bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative evaluation of the transmissibility of SARS-CoV-2 variants of concern
Authors: Wang Liang , Didelot Xavier , Bi Yuhai , Gao George F 
Published: June 2021

AbstractSince the start of the SARS-CoV-2 pandemic in late 2019, several variants of concern (VOC) have been reported, such as B.1.1.7, B.1.351, P.1, and B.1.617.2. The exact reproduction number Rt for these VOCs is important to determine appropriate control measures. Here, we estimated the transmissibility for VOCs and lineages of SAR-CoV-2 based on genomic data and Bayesian inference under an epidemiological model to infer the reproduction number (Rt). We analyzed data for multiple VOCs from the same time period and countries, in order to compare their transmissibility while controlling for geographical and temporal factors. The lineage B had a significantly higher transmissibility than lineage A, and contributed to the global pandemic to a large extent. In addition, all VOCs had increased transmissibility when compared with other lineages in each country, indicating they are harder to control and present a high risk to public health. All countries should formulate specific prevention and control policies for these VOCs when they are detected to curve their potential for large-scale spread.
Truncated RNA-binding protein production by DUX4-induced systemic inhibition of nonsense-mediated RNA decay
Authors: Campbell Amy E. , Dyle Michael C. , Calviello Lorenzo , Matheny Tyler , Sudheendran Kavitha , Cortazar Michael A. , Forman Thomas , Fu Rui , Gillen Austin E. , Caruthers Marvin H. , Floor Stephen N. , Jagannathan Sujatha 
Published: June 2021

ABSTRACTNonsense-mediated RNA decay (NMD) is a surveillance mechanism that degrades both canonical and aberrant transcripts carrying premature translation termination codons. NMD is thought to have evolved to prevent the synthesis of toxic truncated proteins. However, whether global inhibition of NMD results in widespread production of truncated proteins is unknown. A human genetic disease, facioscapulohumeral muscular dystrophy (FSHD) features acute inhibition of NMD upon expression of the disease-causing transcription factor, DUX4. Here, using a cell-based model of FSHD, we show the production of hundreds of truncated proteins from physiological NMD targets. Using ribosome profiling, we map the precise C-terminal end of these aberrant truncated proteins and find that RNA-binding proteins are especially enriched for aberrant truncations. The stabilized NMD isoform of one RNA-binding protein, SRSF3, is robustly translated to produce a stable truncated protein, which can also be detected in FSHD patient-derived myotubes. Notably, ectopic expression of truncated SRSF3 alone confers toxicity and its downregulation is cytoprotective. Our results demonstrate the genome-scale impact of NMD inhibition. This widespread production of potentially deleterious truncated proteins has implications for FSHD biology as well as other genetic diseases where NMD is therapeutically modulated.
SenseNet, a tool for analysis of protein structure networks obtained from molecular dynamics simulations
Authors: Schneider Markus , Antes Iris 
Published: June 2021

AbstractComputational methods play a key role for investigating allosteric mechanisms in proteins, with the potential of generating valuable insights for innovative drug design. Here we present the SenseNet (“Structure ENSEmble NETworks”) framework for analysis of protein structure networks, which differs from established network models by focusing on interaction timelines obtained by molecular dynamics simulations. This approach is evaluated by predicting allosteric residues reported by NMR experiments in the PDZ2 domain of hPTP1e, a reference system for which previous computational predictions have shown considerable variance. We applied two models based on the mutual information between interaction timelines to estimate the conformational influence of each residue on its local environment. In terms of accuracy our prediction model is comparable to the top performing model published for this system, but by contrast benefits from its independence from NMR structures. Our results are complementary to experimental data and the consensus of previous predictions, demonstrating the potential of our new analysis tool SenseNet. Biochemical interpretation of our model suggests that allosteric residues in the PDZ2 domain form two distinct clusters of contiguous sidechain surfaces. SenseNet is provided as a plugin for the network analysis software Cytoscape, allowing for ease of future application and contributing to a system of compatible tools bridging the fields of system and structural biology.Author SummaryRegulation and signal transduction processes in proteins are often correlated to structural changes induced by ligand binding, which can lead to suppression or enhancement of protein function. A common method to investigate such changes are numerical simulations of protein dynamics. We developed the analysis software SenseNet for predicting how protein dynamics and function is affected by e.g. ligand binding events based on molecular dynamics simulations. Our model estimates which structural elements of the protein confer the most information about their local environment, reasoning that these elements are essential for signal propagation. Applying this method on the PDZ2 domain of the hPTP1e protein, we were able to accurately predict structure elements with known signaling roles as determined by previous experiments. Integrating these experimental data with the consensus of other computational models and our predictions, we find two separate pathways which may transmit information through the PDZ2 protein structure. In addition to deepening our insight into the behavior of this particular protein, these results demonstrate the usefulness of our methods for other systems, such as potential drug targets. To make this analysis available to a broad audience, we implemented it as a plugin for the popular network analysis software Cytoscape.
Lack of Host Reproductive Trade-offs Associated with Fecundity Compensation Response to Parasitic Castration
Authors: Davis Annabell A. , Vannatta J. Trevor , Gutierrez Stephanie O. , Minchella Dennis J. 
Published: June 2021

AbstractHost-parasite coevolution may result in life-history changes in hosts that can limit the detrimental effects of parasitism. Fecundity compensation is one such life-history response, occurring when hosts increase their current reproductive output to make up for expected losses in future reproduction due to parasitic infection. However, the potential trade-offs between quantity and quality of offspring produced during fecundity compensation are relatively unexplored. This study uses the trematode, Schistosoma mansoni, and its snail intermediate host, Biomphalaria glabrata, to better understand the impacts of this host life-history response. Measures of host reproductive output as well as offspring hatching success and survival were collected to assess the reproductive consequences of infection. Infected snails exhibited fecundity compensation (increase in the number of eggs laid compared to controls) and had a higher probability of laying any eggs at all. Infection status did not play a significant role in hatching or offspring survival to maturity. However, the age of the parental snail had a significant impact on hatching success, as offspring from older parents demonstrated a higher hatching success rate. Overall, the lack of an apparent trade-off between quantity and quality of offspring suggests that infected parental snails invest more resources towards reproduction in order to maintain the fitness of their offspring, possibly at the expense of their own longevity.
Systematic genome-scale identification of host factors for SARS-CoV-2 infection across models yields a core single gene dependency; ACE2
Authors: Chan Katherine , Farias Adrian Granda , Lee Hunsang , Guvenc Furkan , Mero Patricia , Aulakh Kamaldeep , Brown Kevin R. , Haider Shahan , Marcon Edyta , Braunschweig Ulrich , Yan Tong Amy Hin , Pu Shuye , Habsid Andrea , Christie-Holmes Natasha , Budylowski Patrick , Astori Audrey , Ghalami Ayoob , Mubareka Samira , Banerjee Arinjay , Mossman Karen L. , Greenblatt Jack , Gray-Owen Scott D. , Raught Brian , Blencowe Benjamin J. , Taipale Mikko , Moffat Jason 
Published: June 2021

SUMMARYSARS-CoV-2, depends on host cell components for replication, therefore the identification of virus-host dependencies offers an effective way to elucidate mechanisms involved in viral infection. Such host factors may be necessary for infection and replication of SARS-CoV-2 and, if druggable, presents an attractive strategy for anti-viral therapy. We performed genome wide CRISPR knockout screens in Vero E6 cells and 4 human cell lines including Calu-3, Caco-2, Hek293 and Huh7 to identify genetic regulators of SARS-CoV-2 infection. Our findings identified only ACE2, the cognate SARS-CoV-2 entry receptor, as a common host dependency factor across all cell lines, while all other host genes identified were cell line specific including known factors TMPRSS2 and CTSL. Several of the discovered host-dependency factors converged on pathways involved in cell signalling, lipid metabolism, immune pathways and chromatin modulation. Notably, chromatin modulator genes KMT2C and KDM6A in Calu-3 cells had the strongest impact in preventing SARS-CoV-2 infection when perturbed. Overall, the network of host factors that have been identified will be broadly applicable to understanding the impact of SARS-CoV-2 on human cells and facilitate the development of host-directed therapies.IN BRIEFSARS-CoV-2, depends on host cell components for infection and replication. Genome-wide CRISPR screens were performed in multiple human cell lines to elucidate common host dependencies required for SARS-CoV-2 infection. Only ACE2, the cognate SARS-CoV-2 entry receptor, was common amongst cell lines, while all other host genes identified were cell line specific, several of which converged on pathways involved in cell signalling, lipid metabolism, immune pathways, and chromatin modulation. Overall, a network of host factors was identified that will be broadly applicable to understanding the impact of SARS-CoV-2 on human cells and facilitate productive targeting of host genes and pathways.HIGHLIGHTS- Genome-wide CRISPR screens for SARS-CoV-2 in multiple human cell lines- Identification of wide-ranging cell-type dependent genetic dependencies for SARS-CoV-2 infection- ACE2 is the only common host factor identified across different cell types
Deciphering the landscape of phosphorylated HLA-II ligands
Authors: Solleder Marthe , Racle Julien , Guillaume Philippe , Coukos George , Bassani-Sternberg Michal , Gfeller David 
Published: June 2021

AbstractCD4+ T-cell activation in infectious diseases and cancer is governed by the recognition of peptides presented on class II human leukocyte antigen (HLA-II) molecules. Therefore, HLA-II ligands represent promising targets for vaccine design and personalized cancer immunotherapy. Much work has been done to identify and predict unmodified peptides presented on HLA-II molecules. However, little is known about the presentation of phosphorylated HLA-II ligands. Here, we analyzed Mass Spectrometry HLA-II peptidomics data and identified 1,113 unique phosphorylated HLA-II ligands. This enabled us to precisely define phosphorylated binding motifs for more than 30 common HLA-II alleles and to explore various molecular properties of phosphorylated peptides. Our data were further used to develop the first predictor of phosphorylated peptide presentation on HLA-II molecules.
Analysis of expression Quantitative Trait Loci for NLGN4X in relation to language and neurodevelopmental function: an exploratory analysis using FUSION and GTEx workflows
Authors: Simpson Nuala H. , Bishop Dorothy V.M. , Newbury Dianne F. 
Published: June 2021

AbstractLanguage disorders in children are highly heritable, but progress in identifying genetic variants that contribute to language phenotypes has been slow. Here we applied a novel approach by identifying SNPs that are associated with gene expression in the brain, taking as our focus a gene on the X chromosome, NLGN4X, which has been postulated to play a role in neurodevelopmental disorders affecting language and communication. We found no significant associations between expression quantitative trait loci (eQTLs) and phenotypes of nonword repetition, general language ability or neurodevelopmental disorder in two samples of twin children, who had been selected for a relatively high rate of language problems. We report here our experiences with two methods, FUSION and GTEx, for eQTL analysis. It is likely that our null result represents a true negative, but for the interest of others interested in using these methods, we note specific challenges encountered in applying this approach to our data: a) complications associated with studying a gene on the X chromosome; b) lack of agreement between expression estimates from FUSION and GTEx; c) software compatibility issues with different versions of the R programming language.
Genetic diversity and evolution of SARS-CoV-2 in Belgium during the first wave outbreak
Authors: Wawina-Bokalanga Tony , Martí-Carreras Joan , Vanmechelen Bert , Bloemen Mandy , Wollants Elke , Laenen Lies , Cuypers Lize , Beuselinck Kurt , Lagrou Katrien , André Emmanuel , Van Ranst Marc , Maes Piet 
Published: June 2021

AbstractSARS-CoV-2, the causative agent of COVID-19 was first detected in Belgium on 3rd February 2020, albeit the first epidemiological wave started in March and ended in June 2020. One year after the first epidemiological wave hit the country data analyses reveled the temporal and variant distribution of SARS-CoV-2 and its implication with Belgian epidemiological measures. In this study, 766 complete SARS-CoV-2 genomes of samples originating from the first epidemiological were sequenced to characterize the temporal and geographic distribution of the COVID-19 pandemic in Belgium through phylogenetic and variant analysis. Our analysis reveals the presence of the major circulating SARS-CoV-2 clades (G, GH and GR) and lineages circulating in Belgium at that time. Moreover, it contextualizes the density of SARS-CoV-2 cases over time with non-intervention measures taken to prevent the spread of SARS-CoV-2 in Belgium, specific international case imports and the functional implications of the most representative non-synonymous mutations present in Belgium between February to June 2020.
Metabolically Activated Proteostasis Regulators Protect Against Glutamate Toxicity by Activating NRF2
Authors: Rosarda Jessica D. , Baron Kelsey R. , Nutsch Kayla , Bollong Michael J. , Wiseman R. Luke 
Published: June 2021

SUMMARYThe extracellular accumulation of glutamate is a pathologic hallmark of numerous neurodegenerative diseases including ischemic stroke and Alzheimer’s disease. At high extracellular concentrations, glutamate causes neuronal damage by promoting oxidative stress which can lead to cellular death. This has led to significant interest in developing pharmacologic approaches to mitigate the oxidative toxicity caused by high levels of glutamate. Here, we show that the small molecule proteostasis regulator AA147 protects against glutamate-induced cell death in a neuronal-derived cell culture model by reducing intracellular levels of reactive oxygen species. While originally developed as an activator of the ATF6 arm of the unfolded protein response, we show AA147-dependent protection against glutamate toxicity is primarily mediated through activation of the NRF2-regulated oxidative stress response. We demonstrate that AA147 activates NRF2 through a mechanism involving metabolic activation to a reactive electrophile and covalent modification of KEAP1 – a mechanism analogous to that involved in AA147-dependent activation of ATF6. These results define the potential for AA147 to protect against glutamate induced oxidative toxicity and highlight the potential for metabolically-activated proteostasis regulators like AA147 to activate both protective ATF6 and NRF2 stress-responsive signaling pathways to mitigate oxidative damage associated with diverse neurologic diseases.
Direct detection of the myosin super-relaxed state and interacting heads motif in solution
Authors: Chu Sami , Muretta Joseph M. , Thomas David D. 
Published: June 2021

AbstractWe have used time-resolved fluorescence resonance energy transfer (TR-FRET) to detect the interacting-heads motif (IHM) of β-cardiac myosin in solution. Evidence for the IHM has been observed by several structural techniques, and it has been proposed to be the structural basis for the super-relaxed state (SRX), a low-ATPase state of myosin that has been observed biochemically in skinned muscle fibers using fluorescent ATP. It has been proposed that the disruption of this state, by mutation or chemical modification, is a major cause of heart disease, so drugs are being developed to stabilize it. The goal of the present study is to determine directly and quantitatively the correlation between the measured fractions of myosin in the IHM state and the SRX state under the same conditions in solution. We used TR-FRET to measure the distance between the two heads of bovine cardiac myosin, and found that there are two distinct populations, one of which is observable by FRET at a center distance of 2.0 nm, and the other is not detected, implying a distance greater than 4 nm. Under the same conditions, we also measured the fraction of heads in the SRX state using fluorescent nucleotide and stopped-flow kinetics. We found that, in the absence of crosslinking, the population of SRX exceeded that of IHM. In particular, the stabilizing effect of mavacamten was much greater on SRX (55% increase) than on IHM (4% increase). We conclude that the SRX and IHM states are related, but they are not identical.
Deep learning model for the prediction and classification of protein toxins across all domains of life
Authors: Caceres-Delpiano Javier , Ibañez Roberto , Correa Simon , Dunne Michael P. , Retamal Pedro , Álvarez Leonardo 
Published: June 2021

AbstractToxins are widely produced by different organisms to disrupt the physiology of other organisms, and support their own existence. Their study is useful to understand protein evolution, environmental adaptation and survival competition. In-silico predictions of toxic proteins can support empirical frameworks, and help in the safety measurements needed for various industrial related processes. Some in-silico methods are slow, hard to implement or lack taxa representation in their training datasets. Here we present a deep learning model to classify protein toxins, through the use of Convolutional Neural Networks (ConvTOX). ConvTOX is able to accurately identify toxic proteins across the domains of life, with accuracies over 80% for animal and plant toxins, and over 50% for bacterial toxins. Moreover, ConvTOX is able to generalize the identification of differences among toxin types, such as neurotoxins and myotoxins, and to accurately identify structural similarities between different protein toxins. ConvTOX overcomes limitations from previous models by being able to predict toxin proteins from across all domains of life, and by not being limited to only short toxin peptides. Limitations are still clear in terms of lower accuracies for specific phylogenetic groups (such as bacterial toxins), but still this works presents itself as a one step forward for the universal use, classification and study of toxic proteins.
Cystinosin deficient rats recapitulate the phenotype of nephropathic cystinosis
Authors: Hollywood Jennifer A , Kallingappa Prasanna K , Cheung Pang Yuk , Martis Renita M , Sreebhavan Sree , Chatterjee Aparajita , Buckels Emma J , Mathews Brya G , Lewis Paula M , Davidson Alan J 
Published: June 2021

AbstractBackgroundThe lysosomal storage disease cystinosis is caused by mutations in CTNS, encoding a cystine transporter, and in its severest form leads to proximal tubule dysfunction followed by kidney failure. Patients receive the drug-based therapy cysteamine from diagnosis. However, despite long-term treatment, cysteamine only slows the progression of end-stage renal disease and a kidney transplant is inevitable. Pre-clinical testing in cystinotic rodents is required to evaluate new therapies; however, the current models are sub-optimal. To solve this problem we generated a new cystinotic rat model.MethodsWe utilized CRISPR/Cas9-mediated gene editing to disrupt exon 3 of Ctns and measured various parameters over a 12-month time-course including blood and tissue cystine levels, urine and serum electrolytes, and analysed the histopathology and immunohistochemistry of the kidney.ResultsCtns-/- rats display hallmarks of cystinosis by 3-6 months of age as seen by a failure to thrive, excessive thirst and urination, cystine accumulation in tissues, corneal cystine crystals, a loss of Lrp2 in proximal tubules and immune cell infiltration. High levels of glucose, calcium, albumin and protein are excreted at 6-months of age, consistent with the onset of Fanconi syndrome, with a progressive diminution of urine urea and creatinine from 9-months of age, indicative of chronic kidney disease. The kidney histology and immunohistochemistry showed proximal tubule atrophy and glomerular damage as well as classic ‘swan neck’ lesions. Overall, Ctns-/- rats show a disease progression that more faithfully recapitulates nephropathic cystinosis than existing rodent models.ConclusionsThe Ctns-/- rat provides an excellent new rodent model of nephropathic cystinosis that is ideally suited for conducting pre-clinical drug testing and a powerful tool to advance cystinosis research.Translational StatementGood animal models of disease are essential to perform pre-clinical testing of potential new drugs and therapies before they can progress to human clinical trials. Unfortunately, the cystinosis field has been hampered by a lack of suitable animal models that fully recapitulate the disease. We have overcome this by generating a new rat model of cystinosis by CRISPR-Cas9 gene editing. These rodents closely model the human condition in a time-frame that makes them an excellent model ideally suited for pre-clinical drug testing as well as being a powerful tool to advance cystinosis research.
Fighting the big bad wolf of global trends: technology transfer between HPC centres and SMEs
Authors: Besednjak Valič Tamara , Kolar Janez , Lamut Urša 
Published: June 2021

Purpose
This paper aims to explore the dynamic relationships between high-performance computing centres (HPC centres) and small-to-medium-sized enterprises (SMEs) working in the automotive sector.

Design/methodology/approach
An empirical study was conducted in 14 European countries with a total of 92 participants, representatives of HPC centres and SMEs. Data were collected through focus groups.

Findings
Findings show there is a distinct manner of shaping collaboration and cooperation networks between both spheres. In shaping the relationships, cognitive frames play a role through specific values involved share. Institutions also play an important role.

Research limitations/implications
Research into relationships between HPC centres and SMEs conducted was qualitative; therefore, limitations arise on data not being able to be generalized. The cultural aspect is to be taken into account when conducting further studies.

Practical implications
Findings of this study can be used by policymakers, especially those interested in regional innovation. The results can be of use when tailoring innovation policies, especially when it comes to enhancing the regional and extra-regional cooperation between HPC centres and SMEs.

Originality/value
To the best of authors’ knowledge, this paper is one of the first research contributions to analyse the relationships between HPC centres and SMEs from the automotive sector in selected European countries.