bluuebunny/crossref_metadata_2025_split huggingface dataset:
A late-stage assembly checkpoint of the human mitochondrial ribosome large subunit
Authors: Rebelo-Guiomar Pedro , Pellegrino Simone , Dent Kyle C. , Sas-Chen Aldema , Miller-Fleming Leonor , Garone Caterina , Haute Lindsey Van , Rogan Jack F. , Dinan Adam , Firth Andrew E. , Andrews Byron , Whitworth Alexander J. , Schwartz Schraga , Warren Alan J. , Minczuk Michal 
Published: June 2021

SUMMARYThe epitranscriptome plays a key regulatory role in cellular processes in health and disease, including ribosome biogenesis. Here, analysis of the human mitochondrial transcriptome shows that 2’-O-methylation is limited to residues of the mitoribosomal large subunit (mtLSU) 16S mt-rRNA, modified by MRM1, MRM2, and MRM3. Ablation of MRM2 leads to a severe impairment of the oxidative phosphorylation system, caused by defective mitochondrial translation and accumulation of mtLSU assembly intermediates. Structures of these particles (2.58 Å) present disordered RNA domains, partial occupancy of bL36m and bound MALSU1:L0R8F8:mtACP anti-association module. Additionally, we present five mtLSU assembly states with different intersubunit interface configurations. Complementation studies demonstrate that the methyltransferase activity of MRM2 is dispensable for mitoribosome biogenesis. The Drosophila melanogaster orthologue, DmMRM2, is an essential gene, with its knock-down leading to developmental arrest. This work identifies a key late-stage quality control step during mtLSU assembly, ultimately contributing to the maintenance of mitochondrial homeostasis.
The Brain Time Toolbox, a software library to retune electrophysiology data to brain dynamics
Authors: van Bree Sander , Melcón María , Kolibius Luca D. , Kerrén Casper , Wimber Maria , Hanslmayr Simon 
Published: June 2021

AbstractHuman thought is highly flexible, achieved by evolving patterns of brain activity across groups of cells. Neuroscience aims to understand cognition in the brain by analysing these intricate patterns. We argue this goal is impeded by the time format of our data – clock time. The brain is a system with its own dynamics and regime of time, with no intrinsic concern for the human-invented second. Here, we present the Brain Time Toolbox, a software library that retunes electrophysiology data in line with oscillations that orchestrate neural patterns of cognition. These oscillations continually slow down, speed up, and undergo abrupt changes, introducing a disharmony between the brain’s internal regime and clock time. The toolbox overcomes this disharmony by warping the data to the dynamics of coordinating oscillations, setting oscillatory cycles as the data’s new time axis. This enables the study of neural patterns as they unfold in the brain, aiding neuroscientific inquiry into dynamic cognition. In support of this, we demonstrate that the toolbox can reveal results that are absent in a default clock time format.
Molecular characterization of AMPA receptor trafficking vesicles
Authors: Peters John Jacob , Leitz Jeremy , Oses-Prieto Juan A , Burlingame Alma L , Brunger Axel T. 
Published: June 2021

AbstractRegulated delivery of AMPA receptors (AMPARs) to the postsynaptic membrane is an essential step in synaptic strength modification, and in particular, long-term potentiation (LTP). While LTP has been extensively studied using electrophysiology and light microscopy, several questions regarding the molecular mechanisms of AMPAR delivery via trafficking vesicles remain outstanding, including the gross molecular make up of AMPAR trafficking organelles and identification and location of calcium sensors required for SNARE complex-dependent membrane fusion of such trafficking vesicles with the plasma membrane. Here, we isolated AMPAR trafficking vesicles (ATVs) from whole mouse brains via immunoprecipitation and characterized them using immunoelectron microscopy, immunoblotting, and liquid chromatography tandem mass spectrometry (LC-MS/MS). We identified several proteins on ATVs that were previously found to play a role in AMPAR trafficking, including SNARES (including synaptobrevin 2), Rabs, the SM protein Munc18-1, a calcium-sensor (synaptotagmin-1), as well as several new markers, including synaptophysin and synaptogyrin on ATV membranes. Additionally, we identified two populations of ATVs based on size and molecular composition: small-diameter, synaptobrevin-2- and GluA1-containing ATVs and larger transferrin-receptor-, GluA1-, GluA2-, GluA3-containing ATVs. The smaller population of ATVs likely represents a trafficking vesicle whose fusion is essential for LTP. These findings reveal the important role of AMPAR sorting into fusion-competent trafficking vesicles that are implicated in synaptic strength modification and reveal candidates of putative effectors and regulators of AMPAR trafficking.
A robust field-based method to screen heat tolerance in wheat
Authors: Ullah Najeeb , Christopher Jack , Frederiks Troy , Ma Shangyu , Tan Daniel KY , Chenu Karine 
Published: June 2021

AbstractWheat is highly sensitive to elevated temperatures, particularly during pollen meiosis and early-to-mid grain filling. The impact of heat stress greatly depends on the plant developmental stage. Thus, germplasm ranking for heat tolerance in field trials may be confounded by variations in developmental phase between genotypes at the time of heat events. A photoperiod-extension method (PEM) was developed allowing screening of 35 diverse genotypes at matched developmental phase despite phenological variations. Paired trials were conducted to compare the new PEM against conventional field screening in plots. In the PEM, plants were sown in single rows or small plots. Artificial lighting was installed at one end of each row or plot to extend day length, inducing a gradient of flowering times with distance from the lights. Individual stems or plot quadrats of each genotype were tagged at flowering. Late-sown plants received more heat shocks during early to mid grain filling than earlier sowings, suffering reductions in both individual grain weight (IGW) and yield. IGW was reduced by 1.5 mg for each additional post-flowering day with temperature > 30°C. Significant genotypic differences in heat tolerance ranking were observed between PEM versus conventional plot screening. Strong correlations between trials experiencing similar degree of heat were found both for IGW and for total grain weight with the PEM either with individual-stem tagging (e.g. average r of 0.59 and 0.54, respectively for environments with moderate postflowering heat) or quadrat tagging (r of 0.53 and 0.47). However, correlations for IGW and yield in these environments were either poor or negative for conventional trials (e.g. average r of 0.11 and 0.12, respectively for environments with moderate postflowering heat). Accordingly, a PCA grouped genotypes consistently for heir performance across environments with similar heat stress in PEM trials but not in conventional trials. In this study, most consistent genotype ranking for heat tolerance was achieved with the PEM with tagging and harvesting individual spikes at matched developmental phase. The PEM with quadrat sampling provided slightly less consistent rankings but appears overall more suitable for high-throughput phenotyping. The method promises to improve the efficiency of heat tolerance field screening, particularly when comparing genotypes of different maturity types.
EPIC: inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencing
Authors: Wang Rujin , Lin Dan-Yu , Jiang Yuchao 
Published: June 2021

AbstractMore than a decade of genome-wide association studies (GWASs) have identified genetic risk variants that are significantly associated with complex traits. Emerging evidence suggests that the function of trait-associated variants likely acts in a tissue- or cell-type-specific fashion. Yet, it remains challenging to prioritize trait-relevant tissues or cell types to elucidate disease etiology. Here, we present EPIC (cEll tyPe enrIChment), a statistical framework that relates large-scale GWAS summary statistics to cell-type-specific gene expression measurements from single-cell RNA sequencing (scRNA-seq). We derive powerful gene-level test statistics for common and rare variants, separately and jointly, and adopt generalized least squares to prioritize trait-relevant cell types while accounting for the correlation structures both within and between genes. Using enrichment of loci associated with four lipid traits in the liver and enrichment of loci associated with three neurological disorders in the brain as ground truths, we show that EPIC outperforms existing methods. We apply our framework to multiple scRNA-seq datasets from different platforms and identify cell types underlying type 2 diabetes and schizophrenia. The enrichment is replicated using independent GWAS and scRNA-seq datasets and further validated using PubMed search and existing bulk case-control testing results.
Induce Pluripotency via Specific distal enhancer-promoter associations
Authors: Zhu Xiusheng , Huang Lei , Li Dongwei , Luo Jing , Huang Qitong , Wang Xueyan , Zhang Yubo 
Published: June 2021

AbstractInduced pluripotent stem cell (iPSC) technology promises to be an inexhaustible source of any type of cell needed for therapeutic and research purposes. It is unclear that how distal enhancer-promoter associations/ 3D chromatin conformation involving in the capacity of self-renewal and pluripotency maintenance. In this study, we have selected a few defined enhancer-promoter associations. After screening of enhancer specificity and activity individually, we design the different combinations and transfect these enhancers into the MEF cells. We simultaneously transfect 7 determined enhancers which represents various specific distal chromatin associations into a GFP tracing MEF cell line. We observe that the MEF cells start generating iPS-like clones at day 22. Importantly, our validations with three germ layer marker genes and in vitro experiments have further confirmed the pluripotency of these clones. Here, our study proposes a potential de novo method of a low-genetic risk iPS generation by introducing spatiotemporal distal chromatin associations. This result also paves out the way on utilizing 3D genomic information to alter cell identity and reprogramming for potential therapeutic strategy.
Monod model is insufficient to explain biomass growth in nitrogen-limited yeast fermentation
Authors: Henriques David , Balsa-Canto Eva 
Published: June 2021

AbstractThe yeastSaccharomyces cerevisiaeis an essential microorganism in food biotechnology; particularly, in wine and beer making. During wine fermentation, yeasts transform sugars present in the grape juice into ethanol and carbon dioxide. The process occurs in batch conditions and is, for the most part, an anaerobic process. Previous studies linked limited-nitrogen conditions with problematic fermentations, with negative consequences for the performance of the process and the quality of the final product. It is, therefore, of the highest interest to anticipate such problems through mathematical models. Here we propose a model to explain fermentations under nitrogen-limited anaerobic conditions. We separated the biomass formation into two phases: growth and carbohydrate accumulation. Growth was modelled using the well-known Monod equation while carbohydrate accumulation was modelled by an empirical function, analogous to a proportional controller activated by the limitation of available nitrogen. We also proposed to formulate the fermentation rate as a function of the total protein content when relevant data are available. The final model was used to successfully explain experiments taken from the literature, performed under normal and nitrogen-limited conditions. Our results revealed that Monod model is insufficient to explain biomass formation kinetics in nitrogen-limited fermentations ofS. cerevisiae. The goodness-of-fit of the herewith proposed model is superior to that of previously published models, offering the means to predict, and thus control fermentations.ImportanceProblematic fermentations still occur in the winemaking industrial practise. Problems include sluggish rates of fermentation, which have been linked to insufficient levels of assimilable nitrogen. Data and relevant models can help anticipate poor fermentation performance. In this work, we proposed a model to predict biomass growth and fermentation rate under nitrogen-limited conditions and tested its performance with previously published experimental data. Our results show that the well-known Monod equation does not suffice to explain biomass formation.
Fuzzy RNA-recognition by theTrypanosoma bruceieditosome
Authors: Leeder Wolf-Matthias , Göringer H. Ulrich 
Published: June 2021

AbstractThe recognition of RNA-molecules by proteins and protein complexes is a critical step on all levels of gene expression. Typically, the generated ribonucleoprotein complexes rely on the binary interaction of defined RNA-sequences or precisely folded RNA-motifs with dedicated RNA-binding domains on the protein side. Here we describe a new molecular recognition principle of RNA-molecules by a high molecular mass protein complex. By chemically probing the solvent accessibility of mitochondrial pre-mRNAs when bound to theTrypanosoma bruceieditosome we identified multiple similar but nonidentical RNA-motifs as editosome contact sites. However, by treating the different motifs as mathematical graph objects we demonstrate that they fit a consensus 2D-graph consisting of 4 vertices (V) and 3 edges (E) with a Laplacian eigenvalue of 0.523 (λ2). We establish that a synthetic 4V(3E)-RNA is sufficient to compete for the editosomal pre-mRNA binding site and that it is able to inhibit RNA-editingin vitro. Our analysis corroborates that the editosome has adapted to the structural multiplicity of the mitochondrial mRNA-folding space by recognizing a fuzzy continuum of RNA-folds that fit a consensus graph-descriptor. This provides a mechanism on how the protein complex is able to bind the structurally pleomorphic pool of pre- and partially edited mRNAs. We speculate that other fuzzy RNA-recognition motifs exist especially for proteins that interact with multiple RNA-species.
Psychophysical evidence and perceptual observations show that object recognition is not hierarchical but is a parallel, simultaneous, egalitarian, non-computational system
Authors: Gur Moshe 
Published: June 2021

AbstractObject recognition models have at their core similar essential characteristics: feature extraction and hierarchical convergence leading to a code that is unique to each object and immune to variations in the object appearance. To compare computational, biologically-feasible models to human performance, subjects viewed objects displayed at a wide range of orientations and sizes, and were able to recognize them almost perfectly. These empirical results, together with consideration of thought experiments and analysis of everyday perceptual performance, lead to a conclusion that biologically-plausible object perception models do not even come close to matching our perceptual abilities. We can categorize many thousands of objects, discriminate between enormous numbers of different exemplars within each category, and recognize an object as unique although it may appear in countless variations―most of which have never been seen. This seemingly technical, quantitative failure stems from a fundamental property of our perception: the ability to perceive spatial information instantaneously and in parallel, retain details including their relative properties, and yet be able to integrate details into a meaningful percept such as an object. I present an alternative view of object perception whereby objects are represented by responses in primary visual cortex (V1) which is the only cortical area responding to small spatial elements. The rest of the visual cortex is dedicated to scene understanding and interpretation such as constructing 3D percepts from 2D inputs, coding motion, categorization and memories. Since our perception abilities cannot be explained by convergence to “object cells” or by interactions implemented by axonal transmissions, a parallel-to-parallel field-like process is suggested. In this view, spatial information is not modified by multiple neural interactions but is retained by affecting changes in a “neural field” which preserves the identity of individual elements while enabling a new holistic percept when these elements change.
Computational inference, validation, and analysis of 5’UTR-leader sequences of alleles of immunoglobulin heavy chain variable genes
Authors: Huang Yixun , Thörnqvist Linnea , Ohlin Mats 
Published: June 2021

ABSTRACTUpstream and downstream sequences of immunoglobulin genes may affect the expression of such genes. However, these sequences are rarely studied or characterized in most studies of immunoglobulin repertoires. Inference from large, rearranged immunoglobulin transcriptome data sets offers an opportunity to define the upstream regions (5’-untranslated regions and leader sequences). We have now established a new data pre-processing procedure to eliminate artifacts caused by a 5’-RACE library generation process, reanalyzed a previously studied data set defining human immunoglobulin heavy chain genes, and identified novel upstream regions, as well as previously identified upstream regions that may have been identified in error. Upstream sequences were also identified for a set of previously uncharacterized germline gene alleles. Several novel upstream region variants were validated, for instance by their segregation to a single haplotype in heterozygotic subjects. SNPs representing several sequence variants were identified from population data. Finally, based on the outcomes of the analysis, we define a set of testable hypotheses with respect to the placement of particular alleles in complex IGHV locus haplotypes, and discuss the evolutionary relatedness of particular heavy chain variable genes based on sequences of their upstream regions.
Enteric glial cells favour accumulation of anti-inflammatory macrophages during the resolution of muscularis inflammation
Authors: Stakenborg Michelle , Abdurahiman Saeed , De Simone Veronica , Goverse Gera , Stakenborg Nathalie , van Baarle Lies , Wu Qin , Pirottin Dimitri , Kim Jung-Seok , Chappell-Maor Louise , Pintelon Isabel , Thys Sofie , Boon Louis , Hao Marlene , Van Ginderachter Jo A. , Boeckxstaens Guy E. , Timmermans Jean-Pierre , Jung Steffen , Marichal Thomas , Ibiza Sales , Matteoli Gianluca 
Published: June 2021

AbstractObjectiveMonocyte-derived macrophages (Mφs) are crucial regulators during muscularis inflammation. However, it is unclear which microenvironmental factors are responsible for monocyte recruitment and neurotrophic Mφ differentiation in this paradigm. Here, we investigate Mφ heterogeneity at different stages of muscularis inflammation and determine how environmental cues can attract and activate tissue protective Mφs.DesignSingle cell RNA sequencing was performed on immune cells from the muscularis of wild-type and CCR2-/- mice at different timepoints after muscularis inflammation. CX3CR1GFP/+ and CX3CR1CreERT2 R26YFP mice were analyzed by flow cytometry and immunofluorescence. The transcriptome of enteric glial cells (EGCs) was investigated using PLPCreERT2 Rpl22HA mice. In addition, we assessed the effect of supernatant from neurosphere-derived EGCs on monocyte differentiation based on the expression of pro- and anti-inflammatory factors.ResultsMuscularis inflammation induced marked alterations in mononuclear phagocyte populations associated with a rapid infiltration of Ly6c+ monocytes that locally acquired unique transcriptional states. Trajectory inference analysis revealed two main pro-resolving Mφ subpopulations during the resolution of muscularis inflammation, i.e. Cd206+ MhcIIhi and Timp2+ MhcIIlo Mφs, which were both derived from CCR2+ monocytes. Interestingly, we found that EGCs were able to sense damage to the muscularis to stimulate monocyte recruitment and differentiation towards pro-resolving Mφs via CCL2 and CSF1, respectively.ConclusionOur study provides a comprehensive insight into pro-resolving Mφ differentiation and their regulators during muscularis inflammation. We deepened our understanding in the interaction between EGCs and Mφs, thereby highlighting pro-resolving Mφ differentiation as a potential novel therapeutic strategy for the treatment of intestinal inflammation.
Ghrelin proteolysis by insulin-degrading enzyme
Authors: Bocach David D. , Jones Kierstin L. , Bell Jonathan M. , Zheng Qiuchen , Lazo Noel D. , Smith-Carpenter Jillian E. , Alper Benjamin J. 
Published: June 2021

AbstractHere we report proteolysis of synthetic acylated human ghrelin by recombinant human insulin-degrading enzyme (IDE). Kinetic parameters and sites of proteolytic cleavage were evaluated. Ghrelin proteolysis by IDE was inhibited by ethylenediaminetetraacetate (EDTA), a metal chelating agent. Ghrelin proteolysis appears at least somewhat specific to M16 family proteases such as IDE, as the M13 protease neprilysin (NEP) did not exhibit ghrelin proteolysis in this study. A quenched fluorogenic peptide substrate comprising the primary sites of IDE-mediated ghrelin proteolysis (Mca-QRVQQRKESKK(Dnp)-OH; Mca: 7-methoxycoumarin-3-carboxylic acid; Dnp: 2,4-dinitrophenyl) was developed and used to evaluate enzyme specificity and kinetic parameters of proteolysis. Like acyl ghrelin, Mca-QRVQQRKESKK(Dnp)-OH was efficiently cleaved by IDE central to the target sequence. We anticipate that this quenched fluorogenic peptide substrate will be of value to future studies of ghrelin proteolysis by IDE and potentially other peptidases.
CANT-HYD: A curated database of phylogeny-derived Hidden Markov Models for annotation of marker genes involved in hydrocarbon degradation
Authors: Khot Varada , Zorz Jackie , Gittins Daniel A. , Chakraborty Anirban , Bell Emma , Bautista María A. , Paquette Alexandre J. , Hawley Alyse K. , Novotnik Breda , Hubert Casey R. J. , Strous Marc , Bhatnagar Srijak 
Published: June 2021

ABSTRACTDiscovery of microbial hydrocarbon degradation pathways has traditionally relied on laboratory isolation and characterization of microorganisms. Although many metabolic pathways for hydrocarbon degradation have been discovered, the absence of tools dedicated to their annotation makes it difficult to identify the relevant genes and predict the hydrocarbon degradation potential of microbial genomes and metagenomes. Furthermore, sequence homology between hydrocarbon degradation genes and genes with other functions often results in misannotation. A tool that systematically identifies hydrocarbon metabolic potential is therefore needed. We present the Calgary approach to ANnoTating HYDrocarbon degradation genes (CANT-HYD), a database containing HMMs of 37 marker genes involved in anaerobic and aerobic degradation pathways of aliphatic and aromatic hydrocarbons. Using this database, we show that hydrocarbon metabolic potential is widespread in the tree of life and identify understudied or overlooked hydrocarbon degradation potential in many phyla. We also demonstrate scalability by analyzing large metagenomic datasets for the prediction of hydrocarbon utilization in diverse environments. To the best of our knowledge, CANT-HYD is the first comprehensive tool for robust and accurate identification of marker genes associated with aerobic and anaerobic hydrocarbon degradation.