bluuebunny/crossref_metadata_2025_split huggingface dataset:
Latitudinal clines in the phenology of floral display associated with adaptive evolution during a biological invasion
Authors: Akbar Mia N. , Moskoff Dale R. , Barrett Spencer C.H. , Colautti Robert I. 
Published: June 2024

ABSTRACTPremiseFlowering phenology strongly influences reproductive success in plants. Days to first flower is easy to quantify and widely used to characterize phenology, but reproductive fitness depends on the full schedule of flower production over time.MethodsWe examined floral display traits associated with rapid adaptive evolution and range expansion among thirteen populations ofLythrum salicaria, sampled along a 10-degree latitudinal gradient in eastern North America. We grew these collections in a common garden field experiment at a mid-latitude site and quantified variation in flowering schedule shape using Principal Coordinates Analysis (PCoA) and quantitative metrics analogous to central moments of probability distributions (i.e., mean, variance, skew, and kurtosis).Key ResultsConsistent with earlier evidence for adaptation to shorter growing seasons, we found that populations from higher latitudes had earlier start and mean flowering day, on average, when compared to populations from southern latitudes. Flowering skew increased with latitude whereas kurtosis decreased, consistent with a bet-hedging strategy in biotic environments with more herbivores and greater competition for pollinators.ConclusionsHeritable clines in flowering schedules are consistent with adaptive evolution in response to a predicted shift toward weaker biotic interactions and less variable but more stressful abiotic environments at higher latitudes, potentially contributing to rapid evolution and range expansion of this invasive species.
DeepMASS: Unknown Compound Annotation using Semantic Similarity of Mass Spectral Language and Chemical Space Localization
Authors: Ji Hongchao , Du Ran , Dai Qinliang , Su Meifeng , Lyu Yaqing , Peng Yanchun , Yan Jianbin 
Published: June 2024

ABSTRACTUntargeted analysis using liquid chromatography□mass spectrometry (LC-MS) allows quantification of known and unknown compounds within biological systems. However, in practical analysis of complex biological system, the majority of compounds often remain unidentified. Here, we developed a novel deep learning-based compound annotation approach via semantic similarity analysis of mass spectral language. This approach enables the prediction of structurally related compounds for unknowns. By considering the chemical space, these structurally related compounds provide valuable information about the potential location of the unknown compounds and assist in ranking candidates obtained from molecular structure databases. Validated with two independent benchmark datasets obtained by chemical standards, our method has consistently demonstrated superior performance compared to existing compound annotation methods. A case study of the tomato ripening process indicates that DeepMASS has significant potential for metabolic biomarker identification in real biological systems. Overall, the presented method shows considerable promise in annotating metabolites, particularly in revealing the “dark matter” in untargeted analysis.
Under pressure: integrated endothelial cell response to hydrostatic and shear stresses
Authors: Mandrycky Christian J. , Ishida Takashi , Rayner Samuel G. , Heck Adam , Hadland Brandon , Zheng Ying 
Published: June 2024

AbstractBlood flow within the vasculature is a critical determinant of endothelial cell (EC) identity and functionality, yet the intricate interplay of various hemodynamic forces and their collective impact on endothelial and vascular responses are not fully understood. Specifically, the role of hydrostatic pressure in the EC flow response is understudied, despite its known significance in vascular development and disease. To address this gap, we developed in vitro models to investigate how pressure influences EC responses to flow. Our study demonstrates that elevated pressure conditions significantly modify shear-induced flow alignment and increase endothelial cell density. Bulk and single-cell RNA sequencing analyses revealed that, while shear stress remains the primary driver of flow-induced transcriptional changes, pressure modulates shear- induced signaling in a dose-dependent manner. These pressure-responsive transcriptional signatures identified in human ECs were conserved during the onset of circulation in early mouse embryonic vascular development, where pressure was notably associated with transcriptional programs essential to arterial and hemogenic EC fates. Our findings suggest that pressure plays a synergistic role with shear stress on ECs and emphasizes the need for an integrative approach to endothelial cell mechanotransduction, one that encompasses the effects induced by pressure alongside other hemodynamic forces.
Low abundant intestinal commensals modulate immune control of chronic myeloid leukemia stem cells
Authors: Hinterbrandner Magdalena , Ronchi Francesca , Rubino Viviana , Römmele Michaela , Chiorazzo Tanja , Mooser Catherine , Ganal-Vonarburg Stephanie C. , McCoy Kathy D. , Macpherson Andrew J. , Ochsenbein Adrian F. , Riether Carsten 
Published: June 2024

AbstractLeukemia stem cells (LSCs) are resistant to therapy and immune control. The reason for their resistance to elimination by cytotoxic T cells (CTLs) remains unclear. This study shows that specific low abundant Gram-negative intestinal commensals of the genusSutterellasuppress the anti-leukemia immune response in chronic myeloid leukemia (CML). We found that germ-free and specific opportunistic pathogen-free (SOPF) mice are protected from CML development and that colonization of SOPF mice withSutterella wadsworthensis, but not other related and unrelated bacterial strains, rescues CML development. A higher prevalence of this microbe resulted in Myd88/TRIF-mediated CTL exhaustion in SPF compared to SOPF CML mice as evidenced by higher surface expression of exhaustion markers on CTLs, a reduced capacity to produce interferon-gamma and granzyme B and to kill LSCsin vitro. These findings provide new insights into the immune control of LSCs and identifySutterellaspecies as regulators of anti-leukemic immunity in CML.
Versatile roles of Annexin A4 in ccRCC: impact on membrane repair, transcriptional signatures, and composition of the tumor microenvironment
Authors: Wess Maximilian , Rogg Manuel , Gueib-Picard Constance , Merz Annika , Koessinger Anna L. , Feilen Tobias , Andreev Grigor , Werner Martin , Frew Ian J. , Grabbert Markus , Schilling Oliver , Schell Christoph 
Published: June 2024

AbstractClear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal malignant disease and is characterized by dismal prognosis in the metastasized setting. Invasive growth of cancer cells relates to high levels of compressive forces translating to relevant damage of the plasma membrane. However, functional implications of protein machineries required for plasma membrane repair in ccRCC are not yet completely elucidated. Given the membrane-associated localization of the large family of annexin proteins, we aimed for a global annotation of annexin proteins, which led to the identification of ANXA4 selectively expressed in cancer cells of ccRCC. Interestingly, ANXA4 showed context-dependent distinct localization patterns including the plasma membrane as well as the nuclear compartment/nuclear membrane. We investigated the functional role of ANXA4 in ccRCC employing genetic titration studies (knockdown, CRISPR/Cas9 knockout and overexpression) and identified impaired acute plasma membrane repair as well as invasive capability in conditions of reduced ANXA4 expression. Utilizing computational segmentation of the tumor microenvironment (TME) of ccRCC samples revealed that ANXA4 low tumors exhibited a distinct TME composition compared to ANXA4 high cases. ANXA4 low tumors showed higher levels of tumor infiltrating lymphocytes accompanied by increased deposition of acellular extracellular matrix. Further transcriptomic analysis demonstrated major alterations in transcriptional signatures related to epithelial-mesenchymal transition (EMT) and immune signaling. Transcription factor enrichment analysis and further functional validation identified ELF3 as one central regulator of invasive properties. Our integrative approach including molecular analyses with advanced histopathological segmentation uncovered novel roles for ANXA4 in modulating acute membrane repair, transcriptional regulation, and shaping cellular composition of the ccRCC tumor microenvironment.
The proteotranscriptomic characterization of venom in the white seafanEunicella singulariselucidates the evolution of Octocorallia arsenal
Authors: Modica Maria Vittoria , Leone Serena , Gerdol Marco , Greco Samuele , Aurelle Didier , Oliverio Marco , Fassio Giulia , El Koulali Khadija , Barrachina Célia , Dutertre Sebastien 
Published: June 2024

AbstractAll the members of the phylum Cnidaria are characterized by the production of venom in specialized structures, the nematocysts. Venom of jellyfish (Medusozoa) and sea anemones (Anthozoa) has been investigated since the 1970s, revealing a remarkable molecular diversity. Specifically, sea anemones harbour a rich repertoire of neurotoxic peptides, some of which have been developed in drug leads. However, venoms of the vast majority of Anthozoa species remain uncharacterized, particularly in the class Octocorallia. To fill this gap, we applied a proteo-transcriptomic approach to investigate the venom composition inEunicella singularis, a gorgonian species common in Mediterranean hard-bottom benthic communities. Our results highlighted the peculiarities of the venom ofE. singulariswith respect to sea anemones, which is reflected in the presence of several toxins with novel folds, worthy of functional characterization. A comparative genomic survey across the octocoral radiation allowed us to generalize these findings and provided insights into the evolutionary history, molecular diversification patterns and putative adaptive roles of venom toxins. A comparison of whole-body and nematocyst proteomes revealed the presence of different cytolytic toxins inside and outside the nematocysts. Two instances of differential maturation patterns of toxin precursors were also identified, highlighting the intricate regulatory pathways underlying toxin expression.
Chemical and Sensory Analyses of Cultivated Pork Fat Tissue as a Flavor Enhancer for Meat Alternatives
Authors: Lew Emily T. , Yuen John S.K. , Zhang Kevin L. , Fuller Katherine , Frost Scott C. , Kaplan David L. 
Published: June 2024

AbstractThe emerging field of cellular agriculture has accelerated the development of cell-cultivated adipose tissue as an additive to enhance the flavor of alternative meat products. However, there has been limited research to evaluate the sensory profile ofinvitro-grown tissues compared to conventionally obtained animal fat. This study aimed to investigate the aromatic characteristics of cell-cultivated fat tissue as a flavor enhancer for meat alternatives. Porcine dedifferentiated fat cells were clonally isolated and differentiated into adipocytes. This cultured adipose tissue was then analyzed alongside native porcine fat using gas chromatography-mass spectrometry (GC/MS) coupled with descriptive sensory analysis by human panelists. This evaluation enabled quantitative and qualitative assessments of volatile compounds released during cooking for both in vitro and in vivo porcine fats. The volatile profiles generated during the cooking process and fatty aroma characteristics reported by sensory panelists were largely similar between the two fat sources, with some differences in the concentration of select compounds and aroma attributes. Ultimately, the panelists found comparable overall liking scores reported between the conventional and cultured porcine fats. These findings provide valuable sensory evidence supporting the viability of cell-cultivated adipose tissue as a flavor component of meat alternatives, substituting for conventional animal fat.
Microarray Integrated Spatial Transcriptomics (MIST) for Affordable, Robust, and Comprehensive Digital Pathology
Authors: Juwayria  , Shrivastava Priyansh , Yadav Kaustar , Das Sourabh , Mittal Shubham , Kumar Sunil , Jain Deepali , Malik Prabhat Singh , Gupta Ishaan 
Published: June 2024

Abstract10X Visium, a popular Spatial transcriptomics (ST) method, faces limited adoption due to its high cost and restricted sample usage per slide. To address these issues, we propose Microarray Integrated Spatial Transcriptomics (MIST), combining conventional tissue microarray (TMA) with Visium, using laser-cutting and 3D printing to enhance slide throughput. Our design facilitates independent replication and customization in individual labs to suit specific experimental needs. We provide a step-by-step guide from designing TMAs to the library preparation step. We demonstrate MIST’s cost-effectiveness and technical benefits over Visium and GeoMx Nanostring. We also introduce ‘AnnotateMap’, a novel computational tool for efficient analysis of multiple ROIs processed through MIST.
Low-dimensional representations of genome-scale metabolism
Authors: Cain Samuel , Merzbacher Charlotte , Oyarzún Diego A. 
Published: June 2024

AbstractCellular metabolism is a highly interconnected network with thousands of reactions that convert nutrients into the molecular building blocks of life. Metabolic connectivity varies greatly with cellular context and environmental conditions, and it remains a challenge to compare genome-scale metabolism across cell types because of the high dimensionality of the reaction flux space. Here, we employ self-supervised learning and genome-scale metabolic models to compress the flux space into low-dimensional representations that preserve structure across cell types. We trained variational autoencoders (VAEs) on large fluxomic data (N= 800, 000) sampled from patient-derived models for various cancer cell types. The VAE embeddings have an improved ability to distinguish cell types than the uncompressed fluxomic data, and sufficient predictive power to classify cell types with high accuracy. We tested the ability of these classifiers to assign cell type identities to unlabelled patient-derived metabolic models not employed during VAE training. We further employed the pre-trained VAE to embed another 38 cell types and trained multilabel classifiers that display promising generalization performance. Our approach distils the metabolic space into a semantically rich vector that can be used as a foundation for predictive modelling, clustering or comparing metabolic capabilities across organisms.
Circumventing glioblastoma resistance to temozolomide through optimal drug combinations designed by quantitative systems pharmacology and machine learning
Authors: Corridore Sergio , Verreault Maïté , Martin Hugo , Delobel Thibault , Carrère Cécile , Idbaih Ahmed , Ballesta Annabelle 
Published: June 2024

AbstractGlioblastoma is currently associated to a dismal prognosis despite intensive treatment involving maximal-safe surgery, radiotherapy and temozolomide (TMZ)-based chemotherapy. Disease progression or relapse is often due to initial or acquired resistance to temozolomide, which may be mediated by the over-expression of the repair enzyme MGMT. To design TMZ-based drug combinations circumventing the initial resistance of MGMT-overexpressing cells, a quantitative systems pharmacology (QSP) model representing TMZ cellular pharmacokinetics-pharmacodynamics and their connection to the most altered pathways in GBM was developed. This digital network representation of TMZ cellular pharmacology successfully integrates, in a mechanistic fashion, multi-type time- and dose-resolved datasets, available in control or MGMT-overexpressing cells.In silicotarget inhibition screening identified an optimal antitumor strategy consisting in priming cancer cells with inhibitors of the base excision repair and of the homologous recombination pathway prior to TMZ exposure. This drug combination was validated in dedicated experiments, thus allowing to re-sensitize cells which were initially resistant to TMZ. Using machine learning, functional signatures of response to such optimal multiagent therapy were derived to assist decision making about administering it to other cancer cell lines or patients. The developed framework can be extended to account for additional patientspecific altered pathways and may be translated towards the clinics by representing the tumor micro-environment and drug whole-body pharmacokinetics. Overall, we successfully demonstrated the relevance of combined QSP and machine learning to design multi-agent pharmacotherapies circumventing initial tumor resistance.One Sentence SummaryAn integratedin vitro-in silicoapproach allowed to design optimal drug combinations re-sensitizing temozolomide-resistant glioblastoma cells.
Higher functional resilience of temperate forests at intermediate latitudes of a large latitudinal gradient in South America
Authors: Deng Xiongjie , Carvajal Danny E. , Urrutia-Jalabert Rocío , Machida Waira S. , Rosen Alice , Zhang-Zheng Huanyuan , Galbraith David , Díaz Sandra , Malhi Yadvinder , Aguirre-Gutiérrez Jesús 
Published: June 2024

AbstractAccurately mapping and assessing plant functional composition across space and time is pivotal for understanding environmental change impacts on the biodiversity and functioning of forests. Here, we test the capabilities of a combination ofin-situand remote sensing approaches to deliver accurate estimates of the functional composition of temperate forest ecosystems considering leaf and stem morphological, nutrient, hydraulic, and photosynthetic traits. We identify hydrological stress, soil, and topography as key drivers of plant functional traits. Further, hydrological stress and soil are key determinants of functional dispersion and redundancy in temperate forests distributed across a large latitudinal (30°S to 53°S) gradient in Chile. Functional dispersion peaks across Mediterranean forests, woodlands, and scrub, occupying between 30°S to 35°S. Conversely, functional redundancy peaks between 42°S and 53°S, corresponding to Magellanic subpolar forests. Although functional dispersion and redundancy peak at different latitudes corresponding to distinct forest types; they are both high at latitudes between 35°S and 42°S, coinciding with Valdivian temperate rainforests. Our results highlight areas in temperate forests in South America where both tree functional dispersion and redundancy are high, and hence could potentially be more resilient to environmental changes.
A conserved fungal Knr4/Smi1 protein is vital for maintaining cell wall integrity and host plant pathogenesis
Authors: Kroll Erika , Bayon Carlos , Rudd Jason , Armer Victoria , Umashankar Anjana Magaji- , Ames Ryan , Urban Martin , Brown Neil A. , Hammond-Kosack Kim 
Published: June 2024

AbstractFilamentous plant pathogenic fungi pose significant threats to global food security, particularly through diseases like Fusarium Head Blight (FHB) and Septoria Tritici Blotch (STB) which affects cereals. With mounting challenges in fungal control and increasing restrictions on fungicide use due to environmental concerns, there is an urgent need for innovative control strategies. Here, we present a comprehensive analysis of the stage-specific infection process ofFusarium graminearumin wheat spikes by generating a dual weighted gene co-expression network (WGCN). Notably, the network contained a mycotoxin-enriched fungal module that exhibited a significant correlation with a detoxification gene-enriched wheat module. This correlation in gene expression was validated through quantitative PCR.By examining a fungal module with genes highly expressed during early symptomless infection, we identified a gene encoding FgKnr4, a protein containing a Knr4/Smi1 disordered domain. Through comprehensive analysis, we confirmed the pivotal role of FgKnr4 in various biological processes, including morphogenesis, growth, cell wall stress tolerance, and pathogenicity. Further studies confirmed the observed phenotypes are partially due to the involvement of FgKnr4 in regulating the fungal cell wall integrity pathway by modulating the phosphorylation of the MAP-kinase MGV1. Orthologues ofFgKnr4are widespread across the fungal kingdom but are absent in other Eukaryotes, suggesting the protein has potential as a promising intervention target. Encouragingly, the restricted growth and highly reduced virulence phenotypes observed forΔFgknr4were replicated upon deletion of the orthologous gene in the wheat fungal pathogenZymoseptoria tritici. Overall, this study demonstrates the utility of an integrated network-level analytical approach to pinpoint genes of high interest to pathogenesis and disease control.
Transcription factor binding site divergence across maize inbred lines drives transcriptional and phenotypic variation
Authors: Galli Mary , Chen Zongliang , Ghandour Tara , Chaudhry Amina , Gregory Jason , Li Miaomiao , Zhang Xuan , Dong Yinxin , Song Gaoyuan , Walley Justin W. , Chuck George , Whipple Clinton , Kaeppler Heidi F. , Huang Shao-shan Carol , Gallavotti Andrea 
Published: June 2024

AbstractRegulatory elements are important constituents of plant genomes that have shaped ancient and modern crops. Their identification, function, and diversity in crop genomes however are poorly characterized, thus limiting our ability to harness their power for further agricultural advances using induced or natural variation. Here, we use DNA affinity purification-sequencing (DAP-seq) to map transcription factor (TF) binding events for 200 maize TFs belonging to 30 distinct families and heterodimer pairs in two distinct inbred lines historically used for maize hybrid plant production, providing empirical binding site annotation for 5.3% of the maize genome. TF binding site comparison in B73 and Mo17 inbreds reveals widespread differences, driven largely by structural variation, that correlate with gene expression changes. TF binding site presence-absence variation helps clarify complex QTL such asvgt1, an important determinant of maize flowering time, and DICE, a distal enhancer involved in herbivore resistance. Modification of TF binding regions via CRISPR-Cas9 mediated editing alters target gene expression and phenotype. Our functional catalog of maize TF binding events enables collective and comparative TF binding analysis, and highlights its value for agricultural improvement.