bluuebunny/crossref_metadata_2025_split huggingface dataset:
Targeting Glioblastoma Signaling and Metabolism with A Re-Purposed Brain-Penetrant Drug
Authors: Bi Junfeng , Khan Atif , Tang Jun , Wu Sihan , Zhang Wei , Gimple Ryan C. , Koga Tomoyuki , Armando Aaron M. , Miki Shunichiro , Yang Huijun , Prager Briana , Curtis Ellis J. , Wainwright Derek A. , Furnari Frank B. , Rich Jeremy N. , Cloughesy Timothy F. , Quehenberger Oswald , Kornblum Harley I. , Rzhetsky Andrey , Cravatt Benjamin F. , Mischel Paul S. 
Published: March 2021

AbstractThe highly lethal brain cancer glioblastoma (GBM) poses a daunting challenge because the blood-brain barrier renders potentially druggable amplified or mutated oncoproteins relatively inaccessible. Here, we identify SMPD1, an enzyme that regulates the conversion of sphingomyelin to ceramide and a critical regulator of plasma membrane structure and organization, as an actionable drug target in glioblastoma. We show that the safe and highly brain-penetrant antidepressant fluoxetine, potently inhibits SMPD1 activity, killing GBMs, in vitro and in patient-derived xenografts, through inhibition of EGFR signaling and via activation of lysosomal stress. Combining fluoxetine with the chemotherapeutic agent temozolomide, a standard of care for GBM patients, causes massive increases in GBM cell death, and complete and long-lived tumor regression in mice. Incorporation of real-world evidence from electronic medical records from insurance databases, reveals significantly increased survival in glioblastoma patients treated with fluoxetine, which was not seen in patients treated with other SSRI anti-depressants. These results nominate the repurposing of fluoxetine as a potentially safe and promising therapy for GBM patients and suggest prospective randomized clinical trials.
Deconvolution of Expression for Nascent RNA Sequencing Data (DENR) Highlights Pre-RNA Isoform Diversity in Human Cells
Authors: Zhao Yixin , Dukler Noah , Barshad Gilad , Toneyan Shushan , Danko Charles G. , Siepel Adam 
Published: March 2021

AbstractQuantification of mature-RNA isoform abundance from RNA-seq data has been extensively studied, but much less attention has been devoted to quantifying the abundance of distinct precursor RNAs based on nascent RNA sequencing data. Here we address this problem with a new computational method called Deconvolution of Expression for Nascent RNA sequencing data (DENR). DENR models the nascent RNA read counts at each locus as a mixture of user-provided isoforms. The performance of the baseline algorithm is enhanced by the use of machine-learning predictions of transcription start sites (TSSs) and an adjustment for the typical “shape profile” of read counts along a transcription unit. We show using simulated data that DENR clearly outperforms simple read-count-based methods for estimating the abundances of both whole genes and isoforms. By applying DENR to previously published PRO-seq data from K562 and CD4+ T cells, we find that transcription of multiple isoforms per gene is widespread, and the dominant isoform frequently makes use of an internal TSS. We also identify > 200 genes whose dominant isoforms make use of different TSSs in these two cell types. Finally, we apply DENR and StringTie to newly generated PRO-seq and RNA-seq data, respectively, for human CD4+ T cells and CD14+ monocytes, and show that entropy at the pre-RNA level makes a disproportionate contribution to overall isoform diversity, especially across cell types. Altogether, DENR is the first computational tool to enable abundance quantification of pre-RNA isoforms based on nascent RNA sequencing data, and it reveals high levels of pre-RNA isoform diversity in human cells.
A novel heteromeric pantothenate kinase complex in apicomplexan parasites
Authors: Tjhin Erick T. , Howieson Vanessa M. , Spry Christina , van Dooren Giel G. , Saliba Kevin J. 
Published: March 2021

ABSTRACTCoenzyme A is synthesised from pantothenate via five enzyme-mediated steps. The first step is catalysed by pantothenate kinase (PanK). All PanKs characterised to date form homodimers. Many organisms express multiple PanKs. In some cases, these PanKs are not functionally redundant, and some appear to be non-functional. Here, we investigate the PanKs in two pathogenic apicomplexan parasites,Plasmodium falciparumandToxoplasma gondii. Each of these organisms express two PanK homologues (PanK1 and PanK2). We demonstrate thatPfPanK1 andPfPanK2 associate, forming a single, functional PanK complex that includes the multi-functional protein,Pf14-3-3I. Similarly, we demonstrate thatTgPanK1 andTgPanK2 form a single complex that possesses PanK activity. BothTgPanK1 andTgPanK2 are essential forT. gondiiproliferation, specifically due to their PanK activity. Our study constitutes the first examples of heteromeric PanK complexes in nature and provides an explanation for the presence of multiple PanKs within certain organisms.
A chemogenetic platform for controlling plasma membrane signaling and synthetic signal oscillation
Authors: Hatano Yuka , Suzuki Sachio , Nakamura Akinobu , Yoshii Tatsuyuki , Atsuta-Tsunoda Kyoko , Aoki Kazuhiro , Tsukiji Shinya 
Published: March 2021

ABSTRACTChemogenetic methods that enable the rapid translocation of specific signaling proteins in living cells using small molecules are powerful tools for manipulating and interrogating intracellular signaling networks. However, existing techniques rely on chemically induced dimerization of two protein components and have certain limitations, such as a lack of reversibility, bioorthogonality, and usability. Here, by expanding our self-localizing ligand-induced protein translocation (SLIPT) approach, we have developed a versatile chemogenetic system for plasma membrane (PM)-targeted protein translocation. In this system, a novel engineeredEscherichia colidihydrofolate reductase in which a hexalysine (K6) sequence is inserted in a loop region (iK6DHFR) is used as a universal protein tag for PM-targeted SLIPT. Proteins of interest that are fused to theiK6DHFR tag can be specifically recruited from the cytoplasm to the PM within minutes by addition of a myristoyl-d-Cys-tethered trimethoprim ligand (mDcTMP). We demonstrated the broad applicability and robustness of this engineered protein–synthetic ligand pair as a tool for the conditional activation of various types of signaling molecules, including protein and lipid kinases, small GTPases, heterotrimeric G proteins, and second messengers. In combination with a competitor ligand and a culture-medium flow chamber, we further demonstrated the application of the system for chemically manipulating protein localization in a reversible and repeatable manner to generate synthetic signal oscillations in living cells. The present bioorthogonaliK6DHFR/mDcTMP-based SLIPT system affords rapid, reversible, and repeatable control of the PM recruitment of target proteins, offering a versatile and easy-to-use chemogenetic platform for chemical and synthetic biology applications.
Cost efficiency of institutional incentives in finite populations
Authors: Duong Manh Hong , Anh Han The 
Published: March 2021

AbstractInstitutions can provide incentives to increase cooperation behaviour in a population where this behaviour is infrequent. This process is costly, and it is thus important to optimize the overall spending. This problem can be mathematically formulated as a multi-objective optimization problem where one wishes to minimize the cost of providing incentives while ensuring a desired level of cooperation within the population. In this paper, we provide a rigorous analysis for this problem. We study cooperation dilemmas in both the pairwise (the Donation game) and multi-player (the Public Goods game) settings. We prove the regularity of the (total incentive) cost function, characterize its asymptotic limits (infinite population, weak selection and large selection) and show exactly when reward or punishment is more efficient. We prove that the cost function exhibits a phase transition phenomena when the intensity of selection varies. We calculate the critical threshold in regards to the phase transition and study the optimization problem when the intensity of selection is under and above the critical value. It allows us to provide an exact calculation for the optimal cost of incentive, for a given intensity of selection. Finally, we provide numerical simulations to demonstrate the analytical results. Overall, our analysis provides for the first time a selection-dependent calculation of the optimal cost of institutional incentives (for both reward and punishment) that guarantees a minimum amount of cooperation. It is of crucial importance for real-world applications of institutional incentives since intensity of selection is specific to a given population and the underlying game payoff structure.In this Supplementary Information, we provide detailed calculations and proofs as well as illustrative figures for the analytical results in the main text of the present paper.
Chronic neuronal excitation leads to homeostatic suppression of structural long-term potentiation
Authors: Ueda Hiromi H. , Sato Aiko , Onda Maki , Murakoshi Hideji 
Published: March 2021

SUMMARYSynaptic plasticity is long-lasting changes in synaptic currents and structure. When neurons are exposed to signals that induce aberrant neuronal excitation, they increase the threshold for the induction of synaptic plasticity, called homeostatic plasticity. To further understand the homeostatic regulation of synaptic plasticity and its molecular mechanisms, we investigated glutamate uncaging/photoactivatable (pa)CaMKII-dependent sLTP induction in hippocampal CA1 neurons after chronic neuronal excitation by GABAAreceptor antagonists. The neuronal excitation suppressed the glutamate uncaging-evoked Ca2+influx and failed to induce sLTP. Single-spine optogenetic stimulation using paCaMKII also failed to induce sLTP, suggesting that CaMKII downstream signaling is impaired in response to chronic neuronal excitation. Furthermore, while the inhibition of Ca2+influx was protein synthesis-independent, paCaMKII-induced sLTP depended on it. Our findings demonstrate that chronic neuronal excitation suppresses sLTP in two independent ways (i.e., the inhibitions of Ca2+influx and CaMKII downstream signaling), which may contribute to the robust neuronal protection in excitable environments.
Integrated single-cell transcriptomics and epigenomics reveals strong germinal center-associated etiology of autoimmune risk loci
Authors: King Hamish W , Wells Kristen L , Shipony Zohar , Kathiria Arwa S , Wagar Lisa E , Lareau Caleb , Orban Nara , Capasso Robson , Davis Mark M , Steinmetz Lars M , James Louisa K , Greenleaf William J 
Published: March 2021

AbstractThe germinal center (GC) response is critical for both effective adaptive immunity and establishing peripheral tolerance by limiting auto-reactive B cells. Dysfunction in these processes can lead to defects in immune response to pathogens or contribute to autoimmune disease. To understand the gene regulatory principles underlying the GC response, we generated a single-cell transcriptomic and epigenomic atlas of the human tonsil, a widely studied and representative lymphoid tissue. We characterize diverse immune cell subsets and build a trajectory of dynamic gene expression and transcription factor activity during B cell activation, GC formation, and plasma cell differentiation. We subsequently leverage cell type-specific transcriptomic and epigenomic maps to interpret potential regulatory impact of genetic variants implicated in autoimmunity, revealing that many exhibit their greatest regulatory potential in GC cell populations. Together, these analyses provide a powerful new cell type-resolved resource for the interpretation of cellular and genetic causes underpinning autoimmune disease.One sentence summarySingle-cell chromatin accessibility landscapes of immune cell subsets reveal regulatory potential of autoimmune-associated genetic variants during the germinal center response.
Inhibition of the ubiquitin-proteasome system by a bioactivatable compound
Authors: Giovannucci Tatiana A. , Salomons Florian A. , Haraldsson Martin , Elfman Lotta H. M. , Wickström Malin , Young Patrick , Lundbäck Thomas , Eirich Jürgen , Altun Mikael , Jafari Rozbeh , Gustavsson Anna-Lena , Johnsen John Inge , Dantuma Nico P. 
Published: March 2021

SummaryMalignant cells display an increased sensitivity towards drugs that reduce the function of the ubiquitin-proteasome system (UPS), which is the primary proteolytic system for destruction of aberrant proteins. Here, we report on the discovery of the bioactivatable compound CBK77, which causes an irreversible collapse of the UPS, accompanied by a general accumulation of ubiquitylated proteins and caspase-dependent cell death. CBK77 caused accumulation of ubiquitin-dependent, but not ubiquitin-independent, reporter substrates of the UPS, suggesting a selective effect on ubiquitin-dependent proteolysis. In a genome-wide CRISPR interference screen, we identified the redox enzyme NAD(P)H:quinone oxidoreductase 1 (NQO1) as a critical mediator of CBK77 activity, and further demonstrated its role as the compound bioactivator. Through affinity-based proteomics, we found that CBK77 covalently interacts with ubiquitin. In vitro experiments showed that CBK77-treated ubiquitin conjugates were less susceptible to disassembly by deubiquitylating enzymes.In vivoefficacy of CBK77 was validated by reduced growth of NQO1-proficient human adenocarcinoma cells in nude mice treated with CBK77. This first-in-class NQO1-activatable UPS inhibitor suggests that it may be possible to exploit the intracellular environment in malignant cells for leveraging the impact of compounds that impair the UPS.
Source imaging of high-density visual evoked potentials with multi-scale brain parcellations and connectomes
Authors: Pascucci David , Tourbier Sebastien , Rué-Queralt Joan , Carboni Margherita , Hagmann Patric , Plomp Gijs 
Published: March 2021

AbstractWe describe the multimodal neuroimaging dataset VEPCON (OpenNeuro Dataset ds003505). It includes raw data and derivatives of high-density EEG, structural MRI, diffusion weighted images (DWI) and single-trial behavior (accuracy, reaction time). Visual evoked potentials (VEPs) were recorded while participants (n=20) discriminated briefly presented faces from scrambled faces, or coherently moving stimuli from incoherent ones. EEG and MRI were recorded separately from the same participants. The dataset contains pre-processed EEG of single trials in each condition, behavioral measures, structural MRIs, individual brain parcellations at 5 spatial resolutions (83 to 1015 regions), and the corresponding structural connectomes computed from fiber count, fiber density, average fractional anisotropy and mean diffusivity maps. For source imaging, VEPCON provides EEG inverse solutions based on individual anatomy, with Python and Matlab scripts to derive activity time-series in each brain region, for each parcellation level. The BIDS-compatible dataset can contribute to multimodal methods development, studying structure-function relations, and to unimodal optimization of source imaging and graph analyses, among many other possibilities.
Cluster Analysis of SARS-CoV-2 Gene using Deep Learning Autoencoder: Gene Profiling for Mutations and Transitions
Authors: Miyake Jun , Sato Takaaki , Baba Shunsuke , Nakamura Hayao , Niioka Hirohiko , Nakazawa Yoshihisa 
Published: March 2021

AbstractWe report on a method for analyzing the variant of coronavirus genes using autoencoder. Since coronaviruses have mutated rapidly and generated a large number of genotypes, an appropriate method for understanding the entire population is required. The method using autoencoder meets this requirement and is suitable for understanding how and when the variants emarge and disappear. For the over 30,000 SARS-CoV-2 ORF1ab gene sequences sampled globally from December 2019 to February 2021, we were able to represent a summary of their characteristics in a 3D plot and show the expansion, decline, and transformation of the virus types over time and by region. Based on ORF1ab genes, the SARS-CoV-2 viruses were classified into five major types (A, B, C, D, and E in the order of appearance): the virus type that originated in China at the end of 2019 (type A) practically disappeared in June 2020; two virus types (types B and C) have emerged in the United States and Europe since February 2020, and type B has become a global phenomenon. Type C is only prevalent in the U.S. and is suspected to be associated with high mortality, but this type also disappeared at the end of June. Type D is only found in Australia. Currently, the epidemic is dominated by types B and E.
Alignment and Integration of Spatial Transcriptomics Data
Authors: Zeira Ron , Land Max , Raphael Benjamin J. 
Published: March 2021

AbstractSpatial transcriptomics (ST) is a new technology that measures mRNA expression across thousands of spots on a tissue slice, while preserving information about the spatial location of spots. ST is typically applied to several replicates from adjacent slices of a tissue. However, existing methods to analyze ST data do not take full advantage of the similarity in both gene expression and spatial organization across these replicates. We introduce a new methodPASTE(Probabilistic Alignment of ST Experiments) to align and integrate ST data across adjacent tissue slices leveraging both transcriptional similarity and spatial distances between spots. First, we formalize and solve the problem of pairwise alignment of ST data from adjacent tissue slices, or layers, using Fused Gromov-Wasserstein Optimal Transport (FGW-OT), which accounts for variability in the composition and spatial location of the spots on each layer. From these pairwise alignments, we construct a 3D representation of the tissue. Next, we introduce the problem of simultaneous alignment and integration of multiple ST layers into a single layer with a low rank gene expression matrix. We derive an algorithm to solve the problem by alternating between solving FGW-OT instances and solving a Non-negative Matrix Factorization (NMF) of a weighted expression matrix. We show on both simulated and real ST datasets that PASTE accurately aligns spots across adjacent layers and accurately estimates a consensus expression matrix from multiple ST layers. PASTE outperforms integration methods that rely solely on either transcriptional similarity or spatial similarity, demonstrating the advantages of combining both types of information.Code availabilitySoftware is available athttps://github.com/raphael-group/paste
The spatial network structure of intertidal meiofaunal communities derived from environmental DNA metabarcoding surveys in Northwest Iberia
Authors: Bellisario Bruno , Fais Maria , Duarte Sofia , Vieira Pedro E. , Canchaya Carlos , Costa Filipe O. 
Published: March 2021

AbstractThe identification of the patterns and mechanisms behind species’ distribution is one of the major challenges in ecology, having also important outcomes for the conservation and management of ecosystems. This is especially true for those components of biodiversity providing essential ecosystem functions and for which standard surveys may underestimate their real taxonomic diversity due to their high degree of cryptic diversity and inherent diagnosis difficulties, such as meiofaunal communities. Environmental DNA (eDNA) metabarcoding may provide a fast and reliable way to refine and scale-up the characterization of biological diversity in complex environmental samples, allowing to bypass such drawbacks and increase the resolution of biodiversity estimates. Moreover, the possibility of integrating eDNA metabarcoding-derived data with tools and methods rooted in network theory would deepen the knowledge of the structuring processes of ecological communities in ways that cannot be predicted from studying individual species/communities in isolation. Here, a sediment eDNA metabarcoding of mitochondrial cytochrome c oxidase I (COI) and the nuclear hypervariable V4 region of the 18S rDNA (18S) was used to reconstruct the spatial networks of intertidal meiofaunal OTUs from three estuaries of North-Western Iberian Peninsula. Null models were used to identify the role of environmental and spatial constraints on the structure of COI- and 18S-derived spatial networks and to characterize the macroecological features of surveyed phyla. Our results show the feasibility of eDNA metabarcoding, not only to capture a fair amount of diversity hard to detect with standard surveys procedures, but also to identify hierarchical spatial structures in intertidal meiofaunal assemblages. This suggests that exclusivity of occurrence rather than pervasiveness appears to be the norm in meiofaunal organisms and that niche-based processes predominantly drive the spatial aggregation and contemporary distribution of meiofaunal phyla within the system.
Accurate reconstruction of dynamic gene expression and growth rate profiles from noisy measurements
Authors: Vidal Gonzalo , Vidal-Céspedes Carlos , Rudge Timothy J. 
Published: March 2021

SummaryCells face changing environments to which they sense and respond in complex ways, changing their rates of gene expression and growth. Measuring these dynamics is therefore essential to understanding natural and synthetic regulatory networks that give rise to functional phenotypes. However, reconstruction of gene expression and growth rate profiles from typically noisy measurements of cell populations is difficult due to the effects of noise at low cell densities among other factors. We present here a method for estimation of dynamic gene expression rates and biomass growth rates from noisy measurement data, and show that it is several times more accurate than current approaches. We applied our method to multiple promoter-reporter fusion genes. Gene expression rates of such promoter-reporter fusions are typically used as a proxy for transcription rates. However, using our method we show that fusion gene expression rate dynamics are determined at least by the promoter of interest and the downstream reporter.
L-Thyroxine improves vestibular compensation in a rat model of acute peripheral vestibulopathy
Authors: Rastoldo Guillaume , Marouane Emna , El Mahmoudi Nada , Pericat David , Watabe Isabelle , Lapotre Agnes , Tonetto Alain , López-Juárez Alejandra , Caron Philippe , Fraysse Marie-José Esteve , Zwergal Andreas , Tighilet Brahim 
Published: March 2021

AbstractUnilateral vestibular lesions induce a vestibular syndrome, which recovers over time due to vestibular compensation. The therapeutic effect of L-Thyroxine (L-T4) on vestibular compensation was investigated by behavioral testing and immunohistochemical analysis in a rat model of unilateral vestibular neurectomy (UVN). We demonstrated that an acute L-T4 treatment reduced the vestibular syndrome and significantly promoted vestibular compensation. Thyroid hormone receptors (TRα and TRβ) and type II iodothyronine deiodinase (DIO2) were present in the vestibular nuclei (VN), supporting a local action of L-T4. We confirmed the T4-induced metabolic effects by demonstrating an increase in the number of cytochrome oxidase-labelled neurons in the VN three days after the lesion. L-T4 treatment modulated glial reaction by decreasing both microglia and oligodendrocytes in the deafferented VN three days after UVN and increased cell proliferation. The survival of newly generated cells was not affected, but neuronal differentiation was altered by the L-T4 treatment.