bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microenvironment Impacts the Molecular Architecture and Interactivity of Resident Cells in Marmoset Brain
Authors: Lin Jing-Ping , Kelly Hannah M. , Song Yeajin , Kawaguchi Riki , Geschwind Daniel H. , Jacobson Steven , Reich Daniel S. 
Published: January 2021

AbstractThe microenvironments of the brain consist of specialized cell types that together influence physiological functions in health and pathological outcomes in disease. Despite apparent differences in the density of neurons and oligodendrocytes in various milieus, such as gray matter (GM) and white matter (WM), the extent of structural and functional heterogeneity of other resident cells remains unclear. We profiled RNA in ~500,000 nuclei from 19 tissue types across the central nervous system of the healthy adult common marmoset (Callithrix jacchus) and mapped 87 identified subclusters (including neurons, glia, and vasculature) spatially onto a 3D MRI atlas. We performed cross-species comparison, explored regulatory pathways, surveyed cellular determinants of neurological disorders, and modeled regional intercellular communication. We found spatially segregated microglia, oligodendrocyte lineage cells, and astrocytes in WM and GM. WM-glia are diverse, are enriched with genes involved in stimulus response and biomolecule modification, and interact with other resident cells more extensively than their GM counterparts. GM-glia preserve the expression of developmental morphogens into adulthood and share 6 differentially enriched transcription factors that restrict the transcriptome complexity. Our work in marmoset, an experimentally tractable animal model with >5 times more WM volume and complexity than mouse, identifies novel WM-glia subtypes and their contributions to different neurological disorders. A companionCallithrix jacchusPrimate Cell Atlas (CjPCA) is available through an online portalhttps://cjpca.ninds.nih.govto facilitate data exploration.
GLUER: integrative analysis of single-cell omics and imaging data by deep neural network
Authors: Peng Tao , Chen Gregory M. , Tan Kai 
Published: January 2021

ABSTRACTSingle-cell omics assays have become essential tools for identifying and characterizing cell types and states of complex tissues. While each single-modality assay reveals distinctive features about the sequenced cells, true multi-omics assays are still in early stage of development. This notion signifies the importance of computationally integrating single-cell omics data that are conducted on various samples across various modalities. In addition, the advent of multiplexed molecular imaging assays has given rise to a need for computational methods for integrative analysis of single-cell imaging and omics data. Here, we present GLUER (inteGrative anaLysis of mUlti-omics at single-cEllResolution), a flexible tool for integration of single-cell multi-omics data and imaging data. Using multiple true multi-omics data sets as the ground truth, we demonstrate that GLUER achieved significant improvement over existing methods in terms of the accuracy of matching cells across different data modalities resulting in ameliorating downstream analyses such as clustering and trajectory inference. We further demonstrate the broad utility of GLUER for integrating single-cell transcriptomics data with imaging-based spatial proteomics and transcriptomics data. Finally, we extend GLUER to leverage true cell-pair labels when available in true multi-omics data, and show that this approach improves co-embedding and clustering results. With the rapid accumulation of single-cell multi-omics and imaging data, integrated data holds the promise of furthering our understanding of the role of heterogeneity in development and disease.
Expression and manufacturing of protein therapeutics in spirulina
Authors: Jester Benjamin , Zhao Hui , Gewe Mesfin , Adame Thomas , Perruzza Lisa , Bolick David , Agosti Jan , Khuong Nhi , Kuestner Rolf , Gamble Caitlin , Cruickshank Kendra , Ferrara Jeremy , Lim Rachelle , Paddock Troy , Brady Colin , Ertel Stacey , Zhang Mia , Tasch Michael , Saveria Tracy , Doughty David , Marshall Jacob , Carrieri Damian , Lee Jamie , Goetsch Lauren , Dang Jason , Sanjaya Nathaniel , Fletecher David , Martinez Anissa , Kadis Bryce , Sigmar Kristjian , Afreen Esha , Nguyen Tammy , Randolph Amanda , Taber Alexandria , Krzeszowski Ashley , Robinett Brittney , Grassi Fabio , Guerrant Richard , Spigarelli Michael , Takeuchi Ryo , Finrow Brian , Behnke Craig , Roberts James 
Published: January 2021

ABSTRACTArthrospira platensis(commonly known as spirulina) is a photosynthetic cyanobacterium1. It is a highly nutritious food that has been consumed for decades in the US, and even longer by indigenous cultures2. Its widespread use as a safe food source and proven scalability have driven frequent attempts to convert it into a biomanufacturing platform. But these were repeatedly frustrated by spirulina’s genetic intractability. We report here efficient and versatile genetic engineering methodology for spirulina that allows stable expression of bioactive protein therapeutics at high levels. We further describe large-scale, indoor cultivation and downstream processing methods appropriate for the manufacturing of biopharmaceuticals in spirulina. The potential of the platform is illustrated by pre-clinical development and human testing of an orally delivered antibody therapeutic against campylobacter, a major cause of infant mortality in the developing world and a growing antibiotic resistance threat3,4. This integrated development and manufacturing platform blends the safety of food-based biotechnology with the ease of genetic manipulation, rapid growth rates and high productivity characteristic of microbial platforms. These features combine for exceptionally low-cost production of biopharmaceuticals to address medical needs that are unfeasible with current biotechnology platforms.
Reagent-free Raman and quantitative phase imaging offer a unique morpho-molecular platform for recognition of malignancy and stages of B-cell acute lymphoblastic leukemia
Authors: Paidi Santosh Kumar , Raj Piyush , Bordett Rosalie , Zhang Chi , Karandikar Sukrut Hemant , Pandey Rishikesh , Barman Ishan 
Published: January 2021

AbstractAcute lymphoblastic leukemia (ALL) is one of the most common malignancies which account for nearly one-third of all pediatric cancers. The current diagnostic assays are time-consuming, labor-intensive, and require expensive reagents. Here, we report a label-free approach featuring diffraction phase imaging and Raman microscopy that can retrieve both morphological and molecular attributes for label-free optical phenotyping of individual B cells. By investigating leukemia cell lines of early and late stages along with the healthy B cells, we show that phase image can capture subtle morphological differences among the healthy, early, and late stages of leukemic cells. By exploiting its biomolecular specificity, we demonstrate that Raman microscopy is capable of accurately identifying not only different stages of leukemia cells, but also individual cell lines at each stage. Overall, our study provides a rationale for employing this hybrid modality to screen leukemia cells using the widefield QPI and using Raman microscopy for accurate differentiation of early and late-stage phenotypes. This contrast-free and rapid diagnostic tool exhibits great promise for clinical diagnosis and staging of leukemia in the near future.
Mechanism of Viral Glycoprotein Targeting by Membrane-associated-RING-CH Proteins
Authors: Lun Cheng Man , Waheed Abdul A. , Majadly Alhlam , Powell Nicole , Freed Eric O. 
Published: January 2021

AbstractAn emerging class of cellular inhibitory proteins has been identified that targets viral glycoproteins. These include the membrane-associated RING-CH (MARCH) family of E3 ubiquitin ligases that, among other functions, downregulate cell-surface proteins involved in adaptive immunity. The RING-CH domain of MARCH proteins is thought to function by catalyzing the ubiquitination of the cytoplasmic tails (CTs) of target proteins, leading to their degradation. MARCH proteins have recently been reported to target retroviral envelope glycoproteins (Env) and vesicular stomatitis virus G glycoprotein (VSV-G). However, the mechanism of antiviral activity remains poorly defined. Here we show that MARCH8 antagonizes the full-length forms of HIV-1 Env, VSV-G, Ebola virus glycoprotein (EboV-GP), and the spike (S) protein of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) thereby impairing the infectivity of virions pseudotyped with these viral glycoproteins. This MARCH8-mediated targeting of viral glycoproteins requires the E3 ubiquitin ligase activity of the RING-CH domain. We observe that MARCH8 protein antagonism of VSV-G is CT dependent. In contrast, MARCH8-mediated targeting of HIV-1 Env, EboV-GP and SARS-CoV-2 S protein by MARCH8 does not require the CT, suggesting a novel mechanism of MARCH-mediated antagonism of these viral glycoproteins. Confocal microscopy data demonstrate that MARCH8 traps the viral glycoproteins in an intracellular compartment. We observe that the endogenous expression ofMARCH8in several relevant human cell types is rapidly inducible by type I interferon. These results help to inform the mechanism by which MARCH proteins exert their antiviral activity and provide insights into the role of cellular inhibitory factors in antagonizing the biogenesis, trafficking, and virion incorporation of viral glycoproteins.ImportanceViral envelope glycoproteins are an important structural component on the surface of enveloped viruses that direct virus binding and entry and also serve as targets for the host adaptive immune response. In this study, we investigate the mechanism of action of the MARCH family of cellular proteins that disrupt the trafficking and virion incorporation of viral glycoproteins across several virus families. This research provides novel insights into how host cell factors antagonize viral replication, perhaps opening new avenues for therapeutic intervention in the replication of a diverse group of highly pathogenic enveloped viruses.
Evidence of Chelonid Herpesvirus 5 (ChHV5) in Green Turtles (Chelonia mydas) from Sabah, Borneo
Authors: Loganathan Aswini Leela , Palaniappan Pushpa , Subbiah Vijay Kumar 
Published: January 2021

ABSTRACTFibropapillomatosis (FP) is characterized by cutaneous tumours and is associated with Chelonid herpesvirus 5 (ChHV5), an alphaherpesvirus from the family Herpesviridae. Here, we provide the first evidence of ChHV5-associated FP in endangered Green turtles (Chelonia mydas) from Sabah, which is located at the northern region of Malaysian Borneo. The aims of this study were firstly, to determine the presence of ChHV5 in both tumour exhibiting and tumour-free turtles using molecular techniques and secondly, to determine the phylogeography of ChHV5 in Sabah. We also aim to provide evidence of ChHV5 infection through histopathological examinations. A total of 115 Green turtles were sampled from Mabul Island, Sabah. We observed three Green turtles that exhibited FP tumours and were positive for ChHV5.In addition, six clinically healthy turtles were also positive for the virus based on Polymerase Chain Reaction of three viral genes (Capsid protein gene UL18, Glycoprotein H gene UL22 and Glycoprotein B gene UL27). The prevalence of the ChHV5 was 5.22% in asymptomatic Green turtles. Epidermal intranuclear inclusions were identified in tumour lesions upon histopathological examination. Thus, the emergence of ChHV5 in Green turtle in the waters of Sabah could indicate a possible threat to sea turtle populations in the future and requires further monitoring of the populations along the Bornean coast.
Single-Cell Proteomics Defines the Cellular Heterogeneity of Localized Prostate Cancer
Authors: De Vargas Roditi Laura , Jacobs Andrea , Rueschoff Jan H. , Bankhead Pete , Chevrier Stephane , Jackson Hartland W. , Hermanns Thomas , Fankhauser Christian D. , Poyet Cedric , Chun Felix , Rupp Niels J. , Tschaebunin Alexandra , Bodenmiller Bernd , Wild Peter J. 
Published: January 2021

ABSTRACTLocalized prostate cancer exhibits multiple genomic alterations and heterogeneity at the proteomic level. Single-cell technologies capture important cell-to-cell variability responsible for heterogeneity in biomarker expression that may be overlooked when molecular alterations are based on bulk tissue samples. The aim of this study was to identify novel prognostic biomarkers and describe the heterogeneity of prostate cancer and the associated immune cell infiltrates by simultaneously quantifying 36 proteins using single-cell mass cytometry analysis of over 1,6 million cells from 58 men with localized prostate cancer. To perform this task, we proposed a novel computational pipeline, Franken, which showed unprecedented combination of performance, sensitivity and scalability for high dimensional clustering compared to state of the art methods. We were able to describe subpopulations of immune, stromal, and prostate cells, including unique changes occurring in tumor tissues and high grade disease providing insights into the coordinated progression of prostate cancer. Our results further indicated that men with localized disease already harbor rare subpopulations that typically occur in castration-resistant and metastatic disease, which were confirmed through imaging. Our methodology could be used to discover novel prognostic biomarkers to personalize treatment and improve outcomes.
A high-content platform for physiological profiling and unbiased classification of individual neurons
Authors: DuBreuil Daniel M. , Chiang Brenda , Zhu Kevin , Lai Xiaofan , Flynn Patrick , Sapir Yechiam , Wainger Brian J. 
Published: January 2021

ABSTRACTHigh-throughput physiological assays often lose single cell resolution, precluding subtype-specific analyses of neuronal activation mechanism and drug effects. Here, we demonstrate APPOINT, Automated Physiological Phenotyping Of Individual Neuronal Types. This physiological assay platform combines calcium imaging, robotic liquid handling, and automated analysis to generate physiological activation profiles of single neurons at a large scale. Using unbiased techniques, we quantify responses to multiple sequential stimuli, enabling subgroup identification by physiology and probing of distinct mechanisms of neuronal activation within subgroups. Using APPOINT, we quantify primary sensory neuron activation by metabotropic receptor agonists and identify potential contributors to pain signaling. Furthermore, we expand the role of neuroimmune interactions by showing that human serum can directly activate sensory neurons, elucidating a new potential pain mechanism. Finally, we apply APPOINT to develop a high-throughput, all-optical approach for quantification of activation threshold and pharmacologically separate the contributions of distinct ion channel subsets to optical activation.
Hydrodynamic stress and phenotypic plasticity of the zebrafish regenerating fin
Authors: Dagenais Paule , Blanchoud Simon , Pury David , Pfefferli Catherine , Aegerter-Wilmsen Tinri , Aegerter Christof M. , Jaźwińska Anna 
Published: January 2021

AbstractUnderstanding how extrinsic factors modulate genetically encoded information to produce a specific phenotype is of prime scientific interest. In particular, the feedback mechanism between abiotic forces and locomotory organs during morphogenesis to achieve efficient movement is a highly relevant example of such modulation. The study of this developmental process can provide unique insights on the transduction of cues at the interface between physics and biology. Here, we take advantage of the natural ability of adult zebrafish to regenerate their amputated fins to assess its morphogenic plasticity upon external modulations. Using a variety of surgical and chemical treatments, we are able to induce phenotypic responses to the structure of the fin. In particular, fin cleft depth and the bifurcation of the bony rays are modulated by the surface area of the stump. To dissect the role of mechanotransduction in this process, we investigate the patterns of hydrodynamic forces acting on the surface of a zebrafish fin during regeneration by using particle tracking velocimetry on a range of biomimetic hydrofoils. This experimental approach enables us to quantitatively compare hydrodynamic stress distributions over flapping fins of varying sizes and shapes. As a result, viscous shear stress acting on the tip of the fin and the resulting internal tension are proposed as suitable signals for guiding the regulation of ray growth dynamics and branching pattern. Our findings suggest that mechanical forces are involved in the fine-tuning of the locomotory organ during fin morphogenesis.
Saccades, attentional orienting and disengagement: the effects of anodal tDCS over right posterior parietal cortex (PPC) and frontal eye field (FEF)
Authors: Diana Lorenzo , Pilastro Patrick , Aiello Edoardo N. , Eberhard-Moscicka Aleksandra K. , Müri René M. , Bolognini Nadia 
Published: January 2021

ABSTRACTIn the present work, we applied anodal transcranial direct current stimulation (tDCS) over the posterior parietal cortex (PPC) and frontal eye field (FEF) of the right hemisphere in healthy subjects to modulate attentional orienting and disengagement in a gap-overlap task. Both stimulations led to bilateral improvements in saccadic reaction times (SRTs), with larger effects for gap trials. However, analyses showed that the gap effect was not affected by tDCS. Importantly, we observed significant effects of baseline performance that may mediate side- and task-specific effects of brain stimulation.
Large Organellar Changes Occur during Mild Heat Shock in Yeast
Authors: Keuenhof Katharina , Berglund Lisa Larsson , Hill Sandra Malmgren , Schneider Kara L , Widlund Per O , Nyström Thomas , Höög Johanna L 
Published: January 2021

AbstractWhen the temperature is increased, the heat shock response is activated to protect the cellular environment. The transcriptomics and proteomics of this process are intensively studied, while information about how the cell responds structurally to heat stress is mostly lacking. Here,Saccharomyces cerevisiaewere subjected to a mild continuous heat shock and intermittently cryo-immobilized for electron microscopy. Through measuring changes in all distinguishable organelle numbers, sizes, and morphologies in over 2400 electron micrographs a major restructuring of the cell’s internal architecture during the progressive heat shock was revealed. The cell grew larger but most organelles within it expanded even more. Organelles responded to heat shock at different times, both in terms of size and number, and adaptations of certain organelles’ morphology were observed. Multivesicular bodies grew to almost 170% in size, indicating a previously unknown involvement in the heat shock response. A previously undescribed electron translucent structure accumulated close to the plasma membrane during the entire time course. This all-encompassing approach provides a detailed chronological progression of organelle adaptation throughout the cellular stress response.Summary statementExposure to mild heat shock leads to large quantifiable changes in the cellular ultrastructure of yeast, shows involvement of MVBs in the heat shock response and the apparition of novel structures.
Separate neural dynamics underlying the acquisition of different auditory category structures
Authors: Feng Gangyi , Gan Zhenzhong , Yi Han Gyol , Ell Shawn W. , Roark Casey L. , Wang Suiping , Wong Patrick C. M. , Chandrasekaran Bharath 
Published: January 2021

AbstractCurrent models of auditory category learning argue for a rigid specialization of hierarchically organized regions that are fine-tuned to extracting and mapping acoustic dimensions to categories. We test a competing hypothesis: the neural dynamics of emerging auditory representations are driven by category structures and learning strategies. We designed a category learning experiment where two groups of learners learned novel auditory categories with identical dimensions but differing category structures: rule-based (RB) and information-integration (II) based categories. Despite similar learning accuracies, strategies and cortico-striatal systems processing feedback differed across structures. Emergent neural representations of category information within an auditory frontotemporal pathway exclusively for the II learning task. In contrast, the RB task yielded neural representations within distributed regions involved in cognitive control that emerged at different time-points of learning. Our results demonstrate that learners’ neural systems are flexible and show distinct spatiotemporal patterns that are not dimension-specific but reflect underlying category structures.SignificanceWhether it is an alarm signifying danger or the characteristics of background noise, humans are capable of rapid auditory learning. Extant models posit that novel auditory representations emerge in the superior temporal gyrus, a region specialized for extracting behaviorally relevant auditory dimensions and transformed onto decisions via the dorsal auditory stream. Using a computational cognitive neuroscience approach, we offer an alternative viewpoint: emergent auditory representations are highly flexible, showing distinct spatial and temporal trajectories that reflect different category structures.
LanceOtron: a deep learning peak caller for ATAC-seq, ChIP-seq, and DNase-seq
Authors: Hentges Lance D. , Sergeant Martin J. , Downes Damien J. , Hughes Jim R. , Taylor Stephen 
Published: January 2021

AbstractATAC-seq, ChIP-seq, and DNase-seq have revolutionized molecular biology by allowing researchers to identify important DNA-encoded elements genome-wide. Regions where these elements are found appear as peaks in the analog signal of an assay’s coverage track, and despite the ease with which humans can visually categorize these regions, meaningful peak calls from whole genome datasets require complex analytical techniques. Current methods focus on statistical tests to classify peaks, reducing the information-dense peak shapes to simply maximum height, and discounting that background signals do not completely follow any known probability distribution for significance testing. Deep learning has been shown to be highly accurate for image recognition, on par or exceeding human ability, providing an opportunity to reimagine and improve peak calling. We present the peak calling framework LanceOtron, which combines multifaceted enrichment measurements with deep learning image recognition techniques for assessing peak shape. In benchmarking transcription factor binding, chromatin modification, and open chromatin datasets, LanceOtron outperforms the long-standing, gold-standard peak caller MACS2 through its improved selectivity and near perfect sensitivity. In addition to command line accessibility, a graphical web application was designed to give any researcher the ability to generate optimal peak calls and interactive visualizations in a single step.