bluuebunny/crossref_metadata_2025_split huggingface dataset:
Virus exposure and neurodegenerative disease risk across national biobanks
Authors: Levine Kristin , Leonard Hampton L. , Blauwendraat Cornelis , Iwaki Hirotaka , Johnson Nicholas , Bandres-Ciga Sara , Koroshetz Walter , Ferrucci Luigi , Faghri Faraz , Singleton Andrew B. , Nalls Mike A. 
Published: July 2022

ABSTRACTBACKGROUNDWith recent findings connecting Epstein-Barr virus to increased risk of multiple sclerosis and growing concerns regarding the potential neurological impact of the coronavirus pandemic, we surveyed biobank scale real-world data to identify potential links between viral exposures and neurodegenerative disease risks.METHODSTo assess the potential increased risk of neurodegenerative diseases due to viral exposures, we mined time series data from FinnGen as a discovery dataset and cross-sectional data from the UK Biobank as a replication dataset for 73 pairs of common viral exposures and neurodegenerative disease outcomes. We investigated the impact of time span between viral exposure and disease risk using time series data from FinnGen at 1, 5, and 15 year intervals between exposure and disease onset. This analysis helped us to avoid the potential confounding of concurrent diagnosis due to hospitalization with viral infection. Further, to address the possible bias of reverse causality we examined risk for severe viral infections after NDD diagnosis.RESULTSWe identified 45 viral exposures significantly associated with increased risk of post-exposure neurodegenerative disease onset after multiple test correction in the discovery phase using longitudinal data. 22 of these associations were replicated in cross sectional data from the UK Biobank. The largest effect association we saw replicated was between viral encephalitis exposure and Alzheimer’s disease, with discovery hazard estimates of ∼30 and a replication odds ratio of ∼22. We also replicated the association between Epstein-Barr virus exposure and multiple sclerosis 5-15 years before diagnosis of multiple sclerosis. In total, 17 virus/neurodegeneration pairs were significant with 5-15 years between viral exposure and NDD diagnosis. In an investigation of potential confounding and reverse causality, we generally see larger hazard ratios associated with viruses preceding NDD diagnosis than viruses post NDD diagnosis.CONCLUSIONSViral exposures contribute to later in life risk of neurodegenerative disease with increased risk of neurodegeneration still significant at up to 15 years between some events in this report.
MultiCPA: Multimodal Compositional Perturbation Autoencoder
Authors: Inecik Kemal , Uhlmann Andreas , Lotfollahi Mohammad , Theis Fabian 
Published: July 2022

AbstractSingle-cell multimodal profiling provides a high-resolution view of cellular information. Recently, multimodal profiling approaches have been coupled with CRISPR technologies to perform pooled screens of single or combinatorial perturbations. This opens the possibility of exploring the massive space of combinatorial perturbations and their regulatory effects computationally from the extrapolation of a few experimentally feasible combinations. Here, we proposeMultiCPA, an end-to-end generative architecture to predict multimodal perturbation response at single cell level. Two mixing strategies to integrate multiple modalities are introduced and compared with existing methods. MultiCPA was also shown to accurately predict unseen combinatorial perturbation responses for multiple modalities. The code to reproduce the results is available onGitHub,theislab/multicpa.
Multiomics analyses reveal the central role of nucleolus and nucleoid machinery during heat stress acclimation in Pinus radiata
Authors: Escandón Mónica , Valledor Luis , Lamelas Laura , Álvarez Jóse M , Cañal María Jesús , Meijón Mónica 
Published: July 2022

AbstractClimate warming is causing quick changes in mean annual temperature and more severe drought period. These are major contributors of forest dieback, which is becoming more frequent and widespread, particularly in warm and drought-prone regions. Despite being a hot topic in non-woody plant sciences, the information about how heatwaves impact in tree molecular biology is still scarce. In this work we investigated how the transcriptome of Pinus radiata changes during initial stress response and stress acclimation. To this end, and considering this species is non sequenced, we generated a deep dataset employing Illumina technology. This approach allowed us to reconstruct 77335 contigs which were annotated following gene ontology, and to define 12164 and 13590 transcripts as down- and upregulated, respectively, across the three sampled experimental points. Enrichment analysis allowed to distinguish 9 down-regulated pathways, the most of them related to the reduction of apoplast, and water transport. While 22 were upregulated, which followed two different trends those pathways that peaks at short-term (acute response) from those which accumulated long-term (acclimation response) being most of them related to heat shock response, redox machinery and RNA processing. Additionally, the combination of transcriptome data with other available omics layers, allowed an exceptional understanding of the mechanisms behind heat stress response, involving complex interrelated processes from molecular to physiological level. Nucleolus and nucleoid activities seem to be a central core in acclimating process, producing specific RNA isoforms and other essential elements for anterograde-retrograde stress signaling as NAC proteins, Helicase RVB, RZ1 RNA chaperone, or ribosomal RPS4. These mechanisms are connected by elements already known in heat stress-response (redox, heat shock proteins or ABA-related). But also, novel candidates, as photosynthetic pigments, shikimate, or proline centric proteases activities, have been identified effectively networking biochemical responses to its potential regulatory element. This work provides a first deep overview about what molecular mechanisms underlying heat stress response and acclimation in pines, supporting the development of new breeding strategies to face the challenges that the climate change will impose to forests.
Testing Human Anxiety Associations of Genes Previously Implicated by Mouse Anxiety Models
Authors: Brasher Maizy S. , Mize Travis J. , Thomas Aimee L. , Hoeffer Charles A. , Ehringer Marissa A. , Evans Luke M. 
Published: July 2022

AbstractAnxiety disorders are common and can be debilitating, with effective treatments remaining hampered by an incomplete understanding of the underlying genetic etiology. Improvements have been made in understanding the genetic influences on mouse behavioral models of anxiety, yet it is unclear the extent to which genes identified in these experimental systems contribute to genetic variation in human anxiety phenotypes. Leveraging new and existing large-scale human genome-wide association studies, we tested whether sets of genes previously identified in mouse anxiety-like behavior studies contribute to a range of human anxiety disorders. When tested as individual genes, thirteen mouse-identified genes were associated with human anxiety phenotypes, suggesting an overlap of individual genes contributing to both mouse models of anxiety-like behaviors and human anxiety traits. When genes were tested as sets, we did identify fourteen significant associations between mouse gene sets and human anxiety, but the majority of gene sets showed no significant association with human anxiety phenotypes. These few significant associations indicate a need to identify and develop more translatable mouse models by identifying sets of genes that ‘match’ between model systems and specific human phenotypes of interest. We suggest that continuing to develop improved behavioral paradigms and finer-scale experimental data, for instance from individual neuronal subtypes or cell-type-specific expression data, is likely to improve our understanding of the genetic etiology and underlying functional changes in anxiety disorders.
Potential Energy Weighted Reactive Flux and Total Rate of Change of Potential Energy: Theory and Illustrative Applications
Authors: Li Wenjin 
Published: July 2022

AbstractReactive flux can be largely non-zero in a nonequilibrium ensemble of trajectories and provide insightful information for reactive transitions from the reactant state to the product state. Based on the reactive flux, a theoretical framework is proposed here for two quantities, the potential energy weighted reactive flux and the total rate of change of potential energy, which are useful for the identification of mechanism from a nonequilibrium ensemble. From such quantities, two multidimensional free energy analogues can be derived in the subspace of collective variables and they are equivalent in the regions where the reactive flux is divergence-free. These free energy analogues are assumed to be closely related to the free energy in the subspace of collective variables and they are reduced in the one-dimensional case to be the ensemble average of the potential energy weighted with reactive flux intensity, which was proposed recently and could be decomposed into energy components at the per-coordinate level. In the subspace of collective variables, the decomposition of the multidimensional free energy analogues at the per-coordinate level is theoretically possible and is numerically difficult to be calculated. Interestingly, the total rate of change of potential energy is able to identify the location of the transition state ensemble or the stochastic separatrix, in addition to the locations of the reactant and product states. The total rate of change of potential energy can be decomposed at the per-coordinate level and its components can quantify the contribution of a coordinate to the reactive transition in the subspace of collective variables. We then illustrated the main insights and objects that can be provided by the approach in the application to the alanine peptide in vacuum in various nonequilibrium ensembles of short trajectories and the results from these ensembles were found to be consistent.
Partial protection from fluctuating selection leads to evolution toward wider population size fluctuation and a novel mechanism of balancing selection
Authors: Kim Yuseob 
Published: July 2022

AbstractClassical theory predicted that natural selection favors a variant causing smaller fluctuation of population density. It is also known that if population is partially protected from fluctuating selection, as in the case of seed bank, the variance of fitness is further reduced and therefore the reproductive success of population is ensured. This study, exploring a mathematical model for coupled demographic and evolutionary dynamics, finds that such a ‘refuge’ from fluctuating selection even causes positive selection for a variant increasing the amplitude of population size fluctuation under weak or moderate regulation of population density. Under strong density regulation and constant carrying capacity, long-term maintenance of polymorphism known as the storage effect emerges. However, if the carrying capacity is changing either cyclically or randomly and the density regulation is strong, variants whose fitness fluctuates in phase with population size are positively selected to either fixation or oscillation at intermediate frequencies. The latter dynamics, arising when fitness fluctuates as expected under a simple life-history trade-off, is a novel form of balancing selection. These results highlight the importance of allowing in models the joint demographic and population genetic changes, the failure of which prevents the discovery of important and novel eco-evolutionary dynamics.
Bioelectronic microfluidic wound healing
Authors: Shaner Sebastian , Savelyeva Anna , Kvartuh Anja , Jedrusik Nicole , Matter Lukas , Leal José , Asplund Maria 
Published: July 2022

ABSTRACTThis work delves into the impact of direct current (DC) stimulation on both healthy and diabetic in vitro wound healing models of keratinocytes, the most prevalent cell type of the skin. The augmentation of non-metal electrode materials and prudent microfluidic design allowed for a platform to study the effects of different sustained (12 hours DC) electric field configurations on wound closure dynamics. We found that electric guidance cues (≃ 200mVmm−1) enhance wound closure rate by nearly 3X for both healthy and diabetic-like keratinocyte sheets, compared to their respective controls. The motility-inhibited keratinocytes regained wound closure rates with stimulation (increase from 1.0 to 2.8% hr−1) comparable to healthy non-stimulated keratinocyte collectives (3.5% hr−1). Our results bring hope that electrical stimulation is a viable pathway to accelerate wound repair.
Two-point optical manipulation reveals mechanosensitive remodeling of cell-cell contacts in vivo
Authors: Nishizawa Kenji , Lin Shao-Zhen , Chardès Claire , Rupprecht Jean-François , Lenne Pierre-François 
Published: July 2022

AbstractBiological tissues acquire reproducible shapes during development through dynamic cell behaviors. These events involve the remodeling of cell contacts driven by active cytoskeletal contractile forces. However how cell-cell contacts remodel remains poorly understood because of lack of tools to directly apply forces at cell-cell contacts to produce their remodeling. Here we develop a dual-optical trap manipulation method to impose different force patterns on cell-cell contacts in the early epithelium of the Drosophila embryo. Through different push and pull manipulations at the edges of junctions, the technique allows us to produce junction extension and junction shrinkage. We use these observations to constrain and specify vertex-based models of tissue mechanics, incorporating negative and positive mechanosensitive feedback depending on the type of remodeling. We show that Myosin-II activity responds to junction strain rate and facilitates full junction shrinkage. Altogether our work provides insight into how stress produces efficient deformation of cell-cell contacts in vivo and identifies unanticipated mechanosensitive features of their remodeling.Significance statementThe highly organized tissues and organs that form our body emerge from internal dynamic activities at the cellular level. Among such activities, cell shape changes and cell rearrangement, cell extrusion and cell division sculpt epithelial tissues into elongated sheets, tubes and spherical cavities. Remodeling of cell-cell contacts, powered by actomyosin contractility, is key to all these transformations. Although much is known about the molecular machinery and biochemical signals that regulate remodeling of cell contacts, there is a lack of approaches to directly probe the mechanics of cell contacts and therefore assess their ability to resist or deform in response to mechanical loads. We developed an experimental technique to manipulate and exert contractile and extensile forces to cell-cell junctions. Our results lead to a specific physical model of junctional mechanics, with implications in the modeling of collective cell behavior in epithelial tissues.
Designing Single Cell RNA-Sequencing Experiments for Learning Latent Representations
Authors: Treppner Martin , Haug Stefan , Köttgen Anna , Binder Harald 
Published: July 2022

AbstractTo investigate the complexity arising from single-cell RNA-sequencing (scRNA-seq) data, researchers increasingly resort to deep generative models, specifically variational autoencoders (VAEs), which are trained by variational inference techniques. Similar to other dimension reduction approaches, this allows encoding the inherent biological signals of gene expression data, such as pathways or gene programs, into lower-dimensional latent representations. However, the number of cells necessary to adequately uncover such latent representations is often unknown. Therefore, we propose a single-cell variational inference approach for designing experiments (scVIDE) to determine statistical power for detecting cell group structure in a lower-dimensional representation. The approach is based on a test statistic that quantifies the contribution of every single cell to the latent representation. Using a smaller scRNA-seq data set as a starting point, we generate synthetic data sets of various sizes from a fitted VAE. Employing a permutation technique for obtaining a null distribution of the test statistic, we subsequently determine the statistical power for various numbers of cells, thus guiding experimental design. We illustrate with several data sets from various sequencing protocols how researchers can use scVIDE to determine the statistical power for cell group detection within their own scRNA-seq studies. We also consider the setting of transcriptomics studies with large numbers of cells, where scVIDE can be used to determine the statistical power for sub-clustering. For this purpose, we use data from the human KPMP Kidney Cell Atlas and evaluate the power for sub-clustering of the epithelial cells contained therein. To make our approach readily accessible, we provide a comprehensive Jupyter notebook at https://github.com/MTreppner/scVIDE.jl that researchers can use to design their own experiments based on scVIDE.
Differential ability of three bee species to move genes via pollen
Authors: Fragoso Fabiana P. , Brunet Johanne 
Published: July 2022

AbstractSince the release of genetically engineered (GE) crops, there has been increased concern about the introduction of GE genes into non-GE fields of a crop and their spread to feral or wild cross-compatible relatives. More recently, attention has been given to the differential impact of distinct pollinators on gene flow, with the goal of developing isolation distances associated with specific managed pollinators. To examine the differential impact of bee species on gene movement, we quantified the relationship between the probability of getting a GE seed in a pod, and the order in which a flower was visited, or the cumulative distance travelled by a bee in a foraging bout. We refer to these relationships as ‘seed curves’ and compare these seeds curves among three bee species. The experiments used Medicago sativa L. plants carrying three copies of the glyphosate resistance (GR) allele as pollen donors, such that each pollen grain carried the GR allele, and conventional plants as pollen recipients. Different foraging metrics, including the number of GR seeds produced over a foraging bout, were also quantified and contrasted among bee species. Leafcutting bees produced the lowest number of GR genes in a foraging bout, and moved them the shortest distances, bumble bees the longest. Values for honey bees were intermediate. Seed curves correlated with field-based gene flow estimates. Thus, differential seed curves of bee species, reflecting within foraging bout patterns, translated into distinct abilities of bee species to move genes at a landscape level. Differences in seed curves reflected differences in foraging behavior among bee species, and helped explain their differential impact on gene flow and the spread of GE genes in insect-pollinated crops.
Phenotypic screening using waveform analysis of calcium dynamics in primary cortical cultures
Authors: Sakaguchi Richi , Nakamura Saki , Iha Hiroyuki , Tanaka Masaki 
Published: July 2022

AbstractAt present, in vitro phenotypic screening methods are widely used for drug discovery. In the field of epilepsy research, measurements of neuronal activity have been utilized for predicting efficacy of anti-epileptic drugs. Fluorescence measurements of calcium oscillations in neurons are commonly used for measurement of neuronal activities, and some anti-epileptic drugs have been evaluated using this assay technique. However, changes in waveforms were not quantified in previous reports. Here, we have developed a high-throughput screening system containing a new analysis method for quantifying waveforms, and our method has successfully enabled simultaneous measurement of calcium oscillations in a 96-well plate. Features of waveforms were extracted automatically and allowed the characterization of some anti-epileptic drugs using principal component analysis. Moreover, we have shown that trajectories in accordance with the concentrations of compounds in principal component analysis plots were unique to the mechanism of anti-epileptic drugs. We believe that an approach that focuses on the features of calcium oscillations will lead to better understanding of the characteristics of existing anti-epileptic drugs and allow prediction of the mechanism of action of novel drug candidates.
A single residue within the MCR-1 protein confers anticipatory resilience
Authors: Frantz Renate , Gwozdzinski Konrad , Gisch Nicolas , Doijad Swapnil Prakash , Hudel Martina , Wille Maria , Mraheil Mobarak Abu , Schwudke Dominik , Imirzalioglu Can , Falgenhauer Linda , Ehrmann Michael , Chakraborty Trinad 
Published: July 2022

AbstractThe envelope stress response (ESR) of Gram-negative enteric bacteria senses fluctuations in nutrient availability and environmental changes to avert damage and promote survival. It has a protective role towards antimicrobials but direct interactions between ESR components and antibiotic resistance genes have not been demonstrated. Here we report specific interactions between the two-component conjugative pilus expression (Cpx)RA signal transduction system and the recently described mobile colistin resistance (MCR-1) protein. Purified MCR-1 is specifically cleaved by the serine endoprotease DegP within a structurally conserved periplasmic bridging domain. Cleavage-site mutations in MCR-1 render derivatives either protease-resistant or degradation-susceptible with widely differing consequences for colistin resistance. Transfer of the degradation-susceptible mutant to strains that lack either DegP or its regulator CpxRA restores expression and colistin resistance. MCR-1 production in Escherichia coli induces a Cpx-dependent ESR and imposes growth restriction in strains lacking either DegP or CpxRA, effects that are reversed by transactive expression of DegP. MCR-1 production impairs bacterial motility indicating dissipation of cytoplasmic transmembrane potential. Indeed, growth in media with low pH dramatically increases both MCR-1-dependent phosphoethanolamine (PEA) modification of lipid A as well as colistin-resistance activity. In vitro transferase- and lipid A reconstitution-assays demonstrate that MCR-1 is highly active at acidic pH. Acquiring MCR-1 also renders strains more resistant to antimicrobial peptides. Thus, a conserved motif within MCR-1 induces components of the ESR to confer resilience to stimuili commonly encountered in the environment such as to changes in pH and towards antimicrobial peptides. Excipient allosteric activation of the DegP protease specifically inhibits growth of isolates carrying mcr-1 plasmids indicating that a targeted strategy can lead to the elimination of transferable colistin resistance in Gram-negative bacteria.