bluuebunny/crossref_metadata_2025_split huggingface dataset:
The first horse gut microbiome gene catalog reveals that rare microbiome ensures better cardiovascular fitness in endurance horses
Authors: Mach Núria , Midoux Cédric , Leclercq Sébastien , Pennarun Samuel , Le Moyec Laurence , Rué Olivier , Robert Céline , Sallé Guillaume , Barrey Eric 
Published: January 2022

ABSTRACTEmerging evidence indicates that the gut microbiome contributes to endurance exercise performance, but the extent of their functional and metabolic potential remains unknown. Using elite endurance horses as a model system for exercise responsiveness, we built the first equine gut microbial gene catalog comprising more than 25 million non-redundant genes representing 4,696 genera spanning 95 phyla. The unprecedented resolution unrevealed functional pathways relevant for both the structure of the microbiome and the host health and recovered 369 novel metagenome-assembled bacterial genomes, providing useful reference for future studies. Integration of microbial and host omic datasets suggested that microbiomes harboring rare species were functionally dissimilar from those enriched in Lachnospiraceae taxa. Moreover, they offered expanded metabolic pathways to fine-tune the cardiovascular capacity through mitochondria-mediated mechanisms. The results identify an associative link between horse endurance capability and its microbiome gene function, laying the basis for nutritional interventions that could benefit endurance athletes.
ArtSeg: Rapid Artifact Segmentation and Removal in Brightfield Cell Microscopy Images
Authors: Ali Mohammed A. S. , Hollo Kaspar , Laasfeld Tõnis , Torp Jane , Tahk Maris-Johanna , Rinken Ago , Palo Kaupo , Parts Leopold , Fishman Dmytro 
Published: January 2022

AbstractBrightfield cell microscopy is a foundational tool in life sciences. The acquired images are prone to contain visual artifacts that hinder downstream analysis, and automatically removing them is therefore of great practical interest. Deep convolutional neural networks are state-of-the-art for image segmentation, but require pixel-level annotations, which are time-consuming to produce. Here, we propose ScoreCAM-U-Net, a pipeline to segment artifactual regions in brightfield images with limited user input. The model is trained using only image-level labels, so the process is faster by orders of magnitude compared to pixel-level annotation, but without substantially sacrificing the segmentation performance. We confirm that artifacts indeed exist with different shapes and sizes in three different brightfield microscopy image datasets, and distort downstream analyses such as nuclei segmentation, morphometry and fluorescence intensity quantification. We then demonstrate that our automated artifact removal ameliorates this problem. Such rapid cleaning of acquired images using the power of deep learning models is likely to become a standard step for all large scale microscopy experiments.
Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants
Authors: Wang Eric , Chakraborty Arup K. 
Published: January 2022

AbstractThe rise of SARS-CoV-2 variants and the history of outbreaks caused by zoonotic coronaviruses point to the need for next-generation vaccines that confer protection against variant strains. Here, we combined analyses of diverse sequences and structures of coronavirus spikes with data from deep mutational scanning to design SARS-CoV-2 variant antigens containing the most significant mutations that may emerge. We trained a neural network to predict RBD expression and ACE2 binding from sequence, which allowed us to determine that these antigens are stable and bind to ACE2. Thus, they represent viable variants. We then used a computational model of affinity maturation (AM) to study the antibody response to immunization with different combinations of the designed antigens. The results suggest that immunization with a cocktail of the antigens is likely to promote evolution of higher titers of antibodies that target SARS-CoV-2 variants than immunization or infection with the wildtype virus alone. Finally, our analysis of 12 coronaviruses from different genera identified the S2’ cleavage site and fusion peptide as potential pan-coronavirus vaccine targets.Author SummarySARS-CoV-2 variants have already emerged and future variants may pose greater threats to the efficacy of current vaccines. Rather than using a reactive approach to vaccine development that would lag behind the evolution of the virus, such as updating the sequence in the vaccine with a current variant, we sought to use a proactive approach that predicts some of the mutations that could arise that could evade current immune responses. Then, by including these mutations in a new vaccine antigen, we might be able to protect against those potential variants before they appear. Toward this end, we used various computational methods including sequence analysis and machine learning to design such antigens. We then used simulations of antibody development, and the results suggest that immunization with our designed antigens is likely to result in an antibody response that is better able to target SARS-CoV-2 variants than current vaccines. We also leveraged our sequence analysis to suggest that a particular site on the spike protein could serve as a useful target for a pan-coronavirus vaccine.
The monosialoganglioside GM1a protects trophoblasts, erythrocytes and endothelial cells against complement attack
Authors: Wedekind Henri , Beimdiek Julia , Rossdam Charlotte , Kats Elina , Wittek Vanessa , Schumann Lisa , Tiede Andreas , Buettner Falk F. R. , Weinhold Birgit , Münster-Kühnel Anja , Abeln Markus 
Published: January 2022

AbstractThe complement system is a part of the innate immune system in the fluid phase and efficiently eliminates pathogens. However, its activation requires tight regulation on the host cell surface in order not to compromise cellular viability. Previously, we showed that loss of placental cell surface sialylation in mice in vivo leads to a maternal complement attack at the fetal-maternal interface, ultimately resulting in loss of pregnancy. To gain insight into the regulatory function of sialylation in complement activation, we here generated trophoblast stem cells devoid of sialylation, which also revealed complement sensitivity and cell death in vitro. Glycolipid-analysis by xCGE-LIF allowed us to identify the monosialoganglioside GM1a as a key element of cell surface complement regulation. Exogenously administered GM1a integrated into the plasma membrane of trophoblasts, dramatically increased binding of complement factor H and was sufficient to protect the cells from complement attack and cell death. Furthermore, GM1a treatment rescued sensitized human erythrocytes and endothelial cells from complement attack in a concentration dependent manner. This study demonstrates for the first time the complement regulatory potential of exogenously administered gangliosides and paves the way for sialoglycotherapeutics as a novel substance class for membrane-targeted complement regulators.Key pointsThe naturally occurring sialic acid containing glycosphingolipid GM1a is a potent regulator of complement activation on mammalian trophoblast, erythrocyte and endothelial cell surfaces.Incorporated GM1a recruits complement factor H and thus could represent a novel membrane-targeted complement therapeutic.
Initial assessment of the spatial learning, reversal, and sequencing task capabilities of knock- in rats with humanizing mutations in the Aβ-coding region of App
Authors: Pham Hoa , Yin Tao , D’Adamio Luciano 
Published: January 2022

AbstractModel organisms mimicking the pathogenesis of human diseases are useful for identifying pathogenic mechanisms and testing therapeutic efficacy of compounds targeting them. Models of Alzheimer’s disease and related dementias aim to reproduce the brain pathology associated with these neurodegenerative disorders. Transgenic models, which involve random insertion of disease-causing genes under the control of artificial promoters, are efficient means of doing so. There are confounding factors associated with transgenic approaches, however, including target gene overexpression, dysregulation of endogenous gene expression at transgenes’ integration sites, and limitations in mimicking loss-of-function mechanisms. Furthermore, the choice of species is important, and there are anatomical, physiological, and cognitive reasons for favoring the rat over the mouse, which has been the standard for models of neurodegeneration and dementia. We report an initial assessment of the spatial learning, reversal, and sequencing task capabilities of knock-in Long-Evans rats with humanizing mutations in the Aβ-coding region of App, which encodes amyloid precursor protein (Apph/h rats), using the IntelliCage, an automated operant social home cage system, at 6-8 weeks of age, then again at 4-5 months of age. These rats were previously generated as control organisms for studies on neurodegeneration involving other knock-in rat models from our lab. Apph/h rats of either sex can acquire place learning and reversal tasks. They can also acquire a diagonal sequencing task by 6-8 weeks of age, but not a more advanced serial reversal task involving alternating diagonals, even by 4-5 months of age.
Imprinted genes Cdkn1c and Igf2 interact to promote terminal differentiation of adult NSCs
Authors: Lozano-Ureña Anna , Jiménez-Villalba Esteban , Lázaro-Carot Laura , Montalbán-Loro Raquel , Martínez-Gurrea Irene , Nakayama Keiichi , Kirstein Martina , Ferrón Sacri R. 
Published: January 2022

SummaryGenomic imprinting is implicated in the control of gene dosage in neurogenic niches. Insulin-like growth factor 2 (Igf2), is an imprinted gene that shows biallelic expression only in the vascular compartment contributing to neural stem cells (NSCs) maintenance in the subventricular zone (SVZ) niche. The effects of this factor in adult NSCs differentiation are not well defined. We show here that IGF2 promotes cell fate commitment of NSCs by inducing the expression of another imprinted gene, the maternally expressed gene cyclin-dependent kinase inhibitor 1c (Cdkn1c), which encodes for p57 protein, eliciting cell cycle exit and terminal differentiation into astrocytes, neurons and oligodendrocytes. Using a conditional mouse model with Cdkn1c-deficient neural progenitors, we confirm that IGF2 and p57 interact in a common pathway to regulate the differentiation program of adult NSCs. This occurs through a mechanism involving the PI3K-Akt pathway that mediates regulation of p57 expression. We also show that the imprinted state of the Cdkn1c gene is not altered after IGF2 treatment confirming maternal expression of the gene in NSCs. Our results identify a molecular mechanism by which a paracrine factor produced and secreted by the neurogenic niche compartment can modulate Cdkn1c dosage to trigger differentiation of adult NSCs.
plotsr: Visualising structural similarities and rearrangements between multiple genomes
Authors: Goel Manish , Schneeberger Korbinian 
Published: January 2022

AbstractSummaryThird-generation genomic technologies have led to a sharp increase in the number of high-quality genome assemblies. This allows the comparison of multiple assembled genomes of individual species and demands for new tools for visualising their structural properties. Here we present plotsr, an efficient tool to visualize structural similarities and rearrangements between multiple genomes. It can be used to compare genomes on chromosome level or to zoom in on any selected region. In addition, plotsr can augment the visualisation with regional identifiers (e.g. genes or genomic markers) or histogram tracks for continuous features (e.g. GC content or polymorphism density).Availability and implementationplotsr is implemented as a python package and uses the standard matplotlib library for plotting. It is freely available under the MIT license at GitHub (https://github.com/schneebergerlab/plotsr) and bioconda (https://anaconda.org/bioconda/plotsr).ContactManish Goel (manish.goel@lmu.de), Korbinian Schneeberger (k.schneeberger@lmu.de)
Genomics-based annotations help unveil the molecular composition of edible plants
Authors: Ofaim Shany , Menichetti Giulia , Sebek Michael , Barabási Albert László 
Published: January 2022

AbstractGiven the important role food plays in health and well-being, the past decades have seen considerable experimental efforts dedicated to mapping the chemical composition of food ingredients. As the composition of raw food is genetically predetermined, here we ask, to what degree can we rely on genome-associated metabolic annotations to predict the chemical composition of natural ingredients? To that end, we developed an approach to unveil the chemical composition of 75 edible plants’ genomes, finding that genome-associated functional annotations substantially increase the number of compounds linked to specific plants. To account for the gap between the metabolic potential represented by functional annotations and the compounds likely to be accumulated and detected experimentally, we employed a predictive thermodynamic feasibility approach to systematically identify compounds that are likely to accumulate in plants. To quantify the accuracy of our predictions, we performed untargeted metabolomics on 13 plants, allowing us to experimentally confirm the detectability of the predicted compounds. For example, we observed 59 potentially novel compounds predicted and experimentally detected in corn. Our study shows that the application of genome-associated functional annotations can lead to an integrated metabologenomics platform capable of unveiling the chemical composition of edible plants and the biochemical pathways responsible for the observed compounds.Author SummaryNutrition and well-being take a central role in today’s high pace life, but how much do we really know about the food we eat? Here, we harness existing metabolic knowledge encrypted in staple food ingredients’ genome to help us explore the composition of raw edible plants. We first show the benefit and value of looking into genome-associated functional annotations on a wide scale. Next, we rely on new experimental data to develop a framework that helps us reveal new, potentially bioactive compounds in staple food ingredients. This has significance in, first, extending current food composition knowledge and second in discovering newly detected bioactive compounds, shedding light on the potential impacts of common food ingredients beyond their nutritional value as described in food labels. Finally, we show that staple foods that are already included in our daily diets might have the potential to contribute to our well-being.
Genetic regulation of human aortic smooth muscle cell gene expression and splicing predict causal coronary artery disease genes
Authors: Aherrahrou Rédouane , Lue Dillon , Perry R Noah , Aberra Yonathan Tamrat , Khan Mohammad Daud , Soh Joon Yuhl , Örd Tiit , Singha Prosanta , Gilani Huda , Benavente Ernest Diez , Wong Doris , Hinkle Jameson , Ma Lijiang , Sheynkman Gloria M , den Ruijter Hester M , Miller Clint L , Björkegren Johan LM , Kaikkonen Minna U , Civelek Mete 
Published: January 2022

ABSTRACTCoronary artery disease (CAD) is the leading cause of death worldwide. Recent meta-analyses of genome-wide association studies (GWAS) have identified over 175 loci associated with CAD. The majority of these loci are in non-coding regions and are predicted to regulate gene expression. Given that vascular smooth muscle cells (SMCs) play critical roles in the development and progression of CAD, we hypothesized that a subset of the CAD GWAS risk loci are associated with the regulation of transcription in distinct SMC phenotypes. Here, we measured gene expression in SMCs isolated from the ascending aortas of 151 ethnically diverse heart transplant donors in quiescent or proliferative conditions and calculated the association of their expression and splicing with ∼6.3 million imputed single nucleotide polymorphism (SNP) markers across the genome. We identified 4,910 expression and 4,412 splice quantitative trait loci (sQTL) that represent regions of the genome associated with transcript abundance and splicing. 3,660 of the eQTLs had not been observed in the publicly available Genotype-Tissue Expression dataset. Further, 29 and 880 of the eQTLs were SMC- and sex-specific, respectively. To identify the effector transcript(s) regulated by CAD GWAS loci, we used four distinct colocalization approaches and identified 84 eQTL and 164 sQTLs that colocalized with CAD loci, highlighting the importance of genetic regulation of mRNA splicing as a molecular mechanism for CAD genetic risk. Notably, 20% and 35% of the eQTLs were unique to quiescent or proliferative SMCs, respectively. Two CAD loci colocalized with a SMC sex-specific eQTL (AL160313.1 and TERF2IP) and another locus colocalized with SMC-specific eQTL (ALKBH8). Also, 27% and 37% of the sQTLs were unique to quiescent or proliferative SMCs, respectively. The most significantly associated CAD locus, 9p21, was an sQTL for the long non-coding RNA CDKN2B-AS1, also known as ANRIL, in proliferative SMCs. Collectively, these results provide evidence for the molecular mechanisms of genetic susceptibility to CAD in distinct SMC phenotypes.
Identification of putative reader proteins of 5-methylcytosine and its derivatives in Caenorhabditis elegans RNA
Authors: Navarro Isabela Cunha , Suen Kin Man , Bensaddek Dalila , Tanpure Arun , Lamond Angus , Balasubramanian Shankar , Miska Eric A. 
Published: January 2022

ABSTRACTMethylation of carbon-5 of cytosines (m5C) is a post-transcriptional nucleotide modification of RNA with widespread distribution across organisms. m5C has been shown to participate in mRNA transport and maintain mRNA stability through its recognition by the reader proteins ALYREF and YBX1, respectively. We recently showed that m5C is required for Caenorhabditis elegans development and fertility under heat stress. To contribute to the understanding of how m5C and its oxidative derivatives mediate their functions, we developed RNA baits bearing modified cytosines in diverse structural contexts to pulldown potential readers in C. elegans. Our mass spectrometry analyses reveal unique binding proteins for each of the modifications. We validate our dataset by demonstrating that the nematode ALYREF homologues ALY-1 and ALY-2 preferentially bind m5C in vitro. The dataset presented here serves as an important scientific resource that will support the discovery of new functions of m5C and its derivatives.
Functional wetland loss drives emerging risks to waterbird migration networks
Authors: Donnelly J. Patrick , Moore Johnnie N. , Casazza Michael L. , Coons Shea P. 
Published: January 2022

AbstractMigratory waterbirds (i.e., shorebirds, wading birds, and waterfowl) rely on a diffuse continental network of wetland habitats to support annual life cycle needs. Emerging threats of climate and land-use change raise new concerns over the sustainability of these habitat networks as water scarcity triggers cascading ecological effects impacting wetland habitat availability. Here we use important waterbird regions in Oregon and California, USA, as a model system to examine patterns of landscape change impacting wetland habitat networks in western North America. Wetland hydrology and flooded agricultural habitats were monitored monthly from 1988 to 2020 using satellite imagery to quantify the timing and duration of inundation—a key delimiter of habitat niche values associated with waterbird use. Trends were binned by management practice and wetland hydroperiods (semi-permanent, seasonal, and temporary) to identify differences in their climate and land-use change sensitivity. Wetland results were assessed using 33 waterbird species to detect nonlinear effects of network change across a diversity of life cycle and habitat needs. Pervasive loss of semi-permanent wetlands was an indicator of systemic functional decline. Shortened hydroperiods caused by excessive drying transitioned semi-permanent wetlands to seasonal and temporary hydrologies—a process that in part counterbalanced concurrent seasonal and temporary wetland losses. Expansion of seasonal and temporary wetlands associated with closed-basin lakes offset wetland declines on other public and private lands, including wildlife refuges. Diving ducks, black terns, and grebes exhibited the most significant risk of habitat decline due to semi-permanent wetland loss that overlapped important migration, breeding, molting, and wintering periods. Shorebirds and dabbling ducks were beneficiaries of stable agricultural practices and top-down processes of functional wetland declines that operated collectively to maintain habitat needs. Outcomes from this work provide a novel perspective of wetland ecosystem change affecting waterbirds and their migration networks. Understanding the complexity of these relationships will become increasingly important as water scarcity continues to restructure the timing and availability of wetland resources.
Cannabidiol increases gramicidin current in human embryonic kidney cells: An observational study
Authors: Ghovanloo Mohammad-Reza , Goodchild Samuel J. , Ruben Peter C. 
Published: January 2022

ABSTRACTGramicidin is a monomeric protein that is thought to non-selectively conduct cationic currents and water. Linear gramicidin is considered an antibiotic. This function is considered to be mediated by the formation of pores within the lipid membrane, thereby killing bacterial cells. The main non-psychoactive active constituent of the cannabis plant, cannabidiol (CBD), has recently gained interest, and is proposed to possess various potential therapeutic properties, including being an antibiotic. We previously determined that CBD’s activity on ion channels could be, in part, mediated by altering membrane biophysical properties, including elasticity. In this study, our goal was to determine the empirical effects of CBD on gramicidin currents in human embryonic kidney (HEK) cells, seeking to infer potential direct compound-protein interactions. Our results indicate that gramicidin, when applied to the extracellular HEK cell membrane, followed by CBD perfusion, increases the gramicidin current.
Two roles for choice selective inhibition in decision-making circuits
Authors: Roach James P. , Churchland Anne K. , Engel Tatiana A. 
Published: January 2022

ABSTRACTDuring perceptual decision-making, the firing rates of cortical neurons reflect upcoming choices. Recent work showed that excitatory and inhibitory neurons are equally selective for choice. However, functional consequences of inhibitory choice selectivity in decision-making circuits are unknown. We developed a circuit model of decision-making which accounts for the specificity of inputs to and outputs from inhibitory neurons. We found that selective inhibition expands the space of circuits supporting decision-making, allowing for weaker or stronger recurrent excitation when connected in a competitive or feedback motif. The specificity of inhibitory outputs sets the trade-off between speed and accuracy of decisions by altering the attractor dynamics in the circuit. Recurrent neural networks trained to make decisions display the same dependence on inhibitory specificity and the strength of recurrent excitation. Our results reveal two concurrent roles for selective inhibition in decision-making circuits: stabilizing strongly connected excitatory populations and maximizing competition between oppositely selective populations.