bluuebunny/crossref_metadata_2025_split huggingface dataset:
Explorative Discovery of Gene Signatures and Clinotypes in Glioblastoma Cancer Through GeneTerrain Knowledge Map Representation
Authors: Saghapour Ehsan , Yue Zongliang , Sharma Rahul , Kumar Sidharth , Sembay Zhandos , Willey Christopher D. , Chen Jake Y. 
Published: April 2024

AbstractThis study introduces the GeneTerrain Knowledge Map Representation (GTKM), a novel method for visualizing gene expression data in cancer research. GTKM leverages protein-protein interactions to graphically display differentially expressed genes (DEGs) on a 2-dimensional contour plot, offering a more nuanced understanding of gene interactions and expression patterns compared to traditional heatmap methods. The research demonstrates GTKM’s utility through four case studies on glioblastoma (GBM) datasets, focusing on survival analysis, subtype identification, IDH1 mutation analysis, and drug sensitivities of different tumor cell lines. Additionally, a prototype website has been developed to showcase these findings, indicating the method’s adaptability for various cancer types. The study reveals that GTKM effectively identifies gene patterns associated with different clinical outcomes in GBM, and its profiles enable the identification of sub-gene signature patterns crucial for predicting survival. The methodology promises significant advancements in precision medicine, providing a powerful tool for understanding complex gene interactions and identifying potential therapeutic targets in cancer treatment.
Inferring extrinsic factor-dependent single-cell transcriptome dynamics using a deep generative model
Authors: Kojima Yasuhiro , Arioka Yuko , Hirose Haruka , Hayashi Shuto , Mizuno Yusuke , Nagaharu Keiki , Okumura Hiroki , Ishikawa Masato , Ohishi Kohshi , Suzuki Yutaka , Ozaki Norio , Shimamura Teppei 
Published: April 2024

1AbstractRNA velocity estimation helps elucidate temporal changes in the single-cell transcriptome. However, current methodologies for inferring single-cell transcriptome dynamics ignore extrinsic factors, such as experimental conditions and neighboring cell. Here, we propose ExDyn—a deep generative model integrated with splicing kinetics for estimating cell state dynamics dependent on extrinsic factors. ExDyn enables the counterfactual inference of cell state dynamics under different conditions. Among the extrinsic factors, ExDyn can extract key features which have large effects on cell state dynamics. ExDyn correctly estimated the difference in dynamics between two conditions and showed better accuracy over existing RNA velocity methods. ExDyn were utilized for unveiling the effect of PERK-knockout on neurosphere differentiation, hematopoietic stem cell differentiation driven by chromatin activity and the dynamics of squamous cell carcinoma cells dependent on colocalized neighboring cells. These results demonstrated that ExDyn is useful for analyzing key features in the dynamic generation of heterogeneous cell populations.
High-throughput screening of human genetic variants by pooled prime editing
Authors: Herger Michael , Kajba Christina M. , Buckley Megan , Cunha Ana , Strom Molly , Findlay Gregory M. 
Published: April 2024

ABSTRACTUnderstanding the effects of rare genetic variants remains challenging, both in coding and non-coding regions. While multiplexed assays of variant effect (MAVEs) have enabled scalable functional assessment of variants, established MAVEs are limited by either exogenous expression of variants or constraints of genome editing. Here, we introduce a pooled prime editing (PE) platform in haploid human cells to scalably assay variants in their endogenous context. We first optimized delivery of variants to HAP1 cells, defining optimal pegRNA designs and establishing a co-selection strategy for improved efficiency. We characterize our platform in the context of negative selection by testing over 7,500 pegRNAs targetingSMARCB1for editing activity and observing depletion of highly active pegRNAs installing loss-of-function variants. We next assess variants inMLH1via 6-thioguanine selection, assaying 65.3% of all possible SNVs in a 200-bp region spanning exon 10 and distinguishing LoF variants with high accuracy. Lastly, we assay 362 non-codingMLH1variants across a 60 kb region in a single experiment, identifying pathogenic variants acting via multiple mechanisms with high specificity. Our analyses detail how filtering for highly active pegRNAs can facilitate both positive and negative selection screens. Accordingly, our platform promises to enable highly scalable functional assessment of human variants.
Themex-3 3’ untranslated region is essential for reproduction during temperature stress
Authors: Brown Hannah E. , Varderesian Haik V. , Keane Sara A. , Ryder Sean P. 
Published: April 2024

ABSTRACTOrganisms must sense temperature and modify their physiology to survive environmental stress. Elevated temperature reduces fertility in most sexually reproducing organisms. Maternally supplied mRNAs are required for embryogenesis. They encode proteins that govern early embryonic patterning. RNA-binding proteins (RBPs) are major effectors of maternal mRNA regulation. MEX-3 is a conserved RBP essential for anterior patterning ofCaenorhabditis elegansembryos. We previously demonstrated that themex-33’ untranslated region (3’UTR) represses MEX-3 abundance in the germline yet is mostly dispensable for fertility. Here, we show that the 3’UTR is essential during thermal stress. Deletion of the 3’UTR causes a highly penetrant temperature sensitive embryonic lethality phenotype distinct from amex-3null. Loss of the 3’UTR decreases MEX-3 abundance specifically in maturing oocytes and early embryos during temperature stress. Dysregulation ofmex-3reprograms the thermal stress response by reducing the expression of hundreds of heat shock genes. We propose that the primary role of themex-33’UTR is to buffer MEX-3 expression during fluctuating temperature, ensuring the robustness of oocyte maturation and embryogenesis.
Multiplex, multimodal mapping of variant effects in secreted proteins
Authors: Popp Nicholas A. , Powell Rachel L. , Wheelock Melinda K. , Holmes Kristen J. , Zapp Brendan D. , Sheldon Kathryn M. , Fletcher Shelley N. , Wu Xiaoping , Fayer Shawn , Rubin Alan F. , Lannert Kerry W. , Chang Alexis T. , Sheehan John P. , Johnsen Jill M. , Fowler Douglas M. 
Published: April 2024

AbstractDespite widespread advances in DNA sequencing, the functional consequences of most genetic variants remain poorly understood. Multiplexed Assays of Variant Effect (MAVEs) can measure the function of variants at scale, and are beginning to address this problem. However, MAVEs cannot readily be applied to the ∼10% of human genes encoding secreted proteins. We developed a flexible, scalable human cell surface display method, Multiplexed Surface Tethering of Extracellular Proteins (MultiSTEP), to measure secreted protein variant effects. We used MultiSTEP to study the consequences of missense variation in coagulation factor IX (FIX), a serine protease where genetic variation can cause hemophilia B. We combined MultiSTEP with a panel of antibodies to detect FIX secretion and post-translational modification, measuring a total of 44,816 effects for 436 synonymous variants and 8,528 of the 8,759 possible missense variants. 49.6% of possibleF9missense variants impacted secretion, post-translational modification, or both. We also identified functional constraints on secretion within the signal peptide and for nearly all variants that caused gain or loss of cysteine. Secretion scores correlated strongly with FIX levels in hemophilia B and revealed that loss of secretion variants are particularly likely to cause severe disease. Integration of the secretion and post-translational modification scores enabled reclassification of 63.1% ofF9variants of uncertain significance in theMy Life, Our Futurehemophilia genotyping project. Lastly, we showed that MultiSTEP can be applied to a wide variety of secreted proteins. Thus, MultiSTEP is a multiplexed, multimodal, and generalizable method for systematically assessing variant effects in secreted proteins at scale.
High resolution cryo-EM of V-ATPase in native synaptic vesicles
Authors: Coupland Claire E. , Karimi Ryan , Bueler Stephanie A. , Liang Yingke , Courbon Gautier M. , Di Trani Justin M. , Wong Cassandra J. , Saghian Rayan , Youn Ji-Young , Wang Lu-Yang , Rubinstein John L. 
Published: April 2024

AbstractNeurotransmitter release into the synaptic cleft between neurons enables the intercellular communication central to the function of the brain. In the presynaptic neuron, the proton pumping vesicular- or vacuolar-type ATPase (V-ATPase) powers neurotransmitter loading into synaptic vesicles (SVs), with the V1complex dissociating from the membrane region of the enzyme before exocytosis. We isolated SVs from rat brain using SidK, a V-ATPase-binding bacterial effector protein. Single particle electron cryomicroscopy of the vesicles allowed high-resolution structure determination of V-ATPase within the native SV membrane. In the structure, regularly spaced cholesterol molecules decorate the enzyme’s rotor and the abundant SV protein synaptophysin binds the complex stoichiometrically. Conditions where ATP hydrolysis drives glutamate loading result in loss of V1from the SV membrane, suggesting that SV loading is sufficient to induce V-ATPase dissociation.
msCNVS: medium throughput single cell copy number variation sequencing with barcoded library construction free of preamplification toward clinical implementation
Authors: Lin Guanchuan , Peng Bin , Chen Caiming , Dong Zhanying , Xu Mengchang , Gao Jinyu , Yu Jie , Jia Bei , Luo Chen , Hua Rui , Xiao Changtai , Wang Linlin , Mai Liyao , Zhang Yulong , Lu Yuanfang , He Yuanqiao , Song Yali , Marjani Sadie L , Zhang Weimin , Zhang Junxiao , Zhong Mei , Quan Song , Weissman Sherman M , Zhu Hao , Pan Xinghua 
Published: April 2024

AbstractSingle cell copy number variation sequencing (scCNV-seq) is valuable for genomic analysis of a variety of health and disease systems, yet the available methods either depend on either preamplification of the whole genome of each cell, special devices or untracable, which hinder scCNV-seq practice in clinics. Here we provide scalable multiplex scCNV-seq (msCNVS) that allows direct medium-throughput library construction for single cells, which are barcoded individually with Tn5 transposome in a microplate and immediately pooled for downstream processes, elevating the efficiency by orders of magnitude. An algorithm is developed on the distribution of segmented normalized read count density to identify the major peaks associating with integer copy numbers, further improving the accuracy for objective CNV calling. Here msCNVS faithfully distinguishes the unique CNV patterns of 5 cell lines. The individual msCNVS profiles of 70 individual K562 cells highly correlate with the profile of K562 bulk cells (R=0.90-0.98), and the triplicates of HeLa3 bulk cells correlated nearly perfect (R=0.99). The msCNVS CNV profiles of primary cell cultures of amniotic fluid are confirmed by G-banding karyotype analysis and chromosomal microarray analysis. Additionally, the coverage uniformity of msCNVS is superior to that of MDA and MALBAC and approaches what eMDA and DOP-PCR achieves. Furthermore, msCNVS detects CNV deletions in 2 stunted, abnormal blastocysts, one with CNV mosaicism, and uncovered variants of CNVs in circulated tumor cells, cancerous pleural effusion cells, and patient-derived xenograft nuclei. Thus, msCNVS promises a robust, reliable and highly efficient approach to genomic testing of precious and rare cells like those typically obtained in reproductive and cancer clinics.One-Sentence SummaryBy early pooling of multiple single cells individually barcoded with Tn5 transposome, msCNVS enables efficient CNV profiling of rare clinic samples
An interpretable integration model improving disease-free survival prediction for gastric cancer based on CT images and clinical parameters
Authors: Cen Xiaoping , Hu Can , Yuan Li , Cheng Xiangdong , Dong Wei , Zhou Run , Wang Yuanmei , Zou Jiansheng , Lu Tianyu , Yang Huanming , Tong Yahan 
Published: April 2024

AbstractPreoperative prediction of disease-free survival of gastric cancer is significantly important in clinical practice. Existing studies showed the potentials of CT images in identifying predicting the disease-free survival of gastric cancer. However, no studies to date have combined deep features with radiomics features and clinical features. In this study, we proposed a model which embedded radiomics features and clinical features into deep learning model for improving the prediction performance. Our models showed a 3%-5% C-index improvement and 10% AUC improvement in predicting DFS and disease event. Interpretation analysis including T-SNE visualization and Grad-CAM visualization revealed that the model extract biologically meaning features, which are potentially useful in predicting disease trajectory and reveal tumor heterogeneity. The embedding of radiomics features and clinical features into deep learning model could guide the deep learning to learn biologically meaningful information and further improve the performance on the DFS prediction of gastric cancer. The proposed model would be extendable to related problems, at least in few-shot medical image learning.Key PointsAn integration model combining deep features, radiomics features and clinical parameters improved disease-free-survival prediction of gastric cancer by 3%-5% C-index.Embedding radiomics and clinical features into deep learning model through concatenation and loss design improved feature extraction ability of deep network.The model revealed disease progression trajectory and tumor heterogeneity.
Landscape profiling of PET depolymerases using a natural sequence cluster framework
Authors: Seo Hogyun , Hong Hwaseok , Park Jiyoung , Lee Seul Hoo , Ki Dongwoo , Ryu Aejin , Sagong Hye-Young , Kim Kyung-Jin 
Published: April 2024

AbstractSince the demonstration that rapid polyethylene terephthalate (PET) decomposition using enzymes is feasible, a number of efficient depolymerases have been reported with the aim of resolving the plastic pollution issues. However, sporadic studies on enzymes with PET hydrolysis activity hinder the understanding of the distribution of potential PETases hidden in nature’s repertoire, and subsequently, the identification of potent enzymes. Here, we present the clustering of 1,894 PETase candidates, which include the majority of known PETases, and describe their profiling. An archipelago landscape of 170 lineages shows distribution of 289 representative sequences with features associated with PET-degrading capabilities. A bird’s-eye view of the landscape identifies three highly promising yet unexplored PETase lineages and two potent PETases, Mipa-P and Kubu-P. The engineered Mipa-PM19and Kubu-PM12variants exhibit both high PET hydrolysis activity and thermal stability. In particular, Kubu-PM12outperformed the engineered benchmarks in terms of PET depolymerization in harsh environments, such as with high substrate load and ethylene glycol as the solvent. Our landscape framework and the identified variants assist in the understanding of how biological processes respond to solid-state and non-natural PET plastics.
TLR2 Supports γδ T cell IL-17A Response to ocular surface commensals by Metabolic Reprogramming
Authors: Zhu Wenjie , Xu Xiaoyan , Nagarajan Vijayaraj , Guo Jing , Peng Zixuan , Zhang Amy , Liu Jie , Mattapallil Mary J. , Jittayasothorn Yingyos , Horai Reiko , St. Leger Anthony J. , Caspi Rachel R. 
Published: April 2024

ABSTRACTThe ocular surface is a mucosal barrier tissue colonized by commensal microbes, which tune local immunity by eliciting IL-17 from conjunctival γδ T cells to prevent pathogenic infection. The commensalCorynebacterium mastitidis(C. mast) elicits protective IL-17 responses from conjunctival Vγ4 T cells through a combination of γδ TCR ligation and IL-1 signaling. Here, we identify Vγ6 T cells as a majorC. mast-responsive subset in the conjunctiva and uncover its unique activation requirements. We demonstrate that Vγ6 cells require not only extrinsic (via dendritic cells) but also intrinsic TLR2 stimulation for optimal IL-17A response. Mechanistically, intrinsic TLR2 signaling was associated with epigenetic changes and enhanced expression of genes responsible for metabolic shift to fatty acid oxidation to supportIl17atranscription. We identify one key transcription factor, IκBζ, which is upregulated by TLR2 stimulation and is essential for this program. Our study highlights the importance of intrinsic TLR2 signaling in driving metabolic reprogramming and production of IL-17A in microbiome-specific mucosal γδ T cells.SummaryThe ocular commensalCorynebacterium mastitidis(C. mast) induces the IL-17 responses from γδ T cells by activating TLR2 signaling. γδ T cell-intrinsic TLR2 stimulation promotes fatty acid oxidation and increasesIL-17Atranscription, favoring IL-17A responses.Highlights(1) TLR2-deficient mice exhibit reduced γδ T cell responses to ocular commensal bacteria.(2) γδ T cell-intrinsic TLR2 deficiency causes defects of fatty acid oxidation and IL-17A production in a γδ subset-specific manner.(3) The transcription factor, IκBζ is upregulated by TLR2 stimulation and supports γδ IL-17A production through fatty acid oxidation.
Enhancing metabarcoding efficiency and ecological insights through integrated taxonomy and DNA reference barcoding: a case study on beach meiofauna
Authors: Macher Jan-Niklas , Martínez Alejandro , Çakir Sude , Cholley Pierre-Etienne , Christoforou Eleni , Galletti Marco Curini , van Galen Lotte , García-Cobo Marta , Jondelius Ulf , de Jong Daphne , Leasi Francesca , Lemke Michael , Lopez Iñigo Rubio , Sánchez Nuria , Sørensen Martin Vinther , Todaro M. Antonio , Renema Willem , Fontaneto Diego 
Published: April 2024

AbstractMolecular techniques like metabarcoding, while promising for exploring diversity of communities, are often impeded by the lack of reference DNA sequences available for taxonomic annotation. Our study explores the benefits of combining targeted DNA barcoding and morphological taxonomy to improve metabarcoding efficiency, using beach meiofauna as a case study. Beaches are globally important ecosystems and are inhabited by meiofauna, microscopic animals living in the interstitial space between the sand grains, which play a key role in coastal biodiversity and ecosystem dynamics. However, research on meiofauna faces challenges due to limited taxonomic expertise and sparse sampling. We generated 775 new cytochrome c oxidase I DNA barcodes from meiofauna specimens collected along the Netherlands’ west coast and combined them with the NCBI GenBank database. We analysed alpha and beta diversity in 561 metabarcoding samples from 24 North Sea beaches, a region extensively studied for meiofauna, using both the enriched reference database and the NCBI database without the additional reference barcodes. Our results show a 2.5-fold increase in sequence annotation and a doubling of species-level Operational Taxonomic Units (OTUs) identification when annotating the metabarcoding data with the enhanced database. Additionally, our analyses revealed a bell-shaped curve of OTU richness across the intertidal zone, aligning more closely with morphological analysis patterns, and more defined community dissimilarity patterns between supralittoral and intertidal sites. Our research highlights the importance of expanding molecular reference databases and combining morphological taxonomy with molecular techniques for biodiversity assessments, ultimately improving our understanding of coastal ecosystems.
Trait distribution in Geometrid moth assemblages does not vary along a western Himalayan elevational gradient
Authors: Dey Pritha 
Published: April 2024

AbstractElevation gradients pose challenges for flying insects due to temperature and air density shifts, impacting their thermoregulation, flight abilities and subsequently species distribution patterns. Geometrid moths are a model group for studying these traits among insects. This study examines how trait-patterns and niche differentiation of Geometrid moth assemblages change with elevation. Investigating 697 specimens of 120 Geometrid moth species, I assessed species diversity, turnover, and various traits related to body size and flight capabilities along a 1500m elevation span in the western Himalayas. Results indicate a decline in species diversity along the elevational gradients, accompanied by consistent turnover from lower to higher elevations. Despite this pattern, elevation did not significantly influence morphological traits related to thermal sensitivity (body size) and flight capability (wing loading and manoeuvrability) at the assemblage level in Geometrid moths. Furthermore, there was no significant niche differentiation among species across elevations. This supports the argument that species with similar ecological roles persist through turnover, maintaining consistency in trait values across assemblages. These findings from the paleotropics align with patterns observed in Geometrid moths across neotropical and temperate regions, highlighting the importance of trait-based approaches in understanding species responses to environmental changes.Summary StatementThis study examines how Geometrid moth assemblages in the western Himalayas respond to elevational gradients, revealing consistent turnover, stable traits, and no significant niche differentiation, emphasizing trait-based species adaptation
Brain tumor induce immunoregulatory dendritic cells in tumor draining lymph nodes that can be targeted by OX40
Authors: Badillo-Godinez Oscar , Helfridsson Liam , Niemi Jenni , Karimi Shokoufeh , Ramachandran Mohanraj , Hellström Mats 
Published: April 2024

AbstractBrain tumors and metastases have a poor prognosis due to the unique characteristics of the central nervous system (CNS) and tumor immune microenvironment (TIME). CNS tumors exhibit limited infiltration and activation of dendritic cells (DCs) in tumor tissue and tumor-draining lymph nodes (TdLN), which regulate immune responses influenced by factors in the TIME. The immune response in the brain is significantly different from the rest of the body, and although DC subtypes have been identified in mice and humans with brain tumors or metastases, little is known how they affect the response to immunotherapy. We investigated the immunoregulatory function of cervical DCs (DC-c) compared to peripheral DCs (DC-p) in TdLN. Our analysis revealed that DC-c have unique phenotypes and promoted regulatory T cell expansion and poorly cytotoxic CD8 T cells compared to DC-p. Furthermore, we identified OX40 as a modulator of immunoregulatory DC-c function, andBatf3knockout confirmed the essential role of DC-c in mounting an immune response to brain tumors. Additionally, the expression of markers associated with mature regulatory DCs (mregDC) in TdLN was associated with immune regulation in the CNS and the response to OX40. Our findings highlight that immunotherapy interventions can modulate DC-c’s immunoregulatory function, offering an innovative approach for optimized immunotherapy against CNS malignancies.