bluuebunny/crossref_metadata_2025_split huggingface dataset:
Family-wide evaluation of RALF peptides inArabidopsis thaliana
Authors: Abarca Alicia , Franck Christina M. , Zipfel Cyril 
Published: June 2020

AbstractPlant peptide hormones are important players controlling various aspects of plants’ lives. RAPID ALKALINIZATION FACTOR (RALF) peptides have recently emerged as important players in multiple physiological processes. Numerous studies on RALF peptides focused on broad phylogenetic analysis including multiple species. Thus, progress has been made in understanding the evolutionary processes that shaped this family. Nevertheless, to date, there is no comprehensive, family-wide functional study on RALF peptides. Here, we analysed the phylogeny and function of the proposed multigenic RALF peptide family in the model plantArabidopsis thaliana, ecotype Col-0. Our phylogenetic analysis reveals that two of the previously proposed RALF peptides are not genuine RALF peptides, which leads us to propose a new consensusAtRALF peptide family annotation. Moreover, we show that the majority ofAtRALF peptides are able to induce seedling or root growth inhibition inA. thalianaseedlings when applied exogenously as synthetic peptides. Additionally, we show that most of these responses are dependent on theCatharanthus roseusRLK1-LIKE receptor kinase FERONIA, suggesting a pivotal role in the perception of multiple RALF peptides.One sentence summaryThe majority ofA. thalianaRALF peptides inhibit growth in a FERONIA-dependent manner
Genetic Variability affects the Skeletal Response to Unloading
Authors: Friedman Michael A. , Abood Abdullah , Senwar Bhavya , Zhang Yue , Maroni Camilla Reina , Ferguson Virginia L. , Farber Charles R. , Donahue Henry J. 
Published: June 2020

AbstractMechanical unloading decreases bone volume and strength. In humans and mice, bone mineral density is highly heritable, and in mice the response to changes in loading varies with genetic background. Thus, genetic variability may affect the response of bone to unloading. As a first step to identify genes involved in bone response to unloading, we evaluated the effects of unloading in eight inbred mouse strains: C57BL/6J, PWK/PhJ, WSB/EiJ, A/J, 129S1/SvImJ, NOD/ShiLtJ, NZO/HlLtJ, and CAST/EiJ. C57BL/6J and NOD/ShiLtJ mice had the greatest unloading induced loss of diaphyseal cortical bone volume and strength. NZO/HlLtJ mice had the greatest metaphyseal trabecular bone loss, and C57BL/6J, WSB/EiJ, NOD/ShiLtJ, and CAST/EiJ mice had the greatest epiphyseal trabecular loss. Bone loss in the epiphyses displayed the highest heritability. With immobilization, mineral:matrix was reduced, and carbonate:phosphate and crystallinity were increased. A/J mice displayed the greatest unloading induced loss of mineral:matrix. Changes in gene expression in response to unloading were greatest in NOD/ShiLtJ and CAST/EiJ mice. The most upregulated genes in response to unloading were associated with increased collagen synthesis and extracellular matrix formation. Our results demonstrate a strong differential response to unloading as a function of strain. Diversity outbred (DO) mice are a high-resolution mapping population derived from these eight inbred founder strains. These results suggest DO mice will be highly suited for examining the genetic basis of the skeletal response to unloading.
When killers become thieves: trogocytosed PD-1 inhibits NK cells in cancer
Authors: Hasim Mohammed S. , Marotel Marie , Hodgins Jonathan J. , Vulpis Elisabetta , Shih Han-Yun , Scheer Amit , MacMillan Olivia , Alonso Fernando G. , Burke Kelly P. , Cook David P. , Petrucci Maria Teresa , Santoni Angela , Fallon Padraic G. , Sharpe Arlene H. , Sciumè Giuseppe , Veillette Andre , Zingoni Alessandra , McCurdy Arleigh , Ardolino Michele 
Published: June 2020

AbstractLeucocytes often perform trogocytosis, the process by which cells acquire parts of the plasma membrane from interacting cells. Accumulating evidence indicates that trogocytosis modulates immune responses, but the underlying molecular mechanisms are unclear. Here, using two mouse models of leukemia, we found that cytotoxic lymphocytes perform trogocytosis at high rates with tumor cells. While performing trogocytosis, both Natural Killer and CD8+T cells acquire the checkpoint receptor PD-1 from leukemia cells. In vitro and in vivo investigation revealed that PD-1 protein found on the surface of Natural Killer cells, rather than being endogenously expressed, was derived entirely from leukemia cells. Mechanistically, SLAM receptors were essential for PD-1 trogocytosis. PD-1 acquired via trogocytosis actively suppressed anti-tumor immunity, as revealed by the positive outcome of PD-1 blockade in PD-1-deficient mice. PD-1 trogocytosis was corroborated in patients with clonal plasma cell disorders, where Natural Killer cells that stained for PD-1 also stained for tumor cell markers. Our results, in addition to shedding light on a previously unappreciated mechanism underlying the presence of PD-1 on Natural Killer and cytotoxic T cells, reveal the immune-regulatory effect of membrane transfer occurring when immune cells contact tumor cells.Once sentence summaryNatural Killer cells are inhibited by PD-1 acquired from the surface of tumor cells via trogocytosis.
A survey of pairwise epistasis supports an outside-in hierarchy of clade-specifying and function-defining residues in PSD95 PDZ3
Authors: Nedrud David , Coyote-Maestas Willow , Schmidt Daniel 
Published: June 2020

AbstractDeep mutational scanning enables data-driven models of protein structure and function. Here, we adapted Saturated Programmable Insertion Engineering as an economical and programmable deep mutational scanning technique. We validate this approach with an existing single mutant dataset in the PSD95 PDZ3 domain, and further characterize most pairwise double mutants to study how a mutation’s phenotype depends on mutations at other sites, a phenomenon called epistasis. We observe wide-spread proximal negative epistasis, which we attribute to mutations affecting thermodynamic stability, and strong long-range positive epistasis, which is enriched in an evolutionarily conserved and function-defining network of ‘sector’ and clade-specifying residues. Conditional neutrality of mutations in clade-specifying residues compensates for deleterious mutations in sector positions. This suggests an outside-in hierarchy of interactions through which positive epistasis between clade-specifying residues and the PDZ sector facilitated the evolutionary expansion and specialization of PDZ domains.
BERTology Meets Biology: Interpreting Attention in Protein Language Models
Authors: Vig Jesse , Madani Ali , Varshney Lav R. , Xiong Caiming , Socher Richard , Rajani Nazneen Fatema 
Published: June 2020

AbstractTransformer architectures have proven to learn useful representations for protein classification and generation tasks. However, these representations present challenges in interpretability. Through the lens of attention, we analyze the inner workings of the Transformer and explore how the model discerns structural and functional properties of proteins. We show that attention (1) captures the folding structure of proteins, connecting amino acids that are far apart in the underlying sequence, but spatially close in the three-dimensional structure, (2) targets binding sites, a key functional component of proteins, and (3) focuses on progressively more complex biophysical properties with increasing layer depth. We also present a three-dimensional visualization of the interaction between attention and protein structure. Our findings align with known biological processes and provide a tool to aid discovery in protein engineering and synthetic biology. The code for visualization and analysis is available athttps://github.com/salesforce/provis.
Integration of Machine Learning Improves the Prediction Accuracy of Molecular Modelling for M. jannaschii Tyrosyl-tRNA Synthetase Substrate Specificity
Authors: Duan Bingya , Sun Yingfei 
Published: June 2020

AbstractDesign of enzyme binding pocket to accommodate substrates with different chemical structure is a great challenge. Traditionally, thousands even millions of mutants have to be screened in wet-lab experiment to find a ligand-specific mutant and large amount of time and resources is consumed. To accelerate the screening process, here we propose a novel workflow through integration of molecular modeling and data-driven machine learning method to generate mutant libraries with high enrichment ratio for recognition of specific substrate. M. jannaschii tyrosyl-tRNA synthetase (Mj. TyrRS) is used as an example system to give a proof of concept since the sequence and structure of many unnatural amino acid specific Mj. TyrRS mutants have been reported. Based on the crystal structures of different Mj. TyrRS mutants and Rosetta modeling result, we find D158G/P is the critical residue which influences the backbone disruption of helix with residue 158-163. Our results show that compared with random mutation, Rosetta modeling and score function calculation can elevate the enrichment ratio of desired mutants by 2-fold in a test library having 687 mutants, while after calibration by machine learning model trained using known data of Mj. TyrRS mutants and ligand, the enrichment ratio can be elevated by 11-fold. This molecular modeling and machine learning-integrated workflow is anticipated to significantly benefit to the Mj. tyrRS mutant screening and substantially reduce the time and cost of web-lab experiment. Besides, this novel process will have broad application in the field of computational protein design.CCS Concepts• Applied computing • Life and medical sciences • Computational biology • Molecular structural biology
Host immunity alters successional ecology and stability of the microbiome in a C. elegans model
Authors: Taylor Megan , Vega NM 
Published: June 2020

AbstractA growing body of data suggests that the microbiome of a species can vary considerably from individual to individual, but the reasons for this variation - and the consequences for the ecology of these communities – remain only partially explained. In mammals, the emerging picture is that the metabolic state and immune system status of the host affects the composition of the microbiome, but quantitative ecological microbiome studies are challenging to perform in higher organisms. Here we show that these phenomena can be quantitatively analyzed in the tractable nematode hostCaenorhabditis elegans. Mutants in innate immunity, in particular the DAF-2/Insulin Growth Factor (IGF) pathway, are shown to contain a microbiome that differs from that of wild type nematodes. We analyze the underlying basis of these differences from the perspective of community ecology by comparing experimental observations to the predictions of a neutral sampling model and conclude that fundamental differences in microbiome ecology underlie the observed differences in microbiome composition. We test this hypothesis by introducing a minor perturbation to the colonization conditions, allowing us to assess stability of communities in different host strains. Our results show that altering host immunity changes the importance of inter-species interactions within the microbiome, resulting in differences in community composition and stability that emerge from these differences in host-microbe ecology.ImportanceHere we use aCaenorhabditis elegansmicrobiome model to demonstrate how genetic differences in innate immunity alter microbiome composition, diversity, and stability by changing the ecological processes that shape these communities. These results provide insight into the role of host genetics in controlling the ecology of host-associated microbiota, resulting in differences in community composition, successional trajectories, and response to perturbation.
Pectin induced colony expansion of soil-derived Flavobacterium strains
Authors: Kraut-Cohen Judith , Shapiro Orr H. , Dror Barak , Cytryn Eddie 
Published: June 2020

AbstractThe genusFlavobacteriumis characterized by the capacity to metabolize complex organic compounds and a unique gliding motility mechanism. They are often abundant in root microbiomes of various plants, but the factors contributing to this high abundance are currently unknown. In this study, we evaluated the effect of various plant-associated poly- and mono-saccharides on colony expansion of twoFlavobacteriumstrains. Both strains were able to spread on pectin and other polysaccharides such as microcrystalline cellulose. However, only pectin (but not pectin monomers), a component of plant cell walls, enhanced colony expansion on solid surfaces in a dose- and substrate-dependent manner. On pectin, flavobacteria exhibited bi-phasic motility, with an initial phase of rapid expansion, followed by growth within the colonized area. Proteomic and gene expression analyses revealed significant induction of carbohydrate metabolism related proteins when flavobacteria were grown on pectin, including selected SusC/D, TonB-dependent glycan transport operons. Our results show a positive correlation between colony expansion and the upregulation of proteins involved in sugar uptake, suggesting an unknown linkage between specific operons encoding for glycan uptake and metabolism and flavobacterial expansion. Furthermore, within the context of flavobacterial-plant interactions, they suggest that pectin may facilitate flavobacterial expansion on plant surfaces in addition to serving as an essential carbon source.Contribution to the field statementMembers of theFlavobacteriumgenus are frequently rhizosphere competent,i.e.abundant and generally enriched on root surfaces relative to surrounding bulk soil, and previous studies suggest that they may play a role in plant health and ecosystem functioning. However, little is known about genetic and physiological factors that facilitate flavobacterial colonization and proliferation in this highly competitive environment.In this study we found that pectin stimulates flavobacterial colonies in a bi-phasic manner, initially characterized by rapid expansion on agar followed by increased biomass production. This appears to be linked to pectin-stimulated induction of specific TonB-associated proteins evidentially involved in the binding and uptake of complex sugars. Given the fact that pectin and other glycans are a primary component of plant cell walls, we hypothesize that these mechanisms are at least partially responsible for the rhizosphere competence of flavobacteria.
Prevalence of SARS-CoV-2 among workers returning to Bihar gives snapshot of COVID across India
Authors: Malani Anup , Mohanan Manoj , Kumar Chanchal , Kramer Jake , Tandel Vaidehi 
Published: June 2020

AbstractIndia has reported the fourth highest number of confirmed SARS-CoV-2 cases worldwide. Because there is little community testing for COVID, this case count is likely an underestimate. When India partially exited from lockdown on May 4, 2020, millions of daily laborers left cities for their rural family homes. RNA testing on a near-random sample of laborers returning to the state of Bihar is used to estimate positive testing rate for COVID across India for a 6-week period immediately following the initial lifting of India’s lockdown. Positive testing rates among returning laborers are only moderately correlated with, and 21% higher than, Indian states’ official reports, which are not based on random sampling. Higher prevalence among returning laborers may also reflect greater COVID spread in crowded poor communities such as slums.
Sex, age, and hospitalization drive antibody responses in a COVID-19 convalescent plasma donor population
Authors: Klein Sabra L. , Pekosz Andrew , Park Han-Sol , Ursin Rebecca L. , Shapiro Janna R. , Benner Sarah E. , Littlefield Kirsten , Kumar Swetha , Naik Harnish Mukesh , Betenbaugh Michael J. , Shrestha Ruchee , Wu Annie A. , Hughes Robert M. , Burgess Imani , Caturegli Patricio , Laeyendecker Oliver , Quinn Thomas C. , Sullivan David , Shoham Shmuel , Redd Andrew D. , Bloch Evan M. , Casadevall Arturo , Tobian Aaron A.R. 
Published: June 2020

AbstractConvalescent plasma is currently one of the leading treatments for COVID-19, but there is a paucity of data identifying therapeutic efficacy. A comprehensive analysis of the antibody responses in potential plasma donors and an understanding of the clinical and demographic factors that drive variant antibody responses is needed. Among 126 potential convalescent plasma donors, the humoral immune response was evaluated by a SARS-CoV-2 virus neutralization assay using Vero-E6-TMPRSS2 cells, commercial IgG and IgA ELISA to Spike (S) protein S1 domain (Euroimmun), IgA, IgG and IgM indirect ELISAs to the full-length S or S-receptor binding domain (S-RBD), and an IgG avidity assay. Multiple linear regression and predictive models were utilized to assess the correlations between antibody responses with demographic and clinical characteristics. IgG titers were greater than either IgM or IgA for S1, full length S, and S-RBD in the overall population. Of the 126 plasma samples, 101 (80%) had detectable neutralizing titers. Using neutralization titer as the reference, the sensitivity of the IgG ELISAs ranged between 95-98%, but specificity was only 20-32%. Male sex, older age, and hospitalization with COVID-19 were all consistently associated with increased antibody responses across the serological assays. Neutralizing antibody titers were reduced over time in contrast to overall antibody responses. There was substantial heterogeneity in the antibody response among potential convalescent plasma donors, but sex, age and hospitalization emerged as factors that can be used to identify individuals with a high likelihood of having strong antiviral antibody levels.One Sentence SummaryThere is substantial heterogeneity in the antibody response to SARS-CoV-2 infection, with greater antibody responses being associated with male sex, advancing age, and hospitalization with COVID-19.
Secondary pneumonia in critically ill ventilated patients with COVID-19
Authors: Maes Mailis , Higginson Ellen , Pereira-Dias Joana , Curran Martin , Parmar Surendra , Khokhar Fahad , Cuchet-Lourenço Delphine , Lux Janine , Sharma-Hajela Sapna , Ravenhill Benjamin , Mahroof Razeen , Solderholm Amelia , Forrest Sally , Sridhar Sushmita , Brown Nicholas , Baker Stephen , Navapurkar Vilas , Dougan Gordon , Scott Josefin Bartholdson , Conway Morris Andrew 
Published: June 2020

AbstractBackgroundPandemic COVID-19 caused by the coronavirus SARS-CoV-2 has a high incidence of patients with severe acute respiratory syndrome (SARS). Many of these patients require admission to an intensive care unit (ICU) for invasive artificial ventilation and are at significant risk of developing a secondary, ventilator-associated pneumonia (VAP).ObjectivesTo study the incidence of VAP, as well as differences in secondary infections, and bacterial lung microbiome composition of ventilated COVID-19 and non-COVID-19 patients.MethodsIn this prospective observational study, we compared the incidence of VAP and secondary infections using a combination of a TaqMan multi-pathogen array and microbial culture. In addition, we determined the lung microbime composition using 16S RNA analyisis. The study involved eighteen COVID-19 and seven non-COVID-19 patients receiving invasive ventilation in three ICUs located in a single University teaching hospital between April 13th2020 and May 7th2020.ResultsWe observed a higher percentage of confirmed VAP in COVID-19 patients. However, there was no statistical difference in the detected organisms or pulmonary microbiome when compared to non-COVID-19 patients.ConclusionCOVID-19 makes people more susceptible to developing VAP, partly but not entirely due to the increased duration of ventilation. The pulmonary dysbiosis caused by COVID-19, and the array of secondary infections observed are similar to that seen in critically ill patients ventilated for other reasons.
Nowcasting the COVID–19 pandemic in Bavaria
Authors: Günther Felix , Bender Andreas , Katz Katharina , Küchenhoff Helmut , Höhle Michael 
Published: June 2020

AbstractTo assess the current dynamic of an epidemic it is central to collect information on the daily number of newly diseased cases. This is especially important in real-time surveillance, where the aim is to gain situational awareness, e.g., if cases are currently increasing or decreasing. Reporting delays between disease onset and case reporting hamper our ability to understand the dynamic of an epidemic close to now when looking at the number of daily reported cases only. Nowcasting can be used to adjust daily case counts for occurred-but-not-yet-reported events. Here, we present a novel application of nowcasting to data on the current COVID–19 pandemic in Bavaria. It is based on a hierarchical Bayesian model that considers changes in the reporting delay distribution over time and associated with the weekday of reporting. Furthermore, we present a way to estimate the effective time-dependent case reproduction number Re(t) based on predictions of the nowcast. The approaches are based on previously published work, that we considerably extended and adapted to the current task of nowcasting COVID–19 cases. We provide methodological details of the developed approach, illustrate results based on data of the current epidemic, and evaluate the model based on synthetic and retrospective data on COVID–19 in Bavaria. Results of our nowcasting are reported to the Bavarian health authority and published on a webpage on a daily basis (https://corona.stat.uni-muenchen.de/). Code and synthetic data for the analysis is available from https://github.com/FelixGuenther/nc_covid19_bavaria and can be used for adaptions of our approach to different data.
Time in treatment: Examining mental illness trajectories across inpatient psychiatric treatment
Authors: Oh Hyuntaek , Lee Jaehoon , Kim Seungman , Rufino Katrina A. , Fonagy Peter , Oldham John M. , Schanzer Bella , Patriquin Michelle A. 
Published: June 2020

AbstractEarly discharge or reduced length of stay for inpatient psychiatric patients is related to increased readmission rates and worse clinical outcomes including increased risk for suicide. Trajectories of mental illness outcomes have been identified as an important method for predicting the optimal length of stay but the distinguishing factors that separate trajectories remain unclear. We sought to identify the distinct classes of patients who demonstrated similar trajectories of mental illness over the course of inpatient treatment, and we explore the patient characteristics associated with these mental illness trajectories. We used data (N= 3,406) from an inpatient psychiatric hospital with intermediate lengths of stay. Using growth mixture modeling, latent mental illness scores were derived from six mental illness indicators: psychological flexibility, emotion regulation problems, anxiety, depression, suicidal ideation, and disability. The patients were grouped into three distinct trajectory classes: (1) High-Risk, Rapid Improvement (HR-RI); (2) Low-Risk, Gradual Improvement (LR-GI); and (3) High-Risk, Gradual Improvement (HR-GI). The HR-GI was significantly younger than the other two classes. The HR-GI had significantly more female patients than males, while the LR-GI had more male patients than females. Our findings indicated that younger females had more severe mental illness at admission and only gradual improvement during the inpatient treatment period, and they remained in treatment for longer lengths of stay, than older males.