bluuebunny/crossref_metadata_2025_split huggingface dataset:
The salivary and nasopharyngeal microbiomes are associated with SARS-CoV-2 infection and disease severity
Authors: Kim Josh G. , Zhang Ai , Rauseo Adriana M. , Goss Charles W. , Mudd Philip A. , O’Halloran Jane A. , Wang Leyao 
Published: June 2022

AbstractOral and upper respiratory microbiota play important roles in modulating host immune responses to viral infection. As emerging evidence suggests the host microbiome may be involved in the pathophysiology of COVID-19, we aimed to investigate associations between the oral and nasopharyngeal microbiome and COVID-19 severity. We collected saliva (n = 78) and nasopharyngeal swab (n = 66) samples from a COVID-19 cohort and characterized the microbiomes using 16S ribosomal RNA gene sequencing. We also examined associations between the salivary and nasopharyngeal microbiome and age, COVID-19 symptoms, and blood cytokines. SARS-CoV-2 infection status, but not COVID-19 severity, was associated with community-level differences in the oral and nasopharyngeal microbiomes. Salivary and nasopharyngeal microbiome alpha diversity negatively correlated with age and were associated with fever and diarrhea. Several bacterial genera were differentially abundant by COVID-19 severity, including oral Bifidobacterium, Lactobacillus, and Solobacterium, all of which were depleted in patients with severe COVID-19. Nasopharyngeal Paracoccus was depleted while nasopharyngeal Proteus, Cupravidus, and Lactobacillus were increased in patients with severe COVID-19. Further analysis revealed that the abundance of oral Bifidobacterium was negatively associated with plasma concentrations of known COVID-19 biomarkers interleukin 17F (IL-17F) and monocyte chemoattractant protein-1 (MCP-1). In conclusion, our results suggest COVID-19 disease severity is associated with the relative abundance of certain bacterial taxa.
On the interpretation of the operation of natural selection in class-structured populations
Authors: Priklopil Tadeas , Lehmann Laurent 
Published: June 2022

AbstractBiological adaptation is the outcome of allele-frequency change by natural selection. At the same time, populations are usually class structured as individuals occupy different states such as age, sex, or stage. This is known to result in the differential transmission of alleles through non-heritable fitness differences called class transmission, also affecting allele-frequency change even in the absence of selection. How does one then isolate the allele-frequency change due to selection from that owing to class transmission? We decompose one-generational allele-frequency change in terms of effects of selection and class transmission, and show how reproductive values can be used to reach a decomposition between any two distant generations of the evolutionary process. This provides a missing relationship between multigenerational allele-frequency change and the operation of selection. It also allows to define a measure of fitness summarizing the effect of selection in a multigenerational evolutionary process, which connects asymptotically to invasion fitness.
Inflammation and neuronal gene expression changes differ in early vs late chronic traumatic encephalopathy brain
Authors: Labadorf Adam , Agus Filisia , Aytan Nurgul , Cherry Jonathan , Mez Jesse , McKee Ann , Stein Thor D. 
Published: June 2022

ABSTRACTOur understanding of the molecular underpinnings of chronic traumatic encephalopathy (CTE) and its associated pathology in post-mortem brain is incomplete. Factors including years of play and genetic risk variants influence the extent of tau pathology associated with disease expression, but how these factors affect gene expression, and whether those effects are consistent across the development of disease, is unknown. To address these questions, we conducted an analysis of the largest mRNASeq whole-transcriptome dataset available to date. We examined the genes and biological processes associated with disease by comparing individuals with CTE with control individuals with a history of repetitive head impacts that lack CTE pathology. We then identified genes and biological processes associated with total years of play as a measure of exposure, amount of tau pathology present at time of death, and the presence of APOE and TMEM106B risk variants. Samples were stratified into low and high pathology groups based on extent of tau pathology and years of play to model early vs late changes in response to exposure, and the relative effects associated with these factors were compared between these groups. Substantial gene expression changes were associated with severe disease for most of these factors, primarily implicating diverse, highly increased neuroinflammatory and neuroimmune processes. In contrast, low exposure groups had many fewer genes and processes implicated and show striking differences for some factors when compared with severe disease. Specifically, gene expression associated with amount of tau pathology showed a nearly perfect inverse relationship when compared between these two groups. Together, these results suggest the early disease process may differ substantially from that observed in late stages, that total years of play and tau pathology influence disease expression differently, and that related pathology-modifying risk variants may do so via distinct biological pathways.
The PilT retraction ATPase promotes both extension and retraction of the MSHA type IVa pilus inVibrio cholerae
Authors: Hughes Hannah Q. , Christman Nicholas D. , Dalia Triana N. , Ellison Courtney K. , Dalia Ankur B. 
Published: June 2022

ABSTRACTDiverse bacterial species use type IVa pili (T4aP) to interact with their environments. The dynamic extension and retraction of T4aP is critical for their function, but the mechanisms that regulate this dynamic activity remain poorly understood. T4aP are typically extended via the activity of a dedicated extension motor ATPase and retracted via the action of an antagonistic retraction motor ATPase called PilT. These motors are generally functionally independent, and loss of PilT commonly results in T4aP hyperpiliation due to undeterred pilus extension.However, for the mannose-sensitive hemagglutinin (MSHA) T4aP ofVibrio cholerae, the loss of PilT results in a loss of surface piliation, which is unexpected based on our current understanding of T4aP dynamics. Here, we employ a combination of genetic and cell biological approaches to dissect the underlying mechanism. Our results demonstrate that PilT is necessary for MSHA pilus extension in addition to its well-established role in promoting MSHA pilus retraction. Through a suppressor screen, we also provide genetic evidence that the MshA major pilin impacts pilus extension. Together, these findings contribute to our understanding of the factors that regulate pilus extension and describe a previously uncharacterized function for the PilT motor ATPase.AUTHOR SUMMARYMany bacteria use filamentous appendages called type IVa pili to interact with their environment. These fibers dynamically extend and retract through the activity of ATPase motor proteins. In most pilus systems, deletion of the retraction motor results in uninterrupted pilus extension, leading to hyperpiliation. However, in the MSHA pilus system ofV. cholerae, deletion of the retraction motor,pilT, results in a decrease in the number of surface pili. Here, we show that PilT is unexpectedly required for MSHA pilus extension in addition to its defined role in promoting pilus retraction. These results extend our understanding of the complex mechanisms underlying the dynamic activity of these broadly conserved filamentous appendages.
Impact of glycoengineering and immunogenicity on the anti-cancer activity of a plant-made lectin-Fc fusion protein
Authors: Dent Matthew , Mayer Katarina L. , Garcia Noel Verjan , Guo Haixun , Kajiura Hiroyuki , Fujiyama Kazuhito , Matoba Nobuyuki 
Published: June 2022

ABSTRACTPlants are an efficient production platform for manufacturing glycoengineered monoclonal antibodies and antibody-like molecules. Avaren-Fc (AvFc) is a lectin-Fc fusion protein or lectibody produced in Nicotiana benthamiana, which selectively recognizes cancer-associated high-mannose glycans. In this study, we report the generation of a glycovariant of AvFc that is devoid of plant glycans, including the core α1,3-fucose and β1,2-xylose residues. The successful removal of these glycans was confirmed by glycan analysis using HPLC. This variant, AvFcΔXF, has significantly higher affinity for Fc gamma receptors and induces higher levels of luciferase expression in an antibody-dependent cell-mediated cytotoxicity (ADCC) reporter assay against B16F10 murine melanoma cells without inducing apoptosis or inhibiting proliferation. In the B16F10 flank tumor mouse model, we found that systemic administration of AvFcΔXF, but not an aglycosylated AvFc variant lacking affinity for Fc receptors, significantly delayed the growth of tumors, suggesting that Fc-mediated effector functions were integral. AvFcΔXF treatment also significantly reduced lung metastasis of B16F10 upon intravenous challenge whereas a sugar-binding-deficient mutant failed to show efficacy. Lastly, we determined the impact of anti-drug antibodies (ADAs) on drug activity in vivo by pretreating animals with AvFcΔXF before implanting tumors. Despite a significant ADA response induced by the pretreatment, we found that the activity of AvFcΔXF was unaffected by the presence of these antibodies. These results demonstrate that glycoengineering is a powerful strategy to enhance AvFc’s antitumor activity.
Physical and functional convergence of the autism risk genesScn2aandAnk2in neocortical pyramidal cell dendrites
Authors: Nelson Andrew D. , Catalfio Amanda M. , Gupta Julie M. , Min Lia , Caballero-Floran Rene N. , Dean Kendall P. , Elvira Carina C. , Derderian Kimberly D. , Kyoung Henry , Sahagun Atehsa , Sanders Stephan J. , Bender Kevin J. , Jenkins Paul M. 
Published: June 2022

ABSTRACTDysfunction in sodium channels and their ankyrin scaffolding partners have both been implicated in neurodevelopmental disorders, including autism spectrum disorder (ASD). In particular, the genes SCN2A, which encodes the sodium channel NaV1.2, and ANK2, which encodes ankyrin-B, have strong ASD association. Recent studies indicate that ASD-associated haploinsufficiency in Scn2a impairs dendritic excitability and synaptic function in neocortical pyramidal cells, but how NaV1.2 is anchored within dendritic regions is unknown. Here, we show that ankyrin-B is essential for scaffolding NaV1.2 to the dendritic membrane of mouse neocortical neurons, and that haploinsufficiency of Ank2 phenocopies intrinsic dendritic excitability and synaptic deficits observed in Scn2a+/- conditions. Thus, these results establish a direct, convergent link between two major ASD risk genes and reinforce an emerging framework suggesting that neocortical pyramidal cell dendritic dysfunction can be etiological to neurodevelopmental disorder pathophysiology.
Experimental Test of the Contributions of Initial Variation and New Mutations to Adaptive Evolution in a Novel Environment
Authors: Izutsu Minako , Lenski Richard E. 
Published: June 2022

ABSTRACTExperimental evolution is an approach that allows researchers to study organisms as they evolve in controlled environments. Despite the growing popularity of this approach, there are conceptual gaps among projects that use different experimental designs. One such gap concerns the contributions to adaptation of genetic variation present at the start of an experiment and that of new mutations that arise during an experiment. The primary source of genetic variation has historically depended largely on the study organisms. In the long-term evolution experiment (LTEE) using Escherichia coli, for example, each population started from a single haploid cell, and therefore adaptation depended entirely on new mutations. Most other microbial evolution experiments have followed the same strategy. By contrast, evolution experiments using multicellular, sexually-reproducing organisms typically start with pre-existing variation that fuels the response to selection. New mutations may also come into play in later generations of these experiments, but it is generally difficult to quantify their contribution in these studies. Here, we performed an experiment using E. coli to compare the contributions of initial genetic variation and new mutations to adaptation in a new environment. Our experiment had four treatments that varied in their starting diversity, with 18 populations in each treatment. One treatment depended entirely on new mutations, while the other three began with mixtures of clones, whole-population samples, or mixtures of whole-population samples from the LTEE. By tracking genetic markers associated with particular founders in two of our treatments, we could document the impact of the initial variation during the early generations of our experiment. However, there were no differences in fitness among the treatments after 500 or 2000 generations in the new environment, despite the variation in fitness among the founders. These results indicate that new mutations quickly overcame, and eventually contributed more to adaptation, than did the initial variation. Our study thus shows that pre-existing genetic variation can have a strong impact on early evolution in a new environment, but new beneficial mutations may contribute more to later evolution and can even drive some initially beneficial variants to extinction.
Multi-Agent Reinforcement Learning-based Adaptive Sampling for Conformational Sampling of Proteins
Authors: Kleiman Diego E. , Shukla Diwakar 
Published: June 2022

AbstractMachine Learning is increasingly applied to improve the efficiency and accuracy of Molecular Dynamics (MD) simulations. Although the growth of distributed computer clusters has allowed researchers to obtain higher amounts of data, unbiased MD simulations have difficulty sampling rare states, even under massively parallel adaptive sampling schemes. To address this issue, several algorithms inspired by reinforcement learning (RL) have arisen to promote exploration of the slow collective variables (CVs) of complex systems. Nonetheless, most of these algorithms are not well-suited to leverage the information gained by simultaneously sampling a system from different initial states (e.g., a protein in different conformations associated with distinct functional states). To fill this gap, we propose two algorithms inspired by multi-agent RL that extend the functionality of closely-related techniques (REAP and TSLC) to situations where the sampling can be accelerated by learning from different regions of the energy landscape through coordinated agents. Essentially, the algorithms work by remembering which agent discovered each conformation and sharing this information with others at the action-space discretization step. Astakes functionis introduced to modulate how different agents sense rewards from discovered states of the system. The consequences are threefold: (i) agents learn to prioritize CVs using only relevant data, (ii) redundant exploration is reduced, and (iii) agents that obtain higher stakes are assigned more actions. We compare our algorithm with other adaptive sampling techniques (Least Counts, REAP, TSLC, and AdaptiveBandit) to show and rationalize the gain in performance.
Can Membrane Composition Traffic Toxins? Mycolactone and Preferential Membrane Interactions
Authors: da Hora Gabriel C. A. , Nguyen John D. M. , Swanson Jessica M. J. 
Published: June 2022

ABSTRACTMycolactone is a cytotoxic and immunosuppressive macrolide produced byMycobacterium ulceransand the sole causative agent of the neglected tropical skin disease Buruli ulcer. The toxin acts by invading host cells and interacting with intracellular targets to disrupt multiple fundamental cellular processes. Mycolactone’s amphiphilic nature enables strong interactions with lipophilic environments, including cellular membranes; however, the specificity of these interactions and the role of membranes in the toxin’s pathogenicity remain unknown. It is likely that preferential interactions with lipophilic carriers play a key role in the toxin’s distribution in the host, which, if understood, could provide insights to aid in the development of needed diagnostics for Buruli ulcer disease. In this work, molecular dynamics simulations were combined with enhanced free energy sampling to characterize mycolactone’s association with and permeation through models of the mammalian endoplasmic reticulum (ER) and plasma membranes (PM). We find that increased order in the PM not only leads to a different permeation mechanism compared to that in the ER membrane, but also an energetic driving force for ER localization. Increased hydration, membrane deformation, and preferential interactions with unsaturated lipid tails stabilize the toxin in the ER membrane, while disruption of lipid packing is a destabilizing force in the PM.STATEMENT OF SIGNIFICANCEMycolactone is sole the causative agent of Buruli ulcer, a neglected tropical disease involving large necrotic lesions that can cause permanent disfigurement if left untreated. Due to its amphiphilic nature, the toxin hides from traditional diagnostic detection and the host immune system by associating with lipophilic carriers, including cellular membranes. Our work uses extensive all-atom simulations to query if the toxin has preferential interactions with different types of membranes. We find a clear preference for more disordered membranes, like the endoplasmic reticulum’s, via interactions with unsaturated lipid tails and membrane deformation. The revealed insights can be used to predict host cell distribution between different types of lipophilic carriers and to aid in the design of Buruli ulcer diagnostics.
Retractions and rewards in science: An open question for reviewers and funders
Authors: Ribeiro Mariana D , Kalichman M , Vasconcelos Sonia MR 
Published: June 2022

AbstractIn recent years, the changing landscape for the conduct and assessment of research and of researchers has increased scrutiny of the reward systems of science. In this context, correcting the research record, including retractions, has gained attention and space in the publication system. One question is the possible influence of retractions on the careers of scientists. It might be assessed, for example, through citation patterns or productivity rates for authors who have had one or more retractions. This is an emerging issue today, with growing discussions in the research community about impact. We have explored the influence of retractions on grant review criteria. Here, we present results of a qualitative study exploring the views of a group of six representatives of funding agencies from different countries and of a follow-up survey of 224 reviewers in the US. These reviewers have served on panels for the National Science Foundation, the National Institutes of Health, and/or a few other agencies. We collected their perceptions about the influence of self-correction of the literature and of retractions on grant decisions. Our results suggest that correcting the research record, for honest error or misconduct, is perceived as an important mechanism to strengthen the reliability of science, among most respondents. However, retractions and self-correcting the literature at large are not factors influencing grant review, and dealing with retractions in reviewing grants is an open question for funders.
Lipid-mediated dimerization of membrane-anchored c-Src is driven by a cluster of lysine residues in the N-terminal SH4 domain
Authors: Mohammad Irrem-Laareb , Carvajal Javier , Fernández Alejandro , Taulés Marta , Fourgous Elise , Boublik Yvan , Le Roux Anabel-Lise , Roche Serge , Pons Miquel 
Published: June 2022

AbstractThe membrane-anchored c-Src tyrosine kinase mediates signaling from a wide range of cell surface receptors controlling cell growth, adhesion, and survival. c-Src deregulation is associated with cancer. Dimerization appears to be a novel layer of regulation through a yet unclear mechanism. Binding of c-Src tyrosine kinase to the plasma membrane is mediated by the myristoylated and strongly positively charged N-terminal SH4 domain. Although activation of c-Src is known to require phosphorylation by a second c-Src molecule, electrostatic repulsion between the charged residues was considered to prevent dimerization. Here we show that a cluster of positively charged lysine residues in c-Src SH4 domain not only does not prevent dimerization but, in fact, enhances it through a lipid-mediated process. Dimerization not only depends on the number of positive charges but also on their position and the nature of the charged residues. Replacement of lysine by arginine increases dimerization in vitro and in vivo and, in HEK293T cells, causes a two-fold increase in tyrosine phosphorylation. Lipid mediated protein-protein interactions induced by clusters of basic residues may represent a general mechanism for modulating cell signaling, consistent with the abundance of positively charged residues in the juxta membrane region of many signaling proteins.
A Poisson reduced-rank regression model for association mapping in sequencing data
Authors: Fitzgerald Tiana , Jones Andrew , Engelhardt Barbara E. 
Published: June 2022

AbstractSingle-cell RNA sequencing (scRNA-seq) technologies allow for the study of gene expression in individual cells. Often, it is of interest to understand how transcriptional activity is associated with cell-specific covariates, such as cell type, genotype, or measures of cell health. Traditional approaches for this type of association mapping assume independence between the outcome variables (or genes), and perform a separate regression for each. However, these methods are computationally costly and ignore the substantial correlation structure of gene expression. Furthermore, count-based scRNA-seq data pose challenges for traditional models based on Gaussian assumptions. We aim to resolve these issues by developing a reduced-rank regression model that identifies low-dimensional linear associations between a large number of cell-specific covariates and high-dimensional gene expression readouts. Our probabilistic model uses a Poisson likelihood in order to account for the unique structure of scRNA-seq counts. We demonstrate the performance of our model using simulations, and we apply our model to a scRNA-seq dataset, a spatial gene expression dataset, and a bulk RNA-seq dataset to show its behavior in three distinct analyses. We show that our statistical modeling approach, which is based on reduced-rank regression, captures associations between gene expression and cell- and sample-specific covariates by leveraging low-dimensional representations of transcriptional states.