bluuebunny/crossref_metadata_2025 huggingface dataset:
A human-interpretable machine learning approach to predict mortality in severe mental illness
Authors: Banerjee Soumya , Liò Pietro , Jones Peter B. , Cardinal Rudolf N.
Published: April 2021

Machine learning (ML), one aspect of artificial intelligence (AI), involves computer algorithms that train themselves. They have been widely applied in the healthcare domain. However, many trained ML algorithms operate as “black boxes”, producing a prediction from input data without a clear explanation of their workings. Non-transparent predictions are of limited utility in many clinical domains, where decisions must be justifiable.

Here, we apply class-contrastive counterfactual reasoning to ML to demonstrate how specific changes in inputs lead to different predictions of mortality in people with severe mental illness (SMI), a major public health challenge. We produce predictions accompanied by visual and textual explanations as to how the prediction would have differed given specific changes to the input. We apply it to routinely collected data from a mental health secondary care provider in patients with schizophrenia. Using a data structuring framework informed by clinical knowledge, we captured information on physical health, mental health, and social predisposing factors. We then trained an ML algorithm and other statistical learning techniques to predict the risk of death.

The ML algorithm predicted mortality with an area under receiver operating characteristic curve (AUROC) of 0.80 (95% confidence intervals [0.78, 0.82]). We used class-contrastive analysis to produce explanations for the model predictions. We outline the scenarios in which class-contrastive analysis is likely to be successful in producing explanations for model predictions. Our aim is not to advocate for a particular model but show an application of the class-contrastive analysis technique to electronic healthcare record data for a disease of public health significance.

In patients with schizophrenia, our work suggests that use or prescription of medications like antide-pressants was associated with lower risk of death. Abuse of alcohol/drugs and a diagnosis of delirium were associated with higher risk of death. Our ML models highlight the role of co-morbidities in determining mortality in patients with SMI and the need to manage them. We hope that some of these bio-social factors can be targeted therapeutically by either patient-level or service-level interventions. Our approach combines clinical knowledge, health data, and statistical learning, to make predictions interpretable to clinicians using class-contrastive reasoning. This is a step towards interpretable AI in the management of patients with SMI and potentially other diseases.
Prime hAd5 Spike + Nucleocapsid Vaccination Induces Ten-Fold Increases in Mean T-Cell Responses in Phase 1 Subjects that are Sustained Against Spike Variants
Authors: Sieling Peter , King Thomas , Wong Raymond , Nguyen Andy , Wnuk Kamil , Gabitzsch Elizabeth , Rice Adrian , Adisetiyo Helty , Hermreck Melanie , Verma Mohit , Zakin Lise , Shin Annie , Morimoto Brett , Higashide Wendy , Dinkins Kyle , Balint Joseph , Peykov Victor , Taft Justin , Patel Roosheel , Buta Sofija , Martin-Fernandez Marta , Bogunovic Dusan , Spilman Patricia , Sender Lennie , Reddy Sandeep , Robinson Philip , Rabizadeh Shahrooz , Niazi Kayvan , Soon-Shiong Patrick
Published: April 2021

In response to the need for a safe, efficacious vaccine that elicits vigorous T cell as well as humoral protection against SARS-CoV-2 infection, we have developed a dual-antigen COVID-19 vaccine comprising both the viral spike (S) protein modified to increase cell-surface expression (S-Fusion) and nucleocapsid (N) protein with an Enhanced T-cell Stimulation Domain (N-ETSD) to enhance MHC class I and II presentation and T-cell responses. The antigens are delivered using a human adenovirus serotype 5 (hAd5) platform with E1, E2b, and E3 regions deleted that has been shown previously in cancer vaccine studies to be safe and effective in the presence of pre-existing hAd5 immunity. The findings reported here are focused on human T-cell responses due to the likelihood that such responses will sustain efficacy against emerging variants, a hypothesis supported by ourin silicoprediction of T-cell epitope HLA binding for both the first-wave SARS-CoV-2 ‘A’ strain and the B.1.351 strain K417N, E484K, and N501Y spike and T201I N variants. We demonstrate the hAd5 S-Fusion + N-ETSD vaccine antigens expressed by previously SARS-CoV-2-infected patient dendritic cells elicit Th1 dominant activation of autologous patient T cells, indicating the vaccine antigens have the potential to elicit immune responses in previously infected patients. For participants in our open-label Phase 1b study of the vaccine (NCT04591717;https://clinicaltrials.gov/ct2/show/NCT04591717), the magnitude of Th-1 dominant S- and N-specific T-cell responses after a single prime subcutaneous injection were comparable to T-cell responses from previously infected patients. Furthermore, vaccinated participant T-cell responses to S were similar for A strain S and a series of spike variant peptides, including S variants in the B.1.1.7 and B.1.351 strains. The findings that this dual-antigen vaccine elicits SARS-CoV-2-relevant T-cell responses and that such cell-mediated protection is likely to be sustained against emerging variants supports the testing of this vaccine as a universal booster that would enhance and broaden existing immune protection conferred by currently approved S-based vaccines.
Impaired Humoral and Cellular Immunity after SARS-CoV2 BNT162b2 (Tozinameran) Prime-Boost Vaccination in Kidney Transplant Recipients
Authors: Sattler Arne , Schrezenmeier Eva , Weber Ulrike , Potekhin Alexander , Bachmann Friederike , Budde Klemens , Storz Elena , Proß Vanessa , Bergmann Yasmin , Thole Linda , Tizian Caroline , Hölsken Oliver , Diefenbach Andreas , Schrezenmeier Hubert , Jahrsdörfer Bernd , Zemojtel Tomasz , Jechow Katharina , Conrad Christian , Lukassen Sören , Stauch Diana , Lachmann Nils , Choi Mira , Halleck Fabian , Kotsch Katja
Published: April 2021

Novel mRNA-based vaccines have been proven powerful tools to combat the global pandemic caused by SARS-CoV2 with BNT162b2 efficiently protecting individuals from COVID-19 across a broad age range. Still, it remains largely unknown how renal insufficiency and immunosuppressive medication affect development of vaccine induced immunity. We therefore comprehensively analyzed humoral and cellular responses in kidney transplant recipients after prime-boost vaccination with BNT162b2. As opposed to all healthy vaccinees and the majority of hemodialysis patients, only 4/39 and 1/39 transplanted individuals showed IgA and IgG seroconversion at day 8±1 after booster immunization with minor changes until day 23±5, respectively. Although most transplanted patients mounted spike-specific T helper cell responses, frequencies were significantly reduced compared to controls and dialysis patients, accompanied by a broad impairment in effector cytokine production, memory differentiation and activation-related signatures. Spike-specific CD8+ T cell responses were less abundant than their CD4+ counterparts in healthy controls and hemodialysis patients and almost undetectable in transplant patients. Signs of alloreactivity promoted by BNT162b2 were not documented within the observation period. In summary, our data strongly suggest revised vaccination approaches in immunosuppressed patients, including individual immune monitoring for protection of this vulnerable group at risk to develop severe COVID-19.
Reduction in the 2020 Life Expectancy in Brazil after COVID-19
Authors: Castro Marcia C , Gurzenda Susie , Turra Cassio M , Kim Sun , Andrasfay Theresa , Goldman Noreen
Published: April 2021

Brazil has the second-largest number of COVID-19 deaths worldwide. We use data on reported deaths to measure and compare the death toll across states from a demographic perspective. We estimate a decline in 2020 life expectancy at birth of 1.94 years, resulting in a mortality level not seen since 2013. The reduction in life expectancy at age 65 was 1.58 years, setting Brazil back to 2009 levels. The decline was larger for males, widening by 2.3% and 5.4% the female-male gap in life expectancy at birth and at age 65, respectively. Among states, Amazonas lost 59.6% of the improvements in life expectancy at birth since 2000. With 2021 COVID-19 deaths at about 43% of the total 2020 figures (as of mid-March) the demographic effect is likely to be even higher this year.
The Role of Community Health Workers in Oral Health Promotion and the Impact of their services in Sub-Saharan Africa: A Systematic Review
Authors: Khan Mohammed Azhar , Okeah Bernard Ojiambo , Mbivnjo Etheldreda Leinyuy , Kisangala Ephraim , Pritchard Aaron Wyn
Published: April 2021

Oral ailments are largely preventable but remain a significant public health concern afflicting nearly half the global population. These conditions account for 220 years of life lost per 100,000 people and about US$500 billion in health-related expenditures. Sub-Saharan Africa bears a significant burden of oral health problems thus exerting additional pressure on the scarce human resources for health. Community healthcare workers (CHWs) could be potentially utilised to bridge the shortage of oral health professionals in sub-Saharan Africa, hence, this systematic review that seeks to explore their current roles in oral health and potential impact on general physical health. This review follows the PRISMA guidelines and databases searched include PubMed, Web of Science, Medline, and CINAHL published between January 2010 and December 2019. Nine studies met the study eligibility criteria. This review established that CHWs perform variable roles cutting across primary, secondary, and tertiary prevention including providing oral hygiene education, recognising common pathologies, and treating oral lesions, administration of tooth extractions, dental pain management, and referral for advanced care. Although this could potentially improve oral health, our review did not establish the extent of the specific impact on general physical health of patients and the burden of oral condition.
An extended SEIARD model for COVID-19 vaccination in Mexico: analysis and forecast
Authors: Pérez Ángel G. C. , Oluyori David A.
Published: April 2021

In this study, we propose and analyse an extended SEIARD model with vaccination. We compute the control reproduction number ℛcof our model and study the stability of equilibria. We show that the set of disease-free equilibria is locally asymptotically stable when ℛc< 1 and unstable when ℛc> 1, and we provide a sufficient condition for its global stability. Furthermore, we perform numerical simulations using the reported data of COVID-19 infections and vaccination in Mexico to study the impact of different vaccination, transmission and efficacy rates on the dynamics of the disease.
Propelling and perturbing appendages together facilitate strenuous ground self-righting
Authors: Othayoth Ratan , Li Chen
Published: April 2021

Terrestrial animals must self-right when overturned on the ground, but this locomotor task is strenuous. To do so, the discoid cockroach often pushes its wings against the ground to begin a somersault which rarely succeeds. As it repeatedly attempts this, the animal probabilistically rolls to the side to self- right. During winged self-righting, the animal flails its legs vigorously. Here, we studied whether wing opening and leg flailing together facilitate strenuous ground self-righting. Adding mass to increase hind leg flailing kinetic energy increased the animal’s self-righting probability. We then developed a robot with similar strenuous self-righting behavior and used it as a physical model for systematic experiments. The robot’s self-righting probability increased with wing opening and leg flailing amplitudes. A potential energy landscape model revealed that, although wing opening did not generate sufficient kinetic energy to overcome the high pitch potential energy barrier to somersault, it reduced the barrier for rolling, facilitating the small kinetic energy from leg flailing to probabilistically overcome it to self-right. The model also revealed that the stereotyped body motion during self-righting emerged from physical interaction of the body and appendages with the ground. Our work demonstrated the usefulness of potential energy landscape for modeling self-righting transitions.

Impact statement

Animals can, and robots should, use different types of appendages together to propel and perturb themselves to self-right when overturned, a strenuous yet crucial locomotor task.
Sensory readout accounts for adaptation
Authors: Sheehan Timothy C. , Serences John T.
Published: April 2021

Sensory responses and behavior are strongly shaped by stimulus history. For instance, perceptual reports are sometimes biased towards previously viewed stimuli (serial dependence). While behavioral studies have pointed to both perceptual and post-perceptual origins of this phenomenon, neural data that could elucidate where these biases emerge is limited. We recorded fMRI responses while human participants (male and female) performed a delayed orientation discrimination task. While behavioral reports wereattractedto the previous stimulus, response patterns in visual cortex wererepelled. We reconciled these opposing neural and behavioral biases using a model where both sensory encoding and readout are shaped by stimulus history. First, neural adaptation reduces redundancy at encoding and leads to the repulsive biases that we observed in visual cortex. Second, our modeling work suggest that serial dependence is induced by readout mechanisms that account for adaptation in visual cortex. According to this account, the visual system can simultaneously improve efficiency via adaptation while still optimizing behavior based on the temporal structure of natural stimuli.
Transcriptome profiling and comparison ofRhinanthus majorandRhinanthus minorreciprocal F1hybrids during seed stratification and germination
Authors: Mirzaei Khaled , Wesselingh Renate A.
Published: April 2021

Background and Aims

Germination is a vital stage in a plant’s life cycle, and a different germination behavior of offspring in comparison to their parents can have fitness consequences. In studies on hybridization betweenRhinanthus minorandR. major, low germination rates of F1hybrids withR. majoras the maternal parent have often been reported. In contrast, the F1mhybrid, withR. minoras the maternal parent, germinates readily and rapidly.

Methods

In order to find the cause of this difference, we used RNA-Seq to obtain transcriptome profiles of F1aand F1mseeds during stratification at 4°C and just after germination, after 40 days of stratification for the F1mseeds and 60 days for the F1aseeds.

Key Results

A comparison of the transcriptome of F1aseeds that had just germinated (60 days) with non-germinated F1aseeds after 40 and 60 days revealed 2918 and 1349 differentially expressed (DE) genes, respectively. For F1mseeds, 958 genes showed differential expression in germinated and non-germinated seeds after 40 days. The DE genes of F1aand F1mhybrids clustered into two separate groups, even though they had the same parents, and no differentially expression was found for plastid genes. Non-germinated F1aseeds had an abundance of enzymes and proteins associated with peroxidase activity, peroxiredoxin activity and nutrient reservoir activity. Expression of genes related to seed germination and seed development increased in non-germinated F1ahybrid seeds between 40 and 60 days of cold stratification. F1aseeds that had germinated showed an upregulation of genes related to the gibberellic acid-mediated signaling pathway and response to gibberellin, along with a low expression of DELLA superfamily.

Conclusions

Although the results demonstrated strong differences in gene expression during stratification between the reciprocal hybrids, we could not identify its cause, since no plastid genes were differentially expressed. It is possible that differences in embryo development after seed formation and before stratification play a role, including epigenetic imprinting.
Ligand Strain Energy in Large Library Docking
Authors: Gu Shuo , Smith Matthew S. , Yang Ying , Irwin John J. , Shoichet Brian K.
Published: April 2021

While small molecule internal strain is crucial to molecular docking, using it in evaluating ligand scores has remained elusive. Here, we investigate a technique that calculates strain using relative torsional populations in the Cambridge Structural Database, enabling fast pre-calculation of these energies. In retrospective studies of large docking screens of the dopamine D4 receptor and of AmpC β-lactamase, where close to 600 docking hits were tested experimentally, including such strain energies improved hit rates by preferentially reducing high-scoring decoy molecules that were strained. In a 40 target subset of the DUD-E benchmark, we found two thresholds that usefully distinguished between ligands and decoys: one based on the total strain energy of the small molecules, and one based on the maximum strain allowed for any given torsion within them. Using these criteria, about 75% of the benchmark targets had improved enrichment after strain filtering. Relying on pre-calculated population distributions, this approach is rapid, taking less than 0.04 second to evaluate a conformation on a standard core, making it pragmatic for pre-calculating strain in even ultra-large libraries. Since it is scoring function agnostic, it may be useful to multiple docking approaches; it is openly available athttp://tldr.docking.org
Strain variation and anomalous climate synergistically influence cholera pandemics
Authors: Rodó X. , Bouma M.J. , Rodriguez-Arias M.A. , Roy M. , De Yebra P. , Garcia M. , Pascual M.
Published: April 2021

Explanations for the genesis and propagation of recurrent cholera pandemics since 1817 have remained elusive. Evolutionary change of the pathogen is presumed to have been a dominant factor behind the 7th “El Tor” pandemic, but little is known to support this hypothesis for preceding pandemics. We investigate the concomitant roles of climate and putative strain variation for the 6th cholera pandemic (1899-1923; the one with the highest ever associated mortality in India), using newly assembled historical records for climate variables and cholera deaths for Bengal, Assam, Bihar and Bombay provinces in former British India. We compare this historical pandemic with the 7th (El Tor) one and with the temporary emergence of the O139 strain in Bangladesh and globally. Finally, we ran multi-model climate simulations to infer past and future long-term means of rainfall distributions on the basis of 39 models for 1861-2100, and for different periods of 50 years (1875-1925; 1975-2025 and 2050-2100).

The 6th cholera pandemic featured a large scale synchronisation with a delay of a few years in both seasonal and interannual cholera variability over the endemic Bengal region during the El Niño event of 1904-07. Additional evidence supporting the establishment of a new strain includes a shift of cholera incidence to older age groups, an increase in the case fatality rate and the suppression of the spring cholera peak.

The 6th cholera pandemic of Indian origin was associated with a novel and particularly invasive strain of new territory, and also with some delay, of endemic parts of India that act as a genetic regional reservoir of the disease. Climate anomalies appear to have played an important role in facilitating the establishment of this invasive strain, with environmental conditions similar to those underlying strain changes associated with ENSO in today’s Bangladesh. The evolutionary change of pathogens can act synergistically with climatic conditions in the replacement and propagation of emerging strains, as was the case in cholera’s 7th pandemic. Increased climate variability and extremes under global warming would thus provide windows of opportunity for emerging new pathogens.
In silicoanalysis of the fast-growing thermophileGeobacillussp. LC300 using a novel genome-scale metabolic model
Authors: Ljungqvist Emil , Gustavsson Martin
Published: April 2021

Thermophilic microorganisms show high potential for use as biorefinery cell factories. Their high growth temperatures provide fast conversion rates, lower risk of contaminations, and facilitated purification of volatile products. To date, only a few thermophilic species have been utilized for microbial production purposes, and the development of production strains is impeded by the lack of metabolic engineering tools. In this study, we constructed a genome-scale metabolic model,iGEL601, ofGeobacillussp. LC300, an important part of the metabolic engineering pipeline. The model contains 601 genes, 1240 reactions and 1305 metabolites, and the reaction reversibility is based on thermodynamics at the optimum growth temperature. Using flux sampling, the model shows high similarity to experimentally determined reaction fluxes with both glucose and xylose as sole carbon sources. Furthermore, the model predicts previously unidentified by-products, closing the gap in the carbon balance for both carbon sources. Finally,iGEL601was used to suggest metabolic engineering strategies to maximise production of five industrially relevant compounds. The suggested strategies have previously been experimentally verified in other microorganisms, and predicted production rates are on par with or higher than those previously achieved experimentally. The results highlight the biotechnological potential of LC300 and the application ofiGEL601for use as a tool in the metabolic engineering workflow.
Alpha-Frag: a deep neural network for fragment presence prediction improves peptide identification
Authors: Song Jian , Zhang Fangfei , Yu Changbin
Published: April 2021

Identification of peptides in mass spectrometry-based proteomics typically relies on spectra matches. As MS/MS spectra record presence and intensity of fragment ions, the match should take both fragment presence similarity and intensity similarity into consideration. Fragment presence similarity can be calculated with the help of fragment presence prediction such as theoretical enumeration of all possible fragment ions or selecting non-zero intensity ions from the result of fragment intensity prediction, but neither of these two methods is accurate enough. In this work, we developed a deep neural network based model, Alpha-Frag, to predict precisely the fragment ions that should be present for a given peptide. Alpha-Frag modelled fragment presence prediction as a multi-label classification task and trained with ProteomeTools dataset. In terms of intersection over union (IoU), Alpha-Frag achieved an average of >0.7 and outperformed the benchmarks across the validation datasets. Furthermore, fragment presence similarity was calculated based on presence prediction and incorporated into the peptide statistical validation tools as an additional score to improve peptide identifications. Our preliminary experiments show that this score led to a maximum increase of 26.8% (FDR 0.1%) and 21.6% (FDR 1%) for the DDA and the DIA identification, respectively.

Significance Statement

A better prediction of fragmentation for peptides in mass spectrometry (MS) is beneficial to the peptide identification. As the MS/MS spectra record two-dimensional information of fragment ions derived from precursors, mass-to-charge ratio (m/z) and their corresponding intensities, besides the fragment intensity prediction, it is necessary to study the presence prediction. Although the presence prediction can be realized by enumerating all the possible fragmentation patterns of a peptide with equal probability or by selecting non-zero intensity fragment ions from the result of fragment intensity prediction, neither of these two methods is accurate enough. In this study, deep learning is leveraged to precisely predict the fragment ions of a given peptide. Based on the fragment presence prediction, fragment presence similarity between experimental spectra and predicted spectra can be calculated which is proved to promote the peptide detections both for DDA and for DIA data.
Interpretable Artificial Neural Networks incorporating Bayesian Alphabet Models for Genome-wide Prediction and Association Studies
Authors: Zhao Tianjing , Fernando Rohan , Cheng Hao
Published: April 2021

In conventional linear models for whole-genome prediction and genome-wide association studies (GWAS), it is usually assumed that the relationship between genotypes and phenotypes is linear. Bayesian neural networks have been used to account for non-linearity such as complex genetic architectures. Here, we introduce a method named NN-Bayes, where “NN” stands for neural networks, and “Bayes” stands for Bayesian Alphabet models, including a collection of Bayesian regression models such as BayesA, BayesB, BayesC, Bayesian LASSO, and BayesR. NN-Bayes incorporates Bayesian Alphabet models into non-linear neural networks via hidden layers between SNPs and observed traits. Thus, NN-Bayes attempts to improve the performance of genome-wide prediction and GWAS by accommodating non-linear relationships between the hidden nodes and the observed trait, while maintaining genomic interpretability through the Bayesian regression models that connect the SNPs to the hidden nodes. For genomic interpretability, the posterior distribution of marker effects in NN-Bayes is inferred by Markov chain Monte Carlo (MCMC) approaches and used for inference of association through posterior inclusion probabilities (PIPs) and window posterior probability of association (WPPA). In simulation studies with dominance and epistatic effects, performance of NN-Bayes was significantly better than conventional linear models for both GWAS and whole-genome prediction, and the differences on prediction accuracy were substantial in magnitude. In real data analyses, for the soy dataset, NN-Bayes achieved significantly higher prediction accuracies than conventional linear models, and results from other four different species showed that NN-Bayes had similar prediction performance to linear models, which is potentially due to the small sample size. Our NN-Bayes is optimized for high-dimensional genomic data and implemented in an open-source package called “JWAS”. NN-Bayes can lead to greater use of Bayesian neural networks to account for non-linear relationships due to its interpretability and computational performance.
Distinct Binding Mechanisms for Allosteric Sodium Ion In Cannabinoid Receptors
Authors: Dutta Soumajit , Selvam Balaji , Shukla Diwakar
Published: April 2021

The therapeutical potential of Cannabinoid receptors is not fully explored due to psychoactive side-effects and lack of selectivity associated with the orthosteric ligands. Allosteric modulators have the potential to become selective therapeutics for cannabinoid receptors. Biochemical experiments have shown the effects of the allosteric Na+binding on cannabinoid receptor activity. However, the Na+coordination site, and binding pathway are still unknown. Here, we perform molecular dynamic simulations to explore Na+binding in the cannabinoid receptors, CB1and CB2. Simulations reveal that Na+binds to the primary binding site from different extracellular sites for CB1and CB2. A distinct secondary Na+coordinate site is identified that is not present in CB2. Furthermore, simulations also show that intracellular Na+could bind to the Na+binding site in CB1. Constructed Markov state models show that the standard free energy of Na+binding is similar to the previously calculated free energy for other class A GPCRs.
PsiNorm: a scalable normalization for single-cell RNA-seq data
Authors: Borella Matteo , Martello Graziano , Risso Davide , Romualdi Chiara
Published: April 2021

Single-cell RNA sequencing (scRNA-seq) enables transcriptome-wide gene expression measurements at single-cell resolution providing a comprehensive view of the compositions and dynamics of tissue and organism development. The evolution of scRNA-seq protocols has led to a dramatic increase of cells throughput, exacerbating many of the computational and statistical issues that previously arose for bulk sequencing. In particular, with scRNA-seq data all the analyses steps, including normalization, have become computationally intensive, both in terms of memory usage and computational time. In this perspective, new accurate methods able to scale efficiently are desirable.

Here we proposePsiNorm, a between-sample normalization method based on the power-law Pareto distribution parameter estimate. Here we show that the Pareto distribution well resembles scRNA-seq data, independently of sequencing depths and technology. Motivated by this result, we implementPsiNorm, a simple and highly scalable normalization method. We benchmarkPsiNormwith other seven methods in terms of cluster identification, concordance and computational resources required. We demonstrate thatPsiNormis among the top performing methods showing a good trade-off between accuracy and scalability. MoreoverPsiNormdoes not need a reference, a characteristic that makes it useful in supervised classification settings, in which new out-of-sample data need to be normalized.

PsiNormis available as an R package available athttps://github.com/MatteoBlla/PsiNorm
Machine Learning Identifies Ponatinib as a Potent Inhibitor of SARS-CoV2-induced Cytokine Storm
Authors: Chan Marina , Vijay Siddharth , McElrath M. Juliana , Holland Eric C. , Gujral Taranjit S
Published: April 2021

Although 15-20% of COVID-19 patients experience hyper-inflammation induced by massive cytokine production, cellular triggers of this process and strategies to target them remain poorly understood. Here, we show that the N-terminal domain (NTD) of the spike protein from the SARS-CoV-2 and emerging variants B1.1.7 and B.1.351 substantially induces multiple inflammatory molecules in human monocytes and PBMCs. Further, we identified several protein kinases, including JAK1, EPHA7, IRAK1, MAPK12, and MAP3K8, as essential downstream mediators of NTD-induced cytokine release. Additionally, we found that the FDA-approved, multi-kinase inhibitor Ponatinib is a potent inhibitor of the NTD-mediated cytokine storm. Taken together, we propose that agents targeting multiple kinases required for the SARS-CoV-2-mediated cytokine storm, such as Ponatinib, may represent an attractive therapeutic option for treating moderate to severe COVID-19.
Differing ecological responses of seabirds to invasive species eradication
Authors: Bird Jeremy P. , Fuller Richard A. , Shaw Justine D. S.
Published: April 2021

The impact of invasive species at seabird breeding islands causes a breakdown of important ecological functions such as prey consumption and nutrient transfer, and elevates extinction risk in impacted taxa. Eradicating invasive species from islands can result in substantial short-term recovery of seabird populations and consequently the prevalence of eradication programs as conservation tools is increasing. However, as the scale and complexity of eradications has increased, quantitative data on rates of recovery, especially from larger islands, remain limited. Furthermore, the mechanisms that govern recovery are poorly understood, limiting our ability to forecast outcomes and therefore prioritise effectively. Here, using the world’s largest multi-species vertebrate eradication from Macquarie Island as a case study, we show how responses to invasive species and their eradication differ. Species with broad realised niches whose breeding phenology minimizes time on land and corresponds with summer resource abundance remained extant alongside invasive species while more habitat-specific species present in winter were extirpated. Following eradication, immigration and flexibility to colonise under-utilised optimal habitat appears to be boosting population growth in recolonising species, whereas established populations appear to be tethered to refugial habitats by the influence of philopatry, and their recovery is slower as a result. Unpicking these differential responses and the mechanisms behind them provides valuable information to help predict responses in other systems as future eradications are planned.
Decreased biofilm formation inProteus mirabilisafter short-term exposure to a simulated microgravity environment
Authors: Wang Dapeng , Bai Po , Zhang Bin , Su Xiaolei , Jiang Xuege , Fang Tingzheng , Wang Junfeng , Liu Changting
Published: April 2021

Background

Microbes threaten human health in space exploration. Studies have shown thatP. mirabilishas been found in human space habitats. In addition, the biological characteristics ofP. mirabilisin space have been studied unconditionally. The simulated microgravity environment provides a platform for understanding the changes in the biological characteristics ofP. mirabilis.

Objective

This study intends to explore the effect of simulated microgravity onP. mirabilis, the formation ofP. mirabilisbiofilm and its related mechanism.

Methods

The strange deformable rods were cultured continuously for 14 days under the microgravity simulated by (HARVs) in a high-aspect ratio vessels. The morphology, growth rate, metabolism and biofilm formation of the strain were measured, and the phenotypic changes ofP. mirabiliswere evaluated. Transcriptome sequencing was used to detect differentially expressed genes under simulated microgravity and compared with phenotype.

Results

The growth rate, metabolic ability and biofilm forming ability ofP. mirabiliswere lower than those of normal gravity culture under the condition of simulated microgravity. Further analysis showed that the decrease of growth rate, metabolic ability and biofilm forming ability may be caused by the down-regulation of related genes (pstS,sodBandfumC).

Conclusion

It provides a certain reference for the prevention and treatment ofP. mirabilisinfection in the future space station by exploring the effect of simulated microgravity exposure onP. mirabilis.
A large and diverse autosomal haplotype is associated with sex-linked colour polymorphism in the guppy
Authors: Paris Josephine R , Whiting James R , Daniel Mitchel J , Obiol Joan Ferrer , Parsons Paul J , van der Zee Mijke J , Wheat Christopher W , Hughes Kimberly A , Fraser Bonnie A
Published: April 2021

Colour polymorphism provides a tractable trait that can be harnessed to explore the evolution of sexual selection and sexual conflict. Male colour patterns of the Trinidadian guppy (Poecilia reticulata) are governed by both natural and sexual selection, and are typified by extreme pattern colour variation as a result of negative frequency dependent selection. Since guppy colour patterns are often inherited faithfully from fathers to sons, it has been historically presumed that colour genes are physically linked to sex determining loci as a ‘supergene’ on the sex chromosome. Yet the actual identity and genomic location of the colour pattern genes has remained elusive. We phenotyped and genotyped four guppy ‘Iso-Y lines’, where colour was inherited along the patriline, but backcrossed into the stock population every 2 to 3 generations for 40 generations, thereby homogenising the genome at regions unrelated to colour. Using an unbiased phenotyping method to proportion colour pattern differences between and among the Iso-Y lines, we confirmed that the breeding design was successful in producing four distinct colour patterns. Our analysis of genome resequencing data of the four Iso-Y lines uncovered a surprising genetic architecture for colour pattern polymorphism. Genetic differentiation among Iso-Y lines was repeatedly associated with a large and diverse haplotype (∼5Mb) on an autosome (LG1), not the sex chromosome (LG12). Moreover, the LG1 haplotype showed elevated linkage disequilibrium and exhibited evidence of sex-specific diversity when we examined whole-genome sequencing data of the natural source population. We hypothesise that colour pattern polymorphism is driven by Y-autosome epistasis, and conclude that predictions of sexual conflict should focus on incorporating the effects of epistasis in understanding complex adaptive architectures.
Spectroscopic glimpses of the transition state of ATP hydrolysis trapped in a bacterial DnaB helicase
Authors: Malär Alexander A. , Wili Nino , Völker Laura A. , Kozlova Maria I. , Cadalbert Riccardo , Däpp Alexander , Weber Marco E. , Zehnder Johannes , Jeschke Gunnar , Eckert Hellmut , Böckmann Anja , Klose Daniel , Mulkidjanian Armen Y. , Meier Beat H. , Wiegand Thomas
Published: April 2021

The ATP hydrolysis transition state of motor proteins is a weakly populated protein state that can be stabilized and investigated by replacing ATP with chemical mimics. We present atomic-level structural and dynamic insights on a state created by ADP aluminum fluoride binding to the bacterial DnaB helicase fromHelicobacter pylori. We determined the positioning of the metal ion cofactor within the active site using electron paramagnetic resonance, and identified the protein protons coordinating to the phosphate groups of ADP and DNA using proton-detected31P,1H solid-state nuclear magnetic resonance spectroscopy at fast magic-angle spinning > 100 kHz, as well as temperature-dependent proton chemical-shift values to prove their engagements in hydrogen bonds.19F and27Al MAS NMR spectra reveal a highly mobile, fast-rotating aluminum fluoride unit pointing to the capture of a late ATP hydrolysis translation state in which the phosphoryl unit is already detached from the arginine and lysine fingers.
The methyl phosphate capping enzyme Bin3 is a stable component of the fission yeast telomerase holoenzyme
Authors: Porat Jennifer , El Baidouri Moaine , Grigull Jorg , Deragon Jean-Marc , Bayfield Mark A.
Published: April 2021

The telomerase holoenzyme is critical for maintaining eukaryotic genome integrity. In addition to a reverse transcriptase and an RNA template, telomerase contains additional proteins that protect the telomerase RNA and promote holoenzyme assembly. Here we report that the methyl phosphate capping enzyme (MePCE) Bin3 is a stable component of theS. pombetelomerase holoenzyme. Bin3 associates with the telomerase holoenzyme and U6 snRNA through an interaction with the recently described LARP7 family member Pof8, and we demonstrate that these two factors are evolutionarily linked in fungi. Our data suggest that the association of Bin3 with telomerase is independent of its methyltransferase activity, but rather that Bin3 functions in telomerase holoenzyme assembly by promoting TER1 accumulation and Pof8 recruitment to TER1. Taken together, this work yields new insight into the composition, assembly, and regulation of the telomerase holoenzyme in fission yeast as well as the breadth of its evolutionary conservation.
Caregiving quality modulates neuroendocrine and immunological markers in young children in foster care who have experienced early adversity
Authors: Reindl V. , Schippers A. , Tenbrock K. , Job A.-K. , Gerloff C. , Lohaus A. , Heinrichs N. , Konrad K.
Published: April 2021

Background

Early adversity is believed to alter the body’s stress response systems, putting children at increased risk for somatic and mental health problems. However, it remains unclear whether such alterations normalize under improved caregiving experiences. Thus, the goal of the present study was to investigate i) whether children in foster care show endocrine and immunological alterations relative to children living with their biological families, ii) whether these alterations change over time spent with the foster family and iii) whether the alterations are modulated by current caregiving experiences.

Methods

A total of 94 children in foster care and 157 biological children, aged two to seven years, took part in a longitudinal study with three assessments conducted over a 12-month study period. At the initial assessment, children lived for an average of 18 months with their current foster families. Children’s cortisol, dehydroepiandrosterone (DHEA) and progesterone concentrations and cortisol/DHEA ratios were measured in scalp hair and children’s secretory immunoglobulin A (sIgA) levels in saliva. Caregiving quality was assessed based on caregiver-reports and observational measures of caregiver-child interactions.

Results

Children in foster care had lower cortisol/DHEA ratios and higher progesterone concentrations than biological children, while no group differences were found for cortisol, DHEA or sIgA. Time spent with the current foster family did not significantly influence the child’s endocrine or immunological markers. Importantly, caregiving quality modulated cortisol/DHEA ratios and sIgA concentrations: children in foster care of lower caregiving quality had lower cortisol/DHEA ratios than children in foster care of higher caregiving quality and showed decreasing, rather than increasing, sIgA concentrations across the study period.

Conclusions

Our results indicate that caregiving quality in the foster family may have an important modulating effect on selected indicators of the child’s stress response and could thereby mitigate the possible consequences of early childhood adversity.
Aire-dependent transcripts escape H3K36me3 and Raver2 induced alternative splicing to sustain central immune tolerance
Authors: Padonou Francine , Gonzalez Virginie , Jmari Nada , Maslovskaja Julia , Kisand Kai , Peterson Pärt , Irla Magali , Giraud Matthieu
Published: April 2021

Aire allows medullary thymic epithelial cells (mTECs) to express and present a large number of self-antigens for central tolerance. Although mTECs express a high diversity of self-antigen splice isoforms, the extent and regulation of alternative splicing events (ASEs) included in their transcripts, notably in those induced by Aire, is unknown. Unexpectedly, and in contrast to Aire-neutral genes, we found that the Aire-sensitive genes exhibit in Aire-positive and negative mTECs, a weak inclusion of ASEs, with about a quarter present in peripheral tissues being excluded from the thymus. We identified Raver2, as a splicing-related factor overrepresented in mTECs and dependent on H3K36me3 marks. We discovered that both Raver2 and methylation of H3K36 promoted ASE inclusion for Aire-neutral genes, leaving Aire-sensitive genes unaffected. Profiling of H3K36me3 revealed its depletion at Aire-sensitive genes, supporting a mechanism, whose setup precedes Aire’s expression and by which Aire-sensitive genes exhibit weak ASE inclusion through the escape of Raver2’s effect. Lack of ASEs in Aire-induced transcripts highlights a role for regulatory T cells in controlling the incomplete Aire-dependent negative selection.
In vivoengineered B cells retain memory and secrete high titers of anti-HIV antibodies in mice
Authors: Nahmad A. D. , Lazzarotto C. R. , Zelikson N. , Kustin T. , Tenuta M. , Huang D. , Reuveni I. , Horovitz-Fried M. , Dotan I. , Rosin-Arbesfeld R. , Nemazee D. , Voss J.E. , Stern A. , Tsai S. Q. , Barzel A.
Published: April 2021

As a potential single-shot HIV therapy, transplanted engineered B cells allow robust secretion of broadly neutralizing antibodies (bNAbs). However,ex vivoengineering of autologous B cells is expensive and requires specialized facilities, while allogeneic B cell therapy necessitates MHC compatibility. Here, we developin vivoB cell engineering, by injecting two adeno associated viral vectors, one coding for saCas9 and another coding for a bNAb. Following immunizations, we demonstrate memory retention and bNAb secretion at neutralizing titers. We observed minimal CRISPR/Cas9 off-target cleavage, using unbiased CHANGE-Seq analysis, while on-target cleavage at undesired tissues is reduced by expressing saCas9 from a B cell specific promoter.In vivoB cell engineering is thus a safe, potent and scalable method for expressing desired antibodies against HIV and beyond.

One sentence summary

B cells can be engineeredin vivoto robustly secrete anti-HIV bNAbs in a safe, durable and scalable manner.
Exploration of the Ixodes ricinus virosphere unveils an extensive virus diversity including novel Coltiviruses and other reoviruses
Authors: Vanmechelen Bert , Merino Michelle , Vergote Valentijn , Laenen Lies , Thijssen Marijn , Martí-Carreras Joan , Claerebout Edwin , Maes Piet
Published: April 2021

Recent metagenomics studies have revealed several tick species to host a variety of previously undiscovered RNA viruses. Ixodes ricinus, which is known to be a vector for many viral, bacterial and protozoan pathogens, is the most prevalent tick species in Europe. For this study, we decided to investigate the virosphere of Belgian I. ricinus ticks. High-throughput sequencing of tick pools collected from six different sampling sites revealed the presence of viruses belonging to many different viral orders and families, including Mononegavirales, Bunyavirales, Partitiviridae and Reoviridae. Of particular interest was the detection of several new reoviruses, two of which cluster together with members of the genus Coltivirus. This includes a new strain of Eyach virus, a known causative agent of tick-borne encephalitis. All genome segments of this new strain are highly similar to those of previously published Eyach virus genomes, except for the fourth segment, encoding VP4, which is markedly more dissimilar, potentially indicating the occurrence of a genetic reassortment. Further PCR-based screening of over 230 tick pools for 14 selected viruses showed that most viruses could be found in all six sampling sites, indicating the wide spread of these viruses throughout the Belgian tick population. Taken together, these results illustrate the role of ticks as important virus reservoirs, highlighting the need for adequate tick control measures.
Genome-wide CRISPR activation screen identifies novel receptors for SARS-CoV-2 entry
Authors: Zhu Shiyou , Liu Ying , Zhou Zhuo , Zhang Zhiying , Xiao Xia , Liu Zhiheng , Chen Ang , Dong Xiaojing , Tian Feng , Chen Shihua , Xu Yiyuan , Wang Chunhui , Li Qiheng , Niu Xuran , Pan Qian , Du Shuo , Xiao Junyu , Wang Jianwei , Wei Wensheng
Published: April 2021

The ongoing pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been endangering worldwide public health and economy. SARS-CoV-2 infects a variety of tissues where the known receptor ACE2 is low or almost absent, suggesting the existence of alternative pathways for virus entry. Here, we performed a genome-wide barcoded-CRISPRa screen to identify novel host factors that enable SARS-CoV-2 infection. In addition to known host proteins, i.e. ACE2, TMPRSS2 and NRP1, we identified multiple host components, among which LDLRAD3, TMEM30A and CLEC4G were confirmed as functional receptors for SARS-CoV-2. All these membrane proteins bind directly to spike’s N-terminal domain (NTD). Their essential and physiological roles have all been confirmed in either neuron or liver cells. In particular, LDLRAD3 and CLEC4G mediate SARS-CoV-2 entry and infection in a fashion independent of ACE2. The identification of the novel receptors and entry mechanisms could advance our understanding of the multiorgan tropism of SARS-CoV-2, and may shed light on the development of the therapeutic countermeasures against COVID-19.