bluuebunny/crossref_metadata_2025_split huggingface dataset:
TheMedicago truncatulaHKT family: Ion transport properties and regulation of expression upon abiotic stresses and symbiosis
Authors: Thouin Julien , Guo Man Yuan , Zribi Ikram , Pauly Nicolas , Mouradi Mohammed , Ghoulam Cherki , Sentenac Hervé , Véry Anne-Aliénor 
Published: August 2019

SUMMARYSoil salinity is one of the most important abiotic stresses affecting plant growth. In legumes, symbiotic nitrogen fixation in nodules is affected by salt stress, and salinity tolerance is variable among species. Genes from the High affinity K+Transporter (HKT) family are known to play crucial roles in salt stress tolerance in different plant species. In legumes these transporters are still very poorly characterized.. Here we study the HKT transporter family from the model legumeMedicago trunacatula, which is moderately tolerant to salinity. The genome of this species comprises fiveHKTgenes, hereafter namedMtHKT1;1toMtHKT1;5. Phylogenetic analysis indicated that the MtHKT polypeptides belong to HKT subfamily 1. Three members (MtHKT1;2, MtHKT1;4andMtHKT1;5) of theMedicago truncatulafamily were cloned and expressed inXenopusoocytes. Their electrophysiological properties revealed a permeability 10 times higher for Na+than for K+and varying rectification properties. Expression analyses of the threeMtHKTgenes under different biotic and abiotic conditions suggested that MtHKT1;5 is the main transporter from this family in the root, the three genes sharing a decrease of expression in drought and salt stress conditions in non inoculated plants as well as plants inoculated with rhizobia. In the shoot, the three MtHKT would be present at similar levels independently on the applied stresses. Based on biomass and ion content analysis, the nodule appeared as the most sensitive organ to the applied salt and drought stresses. The level of expression of the threeMtHKTgenes was strongly decreased by both stresses in the nodule.
Supervised-learning is an accurate method for network-based gene classification
Authors: Liu Renming , Mancuso Christopher A , Yannakopoulos Anna , Johnson Kayla A , Krishnan Arjun 
Published: August 2019

AbstractBackgroundAssigning every human gene to specific functions, diseases, and traits is a grand challenge in modern genetics. Key to addressing this challenge are computational methods such as supervised-learning and label-propagation that can leverage molecular interaction networks to predict gene attributes. In spite of being a popular machine learning technique across fields, supervised-learning has been applied only in a few network-based studies for predicting pathway-, phenotype-, or disease-associated genes. It is unknown how supervised-learning broadly performs across different networks and diverse gene classification tasks, and how it compares to label-propagation, the widely-benchmarked canonical approach for this problem.ResultsIn this study, we present a comprehensive benchmarking of supervised-learning for network-based gene classification, evaluating this approach and a state-of-the-art label-propagation technique on hundreds of diverse prediction tasks and multiple networks using stringent evaluation schemes. We demonstrate that supervised-learning on a gene’s full network connectivity outperforms label-propagation and achieves high prediction accuracy by efficiently capturing local network properties, rivaling label-propagation’s appeal for naturally using network topology. We further show that supervised-learning on the full network is also superior to learning on node-embeddings (derived using node2vec), an increasingly popular approach for concisely representing network connectivity.ConclusionThese results show that supervised-learning is an accurate approach for prioritizing genes associated with diverse functions, diseases, and traits and should be considered a staple of network-based gene classification workflows. The datasets and the code used to reproduce the results and add new gene classification methods have been made freely available.Contactarjun@msu.edu
Brain-wide visual habituation networks in wild type and fmr1 zebrafish
Authors: Marquez-Legorreta Emmanuel , Constantin Lena , Piber Marielle , Favre-Bulle Itia A. , Taylor Michael A. , Vanwalleghem Gilles C. , Scott Ethan 
Published: August 2019

AbstractHabituation is a form of learning during which animals stop responding to repetitive stimuli, and deficits in habituation are characteristics of several psychiatric disorders. Due to the technical challenges of measuring brain activity comprehensively and at cellular resolution, the brain-wide networks mediating habituation are poorly understood. Here we report brain-wide calcium imaging during visual learning in larval zebrafish as they habituate to repeated threatening loom stimuli. We show that different functional categories of loom-sensitive neurons are located in characteristic locations throughout the brain, and that both the functional properties of their networks and the resulting behavior can be modulated by stimulus saliency and timing. Using graph theory, we identify a principally visual circuit that habituates minimally, a moderately habituating midbrain population proposed to mediate the sensorimotor transformation, and downstream circuit elements responsible for higher order representations and the delivery of behavior. Zebrafish larvae carrying a mutation in the fmr1 gene have a systematic shift towards sustained premotor activity in this network, and show slower behavioral habituation. This represents the first description of a visual learning network across the brain at cellular resolution, and provides insights into the circuit-level changes that may occur in people with Fragile X syndrome and related psychiatric conditions.
Microbial extracellular polysaccharide production and aggregate stability controlled by Switchgrass (Panicum virgatum) root biomass and soil water potential
Authors: Sher Yonatan , Baker Nameer R. , Herman Don , Fossum Christina , Hale Lauren , Zhang Xing-Xu , Nuccio Erin , Saha Malay , Zhou Jizhong , Pett-Ridge Jennifer , Firestone Mary 
Published: August 2019

ABSTRACTDeep-rooting perennial grasses are promising feedstock for biofuel production, especially in marginal soils lacking organic material, nutrients, and/or that experience significant water stress. Perennial grass roots can alter surrounding soil conditions and influence microbial activities, particularly the production of extracellular polymeric substances composed primarily of extracellular polysaccharides (EPS). These polymers can alleviate cellular moisture and nutrient stress, and enhance soil characteristics through improved water retention and aggregate stability, the latter of which may in turn enhance carbon persistence. In this study we used a13CO2tracer greenhouse experiment to examine the effect of switchgrass cultivation on the production and origin of EPS in a marginal soil with five fertilization/water treatments (control, +N, +NP, +P, low water). Soils with both added nitrogen and phosphorus had the highest root biomass, EPS and percentage of water-stable soil aggregates. Multiple linear regression analyses revealed root biomass was the most important determinant for soil EPS production, potentially by controlling carbon supply and diurnal changes in soil water potential. Path analysis highlighted the role of soil water potential were and EPS on with water-stable soil aggregates, indicating that EPS concentration and soil aggregation have similar drivers in this soil. High mannose content confirmed the microbial origin of EPS.13CO2labeling indicated that 0.18% of newly fixed plant carbon was incorporated into EPS. Analysis of field samples suggests that EPS is significantly enhanced under long-term switchgrass cultivation. Our results demonstrate that switchgrass cultivation can promote microbial production of EPS, providing a mechanism to enhance sustainability of marginal soils.
Adaptation is influenced by the complexity of environmental change during evolution in a dynamic environment
Authors: Boyer Sébastien , Hérissant Lucas , Sherlock Gavin 
Published: August 2019

AbstractThe environmental conditions of microorganisms’ habitats may fluctuate in unpredictable ways, such as changes in temperature, carbon source, pH, and salinity to name a few. Environmental heterogeneity presents a challenge to microorganisms, as they have to adapt not only to be fit under a specific condition, but they must also be robust across many conditionsand be able to deal with the switch between conditions itself. While experimental evolution has been used to gain insight into the adaptive process, this has largely been in either unvarying or consistently varying conditions. In cases where changing environments have been investigated, relatively little is known about how such environments influence the dynamics of the adaptive process itself, as well as the genetic and phenotypic outcomes. We designed a systematic series of evolution experiments where we used two growth conditions that have differing timescales of adaptation and varied the rate of switching between them. We used lineage tracking to follow adaptation, and whole genome sequenced adaptive clones from each of the experiments. We find that both the switch rate and the order of the conditions influences adaptation, and that switching can both speed up and slow down adaptation, depending on those parameters. We also find different adaptive outcomes, at both the genetic and phenotypic levels, even when populations spent the same amount of total time in the two different conditions, but the order and/or switch rate differed. Thus, in a variable environment adaptation depends not only on the nature of the conditions and phenotypes under selection, but also on the complexity of the manner in which those conditions are combined to result in a given dynamic environment.
Genomic adaptations in information processing underpin trophic strategy in a whole-ecosystem nutrient enrichment experiment
Authors: Okie Jordan G. , Poret-Peterson Amisha T. , Lee Zarraz M.P. , Richter Alexander , Alcaraz Luis D. , Eguiarte Luis E. , Siefert Janet L. , Souza Valeria , Dupont Chris L. , Elser James J. 
Published: August 2019

AbstractSeveral universal genomic traits affect the capacity, cost, and efficiency of biochemical information processing underpinning metabolism and reproduction. We analyzed their role in mediating planktonic microbial community responses to nutrient enrichment in an oligotrophic, phosphorus-deficient pond in Cuatro Ciénegas, Mexico—one of the first whole-ecosystem experiments involving replicated metagenomic assessments. As predicted assuming oligotrophy favors lower information-processing costs whereas copiotrophy favors higher processing rates, mean bacteria genome size was higher in the fertilized treatment, as were GC content, total number of tRNA genes, total number of rRNA genes and codon usage bias in ribosomal protein sequences. However, contrasting changes in trait variances also suggested differences between traits in mediating assembly under oligotrophic versus copiotrophic conditions. Tradeoffs in information-processing traits are apparently sufficiently pronounced to play a role in community assembly and all different components of metabolism— information, energy, and nutrient requirements—are fine-tuned to an organism’s growth and trophic strategy.
Anxiety, avoidance, and sequential evaluation
Authors: Zorowitz Samuel , Momennejad Ida , Daw Nathaniel D. 
Published: August 2019

AbstractAnxiety disorders are characterized by a range of aberrations in the processing of and response to threat, but there is little clarity what core pathogenesis might underlie these symptoms. Here we propose that a particular set of unrealistically pessimistic assumptions can distort an agent’s behavior and underlie a host of seemingly disparate anxiety symptoms. We formalize this hypothesis in a decision theoretic analysis of maladaptive avoidance and a reinforcement learning model, which shows how a localized bias in beliefs can formally explain a range of phenomena related to anxiety. The core observation, implicit in standard decision theoretic accounts of sequential evaluation, is that the potential for avoidance should be protective: if danger can be avoided later, it poses less threat now. We show how a violation of this assumption — via a pessimistic, false belief that later avoidance will be unsuccessful — leads to a characteristic, excessive propagation of fear and avoidance to situations far antecedent of threat. This single deviation can explain a range of features of anxious behavior, including exaggerated threat appraisals, fear generalization, and persistent avoidance. Simulations of the model reproduce laboratory demonstrations of abnormal decision making in anxiety, including in situations of approach-avoid conflict and planning to avoid losses. The model also ties together a number of other seemingly disjoint phenomena in anxious disorders. For instance, learning under the pessimistic bias captures a hypothesis about the role of anxiety in the later development of depression. The bias itself offers a new formalization of classic insights from the psychiatric literature about the central role of maladaptive beliefs about control and self-efficacy in anxiety. This perspective also extends previous computational accounts of beliefs about control in mood disorders, which neglected the sequential aspects of choice.
LyophilizedB. subtilisZB183 Spores: 90-Day Repeat Dose Oral (Gavage) Toxicity Study In Wistar Rats
Authors: Naidu. B Appala , Kannan Kamala , Kumar D. P. Santhosh , Oliver John W.K. , Abbott Zachary D. 
Published: August 2019

AbstractA 90-day repeated-dose oral toxicological evaluation was conducted according to GLP and OECD guidelines on lyophilized spores of the novel genetically modified strainB. subtilisZB183. Lyophilized spores at doses of 109, 1010, and 1011CFU/kg body weight/day were administered by oral gavage to Wistar rats for a period of 90 consecutive days.B.SubtilisZB183 had no effects on clinical signs, mortality, ophthalmological examinations, functional observational battery, body weights, body weight gains and food consumption in both sexes. There were no test item-related changes observed in haematology, coagulation, urinalysis, thyroid hormonal analysis, terminal fasting body weights, organ weights, gross pathology and histopathology. A minimal increase in the plasma albumin level was observed at 1010and 1011CFU/kg/day doses without an increase in total protein in males or females and was considered a non-adverse effect. The “No Observed Adverse Effect Level (NOAEL)” is defined at the highest dose of 1011CFU/kg body weight/day for lyophilizedB.SubtilisZB183 Spores under the test conditions employed.
Microbial genomes retrieved from High Arctic lake sediments encode for adaptation to cold and oligotrophic environments
Authors: Ruuskanen Matti O. , Colby Graham , St.Pierre Kyra A. , St.Louis Vincent L. , Aris-Brosou Stéphane , Poulain Alexandre J. 
Published: August 2019

AbstractThe Arctic is currently warming at an unprecedented rate, which may affect environmental constraints on the freshwater microbial communities found there. Yet, our knowledge of the community structure and functional potential of High Arctic freshwater microbes remains poor, even though they play key roles in nutrient cycling and other ecosystem services. Here, using high-throughput metagenomic sequencing and genome assembly, we show that sediment microbial communities in the High Arctic’s largest lake by volume, Lake Hazen, are phylogenetically diverse, ranging from Proteobacteria, Verrucomicrobia, Planctomycetes, to members of the newly discovered Candidate Phyla Radiation (CPR) groups. These genomes displayed a high prevalence of pathways involved in lipid chemistry, and a low prevalence of nutrient uptake pathways, which might represent adaptations to the specific, cold (~3.5°C) and extremely oligotrophic conditions in Lake Hazen. Despite these potential adaptations, it is unclear how ongoing environmental changes will affect microbial communities, the makeup of their genomic idiosyncrasies, as well as the possible implications at higher trophic levels.
Anastrozole mediated modulation of mitochondrial activity by inhibition of mitochondrial permeability transition pore opening: An initial perspective
Authors: Kumar Somesh , Ghosh Subhajit , Choudhary Neha , Faruq Mohammed , Inderganti Prem kumar , Singh Vikram , Saran Ravindra kumar , Sait Haseena , Kapoor Seema 
Published: August 2019

AbstractBackgroundMitochondrial permeability transmembrane pore [mPTP] plays a vital role in alteration of the structure and function of mitochondria. Cyclophillin D is a mitochondrial protein that regulates mPTP function and a known drug target for therapeutic studies involving mitochondria. While aromatase inhibitor’s role on mPTP has been previously studied, the role of anastrazole on mPTP is not completely elucidated.MethodsThe role of anastrozole in modulating the mPTP was evaluated by docking and molecular dynamics using human cyclophillin D data. Peripheral blood mononuclear cells [PBMCs] of patients with mitochondrial disorders and healthy controls were treated with anastrazole and evaluated for mean fluorescence by flow cytometer. Spectrophotometry was employed for total ATP level estimation.FindingsAnastrozole – cyclophillin D complex is more stable when compared to cyclosporine A – cyclophillin D. Anastrozole performed better than cyclosporine in inhibiting mPTP pore. Additional effects included reduction in mitochondrial swelling and mitochondrial membrane depolarization, decreased super oxide generations, caspase 3 intrinsic activity and cellular apoptosis levels and increase in ATP levels.InterpretationThese results highlights the potency of anastrozole as a promising agent in ameliorating the phenotype by inhibiting the opening of mPTP pore. However, larger functional studies are required to validate the efficacy of this molecule as a therapeutic agent in mitochondrial disorders.
Pedigree-based measurement of thede novomutation rate in the gray mouse lemur reveals a high mutation rate, few mutations in CpG sites, and a weak sex bias
Authors: Campbell C. Ryan , Tiley George P. , Poelstra Jelmer W. , Hunnicutt Kelsie E. , Larsen Peter A. , Lee Hui-Jie , Thorne Jeffrey L. , dos Reis Mario , Yoder Anne D. 
Published: August 2019

AbstractSpontaneous germline mutations are the raw material on which evolution acts, and knowledge of their frequency and genomic distribution is crucial for understanding how evolution operates at both long and short timescales. At present, the rate and spectrum ofde novomutations have been directly characterized in only a few lineages. It is therefore critical to expand the phylogenetic scope of these studies to gain a more general understanding of observed mutation rate patterns. Our study provides the first direct mutation rate estimate for a strepsirrhine (i.e., the lemurs and lorises), which comprise nearly half of the primate clade. Using high-coverage linked-read sequencing for a focal quartet of gray mouse lemurs (Microcebus murinus), we estimated the mutation rate to be 1.64 × 10−8(95% credible interval: 1.41 × 10−8to 1.98 × 10−8) mutations/site/generation. This estimate is higher than those measured for most previously characterized mammals. Further, we found an unexpectedly low count of paternal mutations, and only a modest overrepresentation of mutations at CpG-sites. Given the surprising nature of these observations, we conducted an independent analysis of context-dependent substitution types for gray mouse lemur and five additional primate species. This analysis yielded patterns consistent with the mutation spectrum from the pedigree mutation-rate analysis, which provides confidence in our ability to accurately identifyde novomutations with our data and bioinformatic filters.
HOTAIR promotes an epithelial-to-mesenchymal transition through relocation of the histone demethylase Lsd1
Authors: Jarroux Julien , Bertrand Claire , Gabriel Marc , Foretek Dominika , Saci Zohra , Londoño-Valejo Arturo , Pinskaya Marina , Morillon Antonin 
Published: August 2019

SummaryEpithelial-to-mesenchymal transition (EMT) drives a loss of epithelial traits by neoplastic cells enabling metastasis and recurrence in cancer. HOTAIR emerged as one of the most renowned long noncoding RNAs promoting EMT mostly as a scaffold for PRC2 and repressive histone H3 Lys27 methylation at gene promoters. In addition to PRC2, HOTAIR interacts with the Lsd1 lysine demethylase, a known epigenetic regulator of cell fate during development and differentiation. However, Lsd1 role in HOTAIR function is still poorly understood. Here, through expression of truncated variants of HOTAIR, we revealed that, in contrast to PRC2, its Lsd1-interacting domain is essential for acquisition of migratory properties by epithelial cells. HOTAIR induces Lsd1 relocation from its inherent genomic loci hence reprogramming the epithelial transcriptome. Our results uncovered an unexpected role of HOTAIR in EMT as an Lsd1 effector and pointed to the importance of Lsd1 as a guardian of the epithelial identity.
Genomic prediction for commercial traits using univariate and multivariate approaches in Nile tilapia (Oreochromis niloticus)
Authors: Joshi Rajesh , Skaarud Anders , de Vera Mayet , Alvarez Alejandro Tola , Ødegård Jørgen 
Published: August 2019

AbstractBackgroundOver the past three decades, Nile tilapia industry has grown into a significant aquaculture industry spread over 120 tropical and sub-tropical countries around the world accounting for 7.4% of global aquaculture production in 2015. Across species, genomic selection has been shown to increase predictive ability and genetic gain, also extending into aquaculture. Hence, the aim of this paper is to compare the predictive abilities of pedigree- and genomic-based models in univariate and multivariate approaches, with the aim to utilize genomic selection in a Nile tilapia breeding program. A total of 1444 fish were genotyped (48,960 SNP loci) and phenotyped for body weight at harvest (BW), fillet weight (FW) and fillet yield (FY). The pedigree-based analysis utilized a deep pedigree, including 14 generations. Estimated breeding values (EBVs and GEBVs) were obtained with traditional pedigree-based (PBLUP) and genomic (GBLUP) models, using both univariate and multivariate approaches. Prediction accuracy and bias were evaluated using 5 replicates of 10-fold cross-validation with three different cross-validation approaches. Further, impact of these models and approaches on the genetic evaluation was assessed based on the ranking of the selection candidates.ResultsGBLUP univariate models were found to increase the prediction accuracy and reduce bias of prediction compared to other PBLUP and multivariate approaches. Relative to pedigree-based models, prediction accuracy increased by ∼20% for FY, >75% for FW and >43% for BW. GBLUP models caused major re-ranking of the selection candidates, with no significant difference in the ranking due to univariate or multivariate GBLUP approaches. The heritabilities using multivariate GBLUP models for BW, FW and FY were 0.19 ± 0.04, 0.17 ± 0.04 and 0.23 ± 0.04 respectively. BW showed very high genetic correlation with FW (0.96 ± 0.01) and a slightly negative genetic correlation with FY (−0.11 ± 0.15).ConclusionPredictive ability of genomic prediction models is substantially higher than for classical pedigree-based models. Genomic selection is therefore beneficial to the Nile tilapia breeding program, and it is recommended in routine genetic evaluations of commercial traits in the Nile tilapia breeding nucleus.