bluuebunny/crossref_metadata_2025_split huggingface dataset:
The mouse Balbiani body maintains primordial follicle quiescence via RNA storage
Authors: Lei Lei , Ikami Kanako , Abbott Haley , Jin Shiying 
Published: January 2020

AbstractIn mammalian females, the transition between quiescent primordial follicles and follicular development is critical for maintaining ovarian function and reproductive longevity. In primary oocytes of mouse quiescent primordial follicles, Golgi complexes are organized into a spherical structure, the Balbiani body. Here, we show that the structure of the B-body is maintained by microtubules and actin. The B-body stores mRNA-capping enzyme and 597 mRNAs associated with mRNA-decapping enzyme 1A. Proteins encoded by these mRNAs function in enzyme binding, cellular component organization and packing of telomere ends. Pharmacological disassembly of the B-body triggers translation of stored mRNAs and activates primordial follicles in culture andin vivomouse model. Thus, primordial follicle quiescence is maintained by the B-body, and translationally inactive B-body-stored mRNAs may be regulated by 5’-capping.
Multifaceted analysis of training and testing convolutional neural networks for protein secondary structure prediction
Authors: Shapovalov Maxim , Dunbrack Roland L. , Vucetic Slobodan 
Published: January 2020

AbstractProtein secondary structure prediction remains a vital topic with improving accuracy and broad applications. By using deep learning algorithms, prediction methods not relying on structure templates were recently reported to reach as high as 87% accuracy on 3 labels (helix, sheet or coil). Due to lack of a widely accepted standard in secondary structure predictor development and evaluation, a fair comparison of predictors is challenging. A detailed examination of factors that contribute to higher accuracy is also lacking. In this paper, we present: (1) a new test set,Test2018, consisting of proteins from structures released in 2018 with less than 25% similar to any protein published before 2018; (2) a 4-layer convolutional neural network,SecNet, with an input window of ±14 amino acids which was trained on proteins less than 25% identical to proteins inTest2018and the commonly usedCB513test set; (3) a detailed ablation study where we reverse one algorithmic choice at a time inSecNetand evaluate the effect on the prediction accuracy; (4) new 4- and 5-label prediction alphabets that may be more practical for tertiary structure prediction methods. The 3-label accuracy of the leading predictors on bothTest2018andCB513is 81-82%, whileSecNet’s accuracy is 84% for both sets. The ablation study of different factors (evolutionary information, neural network architecture, and training hyper-parameters) suggests the best accuracy results are achieved with good choices for each of them while the neural network architecture is not as critical as long as it is not too simple. Protocols for generating and using unbiased test, validation, and training sets are provided. Our data sets, including input features and assigned labels, andSecNetsoftware including third-party dependencies and databases, are downloadable fromdunbrack.fccc.edu/ssandgithub.com/sh-maxim/ss.
Limiting Self-Renewal of the Basal Compartment Induces Differentiation and Alters Evolution of Mammary Tumors
Authors: Ognjenovic Nevena B. , Bagheri Meisam , Mohamed Gadisti Aisha , Xu Ke , Brown Meredith S. , Chen Youdinghuan , Mohamed Saleem Mohamed Ashick , Nagaraj Shivashankar H. , Muller Kristen E. , Christensen Brock C. , Pattabiraman Diwakar R. 
Published: January 2020

SummaryDifferentiation therapy is an approach that utilizes our understanding of the hierarchy of cellular systems to pharmacologically induce a shift towards terminal commitment. While this approach has been a paradigm in treating certain hematological malignancies, efforts to translate this success to solid tumors have proven challenging. In this study we show that activation of PKA drives aberrant mammary differentiation by diminishing the self-renewing potential of the basal compartment. PKA activation results in tumors that are more benign, exhibiting reduced metastatic propensity, loss of tumor-initiating potential and increased sensitivity to chemotherapy. Analysis of tumor histopathology revealed features of overt differentiation with papillary characteristics. Longitudinal single cell profiling at the hyperplasia and tumor stages uncovered an altered path of tumor evolution whereby PKA curtails the emergence of aggressive subpopulations. PKA activation represents a promising approach as an adjuvant to chemotherapy for certain breast cancers, reviving the paradigm of differentiation therapy for solid tumors.
A Reaction-Diffusion Network model predicts a dual role of Cactus/IκB to regulate Dorsal/NFκB nuclear translocation inDrosophila
Authors: Barros C.D.T. , Cardoso M.A. , Bisch P.M. , Araujo H.M. , Lopes F.J.P. 
Published: January 2020

ABSTRACTDorsal-ventral patterning of theDrosophilaembryo depends on the NFκB superfamily transcription factor Dorsal (Dl). Toll receptor activation signals for degradation of the IκB inhibitor Cactus (Cact), leading to a ventral-to-dorsal nuclear Dl gradient. Cact is critical for Dl nuclear import, as it binds to and prevents Dl from entering the nuclei. Quantitative analysis ofcactmutants revealed an additional Cact function to promote Dl nuclear translocation in ventral regions of the embryo. To investigate this dual Cact role, we developed a predictive model based on a reaction-diffusion regulatory network. This network considers non-uniform Toll activation as well as Toll-dependent Dl nuclear import and Cact degradation. In addition, it incorporates translational control of Cact levels by Dl, a Toll-independent pathway for Cact regulation and reversible nuclear-cytoplasmic Dl flow. Our model successfully reproduces wild-type data and emulates the Dl nuclear gradient in mutantdlandcactallelic combinations. Our results indicate that the dual role of Cact depends on targeting distinct Dl complexes along the dorsal-ventral axis: In the absence of Toll activation, free Dl-Cact trimers inhibit direct Dl nuclear entry; upon ventral-lateral Toll activation, Dl-Cact trimers are recruited into predominant signaling complexes and promote active Dl nuclear translocation. Simulations suggest that Toll-independent regulatory mechanisms that target Cact are fundamental to reproduce the full assortment of Cact effects. Considering the high evolutionary conservation of these pathways, our analysis should contribute to understand NFκB/c-Rel activation in other contexts such as in the vertebrate immune system and disease.
Deciphering the regulatory genome ofEscherichia coli, one hundred promoters at a time
Authors: Ireland William T. , Beeler Suzannah M. , Flores-Bautista Emanuel , Belliveau Nathan M. , Sweredoski Michael J. , Moradian Annie , Kinney Justin B. , Phillips Rob 
Published: January 2020

AbstractAdvances in DNA sequencing have revolutionized our ability to read genomes. However, even in the most well-studied of organisms, the bacteriumEscherichia coli, for ≈ 65% of the promoters we remain completely ignorant of their regulation. Until we have cracked this regulatory Rosetta Stone, efforts to read and write genomes will remain haphazard. We introduce a new method (Reg-Seq) linking a massively-parallel reporter assay and mass spectrometry to produce a base pair resolution dissection of more than 100 promoters inE. coliin 12 different growth conditions. First, we show that our method recapitulates regulatory information from known sequences. Then, we examine the regulatory architectures for more than 80 promoters in theE. coligenome which previously had no known regulation. In many cases, we also identify which transcription factors mediate their regulation. The method introduced here clears a path for fully characterizing the regulatory genome of model organisms, with the potential of moving on to an array of other microbes of ecological and medical relevance.
Studies of human twins reveal genetic variation that affects dietary fat perception
Authors: Lin Cailu , Colquitt Lauren , Wise Paul , Breslin Paul A. S. , Rawson Nancy E. , Genovese Federica , Maina Ivy , Joseph Paule , Fomuso Lydia , Slade Louise , Brooks Dennis , Miclo Aurélie , Hayes John E. , Sullo Antonio , Reed Danielle R. 
Published: January 2020

AbstractTo learn more about the mechanisms of human dietary fat perception, 398 human twins rated fattiness and liking for six types of potato chips that differed in triglyceride content (2.5, 5, 10, and 15% corn oil); reliability estimates were obtained from a subset (n= 50) who did the task twice. Some chips also had a saturated long-chain fatty acid (hexadecanoic acid, 16:0) added (0.2%) to evaluate its effect on fattiness and liking. We computed the heritability of these measures and conducted a genome-wide association study (GWAS) to identify regions of the genome that co-segregate with fattiness and liking. Perceived fattiness and liking for the potato chips were reliable (r= 0.31-0.62,p< 0.05) and heritable (up toh2= 0.29,p< 0.001, for liking). Adding hexadecanoic acid to the potato chips significantly increased ratings of fattiness but decreased liking. Twins with the G allele ofrs263429nearGATA3-AS1or the G allele ofrs8103990withinZNF729reported more liking for potato chips than did twins with the other allele (multivariate GWAS,p< 1×10-5), with results reaching genome-wide suggestive but not significance criteria. Person-to-person variation in the perception and liking of dietary fat was (a) negatively affected by the addition of a saturated fatty acid and (b) related to inborn genetic variants. These data suggest liking for dietary fat is not due solely to fatty acid content and highlight new candidate genes and proteins within this sensory pathway.
Primordial emergence of a nucleic acid binding protein via phase separation and statistical ornithine to arginine conversion
Authors: Longo Liam M. , Despotović Dragana , Weil-Ktorza Orit , Walker Matthew J. , Jabłońska Jagoda , Fridmann-Sirkis Yael , Varani Gabriele , Metanis Norman , Tawfik Dan S. 
Published: January 2020

AbstractDe novo emergence, and emergence of the earliest proteins specifically, demands a transition from disordered polypeptides into structured proteins with well-defined functions. However, can peptides confer evolutionary relevant functions, let alone with minimal abiotic amino acid alphabets? How can such polypeptides evolve into mature proteins? Specifically, while nucleic acids binding is presumed a primordial function, it demands basic amino acids that do not readily form abiotically. To address these questions, we describe an experimentally-validated trajectory from a phase-separating polypeptide to a dsDNA-binding protein. The intermediates comprise sequence-duplicated, functional proteins made of only 10 amino acid types, with ornithine, which can form abiotically, as the only basic amino acid. Statistical, chemical modification of ornithine sidechains to arginine promoted structure and function. The function concomitantly evolved – from phase separation with RNA (coacervates) to avid and specific dsDNA binding – thereby demonstrating a smooth, gradual peptide-to-protein transition with respect to sequence, structure, and function.
Laser-facilitated epicutaneous immunotherapy with hypoallergenic beta-glucan neoglycoconjugates suppresses lung inflammation and avoids local side effects in a mouse model of allergic asthma
Authors: Korotchenko Evgeniia , Schießl Victoria , Scheiblhofer Sandra , Joubert Isabella , Strandt Helen , Neuper Theresa , Sarajlic Muamera , Bauer Renate , Geppert Mark , Joedicke David , Wildner Sabrina , Schaller Susanne , Winkler Stephan , Gadermaier Gabriele , Horejs-Hoeck Jutta , Weiss Richard 
Published: January 2020

AbstractBackgroundAllergen-specific immunotherapy via the skin targets an area rich in antigen presenting cells, but can be associated with local and systemic side effect. Allergen-polysaccharide neoglycogonjugates can increase immunization efficacy by targeting and activating dendritic cells via C-type lectin receptors and reduce side effects.ObjectiveWe investigated the immunogenicity, allergenicity and therapeutic efficacy of laminarin-ovalbumin neoglycoconjugates (LamOVA).MethodsThe biological activity of LamOVA was characterizedin vitrousing bone marrow derived dendritic cells. Immunogenicity and therapeutic efficacy was analyzed in BALB/c mice. Epicutaneous immunotherapy (EPIT) was performed using fractional infrared laser ablation to generate micropores in the skin and the effects of LamOVA on blocking IgG, IgE, cellular composition of BAL, lung, and spleen, lung function, and T cell polarization was assessed.ResultsConjugation of laminarin to ovalbumin reduced its IgE binding capacity 5-fold and increased its immunogenitiy 3-fold in terms of IgG generation. EPIT with LamOVA induced significantly higher IgG levels than OVA, matching the levels induced by s.c. injection of OVA/alum (SCIT). EPIT was equally effective as SCIT in terms of blocking IgG induction and suppression of lung inflammation and airway hyperresponsiveness, but SCIT was associated with a higher level of therapy induced IgE and TH2 cytokines. EPIT with LamOVA induced significantly lower local skin reactions during therapy compared to unconjugated OVA.ConclusionConjugation of the allergen to laminarin increased its immunogenicity while at the same time reducing local side effects. LamOVA EPIT via laser generated micropores is safe and equally effective to SCIT with alum, without the need for adjuvant.
Coupling of dynamic microtubules to F-actin by Fmn2 regulates chemotaxis of neuronal growth cones
Authors: Kundu Tanushree , Dutta Priyanka , Nagar Dhriti , Maiti Sankar , Ghose Aurnab 
Published: January 2020

ABSTRACTDynamic co-regulation of the actin and microtubule subsystems enables the highly precise and adaptive remodeling of the cytoskeleton necessary for critical cellular processes, like axonal pathfinding. The modes and mediators of this interpolymer crosstalk, however, are inadequately understood.We identify Fmn2, a non-diaphanous related formin associated with cognitive disabilities, as a novel regulator of cooperative actin-microtubule remodeling in growth cones. We show that Fmn2 stabilizes microtubules in the growth cones of cultured spinal neurons and alsoin vivo. Superresolution imaging revealed that Fmn2 facilitates guidance of exploratory microtubules along actin bundles into the chemosensory filopodia. Using live imaging, biochemistry and single-molecule assays we show that a C-terminal domain in Fmn2 is necessary for the dynamic association between microtubules and actin filaments. In the absence of the cross-bridging function of Fmn2, filopodial capture of microtubules is compromised resulting in de-stabilized filopodial protrusions and deficits in growth cone chemotaxis.Our results uncover a critical function for Fmn2 in actin-microtubule crosstalk in neurons and demonstrate that modulating microtubule dynamics via associations with F-actin is central to directional motility.SIGNIFICANCE STATEMENTThe formin family member, Fmn2, is associated with cognitive impairment and neurodegenerative conditions though its function in neurons is poorly characterized. We report a novel actin-microtubule cross-bridging activity for Fmn2 that facilitates efficient targeting and capture of microtubules in growth cone filopodia. This activity is necessary for accurate pathfinding of axons and may contribute to Fmn2-associated neuropathologies.The precision and adaptability of cytoskeleton-driven processes are intimately dependent on the coupled activities of its component systems. Our study identifies a novel modality of co-regulated remodelling of the actin and microtubule cytoskeletons that facilitate critical cellular behaviour like neuronal chemotaxis.
Finding new cancer epigenetic and genetic biomarkers from cell-free DNA by combining SALP-seq and machine learning: esophageal cancer as an example
Authors: Liu Shicai , Wu Jian , Xia Qiang , Liu Hongde , Li Weiwei , Xia Xinyi , Wang Jinke 
Published: January 2020

AbstractBackgroundCancer is an important public health problem worldwide and its early diagnosis and effective prognosis are critical for its treatment. In recent years, as a good material for cancer liquid biopsy, plasma cell-free DNA (cfDNA) has been widely analyzed by next generation sequencing (NGS) for finding new molecular markers for cancer diagnosis such as size, methylation and end coordinate. However, the current studies did not still involve esophageal cancer (ESCA), a main cancer that seriously threatens human health and life in China. Here we therefore tried to find new biomarkers for this cancer from cfDNA.Materials & methodsThirty cfDNA samples from 26 ESCA patients and 4 healthy people were used to construct the NGS libraries and sequenced by using SALP-seq. The sequencing data were analyzed with variant bioinformatics methods for finding ESCA molecular biomarkers.Results & conclusionWe identified 103 epigenetic markers (including 54 genome-wide and 49 promoter markers) and 37 genetic markers for ESCA. These markers provide new molecular biomarkers for ESCA diagnosis, prognosis and therapy. Importantly, this study provides a new pipeline for finding new molecular markers for cancers from cfDNA by combining SALP-seq and machine learning. Finally, by finding new molecular markers for ESCA from cfDNA, this study sheds important new insights on the clinical worth of cfDNA.
Feral pigeon populations: their gene pool and links with local domestic breeds
Authors: Giunchi Dimitri , Mucci Nadia , Bigi Daniele , Mengoni Chiara , Baldaccini N. Emilio 
Published: January 2020

AbstractColumba liviais a wild bird whose domestication has led to a large number of pigeon breeds. The occasional loss or straying of domestic birds determined the origin of feral pigeons, which are now widespread all around the world. In this study, we assumed that the main contribution to feral populations is provided by domestic breeds reared in the same areas. We tested this hypothesis by analysing the variability of 12 microsatellite loci in nine Italian feral populations sampled in areas with different intensities of breeding and selecting domestic breeds. We included in the analysis samples belonging to domestic lineages commonly bred in Italy The pattern of geographic differentiation of feral populations turned out to be rather complex and only partially explained by the geographic distance between populations. This pattern can be understood only when the domestic breeds were included in the analysis. In particular, feral populations located in regions with a long-lasting tradition of pigeon breeding showed a high level of admixture with domestic breeds, in particular with Racing Homer and Piacentino. Ferals from Bolzano, Venice and Sassari were characterized by unique genetic components, almost all of which are not shared by other feral populations and by the considered domestic breeds. Our results further emphasize the complex origin of feral populations which can be properly investigated only by considering the pool of domestic pigeons bred in the considered area and their past and present distribution.
Virtual connectomic datasets in Alzheimer’s Disease and aging using whole-brain network dynamics modelling
Authors: Arbabyazd Lucas , Shen Kelly , Wang Zheng , Hofmann-Apitius Martin , Ritter Petra ,   The Alzheimer’s Disease Neuroimaging Initiative, McIntosh Anthony R. , Battaglia Demian , Jirsa Viktor 
Published: January 2020

AbstractLarge neuroimaging datasets, including information about structural (SC) and functional connectivity (FC), play an increasingly important role in clinical research, where they guide the design of algorithms for automated stratification, diagnosis or prediction. A major obstacle is, however, the problem of missing features (e.g., lack of concurrent DTI SC and resting-state fMRI FC measurements for many of the subjects).We propose here to address the missing connectivity features problem by introducing strategies based on computational whole-brain network modeling. Using two datasets, the ADNI dataset and a healthy aging dataset, for proof-of-concept, we demonstrate the feasibility of virtual data completion (i.e., inferring “virtual FC” from empirical SC or “virtual SC” from empirical FC), by using self-consistent simulations of linear and nonlinear brain network models. Furthermore, by performing machine learning classification (to separate age classes or control from patient subjects) we show that algorithms trained on virtual connectomes achieve discrimination performance comparable to when trained on actual empirical data; similarly, algorithms trained on virtual connectomes can be used to successfully classify novel empirical connectomes. Completion algorithms can be combined and reiterated to generate realistic surrogate connectivity matrices in arbitrarily large number, opening the way to the generation of virtual connectomic datasets with network connectivity information comparable to the one of the original data.Significance statementPersonalized information on anatomical connectivity (“structural connectivity”, SC) or coordinated resting state activation patterns (“functional connectivity’, FC) is a source of powerful neuromarkers to detect and track the development of neurodegenerative diseases. However, there are often “gaps” in the available information, with only SC (or FC) being known but not FC (or SC). Exploiting whole-brain modelling, we show that gap in databases can be filled by inferring the other connectome through computational simulations. The generated virtual connectomic data carry information analogous to the one of empirical connectomes, so that machine learning algorithms can be trained on them. This opens the way to the release in the future of cohorts of “virtual patients”, complementing traditional datasets in data-driven predictive medicine.
Efficient inference, potential, and limitations of site-specific substitution models
Authors: Puller Vadim , Sagulenko Pavel , Neher Richard A. 
Published: January 2020

AbstractNatural selection imposes a complex filter on which variants persist in a population resulting in evolutionary patterns that vary greatly along the genome. Some sites evolve close to neutrally, while others are highly conserved, allow only specific states or only change in concert with other sites. Most commonly used evolutionary models, however, ignore much of this complexity and at best account for variation in the rate at which different sites change. Here, we present an efficient algorithm to estimate more complex models that allow for site-specific preferences and explore the accuracy at which such models can be estimated from simulated data. We find that an iterative approximate maximum likelihood scheme uses information in the data efficiently and accurately estimates site-specific preferences from large data sets with moderately diverged sequences. Ignoring site-specific preferences during estimation of branch length of phylogenetic trees – an assumption of most phylogeny software – results in substantial underestimation comparable to the error incurred when ignoring rate variation. However, the joint estimation of branch lengths, site-specific rates, and site-specific preferences can suffer from identifiability problems and is typically unable to recover the correct branch lengths. Site-specific preferences estimated from large HIVpolalignments show qualitative concordance with intra-host estimates of fitness costs. Analysis of site-specific HIV substitution models suggests near saturation of divergence after a few hundred years. Such saturation can explain the inability to infer deep divergence times of HIV and SIVs using molecular clock approaches and time-dependent rate estimates.