bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural heterogeneity of cellular K5/K14 filaments as revealed by cryo-electron microscopy
Authors: Weber Miriam S. , Eibauer Matthias , Sivagurunathan Suganya , Magin Thomas M. , Goldman Robert D. , Medalia Ohad 
Published: May 2021

AbstractKeratin intermediate filaments are an essential and major component of the cytoskeleton in epithelial cells. They form a stable yet dynamic filamentous network extending from the nucleus to the cell periphery. Keratin filaments provide cellular resistance to mechanical stresses, ensure cell and tissue integrity in addition to regulatory functions. Mutations in keratin genes are related to a variety of epithelial tissue diseases that mostly affect skin and hair. Despite their importance, the molecular structure of keratin filaments remains largely unknown. In this study, we analyzed the structure of keratin 5/keratin 14 filaments within ghost keratinocytes by cryo-electron microscopy and cryo-electron tomography. By averaging a large number of keratin segments, we have gained insights into the helical architecture of the filaments. Interestingly, two-dimensional classification revealed profound variations in the diameter of keratin filaments and their subunit organization. Reconstitution of filaments of substantial length from keratin segments uncovered a high degree of internal heterogeneity along single filaments, which can contain regions of helical symmetry, regions with less symmetry and regions with significant diameter fluctuations. Cross section views of filaments revealed that keratins form hollow cylinders consisting of multiple protofilaments, with an electron dense core located in the center of the filament. These findings shed light on the complex architecture of keratin filaments, which demonstrate a remarkable degree of heterogeneity, suggesting that they are highly flexible, dynamic cytoskeletal structures.
An Explainable Deep Learning Approach for Multimodal Electrophysiology Classification
Authors: Ellis Charles A. , Carbajal Darwin A. , Zhang Rongen , Miller Robyn L. , Calhoun Vince D. , Wang May D. 
Published: May 2021

AbstractIn recent years, more biomedical studies have begun to use multimodal data to improve model performance. As such, there is a need for improved multimodal explainability methods. Many studies involving multimodal explainability have used ablation approaches. Ablation requires the modification of input data, which may create out-of-distribution samples and may not always offer a correct explanation. We propose using an alternative gradient-based feature attribution approach, called layer-wise relevance propagation (LRP), to help explain multimodal models. To demonstrate the feasibility of the approach, we selected automated sleep stage classification as our use-case and trained a 1-D convolutional neural network (CNN) with electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG) data. We applied LRP to explain the relative importance of each modality to the classification of different sleep stages. Our results showed that across all samples, EEG was most important, followed by EOG, and EMG. For individual sleep stages, EEG and EOG had higher relevance for classifying awake and non-rapid eye movement 1 (NREM1). EOG was most important for classifying REM, and EEG was most relevant for classifying NREM2-NREM3. Also, LRP gave consistent levels of importance to each modality for correctly classified samples across folds and inconsistent levels of importance for incorrectly classified samples. Our results demonstrate the additional insight that gradient-based approaches can provide relative to ablation methods and highlight their feasibility for explaining multimodal electrophysiology classifiers.
Quantitative proteomics identifies the universally conserved ATPase Ola1p as a positive regulator of heat shock response in Saccharomyces cerevisiae
Authors: Dannenmaier Stefan , Altamirano Christine Desroches , Schüler Lisa , Zhang Ying , Hummel Johannes , Oeljeklaus Silke , Koch Hans-Georg , Rospert Sabine , Alberti Simon , Warscheid Bettina 
Published: May 2021

AbstractThe universally conserved P-loop ATPase Ola1 is implicated in various cellular stress response pathways, as well as in cancer and tumor progression. However, Ola1p functions are divergent between species and the involved mechanisms are only poorly understood. Here, we studied the role of Ola1p in the heat shock response of the yeast Saccharomyces cerevisiae using a combination of quantitative and pulse labeling-based proteomics approaches, in vitro studies and cell-based assays. Our data show that when heat stress is applied to cells lacking Ola1p, the expression of stress-protective proteins is enhanced. During heat stress Ola1p associates with detergent-resistant protein aggregates and rapidly forms assemblies that localize to stress granules. The assembly of Ola1p was also observed in vitro using purified protein and conditions, which resembled those in living cells. We show that loss of Ola1p results in increased protein ubiquitination of detergent-insoluble aggregates recovered from heat-shocked cells. When subsequently cells lacking Ola1p were relieved from heat stress, reinitiation of translation was delayed, whereas, at the same time, de novo synthesis of central factors required for protein refolding and the clearance of aggregates was enhanced when compared to wildtype cells. The combined data suggest that upon acute heat stress, Ola1p is involved in the stabilization of misfolded proteins, which become sequestered in cytoplasmic stress granules. This function of Ola1p enables cells to resume translation in a timely manner as soon as heat stress is relieved.
CsoDIAq Software for Direct Infusion Shotgun Proteome Analysis (DISPA)
Authors: Cranney Caleb W. , Meyer Jesse G. 
Published: May 2021

ABSTRACTNew mass spectrometry data collection methods require new computational tools. Direct Infusion Shotgun Proteome Analysis (DISPA) is a new paradigm for expedited mass spectrometry-based proteomics, but the original data analysis workflow was onerous. Here we introduce CsoDIAq, a user-friendly software package for the identification and quantification of peptides and proteins from DISPA data. In addition to establishing a complete and automated analysis workflow with a graphical user interface, CsoDIAq introduces algorithmic concepts to improve peptide identification speed and sensitivity. These include spectra pooling to reduce search time complexity, and a new spectrum-spectrum match score called match count and cosine (MaCC), which improves target discrimination in a target-decoy analysis. We further show that reanalysis after fragment mass tolerance correction increased the number of peptide identifications. Finally, we adapt CsoDIAq to standard LC-MS DIA, and show that it outperforms other spectrum-spectrum matching software.
Universal amyloidogenicity of patient-derived immunoglobulin light chains
Authors: Sternke-Hoffmann Rebecca , Pauly Thomas , Norrild Rasmus K. , Hansen Jan , Dupré Mathieu , Tucholski Florian , Duchateau Magalie , Rey Martial , Metzger Sabine , Boquoi Amelie , Platten Florian , Egelhaaf Stefan U. , Chamot-Rooke Julia , Fenk Roland , Nagel-Steger Luitgard , Haas Rainer , Buell Alexander K. 
Published: May 2021

ABSTRACTThe deposition of immunoglobulin light chains (IgLCs) in the form of amorphous aggregates or amyloid fibrils in different tissues of patients can lead to severe and potentially fatal organ damage, requiring transplantation in some cases. There has been great interest in recent years to elucidate the origin of the very differentin vivosolubilities of IgLCs, as well as the molecular determinants that drive either the formation of ordered amyloid fibrils or disordered amorphous aggregates. It is commonly thought that the reason of this differential aggregation behaviour is to be found in the amino acid sequences of the respective IgLCs, i.e. that some sequences display higher intrinsic tendencies to form amyloid fibrils. Here we perform in depth Thermodynamic and Aggregation Fingerprinting (ThAgg-Fip) of 9 multiple myeloma patient-derived IgLCs, the amino acid sequences of all of which we have solved byde novoprotein sequencing with mass spectrometry. The latter technique was also used for one IgLc from a patient with AL amyloidosis. We find that all samples also contain proteases that fragment the proteins under physiologically relevant mildly acidic pH conditions, leading to amyloid fibril formation in all cases. Our results suggest that while every pathogenic IgLC has a unique ThAgg fingerprint, all sequences have comparable amyloidogenic potential. Therefore, extrinsic factors, in particular presence of, and susceptibility to, proteolytic cleavage is likely to be a strong determinant ofin vivoaggregation behaviour. The important conclusion, which is corroborated by systematic analysis of our sequences, as well as many sequences of IgLCs from amyloidosis patients reported in the literature, challenges the current paradigm of the link between sequence and amyloid fibril formation of pathogenic light chains.
A catalog of transcription start sites across 115 human tissue and cell types
Authors: Moore Jill E. , Zhang Xiao-Ou , Elhajjajy Shaimae I. , Fan Kaili , Reese Fairlie , Mortazavi Ali , Weng Zhiping 
Published: May 2021

AbstractAccurate transcription start site (TSS) annotations are essential for understanding transcriptional regulation and its role in human disease. Gene collections such as GENCODE contain annotations for tens of thousands of TSSs, but not all of these annotations are experimentally validated nor do they contain information on cell type-specific usage. Therefore, we sought to generate a collection of experimentally validated TSSs by integrating RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression (RAMPAGE) data from 115 cell and tissue types, which resulted in a collection of approximately 50 thousand representative RAMPAGE peaks. These peaks were primarily proximal to GENCODE-annotated TSSs and were concordant with other transcription assays. Because RAMPAGE uses paired-end reads, we were then able to connect peaks to transcripts by analyzing the genomic positions of the 3’ ends of read mates. Using this paired-end information, we classified the vast majority (37 thousand) of our RAMPAGE peaks as verified TSSs, updating TSS annotations for 20% of GENCODE genes. We also found that these updated TSS annotations were supported by epigenomic and other transcriptomic datasets. To demonstrate the utility of this RAMPAGE rPeak collection, we intersected it with the NHGRI/EBI GWAS catalog and identified new candidate GWAS genes. Overall, our work demonstrates the importance of integrating experimental data to further refine TSS annotations and provides a valuable resource for the biological community.
Inferring kinetic parameters of oscillatory gene regulation from single cell time series data
Authors: Burton Joshua , Manning Cerys S. , Rattray Magnus , Papalopulu Nancy , Kursawe Jochen 
Published: May 2021

AbstractGene expression dynamics, such as stochastic oscillations and aperiodic fluctuations, have been associated with cell fate changes in multiple contexts, including development and cancer. Single cell live imaging of protein expression with endogenous reporters is widely used to observe such gene expression dynamics. However, the experimental investigation of regulatory mechanisms underlying the observed dynamics is challenging, since these mechanisms include complex interactions of multiple processes, including transcription, translation, and protein degradation. Here, we present a Bayesian method to infer kinetic parameters of oscillatory gene expression regulation using an auto-negative feedback motif with delay. Specifically, we use a delay-adapted nonlinear Kalman filter within a Metropolis-adjusted Langevin algorithm to identify posterior probability distributions. Our method can be applied to time series data on gene expression from single cells and is able to infer multiple parameters simultaneously. We apply it to published data on murine neural progenitor cells and show that it outperforms alternative methods. We further analyse how parameter uncertainty depends on the duration and time resolution of an imaging experiment, to make experimental design recommendations. This work demonstrates the utility of parameter inference on time course data from single cells and enables new studies on cell fate changes and population heterogeneity.
HASTER is a transcriptional stabilizer of HNF1A
Authors: Beucher Anthony , Miguel-Escalada Irene , Balboa Diego , De Vas Matías G. , Maestro Miguel Angel , Garcia-Hurtado Javier , Bernal Aina , Gonzalez-Franco Roser , Vargiu Pierfrancesco , Heyn Holger , Ravassard Philippe , Ortega Sagrario , Ferrer Jorge 
Published: May 2021

AbstractThe biological purpose and disease relevance of long noncoding RNAs (lncRNAs) is poorly understood. We examined HASTER, a lncRNA antisense to HNF1A. Haploinsufficient mutations in HNF1A, encoding a homeodomain transcription factor, cause diabetes mellitus. Using mouse and human models, we show that HASTER maintains HNF1A at cell-specific physiological concentrations through positive and negative feedback loops. Haster mutant pancreatic β cells thus showed variegated HNF1A overexpression or silencing, causing insulin-deficiency and diabetes. We demonstrate that the HASTER promoter acts in cis to prevent HNF1A overexpression and silencing, and link HASTER-dependent inhibition to local remodelling of 3D chromatin architecture. We further show that HASTER negative feedback ensures that HNF1A creates open chromatin at appropriate cell-specific genome regions. Our studies expose a cis-regulatory element that is unlike enhancers or silencers, and instead stabilizes expression levels of a pioneer transcription factor. They also show that disruption of a mammalian lncRNA can cause diabetes mellitus.
Single-Cell Stochastic Modeling of the Action of Antimicrobial Peptides on Bacteria
Authors: Teimouri Hamid , Nguyen Thao N. , Kolomeisky Anatoly B. 
Published: May 2021

AbstractAntimicrobial peptides (AMPs) produced by multi-cellular organisms as their immune system’s defense against microbes are actively considered as natural alternatives to conventional antibiotics. Although a substantial progress has been achieved in studying the AMPs, the microscopic mechanisms of their functioning remain not well understood. Here, we develop a new theoretical framework to investigate how the AMPs are able to efficiently neutralize the bacteria. In our minimal theoretical model, the most relevant processes, AMPs entering into and the following inhibition of the single bacterial cell, are described stochastically. Using complementary master equations approaches, all relevant features of bacteria clearance dynamics by AMPs, such as the probability of inhibition and the mean times before the clearance, are explicitly evaluated. It is found that both processes, entering and inhibition, are equally important for the efficient functioning of AMPs. Our theoretical method naturally explains a wide spectrum of efficiencies of existing AMPs and their heterogeneity at the single-cell level. Theoretical calculations are also consistent with existing single-cell measurements. Thus, the presented theoretical approach clarifies some microscopic aspects of the action of AMPs on bacteria.
Direct Reconstruction of Gene Regulatory Networks underlying Cellular state Transitions without Pseudo-time Inference
Authors: Wan Ruosi , Zhang Yuhao , Peng Yongli , Tian Feng , Gao Ge , Tang Fuchou , Xie Xiaoliang S. , Jia Jinzhu , Ge Hao 
Published: May 2021

AbstractNowadays the advanced technology for single-cell transcriptional profiling enables people to routinely generate thousands of single-cell expression data, in which data from different cell states or time points are derived from different samples. Without transferring such time-stamped cross-sectional data into pseudo-time series, we propose COSLIR (COvariance restricted Sparse LInear Regression) for directly reconstructing the gene regulatory networks (GRN) that drives the cell-state transition. The differential gene expression between adjacent cell states is modeled as a linear combination of gene expressions in the previous cell state, and the GRN is reconstructed through solving an optimization problem only based on the first and second moments of the sample distributions. We apply the bootstrap strategy as well as the clip threshold method to increase the precision and stability of the estimation. Simulations indicate the perfect accuracy of COSLIR in the oracle case as well as its good performance and stability in the sample case. We apply COSLIR separately to two cell lineages in a published single-cell qPCR dataset during mouse early embryo development. Nearly half of the inferred gene-gene interactions have already been experimentally reported and some of them were even discovered during the past decade after the dataset was published, indicating the power of COSLIR. Furthermore, COSLIR is also evaluated on several single-cell RNA-seq datasets, and the performance is comparable with other methods relying on the pseudo-time reconstruction.
SMCHD1 has separable roles in chromatin architecture and gene silencing that could be targeted in disease
Authors: Tapia del Fierro Andres , den Hamer Bianca , Jansz Natasha , Chen Kelan , Beck Tamara , Vanyai Hannah , Benetti Natalia , Gurzau Alexandra D , Daxinger Lucia , Xue Shifeng , Ly Thanh Thao Nguyen , Wanigasuriya Iromi , Breslin Kelsey , Oey Harald , Krom Yvonne , van der Hoorn Dinja , Bouwman Linde F , Ritchie Matthew E. , Reversade Bruno , Prin Fabrice , Mohun Timothy , van der Maarel Silvère M , McGlinn Edwina , Murphy James M , Keniry Andrew , de Greef Jessica C , Blewitt Marnie E 
Published: May 2021

AbstractThe interplay between 3D chromatin architecture and gene silencing is incompletely understood. Here, we report a novel point mutation in the non-canonical SMC protein SMCHD1 that enhances its silencing capacity at endogenous developmental targets and at the facioscapulohumeral muscular dystrophy associated macro-array, D4Z4. Heightened SMCHD1 silencing perturbs developmental Hox gene activation, causing a homeotic transformation in mice. Paradoxically, the mutant SMCHD1 appears to enhance insulation against another epigenetic regulator complex, PRC2, while depleting long range chromatin interactions akin to what is observed in the absence of SMCHD1. These data suggest that SMCHD1’s role in long range chromatin interactions is not directly linked to gene silencing or insulating the chromatin, refining the model for how the different levels of SMCHD1-mediated chromatin regulation interact to bring about gene silencing in normal development and disease.
Efficacy of the NVX-CoV2373 Covid-19 Vaccine Against the B.1.1.7 Variant
Authors: Heath Paul T. , Galiza Eva P. , Baxter David Neil , Boffito Marta , Browne Duncan , Burns Fiona , Chadwick David R. , Clark Rebecca , Cosgrove Catherine , Galloway James , Goodman Anna L. , Heer Amardeep , Higham Andrew , Iyengar Shalini , Jamal Arham , Jeanes Christopher , Kalra Philip A. , Kyriakidou Christina , McAuley Daniel F. , Meyrick Agnieszka , Minassian Angela M. , Minton Jane , Moore Patrick , Munsoor Imrozia , Nicholls Helen , Osanlou Orod , Packham Jonathan , Pretswell Carol H. , Francisco Ramos Alberto San , Saralaya Dinesh , Sheridan Ray P. , Smith Richard , Soiza Roy L. , Swift Pauline A. , Thomson Emma C. , Turner Jeremy , Viljoen Marianne Elizabeth , Albert Gary , Cho Iksung , Dubovsky Filip , Glenn Greg , Rivers Joy , Robertson Andreana , Smith Kathy , Toback Seth 
Published: May 2021

ABSTRACTBackgroundCovid-19 vaccines are urgently needed, especially against emerging variants. NVX-CoV2373 is a recombinant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 rS) nanoparticle vaccine containing trimeric full-length SARS-CoV-2 spike glycoprotein and Matrix-M adjuvant.MethodsA phase 3, randomized, observer-blinded, placebo-controlled trial was conducted in adults 18-84 years old who received two intramuscular 5-µg doses, 21 days apart, of NVX-CoV2373 or placebo (1:1) across 33 sites in the United Kingdom. The primary efficacy endpoint was virologically confirmed symptomatic Covid-19 with onset 7 days after second vaccination in serologically negative participants.ResultsA total of 15,187 participants were randomized, of whom 7569 received NVX-CoV2373 and 7570 received placebo; 27.2% were 65 years or older, 44.7% had comorbidities and 4.2% had baseline serological evidence of SARS-CoV-2. There were 10 cases of Covid-19 among NVX-CoV2373 recipients and 96 cases among placebo recipients, with symptom onset at least 7 days after second vaccination; NVX-CoV2373 was 89.7% (95% confidence interval, 80.2 to 94.6) effective in preventing Covid-19, with no hospitalizations or deaths reported. There were five cases of severe Covid-19, all in the placebo group. Post hoc analysis revealed efficacies of 96.4% (73.8 to 99.5) and 86.3% (71.3 to 93.5) against the prototype strain and B.1.1.7 variant, respectively. Vaccine efficacy was similar across subgroups, including participants with comorbidities and those ≥65 years old. Reactogenicity was generally mild and transient. The incidence of serious adverse events was low and similar in the two groups.ConclusionA two-dose regimen of NVX-CoV2373 conferred 89.7% protection against a blend of prototype and variant Covid-19, demonstrated high efficacy against the B.1.1.7 variant, and had a reassuring safety profile.(Funded by Novavax, Inc. EudraCT number, 2020-004123-16).
Impact of the COVID-19 pandemic on the mental health and wellbeing of parents with young children: a qualitative interview study
Authors: Dawes Jo , May Tom , McKinlay Alison , Fancourt Daisy , Burton Alexandra 
Published: May 2021

AbstractBackgroundParents have faced unique challenges during the coronavirus disease 2019 (COVID-19) pandemic, including mobility constraints, isolation measures, working from home, and the closure of schools and childcare facilities. There is presently a lack of in-depth qualitative research exploring how these changes have affected parents’ mental health and wellbeing.MethodsSemi-structured qualitative interviews with 29 parents of young children. Interviews were analysed using reflexive thematic analysis.ResultsWe identified five superordinate themes affecting participant mental health and wellbeing: 1) navigation of multiple responsibilities and change inside the home; 2) disruption to home life; 3) changes to usual support networks; 4) changes in personal relationships; and 5) use of coping strategies. Participants described stress and exhaustion from navigating multiple pressures and conflicting responsibilities with home, schooling, and work, without their usual support networks and in the context of disrupted routines. Family roles and relationships were sometimes tested, however, many parents identified coping strategies that protected their wellbeing including access to outdoor space, spending time away from family, and avoiding conflict and pandemic-related media coverage.ConclusionsEmployers must be cognisant of the challenges that the pandemic has placed on parents, particularly women and lone parents. Flexible working arrangements and support might therefore relieve stress and increase productivity. Coping strategies identified by parents in this study could be harnessed and encouraged by employers and policymakers to promote positive wellbeing during times of stress throughout the pandemic and beyond.