bluuebunny/crossref_metadata_2025_split huggingface dataset:
RNA is required for the maintenance of multiple cytoplasmic and nuclear membrane-less organelles
Authors: Decker Carolyn J. , Burke James M. , Mulvaney Patrick K. , Parker Roy 
Published: August 2021

ABSTRACTNumerous membrane-less organelles composed of a combination of RNA and proteins, referred to as RNP granules, are observed in the nucleus and cytoplasm of eukaryotic cells, including stress granules, processing bodies, Cajal bodies, and nuclear speckles. An unresolved issue is how frequently RNA molecules are required for the maintenance of RNP granules in either the nucleus or cytosol. To address this issue, we degraded intracellular RNA in either the cytosol or the nucleus by the activation of RNase L and examined the impact of RNA loss on several RNP granules. Strikingly, we find the majority of RNP granules, including stress granules, processing bodies, Cajal bodies, nuclear speckles and the nucleolus are altered by the degradation of their RNA components. In contrast, super-enhancer complexes and TIS granules were largely unaffected by widespread intracellular RNA degradation. This highlights a critical and widespread role of RNA in the organization of many, but not all, RNP granules.SUMMARYDecker et al. examine the role of RNA in maintaining membrane-less organelles composed of RNA and protein by activating RNase L in the cytoplasm or nucleus. Degradation of RNA alters the majority of membrane-less organelles indicating that RNA plays a widespread role in their organization.
A user-friendly tool for cloud-based whole slide image segmentation, with examples from renal histopathology
Authors: Lutnick Brendon , Manthey David , Becker Jan U. , Ginley Brandon , Moos Katharina , Zuckerman Jonathan E. , Rodrigues Luis , Gallan Alexander J. , Barisoni Laura , Alpers Charles E. , Wang Xiaoxin X. , Myakala Komuraiah , Jones Bryce A. , Levi Moshe , Kopp Jeffrey B. , Yoshida Teruhiko , Han Seung Seok , Jain Sanjay , Rosenberg Avi Z. , Jen Kuang Yu. , Sarder Pinaki ,   the Kidney Precision Medicine Project
Published: August 2021

ABSTRACTBackgroundImage-based machine learning tools hold great promise for clinical applications in nephropathology and kidney research. However, the ideal end-users of these computational tools (e.g., pathologists and biological scientists) often face prohibitive challenges in using these tools to their full potential, including the lack of technical expertise, suboptimal user interface, and limited computation power.MethodsWe have developed Histo-Cloud, a tool for segmentation of whole slide images (WSIs) that has an easy-to-use graphical user interface. This tool runs a state-of-the-art convolutional neural network (CNN) for segmentation of WSIs in the cloud and allows the extraction of features from segmented regions for further analysis.ResultsBy segmenting glomeruli, interstitial fibrosis and tubular atrophy, and vascular structures from renal and non-renal WSIs, we demonstrate the scalability, best practices for transfer learning, and effects of dataset variability. Finally, we demonstrate an application for animal model research, analyzing glomerular features in murine models of aging, diabetic nephropathy, and HIV associated nephropathy.ConclusionThe ability to access this tool over the internet will facilitate widespread use by computational non-experts. Histo-Cloud is open source and adaptable for segmentation of any histological structure regardless of stain. Histo-Cloud will greatly accelerate and facilitate the generation of datasets for machine learning in the analysis of kidney histology, empowering computationally novice end-users to conduct deep feature analysis of tissue slides.
Unravelling Rubber Tree Growth by Integrating GWAS and Biological Network-Based Approaches
Authors: Francisco Felipe Roberto , Aono Alexandre Hild , da Silva Carla Cristina , Gonçalves Paulo de Souza , Scaloppi Erivaldo José , Guen Vincent Le , Neto Roberto Fritsche , Souza Livia Moura , de Souza Anete Pereira 
Published: August 2021

AbstractHevea brasiliensis (rubber tree) is a large tree species of the Euphorbiaceae family with inestimable economic importance. Rubber tree breeding programs currently aim to improve growth and production, and the use of early genotype selection technologies can accelerate such processes, mainly with the incorporation of genomic tools, such as marker-assisted selection (MAS). However, few quantitative trait loci (QTLs) have been used successfully in MAS for complex characteristics. Recent research shows the efficiency of genome-wide association studies (GWAS) for locating QTL regions in different populations. In this way, the integration of GWAS, RNA-sequencing (RNA-Seq) methodologies, coexpression networks and enzyme networks can provide a better understanding of the molecular relationships involved in the definition of the phenotypes of interest, supplying research support for the development of appropriate genomic based strategies for breeding. In this context, this work presents the potential of using combined multiomics to decipher the mechanisms of genotype and phenotype associations involved in the growth of rubber trees. Using GWAS from a genotyping-by-sequencing (GBS) Hevea population, we were able to identify molecular markers in QTL regions with a main effect on rubber tree plant growth under constant water stress. The underlying genes were evaluated and incorporated into a gene coexpression network modelled with an assembled RNA-Seq-based transcriptome of the species, where novel gene relationships were estimated and evaluated through in silico methodologies, including an estimated enzymatic network. From all these analyses, we were able to estimate not only the main genes involved in defining the phenotype but also the interactions between a core of genes related to rubber tree growth at the transcriptional and translational levels. This work was the first to integrate multiomics analysis into the in-depth investigation of rubber tree plant growth, producing useful data for future genetic studies in the species and enhancing the efficiency of the species improvement programs.
A toolbox of engineered mosquito lines to study salivary gland biology and malaria transmission
Authors: Klug Dennis , Arnold Katharina , Mela-Lopez Raquel , Marois Eric , Blandin Stéphanie A. 
Published: August 2021

AbstractMosquito saliva is a vehicle for the transmission of vector borne pathogens such as Plasmodium parasites and different arboviruses. Despite the key role of the salivary glands in the process of disease transmission, knowledge of host-pathogen interactions taking place within this organ is very limited. To improve the experimental tractability of the salivary glands, we have generated fluorescent reporter lines in the African malaria mosquito Anopheles coluzzii using the salivary gland-specific promoters of the anopheline antiplatelet protein (AAPP), the triple functional domain protein (TRIO) and saglin (SAG). Promoter activity was specifically observed in the distal-lateral lobes or in the median lobe of the salivary gland. Besides a comparison of the expression patterns of the selected promoters, the fluorescent probes allowed us to evaluate the inducibility of the selected promoters upon blood feeding and to measure intracellular redox changes. We also combined the aapp-DsRed fluorescent reporter line with a pigmentation-deficient yellow(-) mosquito mutant to assess the feasibility of in vivo microscopy of parasitized salivary glands. This combination allowed locating the salivary gland through the cuticle and imaging of individual sporozoites in vivo, which facilitates live imaging studies of salivary gland colonization by Plasmodium sporozoites.
A point mutation in the kinase domain of CRK10 leads to xylem vessel collapse and activates defence responses
Authors: Piovesana Maiara , Wood Ana K. M. , Smith Daniel P. , Deery Michael J. , Bayliss Richard , Carrera Esther , Napier Johnathan A. , Kurup Smita , Matthes Michaela C. 
Published: August 2021

ABSTRACTCysteine-rich receptor-like kinases (CRKs) are a large family of plasma membrane-bound receptors ubiquitous in higher plants. They are transcriptionally regulated by a wide variety of environmental cues and stresses, however their precise biological roles remain largely unknown. Here we report a novel mutant isolated for the CYSTEINE-RICH RECEPTOR-LIKE KINASE 10 (CRK10) ofArabidopsis thalianawhich harbours the substitution of alanine 397 by a threonine in the αC-helix of its kinase domain and which we registered ascrk10-A397Tin the community database.In situphosphorylation assays with the His-tagged wild type (WT) andcrk10-A397Tversions of the CRK10 kinase domain revealed that both alleles are active kinases capable of auto-phosphorylation with the newly introduced threonine acting as an additional phosphorylation site incrk10-A397T. Phenotypically the mutant is a dwarf and the analysis of thin cross sections with light and transmission electron microscopy revealed that collapsed xylem vessels in roots and hypocotyls are very likely the cause for this reduction in stature. Transcriptomic analysis of WT and mutant hypocotyls revealed that predominantly biotic and abiotic stress-responsive genes are constitutively up-regulated in the mutant. Root-infection assays with the vascular pathogenFusarium oxysporumdemonstrated that thecrk10-A397Tmutant has enhanced resistance to this pathogen compared to WT plants. Taken together our results suggest thatcrk10-A397Tis a gain-of-function allele ofCRK10and open up new avenues for the investigation of this elusive receptor-like kinase family.
Application of components analysis in dynamic thermal breast imaging to identify pathophysiologic mechanisms of heat transfer
Authors: Gershenson Meir , Gershenson Jonathan 
Published: August 2021

AbstractSignificanceOf the most compelling unsolved issues in the paradigm to create success in the field of breast cancer infrared imaging is localization of direct internal heat of the tumor. The contribution of differential heat production related to metabolism versus perfusion is not understood. Previous work until now has not shown progress beyond identifying veins which are fed by the ‘hot’ cancer. Employing signal analysis techniques, we probe important questions which may lead to further understanding pathophysiology of heat transfer occurring in the setting of malignancy.AimWhen using thermal imaging to detect breast cancer, the dominant heat signature is that of indirect heat transported in gradient away from the tumor location. Unprocessed images strikingly display vasculature which acts to direct excess heat superficially towards the skin surface before dissipating. In current clinical use, interpretation of thermogram images considers abnormal vascular patterns and overall temperature as indicators of disease. The goal of this work is to present a processing method for dynamic external stimulus thermogram images to isolate and separate the indirect vascular heat while revealing the desired direct heat from the tumor.ApproachIn dynamic thermal imaging of the breast, a timed series of images are taken following application of external temperature stimulus (most often cooled air). While the tumor heat response is thought to be independent of the external stimulus, the secondary heat of the veins is known to be affected by vasomodulation. The recorded data is analyzed using independent component analysis (ICA) and principal component analysis (PCA) methods. ICA separates the image sequence into new independent images having a common characteristic time behavior. Resulting individual components are analyzed for correspondence to the presence or lack of vasomodulation.ResultsUsing the Brazilian visual lab mastology data set containing dynamic thermograms, applying components analysis resulted in three corresponding images: 1. Minimum change as a function of applied temperature or time (suggests correlation with the cancer generated heat), 2. Moderate temperature dependence (suggests correlation with veins affected by vasomodulation) and 3. Complex time behavior (suggests correlation with heat absorption due to high tumor perfusion). All components appear clear and distinct.ConclusionsApplying signal processing methods to the dynamic infrared data, we found three distinct components with correspondence to understood physiologic processes. The two cases shown are self-evident of the capability of the method but are lacking supporting ground truth that is unavailable with such a limited data set. Validation of this proposed paradigm and studying furthering clinical applications has potential to create significant achievement for IR modality in diagnostic imaging.
Network analysis of ten thousand genomes shed light on Pseudomonas diversity and classification
Authors: Passarelli-Araujo Hemanoel , Franco Glória Regina , Venancio Thiago M. 
Published: August 2021

ABSTRACTThe growth of sequenced bacterial genomes has revolutionized the assessment of microbial diversity. Pseudomonas is a widely diverse genus, containing more than 254 species. Although type strains have been employed to estimate Pseudomonas diversity, they represent a small fraction of the genomic diversity at a genus level. We used 10,035 available Pseudomonas genomes, including 210 type strains, to build a genomic distance network to estimate the number of species through community identification. We identified taxonomic inconsistencies with several type strains and found that 25.65% of the Pseudomonas genomes deposited on Genbank are misclassified. The phylogenetic tree using single-copy genes from representative genomes in each species cluster in the distance network revealed at least 14 Pseudomonas groups, including P. alcaligenes group proposed here. We show that Pseudomonas is likely an admixture of different genera and should be further divided. This study provides an overview of Pseudomonas diversity from a network and phylogenomic perspective that may help reduce the propagation of mislabeled Pseudomonas genomes.
Learning predictive cognitive maps with spiking neurons during behaviour and replays
Authors: Bono Jacopo , Zannone Sara , Pedrosa Victor , Clopath Claudia 
Published: August 2021

AbstractWe describe a framework where a biologically plausible spiking neural network mimicking hippocampal layers learns a cognitive map known as the successor representation. We show analytically how, on the algorithmic level, the learning follows the TD(λ) algorithm, which emerges from the underlying spike-timing dependent plasticity rule. We then analyze the implications of this framework, uncovering how behavioural activity and experience replays can play complementary roles when learning the representation of the environment, how we can learn relations over behavioural timescales with synaptic plasticity acting on the range of milliseconds, and how the learned representation can be flexibly encoded by allowing state-dependent delay discounting through neuromodulation and altered firing rates.
Using Topological Data Analysis and RRT to Investigate Protein Conformational Spaces
Authors: Dehghanpoor Ramin , Afrasiabi Fatemeh , Haspel Nurit 
Published: August 2021

AbstractAn essential step to understanding how different functionalities of proteins work is to explore their conformational space. However, because of the fleeting nature of conformational changes in proteins, investigating protein conformational spaces is a challenging task to do experimentally. Nonetheless, computational methods have shown to be practical to explore these conformational pathways. In this work, we use Topological Data Analysis (TDA) methods to evaluate our previously introduced algorithm called RRTMC, that uses a combination of Rapidly-exploring Random Trees algorithm and Monte Carlo criteria to explore these pathways. TDA is used to identify the intermediate conformations that are generated the most by RRTMC and examine how close they are to existing known intermediate conformations. We concluded that the intermediate conformations generated by RRTMC are close to existing experimental data and that TDA can be a helpful tool to analyze protein conformation sampling methods.
Precision engineering of an anti-HLA-A2 chimeric antigen receptor in regulatory T cells for transplant immune tolerance
Authors: Muller Yannick D. , Ferreira Leonardo M.R. , Ronin Emilie , Ho Patrick , Nguyen Vinh , Faleo Gaetano , Zhou Yu , Lee Karim , Leung Kevin K. , Skartsis Nikolaos , Kaul Anupurna M. , Mulder Arend , Claas Frans H.J. , Wells James A. , Bluestone Jeffrey A. , Tang Qizhi 
Published: August 2021

AbstractInfusion of regulatory T cells (Tregs) engineered with a chimeric antigen receptor (CAR) targeting donor-derived human leukocyte antigen (HLA) is a promising strategy to promote transplant tolerance. Here, we describe an anti-HLA-A2 CAR (A2-CAR) generated by grafting the complementarity-determining regions (CDRs) of a human monoclonal anti-HLA-A2 antibody into the framework regions of the Herceptin 4D5 single-chain variable fragment and fusing it with a CD28-ζ signaling domain. The CDR-grafted A2-CAR maintained the specificity of the original antibody. We then generated HLA-A2 mono-specific human CAR Tregs either by deleting the endogenous T-cell receptor (TCR) via CRISPR/Cas9 and introducing the A2-CAR using lentiviral transduction or by directly integrating the CAR construct into the TCR alpha constant locus using homology-directed repair. These A2-CAR+TCRdeficient human Tregs maintained both Treg phenotype and function in vitro. Moreover, they selectively accumulated in HLA-A2-expressing islets transplanted from either HLA-A2 transgenic mice or deceased human donors. A2-CAR+TCRdeficient Tregs did not impair the function of these HLA-A2+ islets, whereas similarly engineered A2-CAR+TCRdeficientCD4+ conventional T cells rejected the islets in less than 2 weeks. A2-CAR+TCRdeficient Tregs delayed graft-versus-host disease only in the presence of HLA-A2, expressed either by co-transferred peripheral blood mononuclear cells or by the recipient mice. Altogether, we demonstrate that genome-engineered mono-antigen-specific A2-CAR Tregs localize to HLA-A2-expressing grafts and exhibit antigen-dependent in vivo suppression, independent of TCR expression. These approaches may be applied towards developing precision Treg cell therapies for transplant tolerance.
Tardigrade CAHS Proteins Act as Molecular Swiss Army Knives to Mediate Desiccation Tolerance Through Multiple Mechanisms
Authors: Hesgrove Cherie S. , Nguyen Kenny H. , Biswas Sourav , Childs Charles A. , Shraddha KC , Medina Bryan X. , Alvarado Vladimir , Yu Feng , Sukenik Shahar , Malferrari Marco , Francia Francesco , Venturoli Giovanni , Martin Erik W. , Holehouse Alex S. , Boothby Thomas C. 
Published: August 2021

AbstractTardigrades, also known as water bears, make up a phylum of small but extremely hardy animals, renowned for their ability to survive extreme stresses, including desiccation. How tardigrades survive desiccation is one of the enduring mysteries of animal physiology. Here we show that CAHS D, an intrinsically disordered protein belonging to a unique family of proteins possessed only by tardigrades, undergoes a liquid-to-gel phase transition in a concentration dependent manner. Unlike other gelling proteins, such as gelatin, our data support a mechanism in which gel formation of CAHS D is driven by intermolecular β-β interactions. We find that gel formation corresponds with strong coordination of water and slowing of water diffusion. The degree of water coordination correlates with the ability of CAHS D to protect lactate dehydrogenase from unfolding when dried. This implies that the mechanism for unfolding protection can be attributed to a combination of hydration and slowed molecular motion. Conversely, rapid diffusion leading to efficient molecular shielding appears to be the predominant mechanism preventing protein aggregation. Our study demonstrates that distinct mechanisms are required for holistic protection during desiccation, and that protectants, such as CAHS D, can act as molecular ‘Swiss Army Knives’ capable of providing protection through several different mechanisms simultaneously.
A novel transposable element based authentication protocol for Drosophila cell lines
Authors: Mariyappa Daniel , Rusch Douglas B. , Han Shunhua , Luhur Arthur , Overton Danielle , Miller David F. B. , Bergman Casey M. , Zelhof Andrew C. 
Published: August 2021

AbstractDrosophila cell lines are used by researchers to investigate various cell biological phenomena. It is crucial to exercise good cell culture practice. Poor handling can lead to both inter- and intraspecies cross-contamination. Prolonged culturing can lead to introduction of large- and small-scale genomic changes. These factors, therefore, make it imperative that methods to authenticate Drosophila cell lines are developed to ensure reproducibility. Mammalian cell line authentication is reliant on short tandem repeat (STR) profiling, however the relatively low STR mutation rate in D. melanogaster at the individual level is likely to preclude the value of this technique. In contrast, transposable elements (TE) are highly polymorphic among individual flies and abundant in Drosophila cell lines. Therefore, we investigated the utility of TE insertions as markers to discriminate Drosophila cell lines derived from the same or different donor genotypes, divergent sub-lines of the same cell line, and from other insect cell lines. We developed a PCR-based next-generation sequencing protocol to cluster cell lines based on the genome-wide distribution of a limited number of diagnostic TE families. We determined the distribution of five TE families in S2R+, S2-DRSC, S2-DGRC, Kc167, ML-DmBG3-c2, mbn2, CME W1 Cl.8+, and OSS Drosophila cell lines. Two independent downstream analyses of the NGS data yielded similar clustering of these cell lines. Double-blind testing of the protocol reliably identified various Drosophila cell lines. In addition, our data indicate minimal changes with respect to the genome-wide distribution of these five TE families when cells are passaged for at least 50 times. The protocol developed can accurately identify and distinguish the numerous Drosophila cell lines available to the research community, thereby aiding reproducible Drosophila cell culture research.
Carbon isotope composition for agronomic diagnostic: predicting yield and yield response to nitrogen in wheat
Authors: Cossani C. Mariano , Sadras Victor O. 
Published: August 2021

AbstractRainfed crops rely on two sources of water: stored soil water at sowing and seasonal rain. In strongly seasonal winter-rainfall environments, stored soil water at sowing is minor, and uncertain seasonal rainfall is a source of risk. In south-eastern Australia, under-fertilisation is a common outcome of nitrogen risk management with implications for yield and soil mining. Here we explore the use of carbon isotope composition (δ 13C) to capture the effects of water in the prediction of yield and guide nitrogen management. In the sampled environment, crops receive at least 50% of seasonal rainfall by stem elongation, and at least 70% of seasonal rainfall by flowering. In a sample of 1518 plots, yield varied from 0.07 to 9.96 t ha-1 and correlated with δ 13C measured with isotope ratio mass spectrometer (IRMS) at flowering; this is consistent with the rainfall pattern and the physiology of the crop featuring a critical period for yield from 300 °Cd before to 100 °Cd after anthesis. In a sample of 135 plots, yield varied from 1.2 to 8.4 t ha-1 and correlated with δ 13C measured with IRMS at stem elongation. Yield response to nitrogen, defined as the difference between yield in fertilised crops (50 to 200 kg N ha-1) and unfertilised controls, correlated with δ 13C measured with IRMS at stem elongation, except for late-sown crops. Mid-infrared spectroscopy (MIR) returned estimates of δ 13C that agreed with δ 13C measured with IRMS (calibration: R2 = 0.82, RMSE = 0.53‰, n = 833; validation: R2 = 0.70, RMSE = 0.75‰, n = 364). We conclude that a MIR based, high-throughput, affordable measurement of δ 13C could be scaled to guide nitrogen management of wheat in winter-rainfall environments.