bluuebunny/crossref_metadata_2025_split huggingface dataset:
Logic-based Analysis of Gene Expression Data Predicts Pathway Crosstalk between TNF, TGFB1 and EGF in Basal-like Breast Cancer
Authors: Jo Kyuri , Buitrago Beatriz Santos , Kim Minsu , Rhee Sungmin , Talcott Carolyn , Kim Sun 
Published: April 2019

AbstractFor breast cancer, clinically important subtypes are well characterised at the molecular level in terms of gene expression profiles. In addition, signaling pathways in breast cancer have been extensively studied as therapeutic targets due to their roles in tumor growth and metastasis. However, it is challenging to put signaling pathways and gene expression profiles together to characterise biological mechanisms of breast cancer subtypes since many signaling events result from post-translational modifications, rather than gene expression differences.We present a logic-based approach to explain the differences in gene expression profiles among breast cancer subtypes using Pathway Logic and transcriptional network information. Pathway Logic is a rewriting-logic-based formal system for modeling biological pathways including post-translational modifications. Proposed method demonstrated its utility by constructing subtype-specific path from key receptors (TNFR, TGFBR1 and EGFR) to key transcription factor (TF) regulators (RELA, ATF2, SMAD3 and ELK1) and identifying potential pathway crosstalk via TFs in basal-specific paths, which could provide a novel insight on aggressive breast cancer subtypes.AvailabilityAnalysis result is available athttp://epigenomics.snu.ac.kr/PL/
The Chinese chestnut genome: a reference for species restoration
Authors: Staton Margaret , Addo-Quaye Charles , Cannon Nathaniel , Sun Yongshuai , Zhebentyayeva Tetyana , Huff Matthew , Fan Shenghua , Bellis Emily , Islam-Faridi Nurul , Yu Jiali , Henry Nathan , Conrad Anna , Drautz-Moses Daniela I. , Zhu Xingfu , Lu Zhiqiang , Noorai Rooksana E. , Ficklin Stephen , Saski Chris , Mandal Mihir , Wagner Tyler K , Zembower Nicole , Bodénès Catherine , Holliday Jason , Westbrook Jared , Lasky Jesse , Georgi Laura , Hebard Fred V , Nelson C. Dana , Schuster Stephan C , Abbott Albert G , Carlson JE 
Published: April 2019

AbstractForest tree species are increasingly subject to severe mortalities from exotic pests, diseases, and invasive organisms, accelerated by climate change. Forest health issues are threatening multiple species and ecosystem sustainability globally. While sources of resistance may be available in related species, or among surviving trees, introgression of resistance genes into threatened tree species in reasonable time frames requires genome-wide breeding tools. Asian species of chestnut (Castaneaspp.) are being employed as donors of disease resistance genes to restore native chestnut species in North America and Europe. To aid in the restoration of threatened chestnut species, we present the assembly of a reference genome with chromosome-scale sequences for Chinese chestnut (C. mollissima), the disease-resistance donor for American chestnut restoration. We also demonstrate the value of the genome as a platform for research and species restoration, including new insights into the evolution of blight resistance in Asian chestnut species, the locations in the genome of ecologically important signatures of selection differentiating American chestnut from Chinese chestnut, the identification of candidate genes for disease resistance, and preliminary comparisons of genome organization with related species.
The statistical structure of the hippocampal code for space as a function of time, context, and value
Authors: Lee Jae Sung , Briguglio John , Romani Sandro , Lee Albert K. 
Published: April 2019

AbstractHippocampal activity represents many behaviorally important variables, including context, an animal’s location within a given environmental context, time, and reward. Here we used longitudinal calcium imaging in mice, multiple large virtual environments, and differing reward contingencies to derive a unified probabilistic model of hippocampal CA1 representations centered on a single feature – the field propensity. Each cell’s propensity governs how many place fields it has per unit space, predicts its reward-related activity, and is preserved across distinct environments and over months. The propensity is broadly distributed—with many low, and some very high, propensity cells —and thus strongly shapes hippocampal representations. The result is a range of spatial codes, from sparse to dense. Propensity varied ~10-fold between adjacent cells in a salt-and-pepper fashion, indicating substantial functional differences within a presumed cell type. The stability of each cell’s propensity across conditions suggests this fundamental property has anatomical, transcriptional, and/or developmental origins.
DeepGOPlus: Improved protein function prediction from sequence
Authors: Kulmanov Maxat , Hoehndorf Robert 
Published: April 2019

ABSTRACTProtein function prediction is one of the major tasks of bioinformatics that can help in wide range of biological problems such as understanding disease mechanisms or finding drug targets. Many methods are available for predicting protein functions from sequence based features, protein–protein interaction networks, protein structure or literature. However, other than sequence, most of the features are difficult to obtain or not available for many proteins thereby limiting their scope. Furthermore, the performance of sequence-based function prediction methods is often lower than methods that incorporate multiple features and predicting protein functions may require a lot of time.We developed a novel method for predicting protein functions from sequence alone which combines deep convolutional neural network (CNN) model with sequence similarity based predictions. Our CNN model scans the sequence for motifs which are predictive for protein functions and combines this with functions of similar proteins. We evaluate the performance of DeepGOPlus on the CAFA3 dataset and significantly improve the performance of predictions of biological processes and cellular components with Fmax of 0.47 and 0.70, respectively, using only the amino acid sequence of proteins as input. DeepGOPlus can annotate around 40 protein sequences per second, thereby making fast and accurate function predictions available for a wide range of proteins.
The rice leaf microbiome has a conserved community structure controlled by complex host-microbe interactions
Authors: Roman-Reyna Veronica , Pinili Dale , Borja Frances Nikki , Quibod Ian Lorenzo , Groen Simon C. , Mulyaningsih Enung S , Rachmat Agus , Slamet-Loedin Inez H. , Alexandrov Nikolai , Mauleon Ramil , Oliva Ricardo 
Published: April 2019

AbstractUnderstanding the factors that influence the outcome of crop interactions with microbes is key to managing crop diseases and improving yield. While the composition, structure and functional profile of crop microbial communities are shaped by complex interactions between the host, microbes and the environment, the relative contribution of each of these factors is mostly unknown. Here, we profiled the community composition of bacteria across leaves of 3,024 rice (Oryza sativa) accessions from field trials in China and the Philippines using metagenomics. Despite significant differences in diversity between environments, the structure and metabolic profiles of the microbiome appear to be conserved, suggesting that microbiomes converge onto core functions. Furthermore, co-occurrence analysis identified microbial hubs that regulate the network structure of the microbiome. We identified rice genomic regions controlling the abundance of these hubs, enriched for processes involved in stress responses and carbohydrate metabolism. We functionally validated the importance of these processes, finding that abundance of hub taxa was different in rice mutants with altered cellulose and salicylate accumulation, two major metabolites at the host-microbe interactions interface. By identifying key host genomic regions, host traits and hub microbes that govern microbiome composition, our study opens the door to designing future cropping systems.
Degradation levels of continuous speech affect neural speech tracking and alpha power differently
Authors: Hauswald Anne , Keitel Anne , Chen Ya-Ping , Rösch Sebastian , Weisz Nathan 
Published: April 2019

AbstractUnderstanding degraded speech, e.g. following a hearing damage, can pose a challenge. Previous attempts to quantify speech intelligibility in neural terms have usually focused on one of two measures, namely low-frequency speech-brain synchronization or alpha power modulations. However, reports have been mixed concerning the modulation of these measures, an issue aggravated by the fact that they have normally been studied separately. Using a parametric speech degradation approach, we present MEG studies that overcome this shortcoming. In a first study, participants listened to unimodal auditory speech with three different levels of degradation (original, 7-channel and 3-channel vocoding). Intelligibility declined with declining clarity, implemented by fewer vocoding channels but was still intelligible to some extent even for the lowest clarity level used (3-channel vocoding). Low- frequency (1-7 Hz) speech tracking suggested a u-shaped relationship with strongest effects for the medium degraded speech (7-channel) in bilateral auditory and left frontal regions. To follow up on this finding, we implemented three additional vocoding levels (5-channel, 2- channel, 1-channel) in a second MEG study. Using this wider range of degradation, the speech-brain synchronization showed a similar pattern for the degradation levels used in the first study but further shows that when speech becomes unintelligible, synchronization declines again. The relationship differed for alpha power, which continued to decrease across vocoding levels reaching a floor effect for 5-channel vocoding. Predicting subjective intelligibility based on models either combining both measures or each measure alone, showed superiority of the combined model. Our findings underline that speech tracking and alpha power are modified differently by the degree of degradation of continuous speech but together contribute to the subjective understanding of speech.
Effects of sugars and lipids on the growth and development ofCaenorhabditis elegans
Authors: Wang Xiong , Zhang Lin , Zhang Lei , Wang Wenli , Wei Sihan , Wang Jie , Che Huilian , Zhang Yali 
Published: April 2019

AbstractExcessive intake of carbohydrates and fats causes over-nutrition, leading to a variety of diseases and complications. Here, we characterized the effects of different types of sugar and lipids on the growth and development ofCaenorhabditis elegans. We measured the lifespan, reproductive capacity, and length of nematodes after sugars and lipids treatment alone and co-treatment of sugars and lipids. Furthermore, by using transcriptome sequencing technology, we studied the mechanisms underlying the damaged caused by high-sucrose and high-stearic acid onC. elegans. The results showed that a certain concentration of sugar and lipid promoted the growth and development of nematodes. However, excessive sugars and lipids shortened the lifespan and length of nematodes and destroyed their reproductive capacity. Based on the results of the orthogonal test, we selected 400 mmol/L sucrose and 500 μg/mL stearic acid to model a high-sugar and high-lipid diet forC. elegans. High-sugar and high-lipid intake altered the expression of genes involved in biofilm synthesis, genes that catalyze the synthesis and degradation of endogenous substances, and genes involved in innate immunity, resulting in physiological damage.
The PPR-related splicing cofactor MSP1/EMB1025 protein, encoded by At4g20090, encode an essential protein that is required for the splicing ofnad1intron 1 and for the biogenesis of complex I in Arabidopsis mitochondria
Authors: Best Corinne , Zmudjak Michal , Ostersetzer-Biran Oren 
Published: April 2019

AbstractGroup II introns are particularly plentiful within plant mitochondrial genomes (mtDNAs), where they interrupt the coding-regions of many organellar genes, especialy within complex I (CI) subunits. Their splicing is essential for the biogenesis of the respiratory system and is facilitated by various protein-cofactors that belong to a diverse set of RNA-binding cofactors. These including maturases, which co-evolved with their host-introns, and varioustrans-acting factors, such as members of the pentatricopeptide-repeat (PPR) protein family. The genomes of angiosperms contain hundreds ofPPR-related genes that are postulated to reside within the organelles and affect diverse posttranscriptional steps, such as editing, RNA-stability and processing or translation. Here, we report the characterization of MSP1 (Mitochondria Splicing PPR-factor 1; also denoted as EMB1025), which plays a key role in the processing ofnad1pre-RNAs in Arabidopsis mitochondria. Mutations inMSP1gene-locus (At4g20090) result in early embryonic arrest. To analyze the putative roles of MSP1 in organellar RNA-metabolism we used a modified embryo-rescue method, which allowed us to obtain sufficient plant tissue for the analysis of the RNA and protein profiles associated withmsp1mutants. Our data indicate that MSP1 is essential for thetrans-splicing ofnad1intron 1 in Arabidopsis mitochondria. Accordingly,msp1mutants show CI biogenesis defects and reduced respiratory-mediated functions. These results provide with important insights into the roles of nuclear-encoded factors during early plant development, and contribute to our limited understanding of the importance of RNA-maturation and splicing in plant mitochondria during early embryogenesis.
Multifaceted Changes in Synaptic Composition and Astrocytic Involvement in a Mouse Model of Fragile X Syndrome
Authors: Simhal Anish K. , Zuo Yi , Perez Marc M. , Madison Daniel V. , Sapiro Guillermo , Micheva Kristina D. 
Published: April 2019

ABSTRACTFragile X Syndrome (FXS), a common inheritable form of intellectual disability, is known to alter neocortical circuits. However, its impact on the diverse synapse types comprising these circuits, or on the involvement of astrocytes, is not well known. We used immunofluorescent array tomography to quantify different synaptic populations and their association with astrocytes in layers 1 through 4 of the adult somatosensory cortex of a FXS mouse model, the FMR1 knockout mouse. The collected multi-channel data contained approximately 1.6 million synapses which were analyzed using a probabilistic synapse detector. Our study reveals complex, synapse-type and layer specific changes in the neocortical circuitry of FMR1 knockout mice. In layers 1 and 2/3, there is a significant decrease in the density of excitatory glutamatergic synapses, both VGluT1 and VGluT2 type, and their association with astrocytes, while the changes in inhibitory GABAergic synapses are less pronounced. Meanwhile in layer 4, there is a significant increase in the density of small VGluT1 synapses, with no changes in the astrocytic association of synapses. The ability to dissect the circuit deficits by synapse type and astrocytic involvement, will be crucial for understanding how these changes affect circuit function, and ultimately define targets for therapeutic intervention.
Multilayered N-glycoproteomics reveals impaired N-glycosylation promoting Alzheimer’s disease
Authors: Fang Pan , Xie Juan-Juan , Sang Shao-Ming , Zhang Lei , Liu Ming-Qi , Yang Lu-Jie , Xu Yi-Teng , Yan Guo-Quan , Yao Jun , Gao Xing , Qian Wen-Jing , Wang Zhong-Feng , Zhang Yang , Yang Peng-Yuan , Shen Hua-Li 
Published: April 2019

ABSTRACTAlzheimer’s disease (AD) is one of the most common neurodegenerative diseases that currently lacks clear pathogenesis and effective treatment. Protein glycosylation is ubiquitous in brain tissue and site-specific analysis of N-glycoproteome, which is technically challenging, can advance our understanding of the glycoproteins’ role in AD. In this study, we profiled the multilayered variations in proteins, N-glycosites, N-glycans, and in particular site-specific N-glycopeptides in the APP/PS1 and wild type mouse brain through combining pGlyco 2.0 strategy with other quantitative N-glycoproteomic strategies. The comprehensive brain N-glycoproteome landscape was constructed, and rich details of the heterogeneous site-specific protein N-glycosylations were exhibited. Quantitative analyses explored generally downregulated N-glycosylation involving proteins such as glutamate receptors, as well as fucosylated and oligo-mannose type glycans in APP/PS1 mice versus wild type mice. Moreover, our preliminary functional study revealed that N-glycosylation was crucial for the membrane localization of NCAM1 and for maintaining the excitability and viability of neuron cells. Our work offered a panoramic view of the N-glycoproteomes in Alzheimer’s disease and revealed that generally impaired N-glycosylation promotes Alzheimer’s disease progression.
Catestatin improves insulin sensitivity in diet-induced obese mice: in vivo and in silico validation
Authors: Dasgupta Abhijit , Bandyopadhyay Keya , Ray Indrani , Bandyopadhyay Gautam K. , Chowdhury Nirmalya , De Rajat K. , Mahata Sushil K. 
Published: April 2019

AbstractObesity is characterized by a state of chronic, unresolved inflammation in insulin-targeted tissues. Obesity-induced inflammation accumulates proinflammatory macrophages in adipose tissue and liver. Proinflammatory cytokines released from tissue macrophages inhibits insulin sensitivity. Chromogranin A (CgA) peptide catestatin (CST: hCgA352-372) improves obesity-induced hepatic insulin resistance by reducing inflammation and inhibiting proinflammatory macrophage infiltration. Obesity leads to inflammation-induced endoplasmic reticulum (ER) stress and insulin resistance. We reasoned that the anti-inflammatory effects of CST would alleviate ER stress. CST decreased obesity-induced ER dilation in hepatocytes and macrophages. CST reduced phosphorylation of UPR signaling molecules and increased phosphorylation of insulin signaling molecules. We developed an in silico state space model mimicking dynamics of integrated ER stress and insulin pathways. Proportional-Integral-Derivative (PID) controllers helped in checking whether the reduction of phosphorylated PERK resulting in attenuation of ER stress, resembling CST effect, could enhance insulin sensitivity. The simulation results showed CST not only decreased ER stress but also enhanced insulin sensitivity. Simulation results also revealed that enhancement of AKT phosphorylation overcame effects of high ER stress to achieve insulin sensitivity.
Methylation content sensitive enzyme ddRAD (MCSeEd): a reference-free, whole genome profiling system to address cytosine/ adenine methylation changes
Authors: Marconi Gianpiero , Capomaccio Stefano , Comino Cinzia , Acquadro Alberto , Portis Ezio , Porceddu Andrea , Albertini Emidio 
Published: April 2019

AbstractMethods for investigating DNA methylation nowadays either require a reference genome and high coverage, or investigate only CG methylation. Moreover, no large-scale analysis can be performed for N6-methyladenosine (6mA). Here we describe the methylation content sensitive enzyme double-digest restriction-site-associated DNA (ddRAD) technique (MCSeEd), a reduced-representation, reference-free, cost-effective approach for characterizing whole genome methylation patterns across different methylation contexts (e.g., CG, CHG, CHH, 6mA). MCSeEd can also detect genetic variations among hundreds of samples. MCSeEd is based on parallel restrictions carried out by combinations of methylation insensitive and sensitive endonucleases, followed by next-generation sequencing. Moreover, we present a robust bioinformatic pipeline (available athttps://bitbucket.org/capemaster/mcseed/src/master/) for differential methylation analysis combined with single nucleotide polymorphism calling without or with a reference genome.
Perception of aversive stimuli of different gustatory modalities in an haematophagous insect,Rhodnius prolixus
Authors: Masagué Santiago , Cano Agustina , Asparch Yamila , Barrozo Romina B. , Minoli Sebastian 
Published: April 2019

AbstractSensory aversion is an essential link for avoiding potential dangers. Here, we studied the chemical perception of aversive compounds of different gustatory modalities (salty and bitter) in the haematophagous kissing bug,Rhodnius prolixus. Over a walking arena, insects preferred a substrate embedded with 0.3 M NaCl or KCl rather than with distilled water. Same salts were avoided when prepared at 1 M. When NaCl and KCl were confronted, no preferences were evinced by insects. A pre-exposure to amiloride interfered with the repellency of NaCl and KCl equally, suggesting that amiloride-sensitive receptors are involved in the detection of both salts. Discriminative experiments were then performed to determine ifR. prolixuscan distinguish between these salts. An aversive operant conditioning involving either NaCl or KCl modulated the repellency of the conditioned salt, but also of the novel salt. A chemical pre-exposure to the salts did not to modify their repellency levels. When we crossed gustatory modalities by confronting NaCl to caffeine (i.e.a bitter stimulus) no innate preferences were evinced. Aversive operant conditionings with either NaCl or Caf rendered unspecific changes in the repellency of both compounds. A chemical pre-exposure to Caf modulated the response to Caf but not to NaCl, suggesting the existence of two independent neural pathways for the detection of salts and bitter compounds. Overall results suggest thatR. prolixuscannot distinguish between NaCl and KCl but can distinguish between NaCl and Caf and generalizes the response between these two aversive stimuli of different gustatory modality.Summary statementKissing-bugs use contact chemo-perception to avoid aversive substrates. They can sensory distinguish between salty (sodium chloride) and bitter (caffeine) tastes, but not between different salts (sodium and potassium chloride).
Smear positive tuberculosis and genetic diversity ofM. tuberculosisisolates in individuals visiting health facilities in South Gondar Zone, northwest Ethiopia
Authors: Alelign Amir , Petros Beyene , Ameni Gobena 
Published: April 2019

AbstractBackgroundTuberculosis (TB), a bacterial infectious disease, persisted to be a public health concern in many developing countries. However, lack of enough data concerning the public health burden and potential risk factors for the disease hampered control programs in target areas. Therefore, the present study aimed in determining the prevalence of TB and genetic diversity ofM. tuberculosisisolates in South Gondar Zone, northwest Ethiopia.MethodsA cross-sectonal study was conducte between March 2015 and April 2017. Bacteriological examination, region of difference (RD) 9 based polymerase chain reaction (PCR) and spoligotyping were used to undertake the study.ResultsThe overall prevalence of smear positive all forms TB was 6.3% (186/2953). Extra pulmonary TB (EPTB) was clinically characterized on about 62.4% (116/186) TB-positive cases. Some of the patients’ demographic characteristics such as [patients’ origin (chi-square (χ2) value; 62.8, p<0.001) were found to be significantly associated risk factors for the occurrence of TB in the study area. All the mycobacterial isolates were found to beM. tuberculosis.Among the 35 different spoligotype patterns identified, 22 patterns were shared types. The three dominantly identified families were T, CAS and Manu, each consisting of 46.9%, 24.0% and 10.4% of the isolates, respectivelyConclusionThe presented study revealed that TB continued to be a public health problem in South Gondar Zone which suggests a need of implementing effective disease control strategies.