bluuebunny/crossref_metadata_2025_split huggingface dataset:
Among-Population Differentiation in the Tapeworm Proteome through Prediction of Excretory/Secretory and Transmembrane Proteins inSchistocephalus solidus
Authors: Wang Anni , Bolnick Daniel 
Published: October 2024

AbstractBackgroundParasites secrete and excrete a variety of molecules evolve to help establish and sustain infections within hosts. Parasite adaptation to their host may lead to between-population divergence in these excretory and secretory products (ESPs), but few studies have tested for intraspecific variation in helminth proteomes.MethodsSchistocephalus solidusis a cestode that parasitizes three spined stickleback,Gasterosteus aculeatus. We used an ultra-performance liquid chromatography-mass spectrometry protocol to characterize the ESP and whole-body proteome of S. solidus. Specifically, we characterized the proteome of S. solidus at the plerocercoid stage from wild caught stickleback from three lakes on Vancouver Island (British Columbia, Canada) and one lake in Alaska (United States). We tested for differences in proteome composition among the four populations and specifically between ESPs and body tissue.ResultsOverall, we identified 1362 proteins in the total proteome of S. solidus, with 542 of the 1362 proteins detected exclusively in the ESPs. Of the ESP proteins, we found signaling peptides and transmembrane proteins that were previously not detected or characterized in S. solidus. We also found protein spectrum counts greatly varied between all lake populations.ConclusionsThese population-level differences were observed in both ESP and tissue types. Our study suggests that S. solidus can excrete and secrete a wide range of proteins which are distinct among populations. These differences might reflect plastic responses to host genotype differences, or evolved adaptations by Schistocephalus to different local host populations.
Dual transcranial electromagnetic stimulation of the precuneus-hippocampus network boosts human long-term memory
Authors: Borghi Ilaria , Mencarelli Lucia , Maiella Michele , Casula Elias P. , Ferraresi Matteo , Candeo Francesca , Savastano Elena , Assogna Martina , Bonnì Sonia , Koch Giacomo 
Published: October 2024

AbstractNon-invasive brain stimulation techniques have the potential to improve memory functions. However, the results so far have been relatively modest and time-consuming. Here, we implemented a novel 3-minute combination of personalized repetitive transcranial magnetic stimulation (intermittent theta burst-iTBS) coupled with simultaneous application of gamma transcranial alternating current stimulation (γtACS) over the precuneus, a brain area connected with the hippocampus, to modulate long term memory in healthy subjects. Only dual electromagnetic stimulation of the precuneus produced a consistent increase in long-term associative memory as compared to iTBS alone and sham conditions in a sample of healthy volunteers. The effects were replicated in another independent sample, in which the increased associative memory was retained for up to one week. Moreover, dual stimulation increased gamma oscillations and precuneus-hippocampus functional connectivity through the white matter tracts linking the precuneus with the temporal lobe. These findings show that dual stimulation may lead neuronal assemblies in a state favorable to enhance long-term plasticity and identify the precuneus as a key brain area involved in memory formation. Personalized dual electromagnetic stimulation of the precuneus-hippocampus network may represent a new powerful approach for enhancing memory functions in several healthy and clinical conditions.
Genomic Insights Guiding Personalized First-Line Immunotherapy Response in Lung and Bladder Tumors
Authors: Brea-Iglesias Jenifer , Gallardo-Gómez María , Oitabén Ana , Lázaro-Quintela Martin E. , León Luis , Alves Joao M. , Juaneda-Magdalena Laura , García-Benito Carme , Abdulkader Ihab , Muinelo Laura , Paramio Jesús M , Martínez-Fernández Mónica 
Published: October 2024

ABSTRACTImmune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, particularly in advanced non-small cell lung cancer (NSCLC) and muscle-invasive bladder cancer (MIBC). However, identifying reliable predictive biomarkers for ICI response remains a significant challenge. In this study, we analyzed real-world cohorts of advanced NSCLC and MIBC patients treated with ICIs as first-line therapy. Tumor samples underwent Whole Genome Sequencing (WGS) to identify specific somatic variants and assess tumor mutational burden (TMB). Additionally, mutational signature extraction and pathway enrichment analyses were performed to uncover the underlying mechanisms of ICI response. We also characterized HLA-I haplotypes and investigated LINE-1 retrotransposition. Distinct mutation patterns were identified in patients who responded to treatment, suggesting potential biomarkers for predicting ICI effectiveness. In NSCLC, tumor mutational burden (TMB) did not differ significantly between responders and non-responders, while in MIBC, higher TMB was linked to better responses. Specific mutational signatures and HLA haplotypes were associated with ICI response in both cancers. Pathway analysis showed that NSCLC responders had active inflammatory and immune pathways, while non-responders had pathways such related to FGFR3 and neural crest differentiation associated to resistance mechanisms. In MIBC, responders had alterations in DNA repair, leading to more neoantigens and a stronger ICI response. Importantly, for the first time, we found that LINE-1 activation was positively linked to ICI response, especially in MIBC. These findings reveal promising biomarkers and mechanistic insights, offering a new perspective on predicting ICI response and opening up exciting possibilities for more personalized immunotherapy strategies in NSCLC and MIBC.
Association of the benzoxazinoid pathway with boron homeostasis in maize
Authors: Chu Liuyang , Shrestha Vivek , Schäfer Cay Christin , Niedens Jan , Meyer George W. , Darnell Zoe , Kling Tyler , Dürr-Mayer Tobias , Abramov Aleksej , Frey Monika , Jessen Henning , Schaaf Gabriel , Hochholdinger Frank , Nowak-Król Agnieszka , McSteen Paula , Angelovici Ruthie , Matthes Michaela S. 
Published: October 2024

AbstractBoth deficiency and toxicity of the micronutrient boron lead to severe reductions in crop yield. Despite this agricultural importance, the molecular basis underlying boron homeostasis in plants is not resolved. To identify molecular players involved in boron homeostasis in maize (Zea mays), we measured boron levels in the Goodman-Buckler association panel and performed genome-wide association studies. These analyses detected thebenzoxazinless(bx) gene,bx3, involved in the biosynthesis of benzoxazinoids, like DIMBOA, major defense compounds in maize. Genes involved in DIMBOA biosynthesis are all located in close proximity in the genome and the biosynthesis mutants, includingbx3are all DIMBOA deficient. We show that thebx3mutant has enhanced boron concentration in leaves compared to the B73 control plants, which correlates with enhanced leaf tip necrosis, a phenotype associated with boron toxicity. In contrast, other DIMBOA-deficient maize mutants did not show altered boron levels nor the leaf tip necrosis phenotype, suggesting that boron is not associated with DIMBOA. Instead, our analyses suggest that the accumulation of boron is linked to the benzoxazinoid intermediates indolin-2-one (ION) and 3-hydroxy-ION. Therefore, our results connect boron homeostasis to the benzoxazinoid plant defense pathway throughbx3and specific intermediates, rendering the benzoxazinoid biosynthesis pathway a potential target for crop improvement in inadequate boron conditions.One sentence summaryGWAS identifiedbenzoxazinless3in the benzoxazinoid biosynthesis pathway to play a role in boron homeostasis in maize.
Lactococcus lactissubsp.cremorisC60 promotes immunoglobulin A production from B cells through functional modification of dendritic cells in intestinal environment
Authors: Saito Suguru , Okuno Alato , Kakizaki Nanae , Maekawa Toshio , Tsuji Noriko M. 
Published: October 2024

AbstractProbiotics utilizing lactic acid bacteria (LAB) have gained considerable attention in recent trends promoting self-managed health. Specifically, LAB-mediated immune modulation has been a key focus due to its potential to reduce the risk of pathogenic invasion and enhance host immunity. Immunoglobulin A (IgA) plays a crucial role in innate defense against various pathogens. Although only a limited number of probiotic LAB strains have been shown to increase IgA production, this capability remains of great interest. Here, we report a new strain,Lactococcus lactissubsp.cremorisC60 (C60), which promotes IgA production through functional modulation of intestinal B cells and dendritic cells (DCs). Heat-killed (HK)-C60 increased both pro-inflammatory and anti-inflammatory cytokine productions in DCs via the Toll-like receptor (TLR)-Myeloid differentiation primary response 88 (MyD88) signaling pathway, as demonstrated in both a physiological mouse model andin vitrocultures using bone marrow-derived dendritic cells (BMDCs). Notably, intragastric administration of HK-C60 significantly increased systemic IgA production, which was associated with the functional modification of B cells in the Peyer’s patches (PPs) of the small intestine. Immunophenotyping of PP cells from HK-C60-administered mice revealed both an expansion and functional upregulation of B cells. Mechanistically, we identified that DC-derived interleukin-6 (IL-6) and IL-10 play essential roles in the C60-mediated increase in IgA production by B cells. Finally, we evaluated the effect of C60 on IgA production using human peripheral blood mononuclear cells (PBMCs). Consistent with our findings in the mouse model, PBMCs produced IgA upon HK-C60 stimulation in an IL-6- and IL-10-dependent manner. Our results suggest that C60 is a novel probiotic strain capable of promoting intestinal immune homeostasis by upregulating IgA production, underscoring its potential for probiotic applications focused on immune conditioning.
Bioinformatics of combined nuclear and mitochondrial phylogenomics to define key nodes for the classification of Coleoptera
Authors: Creedy Thomas J. , Ding Yinhuan , Gregory Katherine M. , Swaby Luke , Zhang Feng , Vogler Alfried P. 
Published: October 2024

AbstractNuclear genome sequencing is resource-intensive and not practical for building densely sampled phylogenetic trees of the most species rich lineages of animals, while mitochondrial genomes can be sequenced and analysed with relative ease. Here, we develop a conceptual approach and bioinformatics workflow for combining nuclear single-copy orthologs with less informative but densely sampled mitochondrial genomes, for a detailed tree of Coleoptera (beetles). Basal relationships of Coleoptera were first inferred from >2,000 BUSCO loci mined from GenBank’s Short Read Archive for 119 exemplars of all major lineages under various substitution models and levels of matrix completion, to reveal universally supported nodes. Second, the corresponding mitogenomes were extracted and combined with an additional 373 species selected for broad taxonomic and biogeographic coverage, roughly in proportion to the known global species diversity of Coleoptera. Bioinformatic processing of mitogenomes was conducted with a novel pipeline for rapid, accurate annotation of protein-coding genes. Finally, phylogenetic trees from all 492 mitogenomes were generated under a backbone constraint from the universal basal nodes, which produced a well-supported tree of the major lineages at family and superfamily level. Being genetically unlinked and showing unique character variation, mitogenomes provide a unique perspective of the phylogeny. Comparison with three recent nuclear phylogenomic studies resulted in the recognition of >80 nodes universally present across all analyses. These may now support the higher classification of Coleoptera and serve as backbone of further studies, as numerous full mitogenomes and mitochondrial DNA barcodes are added to an increasingly complete phylogenetic tree of this super-diverse insect order.
Host genotype shapes root mycobiota in durum wheat
Authors: Margot Trinquier , Michel Colombo , Hélène Fréville , Jacques David , Aline Rocher , Benoit Lefebvre , Christophe Roux 
Published: October 2024

SummaryIn addition to environmental factors, plant genetics play a key role in shaping the root microbiota; however, the extent of this genetic control remains underexplored. Using a collection of 181 wheat lines derived from a genetically diverse population, we investigated the influence of wheat genotypes on the composition of the root endophytic mycobiota and explored the genetic determinants driving these relationships.We first characterized the mycobiota associated with the roots of field-grown lines from the Evolutionary Prebreeding pOpulation (EPO) using Internal Transcribed Spacer 2 (ITS2) barcoding. Fungal diversity was then correlated with wheat genetics by quantitative methods, including heritability analysis and Genome Wide Association Studies (GWAS), to identify novel genetic determinants influencing the mycobiota composition.Fungal species richness showed a positive correlation across most fungal clades, except betweenMortierellomycotinaandGlomeromycotina. Some specific fungal clades, such asOlpidiomycotaorChytridiomycota, underscored their potential as root endophytes. Additionally, we observed higher heritability in fungal clades (i.e.at the phylum or subphylum rank) that exhibit a homogenous trophic mode, such as the biotrophic Arbuscular Mycorrhizal Fungi (AMF).This study identifies 11 QTLs associated with mycobiota composition at the clade level. By shedding light on the genetic control of fungal diversity and uncovering key fungal associations, this work enhances our understanding of plant-microbiota interactions and highlights the potential for breeding strategies to optimize these relationships.
Directing cellular transitions on gene graph-enhanced cell state manifold
Authors: Wang Tianze , Pan Yan , Ju Fusong , Zheng Shuxin , Liu Chang , Min Yaosen , Liu Xinwei , Xia Huanhuan , Liu Guoqing , Liu Haiguang , Deng Pan 
Published: October 2024

AbstractA select few genes act as pivotal drivers in the process of cell state transitions. However, finding key genes involved in different transitions is challenging. To address this problem, we present CellNavi, a deep learning-based framework designed to predict genes that drive cell state transitions. CellNavi builds a driver gene predictor upon a cell state manifold, which captures the intrinsic features of cells by learning from large-scale, high-dimensional transcriptomics data and integrating gene graphs with causal connections. Our analysis shows that CellNavi can accurately predict driver genes for transitions induced by genetic modifications and chemical treatments across diverse cell types, conditions, and studies. It is proficient in tasks involving critical transitions such as cellular differentiation, disease progression, and drug response by leveraging a biologically meaningful cell state manifold. CellNavi represents a substantial advancement in the methodology for predicting driver genes and manipulating cell states, opening up new research opportunities in disease biology and therapeutic innovation.
Brassinosteroids and Flavonols Confer Temperature Stress Tolerance to Pollen Tube Germination and Growth
Authors: Matsuura-Tokita Kumi , Sakai Ayaka , Suzuki Takamasa , Nakano Akihiko , Higashiyama Tetsuya 
Published: October 2024

AbstractSuccessful reproduction is a prerequisite for the maintenance of species in the era of climate change. In agriculture, temperature has a significant impact on pollen tube elongation and attraction, and consequently, on the efficiency of fruiting and crop yields. Brassinosteroids (BRs) are plant steroid hormones involved in pollen tube germination, elongation, and capacitation. To elucidate the effect of BR signaling in pistils during the reproductive process, transcriptome analysis of BR receptor (BRI1) mutant pistils was performed, which indicated that genes involved in flavonol biosynthesis were downregulated inbri1pistils. Flavonols are essential for pollen tube growth in some plants and facilitate pollen tube elongation under high-temperature conditions. To investigate the effects of BR and flavonols on pollen tubes under temperature stress,in vitroassays were performed using both the compounds. Brassinolide (BL), which is the most active BR, promoted pollen tube germination at high, low, and optimal temperatures. Germination was further enhanced by the flavonol, quercetin, in the presence of BL especially at low temperatures.in vivoanalysis supported the observation that when BL and quercetin were supplied concurrently, the pollen tube guidance rate was rescued at low temperatures. Quercetin enhanced pollen tube elongation under all the conditions tested at an optimal concentration of 15 μM. BL elevated reactive oxygen species (ROS) under all temperature conditions, whereas quercetin regulated ROS synergistically with BR. Thus, BRs and flavonols supplied by pistils are suggested to function in pollen tube germination and elongation through the maintenance of ROS homeostasis.
Probabilistic Fine-mapping of Putative Causal Genes
Authors: Okamoto Jeffrey , Yin Xianyong , Ryan Brady , Chiou Joshua , Luca Francesca , Pique-Regi Roger , Im Hae Kyung , Morrison Jean , Burant Charles , Fauman Eric B. , Laakso Markku , Boehnke Michael , Wen Xiaoquan 
Published: October 2024

AbstractIntegrative genetic analysis of molecular and complex trait data, including colocalization analysis and transcriptome-wide association studies (TWAS), has shown promise in linking GWAS findings to putative causal genes (PCGs) underlying complex diseases. However, existing methods have notable limitations: TWAS tend to produce an excess of false-positive PCGs, while colocalization analysis often lacks sufficient statistical power, resulting in many false negatives. This paper introduces a probabilistic fine-mapping method, INTERFACE, which is designed to identify putative causal genes while accounting for direct variant-to-trait effects within genomic regions harboring multiple gene candidates. INTERFACE lever-ages interpretable, data-informed priors that incorporate both colocalization and TWAS evidence, enhancing the sensitivity and specificity of PCG inference and setting it apart from existing methods. Additionally, INTERFACE implements analytical measures to improve the accuracy of gene-to-trait effect estimation. We apply INTERFACE to METSIM plasma metabolite GWASs and UK Biobank pQTL data to identify causal genes regulating blood metabolite levels and demonstrate the unique biological insights INTERFACE provides.
Obesity induces phenotypic switching of gastric smooth muscle cells through the activation of the PPARD/PDK4/ANGPTL4 pathway
Authors: Dekkar Sanaa , Mahloul Kamilia , Falco Amandine , Konate Karidia , Pisteur Romane , Maurel Sarah , Maimoun Laurent , Chauvet Norbert , Boisguérin Prisca , Nocca David , Sultan Ariane , Pallot Florian , Walther Guillaume , Cenac Nicolas , Breuker Cyril , Faure Sandrine , de Santa Barbara Pascal 
Published: October 2024

ABSTRACTObjectiveClinical research has identified stomach dysmotility as a common feature of obesity. However, the specific mechanisms driving gastric emptying dysfunction in patients with obesity remain largely unknown. In this study, we investigated potential mechanisms by focusing on the homeostasis of gastric smooth muscle, using tissue samples from both patient and mice, as well as human cell culture system.DesignTissue samples were collected from patients who underwent sleeve gastrectomy for obesity, as well as from control subjects with standard weight who were undergoing treatment for gastric or esophageal carcinoma. Stomach tissues were harvested from mice after 12 weeks on a High-Fat Diet (HFD). Differentiated human gastric smooth muscle cells (SMCs) were treated with lipids, siRNA-peptide-based nanoparticles and/or pharmaceutical compounds. All experimental conditions were analyzed for their effects on SMC differentiation using stage-specific smooth muscle markers. Additionally, lipidomic and RNA sequencing analyses were performed on human gastric SMC cultures. The findings were assessed in patients with obesity to evaluate their clinical relevance.ResultsThe smooth muscle layers in gastric tissue from both patients with obesity and mice fed on a HFD exhibited altered differentiation status. Treatment of differentiated human gastric SMCs with lipids phenocopies these alterations and is associated with increased expression ofPDK4andANGPTL4. Inhibition of PDK4 or ANGPTL4 upregulation prevents these lipid-induced modifications. Mechanistically, lipid treatment activates PPARD, which regulatesPDK4andANGPTL4upregulation, leading to SMC dedifferentiation. Notably,PDK4andANGPTL4levels correlate with immaturity and alteration of gastric smooth muscle in patients with obesity.ConclusionObesity triggers a phenotypic change in gastric SMCs, driven by the activation of the PPARD/PDK4/ANGPTL4 pathway. These mechanistic insights offer potential biomarkers for diagnosing stomach dysmotility in patients with obesity.
scMultiNODE: Integrative Model for Multi-Modal Temporal Single-Cell Data
Authors: Zhang Jiaqi , Chakravarthy Manav , Singh Ritambhara 
Published: October 2024

AbstractMeasuring single-cell genomic profiles at different timepoints enables our understanding of cell development. This understanding is more comprehensive when we perform an integrative analysis of multiple measurements (or modalities) across various developmental stages. However, obtaining such measurements from the same set of single cells is resource-intensive, restricting our ability to study them integratively. We propose an unsupervised integration model, scMultiNODE, that integrates gene expression and chromatin accessibility measurements in developing single cells while preserving cell type variations and cellular dynamics. scMultiNODE uses autoencoders to learn nonlinear low-dimensional cell representation and optimal transport to align cells across different measurements. Next, it utilizes neural ordinary differential equations to explicitly model cell development with a regularization term to learn a dynamic latent space. Our experiments on four real-world developmental single-cell datasets show that scMultiNODE can integrate temporally profiled multi-modal single-cell measurements better than existing methods that focus on cell type variations and tend to ignore cellular dynamics. We also show that scMultiNODE’s joint latent space helps with the downstream analysis of single-cell development.AvailabilityThe data and code are publicly available athttps://github.com/rsinghlab/scMultiNODE.