GRAMPA), containing AMP sequences and associated MICs. We designed a convolutional neural network to perform combined classification and regression on peptide sequences to quantitatively predict AMP activity against Escherichia coli. Our predictions outperformed the state of the art at AMP classification and were also effective at regression, for which there were no publicly available comparisons. We then used our model to design novel AMPs and experimentally demonstrated activity of these AMPs against the pathogens E. coli, Pseudomonas aeruginosa, and Staphylococcus aureus. Data, code, and neural network architecture and parameters are available at https://github.com/zswitten/Antimicrobial-Peptides.
Proliferation specific codon usage facilitates oncogene translation
Authors: Benisty Hannah , Weber Marc , Hernandez-Alias Xavier , Schaefer Martin H. , Serrano Luis
Published: July 2019

Tumors evolve under selection for gene mutations that give a growth advantage to the cancer cell. Intriguingly, some cancer genes are more often found mutated in tumors than their closely related family members. For example, KRAS mutations are more frequently observed in cancer in comparison to HRAS and NRAS. Here, we find that for RAS and six oncogene families, the most prevalent mutated members in cancer have a codon usage characteristic of genes involved in proliferation. The codon usage of KRAS is more adapted to be efficiently translated in proliferative cells than the codon usage of HRAS. We also show that the translation efficiency of KRAS varies between cell lines in a manner related to their tRNA expression. Altogether, our study demonstrates that a dynamic translation program contributes to shaping the expression profiles of oncogenes. We propose that codon bias related to cell proliferation contributes to the prevalence of mutations in certain members of oncogene families.
Genome-wide interologous interactome map (TeaGPIN) ofCamellia sinensis
Authors: Singh Gagandeep , Singh Vikram , Singh Vikram
Published: July 2019

Tea, prepared from the young leaves ofCamellia sinensis, is a non-alcoholic beverage globally consumed due to its antioxidant properties, strong taste and aroma. Although, the genomic data of this medicinally and commercially important plant is available, studies related to its sub-cellular interactomic maps are less explored. In this work, we propose a genome-wide interologous protein-protein interaction (PPI) network of tea, termed as TeaGPIN, consisting of 12,033 nodes and 216,107 interactions, developed using draft genome of tea and known PPIs exhaustively collected from 49 template plants. TeaGPIN interactions are prioritized using domain-domain interactions along with the interolog information. A high-confidence TeaGPIN consisting of 5,983 nodes and 58,867 edges is reported and its interactions are further evaluated using protein co-localization similarities. Based on three network centralities (degree, betweenness and eigenvector), 1,302 key proteins are reported in tea to havep-value < 0.01 by comparing the TeaGPIN with 10,000 realizations of Erdős-Rényi and Barabási-Albert based corresponding random network models. Functional content of TeaGPIN is assessed using KEGG and GO annotations and its modular architecture is explored. Network based characterization is carried-out on the transcription factors, and proteins involved flavonoid biosynthesis and photosynthesis pathways to find novel candidates involved in various regulatory processes. We believe the proposed TeaGPIN will impart useful insights in understanding various mechanisms related to growth and development as well as defence against biotic and abiotic perturbations.
Accurate and Sensitive Quantitation of the Dynamic Heat Shock Proteome using Tandem Mass Tags
Authors: Storey Aaron J. , Hardman Rebecca E. , Byrum Stephanie D. , Mackintosh Samuel G. , Edmondson Rick D. , Wahls Wayne P. , Tackett Alan J. , Lewis Jeffrey A.
Published: July 2019

Cells respond to environmental perturbations and insults through modulating protein abundance and function. However, the majority of studies have focused on changes in RNA abundance because quantitative transcriptomics has historically been more facile than quantitative proteomics. Modern Orbitrap mass spectrometers now provide sensitive and deep proteome coverage, allowing direct, global quantification of not only protein abundance, but also post-translational modifications (PTMs) that regulate protein activity. We implemented, and validated using the well-characterized heat shock response of budding yeast, a tandem mass tagging (TMT), triple-stage mass spectrometry (MS3) strategy to measure global changes in the proteome during the yeast heat shock response over nine timepoints. We report that basic pH, ultra-high performance liquid chromatography (UPLC) fractionation of tryptic peptides yields superfractions of minimal redundancy, a crucial requirement for deep coverage and quantification by subsequent LC-MS3. We quantified 2,275 proteins across 3 biological replicates, and found that differential expression peaked near 90 minutes following heat shock (with 868 differentially expressed proteins at 5% FDR). The sensitivity of the approach also allowed us to detect changes in the relative abundance of ubiquitination and phosphorylation PTMs over time. Remarkably, relative quantification of post-translationally modified peptides revealed striking evidence of regulation of the heat shock response by protein PTMs. These data demonstrate that the high precision of TMT-MS3enables peptide-level quantification of samples, which can reveal important regulation of protein abundance and regulatory PTMs under various experimental conditions.
An optimized competitive-aging method reveals gene-drug interactions underlying the chronological lifespan of Saccharomyces cerevisiae
Authors: Avelar-Rivas J. Abraham , Munguía-Figueroa Michelle , Juárez-Reyes Alejandro , Garay Erika , Campos Sergio E. , Shoresh Noam , DeLuna Alexander
Published: July 2019

The chronological lifespan of budding yeast is a model of aging and age-related diseases. This paradigm has recently allowed genome-wide screening of genetic factors underlying post-mitotic viability in a simple unicellular system, which underscores its potential to provide a comprehensive view of the aging process. However, results from different large-scale studies show little overlap and typically lack quantitative resolution to derive interactions among different aging factors. We previously introduced a sensitive, parallelizable approach to measure the chronological-lifespan effects of gene deletions based on the competitive aging of fluorescence-labeled strains. Here, we present a thorough description of the method, including an improved multiple-regression model to estimate the association between death rates and fluorescent signals, which accounts for possible differences in growth rate and experimental batch effects. We illustrate the experimental procedure—from data acquisition to calculation of relative survivorship—for ten deletion strains with known lifespan phenotypes, which is achieved with high technical replicability. We apply our method to screen for gene-drug interactions in an array of yeast deletion strains, which reveals a functional link between protein glycosylation and lifespan extension by metformin. Competitive-aging screening coupled to multiple-regression modeling provides a powerful, straight-forward way to identify aging factors in yeast and their interactions with pharmacological interventions.
Decoding brain functional connectivity implicated in AD and MCI
Authors: Gupta Sukrit , Chan Yi Hao , Rajapakse Jagath C. ,   the Alzheimers Disease Neuroimaging Initiative
Published: July 2019

Deep neural networks have been demonstrated to extract high level features from neuroimaging data when classifying brain states. Identifying salient features characterizing brain states further refines the focus of clinicians and allows design of better diagnostic systems. We demonstrate this while performing classification of resting-state functional magnetic resonance imaging (fMRI) scans of patients suffering from Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI), and Cognitively Normal (CN) subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We use a 5-layer feed-forward deep neural network (DNN) to derive relevance scores of input features and show that an empirically selected subset of features improves accuracy scores for patient classification. The common distinctive salient brain regions were in the uncus and medial temporal lobe which closely correspond with previous studies. The proposed methods have cross-modal applications with several neuropsychiatric disorders.
Temporal changes in genetic admixture are linked to heterozygosity and health diagnoses in humans
Authors: Mautz Brian S. , Hellwege Jacklyn N. , Li Chun , Xu Yaomin , Zhang Siwei , Denny Joshua C. , Roden Dan M. , McGregor Tracy L. , Velez Edwards Digna R. , Edwards Todd L.
Published: July 2019

Reproduction between individuals from different ancestral populations creates genetically admixed offspring. Admixture can have positive and negative impacts on individual health, feeding back to population health. Historical and forced migrations, and recent mobility, have brought formerly disparate populations of humans together. Here we sought to better understand how temporal changes in genetic admixture influence levels of heterozygosity and health outcomes. We evaluated variation in ancestry over 100 birth years in 35,842 individuals from a genetic database linked to health records in a population in the Southeastern United States. Analysis of 2,678 ancestrally informative markers revealed increased admixture and heterozygosity for all clinically-defined race groups since 1990. Most groups also exhibited increasing long-range linkage disequilibrium over time. A phenome-wide association study of clinical outcomes detected protective associations with female reproductive disorders and increased risk for diseases with links to autoimmunity dysfunction. These mixed effects have important ramifications for human health.
HIV-1 Nef interacts with LMP7 to attenuate immunoproteasome formation and MHC-I antigen presentation
Authors: Yang Yang , Liu Weiyong , Hu Dan , Su Rui , Ji Man , Huang Yuqing , Shereen Muhammad Adnan , Xu Xiaodi , Luo Zhen , Zhang Qi , Liu Fang , Wu Kailang , Liu Yingle , Wu Jianguo
Published: July 2019

Abstract

Proteasome is major protein degradation machinery and plays essential roles in diverse biological functions. Upon cytokine inductions, proteasome subunits β1, β2, and β5 are replaced by β1i/LMP2, β2i/MECL-1, and β5i/LMP7, leading to the formation of immunoproteasome. Immunoproteasome-degraded products are loaded onto the major histocompatibility complex class I (MHC-I) to regulate immune responses and induce cytotoxic-T-lymphocytes (CTLs). Human immunodeficiency virus type 1 (HIV-1) is the causal agent of acquired immunodeficiency syndrome (AIDS). HIV-1-specific CTLs represent critical immune responses to limit viral replication. HIV-1 negative regulatory factor (Nef) counteracts host immunity, especially the MHC-I/CTL. This study reveals a distinct mechanism by which Nef facilitates immune evasion through attenuating the functions of immunoproteasome and MHC-I. Nef interacts with LMP7 on the endoplasmic reticulum (ER) to down-regulate the incorporation of LMP7 into immunoproteasome, and thereby attenuating immunoproteasome formation. Moreover, Nef represses immunoproteasome protein degradation function, MHC-I trafficking, and antigen presentation activity.

Importance

Ubiquitin-proteasome system (UPS) is essential for degradation of damaged proteins, which takes place in proteasome. Upon cytokine inductions, proteasome catalytic activities are replaced by distinct isoforms resulting in formation of immunoproteasome. Immunoproteasome generates peptides for MHC-I antigen presentation and plays important roles in immune responses. HIV-1 is the agent of AIDS, and HIV-1-specific CTLs represent immune responses to limit viral replication. This study reveals a distinct mechanism by which HIV-1 promotes immune evasion. Viral protein Nef interacts with immunoproteasome component LMP7 to attenuate immunoproteasome formation and protein degradation function, and repress MHC-I antigen presentation activity. Therefore, HIV-1 targets LMP7 to inhibit immunoproteasome activation and LMP7 may be used as a target for the development of anti-HIV-1/AIDS therapy.
VolcanoFinder: genomic scans for adaptive introgression
Authors: Setter Derek , Mousset Sylvain , Cheng Xiaoheng , Nielsen Rasmus , DeGiorgio Michael , Hermisson Joachim
Published: July 2019

Recent research shows that introgression between closely-related species is an important source of adaptive alleles for a wide range of taxa. Typically, detection of adaptive introgression from genomic data relies on comparative analyses that require sequence data from both the recipient and the donor species. However, in many cases, the donor is unknown or the data is not currently available. Here, we introduce a genome-scan method—VolcanoFinder—to detect recent events of adaptive introgression using polymorphism data from the recipient species only.

VolcanoFinderdetects adaptive introgression sweeps from the pattern of excess intermediate-frequency polymorphism they produce in the flanking region of the genome, a pattern which appears as a volcano-shape in pairwise genetic diversity.

Using coalescent theory, we derive analytical predictions for these patterns. Based on these results, we develop a composite-likelihood test to detect signatures of adaptive introgression relative to the genomic background. Simulation results show thatVolcanoFinderhas high statistical power to detect these signatures, even for older sweeps and for soft sweeps initiated by multiple migrant haplotypes. Finally, we implementVolcanoFinderto detect archaic introgression in European and sub-Saharan African human populations, and uncovered interesting candidates in both populations, such asTSHRin Europeans andTCHH-RPTNin Africans. We discuss their biological implications and provide guidelines for identifying and circumventing artifactual signals during empirical applications ofVolcanoFinder.

Author summary

The process by which beneficial alleles are introduced into a species from a closely-related species is termed adaptive introgression. We present an analytically-tractable model for the effects of adaptive introgression on non-adaptive genetic variation in the genomic region surrounding the beneficial allele. The result we describe is a characteristic volcano-shaped pattern of increased variability that arises around the positively-selected site, and we introduce an open-source methodVolcanoFinderto detect this signal in genomic data. Importantly,VolcanoFinderis a population-genetic likelihood-based approach, rather than a comparative-genomic approach, and can therefore probe genomic variation data from a single population for footprints of adaptive introgression, even froma prioriunknown and possibly extinct donor species.
Guidelines for cell-type heterogeneity quantification based on a comparative analysis of reference-free DNA methylation deconvolution software
Authors: Decamps Clementine , Privé Florian , Bacher Raphael , Jost Daniel , Waguet Arthur ,   HADACA consortium, Houseman Eugene Andres , Lurie Eugene , Lutsik Pavlo , Milosavljevic Aleksandar , Scherer Michael , Blum Michael G.B. , Richard Magali
Published: July 2019

Cell-type heterogeneity of tumors is a key factor in tumor progression and response to chemotherapy. Tumor cell-type heterogeneity, defined as the proportion of the various cell-types in a tumor, can be inferred from DNA methylation of surgical specimens. However, confounding factors known to associate with methylation values, such as age and sex, complicate accurate inference of cell-type proportions. While reference-free algorithms have been developed to infer cell-type proportions from DNA methylation, a comparative evaluation of the performance of these methods is still lacking.

Here we use simulations to evaluate several computational pipelines based on the software packages MeDeCom, EDec, and RefFreeEWAS. We identify that accounting for confounders, feature selection, and the choice of the number of estimated cell types are critical steps for inferring cell-type proportions. We find that removal of methylation probes which are correlated with confounder variables reduces the error of inference by 30-35%, and that selection of cell-type informative probes has similar effect. We show that Cattell’s rule based on the scree plot is a powerful tool to determine the number of cell-types. Once the pre-treatment steps are achieved, the three deconvolution methods provide comparable results. We observe that all the algorithms’ performance improves when inter-sample variation of cell-type proportions is large or when the number of available samples is large. We find that under specific circumstances the methods are sensitive to the initialization method, suggesting that averaging different solutions or optimizing initialization is an avenue for future research. Based on the lessons learned, to facilitate pipeline validation and catalyze further pipeline improvement by the community, we develop a benchmark pipeline for inference of cell-type proportions and implement it in the R packagemedepir.
The place-cell representation of volumetric space in rats
Authors: Grieves Roddy M. , Jedidi-Ayoub Selim , Mishchanchuk Karyna , Liu Anyi , Renaudineau Sophie , Jeffery Kate J.
Published: July 2019

Place cells are spatially modulated neurons found in the hippocampus that underlie spatial memory and navigation: how these neurons represent 3D space is crucial for a full understanding of spatial cognition. We wirelessly recorded place cells in rats as they explored a cubic lattice climbing frame which could be aligned or tilted with respect to gravity. Place cells represented the entire volume of the mazes: their activity tended to be aligned with the maze axes, and when it was more difficult for the animals to move vertically the cells represented space less accurately and less stably. These results demonstrate that even surface-dwelling animals represent 3D space and suggests there is a fundamental relationship between environment structure, gravity, movement and spatial memory.
PDAC-ANN: an artificial neural network to predict Pancreatic Ductal Adenocarcinoma based on gene expression
Authors: Almeida Palloma Porto , Cardoso Cristina Padre , de Freitas Leandro Martins
Published: July 2019

Background

Although the pancreatic ductal adenocarcinoma (PDAC) presents high mortality and metastatic potential, there is a lack of effective therapies and a low survival rate for this disease. This PDAC scenario urges new strategies for diagnosis, drug targets, and treatment.

Methods

We performed a gene expression microarray meta-analysis of the tumor against healthy tissues in order to identify differentially expressed genes shared among all datasets, named core-genes (CG). We confirmed the pancreatic expressed proteins of the CG through The Human Protein Atlas. The five most expressed proteins in the tumor group were selected to train an artificial neural network to classify samples.

Results

This microarray included 110 tumor and 77 healthy samples. We identified a CG composed of 60 genes, 58 upregulated and two downregulated. The upregulated CG included proteins and extracellular matrix receptors linked to actin cytoskeleton reorganization. With the Human Protein Atlas, we verified that thirteen genes of the CG are translated, with high or medium expression in most of the pancreatic tumor samples. To train our artificial neural network, we used the five most expressed genes (KRT19, LAMC2, MELK, MET, TOP2A). The artificial neural network model (PDAC-ANN) classified the train samples with sensitivity of 0.95, specificity of 0.9, and f1-score of 0.93. The PDAC-ANN could classify the test samples with a sensitivity of 0.97, specificity of 0.88, and f1-score 0.94.

Conclusion

The gene expression meta-analysis and confirmation of the protein expression allow us to select five genes highly expressed PDAC samples. We could build a python script to classify the samples based on mRNA expression. This software can be useful in the PDAC diagnosis.
Cell growth kinetics and accumulation of secondary metabolite of Bletilla striata Rchb.f. using cell suspension culture
Authors: Pan Yinchi , Xu Delin , Xiao Shiji , Chen Zhongjie , Sarsaiya Surendra , Zhang Shebo , ShangGuan Yanni , Liu Houbo , Li Lin , Chen Jishuang
Published: July 2019

Bletilla striata (Orchidaceae) is a well-recognized endangered medicinal plant due to inadequate natural reproduction with high market worth. To evaluate the cell growth kinetics and accumulation of secondary metabolites (SMs), the cell suspension culture is proved to be a valuable approach for acquiring the high yield of medicinal parts. An effective cell suspension culture for obtaining B. striata cell growth and its SMs was in vitro induction of callus from B. striata seeds. The cell growth kinetics and accumulation of SMs were analyzed using the mathematical model. Results cell growth kinetic model revealed that the growth curve of B. striata suspension cells was curved as sigmoid shape, indicating the changes of the growth curve of suspension cells. Improved Murashige and Skoog cell growth medium was the utmost favorable medium for B. striata callus formation with the highest cell growth during the stationary phase of cultivation period, the cell growth acceleration was started after 7 days and thereafter gradually decrease at 24 day and then reached to highest at 36 day of cultivation period in both dry weight and fresh weight. The coelonin concentration was peak during exponential growth stage and decreased afterward at the stationary phase in the cell suspension culture. The maximum content of coelonin (about 0.3323 mg/g cell dry weight) was observed on the 18th day of the cultivation cycle while the dactylorhin A and militarine reached highest at 24 day, and p-hydroxybenzyl alcohol at 39 day. This investigation also laid a foundation for multi-mathematical model to better describe the accumulation variation of SMs. The production of SMs had shown great specificity during cells growth and development. This research provided a well-organized way to more accumulation and production of SMs, on scale-up biosynthesis in B. striata cell suspension culture.
TMT-Opsins differentially modulate medaka brain function in a context-dependent manner
Authors: Fontinha Bruno M. , Zekoll Theresa , Al-Rawi Mariam , Gallach Miguel , Reithofer Florian , Barker Alison J. , Hofbauer Maximilian , Fischer Ruth M. , von Haeseler Arndt , Baier Herwig , Tessmar-Raible Kristin
Published: July 2019

Vertebrate behavior is strongly influenced by light. Light receptors, encoded by functional Opsin proteins, are present inside the vertebrate brain and peripheral tissues. This expression feature is present from fishes to human and appears to be particularly prominent in diurnal vertebrates. Despite their conserved widespread occurrence, the non-visual functions of Opsins are still largely enigmatic. This is even more apparent when considering the high number of Opsins. Teleosts possess around 40 Opsin genes, present from young developmental stages to adulthood. Many of these Opsins have been shown to function as light receptors. This raises the question, if this large number might mainly reflect functional redundancy or rather maximally enables teleosts to optimally use the complex light information present under water. We focus ontmt-opsin1bandtmt-opsin2, c-Opsins with ancestral-type sequence features, conserved across several vertebrate phyla, expressed with partly similar expression in non-rod, non-cone, non-RGCs brain tissues and a similar spectral sensitivity. The characterization of the single mutants revealed age- and light-dependent behavioral changes, as well as an impact on the levels of the preprohormonesst1band the voltage-gated sodium channel subunitscn12aa.The amount of day-time rest is affected independently of eyes, pineal and the circadian clock intmt-opsin1bmutants. We further focused on day-time behavior and the molecular changes intmt-opsin1b/2double mutants, and revealed that – despite their similar expression and spectral features– these Opsins interact in part non-additively. Specifically, double mutants complement molecular and (age-dependently) behavioral phenotypes observed in single mutants.Our work provides a starting point to disentangle the highly complex interactions of vertebrate non-visual Opsins, suggesting thattmt-opsin-expressing cells together with other visual and non-visual Opsins provide detailed light information to the organism for behavioral fine-tuning. This work also provides a stepping stone to unravel how vertebrate species with conserved Opsins, but in different ecological niches respond to similar light cues and how human generated artificial light might impact on behavioral processes in natural environments.
From Single Neurons to Behavior in the JellyfishAurelia aurita
Authors: Pallasdies Fabian , Goedeke Sven , Braun Wilhelm , Memmesheimer Raoul-Martin
Published: July 2019

Jellyfish nerve nets provide insight into the origins of nervous systems, as both their taxonomic position and their evolutionary age imply that jellyfish resemble some of the earliest neuron-bearing, actively-swimming animals. Here we develop the first neuronal network model for the nerve nets of jellyfish. Specifically, we focus on the moon jellyAurelia auritaand the control of its energy-eZcient swimming motion. The proposed single neuron model disentangles the contributions of different currents to a spike. The network model identifies factors ensuring non-pathological activity and suggests an optimization for the transmission of signals. After modeling the jellyfish’s muscle system and its bell in a hydrodynamic environment, we explore the swimming elicited by neural activity. We find that different delays between nerve net activations lead to well-controlled, differently directed movements. Our model bridges the scales from single neurons to behavior, allowing for a comprehensive understanding of jellyfish neural control.
Comparative evaluation of full-length isoform quantification from RNA-Seq
Authors: Sarantopoulou Dimitra , Brooks Thomas G. , Nayak Soumyashant , Mrcela Anthonijo , Lahens Nicholas F. , Grant Gregory R.
Published: July 2019

Full-length isoform quantification from RNA-Seq is a key goal in transcriptomics analyses and has been an area of active development since the beginning. The fundamental difficulty stems from the fact that RNA transcripts are long, while RNA-Seq reads are short. Here we use simulated benchmarking data that reflects many properties of real data, including polymorphisms, intron signal and non-uniform coverage, allowing for systematic comparative analyses of isoform quantification accuracy and its impact on differential expression analysis. Genome, transcriptome and pseudo alignment-based methods are included; and a simple approach is included as a baseline control. Salmon, kallisto, RSEM, and Cufflinks exhibit the highest accuracy on idealized data, while on more realistic data they do not perform dramatically better than the simple approach. We determine the structural parameters with the greatest impact on quantification accuracy to be length and sequence compression complexity and not so much the number of isoforms. The effect of incomplete annotation on performance is also investigated. Overall, the tested methods show sufficient divergence from the truth to suggest that full-length isoform quantification and isoform level DE should still be employed selectively.
Evolclust: automated inference of evolutionary conserved gene clusters in eukaryotes
Authors: Marcet-Houben Marina , Gabaldón Toni
Published: July 2019

Motivation

The evolution and role of gene clusters in eukaryotes is poorly understood. Currently, most studies and computational prediction programs limit their focus to specific types of clusters, such as those involved in secondary metabolism.

Results

We present Evolclust, a python-based tool for the inference of evolutionary conserved gene clusters from genome comparisons, independently of the function or gene composition of the cluster. Evolclust predicts conserved gene clusters from pairwise genome comparisons and infers families of related clusters from multiple (all vs all) genome comparisons.

Availability

https://github.com/Gabaldonlab/EvolClust/

Contact

tgabaldon@crg.es
Functional module detection through integration of single-cell RNA sequencing data with protein–protein interaction networks
Authors: Klimm Florian , Toledo Enrique M. , Monfeuga Thomas , Zhang Fang , Deane Charlotte M. , Reinert Gesine
Published: July 2019

Recent advances in single-cell RNA sequencing (scRNA-seq) have allowed researchers to explore transcriptional function at a cellular level. In this study, we present scPPIN, a method for integrating single-cell RNA sequencing data with protein–protein interaction networks (PPINs) that detects active modules in cells of different transcriptional states. We achieve this by clustering RNA-sequencing data, identifying differentially expressed genes, constructing node-weighted PPINs, and finding the maximum-weight connected subgraphs with an exact Steiner-tree approach. As a case study, we investigate RNA-sequencing data from human liver spheroids but the techniques described here are applicable to other organisms and tissues. scPPIN allows us to expand the output of differential expressed genes analysis with information from protein interactions. We find that different transcriptional states have different subnetworks of the PPIN significantly enriched which represent biological pathways. In these pathways, scPPIN also identifies proteins that are not differentially expressed but have a crucial biological function (e.g., as receptors) and therefore reveals biology beyond a standard differentially expressed gene analysis.
Sequencing, de novo assembly and annotation of the genome of the scleractinian coral, Pocillopora acuta
Authors: Vidal-Dupiol Jeremie , Chaparro Cristian , Pratlong Marine , Pontarotti Pierre , Grunau Christoph , Mitta Guillaume
Published: July 2019

Coral reefs are the most divers marine ecosystem. However, under the pressure of global changes and anthropogenic disturbances corals and coral reefs are declining worldwide. In order to better predict and understand the future of these organisms all the tools of modern biology are needed today. However, many NGS based approaches are not feasible in corals because of the lack of reference genomes. Therefore we have sequenced, de novo assembled, and annotated, the draft genome of one of the most studied coral species, Pocillopora acuta (ex damicornis). The sequencing strategy was based on four libraries with complementary insert size and sequencing depth (180pb, 100x; 3Kb, 25x; 8kb, 12x and 20 kb, 12x). The de novo assembly was performed with Platanus (352 Mb; 25,553 scaffolds; N50 171,375 bp). 36,140 genes were annotated by RNA-seq data and 64,558 by AUGUSTUS (Hidden-Markov model). Gene functions were predicted through Blast and orthology based approaches. This new genomic resource will enable the development of a large array of genome wide studies but also shows that the de novo assembly of a coral genome is now technically feasible and economically realistic.
Hierarchical chromatin organization detected by TADpole
Authors: Soler-Vila Paula , Pons Pol Cuscó , Farabella Irene , Di Stefano Marco , Marti-Renom Marc A.
Published: July 2019

The rapid development of chromosome conformation capture (3C-based) techniques as well as super-resolution imaging together with bioinformatics analyses has been fundamental for unveiling that chromosomes are organized into the so-called topologically associating domains or TADs. While these TADs appear as nested patterns in the 3C-based interaction matrices, the vast majority of available computational methods are based on the hypothesis that TADs are individual and unrelated chromatin structures. Here we introduce TADpole, a computational tool designed to identify and analyze the entire hierarchy of TADs in intra-chromosomal interaction matrices. TADpole combines principal component analysis and constrained hierarchical clustering to provide an unsupervised set of significant partitions in a genomic region of interest. TADpole identification of domains is robust to the data resolution, normalization strategy, and sequencing depth. TADpole domain borders are enriched in CTCF and cohesin binding proteins, while the domains are enriched in either H3K36me3 or H3k27me3 histone marks. We show TADpole usefulness by applying it to capture Hi-C experiments in wild-type and mutant mouse strains to pinpoint statistically significant differences in their topological structure.
Mast seeding promotes evolution of scatter-hoarding
Authors: Zwolak Rafał , Clement Dale , Sih Andrew , Schreiber Sebastian J.
Published: July 2019

Many plant species worldwide are dispersed by scatterhoarding granivores: animals that hide seeds in numerous, small caches for future consumption. Yet, the evolution of scatterhoarding is difficult to explain because undefended caches are at high risk of pilferage. Previous models have attempted to solve this problem by giving cache owners large advantages in cache recovery, by kin selection, or by introducing reciprocal pilferage of “shared” seed resources. However, the role of environmental variability has been so far overlooked in this context. One important form of such variability is masting, which is displayed by many plant species dispersed by scatterhoarders. We use a mathematical model to investigate the influence of masting on the evolution of scatter-hoarding. The model accounts for periodically varying annual seed fall, caching and pilfering behavior, and the demography of scatterhoarders. The parameter values are based mostly on research on European beech (Fagus sylvatica) and yellow-necked mice (Apodemus flavicollis). Starvation of scatterhoarders between mast years decreases the population density that enters masting events, which leads to reduced seed pilferage. Satiation of scatterhoarders during mast events lowers the reproductive cost of caching (i.e. the cost of caching for the future rather than using seeds for current reproduction). These reductions promote the evolution of scatter-hoarding behavior especially when interannual variation in seed fall and the period between masting events are large.
HLA upregulation during dengue virus infection suppresses the natural killer cell response
Authors: McKechnie Julia L. , Beltran Davis , Pitti Arcelys , Saenz Lisseth , Araúz Ana B. , Vergara Rosemary , Harris Eva , Lanier Lewis L. , Blish Catherine A. , López-Vergès Sandra
Published: July 2019

Dengue virus (DENV) is the most prevalent mosquito-borne virus in the world and a major cause of morbidity in the tropics and subtropics. Upregulation of HLA class I molecules has long been considered a feature of DENV infection, yet this has not been evaluated in the setting of natural infection. Natural killer (NK) cells, an innate immune cell subset critical for mounting an early response to viral infection, are inhibited by self HLA class I, suggesting that upregulation of HLA class I during DENV infection could dampen the NK cell response. Here we addressed whether upregulation of HLA class I molecules occurs duringin vivoDENV infection and, if so, whether this suppresses the NK cell response. We found that HLA class I expression was indeed upregulated during acute DENV infection across multiple cell lineagesin vivo. To better understand the role of HLA class I upregulation, we infected primary human monocytes, a major target of DENV infection,in vitro. Upregulation of total HLA class I is dependent on active viral replication and is mediated in part by cytokines and other soluble factors induced by infection, while upregulation of HLA-E occurs in the presence of replication-incompetent virus. Importantly, blocking DENV-infected monocytes with a pan-HLA class I Fab nearly doubles the frequency of degranulating NK cells, while blocking HLA-E does not significantly improve the NK cell response. These findings demonstrate that upregulation of HLA class I during DENV infection suppresses the NK cell response, potentially contributing to disease pathogenesis.