bluuebunny/crossref_metadata_2025_split huggingface dataset:
Drug combinations targeting FAK and MEK overcomes tumour heterogeneity in glioblastoma
Authors: Furqan Muhammad , Elliott Richard J R , Nagle Peter , Dawson John C. , Masalmeh Roza , Garcia Virginia Alvarez , Munro Alison F. , Drake Camilla , Morrison Gillian M , Pollard Steven M. , Ebner Daniel , Brunton Valerie G. , Frame Margaret C , Carragher Neil O. 
Published: December 2024

AbstractGlioblastoma (GBM) is an aggressive brain tumour with limited treatment options and poor prognosis, largely due to its heterogeneity and the involvement of multiple intracellular signalling pathways that contribute to drug resistance. Standard therapies have not significantly improved patient outcomes over the past two decades. While recent advancements in targeted drug combination therapies, such as dabrafenib and trametinib, show promise for certain GBM subgroups, identifying drug combinations effective across the broader GBM population remains a challenge. Integrin-mediated signalling, particularly through Focal Adhesion Kinase (FAK), plays a pivotal role in GBM pathogenesis and invasion, making it a potential therapeutic target [1].In our study, we utilized a chemogenomic screening approach to identify synergistic drug combinations that target FAK in glioblastoma. We initially employed a CRISPR-engineered GBM model to assess the effects of FAK depletion and discovered that combining FAK inhibitors with MEK inhibitors, particularly trametinib, demonstrated synergistic effects. This potent combination was validated through various 2D & 3D assays, including cell viability/apoptotic assessment, synergistic analysis, cellular imaging, and target engagement assays. The combination also effectively inhibited spheroid growth and invasion across a diverse panel of patient derived GBM stem cells. Molecular mechanisms underlying these effects included suppression of multiple kinase signalling pathways and enhanced apoptosis, elucidated using Reverse Phase Protein Array (RPPA) profiling and western blot validation.In vivo, the combination therapy significantly reduced tumour volume in orthotopic transplantation models. These findings suggest that combining FAK and MEK inhibitors represent a promising therapeutic strategy to overcome the challenges of GBM treatment.
fluxTrAM: Integration of tracer-based metabolomics data into atomically resolved genome-scale metabolic networks for metabolic flux analysis
Authors: Huang Luojiao , Preciat German , Alarcon-Gil Jesus , Moreno Edinson L. , Wegrzyn Agnieszka , Thiele Ines , Schymanski Emma L. , Harms Amy , Fleming Ronan M.T. , Hankemeier Thomas 
Published: December 2024

AbstractQuantitative inference of intracellular reaction rates is essential for characterising metabolic phenotypes. The classical experimental method for measuring metabolic fluxes makes use of stable-isotope tracing of metabolites through the metabolic network, followed by mass spectrometry analysis. The most common13C-based metabolic flux analysis requires multidisciplinary knowledge in analytical chemistry, cell biology, and mathematical modelling, as well as the use of multiple independent tools for handling mass spectrometry data. Besides, flux analysis is usually carried out within a small network to validate a specific biological hypothesis. To overcome interdisciplinary barriers and extend flux interpretation towards a genome-scale level, we developed fluxTrAM, a semi-automated pipeline for processing tracer- based metabolomics data and integrating it with atomically resolved genome-scale metabolic networks to enable flux predictions at genome-scale. fluxTrAM integrates different software packages inside and outside of the COBRA Toolbox v3.4 for the generation of metabolite structure and reaction databases for a genome-scale model, labelled mass spectrometry data processing into standardised mass isotopologue distribution data (MID), and metabolic flux analysis. To demonstrate the utility of this pipeline, we generated13C-labeled metabolomics data on anin vitrohuman induced pluripotent stem cell (iPSC)-derived dopaminergic neuronal culture and processed13C-labeled MID datasets. In parallel, we generated a cheminformatic database of standardised and context-specific metabolite structures, and atom-mapped reactions for a genome-scale dopaminergic neuronal metabolic model. MID data could be exported into established flux inference software for conventional flux inference on a core model scale. It could also be integrated into the atomically resolved metabolic model for flux inference at genome-scale using moiety fluxomics method. The core model flux solution and moiety flux solution were then compared to two additional flux solutions predicted via flux balance analysis and entropic flux balance analysis. The extensive computational flux analysis and comparison helped to better evaluate the obtained flux feasibility of the neuron-specific genome-scale model and suggested new tracer-based metabolomics experiments with novel labeling configurations, such as labelling a moiety within the thymidine metabolite. Overall, fluxTrAM enables the automation of labelled liquid chromatography (LC)-mass spectrometry (MS) data processing into MID datasets and atom mapping for any given genome-scale metabolic model. It contributes to the standardisation and high throughput of metabolic flux analysis at genome- scale.
Label-Free Visualization and Segmentation of Endothelial Cell Mitochondria Using Holotomographic Microscopy and U-Net
Authors: Michael Raul , Modirzadeh Tallah , Issa Tahir Bachar , Jurney Patrick 
Published: December 2024

AbstractUnderstanding the physiological processes underlying age-related cardiovascular disease (CVD) requires examination of endothelial cell (EC) mitochondrial networks, because mitochondrial function and adenosine triphosphate production are crucial in EC metabolism, and consequently influence CVD progression. Although current biochemical assays and immunofluorescence microscopy can reveal how mitochondrial function influences cellular metabolism, they cannot achieve live observation and tracking changes in mitochondrial networks through fusion and fission events. Holotomographic microscopy (HTM) has emerged as a promising technique for real-time, label-free visualization of ECs and their organelles, such as mitochondria. This non-destructive, non-interfering live cell imaging method offers unprecedented opportunities to observe mitochondrial network dynamics. However, because existing image processing tools based on immunofluorescence microscopy techniques are incompatible with HTM images, a machine-learning model is required. Here, we developed a model using a U-net learner with a Resnet18 encoder to identify four classes within HTM images: mitochondrial networks, cell borders, ECs, and background. This method accurately identifies mitochondrial structures and positions. With high accuracy and similarity metrics, the output image successfully provides visualization of mitochondrial networks within HTM images of ECs. This approach enables the study of mitochondrial networks and their effects, and holds promise in advancing understanding of CVD mechanisms.
Evolution of thermal tolerance in marine diatoms: Metabolic strategies under heat stress
Authors: Aranguren-Gassis María , Diz Angel P. , Huete-Ortega María , Allen Andrew , Litchman Elena 
Published: December 2024

ABSTRACTIn the last decade, numerous laboratory experiments have demonstrated that when marine phytoplankton are exposed to thermal stress, they can evolve high temperature tolerance in a short time (weeks to months). This evolutionary potential may ensure the persistence of marine phytoplankton species under current and future global warming. However, the effect of such adaptation on the phytoplankton interaction with the environment and other organisms depends on how cellular metabolism shifts during the evolutionary process. In order to elucidate which cellular strategies allow the emergence of thermo-tolerant populations, we analyzed the proteomics response of a marine diatom (Chaetoceros simplex) to both thermal acclimation and evolutionary adaptation. We found that high temperature-tolerant populations exhibit a conservative cellular strategy when acclimated to high, above-optimal temperature, where recycling and reallocation is favored at the expense of new structures’ biosynthesis. While this strategy gives the populations that evolved high temperature tolerance an advantage under thermal stress, the shift to resource reallocation may explain the absence of high-temperature adaptation when cells are exposed to low nitrate availability.
Genome-scale prediction of gene ontology from mass fingerprints reveals new metabolic gene functions
Authors: Vavricka Christopher J. , Mochizuki Masao , Yuzawa Satoshi , Murata Masahiro , Yoshida Takanobu , Watanabe Naoki , Nakatsui Masahiko , Ishii Jun , Hara Kiyotaka , Alper Hal S. , Hasunuma Tomohisa , Kondo Akihiko , Araki Michihiro 
Published: December 2024

AbstractMass-based fingerprinting can characterize unknown strains, however expansion of these methods to predict specific gene functions is lacking. Therefore, rapid mass fingerprinting was developed to functionally profile a comprehensive yeast knockout library. Matrix assisted laser desorption ionization (MALDI)-time of flight (TOF) mass fingerprints of 3,238 Saccharomyces cerevisiae knockouts were digitized for correlation with gene ontology (GO) annotations. Random forests and support vector machine (SVM) algorithms precisely assigned GO accessions with AUC scores all above 0.83. SVM was the best predictor with average true positive and true negative rates of 0.975 and 0.991, respectively. The SVM model suggested new functions for 28 uncharacterized yeast genes. Metabolomics analysis of two knockouts (YDR215C and YLR122C) of uncharacterized genes predicted to be involved in methylation-related metabolism, showed altered intracellular contents of methionine-related metabolites. Increased S-adenosylmethionine in YDR215C highlights potential for enhancement of methylation pathways. These results demonstrate that MALDI-TOF fingerprints can be rapidly digitized, resulting in datasets that enable prediction of microbial genotypes and even the function of specific genes. This fingerprinting method can inform optimal bioproduction chassis selection.
Alevin-fry-atac enables rapid and memory frugal mapping of single-cell ATAC-seq data using virtual colors for accurate genomic pseudoalignment
Authors: Singh Noor Pratap , Khan Jamshed , Patro Rob 
Published: December 2024

AbstractUltrafast mapping of short reads via lightweight mapping techniques such as pseudoalignment has significantly accelerated transcriptomic and metagenomic analyses, often with minimal accuracy loss compared to alignment-based methods. However, applying pseudoalignment to large genomic references, like chromosomes, is challenging due to their size and repetitive sequences.We introduce a new and modified pseudoalignment scheme that partitions each reference into “virtual colors…. These are essentially overlapping bins of fixed maximal extent on the reference sequences that are treated as distinct “colors” from the perspective of the pseudoalignment algorithm.We apply this modified pseudoalignment procedure to process and map single-cell ATAC-seq data in our new toolalevin-fry-atac. We comparealevin-fry-atacto bothChromapandCell Ranger ATAC.Alevin-fry-atacis highly scalable and, when using 32 threads, is approximately 2.8 times faster thanChromap(the second fastest approach) while using approximately one third of the memory and mapping slightly more reads.The resulting peaks and clusters generated fromalevin-fry-atacshow high concordance with those obtained from bothChromapand theCell Ranger ATACpipeline, demonstrating that virtual colorenhanced pseudoalignment directly to the genome provides a fast, memory-frugal, and accurate alternative to existing approaches for single-cell ATAC-seq processing. The development ofalevin-fry-atacbrings single-cell ATAC-seq processing into a unified ecosystem with single-cell RNA-seq processing (viaalevin-fry) to work toward providing a truly open alternative to many of the varied capabilities ofCellRanger. Furthermore, our modified pseudoalignment approach should be easily applicable and extendable to other genome-centric mapping-based tasks and modalities such as standard DNA-seq, DNase-seq, Chip-seq and Hi-C.
Genetic determinants of gene expression noise and its role in complex trait variation
Authors: Long Yuexuan , Ni Xiaolin , Chen Tingwei , Hong Qiyang , Wang Jixin , Wang Cong , Huang Zigeng , Xu Haiqing , Sun Mengyi , Pang Junling , Choi Jiyeon , Zhang Tongwu , Long Erping 
Published: December 2024

ABSTRACTEven genetically identical cells in a homogeneous environment can exhibit heterogeneous mRNA abundance because of widely unavoidable random fluctuations, typically referred to as ‘gene expression noise’. Recent studies showed that noise, not just a nuisance, is indeed involved in cellular activities (e.g., immune response), evolutionary processes, and diseases mechanisms. However, determinants of the gene expression noise and its functional role in variations of human complex traits remain largely unexplored. Here, we established an atlas of gene expression noise from 1.23 million human peripheral blood cells of 981 individuals, identifying its age- and gender-dependent pattern. We then identified 10,770 independent expression noise quantitative trait loci (enQTLs) for 6,743 unique enGenes (genetically driven gene expression noise) across 7 immune cell types. Most enQTLs were distinct from expression quantitative trait loci (eQTLs) and showed differential enrichment of functional elements across the genome. Colocalization of enQTLs with trait-associated genetic loci interpreted previously unexplained loci and pinpointed novel putative genes underlying hematopoietic traits and autoimmune diseases. Overall, this study unravels the genetic determinants of gene expression noise and implicates as a previously underappreciated mechanism underlying variation of human complex traits and diseases.
Neonatal amygdala microstructure and structural connectivity are associated with autistic traits at 2 years of age
Authors: Vaher Kadi , Neal Samuel R , Blesa Cábez Manuel , Jiménez-Sánchez Lorena , Corrigan Amy , Stoye David Q , Turner Helen L , Smikle Rebekah , Cruickshank Hilary , Rudnicka Magda , Bastin Mark E , Thrippleton Michael J , Reynolds Rebecca M , Boardman James P 
Published: December 2024

ABSTRACTBackgroundPrenatal exposure to maternal stress is linked to behavioural and neurodevelopmental disorders in childhood. Maternal hair cortisol concentration in pregnancy associates with neonatal amygdala microstructure and structural connectivity ascertained from MRI, suggesting that amygdala development is sensitive to the impact of antenatal stress via hypothalamic-pituitary-adrenal axis. Here, we investigate whether amygdala microstructure and/or connectivity associate with neurodevelopment at 2 years of age.Methods174 participants (105 very preterm) underwent brain MRI at term-equivalent age and assessment of neurodevelopment, autistic traits, temperament, and executive function at 2 years corrected age. We calculated diffusion tensor imaging and neurite orientation dispersion and density imaging metrics for left and right amygdalae. Structural connectivity was measured by mean fractional anisotropy from the amygdalae to 6 ipsilateral regions of interest (insula, putamen, thalamus, inferior temporal gyrus, medial orbitofrontal cortex, rostral anterior cingulate cortex). We used linear regression to model amygdala-outcome associations, adjusting for gestational age at birth and at scan, sex, maternal education, and maternal postnatal depression score. Network-based statistics (NBS) was used for a whole-brain analysis.ResultsAfter adjusting for multiple comparisons, lower amygdala mean diffusivity bilaterally (left: β=-0.32, p=0.026, right: β=-0.38, p=0.012), higher left amygdala neurite density index (β=0.35, p=0.026), and increased left amygdala-putamen connectivity (β=0.31, p=0.026) associated with higher autistic traits. NBS revealed amygdala-involving networks associated with cognition and surgency temperament trait among preterm infants. Other neurodevelopmental outcomes did not significantly associate with amygdala imaging features.ConclusionsMicrostructural variation in the neonatal amygdala may be important in the development of autistic traits.
The emergence and loss of cyclic peptides inNicotianailluminate dynamics and mechanisms of plant metabolic evolution
Authors: Suh Elliot M , Reinhardt Jakob K , Weng Jing-Ke 
Published: December 2024

AbstractSpecialized metabolism plays a central role in how plants cope with both biotic and abiotic stresses in order to survive and reproduce within dynamic and challenging environments. One recently circumscribed class of plant-specific, ribosomally synthesized and post-translationally modified peptides are the burpitides, which are characterized by the installation of distinct sidechain macrocycles by enzymes known as burpitide cyclases. While they are found across many plant families and exhibit diverse bioactivities, little is known about their evolution or how new variants arise. Here we present the discovery of a new burpitide cyclase, resurrected from a defunct pseudogene from the model organismNicotiana attenuata, the coyote tobacco. By repairing the pseudogeneΨNatBURP2and expressing it heterologously inNicotiana benthamiana, we successfully reconstituted its original enzymatic activity. As an autocatalytic peptide cyclase, it installs a unique C-C bond between the tyrosine side chain and a specific backbone a-carbon of a heptapeptide core motif, resulting in the burpitide dubbed "nanamin." Despite its pseudogenization inN. attenuata, we found that the closely related species,N. clevelandii, retains the wild-type gene and produces nanamins. Phylogenetic analyses and targeted mutagenesis experiments reveal that this chemotype must have evolved from the duplication and neofunctionalization of a more promiscuous ancestral gene. This work highlights how novel peptide chemotypes may rapidly emerge and disappear in plants, while expanding the molecular toolkit for engineering novel peptides with applications in agriculture and drug discovery.SignificanceWhile RiPPs represent a major source of antibiotics and bioactive compounds, much research has focused on microbial sources even as plant RiPPs go understudied. Here, we resurrect an extinct peptide cyclase from the coyote tobacco through analysis of its functional relatives in other species. This newly identified cyclase installs a novel carbon-carbon macrocycle into heptapeptides, expanding the diversity of plant-derived cyclic peptides. By interconverting two distinct cyclases through targeted mutations, we illuminate how these enzymes evolve new functions. This work highlights the evolutionary dynamics of plant peptide natural products and their potential applications in drug discovery and biotech crop development, while illustrating how genomic archaeology can reveal lost biosynthetic capabilities.
Two Novel Red-FRET ERK Biosensors in the 670-720nm Range
Authors: DeCuzzi Nicholaus L. , Hu Jason Y. , Xu Florene , Rodriguez Brayant , Pargett Michael , Albeck John G. 
Published: December 2024

AbstractCell fate decisions are regulated by intricate signaling networks, with Extracellular signal-Regulated Kinase (ERK) being a central regulator. However, ERK is rarely the only signaling pathway involved, creating a need to study multiple signaling pathways simultaneously at the single-cell level. Many existing fluorescent biosensors for ERK and other pathways have significant spectral overlap, limiting their ability to be multiplexed. To address this limitation, we developed two novel red-FRET ERK biosensors, REKAR67 and REKAR76, which operate in the 670-720 nm range using miRFP670nano3 and miRFP720. REKAR67 and REKAR76 differ in fluorophore position, which impacts biosensor characteristics; REKAR67 displayed a higher dynamic range but greater signal variance than REKAR76. Mixed populations of REKAR67 or REKAR76 displayed similar Signal-to-Noise ratio (SNR), but in clonal cell populations, REKAR76 had a significantly higher SNR. Overall, our red-FRET ERK biosensors were highly consistent with existing ERK FRET biosensors and in reporting ERK activity and are spectrally compatible with CFP/YFP FRET and cpGFP -based biosensors. Both REKAR biosensors expand the available methods for measuring single-cell ERK activity.
Prevalence of the major thyroid cancer-associated syndromes in the United States
Authors: White Samantha L. , Jamil Taylor , Bell Caitlin , Fishbein Lauren , Haugen Bryan R. , Gignoux Christopher R. , Pozdeyev Nikita 
Published: December 2024

AbstractImportanceA subset of thyroid cancers develops in a setting of a known hereditary cancerassociated syndrome. Understanding the population prevalence of thyroid cancer-associated syndromes is important to guide germline genetic testing and clinical management.ObjectiveTo estimate the prevalence of the major thyroid cancer-associated syndromes in the United States using the All of Us Research Program (AoU) data.DesignIn this cohort study, we identified pathogenic and likely pathogenic (P/LP) variants from the ClinVar database in 245,394 AoU biobank participants. We performed a logistic regression analysis of the association of ClinVar P/LP variants with thyroid cancer. P/LP variants in the genes of interest were manually curated to ensure match and pathogenicity status. We calculated the prevalence of thyroid cancer-associated syndromes defined by the presence of P/LP variants.ResultsUsing logistic regression, we found that three hereditary syndromes, multiple endocrine neoplasia type 2 (MEN2,RETgene, p = 3.23e-20), PTEN hamartoma syndrome (PHPS,PTENgene, p = 2.59e-15), and familial adenomatous polyposis type 1 (FAP,APCgene, p = 2.73e-10) were significantly associated with thyroid cancer. All these syndromes were previously reported to increase the risk of thyroid cancer. The prevalence of thyroid cancer-associated syndromes in the AoU was 1:2,172 (113 cases), 1:8,764 (28 cases), and 1:8,461 (29 cases) for MEN2, PHPS, and FAP, respectively. Most carriers of P/LP variants were not diagnosed with the features of the syndromes, including thyroid cancer, pheochromocytoma, or primary hyperparathyroidism. Three pathogenicRETvariants that cause two amino acid substitutions, V804M and V804L, constitute 65% of all MEN2 variants in the AoU, and none of these carriers were diagnosed with thyroid cancer.Conclusions and RelevanceThe prevalence of MEN2 and PHPS is ∼10-20 times higher than it is currently estimated for the general population (1:35,000 – 1,50,000 for MEN2 and 1:200,000-1:250,000 for PHTS). Most affected individuals are not diagnosed with thyroid cancer. These results further refine our understanding of the prevalence of hereditary syndromic thyroid cancers and may change the clinical approach to patients with moderate-riskRETmutations (such as V804M and V804L), potentially emphasizing active surveillance over prophylactic thyroidectomy.Key PointsQuestionWhat is the prevalence of the major thyroid cancer-associated syndromes in the United States?FindingsIn this cohort study that includes 245,394 genotyped participants in the All of Us Research Program (AoU), the prevalence was 1:2,172 for multiple endocrine neoplasia type 2 (MEN2) and 1:8,764 for PTEN hamartoma syndrome (PHTS).MeaningThe prevalence of MEN2 and PHPS is ∼10-20 times higher than currently estimated for the general population.