bluuebunny/crossref_metadata_2025_split huggingface dataset:
Glyco-Engineering Cell Surfaces by Exo-Enzymatic Installation of GlcNAz and LacNAz Motifs
Authors: De León González Fabiola V. , Boddington Marie E. , Prindl Martha I. , Capicciotti Chantelle J. 
Published: August 2023

AbstractExo-enzymatic glyco-engineering of cell-surface glycoconjugates enables the selective display of well-defined glyco-motifs bearing bioorthogonal functional groups which can be used to study glycans and their interactions with glycan-binding proteins. While the installation of monosaccharides and their derivatives using glycosyltransferase enzymes has rapidly evolved, similar strategies to introduce chemical-reporter functionalized Type 2 LacNAc motifs have not been reported. Herein, we report the chemo-enzymatic synthesis of unnatural UDP-GlcNAc and UDP-GalNAc nucleotide-sugars, and the donor and acceptor substrate tolerance of the human glycosyltransferases B3GNT2 and B4GalT1, respectively, to form derivatized LacNAc moieties. We also demonstrate that B3GNT2 can be used to exo-enzymatically install GlcNAc and GlcNAz onto cell-surface glycans. GlcNAc- or GlcNAz-engineered cells can be further extended by B4GalT1, producing LacNAc or LacNAz-engineered cells. Our glyco-engineering labeling strategy is amenable to different cell types and our work expands the exo-enzymatic glycan editing toolbox to selectively introduce unnatural Type 2 LacNAc motifs.
Dysregulation of extracellular vesicle protein cargo in female ME/CFS cases and sedentary controls in response to maximal exercise
Authors: Giloteaux Ludovic , Glass Katherine A. , Germain Arnaud , Zhang Sheng , Hanson Maureen R. 
Published: August 2023

ABSTRACTIn healthy individuals, physical exercise improves cardiovascular health and muscle strength, alleviates fatigue, and reduces risk of chronic diseases. Although exercise is suggested as a lifestyle intervention to manage various chronic illnesses, it negatively affects people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), who suffer from exercise intolerance. We hypothesized that altered extracellular vesicle (EV) signaling in ME/CFS patients after an exercise challenge may contribute to their prolonged and exacerbated negative response to exertion (post-exertional malaise). EVs were isolated by size exclusion chromatography from the plasma of 18 female ME/CFS patients and 17 age- and BMI-matched female sedentary controls at three time points: before, 15 minutes, and 24 hours after a maximal cardiopulmonary exercise test. EVs were characterized using nanoparticle tracking analysis and their protein cargo was quantified using Tandem Mass Tag-based (TMT) proteomics. The results show that exercise affects the EV proteome in ME/CFS patients differently than in healthy individuals and that changes in EV proteins after exercise are strongly correlated with symptom severity in ME/CFS. Differentially abundant proteins in ME/CFS patients vs. controls were involved in many pathways and systems, including coagulation processes, muscle contraction (both smooth and skeletal muscle), cytoskeletal proteins, the immune system, and brain signaling.
Sex-dependent effects of stress on insular cortex-to-nucleus accumbens synaptic plasticity
Authors: Gauthier Manon , Dugast Emilie , Lardeux Virginie , Letort Kevin , Belnoue Laure , Balado Eric , Solinas Marcello , Belujon Pauline 
Published: August 2023

ABSTRACTStress is an important risk factor for the development of psychiatric disorders and men and women tend to react differently to stress. Sex differences are also observed in many stress-related psychiatric disorders such as depression, anxiety disorders or addiction. Therefore, identifying specific neuroadaptations induced by stress, in males and females, is a necessary step to the understanding of stress-related sex dimorphism in these disorders. Here, we tested the hypotheses that acute stress could affect plasticity in the anterior insular cortex (aIC)-nucleus accumbens core (NAcC) pathway, two structures involved in the stress response, in a sex-dependent manner. Usingin vivoextracellular recordings in anesthetized rats, we show that synaptic plasticity in the aIC-NAcC pathway is different between male and female rats. Whereas in males, long-term potentiation and long-term depression were equally induced, in females, there was mostly a long-term potentiation induced. Moreover, stress affected synaptic plasticity in the aIC-NAcC differently in male and female rats. In males, stress induced a loss of long-term-depression that lasted for at least 24h, whereas in females, stress induced less neurons displaying LTP, which did not last.These results demonstrate that integration of aIC information to NAcC is different between males and females. This study provides mechanistic support for differential reactivity to stress between males and females that may relate to stress-related psychiatric disorders and sex dimorphism in these disorders.
Transcription factors operate on a limited vocabulary of binding motifs inArabidopsis thaliana
Authors: Zenker Sanja , Wulf Donat , Meierhenrich Anja , Becker Sarah , Eisenhut Marion , Stracke Ralf , Weisshaar Bernd , Bräutigam Andrea 
Published: August 2023

AbstractPredicting gene expression from promoter sequence requires understanding of the different signal integration points within a promoter. Sequence-specific transcription factors (TFs) binding to their cognate TF binding motifs control gene expression in eukaryotes by activating and repressing transcription. Their interplay generates complex expression patterns in reaction to environmental conditions and developmental cues.We hypothesized that signals are not only integrated by different TFs binding various positions in a promoter, but also by single TF binding motifs onto which multiple TFs can bind. Analyzing 2,190 binding motifs, we identified only 76 core TF binding motifs in plants. Twenty-one TF protein families act highly specific and bind a single conserved motif. Four TF families are classified as semi-conserved as they bind up to four motifs within a family, with divisions along phylogenetic groups. Five TF families bind diverse motifs. Expression analyses revealed high competition within TF families for the same binding motif. The results show that singular binding motifs act as signal integrators in plants where a combination of binding affinity and TF abundance likely determine the output.
Intermodal consistency of whole-brain connectivity and signal propagation delays
Authors: Jedynak Maciej , Lopez Emahnuel Troisi , Romano Antonella , Jirsa Viktor , David Olivier , Sorrentino Pierpaolo 
Published: August 2023

AbstractMeasuring the propagation of perturbations across the human brain and their transmission delays is critical for network neuroscience, but it is a challenging problem that still requires cross-validation approaches. Here, we compare results from a recently introduced, non-invasive technique of functional delays estimation from source-reconstructed electro/magnetoencephalography, to the corresponding findings from a large dataset of cortico-cortical evoked potentials estimated from intracerebral stimulations of epileptic pharmaco-resistant patients. The two methods yield significantly similar probabilistic connectivity maps and signal propagation delays. This similarity suggests a correspondence between the mechanisms underpinning the propagation of spontaneously generated scale-free perturbations (i.e. neuronal avalanches observed in resting state activity studied using magnetoencephalography) and the spreading of cortico-cortical evoked potentials. This manuscript provides evidence for the accuracy of a subject-specific estimate of functional delays obtained non-invasively from reconstructed sources. Conversely, our findings show that estimates obtained from externally-induced perturbations capture physiological activities. In conclusion, this manuscript constitutes a cross-validation between two different modalities. Importantly, the capability to measure delays non-invasively (as per MEG) paves the way for the inclusion of functional delays in personalized large-scale brain models as well as in diagnostic and prognostic algorithms.
Lesion aware automated processing pipeline for multimodal neuroimaging stroke data and The Virtual Brain (TVB)
Authors: Bey Patrik , Dhindsa Kiret , Kashyap Amrit , Schirner Michael , Feldheim Jan , Bönstrup Marlene , Schulz Robert , Cheng Bastian , Thomalla Götz , Gerloff Christian , Ritter Petra 
Published: August 2023

AbstractBackgroundProcessing stroke magnetic resonance imaging (MRI) brain data can be susceptible to lesion-based abnormalities. In this study we developed and validated the Lesion Aware automated Processing Pipeline (LeAPP) that incorporates mitigation measures, improving volumetric and connectomics outputs compared to current standards in automated MRI processing pipelines.MethodsBuilding upon the Human Connectome Project (HCP) minimal processing pipeline, we introduced correction measures, such as cost-function masking and virtual brain transplant, and extended functional and diffusion processing to match acquisition protocols often found in a clinical context. A total of 51 participants (36 stroke patients (65.7±12.96 years, 18 female) and 15 healthy controls (69.2±7.4 years, 7 female)) were processed across four time points for patients (3-5, 30-40, 85-95, 340-380 days after stroke onset) and one time point for controls. Artificially lesioned brains (N=82), derived from healthy brains and informed by real stroke lesions were created, thus generating ground-truth data for validation. The processing pipeline and validation framework are available as containerized open-source software. Reconstruction quality has been quantified on whole brain level and for lesion affected and unaffected regions-of-interest (ROIs) using metrics like dice score, volume difference and center-of-gravity distance. Global and local level connectome reconstruction was assessed using node strength, node centrality and clustering coefficient.ResultsThe new pipeline LeAPP provides close reconstructions of the ground truth. Deviations in reconstructed averaged whole brain node strength and all ROI based volume and connectome metrics were significantly reduced compared to the HCP pipeline without stroke specific mitigation measures.ConclusionsLeAPP improves reconstruction quality of multimodal MRI processing for brain parcellation and structural connectome estimation significantly over the non-adapted HCP in the presence of lesions and provides a robust framework for diffusion and functional image processing of clinical stroke data. This novel open-source automated processing pipeline contributes to a development towards reproducible research.Graphical abstract
Expansion Strategy-Driven Micron-Level Resolution Mass Spectrometry Imaging of Lipids in Mouse Brain Tissue
Authors: Winnie Hung Yik Ling , Xie Chengyi , Wang Jianing , Diao Xin , Li Ruxin , Wang Xiaoxiao , Qiu Shulan , Fang Jiacheng , Cai Zongwei 
Published: August 2023

AbstractA novel method for enhanced resolution, termed expansion mass spectrometry imaging (Ex-MSI), has been developed for lipid mass spectrometry imaging, utilizing existing commercially available mass spectrometers without necessitating modifications. This approach involves embedding tissue sections in a swellable polyelectrolyte gel, with the target biomolecules indirectly anchored to the gel network. By employing matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI), the method has realized an enhancement in spatial resolution that surpasses the conventional resolution limits of commercial instruments by approximately 4.5 folds. This enhancement permits the detailed visualization of intricate structures within the mouse brain at a subcellular level, with a lateral resolution nearing 1 μm. As a physical technique for achieving resolution beyond standard capabilities, this approach is readily adaptable and presents a powerful tool for high-definition imaging in biological research.
PP2A and GSK3 act as modifiers of FUS-ALS by modulating mitochondrial transport
Authors: Tziortzouda Paraskevi , Steyaert Jolien , Scheveneels Wendy , Sicart Adria , Stoklund Dittlau Katarina , Barbosa Correia Adriana Margarida , Pal Arun , Hermann Andreas , Van Damme Philip , Moens Thomas , Van Den Bosch Ludo 
Published: August 2023

AbstractALS is a fatal neurodegenerative disease which currently lacks effective treatments. Mutations in the RNA-binding protein FUS are a common cause of familial ALS, accounting for around 4% of fALS cases. Studying the mechanisms by which mutant FUS is toxic to neurons may provide insight into the pathogenesis of both familial and sporadic forms of ALS. Here we identify Protein Phosphatase 2A (PP2A) and Glycogen Synthase Kinase 3 (GSK3) as novel modifiers of FUS-ALSin vivo, looking from fly to human. PP2A-C and GSK3β inhibition rescued FUS-induced toxicity inDrosophilaand disease-relevant phenotypes in human iPSC-derived spinal motor neurons (sMNs). In bothDrosophilaand human iPSC-sMNs, we observed reduced GSK3β inhibitory phosphorylation, suggesting that FUS dysfunction results in GSK3β hyperactivity. We found that PP2A acts upstream of GSK3, affecting its inhibitory phosphorylation, and in synergy they modulate mitochondrial transport through the motor protein kinesin. Our data providein vivoevidence that PP2A and GSK3 are disease modifiers, and reveal an unexplored mechanistic link between PP2A, GSK3 and kinesin in FUS-associated ALS.
Social network structure scales with group size in a multi-species analysis
Authors: Gagliardi Brenna Marie , St-Amant Nader , Dakin Roslyn 
Published: August 2023

AbstractSocial networks can shape the evolution and transmission of behaviours. Recent studies have characterized social networks within species, but we know relatively little about the drivers of variation in the structure of social networks across species. Here, we analyze a database of 631 social networks from more than 30 animal species to test how social network properties scale with group size. We examine three properties of social network topology: the uniformity of edge weights within the group, the selectivity of individuals for particular social partners, and the amount of heterogeneity among individuals in social behaviour. We show that most of the variation in these three network properties is due to differences between focal species and/or study methodologies, with only negligible differences between the three animal classes in our analysis (birds, mammals, and insects). Our analysis also indicates that group size is the key factor that determines the topology of animal social networks. In smaller groups, edge weights are distributed more uniformly, and individuals show greater selectivity regarding their social partners. These results suggest that there are general scaling rules governing the social networks of diverse animal species. In small groups, individuals form strong connections to a selective set of partners, whereas in large groups, weaker ties are common, and individuals are less likely to limit their interactions to specific partners.Significance StatementSociality is observed throughout the animal kingdom. Animal societies also vary widely in group size, from a few individuals to groups with millions on individuals. How do animal social networks vary across this spectrum? We investigated this question using data compiled from recent bird, mammal, and insect studies. Surprisingly, we found broad overlap in the social network structures of these three distinct animal classes. We tested the effect of group size on social network structure, and found that in small groups, individuals form stronger social ties with preferred social partners; by contrast, animals in large groups have weaker and less selective social ties. These results suggest that diverse animal groups are governed by similar processes that determine the structure of their social networks.
The genomic landscape, causes, and consequences of extensive phylogenomic discordance in Old World mice and rats
Authors: Thomas Gregg W. C. , Hughes Jonathan J. , Kumon Tomohiro , Berv Jacob S. , Erik Nordgren C. , Lampson Michael , Levine Mia , Searle Jeremy B. , Good Jeffrey M. 
Published: August 2023

AbstractA species tree is a central concept in evolutionary biology whereby a single branching phylogeny reflects relationships among species. However, the phylogenies of different genomic regions often differ from the species tree. Although tree discordance is often widespread in phylogenomic studies, we still lack a clear understanding of how variation in phylogenetic patterns is shaped by genome biology or the extent to which discordance may compromise comparative studies. We characterized patterns of phylogenomic discordance across the murine rodents (Old World mice and rats) – a large and ecologically diverse group that gave rise to the mouse and rat model systems. Combining new linked-read genome assemblies for seven murine species with eleven published rodent genomes, we first used ultra-conserved elements (UCEs) to infer a robust species tree. We then used whole genomes to examine finer-scale patterns of discordance and found that phylogenies built from proximate chromosomal regions had similar phylogenies. However, there was no relationship between tree similarity and local recombination rates in house mice, suggesting that genetic linkage influences phylogenetic patterns over deeper timescales. This signal may be independent of contemporary recombination landscapes. We also detected a strong influence of linked selection whereby purifying selection at UCEs led to less discordance, while genes experiencing positive selection showed more discordant and variable phylogenetic signals. Finally, we show that assuming a single species tree can result in high error rates when testing for positive selection under different models. Collectively, our results highlight the complex relationship between phylogenetic inference and genome biology and underscore how failure to account for this complexity can mislead comparative genomic studies.
Ribose lowers RpoS translation through RbsD mRNA
Authors: Badaoui Andrew , Smith Isabel , Balla Melisa , Cavanaugh Mikayla , Lockart Julia , Parsons Dylan , Martes Esteban , Dorean Shaina , Diop Cheik , Tran Thomas , Peterson Celeste N. 
Published: August 2023

AbstractTheEscherichia colisigma factor RpoS accumulates during starvation, activates transcription of the general stress response, and then rapidly returns to low levels upon nutrient replenishment. Sugar levels modulate RpoS levels by signaling though central metabolism, ATP and the phosphoenolpyruvate-carbohydrate phosphotransferase system (PTS) transport system, which favors glucose. However, there have been few examples of dedicated control pathways for specific sugars regulating RpoS. We screened an overexpression library with a RpoS’-‘LacZ reporter and found that overexpressing the ribose metabolismrbsDgene reduced RpoS levels. A functional RbsD ribose pyranase protein was not necessary for the effect, suggesting that the RbsD mRNA was responsible for the effect. We used a series of LacZ fusions and RT-qPCR to determine how RbsD mRNA affects RpoS and found that regulation of RpoS occurred at the level of translation. Furthermore, the effect ofrbsDoverexpression was diminished in strain that did not have the RpoS untranslated hairpin loop or the small RNA chaperone Hfq. RbsD mRNA has previously been shown to bind to the sRNA DsrA. We demonstrated that the effect of RbsD on RpoS was dependent on the sRNAs DsrA and ArcZ and Hfq. Finally, we showed that the sugar ribose lowers RpoS levels in a manner that requires RbsD. In summary, our results demonstrate that RpoS levels respond specifically to ribose though a component of the ribose metabolism pathway and the main player, RbsD, acts as dual function mRNA that has a regulatory role by interacting with the sRNAs that control RpoS.
A systems vaccinology resource to develop and test computational models of immunity
Authors: Shinde Pramod , Soldevila Ferran , Reyna Joaquin , Aoki Minori , Rasmussen Mikkel , Willemsen Lisa , Kojima Mari , Ha Brendan , Greenbaum Jason A , Overton James A , Guzman-Orozco Hector , Nili Somayeh , Orfield Shelby , Gygi Jeremy P. , da Silva Antunes Ricardo , Sette Alessandro , Grant Barry , Olsen Lars Rønn , Konstorum Anna , Guan Leying , Ay Ferhat , Kleinstein Steven H. , Peters Bjoern 
Published: August 2023

AbstractComputational models that predict an individual’s response to a vaccine offer the potential for mechanistic insights and personalized vaccination strategies. These models are increasingly derived from systems vaccinology studies that generate immune profiles from human cohorts pre- and post-vaccination. Most of these studies involve relatively small cohorts and profile the response to a single vaccine. The ability to assess the performance of the resulting models would be improved by comparing their performance on independent datasets, as has been done with great success in other areas of biology such as protein structure predictions. To transfer this approach to system vaccinology studies, we established a prototype platform that focuses on the evaluation of Computational Models of Immunity to Pertussis Booster vaccinations (CMI-PB). A community resource, CMI-PB generates experimental data for the explicit purpose of model evaluation, which is performed through a series of annual data releases and associated contests. We here report on our experience with the first such ‘dry run’ for a contest where the goal was to predict individual immune responses based on pre-vaccination multi-omic profiles. Over 30 models adopted from the literature were tested, but only one was predictive, and was based on age alone. The performance of new models built using CMI-PB training data was much better, but varied significantly based on the choice of pre-vaccination features used and the model building strategy. This suggests that previously published models developed for other vaccines do not generalize well to Pertussis Booster vaccination. Overall, these results reinforced the need for comparative analysis across models and datasets that CMI-PB aims to achieve. We are seeking wider community engagement for our first public prediction contest, which will open in early 2024.
Novel hepatocellular carcinomas (HCC) Subtype-Specific Biomarkers
Authors: Croft Jacob , Quintanar Odalys , Gao Liyuan , Sheng Victor , Zhang Jun 
Published: August 2023

AbstractIntroductionHepatocellular carcinoma (HCC), the most common form of liver cancer, is a global health concern and a leading cause of cancer-related deaths. HCC accounts for a significant portion of liver cancers and has low survival rates of 5% to 30%, especially for HCC patients with a survival rate of 15%. Early detection is challenging due to the absence of symptoms in the early stages. The complexity and molecular diversity of HCC contribute to its poor prognosis. Understanding its molecular subtypes and mechanisms is crucial for improved management.MethodsThe study utilized publicly available data to investigate the potential diagnostic and prognostic biomarkers for hepatocellular carcinoma (HCC) based on their transcript per million (TPM) expression levels. A dataset of 407 HCC patient profiles was analyzed for survival trends and gene expression patterns.ResultsThrough a comprehensive approach, over 900 potential prognostic candidates were identified. Further analysis narrowed down 647 prognostic and diagnostic candidate biomarkers. The study also explored the role of the CmPn signaling network in HCC, reaffirming that its components could act as prognostic markers. Additionally, the study-utilized machine learning to discover 102 transcription factors (TFs) associated with HCC, from candidate biomarkers.ConclusionsThe findings provide insights into the molecular basis of HCC and offer potential avenues for improved diagnosis, treatment, and patient outcomes. The expanded prognostic biomarker pool aids in pinpointing HCC-specific grading and staging biomarkers, facilitating targeted therapies for improved patient outcomes and survival rates